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Background: There is widespread evidence that statistical methods play an important role in original research articles, especially in medical research. The evaluation of statistical methods and reporting in journals suffers from a lack of standardized methods for assessing the use of statistics. The objective of this study was to develop and evaluate an instrument to assess the statistical intensity in research articles in a standardized way. Methods: A checklist-type measure scale was developed by selecting and refining items from previous reports about the statistical contents of medical journal articles and from published guidelines for statistical reporting. A total of 840 original medical research articles that were published between 2007±2015 in 16 journals were evaluated to test the scoring instrument. The total sum of all items was used to assess the intensity between sub-fields and journals. Inter-rater agreement was examined using a random sample of 40 articles. Four raters read and evaluated the selected articles using the developed instrument. Results: The scale consisted of 66 items. The total summary score adequately discriminated between research articles according to their study design characteristics. The new instrument could also discriminate between journals according to their statistical intensity. The inter-observer agreement measured by the ICC was 0.88 between all four raters. Individual item analysis showed very high agreement between the rater pairs, the percentage agreement ranged from 91.7% to 95.2%. Conclusions: A reliable and applicable instrument for evaluating the statistical intensity in research papers was developed. It is a helpful tool for comparing the statistical intensity between sub-fields and journals. The novel instrument may be applied in manuscript peer review to identify papers in need of additional statistical review.

Researchers in a variety of academic fields often debate the relative merits and drawbacks of pursuing frequent publications. This paper, authored by Ulf Sandstrom of the KTH Royal Institute of Technology in Sweden and Peter van den Besselaar of the Network Institute & Institute for Social Resilience in the Netherlands, explores this debate by comparing the number of publications and the number of scholarly citations of 48 Swedish researchers over the course of three years. The authors examine publications in a variety of fields, including Computer Science/Mathematics, Humanities, Sociology, and more. Based on this investigation, the authors conclude that "quantity [of publications] does make a difference." Those interested in learning more can download the 16-page paper, including detailed graphs, through the link above.

Researchers in a variety of academic fields often debate the relative merits and drawbacks of pursuing frequent publications. This paper, authored by Ulf Sandstrom of the KTH Royal Institute of Technology in Sweden and Peter van den Besselaar of the Network Institute & Institute for Social Resilience in the Netherlands, explores this debate by comparing the number of publications and the number of scholarly citations of 48 Swedish researchers over the course of three years. The authors examine publications in a variety of fields, including Computer Science/Mathematics, Humanities, Sociology, and more. Based on this investigation, the authors conclude that "quantity [of publications] does make a difference." Those interested in learning more can download the 16-page paper, including detailed graphs, through the link above.

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. Authorship of peer-reviewed journal articles and abstracts has become the primary currency and reward unit in academia. Such a reward is crucial for students and postdocs who are often under-compensated and thus highly value authorship as an incentive. While numerous scientific and publishing organizations have written guidelines for determining author qualifications and author order, there remains much ambiguity when it comes to how these criteria are weighed by research faculty. Here, we sought to provide some initial insight on how faculty view the relative importance of 11 criteria for scientific authorship. We distributed an online survey to 564 biomedical engineering, biology, and bioengineering faculty members at 10 research institutions across the United States. The response rate was approximately 18%, resulting in a final sample of 102 respondents. Results revealed an agreement on some criteria, such as time spent conducting experiments, but there was a lack of agreement regarding the role of funding procurement. This study provides quantitative assessments of how faculty members in the biosciences evaluate authorship criteria. We discuss the implications of these findings for researchers, especially new graduate students, to help navigate the discrepancy between official policies for authorship and the contributions that faculty truly value.

Monitoring for drug-induced liver injury (DILI) via serial transaminase measurements in patients on potentially hepatotoxic medications (e.g., for HIV and tuberculosis) is routine in resource-rich nations, but often unavailable in resource-limited settings. Towards enabling universal access to affordable point-of-care (POC) screening for DILI, we have performed the first field evaluation of a paper-based, microfluidic fingerstick test for rapid, semi-quantitative, visual measurement of blood alanine aminotransferase (ALT). Our objectives were to assess operational feasibility, inter-operator variability, lot variability, device failure rate, and accuracy, to inform device modification for further field testing. The paper-based ALT test was performed at POC on fingerstick samples from 600 outpatients receiving HIV treatment in Vietnam. Results, read independently by two clinic nurses, were compared with gold-standard automated (Roche Cobas) results from venipuncture samples obtained in parallel. Two device lots were used sequentially. We demonstrated high inter-operator agreement, with 96.3% (95% C.I., 94.3–97.7%) agreement in placing visual results into clinically-defined “bins” (<3x, 3–5x, and >5x upper limit of normal), >90% agreement in validity determination, and intraclass correlation coefficient of 0.89 (95% C.I., 0.87–0.91). Lot variability was observed in % invalids due to hemolysis (21.1% for Lot 1, 1.6% for Lot 2) and correlated with lots of incorporated plasma separation membranes. Invalid rates <1% were observed for all other device controls. Overall bin placement accuracy for the two readers was 84% (84.3%/83.6%). Our findings of extremely high inter-operator agreement for visual reading–obtained in a target clinical environment, as performed by local practitioners–indicate that the device operation and reading process is feasible and reproducible. Bin placement accuracy and lot-to-lot variability data identified specific targets for device optimization, National Institutes of Health (U.S.) (PATH Center to Advance Point of Care Diagnostics for Global Health NIBIB U54-EB007949), National Institute of Neurological Disorders and Stroke (U.S.) (Grant 5F30NS06468)

