bluuebunny/crossref_metadata_2025_split huggingface dataset:
N-ethylmaleimide-sensitive factor elicits a neuroprotection against ischemic neuronal injury by restoring autophagic/lysosomal dysfunction
Authors: Qiu Miaomiao , Zhao Xiaoming , Guo Tao , He Hongyun , Deng Yihao 
Published: August 2024

AbstractAutophagosome-lysosome fusion defects play a critical role in driving autolysosomal dysfunction, leading to autophagic/lysosomal impairment in neurons following ischemic stroke. However, the mechanisms hindering autophagosome-lysosome fusion remain unclear. Soluble N-ethylmaleimide-sensitive factor (NSF) is an essential ATPase to reactivate STX17 and VAMP8, which are the paired molecules to mediate fusion between autophagosomes and lysosomes. However, NSF is frequently inactivated to inhibit the reactivation of STX17 and VAMP8 in ischemic neurons. Herein, we investigated whether autophagosome-lysosome fusion could be facilitated to alleviate autophagic/lysosomal impairment in ischemic neurons by over-expressing NSF. Rat model of middle cerebral artery occlusion (MCAO) and HT22 neuron ischemia model of oxygen-glucose deprivation (OGD) were prepared, respectively. The results demonstrated that NSF activity was significantly suppressed, accompanied by reduced expressions of STX17 and VAMP8 in penumbral neurons 48 h post-MCAO and in HT22 neurons 2 h post-OGD. Moreover, the attenuated autolysosome formation accompanied by autophagic/lysosomal dysfunction was observed. Thereafter, NSF activity in HT22 neurons was altered by over-expression and siRNA knockdown, respectively. After transfection with recombinant NSF-overexpressing lentiviruses, both STX17 and VAMP8 expressions were concurrently elevated to boost autophagosome-lysosome fusion, as shown by enhanced immunofluorescence intensity co-staining with LC3 and LAMP-1. Consequently, the OGD-created autophagic/lysosomal dysfunction was prominently ameliorated, as reflected by augmented autolysosomal functions and decreased autophagic substrates. By contrast, NSF knockdown conversely aggravated the autophagic/lysosomal impairment, and thereby exacerbated neurological damage. Our study indicates that NSF over-expression induces neuroprotection against ischemic neuronal injury by restoring autophagic/lysosomal dysfunction via the facilitation of autophagosome-lysosome fusion.
Gauge field dynamics in multilayer Kitaev spin liquids
Authors: Joy Aprem P. , Rosch Achim 
Published: August 2024

AbstractThe Kitaev spin liquid realizes an emergent static $${{\mathbb{Z}}}_{2}$$

Z

2

gauge field with vison excitations coupled to Majorana fermions. We consider Kitaev models stacked on top of each other, weakly coupled by Heisenberg interaction ∝ J⊥. This inter-layer coupling breaks the integrability of the model and makes the gauge fields dynamic. Conservation laws and topology keep single visons immobile. However, an inter-layer vison pairs can hop with a hopping amplitude linear in J⊥ confined to the layer, but their motion is strongly influenced by the type of stacking. For AA stacking, an interlayer pair has a two-dimensional motion but for AB or ABC stacking, sheet conservation laws restrict its motion to a one-dimensional channel within the plane. For all stacking types, an intra-layer vison-pair is constrained to move out-of-plane only. Depending on the anisotropy of the Kitaev couplings Kx, Ky, Kz, the intra-layer vison pairs can display either coherent tunnelling or purely incoherent hopping. When a magnetic field opens a gap for Majorana fermions, there exist two types of intra-layer vison pairs - a bosonic and a fermionic one. Only the bosonic pair obtains a hopping rate linear in J⊥. We use our results to identify the leading instabilities of the spin liquid phase induced by the inter-layer coupling.
Geometry of plastic deformation in metals as piecewise isometric transformations
Authors: Beygelzimer Yan , Filippov Alexander , Orlov Dmytro 
Published: August 2024

