bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of recent level changes in Lake Van using water balance, LSTM and ANN approaches
Authors: Aydin Mehmet Cihan , Gelberi Gamze , Ulu Ali Emre
Published: February 2024

Lake Van, the greatest soda water lake in the world located in the east of Turkey, has always attracted the attention of researchers due to its significant water level changes. Identifying the causes for these level changes is very important with respect to the scientific world and the sustainability of the ecological balance. Although extensive research has been carried out on the water level changes in Lake Van in the past years, no any study exists which analyzes the recent level changes. In this study, recent water level changes in Van Lake were analyzed using two different methods, and the results were evaluated. First, the water level changes during the period 2010–2020 were examined through the meteorological and hydrological data collected by the water budget method. Second, the water level changes for 2000–2020 were estimated using the LSTM and NAR neural networks. In the light of the results, reasons for the recent level changes in Lake Van were discussed. It was concluded that the changes, especially those occurred after 2014, may be hydrometeorological. However, the unusual level changes between 2010 and 2013 cannot be explained by water balance, may be tectonic or volcanic origin. The findings of this study indicate that these changes may continue in the future, and therefore, further research with different disciplines is needed on this subject.
Modeling fluid flow in fractured porous media: a comparative analysis between Darcy–Darcy model and Stokes–Brinkman model
Authors: Dudun Anireju , Feng Yin
Published: February 2024

There are limited comparative studies on modeling fluid transport in fractured porous media. Hence, this paper systematically compares the steady-state creeping flow Stokes–Brinkman and Darcy–Darcy models for computational efficiency and accuracy. Sensitivity analyses were also conducted on the effect of fracture orientations, fracture sizes, mesh resolution, and fractures with Local Grid Refinement (LGR) under the FEniCS computational framework. Both models were validated numerically, and the accuracy of their solution is compared using the R-squared metric and L2 norm estimates. Key results showed that both models have similar pressure and velocity field solutions for a given fracture orientation. The computational time required for solving the Stokes–Brinkman models for a single fracture case was unusually lower than that of the Darcy–Darcy model when the pressure and velocity terms in the Darcy–Darcy model were solved simultaneously using two equations, contrary to where only one equation solves for the pressure and the velocity is obtained by projecting the gradient of pressure onto a vector space. The Stokes–Brinkman model is more sensitive to mesh resolution, and as a result, the Darcy–Darcy model tends to be more accurate than the Stokes–Brinkman model at low resolutions. Local Grid Refinement (LGR) can improve the Stokes–Brinkman model's accuracy at low mesh resolution. Furthermore, both models showed similar results when compared for complex fracture systems such as multiple fracture cases: interconnecting and isolated fractured porous media systems under low-velocity and steady-state creeping flow conditions. The FEniCS code in this paper is shared for future researchers to reproduce results or extend the research work.
Prevalence of Adverse Childhood Experiences in Adolescents with Special Educational and Care Needs in the Netherlands: A Case-File Study of Three Special Educational and Care Settings
Authors: Mercera Gabriëlle , Vervoort-Schel Jessica , Offerman Evelyne , Pronk Sanne , Wissink Inge , Lindauer Ramón
Published: February 2024

To date, Adverse Childhood Experiences (ACEs) in adolescents with special educational and care needs have received little attention as an important risk factor for their behavioral, emotional, and learning problems. This study provides insight into ACE prevalence and family risk factors in three Dutch special educational and care settings for vulnerable school-aged youth. 268 adolescents (10–18 years old) with severe and persistent problems at individual and family level, from a special educational setting (setting 1; n = 59), a residential care setting (setting 2; n = 86) and an alternative educational setting (setting 3; n = 123) were included. A retrospective cross-sectional study design was used. Data were collected between 2016 and 2019 through structured case-file analysis. A substantial proportion of the adolescents in all settings experienced at least one ACE, with 69.5% in setting 1, 84.9% in setting 2 and 95.1% in setting 3. Family risk factors were relatively common, among which a limited social network in all settings (20–50%) and debts in setting 2 and 3 (25–40%). The substantial ACE prevalence underlines the need for early ACE awareness. Trauma-informed care and education are needed to adequately understand trauma-related behaviors, prevent retraumatization, and enhance learning and healthy development. Given that ACEs regarding household dysfunction and family risk factors seem to be common in adolescents with special educational and care needs, family centered approaches should be implemented as well in the interest of lifelong health and well-being for both adolescents and their families.
Genre: generative multi-turn question answering with contrastive learning for entity–relation extraction
Authors: Wang Lulu , Yu Kai , Wumaier Aishan , Zhang Peng , Yibulayin Tuergen , Wu Xi , Gong Jibing , Maimaiti Maihemuti
Published: February 2024