Ecological studies of orangutans have almost exclusively focused on populations living in primary or selectively logged rainforest. The response of orangutans to severe habitat degradation remains therefore poorly understood. Most experts assume that viable populations cannot survive outside undisturbed or slightly disturbed forests. This is a concern because nearly 75% of all orangutans live outside protected areas, where degradation of natural forests is likely to occur, or where these are replaced by planted forests. To improve our understanding of orangutan survival in highly altered forest habitats, we conducted population density surveys in two pulp and paper plantation concessions in East Kalimantan, Indonesia. These plantations consist of areas planted with fast-growing exotics intermixed with stands of highly degraded forests and scrublands. Our rapid surveys indicate unexpectedly high orangutan densities in plantation landscapes dominated by Acacia spp., although it remains unclear whether such landscapes can maintain long-term viable populations. These findings indicate the need to better understand how plantation-dominated landscapes can potentially be incorporated into orangutan conservation planning. Although we emphasize that plantations have less value for overall biodiversity conservation than natural forests, they could potentially boost the chances of orangutan survival. Our findings are based on a relatively short study and various methodological issues need to be addressed, but they suggest that orangutans may be more ecologically flexible than previously thought.

n/a, THE LINK TO THE ARTICLE FOR THIS DATA SET IS: http://hdl.handle.net/10344/4774, This is the data set for the article titled “Teacher competencies in Health Education: Results of a Delphi Study”. Published online in PLOS ONE. The data was collected in the 2011/2012 academic year. Three files are included, the raw data file from Round 2 and Round 3 and a file which contains the codes used for the data.

Cost information is critical to ease managers’ decisions in daily business, but its provision is informationally demanding and error prone. Effective design choices for costing systems that can reduce errors are the subject of a growing body of research. The computational model by Anand, Balakrishnan, and Labro (2019) collates previous research in a unifying framework, turning it into a potential standard for future studies. This paper uses this framework and aims to investigate the mechanism behind the well-documented empirical pattern of product cost cross-subsidization in a large-scale simulation experiment. According to this pattern, volume-based costing systems bias the costs of high-volume products upward and of low-volume products downward. Although this pattern has important implications for firms and is discussed extensively in the literature, it has not yet been investigated with computational models. As the first objective of this paper, we replicate the original model by following a pattern-oriented model replication approach. The second objective is to study the mechanism behind the pattern of product cost cross-subsidization. We are unable to reproduce it systematically with the original model. However, the pattern emerges when we extend the model to include a simple cost hierarchy with distinct resource consumption types and volume- based cost drivers. This allows us to specify the likely mechanism behind it. Building on these results, we further extend the model with empirical and theory-based ABC cost hierarchies and assess their effect on product cost cross-subsidization. Our results suggest that production environments underpin more diverse cost hierarchies in practice than previously implemented in the model. Overall, we argue that our extension provides relevant insights into the pattern of product cost cross-subsidization, while our replication and extension strengthen the models’ credibility and usability for future research.

The mechanisms underlying the emergence of seizures are one of the most important unresolved issues in epilepsy research. In this paper, we study how perturbations, exogenous or endogenous, may promote or delay seizure emergence. To this aim, due to the increasingly adopted view of epileptic dynamics in terms of slow-fast systems, we perform a theoretical analysis of the phase response of a generic relaxation oscillator. As relaxation oscillators are effectively bistable systems at the fast time scale, it is intuitive that perturbations of the non-seizing state with a suitable direction and amplitude may cause an immediate transition to seizure. By contrast, and perhaps less intuitively, smaller amplitude perturbations have been found to delay the spontaneous seizure initiation. By studying the isochrons of relaxation oscillators, we show that this is a generic phenomenon, with the size of such delay depending on the slow flow component. Therefore, depending on perturbation amplitudes, frequency and timing, a train of perturbations causes an occurrence increase, decrease or complete suppression of seizures. This dependence lends itself to analysis and mechanistic understanding through methods outlined in this paper. We illustrate this methodology by computing the isochrons, phase response curves and the response to perturbations in several epileptic models possessing different slow vector fields. While our theoretical results are applicable to any planar relaxation oscillator, in the motivating context of epilepsy they elucidate mechanisms of triggering and abating seizures, thus suggesting stimulation strategies with effects ranging from mere delaying to full suppression of seizures., Depto. de Análisis Matemático y Matemática Aplicada, Fac. de Ciencias Matemáticas, TRUE, pub

Social skills training, performed by human trainers, is a well-established method for obtaining appropriate skills in social interaction. Previous work automated the process of social skills training by developing a dialogue system that teaches social communication skills through interaction with a computer avatar. Even though previous work that simulated social skills training only considered acoustic and linguistic information, human social skills trainers take into account visual and other non-verbal features. In this paper, we create and evaluate a social skills training system that closes this gap by considering the audiovisual features of the smiling ratio and the head pose (yaw and pitch). In addition, the previous system was only tested with graduate students; in this paper, we applied our system to children or young adults with autism spectrum disorders. For our experimental evaluation, we recruited 18 members from the general population and 10 people with autism spectrum disorders and gave them our proposed multimodal system to use. An experienced human social skills trainer rated the social skills of the users. We evaluated the system’s effectiveness by comparing pre- and post-training scores and identified significant improvement in their social skills using our proposed multimodal system. Computer-based social skills training is useful for people who experience social difficulties. Such a system can be used by teachers, therapists, and social skills trainers for rehabilitation and the supplemental use of human-based training anywhere and anytime.

