bluuebunny/crossref_metadata_2025_split huggingface dataset:
Photon-stimulated desorption from laser-etched vacuum structural materials of accelerators
Authors: Zhang Wenli , Ma Wenjing , Ge Xiaoqin , Fan Le , Huang Tao , Fang Jianwei , Wang Sihui , Wang Yong 
Published: February 2025

Abstract
The electron multipacting (EM) and the electron cloud
(e-cloud) can have detrimental impact on the operation of the high
energy or high current intensity particle accelerators. The enhanced
performance of new generation particle accelerators has necessitated
the development of advanced structural materials and vacuum
systems. The EM and e-cloud effect have emerged as significant
challenges which cannot be ignored during the design and
construction of these advanced accelerators. Laser-etching technique
represents a promising approach for the suppression of secondary
electron emission from materials, which can lower the secondary
electron yield (SEY) of the structural materials to
below 1. Nevertheless, the deployment of laser-etching technique in
the next generation of large particle accelerators requires a
comprehensive investigation into its vacuum performance. In this
work, a photo-stimulated desorption (PSD) experimental beamline was
constructed on the Hefei Light Source II. The PSD yields of the
structural materials (oxygen-free copper, chrome zirconium copper,
stainless steel, and aluminum alloy) with and without laser-etching
of the vacuum chambers were tested at normal incidence using the
throughput method. The main gases desorbed from all sample surfaces
are H2, CO, CO2, CH4, and H2O. The initial PSD
yield of laser-etched material is higher than that of unetched
material. However, the PSD yield of the laser-etched material
decreases at a faster rate, and after a certain photon dose, the PSD
yield of the laser-etched material is in the same order of magnitude
as that of the unetched material.
Fe3O4 modified graphene epoxy composite materials via polyether amine reduction with enhanced microwave absorption performance
Authors: Yang Guangyuan , Che Jing , Zhao Xiaokang , Chen Congxin , Peng Sanwen , Yang Heng , Zhang Bin 
Published: February 2025

Abstract
The increasing complexity of electromagnetic environments demands the development of advanced absorbers with superior performance. In this study, a novel magnetic Fe3O4-modified graphene-based absorber (FARGO) is synthesized via an in situ reduction process using polyether amine. The resulting FARGO composite exhibits excellent microwave absorption properties. When the filling content of FARGO is 5 wt% in epoxy resin, the optimal reflection loss is −23.12 dB with a thickness of 4 mm and a broad absorption bandwidth of 5.6 GHz can be achieved as the thickness changes to 2 mm. Polyether amine efficiently reduces GO to rGO, significantly improving electrical conductivity. Simultaneously, it grafts amine groups onto the graphene surface, enhancing dispersion and reactivity within the epoxy resin matrix. These synergistic effects make it a promising candidate for high-performance microwave absorbing materials.
Characteristics and properties of hot-deformed duplex stainless steel 2205: an overview
Authors: Baruwa Akinsanya Damilare , Ndou Ndivhuwo 
Published: February 2025

Abstract
This overview details the characteristics and attributes of hot-deformed Duplex Stainless Steel (DSS) 2205, emphasizing its phases, alloying elements, and deformation behaviour. Due to its exceptional mix of mechanical qualities and corrosion resistance, it has found extensive applications in water treatment and desalination, chemical industries, oil and gas storage tankers, construction, food production, and marine environments. Its properties during hot deformation are crucial in defining its applications. DSS 2205 features a balanced dual-phase microstructure, with ferrite (α) and austenite (γ) phases in roughly equal quantities, resulting in high mechanical characteristics and corrosion resistance. Depending on the alloy composition and processing conditions, hot deformation can result in the development of secondary phases. Temperature, strain rate, and initial microstructure impact DSS 2205’s hot deformation. Hot deformation initiates several forms of grain boundaries, which contribute to microstructural evolution and yielding properties. Therefore, the characteristics of hot-deformed DSS 2205 show a refined and dynamically recrystallized microstructure, resulting in improved properties. Understanding the interaction of alloying components, phases, and deformation conditions can help optimize the hot deformation process for DSS 2205. In conclusion, this study emphasizes optimizing the phases and deformation parameters to fully utilize DSS 2205 in demanding applications.
Flame recognition and location algorithm based on YOLO v5s and binocular vision
Authors: Wu Yapeng , Chen Yanwei , Yang Chen , Guo Haoyan , Li Mengshi , Yang Min 
Published: February 2025

