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Many complex physical systems exhibit a rich variety of discrete behavioural modes. Often, the system complexity limits the applicability of standard modelling tools. Hence, understanding the underlying physics of different behaviours and distinguishing between them is challenging. Although traditional machine learning techniques could predict and classify behaviour well, typically they do not provide any meaningful insight into the underlying physics of the system. In this paper we present a novel method for extracting physically meaningful clusters of discrete behaviour from limited experimental observations. This method obtains a set of physically plausible functions that both facilitate behavioural clustering and aid in system understanding. We demonstrate the approach on the V-shaped falling paper system, a new falling paper type system that exhibits four distinct behavioural modes depending on a few morphological parameters. Using just 49 experimental observations, the method discovered a set of candidate functions that distinguish behaviours with an error of 2.04%, while also aiding insight into the physical phenomena driving each behaviour. © 2019 Howison et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

The Panama Papers comprise one of the most recent influential leaks containing detailed information on intermediary companies (such as law firms), offshore entities and company officers, and serve as a valuable source of insight into the operations of (approximately) 214,000 shell companies incorporated in tax havens around the globe over the past half century. Entities and relations in the papers can be used to construct a network that permits, in principle, a systematic and scientific study at scale using techniques developed in the computational social science and network science communities. In this paper, we propose such a study by attempting to quantify and profile the importance of entities. In particular, our research explores whether intermediaries are significantly more influential than offshore entities, and whether different centrality measures lead to varying, or even incompatible, conclusions. Some findings yield conclusions that resemble Simpson’s paradox. We also explore the role that jurisdictions play in determining entity importance.

In our planned study, we shall empirically study the assessment of cited papers within the framework of the anchoring-and-adjustment heuristic. We are interested in the question whether citation decisions are (mainly) driven by the quality of cited references. The design of our study is oriented towards the study by Teplitskiy, Duede [10]. We shall undertake a survey of corresponding authors with an available email address in the Web of Science database. The authors are asked to assess the quality of papers that they cited in previous papers. Some authors will be assigned to three treatment groups that receive further information alongside the cited paper: citation information, information on the publishing journal (journal impact factor), or a numerical access code to enter the survey. The control group will not receive any further numerical information. In the statistical analyses, we estimate how (strongly) the quality assessments of the cited papers are adjusted by the respondents to the anchor value (citation, journal, or access code). Thus, we are interested in whether possible adjustments in the assessments can not only be produced by quality-related information (citation or journal), but also by numbers that are not related to quality, i.e. the access code. The results of the study may have important implications for quality assessments of papers by researchers and the role of numbers, citations, and journal metrics in assessment processes.

Objective To survey the knowledge, attitude, and practices of Vietnamese pharmacists regarding the COVID-19 pandemic. Method This cross-sectional, paper-based study was conducted from June to August 2020. A validated questionnaire (Cronbach’s alpha = 0.84) was used to interview 1,023 pharmacists in nine provinces of Vietnam. Analysis of covariance was employed to identify factors associated with the knowledge of pharmacists. The best model was chosen by using the Bayesian Model Averaging method in R software version 4.0.4. Results The mean knowledge score was 12.02 ± 1.64 (range: 6–15), which indicated that 93.4% of pharmacists had good knowledge of COVID-19. There was no difference in the average score between males and females (p > 0.05). The multivariate linear regression model revealed that the knowledge was significantly associated with pharmacists’ age, education level, and residence (p < 0.001). About attitude and practices, pharmacists daily sought and updated information on the COVID-19 pandemic through mass media and the internet (social network and online newspapers). Nearly 48% of them conceded that they communicated with customers when at least one person did not wear a face mask at the time of the COVID-19 outbreak. At medicine outlets, many measures were applied to protect pharmacists and customers, such as equipping pharmacists with face masks and hand sanitizers (95.0%), using glass shields (83.0%), and maintaining at least one-meter distance between two people (85.2%). Conclusion The pharmacists’ knowledge of COVID-19 transmission, symptoms, and prevention was good. Many useful measures against the spread of this perilous virus were applied in medicine outlets. However, pharmacists should restrict forgetting to wear face masks in communication with medicine purchasers. The government and health agencies should have practical remedies to reduce the significant differences in the COVID-19 knowledge of pharmacists among provinces and education-level groups.

The cost of specialized scientific equipment can be high and with limited funding resources, researchers and students are often unable to access or purchase the ideal equipment for their projects. In the fields of materials science and mechanical engineering, fundamental equipment such as tensile testing devices can cost tens to hundreds of thousands of dollars. While a research lab often has access to a large-scale testing machine suitable for conventional samples, loading devices for meso- and micro-scale samples for in-situ testing with the myriad of microscopy tools are often hard to source and cost prohibitive. Open-source software has allowed for great strides in the reduction of costs associated with software development and open-source hardware and additive manufacturing have the potential to similarly reduce the costs of scientific equipment and increase the accessibility of scientific research. To investigate the feasibility of open-source hardware, a micro-tensile tester was designed with a freely accessible computer-aided design package and manufactured with a desktop 3D-printer and off-the-shelf components. To our knowledge this is one of the first demonstrations of a tensile tester with additively manufactured components for scientific research. The capabilities of the tensile tester were demonstrated by investigating the mechanical properties of Graphene Oxide (GO) paper and thin films. A 3D printed tensile tester was successfully used in conjunction with an atomic force microscope to provide one of the first quantitative measurements of GO thin film buckling under compression. The tensile tester was also used in conjunction with an atomic force microscope to observe the change in surface topology of a GO paper in response to increasing tensile strain. No significant change in surface topology was observed in contrast to prior hypotheses from the literature. Based on this result obtained with the new open source tensile stage we propose an alternative hypothesis we term 'superlamellae consolidation' to explain the initial deformation of GO paper. The additively manufactured tensile tester tested represents cost savings of >99% compared to commercial solutions in its class and offers simple customization. However, continued development is needed for the tensile tester presented here to approach the technical specifications achievable with commercial solutions.

Before organizing mixed-mode data collection for the self-administered questionnaire of the Belgian Health Interview Survey, measurement effects between the paper-and-pencil and the web-based questionnaire were evaluated. A two-period cross-over study was organized with a sample of 149 employees of two Belgian research institutes (age range 22-62 years, 72% female). Measurement agreement was assessed for a diverse range of health indicators related to general health, mental and psychosocial health, health behaviors and prevention with kappa coefficients and intraclass correlation (ICC). The quality of the data collected by both modes was evaluated by quantifying the missing, 'don't know' and inconsistent values and data entry mistakes. Good to very good agreement was found for all categorical indicators with kappa coefficients superior to 0.60, except for two mental and psychosocial health indicators namely the presence of a sleeping disorder and of a depressive disorder (kappa≥0.50). For the continuous indicators high to acceptable agreement was observed with ICC superior to 0.70. Inconsistent answers and data-entry mistakes were only occurring in the paper-and-pencil mode. There were no less missing values in the web-based mode compared to the paper-and-pencil mode. The study supports the idea that web-based modes provide, in general, equal responses to paper-and-pencil modes. However, health indicators based upon factual and objective items tend to have higher measurement agreement than indicators requiring an assessment of personal subjective feelings. A web-based mode greatly facilitates the data-entry process and guides the completing of a questionnaire. However, item non-response was not positively affected. ispartof: PLOS ONE vol:13 issue:5 ispartof: location:United States status: published

