title: Suspected Close Contacts as the Pilot Indicator of the Growth Trend of Confirmed Population During the COVID-19 Pandemic: A Simulation Approach

text: BACKGROUND: Regarding to the actual situation of the new coronavirus disease 2019 epidemic, social factors should be taken into account and the increasing growth trend of confirmed populations needs to be explained. A proper model needs to be established, not only to simulate the epidemic, but also to evaluate the future epidemic situation and find a pilot indicator for the outbreak. METHODS: The original susceptible-infectious-recover model is modified into the susceptible-infectious-quarantine-confirm-recover combined with social factors (SIDCRL) model, which combines the natural transmission with social factors such as external interventions and isolation. The numerical simulation method is used to imitate the change curve of the cumulative number of the confirmed cases and the number of cured patients. Furthermore, we investigate the relationship between the suspected close contacts (SCC) and the final outcome of the growth trend of confirmed cases with a simulation approach. RESULTS: This article selects four representative countries, that is, China, South Korea, Italy, and the United States, and gives separate numerical simulations. The simulation results of the model fit the actual situation of the epidemic development and reasonable predictions are made. In addition, it is analyzed that the increasing number of SCC contributes to the epidemic outbreak and the prediction of the United States based on the population of the SCC highlights the importance of external intervention and active prevention measures. CONCLUSIONS: The simulation of the model verifies its reliability and stresses that observable variable SCC can be taken as a pilot indicator of the coronavirus disease 2019 pandemic.


Construction des savoirs en ces temps de distanciation sociale


Jeden Verdacht melden!


Dispel clouds of pandemic through cooperation


Entschädigung für Praxis-schließung wegen Covid-19


title: Orts- und zeitflexibles Arbeiten: Alte Geschlechterungleichheiten und neue Muster der Arbeitsteilung durch Digitalisierung

text: This paper follows the question to what extent the compatibility of work and family life and gender inequalities in the domestic division of labour change when working with digital technologies in a flexible manner in terms of time and place. It is based on the results of the research project “Changing gender relations through digital transformation” (Hans Böckler Foundation). Various effects have been observed: For example, mobile working and home office enable part-time workers to increase their contractual working hours; flexible digital work provides emotional and time relief in the event of spontaneous emergencies such as child illness; however, the extent of invisible and unpaid overtime is also increasing. In most cases, this does not lead to a reorganisation or redistribution of unpaid domestic and care work. Nevertheless, there are signs of shifts in the domestic division of labour. This article presents the central results of the project and discusses them with regard to their implications for gender inequality. Practical Relevance: The text provides information on current experiences with flexible working times and places from a gender perspective. It provides indications of conducive and obstructive conditions for reducing inequalities in the responsibility for care work and in domestic division of labour. The results can be used for the design of conditions and regulations for flexible work in terms of time and place in companies.


9 Tipps für die Ärztegesundheit


title: Characterization and mutational analysis of haemagglutinin and neuraminidase of H3N2 and H1N1pdm09 human influenza A viruses in Egypt

text: Seasonal influenza viruses constitute a major global concern. Currently, H3N2 and H1N1pdm09 are the commonly circulating influenza A viruses. The haemagglutin and neuraminidase genes of influenza A(H3N2) and A(H1N1)pdm09 viruses from Egyptian paediatric patients with respiratory distress were sequenced. Mutational analysis of all published sequences from Egypt was evolutionary tracked for both HA and NA genes. Phylogenetic analysis of H3N2 HA showed that the Egyptian strains belong to 3C2 subclade while Egyptian A(H1N1)pdm09 strains belong to 6B1 subclade. Some Egyptian A(H1N1)pdm09, 2013–2014, strains form a new subclade; 6B3. High score of mutations were recorded in HA of H1N1pdm09 but higher was recorded in H3N2 strains. These findings confirmed a high mutation rate of influenza A subtypes specially H3N2 strains.


title: Learning curve in robotic transabdominal preperitoneal (rTAPP) ventral hernia repair: a cumulative sum (CUSUM) analysis

text: PURPOSE: rTAPP-VHR is a novel technique which may be added to a surgeon’s armamentarium. We aim to evaluate the robotic transabdominal preperitoneal ventral hernia repair (rTAPP-VHR) learning curve based on operative times while accounting for peritoneal flap integrity. METHODS: We performed a retrospective analysis of a database collected over a 7-year period. Patients with primary ventral hernias were included and a cumulative sum analysis(CUSUM) was used to create learning curves for three subsets of operative times. A risk-adjusted CUSUM (RA-CUSUM) accounted for repair quality based on peritoneal flap completeness. The flap was considered as incomplete when peritoneal gaps were unable to be closed. RESULTS: 105 patients undergoing rTAPP-VHR were included. Learning curves were created for skin-to-skin, console, and off-console times. Patients were divided into three phases. In terms of skin-to-skin times, both phase 2&3 had a mean 11 min shorter than that of phase 1 (p = 0.0498, p = 0.0245, respectively), with a steady decrease after forty-six cases. An incomplete peritoneal flap was noted in 25/36 patients in phase 1, as compared to 5/24 and 5/45 patients in phase 2&3, respectively. When risk-adjusted for peritoneal flap completeness, gradually decreasing skin-to-skin times were observed after sixty-one cases. In terms of off-console times, the mean across three phases was 14 min, with marked improvement after forty-three cases. CONCLUSIONS: Forty-six cases were needed to achieve steadily decreasing operative times. We can assume that ensuring good-quality repairs, through maintenance of peritoneal flap integrity, was gradually improved after sixty-one cases. Moreover, familiarization with port placements and robotic docking was accomplished after forty-three cases.


Online Meetings in Times of Global Crisis: Toward Sustainable Conferencing


COVID - 19 fact sheet for the dental professional


From the Editor's Desk


title: A DEA model for measuring financial intermediation

text: It is common practice in data envelopment analysis to assess commercial banks by the efficiency that they display in their operations under different outlooks on their behaviour; yet, even the intermediation approach does not measure actually the success with which commercial banks or a banking sector fulfil their mission of financial intermediaries. Such an assessment is traditionally accomplished by means of the loan-to-deposit ratio that captures rather size or depth of financial intermediation, but no link is sought to best practices that are observed in the banking sector. The paper proposes a model of financial intermediation that permits assessing on a comparative basis the attainment in financial intermediation. The devised index of financial intermediation recognizes through weights that diverse outcomes of financial intermediation exhibit differentiated importance to the economy and is closely connected with the weighted slacks-based measure (WSBM). The WSBM that emerges in this respect encompasses only production variables that define financial intermediation (i.e. deposits and intermediated outputs) whilst other production variables are treated as non-discretionary. The model can be applied in variants for a single commercial bank in one specific year (Model I) or for aggregated bank-years such as one particular bank over the entire period or various banks in one year (Model II). The ideas are demonstrated on a data set of Slovak commercial banks for the period between 2008 and 2016 and the difference of the proposed approach with traditional efficiency measurement under the intermediation approach is discussed.


Spatiotemporal changes of epidemics and their relationship with human living environments in China over the past 2200 years


Sun Chemical Addresses Supply Chain Preparations amid Coronavirus Outbreak


title: Value of endoscopic examination of airways and swallowing in tracheostomy decannulation

text: BACKGROUND: Tracheostomy decannulation decision is the major challenge in the clinical management of tracheostomy patients. Little evidence is available to guide the weaning process and optimal timing of tracheostomy tube removal. The purpose of the study was to investigate the value of endoscopic assessment in the tracheostomy decannulation decision. RESULTS: The study included 154 tracheostomized adult patients. Bedside assessment was done for 112 patients, and the other 42 patients were deceased. The results of bedside assessment lead to successful decannulation in 18 patients (16%), while 94 patients (84%) were unfit for decannulation. The most common cause of unfitness was aspiration and poor swallowing in 41% of patients. The endoscopic assessment was done for 59 patients out of 94 patients that were unfit for decannulation; thirteen patients of them were fit for decannulation (22%). The final status of the patients before discharge was decannulated in 31 cases and 81 patients were discharged with a tracheostomy. CONCLUSIONS: The results indicated the importance of endoscopic assessment in the decannulation decision of tracheostomized patients. A large proportion of patients who are unfit for decannulation by bedside assessment could be fit after endoscopic assessment. Endoscopic assessment is essential particularly in tracheostomized patients who have failed to achieve decannulation through conventional protocols.


Diagnostic microbiologique de la grippe : service rendu aux urgences par le BioFire® Film Array® Respiratory panel 2 plus


Expression of concern: Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis


title: Kan inhalatieanesthesie midazolam vervangen bij ARDS-patiënten op de ic?

text: Op de intensive care (ic) wordt meestal intraveneus midazolam toegediend om ARDS-patiënten te sederen. Midazolam is voor ic-patiënten echter geen ideaal sedatiemiddel: bij lever- en nierfunctiestoornissen duurt het langer voordat het is uitgewerkt en het geeft gewenning en ontwenning. Inhalatieanesthetica kunnen een alternatief zijn.


Re: Maria J. Ribal, Philip Cornford, Alberto Briganti, et al. European Association of Urology Guidelines Office Rapid Reaction Group: An Organisation-wide Collaborative Effort to Adapt the European Association of Urology Guidelines Recommendations to the Coronavirus Disease 2019 Era. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2020.04.056: Metastatic Prostate Cancer and COVID-19: Do Current Data Allow Modification of Established Treatment Recommendations?