AbstractDeformation mechanisms of crystalline solids has been the subject of research for more than two centuries. The theory of dislocations dominates modern views but still has significant gaps demanding the introduction of additional concepts for the coherent quantitative description of physical phenomena. In this work, we propose a coherent geometric description of motion and deformation in crystalline solids as piecewise isometric transformations (PWIT). The latter only includes operations that, similar to interatomic spacing in crystalline lattice, do not alter distances between reference points, i.e. translations, rotations and mirror reflections. The difference between solid-body translations and plastic deformations is that the isometric transformations have discontinuities that in real-life materials realise through dislocations (termination of shifts), disclinations (termination of rotations), and twins (mirror reflections). The conceptual description of plastic deformations as PWIT can be useful for the better description of physical phenomena, proposing new hypothesis, and for developing predictive analytical models. In this paper, the use of this conceptual description enables proposing new hypothesis about the nature of such interesting phenomena in severe plastic deformation as (i) stationary ‘solid state turbulence’ stage in high pressure torsion, and (ii) rate of mass transfer (mechanically assisted diffusion) in simple-shear deformation.
Neolithic Yersinia pestis infections in humans and a dog
Authors: Susat Julian , Haller-Caskie Magdalena , Bonczarowska Joanna H. , da Silva Nicolas A. , Schierhold Kerstin , Rind Michael M. , Schmölcke Ulrich , Kirleis Wiebke , Sondermann Holger , Rinne Christoph , Müller Johannes , Nebel Almut , Krause-Kyora Ben 
Published: August 2024

AbstractYersinia pestis has been infecting humans since the Late Neolithic (LN). Whether those early infections were isolated zoonoses or initiators of a pandemic remains unclear. We report Y. pestis infections in two individuals (of 133) from the LN necropolis at Warburg (Germany, 5300–4900 cal BP). Our analyses show that the two genomes belong to distinct strains and reflect independent infection events. All LN genomes known today (n = 4) are basal in the phylogeny and represent separate lineages that probably originated in different animal hosts. In the LN, an opening of the landscape resulted in the introduction of new rodent species, which may have acted as Y. pestis reservoirs. Coincidentally, the number of dogs increased, possibly leading to Y. pestis infections in canines. Indeed, we detect Y. pestis in an LN dog. Collectively, our data suggest that Y. pestis frequently entered human settlements at the time without causing significant outbreaks.
Peripheral sequestration of huntingtin delays neuronal death and depends on N-terminal ubiquitination
Authors: Boulos Ayub , Maroun Dunia , Ciechanover Aaron , Ziv Noam E. 
Published: August 2024

AbstractHuntington’s disease (HD) is caused by a glutamine repeat expansion in the protein huntingtin. Mutated huntingtin (mHtt) forms aggregates whose impacts on neuronal survival are still debated. Using weeks-long, continual imaging of cortical neurons, we find that mHtt is gradually sequestrated into peripheral, mainly axonal aggregates, concomitant with dramatic reductions in cytosolic mHtt levels and enhanced neuronal survival. in-situ pulse-chase imaging reveals that aggregates continually gain and lose mHtt, in line with these acting as mHtt sinks at equilibrium with cytosolic pools. Mutating two N-terminal lysines found to be ubiquitinated in HD animal models suppresses peripheral aggregate formation and reductions in cytosolic mHtt, promotes nuclear aggregate formation, stabilizes aggregates and leads to pervasive neuronal death. These findings demonstrate the capacity of aggregates formed at peripheral locations to sequester away cytosolic, presumably toxic mHtt forms and support a crucial role for N-terminal ubiquitination in promoting these processes and delaying neuronal death.
Enhancing pre-service teachers’ classroom management competency in a large class context: the role of fully immersive virtual reality
Authors: Li Li , Hu Yongbin , Yang Xianmin , Wu Meiling , Tao Pengrui , Chen Meitan , Yang Chuanwen 
Published: August 2024

AbstractEffective classroom management is essential for creating an optimal learning environment, particularly in large classes. However, pre-service teachers often struggle to develop this competency through traditional training methods such as instructional videos and role-playing, which fail to provide authentic practice opportunities. This study investigated the efficacy of an innovative Immersive Virtual Reality (IVR) system, ClassMaster, in enhancing pre-service teachers’ classroom management skills. A quasi-experimental design was employed, involving 57 pre-service teachers randomly assigned to either an IVR group using ClassMaster or a control group using video-based learning. Participants’ classroom management competencies, self-efficacy, attitudes, and reflective thinking were assessed through pre-tests, post-tests, and delayed tests. Results revealed that while both methods improved immediate classroom management competencies equally, the IVR group demonstrated significantly better performance on delayed tests, indicating enhanced long-term knowledge retention. The IVR group also reported more positive attitudes towards classroom management. Reflective thinking levels were comparable between the two groups. Qualitative interviews highlighted the perceived benefits of the IVR system, including its innovative, immersive, and practical nature, which contributed to a profound and lasting impact on participants’ learning experiences. The study concludes that IVR-based learning, through systems like ClassMaster, offers a promising approach to enhancing pre-service teachers’ classroom management competencies, particularly in large class contexts. The research underscores the potential of IVR as a transformative tool in teacher education, warranting further exploration and integration into teacher training programs.
Silane modified Cr2O3/polyimide nanocomposite films with excellent surface insulation performance for space applications
Authors: Li Wenrui , Yang Xiong , Qi Changchun , Zhang Yucheng , Dong Yibo , Zhao Xin , Gao Zhiliang , Feng Na , Song Baipeng , Zhang Guan-Jun 
Published: August 2024

