bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Laser Process Loops on the Hole Diameter and Hole Formation of Laser Micro Drilling on TC4
Authors: Adzman Ku Ahmad Irfan Fitri Bin Ku , Halil Aiman Bin Mohd , Muhammad Mahadzir Bin Ishak @ , Yusof Mohd Fadhlan Bin Mohd , Shah Luqman Hakim Bin Ahmad 
Published: January 2024

Abstract
Laser micro drilling stands as a precise manufacturing method that employs a focused laser beam to craft accurate, small holes within a diverse array of materials. Its applications span across vital industries like aerospace, medical, and electronics, playing a pivotal role in creating components like fuel injectors, medical implants, and microelectronics. Within this context, a notable challenge emerges in obtaining a refined surface finish during laser micro drilling. This study delves into the impact of a laser loop, a crucial parameter, on the surface quality of TC4, also known as Ti6Al4V—an aerospace staple. Employing a Conventional Fiber Laser with a peak output of 30 W, the experiment meticulously directs the laser beam onto the TC4 surface via a microscope objective lens. The drilling process unfolds in controlled conditions, mitigating external variables such as temperature and humidity. Assessment of drilled hole surfaces transpires through both light and 3D microscopes. Interestingly, holes subjected to higher laser power and increased laser loop rates demonstrate enhanced surface smoothness. In essence, this inquiry demonstrates the substantial influence of laser loop on TC4’s surface finish during laser micro drilling. Elevating the laser loop factor leads to heightened surface refinement and diminished roughness in drilled holes. It was found that the diameter entry of the micro-holes was increased by 61% - 89.35% and the diameter exit of the micro-holes also increased by 55.55% - 62.79%. The outcomes of this investigation offer valuable insights for refining the laser micro drilling process to achieve premium surface quality on TC4 and comparable materials. As such, these findings extend guidance for optimal laser loop settings in the realm of laser micro drilling across various materials, benefiting future manufacturing endeavors.
Effect of Tube Length on the Performance of Cooling Necklace with Vortex Tube Cold Flow Generator
Authors: Adnan Nur Shuhada , Hisamudin Wan Nur Adibah Wan , Yusof Mohd Hazwan , Suhaimi Muhammad Fadhli 
Published: January 2024

Abstract
The vortex tube, a compact and eco-friendly device, can generate both low-temperature cold flow and high-temperature hot flow from a room-temperature compressed gas supply. Despite its potential, there has been limited research on its application as a cooling device, particularly in the context of a cooling necklace. This study aims to fill this gap by examining the performance of the vortex tube under various conditions. The experiment was conducted indoors, with tube lengths ranging from 60 cm to 140 cm and inlet pressures from 0.2 MPa to 0.4 MPa. The results suggest that an inlet pressure of 0.4 MPa and a tube length of 60 cm are optimal for achieving the lowest temperature cold flow and minimizing heat transfer effects between the cold flow and the environment.
Parametric Analysis of Process Loop and Scanning Line Distance in Laser Cleaning of Corrosion on Boron Steel
Authors: Azman Irfan Bin , Halil Aiman Bin Mohd , Muhammad Mahadzir Bin Ishak @ , Quazi Moinuddin Mohammed 
Published: January 2024

Abstract
This project is a comprehensive exploration conducted within the Laser Micro Cleaning Lab at the Pekan Campus of University Malaysia Pahang. The objective of the project is to delve into laser material processing, particularly in the context of laser micro cleaning. The undertaking involves a meticulous research approach, drawing insights from authoritative and relevant journal articles sourced primarily from online platforms. The primary goal of this investigation is twofold: firstly, to scrutinize the effects of mark loops on corrosion depth in boron steel, and secondly, to examine how alterations in line distance influence the surface roughness during corrosion laser cleaning. The study will encompass a diverse range of laser cleaning parameters and materials, facilitating a comprehensive assessment of their impact on both laser mark loops and line distances. To delve deeper, a sophisticated 3D microscope analysis will be employed, focusing on evaluating corrosion depth and surface roughness. The anticipated outcomes of this research hold the promise of invaluable insights, offering optimized strategies for enhancing laser cleaning processes and achieving more efficient results.
The Simulation of Biogas Combustion in Top Open Burner
Authors: Selvam A. , Noor M.M. , Norhafana M. , Ihsan C.K. , Khalid A. , Mahmood R.A. , Harikrishnan S. , Nayak S. 
Published: January 2024

