bluuebunny/crossref_metadata_2025_split huggingface dataset:
Crystal growth, magnetic and electrical transport properties of the kagome magnet RCr6Ge6 (R = Gd–Tm)
Authors: Yang 杨 Xingyu 星宇 , Zeng 曾 Qingqi 庆祺 , He 何 Miao 苗 , Xu 许 Xitong 锡童 , Du 杜 Haifeng 海峰 , Qu 屈 Zhe 哲 
Published: April 2024

Abstract
Kagome magnets have attracted considerable research attention due to the interplay between topology, magnetism and electronic correlations. In this study we report single-crystal synthesis of a series of the kagome magnets RCr6Ge6 (R = Gd–Tm) that possess defect-free Cr kagome lattices and systematically study their magnetic and electrical transport properties. The transition from a canted ferrimagnetic to a paramagnetic state in GdCr6Ge6, TbCr6Ge6, DyCr6Ge6, HoCr6Ge6, ErCr6Ge6 and TmCr6Ge6 occurs at 11.3 K, 10.8 K, 4.3 K, 2.5 K, 3.3 K and below 2 K, respectively, due to R–R interactions within the compounds. Magnetization measurements reveal highly anisotropic magnetism with canted magnetic moments in these compounds. In electrical transport, both negative and positive magnetoresistances at different magnetic fields and temperatures have been observed due to the competition between different scattering mechanisms. This work enriches our understanding of the Cr-based kagome magnets and paves the way to search for possible topological responses in this family.
Thermodynamics of charged black holes in Maxwell-dilaton-massive gravity*
Authors: Yue 岳 Rui-Hong 瑞宏 , Qian 钱 Kai-Qiang 凯强 , Liu 刘 Bo 博 , Zou 邹 De-Cheng 德成 
Published: April 2024

Abstract
Considering the nonminimal coupling of the dilaton field to the massive graviton field in Maxwell-dilaton-massive gravity, we obtain a class of analytical solutions of charged black holes, which are neither asymptotically flat nor (A)dS. The calculated thermodynamic quantities, such as mass, temperature, and entropy, verify the validity of the first law of black hole thermodynamics. Moreover, we further investigate the critical behaviors of these black holes in the grand canonical and canonical ensembles and find a novel critical phenomenon never before observed, known as the "reverse" reentrant phase transition with a tricritical point. It implies that the system undergoes a novel "SBH-LBH-SBH" phase transition process and is the reverse of the "LBH-SBH-LBH" process observed in reentrant phase transitions.
The role of shear flow collapse and enhanced turbulence spreading in edge cooling approaching the density limit
Authors: Long Ting , Diamond P.H. , Ke Rui , Chen Zhipeng , Xu Xin , Tian Wenjing , Hong Rongjie , Cao Mingyun , Liu Yanmin , Xu Min , Wang Lu , Yang Zhoujun , Yuan Jinbang , Zhou Yongkang , Yan Qinghao , Yang Qinghu , Shen Chengshuo , Nie Lin , Wang Zhanhui , Hao Guangzhou , Wang Nengchao , Chen Zhongyong , Li Jiquan , Chen Wei , Zhong Wulyu 
Published: April 2024

Abstract
Experimental studies of the dynamics of shear flow and turbulence spreading at the edge of tokamak plasmas are reported. Scans of line-averaged density and plasma current are carried out while approaching the Greenwald density limit on the J-TEXT tokamak. In all scans, when the Greenwald fraction

f

G

=

n
¯

/

n

G

=

n
¯

/

(

I

p

/

π

a
2

)

increases, a common feature of enhanced turbulence spreading and edge cooling is found. The result suggests that turbulence spreading is a good indicator of edge cooling, indeed better than turbulent particle transport is. The normalized turbulence spreading power increases significantly when the normalized

E

×

B

shearing rate decreases. This indicates that turbulence spreading becomes prominent when the shearing rate is weaker than the turbulence scattering rate. The asymmetry between positive/negative (blobs/holes) spreading events, turbulence spreading power and shear flow are discussed. These results elucidate the important effects of interaction between shear flow and turbulence spreading on plasma edge cooling.
Practical aspects of hybrid cooling devices engineering design for HPGe detectors
Authors: Malgin V. 
Published: April 2024

