bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temperature dependence of the electric field strength in a pyroelectric deflector of charged relativistic particles
Authors: Ivashchuk O.O. , Kishin I.A. , Kidanova E.Y. , Dronik V.I. , Gilts M.E. , Kenzhebayeva Zh.E. , Allaniyazova M.A. 
Published: February 2025

Abstract
The paper presents the dependence of the electric field
strength between the crystals of a pyroelectric deflector on their
temperature at various rates of temperature change in a
vacuum. Three measurement cycles were conducted at different heating
rates (0.059∘C/s, 0.015∘C/s, and
0.008∘C/s) followed by subsequent natural cooling. A
phenomenon of electric field strength saturation was observed in the
temperature range of 40–72∘C during heating and
50–22∘C during cooling of the crystals in the pyroelectric
deflector under vacuum conditions. A discrepancy in trends between
the extreme states is observed on the graphs of the temperature
dependence of the electric field strength in the pyroelectric
deflector. The maximum electric field strength between the crystals
reaches 40 kV/cm. A tentative explanation is provided for the
occurrence of electrical breakdowns between pyroelectric crystals at
an electric field strength of 30 kV/cm and a residual gas pressure
of 1.5 × 10-5 Torr. The potential application of the
pyroelectric deflector in accelerator systems and the prospects for
the development of miniature charged particle deflectors are
discussed.
Attribution and projection of regional winter wind energy drought in Europe
Authors: Yu Shuang , Vautard Robert 
Published: February 2025

Abstract
The decline of surface wind speed in many regions of the world is an important phenomenon as it is potentially expected to decrease wind power production. It is not clear, however, whether this decline takes the form of a gradual wind speed decrease or an increase in “wind energy droughts”, long periods with weak wind speeds. Both types of wind speed reductions contribute to a decline in wind power production. Prolonged and more frequent wind energy droughts, in particular, may reduce revenue and jeopardize wind farm projects. Past and future changes in wind energy droughts, as well as their underlying drivers, remain poorly understood. Here we show that winter wind energy droughts will become more probable in Europe and the return period of 10.3-year events during 1971-2000 have been shortened to about 10 years in the whole Europe, and it would be shortened to about 6.6 years during 2041-2070, under uncurbed greenhouse gases emission (scenario RCP8.5). In the current period, low wind energy winter has become more probable in most European countries, especially in the northern countries, showing a higher probability ratio of wind droughts. In the future, for some southern countries, the frequency of wind energy winter droughts is projected to decrease compared with the current period, which is helpful for the development of wind power generation in these countries. In addition, the changes in wind energy droughts are sensitive to the global warming level. With global warming at 1.5, 2, 3, 4 ℃ levels, low wind energy winter in Europe will occur more frequently as the probability is more than 1.13, 1.46, 1.53, 1.60 times as much as that in the current climate, respectively. The regional difference of attribution is meaningful for the optimization of wind energy transmission networks in Europe, which may be considered by large-scale wind energy producers.
Influence of asymmetric microchannels in the structure and function of engineered neuronal circuits
Authors: Mateus J C , Melo P , Aroso M , Charlot B , Aguiar P 
Published: February 2025

