In areas where malaria transmission has been suppressed by vector control interventions many malaria control and elimination programmes are actively seeking new interventions to further reduce malaria prevalence, incidence and transmission. Malaria infection prevalence and incidence has been shown to cluster geographically, especially at lower transmission levels, and as such a reactive strategy is frequently used, by which index cases presenting to a passive surveillance system are used to target small areas for testing and treatment, reactive case detection (RCD), or focal drug administration (fDA). This study utilizes geo-located data from a census with parasitological testing with rapid diagnostic tests (RDTs) and treatment-seeking data collection conducted in southern Zambia to estimate the coverage of RCD or fDA in terms of the population and parasite reservoir as well as the operational requirements of such strategies, using a re-sampling algorithm developed exclusively for this purpose. This re-sampling algorithm allows for the specification of several parameters, such that different operational variants of these reactive strategies can be examined, including varying the search radius, screening for fever, or presumptive treatment (fDA).Results indicate that RCD, fDA and active fever screening followed by RCD, even with search radii over several hundered meters will only yield limited coverage of the RDT positive parasite reservoir during a short period. Long-term use of these strategies may increase this proportion. Reactive strategies detect a higher proportion of the reservoir of infections than random searches, but this effect appears to be greater in areas of low, but not moderate malaria prevalence in southern Zambia.Increases in the sensitivity of RDTs could also affect these results. The number of individuals and households that need to be searched increase rapidly, but approximately linearly with search radius.Reactive strategies in southern Zambia yield improved identification of the parasite reservoir when targeted to areas with prevalence less than 10%. The operational requirements of delivering reactive strategies routinely are likely to prevent their uptake until prevalence falls far below this level. In areas where malaria transmission has been suppressed by vector control interventions many malaria control programmes actively seek new interventions to further reduce malaria prevalence, incidence, and transmission. Additionally, programmes which are considering or have undergone a re-orientation towards malaria elimination may be seeking interventions to actively reduce or eliminate remaining foci of infection. Malaria infection prevalence and incidence have been shown to cluster geographically, especially at lower transmission levels –3, and aLittle is known, however, about the effectiveness of the use of reactive approaches to guide MDA and MTAT, and few studies have made an attempt to estimate the potential of reactive strategies to cover high proportions of the reservoir of infections –7. A numIn order to effectively plan for the deployment and testing of RCD or fDA strategies, when and if they are used, it will be necessary for malaria control programmes to make local assessments of both the expected coverage of the intervention in operational and parasitological terms as well as the resource requirements and the ideal search strategy to use in the response to index case identification.In Zambia, malaria vector control, intermittent preventive treatment in pregnancy (IPTp) and treatment with artemisinin-based combination therapy (ACT) have been scaled up nationwide. These interventions, along with community case management, have reached high and sustained coverage, resulting in significant reductions in the malaria burden in some areas , 13. In This study utilizes geo-located data from a census of 23 health facility catchment areas with parasitological testing and treatment-seeking data collection, which was conducted in southern Zambia. These data were used to estimate the coverage of RCD or fDA in terms of the total population and the parasite reservoir as well as the operational requirements of such strategies, using a re-sampling algorithm developed exclusively for this purpose.Southern Province, Zambia is an area of moderate but heterogeneous malaria transmission. In the years 2012 and 2013, six rounds of dry-season MTAT were conducted in four districts as part of a community randomized controlled trial. The current study utilizes data from one round of data collection covering 23 health facility catchment areas. The study site has been described in detail elsewhere . Figure SD Bioline Pf and ICT Mal Pf brands); both detect histidine-rich protein 2 (HRP2). CHWs conducted the screening alongside survey teams collecting household and individual level data. Data were entered using personal digital assistants equipped with GPS devices. The data collected among consented households and individuals included household geo-location, household composition, RDT positivity/negativity, household bed net ownership, individual fever history and treatment seeking for malaria among all household residents. Data collection has been described in more detail previously  programming language . The basOutputs include several summary measures for each simulation  or by first summarizing within each catchment area and then taking the catchment level estimates as individual data points and summarizing across the entire study area .Operational analysis consisted of summarizing outputs including the number of index cases, and the number of houses searched and individuals tested, treated, or identified with parasite infections. These parameters were summarized in terms of means across all simulations with a given set of search criteria and the credible intervals generated by taking appropriate quantiles of the resulting distribution of outputs.Based on these re-samples, the likely coverage and resource requirements for RCD in the context of southern Zambia was estimated. Figure Increasing search radius or the number of households searched in a RCD re-sample increased the probability of finding a higher proportion of infected individuals. This is necessarily true across both higher and lower prevalence settings. However, even search radii up to 1.5 km found less than 80% of RDT positive individuals in the majority of re-samples Figs. a, 5. TheMeaningful levels of clustering of malaria RDT positive individuals were present in lower prevalence areas. Varying the number of nearby households searched resulted in similar findings, though calibrated on a different scale. With a fixed RCD search radius, lowering the coverage of households within the search area and of individuals within searched households who are tested or treated limited the overall ability of the RCD system to identify infected persons.The algorithm allows for individual treatment-seeking probability to be specified. Individuals who reported a history of fever in the previous two weeks were given a probability of seeking treatment. This allowed for the investigation of the impact that failure to seek treatment has on the ability of an RCD system to identify significant portions of the RDT positive reservoir of infected individuals. Increasing the treatment-seeking probability from levels actually observed to much higher values increased the coverage of the RCD system for a given search radius, mainly by increasing the number of index cases generated, this was true in both high and low prevalence areas Fig. b.Fig. 6RTreatment-seeking by all febrile cases would result in more efficient identification of malaria infected individuals than random testing in the population Fig. , suggestHigher proportions of the infectious reservoir were detected in low prevalence areas vs. moderate prevalence areas after controlling search radius and treatment-seeking probability Fig. . SimilarResults for RCD identification of an RDT positive individual are dependent on the sensitivity of the diagnostic used in the RCD search Fig. , as wellIncreasing the diagnostic sensitivity in the field results in a higher proportion of RDT positive individuals identified in the search process though gains are small, even when sensitivity is increased to its maximum levels Fig. . DecreasIncreasing search radii or number of households searched in response to an index case led to increases in the number of individuals and households searched Table . HoweverWhen households were searched uniquely, the number of houses or individuals who would be searched with a RCD approach showed diminishing returns to expansion of the search radius, while the number of household searches which occurred when such searches could occur more than once in a short period (~2 weeks) increased roughly linearly with the increase of radius over a search area.Differences between the total houses searched in a non-unique search framework and in a unique search framework were considerable, indicating that as search radius was swept to larger values that there was significant overlap in the areas indicated for RCD.Increasing individual treatment-seeking probability led to higher numbers of households and individuals searched Table  when comIn addition to sensitivity, diagnostic specificity will also affect the performance of a system Table . ReducinIncreasing the sensitivity of the diagnostic at the facility leads to minimally increased numbers of investigations, households and individuals searched while decreasing the specificity of the diagnostic used at the facility leads to an increase in the number of searches, households and individuals searched for small search radii. Though this effect is mitigated at larger search radii where, overlap between searched households reduces the number of newly searched households for each index case.RCD and related strategies are used mainly by malaria elimination programmes, and have been deployed widely in Asia though only to a limited extent in Africa. The literature on operational issues, reservoir coverage and programme effectiveness is limited, but has expanded in recent years , 16–23. While a shift from RCD to an active fever search would mitigate some of the problems with low treatment seeking, it would also require wide population sweeps to identify persons with a history of fever or a current febrile illness as candidate index cases. Such an approach would be operationally challenging and costly to carry out on large scales. Other strategies to change treatment-seeking for febrile illness including the expansion of the health system and behaviour change communication may also be options. For example, fever treatment could be improved by extending testing and treatment services into communities and closer to areas where malaria infections occur. Other methods to increase the number number index cases generated such as decreasing the specificty of criteria for selection of index cases at the facility could also improve reservoir coverage.The data represents a time when no RCD system was in place in the MTAT areas and when the transmission was much higher than currently in Southern Province. In simulations where reported treatment seeking was used these were based on people attending health facilities, not to local CHWs or other community case management (iCCM) implementers. While the treatment-seeking probability was explored in sensitivity analysis, results of improving treatment-seeking for the average person with fever may not reflect the same patterns as occur with the roll out of CHWs as part of iCCM. Currently RCD systems are being piloted in Zambia and expansion of the health system through the roll out of iCCM has also occurred , 25. TheOne earlier study used population level summaries from southern Zambia survey data to develop an agent-based transmission model to simulate the population data to which an approach to RCD similar to the one described here was applied . This stAnother earlier study using survey data from southern Zambia used a combination of logistic regression methods, and geographic analysis to estimate the proportion of infected individuals living within a specified radius of a household with a positive malaria RDT result for a person who was positive and sought care . The SeaThis study is limited by several threats to external and internal validity. One major factor is that, though it utilizes census data, which mitigates some limitations of previous studies which had to impute outcomes for a majority of households , it stilThis study only estimates the reservoir coverage that might be expected in RCD and related systems over a short period of time (~2 weeks). This neither implies that coverage will remain low over extend periods should RCD or related approaches be sustained, nor that there will be no effect on transmission even at low reservoir coverage (though results for previous studies indicate that even high reservoir coverage in a short period are unlikely to have major effects in this setting ). FurtheA number of additional factors will be important to consider in future work in this area. These include generating field trial data and mathematical model based estimates of the effectiveness and efficacy of RCD and related strategies, and identifying the determinants which may affect coverage. Some modelling work on limited data sets from this area of Zambia has already been conducted .Additionally, as this study has shown that the resource requirements of conducting RCD and similar strategies may be significant, a finding consistent with qualitative and quantitative work already undertaken in Zambia , 27. An RCD, fDA and active fever screening followed by RCD will only yield limited coverage of the RDT positive parasite reservoir over a short time period. Use of reactive strategies as routine tools for an extended period may increase this proportion. Reactive strategies with a fixed radius around an index case detect a higher proportion of the reservoir of infections than similar searches around randomly selected househods, but this effect appears to be greater in areas of low, but not moderate malaria prevalence in southern Zambia. Changes in the detection limit of RDTs could also affect results. The number of individuals who need to be searched, and thus the resource requirements to do so increase rapidly, but approximately linearly with search radius. RCD, if implemented in southern Zambia, would yield higher fractions of the reservoir detected with similar effort if targeted to areas with prevalence less than 10%. Increasing the probability that febrile individuals seek care or the search radius around index cases can both increase the proportion of the reservoir covered by RCD and related strategies, however, both approaches will increase the coverage most quickly when they start from low levels, and neither appears to greatly increase the fraction detected once moderate levels of sensitivity or treatment seeking are reached. The success of an RCD system appears highly dependent on its ability to actually search the houses and individuals that are within target areas for additional malaria infections—programmes implementing these strategies should not neglect the operational aspects of these systems.