Addendum to: “COVID-19 Personal Protective Equipment (PPE) for the Emergency Physician” Visual Journal of Emergency Medicine 19 (2020) 100740


Mars mission gets put back two years


Coronavirus et professionnels de santé au travail


European TiO(2) demand is likely to be soft again in 2020


title: The academic turn: Social media in higher education

text: Universities must transform to fulfil expectations of the knowledge society. At the same time academics are required to respond to the dynamic environment that information and communications technologies (ICT) bring to effective and efficient teaching methods. Utilizing a qualitative case study approach, this study set out to explore experiences of academics’ as they made a pedagogic turn towards using social media technology for teaching in a resource-constrained context. The Technology Acceptance Model served as the theoretical mooring of this study. Data capture included a mix of semi-structured interviews, classroom observations, document analysis and field notes. Findings are presented as three academic turns. First, a turn away from the institutions’ LMS due to contextual exigencies. Second, a pedagogical turn towards Web 2.0 technologies using social media tools to enhance their pedagogy. Third, a beliefs and attitude turn about the affordances of social media; augmenting academics’ resilience to persevere with this technology of choice. This study recommends that the use of social media networking in higher education creates a viable form of technology enhanced teaching, particularly in resource-constrained contexts. Further studies should explore academics emerging pedagogical practices in their use of social media, and students’ perceptions and engagement in social media learning communities.


Olivier Véran hérite d’un dossier biologie médicale stabilisé


269 Rare Case of Pulmonary Necrotic Rhodococcus Equi Infection in a Kidney Pancreas Transplant Recipient.


title: Detection of Antibodies Against Canine Circovirus in Naturally and Experimentally Infected Canines by Recombinant Capsid Enzyme-Linked Immunosorbent Assay

text: Canine circovirus (CanineCV), a new pathogen, was found to be associated with canine hemorrhagic diarrhea, vasculitis, granulomatous lymphadenitis, and acute gastroenteritis. Although CanineCV was highly positive rate in diarrhea cases, its pathogenicity remains controversial. In this study, the seroprevalence and associated risk factors of CanineCV infection among domestic dogs in northeastern China was investigated by an indirect enzyme-linked immunosorbent assay (iELISA) based on recombinant capsid protein. Results revealed the proposed iELISA had no cross-reactivity with other related pathogens, and yielded good diagnostic values. Then, to evaluate the rCap iELISA, this study applied it to detect antibodies against CanineCV in 1,047 clinical serum samples obtained from northeastern China in 2016–2017. Results showed the positive rates in the five cities of Jilin, Liaoning, and Heilongjiang provinces ranged from 22.22 to 42.29%. Statistical analysis shows a significant difference in age between dogs <3 months old with respect to the >1-year-old dogs (p = 0.005), that is, the CanineCV infection was more frequently identified from older dogs. In the artificially infected experiment, the dogs developed seroconversion after 9 or 12 days and the main way of virus excretion was through feces. More interestingly, among the 32 ELISA-positive serum samples, 34.75% samples tested positive for the CanineCV DNA by qPCR, far higher than that in ELISA-negative serum samples (5.26%, 2/38). This report is the first to demonstrate that CanineCV infection is common in the dog population in northeastern China. The results showed obvious differences in the positive rate associated with diarrhea, age, but not with different cities. This study also provide basis for evaluating the pathogenic potential of CanineCV. But, the pathogenicity, the relationship between antibody level and immune protection, and the harmful effects of this virus remain to be established.


Highlights


270 Acute Kidney Injury in Mushroom Poisoning


Editorial Note


267 Acute Kidney Injury Caused by Juicing and Volume Depletion Lading to End Stage Renal Disease.


Age, diabetes and heart disease linked to risk of death


Actualités santé publique


Innovations in Teaching and Learning during a Time of Crisis


Polyethylene sector seeks upside from trough


273 Severe Hypothyroidism-Induced Rhabdomyolysis and Acute Kidney Injury


271 What Is the Cause Of This Patient’s Hypertension?


Infections respiratoires du sujet âgé : pneumonies virales et à germes intracellulaires


Tributes to William Helmreich, z”l


title: Association of anesthesia type with prolonged postoperative intubation in neonates undergoing inguinal hernia repair

text: PURPOSE: The purpose of this study is to determine factors associated with prolonged intubation after inguinal herniorrhaphy in neonates. METHODS: Retrospective, single institution review of neonates undergoing inguinal herniorrhaphy between 2010 and 2018. Variables recorded included demographics, comorbidities, ventilation status at time of hernia repair, and anesthetic technique. RESULTS: We identified 97 neonates (median corrected gestational age 39.9 weeks, IQR 6.6). The majority (87.6%) received general anesthesia (GA); the remainder received caudal anesthesia (CA). Among the GA subjects, 25.8% remained intubated for at least 6 h after surgery, whereas none of the CA patients required intubation postoperatively (p = 0.03). Two risk factors associated with prolonged postoperative intubation: a history of intubation before surgery (p = 0.04) and a diagnosis of bronchopulmonary dysplasia (p = 0.03). CONCLUSIONS: Neonates undergoing inguinal herniorrhaphy under GA have a greater rate of prolonged postoperative intubation compared with those undergoing CA. A history of previous intubation and bronchopulmonary dysplasia were significant risk factors for prolonged postoperative intubation.


Dermatologie im Sanitätsdienst der Bundeswehr – ein essenzielles Fachgebiet


SAT-028 ACUTE KIDNEY INJURY ASSOCIATED WITH MIDDLE EAST RESPIRATORY SYNDROME CORONAVIRUS (MERS-CoV) INFECTION


title: Drug search continues

text: There has been much enthusiasm for promising medicines, but it is unclear if any will help those who really need them, reports Michael Le Page


AI forecasts harmful particle levels in Beijing


News & Notes


COVID 19 – Journal de bord – 15/03/2020 : premières réflexions


Comparison of SARS-CoV-2 detection in nasopharyngeal swab and saliva


News Beyond Our Pages


China refineries reduce operating rates


title: Identity Narratives in China and the EU’s Economic Diplomacy: Comparing the BRI and the EU Connectivity Strategy for Asia

text: The Belt and Road Initiative (BRI) and the EU Connectivity Strategy for Asia represent China and the EU’s respective flagship initiatives of economic diplomacy in the twenty-first century and offer two separate blueprints for shaping the future of shared economic prosperity on the Eurasian continent. The basic understanding of external economic engagement in China and the EU is heavily marked by the respective actors’ identity narratives—that is, ‘ national rejuvenation’ and national interest in the case of China, and ‘reconciliation’ and the support for rules-based multilateralism in the case of the European Union. While China and the EU pursue similar objectives, it is more the political questions of how to guarantee a ‘level playing field’ and ‘shared benefits’ that cause uncertainty and tension between them.


Coronavirus infection (COVID-19) in Anales de Pediatría()


Francis (Frank) Allan Plummer


274 The Different Patterns and Mechanisms of Kidney Injury in a Single Case of Multiple Myeloma


She Ji: The Next Five Years


Coronavirus : des kits de protection pour les professionnels de santé


Airway closure, more harmful than atelectasis in intensive care?


title: Susceptibility Patterns of Multidrug-Resistant Acinetobacter baumannii

text: OBJECTIVES: To investigate the antimicrobial resistance patterns of multidrug-resistant Acinetobacter baumannii (MDRAB) in patients in pediatric intensive care units (PICU) in order to determine a guide for the empirical antibiotic treatment of MDRAB. METHODS: The authors retrospectively evaluated the medical records of patients with MDRAB infections in the PICU during a follow-up period, between January 2015 and January 2017. The identification of A. baumannii was performed using a BD Phoenix 100 Automated Microbiology System. A BD Phoenix NMIC/ID-400 commercial kit was used to test antibiotic susceptibility. All data was entered into Microsoft Excel, and the data was analyzed using SPSS version 23.0. RESULTS: The mean age of the patients was 8.1 ± 6.2 y. In all, 46 isolates were obtained from 33 patients. The most effective antimicrobial agents were colistin, trimethoprim/sulfamethoxazole, and tigecycline. Nevertheless, with the exception of colistin, no antibiotic was associated with a susceptibility rate of >45% for the isolates. Low sensitivities in 2015 to tigecycline, aminoglycosides, levofloxacin, and carbapenems had been lost in 2016. CONCLUSIONS: Many drugs that were previously effective against MDRAB, have lost their effectiveness. Currently, there is no effective drug to fight MDRAB, apart from colistin. Thus, it is clear that new drugs and treatment protocols should be developed urgently.


title: Estimation of socioeconomic attributes from location information

text: Timely estimation of the distribution of socioeconomic attributes and their movement is crucial for academic as well as administrative and marketing purposes. In this study, assuming personal attributes affect human behavior and movement, we predict these attributes from location information. First, we predict the socioeconomic characteristics of individuals by supervised learning methods, i.e., logistic Lasso regression, Gaussian Naive Bayes, random forest, XGBoost, LightGBM, and support vector machine, using survey data we collected of personal attributes and frequency of visits to specific facilities, to test our conjecture. We find that gender, a crucial attribute, is as highly predictable from locations as from other sources such as social networking services, as done by existing studies. Second, we apply the model trained with the survey data to actual GPS log data to check the performance of our approach in a real-world setting. Though our approach does not perform as well as for the survey data, the results suggest that we can infer gender from a GPS log.


title: Organ Systems and Disease

text: This chapter provides an overview of organ systems and diseases caused by the infections of these organ systems. The respiratory system is a portal of entry for micro-organisms. Viruses are responsible for the majority of upper respiratory tract infections, while bacteria are responsible for the majority of the lower respiratory tract infections. The urinary tract is a sterile system. Infection of the urinary tract can be exogenous or endogenous. Urinary tract infection is expressed as bladder infection — frequency, urgency, and burning. The cardio-vascular system represents one of the normally sterile anatomical areas. Invasion of the blood stream by bacteria may occur from breaches in the skin or mucous membranes. Infection of any organ system may be associated with a bacteraemia, for example, pneumococcal pneumonia can often be diagnosed by the presence of lung pathology and a positive blood culture. Certain diseases are typically characterized by the blood spread of organisms during particular phases of the illness, such as, typhoid, and measles.