Abstract
Understanding the intricate structure–function relationships of neuronal circuits is crucial for unraveling how the brain achieves efficient information transfer. In specific brain regions, like the hippocampus, neurons are organized in layers and form unidirectional connectivity, which is thought to help ensure controlled signal flow and information processing. In recent years, researchers have tried emulating these structural principles by providing cultured neurons with asymmetric environmental cues, namely microfluidics’ microchannels, which promote directed axonal growth. Even though a few reports have claimed to achieve unidirectional connectivity of in vitro neuronal circuits, given the lack of functional characterization, it remains unknown if this structural connectivity correlates with functional connectivity. We have replicated and tested the performance of asymmetric microchannel designs previously reported in the literature to be successful in promoting directed axonal growth, as well as other custom variations. A new variation of ‘Arrowhead’, termed ‘Rams’, was the best-performing motif with a ∼76% probability per microchannel of allowing strictly unidirectional connections at 14 d in vitro. Importantly, we assessed the functional implications of these different asymmetric microchannel designs. For this purpose, we combined custom microfluidics with microelectrode array technology to record the electrophysiological activity of two segregated populations of hippocampal neurons (‘Source’ and ‘Target’). This functional characterization revealed that up to ∼94% of the spiking activity recorded along microchannels with the ‘Rams’ motif propagates towards the ‘Target’ population. Moreover, our results indicate that these engineered circuits also tended to exhibit network-level synchronizations with defined directionality. Overall, this functional characterization of the structure–function relationships promoted by asymmetric microchannels has the potential to provide insights into how neuronal circuits use specific network architectures for effective computations. Moreover, the here-developed devices and approaches may be used in a wide range of applications, such as disease modeling or preclinical drug screening.
Simulating open quantum systems with giant atoms
Authors: Chen Guangze , Frisk Kockum Anton 
Published: February 2025

Abstract
Open quantum many-body systems are of both fundamental and applicational interest. However, it remains an open challenge to simulate and solve such systems, both with state-of-the-art classical methods and with quantum-simulation protocols. To overcome this challenge, we introduce a simulator for open quantum many-body systems based on giant atoms, i.e. atoms (possibly artificial), that couple to a waveguide at multiple points, which can be wavelengths apart. We first show that a simulator consisting of two giant atoms can simulate the dynamics of two coupled qubits, where one qubit is subject to different drive amplitudes and dissipation rates. This simulation enables characterizing the quantum Zeno crossover in this model. We further show that by equipping the simulator with post-selection, it becomes possible to simulate the effective non-Hermitian Hamiltonian dynamics of the system and thereby characterize the transition from oscillatory to non-oscillatory dynamics due to varying dissipation rates. We demonstrate and analyze the robustness of these simulation results against noise affecting the giant atoms. Finally, we discuss and show how giant-atom-based simulators can be scaled up for digital–analog simulation of large open quantum many-body systems, e.g. generic dissipative spin models.
Reporting units in life-cycle assessments of hospitals: a systematized review of the literature
Authors: Keil Mattis 
Published: February 2025

Abstract
This systematized literature review aims to assess reporting units used by hospital LCAs to communicate their environmental impact through life-cycle assessment (LCA). As the healthcare sector increasingly prioritizes sustainability, understanding the choice of reporting unit is crucial. This analysis aims to provide recommendations for effective communication of environmental performance. A systematized literature search was conducted for LCAs and carbon footprint studies of healthcare organizations or systems in the databases PubMed and Web of Science. The identified units were analyzed using seven criteria, including the differentiation between input and output flows, treatment complexities, quantity of provided services, quality of provided services, longevity of services, matching with system boundaries, and data availability. Seven reporting flows were identified: (i) floor area, (ii) number of beds, (iii) workforce, (iv) expenditure, (v) patient load, (vi) revenue, and (vii) the diagnosis-related groups case mix. Each flow has its own advantages and disadvantages; the best reporting flow for an assessment depends on the specific goals and objectives and should be meaningful to stakeholders. However, none of the reporting flows measure the actual function of healthcare organizations, i.e. the impact on the health of the patients. However, data on this flow, such as quality-adjusted life years, are not available in a meaningful quantity. In conclusion, this literature review highlights the importance of reporting unit selection in communicating the environmental impact of healthcare organizations through LCA. The present analysis identified seven reporting flows, each with its own advantages and disadvantages. These findings are of importance for decision makers to contextualize given data and to choose the most suitable reporting flow for their own assessment. Future research might evaluate the quantitative impact of the reporting flow decision.
The Emotions of Nonviolence
Authors: Krishnamurthy Meena 
Published: February 2025