A new term, malnutrition-sarcopenia syndrome (MSS), was recently coined to describe the clinical presentation of both malnutrition and sarcopenia. The aim of this study was to investigate the association between MSS and long-term mortality in older inpatients. We conducted a prospective study in acute geriatric wards of two local hospitals in China. Muscle mass and malnutrition were estimated by anthropometric measures and the Mini Nutritional Assessment (MNA). Of the 453 participants, 14 (3.1%) had sarcopenia with normal nutrition, 139 (30.7%) had malnutrition risk without sarcopenia, 48 (10.6%) had malnutrition risk with sarcopenia, 25 (5.5%) had malnutrition without sarcopenia, and 22 (4.9%) had MSS at baseline. Compared with non-sarcopenic subjects with normal nutrition, subjects with MSS and subjects with malnutrition risk and sarcopenia were more than four times more likely to die ; non-sarcopenic subjects with malnutrition risk were more than two times more likely to die . In conclusion, MSS may serve as a prognostic factor in the management of hospitalized older patients. Older people with malnutrition  are at increased risk of adverse clinical outcomes, such as prolonged length of hospital stay, increased health costs, poor quality of life, and mortality2.Malnutrition is common in different populations, but especially in older adults3. Sarcopenia is also prevalent in older adults, especially among those in health care settings4. Furthermore, sarcopenia is also associated with many adverse health outcomes, including death5. Although malnutrition and sarcopenia may share some clinical features, such as abnormal body weight or inactivity6, the fundamental mechanisms of the two conditions differ7.Sarcopenia is a new geriatric syndrome that comprises age-related loss of muscle mass, strength, and performance7. This concept has not yet been widely accepted, and its value for clinical practices and research remains unclear. In hospitalized older patients, both malnutrition8 and sarcopenia10 are highly prevalent and have been proven to increase the risk of death; therefore, we speculated that older inpatients with both syndromes  were at higher risk of mortality than those only suffering from either malnutrition or sarcopenia. We conducted a prospective study with the following objectives: 1) to identify the prevalence of malnutrition, sarcopenia, and MSS in a study population of hospitalized older patients; and 2) to investigate the association between MSS and long-term mortality in this population.Based on these facts, Vandewoude and colleagues recently suggested using a new term, “malnutrition-sarcopenia syndrome (MSS)”, to describe the clinical presentation of both malnutrition and sarcopeniaWe conducted a prospective study in the acute geriatric wards of two local hospitals located in Chengdu, China: West China Hospital of Sichuan University and the Fifth People’s Hospital of Chengdu City. The study protocol was approved by the Research Ethics Committee of Sichuan University. A written informed consent was obtained from all participants or their legal proxies. All methods in this study were in accordance with relevant regulations and guidelines.During August to December 2012, we recruited the consecutively admitted older patients (aged 60 years or older) from the acute geriatric wards of the two hospitals to participate in this study. Patients with the following conditions at admission were excluded: 1) end-of-life diseases; 2) clinically visible edema; 3) severe cognitive impairment, and 4) delirium.Trained interviewers performed face-to-face interviews to obtain the baseline data from all participants within 48 hours after admission. In addition, the following anthropometric measurements were performed by trained technicians: body weight, height, mid-arm circumference (MAC), and calf circumference (CC).11 was applied to define sarcopenia. According to the AWGS recommendation, patients with low muscle mass combined with low handgrip strength (HS) and/or a low gait speed (GS) were considered to have sarcopenia 12:The appendicular skeletal muscle mass (ASM) was estimated using an equation previously validated in a Chinese population12. The agreement of the ASM equation model and dual X-ray absorptiometry (DXA) was good  = 1.63 kg)12.The body weight, height, and age were measured in kilograms, centimeters, and years, respectively. For gender, a value of 1 represented men, and a value of 2 represented women2. Similar to previous studies15, the cut-off for defining low muscle mass was based on the SMI of the lowest 20th% percentile of the study population. Therefore, a low muscle mass was defined as an SMI less than 6.92 kg/m2 in men and less than 5.13 kg/m2 in women.Thereafter, the muscle mass index (SMI) was calculated using the following equation: SMI = ASM/heightThe HS was measured by trained technicians using a handheld dynamometer based on strain gauge sensors  to the nearest 0.1 kg. According to the AWGS consensus, a low HS was defined as less than 26 kg for men and less than 18 kg for women.11, a 4-meter walking test was performed to measure the usual gait speed. Canes or walkers were accepted during the walking test, if necessary. A low GS was defined as less than 0.8 m/s11.As recommended by the AWGS16 to assess the participants’ nutritional status. The MNA is “the most widely used tool for nutritional screening and assessment of the elderly”16. It has been validated in different populations including Chinese17. The total score of the MNA is 30 points, a higher score is preferable. Subjects with scores of 23.5 or more were classified as normally nourished; a score between 17 and 23.5 indicated that a subject had “malnutrition risk”; and a score of less than 17 indicated that a subject had malnutrition16.We used the Mini Nutritional Assessment (MNA)19. And we compared the nutrition status defined by the MNA and the modified “MNA without BMI”.It is noteworthy that the BMI is included in both the MNA and the aforementioned SMI equation as a component. However, the MNA includes 18 items with a total of 30 points and the BMI is only one item of the MNA (with a maximum of 3 points). Therefore, we hypothesized that nutrition status, which is defined by the MNA, would not be significantly influenced by the BMI. To support our hypothesis, we also defined the nutrition status by using the modified “MNA without BMI” that has been validated previously in Taiwanese20 and the Chinese version of the Mini-Mental Status Examination (MMSE)21, respectively. The Older Americans Resources and Services (OARS) multidimensional functional assessment questionnaire22 was applied to assess the activity of daily living (ADL) and instrumental activity of daily living (IADL) of each participant.We collected the following covariates from the face-to-face interviews: age, gender, education level, physical activity ≥30 min/d, smoking status, and alcohol drinking status. We also identified the following conditions using the hospital information systems: hypertension, ischemic heart disease, chronic obstructive pulmonary disease (COPD), diabetes, stroke, chronic kidney disease, acute infection, tumor of any type, osteoarthritis, liver disease, gastrointestinal disease, urinary incontinence, chronic pain, and receiving nutritional supplements during hospitalization. Furthermore, we evaluated depression and cognitive function using the Chinese version of the 30-item Geriatric Depression Scale (GDS-30)The survival status of the participants was collected by telephone interviews at 12, 24, and 36 months during the 3-year follow-up period. These survival data were also confirmed using the Local Death Registry Database. Time to death was calculated as the time between the first interview and the date of death.We presented the categorical data as absolute number and percentages (%) and the continuous data as the mean ± standard deviation (SD). We applied the Pearson chi-squared test for categorical data and the one-way ANOVA for continuous data to compare the differences between groups. A p value less than 0.05 was considered statistically significant. We applied Cox regression models with a backward stepwise selection to calculate the adjusted hazard ratios (HR) and 95% confidence intervals (CI) and identify independent prognostic factors for all-cause mortality. The initial model of backward stepwise selection included the following covariates: age, gender, education level, smoking status, alcohol drinking status, physical activity status, conditions listed above, ADL scores, IADL scores, GDS-30 scores, and MMSE scores. In these models, the criteria for entry and removal were p < 0.05 and p > 0.10, respectively. Multiplicative interaction was evaluated by creating a cross-product of each aforementioned covariate and the “nutrition combined with sarcopenia” status. And we included these cross-product terms, along with their main effects and the other covariates, in a Cox proportional hazard model. In addition, Survival curves were estimated using the Kaplan–Meier method. Survival curves were compared using log-rank tests. Statistical analysis was performed using SPSS 20.0 .A total of 453 subjects were included in the baseline analyses Fig. . In the Based on the recommendation of the AWGS, 83 participants (18.3%) were found to have sarcopenia at the baseline investigation. The prevalence of sarcopenia was similar between men and women . Supplementary Table Based on the results of the MNA scale, the prevalence of malnutrition risk and malnutrition were 41.3% and 10.4%, respectively. Men were more prone to suffered from malnutrition risk than women , however, there was no significant difference between men and women with respect to malnutrition . Table When using the modified “MNA without BMI” scale, the prevalences of malnutrition risk and malnutrition were very similar  and malnutrition . In addition, both sarcopenic men