Surgical specialties account for a high proportion of antimicrobial use in hospitals, and misuse has been widely reported resulting in unnecessary patient harm and antimicrobial resistance. We aimed to synthesize qualitative studies on surgical antimicrobial prescribing behavior, in hospital settings, to explain how and why contextual factors act and interact to influence practice. Stakeholder engagement was integrated throughout to ensure consideration of varying interpretive repertoires and that the findings were clinically meaningful. The meta-ethnography followed the seven phases outlined by Noblit and Hare. Eight databases were systematically searched without date restrictions. Supplementary searches were performed including forwards and backwards citation chasing and contacting first authors of included papers to highlight further work. Following screening, 14 papers were included in the meta-ethnography. Repeated reading of this work enabled identification of 48 concepts and subsequently eight overarching concepts: hierarchy; fear drives action; deprioritized; convention trumps evidence; complex judgments; discontinuity of care; team dynamics; and practice environment. The overarching concepts interacted to varying degrees but there was no consensus among stakeholders regarding an order of importance. Further abstraction of the overarching concepts led to the development of a conceptual model and a line-of-argument synthesis, which posits that social and structural mediators influence individual complex antimicrobial judgements and currently skew practice towards increased and unnecessary antimicrobial use. Crucially, our model provides insights into how we might ‘tip the balance’ towards more evidence-based antimicrobial use. Currently, healthcare workers deploy antimicrobials across the surgical pathway as a safety net to allay fears, reduce uncertainty and risk, and to mitigate against personal blame. Our synthesis indicates that prescribing is un

The interplay between science and society takes place through a wide range of intertwined relationships and mutual influences that shape each other and facilitate continuous knowledge flows. Stylised consequentialist perspectives on valuable knowledge moving from public science to society in linear and recursive pathways, whilst informative, cannot fully capture the broad spectrum of value creation possibilities. As an alternative we experiment with an approach that gathers together diverse science-society interconnections and reciprocal research-related knowledge processes that can generate valorisation. Our approach to value creation attempts to incorporate multiple facets, directions and dynamics in which constellations of scientific and societal actors generate value from research. The paper develops a conceptual model based on a set of nine value components derived from four key research-related knowledge processes: production, translation, communication, and utilization. The paper conducts an exploratory empirical study to investigate whether a set of archetypes can be discerned among these components that structure science-society interconnections. We explore how such archetypes vary between major scientific fields. Each archetype is overlaid on a research topic map, with our results showing the distinctive topic areas that correspond to different archetypes. The paper finishes by discussing the significance and limitations of our results and the potential of both our model and our empirical approach for further research.

The paper examines the interest of the commercial banks' stakeholders in Pillar 3 disclosures and their behaviour during the timing of serious market turbulence. The aim is to discover to which extent current banking regulation supports stakeholders' interest in the information required by regulators to be disclosed. The examined data consists of log files that were pre-processed using web mining techniques and from which were extracted frequent item sets by quarters and evaluated in terms of quantity. The authors have proposed a methodology to evaluate frequent item sets of web parts over a dedicated time. Based on the verification of applied methodology on two commercial banks, the results show that stakeholders' interest in disclosures is highest in the first quarter at each year and after turbulent times in 2009 their interests decreased. Moreover, the results suggest that stakeholders expressed higher interest than in regulatory required Pillar 3 information in the following group of information: Pillar3 related information, Annual reports, Information on Group. Following our results, the paper contributes to cover the gap in the research by analysing Pillar 3 disclosures and their compliance with regulatory requirements, which also increase the interest of the relevant stakeholders to conduce them as an effective market discipline tool., Článek zkoumá zájem zainteresovaných stran komerčních bank o zveřejňování informací podle 3. pilíře a jejich chování v době vážných tržních turbulencí. Cílem je zjistit, do jaké míry současná bankovní regulace podporuje zájem zainteresovaných stran o informace, jejichž zveřejnění regulátoři vyžadují. Zkoumaná data se skládají z logů, které byly předem zpracovány pomocí technik web miningu a z nichž byly extrahovány soubory častých položek podle čtvrtletí a vyhodnoceny z hlediska kvantity. Autoři navrhli metodiku vyhodnocování sad častých položek webových částí za vyhrazený čas. Na základě ověření aplikované metodiky na dvou komerčních bankách výsledky ukazují, že zájem zainteresovaných stran o zveřejňované informace je v každém roce nejvyšší v prvním čtvrtletí a po turbulentním období v roce 2009 jejich zájem poklesl. Výsledky dále naznačují, že zainteresované strany projevily vyšší zájem než o regulatorně požadované informace 3. pilíře o následující skupinu informací: Informace související s pilířem 3, Výroční zprávy, Informace o skupině. V návaznosti na naše výsledky přispívá tento článek k pokrytí mezery ve výzkumu analýzou informací zveřejňovaných v rámci Pilíře 3 a jejich souladu s regulatorními požadavky, což také zvyšuje zájem příslušných zainteresovaných stran o jejich vedení jako účinného nástroje tržní disciplíny.

Appropriate descriptions of statistical methods are essential for evaluating research quality and reproducibility. Despite continued efforts to improve reporting in publications, inadequate descriptions of statistical methods persist. At times, reading statistical methods sections can conjure feelings of dèjá vu, with content resembling cut-and-pasted or “boilerplate text” from already published work. Instances of boilerplate text suggest a mechanistic approach to statistical analysis, where the same default methods are being used and described using standardized text. To investigate the extent of this practice, we analyzed text extracted from published statistical methods sections from PLOS ONE and the Australian and New Zealand Clinical Trials Registry (ANZCTR). Topic modeling was applied to analyze data from 111,731 papers published in PLOS ONE and 9,523 studies registered with the ANZCTR. PLOS ONE topics emphasized definitions of statistical significance, software and descriptive statistics. One in three PLOS ONE papers contained at least 1 sentence that was a direct copy from another paper. 12,675 papers (11%) closely matched to the sentence “a p-value < 0.05 was considered statistically significant”. Common topics across ANZCTR studies differentiated between study designs and analysis methods, with matching text found in approximately 3% of sections. Our findings quantify a serious problem affecting the reporting of statistical methods and shed light on perceptions about the communication of statistics as part of the scientific process. Results further emphasize the importance of rigorous statistical review to ensure that adequate descriptions of methods are prioritized over relatively minor details such as p-values and software when reporting research outcomes.