Abstract
The Emotions of Nonviolence offers a novel interpretation of Martin Luther King Jr.’s beloved “Letter from Birmingham Jail”: it is not merely a discussion of civil disobedience—as is usually thought—but is also and perhaps even primarily an essay on political motivation. On this reading, the Letter seeks to answer a central question in democratic theory: namely, how can and ought one motivate the racially oppressed to engage in civil disobedience—in what King called nonviolent direct action? King’s answer is that one must appeal to and encourage the political emotions, both positive and negative. Fear, courage, faith, dignity, indignation, and love can together motivate nonviolent action, and nonviolent action can reciprocally motivate and sustain these same emotions. This new and exciting reading of King’s Letter restores its complexity. The Letter’s true addressees are not merely the eight clergymen to whom King explicitly responded but are also the white moderates, Black clergymen, and Black middle-class moderates, and perhaps most of all, the Black masses. Read in this light, the Letter points to an underlying theory of political emotions, details the impediments to action under conditions of injustice, calls various audiences to account for their hypocritical, self-serving, or fearful inaction, engages in propagandizing—working on both intellect and emotion—to motivate a change, and to commend and support the thousands of ordinary Black people already in motion in pursuit of democracy, freedom, and justice.
cfDiffusion: diffusion-based efficient generation of high quality scRNA-seq data with classifier-free guidance
Authors: Zhang Tianjiao , Zhao Zhongqian , Ren Jixiang , Zhang Ziheng , Zhang Hongfei , Wang Guohua 
Published: February 2025

Abstract
Single-cell RNA sequencing (scRNA-seq) technology provides a powerful means to measure gene expression at the individual cell level, thereby uncovering the intricate cellular heterogeneity that underlies various biological processes, including embryonic development, tumor metastasis, and microbial reproduction. However, the variable amounts of data generated across different cell types within tissues can compromise the accuracy of downstream analyses. Traditional approaches for generating scRNA-seq simulation data often rely on predefined data distributions, which can negatively impact the quality of the simulated data. Furthermore, these methods typically focus on simulating single-attribute cells, necessitating substantial additional data for the simulation of multi-attribute cells, which can lead to increased training times. To address these limitations, we propose cfDiffusion, a novel method grounded in diffusion models that incorporates Classifier-Free Guidance and a high-level feature caching mechanism. By leveraging Classifier-Free Guidance, cfDiffusion significantly reduces the training costs associated with model development compared to traditional Classifier Guidance methods. The integration of a caching mechanism further enhances efficiency by shortening inference times. While the inference duration of cfDiffusion remains longer than that of scDiffusion, it exhibits superior expressiveness and efficiency in generating multi-attribute single-cell data. Evaluated across datasets from multiple sequencing platforms, cfDiffusion consistently outperforms state-of-the-art models across various performance metrics. Additionally, cfDiffusion enables the simulation of single-cell data along a pseudo-time scale, facilitating advanced analyses such as tracking cell differentiation, investigating intercellular communication, and elucidating cellular heterogeneity.
mapPat: tracking pathogens evolution in space and time
Authors: Ferrandi Erika , Pesole Graziano , Chiara Matteo 
Published: February 2025

Abstract

Motivation
The COVID-19 pandemic highlighted the importance of genomic surveillance for monitoring pathogens evolution, mitigating the spread of infectious disorders, and informing decision-making by public health authorities. Since the need for the summarization and interpretation of large bodies of data, computational methods are critical for the implementation of effective genomic surveillance strategies.

Results
Here, we introduce mapPat, an R Shiny application for the interactive visualization of pathogens genomic data in space and time. mapPat is designed as a user-friendly dashboard and allows the dynamic monitoring of the evolution of variants, lineages, and mutations in the genome of a pathogen at glance through informative geographic maps and elegant data visuals. mapPat provides a fine-grained map of pathogens evolution and circulation and represents a useful addition to the catalogue of bioinformatics methods for the genomic surveillance of pathogens.