and women exhibited a lower BMI, MAC, and CC compared with their counterparts without sarcopenia  had sarcopenia with normal nutrition, 139 (30.7%) had malnutrition risk without sarcopenia, 48 (10.6%) had malnutrition risk and sarcopenia, 25 (5.5%) had malnutrition without sarcopenia, and 22 (4.9%) had MSS. Figure During the 3-year follow-up, 79 participants (19.1%) died . The 3-year all-cause mortality was 9.3% in subjects with non-sarcopenia and normal nutritional status, 21.4% in sarcopenic subjects with normal nutritional status, 22.7% in non-sarcopenic subjects with malnutrition risk, 23.8% in non-sarcopenic subjects with malnutrition, 43.2% in sarcopenic subjects with malnutrition risk, and 38.1% in subjects with MSS (p < 0.001). Table In addition, the sensitivity analyses did not find any evidence of multiplicative interaction between each covariate and the “nutrition combined with sarcopenia” status on all-cause mortality  were at even higher risk of 3-year all-cause mortality.1. Many screening tools have been developed for identifying malnutrition in older adults, such as the Nutritional Risk Screening 2002 (NRS-2002), the Malnutrition Universal Screening Tool (MUST), Subjective Global Assessment (SGA), and MNA1. According to a recent systematic review22, MNA performed fair to good in older people; MUST performed fair to good in adults; whereas SGA, NRS-2002 and MUST did not perform well in predicting health care outcomes in older patients. Therefore, we chose MNA for screening malnutrition in this study.Malnutrition currently lacks clear and well-accepted diagnostic criteria7. However, when focusing on malnutrition as defined by the MNA, inconsistent results were identified in previous studies. For example, a prospective study demonstrated that malnourished inpatients (assessed by the MNA) in acute geriatric wards had a higher risk of 1-, 2- and 3-year mortality compared with their counterparts with normal nutrition23. Similarly, another prospective study found that malnutrition defined by the MNA was an independent prognostic factor for long-term mortality in hospitalized geriatric patients with heart failure24. Our study found similar results in a study population of Chinese older inpatients. However, several other studies have found opposite results26. For example, Vischer et al. reported that malnutrition, as defined by the MNA, failed to predict long-term mortality in older inpatients with a heavy disease burden25.The association between malnutrition and mortality has been well documented in previous studies27. Because all participants were Han Chinese, we applied the diagnostic algorithm from the AWGS11 to define sarcopenia in this study. It is notable that the AWGS11 recommended using bioelectrical impedance analysis (BIA) or DXA to estimate muscle mass; however, we estimated muscle mass using a previously validated anthropometric equation in this study. The reason for this inconsistency is that BIA has recently been proven to overestimate muscle mass compared with DXA in older inpatients. Furthermore, the cut-off points for defining low muscle mass in Chinese older adults using BIA have not yet been established29. On the other hand, DXA is expensive and associated with a risk of X-ray exposure. Furthermore, Alexandre et al. recently reported that the use of anthropometric equations to estimate muscle mass combined with the handgrip and gait speed constituted an important alternative to DXA for diagnosis of sarcopenia and reduced costs15.Well-accepted diagnostic criteria for sarcopenia is lacking. There are currently at least five international consensuses available for defining sarcopenia30. Cerri et al. reported that sarcopenia was associated with short-term mortality in older inpatients with or at-risk for malnutrition31.This study indicated that older inpatients with MSS or with malnutrition risk and sarcopenia were at higher risk of long-term mortality when compared with those having either of the two syndromes alone; whereas sarcopenic subjects with normal nutrition had no significantly increased risk of death. These findings imply that it is valuable to assess sarcopenia together with nutritional status in the management of geriatric inpatients. Although there is no published study addressing the association between MSS and mortality, several studies did evaluate malnutrition and sarcopenia at the same time in various study populations. For example, a recent prospective study demonstrated that malnutrition and sarcopenia were separately and significantly associated with post-liver transplant morbidity and 1-year mortalityThis study demonstrated that subjects with MSS and subjects with malnutrition risk and sarcopenia were at similarly increased risk of death. Similarly, non-sarcopenia subjects with malnutrition and with malnutrition risk were also at similar risk of death. These findings suggest that the identification of malnutrition risk in hospitalized older patients is at least as importance as the screening of malnutrition in either sarcopenic or non-sarcopenic individuals. Our study provides a confirmative answer to the question of whether subjects with malnutrition risk and sarcopenia fall within the MSS.7. However, the reliability and validity of the assessment tool are unknown. In this study, we did not apply that assessment tool because we did not estimate the muscle mass by DXA, BIA, CT or MRI, as Vandewoude et al. required. Second, because of the study design, survival bias prior to entry in the cohort should be considered. Last, the sample size of the study population was relatively small, especially for those with MSS.Several limitations need to be considered when interpreting the results of this study. First, although the diagnostic criteria of MSS remain unclear, Vandewoude and colleagues did offer an assessment tool for MSS based on their experienceIn a population of geriatric inpatients, subjects with MSS or malnutrition risk and sarcopenia are at increased risk of long-term all-cause mortality compared to subjects with either malnutrition/malnutrition risk or sarcopenia. Therefore, MSS may serve as an important prognostic factor in the management of hospitalized older patients. Further studies are warranted to address the association between MSS (with various diagnostic criteria) and other adverse health outcomes, such as disability and frailty, and heath costs in different study populations.Supplementary Tables


When using behavioral-observation methods for coding video footage, it is unknown how much time of an interaction needs to be coded to gain results that are representative for the behavior of interest. The current study examined this problem using the INTAKT, a standardized observational measure for assessing the quality of mother-child interactions. Results from coding only 10 min of each video  were compared with results from coding the remaining parts (averaging about 40 min) of the interaction. Inter-rater agreement for the short versions taken from the beginning or the middle, but not the end of the interactions indicated satisfactory observer accuracy. Coding results did not differ between short and long video sequences, when sequences were taken from the middle of the interactions. Importantly, characteristic differences between different interactive situations were equally well represented in the short and long video sequences. Therefore, our results show that coding only 10 min of an interaction is as reliable and valid as coding full-length videos, if those short sequences are taken from the middle of an interaction. Our findings support the idea that for every method, it is necessary to individually determine the window duration that is long enough to gain results that are reliable and valid. The behavioral observation of interactions between mothers and their children can be an important part of the psychological assessment process. Oftentimes, video recordings are used as helpful tools for observing interactions, but their coding is frequently more time-consuming than desirable in practice. Therefore, coding of thin slices  may prove beneficial to increase the usefulness of observational methods. However, even though it is common practice to use only a small portion of the video in order to minimize the necessary effort, there does not seem to be unequivocal empirical evidence that supports such an approach. Rather, studies that have examined this topic in more detail yielded often quite different conclusions.r = .39. They argued that other studies that did not use behavioral observation but had used different methods  to predict similar criterion variables found similar effect sizes. Moreover, comparing studies that used shorter or longer sequences (from less than 30 s to 5 min) showed that duration of behavioral observation did not have an impact on observed effects. However, they did not find or use any studies that directly compared results from coding longer segments with coding shorter segments of the same situation.A meta-analysis by Ambady and Rosenthal  suggestsMore recently, James et al.  focused In their own study, James et al.  comparedConsidering this conflicting evidence, it seems important to empirically test how much time needs to be coded, when using behavioral-observation methods. Therefore, when developing the behavioral-observation method INTAKT . Maternal age ranged from 24 to 50 years . All mothers gave informed, written consent for the videos to be used for research purposes.This study used data from 80 mother-child dyads who had participated in various studies concerning the coding system INTAKT. There were 46 girls and 34 boys in the sample. Their age ranged from 3.0 to 5.9 years  were excluded. Each video consisted of a structured situation in which mother and child could work with craft materials and an unstructured free-play situation. Mother and child were free to decide how much time they wished