Extractive approaches have been the mainstream paradigm for identifying overlapping entity–relation extraction. However, limited by their inherently methodological flaws, which hardly deal with three issues: hierarchical dependent entity–relations, implicit entity–relations, and entity normalization. Recent advances have proposed an effective solution based on generative language models, which cast entity–relation extraction as a sequence-to-sequence text generation task. Inspired by the observation that humans learn by getting to the bottom of things, we propose a novel framework, namely GenRE, Generative multi-turn question answering with contrastive learning for entity–relation extraction. Specifically, a template-based question prompt generation first is designed to answer in different turns. We then formulate entity–relation extraction as a generative question answering task based on the general language model instead of span-based machine reading comprehension. Meanwhile, the contrastive learning strategy in fine-tuning is introduced to add negative samples to mitigate the exposure bias inherent in generative models. Our extensive experiments demonstrate that GenRE performs competitively on two public datasets and a custom dataset, highlighting its superiority in entity normalization and implicit entity–relation extraction. (The code is available at https://github.com/lovelyllwang/GenRE).
Enhancing sustainability for pavement maintenance decision-making through image processing-based distress detection
Authors: fawzy Mohamed Mahmoud , shrakawy Ahmed shawky el , Hassan Abbas atef , khalifa Yasser ali
Published: February 2024

Road maintenance sustainability entails implementing practices that reduce the impact of road accident. while simultaneously ensuring the durability and functionality of the road infrastructure. Pavement distress is a major concern for transportation agencies as it affects the safety and comfort of road users. This paper presents a novel approach for prioritizing pavement distress through the application of image processing techniques and the Analytic Hierarchy Process (AHP). The proposed method involves capturing images of the pavement surface using a high-resolution camera and analyzing them using image processing algorithms. The images are processed to identify different types of pavement distress such as cracks, potholes, and rutting. The severity of each type of distress is then quantified. AHP is utilized to prioritize the identified distress based on its severity and impact on road users. The proposed approach has been tested on real-world pavement images, and the results demonstrate its effectiveness in accurately identifying and prioritizing pavement distress. This method can assist transportation agencies in making informed decisions about maintenance and repair activities, leading to improved road safety and reduced maintenance costs. This automated method achieved an accuracy percentage of about 95%.
Factors associated with delirium in a real-world acute-care setting: analysis considering the interdependence of clinical variables with the frailty syndrome
Authors: Ticinesi Andrea , Parise Alberto , Delmonte Davide , Coppi Chiara , Prati Beatrice , Cerundolo Nicoletta , Guerra Angela , Nouvenne Antonio , Meschi Tiziana
Published: February 2024

Purpose

Delirium risk assessment in the acute-care setting generally does not account for frailty. The objective of this retrospective study was to identify factors associated with delirium, considering the interdependency of clinical variables with frailty syndrome in complex older patients.

Methods

The clinical records of 587 participants (248 M, median age 84) were reviewed, collecting clinical, anamnestic and pharmacological data. Frailty syndrome was assessed with the Clinical Frailty Scale (CFS). Delirium was the main study endpoint. The correlations of the considered anamnestic and clinical variables with delirium and its subtypes were investigated selecting only those variables not showing a high overlap with frailty. Correlations associated with a 25% excess of frequency of delirium in comparison with the average of the population were considered as statistically significant.

Results

Delirium was detected in 117 (20%) participants. The presence of one among age > 85 years old, CFS > 4 and invasive devices explained 95% of delirium cases. The main factors maximizing delirium incidence at the individual level were dementia, other psychiatric illness, chronic antipsychotic treatment, and invasive devices. The coexistence of three of these parameters was associated with a peak frequency of delirium, ranging from 57 to 61%, mostly hypoactive forms.

Conclusions

In acute-care wards, frailty exhibited a strong association with delirium during hospitalization, while at the individual level, dementia and the use of antipsychotics remained important risk factors. Modern clinical prediction tools for delirium should account for frailty syndrome.
Reflexionsfähigkeit von Physiklehramtsstudierenden: Ein Online-Self-Assessment mit Feedback
Authors: Weißbach Anna , Kulgemeyer Christoph
Published: February 2024