Availability and implementation
mapPat is available at GitHub (https://github.com/F3rika/mapPat.git).
Understanding Ecological Systems Using Knowledge Graphs: An Application to Highly Pathogenic Avian Influenza
Authors: Robertson Hailey , Han Barbara A , Castellanos Adrian A , Rosado David , Stott Guppy , Zimmerman Ryan , Drake John M , Graeden Ellie 
Published: February 2025

Abstract

Motivation
Ecological systems are complex. Representing heterogeneous knowledge about ecological systems is a pervasive challenge because data are generated from many subdisciplines, exist in disparate sources, and only capture a subset of interactions underpinning system dynamics. Knowledge graphs have been successfully applied to organize heterogeneous data and to predict new linkages in complex systems. Though not previously applied broadly in ecology, knowledge graphs have much to offer in an era when system dynamics are responding to rapid changes across multiple scales.

Results
We developed a knowledge graph to demonstrate the method’s utility for ecological problems focused on highly pathogenic avian influenza (HPAI), a highly transmissible virus with a broad host range, wide geographic distribution, and rapid evolution with pandemic potential. We describe the development of a graph to include data related to HPAI including pathogen-host associations, species distributions, and population demographics, using a semantic ontology that defines relationships within and between datasets. We use the graph to perform a set of proof-of-concept analyses validating the method and identifying patterns of HPAI ecology. We underscore the generalizable value of knowledge graphs to ecology including ability to reveal previously known relationships and testable hypotheses in support of a deeper mechanistic understanding of ecological systems.

Availability and implementation
The data and code are available under the MIT License on GitHub at https://github.com/cghss-data-lab/uga-pipp.
Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters
Authors: Lapp Zena , Yoon Hyejin , Foley Brian , Leitner Thomas 
Published: February 2025

Abstract

Motivation
The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment.

Results
Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified.

Availability and implementation
Hypermut 3 is written in Python 3. It is available as a command-line tool at https://github.com/MolEvolEpid/hypermut3 and as a webtool at https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html.
Successful resolution of gastric pneumatosis due to a strangulated hiatus hernia and malrotation through non-surgical management: a case report
Authors: Hadani Shiv , Bhatt Dhaara , Bhagat Ashish , Malhotra Vivek 
Published: February 2025

Abstract
Gastric pneumatosis is a rare finding, and clinicians, when under pressure, find it challenging to immediately identify the cause and decide if the patient requires emergency surgery. We present a case where an initial CT scan demonstrated gastric pneumatosis involving only the greater curvature of the antrum caused by a strangulated hiatus hernia and malrotation of the distal stomach. The CT features suggested the patient required immediate surgery; however, a conservative approach was taken, and a follow-up CT scan 4 days after the onset demonstrated complete resolution and no long-term complications.
Quality matters: chronic kidney disease progression is associated to reduced muscle strength independently of changes in skeletal muscle mass: an observational study
Authors: Chatrenet Antoine , de Müllenheim Pierre-Yves , Torreggiani Massimo , Hernández Julia Nava , Arronte Rocío Urbina , Espinoza Abril Gutiérrez , Piccoli Giorgina Barbara 
Published: February 2025

Abstract

Background and hypothesis
Chronic kidney disease (CKD) is commonly associated with multifactorial neuromuscular impairments. Few studies have investigated CKD-induced changes in maximal voluntary force (MVF), and even fewer have longitudinal follow-up. The aim of this study is to investigate whether CKD progression modifies the relationship between skeletal muscle mass and force and the prevalence of sarcopenia and sarcopenic obesity.

Methods
The data used were prospectively collected during routine check-ups in a network of nutritional centres in Mexico and retrospectively analysed. From a dataset of 5430 patients, we selected 1098 patients with available anthropometric, kidney function, handgrip and bioimpedance data. The relationship between appendicular skeletal muscle mass (ASM) and MVF was investigated using mixed models and adjusted for age, sex, BMI, physical activity level and CKD aetiology. Sarcopenia prevalence were tested across period of follow-up using the Cochran-Mantel-Haenzen for repeated measures and across CKD stages using the Chi-2 test.