Electron and Immunoelectron Microscopic Procedures for Diagnosis of Viral Infections


Viruses and their system/hosts


Pathogen Removal from Wastewater during Groundwater Recharge


Male Genital System


The cat with weight loss and a good appetite


title: Aquatic Ecosystems, Human Health, and Ecohydrology

text: This chapter treats two main topics: the relationship between human health, aquatic ecosystems, and water use; and the necessity of interdisciplinary approaches for the development of water management policies and disease control. Main waterborne diseases, mostly affecting developing countries and relevant in terms of water management and changes in land use, such as malaria, schistosomiasis, or cholera, are discussed stressing links to the global water crisis. Also, the role of artificial and natural wetlands in influenza epidemics is treated. The effects of increasing water use and scarcity on human health are discussed considering historical and contemporary incidence of diarrheal diseases in European and South Asian megacities, relationships between dams and on waterborne diseases in Asia and Africa, and intensive agri- and aquaculture resulting in man-made ecotones, fragmented aquatic ecosystems, and pathogen mutations. It is emphasized that the comprehension of the multiple interactions among changes in environmental settings, land use, and human health requires a new synthesis of ecohydrology, biomedical sciences, and water management for surveillance and control of waterborne diseases in basin-based, transboundary health systems. Surveillance systems should monitor changes in water management, ecotones, and hydrological cycles and shifts in, for example, the outbreak timing of strongly seasonal diseases. These indicators would provide criteria for the development of innovative water management policies, combining methods of vector control and the safe creation of water reservoirs, irrigation systems, and wetland habitats.


title: Propagation of Adenoviral Vectors: Use of PER. C6 Cells

text: This chapter discusses the production systems of adenoviral vectors. Particular attention is paid to the generation and use of complementation cell lines that carry the El genes and emphasizes on the PER.C6 cell line, which was developed to prevent generation of replication-competent adenovirus (RCA) during propagation of El-deleted adenoviral vectors. Further, safety issues with respect to the use of the cell line for making clinical grade material are also addressed in this chapter. The PER.C6 cell line is the best substrate for the production of adenoviral vectors for gene therapy or vaccines. PER.C6 permits extensive analysis for adventitial agents and other safety concerns and thus is less hazardous than short-lived primary cell cultures for which testing must be repeated for each newly established culture.


title: Health Delivery and Quality Assurance Programs for Mice

text: This chapter covers health care delivery for individual mice, quality assurance (QA) programs for research colonies of mice, and infectious outbreak sources and management. Comprehensive health care must be provided in all of these areas to be effective. An unwanted infectious agent that does not cause clinically evident signs could still have a major adverse impact on research results if allowed to disseminate. As a result, the program for providing health care must include detection and care of individual mice that are ill, routine colony surveillance to guard against the undetected entry and spread of previously excluded infectious agents, and a response plan if such agents are detected. Such programs result in humane care of animals and the best protection of experimental repeatability and validity. As infectious agents, detection and treatment methods, and the research environment evolve, the veterinary and husbandry staff caring for research animals must strive to keep themselves educated and informed. Animal health and QA programs are not static but are always a work in progress and must also evolve in response to the challenges and needs of the research community.


Astrocyte—Microglia Interactions


The Eye


MICROBIOLOGICAL HEALTH EFFECTS ASSOCIATED WITH THE USE OF MUNICIPAL WASTEWATER FOR IRRIGATION


title: Proteinases Involved in Plant Virus Genome Expression

text: This chapter discusses the proteinases involved in plant virus genome expression. The chapter focuses on virus-encoded proteinases. It gives an overall view of the use of proteolytic processing by different plant virus groups for the expression of their genomes. It also discusses that the development of full-length cDNA clones from which infectious transcripts can be produced either in vitro or in vivo, has facilitated the functional analysis of the plant virus proteinases. In spite of the high specificity of the viral proteinases, cellular substrates for animal virus proteinases have been described in this chapter. The activity of the viral proteinases can interfere with important cellular processes to favor virus replication. The recent use of proteinase inhibitors in AIDS therapy has emphasized the convenience of virus-encoded proteinases as targets of antiviral action. A mutant protein able to inhibit the activity of the TEV proteinase by manipulation of the α(2)-macroglobulin bait region was designed by Van Rompaey.


Respiratory System, Mediastinum, and Pleurae


Gastrointestinal complications of secondary immunodeficiency syndromes


Special Studies


Pet Rodents


Alkaloid Glycosidase Inhibitors


The Urinary System


title: Gastrointestinal Function

text: This chapter discusses the functions of gastrointestinal tract. The principal functions of the gastrointestinal tract are assimilation of nutrients and excretion of the waste products of digestion. Within the gastrointestinal tract, these substances are solubilized and degraded enzymatically to simple molecules, sufficiently small in size and in a form that permits absorption across the mucosal epithelium. The distribution of the different types of secretory cells in the salivary glands varies among species. The mandibular and sublingual glands are mixed salivary glands containing both mucous and serous types of cells, and produce a viscous secretion that contains large amounts of mucus. The cytoplasm of the secretory cells contains numerous zymogen granules that vary in size and number depending on the activity of the gland. These granules contain the precursors of the hydrolytic enzymes responsible for digestion of the major dietary components. The cells of the terminal ducts probably secrete the bicarbonate ion responsible for neutralizing hydrochloric acid that enters the duodenum from the stomach.


A SUGGESTED CHECK LIST FOR EFFECTIVE PREVENTION OF INFECTION IN RODENT COLONIES


Hotel Buildings


Hematology and Immune-Related Disorders


Becken, Hüfte und Oberschenkel


Systemorientiertes Wissen


Leber


Essentials of Pulmonology


Spezielle Arzneimitteltherapie in der Schwangerschaft


Pathology of Pulmonary Infection


Large Intestine (Colon)


Enfermedades infecciosas de los pulmones


Breaking News in the Powder Coating World


title: Zoonoses and Other Human Health Hazards

text: This chapter discusses known or potential zoonotic agents and the disease manifestations produced in man by exposure to infected mice. It also discusses other health hazards that may be encountered when working with mice, such as bites and allergies. Selected transmission of human infectious agents to mice is also briefly described in the chapter. Of the many latent viruses present in the mouse, only the lymphocytic choriomeningitis virus (LCM) naturally infects man. A review of the literature attests to the ease with which the LCM can be transmitted from animals to man. Although its expression can vary greatly, the LCM virus infection appears most frequently as a mild influenza-like syndrome, with or without apparent involvement of the central nervous system. In one epidemic of the non-meningitic LCM virus infection caused by exposure to infected hamsters, an influenza-like illness was described with typical symptoms of retro-orbital headache, severe myalgia, malaise, anorexia, and aching pain in the chest. A variety of rodent hosts are included in the transmission cycle of the rickettsial disease in nature. The house mouse is the natural host of Rickettsia akari, which is the causative agent of rickettsialpox and a member of the spotted fever group of rickettsiae. Another rickettsial disease—murine typhus or endemic typhus—is transmitted to man by rat fleas; rats and mice are its natural reservoirs. Rickettsia mooseri—the causative agent—has not been isolated from natural infections in laboratory mice. Clinical signs, diagnosis, and control in man are similar to those described for rickettsialpox.


title: Lockdown Maths: Part 2: Relaxation of Lockdown—Perilous

text: The following article is reproduced with permission from The Telegraph, Kolkata (Guest Column, Published 30 March 2020).


title: “Holidays Come, Sundays Come. It is Very Sad to be Alone”: Transnational Practices and the Importance of Family for Mexican and Puerto Rican Latinxs Living with HIV in the Continental U.S.

text: Latinxs continue to be overrepresented in the U.S. HIV epidemic. We examined the transnational practices, family relationships, and realities of life of Mexicans and Puerto Ricans living with HIV in the continental U.S. We conducted qualitative interviews with 44 persons of Mexican and Puerto Rican origin participating in HIV care engagement interventions. Framework Analysis guided our data analysis. Among participants, a strong connection to the family was intertwined with transnational practices: communication, travel to their place of origin to maintain family ties, and material and/or emotional support. Separation from their family contributed to social isolation. Many participants lacked emotional support regarding living with HIV. Transnational practices and family relationships were intrinsic to the experiences of Mexicans and Puerto Ricans living with HIV in the continental U.S.; and may help understand the points of reference, health-seeking behaviors, and support sources that influence their health, well-being and engagement in HIV care.


title: Respiratory syncytial virus hospitalizations in US preterm infants after the 2014 change in immunoprophylaxis guidance by the American Academy of Pediatrics

text: Palivizumab is the only licensed and effective immunoprophylaxis (IP) available to prevent respiratory syncytial virus (RSV) infection in high-risk infants including infants born at ≤35 weeks’ gestational age (wGA). In 2014, the American Academy of Pediatrics stopped recommending IP for otherwise healthy 29–34 wGA infants, stating that their risk of RSV hospitalization (RSVH) was similar to term infants. Recent studies have demonstrated a significant decline in IP use after 2014 that was accompanied by an increased risk of RSVH in 29–34 wGA infants vs term infants. Severity and healthcare utilization of RSVH were high among 29–34 wGA infants. In 2018, the National Perinatal Association developed guidelines advocating IP use in all ≤32 wGA infants and 32–35 wGA infants with additional risk factors. Risk factor predictive models can identify infants who are at risk for RSVH and promote cost-effective use of palivizumab until new methods of RSV prevention become available.


Reflecting on the EU: the Good and the Bad Times, and Those That Are Yet to Come


title: Conclusions and Recommendations

text: Brexit represents an unprecedented moment for the European integration project. Despite the evident difficulties in assessing the impact of the still ongoing process on the cladenstine activity of illicit tradde, all in all, the potential effects of Brexit on illicit tobacco trade in the UK could be rather modest. One thing which emerges with certain clarity is that just as in many other policy areas, the control of the illicit trade of tobacco by the UK will depend ultemately on the Brexit scenario negotiated with EU. In the event of a leaving the single market, while losing economically on many ends, the UK would retain higher policy flexibilites. While still bound by the ITP, this may mean greater speed and flexibility in learning and improving upon existing global or regional norms in this field to its own benefit.


Almitrine as a non-ventilatory strategy to improve intrapulmonary shunt in COVID-19 patients


Entre guerras y pandemias ¿volveremos a ser los mismos? ¿Hay duda de la resiliencia de la humanidad?