Unterrichtsreflexion ist von zentraler Bedeutung für die Verbesserung von Unterricht und die Professionalisierung von Lehrkräften. Die Reflexionsfähigkeit Studierender ist allerdings häufig nur schwach ausgeprägt. In diesem Beitrag wird ein Testinstrument mit Assessment-Feedback vorgestellt, das Studierenden eine Selbsteinschätzung ihrer Reflexionsfähigkeit ermöglicht und das Ziel hat, Assessment-Feedback als Ausgangspunkt für Förderung zu nutzen. Dazu wird die Interpretation der Testwerte als Maß für die Reflexionsfähigkeit argumentbasiert validiert. In Teilstudie 1 (inhaltliche Validität) wird die Passung zwischen Testinstrument und theoretischer Modellierung des Konstrukts diskutiert. In Teilstudie 2 wird die kognitive Validität mit Think-Aloud-Protokollen der Testbearbeitung von N = 7 Studierenden untersucht. In Teilstudie 3 (externe Validität) führen N = 39 Studierende zusätzlich einen etablierten Reflexionsperformanztest durch, der es ermöglicht, Reflexionen in einem authentischeren, aber standardisierten Format zu erfassen. Teilstudie 4 beschäftigt sich mit der Generalisierbarkeit der Ergebnisse über das Bachelor- und Masterstudium. Dazu werden N = 136 Bearbeitungen von Studierenden dieser Studienphasen berücksichtigt und in Bezug auf statistische Kenngrößen (z. B. Lösungshäufigkeit) verglichen. In Teilstudie 5 werden zur Untersuchung der konsequentiellen Validität N = 12 Studierende in leitfadengestützten Interviews zu ihrer Interpretation des Assessment-Feedbacks befragt. Insgesamt können starke Argumente für die Validität der Testwertinterpretation und die Eignung des Instruments gefunden werden. Geringe Einschränkungen liegen bezüglich der inhaltlichen Validität in der Beschränkung auf den Themenbereich Mechanik und bezüglich der konsequentiellen Validität in der Vorstellung weniger Studierender, das Testinstrument biete Beispielaufgaben für universitäre Prüfungen. Das Instrument wird online frei zur Verfügung gestellt, um insbesondere in Praxisphasen der Lehramtsausbildung genutzt werden zu können.
Efficacy of sterilants to kill Erwinia amylovora
Authors: Horner Mary B. , Newland Jayne , McCourt Tyler
Published: February 2024

Fire blight, caused by Erwinia amylovora, can be spread through orchards and nurseries because of poor sanitation practices such as contaminated secateurs. This research investigated the efficacy of 12 commercial sterilants at varying concentrations to kill E. amylovora on secateurs. Secateurs were dipped into an Erwinia amylovora inoculum solution (106 colony forming units/mL), and then misted with a test sterilant. After 10 s, secateurs were swabbed and plated onto Kings B agar plate, incubated at 26 °C for 48 h and bacterial colonies counted. Sterilants were also assessed for cotton bleaching and metal corrosion. Best performing sterilants were then tested as described above by cutting through infected plant material containing sticky bacterial ooze as inoculum. Each of the sterilants tested (methylated spirits (95% and 70%), sodium hypochlorite (NaOCl) (1%, 0.5%, 0.135%), Bac-Stop/benzalkonium chloride (2%, 1%), Virkon™ (label rate), Dettol (50%, 10%, 1%, 0.1%), and HarvestCide® gel (0.1%, 0.5%, 1%)) were found to be effective to kill E. amylovora on inoculum-coated secateurs. The best performing sterilants (methylated spirits, Dettol, HarvestCide gel, NaOCl) were also effective in killing E. amylovora on infected plant material when compared with the untreated control. Most sterilants, except methylated spirits or Dettol, caused corrosion of metal and bleaching of cotton. Each of the tested sterilants were found to be effective to kill Erwinia amylovora on inoculum-coated secateurs and inoculum in plant material and bacterial ooze. Many of the best performing sterilants were likely to damage tools over time and cause bleaching on clothing. However, Dettol or methylated spirits did not cause metal corrosion or bleaching.
Betwixt and between student and professional identities: UK medical students during COVID times
Authors: Polidano Kay , Wenning Brianne , Mallen Christian D. , Dikomitis Lisa ,   the Q-COVID-19 Group
Published: February 2024

The COVID-19 pandemic lockdown in Spring 2020 brought about unprecedented disruption to medical education in the United Kingdom (UK). Medical students were encouraged to take up paid roles in the National Health Service to help with workforce shortages. This article explores medical students’ views and experiences of the COVID-19 pandemic vis-à-vis their professional identity formation. Semi-structured interviews were conducted with 22 medical students from all five undergraduate years in one UK medical school, between April and June 2020. Three themes were generated: (1) disruption to medical education involving suspension of clinical placements, cancellation of assessments and ceremonial markers; (2) decision-making around joining the clinical workforce, decisions which were influenced by students’ sense of professional obligation, perceived personal gains, and health and safety considerations; (3) experiences of working in clinical settings during the pandemic, including reflections about managing risks and challenges, learning on the job and becoming a better doctor. The findings provide evidence that the UK’s first lockdown destabilised many medical students’ expectations tied to their educational and career trajectory, requiring them to improvise to address gaps in learning and professional development. Taking on a paid healthcare role catapulted them into a liminal period, working in a space ‘betwixt and between’ a medical student and healthcare professional. This swift readjustment of roles and responsibilities accelerated their identity formation as ‘future doctors’. Support for medical students around negotiating such dual role is important in present and future public health crises.
The interplay between competitive advantage and sustainability in the wine industry: a bibliometric and systematic review
Authors: Martínez-Falcó Javier , Sánchez-García Eduardo , Marco-Lajara Bartolomé , Georgantzis Nikolaos
Published: February 2024

