bluuebunny/crossref_metadata_2025_split huggingface dataset:
To see, or not to see… pathogens in virtual reality hand hygiene training
Authors: Wolfensberger Aline , Désiron Juliette C. , Domenech-Jakob Beatrice , Petko Dominik , Zingg Walter 
Published: October 2024

AbstractBackground:ViRTUE, a virtual reality (VR) hand hygiene trainer, offers users the option of visualizing pathogen transfers during virtual patient care either in “real-time” or at the end of a level as a “summary” visualization. In this study, we aimed to evaluate the effect of different timings of pathogen visualization (“real-time” vs “summary”) on in-trainer performance and user’s immersion.Methods:The study included first-year medical students undergoing hand hygiene training with ViRTUE, randomized to one of three visualization set-ups: set-up 1 (“on-off-off”, with “real-time” visualization at the first level only, and “summary” visualization at level 2 and 3), set-up 2 (“off-on-off”), and set-up 3 (“off-off-off”). In-trainer performance was defined by number of pathogen transmission events (=contaminations) in level 3. The virtual experience of user’s (among others: immersion) was assessed with a questionnaire.Results:173 medical students participated in the study, with 58, 54, and 61 assigned to set-up 1, set-up 2, and set-up 3, respectively. Users assigned to set-up 3 with “summary” visualization at all levels, performed best with 1.02 (standard deviation (SD) +/- 1.86) contaminations, compared to 2.34 (SD +/- 3.09) and 2.07 (SD +/- 2.52) contaminations of users assigned to the other set-ups. “Summary” visualization at all levels also resulted in higher immersion of users.Conclusions:“Real-time” visualization of pathogen transmission during VR hand hygiene training with ViRTUE may negatively affect in-trainer performance and user immersion. This emphasizes the importance of pilot testing the effect of VR-based trainings in order to understand their impact on users.
Parallel evolution of unusual ‘harpiform’ morphologies in distantly related trilobites
Authors: Beech James D. , Bottjer David J. , Smith Nathan D. 
Published: October 2024

AbstractHarpetid and trinucleid trilobites share a similar and unusual morphology, the most striking feature of which is a wide, flattened cephalic brim with many pits or holes. This similarity was once interpreted as a sign that these two groups of trilobites were closely related, but in recent years it has instead been assumed that the ‘harpiform’ brim arose in both groups independently. However, relatedness and similarity can be difficult to disentangle in fossil taxa without close living relatives, and this assumption about the harpiform brim has never been explicitly tested. Our study re-evaluates the relationship between Harpetida and Trinucleioidea in order to test a longstanding assumption about trilobite relationships and as a case study in evaluating different kinds of morphological similarity in extinct groups. We inferred a new phylogenetic tree using parsimony methods and discrete morphological character data from a broad sampling of harpetids, trinucleids, and their relatives. Despite their gross morphological similarities, we found that harpetids and trinucleids were readily distinguished in our analyses, a result consistent with a hypothesis of multiple origins for the harpiform brim. By mapping brim-related characters across our new phylogeny, we identified a sequence of morphological innovations that arose in parallel in both groups and led ultimately in each case to the evolution of the harpiform brim. These results indicate that harpiform brims are a prime example of parallel evolution—the similar development of a morphological trait in distantly related taxa that nevertheless share a similar original morphology. In addition, our phylogeny supports the idea that trinucleids are specialized, harpiform asaphids, rather than an independent order of trilobites. We also provide new information on the relationships of the putative ‘basal-most’ members of Trinucleioidea, the Liostracinidae, and confirm recent assessments that this family is more distantly related to trinucleids.
The impact of pinning points on memorylessness in Lévy random bridges
Authors: Louriki Mohammed 
Published: October 2024