Distance e-learning is closer than everybody thought: A Pharmacy Education Perspective


Virtual Didactics Exchanges to Enhance Trainee Education


title: Interrogating Naturalness of National Identity

text: Nation-state has been considered both an intellectual brainchild and a practical offshoot of the European Enlightenment. The liberal philosophy as an intellectual representative of the Enlightenment tradition and the modernists who emphasize modernization as the practical derivative of it not only deliberated on the simultaneousness and coexistence of the two happenings—the rise of national consciousness on the one hand and appreciation for modern values such as equality, liberty and justice on the other, many theorists argued that these modern values could be realized within a nation-state model (a modern institution). Hence, they contributed to naturalization and de-politicization of the nation-state model. Naturalization/secularization of the nation-state idea without deliberating on the possibilities of politicization and construction of national identities legitimize exclusion of people from national space, drives toward homogenization and nation-building process producing refugees and stateless people. Further, nation-states do not feel the urgency in meeting the normative demands of the international order that strive to defend human rights and address the problem of statelessness. In this context, the article seeks to interrogate the naturalness of national identity of individuals by examining the factors that tend to secularize and naturalize it and by unraveling the real socioeconomic forces that engender and shape national identity and help it look the way it does.


EP News Clinical June 2020


Salient lessons from Russia's COVID-19 outbreak


Fernando Morales


Healthier societies for healthy populations


Positive Outcome in a COVID-19 patient with Common Variable Immunodeficiency after IVIG


July 2020 - Avian & Exotic News


Test Technology Newsletter


From phenotypes to black holes… and back


1-(3-Dimethylaminopropyl)-3-Ethylcarbodiimide in the Synthesis of Glycyrrhizic Acid Amino-Acid Conjugates


title: Promote an unexpected online experience through richer content

text: Remote learning isn't a new concept, but it's been thrust into the spotlight as colleges and universities moved their traditionally face‐to‐face campus programs to online platforms in response to the COVID‐19 pandemic. It's too early to know for sure if this format of learning will continue to temporarily replace on‐the‐ground classes into the fall 2020 semester.


title: Alternatives to In‐Person Directors' Meetings

text: Edmund Polubinski, Jr. is a corporate lawyer at Lyne, Woodworth & Evarts LLP, a Boston‐based law firm. In this article, he notes the rise in virtual directors' meetings due to the COVID‐19 crisis and discusses how virtual meetings and several other alternatives to in‐person meetings can be a useful tool for many boards.


Educators Reflect on the COVID‐19 Crisis


Webinar looks at donor engagement during crises


Panic‐gogy: A Conversation With Sean Michael Morris


title: 2019 sees ‘return to normal’ when it comes to online giving

text: The latest Benchmarks Study from M+R Strategic Services shows that donations made online via email, text messages, social media platforms and organization websites logged double‐digit growth in 2019, after a flat 2018 and a big upward surge the year before that. In addition, email response rates improved for the first time in recent memory, and the use of text messaging and Facebook Fundraising has also grown as nonprofits find new ways to leverage tech to reach their supporters.


Contagion and memory


Schooling Amid a Pandemic


title: News

text: Students organize virtual reality commencement. Students studying abroad return home. AACRAO publishes survey on COVID‐19 changes. Paper calls for credit overhaul in midst of COVID‐19.


Uncertainty and Dark Optimism: A Sociological Account of Youth and the Promise of Higher Education in Post-Truth Era: Book Review of: Black, R., & Walsh, L. (2019): Imagining Youth Futures: University Students in Post-truth Times. Singapore: Springer


title: Scholar in the SEPR spotlight: Ian Douglas

text: In this reflective essay of intellectual autobiography, I respond to a series of questions the journal editor Wei-Ning Xiang asked about my 55-year journey from applied geography to socio-ecological practice research. These are (1) what and/or who had inspired your career most in geography and socio-ecological practice research? (2) Throughout your 55-year academic journey, did you ever reorient your ambitions in scholarly pursuit, or even reinvent yourself in your academic life? What motivated you in each of these instances? (3) How do you measure success in your work? Among many accomplishments, what are the top three that you are most proud of? (4) From your personal experience, what would be the most important attributes for a well-lived, fully realised, and meaningful life? Do you have any tips for maintaining work-life balance? (5) Do you have any specific advice for younger scholars in geography and socio-ecological practice research? (6) What are the three most interesting images reflecting turning points in your career? I hope that my experiences and insights showcased in this essay are helpful to the younger generations of geographers and socio-ecological practice researchers.


El papel del editor de una revista científica durante la pandemia del Covid-19


Mechanical power and driving pressure as predictors of mortality among patients with ARDS


title: Burnout in nursing: a theoretical review

text: BACKGROUND: Workforce studies often identify burnout as a nursing ‘outcome’. Yet, burnout itself—what constitutes it, what factors contribute to its development, and what the wider consequences are for individuals, organisations, or their patients—is rarely made explicit. We aimed to provide a comprehensive summary of research that examines theorised relationships between burnout and other variables, in order to determine what is known (and not known) about the causes and consequences of burnout in nursing, and how this relates to theories of burnout. METHODS: We searched MEDLINE, CINAHL, and PsycINFO. We included quantitative primary empirical studies (published in English) which examined associations between burnout and work-related factors in the nursing workforce. RESULTS: Ninety-one papers were identified. The majority (n = 87) were cross-sectional studies; 39 studies used all three subscales of the Maslach Burnout Inventory (MBI) Scale to measure burnout. As hypothesised by Maslach, we identified high workload, value incongruence, low control over the job, low decision latitude, poor social climate/social support, and low rewards as predictors of burnout. Maslach suggested that turnover, sickness absence, and general health were effects of burnout; however, we identified relationships only with general health and sickness absence. Other factors that were classified as predictors of burnout in the nursing literature were low/inadequate nurse staffing levels, ≥ 12-h shifts, low schedule flexibility, time pressure, high job and psychological demands, low task variety, role conflict, low autonomy, negative nurse-physician relationship, poor supervisor/leader support, poor leadership, negative team relationship, and job insecurity. Among the outcomes of burnout, we found reduced job performance, poor quality of care, poor patient safety, adverse events, patient negative experience, medication errors, infections, patient falls, and intention to leave. CONCLUSIONS: The patterns identified by these studies consistently show that adverse job characteristics—high workload, low staffing levels, long shifts, and low control—are associated with burnout in nursing. The potential consequences for staff and patients are severe. The literature on burnout in nursing partly supports Maslach’s theory, but some areas are insufficiently tested, in particular, the association between burnout and turnover, and relationships were found for some MBI dimensions only.


title: What Contributes to Stigma Towards Autistic University Students and Students with Other Diagnoses?

text: Little remains known about the degree to which autistic university students are stigmatized relative to students with other diagnoses. We conducted an online survey with students in New York City (n = 633) and Beirut (n = 274). Students with diagnoses that were perceived as dangerous (e.g., psychopathy) were more stigmatized than students with diagnoses that were perceived as less dangerous (e.g., autism). Disruptive autistic behaviors (described via vignettes) evoked more stigma than withdrawn behaviors. Perceived dangerousness predicted autism stigma. Greater acceptance of inequality, less openness, and lower cognitive empathy co-occurred with heightened stigma towards most conditions. Diagnostic labels were typically less stigmatized than behaviors. Findings suggest that interventions are needed to decrease stigma towards varied diagnoses in collegiate communities. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10803-020-04556-7) contains supplementary material, which is available to authorized users.


Zusammenhang zwischen Angiotensinblockade und Influenza-A-Inzidenz


title: Settler Witnessing at the Truth and Reconciliation Commission of Canada

text: This article offers an account of settler witnessing of residential school survivor testimony that avoids the politics of recognition and the pitfalls of colonial empathy. It knits together the concepts of bearing witness, Indigenous storytelling, and affective reckoning. Following the work of Kelly Oliver, it argues that witnessing involves a reaching beyond ourselves and responsiveness to the agency and self-determination of the other. Given the cultural genocide of residential schools, responsiveness to the other require openness to and nurturing of Indigenous ways of knowing and being. In order to illustrate the complexities and challenges of settler witnessing, the author reflects on her experiences in attending six of the TRC’s national events and, in particular, what she has learned from Frederick “Fredda” Paul, Passamaquoddy Elder, healer, storyteller, and residential school survivor. The article analyzes (1) aesthetics and emotions in the staging of TRC events and (2) making meaning over time and the temporality of transitional justice.