The objective of this research is to analyze the knowledge structure of the academic literature indexed in the Core Collection of the Web of Science (WoS) on gaining a competitive advantage through sustainability in the wine industry, from the first article registered in 2009 to 2023, in order to identify the latest trends in the topics under study. For this purpose, a bibliometric and systematic analysis of the literature was carried out. First, for the quantitative analysis of the scientific production, the bibliometric study was conducted, using the WoS database for data collection and the VosViewer and Bibliometrix applications to create the network maps. Second, once the bibliography had been examined quantitatively, the content analysis was performed following the PRISMA methodology. The results show, among other aspects, the uneven pace of growth of the scientific production studied since 2009, that innovation, wine tourism, carbon footprint, dynamic capabilities and climate change are among the current major topics of study, as well as the predominance of Italy, Spain, the United States and Australia in terms of scientific production in the subject matter. There are several justifications for the originality of this study, given that, first, it contributes to the understanding of the academic literature and the identification of the most recent trends in the field and, second, to the best of the authors' knowledge, there are no previous bibliometric studies that have addressed the topic analyzed.
Assessment of depression and internalized-stigma among adult asthma patients in Bangladesh: a cross-sectional study
Authors: Ahmed-Chowdhury Saquib , Ahmad Sohail , Sarker Md. Moklesur Rahman , Ismail Nahlah Elkudssiah
Published: February 2024

Objective

Suboptimal asthma control among patients is associated with psychosocial factors, including depression and stigma, hindering effective asthma management. This study aimed to assess depressive symptoms and internalized stigma among adult asthma patients while investigating their relationships with sociodemographic and asthma-related medical factors.

Methods

In this cross-sectional study, 325 adult asthma patients (aged > 18 years old) were recruited from the National Asthma Centre in Dhaka, Bangladesh, using a researcher-administered questionnaire and convenience sampling. The questionnaire included sections on sociodemographic characteristics, medical data, the 9-item Patient Health Questionnaire (PHQ-9) to assess depressive symptoms, and a 22-item stigma scale to assess internalized stigma. Data were analyzed using descriptive and inferential statistics.

Results

The majority of participants were aged 18–40 years (54.2%), male (53.5%), from rural areas (50.8%), with a monthly family income of < US$250 (55.1%), and diagnosed with asthma for > 5 years (46.5%). The mean PHQ-9 score was 7.36 (± 6), indicating mild depressive symptoms, and the internalized stigma score was 62.2 (± 10.26), indicating moderate internalized stigma. Depression and stigma varied significantly across several factors, including age, education, ED visits, hospitalizations for asthma, number of asthma medicines, home nebulizer use, PEF rate, BMI, comorbidities, and asthma symptom control (p < 0.05). Stigma was correlated with depression and negatively correlated with age and years since asthma diagnosis (p < 0.01).

Conclusion

This study highlights associations between depressive symptoms, internalized stigma, and various sociodemographic and medical factors among asthma patients. Notably, stigma was higher among younger adults and recently diagnosed patients. Effective interventions are needed to mitigate stigma and depression in this patient population.
Generative approaches for solving tangram puzzles
Authors: Yamada Fernanda Miyuki , Batagelo Harlen Costa , Gois João Paulo , Takahashi Hiroki
Published: February 2024

The Tangram is a dissection puzzle composed of seven polygonal pieces that can form different patterns. Solving the Tangram is an irregular shape packing problem known to be NP-hard. This paper investigates the application of four deep-learning architectures—Convolutional Autoencoder, Variational Autoencoder, U-Net, and Generative Adversarial Network—specifically designed for solving Tangram puzzles. We explore the potential of these architectures in learning the complex spatial relationships inherent in Tangram configurations. Our experiments show that the Generative Adversarial Network competes well with other architectures and converges considerably faster. We further prove that traditional evaluation metrics based on pixel accuracy often fail in assessing the visual quality of the generated Tangram solutions. We introduce a loss function based on a Weighted Mean Absolute Error that prioritizes pixels representing inter-piece sections over those covered by individual pieces. Extending this loss function, we propose a novel evaluation metric as a more fitting measure for assessing Tangram solutions compared to traditional metrics. This investigation advances our understanding of the capabilities of artificial intelligence in complex geometrical problem domains.
Perspectives on interfacial thermal resistance of 2D materials: Raman characterization and underlying physics
Authors: Liu Jing , Al Keyyam Ibrahim , Xie Yangsu , Wang Xinwei
Published: February 2024

Interfacial thermal resistance plays a crucial role in efficient heat dissipation in modern electronic devices. It is critical to understand the interfacial thermal transport from both experiments and underlying physics. This review is focused on the transient opto-thermal Raman-based techniques for measuring the interfacial thermal resistance between 2D materials and substrate. This transient idea eliminates the use of laser absorption and absolute temperature rise data, therefore provides some of the highest level measurement accuracy and physics understanding. Physical concepts and perspectives are given for the time-domain differential Raman (TD-Raman), frequency-resolved Raman (FR-Raman), energy transport state-resolved Raman (ET-Raman), frequency domain ET-Raman (FET-Raman), as well as laser flash Raman and dual-wavelength laser flash Raman techniques. The thermal nonequilibrium between optical and acoustic phonons, as well as hot carrier diffusion must be considered for extremely small domain characterization of interfacial thermal resistance. To have a better understanding of phonon transport across material interfaces, we introduce a new concept termed effective interface energy transmission velocity. It is very striking that many reported interfaces have an almost constant energy transmission velocity over a wide temperature range. This physics consideration is inspired by the thermal reffusivity theory, which is effective for analyzing structure-phonon scattering. We expect the effective interface energy transmission velocity to give an intrinsic picture of the transmission of energy carriers, unaltered by the influence of their capacity to carry heat.
Random Graphs and Complex Networks
Authors: van der Hofstad Remco
Published: February 2024