to spend on each task, in order to avoid frustration in the young children by taking away crafting materials before their work was finished. Therefore, videos differed in length. On average, working with the craft materials lasted for 20:40 min and the free-play situation lasted for 28:20 min (roughly a 2:3 ratio). In a few videos, one or the other situation lasted for only a short time. Therefore, it was necessary to determine a minimum length of each situation that still allowed for a meaningful shortening of the sequence (because shortening the videos was the purpose of the study). Those minimums were set at 10 min for the crafting situation and 14 min for the free-play situation . According to those criteria, another six videos had to be excluded.Third, after particularly short videos had been excluded in our second step, particularly long videos were excluded as well. This concerned eight videos for which the duration of the crafting and/or the free-play situation deviated extremely from the average. For each video, differences between the duration of each situation and the average duration were squared and summed up to determine which videos showed a particularly large deviation from the norm. According to this criterion, 10% of videos which differed the most from the average were excluded. Therefore, after this final selection 80 videos were included in the present study. These videos had an average length of 46:56 min (19:38 min of crafting and 27:18 min of free play).For video recording interactions between mothers and their children, crafting materials  were prepared on a table and a box containing various play materials  was placed aside. Mother and child were told, “Look, I have got a crafts project for you! Would you [instructor looks at child] like to turn this boring house [instructor points to a copy of a black-and-white drawing of a house] into a beautiful and colorful house? Your Mum can help you and you can use all the materials you can find on the table. The house is done as soon as [child’s name] says so. When you are done with the house there [instructor points to box with play materials] is something to play with, for you and your Mum.” They were allowed to take a break if desired. Following the recording of the interaction, each camera file was converted into WMV format with 24 frames per second.Sensitivity, Feedback, and Joint Attention. Each dimension is coded separately, thus making it necessary to watch the video at least three times. Sensitivity is rated on a 7-point Likert-typed scale, ranging from very low sensitivity (1) to very high sensitivity (7). Every other step of the rating scale is precisely verbally anchored, thus giving exact descriptions of corresponding maternal behaviors. Descriptions, for example, focus on whether the mother notices the child’s signals and reacts promptly and appropriately to them, whether she can adopt the child’s viewpoint, and whether her language is appropriate for the child’s developmental status. For coding, the video is stopped after two minutes, watched again if necessary, and then maternal behavior during this interval is rated according to the scale. This procedure is repeated every two minutes until the end of the video.Each video was coded with the behavioral coding system INTAKT , corrective feedback , negative feedback , and no feedback (mother gives no feedback to the child). Joint Attention is a classification system comprising six categories: active maintenance , verbal maintenance , passive maintenance , attention manipulation , attention switching , and no joint attention . For both classification systems, categories are mutually exclusive and exhaustive. Therefore, within each classification system one of the categories is coded for every moment of the video .Coding of all 80 videos was shared by six different coders, who coded 4, 5, 12, 16, 19, and 24 videos, respectively. Twenty-two (27.5%) of those videos were independently coded by a second coder to obtain estimates for inter-rater agreement. Coder 1 additionally coded two videos that had already been coded by Coder 2, and Coder 2 additionally coded two videos that had already been coded by Coder 1. Furthermore, a seventh coder coded 18 videos that had already been coded . Inter-rater agreement for maternal Feedback and Joint Attention were calculated with INTERACT. For every video, this was done for the whole video, for the shortened versions of the video (4 min crafting and 6 min free play), and for the respective rests of the video. Results from INTERACT were transferred into Microsoft Excel and SPSS, where all further calculations were accomplished.Means for maternal-sensitivity ratings were calculated using SPSS. Durations and frequencies of all categories of Sensitivity was examined using SPSS. Because Sensitivity is assessed on a rating scale and videos were coded by different coders, intra-class correlation coefficients  were calculated. Inter-rater agreement for Feedback and Joint Attention were examined using the Generalized Sequential Querier . Because Feedback and Joint Attention were coded with an event-sampling method, time-unit kappa with tolerance was used as an agreement measure. To this end, the stream of events is divided into equal units . For each time unit, it is observed whether the other coder decided for the same category within a specified time window of tolerance (plus/minus 3 s in our case). GSEQ then reports two kappa values for each calculation, one for each coder as the first one . In all videos that were used for analysis, the crafting situation was at least 10 min long and the free-play situation lasted at least 14 min see “ above. AAll analyses were done for three different time points. First, 4 min of the crafting situation and 6 min of the free-play situation were taken starting from one minute after crafting and one minute after free play started. Second, the length of the crafting situation was divided in half and a 4 min interval that started 2 min before and ended 2 min after that point was taken. Similarly, for the free-play situation, a 6 min interval that started 3 min before and ended 3 min after half of the free-play situation was taken. Third, 4 min of the crafting situation and 6 min of the free-play situation were taken from one minute before crafting and one minute before free play ended.To examine whether coding shorter segments is as reliable and valid as coding the full-length video, three analyses were conducted. First, inter-rater reliabilities were examined. To this end, observer-agreement indices for the shortened versions were compared with observer-agreement indices for the full-length videos. Second, to investigate whether results from the shortened versions are comparable with results from the long versions, results from the shortened version were compared with results from the respective rests of the videos. We consciously chose not to compare the sequences with the full-length videos to provide a conservative estimate . Third, for further validation we assessed typical differences between the crafting situation and the free-play situation in the full-length videos and examined if the same differences appeared in the shortened versions.Sensitivity was coded for every two minutes of a video. For analyses, those ratings can be averaged per video to yield a value that represents the mean level of maternal Sensitivity for a given interaction. Thus, intra-class correlations for maternal Sensitivity can be calculated either for the single ratings or for the averaged ratings per video. As can be seen in Table Maternal Feedback, time-unit kappas with tolerance showed no significant difference between full-length videos and a shortened sequence taken from the beginning of each situation. Kappas were significantly higher for a shortened sequence that was taken from the middle, and significantly lower for a shortened sequence that was taken from the end of each situation than for full-length videos.Regarding Joint Attention, codings of the shortened versions that had been taken from the beginning or the middle of each situation yielded significantly lower kappa values than codings of the full-length videos, whereas codings of a shortened sequence that had been taken from the end of each situation yielded significantly higher kappa values . If they gave feedback, it was more often positive or corrective than negative feedback (the latter only between 0.19% and 0.53% of the time) for all three time points.Regarding Joint Attention, some differences emerged between the shortened versions that were taken from the beginning of the two situations and the respective remaining parts of the videos . For Feedback, correlations exhibited medium to large values in the crafting situation (with the exception of negative feedback in the end slice) and small to large values in the free-play situation. Correlations for Joint Attention yielded predominantly medium-sized to large coefficients. Of note, two correlations could not be calculated, because attention switching did not occur in the thin slices taken from the beginning or middle of the crafting situation.To assess whether mother-child dyads retained their relative position when short segments instead of long sequences were used, correlations between shortened versions and the remaining parts of the videos were examined  show no significant differences between full-length videos or shortened versions. This finding is consistent for all three shortened versions from different time points and holds up for single ratings as well as for averaged ratings. Regarding Feedback, observer-agreement indices  remain stable for a shortened version from the beginning but are significantly higher for a shortened version from the middle of the two situations. They are significantly lower, if the shortened version is taken from the end of the crafting and free-play situation. Regarding Joint Attention, observer-agreement indices  of shortened versions from the beginning or the middle are significantly lower than those of the full-length videos, whilst observer-agreement indices of shortened versions from the end of the two situations are significantly higher than those of the full-length videos. Results from analyses of inter-rater agreement support the possibility of coding only segments from the beginning or the middle of the two situations. Those sequences exhibit observer-agreement indices that are either not significantly different from or even higher than those of the full-length videos (Sensitivity and Feedback) or significantly lower but still at a substantial level (Joint Attention), according to commonly used benchmarks . Future researchers may wish to investigate the influence of total video length on the observed behaviors.In conclusion, our findings show that thin slices are a viable option when coding behavioral-observation data. In accordance with the findings of James et al. , we reco