Editor's Note


Kongressankündigungen


Meldungen aus der SMS


title: Akupunktur und Moxibustion bei Pneumonie durch Infektion mit dem Corona-Virus (SARS-CoV-2): Übersetzt von Gerlinde Wislsperger, München

text: The author describes the ways in which acu-moxi therapy can be used to treat pneumonia following infection with the SARS-CoV-2-Virus, as proposed by selected experts in official bodies in the People’s Republic of China as guidance for hospital staff. At the beginning of the article, he makes it clear with a few historical quotations that Chinese medicine has been dealing with epidemic diseases for a long time and offers a range of treatment options for combating them. For the purpose of therapy, he differentiates between three stages of the disease: the suspected, the disease and the convalescence phase. In describing the interventions, acupuncture, moxibustion and ear acupuncture are of primary importance. In addition to focusing on the main therapeutic principle of strengthening the immune system, the article also mentions points for treating accompanying symptoms such as various forms of coughing, fever, weakness or nausea and vomiting. The possibilities of acupressure, Tuina and Qigong/Taiji are also considered as ways in which patients can actively participate in prevention and therapy.


title: Biomarkers of sepsis: time for a reappraisal

text: INTRODUCTION: Sepsis biomarkers can have important diagnostic, therapeutic, and prognostic functions. In a previous review, we identified 3370 references reporting on 178 different biomarkers related to sepsis. In the present review, we evaluate the progress in the research of sepsis biomarkers. METHODS: Using the same methodology as in our previous review, we searched the PubMed database from 2009 until September 2019 using the terms “Biomarker” AND “Sepsis.” There were no restrictions by age or language, and all studies, clinical and experimental, were included. RESULTS: We retrieved a total of 5367 new references since our previous review. We identified 258 biomarkers, 80 of which were new compared to our previous list. The majority of biomarkers have been evaluated in fewer than 5 studies, with 81 (31%) being assessed in just a single study. Apart from studies of C-reactive protein (CRP) or procalcitonin (PCT), only 26 biomarkers have been assessed in clinical studies with more than 300 participants. Forty biomarkers have been compared to PCT and/or CRP for their diagnostic value; 9 were shown to have a better diagnostic value for sepsis than either or both of these biomarkers. Forty-four biomarkers have been evaluated for a role in answering a specific clinical question rather than for their general diagnostic or prognostic properties in sepsis. CONCLUSIONS: The number of biomarkers being identified is still increasing although at a slower rate than in the past. Most of the biomarkers have not been well-studied; in particular, the clinical role of these biomarkers needs to be better evaluated.


title: Prevalence of HCV and/or HBV coinfection in Iranian HIV-infected patients

text: Aim: HIV-infected patients risk coinfection with HBV and HCV. This study aimed to investigate molecular epidemiology of HBV and HCV coinfection in Iranian HIV-infected individuals. Materials & methods: In this cross-sectional study, serological markers of HBV and HCV infection (hepatitis B surface antigen [HBsAg], hepatitis B e-antigen [HBeAg], hepatitis B e-antibody [HBeAb] and hepatitis B core antibody [HBcAb]) and anti-HCV antibodies [anti-HCV Abs] were tested in 198 Iranian HIV-infected patients. From plasma, HBV viral load was determined using COBAS TaqMan 48, and HCV-RNA was detected by reverse transcriptase-nested PCR. Results: 85 out of 198 (42.9%) patients were anti-HCV Ab positive and 42/198 (21.2%) had detectable HCV-RNA. Eight (4.0%) had traceable HBV-DNA. All these patients were infected by HBV genotype D. 55 (27.8%) were HBcAb positive. Nine (4.4%) were HBsAg and anti-HCV Ab positive. Conclusion: None were HIV-RNA/HCV-RNA/HBV-DNA positive, 21.2% were HIV-RNA/HCV-RNA positive and 4.0% were HIV-RNA/HBV-DNA positive. Therefore, studies on diagnosing these infections in HIV-infected individuals may be valuable.


Safe and Valuable Endoscopy in the COVID Era


The Impact of SARS-CoV-2 on Inflammatory Bowel Disease


Hepatology in the COVID Era: Another C Virus, again Challenging the Liver


Training Program in Gastroenterology: How Can It Survive the Pandemic?


Editorial Commentary


Abgesichert bei behördlich angeordneter Praxissschließung


In diesem Jahr ist alles anders!: Kein VSOU-Frühjahrskongress 2020 - ein Kommentar


Entlastungspraxen und Reserven mobilisieren


Het is zo stil


DGUV lässt D-Ärzte hängen


'Een pleister tegen tranen': Voorpublicatie


Wendbaarheid


COVID-19 - eine Bewährungsprobe


Versorgungsengpässe beseitigen


Verschiebung: EFORT-Kongress 2020


Jannie Oskam: 'Palliatieve zorgwereld kan wel wat patiënteninbreng gebruiken'


Praxisschließung bei fehlender Schutzausrüstung?: Fragen an BVOU-Justitiar Dr. Jörg Heberer


Sonderforschungsprojekt Online-Sprechstunde: Praxisbewertung durch den Sanitätsdienst der Bundeswehr


Nach 20 Jahren ist Schluss oder nicht?


Auch VSOU 2020 abgesagt: Fachliche und finanzielle Folgen


Zertifizierungen von EndoCert : ... in Zeiten von COVID-19


Ein Virus - viele Fragen: Antworten auf die wichtigsten arbeitsrechtlichen Fragen für Ärzte


The Impact of Trauma Systems on Patient Outcomes


Tuberculosis sepsis after tocilizumab treatment


We are great when we collaborate


The no-test abortion is a patient-centered abortion


title: Data-Driven Classifiers for Predicting Grass Growth in Northern Ireland: A Case Study

text: There are increasing pressures to combat climate change and improve sustainable land management. The agriculture industry is one of the most challenging areas for these changes, especially in Northern Ireland, as agriculture is one of the larger industries. Research has been carried out across the island of Ireland into methods of improving farm efficiency in multiple areas of farming, including livestock health, machinery improvements, and crop growth. Research has been carried out in this study into grass growth in the dairy farming sector, specifically within Northern Ireland. Grass growth prediction aims to inform farmers and policy makers in their decision-making process regarding sustainable land management in agriculture. The present work focuses on analysing and evaluating how data-driven classifiers can be used for grass growth prediction using the data related to soil content, weather, grass quality components etc. Four classifiers, namely Decision Trees, Random Forest, Naïve Bayes, and Neural Networks, are chosen for this purpose. Classification results based on a real-world data set are analysed and compared to evaluate and illustrate the performance and robustness of the classifiers. The results indicate that it is difficult to declare a single classifier with the highest performance and robustness. Nevertheless, it indicates that tree classification methods are better suited to the data to be studied, as opposed to probabilistic methods and weighted methods, e.g., the naïve Bayes classifier obtained a predictive performance of 78% when classifying spring seasonal grass growth data.


title: Investigation of Ranking Methods Within the Military Value of Information (VoI) Problem Domain

text: Determining the relative importance among vast amounts of individual pieces of information is a challenge in the military environment. By aggregating various military intelligence experts’ knowledge, decision support tools can be created. A next step in the continuing research in this area is to investigate the use of three prominent ranking methods for aggregating opinions of military intelligence analysts with respect to the Value of Information (VoI) problem domain. This paper offers discussion about ongoing VoI research and demonstrates outcomes from a military-related experiment using Borda count, Condorcet voting, and Instant-runoff voting (IRV) methods as ranking aggregation models. These ranking methods are compared to the “ground truth” as generated by the current fuzzy-based VoI prototype system. The results by incorporating the ranking models on the experiment’s data demonstrate the efficacy of these methods in aggregating Subject Matter Expert (SME) opinions and clearly demonstrate the “wisdom of the crowd” effect. Implications related to ongoing VoI research are discussed along with future research plans.


title: Performance and Interpretability in Fuzzy Logic Systems – Can We Have Both?

text: Fuzzy Logic Systems can provide a good level of interpretability and may provide a key building block as part of a growing interest in explainable AI. In practice, the level of interpretability of a given fuzzy logic system is dependent on how well its key components, namely, its rule base and its antecedent and consequent fuzzy sets are understood. The latter poses an interesting problem from an optimisation point of view – if we apply optimisation techniques to optimise the parameters of the fuzzy logic system, we may achieve better performance (e.g. prediction), however at the cost of poorer interpretability. In this paper, we build on recent work in non-singleton fuzzification which is designed to model noise and uncertainty ‘where it arises’, limiting any optimisation impact to the fuzzification stage. We explore the potential of such systems to deliver good performance in varying-noise environments by contrasting one example framework - ADONiS, with ANFIS, a traditional optimisation approach designed to tune all fuzzy sets. Within the context of time series prediction, we contrast the behaviour and performance of both approaches with a view to inform future research aimed at developing fuzzy logic systems designed to deliver both – high performance and high interpretability.


title: Modeling the Costs of Trade Finance During the Financial Crisis of 2008–2009: An Application of Dynamic Hierarchical Linear Model

text: The authors propose a dynamic hierarchical linear model (DHLM) to study the variations in the costs of trade finance over time and across countries in dynamic environments such as the global financial crisis of 2008–2009. The DHLM can cope with challenges that a dynamic environment entails: nonstationarity, parameters changing over time and cross-sectional heterogeneity. The authors employ a DHLM to examine how the effects of four macroeconomic indicators – GDP growth, inflation, trade intensity and stock market capitalization - on trade finance costs varied over a period of five years from 2006 to 2010 across 8 countries. We find that the effect of these macroeconomic indicators varies over time, and most of this variation is present in the year preceding and succeeding the financial crisis. In addition, the trajectory of time-varying effects of GDP growth and inflation support the “flight to quality” hypothesis: cost of trade finance reduces in countries with high GDP growth and low inflation, during the crisis. The authors also note presence of country-specific heterogeneity in some of these effects. The authors propose extensions to the model and discuss its alternative uses in different contexts.


title: A Graph Theory Approach to Fuzzy Rule Base Simplification

text: Fuzzy inference systems (FIS) gained popularity and found application in several fields of science over the last years, because they are more transparent and interpretable than other common (black-box) machine learning approaches. However, transparency is not automatically achieved when FIS are estimated from data, thus researchers are actively investigating methods to design interpretable FIS. Following this line of research, we propose a new approach for FIS simplification which leverages graph theory to identify and remove similar fuzzy sets from rule bases. We test our methodology on two data sets to show how this approach can be used to simplify the rule base without sacrificing accuracy.


title: Multi-agent Systems and Voting: How Similar Are Voting Procedures

text: We consider the problem of the evaluation of similarity of voting procedures which are crucial in voting, social choice and related fields. We extend our approach proposed in our former works and compare the voting procedures against some well established and intuitively appealing criteria, and using the number of criteria satisfied as a point of departure for analysis. We also indicate potential of this approach for extending the setting to a fuzzy setting in which the criteria can be satisfied to a degree, and to include a distance based analysis. A possibility to use elements of computational social choice is also indicated.


title: Polar Representation of Bipolar Information: A Case Study to Compare Intuitionistic Entropies

text: In this paper, a new approach to compare measures of entropy in the setting of the intuitionistic fuzzy sets introduced by Atanassov. A polar representation is introduced to represent such bipolar information and it is used to study the three main intuitionistic fuzzy sets entropies of the literature. A theoretical comparison and some experimental results highlight the interest of such a representation to gain knowledge on these entropies.