Background A paper-based, multiplexed, microfluidic assay has been developed to visually measure alanine aminotransferase (ALT) in a fingerstick sample, generating rapid, semi-quantitative results. Prior studies indicated a need for improved accuracy; the device was subsequently optimized using an FDA-approved automated platform (Abaxis Piccolo Xpress) as a comparator. Here, we evaluated the performance of the optimized paper test for measurement of ALT in fingerstick blood and serum, as compared to Abaxis and Roche/Hitachi platforms. To evaluate feasibility of remote results interpretation, we also compared reading cell phone camera images of completed tests to reading the device in real time. Methods 96 ambulatory patients with varied baseline ALT concentration underwent fingerstick testing using the paper device; cell phone images of completed devices were taken and texted to a blinded off-site reader. Venipuncture serum was obtained from 93/96 participants for routine clinical testing (Roche/Hitachi); subsequently, 88/93 serum samples were captured and applied to paper and Abaxis platforms. Paper test and reference standard results were compared by Bland-Altman analysis. Findings For serum, there was excellent agreement between paper test and Abaxis results, with negligible bias (+4.5 U/L). Abaxis results were systematically 8.6% lower than Roche/Hitachi results. ALT values in fingerstick samples tested on paper were systematically lower than values in paired serum tested on paper (bias -23.6 U/L) or Abaxis (bias -18.4 U/L); a correction factor was developed for the paper device to match fingerstick blood to serum. Visual reads of cell phone images closely matched reads made in real time (bias +5.5 U/L). Conclusions The paper ALT test is highly accurate for serum testing, matching the reference method against which it was optimized better than the reference methods matched each other. A systematic difference exists between ALT values in fingerstick and paired serum samples, and can be addressed by application of a correction factor to fingerstick values. Remote reading of this device is feasible.

We propose to use Twitter data as social-spatial sensors. This study deals with the question whether research papers on certain diseases are perceived by people in regions (worldwide) that are especially concerned by these diseases. Since (some) Twitter data contain location information, it is possible to spatially map the activity of Twitter users referring to certain papers (e.g., dealing with tuberculosis). The resulting maps reveal whether heavy activity on Twitter is correlated with large numbers of people having certain diseases. In this study, we focus on tuberculosis, human immunodeficiency virus (HIV), and malaria, since the World Health Organization ranks these diseases as the top three causes of death worldwide by a single infectious agent. The results of the social-spatial Twitter maps (and additionally performed regression models) reveal the usefulness of the proposed sensor approach. One receives an impression of how research papers on the diseases have been perceived by people in regions that are especially concerned by these diseases. Our study demonstrates a promising approach for using Twitter data for research evaluation purposes beyond simple counting of tweets.

Type 1 diabetes (T1D) is increasing in incidence and predictable with measurement of serum islet autoantibodies (iAb) years prior to clinical disease onset. Identifying iAb positive individuals reduces diabetic ketoacidosis and identifies individuals for T1D prevention trials. However, large scale screening for iAb remains challenging as assays have varying sensitivities and specificities, insulin autoantibodies remain difficult to measure and venipuncture is generally required to obtain serum. We developed an approach to reliably measure all four major iAb, including insulin autoantibodies, from dried blood spots (DBS) on filter-paper. By spiking iAb positive serum into iAb negative whole blood in a dose titration, we optimized the conditions for autoantibody elution from filter paper as measured by fluid phase radioimmunoassays. After assessing stability of measuring iAb from DBS over time, we then screened iAb from DBS and the corresponding serum in new-onset T1D (n = 52), and controls (n = 72) which included first-degree relatives of T1D patients. iAb measured from eluted DBS in new-onset T1D strongly correlated with serum measurements (R2 = 0.96 for mIAA, GADA = 0.94, IA-2A = 0.85, ZnT8A = 0.82, p

Background Paper mulberry (Broussonetia papyrifera (L.) L'Hér. ex Vent) is a dioecious tree native to East Asia and mainland Southeast-Asia, introduced prehistorically to Polynesia as a source of bark fiber by Austronesian-speaking voyagers. In Oceania, trees are coppiced and harvested for production of bark-cloth, so flowering is generally unknown. A survey of botanical records of paper mulberry revealed a distributional disjunction: the tree is apparently absent in Borneo and the Philippines. A subsequent study of chloroplast haplotypes linked paper mulberry of Remote Oceania directly to a population in southern Taiwan, distinct from known populations in mainland Southeast-Asia. Methodology We describe the optimization and use of a DNA marker designed to identify sex in paper mulberry. We used this marker to determine the sex distribution in selected localities across Asia, Near and Remote Oceania. We also characterized all samples using the ribosomal internal transcribed spacer sequence (ITS) in order to relate results to a previous survey of ITS diversity. Results In Near and Remote Oceania, contemporary paper mulberry plants are all female with the exception of Hawaii, where plants of both sexes are found. In its natural range in Asia, male and female plants are found, as expected. Male plants in Hawaii display an East Asian ITS genotype, consistent with modern introduction, while females in Remote Oceania share a distinctive variant. Conclusions Most paper mulberry plants now present in the Pacific appear to be descended from female clones introduced prehistorically. In Hawaii, the presence of male and female plants is thought to reflect a dual origin, one a prehistoric female introduction and the other a modern male introduction by Japanese/Chinese immigrants. If only female clones were dispersed from a source-region in Taiwan, this may explain the absence of botanical records and breeding populations in the Philippines and Borneo, and Remote Oceania.

In order to reduce the ecotoxicity of paper mill, four different enzymatic pretreatment strategies were investigated in comparison to conventional chemical based processes. In strategy I, xylanase-aided pretreatment of pulp was carried out, and in strategy II, xylanase and laccase-mediator systems were used sequentially. Moreover, to compare the efficiency of Bacillus stearothermophilus xylanase and Ceriporiopsis subvermispora laccase in the reduction of ecotoxicity and pollution, parallel strategies (III and IV) were implemented using commercial enzymes. Conventional C(D)E(OP)D(1)D(2) (C(D), Cl(2) with ClO2; EOP, H2O2 extraction; D1 and D2, ClO2) and X/XLC(D)E(OP)D(1)D(2) (X, xylanase; L, laccase) sequences were employed with non-enzymatic and enzymatic strategies, respectively. Acute toxicity was determined by the extent of inhibition of bioluminescence of Vibrio fischeri with different dilutions of the effluent. Two-fold increase was observed in EC50 values for strategy I compared to the control process. On the other hand, sequential application of commercial enzymes resulted in higher acute toxicity compared to lab enzymes. In comparison to the control process, strategy II was the most efficient and successfully reduced 60.1 and 25.8% of biological oxygen demand (BOD) and color of effluents, respectively. We report for the first time the comparative analysis of the ecotoxicity of industrial effluents.

Background Adiponectin is an adipocyte-derived hormone that acts as a marker of insulin sensitivity. Bloodspot sampling by fingerstick onto filter paper may increase the feasibility of large-scale studies of the determinants of insulin sensitivity. We first describe the validation of an enzyme-linked immunoassay (ELISA) for quantifying adiponectin from dried blood spots and then demonstrate its application in a large trial (PROBIT). Methods We quantified adiponectin from 3-mm diameter discs (≈3 µL of blood) punched from dried blood spots obtained from: i) whole blood standards (validation); and ii) PROBIT trial samples (application) in which paediatricians collected blood spots from 13,879 children aged 11.5 years from 31 sites across Belarus. We examined the distribution of bloodspot adiponectin by demographic and anthropometric factors, fasting insulin and glucose. Results In the validation study, mean intra-assay coefficients of variation (n = 162) were 15%, 13% and 10% for ‘low’ (6.78 µg/ml), ‘medium’ (18.18 µg/ml) and 'high’ (33.13 µg/ml) internal quality control (IQC) samples, respectively; the respective inter-assay values (n = 40) were 23%, 21% and 14%. The correlation coefficient between 50 paired whole bloodspot versus plasma samples, collected simultaneously, was 0.87 (95% CI: 0.78 to 0.93). Recovery of known quantities of adiponectin (between 4.5 to 36 µg/ml) was 100.3–133%. Bloodspot adiponectin was stable for at least 30 months at −80°C. In PROBIT, we successfully quantified fasting adiponectin from dried blood spots in 13,329 of 13,879 (96%) children. Mean adiponectin (standard deviation) concentrations were 17.34 µg/ml (7.54) in boys and 18.41 µg/ml (7.92) in girls and were inversely associated with body mass index, fat mass, triceps and subscapular skin-fold thickness, waist circumference, height and fasting glucose. Conclusions Bloodspot ELISA is suitable for measuring adiponectin in very small volumes of blood collected on filter paper and can be applied to large-scale studies.