Scientists routinely use images to display data. Readers often examine figures first; therefore, it is important that figures are accessible to a broad audience. Many resources discuss fraudulent image manipulation and technical specifications for image acquisition; however, data on the legibility and interpretability of images are scarce. We systematically examined these factors in non-blot images published in the top 15 journals in 3 fields; plant sciences, cell biology, and physiology (n = 580 papers). Common problems included missing scale bars, misplaced or poorly marked insets, images or labels that were not accessible to colorblind readers, and insufficient explanations of colors, labels, annotations, or the species and tissue or object depicted in the image. Papers that met all good practice criteria examined for all image-based figures were uncommon (physiology 16%, cell biology 12%, plant sciences 2%). We present detailed descriptions and visual examples to help scientists avoid common pitfalls when publishing images. Our recommendations address image magnification, scale information, insets, annotation, and color and may encourage discussion about quality standards for bioimage publishing., source:https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001161, source:https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001161&rev=1

Cattle were the predominant domestic animal in the Iron Age and Roman Netherlands, yet their management is still incompletely understood. Some aspects of cattle management, such as birth season and the provision of fodder, have received little or no attention so far. This paper is the first to investigate these aspects for the Iron Age and Roman Netherlands, through a case study of the site of Houten-Castellum. The rural settlement of Houten-Castellum was inhabited from the Middle Iron Age to the Middle Roman period, allowing a comparison between the Iron Age and Roman period. Excavations at this site have yielded a large, well-preserved animal bone assemblage. This paper investigates cattle husbandry by using an integrated approach, combining a multi-isotope analysis (oxygen, carbon and strontium) with archaeozoological and archaeobotanical results from Houten-Castellum and comparing the results with archaeobotanical evidence for fodder and evidence for dairy use for the Iron Age and Roman Netherlands in general. While our data set is small and results must therefore be interpreted cautiously, there is convincing evidence for an extended birth season in the Middle Iron Age, as well as the use of fodder.

This study establishes a new method for estimating the monthly Average Population Present (APP) in Australian regions. Conventional population statistics, which enumerate people where they usually live, ignore the significant spatial mobility driving short term shifts in population numbers. Estimates of the temporary or ambient population of a region have several important applications including the provision of goods and services, emergency preparedness and serve as more appropriate denominators for a range of social statistics. This paper develops a flexible modelling framework to generate APP estimates from an integrated suite of conventional and novel data sources. The resultant APP estimates reveal the considerable seasonality in small area populations across Australia's regions alongside the contribution of domestic and international visitors as well as absent residents to the observed monthly variations. The modelling framework developed in the paper is conceived in a manner such that it can be adapted and re-deployed both for use with alternative data sources as well as other situational contexts for the estimation of temporary populations.

Numerous and extensive ‘Stone Walled Sites’ have been identified in southern African Iron Age landscapes. Appearing from around 1200 CE, and showing considerable variability in size and form, these settlements are named after the dry-stone wall structures that characterize them. Stone Walled Sites were occupied by various Bantu-speaking agropastoral communities. In this paper we test the use of pXRF (portable X-ray fluorescence analysis) to generate a ‘supplementary’ archaeological record where evident stratigraphy is lacking, survey conditions may be uneven, and excavations limited, due to the overall site size. We propose herein the application of portable X-ray fluorescence analysis (pXRF) coupled with multivariate exploratory analysis and geostatistical modelling at Seoke, a southern African SWS of historical age (18 century CE). The aim of the paper is twofold: to explore the potential of the application of a low cost, quick, and minimally invasive technique to detect chemical markers in anthropogenic sediments from a Stone Walled Site, and to propose a way to analyse the results in order to improve our understanding of the use of space at non-generalized scales in such sites.

Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how n

Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how n

Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how n

Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how n

Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how n

Numerous and extensive 'Stone Walled Sites' have been identified in southern African Iron Age landscapes. Appearing from around 1200 CE, and showing considerable variability in size and form, these settlements are named after the dry-stone wall structures that characterize them. Stone Walled Sites were occupied by various Bantu-speaking agropastoral communities. In this paper we test the use of pXRF (portable X-ray fluorescence analysis) to generate a 'supplementary' archaeological record where evident stratigraphy is lacking, survey conditions may be uneven, and excavations limited, due to the overall site size. We propose herein the application of portable X-ray fluorescence analysis (pXRF) coupled with multivariate exploratory analysis and geostatistical modelling at Seoke, a southern African SWS of historical age (18th century CE). The aim of the paper is twofold: to explore the potential of the application of a low cost, quick, and minimally invasive technique to detect chemical markers in anthropogenic sediments from a Stone Walled Site, and to propose a way to analyse the results in order to improve our understanding of the use of space at non-generalized scales in such sites.