title: A L1 Minimization Optimal Corrective Explanation Procedure for Probabilistic Databases

text: We propose to use a, recently introduced, efficient L1 distance minimization through mixed-integer linear programming for minimizing the number of valuations to be modified inside an incoherent probabilistic assessment. This is in line with one basic principle of optimal corrective explanation for decision makers. A shrewd use of constraints and of slack variables permit to steer the correction of incoherent assessments towards aimed directions, like e.g. the minimal number of changes. Such corrective explanations can be searched alone, as minimal changes, or jointly with the property of being also inside the L1 distance minimizers (in a bi-optimal point of view). The detection of such bi-optimal solutions can be performed efficiently by profiting from the geometric characterization of the whole set of L1 minimizers and from the properties of L1 topology.


title: On the Impact of Fuzzy Constraints in the Variable Size and Cost Bin Packing Problem

text: The Variable Size and Cost Bin Packing Problem (VSCBPP) consists of minimizing the cost of all bins used to pack a set of items without exceeding the bins capacities. It is a well known NP-Hard problem with many practical applications. In this contribution we assume that the capacity of a bin can be understood in a flexible way (so it may allow some overload) thus leading to a fuzzy version of the VSCBPP with fuzzy constraints. We solve the proposed fuzzy VSCBPP by using the parametric approach based on [Formula: see text]-cuts, thus defining a set of related crisp problems. By using three different solving algorithms and several instances, we explore the impact of different degrees of relaxation not only in terms of cost, but also in the structure of the solutions.


title: From Eliza to Siri and Beyond

text: Since Eliza, the first chatbot ever, developed in the 60s, researchers try to make machines understand (or mimic the understanding) of Natural Language input. Some conversational agents target small talk, while others are more task-oriented. However, from the earliest rule-based systems to the recent data-driven approaches, although many paths were explored with more or less success, we are not there yet. Rule-based systems require much manual work; data-driven systems require a lot of data. Domain adaptation is (again) a current hot-topic. The possibility to add emotions to the conversational agents’ responses, or to make their answers capture their “persona”, are some popular research topics. This paper explains why the task of Natural Language Understanding is so complicated, detailing the linguistic phenomena that lead to the main challenges. Then, the long walk in this field is surveyed, from the earlier systems to the current trends.


title: Dynamic Pricing Using Thompson Sampling with Fuzzy Events

text: In this paper we study a repeated posted-price auction between a single seller and a single buyer that interact for a finite number of periods or rounds. In each round, the seller offers the same item for sale to the buyer. The seller announces a price and the buyer can decide to buy the item at the announced price or the buyer can decide not to buy the item. In this paper we study the problem from the perspective of the buyer who only gets to observe a stochastic measurement of the valuation of the item after he buys the item. Furthermore, in our model the buyer uses fuzzy sets to describe his satisfaction with the observed valuations and he uses fuzzy sets to describe his dissatisfaction with the observed price. In our problem, the buyer makes decisions based on the probability of a fuzzy event. His decision to buy or not depends on whether the satisfaction from having a high enough valuation for the item out weights the dissatisfaction of the quoted price. We propose an algorithm based on Thompson Sampling and demonstrate that it performs well using numerical experiments.


title: Explaining the Neural Network: A Case Study to Model the Incidence of Cervical Cancer

text: Neural networks are frequently applied to medical data. We describe how complex and imbalanced data can be modelled with simple but accurate neural networks that are transparent to the user. In the case of a data set on cervical cancer with 753 observations excluding, missing values, and 32 covariates, with a prevalence of 73 cases (9.69%), we explain how model selection can be applied to the Multi-Layer Perceptron (MLP) by deriving a representation using a General Additive Neural Network. The model achieves an AUROC of 0.621 CI [0.519,0.721] for predicting positive diagnosis with Schiller’s test. This is comparable with the performance obtained by a deep learning network with an AUROC of 0.667 [1]. Instead of using all covariates, the Partial Response Network (PRN) involves just 2 variables, namely the number of years on Hormonal Contraceptives and the number of years using IUD, in a fully explained model. This is consistent with an additive non-linear statistical approach, the Sparse Additive Model [2] which estimates non-linear components in a logistic regression classifier using the backfitting algorithm applied to an ANOVA functional expansion. This paper shows how the PRN, applied to a challenging classification task, can provide insights into the influential variables, in this case correlated with incidence of cervical cancer, so reducing the number of unnecessary variables to be collected for screening. It does so by exploiting the efficiency of sparse statistical models to select features from an ANOVA decomposition of the MLP, in the process deriving a fully interpretable model.


title: Ordinal Graph-Based Games

text: The graphical, hypergraphical and polymatrix games frameworks provide concise representations of non-cooperative normal-form games involving many agents. In these graph-based games, agents interact in simultaneous local subgames with the agents which are their neighbors in a graph. Recently, ordinal normal form games have been proposed as a framework for game theory where agents’ utilities are ordinal. This paper presents the first definition of Ordinal Graphical Games (OGG), Ordinal Hypergraphical Games (OHG), and Ordinal Polymatrix Games (OPG). We show that, as for classical graph-based games, determining whether a pure NE exists is also NP-hard. We propose an original CSP model to decide their existence and compute them. Then, a polynomial-time algorithm to compute possibilistic mixed equilibria for graph-based games is proposed. Finally, the experimental study is dedicated to test our proposed solution concepts for ordinal graph-based games.


title: Image-Based World-perceiving Knowledge Graph (WpKG) with Imprecision

text: Knowledge graphs are a data format that enables the representation of semantics. Most of the available graphs focus on the representation of facts, their features, and relations between them. However, from the point of view of possible applications of semantically rich data formats in intelligent, real-world scenarios, there is a need for knowledge graphs that describe contextual information regarding realistic and casual relations between items in the real world. In this paper, we present a methodology of generating knowledge graphs addressing such a need. We call them World-perceiving Knowledge Graphs – WpKG. The process of their construction is based on analyzing images. We apply deep learning image processing methods to extract scene graphs. We combine these graphs, and process the obtained graph to determine importance of relations between items detected on the images. The generated WpKG is used as a basis for constructing possibility graphs. We illustrate the process and show some snippets of the generated knowledge and possibility graphs.


title: Forecasting Electricity Consumption in Residential Buildings for Home Energy Management Systems

text: Prediction of the energy consumption is a key aspect of home energy management systems, whose aim is to increase the occupant’s comfort while reducing the energy consumption. This work, employing three years measured data, uses radial basis function neural networks, designed using a multi-objective genetic algorithm (MOGA) framework, for the prediction of total electric power consumption, HVAC demand and other loads demand. The prediction horizon desired is 12 h, using 15 min step ahead model, in a multi-step ahead fashion. To reduce the uncertainty, making use of the preferred set MOGA output, a model ensemble technique is proposed which achieves excellent forecast results, comparing additionally very favorably with existing approaches.


title: Combining Multi-Agent Systems and Subjective Logic to Develop Decision Support Systems

text: Nowadays, the rise of the interconnected computer networks and the increase of processed data have led to producing distributed systems. These systems usually separate multiple tasks into other simpler with the goal of maintaining efficiency. This paradigm has been observed for a long time in different animal organisations as insect colonies and fish shoals. For this reason, distributed systems that emulate the biological rules that govern their collective behaviour have been developed. Multi-Agent Systems (MAS) have shown their ability to address this issue. This paper proposes Ant Colony based Architecture with Subjective Logic (ACA-SL). It is a bio-inspired model based on ant colony structures. It makes use of MAS to distribute tasks and Subjective Logic (SL) to produce Decision Support Systems (DSS) according to the combination of individual opinions. A system implementation based on the proposed architecture has been generated to illustrate the viability of the proposal. The proposed architecture is intended to be the starting point for developing systems that solve a variety of problems.


title: Average Jane, Where Art Thou? – Recent Avenues in Efficient Machine Learning Under Subjectivity Uncertainty

text: In machine learning tasks an actual ‘ground truth’ may not be available. Then, machines often have to rely on human labelling of data. This becomes challenging the more subjective the learning task is, as human agreement can be low. To cope with the resulting high uncertainty, one could train individual models reflecting a single human’s opinion. However, this is not viable, if one aims at mirroring the general opinion of a hypothetical ‘completely average person’ – the ‘average Jane’. Here, I summarise approaches to optimally learn efficiently in such a case. First, different strategies of reaching a single learning target from several labellers will be discussed. This includes varying labeller trustability and the case of time-continuous labels with potential dynamics. As human labelling is a labour-intensive endeavour, active and cooperative learning strategies can help reduce the number of labels needed. Next, sample informativeness can be exploited in teacher-based algorithms to additionally weigh data by certainty. In addition, multi-target learning of different labeller tracks in parallel and/or of the uncertainty can help improve the model robustness and provide an additional uncertainty measure. Cross-modal strategies to reduce uncertainty offer another view. From these and further recent strategies, I distil a number of future avenues to handle subjective uncertainty in machine learning. These comprise bigger, yet weakly labelled data processing basing amongst other on reinforcement learning, lifelong learning, and self-learning. Illustrative examples stem from the fields of Affective Computing and Digital Health – both notoriously marked by subjectivity uncertainty.


title: Feature Reduction in Superset Learning Using Rough Sets and Evidence Theory

text: Supervised learning is an important branch of machine learning (ML), which requires a complete annotation (labeling) of the involved training data. This assumption, which may constitute a severe bottleneck in the practical use of ML, is relaxed in weakly supervised learning. In this ML paradigm, training instances are not necessarily precisely labeled. Instead, annotations are allowed to be imprecise or partial. In the setting of superset learning, instances are assumed to be labeled with a set of possible annotations, which is assumed to contain the correct one. In this article, we study the application of rough set theory in the setting of superset learning. In particular, we consider the problem of feature reduction as a mean for data disambiguation, i.e., for the purpose of figuring out the most plausible precise instantiation of the imprecise training data. To this end, we define appropriate generalizations of decision tables and reducts, using information-theoretic techniques based on evidence theory. Moreover, we analyze the complexity of the associated computational problems.