Research paper recommenders emerged over the last decade to ease finding publications relating to researchers' area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collaborative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommendations. The novelty of our proposed approach is that it provides personalized recommendations regardless of the research field and regardless of the user's expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list.

BackgroundThe objectives of the study were to develop web-based Spanish and Catalan versions of the KIDSCREEN, and to compare scores and psychometric properties with the paper version.MethodsInternet and paper Spanish and Catalan versions of the KIDSCREEN-52 were included in a cross-sectional study in school-age children. Web-based and paper Spanish or Catalan versions of the KIDSCREEN-52 were administered to students aged 8 to 18 years from primary and secondary schools in Palafolls (Barcelona, Spain, n = 923). All students completed both web-based and paper versions during school time with an interval of at least 2 hours between administrations. The order of administration was randomized. The KIDSCREEN-52, the Strengths and Difficulties Questionnaire (SDQ), and sociodemographic variables were collected. Missing values, floor and ceiling effects, and internal consistency were compared between both versions, as well as mean score differences, level of agreement, and known groups and construct validity.ResultsParticipation rate was 77% (n = 715). Web-based and paper versions showed low percentage of missing values and similar high ceiling effect (range 0 to 44%). Mean score differences showed an effect size (ES) lower than 0.2 in all dimensions. Internal consistency ranged from 0.7 to 0.88, and degree of agreement was excellent (Intraclass correlation coefficient [ICC] range 0.75 to 0.87). Expected differences were seen by sex, age, socioeconomic status and mental health status.ConclusionsThe web-based KIDSCREEN-52 showed similar scale score and reliability and validity than the paper version. It will incorporate the child population in the assessment of quality of life providing a more attractive format.

Paper mulberry (Broussonetia papyrifera (L.) L'Hér. ex Vent) is a dioecious tree native to East Asia and mainland Southeast-Asia, introduced prehistorically to Polynesia as a source of bark fiber by Austronesian-speaking voyagers. In Oceania, trees are coppiced and harvested for production of bark-cloth, so flowering is generally unknown. A survey of botanical records of paper mulberry revealed a distributional disjunction: the tree is apparently absent in Borneo and the Philippines. A subsequent study of chloroplast haplotypes linked paper mulberry of Remote Oceania directly to a population in southern Taiwan, distinct from known populations in mainland Southeast-Asia.We describe the optimization and use of a DNA marker designed to identify sex in paper mulberry. We used this marker to determine the sex distribution in selected localities across Asia, Near and Remote Oceania. We also characterized all samples using the ribosomal internal transcribed spacer sequence (ITS) in order to relate results to a previous survey of ITS diversity.In Near and Remote Oceania, contemporary paper mulberry plants are all female with the exception of Hawaii, where plants of both sexes are found. In its natural range in Asia, male and female plants are found, as expected. Male plants in Hawaii display an East Asian ITS genotype, consistent with modern introduction, while females in Remote Oceania share a distinctive variant.Most paper mulberry plants now present in the Pacific appear to be descended from female clones introduced prehistorically. In Hawaii, the presence of male and female plants is thought to reflect a dual origin, one a prehistoric female introduction and the other a modern male introduction by Japanese/Chinese immigrants. If only female clones were dispersed from a source-region in Taiwan, this may explain the absence of botanical records and breeding populations in the Philippines and Borneo, and Remote Oceania.

BackgroundAlthough researchers have worked in collaboration since the origins of modern science and the publication of the first scientific journals in the eighteenth century, this phenomenon has acquired exceptional importance in the last several decades. Since the mid-twentieth century, new knowledge has been generated from within an ever-growing network of investigators, working cooperatively in research groups across countries and institutions. Cooperation is a crucial determinant of academic success.ObjectiveThe aim of the present paper is to analyze the evolution of scientific collaboration at the micro level, with regard to the scientific production generated on psoriasis research.MethodsA bibliographic search in the Medline database containing the MeSH terms "psoriasis" or "psoriatic arthritis" was carried out. The search results were limited to articles, reviews and letters. After identifying the co-authorships of documents on psoriasis indexed in the Medline database (1942-2013), various bibliometric indicators were obtained, including the average number of authors per document and degree of multi-authorship over time. In addition, we performed a network analysis to study the evolution of certain features of the co-authorship network as a whole: average degree, size of the largest component, clustering coefficient, density and average distance. We also analyzed the evolution of the giant component to characterize the changing research patterns in the field, and we calculated social network indicators for the nodes, namely betweenness and closeness.ResultsThe main active research clusters in the area were identified, along with their authors of reference. Our analysis of 28,670 documents sheds light on different aspects related to the evolution of scientific collaboration in the field, including the progressive increase in the mean number of co-authors (which stood at 5.17 in the 2004-2013 decade), and the rise in multi-authored papers signed by many different authors (in the same decade, 25.77% of the documents had between 6 and 9 co-authors, and 10.28% had 10 or more). With regard to the network indicators, the average degree gradually increased up to 10.97 in the study period. The percentage of authors pertaining to the largest component also rose to 73.02% of the authors. The clustering coefficient, on the other hand, remained stable throughout the entire 70-year period, with values hovering around 0.9. Finally, the average distance peaked in the decades 1974-1983 (8.29) and 1984-2003 (8.12) then fell over the next two decades, down to 5.25 in 2004-2013. The construction of the co-authorship network (threshold of collaboration ≥ 10 co-authored works) revealed a giant component of 161 researchers, containing 6 highly cohesive sub-components.ConclusionsOur study reveals the existence of a growing research community in which collaboration is increasingly important. We can highlight an essential feature associated with scientific collaboration: multi-authored papers, with growing numbers of collaborators contributing to them, are becoming more and more common, therefore the formation of research groups of increasing depth (specialization) and breadth (multidisciplinarity) is now a cornerstone of research success.

Background In the context of a randomized controlled trial (RCT) on HIV testing in the emergency department (ED) setting, we evaluated preferences for survey modality and data quality arising from each modality. Methods Enrolled participants were offered the choice of answering a survey via audio computer assisted self-interview (ACASI) or pen and paper self-administered questionnaire (SAQ). We evaluated factors influencing choice of survey modality. We defined unusable data for a particular survey domain as answering fewer than 75% of the questions in the domain. We then compared ACASI and SAQ with respect to unusable data for domains that address sensitive topics. Results Of 758 enrolled ED patients, 218 (29%) chose ACASI, 343 chose SAQ (45%) and 197 (26%) opted not to complete either. Results of the log-binomial regression indicated that older (RR = 1.08 per decade) and less educated participants (RR = 1.25) were more likely to choose SAQ over ACASI. ACASI yielded substantially less unusable data than SAQ. Conclusions In the ED setting there may be a tradeoff between increased participation with SAQ versus better data quality with ACASI. Future studies of novel approaches to maximize the use of ACASI in the ED setting are needed.

Scholars traditionally receive career credit for a paper based on where in the author list they appear, but position in an author list often carries little information about what the contribution of each researcher was. “Contributorship” refers to a movement to formally document the nature of each researcher’s contribution to a project. We discuss the emerging CRediT standard for documenting contributions and describe a web-based app and R package called tenzing that is designed to facilitate its use. tenzing can make it easier for researchers on a project to plan and record their planned contributions and to document those contributions in a journal article.

