bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microservice Deployment in Cloud-Edge Environment using Enhanced Global Search Grey Wolf Optimizer-Greedy Algorithm
Authors: Wang Shudong , Zhang Yanxiang , He Xiao , Wang Nuanlai , Lu Zhi , Chen Baoyun , Pang Shanchen 
Published: August 2024

Abstract

The rapid advancement of edge-cloud technologies has made service deployment increasingly crucial. Additionally, benefiting from the reusability of services, complex applications are subdivided into different microservices. Given the constraints of limited resources, heterogeneous servers, and the geographical diversity of users, how to reasonably deploy microservices becomes a significant challenge. In this paper, we propose a microservice deployment model aimed at minimizing users' latency and maximizing edge providers' profits. The model is divided into different scenarios, each with varying trends in user request categories. To seek microservice deployment strategies, we introduce an Enhanced Global Search Grey Wolf Optimizer-Greedy (EGSGWO-G) algorithm designed for microservice deployment-offloading frameworks. This algorithm leverages EGSGWO to search for deployment strategies and evaluates them using greedy service offloading algorithm. Finally, extensive experiments demonstrate that the EGSGWO-G algorithm improves convergence speed by 31.78%, reduces latency by 12.64%, and increases provider profits by 1.30% compared to GWO-G.
Machine Learning Enabled Fast Optical Identification and Characterization of 2D Materials
Authors: Wu Yingying , Leger Polina , Ramesh Aditya , Ulloa Talianna 
Published: August 2024

Abstract

Two-dimensional materials are a class of atomically thin materials with assorted electronic and quantum properties. Accurate identification of layer thickness, especially for a single monolayer, is crucial for their characterization. This characterization process, however, is often time-consuming, requiring highly skilled researchers and expensive equipment like atomic force microscopy. This project aims to streamline the identification process by using machine learning to analyze optical images and quickly determine layer thickness. In this paper, we evaluate the performance of three machine learning models - SegNet, 1D U-Net, and 2D U-Net- in accurately identifying monolayers in microscopic images. Additionally, we explore labeling and image processing techniques to determine the most effective method for identifying layer thickness in this class of materials.
Decreased Metal Dusting Resistance of Ni-Cu Alloys by Fe and Mn Additions
Authors: Ulrich Anke S. , Kasatikov Sergey , König Till , Fantin Andrea , Margraf Johannes T. , Galetz Mathias C. 
Published: August 2024

Abstract

Ni-Cu alloys are promising for application at temperatures between 400–900°C and reducing atmospheres with high C-contents. Typically, under such conditions, metallic materials in contact with the C-rich atmosphere are degraded by a mechanism called MD. Ni-Cu-alloys do not form protective oxide scales, but their resistance is attributed to Cu, which catalytically inhibits the C-deposition on the surface. Adding other alloying elements, such as Mn or Fe, was found to enhance the MD attack of Ni-Cu alloys again. In this study, the effect of the Mn and Fe is divided into two affected areas: the surface and the bulk. The MD attack on binary Ni-Cu alloys, model alloys with Fe and Mn additions, and commercial Monel Alloy 400 is experimentally demonstrated. The surface electronic structure causing the adsorption and dissociation of C-containing molecules is investigated for model alloys. Analytical methods such as scanning electron microscopy combined with energy-dispersive X-ray spectroscopy, electron probe microanalysis combined with wavelength-dispersive X-ray spectroscopy, X-ray diffraction analysis, and near-edge X-ray absorption fine structure measurements were used. The results are correlated to CALPHAD calculations and atomistic simulations combining density functional theory calculations and machine learning. It is found that the Cu content plays a significant role in the surface reaction. The effect of Mn and Fe is mainly attributed to oxide formation. A mechanism explaining the enhanced attack by adding both Fe and Mn is proposed.
Structural Study of Selectivity Mechanisms for JNK3 and p38α with Indazole Scaffold Probing Compounds
Authors: Park HaJeung , Feng Yangbo 
Published: August 2024