Abstract
An improved YOLO v5s framework in conjunction with binocular vision is developed to fulfill the stringent requirements for precise identification and accurate localization of flames. An Efficient Multi-scale Attention (EMA) mechanism is seamlessly integrated into the backbone network of the YOLO v5s model, thereby significantly improving the capacity to focus on and interpret critical target features. To bolster the multi-scale feature fusion capability, the Bidirectional Feature Pyramid Network (BiFPN) is strategically introduced at the fusion layer within the object detection architecture. The Semi-Global Block Matching (SGBM) algorithm is deployed to synchronize the binocular images, complemented by the least squares curve fitting method to adjust location inaccuracies, enhancing the precision of flame positioning. A binocular vision system is meticulously constructed to facilitate a series of rigorous experiments on flame detection and location. The experimental results demonstrate that the improved YOLO v5s network model achieves an exceptional flame recognition rate of 96.25%, which represents a noteworthy increase of 0.98% in accuracy in comparison to the original YOLO v5s model. Additionally, within a distance range of 3 to 10 meters, the flame ranging error is consistently less than 0.1 meters, successfully realizing the objective of high-precision flame detection and localization.
Switching and its Impact on Perseveration in a Verbal Fluency Task: a Study in Persons With Alzheimer’s Clinical Syndrome
Authors: Dubey Neha , Basu Jayanti , Pandey Dinkar , Ghosh Amitabha 
Published: February 2025

Abstract

Objective
The relationship between perseveration and switching in semantic verbal fluency tasks and the possible role of self-generated interference one must overcome before switching back to a previously visited subcategory has not been explored.

Participants & Method
We studied the performance on semantic verbal fluency in 60 cognitively unimpaired subjects, 30 patients with amnestic mild cognitive impairment (aMCI) and 30 patients with Alzheimer’s Clinical Syndrome–dementia (ACS-Dementia). Our primary analysis focused on the association of switching and switchback with the first perseverative error.

Results
Perseveration was significantly associated with switchback in all three groups (χ2 = 24.88, p &lt; .001). Within-cluster perseverations were few. The number of switchbacks was the only significant variable to predict perseverative responses (p &lt; .01). Moving from cognitively unimpaired to aMCI to ACS-Dementia, progressively fewer switches and switchbacks were needed to trigger perseveration. In over half of the perseverations after a switchback in the cognitively unimpaired and aMCI groups and in over a third in the ACS-Dementia group, the subjects had already activated a new word in the switched back subcategory.

Conclusion
Switching between subcategories and subsequent switchback play an important role in triggering perseverations in semantic verbal fluency tasks in the cognitively unimpaired as well as in aMCI and ACS-Dementia. Self-generated interference caused by repeated switching may overwhelm the working memory capacity enough to reactivate a previously suppressed response when revisiting an earlier subcategory. Our findings may facilitate a deeper understanding of the cognitive mechanisms underlying perseveration in semantic fluency tests.
Leveraging LASSO-Based Methodologies for Enhanced SNP Analysis in Plant Genomes
Authors: Puthiyedth Nisha , Zeinalinesaz Farshad , Hou Dongdong , Zhang Yue , Lin Wenjun , Yan Yan 
Published: February 2025