Abstract
The exploration of deep space significantly increases the probability of spacecraft failures due to surface electrostatic discharge, which imposes higher vacuum insulation protection requirements on polyimide (PI), the external insulation material of spacecrafts. To address this challenge, this study proposes using silane coupling agent KH550 for organic grafting treatment of Cr2O3 nanoparticles, which are then used to dope and modify PI to enhance the vacuum surface insulation of PI films. The KH550 grafting improves the interface strength between the fillers and the matrix, allowing the fillers to be uniformly dispersed in the matrix. Compared to pure PI films, the prepared PI-Cr2O3@KH550 composite films exhibit significantly enhanced vacuum surface flashover voltage, improved surface/volume resistivity, and dielectric properties. The results demonstrate that PI composite films with 0.8% by mass of Cr2O3@KH550 show the most notable performance improvement, with the DC flashover voltage and impulse flashover voltage in vacuum increasing by 20.7% and 27.8%, respectively. The doping of chromium oxide nanoparticles introduces more deep traps into the PI films and reduce the surface resistivity. The higher deep trap density inhibits charge migration, thereby alleviating secondary electron emission and surface electric field distortion. Simultaneously, the lower surface resistivity facilitates dissipating surface charges and improves the surface insulation. These findings are of significant reference value for promoting the enhancement of aerospace insulation performance.
Analysis and prediction of sputtering yield using combined hierarchical clustering analysis and artificial neural network algorithms
Authors: CHEN 陈 Yu 煜 , LUO 罗 Jiawei 嘉伟 , LEI 雷 Wen 玟 , SHEN 沈 Yan 岩 , CAO 曹 Shuai 帅 
Published: August 2024

Abstract
Sputtering is a crucial technology in fields such as electric propulsion, materials processing and semiconductors. Modeling of sputtering is significant for improving thruster design and designing material processing control algorithms. In this study we use the hierarchical clustering analysis algorithm to perform cluster analysis on 17 descriptors related to sputtering. These descriptors are divided into four fundamental groups, with representative descriptors being the mass of the incident ion, the formation energy of the incident ion, the mass of the target and the formation energy of the target. We further discuss the possible physical processes and significance involved in the classification process, including cascade collisions, energy transfer and other processes. Finally, based on the analysis of the above descriptors, several neural network models are constructed for the regression of sputtering threshold E
th, maximum sputtering energy E
max and maximum sputtering yield SY
max. In the regression model based on 267 samples, the four descriptor attributes showed higher accuracy than the 17 descriptors (R
2 evaluation) in the same neural network structure, with the 5×5 neural network structure achieving the highest accuracy, having an R
2 of 0.92. Additionally, simple sputtering test data also demonstrated the generalization ability of the 5×5 neural network model, the error in maximum sputtering yield being less than 5%.
Development of multi droplet-based electricity generator system for energy harvesting improvement from a single droplet
Authors: Gwon Girak , Kam Dongik , Jang Sunmin , La Moonwoo , Choi Dongwhi 
Published: August 2024

Abstract
Due to high output performance, the droplet-based electricity generator (DEG) is garnering attention as a promising alternative power source for small electronic devices. Accordingly, to utilize the DEG as a power source, the efforts to boost the output have focused on methods to modify material modification and introduce surface structure. However, the behavior feature that the reconfigured droplet falls after the DEG operation leaves room for one more droplet energy harvesting from a single droplet. Here, a multi DEG system (MDEG) constructed with multiple DEG units is proposed to harvest more energy from a single droplet. The continuous movement of a water droplet is realized through the inclined stair structure of the MDEG, resulting in electrical energy generation from a single water droplet as many times as it falls. In particular, 2-step MDEG consisting of two DEG units can have 45% higher performance than a single DEG. Therefore, this study implies a contribution to the development of DEGs by considering the droplet dynamics, which has been overlooked in existing DEG studies.
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs
Authors: Chen Lei , Gu Jiahui , Zhou Bo 
Published: August 2024