Abstract
The article discusses some practical aspects of engineering
design associated with the use of Stirling cryocoolers in liquefiers
of hybrid cooling devices for HPGe detectors. A feature of hybrid
cooling devices is the presence of two modes: the recondensation
mode when the cryocooler is operating, and the power interruption
mode with a non-renewable LN
2 boil-off. Based on the Thermal
Networks Method, models for each mode are proposed, for analyzing
heat fluxes between standard components forming the liquefier
unit. The proposed models were validated by comparing calculated
parameters of the transition process between the two above-mentioned
operating modes with those obtained experimentally. It is shown that
the minimization of heat gain through the liquefier unit into Dewar
for both operating modes of the hybrid cooling device leads to
contradictory engineering design requirements. Preliminary
conclusions based on the thermal network models are confirmed
experimentally on a serial hybrid cooling device, produced by the
Baltic Scientific Instruments Company. This resulted in practical
recommendations on the choice of condenser position, which depended
on operating conditions of hybrid cooling device, for example as a
laboratory equipment or as a part of remote radiation monitoring
stations.
Fractal Schrödinger equation: implications for fractal sets
Authors: Khalili Golmankhaneh Alireza , Pellis Stergios , Zingales Massimiliano 
Published: April 2024

Abstract
This paper delves into the world of fractal calculus, investigating its implications for fractal sets. It introduces the Fractal Schrödinger equation and provides insights into its consequences. The study presents a general solution for the time-dependent Schrödinger equation, unveiling its core aspects. Exploring quantum mechanics in the context of fractals, the paper analyzes the probability density of the radial hydrogen atom, unveiling its behavior within fractal dimensions. The investigation extends to deciphering the intricate energy levels of the hydrogen atom, uncovering the interplay of quantum mechanics and fractal geometry. Innovatively, the research applies the Fractal Schrödinger equation to simple harmonic motion, leading to the introduction of the fractal probability density function for the harmonic oscillator. The paper employs a series of illustrative figures that enhance the comprehension of the findings. By intertwining quantum mechanics and fractal mathematics, this research paves the way for deeper insights into their relationship.
Thermalization of linear Fermi systems
Authors: Reslen Jose 
Published: April 2024

AbstractThe issue of thermalization in open quantum systems is explored from the perspective of fermion models with quadratic couplings and linear baths. Both the thermodynamic state and the stationary solution of the Lindblad equation are rendered as a matrix-product sequence following a reformulation in terms of underlying algebras, allowing to characterize a family of stationary solutions and determine the cases where they correspond to thermal states. This characterization provides insight into the operational mechanisms that lead the system to thermalization and their interplay with mechanisms that tend to drive it out of thermal equilibrium.
Optimization method for freeform progressive addition lenses using the coincident degree of weight distributions for power deviation and astigmatism
Authors: Xiang Huazhong , Ding Qihui , Wang Yaqiong , Ma Lefei , Cheng Hui , Zheng Zexi , Chen Jiabi , Wang Cheng , Zhang Dawei , Zhuang Songlin 
Published: April 2024