In newborn screening, samples suspected for congenital adrenal hyperplasia (CAH), a potentially lethal inborn error of steroid biosynthesis, need to be confirmed using liquid chromatography–tandem mass spectrometry. Daily quality controls (QCs) for the 2nd-tier CAH assay are not commercially available and are therefore generally prepared within the laboratory. For the first time, we aimed to compare five different QC preparation approaches used in routine diagnostics for CAH on the concentrations of cortisol, 21-deoxycortisol, 11-deoxycortisol, 4-androstenedione and 17-hydroxyprogesterone in dried blood spots. The techniques from Prep1 to Prep5 were tested at two analyte concentrations by spiking aliquots of a steroid-depleted blood, derived from washed erythrocyte suspension and steroid-depleted serum. The preparation processes differed in the sequence of the preparation steps and whether freeze-thaw cycles were used to facilitate blood homogeneity. The five types of dried blood spot QCs were assayed and quantitated in duplicate on five different days using a single calibration row per day. Inter-assay variations less than 15% and concentrations within ±15% of the nominal values were considered acceptable. Results obtained by means of the four dried blood spot QC preparation techniques (Prep1, Prep2, Prep4 and Prep5) were statistically similar and remained within the ±15% ranges in terms of both reproducibility and nominal values. However, concentration results for Prep3 (spiking prior to three freeze-thaw cycles) were significantly lower than the nominal values in this setting, with differences exceeding the ±15% range in many cases despite acceptable inter-assay variations. These findings have implications for the in-house preparation of QC samples in laboratory developed tests for CAH, including 2nd-tier assays in newborn screening.

Among the challenges of sustainable management of meat production, the key issue is to improve the energy efficiency of production processes, which will consequently affect the reduction of greenhouse gas emissions. Such effects are achieved by combining various chilling systems with electrical stimulation that determines the quality of meat at the slaughter stage. The novelties of the research undertaken included determining the impact of various variants of meat production (chilling method: slow, fast, accelerated + HVES/NES) on changes in the basic (industrial) quality indicators (pH and temperature) of beef produced from Polish Holstein-Friesian breed cattle, and then indicating the optimal variant for energy-efficient (sustainable) beef production. The HVES and the fast chilling method yielded positive economic (meat weight loss), technological (high quality, hot-boning), energetic (lower electricity consumption), and organizational effects (reduced chilling and storage surfaces and expenditures for staff wages) compared to the slow and accelerated methods. Reaching the desired final temperature with an increased amount of chilled meat enables obtaining a few-fold decrease in the specific energy consumption and a higher energy efficiency of the process. This allows recommending the above actions to be undertaken by entrepreneurs in the pursuit of sustainable meat production.

The use of personal protective equipment (PPE) has been considered the most effective way to avoid the contamination of healthcare workers by different microorganisms, including SARS-CoV-2. A spray disinfection technology (chamber) was developed, and its efficacy in instant decontamination of previously contaminated surfaces was evaluated in two exposure times. Seven test microorganisms were prepared and inoculated on the surface of seven types of PPE (respirator mask, face shield, shoe, glove, cap, safety glasses and lab coat). The tests were performed on previously contaminated PPE using a manikin with a motion device for exposure to the chamber with biocidal agent (sodium hypochlorite) for 10 and 30s. In 96.93% of the experimental conditions analyzed, the percentage reduction was >99% (the number of viable cells found on the surface ranged from 4.3x106 to E. faecalis collected from the glove showed the lowest percentages reduction, with 86.000 and 86.500% for exposure times of 10 and 30 s, respectively. The log10 reduction values varied between 0.85 log10 (E. faecalis at 30 s in glove surface) and 9.69 log10 (E. coli at 10 and 30 s in lab coat surface). In general, E. coli, S. aureus, C. freundii, P. mirabilis, C. albicans and C. parapsilosis showed susceptibility to the biocidal agent under the tested conditions, with >99% reduction after 10 and 30s, while E. faecalis and P. aeruginosa showed a lower susceptibility. The 30s exposure time was more effective for the inactivation of the tested microorganisms. The results show that the spray disinfection technology has the potential for instant decontamination of PPE, which can contribute to an additional barrier for infection control of healthcare workers in the hospital environment.

Since the innovation of our new half-piece elastometric respirator, this type of filtering facepiece respirator (FFR) has been used widely in Thailand. Decontamination methods including ultraviolet C (UVC) germicidal irradiation and 70% alcohol have been implemented to decontaminate these respirators. We then examined the inactivation potential of different decontamination processes on porcine epidemic diarrhea virus (PEDV) and numerous bacterial strains, most of which were skin-derived. To enable rigorous integrity of the masks after repeated decontamination processes, fit tests by the Bitrex test, tensile strength and elongation at break were also evaluated. Our results showed that UVC irradiation at a dose of 3 J/cm2 can eradicate bacteria after 60 min and viruses after 10 min. No fungi were found on the mask surface before decontamination. The good fit test results, tensile strength and elongation at break were still maintained after multiple cycles of decontamination. No evidence of physical degradation was found by gross visual inspection. Alcohol (70%) is also an easy and effective way to eradicate microorganisms on respirators. As the current pandemic is expected to continue for months to years, the need to supply adequate reserves of personnel protective equipment (PPE) and develop effective PPE reprocessing methods is crucial. Our studies demonstrated that the novel silicone mask can be safely reprocessed and decontaminated for many cycles by UVC irradiation, which will help ameliorate the shortage of important protective devices in the COVID-19 pandemic era.

The safety of highly aggregated tourist crowds is a challenging and important issue. This paper not only provided a comprehensive analysis of the accidents of highly aggregated tourist crowds but also determined the occurrence mechanism and coping paths. Based on the analysis of multiple cases, we found that the variable status of highly aggregated tourist crowds was the result of the interaction of three main elements: multisource pressure, state mutations and management responses. A series of factors interact and result in accidents, and the lack of a management response or a low-quality management response is the root cause of such accidents. A high-quality management response is a basic safety precaution for highly aggregated tourist crowds. Therefore, forming a virtuous circle of multisource pressure, state mutations and management responses is an effective path for coping with accidents.

The response to the COVID-19 epidemic is generating severe shortages of personal protective equipment around the world. In particular, the supply of N95 respirator masks has become severely depleted, with supplies having to be rationed and health care workers having to use masks for prolonged periods in many countries. We sought to test the ability of 7 different decontamination methods: autoclave treatment, ethylene oxide gassing (ETO), low temperature hydrogen peroxide gas plasma (LT-HPGP) treatment, vaporous hydrogen peroxide (VHP) exposure, peracetic acid dry fogging (PAF), ultraviolet C irradiation (UVCI) and moist heat (MH) treatment to decontaminate a variety of different N95 masks following experimental contamination with SARS-CoV-2 or vesicular stomatitis virus as a surrogate. In addition, we sought to determine whether masks would tolerate repeated cycles of decontamination while maintaining structural and functional integrity. All methods except for UVCI were effective in total elimination of viable virus from treated masks. We found that all respirator masks tolerated at least one cycle of all treatment modalities without structural or functional deterioration as assessed by fit testing; filtration efficiency testing results were mostly similar except that a single cycle of LT-HPGP was associated with failures in 3 of 6 masks assessed. VHP, PAF, UVCI, and MH were associated with preserved mask integrity to a minimum of 10 cycles by both fit and filtration testing. A similar result was shown with ethylene oxide gassing to the maximum 3 cycles tested. Pleated, layered non-woven fabric N95 masks retained integrity in fit testing for at least 10 cycles of autoclaving but the molded N95 masks failed after 1 cycle; filtration testing however was intact to 5 cycles for all masks. The successful application of autoclaving for layered, pleated masks may be of particular use to institutions globally due to the virtually universal accessibility of autoclaves in health care settings. Given the ability to modify widely available heating cabinets on hospital wards in well-resourced settings, the application of moist heat may allow local processing of N95 masks.