Abstract
The microRNAs (miRNAs) play crucial roles in several biological processes. It is essential for a deeper insight into their functions and mechanisms by detecting their subcellular localizations. The traditional methods for determining miRNAs subcellular localizations are expensive. The computational methods are alternative ways to quickly predict miRNAs subcellular localizations. Although several computational methods have been proposed in this regard, the incomplete representations of miRNAs in these methods left the room for improvement. In this study, a novel computational method for predicting miRNA subcellular localizations, named PMiSLocMF, was developed. As lots of miRNAs have multiple subcellular localizations, this method was a multi-label classifier. Several properties of miRNA, such as miRNA sequences, miRNA functional similarity, miRNA-disease, miRNA-drug, and miRNA–mRNA associations were adopted for generating informative miRNA features. To this end, powerful algorithms [node2vec and graph attention auto-encoder (GATE)] and one newly designed scheme were adopted to process above properties, producing five feature types. All features were poured into self-attention and fully connected layers to make predictions. The cross-validation results indicated the high performance of PMiSLocMF with accuracy higher than 0.83, average area under the receiver operating characteristic curve (AUC) and area under the precision-recall curve (AUPR) exceeding 0.90 and 0.77, respectively. Such performance was better than all previous methods based on the same dataset. Further tests proved that using all feature types can improve the performance of PMiSLocMF, and GATE and self-attention layer can help enhance the performance. Finally, we deeply analyzed the influence of miRNA associations with diseases, drugs, and mRNAs on PMiSLocMF. The dataset and codes are available at https://github.com/Gu20201017/PMiSLocMF.
A systematic evaluation of computational methods for cell segmentation
Authors: Wang Yuxing , Zhao Junhan , Xu Hongye , Han Cheng , Tao Zhiqiang , Zhou Dawei , Geng Tong , Liu Dongfang , Ji Zhicheng 
Published: August 2024

Abstract
Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation and instance segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including image channels, choice of training data, and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, substantially reducing the time and effort for training cell segmentation models.
Application of singular spectrum analysis to InSAR time-series for constraining the post-seismic deformation due to moderate magnitude earthquakes: the case of 2019 Mw 6 Mirpur earthquake, NW Himalaya
Authors: Jasir M C M , Sreejith K M , Agrawal R , Begum S K 
Published: August 2024

SUMMARY
Detection and separation of the subtle post-seismic deformation signals associated with moderate magnitude earthquakes from interferometric synthetic aperture radar (InSAR) time-series is often challenging. Singular spectrum analysis (SSA) is a statistical non-parametric technique used to decompose and reconstruct signals from complex time-series data. We show that the SSA analysis effectively distinguished the post-seismic signal associated with the 2019 Mw 6 Mirpur earthquake from periodic and noise components. The SSA-derived post-seismic deformation signal is smoother and fits better to an exponential model with a decay time of 34 d. The post-seismic deformation is confined to the southeast of the rupture area and lasted for ∼90 d following the main shock. Inversion of the post-seismic deformation suggests an afterslip mechanism with a maximum slip of ∼0.07 m on the shallow, updip portions of the Main Himalayan Thrust. The 2019 Mirpur earthquake and afterslip together released less than 12 per cent of the accumulated strain energy since the 1555 Kashmir earthquake and implies continued seismic hazard in the future.
The effects of global populism: assessing the populist impact on international affairs
Authors: Wajner Daniel F , Destradi Sandra , Zürn Michael 
Published: August 2024

Abstract
With the global rise to power of populist leaders over the past decade, research on populism, including its international implications, has flourished. However, we still lack a nuanced understanding of the international effects of this new populist wave. The special section that this article introduces seeks to bridge this gap by systematically examining three types of international effects of populism. One group of contributions addresses the impact of populism on the processes of foreign policy-making in countries governed by populists (politics). Another group focuses on effects in terms of foreign policy agenda and its substantive outcomes (policies). A third group of contributions studies the impact of populism on states' stances towards international institutions (international polity). This introduction proposes a theoretical framework that takes into account the existent diversity among populist governments, specifically addressing how the more or less authoritarian character of populism explains variations in international outcomes across politics, policies and polities. A better understanding of these varied characters and effects can contribute new insights to lively debates about the potential challenges posed by populism and populists in the contemporary international order, and the prospects for mitigation.
On the p-irreducibility of quintic positive polynomials
Authors: Kamizawa Takeo , Jamiołkowski Andrzej , Matsuoka Takashi , Watanabe Noboru 
Published: August 2024

Abstract
In this paper we will discuss the p-reducibility/irreducibility of positive polynomials, and we will give some sufficient conditions for quintic polynomials to be p-reducible/irreducible. This research is closely related to some problems in bio-chemistry, especially to the cooperativity in bio-systems. We will study some applications of our results to these problems.