title: Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria

text: In many practical situations, we only know the interval containing the quantity of interest, we have no information about the probabilities of different values within this interval. In contrast to the cases when we know the distributions and can thus use Monte-Carlo simulations, processing such interval uncertainty is difficult – crudely speaking, because we need to try all possible distributions on this interval. Sometimes, the problem can be simplified: namely, for estimating the range of values of some characteristics of the distribution, it is possible to select a single distribution (or a small family of distributions) whose analysis provides a good understanding of the situation. The most known case is when we are estimating the largest possible value of Shannon’s entropy: in this case, it is sufficient to consider the uniform distribution on the interval. Interesting, estimating other characteristics leads to the selection of the same uniform distribution: e.g., estimating the largest possible values of generalized entropy or of some sensitivity-related characteristics. In this paper, we provide a general explanation of why uniform distribution appears in different situations – namely, it appears every time we have a permutation-invariant optimization problem with the unique optimum. We also discuss what happens if we have an optimization problem that attains its optimum at several different distributions – this happens, e.g., when we are estimating the smallest possible value of Shannon’s entropy (or of its generalizations).


title: Dempster-Shafer Parzen-Rosenblatt Hidden Markov Fields for Multichannel Image Segmentation

text: Theory of evidence has been successfully used in many areas covering pattern recognition and image processing due to its effectiveness in both information fusion and reasoning under uncertainty. Such notoriety led to extension of many existing Bayesian tools such as hidden Markov models, extensively used for image segmentation. This paper falls under this category of frameworks and aims to propose a new hidden Markov field that better handles nonGaussian forms of noise, designed for multichannel image segmentation. To this end, we use a recent kernel smoothing- based noise density estimation combined with a genuine approach of mass determination from data. The proposed model is validated on sampled and real remote sensing images and the results obtained outperform those produced by conventional hidden Markov fields.


title: On Relevance of Linguistic Summaries – A Case Study from the Agro-Food Domain

text: We present an application of linguistic summaries in the agro-food domain. We focus on the relevance aspect. Using the interviews we determine which linguistic summaries are useful and appropriate for target users (farmers). The user evaluation with a TAM survey indicates that linguistic summaries allow farmers to understand quickly the past performance of their pig barns.


title: Creating Classification Models from Textual Descriptions of Companies Using Crunchbase

text: This paper compares different models for multilabel text classification, using information collected from Crunchbase, a large database that holds information about more than 600000 companies. Each company is labeled with one or more categories, from a subset of 46 possible categories, and the proposed models predict the categories based solely on the company textual description. A number of natural language processing strategies have been tested for feature extraction, including stemming, lemmatization, and part-of-speech tags. This is a highly unbalanced dataset, where the frequency of each category ranges from 0.7% to 28%. Our findings reveal that the description text of each company contain features that allow to predict its area of activity, expressed by its corresponding categories, with about 70% precision, and 42% recall. In a second set of experiments, a multiclass problem that attempts to find the most probable category, we obtained about 67% accuracy using SVM and Fuzzy Fingerprints. The resulting models may constitute an important asset for automatic classification of texts, not only consisting of company descriptions, but also other texts, such as web pages, text blogs, news pages, etc.


title: On the Analysis of Illicit Supply Networks Using Variable State Resolution-Markov Chains

text: The trade in illicit items, such as counterfeits, not only leads to the loss of large sums of private and public revenue, but also poses a danger to individuals, undermines governments, and—in the most extreme cases—finances criminal organizations. It is estimated that in 2013 trade in illicit items accounted for [Formula: see text] of the global commerce. To combat illicit trade, it is necessary to understand its illicit supply networks. Therefore, we present in this article an approach that is able to find an optimal description of an illicit supply network using a series of Variable State Resolution-Markov Chains. The new method is applied to a real-world dataset stemming from the Global Product Authentication Service of Micro Focus International. The results show how an illicit supply network might be analyzed with the help of this method.


The discovery of knowledge by analyzing time series is an important field of research. In this paper we investigate multiple multivariate time series, because we assume a higher information value than regarding only one time series at a time. There are several approaches which make use of the granger causality or the cross correlation in order to analyze the influence of time series on each other. In this paper we extend the idea of mutual influence and present FCSETS (Fuzzy Clustering Stability Evaluation of Time Series), a new approach which makes use of the membership degree produced by the fuzzy c-means (FCM) algorithm. We first cluster time series per timestamp and then compare the relative assignment agreement (introduced by Eyke Hüllermeier and Maria Rifqi) of all subsequences. This leads us to a stability score for every time series which itself can be used to evaluate single time series in the data set. It is then used to rate the stability of the entire clustering. The stability score of a time series is higher the more the time series sticks to its peers over time. This not only reveals a new idea of mutual time series impact but also enables the identification of an optimal amount of clusters per timestamp. We applied our model on different data, such as financial, country related economy and generated data, and present the results.


title: Maximal Clique Based Influence Maximization in Networks

text: Influence maximization is a fundamental problem in several real life applications such as viral marketing, recommendation system, collaboration and social networks. Maximizing influence spreading in a given network aims to find the initially active vertex set of size k called seed nodes (or initial spreaders (In this paper, we use seed set and initial spreaders interchangeably.)) which maximizes the expected number of the infected vertices. The state-of-the-art local-based techniques developed to solve this problem are based on local structure information such as degree centrality, nodes clustering coefficient, and others utilize the whole network structure, such as k-core decomposition, and node betweenness. In this paper, we aim at solving the problem of influence maximization using maximal clique problem. Our intuition is based on the fact that the presence of a dense neighborhood around a node is fundamental to the maximization of influence. Our approach follows the following three steps: (1) discovering all the maximal cliques from the complex network; (2) filtering the set of maximal cliques; we then denote the vertices belonging to the rest of maximal cliques as superordinate vertices, and (3) ranking the superordinate nodes according to some indicators. We evaluate the proposed framework empirically against several high-performing methods on a number of real-life datasets. The experimental results show that our algorithms outperform existing state-of-the-art methods in finding the best initial spreaders in networks.


title: Evaluation of Uncertainty Quantification in Deep Learning

text: Artificial intelligence (AI) is nowadays included into an increasing number of critical systems. Inclusion of AI in such systems may, however, pose a risk, since it is, still, infeasible to build AI systems that know how to function well in situations that differ greatly from what the AI has seen before. Therefore, it is crucial that future AI systems have the ability to not only function well in known domains, but also understand and show when they are uncertain when facing something unknown. In this paper, we evaluate four different methods that have been proposed to correctly quantifying uncertainty when the AI model is faced with new samples. We investigate the behaviour of these models when they are applied to samples far from what these models have seen before, and if they correctly attribute those samples with high uncertainty. We also examine if incorrectly classified samples are attributed with an higher uncertainty than correctly classified samples. The major finding from this simple experiment is, surprisingly, that the evaluated methods capture the uncertainty differently and the correlation between the quantified uncertainty of the models is low. This inconsistency is something that needs to be further understood and solved before AI can be used in critical applications in a trustworthy and safe manner.


title: To BERT or Not to BERT Dealing with Possible BERT Failures in an Entailment Task

text: In this paper we focus on an Natural Language Inference task. Being given two sentences, we classify their relation as NEUTRAL, ENTAILMENT or CONTRADICTION. Considering the achievements of BERT (Bidirectional Encoder Representations from Transformers) in many Natural Language Processing tasks, we use BERT features to create our base model for this task. However, several questions arise: can other features improve the performance obtained with BERT? If we are able to predict the situations in which BERT will fail, can we improve the performance by providing alternative models for these situations? We test several strategies and models, as alternatives to the standalone BERT model in the possible failure situations, and we take advantage of semantic features extracted from Discourse Representation Structures.


title: Generalized Weak Transitivity of Preference

text: Decision making processes are often based on (pairwise) preference relations. An important property of preference relations is transitivity. Many types of transitivity have been proposed in the literature, such as max–min and max–max transitivity, restricted max–min and max–max transitivity, additive and multiplicative transitivity, or Łukasiewicz transitivity. This paper focuses on weak transitivity. Weak transitivity has been defined for additive preference relations. We extend this definition to multiplicative preference relations and further introduce a generalized version called generalized weak transitivity. We show that for reciprocal additive and multiplicative preference relations weak transitivity is equivalent to generalized weak transitivity, and we also illustrate generalized weak transitivity for preference relations that are neither additive nor multiplicative. Finally, we show how a total order (ranking of the options) can be constructed for any generalized weak transitive preference relation.


title: Towards Multi-perspective Conformance Checking with Aggregation Operations

text: Conformance checking techniques are widely adopted to validate process executions against a set of constraints describing the expected behavior. However, most approaches adopt a crisp evaluation of deviations, with the result that small violations are considered at the same level of significant ones. Furthermore, in the presence of multiple data constraints the overall deviation severity is assessed by summing up each single deviation. This approach easily leads to misleading diagnostics; furthermore, it does not take into account user’s needs, that are likely to differ depending on the context of the analysis. We propose a novel methodology based on the use of aggregation functions, to assess the level of deviation severity for a set of constraints, and to customize the tolerance to deviations of multiple constraints.


title: Solving Dynamic Delivery Services Using Ant Colony Optimization

text: This article presents a model for courier services designed to guide a fleet of vehicles over a dynamic set of requests. Motivation for this problem comes from a real-world scenario in an ever-changing environment, where the time to solve such optimization problem is constrained instead of endlessly searching for the optimal solution. First, a hybrid method combining Ant Colony Optimization with Local Search is proposed, which is used to solve a given static instance. Then, a framework to handle and adapt to dynamic changes over time is defined. A new method pairing nearest neighbourhood search with subtractive clustering is proposed to improve initial solutions and accelerate the convergence of the optimization algorithm. Overall, the proposed strategy presents good results for the dynamic environment and is suitable to be applied on real-world scenarios.