Abstract
Genome-wide association studies (GWAS) have been widely used to reveal the associations between genetic variations and phenotypes in a population of individuals. However, they have been criticized for missing important genetic markers usually due to the fact that the data may not fit the statistical models well. In this study, we address the challenge of identifying significant single nucleotide polymorphisms (SNPs) in GWAS by harnessing the capabilities of two sophisticated regression models, BIGLASSO and AUTALASSO. They are both variants of the least absolute shrinkage and selection operator (LASSO). Our research contributes to the field of genomics through detailed comparative analysis of Arabidopsis thaliana, revealing how each method specializes in uncovering SNPs for different trait types. Our findings indicate that BIGLASSO shows stronger alignment with GWAS results, particularly excelling in the analysis of binary traits, even when these are derived from categorical phenotypes. AUTALASSO could be effective for quantitative traits and complement GWAS. We demonstrate that these LASSO-based methods can significantly enhance the identification of genetic markers, offering a potent complement to traditional GWAS approaches. Our findings not only bridge the gap between statistical and machine learning methodologies in genetic studies but also provide a practical framework for researchers seeking to validate reported SNPs or explore new genomic regions for trait association. This work stands as a pivotal step towards the integration of advanced computational techniques in genomics, paving the way for more precise and comprehensive genetic analyses.
NetworkCommons: bridging data, knowledge, and methods to build and evaluate context-specific biological networks
Authors: Paton Victor , Türei Denes , Ivanova Olga , Müller-Dott Sophia , Rodriguez-Mier Pablo , Venafra Veronica , Perfetto Livia , Garrido-Rodriguez Martin , Saez-Rodriguez Julio 
Published: February 2025

Abstract

Summary
We present NetworkCommons, a platform for integrating prior knowledge, omics data, and network inference methods, facilitating their usage and evaluation. NetworkCommons aims to be an infrastructure for the network biology community that supports the development of better methods and benchmarks, by enhancing interoperability and integration.

Availability and implementation
NetworkCommons is implemented in Python and offers programmatic access to multiple omics datasets, network inference methods, and benchmarking setups. It is a free software, available at https://github.com/saezlab/networkcommons, and deposited in Zenodo at https://doi.org/10.5281/zenodo.14719118.
MolFCL: predicting molecular properties through chemistry-guided contrastive and prompt learning
Authors: Tang Xiang , Zhao Qichang , Wang Jianxin , Duan Guihua 
Published: February 2025

Abstract

Motivation
Accurately identifying and predicting molecular properties is a crucial task in molecular machine learning, and the key lies in how to extract effective molecular representations. Contrastive learning opens new avenues for representation learning, and a large amount of unlabeled data enables the model to generalize to the huge chemical space. However, existing contrastive learning-based models face two challenges: (1) existing methods destroy the original molecular environment and ignore chemical prior information, and (2) there is a lack of a prior knowledge to guide the prediction of molecular properties.

Results
In this work, we propose a molecular property prediction framework called MolFCL, which consists of fragment-based contrastive learning and functional group-based prompt learning. Specifically, we introduced fragment-fragment interactions for the first time in the contrastive learning framework and designed a fragment-based augmented molecular graph that integrates the original chemical environment and fragment reactions. Furthermore, we proposed a novel functional group-based prompt learning during fine-tuning, which first incorporates functional group knowledge and the corresponding atomic signals, to improve molecular representation and provide interpretable analyses. The results show that MolFCL outperforms state-of-the-art baseline models on 23 molecular property prediction datasets. Moreover, visualizations show that MolFCL can learn to embed molecules into representations that can distinguish chemical properties. MolFCL can give higher weight to functional groups consistent with chemical knowledge during the prediction of molecular properties, which offers an interpretable ability of the model. Overall, MolFCL is a practically useful tool for molecular property prediction and assists drug scientists in designing drugs more effectively.

Availability and implementation
MolFCL is available at https://github.com/tangxiangcsu/MolFCL

Supplementary Information
Supplementary data are available at Bioinformatics online.
Metabolic remodeling and de novo mutations transcend cryptic variation as drivers of adaptation in yeast
Authors: Routh Shreya , Lindsay Richard J , Gudelj Ivana , Dhar Riddhiman 
Published: February 2025