Currently, many imaging photoplethysmography (IPPG) researches have reported non-contact measurements of physiological parameters, such as heart rate (HR), respiratory rate (RR), etc. However, it is accepted that only HR measurement has been mature for applications, and other estimations are relatively incapable for reliable applications. Thus, it is worth keeping on persistent studies. Besides, there are some issues commonly involved in these approaches need to be explored further. For example, motion artifact attenuation, an intractable problem, which is being attempted to be resolved by sophisticated video tracking and detection algorithms.This paper proposed a blind source separation-based method that could synchronously measure RR and HR in non-contact way. A dual region of interest on facial video image was selected to yield 6-channels Red/Green/Blue signals. By applying Second-Order Blind Identification algorithm to those signals generated above, we obtained 6-channels outputs that contain blood volume pulse (BVP) and respiratory motion artifact. We defined this motion artifact as respiratory signal (RS). For the automatic selections of the RS and BVP among these outputs, we devised a kurtosis-based identification strategy, which guarantees the dynamic RR and HR monitoring available.The experimental results indicated that, the estimation by the proposed method has an impressive performance compared with the measurement of the commercial medical sensors.The proposed method achieved dynamic measurement of RR and HR, and the extension and revision of it may have the potentials for more physiological signs detection, such as heart rate variability, eye blinking, nose wrinkling, yawn, as well as other muscular movements. Thus, it might provide a promising approach for IPPG-based applications such as emotion computation and fatigue detection, etc.The online version of this article (doi:10.1186/s12938-016-0300-0) contains supplementary material, which is available to authorized users. Currently, IPPG technique has been developed for measurements of physiological parameters, such as HR, RR, etc., which uses an imaging devices to capture video of body surface that contains physiological information, and restructures the information by specific algorithms –5. It haPreviously, Takano and Ohta initially presented the feasibility of HR assessment based on IPPG system that used ambient light as the illumination . Also, u2, etc. T and T]. After BSS, the breathing rhythms were separated out from the R/G/B signals T and T], while the redundancies still exist on two groups of outputs.Figure Figure In the above circumstances, the 3-channels BSS based on single ROI is generally insufficient for separating the two physiological signals. The number of observations needs to be increased in order to improve the separation effect. Therefore, we took the two groups of R/G/B signals together as the observations, disposed them by using dual ROI-based BSS . The separation effects of new approach applied on the same two video segments were displayed in Figs. Nevertheless, there are still some residual noises remained in the source signals see Fig. d, 7d thaIn our work, we devised the kurtosis-based methods, assisted with some tactics, to achieve the automatic selections of RS and BVP signal.RS could be classified to typical sub-Gaussian signal on account of the feature of the waveform. It might be feasible to identify the RS by measuring sub-Gaussianity of the target signals from the perspective of kurtosis . For datIt can be seen in Fig. After obtaining RS, the five channels target signals remained (it was still six channels if there was no RS identified). In order to avoid interferences from the low frequency components, the HPF with cutoff at 0.8 Hz was used to remove them. Then, the power spectrum kurtosis of the remaining signals were used to detect the BVP components.The periodic components would display more distinguishable features on power spectrum kurtosis than power spectrum. In the remaining target signals removed low frequency components, the BVP signal has the strongest periodicity, i.e., the value of power spectrum kurtosis is maximum. Therefore, Power spectrum kurtosis method is feasible to identify the BVP component. Figure In Fig. There were eight subjects aged 22–31 years without medical history of heart and respiratory system selected for experiments. The experiments were carried out indoors with adequate and stable ambient light as illumination, according to the experimental paradigms under ideal condition and noise condition. Reference RR and reference HR were recorded by using HKH-11B breathing apparatus and HKG-07A pulse sensor  respectively. For the video recorded, based on sliding window analysis, we obtained estimated RR sequence and HR sequence by the proposed method, without pre-knowledge of the subjects’ actual HR and RR, then compared them with reference values from commercial medical sensors.The subjects need to maintain the condition: sit still without movements, ensuring that face and neck are located in the video region, keeping breaths standard and well-balanced as far as possible.Each subject needs to perform the experiment twice.The time of capturing video in each experiment is limited to 4–6 min, the subject needs to alternate gentle breath (45–60 s) and short breath (45–60 s) at least twice during this time.We devised the experimental paradigm of ideal condition to acquire data with high SNR for experimental verification. The details are as follows:Notes: If there are some abrupt movements or jitters happened, which bring serious corruption in commercial medical sensors, the experiment is allowed to be terminated with marking the recording as defective data, and then the subject could give up or try it again after a rest.There were eight groups of data captured in experiments. We discarded three defective ones, and then obtained a valid original experimental data set with a high SNR. Table For further illustration, we picked out an experimental data (Video 7) from Table The subjects maintain the relaxed state: Keep breathing natural and symmetry .Each subject needs to perform the experiment twice.The time of capturing video in each experiment is limited to 10–15 min, the subject needs to alternate gentle breath (45–60 s) and short breath (45–60 s) about 5–8 times during this time.Similarly, for acquisition of data with low SNR, the experimental paradigm of noise condition is developed as follows:Notes: The same as ideal condition mentioned above.Similar to the procedure above, we reorganized experimental data with discarding the defective one. Then, the result of the statistic was given in Table Figure Dual ROI-based BSS For the insufficient capability of separation in single ROI-based ICA/BSS  as much as possible, so we gave up LPF that is the removal of high-frequency noises.Furthermore, after BSS, it is found that quite a few residual noises emerged in ICs, which would interfere with automatic selections , to avoid interference from unknown periodic components.Besides, it is significant to be mentioned that the proposed method has the potentials for extracting more vital signs, such as blinking, wrinkling nose, yawn, as well as other muscular movements, which are all intricate local motion artifacts for facial video tracking and detection algorithms. Figure There are still some limitations existed in the proposed method. In our research, we have not employed facial video tracking and automatic region selection algorithms, which brought a shortcoming that the ROI can only be marked manually. Besides, the proposed method might be unable to handle the serious artifacts caused by heavy motions, which gave rise to serious drifts or deformation on R/G/B signals . We are taking efforts to cover these problems.Dynamic measurements of RR and HR from facial video have been proved in this proposed method. And it may have the potentials to be extended further to extract more physiological parameters, such as HRV, eye blinking, wrinkling nose, yawn, and other muscular movements, etc. The research has a good application prospect in the field of face-based physiological parameters assessments or emotion computation fields, especially for the subjects in the trial, the sniper or the people under special working environment. All the related issues could have further exploration in follow-up work.Additional file 1. The raw video picked from Table Additional file 2. Reference RR recorded by commercial medical sensors during recording video 7.Additional file 3. Reference HR recorded by commercial medical sensors during recording video 7.Additional file 4. The raw video picked from Table Additional file 5. Reference RR recorded by commercial medical sensors during recording video 2.Additional file 6. Reference HR recorded by commercial medical sensors during recording video 2.