Abstract
The top open furnace is commonly used for the heating processes. The efficiency of the top open furnace is low due to the amount of heat wasted through the top open. This study was using ANSYS Fluent, a two-dimensional computational fluid dynamic (CFD) model that was used to build the top open furnace. Exhaust gas recirculation (EGR) was installed in the boiler in order to collect the exhaust gas and reuse it to dilute the oxygen supply. To check the combustion of low calorific gas (LCV) gas, which is biogas composed of 60% methane and 40% carbon dioxide by mass fraction, the computational study started with a standard combustion with EGR. Medium-sized mesh is used for the smoothing grid. This mesh uses inflation to enable the size of the cells and the stack element. The findings of the numerical sensitivity test show that the boundary conditions along the combustion chamber wall can affect the flame temperatures. The MILD regime was reached using biogas fuels when the right parameters were used.
A custom discrete amplifier-shaper-discriminator circuit for the drift chambers of the R3B experiment at GSI
Authors: Wiebusch Michael , Heggen Henning , Heil Michael 
Published: January 2024

Abstract
This contribution presents a pragmatic approach to read-out electronics for drift chambers used in particle physics experiments, specifically for the R3B experiment at GSI. The design uses discrete miniature SMD components and LVDS inputs of a low-cost FPGA to achieve a performance similar to classic ASIC solutions to the problem. The circuit comprises a high gain, low noise amplifier, a custom signal shaper, tailored to the specifics of proportional counter signals, and a leading-edge discriminator with programmable threshold. The presented approach offers an attractive solution for small to medium sized detector systems that require specialized read-out electronics but cannot afford the high cost and development effort associated with ASICs.
A 131-year evidence of more extreme and higher total amount of hourly precipitation in Hong Kong
Authors: Lai Yangchen , Li Jianfeng , Lee Tsz-cheung , Tse Wai-Po , Chan Faith Ka Shun , Chen Yongqin David , Gu Xihui 
Published: January 2024

Abstract
Based on the observations of hourly precipitation for 131 years from Hong Kong Observatory Headquarters, this study examined the long-term changes in the characteristics of hourly precipitation extremes in terms of intensity, total precipitation amount, duration, and frequency. Results show that the hourly precipitation extremes have significantly intensified by 29%–38% from 1885 to 2022. The 131-year observations evidence that the more extreme the hourly precipitation is (i.e. higher percentiles), the faster the increasing rate it has. Specifically, the magnitudes of hourly precipitation with the 95th, 97.5th, 99th, and 99.9th percentiles increased by rates of 0.03 mm, 0.05 mm, 0.07 mm, and 0.12 mm per year, respectively. Through the secular trend analysis, we found that only the maximum intensity of extreme precipitation events (i.e. events with maximum intensity exceeding the 95th percentiles) shows a significant increasing trend during 1885–2022, while the trends in the total precipitation amount, duration, and mean intensity are not significant. However, by comparing the percentile bin values between three sub-periods of the 131-year record, we found a significant rise over time in the total precipitation amount, mean intensity, and maximum intensity of extreme precipitation events with different intensities (i.e. 95th, 96th, 97th, 98th, and 99th percentiles), while the change in the duration is not significant. The analysis of the frequency of precipitation events shows significant increases in the proportion of extreme precipitation events during 1885–2022. The observations of 53 stations across Hong Kong from 1986 to 2022 show significant intensification and increasing frequency in the hourly precipitation extremes in most areas of Hong Kong. Meanwhile, the precipitation duration shows a decreasing tendency, which may explain the insignificant changes in the total precipitation amount. These findings provide important insights into the longer-term variations in the characteristics of hourly precipitation extremes.
Unraveling the mechanism of vanadium self-intercalation in 1T-VSe2: atomic-scale evidence for phase transition and superstructure model for intercalation compound
Authors: He Daliang , Wang Bo , Cao Wang , Jiang Yongjun , Dai Sheng , Zhao Wei , Cui Xiaodong , Jin Chuanhong 
Published: January 2024