When clothes are worn and washed, they emit fibres into the ecosystem via discharges of sewage that have been linked to the global dispersion of clothing fibres. Facilities that treat sewage divert some fibres from sewage effluent to sludge, but no current methods of filtration eliminate their environmental release. While filters for washing-machines are sold to consumers with the argument they will reduce the emissions of fibres from clothes to the environment, there is insufficient scientific peer-reviewed evidence assessing their ability to retain fibres from washed clothes and reduce environmental contamination. To improve our understanding and develop more realistic methods to assess the efficiency of filters, we washed replicate cotton and polyester garments in replicate domestic front-loaded washing-machines with and without replicate filters (micro- and milli-meter-sized pores), and then quantified the masses of the fibres retained by the filters and those released in the effluent. Here we show micrometer-sized filters significantly reduced the mass of cotton by 67% (F-2,F-6= 11.69, P

Coal gangue has the shortcomings of low calorific value and refractory burnout, while polyvinyl chloride has the advantages of a long combustion process and high calorific value. In order to make up for these shortcomings of coal gangue, the possibility of a treatment method based on co-combustion of coal gangue with polyvinyl chloride, which can be centrally recovered from municipal solid waste, is proposed. In order to analyze the combustion effect of a mixture of these two substances, experimental samples were prepared by mixing these two substances in three different ratios, and they were tested by thermogravimetric analysis. The experimental results were compared, analyzed and evaluated. The effects of the proportion of polyvinyl chloride in the mixture on the temperature parameters, activation energy, and interaction during co-combustion were analyzed. In order to analyze the interaction during co-combustion of the two, a coupling analysis method for mixed combustion is presented, and the effectiveness of this method is verified by comparing with the correlation analysis results of co-combustion. The results show that co-combustion can mitigate the ignition difficulty and burnout of coal gangue. When the proportion of polyvinyl chloride in the mixture was increased from 20% to 80%, the maximum weightlessness rate of the first stage rapidly increased from 4.5%/min to 15.6%/min; however, that of the second stage slowly increased from 3.7%/min to 4.2%/min. A 20% proportion of polyvinyl chloride showed the most significant promotion of co-combustion, with a maximum coupling coefficient of 0.00318, which was 1.11 and 1.35 times greater than that of 50% and 80% proportions, respectively. Co-combustion can reduce the activation energy of coal gangue during the initial and end stages. Therefore, co-combustion is helpful to improve the problems of low calorific value and refractory burnout of coal gangue.

The sustainable recovery of resources from wastewater streams can provide many social and environmental benefits. A common strategy to recover valuable resources from wastewater is to harness the products of fermentation by complex microbial communities. In these fermentation bioreactors high microbial community diversity within the inoculum source is commonly assumed as sufficient for the selection of a functional microbial community. However, variability of the product profile obtained from these bioreactors is a persistent challenge in this field. In an attempt to address this variability, the impact of inoculum on the microbial community structure and function within the bioreactor was evaluated using controlled laboratory experiments. In the course of this work, sequential batch reactors were inoculated with three complex microbial inocula and the chemical and microbial compositions were monitored by HPLC and 16S rRNA amplicon analysis, respectively. Microbial community dynamics and chemical profiles were found to be distinct to initial inoculate and highly reproducible. Additionally we found that the generation of a complex volatile fatty acid profile was not specific to the diversity of the initial microbial inoculum. Our results suggest that the composition of the original inoculum predictably contributes to bioreactor community structure and function., United States. National Institutes of Health (P30-ES002109)

The use of Polymerase Chain Reaction (PCR) assays for pathogen detection in travelers' diarrhea (TD) field studies is limited by the on-site processing and storage requirements for fecal specimens. The objectives of this investigation were to i) characterize the pathogen distribution in deployed military personnel with TD using the TaqMan® Array Card PCR (TAC) on frozen stool and diarrheal smears on Whatman FTA Elute cards (FTA cards), and to ii) compare TAC detection of enteropathogen targets using smeared FTA cards and frozen stool, using TAC on frozen stool as the 'reference standard'. Stool samples, obtained from active duty personnel with acute TD enrolled in a field trial, were smeared onto FTA cards and stored at room temperature. A corresponding aliquot of stool was frozen in a cryovial. FTA cards and frozen stool samples were tested at a central lab, using a customized TAC for detection of TD pathogens. 187 paired frozen stool samples and smeared FTA cards were stored for a median of 712 days (IQR 396-750) before testing. Overall detection rates were 78.6% for frozen stool and 73.2% for FTA cards. Diarrheagenic Escherichia coli were the most common bacteria identified. Using the TAC results on frozen stool as the reference, the overall sensitivity and specificity of TAC on FTA cards was 72.9% and 98.0% respectively. TAC on FTA cards demonstrated a decrease in sensitivity with increasing frozen stool quantification cycle (Cq) (90.0% in FTA cards with a corresponding frozen stool Cq < 30, and 72.9% in samples with a corresponding frozen stool Cq < 35). Our findings support the use and further development of FTA cards in combination with a quantitative PCR assay for enteropathogen detection in TD field studies.

Background Paper pulp wastewater resulting from alkaline extraction of wheat straw, known as black liquor, is very difficult to be treated and causes serious environmental problems due to its high pH value and chemical oxygen demand (COD) pollution load. Lignin, semicellulose and cellulose are the main contributors to the high COD values in black liquor. Very few microorganisms can survive in such harsh environments of the alkaline wheat straw black liquor. A naturally developed microbial community was found accidentally in a black liquor storing pool in a paper pulp mill of China. The community was effective in pH decreasing, color and COD removing from the high alkaline and high COD black liquor. Findings Thirty-eight strains of bacteria were isolated from the black liquor storing pool, and were grouped as eleven operational taxonomy units (OTUs) using random amplified polymorphic DNA-PCR profiles (RAPD). Eleven representative strains of each OTU, which were identified as genera of Halomonas and Bacillus, were used to construct a consortium to treat black liquor with a high pH value of 11.0 and very high COD pollution load of 142,600 mg l−1. After treatment by the constructed consortium, about 35.4% of color and 39,000 mg l−1 (27.3%) CODcr were removed and the pH decreased to 7.8. 16S rRNA gene polymerase chain reaction denaturant gradient gel electrophoresis (PCR-DGGE) and gas chromatography/mass spectrometry (GC/MS) analysis suggested a two-stage treatment mechanism to elucidate the interspecies collaboration: Halomonas isolates were important in the first stage to produce organic acids that contributed to the pH decline, while Bacillus isolates were involved in the degradation of lignin derivatives in the second stage under lower pH conditions. Conclusions/Significance Tolerance to the high alkaline environment and good controllability of the simple consortium suggested that the constructed consortium has good potential for black liquor treatment. Facilitating the treatment process by the constructed consortium would provide a promising opportunity to reduce the pollution, as well as to save forest resources and add value to a waste product.

We show in this study that the combination of a swirl flow reactor and an antimicrobial agent (in this case copper alginate beads) is a promising technique for the remediation of contaminated water in waste streams recalcitrant to UV-C treatment. This is demonstrated by comparing the viability of both common and UV-C resistant organisms in operating conditions where UV-C proves ineffective - notably high levels of solids and compounds which deflect UV-C. The swirl flow reactor is easy to construct from commonly available plumbing parts and may prove a versatile and powerful tool in waste water treatment in developing countries.

