Thorough spatial and statistical analyses were undertaken to identify the pre- and during pandemic nitrogen dioxide concentrations. Complementarily, Spearman’s correlation test was performed with variables that impact air quality. The study results a fall in nitrogen dioxide concentration levels in 21 of the 24 metropolitan regions which was observed. The Spearman’s correlation coefficient between the nitrogen dioxide variation and the vehicle density was 0.485, at a significance level of 0.05. With these findings in mind, the paper advocates that while the pandemic has a significant negative consequence on the health of population globally, a series of measures that result in a new social organization directly interfere in the reduction of air pollution that contributes to the quality of the air we breathe.The Covid-19 pandemic has negatively disrupted the way our economy and society functions. Nonetheless, there have also been some positive externalities of the pandemic on the environment. This paper aims to evaluate the concentration of nitrogen dioxide in Brazilian metropolitan regions after the policies adopted to confront Covid-19. In terms of methodological approach, the study employs cross-sectional quantitative analyses to compare the period of 36 days, i.e., 12 March to 16 April—before (in 2019) and after (in 2020) the pandemic declaration. The data were obtained from the Sentinel 5-P low-Earth polar satellite concerning Brazilian metropolitan regions ( Due to Nonetheless, the recent changes in the diagnostic criteria of the disease have led to an increase in the rate of new cases and, every day, increasing numbers and challenges have been the subject of intense debate in the scientific community , thin particulate material , and increased ozone (O3) concentration in different regions of the globe , people declared they have noticed an improvement in the quality of the breathed air after the adoption of social isolation in their regions . In a complementary way, the study focused on evaluating the association of other variables that can directly impact the concentration of atmospheric NO2, such as the density of vehicles, especially of combustion engines, in the Brazilian metropolitan regions , whose purpose is to obtain information and services of air quality, ozone layer, and climate (TROPOMI 2018). The satellite is equipped with the tropospheric monitoring instrument (TROPOMI—Tropospheric Monitoring Instrument), an image spectrometer that covers ranges of ultraviolet (UV—ultraviolet), visible (VIS—visible), near infrared (NIR), and short-wave infrared (SWIR), using passive remote sensing techniques to measure, at the top of the atmosphere, the reflected and irradiated solar radiation of the Earth , nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), methane (CH4), formaldehyde (HCHO), and aerosols  of Google Earth Engine, from where it is possible to obtain the mean and standard deviation of NO2 concentrations in the troposphere, also called Near Real-time High-resolution Imagery (NRTI), distributed by ESA and post-processed by the Google Earth Engine API. It is worth noting that daily climatic events, such as the presence of clouds, reduce the quality of images and can influence reading at the time of the satellite overpass. For this purpose, only satellite images with pixels of quality above 75% were used, that is, with the attribute “qa_value” greater than 0.75, in order to avoid erroneous interpretations affected by data quality , with 24 regions participating in the study.The maps of this 36-day average time were compared to maps from the same period in 2019 to assess the change in NO2 concentration variations were obtained, these data were compared with the population and vehicle densities of the metropolitan regions, in addition to the variation in the ozone (O3) concentration. The population data of the municipalities that make up the metropolitan regions were obtained on the website of the Brazilian Institute of Geography and Statistics (IBGE 2020), taking into account the population estimate of 2020, in order to obtain the ratio of inhabitants per kilometer square of each region.Once the NOThe density of vehicles in the metropolitan regions was calculated by the relationship between the fleet of licensed vehicles in the municipalities that make up the metropolitan region in April 2020 and the area of each metropolitan region. The fleet of licensed vehicle was obtained from the website of the National Transportation Department (DENATRAN 2020) of the Ministry of Infrastructure and the metropolitan region area was obtained from Institute of Applied Economic Research (IPEA) (IPEA 2020), in order to obtain the ratio of number of vehicles per kilometer square.3 was obtained by the same method used to define the concentration of NO2, previously described. To examine the monotonic association between the variables, the SPSS software was used, where Spearman’s correlation test was performed. The test was chosen in order to assess the strength of the correlation between the variables, and the association results generated were plotted in a table and interpreted at a significance level of 0.05 , which demonstrate the variation of NO2 in all metropolitan regions studied, and also in Table The results of the atmospheric concentration of NO2 in the comparison between the period of 2019 (left) and 2020 (right). This was the highest percentage reduction observed in the metropolitan regions that were object of this study.Baixada Santista metropolitan region, located on the coast of the state of São Paulo, showed a 48.7% reduction in the concentration of NO2 were limited to the urban and industrial nucleus of the cities of Cubatão and Santos, unlike the period of 2019, where the high concentrations were observed more than 40 km from these cities.As shown in Fig. 2 in the two periods studied. The map in Fig. Belém metropolitan region, located in northern Brazil, presented a little significant reduction of 2.6% in the concentration of NOIn Belo Horizonte metropolitan region, located in southeastern Brazil, the reduction observed was 11.3%, even though it was delimited in a polygon of larger scale. Then, we observe a significant reduction of 20% in the region of Campinas, which had high concentrations, in 2019, between Campinas and Americana, not observed in the period of 2020.Finally, the reduction is also substantial in the metropolitan region of Curitiba, located in the Southern region of Brazil, where there was a decrease of 17.5%.2. As shown in Table In the metropolitan region of Florianópolis, in southern Brazil, there was an expressive reduction of 30.3% in the concentration of NO2 concentration; however, this reduction of only 5.2% is overshadowed by the scale of the metropolitan region, which covers a polygon with thousands of square kilometers, as illustrated in Fig. 2, different from results observed so far.The metropolitan region of Manaus, located in the state of Amazonas, northern Brazil, showed a small reduction in atmospheric NO2 concentration, 26.6%. In this case, the substantial reduction was observed in both the mean concentration of NO2 and the standard deviation when comparing the results of 2019 and 2020.In the metropolitan region of Rio de Janeiro, located in the state of the same name and southeastern region of Brazil, there was a significant reduction in NOIn the metropolitan regions of Salvador and São Luís, both located in the northeast region, there was a reduction of 32.5 and 11.2%, respectively. Figure Finally, the metropolitan region of São Paulo, the largest in the country, also located in the southeast region, had the second largest percentage (37.9%) reduction among the metropolitan regions studied.2 in the compared periods was 21.6%. Figure 2, although there was a reduction, according to Fig. In the metropolitan region of Sorocaba, located in the state of São Paulo, the reduction of NO2.The metropolitan region of Teresina, located in the northeast, also showed low variation in the atmospheric concentration of NOA percentage reduction of 18.8% was observed in the Distrito Federal , in the Brazilian Midwest region. Although the reduction is significant, the concentration values are considered low in both periods, as shown in Fig. Finally, the metropolitan region of Cuiabá, also in the Midwest, registered an increase of 15.7% in 2020 compared to 2019, a movement in the opposite direction to that observed in most metropolitan regions. It is observed, however, that like Manaus MR, the MR scale can distort the results, since the urban center of Cuiabá occupies only a small fraction of the polygon.2 concentration (only reduction) in all metropolitan regions. The higher the reduction, the higher the intensity of green color.Figures 2 concentration in the Brazilian metropolitan regions evaluated.Table 2. Even in regions with no reduction, one can verify the effect of the scale of the metropolitan region on the result, as occurred in Cuiabá. Similarly, in Vitória MR, there was a significant reduction in the urban centers of Vitória and Vila Velha; however, the result was affected by the adjacent regions and not necessarily in inhabited areas, although within the metropolitan region.It is possible to observe that in 21 (87.5%) of the 24 metropolitan regions there was a reduction in the mean concentration of atmospheric NO2 in the comparison between the two periods was observed in most of the metropolitan regions. However, being a continental country, the Brazilian metropolitan regions have different socioeconomic characteristics, such as territorial extension, population, and number of vehicles circulating in the regions.The reduction of NO2 concentration and the population density (number of inhabitants per square kilometer), the density of vehicles (number of vehicles per square kilometer), and the variation in O3 concentration  in metropolitan regions.Table 2 variation and the vehicle density. This means that in the evaluated metropolitan regions, as the density of vehicles increases, a reduction in the concentration of atmospheric NO2 is expected. The existence of a positive moderate correlation was also verified for population density (Spearman’s Rho = 0.424). These are indications that point to the relevance of the contribution of combustion engines to air quality in metropolitan regions.At a significance level of 0.05, a moderate positive correlation (Spearman’s Rho = 0.485) was found between the NO3, as the p-value is above the 0.05 significance level, the association between variations in the concentration of NO2 and O3 was inconclusive, although the correlation coefficient shows a moderate negative correlation.Regarding O2 concentrations in 21 Brazilian metropolitan regions between March 12 and April 16, 2020, compared to the same period in 2019. Table 2 of 48.7% in the metropolitan region of Baixada Santista, a place with the greatest reduction, followed by the region of São Paulo (37.8%) and Salvador (32.5%). In São Paulo, the reduction observed in this study for the concentration of NO2 is in line with the results obtained by automatic air quality monitoring stations, which revealed a 25% reduction in concentration in March 2020 when compared to March from 2015 to 2019 . In this work was verified a small increase of 3.6% in the concentration of NO2 in the MR, confirming the insignificant variation observed by the environmental agency.In the state of Rio Grande do Sul, the State Foundation for Environmental Protection (FEPAM) issued a report concluding that there were no significant changes in the concentration of