Abstract
Self-intercalation is an efficient strategy for tailoring the property of layer structured materials like transition metal dichalcogenides (TMDCs), while the associated kinetics and mechanism remain scarcely explored. In this study, we investigate the atomic-scale dynamics and mechanism of vanadium (V) self-intercalation in multi-layer 1T-VSe2 using in situ high resolution scanning transmission electron microscopy. The results reveal that the self-intercalation of V induces structural transformation of pristine VSe2 into three V-enrich intercalated compounds, i.e. V5Se8, V3Se4 and VSe. The self-intercalated V follows an ordered arrangement of

2
×
2

,

2
×
1

, and

1
×
1

within the interlayer octahedral sites, corresponding to an intercalation concentration of 25%, 50% and 100% in V5Se8, V3Se4 and VSe, respectively. The V intercalants induced lattice distortions to the host 1T-VSe2 such as the dimerization of neighboring lattice V is observed experimentally, which are further supported by density functional theory (DFT) calculations. Finally, a superstructure model generalizing the possible structures of self-intercalated compounds in layered TMDCs is proposed and then validated by the DFT determined formation energy landscape. This study provides comprehensive insights on the kinetics and mechanism of the self-intercalation in layered TMDC materials, contributing to the precise control for the structure and stoichiometry of self-intercalated TMDC compounds.
The role of ant-mediated biological interactions in agroecosystems
Authors: Sankovitz Madison , Rivera Monique J , Manjarress Tobias , Mathis Kaitlyn A 
Published: January 2024

Abstract
Ants are common in agroecosystems, where they can significantly impact agricultural production and yield through interactions with other organisms. By regulating crop-damaging insects and occasionally pollinating flowers, ants provide ecosystem services. However, ants can harm crops through herbivory, tending hemipterans, eating beneficial arthropods, or vectoring disease. In this review, we provide an overview of the roles played by ants in agroecosystems through their interactions with other species. We categorize ant species interactions as beneficial or harmful, direct or indirect, and address the importance of context-dependency. In addition to reviewing the role of ant-mediated biological interactions in agroecosystems, we discuss management implications that should be considered when supporting or suppressing ants. This article provides new insights and suggests promising directions for utilizing ants to implement more sustainable agricultural practices in agroecosystems across the globe. We propose that ants play critical roles in agroecosystems through their interactions with other organisms and should be considered when making management decisions.
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction
Authors: Liu Jiaxuan , Lu Yonggang , Zhu Li 
Published: January 2024

Abstract
Cryo-Electron Microscopy (cryo-EM) is a widely used and effective method for determining the three-dimensional (3D) structure of biological molecules. For ab-initio Cryo-EM 3D reconstruction using single particle analysis (SPA), estimating the projection direction of the projection image is a crucial step. However, the existing SPA methods based on common lines are sensitive to noise. The error in common line detection will lead to a poor estimation of the projection directions and thus may greatly affect the final reconstruction results. To improve the reconstruction results, multiple candidate common lines are estimated for each pair of projection images. The key problem then becomes a combination optimization problem of selecting consistent common lines from multiple candidates. To solve the problem efficiently, a physics-inspired method based on a kinetic model is proposed in this work. More specifically, hypothetical attractive forces between each pair of candidate common lines are used to calculate a hypothetical torque exerted on each projection image in the 3D reconstruction space, and the rotation under the hypothetical torque is used to optimize the projection direction estimation of the projection image. This way, the consistent common lines along with the projection directions can be found directly without enumeration of all the combinations of the multiple candidate common lines. Compared with the traditional methods, the proposed method is shown to be able to produce more accurate 3D reconstruction results from high noise projection images. Besides the practical value, the proposed method also serves as a good reference for solving similar combinatorial optimization problems.
Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks
Authors: Nourbakhsh Mona , Degn Kristine , Saksager Astrid , Tiberti Matteo , Papaleo Elena 
Published: January 2024