AbstractRandom bridges have gained significant attention in recent years due to their potential applications in various areas, particularly in information-based asset pricing models. This paper aims to explore the potential influence of the pinning point’s distribution on the memorylessness and stochastic dynamics of the bridge process. We introduce Lévy bridges with random length and random pinning points, and analyze their Markov property. Our study demonstrates that the Markov property of Lévy bridges depends on the nature of the distribution of their pinning points. The law of any random variables can be decomposed into singular continuous, discrete, and absolutely continuous parts with respect to the Lebesgue measure (Lebesgue’s decomposition theorem). We show that the Markov property holds when the pinning points’ law does not have an absolutely continuous part. Conversely, the Lévy bridge fails to exhibit Markovian behavior when the pinning point has an absolutely continuous part.
Association between dietary fatty acids and depressive symptoms in Chinese haemodialysis patients: a cross-sectional study
Authors: Zhang Shuang , Liu Shu-Xin , Wu Qi-Jun , Wang Zhi-Hong , Liu Hong , Xiao Ping , Lu Yan , Dong Cui , Meng Qing-Mei 
Published: October 2024

AbstractDepression is highly prevalent in haemodialysis patients, and diet might play an important role. Therefore, we conducted this cross-sectional study to determine the association between dietary fatty acids (FA) consumption and the prevalence of depression in maintenance haemodialysis (MHD) patients. Dietary intake was assessed using a validated FFQ between December 2021 and January 2022. The daily intake of dietary FA was categorised into three groups, and the lowest tertile was used as the reference category. Depression was assessed using the Patient Health Questionnaire-9. Logistic regression and restricted cubic spline (RCS) models were applied to assess the relationship between dietary FA intake and the prevalence of depression. As a result, after adjustment for potential confounders, a higher intake of total FA [odds ratio (OR)T3 vs. T1 = 1·59, 95 % confidence interval (CI) = 1·04, 2·46] and saturated fatty acids (SFA) (ORT3 vs. T1 = 1·83, 95 % CI = 1·19, 2·84) was associated with a higher prevalence of depressive symptoms. Significant positive linear trends were also observed (P < 0·05) except for SFA intake. Similarly, the prevalence of depression in MHD patients increased by 20% (OR = 1.20, 95% CI = 1.01–1.43) for each standard deviation increment in SFA intake. RCS analysis indicated an inverse U-shaped correlation between SFA and depression (Pnonlinear > 0·05). Additionally, the sensitivity analysis produced similar results. Furthermore, no statistically significant association was observed in the subgroup analysis with significant interaction. In conclusion, higher total dietary FA and SFA were positively associated with depressive symptoms among MHD patients. These findings inform future research exploring potential mechanism underlying the association between dietary FA and depressive symptoms in MHD patients.
Geographical disparities in temporal trends of low birth weight in Saskatchewan from 2002/2003 to 2021/2022: insights from a joinpoint regression analysis
Authors: Adeyinka Daniel A 
Published: October 2024

AbstractLow birth weight (LBW) is an important public health indicator that is associated with various negative health outcomes in infants. To effectively implement interventions that would improve health outcomes in children, it is important to understand both the historical trends and current levels of LBW rates. In this study, trends and regional differences in LBW rates in Saskatchewan from 2002/2003 to 2021/2022 were assessed. A joinpoint regression analysis was conducted using historical LBW rates, obtained from the Canadian Institute for Health Information database. Data were analysed using average percent change and average annual percent change. Spatial patterns and trends were identified using a choropleth map. From a provincial and national rate of 5.2% in 2002/2003, the LBW rate in Saskatchewan increased to 6.5% in 2021/2022, approaching the national rate of 6.8%. Over the 20-year period, average annual changes for Canada were 1.4% and 1.0% for Saskatchewan. There was a turning point in the study: 2004/2005 for Canada and 2011/2012 for Saskatchewan. Initially, Saskatchewan had stable LBW rates, increasing yearly by 0.1%, while the national rate was 5.7%. However, in recent years, Saskatchewan’s rate increased to 1.8% annually, surpassing the national rate of 0.9%. Geographical differences were also observed within Saskatchewan, with the Far North region having the highest LBW rate (9.2%), and the Central West region having the lowest rate (4.3%) in 2021/2022. The Central East, Regina Qu’Appelle, and southern Saskatchewan saw significant upwards trends in LBW rates between 2015/2016 and 2021/2022. There is an increasing trend in LBW rates in Canada and Saskatchewan, as well as geographical disparities within the province. The geographical disparities in LBW rates underscore the need for tailored interventions in high-risk regions in the province.
Doing social science with conservation: co-reflexivity on the project model in conservation
Authors: Schreer Viola , Thung Paul , Freeman Scott , Anirudh Namrata Biligeri , Campbell-Smith Gail , Eghenter Cristina , Spehar Stephanie 
Published: October 2024