NO2.5 and PM10 in the periods of 20 March and 20 April in 2019 and 2020. There are two automatic monitoring stations in the metropolitan region of Belo Horizonte. The first showed a reduction of 31% in the concentration of PM10 and 45% in the concentration of PM2.5, while the second station pointed out a reduction of 10% for PM10 and 26% for PM2.5  in all metropolitan regions, that a reduction in concentration was observed and the population and vehicle fleet remained relatively stable during the period, it was possible to observe the indirect effects of population and vehicle density in the reduction of NO2 concentration. At a significance level of 0.05, the Spearman correlation coefficient found was 0.424 (population density) and 0.485 (vehicle density). The results indicate that there seems to be a dependency, albeit indirect, between the variables. This means that in those metropolitan regions where there are more vehicles per square kilometer there is a tendency for a more accentuated variation in the concentration of NO2. Higher vehicle densities may be related to a greater number of NO2 emitting hot spots, such as high-flow highways or roads and traffic jams.The study at hand also investigated the effects of population and vehicle density on the percentage variation of NO2 emission that, consequently, will interfere in other important health indicators.This measure of concentration of pollutants in the air can be an important public health factor, because as pollution levels decrease, there is a 6% reduction in mortality cases (39). Considering that the interaction of the human being with the environment that is lived produces an important part of emissions that lead to air pollution Derísio , the eviThis is because data from the WHO show that more than four million people died worldwide from respiratory diseases per year  pandemic showed a reduction in the emission of NO2 causes toxicity when there is long-term exposure, in the maintenance of air quality and the planet’s biodiversity, because the high level of this compound in the air leads to damage to nature due to its corrosive characteristic, causing acid rain which, when falling to the surface, alters the chemical composition of the soil and water, reaching food chains, destroying forests and crops.This study raises the government’s need to encourage public policies that enable a rational organization about economic activities and the preservation of the environment in the post-pandemic period, since such actions impact on the reduction of mortality rates from other diseases respiratory, since the increase in NO2 emission, such as accessible public transport, use of alternative energy sources, such as electricity, solar, biofuel, to maintain the health of the population.Therefore, this research leads to reflection on new strategies that are alternatives to the reduction of NO2 emissions has begun to falter. The pervasive disruptions from the Covid-19 pandemic have radically altered the trajectory of global CO2 emissions. Contradictory effects of the post-Covid-19 investments in fossil fuel-based infrastructure and the recent strengthening of climate targets must be addressed with new policy choices to sustain a decline in global emissions in the post-Covid-19 era.” As emphasized by Sarimin and Yigitcanlar , since we considered the WHO declaration of pandemic as the start date for the execution of the research in all regions. Nonetheless, there is a delay between that declaration and the restriction measures adopted by governments and regional agencies. Furthermore, investigation of a single air pollutant is a limitation, despite we also liked at the O3. Another limitation of this study is not to focus on the policy issues and prescribe public policy and actions to address the air pollution and climate change issues in Brazil. Nevertheless, our prospective research will focus on these limitations by considering NO2 and also other pollutants and investigating larger timeframes and conduct time series analyses and prescribe relevant policy actions.Besides the NO


Participants held executive, director/manager or project/clinical lead roles. Data were analysed in two phases (1) automated content analysis using machine learning (Leximancer v4.5) (2) researcher-led interpretation of the text analytics. Final themes were consolidated into a proposed decision-making framework  for NCD prevention in healthcare organisations. Decision-making was driven by four themes: Data, Evidence, Ethics and Health, i.e., data, its quality and the story it tells; traditional and non-traditional sources of evidence; ethical grounding in fairness and equity; and long-term value generated across multiple determinants of health. The strength of evidence was directly proportional to confidence in the ethics of a decision. PREVIDE can be adapted by public health practitioners and policymakers to guide real-world policy, practice and investment decisions for obesity prevention and with further validation, other NCDs and priority settings .Noncommunicable diseases (NCDs), including obesity, remain a significant global public health challenge. Prevention and public health innovation are needed to effectively address NCDs; however, understanding of how healthcare organisations make prevention decisions is immature. This study aimed to (1) explore how healthcare organisations make decisions for NCD prevention in Queensland, Australia (2) develop a contemporary decision-making framework to guide NCD prevention in healthcare organisations. Cross-sectional and qualitative design, comprising individual semi-structured interviews. Participants ( Non-communicable diseases (NCDs)remain the largest global public health threat. People of all ages and countries are affected by NCDs; they contribute to 71% of deaths globally . OverweiIn the context of obesity prevention, traditional models of public health have relied upon evidence generated from crude retrospective data captured in in point-prevalence surveys, retrospective cohorts, clinical trials or disease-specific research databases or registries ,7. Such precision public health approaches that target communities based upon risk and need, and in real-time, i.e., the right intervention for the right population at the right time [Public health innovation is needed to effectively address obesity. New sources of real-world data  and digital technologies are the foundation for innovative ‘digital public health’ ,9 approaght time . Digitalght time ,12,13 bught time  (b) deveght time  (c) idenght time .how their end-users—healthcare organisations—make decisions to support contemporary policy and practice for NCD prevention. Addressing this gap will mean digital public health can be tailored to organisational decision workflows and ultimately enhance the translation and impact of innovative tools, products and precision models of care. In designing our research question and aims to address this gap, we referred to the health improvement decision-making triangle, a seminal theory (2008) of decision-making for public health [New population health analytics tools and strategic visions to advance precision public health for NCDs have been developed ; howeverc health . An assu“how do healthcare organisations make decisions for NCD prevention?”. To situate our study, we focus on the context of Queensland, Australia. Queensland offers a representative site because obesity rates remain troubling and there is significant political and organisational inertia to address the problem. We hypothesised that preventive decision-making comprises a balance between evidence and community need.Our research question is To (a) explore and (b) compare decision-making in two healthcare organisations  for NCD prevention using a qualitative approach and Queensland, Australia as the use case setting.To develop a contemporary decision-making framework for NCD prevention in healthcare organisations.Our aims were:This study was cross-sectional and qualitative  in design and comprised individual semi-structured interviews to investigate its research question. A qualitative design was chosen to derive rich perspectives and experiences of decision-making for NCD prevention from participants in healthcare organisations. A phenomenological method  suited exploration of decision-making—a fluid and dynamic real-world process—and allowed deep analysis of the NCD prevention and unique organisational contexts . We adheParticipants were recruited from the state public health service (CareQ) and health promotion organisation (PrevQ). CareQ is responsible for clinical healthcare delivery. PrevQ is a recently established (July 2019) statutory health promotion agency dedicated to obesity prevention. Participants were change-agents: actors whose leadership position influences decision-making, strategy and policy at an organisational level. Participants were targeted across three groups according to seniority (1) Executive (2) Director/Manager (3) Project/Clinical Lead. Executive participants were members of executive leadership and provided governance, strategic and directional leadership to the organisation. Director/Manager participants were members of senior leadership and provided team-based strategy and direction to digital healthcare delivery (CareQ) or health promotion programs and policies (PrevQ). Project/Clinical lead participants were frontline leaders and conducted project-specific activities in small teams.n = 14) was contextual; it represented the small number of eligible and consenting participants in high-level, statewide organisational roles in CareQ and PrevQ.. The study team delivered a short presentation to eligible change-agents at CareQ and PrevQ on the study rationale, aim, design, risks, benefits and significance. Potential participants could then express interest via email or phone. A detailed explanation of the study purpose, methods, demands, risks and outcomes was then provided. Participants provided informed consent online and completed a short demographics questionnaire. Participants who expressed initial interest but did not engage further were followed up with two emails. No interviewer-participant relationship was established prior to data collection. No rewards or incentives were offered to participants.Participants were first approached at an organisational level. We employed a purposive sampling strategy due to the specificity of our target population. A snowballing approach was also used to identify other potential participants beyond those initially approached. As per contemporary recommendations for qualitative research, we did not adhere to sample size numerical guidelines or norms . Our finDemographic questionnaires were completed by participants via a secure, online survey tool—‘Checkbox’. Demographic data included: role category , professional background , length of time in current role  and years of total experience .Videoconference semi-structured interviews were conducted in a closed room at a university research centre by two digital health and obesity researchers . Interviews were audio recorded and transcribed verbatim by an external transcription service. Interview duration was 22–37 min. Transcribed interviews were not returned to participants.