Silica Company, Berkeley springs. Wv, USA）；色谱级正丁醇、乙腈、分析级1, 200万盐酸、胰蛋白酶（Pittsburgh, PA, USA）；Hank’s平衡盐溶液（Carlsbad, CA, USA）；磺酰罗丹明B，三氯乙酸（Irvine, CA, USA）；1, 1, 3, 3-四甲氧基丙烷、硫代巴比妥酸、2 -吡啶、2', 7'-二氯荧光素二脂（上海富众仪器有限公司）；L-丝氨酸、硼酸、二亚乙基三胺五乙酸（97%）（上海安谱科学仪器公司）；盐酸三氯三乙胺、丁基羟基甲苯、醋酸和磷酸二钠（北京华尔博科技公司）。QUANTA200型扫描电子显微镜（Philips Company, Holland），OXFORD型透视电子显微镜镜（Oxford, US），Phoenix+DIM一体化能谱及电子背散射衍射仪（EDAX Company, USA），Sartorius电子天平（Sartorius, Germany），高机能马弗炉FP310（YAMATO company, Japan），马尔文激光粒度分析仪（Malvern Instruments Ltd., USA），NOVA2000e型BET氮吸附比表面积仪（Quantachrome instruments Ltd/USA）。1.42培养基中孵化。取对数生长期的BEAS-2B细胞接种于96孔培养板中，5×104个细胞/孔。每组设3个复孔，待细胞贴壁48 h后加入刺激物悬浮液共同培养。共设3个处理组，宣威组（C烟煤中自然产出的二氧化硅）、50 nm工业生产的二氧化硅组和结晶型二氧化硅组（Min-U-Sil5），其基本特征见BEAS-2B细胞复苏后用含10%胎牛血清的Hams F-12（含L-谷氨酰胺）培养基中培养，培养基中加入100 U/mL的青霉素和100 μg/mL的链霉素，在37 ℃、5%CO1.5应用3--2, 5-二苯基溴化四唑（methyl thiazolyl tetrazolium, MTT）比色法检测经处理后的BEAS-2B细胞成活率变化。1.6细胞内活性氧化酶（reactive oxygen species, ROS）的测定：细胞内活性氧化酶通过2', 7'-二氯荧光素二乙酸酯方法测量（2', 7'-dichlorofluorescin diacetate, DCFH-DA），DCFH-DA进入细胞内和细胞内活性氧化酶结合形成荧光化合物二氯荧光素二乙酸酯。具体方法是：10 mM的DCFH-DA原液用Hank’s平衡盐溶液稀释500倍后作为工作液备用，待刺激物和BEAS-2B细胞共同培养24 h、48 h和72 h后用Hank’s平衡盐溶液洗涤2次，将洗涤后的细胞在2 mL的工作液中37 oC孵育30 min。荧光素通过酶标仪（Thermo Scientific Microplate Reader/USA）在485 nm和525 nm波长处测定。乳酸脱氢酶（lactate dehydrogenase, LDH）水平测定：乳酸脱氢酶水平根据商业试剂盒操作指南进行测量（Pointe Scientific, Inc, Lincoln Park, MI, USA）。1.7t检验。P < 0.05为差异有统计学意义。用SPSS 17.0统计软件包进行统计学处理。每个实验重复3次，每次实验设3个复孔，所得数值采用Mean±SD表示，组间比较采用两样本22.1C1烟煤燃烧后底灰中出现大量的游离微米级和纳米级二氧化硅颗粒物，呈纤维状或球形，赋存有钙、铁等元素（通过透射电子显微镜进行单颗粒形态分析，发现这些颗粒物表面不光滑，形态不规整，少数呈纤维状，单颗粒主要成分为硅元素，赋存有铝、铁和锰等元素（2.2P=0.036, 7）；当二氧化硅刺激浓度为50 μg/mL时，其各组的细胞成活率分别为76.6%、87.6%和90.2%，宣威组的细胞成活率下降与50 nm二氧化硅组和结晶型二氧化硅组相比均有明显差异（P=0.007, P=0.001）；当刺激浓度为100 μg/mL时，各组的细胞成活率分别为57.3%、72.5%和78.7%，宣威组的细胞成活率下降与50 nm二氧化硅组和结晶型二氧化硅组相比均有明显差异（P < 0.05）（-9。将0.1 g分离出的二氧化硅颗粒物溶于100 mL超纯水中，在超声波浴缸中震荡，配制成1 mg/mL的悬浮溶液为实验组（宣威组）。设相同浓度工业化生产的50 nm二氧化硅组、结晶型二氧化硅（Min-U-Sil 5）组和空白组为对照。待细胞贴壁48 h后，在培养基内分别加入配制的悬浮溶液，使刺激浓度分别达10 μg/mL、50 μg/mL和100 μg/mL。共同培养48 h后，应用MTT法检测细胞成活率变化情况。当刺激浓度为10 μg/mL时，与空白组相比，宣威组、50 nm二氧化硅组和结晶型二氧化硅组的细胞成活率分别为88.7%、89.1%和94.9%，宣威组的细胞成活率下降与结晶性二氧化硅组相比有差异（2.3P=0.027），在刺激72 h时有明显差异（P=0.001），与工业生产的50 nm二氧化硅组相比在各时间点均无明显差异。细胞培养基中的乳酸脱氢酶水平升高，提示存在细胞膜损伤，且上升越明显其细胞膜损伤越严重。宣威烟煤燃烧后底灰中提取的自然产出的二氧化硅颗粒物因形态不规则，表面不光滑，部分呈纤维状而更容易穿透细胞膜而造成细胞膜损伤。因此，在相同的刺激时间、刺激浓度和相近的粒径下（50 nm组），宣威组的乳酸脱氢酶升高最明显（待细胞贴壁48 h后，在培养基内分别加入配制好的悬浮溶液，使刺激浓度达100 μg/mL，待刺激培养基中的BEAS-2B细胞24 h、48 h和72 h后，测得各组BEAS-2B细胞的乳酸脱氢酶（LDH）水平逐渐升高，在相同时间点上，以宣威组细胞升高最为明显，与空白对照组相比分别升高了3.4%、9.2%和18.8%，结晶型二氧化硅组和50 nm二氧化硅组分别上升2.7%、3.8%、4.1%和5.2%、7.9%、10.3%。宣威组和结晶型二氧化硅组相比，在刺激48 h时，乳酸脱氢酶（LDH）升高有差异（P=0.047, 2）；当刺激时间为48 h时，宣威组的荧光强度增加了48.1%，与结晶型二氧化硅组增加的26.8%相比有明显差异（P < 0.001），与50 nm二氧化硅组增加的30.1%相比有差异（P=0.031, 2）；当刺激时间为72 h时，宣威组的荧光强度增加了70.5%，与50 nm二氧化硅组增加的48.9%和结晶型二氧化硅增加的41.2%相比均有明显差异（P < 0.001, P=0.001）（。细胞内活性氧化酶（reactive oxygen species, ROS）通过二氯荧光素（dichlorofluorescin, DCF）荧光强度来表示，DCF荧光强度随二氧化硅刺激时间的延长而增加。与空白组相比，当刺激时间为24 h时，宣威组的荧光强度增加了37.4%，与结晶型二氧化硅组增加的16.6%相比有差异（3。本研究的目的在于：①应用物理方法从宣威肺癌高发地区开采和使用的C1烟煤燃烧产物中分离出纳米二氧化硅，观察二氧化硅颗粒物的形态特征以及和其它元素之间的依存关系；②通过体外细胞实验，明确这种自然产出的纳米二氧化硅与工业生产的纳米二氧化硅和结晶型二氧化硅对正常人支气管上皮细胞的体外毒性有何不同。中国云南省宣威地区是我国非吸烟女性肺癌发病率最高的地区之一。研究表明，宣威地区肺癌高发与吸烟和工业污染等因素相关不明显，可能与当地开采和使用的C1烟煤中不同寻常的二氧化硅含量相关。这种假设主要是通过初步的煤地质化学评价，发现C1烟煤中相对富集的硅元素提出，但没有在统计学上定量，也没有观察二氧化硅颗粒物形态，然而，二氧化硅颗粒物形态在肺损伤方面是一个主要因素3.1。我们从C1烟煤底灰中分离出的二氧化硅颗粒物多数为纳米级，这些颗粒物可以随着清理灰槽和抛洒底灰过程中产生的飞灰进入呼吸道。我们在调查中发现，宣威地区农村女性主要承担了清理灰槽和抛洒底灰作为农田肥料等工作，长时间吸入这些颗粒物可能对健康造成损害。另外，这种天然产出的纳米二氧化硅颗粒物形态各异，多成球形，少数呈纤维状，表面多不光滑，在相同质量浓度下，自然产出的纳米二氧化硅颗粒物比工业生产的纳米二氧化硅具有更大的表面积。能谱分析发现赋存有铝、钙和铁等元素，目前没有发现人类摄入钙和铁元素可能导致癌症发生的报道，但是，如果人类过多的摄入铝元素可能与癌症发生相关。因此，从烟煤底灰中分离出的纳米二氧化硅颗粒物因其具有独特的粒径分布、巨大的比表面积和复杂的显微组分可能造成比工业生产的纳米二氧化硅和结晶型二氧化硅更严重的健康危害。我们应用物理方法从C1烟煤燃烧底灰中分离出的二氧化硅颗粒物，通过激光粒度分析后发现其粒经主要分布在30 nm到120 nm之间。颗粒物的粒径是重要的物理参数，它决定了颗粒物在人体呼吸系统中的沉积位置，粗颗粒物（2.5 μm-10 μm）主要附着在上呼吸道内，细颗粒（0.1 μm-2.5 μm）大部分沉积在下呼吸道中，而纳米颗粒物（< 0.1 μm）能深入末端支气管中，为颗粒物进一步迁移及毒害作用创造了条件3.2物理方法从煤燃烧底灰中分离纳米二氧化硅颗粒物较化学方法简单、易行、廉价和分离过程无污染等特点，最重要的是这种方法没有改变原有纳米二氧化硅颗粒物的形貌、粒径和显微组份的依存关系。。另外，这种天然产出的纳米二氧化硅还赋存有铝、钙和铁等元素。因此，在进行C1烟煤中的纳米二氧化硅颗粒物细胞毒性研究方面，既要考虑这些颗粒物的粒径和形貌特征，还要考虑其显微组分的依存关系。通过使用从C1烟煤底灰中分离出的纳米二氧化硅颗粒物刺激体外培养的BEAS-2B细胞，发现对细胞成活率和细胞活性氧（ROS）水平的影响较明显，当刺激时间超过24 h，与工业化生产的纳米二氧化硅和结晶型二氧化硅相比均有差异，说明这种天然产出的纳米二氧化硅颗粒物可能具有比结晶型二氧化硅和工业生产的纳米二氧化硅更高的细胞毒性。这种自然产出的纳米二氧化硅颗粒物粒径大小不等、表面不光滑、形态不规则，巨大的表面积可保持很高的生物学活性，能导致氧化应激甚至DNA损伤，这些影响被认为可能与癌症发生相关对于致癌物质的分离和鉴定，是一个非常复杂的工作，本研究的主要成果是用物理方法分离出了烟煤燃烧产物中的纳米二氧化硅颗粒物，保持了原有的理化特性，为进一步进行更深入的体外细胞实验和标准动物模型的建立提供了物质基础。


Under perfect and extremely noisy information, aggregate behavior does not differ between institutions. Under intermediate noise, punishment escalates in the decentralized peer-to-peer punishment regime which badly affects efficiency while sustaining cooperation for longer. Only decentralized punishment is often directed at cooperators (perverse punishment). We report several, sometimes subtle, differences in punishment behavior, and how contributions react.We run several experiments which allow us to compare  We introduce noise in the signals about individual contributions in order to test whether decentralized or centralized punishment is more robust to imperfect information. By abstracting from institutional factors, we return to the origins of formal punishment as a centralization of informal sanctioning regimes  and Centralized punishment (CEN). In the second we control for the accuracy of the signal about the contributions in the group. More specifically, we compare a perfect signal with three different levels of noise, indicated by the probability λ of an accurate signal with λ = 1, λ = 0.75, or λ = 0.50. Thus, the signal is either always accurate, or only 75 or 50% of the time. In the following we identify a treatment condition by the combination of institution and λ. For example DEC/1 is the treatment with decentralized punishment and a perfect signal.We use a standard finitely repeated linear public-good game with a voluntary contribution mechanism. Participants interact in groups of five over 30 periods in a partner design, where every period has two stages, a contribution and a punishment stage. In our set of experiments we have two treatments. In the first we compare two different punishment C-participants (i ∈ {1…4}) and one Authority (A), and every period consists of two stages, a contribution and a punishment stage. In the first stage, the contribution stage, the four C-participants can contribute to the public good; the remaining participant, the Authority (A), benefits from the public good but cannot contribute herself. After the contribution stage, all five participants first receive a common signal about the contributions, where the quality of the signal depends on λ. Then, in treatments with centralized punishment (CEN) the authority decides over punishment. In treatments with decentralized punishment (DEC) this is done by the C-participants and the Authority is merely passive. More specifically, she cannot influence punishment but is, nevertheless, affected by the contribution and punishment decisions of the four C-participants. In the following we describe each stage in more detailThere are five participants in every group, four eg = 20 tokens. They then simultaneously and independently determine their contribution to the public good gi with gi ∈ G = {0, 2, 4, …, 20}In the first stage of each of the 30 rounds, each of the four C-participants receives an endowment of i in the first stage is given byIn line with most experiments on decentralized punishment in public good games, we chose a marginal per capita return of 0.4. Hence, the monetary payoff of player A, despite not contributing, equally benefits from the public good:The authority i and authority A receives the same signal sk about the contributions gk of participant k with k ≠ i. The signal itself is independently determined for every contribution in the group. With probability λ the signal is correct and sk = gk, with probability 1−p the signal is incorrect. An incorrect signal is taken from the uniform distribution of all possible contributions excluding the actual one. More specifically,In the second stage, every C-participant G \ {gk}. As all participants receive the same signals about contributions of others, information conditions for punishers are constant across treatments. Note, however, that every C-participant always knows for sure how much he contributed himself but they do not know which signal others receive about their own contributionwhere λ is the accuracy of the signal and C-participants were identified by numbers 1–4 which were assigned randomly anew every period and made identification of group members difficult. We contrast a perfect signal (λ = 1) with three levels of noise: λ = 0.5 and λ = 0.75. For example, for λ = 0.5, a contribution of 6 would lead to the signal “6” with probability 0.5, and to any other signal, each with probability 0.05 (0.5/10). Thus, despite considerable noise, a signal is still informative.i receives a punishment endowment of ep = 10 punishment points, and authority A receives an additional endowment of In both punishment institutions, each of the four C-participants