Complex networks are key to describing the connected nature of the society that we live in. This book, the second of two volumes, describes the local structure of random graph models for real-world networks and determines when these models have a giant component and when they are small-, and ultra-small, worlds. This is the first book to cover the theory and implications of local convergence, a crucial technique in the analysis of sparse random graphs. Suitable as a resource for researchers and PhD-level courses, it uses examples of real-world networks, such as the Internet and citation networks, as motivation for the models that are discussed, and includes exercises at the end of each chapter to develop intuition. The book closes with an extensive discussion of related models and problems that demonstratemodern approaches to network theory, such as community structure and directed models.
Interdisciplinary lessons and recommendations for the evaluation of replicability in behavioral sciences
Authors: Brown Mitch , Sacco Donald F.
Published: February 2024

As the scientific community becomes aware of low replicability rates in the extant literature, peer-reviewed journals have begun implementing initiatives with the goal of improving replicability. Such initiatives center around various rules to which authors must adhere to demonstrate their engagement in best practices. Preliminary evidence in the psychological science literature demonstrates a degree of efficacy in these initiatives. With such efficacy in place, it would be advantageous for other fields of behavioral sciences to adopt similar measures. This letter provides a discussion on lessons learned from psychological science while similarly addressing the unique challenges of other sciences to adopt measures that would be most appropriate for their field. We offer broad considerations for peer-reviewed journals in their implementation of specific policies and recommend that governing bodies of science prioritize the funding of research that addresses these measures.
NOTES ON THE TEXT OF VARRO'S DE LINGVA LATINA
Authors: Deufert Marcus , Graf Vincent , Ottaviano Silvia , Protze Kevin
Published: February 2024

This article discusses the text of seven passages in the etymological books 5–7 of Varro's De lingua Latina, and proposes new conjectures for all of them. The discussions are of direct relevance to the interpretation of fragments and testimonies of lost Latin authors quoted by Varro: the scenic poets Naevius, Pacuvius, Caecilius Statius, Juventius and Atilius, and the grammarian Aurelius Opillus. The starting point for the discussions is the new Oxford edition of Varro's De lingua Latina by Wolfgang de Melo.
The White Fraud: White Elephants, Siam, and Comparative Racialization
Authors: BULLEN ROSS
Published: February 2024

In this paper I examine P. T. Barnum's attempt to bring the first “sacred white elephant” to America, and his subsequent “white elephant war” with rival showman Adam Forepaugh, through the lens of Afro-Asian comparative racialization. I look at several accounts of white elephants that describe their skin color in terms of the US's Black/white race dichotomy and ask why this animal was a popular figure for examining the US's shifting attitude toward race and transpacific imperialism in the late nineteenth century. By reading the “white elephant war” through a comparative framework, I argue that the heterogeneous histories of both African American and Asian racialization inhered and intersected in this specific instance of racial comparison, while tracking the overlaps and oversights that this analysis reveals.
Does Central Bank Tone Move Asset Prices?
Authors: Schmeling Maik , Wagner Christian
Published: February 2024

This article shows that changes in the tone of central bank communication have a significant effect on asset prices. Tone captures how the central bank frames economic fundamentals and its monetary policy. A positive tone surprise is associated with increases in stock prices and interest rates, whereas credit spreads and volatility risk premia decrease. These tone effects are robust to controlling for policy actions as well as for conventional measures of monetary policy shocks. Our results suggest that communication tone is a powerful instrument of monetary policy, which affects risk premia embedded in asset prices.
Identifying medium- and large-sized mammal species sensitive to anthropogenic impacts for monitoring in subtropical montane forests
Authors: Bardavid Sofía , Rivera Luis , Martinuzzi Sebastián , Pidgeon Anna M , Radeloff Volker C , Politi Natalia
Published: February 2024