“healthcare delivery decisions that target disease prevention at all levels”; PrevQ—“health promotion decisions that seek to improve healthy weight, food and drink choices”. Decisions were defined at the organisational level, and may have related to investment, intervention design, choosing target settings or conducting research studies, as examples. In the participant feedback interviews, participants were invited to a semi-structured discussion about their overall impressions of the results, and perceived strengths, weaknesses and gaps.Semi-structured interview design  was guidInterview data were analysed in a two-stage approach.The first stage of analysis was undertaken via the text analytics tool ‘Leximancer’ (v4.5) . LeximanOne researcher loaded the observational data into Leximancer and created an initial concept map  without altering any settings. Leximancer’s tagging functionality was also used to stratify and analyse data according to organisation and position seniority as subgroups. Concepts were then iteratively reviewed for ‘lexical value’ and removed where appropriate. Concepts were merged where relevant . The concept map was initially observed at a summary level through ‘zooming out’ then individual themes and concepts were investigated in more detail by ‘zooming in’ as described by Haynes et al. . MultiplA second stage of researcher-led interpretive analysis was applied to the preliminary themes and concepts identified by Leximancer’s text analytics. Leximancer was queried for samples of text that supported each preliminary theme. Relevant text was extracted by one researcher. Manual inductive, thematic analysis was performed by independently by two researchers; results were then discussed in two iterative rounds of grouping to generate new, interpretive themes and sub-themes based on contextual understanding of the field (chronic disease prevention). Researchers performed a ‘cluster and name’ process whereby themes and sub-themes were synthesised into a preliminary decision-making framework for NCD prevention in healthcare organisations ready for feedback.n = 3) from CareQ and PrevQ. Research team and participants feedback was synthesised into a final proposed decision-making framework for NCD prevention in healthcare organisations.The preliminary framework was refined in two iterative phases: (1) presentation, discussion and refinement with the research team (2) individual consultation with select executive participants , then Director/Manager  and Executive . Public health  and clinical  were the most commonly reported professional backgrounds. Most change-agents had spent 1–2 years  or greater  in their current role. Change-agents were highly experienced with most reporting 11–30 years of total experience .At a theme size of 60%, six themes were automatically derived (in order of identified ‘importance’): data, evidence, health, ethical, investment, access. The analysis identified 44 total concepts within all themes. The top 10 most frequent concepts were: data, evidence, people, work, health, need, use, example, understand, look.A total of four themes , 11 sub-themes and one minor theme  were manually derived from stage two (researcher-led interpretation of the Leximancer outputs) data analysis .(PREVIDE—PREVention decIDE) based on all themes and iteratively refined with the research team and change-agents. ‘Investment’ (a theme derived from stage one) was interpreted as the final decision arising from a complex interrelationship between Data, Evidence, Health and Ethics themes, rather than a true theme. Ultimately, decision-making results in either (a) investment of time, resources, money and/or organisational inertia (b) no action, i.e., neutral position or (c) disinvestment, which is a withdrawal of investment.Theme 1 and its sub-themes were derived from the strongest ‘Data’ theme identified by Leximancer  personal level, where variation between individuals was possible (b) community level, where community need and equity was absolute, and (c) organisational level, where ethics were principled, such as ‘do no harm’ and ‘the right choices to benefit the most people’, and based around organisational structures, such as strategy, investment frameworks and policy.Theme 3 and its sub-themes were derived from the ‘Ethics’ theme identified by Leximancer  from CareQ and PrevQ felt the framework (PREVIDE) was fair, logical, and appropriately representative of the real-world context. The four pillars—Data, Evidence, Ethics, Health—were viewed as consistent across heterogenous healthcare settings, such as treatment and management services . It was suggested that each pillar does not have equal strength—and thus contribution to—a final decision, rather, the weighting of each pillar may and likely should fluctuate and be tailored to each decision context. Considering the pillars as equal contributors to a decision was viewed as a weakness and risk.Overall, select executive participants An investment model for prevention (and an evidence-based mechanism to increase investment)A decision-making tool that can help guide investment (or disinvestment) at an organisational level, and not just a tool that describes how decisions are made.Translation of PREVIDE in action and considering organisational readiness for decision workflow disruption.Enablers to successful translation were using real-world use cases to ground At a theme size of 56%, five themes were automatically derived (in order of identified ‘importance’): data, evidence, trying, information, population. CareQ and PrevQ were both linked to all themes. The top 5 linked concepts for CareQ were: research, unclear, looking, approach and outcomes. The top 5 linked concepts for PrevQ were: access, system, used, understand and need.CareQ was driven by evidence-based, research-driven approaches to decision-making, and collaborated with research organisations to help build evidence and guide investment decisions. PrevQ decision-making was often discussed at a systems and population level; the need to generate prevention impacts for those most in need that can positively change the system towards a ‘predict-prevent’ model of healthcare.Box 6“I don’t believe in approaches that have no evidence-baseat all… there has to be a foundation and I go to the research literaturelooking for that” (CareQ)“We just didn’t have the data points that we needed toshow impact at the level that was required, at the system level…” (PrevQ)At a theme size of 56%, five themes were automatically derived (in order of identified ‘importance’): data, people, ethical, activity, investment. Executive was linked to all themes, with the top 5 linked concepts including: framework, access, used, approach and data. Director/Manager was also linked to all themes, with the top 5 linked concepts including: research, unclear, looking, approach, outcomes. Project/Clinical Lead was linked to four themes: data, people, ethical and activity. The top 5 linked concepts were access, system, used, understand, need.Executive change-agents grounded their decisions in structured frameworks, based upon data and evidence, that could be applied consistently to different contexts. Director/Manager’s referred to research as one pillar of decision-making among other forms of evidence, such as practise-based experience and anecdotal evidence, and were motivated by generating and measuring health outcomes. Project/Clinical Leads were focused on data outside health, such as community access to healthy environments, and access to additional high-quality data  to support decisions where need was greatest.Box 7“From the start I wanted to make sure that had evidence,research and learning framework around everything”“You’ve got the research evidence, you’ve got thescientific evidence… and then you’ve got your practise evidence, and thatkind of goes into more andecdotal clinical evidence”“I would really like to see us have more access toeconomic data or the cost of things”(PREVIDE) was seen to have pragmatic value by change-agents as a decision-making tool—beyond a traditional theoretical framework—to guide prevention investment (or disinvestment) by healthcare organisations, including at the individual patient and community level. PREVIDE is a first step in modelling organisational decision-making for NCD prevention, using obesity as a public health use case and Queensland, Australia as the use case setting.This study engaged 14 change-agents from healthcare organisations in Queensland, Australia to explore how decisions are made for NCD prevention. Overall, preventive decision-making is driven by four domains that vary in weight depending upon the decision context: data, its quality and the story it tells; traditional and non-traditional sources of evidence; ethical grounding in fairness and equity; and long-term value generated across multiple determinants of health. Whilst change-agents were ethically bound to make fair and just decisions regardless of supportive data and evidence, their level of confidence in the ethics of a decision was directly proportional to the amount of traditional and non-traditional evidence supporting the decision. The framework The literature on decision-making for health promotion and public health has evolved considerably over the previous two decades. Seminal theories 1997) focused solely on evidence to drive decisions about the care of communities and populations—a top-down approach . Later w focused PREVIDE as theory collapsed into ‘evidence’ as a non-traditional source important for prevention decision-making. One reason for this finding lies in the prevention paradox; prevention  is empirically more effective than break-fix models of healthcare [In 2009, Tannahill developed a new framework for decision-making for health promotion, public health, and health improvement: the decision-making triangle with the pillars evidence, ethics and theory . Subsequalthcare ,26; yet,PREVIDE—our proposed framework [just and right, underpinned by accountability to the communities they serve and regardless of data and evidence availability. Carter et al. [Ethics as a pillar of decision-making for health promotion and public health remained consistent between previous frameworks and ramework ,25. Tannramework  promotesPREVIDE is ‘Data’ existing as an independent pillar separate to ‘Evidence’. Historically, data may have nested within the evidence domain; however, rapid digital transformation of society and healthcare is creating new models of precision public health based upon real-world and big data [One unique component of big data ,10,27. Dbig data . More daPREVIDE. Change-agents were clear that understanding and targeting risk factors for poor health across multiple sectors  was core prevention practice for NCDs. This was not explicitly reflected in the frameworks of Tannahill [National Obesity Strategy (2022–2032) [‘Health’ as a pillar of decision-making was another finding unique to annahill  and Cartannahill , perhaps22–2032)  in Austr22–2032) . Our undPREVIDE and existing decision frameworks ; however, prevention requires further consideration of non-traditional evidence, which contributes significantly to decision-making.Theoretical models of decision-making for public health and health promotion have now matured into pragmatic decision frameworks. Creating evidence-informed policies and recommendations requires translating theoretical pillars such as data, evidence, ethics and health, into real-world action. Contemporary ‘Evidence-to-Decision’ frameworks exist to assist public health practitioners and policymakers formulate evidence-driven decisions, such as in environmental health  and healPREVIDE into healthcare organisations to embed contemporary decision-making workflows into routine prevention practice. One real-world example is use of the GRADE Evidence-to-Decision framework to strengthen decision-making in national food fortification programming in Nigeria [National Obesity