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

Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how n

Objective Digital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior. Method The search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online. Results The review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges’ g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions. Conclusion Identifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how n

Innovations supporting a shift towards more sustainable food systems can be developed within the dominant food system regime or in alternative niches. No study has compared the challenges faced in each context. This paper, based on an analysis of 25 cases of European innovations that support crop diversification, explores the extent to which barriers to crop diversification can be related to the proximity of innovation settings with dominant food systems. Drawing on a qualitative analysis of interviews and participatory brainstorming, we highlight 46 different barriers to crop diversification across the cases, at different levels: production; downstream operations from farm to retailing, marketing and consumers; and contracts and coordination between actors. To characterise the diversity of innovation strategies at food system level, we introduce the concept of “food system innovation settings” combining: (i) the type of innovative practice promoted at farm level; (ii) the type of value chain supporting that innovation; and (iii) the type of agriculture involved (organic or conventional). Through a multiple correspondence analysis, we show different patterns of barriers to crop diversification according to three ideal-types of food system innovation settings: (i) “Changing from within”, where longer rotations are fostered on conventional farms involved in commodity supply chains; (ii) “Building outside”, where crop diversification integrates intercropping on organic farms involved in local supply chains; and (iii) “Playing horizontal”, where actors promote alternative crop diversification strategies—either strictly speaking horizontal at spatial level (e.g. strip cropping) or socially horizontal (arrangement between farmers)–without directly challenging the vertical organisation of dominant value chains. We recommend designing targeted research and policy actions according to the food systems they seek to develop. We then discuss further development of our approach

The spread of COVID-19 implied a large and fast increase of demand for intensive care services. To face this increase in demand, health care systems need to adapt their response by increasing hospital beds, intensive care unit (ICU) capacity and by (re-)deploying doctors and other personnel. This paper proposes a forecast approach based on the Vector Error Correction model for the daily counts of hospitalized patients with symptoms and of patients in ICU, using publicly available data on the current COVID-19 outbreak in Italy, Switzerland and Spain. The level of analysis is the local government managing the health care system response, which corresponds to regions for Italy. The one-week-ahead forecasts are validated with out-of-sample data over successive weeks; they are found to provide timely and robust prediction of ICU capacity needs in Lombardy, the most-affected Italian region, starting from the sample of the first 2 weeks of data. The same methodology is successfully validated on other Italian regions, Switzerland and Spain. This approach may be used in other countries/regions/provinces to help adapt the health care system response to COVID-19 (or other similar disease); for this purpose, the open-source software code to produce the forecasts is provided with the paper.

Innovations supporting a shift towards more sustainable food systems can be developed within the dominant food system regime or in alternative niches. No study has compared the challenges faced in each context. This paper, based on an analysis of 25 cases of European innovations that support crop diversification, explores the extent to which barriers to crop diversification can be related to the proximity of innovation settings with dominant food systems. Drawing on a qualitative analysis of interviews and participatory brainstorming, we highlight 46 different barriers to crop diversification across the cases, at different levels: production; downstream operations from farm to retailing, marketing and consumers; and contracts and coordination between actors. To characterise the diversity of innovation strategies at food system level, we introduce the concept of “food system innovation settings” combining: (i) the type of innovative practice promoted at farm level; (ii) the type of value chain supporting that innovation; and (iii) the type of agriculture involved (organic or conventional). Through a multiple correspondence analysis, we show different patterns of barriers to crop diversification according to three ideal-types of food system innovation settings: (i) “Changing from within”, where longer rotations are fostered on conventional farms involved in commodity supply chains; (ii) “Building outside”, where crop diversification integrates intercropping on organic farms involved in local supply chains; and (iii) “Playing horizontal”, where actors promote alternative crop diversification strategies—either strictly speaking horizontal at spatial level (e.g. strip cropping) or socially horizontal (arrangement between farmers)–without directly challenging the vertical organisation of dominant value chains. We recommend designing targeted research and policy actions according to the food systems they seek to develop. We then discuss further development of our approach

[EN] The paper is concerned with the consensus problem in a multi-agent system such that each agent has boundary constraints. Classical Olfati-Saber's consensus algorithm converges to the same value of the consensus variable, and all the agents reach the same value. These algorithms find an equality solution. However, what happens when this equality solution is out of the range of some of the agents? In this case, this solution is not adequate for the proposed problem. In this paper, we propose a new kind of algorithms called supportive consensus where some agents of the network can compensate for the lack of capacity of other agents to reach the average value, and so obtain an acceptable solution for the proposed problem. Supportive consensus finds an equity solution. In the rest of the paper, we define the supportive consensus, analyze and demonstrate the network's capacity to compensate out of boundaries agents, propose different supportive consensus algorithms, and finally, provide some simulations to show the performance of the proposed algorithms.

[EN] The paper is concerned with the consensus problem in a multi-agent system such that each agent has boundary constraints. Classical Olfati-Saber's consensus algorithm converges to the same value of the consensus variable, and all the agents reach the same value. These algorithms find an equality solution. However, what happens when this equality solution is out of the range of some of the agents? In this case, this solution is not adequate for the proposed problem. In this paper, we propose a new kind of algorithms called supportive consensus where some agents of the network can compensate for the lack of capacity of other agents to reach the average value, and so obtain an acceptable solution for the proposed problem. Supportive consensus finds an equity solution. In the rest of the paper, we define the supportive consensus, analyze and demonstrate the network's capacity to compensate out of boundaries agents, propose different supportive consensus algorithms, and finally, provide some simulations to show the performance of the proposed algorithms.

[EN] The paper is concerned with the consensus problem in a multi-agent system such that each agent has boundary constraints. Classical Olfati-Saber's consensus algorithm converges to the same value of the consensus variable, and all the agents reach the same value. These algorithms find an equality solution. However, what happens when this equality solution is out of the range of some of the agents? In this case, this solution is not adequate for the proposed problem. In this paper, we propose a new kind of algorithms called supportive consensus where some agents of the network can compensate for the lack of capacity of other agents to reach the average value, and so obtain an acceptable solution for the proposed problem. Supportive consensus finds an equity solution. In the rest of the paper, we define the supportive consensus, analyze and demonstrate the network's capacity to compensate out of boundaries agents, propose different supportive consensus algorithms, and finally, provide some simulations to show the performance of the proposed algorithms.