Medium- and large-sized mammals play important roles in maintaining forest ecosystem functions, and these functions often diminish when mammal species are depleted by human activities. Understanding the sensitivity or tolerance of mammal species to human pressure and detecting species changes through monitoring programmes can inform appropriate management decisions. The objective of our study was to identify medium- and large-sized mammal species that can be included in a monitoring programme in the Southern Yungas of Argentina. We used occupancy modelling to estimate the probability of habitat use (ψ) of 13 of 25 mammal species detected by 165 camera traps placed in forests across a range of human footprint index (HFI) values. As defined by the HFI, 54% of the study area is wilderness. The probabilities of habitat use of two mammal species were significantly associated with the HFI: the lowland tapir (Tapirus terrestris; ψ = 0.33, range = 0.22–0.50) was inversely associated with HFI values, whereas the grey brocket deer (Mazama gouazoubira; ψ = 0.79, range = 0.67–0.87) was positively associated with the HFI. Monitoring the probability of habitat use of the sensitive species (lowland tapir) could help us to detect changes in areas experiencing anthropogenic impacts before they cause extirpation, whereas the high probability of the habitat use values of the tolerant species (grey brocket deer) might indicate that anthropogenic impacts are strongly influencing habitat, signalling that mitigation strategies might be warranted. The Southern Yungas retains an intact mammal fauna, and we showed that the HFI is useful for monitoring anthropogenic impacts on these mammals. There are still opportunities to develop conservation strategies to minimize threats to mammal species in the region by implementing a monitoring programme with the proposed species.
Relationship between extreme precipitation and acute gastrointestinal illness in Toronto, Ontario, 2012–2022
Authors: Ethan Crystal J. , Sanchez Johanna , Grant Lauren , Tustin Jordan , Young Ian
Published: February 2024

Extreme precipitation events are occurring more intensely in Canada. This can contaminate water sources with enteric pathogens, potentially increasing the risk of acute gastrointestinal illness. This study aimed to investigate the relationship between extreme precipitation and emergency department (ED) visits for acute gastrointestinal illness in Toronto from 2012 to 2022. Distributed lag non-linear models were constructed on ED visit counts with a Quasi Poisson distribution. Extreme precipitation was modelled as a 21-day lag variable, with a linear relationship assumed at levels ≧95th percentile. Separate models were also conducted on season-specific data sets. Daily precipitation and gastrointestinal illness ED visits ranged between 0 to 126 mm, and 12 to 180 visits respectively. Overall, a 10-mm increase in precipitation >95th percentile had no significant relationship with the risk of ED visits. However, stratification by seasons revealed significant relationships during spring (lags 1–19, peak at lag 14 RR = 1.04; 95% CI: 1.03, 1.06); the overall cumulative effect across the 21-day lag was also significant (RR = 1.94; 95% CI: 1.47, 2.57). Extreme precipitation has a seasonal effect on gastrointestinal health outcomes in Toronto city, suggesting varying levels of enteric pathogen exposures through drinking water or other environmental pathway during different seasons.
From NeurODEs to AutoencODEs: A mean-field control framework for width-varying neural networks
Authors: Cipriani Cristina , Fornasier Massimo , Scagliotti Alessandro
Published: February 2024

The connection between Residual Neural Networks (ResNets) and continuous-time control systems (known as NeurODEs) has led to a mathematical analysis of neural networks, which has provided interesting results of both theoretical and practical significance. However, by construction, NeurODEs have been limited to describing constant-width layers, making them unsuitable for modelling deep learning architectures with layers of variable width. In this paper, we propose a continuous-time Autoencoder, which we call AutoencODE, based on a modification of the controlled field that drives the dynamics. This adaptation enables the extension of the mean-field control framework originally devised for conventional NeurODEs. In this setting, we tackle the case of low Tikhonov regularisation, resulting in potentially non-convex cost landscapes. While the global results obtained for high Tikhonov regularisation may not hold globally, we show that many of them can be recovered in regions where the loss function is locally convex. Inspired by our theoretical findings, we develop a training method tailored to this specific type of Autoencoders with residual connections, and we validate our approach through numerical experiments conducted on various examples.
Bosentan in the treatment of persistent pulmonary hypertension in newborns: a systematic review and meta-analysis
Authors: Gao Ning , Lv Yuanyuan , Cui Yanbin , Wang Pengchun , He Xin
Published: February 2024

Background:

Persistent pulmonary hypertension of the newborn is a life-threatening condition that affects about 1–2 per 1,000 live births worldwide. Bosentan is an oral dual endothelin receptor antagonist that may have a beneficial effect on persistent pulmonary hypertension of the newborn by reducing pulmonary vascular resistance and improving oxygenation. However, its role in persistent pulmonary hypertension of the newborn remains unclear.

Objectives:

To systematically evaluate the efficacy and safety of bosentan as an adjuvant therapy for persistent pulmonary hypertension of the newborn in newborns.

Methods:

We searched six English and two Chinese databases from their inception to 1 January 2023 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We included randomised controlled trials and retrospective studies that compared bosentan with placebo or other drugs for persistent pulmonary hypertension of the newborn in newborns. We performed a meta-analysis using random-effects models and assessed the risk of bias and heterogeneity in the included studies.

Results:

We included 10 studies with a total of 550 participants. Bosentan significantly reduced the treatment failure rate (relative risk = 0.25, P < 0.001), pulmonary artery pressure (mean difference = −11.79, P < 0.001), and length of hospital stay (mean difference = −1.04, P = 0.003), and increased the partial pressure of oxygen (mean difference = 10.02, P < 0.001) and blood oxygen saturation (SpO2) (mean difference = 8.24, P < 0.001) compared with a placebo or other drugs. The occurrence of adverse reactions was not significantly different between bosentan and a placebo or other drugs.