Strategy (2022–2032) [Strategy prioritises developing new prevention policies and interventions at a system and population level, and difficult investment decisions will need to be made at a high organisational level. Strategy and policy decisions at a healthcare organisation level can be guided by political priorities, such as leadership, budget and beneficiaries, a factor not identified by change-makers in our present study [Change-makers in our study were quick to identify the translation potential of  Nigeria . In an A22–2032)  could bent study . It may PREVIDE. Data analysis was strengthened by a machine learning (via Leximancer) approach to provide initial text analytics that informed researcher-led inductive analysis. The primary limitation of this study was the overrepresentation of change-makers from PrevQ, the state health promotion organisation, compared to CareQ, the state healthcare system. Decision-making for prevention in clinical settings may thus have been underrepresented and clinical validation of PREVIDE would be required to justify application at a hospital, health service or point-of-care environment.To our knowledge, our study is the first to develop a contemporary decision-making framework to support healthcare organisations in NCD prevention. We adopted an evidence-based qualitative approach that guided development of (PREVIDE) that can be adapted by public health practitioners and policymakers to support policy, practice and investment decisions for obesity prevention and with further validation, broader NCDs  in healthcare organisations. Researchers may also use PREVIDE and its decision-making pillars to guide new research questions and research uptake in prevention organisations. Future research can prioritise validation of PREVIDE in real-world settings and other NCD contexts to support emerging precision public health models of care and evaluating its impact on decision-making confidence and impact.This study provides empirical evidence for how healthcare organisations in Queensland, Australia—both health promotion and healthcare delivery—make decisions for NCD prevention. Overall, decisions are driven by four core pillars that vary in strength depending upon the decision context: data, its quality and the story it tells; traditional and non-traditional sources of evidence; ethical grounding in fairness and equity; and long-term value generated across multiple determinants of health. Confidence in decision ethics was directly proportional to the supporting evidence-base. As a first step in a nascent area, we developed a pragmatic framework


Neurotoxicity, including optic nerve injury, is one of the most common adverse effects of tacrolimus, the principal calcineurin inhibitor used after kidney transplantation (KTx). The electrophysiologic measurements of both pattern visual evoked potentials (PVEP) and flash visual evoked potentials (FVEP) are valuable when drug-induced optic neuropathy is suspected.To determine whether VEP measurement is a sensitive and repeatable method for monitoring tacrolimus neurotoxicity.This prospective study focused on 35 patients  who were at a median of 3.0  months after KTx at the time of the initial VEP evaluation and were treated with tacrolimus since KTx. The follow-up VEP examination was done after a median of 24 (22–27) months (both VEP measurements followed the ISCEV standards). The P100 wave latency and amplitude for the 1° and 15’ PVEP simulations, and the P2 wave latency and amplitude for the FVEP were analyzed.R = 0.499; p = 0.005) and the P2 latency  only in patients treated with the once-daily, but not the twice-daily, tacrolimus formulation.For the 1° checks, the P100 wave latency and amplitude values were significantly worse in the follow-up examination compared to the early post-transplant time-point. Independent associations between FVEP parameters and the tacrolimus blood trough level were observed in the follow-up examination but not at the early post-transplant period. The P2 wave latency correlated with the tacrolimus trough level only in patients treated with the twice-daily, but not the once-daily, tacrolimus formulation. The brain derived neurotrophic factor (BDNF) level correlated with the P100 (15’) latency (The observations in this study may support the rationale for the use of VEP measurements as non-invasive monitoring of subclinical tacrolimus neurotoxicity. Thus, the latency (1°) and amplitude (1°) percentage changes in the control group were −1.9 and 13.5%, respectively. Similar longitudinal values of latency and amplitude were also found in FVEP examinations, both in the study and control groups. There were also no significant differences in the analyzed VEP parameters between the study and control groups, both at baseline and in the follow-up period.In the control group, no significant differences were observed between the baseline and follow-up PVEP measurements [median P100 latency (1°): 107.2  vs. 105.1 (102.2–107.4) ms; R = 0.294; p = 0.015) but P100 was not correllated with P2 latency . P100 latency for the 1° checks was negatively correlated with (1°) and (15’) amplitudes  and with P2 amplitude . There was a weak correlation between tacrolimus trough level and P2 wave latency . No other correlations were observed between either tacrolimus trough level or tacrolimus AUC and the other VEP parameters measured shortly after kidney transplantation. Notably, almost all VEP parameters (except P100 amplitude (15’) and P2 latency) showed a baseline association with recipient age, and all examined latencies, but not amplitudes, were much more pronounced in the follow-up examination , but not age or log tacrolimus trough level, independently influenced P2 latency.At the first examination, P100 latencies were positively correlated between the check sizes (1° versus 15’)  and between P100 for the 15' checks and P2 latency , whereas the correlations of (1°) amplitude with (15’) amplitude (R = 0.710); p < 0.001) and P2 wave amplitude  were much more pronounced. Notably, P2 wave amplitude, but not latency, correlated with tacrolimus trough level  , whereas in the once-daily formulation subgroup, only amplitude , but not latency (p = 0.43), correlated with tacrolimus level. In the whole study group, the stepwise multiple regression analyses showed that P2 wave latency was independently influenced only by log tacrolimus trough level , whereas P2 wave amplitude was affected by log tacrolimus trough level  and age .In the follow-up examination, there were only weak associations of P100 latencies between the check sizes , but not in the follow-up, examination.In the analysing of inflammatory markers, IL-6 values significantly correlated only with P100 (15’) latency in the first  was not found in the follow-up examination (p = 0.98). Early after transplantation, there was a positive correlation of BDNF with P100 (15’) latency    and P2 latency  only in patients treated with the once-daily, but not the twice-daily, tacrolimus formulation. Stepwise multiple regression analysis showed that log BDNF  and eGFR  were independently associated with P100 (15’) amplitude. Age and log tacrolimus trough level were not included in the final model.The significant baseline association between BDNF plasma level and patient age , but not with tacrolimus blood trough level.In the follow-up examination, P100 (1°) latency and (1°) amplitude were associated with ET-1 levels  latency and (1°) amplitude values were significantly worse  in the follow-up examination compared with the early post-transplant time point. Second, independent associations between FVEP parameters and log tacrolimus blood trough level were observed in the follow-up examination but not in the early post-transplant period. Interestingly, P2 wave latency correlated with tacrolimus trough level only in patients treated throughout with the twice-daily formulation but not in those converted to the once-daily formulation.VEP is a recorded occipital cortical evoked potential in response to visual stimulation . PVEP abIf this is the case, a greater degree of VEP abnormalities should be observed in patients who have been on tacrolimus-based immunosuppressive therapy for a longer period. In the study group, both the P100 latency and amplitude stimulated with a large angular (1°) pattern were significantly worse in the follow-up examination, whereas both the (15’) latency and amplitude did not change over the period of observation. Because the (1°) VEP measures are particularly linked with the detection of subclinical optic neuropathy , the toxInterestingly, there were significant differences in the latter associations depending on the pharmacologic formulation of tacrolimus, with the P2 latency positively correlated with tacrolimus level only in the twice-daily subgroup. In our earlier analysis of stable kidney transplant patients, both the type of tacrolimus formulation and drug exposure influenced VEP parameters . Thus, bTo get some insight into the pathophysiologic mechanism of tacrolimus neurotoxicity, the plasma levels of BDNF were assessed at both VEP examinations. BDNF, a critical protein for the maintenance of neuronal functions, has been postulated to control neural development, modulate synaptogenesis, and have some neuroprotective effects . ExperimThe main limitation of this study is the low number of participants, mainly due to the strict exclusion criteria, which include any form of both pre- and post-transplant diabetes and previous neurologic abnormalities. It is worth noting that in the main cohort, except for approximately 20% of kidney recipients with preexisting diabetes transplanted during the study recruitment, another 20% was excluded due to the ongoing glucose metabolism disturbances; some other patients were excluded due to unfavorable data in their anamnesis. Additionally, because an age-related P100 latency increase was noted in patients older than 60 years , anotherIt is worth emphasizing that regular monitoring and detection of subclinical tacrolimus neurotoxicity by using VEP may be beneficial not only in the ophthalmologic setting, in which it offers the advantage of very sensitive recognition of neurotoxicity before visual alterations are detected by ophthalmologic exam. In future clinical practice, abnormal VEP results should motivate the modification of maintenance immunosuppressive therapy toward the less neuro- and nephrotoxic tacrolimus formulations or other immunosuppressants without such an undesirable potential. Such a maneuver, resulting in the minimization of long-term tacrolimus nephrotoxicity, could improve kidney graft survival in this specific subgroup of kidney transplant recipients.The present study showed that both P100 latency and amplitude values for 1° checkerboard reversal were significantly delayed and diminished, respectively, after 2 years of tacrolimus treatment compared with the early post-transplant period. During the third post-transplant year, both P2 wave latency and amplitude values were negatively associated with tacrolimus blood trough level. Moreover, P2 latency correlated with tacrolimus trough level only in patients treated with the twice-daily, but not the once-daily tacrolimus formulation. These observations may support the rationale for the use of VEP measurements as a valuable tool for non-invasive monitoring of suspected subclinical tacrolimus neurotoxicity. In this regard, abnormal VEP values provide strong support for immunosuppressive regimen modification, such as a decrease in the tacrolimus dose or conversion to the alternative, non-neurotoxic mTOR inhibitor therapy.