Innovations supporting a shift towards more sustainable food systems can be developed within the dominant food system regime or in alternative niches. No study has compared the challenges faced in each context. This paper, based on an analysis of 25 cases of European innovations that support crop diversification, explores the extent to which barriers to crop diversification can be related to the proximity of innovation settings with dominant food systems. Drawing on a qualitative analysis of interviews and participatory brainstorming, we highlight 46 different barriers to crop diversification across the cases, at different levels: production; downstream operations from farm to retailing, marketing and consumers; and contracts and coordination between actors. To characterise the diversity of innovation strategies at food system level, we introduce the concept of “food system innovation settings” combining: (i) the type of innovative practice promoted at farm level; (ii) the type of value chain supporting that innovation; and (iii) the type of agriculture involved (organic or conventional). Through a multiple correspondence analysis, we show different patterns of barriers to crop diversification according to three ideal-types of food system innovation settings: (i) “Changing from within”, where longer rotations are fostered on conventional farms involved in commodity supply chains; (ii) “Building outside”, where crop diversification integrates intercropping on organic farms involved in local supply chains; and (iii) “Playing horizontal”, where actors promote alternative crop diversification strategies—either strictly speaking horizontal at spatial level (e.g. strip cropping) or socially horizontal (arrangement between farmers)–without directly challenging the vertical organisation of dominant value chains. We recommend designing targeted research and policy actions according to the food systems they seek to develop. We then discuss further development of our approach

Introduction Since its initial recognition, HIV has been responsible for around 35 million deaths globally. The introduction of Antiretroviral Therapy has helped to reduce mortality from HIV. However, the resulting increased longevity has influenced the experience of people living with HIV, which now manifests as a chronic condition requiring effective self-management. This review aimed to identify and evaluate the effectiveness of interventions to improve self-management of adults living with HIV on Antiretroviral therapy. Methods The review included published experimental studies addressing interventions to improve self-management of adults living with HIV on Antiretroviral Therapy. Studies were included if they addressed two or more outcomes of self-management, as defined by the Theory of Individual and Family Self-Management. The search covered four databases and was limited to papers published in the English language from 2001 to March 30, 2019. The reference lists of included studies were further searched for additional studies. Two independent reviewers using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI SUMARI) assessed the methodological quality of the reviewed papers. Data extraction was undertaken using the JBI SUMARI standardized data extraction tool. As the included papers were not homogeneous, it was not possible to conduct a meta-analysis. A narrative synthesis was undertaken to synthesize the findings of the included studies. Results The search identified 337 articles from which 10 experimental and 2 quasi-experimental studies were included. The total participant sample in the included studies was 1661 adults living with HIV. The overall evidence quality of the findings was considered moderate. Many of the studies included in this review comprised multi-component interventions to improve self-management. Skills training, in conjunction with

Innovations supporting a shift towards more sustainable food systems can be developed within the dominant food system regime or in alternative niches. No study has compared the challenges faced in each context. This paper, based on an analysis of 25 cases of European innovations that support crop diversification, explores the extent to which barriers to crop diversification can be related to the proximity of innovation settings with dominant food systems. Drawing on a qualitative analysis of interviews and participatory brainstorming, we highlight 46 different barriers to crop diversification across the cases, at different levels: production; downstream operations from farm to retailing, marketing and consumers; and contracts and coordination between actors. To characterise the diversity of innovation strategies at food system level, we introduce the concept of “food system innovation settings” combining: (i) the type of innovative practice promoted at farm level; (ii) the type of value chain supporting that innovation; and (iii) the type of agriculture involved (organic or conventional). Through a multiple correspondence analysis, we show different patterns of barriers to crop diversification according to three ideal-types of food system innovation settings: (i) “Changing from within”, where longer rotations are fostered on conventional farms involved in commodity supply chains; (ii) “Building outside”, where crop diversification integrates intercropping on organic farms involved in local supply chains; and (iii) “Playing horizontal”, where actors promote alternative crop diversification strategies—either strictly speaking horizontal at spatial level (e.g. strip cropping) or socially horizontal (arrangement between farmers)–without directly challenging the vertical organisation of dominant value chains. We recommend designing targeted research and policy actions according to the food systems they seek to develop. We then discuss further development of our approach

The use of English as the common language of science represents a major impediment to maximising the contribution of non-native English speakers to science. Yet few studies have quantified the consequences of language barriers on the career development of researchers who are non-native English speakers. By surveying 908 researchers in environmental sciences, this study estimates and compares the amount of effort required to conduct scientific activities in English between researchers from different countries and, thus, different linguistic and economic backgrounds. Our survey demonstrates that non-native English speakers, especially early in their careers, spend more effort than native English speakers in conducting scientific activities, from reading and writing papers and preparing presentations in English, to disseminating research in multiple languages. Language barriers can also cause them not to attend, or give oral presentations at, international conferences conducted in English. We urge scientific communities to recognise and tackle these disadvantages to release the untapped potential of non-native English speakers in science. This study also proposes potential solutions that can be implemented today by individuals, institutions, journals, funders, and conferences.

Air pollution is one of the most severe environmental problems that Mexico is currently facing. The objective of this paper is to quantify the most relevant socioeconomic driving forces behind air polluting emissions and, more specifically, 7 local pollutants in Mexico. We do so in a multilevel version of the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that accounts for the spatial heterogeneity at the municipal level across the country. The results show that the most relevant variables to determine the emissions of atmospheric pollutants are the population, the harvested area and the number of cars, while technological development helps to mitigate such emissions. The ecological elasticities are, in all cases, smaller than one. Our purpose is to provide quantitative information about these socioeconomic driving forces of air deterioration as a basis to establish some recommendations for environmental policy decision-making