DEC the four C-participants can distribute punishment points amongst each other, where each point costs them one unit and also reduces the authority's income by onei to j with pij, the total payoff of participant i is:In A is:and the payoff of participant A in treatment DEC as a passive participant in order to hold considerations, such as the externalities from punishment . Furthermore, we kept the maximal amount of punishment points that could be assigned to one participant constant across treatments by limiting A to distributing at most 30 points to one individual. Thus, in CEN, final payoffs are determined as follows:In andpij we denote with pAj the number of punishment points assigned to j by A. This payoff structure keeps everything constant across institutions, including externalities, efficiency concerns, commitment, and punishment power, such that we exclusively explore the effect of centralization per se.where equivalently to At the end of a round, every participant is informed about his income from the public good, the amount of punishment received, and his final total payoff. Thus, any inaccurate perception about one's own income, resulting from noisy signals about group contributions, are resolved at the end of every round.A in CEN, as well as for the regular participants in DEC. Thus, play at the contribution stage remains unaffected and zero contribution by all remains the unique equilibrium in dominant strategies. As zero contribution and no punishment guarantees the minmax payoff, the equilibrium is not affected by the finite number of repetitions, and there should be no cooperation and no punishment throughout the 30 periods. This rationale applies to all treatments, such that there should be no differences between different punishment institutions and different levels of noise.To find the set of equilibria under the assumptions of selfishness, common knowledge of rationality and sequential rationality, we first look at the stage game. As punishment is costly, it is strictly dominated, both for We use a 2 × 3 factorial design between subjects, i.e., every subject participates in only one of our six treatment combinations. Subjects interact repeatedly over 30 periods in a partners design, i.e., groups are kept constant. All rounds are paid.The experiments were run in the experimental laboratory of the University of Bonn (EconLab) and was programmed and conducted with the software z-Tree  and participants earned on average €14.28 (including a show up fee of €2.50), about USD 18.80, which is more than the usual hourly wage for student jobs.For 100 experimental We first report aggregate results with respect to institutions and noise before we analyze punishment behavior, the resulting incentives, and intertemporal reactions in more detail.We compare contributions, overall punishment, and efficiency between institutions and noise levels. The graphs in Figure p-values of two-sided Wilcoxon rank-sum tests comparing the distributions of matching group averages between DEC and CEN within each noise condition (see rows)Table Profits of C-participants, results are very similar and qualitatively identical for all levels of λ.For a perfect signal, i.e., whenever λ = 1 there are neither significant differences in contributions nor in punishment or efficiency. Similarly, for considerable noise of λ = 0.50 Table If signals are perfect (λ = 1) or highly distorted (λ = 0.5) aggregate outcomes do not differ significantly between institutions. For λ = 0.75 there is significantly more punishment and less efficiency in DEC early in the experiment, and in later periods contributions remain significantly higher in DEC/0.75 than in CEN/0.75.Result 1. Most contributions in CEN/1 and DEC/1 are close to the ceiling of 20. In Section p-values of Wilcoxon rank sum tests comparing outcomes between different levels of noise within each institution. Again we distinguish between the first and second half of the experiment (see columns).Comparisons between different levels of noise within each institution mirror our previous results. Table contributions are always significantly smaller the more noisy the signal. In DEC, however, there are no significant differences between λ = 1 and λ = 0.75 in the first half of the experiment, while otherwise comparative statics are as in CEN. Aggregate Punishment, on the other hand remains unaffected by noise in CEN in the first half, but not in the second, where it is smaller in CEN/1 than in CEN/0.75 and CEN/0.50. In DEC only λ = 0.75 stands out. While punishment never differs between DEC/1 and DEC/0.50, there is significantly more punishment in DEC/0.75 than in in either DEC/1 or DEC/0.50 in the first half and significantly more than in DEC/1 also in the second half. In both institutions, efficiency is similarly affected by noise in the first half of the experiment. It is significantly higher for λ = 1 than for λ = 0.75 or λ = 0.50. While there are no significant differences between CEN/0.75 and CEN/0.50 throughout the experiment, efficiency is significantly higher for DEC/0.75 than for DEC/0.50 in the second half, a consequence of the higher contributions towards the end of DEC/0.75. In summary we find an interaction effect between institution and noise:In CEN Irrespective of institution, noise has a negative effect on contributions in the long run. The effect of noise on punishment and efficiency, however, is non-monotonic and differs between institutions. Under centralized punishment CEN/1 stands out with significantly less punishment and higher efficiency in the long run, while there are hardly any differences between CEN/0.75 and CEN/0.50. Under decentralized punishment, DEC/0.75 stands out with more punishment and less efficiency especially in early rounds.Result 2. DFree is a dummy variable indicating a signal of no contribution. Variables DaboveGroup and DbelowGroup are dummy variables indicating that, according to the signal, the receiver of punishment has contributed more than the group average and less, respectively. In CEN we calculate the average group contribution as the average signal. In DEC we take the average over one's own contribution and the signals about the contributions of the other three. Similarly, variables Dmore and Dless in treatment DEC are dummy variables indicating that, according to the signal, the  receiver of punishment contributed more than the one who decides whether to punish and less, respectively. The definitions of Dmore, Dless, DaboveGroup, and DbelowGroup all exclude the case of no difference (avoiding perfect collinearity)We turn to regression analysis to identify how the decision to punish is correlated to signals about contributions. The columns in Table All regressions are maximum likelihood Poisson estimations which besides the above mentioned fixed effects have a random intercept effect per matching group, and in DEC also per participant (independent of group effect). Estimations also include fixed effects for periods (following period 2). We use Poisson estimations as this best controls for the skewed distribution of integer punishment points.DFreerider). In all treatments someone gets punished more when the signal about his contribution is below the group average (DbelowGroup), an effect which is significant in all treatments except CEN/0.75 and CEN/0.50. Similarly, participants who contribute less than the punisher (Dless) in DEC are punished significantly more.While in DEC patterns of punishment decisions are similar for all levels of λ, in CEN punishment becomes fairly undirected with increasing noise. In all treatment combinations, punishment decreases with increasing Signal about the contribution. Only in DEC/1 and CEN/0.50 this is not significant. Of all treatment combinations, only DEC/1 has significant additional punishment of free rider behavior , > (p < 0.05), or ≫ (p < 0.01) between the two columns.We furthermore tested whether there are different patterns in punishment behavior between the first 10, 15, last 15, and last 20 periods, especially in DEC/0.75. While there are some minor differences in the size of reactions, the overall patterns are similar. We furthermore tested whether differences in coefficients between, for example DEC/1 and CEN/1 are significantWith only a few exceptions, punishment behavior differs significantly between institutions.Result 4. Dbelow with Dabove or Dless with Dmore confirm that these differences are significant in treatments with λ = 1 or λ = 0.75 , but not for λ = 0.50 (p ≥ 0.2073)Finally, which effect is stronger, punishment of negative or positive deviators?Except for treatment combinations with λ = 0.50, punishment of negative deviators is significantly stronger than that of positive deviators.Result 5. Dmore and Dless are now undetermined in both institutions, which puts the two back on equal footing. Furthermore, for DEC it is conceivable that due to the many repetitions, behavior of “sophisticated” punishers may add a non-random component to how