Common ankle sprains are often accompanied by injury to the subtalar joint, which eventually leads to subtalar joint instability. Because the clinical manifestations for subtalar joint instability are similar to ankle joint injuries, these are often overlooked. This study aimed to establish an animal model of subtalar joint instability to study post-traumatic osteoarthritis of the subtalar joint caused by long-term subtalar joint instability and to provide a reference for future clinical research on chronic subtalar joint instability.In all, 24 C57BL/6 male mice were randomly divided into three groups: Sham, cervical ligament (CL) transection and CL + calcaneofibular ligament (CFL) transection groups. One week after surgical operation, all mice were trained to run in the mouse rotation fatigue machine every day. During this period, a balance beam test was used to evaluate the motor level and coordination ability of the mice before the operation and three days, one week, four weeks, eight weeks, and twelve weeks after operation. Further, post-traumatic osteoarthritis of the subtalar joint was quantified via micro-CT and histological staining.The mice in the partial ligament transection group took significantly longer than those in the Sham group to pass through the balance beam and showed an increased number of hindfoot slips. Micro-CT analysis showed that the subtalar bone volume fraction in the CL + CFL transection group and CL transection group was 5.8% and 2.8% higher than that in the Sham group, respectively. Histological staining showed obvious signs of post-traumatic osteoarthritis (PTOA) in the subtalar joint of the ligament transection group.The transection of CL and CL + CFL can cause instability of the subtalar joint in mice, resulting in a decrease in motor coordination, and long-term instability of the subtalar joint in mice can cause PTOA of the subtalar joint, which is manifested as destruction and loss of articular cartilage. Ankle sprain (AS) is one of the most common athletic injuries occurring during sports activities. Among all AS cases, approximately 25% patients present with combined injuries of the lateral ankle and the subtalar joint –3. HowevAt present, there are several reports on chronic ankle instability (CAI), and experts have reached consensus on its diagnosis and treatment . HoweverTo date, the exact mechanism of injuries causing subtalar instability remains unknown, and the impact of ligaments around the subtalar joint on subtalar stability remains a controversial topic. Thus, the anatomical structure of the subtalar joint and the distribution of ligaments around the subtalar joint in C57BL/6 mice are similar to those in humans . They arWe hypothesized that transecting the ligaments around the subtalar joint of the mouse could lead to chronic subtalar joint instability accompanied by subtalar joint osteoarthritis. To test this hypothesis, we designed two mouse models of chronic subtalar joint instability accompanied by subtalar joint osteoarthritis induced by ligament disruption . In this study, the balancing results were used to evaluate the behavioral stability of mice, and the results of specimens subject to micro-CT, safranin O-Fast green staining, hematoxylin and eosin (H&E) staining, and immunohistochemical staining were employed to evaluate inflammation of the subtalar joint. The successful establishment of the mouse model of chronic subtalar joint instability accompanied by subtalar joint osteoarthritis not only provides a new understanding for the research of foot diseases, but also provides a reference for clinical research on the mechanism and treatment of injury of chronic subtalar joint instability.In all, 24 male C57BL/6 mice  purchased from JOINN Laboratories (Suzhou), Inc. (License No. SCXK (Su) 2018-0006, Suzhou, China) were used in the present experiment. All mice were randomly distributed into six plastic cages, with an average of four mice per cage. The mice were housed in a specific pathogen-free (SPF) environment with a light/dark cycle of 12 h, and constant temperature and humidity of 18–22 °C and 40–70%, respectively. The mice were free to move around in the cage and were provided with adequate food and water. The beddings in the cages were changed regularly, and the health of the mice was carefully observed. In the first week, the mice were allowed to adapt to the new feeding environment and were trained on the balance beam.At 8 weeks of age, the six cages of mice were randomly divided into three groups, with two cages (eight mice) per group. The mice were weighed before surgery, and anesthetized via an intraperitoneal injection of 4% chloral hydrate at a dose of 0.01 ml/g. A shaver was then used to clean the hair on the right hind limbs of the anesthetized mice, and their right hind limbs were disinfected in strict accordance with the principles of surgical disinfection. Following this, the disinfected mice were placed on a microsurgical operating table, and the anatomical structures of the right hind feet of the mice were observed using an operating microscope. In the CFL + CL transection group, a longitudinal incision was made on the skin over the lateral aspect of the right ankle joint, and the subcutaneous tissue was separated to expose the ankle and subtalar joints. The CFL  with the following scanning parameters: 50 kV, 500 mA, and 9 um resolution. The scanned image was processed and reconstructed using software. In the software, continuous subchondral bone of the ankle joint and subtalar joint in the region of interest were selected for quantitative analysis of specific indicators such as bone volume fraction and trabecular bone thickness. Subsequently, a three-dimensional reconstructed image was obtained using the software.After high-resolution microcomputed tomography, all specimens were decalcified in 10% ethylenediamine tetraacetic acid (EDTA) (pH 7.4) solution for one month, and excess soft tissue on the specimens was trimmed and dehydrated in a concentration gradient alcohol. Next, the specimens were transferred to n-butanol for 10 h and soaked in paraffin for 7 h. Finally, according to the standard scheme, a paraffin block wrapped with the specimen was cut into coronal sections  with a thickness of 6 microns using a rotary paraffin slicer. The sections were stained with H&E to evaluate the thickness changes of the ankle and subtalar articular cartilage and subchondral bone, and the modified Mankin score was used to evaluate pathological changes . Changesp values < 0.05 were considered to be statistically significant [SPSS v23.0  and GraphPad Prism 8.0  were used for statistical analysis. First, the normality of the distribution and the homogeneity of variance in each group of data were tested. Normally distributed data that had equal variance were analyzed by one-way ANOVA; otherwise, the data were analyzed via Kruskal–Wallis test. The data are expressed as means ± standard deviation (SD). nificant .p = 0.165).In intergroup comparisons of preoperative balance beam test, no significant difference was observed in the time taken to pass through the balance beam between the three groups (p < 0.05). In comparing ligament transection groups, the time required to pass through the balance beam in the CL transection group was significantly shorter than that in the CL + CFL transection group at 12 weeks after operation (p < 0.05) . Compared with the Sham group, the CL + CFL transection group showed a significantly increased number of pulleys passing through the balance beam after operation (p < 0.05). There was no statistically significant difference between the CL transection group and Sham group in this regard at one week and four weeks after surgery (p > 0.05), but there was statistically significant difference at three days, eight weeks, and twelve weeks after operation . Twelve weeks after operation, the mice in the CL + CFL transection group slipped more easily than those in the CL transection group (p < 0.05)    Fig. A–D. In t1) Figs. C, 4E, F.p < 0.05), This showed that the amount of subchondral bone in the subtalar joint and ankle joint had increased, the bone mineral density had increased, indicating a state of "osteosclerosis."Twelve weeks after the operation, the cartilage layer of the ankle joint surface and subtalar joint surface in the right hind limb of the mice was examined via micro-CT to quantitatively evaluate the subchondral bone. As shown in Fig. Ankle sprain is one of the most common injuries in sports. A Sprain can lead to the relaxation or rupture of ligaments around the ankle, resulting in a change in the mechanical properties of the ankle or subtalar joint and uneven force distribution around the subtalar joint, and further lead to instability of the ankle or subtalar joint –3. InjurRegarding the ligaments around the subtalar joint, isolated CL injury is not common, because its injury is usually accompanied by the injury of ligaments around the ankle . The CFLThe time required to pass through the balance beam for three days and one week in the ligament transection group was significantly longer than that in the Sham group. This may be because there is obvious edema and pain in the foot and ankle of mice in the early post-surgery period, resulting in a decrease in the crawling speed of mice on the balance beam due to pain feedback and an increase in time-consuming accordingly, which suggests that physical activity should be reduced in the early stage after acute ankle injury and as reported in Hubbard-Turner study, early rest after severe ankle sprain is essential to restore the level of physical activity . Four weWith regard to the incidence of slipping on the balance beam, the number of slip in the CL + CFL transection group was significantly higher than that in the Sham group, and the number in CL transection group was significantly higher than that in the Sham group at three days, eight weeks, and 12 weeks after surgery. After 12 weeks, the number of slip in the CL group increased by 2.13-fold, and 3.13-fold in the CL + CFL group. In addition, the number of slip in the CL + CFL group 12 weeks after surgery was 1.47-fold that of the CL group, which had same trends with that observed by Hubbard-Turner , 26. TheTwelve weeks after operation, the time required for passing through the balance beam and the instances of slipping from the balance beam in the ligament transection group were significantly higher than those in the Sham group, and the motor balance function was significantly damaged in the ligament transection group. By this time, the mice may have developed long-term chronic subtalar joint instability to post-traumatic subtalar osteoarthritis. Numerous studies have reported that individuals with post-traumatic subtalar osteoarthritis have balancing disorders and movement pattern changes, and there are static and dynamic balance defects in a series of postural controls. These findings are consistent with the results of the mouse model in this study –29.H&E and Safranin O-Fast green staining showed obvious discontinuities and large defects on the surface of subtalar joint in the ligament transection group. The number of chondrocytes on the joint surface decreased and disappeared, and hollow-nucleated osteocytes were observed, which suggested that the transection of ligament leads to the instability of the subtalar joint, and the instability of subtalar joint without effective treatment can cause PTOA, similar to the previous results of constructing the ankle joint model by cutting the ligament around the ankle joint in mice , 16. In Under normal physiological conditions, the bone resorption effect of osteoclasts and the osteogenesis effect of osteoblasts maintain the dynamic balance of the bone state , 32. QuaThis study has some limitations. First, the animals used in the experiment were mice. Although the structure of the hind foot and ankle of mice is similar to that of humans, strictly speaking, mice are quadruped, whereas humans are bipedal, and the forces borne by the joints during exercise are not completely consistent. Second, the ankle joint and subtalar joint surface of mice are very small, and the cartilage layer area is also thin; accordingly, it is impossible to extract the corresponding cartilage cells and further elaborate on the signaling pathway and molecular mechanism of joint degeneration at a cellular level. Finally, PTOA is a chronic degenerative disease, the study period of only 12 weeks is not long enough for subtalar osteoarthritis development, and an experiment of a longer duration is required to observe the relationship between CSI and subtalar PTOA. It is believed that more reasonable animal models will be developed in future research.In this study, we successfully established a mouse model of subtalar PTOA caused by subtalar joint instability by disconnecting the subtalar periarticular ligaments (CFL and CL), which could provide a new understanding of how acute foot ligament injury develops into chronic articular cartilage degeneration and paves the way for the related research on subtalar osteoarthritis in the future.