In this paper, we aimed at developing and validating a novel instrument to evaluate personality in 10-14 years old adolescents with six basic traits, with two dedicated studies. In Study 1, we generated a large pool of items (384 items) from three basic items sources, which we administered to 714 Italian adolescents. Using principal component analysis (PCA) and extension factor analysis, we selected the best eight items for each facet, and so the best 32 items for each factor, except for the Unconventionality facet of Openness to Experience (O) for which we selected the best six items. This resulted in a total of 190 items. The 190-item HEXACO-MSI had very good levels of dimensional validity and reliability, but it fell short in containing 8 items for each facet (i.e., for Unconventionality) and in balancing normal and reversed items within each facet. Therefore, in a second study we added items to the scale and verified again the dimensionality and reliability with the goal of developing a final version of the scale. In Study 2, we administered a version of the HEXACO-MSI consisting of 219 items to 1175 Italian adolescents. Using principal component analysis (PCA), we selected the best eight items for each facet equally balanced between normal and reversed items within each facet and factor. Confirmatory factor analysis (CFA) confirmed the six-factor structure and its invariance. The results showed that the HEXACO-MSI-E had a clear six-factor structure in adolescents, that was invariant across gender and across the three middle school classes, and was reliable. Finally, we established temporal stability of each factor in two measurements after one year. Together with the positive results of this contribution, we discussed some aspects for future studies.

Background Psychological aspects of labor and birth have received little attention within maternity care service planning or clinical practice. The aim of this paper is to propose a model demonstrating how neurohormonal processes, in particular oxytocinergic mechanisms, not only control the physiological aspects of labor and birth, but also contribute to the subjective psychological experiences of birth. In addition, sensory information from the uterus as well as the external environment might influence these neurohormonal processes thereby influencing the progress of labor and the experience of birth. Methodology In this new model of childbirth, we integrated the findings from two previous systematic reviews, one on maternal plasma levels of oxytocin during physiological childbirth and one meta-synthesis of women´s subjective experiences of physiological childbirth. Findings The neurobiological processes induced by the release of endogenous oxytocin during birth influence maternal behaviour and feelings in connection with birth in order to facilitate birth. The psychological experiences during birth may promote an optimal transition to motherhood. The spontaneous altered state of consciousness, that some women experience, may well be a hallmark of physiological childbirth in humans. The data also highlights the crucial role of one-to-one support during labor and birth. The physiological importance of social support to reduce labor stress and pain necessitates a reconsideration of many aspects of modern maternity care. Conclusion By listening to women’s experiences and by observing women during childbirth, factors that contribute to an optimized process of labor, such as the mothers’ wellbeing and feelings of safety, may be identified. These observations support the integrative role of endogenous oxytocin in coordinating the neuroendocrine, psychological and physiological aspects of labor and birth, including oxytocin mediated. decrease of pain, fear and stress, sup, EU COST (European Cooperation in Science and Technology), Depto. de Lógica y Filosofía Teórica, Fac. de Filosofía, TRUE, pub

© Public Library of Science. We are grateful to Y. Tu, D. Zwicker, R. Ma, R.G. Endres, G. Aquino, G. de Palo and S. Pigolotti for comments on this manuscript, and P. Mehta for helpful discussions., Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli’s chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response., Depto. de Estructura de la Materia, Física Térmica y Electrónica, Fac. de Ciencias Físicas, TRUE, pub

Sinking marine aggregates have been studied for a long time to understand their role in carbon sequestration. Traditionally, sinking speed and respiration rates have been treated as independent variables, but two recent papers suggest that there is a connection albeit in contrasting directions. Here we collected recently formed (<2 days old) aggregates from sediment traps mounted underneath mesocosms during two different experiments. The mesocosms were moored off Gran Canaria, Spain (~ 27.9 N; 15.4 E) in a coastal, sub-tropical and oligotrophic ecosystem. We determined the respiration rates of organisms (mainly heterotrophic prokaryotes) attached to aggregates sinking at different velocities. The average respiration rate of fast sinking aggregates (>100 m d-1) was 0.12 d-1 ± 0.08 d-1 (SD). Slower sinking aggregates (<50 m d-1) had on average higher (p <0.001) and more variable respiration rates (average 0.31 d-1 ± 0.16 d-1, SD). There was evidence that slower sinking aggregates had higher porosity than fast sinking aggregates, and we hypothesize that higher porosity increase the settlement area for bacteria and the respiration rate. These findings provide insights into the efficiency of the biological carbon pump and help resolve the apparent discrepancy in the recent studies of the correlation between respiration and sinking speed. © 2023 Spilling 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.

Sinking marine aggregates have been studied for a long time to understand their role in carbon sequestration. Traditionally, sinking speed and respiration rates have been treated as independent variables, but two recent papers suggest that there is a connection albeit in contrasting directions. Here we collected recently formed (<2 days old) aggregates from sediment traps mounted underneath mesocosms during two different experiments. The mesocosms were moored off Gran Canaria, Spain (~ 27.9 N; 15.4 E) in a coastal, sub-tropical and oligotrophic ecosystem. We determined the respiration rates of organisms (mainly heterotrophic prokaryotes) attached to aggregates sinking at different velocities. The average respiration rate of fast sinking aggregates (>100 m d-1) was 0.12 d-1 ± 0.08 d-1 (SD). Slower sinking aggregates (<50 m d-1) had on average higher (p <0.001) and more variable respiration rates (average 0.31 d-1 ± 0.16 d-1, SD). There was evidence that slower sinking aggregates had higher porosity than fast sinking aggregates, and we hypothesize that higher porosity increase the settlement area for bacteria and the respiration rate. These findings provide insights into the efficiency of the biological carbon pump and help resolve the apparent discrepancy in the recent studies of the correlation between respiration and sinking speed. © 2023 Spilling 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.