The study of the stability of concentrated oil-in-water emulsions is imperative to provide a scientific approach for an important problem in the beverage industry, contributing to abolish the empiricism still present nowadays. The use of these emulsions would directly imply a reduction of transportation costs between production and the sales points, where dilution takes place. The goal of this research was to evaluate the influence of the main components of a lemon emulsion on its stability, aiming to maximize the concentration of oil in the beverage and to correlate its physicochemical characteristics to product stability, allowing an increase of shelf life of the final product. For this purpose, analyses of surface and interface tension, electrokinetic potential, particle size and rheological properties of the emulsions were conducted. A 2(4-1) fractional factorial design was performed with the following variables: lemon oil/water ratio (30% to 50%), starch and Arabic gum concentrations (0% to 30%) and dioctyl sodium sulfosuccinate (0 mg/L to 100 mg/L), including an evaluation of the responses at the central conditions of each variable. Sequentially, a full design was prepared to evaluate the two most influential variables obtained in the first plan, in which concentration of starch and gum ranged from 0% to 20%, while concentration of lemon oil/water ratio was fixed at 50%, without dioctyl sodium sulfosuccinate. Concentrated emulsions with stability superior to 15 days were obtained with either starch or Arabic gum and 50% lemon oil. The most stable formulations presented viscosity over 100 cP and ratio between the surface tension of the emulsion and the mucilage of over 1. These two answers were selected, since they better represent the behavior of emulsions in terms of stability and could be used as tools for an initial selection of the most promising formulations.

Ifosfamide blood concentrations are necessary to monitor its therapeutic response, avoiding any adverse effect. We developed and validated an analytical method by UPLC-MS/MS to quantify ifosfamide in dried blood spots (DBS). Blood samples were collected on Whatman 903® filter paper cards. Five 3 mm disks were punched out from each dried blood spot. Acetonitrile and ethyl acetate were used for drug extraction. Chromatographic separation was carried out in an Acquity UPLC equipment with a BEH-C18 column, 2.1 x 100 mm, 1.7 μm (Waters®). The mobile phase consisted in 5 mM ammonium formate and methanol:acetonitrile (40:48:12 v/v/v) at 0.2 mL/min. LC-MS/MS detection was done by ESI+ and multiple reaction mode monitoring, ionic transitions were m/z1+ 260.99 > 91.63 for ifosfamide and 261.00 > 139.90 for cyclophosphamide (internal standard). This method was linear within a 100–10000 ng/mL range and it was accurate, precise and selective. Ifosfamide samples in DBS were stable for up to 52 days at -80°C. The procedure was tested in 14 patients, ages 1 month to 17 years (9 males and 5 females), with embryonic tumours treated with ifosfamide, alone or combined, at a public tertiary referral hospital. Ifosfamide blood levels ranged from 11.1 to 39.7 μmol/L at 12 hours after the last infusion, while 24-hour levels ranged from 0.7–19.7 μmol/L. The median at 12 hours was 19.5 μmol/L (Q25 14.4–Q75 29.0) and 3.8 μmol/L (Q25 1.5–Q75 9.9) at 24 hours, p

The fermentation of cocoa pulp is one of the few remaining large-scale spontaneous microbial processes in today's food industry. The microbiota involved in cocoa pulp fermentations is complex and variable, which leads to inconsistent production efficiency and cocoa quality. Despite intensive research in the field, a detailed and comprehensive analysis of the microbiota is still lacking, especially for the expanding Asian production region. Here, we report a large-scale, comprehensive analysis of four spontaneous Malaysian cocoa pulp fermentations across two time points in the harvest season and two fermentation methods. Our results show that the cocoa microbiota consists of a "core" and a "variable" part. The bacterial populations show a remarkable consistency, with only two dominant species, Lactobacillus fermentum and Acetobacter pasteurianus. The fungal diversity is much larger, with four dominant species occurring in all fermentations ("core" yeasts), and a large number of yeasts that only occur in lower numbers and specific fermentations ("variable" yeasts). Despite this diversity, a clear pattern emerges, with early dominance of apiculate yeasts and late dominance of Saccharomyces cerevisiae. Our results provide new insights into the microbial diversity in Malaysian cocoa pulp fermentations and pave the way for the selection of starter cultures to increase efficiency and consistency. ispartof: PLOS ONE vol:8 issue:12 ispartof: location:United States status: published

To prevent transmission in Ebola Virus Disease (EVD) outbreaks, it is recommended to disinfect living things (hands and people) with 0.05% chlorine solution and non-living things (surfaces, personal protective equipment, dead bodies) with 0.5% chlorine solution. In the current West African EVD outbreak, these solutions (manufactured from calcium hypochlorite (HTH), sodium dichloroisocyanurate (NaDCC), and sodium hypochlorite (NaOCl)) have been widely used in both Ebola Treatment Unit and community settings. To ensure solution quality, testing is necessary, however test method appropriateness for these Ebola-relevant concentrations has not previously been evaluated. We identified fourteen commercially-available methods to test Ebola-relevant chlorine solution concentrations, including two titration methods, four DPD dilution methods, and six test strips. We assessed these methods by: 1) determining accuracy and precision by measuring in quintuplicate five different 0.05% and 0.5% chlorine solutions manufactured from NaDCC, HTH, and NaOCl; 2) conducting volunteer testing to assess ease-of-use; and, 3) determining costs. Accuracy was greatest in titration methods (reference-12.4% error compared to reference method), then DPD dilution methods (2.4-19% error), then test strips (5.2-48% error); precision followed this same trend. Two methods had an accuracy of

The challenges which the large scale microalgal industry is facing are associated with the high cost of key operations such as harvesting, nutrient supply and oil extraction. The high-energy input for harvesting makes current commercial microalgal biodiesel production economically unfeasible and can account for up to 50% of the total cost of biofuel production. Co-cultivation of fungal and microalgal cells is getting increasing attention because of high efficiency of bio-flocculation of microalgal cells with no requirement for added chemicals and low energy inputs. Moreover, some fungal and microalgal strains are well known for their exceptional ability to purify wastewater, generating biomass that represents a renewable and sustainable feedstock for biofuel production. We have screened the flocculation efficiency of the filamentous fungus A. fumigatus against 11 microalgae representing freshwater, marine, small (5 µm), large (over 300 µm), heterotrophic, photoautotrophic, motile and non-motile strains. Some of the strains are commercially used for biofuel production. Lipid production and composition were analysed in fungal-algal pellets grown on media containing alternative carbon, nitrogen and phosphorus sources contained in wheat straw and swine wastewater, respectively. Co-cultivation of algae and A. fumigatus cells showed additive and synergistic effects on biomass production, lipid yield and wastewater bioremediation efficiency. Analysis of fungal-algal pellet's fatty acids composition suggested that it can be tailored and optimised through co-cultivating different algae and fungi without the need for genetic modification.

It is generally accepted as a fact in the biogas technology that protein-rich biomass substrates should be avoided due to inevitable process inhibition. Substrate compositions with a low C/N ratio are considered difficult to handle and may lead to process failure, though protein-rich industrial waste products have outstanding biogas generation potential. This common belief has been challenged by using protein-rich substrates, i.e. casein and precipitated pig blood protein in laboratory scale continuously stirred mesophilic fed-batch biogas fermenters. Both substrates proved suitable for sustained biogas production (0.447 L CH4/g protein oDM, i.e. organic total solids) in high yield without any additives, following a period of adaptation of the microbial community. The apparent key limiting factors in the anaerobic degradation of these proteinaceous materials were the accumulation of ammonia and hydrogen sulfide. Changes in time in the composition of the microbiological community were determined by next-generation sequencing-based metagenomic analyses. Characteristic rearrangements of the biogas-producing community upon protein feeding and specific differences due to the individual protein substrates were recognized. The results clearly demonstrate that sustained biogas production is readily achievable, provided the system is well-characterized, understood and controlled. Biogas yields (0.45 L CH4/g oDM) significantly exceeding those of the commonly used agricultural substrates (0.25-0.28 L CH4/g oDM) were routinely obtained. The results amply reveal that these high-energy-content waste products can be converted to biogas, a renewable energy carrier with flexible uses that can replace fossil natural gas in its applications. Process control, with appropriate acclimation of the microbial community to the unusual substrate, is necessary. Metagenomic analysis of the microbial community by next-generation sequencing allows a precise determination of the alterations in the community composition in the course of the process.