Microwave imaging has been recently proposed as alternative technology for in-line inspection of packaged products in the food industry, thanks to its non-invasiveness and the low-cost of the equipment. In this framework, simple and effective detection/imaging strategies, able to reveal the presence of foreign bodies that may have contaminated the product during the packaging stage, are needed to allow real-time and reliable detection, thus avoiding delays along the production line and limiting occurrence of false detections (either negative or positive). In this work, a novel detection/imaging approach meeting these requirements is presented. The approach performs the detection/imaging of the contaminant by exploiting the symmetries usually characterizing the food items. Such symmetries are broken by the presence of foreign bodies, thereby determining a differential signal that can be processed to reveal their presence. In so doing, the approach does not require the prior measurement of a reference, defect-free, item. With respect to the quite common case of homogeneous food packaged in circular plastic/glass jars, numerical analyses are provided to show the effectiveness of the proposed approach. In the food industry, the inspection of the integrity of food items before their commercialization has become a key step in the control of product quality. In this framework, particular attention is paid to the detection/imaging of the presence of small foreign bodies that may have contaminated food during the different production processes, particularly in the packaging stage .Such an inspection can be carried out off-line, on selected samples, or directly in-line, . The former approach is surely a less effective and more expensive solution, as the presence of even a single contaminated product requires discarding the entire batch and at the same time does not guarantee that all contaminated food is actually detected. Hence, the second solution is preferable. Currently, such task is carried out by employing metal detectors, X-ray scanners, near infrared sensors and/or optical cameras specifically designed to fit and be compliant with the production chain . HoweverAs a result, an alternative solution allowing for the overcoming of these drawbacks is of interest. In this respect, an interesting alternative to the above diagnostic tools is represented by microwave imaging (MWI) ,4,5,6.MWI performs the detection/imaging relying on the difference in the dielectric permittivity characterizing the different materials making the packaged food item, in the microwave frequency range . As a reThese features motivated the recent development of a MWI system specifically meant for food inspection ,10,11. IA drawback of such an approach is that the reference may be not sufficiently identical to the object under test (OUT) or, more simply, the positions at which the OUT is probed, when moving on the production line, may be not the same as the one at which the data relative to the reference object were acquired. This circumstance can increase the false positive rate, namely the wrong detection of foreign inclusions in contaminant-free products, which, while not increasing the risk of putting contaminated products on market, can represent a significant economic loss for the manufacturer, forced to discard an amount of product larger than necessary.In the present paper, a different detection/imaging strategy is proposed, which allows one to perform the detection/imaging task without the need of a reference. The idea, preliminarily presented in , is stilThe second one, hereafter denoted as the Orthogonal Symmetry Plane (OSP)-based approach, exploits as symmetry plane the one orthogonal to the direction of movement and splitting each antenna into two identical half-parts (assuming the antennas perfectly symmetric with respect to such plane).The performances of the two approaches, either operating individually or combined together, are assessed by means of a comprehensive 3D numerical study, reproducing as faithfully as possible the real situation commonly encountered in the considered application. The robustness of the two approaches against a not perfectly centering of the OUT, with respect to the two antennas, is also investigated. The paper is organized as follows. In mf . Moreover, by exploiting the movement of the OUT, each scattering matrix is measured at N different positions, say zn  of the OUT along the production line, having assumed as reference position, z0 = 0 cm, that when the OUT is just in the middle between the two antennas. Due to the movement, this configuration is equivalent to having a synthetic array of N “virtual” pairs of antennas placed on both sides of the line, at the positions zn, while the OUT stands in the middle, at the position z0 = 0 cm . ijS , i,j = 1, 2, such a difference and with χ(r) the (unknown) variation of electric contrast due to the presence of the inclusion, it results :bEij]10], the x-axis, so that hereafter only such component, say Ebx, of the radiated electric field will be considered.Since the inclusion is expected to be a weak scatterer, its reconstruction from differential data reduces to the solution of a linear inverse problem where the Green’s function is that evaluated in presence of the OUT free of inclusions see also . Let us bx for each antenna is P = M × N, each of which is stored in a matrix of Q (=50 × 40 × 40) elements representing bx evaluated on a grid of cubic cells (2 × 2 × 2 mm in size) into which the OUT is discretized . As the differential data are organized as column vectors of P elements, each of the above matrix was recast as a row vector of Q elements and stacked in a P × Q matrix representing  the numerical Green’s function employed in the inversion algorithm. Since the system consists of two antennas, we computed two Green’s functions, say 1 and 2, where, by virtue of the assumed symmetry, 2 can be computed by “mirroring” 1 with respect to the y-axis, or vice versa.Since the OUT is probed at M frequencies and N positions, the total number of simulated EsR the Px1  vector of the differences between the measured Sii and Sjj  and with i the Hadamard-Schur product [i by itself , the numerical counterpart of (1) is:χ the Qx1 vector of the searched unknown contrast in the OUT (representing the inclusion).Now, regarding the PSP-based approach, denoting with  product  of G=i bsii the Px1 vector of the differences between Sii and Sii , with s21 the Px1 vector of the differences between S21 and S21 and with ij the Hadamard-Schur product of i by j , the numerical counterpart of (1) is:Concerning the OSP-based approach, denoted with χ is solution of a (ill-conditioned) linear system of equations. An estimate of χ can be then achieved by a TSVD inversion algorithm, according to the scheme (2), by choosing a proper truncation threshold for the singular values of the matrixes appearing in (3) and (4). In our reconstructions, we have set a value for the truncation threshold of −40 dB below the largest  singular value.For both the PSP and OSP based approaches, 11(zn) and S22(zn) simulated at the two antenna ports, for each of the positions zn at which the OUT is probed, when the glass inclusion is present in the OUT (solid lines). For comparison, 11−S22| obtained in presence of the inclusion are appreciably larger than those in absence of it, clearly indicating that the presence of the glass inclusion breaks the symmetry of the OUT (and of the MWI system) with respect to the xz-plane, thereby determining an appreciable difference in the reflection coefficients measured at the two antenna ports, not detected in absence of inclusion. From the figure, one can also note that the level of such difference variates with the position at which the OUT is probed: it is higher when the inclusion is nearer to the antennas and lower when the inclusion is farer. This is an expected result due to the directivity of the employed antennas and confirms that for the application at hand a more convenient choice is that of employing poorly directive antennas.As it can be seen, the values of |SThe detected differential data can be then processed to establish the presence of the inclusion (detection) and possibly to image it by means of the linear inversion algorithm described in n, at which the OUT is probed when moving along the production line (represented in the set-up by the z-axis). Indeed, as pointed out in z-axis allows for creating a synthetic array of N virtual couples of antennas along the z-axis, which increases the spatial diversity, hence the resolution, along such axis.Apart from the presence of the ghost, a satisfactory reconstruction is obtained, with the inclusion better localized in the yz  cut plane than the other two . This is an expected result and is due to the different positions, zThe above results refer to a glass inclusion of 8 mm in size. The smallest size of the inclusion that can be effectively revealed depends on several factors. One of them is the measurement noise, here assumed with a level of 65 dB below the level of the signal feeding each antenna. Since the level of the signal scattered by the inclusion, i.e., the collected differential data, decreases as the third power of the size, this implies that an inclusion smaller than the one considered in this study can be revealed by lowering the noise level. For instance, it is expected that an inclusion of 4 mm in size  can be detected if the noise level does not exceed −83 dB, which is a very low value, but not prohibitive for the measurement instruments commercially available. However, it must be noted that other factors influence the detection capability of the system and so the minimum size of the detectable inclusion. The material of the inclusion , namely its electric contrast with respect to the food, is one of them. The higher the contrast, the smaller the size of the inclusion that can be detected. A further factor is the antenna return loss, that in this study is below −18 dB over the entire analyzed frequency band. A lower return loss ensures a higher radiated power, hence a higher level of the signal scattered by the inclusion, and so a higher signal to noise ratio for a given inclusion size. In any case, we retain that an inclusion of 4 mm in size can be confidently revealed as, on the other hand, it is shown by the experimental results reported in ,17.In conclusion, it is worth noting that the implementation of such an approach, in addition to requiring two almost identical antennas, requires a perfect alignment of the two in order to ensure a perfect symmetry of the radiating system with respect to the xz-plane.21(zn) − S21(zn−), for zn = 1 ÷ 6 cm, with (solid lines) and without (dashed lines) the glass inclusion in the OUT. The values of the difference obtained in presence of the inclusion are appreciably larger than those without it. Again, this result is due to the presence of the glass inclusion, which, in this case, destroys the symmetry of the OUT (and of the MWI system) with respect to the xy-plane, thus leading to a difference in the transmission parameters measured at the two mirror positions, zn and zn−, assumed by the OUT in moving along the z-axis. The same trend is observed for |S11(zn) − S11(zn−)| and |S22(zn) − S22(zn−)| but not reported for the sake of brevity.These differential data can be then exploited to detect the