Abstract

Selectivity is a primary focus in medicinal chemistry for ATP-competitive kinase inhibitors due to the highly conserved ATP binding pockets in the kinome. A decade of medicinal chemistry efforts has been carried out to develop selective inhibitors for JNKs, resulting in the identification of numerous promising scaffolds that even exhibit isoform selectivity. Thiophene-indazole is one of the scaffolds explored for isoform selectivity. Some iterations of this scaffold have also shown selectivity for p38α. In this study, we utilized four compounds derived from thiophene-indazole to investigate the mechanisms of selectivity for JNK3 and p38α. We determined crystal structures of the inhibitors bound to either JNK3 or p38α and subjected them to molecular dynamics (MD) simulations to understand the binding mechanism and critical interactions that govern affinity and selectivity for these two important kinases. The findings from this study provides valuable information for improving current lead inhibitors and developing a new generation of JNK3 isoform inhibitors.
NeuroVelo: interpretable learning of temporal cellular dynamics from single-cell data
Authors: Boudjelthia Idris Kouadri , Milite Salvatore , Kazwini Nour El , Huang Yuanhua , Sottoriva Andrea , Sanguinetti Guido 
Published: August 2024

Abstract

Reconstructing temporal cellular dynamics from static single-cell transcriptomics remains a major challenge. Methods based on RNA velocity are useful, but interpreting their results to learn new biology remains difficult, and their predictive power is limited. Here we propose NeuroVelo, a method that couples learning of an optimal linear projection with non-linear Neural Ordinary Differential Equations. Unlike current methods, it uses dynamical systems theory to model biological processes over time, hence NeuroVelo can identify what genes and mechanisms drive the temporal cellular dynamics. We benchmark NeuroVelo against several state-of-the-art methods using single-cell datasets, demonstrating that NeuroV-elo has high predictive power but is superior to competing methods in identifying the mechanisms that drive cellular dynamics over time. We also show how we can use this method to infer gene regulatory networks that drive cell fate directly from the data.
Federated Gradient Boosting using Minimal Variance Sampling
Authors: Lindskog-Münzing William , Nugraha Daniel Nata , Prehofer Christian 
Published: August 2024

Abstract

Federated learning (FL) has emerged as a paradigm for training machine learning models on decentralized data while preserving privacy. This paper introduces a novel approach called Federated gradient BOOsting using Minimal variance sampling (FedBOOM). FedBOOM leverages gradient boosting to construct a robust global model by iteratively aggregating weak learners trained on locally sampled data from clients. Crucially, it employs minimal variance sampling (MVS) to select relevant data points from each client, reducing overhead communication and mitigating the impact of data heterogeneity. Through theoretical analysis and extensive experiments, we find that FedBOOM achieves a superior performance with a subsampling fraction of less than 1.0. In most experiments, a fraction of 0.4-0.6 is optimal and outperforms that of no subsampling (fraction of 1.0) with on average 5.5\%. Use of optimal subsampling fraction for FedBOOM can also reduce communication cost with 40\% on average.
­­Tsunami hazard induced by an Early Holocene landslide in the Tagus delta off Lisbon (Portugal)
Authors: Ramalho I. , Omira R. , Terrinha P. 
Published: August 2024