Conclusions:

Bosentan is effective in the treatment of persistent pulmonary hypertension of the newborn but adverse reactions such as abnormal liver function should be observed when using it.
Staff Rides as Pedagogical Practice
Authors: Lee So Jin , Szarejko Andrew A.
Published: February 2024

Political science instructors have started to make use of the “staff ride”—that is, the combined study of a military campaign, structured visits to related sites, and after-action analysis. Our study is the first examination of the potential utility of this pedagogical tool in civilian political science programs. Although the specific knowledge and skills that any given staff ride promotes depend on its content and structure, the potential benefits include four student learning outcomes: (1) staff rides show students how we might draw lessons from the past and apply them to present or future problems; (2) students may derive an enhanced ability to empathize with military and civilian decision makers; (3) staff rides can highlight the normative stakes in politics; and (4) they can foster connections among the participants. This article describes potential benefits of a staff ride, provides detailed instructional models based on the Battle of Gettysburg and the Tet Offensive, and considers ways to replicate these experiences in more accessible formats.
Machine learning algorithm to extract properties of ATE phantoms from microwave measurements
Authors: Mattsson Viktor , Perez Mauricio D. , Joseph Laya , Augustine Robin
Published: February 2024

The Muscle Analyzer System (MAS) project wants to create a standalone microwave device that can assess the muscle quality, called the MAS device. To achieve that an algorithm that can derive the properties of skin, fat and muscle from the measurements is needed. This paper presents a machine learning algorithm that aims to do precisely that. The algorithm relies on first predicting the skin using the data from the MAS device, then predicting the fat again using the data from the MAS but also the predicted skin value and lastly the muscle is predicted using the microwave data together with the skin and fat predictions. Data have been collected in phantom experiments, materials that mimick the dielectric properties of human tissues. The algorithm is trained to predict the properties of said phantoms. The results show that the prediction for skin thickness works well, the fat thickness prediction is okay but the muscle prediction struggles. This is partly due to the error from the skin and fat layers are propagated to the muscle layer and partly because the muscle layer is farthest away from the sensor, which makes getting information from that layer harder.
Somatic disease burden and depression risk in late life: a community-based study
Authors: Triolo Federico , Vetrano Davide Liborio , Sjöberg Linnea , Calderón-Larrañaga Amaia , Belvederi Murri Martino , Fratiglioni Laura , Dekhtyar Serhiy
Published: February 2024

Aims

Co-occurring somatic diseases exhibit complex clinical profiles, which can differentially impact the development of late-life depression. Within a community-based cohort, we aimed to explore the association between somatic disease burden, both in terms of the number of diseases and their patterns, and the incidence of depression in older people.

Methods

We analysed longitudinal data of depression- and dementia-free individuals aged 60+ years from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression diagnoses were clinically ascertained following the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision over a 15-year follow-up. Somatic disease burden was assessed at baseline through a comprehensive list of chronic diseases obtained by combining information from clinical examinations, medication reviews and national registers and operationalized as (i) disease count and (ii) patterns of co-occurring diseases from latent class analysis. The association of somatic disease burden with depression incidence was investigated using Cox models, accounting for sociodemographic, lifestyle and clinical factors.

Results

The analytical sample comprised 2904 people (mean age, 73.2 [standard deviation (SD), 10.5]; female, 63.1%). Over the follow-up (mean length, 9.6 years [SD, 4 years]), 225 depression cases were detected. Each additional disease was associated with the occurrence of any depression in a dose–response manner (hazard ratio [HR], 1.16; 95% confidence interval [CI]: 1.08, 1.24). As for disease patterns, individuals presenting with sensory/anaemia (HR, 1.91; 95% CI: 1.03, 3.53), thyroid/musculoskeletal (HR, 1.90; 95% CI: 1.06, 3.39) and cardiometabolic (HR, 2.77; 95% CI: 1.40, 5.46) patterns exhibited with higher depression hazards, compared to those without 2+ diseases (multimorbidity). In the subsample of multimorbid individuals (85%), only the cardiometabolic pattern remained associated with a higher depression hazard compared to the unspecific pattern (HR, 1.71; 95% CI: 1.02, 2.84).

Conclusions

Both number and patterns of co-occurring somatic diseases are associated with an increased risk of late-life depression. Mental health should be closely monitored among older adults with high somatic burden, especially if affected by cardiometabolic multimorbidity.
FY‐4A/AGRI Infrared Brightness Temperature Estimation of Precipitation Based on Multi‐Model Ensemble Learning
Authors: Wang Gen , Han Wei , Ye Song , Yuan Song , Wang Jing , Xie Feng
Published: February 2024