Abstract
The vast amount of available sequencing data allows the scientific community to explore different genetic alterations that may drive cancer or favor cancer progression. Software developers have proposed a myriad of predictive tools, allowing researchers and clinicians to compare and prioritize driver genes and mutations and their relative pathogenicity. However, there is little consensus on the computational approach or a golden standard for comparison. Hence, benchmarking the different tools depends highly on the input data, indicating that overfitting is still a massive problem. One of the solutions is to limit the scope and usage of specific tools. However, such limitations force researchers to walk on a tightrope between creating and using high-quality tools for a specific purpose and describing the complex alterations driving cancer. While the knowledge of cancer development increases daily, many bioinformatic pipelines rely on single nucleotide variants or alterations in a vacuum without accounting for cellular compartments, mutational burden or disease progression. Even within bioinformatics and computational cancer biology, the research fields work in silos, risking overlooking potential synergies or breakthroughs. Here, we provide an overview of databases and datasets for building or testing predictive cancer driver tools. Furthermore, we introduce predictive tools for driver genes, driver mutations, and the impact of these based on structural analysis. Additionally, we suggest and recommend directions in the field to avoid silo-research, moving towards integrative frameworks.
GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference
Authors: Li Shuo , Liu Yan , Shen Long-Chen , Yan He , Song Jiangning , Yu Dong-Jun 
Published: January 2024

Abstract
The recent advances of single-cell RNA sequencing (scRNA-seq) have enabled reliable profiling of gene expression at the single-cell level, providing opportunities for accurate inference of gene regulatory networks (GRNs) on scRNA-seq data. Most methods for inferring GRNs suffer from the inability to eliminate transitive interactions or necessitate expensive computational resources. To address these, we present a novel method, termed GMFGRN, for accurate graph neural network (GNN)-based GRN inference from scRNA-seq data. GMFGRN employs GNN for matrix factorization and learns representative embeddings for genes. For transcription factor–gene pairs, it utilizes the learned embeddings to determine whether they interact with each other. The extensive suite of benchmarking experiments encompassing eight static scRNA-seq datasets alongside several state-of-the-art methods demonstrated mean improvements of 1.9 and 2.5% over the runner-up in area under the receiver operating characteristic curve (AUROC) and area under the precision–recall curve (AUPRC). In addition, across four time-series datasets, maximum enhancements of 2.4 and 1.3% in AUROC and AUPRC were observed in comparison to the runner-up. Moreover, GMFGRN requires significantly less training time and memory consumption, with time and memory consumed &lt;10% compared to the second-best method. These findings underscore the substantial potential of GMFGRN in the inference of GRNs. It is publicly available at https://github.com/Lishuoyy/GMFGRN.
Reconstructing complex admixture history using a hierarchical model
Authors: Zhang Shi , Zhang Rui , Yuan Kai , Yang Lu , Liu Chang , Liu Yuting , Ni Xumin , Xu Shuhua 
Published: January 2024

Abstract
Various methods have been proposed to reconstruct admixture histories by analyzing the length of ancestral chromosomal tracts, such as estimating the admixture time and number of admixture events. However, available methods do not explicitly consider the complex admixture structure, which characterizes the joining and mixing patterns of different ancestral populations during the admixture process, and instead assume a simplified one-by-one sequential admixture model. In this study, we proposed a novel approach that considers the non-sequential admixture structure to reconstruct admixture histories. Specifically, we introduced a hierarchical admixture model that incorporated four ancestral populations and developed a new method, called HierarchyMix, which uses the length of ancestral tracts and the number of ancestry switches along genomes to reconstruct the four-way admixture history. By automatically selecting the optimal admixture model using the Bayesian information criterion principles, HierarchyMix effectively estimates the corresponding admixture parameters. Simulation studies confirmed the effectiveness and robustness of HierarchyMix. We also applied HierarchyMix to Uyghurs and Kazakhs, enabling us to reconstruct the admixture histories of Central Asians. Our results highlight the importance of considering complex admixture structures and demonstrate that HierarchyMix is a useful tool for analyzing complex admixture events.
cloudrnaSPAdes: isoform assembly using bulk barcoded RNA sequencing data
Authors: Meleshko Dmitry , Prjbelski Andrey D , Raiko Mikhail , Tomescu Alexandru I , Tilgner Hagen , Hajirasouliha Iman 
Published: January 2024