title: Competitive Online Quantile Regression

text: Interval prediction often provides more useful information compared to a simple point forecast. For example, in renewable energy forecasting, while the initial focus has been on deterministic predictions, the uncertainty observed in energy generation raises an interest in producing probabilistic forecasts. One aims to provide prediction intervals so that outcomes lie in the interval with a given probability. Therefore, the problem of estimating the quantiles of a variable arises. The contribution of our paper is two-fold. First, we propose to apply the framework of prediction with expert advice for the prediction of quantiles. Second, we propose a new competitive online algorithm Weak Aggregating Algorithm for Quantile Regression (WAAQR) and prove a theoretical bound on the cumulative loss of the proposed strategy. The theoretical bound ensures that WAAQR is asymptotically as good as any quantile regression. In addition, we provide an empirical survey where we apply both methods to the problem of probability forecasting of wind and solar powers and show that they provide good results compared to other predictive models.


title: Fuzzy Memories of Enrique Hector Ruspini (1942–2019)

text: This paper is a personal obituary of Enrique Hector Ruspini, an extraordinary scientist, tireless researcher, a smart science organizer and a great man. It can only mention a few of his scientific and private interests, achievements and achievements.


title: MaTED: Metadata-Assisted Twitter Event Detection System

text: Due to its asynchronous message-sharing and real-time capabilities, Twitter offers a valuable opportunity to detect events in a timely manner. Existing approaches for event detection have mainly focused on building a temporal profile of named entities and detecting unusually large bursts in their usage to signify an event. We extend this line of research by incorporating external knowledge bases such as DBPedia, WordNet; and exploiting specific features of Twitter for efficient event detection. We show that our system utilizing temporal, social, and Twitter-specific features yields improvement in the precision, recall, and DERate on the benchmarked Events2012 corpus compared to the state-of-the-art approaches.


title: Possibilistic Estimation of Distributions to Leverage Sparse Data in Machine Learning

text: Prompted by an application in the area of human geography using machine learning to study housing market valuation based on the urban form, we propose a method based on possibility theory to deal with sparse data, which can be combined with any machine learning method to approach weakly supervised learning problems. More specifically, the solution we propose constructs a possibilistic loss function to account for an uncertain supervisory signal. Although the proposal is illustrated on a specific application, its basic principles are general. The proposed method is then empirically validated on real-world data.


title: Why Spiking Neural Networks Are Efficient: A Theorem

text: Current artificial neural networks are very successful in many machine learning applications, but in some cases they still lag behind human abilities. To improve their performance, a natural idea is to simulate features of biological neurons which are not yet implemented in machine learning. One of such features is the fact that in biological neural networks, signals are represented by a train of spikes. Researchers have tried adding this spikiness to machine learning and indeed got very good results, especially when processing time series (and, more generally, spatio-temporal data). In this paper, we provide a possible theoretical explanation for this empirical success.


title: A Probabilistic Approach for Discovering Daily Human Mobility Patterns with Mobile Data

text: Analyzing human mobility with geo-location data collected from smartphones has been a hot research topic in recent years. In this paper, we attempt to discover daily mobile patterns using the GPS data. In particular, we view this problem from a probabilistic perspective. A non-parametric Bayesian modeling method, the Infinite Gaussian Mixture Model (IGMM) is used to estimate the probability density of the daily mobility. We also utilize the Kullback-Leibler (KL) divergence as the metrics to measure the similarity of different probability distributions. Combining the IGMM and the KL divergence, we propose an automatic clustering algorithm to discover mobility patterns for each individual user. Finally, the effectiveness of our method is validated on the real user data collected from different real users.


title: Decision Under Ignorance: A Comparison of Existing Criteria

text: In this study, we compare the behavior of classic Hurwicz criterion with three more recent criteria [Formula: see text]-anchor, [Formula: see text] and [Formula: see text]. This evaluation is realized on linear optimization problems with uncertain costs coefficients taking into account the risk aversion of the decision maker. The uncertainty is represented by a scenario set.


title: Hierarchical Reasoning and Knapsack Problem Modelling to Design the Ideal Assortment in Retail

text: The survival of a supermarket chain is heavily dependent on its capacity to maintain the loyalty of its customers. Proposing adequate products to customers is the issue of the store’s assortment. With tens thousands of products on shelves, designing the ideal assortment is theoretically a thorny combinatorial optimization problem. The approach we propose includes prior knowledge on the hierarchical organization of products by family to formalize the ideal assortment problem into a knapsack problem. The main difficulty of the optimization problem remains the estimation of the expected benefits associated to changes in the product range of products’ families. This estimate is based on the accounting results of similar stores. The definition of the similarity between two stores is then crucial. It is based on the prior knowledge on the hierarchical organization of products that allows approximate reasoning to compare any two stores and constitutes the major contribution of this paper.


title: Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems

text: This work introduces a scheduling technique using the Artificial Bee Colony (ABC) algorithm for static and dynamic environments. The ABC algorithm combines different initial populations and generation of new food source methods, including a moving operations technique and a local search method increasing the variable neighbourhood search that, as a result, improves the solution quality. The algorithm is validated and its performance is tested in a static environment in 9 instances of Flexible Job Shop Problem (FJSP) from Brandimarte dataset obtaining in 5 instances the best known for the instance under study and a new best known in instance mk05. The work also focus in developing tools to process the information on the factory through the development of solutions when facing disruptions and dynamic events. Three real-time events are considered on the dynamic environment: jobs cancellation, operations cancellation and new jobs arrival. Two scenarios are studied for each real-time event: the first situation considers the minimization of the disruption between the previous schedule and the new one and the second situation generates a completely new schedule after the occurrence. Summarizing, six adaptations of ABC algorithm are created to solve dynamic environment scenarios and their performances are compared with the benchmarks of two case studies outperforming both.


title: Feature Extraction with TF-IDF and Game-Theoretic Shadowed Sets

text: TF-IDF is one of the most commonly used weighting metrics for measuring the relationship of words to documents. It is widely used for word feature extraction. In many research and applications, the thresholds of TF-IDF for selecting relevant words are only based on trial or experiences. Some cut-off strategies have been proposed in which the thresholds are selected based on Zipf’s law or feedbacks from model performances. However, the existing approaches are restricted in specific domains or tasks, and they ignore the imbalance of the number of representative words in different categories of documents. To address these issues, we apply game-theoretic shadowed set model to select the word features given TF-IDF information. Game-theoretic shadowed sets determine the thresholds of TF-IDF using game theory and repetition learning mechanism. Experimental results on real world news category dataset show that our model not only outperforms all baseline cut-off approaches, but also speeds up the classification algorithms.


title: From Truth Degree Comparison Games to Sequents-of-Relations Calculi for Gödel Logic

text: We introduce a game for (extended) Gödel logic where the players’ interaction stepwise reduces claims about the relative order of truth degrees of complex formulas to atomic truth comparison claims. Using the concept of disjunctive game states this semantic game is lifted to a provability game, where winning strategies correspond to proofs in a sequents-of-relations calculus.


title: Acoustic Feature Selection with Fuzzy Clustering, Self Organizing Maps and Psychiatric Assessments

text: Acoustic features about phone calls are promising markers for prediction of bipolar disorder episodes. Smartphones enable collection of voice signal on a daily basis, and thus, the amount of data available for analysis is quickly growing. At the same time, even though the collected data are crisp, there is a lot of imprecision related to the extraction of acoustic features, as well as to the assessment of patients’ mental state. In this paper, we address this problem and perform an advanced approach to feature selection. We start from the recursive feature elimination, then two alternative approaches to clustering (fuzzy clustering and self organizing maps) are performed. Finally, taking advantage of the partially assumed labels about the state of a patient derived from psychiatric assessments, we calculate the degree of agreement between clusters and labels aiming at selection of most adequate subset of acoustic parameters. The proposed method is preliminary validated on the real-life data gathered from smartphones of bipolar disorder patients.


title: Continuous Analogical Proportions-Based Classifier

text: Analogical proportions, often denoted [Formula: see text], are statements of the form “A is to B as C is to D” that involve comparisons between items. They are at the basis of an inference mechanism that has been recognized as a suitable tool for classification and has led to a variety of analogical classifiers in the last decade. Given an object D to be classified, the basic idea of such classifiers is to look for triples of examples (A, B, C), in the learning set, that form an analogical proportion with D, on a maximum set of attributes. In the context of classification, objects A, B, C and D are assumed to be represented by vectors of feature values. Analogical inference relies on the fact that if a proportion [Formula: see text] is valid, one of the four components of the proportion can be computed from the three others. Based on this principle, analogical classifiers have a cubic complexity due to the search for all possible triples in a learning set to make a single prediction. A special case of analogical proportions involving only three items A, B and C are called continuous analogical proportions and are of the form “A is to B as B is to C” (hence denoted [Formula: see text]). In this paper, we develop a new classification algorithm based on continuous analogical proportions and applied to numerical features. Focusing on pairs rather than triples, the proposed classifier enables us to compute an unknown midpoint item B given a pair of items (A, C). Experimental results of such classifier show an efficiency close to the previous analogy-based classifier while maintaining a reduced quadratic complexity.


title: Using Topic Information to Improve Non-exact Keyword-Based Search for Mobile Applications

text: Considering the wide offer of mobile applications available nowadays, effective search engines are imperative for an user to find applications that provide a specific desired functionality. Retrieval approaches that leverage topic similarity between queries and applications have shown promising results in previous studies. However, the search engines used by most app stores are based on keyword-matching and boosting. In this paper, we explore means to include topic information in such approaches, in order to improve their ability to retrieve relevant applications for non-exact queries, without impairing their computational performance. More specifically, we create topic models specialized on application descriptions and explore how the most relevant terms for each topic covered by an application can be used to complement the information provided by its description. Our experiments show that, although these topic keywords are not able to provide all the information of the topic model, they provide a sufficiently informative summary of the topics covered by the descriptions, leading to improved performance.