Abstract

Submarine landslides are a major source of tsunamis, with waves highly dependent of the properties of both the landslide and the marine domain. This study investigates the tsunamigenesis of a shallow-water submarine landslide, recently mapped at the mouth of the Tagus delta River, off Lisbon, Portugal. The Tagus delta landslide is estimated to be 8 ky old, with a depositional maximum thickness of ~ 20 m and a volume of approximately 0.27 km3, extending over more than 9 km in length and 3 km in width. We assess the tsunamigenic potential and hazard of this possible early Holocene landslide using numerical simulations over high resolution reconstructed paleo-bathymetry, and project a similar future landslide scenario under the present-day conditions. Results show that both paleo- and future landslide scenarios are tsunamigenic, posing a significant tsunami hazard to the nearest coasts of Lisbon and surrounding areas. At the source region, the formed tsunami reached heights of 0.8 m (paleo-scenario) and 1.45 m (future-scenario), increasing to approximately 2 m (both scenarios) as it propagated towards Lisbon’s coastline. This study is a first attempt to address the tsunamigenic potential of a submarine landslide occurring in a shallow water environment of the Portuguese margin domain. The results reinforce the need to include these small, but frequent, events and their induced tsunamis in marine geo-hazard assessments of the region.
Improved YOLOv8n-based Helmet Wearing Inspection Measurement Method Study
Authors: chen xinying , jiao zhisheng , liu yuefan 
Published: August 2024

Abstract

This paper proposes the YOLOv8n_H method to address issues regarding parameter redundancy, slow inference speed, and suboptimal detection precision in contemporary helmet-wearing target recognition algorithms. The YOLOv8 C2f module is enhanced with a new SC_Bottleneck structure, incorporating the SCConv module, now termed SC_C2f, to mitigate model complexity and computational costs. Additionally, the original Detect structure is substituted with the PC-Head decoupling head, leading to a significant reduction in parameter count and an enhancement in model efficiency. Moreover, the original Detect structure is replaced by the PC-Head decoupling head, significantly reducing parameter count and enhancing model efficiency. Finally, regression accuracy and convergence speed are boosted by the dynamic non-monotonic focusing mechanism introduced through the WIoU boundary loss function. Experimental results on the expanded SHWD dataset demonstrate a 46.63% reduction in model volume, a 44.19% decrease in parameter count, a 54.88% reduction in computational load, and a maximum accuracy improvement to 93.8% compared to the original YOLOv8 algorithm. In comparison to other algorithms, the model proposed in this paper markedly reduces model size, parameter count, and computational load while ensuring superior detection accuracy.
Research on wear and grinding treatment of high-speed turnout rails
Authors: Li Jincheng , Qi Yayun , Wu Pengpeng , Ding Junjun , Ding Haohao 
Published: August 2024

Abstract

To mitigate steel rail wear in turnouts, this study examines wear mechanisms and influencing factors in high-speed turnouts. We establish a coupled dynamics model to analyze vehicle-turnout interactions, incorporating actual turnout rail profiles, continuous traction forces from passing vehicles, and running resistance. This study evaluates the suitability of various wear models, update procedures, wear superposition methods, and filtering techniques for predicting turnout rail wear. A predictive model for turnout rail wear is developed, and the influence of different turnout parameters on rail wear is investigated. Computational results indicate that the wear power model provides superior accuracy and efficiency in predicting turnout rail wear. A depth update step of 0.05mm proves optimal for turnout steel rail wear, while an adaptive filtering algorithm tailored to turnout wear characteristics effectively filters rail wear. Compared to traditional models, our dynamic model, which accounts for traction-resistance, closely aligns with actual measured data, demonstrating higher computational accuracy. Excessive longitudinal and lateral stiffness during vehicle passage through turnouts is found to be detrimental to reducing turnout steel rail wear. Conversely, appropriately increasing anti-snaking damper stiffness and lateral damper damping can mitigate rail wear. Based on the distribution of rail wear in the turnout area, an holistic grinding scheme was formulated. This scheme effectively improved the wheel-rail contact conditions in the turnout area, reducing the lateral vibration acceleration of vehicles passing through the turnout by 52.56% and the vertical vibration acceleration by 30.43%. The holistic grinding scheme can effectively improve the smoothness of the turnout and reduce vehicle vibrations when passing through. This research provides a theoretical basis for suppressing rail wear in high-speed turnouts, effectively reducing the maintenance costs of turnout rails, and has significant implications for improving the operational safety and economic benefits of high-speed trains.
Shifting from competition toward facilitation with abiotic stress is limited for two codominant grass species
Authors: Gray Jesse E. , Smith Melinda D. 
Published: August 2024