Results
After normalization with ASM, MVF was higher in CKD G1-G3 compared to G4 and G5 (p ≤ 0.001, Cohen's d = 0.270–0.576). Slopes between MVF and ASM were lower in CKD G3, G4 and G5 than in CKD G1-G2 (-2.268 [-3.927,-0.609], p = 0.008; -2.694 [-4.593,-0.794], p = 0.006; -3.675 [-5.326,-1.725], p &lt; 0.001, respectively). The prevalence of sarcopenia and sarcopenic obesity did not differ across CKD stages, but recovery was most commonly observed in CKD G1-G2. Slope analysis showed an independent interaction between the slopes of kidney function and ASM on MVF evolution over time.

Conclusions
CKD negatively, progressively and independently affects the neuromuscular system, and force production is reduced for any given muscle mass as CKD progresses. While no association was found between CKD stage and prevalence of sarcopenia, recovery was more frequent in the early CKD stages. These results suggest the importance of early rehabilitation programs to improve musculoskeletal health, quality of life and survival in CKD patients.
Alternating-update-strategy based Graph Autoencoder for graph neural network
Authors: Shan Lingxiao , Li Jian , Liu Guanjun 
Published: February 2025

Abstract
Self-supervised learning (SSL) has become a promising and popular learning paradigm for graph data, offering the advantage of capturing informative knowledge without reliance on manual labels. As a representative class of generative graph SSL models, existing graph autoencoders (GAE) excel in link prediction tasks and are steadily improving in node classification tasks. However, GAE is essentially based on the Information Maximization (InfoMax) principle, always captures much redundant information. In this paper, we propose an Alternating-update-strategy based Graph Autoencoder, including alternating update module (AUM) and GAE. For AUM, we design an Alternating-update-strategy to generate a new graph with reduced redundancy, in order to reduce the amount of redundant information that the encoder may capture. For GAE, we feed it the new graph and employ a re-mask decoding strategy to generate node representations. Our model is evaluated on five common real-world datasets for the node classification task, and the experimental results demonstrate its superiority. Meanwhile, our model has also achieved excellent results in specific e-commerce warehousing application scenarios.
Development and assessment of a prototype of an interproximal image receptor-holding device for use in pediatric dentistry
Authors: Ocampo Thaís Santos Cerqueira , de Alencar-Palha Caio , Cascante-Sequeira Deivi Antonio , Tarosso Réa Marcela , Queiroz Freitas Deborah , Haiter-Neto Francisco 
Published: February 2025

Abstract

Objective
To develop and test a prototype for interproximal radiography positioning intended for pediatric dentistry and compare the technical quality of image receptor-holding devices (IRHD) commonly used in clinical practice.

Methods
Six prototypes, with three wedge dimensions (0.5 mm, 1 mm, and 2 mm) in upper and lower positions on the bitewing surface were compared regarding their capacity to acquire interproximal radiographs without overlapping surfaces with other IRHDs: RinnXCPTM, Hawe KerrTM, and Cone Indicator. Fifteen graduate students obtained images of deciduous molars in a child’s skull and mandible. The chi-square and Fisher's exact tests were employed to analyze significant differences in the number of repetitions and failures in obtaining correct images. A one-way ANOVA assessed the difference between the mean times required for image acquisition according to each IRHD, adopting a significance level of 5%.

Results
The effectiveness of the tested devices, evaluated by the number of correct and incorrect acquisitions using Fisher's exact test, revealed a p-value of 0.057. The ANOVA demonstrated statistically significant differences in the mean acquisition times (p &lt; 0.0000). The upper and lower wedge prototypes 2 mm performed better in acquiring only one radiograph (76.7%) and took less time to execute the technique (1.17 min and 1.12 min, respectively).

Conclusion
The prototypes showed comparable performance to alternative IRHDs but provided advantages in time efficiency and radiation exposure.