Satellite infrared detectors cannot penetrate clouds, especially precipitating clouds. Improving precipitation estimation accuracy based on infrared brightness temperature has always been important but challenging. In this paper, based on the infrared brightness temperature of the Advanced Geosynchronous Radiation Imager (AGRI) onboard China's Feng‐Yun 4A satellite, we develop and evaluate a new precipitation estimation method. First, using static data, physical characteristics of clouds, cloud image texture features, temporal motion features, and AGRI infrared channel brightness temperature, we construct features for a machine learning model. Then, we develop precipitation estimation methods. Precipitation is estimated in two steps: classification and regression. We employ a random forest classification model to identify whether there is precipitation in a given field of view. If there is precipitation, a multi‐model ensemble regression learning method is used to estimate the areas with this precipitation. The ensemble learning method uses convex optimization to integrate prediction results based on the optimization of hyperparameters of five basic models (i.e., those of random forest, XGBoost, LightGBM, decision tree, and extra tree models). Furthermore, two regression stacking ensemble models—the Least Absolute Shrinkage and Selection Operator (herein referred to as Stacking1‐LASSO) and K‐nearest neighbor (herein referred to as Stacking2‐KNN)—are used to predict the results of the aforementioned basic models. The results of basic models are used as inputs of these two stacking models. Finally, based on the Integrated Multi‐satellitE Retrievals for GPM (IMERG) precipitation product and rain gauge precipitation data, we conduct precipitation estimation experiments and evaluate our methods. The results show that ensemble learning models have greater accuracy in estimating precipitation than the basic models. When using IMERG precipitation as the target precipitation, ensemble learning models can estimate the central area of heavy precipitation during typhoons Ampil and Maria. The ensemble learning estimation effect is better than that of Stacking2‐KNN. Moreover, when rain gauge data is used as the target precipitation, ensemble learning can also estimate the center of heavy precipitation and with good consistency with recorded satellite brightness temperature data.
TNFSF15 inhibits progression of diabetic retinopathy by blocking pyroptosis via interacting with GSDME
Authors: Zhao Hongkun , Dai Yating , Li Yunqin , Li Juanjuan , Li Hua
Published: February 2024

Diabetic retinopathy is a common microvascular complication of diabetes and a leading cause of blindness. Pyroptosis has emerged as a mechanism of cell death involved in diabetic retinopathy pathology. This study explored the role of GSDME-mediated pyroptosis and its regulation by TNFSF15 in diabetic retinopathy. We found GSDME was upregulated in the progression of diabetic retinopathy. High glucose promoted GSDME-induced pyroptosis in retinal endothelial cells and retinal pigment epithelial cells, attributed to the activation of caspase-3 which cleaves GSDME to generate the pyroptosis-executing N-terminal fragment. TNFSF15 was identified as a binding partner and inhibitor of GSDME-mediated pyroptosis. TNFSF15 expression was increased by high glucose but suppressed by the caspase-3 activator Raptinal. Moreover, TNFSF15 protein inhibited high glucose- and Raptinal-induced pyroptosis by interacting with GSDME in retinal cells. Collectively, our results demonstrate TNFSF15 inhibits diabetic retinopathy progression by blocking GSDME-dependent pyroptosis of retinal cells, suggesting the TNFSF15-GSDME interaction as a promising therapeutic target for diabetic retinopathy.
Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment
Authors: França Lucas G. S. , Ciarrusta Judit , Gale-Grant Oliver , Fenn-Moltu Sunniva , Fitzgibbon Sean , Chew Andrew , Falconer Shona , Dimitrova Ralica , Cordero-Grande Lucilio , Price Anthony N. , Hughes Emer , O’Muircheartaigh Jonathan , Duff Eugene , Tuulari Jetro J. , Deco Gustavo , Counsell Serena J. , Hajnal Joseph V. , Nosarti Chiara , Arichi Tomoki , Edwards A. David , McAlonan Grainne , Batalle Dafnis
Published: February 2024

Brain dynamic functional connectivity characterises transient connections between brain regions. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.
Trophoblast stem cell-based organoid models of the human placental barrier
Authors: Hori Takeshi , Okae Hiroaki , Shibata Shun , Kobayashi Norio , Kobayashi Eri H. , Oike Akira , Sekiya Asato , Arima Takahiro , Kaji Hirokazu
Published: February 2024

Human placental villi have essential roles in producing hormones, mediating nutrient and waste exchange, and protecting the fetus from exposure to xenobiotics. Human trophoblast organoids that recapitulate the structure of villi could provide an important in vitro tool to understand placental development and the transplacental passage of xenobiotics. However, such organoids do not currently exist. Here we describe the generation of trophoblast organoids using human trophoblast stem (TS) cells. Following treatment with three kinds of culture medium, TS cells form spherical organoids with a single outer layer of syncytiotrophoblast (ST) cells that display a barrier function. Furthermore, we develop a column-type ST barrier model based on the culture condition of the trophoblast organoids. The bottom membrane of the column is almost entirely covered with syndecan 1-positive ST cells. The barrier integrity and maturation levels of the model are confirmed by measuring transepithelial/transendothelial electrical resistance (TEER) and the amount of human chorionic gonadotropin. Further analysis reveals that the model can be used to derive the apparent permeability coefficients of model compounds. In addition to providing a suite of tools for the study of placental development, our trophoblast models allow the evaluation of compound transfer and toxicity, which will facilitate drug development.