Abstract

It’s unclear why the C4 grasses, Andropogon gerardii and Sorghastrum nutans, codominate in the tallgrass prairie despite asymmetric competition and drought tolerance that favors A. gerardii. According to the stress gradient hypothesis (SGH), net interactions between these species may shift from negative (competitive) to positive (facilitative) in harsher conditions. We tested this hypothesis in a greenhouse experiment manipulating community composition and water availability. We found no evidence of such a shift, suggesting limits to the SGH and the existence of other mechanisms driving codominance between these grasses.
Water Footprint and Virtual Water Assessment for Textile Industries of Bangladesh
Authors: Dipu Salah Uddin Ahmed , Piyash Nabil Ahemed 
Published: August 2024

Abstract

The textile and garment industry in Bangladesh, a significant contributor to the national economy and major exporter, heavily consumes water and causes environmental pollution(Sagris et al., 2015). This thesis evaluates the water usage and pollution in the sector by assessing its blue, green, and grey water footprints, focusing on the dyeing, printing, and finishing stages in three industries: KDS, FOURH, and AMBER. The study aims to provide insights into the virtual water footprint and current water management practices, identifying areas for improvement to promote sustainable water resource management in the textile industry.
Correlation Between Literacy Rate and Sex Ratio in Sawai Madhopur District: A Geographical Study
Authors: Rajawat Rakshita Kanwar , sharma Rashmi 
Published: August 2024

Abstract

This study aims to examine the correlation between literacy and the sex ratio in Rajasthan's Sawaimadhopur District. The socioeconomic progress of any region depends significantly on two key demographic factors: the literacy rate and the sex ratio. For the purposes of the 2011 Census, a person is considered to be literate if they are seven years old or older and can read and write in any language with comprehension. A person is not literate if they can just read and cannot write. Literate people are thought to have higher knowledge, which aids in socioeconomic development, particularly in countries like India, the second-most populous nation in the world. In India, the word "sex ratio" refers to the proportion of females to males. The 2011 Indian Census provided the secondary sources used in this analysis. Two variables in Sawaimadhopur have been examined: literacy and the gender ratio. The primary goals of this research are to examine and correlate the spatial distributions of literacy rate and sex ratio. The correlation between the sex ratio and the literacy rate has been determined using the Spearman's Rank correlation approach. Based on statistical analysis, it can be seen that there is a slight but positive correlation between these two variables (r=0.11)
Performance Comparison of different Rapid Freeze-Quench Strategies for Electron Paramagnetic Resonance
Authors: Bracci Maruan , Serra Ilenia , García-Rubio Inés , Doorslaer Sabine Van 
Published: August 2024

Abstract

This work addresses the development of a custom-made home-built rapid freeze-quench (RFQ) device and the comparison of its performance to the one of a commercial RFQ setup that was in-house custom adapted. Both systems consist of two syringes that push the reactants into a mixing chamber and the products to a subsequent freezing setup. Using the binding of azide to myoglobin as a calibration reaction, the quenching times of the different setups were compared, evaluating different instrumental parameters, such as software-controlled variation of the ageing time, variations of the flow rate and variations of the distance travelled by the mixed sample before freezing. In addition to minimal sample consumption, the home-built RFQ device was found to lead to the shorter reaction times which could be controlled in a time range from 10 to 25 ms. The commercial RFQ system yielded optimal reaction control in a time range from 50 to 200 ms, although a larger volume of reactants needed to be used due to the significant dead volume of the system. Three different freezing methods were also evaluated, among which, in our hands, freezing the jet directly in a deep bath of cold isopentane yielded shorter and reproducible freezing times.
Genome-wide fine-mapping improves identification of causal variants
Authors: Wu Yang , Zheng Zhili , Thibaut Loic , Goddard Michael , Wray Naomi , Visscher Peter , Zeng Jian 
Published: August 2024