An electrocardiograph (ECG) is widely used in diagnosis and prediction of cardiovascular diseases (CVDs). The traditional ECG classification methods have complex signal processing phases that leads to expensive designs. This paper provides a deep learning (DL) based system that employs the convolutional neural networks (CNNs) for classification of ECG signals present in PhysioNet MIT-BIH Arrhythmia database. The proposed system implements 1-D convolutional deep residual neural network (ResNet) model that performs feature extraction by directly using the input heartbeats. We have used synthetic minority oversampling technique (SMOTE) that process class-imbalance problem in the training dataset and effectively classifies the five heartbeat types in the test dataset. The classifier's performance is evaluated with ten-fold cross validation (CV) using accuracy, precision, sensitivity, F1- score, and kappa. We have obtained an average accuracy of 98.63%, precision of 92.86%, sensitivity of 92.41%, and specificity of 99.06%. The average F1-score and Kappa obtained were 92.63% and 95.5% respectively. The study shows that proposed ResNet performs well with deep layers compared to other 1-D CNNs.

Obtaining an accurate prediction of the number of influenza patients in specific areas is a crucial task undertaken by medical institutions. Infections (such as influenza) spread from person to person, and people are rarely confined to a single area. Therefore, creating a regional influenza prediction model should consider the flow of people between different areas. Although various regional flu prediction models have previously been proposed, they do not consider the flow of people among areas. In this study, we propose a method that can predict the geographical distribution of influenza patients using commuting data to represent the flow of people. To elucidate the complex spatial dependence relations, our model uses an extension of the graph convolutional network (GCN). Additionally, a prediction interval for medical institutions is proposed, which is suitable for cyclic time series. Subsequently, we used the weekly data of flu patients from health authorities as the ground-truth to evaluate the prediction interval and performance of influenza patient prediction in each prefecture in Japan. The results indicate that our GCN-based model, which used commuting data, considerably improved the predictive accuracy over baseline values both temporally and spatially to provide an appropriate prediction interval. The proposed model is vital in practical settings, such as in the decision making of public health authorities and addressing growth in vaccine demand and workload. This paper primarily presents a GCN as a useful means for predicting the spread of an epidemic.

Admixture graphs are mathematical structures that describe the ancestry of populations in terms of divergence and merging (admixing) of ancestral populations as a graph. An admixture graph consists of a graph topology, branch lengths, and admixture proportions. The branch lengths and admixture proportions can be estimated using numerous numerical optimization methods, but inferring the topology involves a combinatorial search for which no polynomial algorithm is known. In this paper, we present a reversible jump MCMC algorithm for sampling high-probability admixture graphs and show that this approach works well both as a heuristic search for a single best-fitting graph and for summarizing shared features extracted from posterior samples of graphs. We apply the method to 11 Native American and Siberian populations and exploit the shared structure of high-probability graphs to characterize the relationship between Saqqaq, Inuit, Koryaks, and Athabascans. Our analyses show that the Saqqaq is not a good proxy for the previously identified gene flow from Arctic people into the Na-Dene speaking Athabascans.

Tropical peatlands are important carbon stores that are vulnerable to drainage and conversion to agriculture. Protection and restoration of peatlands are increasingly recognised as key nature based solutions that can be implemented as part of climate change mitigation. Identification of peatland areas that are important for protection and restauration with regards to the state of their carbon stocks, are therefore vital for policy makers. In this paper we combined organic geochemical analysis by Rock-Eval (6) pyrolysis of peat collected from sites with different land management history and optical remote sensing products to assess if remotely sensed data could be used to predict peat conditions and carbon storage. The study used the North Selangor Peat Swamp forest, Malaysia, as the model system. Across the sampling sites the carbon stocks in the below ground peat was ca 12 times higher than the forest (median carbon stock held in ground vegetation 114.70 Mg ha-1 and peat soil 1401.51 Mg ha-1). Peat core sub-samples and litter collected from Fire Affected, Disturbed Forest, and Managed Recovery locations (i.e. disturbed sites) had different decomposition profiles than Central Forest sites. The Rock-Eval pyrolysis of the upper peat profiles showed that surface peat layers at Fire Affected, Disturbed Forest, and Managed Recovery locations had lower immature organic matter index (I-index) values (average I-index range in upper section 0.15 to -0.06) and higher refractory organic matter index (R -index) (average R-index range in upper section 0.51 to 0.65) compared to Central Forest sites indicating enhanced decomposition of the surface peat. In the top 50 cm section of the peat profile, carbon stocks were negatively related to the normalised burns ratio (NBR) (a satellite derived parameter) (Spearman’s rho = -0.664, S = 366, p-value = <0.05) while there was a positive relationship between the hydrogen index and the normalised burns ratio profile (Spearman’s rho = 0.7

Sinking marine aggregates have been studied for a long time to understand their role in carbon sequestration. Traditionally, sinking speed and respiration rates have been treated as independent variables, but two recent papers suggest that there is a connection albeit in contrasting directions. Here we collected recently formed (<2 days old) aggregates from sediment traps mounted underneath mesocosms during two different experiments. The mesocosms were moored off Gran Canaria, Spain (~ 27.9 N; 15.4 E) in a coastal, sub-tropical and oligotrophic ecosystem. We determined the respiration rates of organisms (mainly heterotrophic prokaryotes) attached to aggregates sinking at different velocities. The average respiration rate of fast sinking aggregates (>100 m d-1) was 0.12 d-1 ± 0.08 d-1 (SD). Slower sinking aggregates (<50 m d-1) had on average higher (p <0.001) and more variable respiration rates (average 0.31 d-1 ± 0.16 d-1, SD). There was evidence that slower sinking aggregates had higher porosity than fast sinking aggregates, and we hypothesize that higher porosity increase the settlement area for bacteria and the respiration rate. These findings provide insights into the efficiency of the biological carbon pump and help resolve the apparent discrepancy in the recent studies of the correlation between respiration and sinking speed. © 2023 Spilling 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.