Abstract
The conservation sector increasingly values reflexivity, in which professionals critically reflect on the social, institutional and political aspects of their work. Reflexivity offers diverse benefits, from enhancing individual performance to driving institutional transformation. However, integrating reflexivity into conservation practice remains challenging and is often confined to informal reflections with limited impact. To overcome this challenge, we introduce co-reflexivity, offering an alternative to the binary distinction between social science on or for conservation, which respectively produce critical outsider accounts of conservation or provide social science instruments for achieving conservation objectives. Instead, co-reflexivity is a form of social science with conservation, in which conservation professionals and social scientists jointly develop critical yet constructive perspectives on and approaches to conservation. We demonstrate the value of co-reflexivity by presenting a set of reflections on the project model, the dominant framework for conservation funding, which organizes conservation activity into distinct, target-oriented and temporally bounded units that can be funded, implemented and evaluated separately. Co-reflexivity helps reveal the diverse challenges that the project model creates for conservation practice, including for the adoption of reflexivity itself. Putting insights from social science research in dialogue with reflections from conservation professionals, we co-produce a critique of project-based conservation with both theoretical and practical implications. These cross-disciplinary conversations provide a case study of how co-reflexivity can enhance the conservation–social science relationship.
Deprescribing antipsychotics in patients with schizophrenia: findings from a specialized clinic
Authors: Nøstdal Alexander , Hilker Rikke , Halgren Christina , Speyer Helene , Nielsen Mette Ødegaard , Nielsen Jimmi 
Published: October 2024

AbstractBackgroundWhile antipsychotic medication reduces the risk of relapse for patients with schizophrenia, high prevalence of adverse effects results in low adherence. Lower doses of antipsychotics have been associated with increased level of function but also with increased risk of relapse. This study presents findings from a specialized deprescribing clinic. In addition, we aim to identify clinical predictors for relapse.MethodsPatients diagnosed with schizophrenia were referred to the clinic, which offers a six-month guided tapering program. Antipsychotic dose was reduced by 10% every four weeks. Patients were monitored closely for symptom progression or decrease in level of function, with defined cut-offs prompting a pause in or cessation of dose reduction.ResultsAfter 12 months, the antipsychotic dose was reduced from 404 (±320 mg) to 255 (±236 mg) chlorpromazine equivalent. Of the 88 patients included, 22 (27%) experienced relapse during the six-month tapering period, while 29 (37%) experienced relapse at the 12-month follow-up visit and nine patients were antipsychotic free. Patients who remained stable experienced a slightly increased level of functioning and markedly fewer side effects (p < 0.001). Following relapse, patients were clinically stabilized and showed an improved attitude toward antipsychotic medication. The predictive models were weak.ConclusionsWe show that most patients undergoing guided antipsychotic tapering remained stable after one year and improved in level of function, while most patients who relapsed were quickly stabilized. Our inability to create strong predictive models could be due to limitations in the study design, warranting future studies exploring tapering of antipsychotics in patients with schizophrenia.
Forecasting Partisan Collective Accountability during the 2024 US Presidential and Congressional Elections
Authors: Algara Carlos , Gomez Lisette , Headington Edward , Liu Hengjiang , Nigri Bianca 
Published: October 2024