presence of the inclusion and possibly to image it by means of the linear inversion algorithm described in In this case as well, leaving aside the ghost, a good reconstruction is obtained, with the inclusion better localized in the yz  cut plane than the other two . Of course, this approach fails when the inclusion lies on the xy-plane , as in this case the symmetry is preserved even in presence of it. However, this drawback can be alleviated by exploiting together the PSP and OSP-based approaches.n− and zn, along the z-axis. In any case, the knowledge of the displacement is still required to perform the imaging as this information is needed to evaluate the right Green’s functions to be employed in the inversion algorithm .Moreover, the failure region is restricted to the only central region of the OUT, namely to the points along the d = 5 mm from the middle was considered.Finally, the robustness of both the PSP and OSP based approaches was assessed when the OUT was not perfectly in the middle between the two antennas, but it was slightly displaced toward one of them. Specifically, a displacement along the y axis of 11 − S22| (in dB) vs. frequency simulated in presence of the glass inclusion in the OUT. As it can be seen, the difference is much larger than the difference observed in the case of the perfectly centered OUT .The imaging is then performed by processing the calibrated differential data d, of the OUT with respect to the antennas , to be used in the calibration procedure in (5), such to minimize the root mean square error of posed in ). AlternSii,0 and Siid, . In absence of this, one could physically measure (at the moment the system is deployed) Sii,0 and Siid,  for a reference object, for different d, and store the data for the subsequent calibration.Another challenging aspect is to have a quite accurate numerical modeling of the OUT and of the system in order to accurately simulate 21(zn) − S21(zn−)| (in dB) vs. frequency simulated in presence (solid lines) and in absence (dashed lines) of the glass inclusion in the OUT. As it can be seen, in this case, a remarkable difference is still observed only when the inclusion is present, while it is practically zero in absence of it. Same behavior is observed for |S11(zn) − S11(zn−)| and |S22(zn) − S22(zn−)| but not reported for the sake of brevity. This confirms that, unlike the PSP-based approach, the detection capability of the OSP-based approach is not impaired by not perfectly centering OUT with respect to the two antennas. Therefore, at least when only the detection of the inclusion is of interest, the OSP-based approach is more robust than the PSP-based approach, as it does not require knowing possible displacements of the OUT from the middle between the two antennas. Therefore, it can be employed as a stand-alone approach of detection. Anyway, such information is still needed for the imaging, even if in this case we do not need to calibrate the data through (5), but the displacement must be taken into account solely in the computation of the Green’s matrixes in (4).As for the OSP-based approach, Finally, let us note that a similar analysis should be carried out by assuming not perfectly symmetric antennas. However, the effect of such asymmetry on the performances of the two approaches is analogous to that produced by a not perfect centering of the OUT between the two antennas, so that the above outcomes can be directly applied to this case.11 and S22 without inclusion, of approximately −55 dB, which is larger than the considered noise level (−65 dB) but comparable to the level of the signal scattered by the considered inclusion , tin welds and so on. Indeed, while the geometry/layout is almost the same for both antennas , the connection components, especially the tin welds, can be significantly different. However, in this study, not printed antennas  were considered, which allows for minimizing this source of asymmetry. In any case, it is worth mentioning that possible residual asymmetries in the antennas’ behavior can be characterized and compensated or treated as a further source of noise, with the effect of increasing the level of the threshold above which the level of the differential data must be located to establish the presence of the inclusion. For instance, by indicatively assuming an (average) antenna return loss of approximately −25 dB, over the analyzed band see , and a dsion see .As final remark, let us note that, as happens in the case of a not perfect centering of the OUT between the two antennas, asymmetries in the antenna behavior only affects the performance of the PSP-based approach but not that of the OSP-based approach.In this paper a simple MWI detection/imaging strategy enabling the in-line inspection of the possible presence of foreign bodies in packaged food, has been proposed. The strategy relies on the symmetries usually characterizing food items (and the radiating system), which can be broken by the presence of inclusions, thus determining a differential signal, revealing their presence. A quite common case, analyzed in this work, is that of homogeneous food packaged in a circular non-metallic jar. For this case, two approaches have been proposed, differing for the exploited symmetry: the PSP-based approach, which processes the difference arising in the reflection coefficients, measured at the two antennas, when the symmetry with respect to the PSP  is broken by the presence of an inclusion; and the OSP-based approach which processes the difference arising in all the scattering parameters, measured for each couple of positions of the OUT along the direction of movement, when the symmetry with respect to the OSP  is broken by the presence of an inclusion.A comprehensive numerical analysis has shown the capability of both the approaches in detecting the inclusion as long as it does not lie on one of the symmetry planes characterizing each approach. A good reconstruction of the inclusion has also been achieved, except for the presence of a second “spot” in the mirror position, due to symmetrization. In any case, both of these drawbacks can be mitigated by combining the re-constructions achieved with both the approaches.The robustness against possible displacements of the OUT from the middle between the two antennas has also been investigated. The analysis showed that the PSP-based approach is very sensitive to this, as the considered symmetry is also lost in the absence of inclusions. However, the approach still works provided to know, and hence to compensate, the displacement. On the contrary, at least for what concern the detection, the OSP-based approach is poorly sensitive to such error as the considered symmetry is not broken by such displacements. However, its knowledge is still required to achieve a reliable imaging of the inclusion. Accordingly, the OSP-based approach is preferable to the PSP-based approach at least when the only detection of the inclusion is of interest.As final remark, it is worth remarking that the proposed approach works as long as the food product is  homogeneous. However, this condition could be not verified by the possible formation of air bubbles in the food during its pouring in the jar, which may render the food not homogeneous. Fortunately, this is issue can be easily eliminated by slightly shaking the object. Also, due to the negative electric contrast that air bubbles would induce in the food , they could be recognized as such, for instance, by employing, in combination, an algorithm of machine learning, as the one in .In addition, we would like to stress that, while the presented study is still at numerical level, there are works in the literature wherein an experimental assessment  of a similar MWI tool has already been provided . Indeed,


We recently demonstrated that human skin is equipped with ultrafast (Aβ range) nociceptors. Here, we investigated the short-latency component of the reflex and explored the relationship between reflex latency and pain perception.The role of pain as a warning system necessitates a rapid transmission of information from the periphery for the execution of appropriate motor responses. The nociceptive withdrawal reflex (NWR) is a physiological response to protect the limb from a painful stimulus and is often considered an objective measure of spinal nociceptive excitability. The NWR is commonly defined by its latency in the presumed Aδ range were considered. In our current analysis, we expanded the time window to search for shorter latency responses and compared those with pain ratings.We revisited our earlier work on NWR measurements in which, following convention, only reflex responses in the presumed AIn both cohorts, we found an abundance of recordings with short-latency reflex responses. In nearly 90% of successful recordings, only single reflex responses  were seen which allowed us to compare pain ratings based on reflex latencies. We found that shorter latency reflexes were just as painful as those in the conventional latency range.We found a preponderance of short-latency painful reflex responses. Based on this finding, we suggest that short-latency responses must be considered in future studies. Whether these are signaled by the ultrafast nociceptors remains to be determined. It has been investigated both as a tool to probe spinal nociceptive excitability and because of its close association with subjective pain thresholds –7. The NI fibers . The conI fibers ). While I fibers , 10–12.β range) nociceptors in the skin  and 10 healthy controls . For details on patient eligibility criteria, refer to Ydrefors et al. . Raw datFor full details on the testing procedure, refer to Ydrefors et al. . BrieflyAll participants rated the intensity of the sensation, immediately after receiving the electrical stimulus, on a descriptive numeric scale from 0 to 10. Zero corresponded to “no feeling”, 1 to a “slight feeling”, 2 to a “distinct feeling”, 3 to “unpleasantness”, 4 to “just noticeable pain”, 5 to “slight pain”, 6 to “distinct pain”, 7 to “moderately intense pain”, 8 to “intense pain”, 9 to “very intense pain” and 10 to the “worst imaginable pain” .Z-scores were calculated for the early time window of 50 to 89 ms after stimulus onset, using the same MATLAB algorithm that was used for the 90 to 150 ms time window. Careful visual inspection of the data allowed us to extract reflex responses with Z-scores ≥6.The data were pseudonymized and information on latency, Z-scores, NWR thresholds, and age were stored in a relational database. NWR responses were converted from text files (.txt) into graphs (.png), using a script made in Python Distribution  and latencies were visually inspected by the author (OT) in LabChart  and in MATLAB . Statistical analysis was done in GraphPad Prism . QQ plots, means, standard deviations, and skewness were assessed to determine the normal distribution of the data. Where possible, parametric tests were used. If assumptions for parametric tests were violated, non-parametric tests were conducted.U test. Two-way ANOVA was used to compare multiple independent groups with Tukey's test as a multiple comparison (post-hoc) test. Only main effects were analyzed due to uneven sample sizes. A statistical value of p < 0.05 was considered statistically significant.To compare independent differences between HC and FM, unpaired two-tailed t-test was used, while small sample size data