Aims To evaluate the relative efficiencies of five Internet-based digital and three paper-based scientific surveys and to estimate the costs for different-sized cohorts.

Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in high segmentation accuracy. Although there are proposed machine learning and deep learning algorithms for plant segmentation, predictions rely on the specific features being present in the training set. The need for a multi-featured dataset and analytics for cosegmentation becomes critical to better understand and predict plants’ responses to the environment. High-throughput phenotyping produces an abundance of data that can be leveraged to improve segmentation accuracy and plant phenotyping. This paper introduces four datasets consisting of two plant species, Buckwheat and Sunflower, each split into control and drought conditions. Each dataset has three modalities (Fluorescence, Infrared, and Visible) with 7 to 14 temporal images that are collected in a high-throughput facility at the University of Nebraska-Lincoln. The four datasets (which will be collected under the CosegPP data repository in this paper) are evaluated using three cosegmentation algorithms: Markov random fields-based, Clustering-based, and Deep learning-based cosegmentation, and one commonly used segmentation approach in plant phenotyping. The integration of CosegPP with advanced cosegmentation methods will be the latest benchmark in comparing segmentation accuracy and finding areas of improvement for cosegmentation methodology.

Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important influence on the reliability of human behavior. A review of current human reliability techniques confirms that there is a lack of quantitative analysis of human errors in high-temperature molten metal operating environments. In this paper, a model was proposed to support the human reliability analysis of high-temperature molten metal operation in the metallurgy industry based on cognitive reliability and error analysis method (CREAM), fuzzy logic theory, and Bayesian network (BN). The comprehensive rules of common performance conditions in conventional CREAM approach were provided to evaluate various conditions for high-temperature molten metal operation in the metallurgy industry. This study adopted fuzzy CREAM to consider the uncertainties and used the BN to determine the control mode and calculate human error probability (HEP). The HEP for workers involved in high-temperature melting in steelmaking production process was calculated in a case with 13 operators being engaged in different high-temperature molten metal operations. The human error probability of two operators with different control modes was compared with the calculation result of basic CREAM, and the result showed that the method proposed in this paper is validated. This paper quantified point values of human error probability in high-temperature molten metal operation for the first time, which can be used as input in the risk evaluation of metallurgical industry.

The COVID-19 pandemic has been particularly deadly for residents of nursing homes and other long-term care facilities. This paper analyzes COVID-19 deaths at nursing homes during the first wave of the pandemic in the United States during the spring and early summer 2020. By combining data on facility-level COVID-19 deaths during this period with data on the neighborhoods where nursing home staff reside for a sample of eighteen states, this paper finds that staff neighborhood characteristics were a large and significant predictor of COVID-19 nursing home deaths. Even after controlling for the county where a facility is located, one standard deviation increases in average staff neighborhood (Census tract) population density, public transportation use, and non-white share were associated with 1.3 (p < .001), 1.4 (p < .001), and 0.9 (p < .001) additional deaths per 100 beds, respectively. These effects are larger than all facility management or quality variables, and larger than the effect of the nursing home’s own neighborhood characteristics. These results suggest COVID-19 outbreaks in staff communities can have large consequences for the facilities where they work, even in highly-rated facilities, and that disparities in nursing home outbreaks may be related to differences in the types of neighborhoods nursing home staff live in.

Segmentation of retinal vessels is important for doctors to diagnose some diseases. The segmentation accuracy of retinal vessels can be effectively improved by using deep learning methods. However, most of the existing methods are incomplete for shallow feature extraction, and some superficial features are lost, resulting in blurred vessel boundaries and inaccurate segmentation of capillaries in the segmentation results. At the same time, the “layer-by-layer” information fusion between encoder and decoder makes the feature information extracted from the shallow layer of the network cannot be smoothly transferred to the deep layer of the network, resulting in noise in the segmentation features. In this paper, we propose the MFI-Net (Multi-resolution fusion input network) network model to alleviate the above problem to a certain extent. The multi-resolution input module in MFI-Net avoids the loss of coarse-grained feature information in the shallow layer by extracting local and global feature information in different resolutions. We have reconsidered the information fusion method between the encoder and the decoder, and used the information aggregation method to alleviate the information isolation between the shallow and deep layers of the network. MFI-Net is verified on three datasets, DRIVE, CHASE_DB1 and STARE. The experimental results show that our network is at a high level in several metrics, with F1 higher than U-Net by 2.42%, 2.46% and 1.61%, higher than R2U-Net by 1.47%, 2.22% and 0.08%, respectively. Finally, this paper proves the robustness of MFI-Net through experiments and discussions on the stability and generalization ability of MFI-Net.

Introduction Viral outbreaks present a particular challenge in countries in Africa where there is already a high incidence of other infectious diseases, including malaria which can alter immune responses to secondary infection. Ebola virus disease (EVD) is one such problem; understanding how Plasmodium spp. and Ebolavirus (EBOV) interact is important for future outbreaks. Methods We conducted a systematic review in PubMed and Web of Science to find peer-reviewed papers with primary data literature to determine 1) prevalence of EBOV/Plasmodium spp. coinfection, 2) effect of EBOV/Plasmodium spp. coinfection on EVD pathology and the immune response, 3) impact of EBOV/Plasmodium spp. coinfection on the outcome of EVD-related mortality. Random effects meta-analyses were conducted with the R package meta to produce overall proportion and effect estimates as well as measure between-study heterogeneity. Results From 322 peer-reviewed papers, 17 were included in the qualitative review and nine were included in a meta-analysis. Prevalence of coinfection was between 19% and 72%. One study reported significantly lower coagulatory response biomarkers in coinfected cases but no difference in inflammatory markers. Case fatality rates were similar between EBOV(+)/Pl(+) and EBOV(+)/Pl(-) cases (62.8%, 95% CI 49.3–74.6 and 56.7%, 95% CI 53.2–60.1, respectively), and there was no significant difference in risk of mortality (RR 1.09, 95% CI 0.90–1.31) although heterogeneity between studies was high. One in vivo mouse model laboratory study found no difference in mortality by infection status, but another found prior acute Plasmodium yoeli infection was protective against morbidity and mortality via the IFN-γ signalling pathway. Conclusion The literature was inconclusive; studies varied widely and there was little attempt to adjust for confounding variables. Laboratory studies may present the best option to answer how pathogens interact within the body but improvement in data collection and analysis and in diagnostic methods would aid patient studies in the future.

To evaluate actions taken to implement the Telecommunications Act of 1996, the primary goal of which was to foster competition in the industry, the FCC created a standardized form (Form 477) to collect information about broadband deployment and competition in local telephone service. These data represent the best publicly available record of broadband provision in the United States. Despite the potential benefits offered by this database, there are several nuances to these data related to shifting geographies and reporting requirements that uncorrected, prevent them from being used as an uninterrupted time series for longitudinal analyses. Given the analytical challenges associated with the FCC Form 477 data, the purpose of this paper is to present a solution to the fragmented nature of these data which prevents meaningful longitudinal analyses of the digital divide. Specifically, this paper develops and describes a procedure for producing an integrated broadband time series (BITS) for the last decade (2008–2018). This includes the procedures for using these data, their value to social and economic analysis, and their underlying limitations. The core contribution of this paper is the creation of data infrastructure for investigating the evolution of the digital divide.

This paper provides an institutional and empirical analysis of the highly concentrated market of academic publishing, characterized by over proportionally high profit margins for publishing companies. The availability of latest research findings is an important issue for researchers, universities and politicians alike. Open access (OA) publication provides a promising but also costly solution to overcome this problem. However, in this paper we argue that OA publication costs are an important, but by far not the only way for academic publishers to gain access to public funding. In contrast, our study provides a comprehensive overview of the channels through which public expenditure benefits big academic publishing companies. Furthermore, we offer the results of an explorative case study, where we estimate the annual financial flows of public expenditures in Austria for the field of social sciences. In all, these expenditures add up to about 66.55 to 103.2 million € a year, which amounts to a fourth of total public funding for this field. Against this background, we contribute to the debate whether and to what extent public subsidies are justified for economically successful companies.

