bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interdisciplinary lessons and recommendations for the evaluation of replicability in behavioral sciences
Authors: Brown Mitch , Sacco Donald F. 
Published: February 2024

AbstractAs 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

AbstractThis 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.
Does Central Bank Tone Move Asset Prices?
Authors: Schmeling Maik , Wagner Christian 
Published: February 2024

Abstract
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

SummaryMedium- 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

Abstract
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

AbstractThe 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

AbstractBackground: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

ABSTRACTPolitical 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

Abstract
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

Abstract

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

AbstractSatellite 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

AbstractDiabetic 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

AbstractBrain 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

AbstractHuman 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.
Assessment of human leukocyte antigen-based neoantigen presentation to determine pan-cancer response to immunotherapy
Authors: Han Jiefei , Dong Yiting , Zhu Xiuli , Reuben Alexandre , Zhang Jianjun , Xu Jiachen , Bai Hua , Duan Jianchun , Wan Rui , Zhao Jie , Bai Jing , Xia Xuefeng , Yi Xin , Cheng Chao , Wang Jie , Wang Zhijie 
Published: February 2024

Abstract
Despite the central role of human leukocyte antigen class I (HLA-I) in tumor neoantigen presentation, quantitative determination of presentation capacity remains elusive. Based on a pooled pan-cancer genomic dataset of 885 patients treated with immune checkpoint inhibitors (ICIs), we developed a score integrating the binding affinity of neoantigens to HLA-I, as well as HLA-I allele divergence, termed the HLA tumor-Antigen Presentation Score (HAPS). Patients with a high HAPS were more likely to experience survival benefit following ICI treatment. Analysis of the tumor microenvironment indicated that the antigen presentation pathway was enriched in patients with a high HAPS. Finally, we built a neural network incorporating factors associated with neoantigen production, presentation, and recognition, which exhibited potential for differentiating cancer patients likely to benefit from ICIs. Our findings highlight the clinical utility of evaluating HLA-I tumor antigen presentation capacity and describe how ICI response may depend on HLA-mediated immunity.