were analysed using two-tailed Mann-Whitney 2p) for the two-way ANOVA. Common language effect sizes (CLES) are shown for statistically significant ANOVA results. When using non-parametric tests, CLES is shown to compare effects to the parametric results. Effect sizes were calculated in statistical calculators  reflex responses were identified in the 90- to 150-ms latency range corresponding to RIII, and 190 reflexes (49.7%) were identified in the 50- to 90 ms latency range corresponding to RII. The RII data are new: the pre-set 90 ms latency cut-off implemented in Ydrefors et al.  resultedp = .717) (Eighteen out of 20 HC (90%) and 13 out of 20 FM (65%) had an RII. No differences were found in stimulus intensities between RII and RIII ( = .717) . To dete = .717) . FM had  = .717) . A small = .717) .As an alternative to a pre-set latency cut-off for RII/III (90 ms), we used the data from dual reflex responses to distinguish between RII and RIII latencies. No dual responses occurred before 93 ms or after 99 ms, therefore we took an in-between value of 96 ms to separate RII and RIII responses . PredictZ-scores ≥6. For comparison, we performed the analysis implementing the original Z-score (≥12) condition. A total of 234 NWR responses had a Z-score of 12 or higher  of the NWR in the current study. One study based on afferent CVs from single painful shocks with near-nerve stimulation of the tibial nerve reported velocities of 18.5 ± 1.3 m/s with onset latencies between 100 and 200 ms . Anotherty range , howeverβ nociceptors remains to be determined.We found a great many short-latency NWR responses that were as prevalent and as painful as the conventional longer latency NWR responses. Reflex responses that were not painful rarely occurred. Only a minority of NWR recordings consisted of dual reflexes. Pain ratings were similar across all latencies, suggesting that the short-latency component is not tactile but nociceptive. Whether this fast signaling involves A


Failure mode and effects analysis (FMEA) has been widely used for potential risk modeling and management. Expert evaluation is used to model the risk priority number to determine the risk level of different failure modes. Dempster–Shafer (D–S) evidence theory is an effective method for uncertain information modeling and has been adopted to address the uncertainty in FMEA. How to deal with conflicting evidence from different experts is an open issue. At the same time, different professional backgrounds of experts may lead to different weights in modeling the evaluation. How to model the relative weight of an expert is an important problem. We propose an improved risk analysis method based on triangular fuzzy numbers, the negation of basic probability assignment (BPA) and the evidence distance in the frame of D–S evidence theory. First, we summarize and organize the expert’s risk analysis results. Then, we model the expert’s assessments based on the triangular fuzzy numbers as BPAs and calculate the negation of BPAs. Third, we model the weight of expert based on the evidence distance in the evidence theory. Finally, the Murphy’s combination rule is used to fuse the risk assessment results of different experts and calculate the new risk priority number (RPN). At the end of this paper, we apply the proposed method to analyze seventeen failure modes of aircraft turbine blades. The experimental results verify the rationality and effectiveness of this method. FMEA can improve the quality, safety and reliability of the products. Due to its remarkable advantages, FMEA has been widely used in various fields, such as steel production7, fishing boat propulsion system8, sewage treatment9 and so on11. The most commonly used tool for FMEA is the risk priority number (RPN), which is expressed as the product of occurrence (O), severity (S) and detection(D). Although FMEA has significant advantages12, as the assessment system becomes more and more complex, the results of the assessment are subject to great uncertainty, which greatly influences the final risk analysis. Firstly, different risk factors will produce the same RPN value. For example,  and , the final RPN value is same, but the occurrence and severity of the two are quite different. Secondly, traditional risk priority number treats O, S and D as equally crucial, but in fact their weights may vary. Finally, the rating of each risk factor is rated as , so that the final RPN value will be between 1 and 1000, but not all the numbers between them can represent RPN values, in fact, there are only 120 discrete values14. When we do FMEA, we need to deal with uncertain information. At present, there are many methods to study uncertain information, such as fuzzy set theory18, D numbers theory19, Dempster–Shafer (D–S) evidence theory21, grey theory23, analytic hierarchy process25 and so on. Because D–S evidence theory has significant advantages in dealing with uncertain information and independent evidence fusion, Ma et al.26 applied D–S evidence theory to the gender analysis. In addition, Liu et al.27 applied D–S evidence theory to supplier selection, Perez et al.28 applied D–S evidence theory to 3D human motion recognition. In this study, we also choose D–S evidence theory as our research method to figure out uncertain information.Failure Mode and Effects Analysis (FMEA) was first proposed by NASA in 1960s. It is a tool of risk analysis and management, which aims at allocating limited resources to the projects with the highest riskIn application of D–S evidence theory, how to generate basic probability assignment (BPA) is an open issue. For FMEA, we propose a novel method of generating BPAs for modeling the risk priority number in this paper.29, Su et al. used Gaussian function to construct BPAs30. Tang et al. used triangular distribution to construct BPAs for incomplete and uncertain information31. Mendonca et al. used game theory to solve data conflicts32. The base BPAs is an option in generating BPAs considering potential conflict information33. In this paper, we firstly construct BPAs through triangular fuzzy numbers to reduce the evidence conflict, and then consult the negation35 of BPAs to study the uncertainty of uncertain information from another angle.Quite a few scholars have put forward their own solutions to this problem. Jiang et al. proposed using fuzzy set theory to solve evidence conflictDue to the different professional backgrounds of different experts, the assessment weight of each risk factor for the same failure mode may be different.36. However, the evaluation of each failure mode by experts is based on their own subjective evaluation, which aggravates the uncertainty and ambiguity of the evaluation results37. Based on this consideration, we calculate expert weight by the evidence distance39, and finally fuse the evidence with expert weight. Other solutions for conflict data fusion can be belief entropy-based methods41.As an important reference in the field, expert knowledge plays a vital role in FMEA42 proposed a method to reduce the evidence conflict based on Tanimoto measure. Miao et al.43 achieved the goal of reducing the evidence conflict by modifying the D–S combination rule. Hu et al.44 used feature fusion method to solve this problem. Generally speaking, there are two main methods to reduce evidence conflict. One is to modify the preliminary test information, and the other is to modify the combination rule. Our research integrates these two methods. And then the idea of construct the negation46 is firstly applied to the failure mode and effects analysis.To reduce the evidence conflict, we introduce triangular fuzzy numbers to construct BPAs. In fact, different scholars have proposed many methods to reduce the evidence conflict. Bi et al.47, AMWRPN48, Ambiguity Measure49 and so on52. These methods show good characteristics in some attributes. Compared with these methods, the evidence distance can accurately calculate the distance between two bodies of evidence, so as to provide a reliable guarantee for calculating similarity, which is why we choose evidence distance to calculate expert weight.The evidence distance is used to calculate the weight of the experts participating in the risk assessment, which reduces the uncertainty and ambiguity of the assessment results caused by the subjectivity of the expert assessment. As a matter of fact, there are many ways to get the weight of experts, including Deng entropyCompared with a large number of FMEA methods, the main contributions of the method proposed in this paper are as follows:In this paper, the rest of the content is arranged as follow. In “In this part, we introduce some basic concepts, including D–S evidence theory, the negation of BPA, Murphy combination rule, the evidence distance, triangular fuzzy numbers and risk priority number(RPN).m mutually exclusive events. The power set Frame of discernment mass function m is the mapping of set m(A) is the mass function value of proposition subset A, also known as Basic Probability Assignment (BPA), the sum of all mass functions is 1. We call A fatal element if m(A)>0.Within the frame of discernment, the basic evidence function is defined to represent uncertain information, mass functions 54:Under the framework of evidence theory, two groups of independent k the conflict coefficient.We call n groups of independent mass functions n groups of mass as n-1) times to get the new mass function. Murphy combination rule is defined as follows:For n is the amount of fatal element, and In the evidence theory,Yagar proposed a concept of negation for probability distribution. The main ideas are as follows:N elements, the evidence distance between two bodies of evidence, severity (S) and detection (D).FMEA method is used for risk analysis based on the RPN number. RPN is expressed as the product of three risk factors: occurrence  results of two experts12), we g and Eq. , the res and Eq.  to normaThen, we use credibility as the weight of BPAs to calculate the Finally, we can get the improved RPN value:48 uses the method of Ambiguity Measurement to calculate the weight of experts. MVRPN60 averages the obtained RPN values. Improved MVRPN30 further improves the combination rule of MVRPN60. As described in the literature, FM2 and FM9 have the highest priority, indicates that more resources should be allocated to it. In Fig. After the same calculation process for 17 failure modes, using Eq.  we get tIn the frame of D–S evidence theory, this paper proposes an improved failure mode and effects analysis method based on triangular fuzzy numbers, negation of BPAs and evidence distance. Firstly, the new BPAs was constructed by fuzzy modeling of expert evaluation results, then calculate the negation of BPAs, next BPAs weight was calculated by evidence distance, and finally, a new RPN value was calculated by fusion of Murphy combination rule. In short, the method considers how to fuse conflicting evidence from experts and also considers the relative weight inconsistency caused by the uncertainty of experts’ evaluation. We apply the proposed method to the failure mode analysis of compressor rotor blades and turbo rotor blades. The experimental results verify the effectiveness and rationality of this method. In the future research, we can broaden our approach to other fields. Moreover, we can consider the relative importance of each risk factor to enrich our study.