Abstract
This study proposed an optimization method for freeform progressive addition lenses (PALs) based on the coincident degree of weight distributions (WD) for power deviation and astigmatism. Compared with the existing methods which were limited in optimizing WDs for power deviation and astigmatism, our proposed approach offers a more refined optimization. In the design phase, the power deviation and astigmatism of these lenses were evaluated using the existing surface shape. Compared with the prescriptions of the patients, the coincident degrees between the obtained distributions and prescriptions of the PAL power and astigmatism were calculated in the multi-view axis condition. Normalization processing of coincident degrees was performed, yielding the corresponding threshold value of WDs and optimizing the allocated coincident degrees. Based on a minimization error function model, two PALs were designed, simulated, machined, and evaluated using a commercial software. The optimized method reduced peripheral astigmatism and improved the optical properties of PALs. The proposed approach optimizes the freeform PALs and enhances their design optimization in optometry.
Studies on the motion and radiation of interior plasmas in gas-filled hohlraums with different laser entrance hole sizes
Authors: GUO 郭 Liang 亮 , LI 李 Xin 欣 , LI 李 Qi 琦 , LI 李 Sanwei 三伟 , HU 胡 Xin 昕 , LI 李 Jin 晋 , DENG 邓 Bo 博 , DENG 邓 Keli 克立 , WANG 王 Qiangqiang 强强 , CAO 曹 Zhurong 柱荣 , HOU 侯 Lifei 立飞 , CHE 车 Xingsen 兴森 , DU 杜 Huabing 华冰 , XU 徐 Tao 涛 , HE 何 Xiaoan 小安 , LI 李 Zhichao 志超 , JIANG 蒋 Xiaohua 小华 , JIANG 蒋 Wei 炜 , ZHENG 郑 Chunyang 春阳 , ZHENG 郑 Wudi 无敌 , SONG 宋 Peng 鹏 , DING 丁 Yongkun 永坤 , YANG 杨 Dong 冬 , YANG 杨 Jiamin 家敏 
Published: April 2024

Abstract
An experiment on 100 kJ laser facility is performed to study the motive features and radiation properties of plasmas from different areas inside gas-filled cylindrical hohlraums. These hohlraums are designed to possess one open end and one laser entrance hole (LEH) with different diameters, which would or not result in the blocking of the LEH. An x-ray streak camera that is set at 16 degrees with respect to the hohlraum axis is applied to acquire the time-resolved x-ray images from the open end. Based on the images, we can study the evolutions of the wall plasma, corona bubble plasma and LEH plasma simultaneously through an equivalent view field of hohlraum interior. Multi-group flat response x-ray detectors are applied to measure the x-ray fluxes. In order to understand these characteristics, our two-dimensional radiation hydrodynamic code is used to simulate the experimental results. For the accuracy of reproduction, dielectronic recombination and two parameter corrections are applied in our code. Based on the comparison between experiments and simulations, we quantitatively understand the blocking process of LEH and the motion effects of other plasmas. The calibrated code is beneficial to design the gas-filled hohlraum in a nearby parameter space, especially the limit size of LEH.
Solutions of Gross–Pitaevskii equation with periodic potential in dimension three
Authors: Karpeshina Yu. , Kim Seonguk , Shterenberg R. 
Published: April 2024

Quasiperiodic solutions of the Gross–Pitaevskii equation with a periodic potential in dimension three are studied. It is proved that there is an extensive “nonresonant” set

G

⊂

R

3

\mathcal {G}\subset \mathbb {R}^3

such that for every

\vv k\in \mathcal {G} there is a solution asymptotically close to a plane wave

Ae^{i\langle \vv {k},\vv {x}\rangle } as

|\vv k|\to \infty , given

A
A

is sufficiently small.
Taking the legal perspective seriously
Authors: Ryu Angelo , Sewell Trenton 
Published: April 2024

Abstract
Perspectivalism is a popular way to understand legal obligations. That there is a legal obligation, on this view, is equivalent to there being a moral obligation from the legal perspective. But Adam Perry argues that perspectivalism cannot account for arguments going from legal premisses to a factual conclusion. Take, for instance, the premisses (i) only those over 18 have a legal right to vote and (ii) Sarah has a legal right to vote. Seemingly we should be able to arrive at the valid conclusion that Sarah is over 18. Perry says perspectivalism cannot explain the validity of this conclusion. We show that it can. So his objection – that perspectivalism cannot make sense of an important feature of legal argumentation – fails. Along the way, our discussion reveals an important lesson: those who endorse perspectivalism must take care to ensure that all parts of a legal argument, both premisses and conclusions, are true according to the legal perspective.
The effect of global change on the expression and evolution of floral traits
Authors: Day Briggs Samantha , Anderson Jill T 
Published: April 2024

Abstract

Background
Pollinators impose strong selection on floral traits, but other abiotic and biotic agents also drive the evolution of floral traits and influence plant reproduction. Global change is expected to have widespread effects on biotic and abiotic systems, resulting in novel selection on floral traits in future conditions.