Abstract
Many organisms live in predictable environments with periodic variations in growth conditions. Adaptation to these conditions can lead to loss of nonessential functions, which could be maladaptive in new environments. Alternatively, living in a predictable environment can allow populations to accumulate cryptic genetic variation that may have no fitness benefit in that condition, but can facilitate adaptation to new environments. However, how these processes together shape the fitness of populations growing in predictable environments remains unclear. Through laboratory evolution experiments in yeast, we show that populations grown in a nutrient-rich environment for 1,000 generations generally have reduced fitness and lower adaptability to novel stressful environments. These populations showed metabolic remodeling and increased lipid accumulation in rich medium which seemed to provide osmotic protection in salt stress. Subsequent adaptation to stressors was primarily driven by de novo mutations, with very little contribution from the mutations accumulated prior to the exposure. Thus, our work suggests that without exposure to new environments, populations might lose their ability to respond effectively to these environments. Furthermore, our findings highlight a major role of exaptation and de novo mutations in adaptation to new environments but do not reveal a significant contribution of cryptic variation in this process.
Quantifying the phenome-wide response to sex-specific selection in Drosophila melanogaster
Authors: Keaney Thomas A , Holman Luke 
Published: February 2025

Abstract
In species with separate sexes, selection on males causes evolutionary change in female traits values (and vice versa) via genetic correlations, which has far-reaching consequences for adaptation. Here, we utilise a sex-specific form of Robertson’s Secondary Theorem of Natural Selection to estimate the expected response to selection for 474 organismal-level traits and ~28,000 gene expression traits measured in the Drosophila Genetic Reference Panel (DGRP). Across organismal-level traits, selection acting on males produced a larger predicted evolutionary response than did selection acting on females, even for female traits; while for transcriptome traits selection on each sex produced a roughly equal average evolutionary response. For most traits, selection on males and females was predicted to move average trait values in the same direction, though for some traits, selection on one sex increased trait values while selection on the other sex decreased them, implying intralocus sexual conflict. Our results provide support for the hypothesis that males experience stronger selection than females, potentially accelerating adaptation in females. Furthermore, sex-opposite responses to selection appear to exist for only a small proportion of traits, consistent with observations that the inter-sex genetic correlation for fitness is positive but less than one in most populations so far studied.
Tailored Approach to Designing a Digital Research Platform for Adults Aged 95 and older: SuperAgers Family Study
Authors: Milman Sofiya , Montgomery Aisha , Barzilai Nir , Gao Tina , Wilson Kara A , Perls Thomas , Leahy Aoife Mc Govern , Burgis Elizabeth , Ruxton Megan , Jain Praduman , Shuldiner Alan R 
Published: February 2025

Abstract

Background
The SuperAgers Family study aims to investigate phenotypic and genetic mechanisms related to healthy aging in nonagenarians, centenarians, and their family members. A remote study design was tested to demonstrate the feasibility of using digital technology to conduct health research within this rare population of advanced age. This paper describes key design elements of the digital research platform developed to deliver consent, enrollment, and study data collection in a cohort of older adults.

Methods
SuperAgers participants aged 95 years or older, their offspring, and offspring’s spouses were invited to join the study via media and community outreach. Participants completed registration, consent, submitted study data, and completed remote biospecimen collection via the web-based study app. Platform design elements and functionality were adapted for use by older aged adults. Qualitative process evaluation assessed usability and participant data entry completion throughout the study workflow.

Results
Preliminary data from SuperAgers (n = 160) of average age 98 years (± 3 SD) and offspring/spouses (n = 127) of average age 69 years (± 5 SD) were evaluated. 97% of participants in both groups successfully used the platform to complete eligibility screening, eConsent, and study surveys.