distributed punishment is aggregated in the groupTo adequately compare institutions we must compare how punishment is being experienced. In treatment DEC recipients of punishment can not identify individual punishers and therefore whether the punisher contributed more or less. Thus, contrary to distributed punishment, DaboveGroup and DbelowGroup.Table DaboveGroup) in DEC/1 only. Contrary to our previous results, neither in DEC/0.75 nor in DEC/0.50 do participants experience significant perverse punishment. Despite the noise, in all treatments except for DEC/0.50, negative deviators receive significantly more punishment. Finally, there is no experience of perverse punishment in any of the CEN treatments.For perfect signals our estimations by and large confirm our previous resultsIn DEC/1 negative and positive deviators experience punishment.Result 6. • In DEC/0.75 only negative deviators experience punishment.In DEC/0.50 received punishment is independent of how one's contribution relates to those in the group.In all CEN treatments negative deviators experience significantly more punishment while positive deviators do not.Again we compared coefficients between institutions. Significant results are indicated by symbols such as > between columns in Table With only a few exceptions, experienced punishment differs significantly between institutions.Result 7. above and below which measure the absolute distance of the contribution to the group average (rather than merely indicator variables DaboveGroup and DbelowGroup). We report detailed results in the online supplement. The barplots in Figure In addition to the regressions reported in Table t-contributiont−1) on outcomes in the previous round - one regression each for every level of noise. More specifically, the first estimation (first two columns) includes data from λ = 1 treatments only, and we estimated the average change in contributions for DEC and CEN for six possible outcomes in the previous round. The outcomes in the previous round are identified by (i) whether the participant contributed more than the group average (above), the same amount , or less (below), and (ii) whether she was punished or not. Every regressor is a dummy variable indicating the relevant combination and all calculations are based on actual contributions rather than signals. The maximum likelihood estimations correct for random effects on participants and groupTable In both institutions and for all levels of noise, those who in the previous round contributed less, on average significantly increase their contribution, irrespective of whether they were punished or not. In all treatments except CEN/0.5, punishment significantly enhances this reaction. Those who contributed more and were not punished decrease their contributions in all treatment combinations. In DEC, punishment of such cooperative participants has no significant effect on this reaction. In CEN, however, such perverse punishment dampens the reduction, significantly so in CEN/1 and CEN/0.75. Comparing immediate reactions between institutions, treatments CEN/1 and CEN/0.75 in most cases show significantly more cooperative changes in contributions than the equivalent DEC treatments. Note, however, that there are other reactions that span over more periods.above or below average or equal contribution). Including the amount of the received punishment into the regression increases the shift effect (or “intercept”) throughout, and with only one exception , the reaction to the amount of punishment is negative. For those contributing below average it is significantly negative in all treatments except for CEN/0.75, and for above average contributors it is significantly negative in all except for DEC/0.50 and CEN/0.50.In Table For negative deviators we find:Result 8. Negative deviators increase their contribution in the next period in both institutions.- This effect is stronger if they were punished and punishment was not too high.- A large amount of punishment has a negative effect on contributions.- These immediate reactions are stronger in CEN than in DEC.- For positive deviators we find:Positive deviators decrease their contribution in the next period.- In DEC punishment has no effect.- In CEN punishment tends to reduce this adjustment.- However, a lot of punishment has a negative effect on contributions in DEC and CEN.- We furthermore tested whether reactions to punishment differ in early rounds. By and large results are similar and do not differ significantly from the one we reported. The most noteworthy (though insignificant) difference is that in CEN/1 in early rounds, the positive reaction of cooperative types to punishment is much smaller and only later becomes significant.Δb (DEC/1) the following differences in coefficients from Table Δb = (below & punished)-(below & not pun.). We compared these differences between institutions by testing for example H0 : Δb (DEC/1) = Δb (CEN/1) against H1 : Δb (DEC/1) > Δb (CEN/1). The result of these tests are indicated by appropriate signs between the columns of Table Finally, to fully assess the question whether punishment has a stronger effect on contribution behavior in DEC or CEN, we compare the change in contribution due to punishment on top of the change in contribution without punishmentFor λ = 1 and λ = 0.75, the effectiveness of punishment on contributions only differs significantly between institutions for positive deviators. For λ = 0.50, it differs significantly for negative deviators.Result 9. per se under perfect and imperfect information affects behavior and outcomes in voluntary contribution public good games. Both, institution and noisiness of signals are imposed exogenously, and efficiency and cost of punishment are held constant across institutions.We test whether centralization of punishment We find significant differences in how contribution behavior is being punished. While centralized authorities do not punish those who contribute more than average, we observe such perverse and furthermore anti-social punishment in the decentralized regime. While in treatments with noise, this perverse punishment is being averaged out, it remains highly relevant if signals are perfect. Otherwise we observe socially reasonable punishment of those who contribute less than the group average in all treatments. Similarly, distributed and received punishment decrease with signal and actual contribution, respectively.Reactions to punishment by negative deviators are similar between institutions. Even if they are not punished they increase their contribution but punishment enhances this positive adjustment in both institutions by about the same. Positive deviators on the other hand, reduce their contributions in both institutions as long as they were not punished. Interestingly, perverse punishment by their peers has no effect on this reaction in DEC. Thus, while perverse punishment directly induces inefficiencies, it has hardly any consequences in the long run. In CEN on the other hand, where this type of punishment was not as pronounced, it has significant positive effects on contributions.Despite these differences in behavior, we find that the institution has no effect, neither on contributions, aggregate punishment nor overall efficiency, both if information is perfect (λ = 1) and if there is considerable noise (λ = 0.5). Under intermediate noise (λ = 0.75), however, punishment differs significantly but with only limited consequences for contributions and overall efficiency. More specifically, in the peer to peer punishment institution, punishment escalates during the first third of the experiment keeping contributions higher than under centralized punishment. However, due to the excessive punishment, efficiency is not significantly different.Anti-social and perverse punishment are frequently observed in public good experiments with peer to peer punishment. In a detailed study of such behavior (Herrmann et al., What remains difficult to explain is the escalation of punishment in DEC/0.75 which is absent in the equivalent treatment with centralized punishment CEN/0.75. Could it be explained by ruthless satisfaction of punishment sentiments and expression of anger (Dickinson and Masclet, per se that is beneficial but other institutional differences. This issue carries over to studies with endogenous institutions, where centralized punishment prevails if it comes with additional advantages (Traulsen et al., ceteris paribus comparison under perfect information (Grechenig et al., Centralized punishment institutions have been praised in the economic, legal, and political science literature, with recent support from experimental research. However, it is not centralization All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.We gratefully acknowledge financial support from the Max Planck Institute for Research on Collective Goods, Bonn, Germany.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer DN and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.