Abstract

Fine-mapping refines genotype-phenotype association signals to identify causal variants underlying complex traits. However, current methods typically focus on individual genomic segments without considering the global genetic architecture. Here, we demonstrate the advantages of performing genome-wide fine-mapping (GWFM) and develop methods to facilitate GWFM. In simulations and real data analyses, GWFM outperforms current methods in error control, mapping power and precision, replication rate, and trans-ancestry phenotype prediction. For 48 well-powered traits in the UK Biobank, we identify causal variants that collectively explain 17% of the SNP-based heritability, and predict that fine-mapping 50% of that would require 2 million samples on average. We pinpoint a known causal variant, as proof-of-principle, at FTO for body mass index, unveil a hidden secondary variant with evolutionary conservation, and identify new missense causal variants for schizophrenia and Crohn’s disease. Overall, we analyse 600 complex traits with 13 million SNPs, highlighting the efficacy of GWFM with functional annotations.
Congenital absence of touch does not preclude normal cognitive and socioemotional development
Authors: Mason Peggy , Reder Anthony , Lacy Maureen , Pinto Jayant 
Published: August 2024

Abstract

Attachment theory holds that development of normal affective and social behavior requires physical contact between infant and caregiver. The elevation of touch to paramount importance has gone unchallenged because, prior to the present study, no individual with a congenital lack of somatosensation has been reported, much less studied for psychosocial development. Here we describe Kim, who since birth, has been unable to perceive touch, temperature changes, or pain on the body surface. Despite her inability to sense physical contact, Kim has above-average intelligence. She functions normally in social situations with a variety of people, recognizing emotions in herself and others and demonstrating appropriate affect. Kim experiences anxiety that appears grounded in realistic fears and uncertainties particular to her somatic insensitivity, thus serving as adaptive vigilance in reaction to an abnormal sensorium. Her normal socioemotional development, evident from an early age, likely resulted from Kim being able to appreciate her parents’ loving care through gaze, movement, and hearing. In sum, Kim upends the idea of touch as critical to developing a sense of self, secure attachment, and family bonds.
The Mechanism of Rose in Treating Sjögren's Syndrome Based on Network Pharmacology and Molecular Docking
Authors: Zhou Xi 
Published: August 2024

Abstract

Background:
Modern medicine has yet to cure the xerostomia and other symptoms caused by the early onset of Sjögren's Syndrome (SS). Rose, a common flower used in traditional Chinese medicine, is investigated in this study using network pharmacology and molecular docking techniques to explore its potential mechanisms of action against SS.
Methods:
The active components and targets of rose were identified using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The genes encoding these targets were identified using the UniProt database. Additionally, SS-related targets were identified from the GeneCards and OMIM databases. By intersecting the compound targets with SS targets, the predicted targets for rose in the treatment of SS were obtained. A "candidate compound-target" network was constructed using Cytoscape 3.10.2, and a protein-protein interaction network was built. Further analysis of active compounds and their targets was performed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using R software. Finally, molecular docking techniques were employed to validate the affinity between the candidate compounds and key targets.
Results:
Quercetin, beta-carotene, beta-sitosterol, and demethoxycapillarisin in rose interacted with IL6, TNF, AKT1, ALB, IL1B, TP53, JUN, TGFB1, BCL2, and ESR1. These findings indicate that rose exerts therapeutic effects on peripheral glandular damage in SS and its associated cardiovascular diseases and tumorigenesis through anti-inflammatory and antioxidant pathways.
Conclusion:
From a network pharmacology perspective, this study systematically identified the main active ingredients, targets, and specific mechanisms of rose in treating SS, providing a theoretical basis and research direction for further exploration of rose's therapeutic mechanisms in SS.