Scope
Global change has depressed pollinator abundance and altered abiotic conditions, thereby exposing flowering plant species to novel suites of selective pressures. Here, we consider how biotic and abiotic factors interact to shape the expression and evolution of floral characteristics (the targets of selection), including floral size, colour, physiology, reward quantity and quality, and longevity, amongst other traits. We examine cases in which selection imposed by climatic factors conflicts with pollinator-mediated selection. Additionally, we explore how floral traits respond to environmental changes through phenotypic plasticity and how that can alter plant fecundity. Throughout this review, we evaluate how global change might shift the expression and evolution of floral phenotypes.

Conclusions
Floral traits evolve in response to multiple interacting agents of selection. Different agents can sometimes exert conflicting selection. For example, pollinators often prefer large flowers, but drought stress can favour the evolution of smaller flowers, and the size of floral organs can evolve as a trade-off between selection mediated by these opposing actors. Nevertheless, few studies have manipulated abiotic and biotic agents of selection factorially to disentangle their relative strengths and directions of selection. The literature has more often evaluated plastic responses of floral traits to stressors than it has considered how abiotic factors alter selection on these traits. Global change will likely alter the selective landscape through changes in the abundance and community composition of mutualists and antagonists and novel abiotic conditions. We encourage future work to consider the effects of abiotic and biotic agents of selection on floral evolution, which will enable more robust predictions about floral evolution and plant reproduction as global change progresses.
Evaluation of Differential Diagnostics Potential of Uniform Data Set 2 Neuropsychology Battery Using Alzheimer’s Disease Biomarkers
Authors: Čihák Martin , Horáková Hana , Vyhnálek Martin , Veverová Kateřina , Matušková Veronika , Laczó Jan , Hort Jakub , Nikolai Tomáš 
Published: April 2024

Abstract

Objective
This study aims to evaluate the efficacy of the Uniform Data Set (UDS) 2 battery in distinguishing between individuals with mild cognitive impairment (MCI) attributable to Alzheimer’s disease (MCI-AD) and those with MCI due to other causes (MCI-nonAD), based on contemporary AT(N) biomarker criteria. Despite the implementation of the novel UDS 3 battery, the UDS 2 battery is still used in several non-English-speaking countries.

Methods
We employed a cross-sectional design. A total of 113 Czech participants with MCI underwent a comprehensive diagnostic assessment, including cerebrospinal fluid biomarker evaluation, resulting in two groups: 45 individuals with prodromal AD (A+T+) and 68 participants with non-Alzheimer’s pathological changes or normal AD biomarkers (A−). Multivariable logistic regression analyses were employed with neuropsychological test scores and demographic variables as predictors and AD status as an outcome. Model 1 included UDS 2 scores that differed between AD and non-AD groups (Logical Memory delayed recall), Model 2 employed also Letter Fluency and Rey’s Auditory Verbal Learning Test (RAVLT). The two models were compared using area under the receiver operating characteristic curves. We also created separate logistic regression models for each of the UDS 2 scores.

Results
Worse performance in delayed recall of Logical Memory significantly predicted the presence of positive AD biomarkers. In addition, the inclusion of Letter Fluency RAVLT into the model significantly enhanced its discriminative capacity.

Conclusion
Our findings demonstrate that using Letter Fluency and RAVLT alongside the UDS 2 battery can enhance its potential for differential diagnostics.
DockingGA: enhancing targeted molecule generation using transformer neural network and genetic algorithm with docking simulation
Authors: Gao Changnan , Bao Wenjie , Wang Shuang , Zheng Jianyang , Wang Lulu , Ren Yongqi , Jiao Linfang , Wang Jianmin , Wang Xun 
Published: April 2024