Conclusions
SuperAgers and offspring successfully used the digital research platform to complete eConsent and submit study data. This supports the feasibility of conducting digitally enabled research in older-aged populations using tailored platform design elements that increase usability and minimize entry errors. These findings may contribute to the development of best practices for digitally delivered research studies in aging populations.
Stress, occurrence rates and b-value on the Nankai megathrust system inferred from earthquake simulation
Authors: Console Rodolfo , Carluccio Roberto , Vannoli Paola 
Published: February 2025

SUMMARY
We aim to improve our comprehension of the seismic process and to identify possible long-term predictability tools of strong earthquakes through the simulation performed by a new-generation simulator code based on a well-elaborated model of the earthquake sources. we applied our previously tested physics-based earthquake simulator to the Nankai megathrust fault system, characterized by a 13 centuries historical record of strong earthquakes. Our results show these significant seismicity patterns characterizing the seismic cycles: the average stress increases almost linearly, while its standard deviation decreases more and more rapidly as the next major earthquake approaches; the coseismic stress drop and the simultaneous increase of the standard deviation mark the beginning of the new seismic cycle; and the b-value tends to increase some decades before major earthquakes and exhibits correlation with the occurrence rate. Our results encourage further investigations about the application of simulators in support of other methodologies of earthquake forecasting.
Correlation between cementation exponent and pore geometry with varying pore pressure for the joint elastic–electrical modelling of porous sandstones
Authors: Han Tongcheng , Yang Yuting , Fu Li-Yun 
Published: February 2025

SUMMARY
Seismic and electrical surveys are the most employed geophysical exploration applications for understanding the subsurface earth. Differential effective medium (DEM) models are the models to interpret the seismic and electrical survey data with the greatest success. However, cementation exponent and pore aspect ratio as the indispensable geometric parameters in the electrical and elastic DEM models are independent, making the models not suitable for the joint elastic–electrical modelling, a key requirement for the joint interpretation of seismic and electrical exploration data to better understand the increasingly complex hydrocarbon reservoirs. We show how cementation exponent and pore aspect ratio are correlated in three Berea sandstone samples with changing porosity resulting from varying pore pressure. We find that cementation exponent inverted from the electrical DEM model shows a strong positive linear correlation with pore aspect ratio obtained from the elastic DEM model as an implicit function of porosity-induced by increasing pore pressure. We also find that the established linear correlation can enable the DEM models to calculate one physical property (e.g. elastic or electrical) from the geometric parameter describing the other property (e.g. electrical or elastic). The results reveal how the elastic and electrical geometric parameters are linked, and provide a consistent microstructure that enables the existing elastic and electrical DEM models to be suitable for the joint elastic–electrical modelling of rocks undergoing varying pore pressure.
Alcohol marketing as a commercial determinant of health: daily diary insights from young women in Kampala
Authors: Swahn Monica H , Natuhamya Charles , Culbreth Rachel , Palmier Jane , Kasirye Rogers , Dumbili Emeka W 
Published: February 2025

Abstract
Alcohol marketing, as a commercial determinant of health, presents an emerging threat to global health and is of particular importance in low-resource settings. This study is composed of data from ‘The Onward Project On Wellbeing and Adversity’ (TOPOWA) project, a multicomponent prospective cohort study examining the mechanistic pathways of adverse mental health conditions among women aged 18 to 24 years living in the Kampala slums in Uganda. The cohort consists of 300 women recruited in 2023 from three study sites (i.e., Banda, Bwaise, and Makindye). In this study, we deployed an underutilized tool, daily diaries, for assessing the exposure to alcohol marketing and an alcohol-promoting environment among young women living in the urban slums of Kampala, Uganda to spur new research and action. At baseline, participants completed a 5-day daily diary and an interviewer-administered survey. Findings show that alcohol-related neighborhood features were most frequently reported, including bars (Mean = 3.88 days), people drinking alcohol (Mean = 3.75), alcohol selling points (Mean = 3.45) and alcohol ads on TV (Mean = 2.51). Women who were exposed to bars (PR = 1.31) and alcohol ads on billboards (PR = 1.14) in a day were more likely to report alcohol use. Similarly, those exposed to alcohol ads on billboards (PR = 1.76) and bars (PR = 2.02) every day were more likely to report alcohol use. Higher cumulative exposure to different alcohol-related features was associated with a greater likelihood of alcohol use, particularly in the group with the highest exposure level. These findings underscore a need to develop alcohol counter-marketing strategies and harm reduction approaches. Daily diaries proved to be a feasible strategy in capturing real-time exposure data, which could in turn support prevention measures and the evaluation of intervention strategies.