Abstract

Motivation
Recent advancements in long-read RNA sequencing have enabled the examination of full-length isoforms, previously uncaptured by short-read sequencing methods. An alternative powerful method for studying isoforms is through the use of barcoded short-read RNA reads, for which a barcode indicates whether two short-reads arise from the same molecule or not. Such techniques included the 10x Genomics linked-read based SParse Isoform Sequencing (SPIso-seq), as well as Loop-Seq, or Tell-Seq. Some applications, such as novel-isoform discovery, require very high coverage. Obtaining high coverage using long reads can be difficult, making barcoded RNA-seq data a valuable alternative for this task. However, most annotation pipelines are not able to work with a set of short reads instead of a single transcript, also not able to work with coverage gaps within a molecule if any. In order to overcome this challenge, we present an RNA-seq assembler that allows the determination of the expressed isoform per barcode.

Results
In this article, we present cloudrnaSPAdes, a tool for assembling full-length isoforms from barcoded RNA-seq linked-read data in a reference-free fashion. Evaluating it on simulated and real human data, we found that cloudrnaSPAdes accurately assembles isoforms, even for genes with high isoform diversity.

Availability and implementation
cloudrnaSPAdes is a feature release of a SPAdes assembler and version used for this article is available at https://github.com/1dayac/cloudrnaSPAdes-release.
Effect of ATG8 or SAC1 deficiency on the cell proliferation and lifespan of the long-lived PMT1 deficiency yeast cells
Authors: Cui Hongjing , Cui Xiaojing , Yang Xiaodi , Cui Xingang , Sun Yaxin , Yuan Di , Cui Qiong , Deng Yanwen , Sun Enhao , Chen Ya-qin , Guo Hongsheng , Deng Ziliang , Wang Junfang , Xu Shun , Sun Xuerong , Wei Zhao , Liu Xinguang 
Published: January 2024

Abstract
Autophagy is pivotal in maintaining intracellular homeostasis, which involves various biological processes, including cellular senescence and lifespan modulation. Being an important member of the protein O-mannosyltransferase (PMT) family of enzymes, Pmt1p deficiency can significantly extend the replicative lifespan (RLS) of yeast cells through an endoplasmic reticulum (ER) unfolded protein response (UPR) pathway, which is participated in protein homeostasis. Nevertheless, the mechanisms that Pmt1p regulates the lifespan of yeast cells still need to be explored. In this study, we found that the long-lived PMT1 deficiency strain (pmt1Δ) elevated the expression levels of most autophagy-related genes, the expression levels of total GFP–Atg8 fusion protein and free GFP protein compared with wild-type yeast strain (BY4742). Moreover, the long-lived pmt1Δ strain showed the greater dot-signal accumulation from GFP–Atg8 fusion protein in the vacuole lumen through a confocal microscope. However, deficiency of SAC1 or ATG8, two essential components of the autophagy process, decreased the cell proliferation ability of the long-lived pmt1Δ yeast cells, and prevented the lifespan extension. In addition, our findings demonstrated that overexpression of ATG8 had no potential effect on the RLS of the pmt1Δ yeast cells, and the maintained incubation of minimal synthetic medium lacking nitrogen (SD-N medium as starvation-induced autophagy) inhibited the cell proliferation ability of the pmt1Δ yeast cells with the culture time, and blocked the lifespan extension, especially in the SD-N medium cultured for 15 days. Our results suggest that the long-lived pmt1Δ strain enhances the basal autophagy activity, while deficiency of SAC1 or ATG8 decreases the cell proliferation ability and shortens the RLS of the long-lived pmt1Δ yeast cells. Moreover, the maintained starvation-induced autophagy impairs extension of the long-lived pmt1Δ yeast cells, and even leads to the cell death.