Abstract
Generative molecular models generate novel molecules with desired properties by searching chemical space. Traditional combinatorial optimization methods, such as genetic algorithms, have demonstrated superior performance in various molecular optimization tasks. However, these methods do not utilize docking simulation to inform the design process, and heavy dependence on the quality and quantity of available data, as well as require additional structural optimization to become candidate drugs. To address this limitation, we propose a novel model named DockingGA that combines Transformer neural networks and genetic algorithms to generate molecules with better binding affinity for specific targets. In order to generate high quality molecules, we chose the Self-referencing Chemical Structure Strings to represent the molecule and optimize the binding affinity of the molecules to different targets. Compared to other baseline models, DockingGA proves to be the optimal model in all docking results for the top 1, 10 and 100 molecules, while maintaining 100% novelty. Furthermore, the distribution of physicochemical properties demonstrates the ability of DockingGA to generate molecules with favorable and appropriate properties. This innovation creates new opportunities for the application of generative models in practical drug discovery.
Self-supervised learning on millions of primary RNA sequences from 72 vertebrates improves sequence-based RNA splicing prediction
Authors: Chen Ken , Zhou Yue , Ding Maolin , Wang Yu , Ren Zhixiang , Yang Yuedong 
Published: April 2024

Abstract
Language models pretrained by self-supervised learning (SSL) have been widely utilized to study protein sequences, while few models were developed for genomic sequences and were limited to single species. Due to the lack of genomes from different species, these models cannot effectively leverage evolutionary information. In this study, we have developed SpliceBERT, a language model pretrained on primary ribonucleic acids (RNA) sequences from 72 vertebrates by masked language modeling, and applied it to sequence-based modeling of RNA splicing. Pretraining SpliceBERT on diverse species enables effective identification of evolutionarily conserved elements. Meanwhile, the learned hidden states and attention weights can characterize the biological properties of splice sites. As a result, SpliceBERT was shown effective on several downstream tasks: zero-shot prediction of variant effects on splicing, prediction of branchpoints in humans, and cross-species prediction of splice sites. Our study highlighted the importance of pretraining genomic language models on a diverse range of species and suggested that SSL is a promising approach to enhance our understanding of the regulatory logic underlying genomic sequences.
BEERS2: RNA-Seq simulation through high fidelity in silico modeling
Authors: Brooks Thomas G , Lahens Nicholas F , Mrčela Antonijo , Sarantopoulou Dimitra , Nayak Soumyashant , Naik Amruta , Sengupta Shaon , Choi Peter S , Grant Gregory R 
Published: April 2024

Abstract
Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully length messenger RNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in polymerase chain reaction (PCR) amplification, barcode read errors and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction
Authors: Ji Boya , Zou Haitao , Xu Liwen , Xie Xiaolan , Peng Shaoliang 
Published: April 2024

Abstract
MicroRNAs (miRNAs) synergize with various biomolecules in human cells resulting in diverse functions in regulating a wide range of biological processes. Predicting potential disease-associated miRNAs as valuable biomarkers contributes to the treatment of human diseases. However, few previous methods take a holistic perspective and only concentrate on isolated miRNA and disease objects, thereby ignoring that human cells are responsible for multiple relationships. In this work, we first constructed a multi-view graph based on the relationships between miRNAs and various biomolecules, and then utilized graph attention neural network to learn the graph topology features of miRNAs and diseases for each view. Next, we added an attention mechanism again, and developed a multi-scale feature fusion module, aiming to determine the optimal fusion results for the multi-view topology features of miRNAs and diseases. In addition, the prior attribute knowledge of miRNAs and diseases was simultaneously added to achieve better prediction results and solve the cold start problem. Finally, the learned miRNA and disease representations were then concatenated and fed into a multi-layer perceptron for end-to-end training and predicting potential miRNA–disease associations. To assess the efficacy of our model (called MUSCLE), we performed 5- and 10-fold cross-validation (CV), which got average the Area under ROC curves of 0.966${\pm }$0.0102 and 0.973${\pm }$0.0135, respectively, outperforming most current state-of-the-art models. We then examined the impact of crucial parameters on prediction performance and performed ablation experiments on the feature combination and model architecture. Furthermore, the case studies about colon cancer, lung cancer and breast cancer also fully demonstrate the good inductive capability of MUSCLE. Our data and code are free available at a public GitHub repository: https://github.com/zht-code/MUSCLE.git.