ABSTRACT
This article considers both presidential approval and party brand differentials, as measured by the generic ballot, to forecast the 2024 US presidential and congressional elections. Although both variables are leveraged to forecast collective partisan election outcomes, we consider the variables together as distinct determinants of partisan fortunes at both the executive and legislative levels. First, using a novel time series of mass national opinion since 1937, we show that presidential approval and generic brands are distinct conceptual and empirical measures of mass public assessments of collective institutions. Second, in a series of fully specified models validated with out-of-sample predictions, we show that presidential approval is the main predictor of presidential elections, yet, perhaps surprisingly, the vast bulk of the incumbent party’s performance in congressional elections is explained by partisan brands. Lastly, we forecast the 2024 U.S. national elections and find that Republicans are well positioned to win back the White House this November. By contrast, our model forecasts control of both chambers of the US Congress to be essentially a tied contest.
State-Level Forecasts for the 2024 US Presidential Election: Trump Back with a Vengeance?
Authors: Mongrain Philippe , Nadeau Richard , Jérôme Bruno , Jérôme Véronique 
Published: October 2024

ABSTRACT
The outcome of the 2016 election made it abundantly clear that victory in US presidential contests depends on the Electoral College much more than on direct universal suffrage. This fact points to the importance of using state-level models to arrive at adequate predictions of winners and losers in US presidential elections. In fact, the use of a model disaggregated to the state level and focusing on three types of measures—namely, changes in the unemployment rate, presidential popularity, and indicators of long-term patterns in the regional strength of the Democratic and Republican parties—has in the past enabled us to produce fairly accurate forecasts of the number of Electoral College votes for the presidential candidates of the two major American parties. In this article, we bring various modifications to this model to improve its overall accuracy. With Joe Biden out of the race, this revised model predicts that Donald Trump will succeed in winning back the presidency with 341 electoral votes against 197 for Kamala Harris.
The Political Economy Model: Presidential Forecast for 2024
Authors: Tien Charles , Lewis-Beck Michael S. 
Published: October 2024

ABSTRACT
Our political economy model, as it has come to be called, has offered up forecasts of the American presidential election outcome since the early 1980s. The model, based on referendum theory, as measured by the job performance of the president and the economy (1948 to the present), yields a forecast from data available in the summer of the election year. We consider alternative specifications of this parsimonious model, examining the possible effects of other economic measures, Covid-19, and incumbency advantage on forecasting. The current point estimate of the core political economy model predicts the Democratic candidate will receive 48 percent of the two-party popular vote, which translates into a narrow Electoral College loss for the incumbent party. This point forecast, however, comes with a considerable amount of uncertainty. There is an 11-point spread around our point estimate, which effectively means we have a horserace on our hands, with both horses close to the finish line.
A Political History Forecast of the 2024 US Congressional Elections
Authors: Lewis-Beck Michael S. , Quinlan Stephen 
Published: October 2024

ABSTRACT
Statesman and scholar Alexis de Tocqueville (1876) once noted, “History is a gallery of pictures in which there are few originals and many copies.” In other words, history has a habit of repeating itself, and we can deduce cycles and patterns that likely will recur. Such stability and inertia should bode well for prediction. Nevertheless, when it comes to election forecasting, especially in the United States, most prognostications rely on short-term political fundamentals measuring macroeconomic performance or government or leader popularity. In this contribution, we adopt a structural approach but depart from existing literature by focusing on historical party and governance dynamics in the vein of de Tocqueville to establish whether they offer solid guidance regarding the performance of Democrats in US congressional elections. Our ex-post political history models provide solid predictions of which party will control Congress and the Democrats’ seat tally in each chamber between 1946 and 2022. This creates conditions to assume that political history may help us forecast Campaign 2024. Our study applied this political history model to predict the 2024 congressional elections. It forecast Democrats to lose control of the Senate with a net loss of three seats and estimated an exceptionally close race for House control, with the point estimate for the House suggesting that the Democrats would fall short of winning control.
Understanding Biden’s Exit and the 2024 Election: The State Presidential Approval/State Economy Model
Authors: Enns Peter K. , Colner Jonathan , Kumar Anusha , Lagodny Julius 
Published: October 2024