As in other countries, short-term rentals for tourism services are growing rapidly in China’s tourist cities, which are mainly operated through Airbnb. This paper explores whether the spatial distribution of Airbnb in China’s rapid urbanization process exhibits characteristics, paths, and drivers that are different from those of cities in other countries. Airbnb is a model for the global sharing economy, but it is increasingly influenced by other functions and facilities in cities as it grows. In this paper, the zero-expansion negative binomial regression was used to study the factors affecting the spatial distribution of Airbnb in Nanjing, China. The results showed that the spatial distribution of Airbnb listings was correlated with the distribution of cultural attractions, universities, public transport accessibility, shopping centers, and business apartments. By analyzing the driving forces of Airbnb’s development in Nanjing, this paper found that a large number of business apartments developed in cities were essential providers of Airbnb listings, and affected its spatial distribution. The gap between short-term and long-term rentals was also correlated with the distribution of Airbnb. In addition, similar to the previous literature findings, the increase in the proportion of professional hosts changes the original intention of Airbnb for sharing and communication. Our empirical results applies to the current situation of Airbnb in Chinese cities, which is conducive to the government’s more intelligent management and effective promotion of the Airbnb market. Our findings also provide positive references for urban renewal policies and public participation methods in China.

Background The objectives of this scoping review are to investigate the characteristics assessed by existing vulnerability indices and the health outcomes achieved by applying them to people experiencing homelessness. This review forms part of the development and implementation of a novel tool to prioritise people experiencing homelessness for healthcare based on their need and capacity to access healthcare. Methods Included papers were primary research, published in the English language, participants were experiencing homelessness and aged over 18 years at the time of the study, a vulnerability index was used in the study, sample size was greater than 30, and the study had a health focus. Databases searched were MEDLINE, Embase, CINAHL, Scopus, PubMed and Web of Science, between January-April 2020. The Joanna Briggs Appraisal criteria were used to quality appraise the included studies. Results were synthesised narratively. Results Six papers were included, a total of 27,509 participants. The reported use of the indices varied; they included screening and profiling homeless populations, comparing homeless populations, and two studies evaluated the predictive capacity, reliability and validity of the indices. One vulnerability index focused on screening for human immunodeficiency virus, one used a 50-item index and four used a nine-item index. No direct health outcomes were reported from applying the vulnerability indices. The studies identified limitations of using vulnerability indices, including the potential bias of relying on self-reported data and two studies highlighted the need for further psychometric testing to ensure validity and reliability of the indices. Discussion The sample of included studies was small. Vulnerability indices are reportedly a useful and easily accessible method of gaining valuable data on the health status and health needs of people experiencing homelessness. The variety of characteristics included in the vulnerability indices suggests the importance of tailoring vulnerability indices to the needs of the population to which it is to be applied. Conducting appropriate psychometric testing is critical so that an index can be used to accurately inform decision making and accurately prioritise people experiencing homelessness who are most at risk of mortality and morbidity. A specific tool that prioritises people experiencing homelessness for access to health care is not yet available. The review was funded by a St Vincent’s Network Inclusive Health grant.

An unbiased, widely accepted estimate of the rate of occurrence of new cases of autism over time would facilitate progress in understanding the causes of autism. The same may also apply to other disorders. While incidence is a widely used measure of occurrence, birth prevalence—the proportion of each birth year cohort with the disorder—is the appropriate measure for disorders and diseases of early childhood. Studies of autism epidemiology commonly speculate that estimates showing strong increases in rate of autism cases result from an increase in diagnosis rates rather than a true increase in cases. Unfortunately, current methods are not sufficient to provide a definitive resolution to this controversy. Prominent experts have written that it is virtually impossible to solve.This paper presents a novel method, time-to-event birth prevalence estimation (TTEPE), to provide accurate estimates of birth prevalence properly adjusted for changing diagnostic factors. It addresses the shortcomings of prior methods. TTEPE is based on well-known time-to-event (survival) analysis techniques. A discrete survival process models the rates of incident diagnoses by birth year and age. Diagnostic factors drive the probability of diagnosis as a function of the year of diagnosis. TTEPE models changes in diagnostic criteria, which can modify the effective birth prevalence when new criteria take effect. TTEPE incorporates the development of diagnosable symptoms with age. General-purpose optimization software estimates all parameters, forming a non-linear regression. The paper specifies all assumptions underlying the analysis and explores potential deviations from assumptions and optional additional analyses.A simulation study shows that TTEPE produces accurate parameter estimates, including trends in both birth prevalence and the probability of diagnosis in the presence of sampling effects from finite populations. TTEPE provides high power to resolve small differences in parameter values by utilizing all available data points.

Small and Medium Enterprises (SMEs) are considered as the fundamental tool for economic growth, nevertheless, they face continuous financing challenges. SMEs are a major source for generating employment, creation of wealth and alleviating poverty from the rural regions in developing countries. Their access to finance is key to the expansion of this sector. The paper aims to discover the intervening role of “access of SMEs to finance” in the link between SME’s evolution and rural development, in the context of Pakistan. In total 338 entrepreneurs operating SMEs in rural areas completed a survey for the study. Through a multi-stage stratified random sampling technique, entrepreneurs were selected from three districts. Confirmatory factor analysis and structural equation modeling were used to test hypotheses. This study shows that SME’s evolution has a positive and optimistic influence on rural development. Further, the study also reveals that on SME’s progress a positive influence happens by the “access of SMEs to finance”. Particularly, the study finds that “access of SMEs to finance” significantly mediated the effect of SME’s evolution on rural development. The findings of this paper hold significant implications for both the research society and loan-issuing institutions and departments.

Research papers are a repository of information on the various elements that make up science and technology R&D activities. Generating knowledge maps based on research papers enables identification of specific areas of scientific and technical research as well as understanding of the flow of knowledge between those areas. Recently, as the number of electronic publishing and informatics archives along with the amount of accumulated knowledge related to science and technology has proliferated, the need to utilize the meta-knowledge obtainable from research papers has increased. Therefore, this study devised a model based on meta-knowledge (i.e., text information including citations, abstracts, area codes) for prediction of future growth potential using deep learning algorithms and investigated the applicability of the various forms of meta-knowledge to the prediction of future growth potential. It also proposes how to select the promising technology clusters based on the proposed model.

In recent years, China’s economic development has advanced by leaps and bounds, but the development of China’s rural logistics system is still at its primary stage. Some remote areas with inconvenient transportation are still in a state of serious lack or even blank, and due to the high cost of rural logistics delivery services, the rural logistics business of the enterprise also has a profit problem, which limits the development of rural logistics talent innovation to some extent. The purpose of this paper is to study a new influencing factor model of the Internet rural logistics talent innovation mechanism. This paper innovatively proposes countermeasures to improve the innovation of e-commerce practitioners in rural areas. Through research, the author finds that the innovation of rural e-commerce application talents in China is generally low. The key point of the solution lies in how to improve the level of innovation in rural e-commerce application talents. According to the status quo, identify the factors that hinder the innovation and improvement of rural e-commerce application talents. Combined with the great environment of the development of rural e-commerce industry in China, the paper proposes to improve the countermeasures for improving the innovation of rural e-commerce application talents. Improve the current situation of rural e-commerce application talents mediocrity and promote the innovation of rural e-commerce application talents. Fundamentally promote agricultural development and the building of a new socialist countryside. This paper adopts the literature research method based on fuzzy comprehensive evaluation method, system analysis method and the combination of questionnaire survey and interview. Through big data and information science methods for data processing, using a company’s Internet rural talent data set to simulate, the results It shows that with the method of this paper, the recognition rate reaches 98%, the speed increases obviously, and it is 20% faster than others.