ABSTRACT
Our 2020 analysis correctly forecasted Joe Biden’s victory and the outcome of every state except Georgia. That forecast relied on economic data from 125 days prior to Election Day and presidential approval data from 104 days (or more) before the election. Since 2000, our model would have correctly forecasted the winner in 95% of all states. We updated our State Presidential Approval/State Economy Model for 2024. This article summarizes the model and its historical accuracy as well as new data updates. We then generate forecasts for the overall two-party popular vote, each state’s outcome, and the Electoral College winner for the 2024 US presidential election. One hundred days prior to Election Day, our model forecasts a split two-party popular vote (50.3% for Trump, 49.7% for Harris) but a notable Trump advantage in the Electoral College, with slightly less than a three-in-four chance that Trump wins the election. This Republican advantage 100 days prior to Election Day sheds light on Biden’s abrupt decision to drop out of the race and suggests that if Harris wins, she will have overcome extremely challenging fundamentals, and/or that Donald Trump and the Republican Party will have squandered a sizeable Electoral College advantage.
The application of organic fertilizers and farmers' income increase
Authors: Li Bowei , Zhang Congming , Qian Yanjun 
Published: October 2024

Abstract
The extension of organic fertilizers helps improve soil quality and reduces non-point source pollution caused by excessive use of fertilizers, however, whether the application of organic fertilizers (OFA) contributes to an increase in farmers' income is a matter of debate. This paper discussed how the application of soil-testing formulas and outsourcing services that some or all links of agricultural production to professional organizations moderate the income-increasing effect of OFA, and Multinomial Endogenous Switching Regression Model (MESR) is selected to do the empirical test. The results indicate that OFA with soil-testing formula and OFA with outsourcing service can effectively increase farmers' income, in specific, OFA with soil-testing formula increases the net monetary income of wheat growing on per hectare (ha) of land by 2150 Renminbi (RMB), and OFA with outsourcing service increases the net monetary income of wheat growing on per ha of land by 3950 RMB, however, OFA has no effectiveness on increasing farmers' income if neither soil-testing formulas nor outsourcing services is available. The influence mechanism of OFA to improve farmers' income is to increase crop yield, but OFA has no effectiveness on increasing the price of products. A systematic extension services including the extension of organic fertilizers, soil testing formulas and outsourcing services should be formed in the future.
Examining the Mid to Long‐Term Variability in Saturated Hydraulic Conductivity of Sandy Soils and Its Influencing Factors Under Constant Head Test in the Laboratory
Authors: Nikghalb Ashouri Saeed , Pittari Adrian , Moon Vicki , Shokri Ali 
Published: October 2024

AbstractSaturated hydraulic conductivity (Ks) is a crucial parameter that influences water flow in saturated soils, with applications in various fields such as surface water runoff, soil erosion, drainage, and solute transport. However, accurate determination of Ks is challenging due to temporal and spatial uncertainties. This study addresses the knowledge gap regarding the long‐term behavior of Ks in sandy soils with less than 10% fine particles. The research investigates the changes in Ks over a long period of constant head tests and examines the factors influencing its variation. Two sandy samples were tested using a hydraulic conductivity cell, and the hydraulic head and discharge were recorded for over 50 days. The results show a general decline in Ks throughout the test, except for brief periods of increase. At the end of both tests, there are noticeable reductions in the saturated hydraulic conductivities of the samples, with one sample being 96% and the other sample 91% less than the maximum recorded saturated hydraulic conductivity during the tests. Furthermore, the relationship between flow rate and hydraulic head gradient does not follow the expected linear correlation from Darcy's law, highlighting the complex nature of sandy soil saturated hydraulic conductivity. The investigation of soil properties in three different sections of the samples before and after the tests revealed a decrease in the percentage of fine particles and a shift in specific gravity from the bottom to the top of the sample, suggesting particle migration along the flow direction. Factors such as clogging by fine particles and pore pressure variation contribute to the changes in Ks. The findings of this research show the importance of considering changes of saturated hydraulic conductivity during constant‐head laboratory tests. Therefore, this study provides evidence for the requirement to further assess the laboratory methods for measurement of the saturated hydraulic conductivity in sandy soil mixtures.