bluuebunny/crossref_metadata_2025_split huggingface dataset:
INTEGRASI METODE PCQ DAN HTB UNTUK MENGOPTIMALKAN PENGGUNAAN BANDWIDTH INTERNET DI LINGKUNGAN SEKOLAH
Authors: Mukti Fransiska Sisilia , Latul Roza Syahfadi 
Published: January 2025

Berlangganan kapasitas bandwidth yang besar tidak selalu memberikan jaminan bahwa layanan yang diberikan kepada pengguna akan maksimal. Tanpa adanya manajemen bandwidth yang tepat, maka pengguna dapat saja berebut internet dan terjadi sebuah ketimpangan bandwidth yang diterima. Pengelolaan bandwidth biasanya akan diimbangi dengan adanya pengelolaan user melalui konsep pemetaan tingkat prioritas user, dengan tujuan untuk mendapatkan hasil manajemen jaringan yang lebih baik. Untuk itu, penelitian ini secara khusus mengusulkan sebuah metode pengintegrasian skema manajemen jaringan dalam bentuk manajemen pengguna dan manajemen bandwidth. Manajemen pengguna dilakukan melalui pengklasifikasian pengguna berdasarkan tingkat kepentingannya masing-masing dengan menggunakan metode Hierarchical Token Bucket (HTB). Sementara manajemen bandwidth yang merata untuk seluruh pengguna diusulkan dengan mengintegrasikan konsep Per Connection Queue (PCQ) yang bersifat dinamis, tanpa membebani router. Hasil penelitian menunjukkan bahwa pengintegrasian metode PCQ-HTB memberikan sebuah alternatif baru dalam manajemen jaringan. Terjadi peningkatan nilai throughput yang dihasilkan mencapai 12,18 kali lipat, yang juga diimbangi dengan akses internet pengguna yang lebih merata. Kata kunci: HTB, Internet Sekolah, Manajemen Bandwidth, Mikrotik, PCQ
Screen Necroptosis-related Genes and evaluate the prognostic capacity, clinical value and the affection of their copy number variations in acute myeloid leukemia
Authors: Wen Dake , Yan Ru , Zhang Lin , Zhang Haoyang , Chen Xuyang , Zhou Jian 
Published: January 2025

Abstract

Background：Acute myeloid leukemia (AML) is an aggressive hematological neoplasm. Little improvement in survival rates has been achieved over the past few decades. Necroptosis has relationship with certain types of malignancies outcomes. Here, we evaluated the diagnostic ability, prognostic capacity of necroptosis-related genes (NRGs) and the affection of their copy number variations (CNVs) in AML.
Methods：Necroptosis-related differentially expressed genes (NRDEGs) were acquired after intersecting Differentially expressed genes (DEGs) from Gene Expression Omnibus(GEO) database with NRGs from GeneCards, Molecular Signatures Database (MsigDB) and literatures. Machine learning was applied to obtain hub-NRDEGs. The expression levels of 6 hub-NRDEGs were validated in vitro. mRNA-miRNA and mRNA-TF interaction networks with hub-NRDEGs were screened by Cytoscape@. Single-sample gene set enrichment analysis (ssGSEA) was utilized to calculate correlationships between hub-NRDEGs and immune cells. CNVs analysis on hub-NRDEGs was carried out based on TCGA-LAML datasets from the TCGA database. Kaplan–Meier(K-M) survival analyses was utilized to evaluate the prognostic values along with COX model.
Results：6 hub-NRDEGs (SLC25A5, PARP1, CTSS, ZNF217, NFKB1, PYGL) were obtained and their expression changes derived from CNVs in AML were visualized. 65 mRNA-miRNA and 80 mRNA-TF interaction networks with hub-NRDEGs was screened. ssGSEA result showed the expression of RAPR1 is inversely related with CD56dim natural killer cell and CTSS positive with MDSCs in AML. K-M results demonstrated ZNF217 had significant difference in duration of survival in AML patients. Cox regression models revealed hub-NRDEGs had better predictive power at year-1 and year-5.
Conclusion： These screened NRDEGs could be exploited as clinical prognosis predictions in AML patients, as well as potential biomarkers for diagnosis and therapeutic targeting.
Planar lithium deposition/dissolution enabling practical 500 Wh kg–1 anode-free pouch cells
Authors: Wang Jianhui , Liu Lei , Xiang Yuxuan , Lu Xingyu 
Published: January 2025

Abstract

Anode-free lithium metal batteries (AFLMBs), characterized by the absence of anode active materials during manufacturing, offer great potential for high-energy-density, low-cost energy storage. However, AFLMBs face a long-standing challenge of short lifespan due to the harsh conditions of lacking excess lithium and an anode host. This issue is associated with uneven lithium deposition/dissolution, rooted in the micro-inhomogeneity and fragility of solid electrolyte interphase (SEI) on the lithium metal surface. Here, we present a practical 500 Wh kg–1-level AFLMB design with enhanced lifespan, achieved using an electrolyte of 1.6 M lithium difluoro(oxalate)borate in N,N-Dimethyltrifluoroacetamide solvent. The electrolyte-derived B-F-based polymer-rich SEI exhibits sub-nanometer homogeneity, high flexibility, and fast Li-ion conductivity, which spontaneously evolves a self-adaptive mesh-film structure that ensures uniform ion flux and large-volume-change accommodation, thereby realizing reversible planar lithium-orientated deposition/dissolution of 5.6 mAh cm–2. Consequently, a 2.7 Ah AFLMB (508 Wh kg–1, 1668 Wh L–1) without any host-material coating demonstrates stable cycling for 100 cycles at 100% depth of discharge (DoD) and 250 cycles at 80% DoD, with 80% capacity retention and an unprecedentedly high-power output of 2650 W kg–1 at 96 Wh kg–1. Our findings address the inherent structural instability of host-free electrodes, advancing the practical implementation of AFLMBs.
A sub-galaxy-filament of the cosmic web in a nearby galaxy cluster
Authors: Xu Jinlong , Zhu Ming , Jiang P. , Yu NaiPing , Zhang Chuan-Peng , Liu XiaoLan , Guan Xin , Ai Mei , Wang Jie , Jing Ying-jie , Wang Jun-Jie 
Published: January 2025

Abstract

Galaxy filaments, as quasi-linear and extensive features of galaxy distributions, are a crucial component of the cosmic web. Cosmological simulations have predicted a hierarchical nature to the filaments. However, a direct view of small-scale filaments has been lacking to validate this prediction. Here we report the detection of a sub-galaxy-filament in the Ursa Major cluster using the atomic-hydrogen observations. This filament consists of cold gas clumps and various types of galaxies, spanning a length of approximately 0.9 megaparsec. Notably, it is extremely thin, with a thickness comparable to the diameter of a galaxy. The baryonic fraction within the filament is measured at 0.18. We observed a velocity gradient and a consistent galaxy alignment within the filament. These findings strongly suggest an accretion flow along the filament, potentially contributing to the formation and growth of the galaxies.
The Selective Glucocorticoid Receptor Modulator CORT125329 Decreases Neuroinflammation and Gliosis and Enhances Myelination in the Wobbler Model of Amyotrophic Lateral Sclerosis
Authors: Esperante Iván , Banzan Carolina , Munuera Jimena Zhan , Lima Analía , Hunt Hazel , De Kloet Edo R. , Deniselle María Claudia Gonzalez , De Nicola Alejandro F. , Meyer María 
Published: January 2025

Abstract

The Wobbler mouse is a genetic model of familial amyotrophic lateral sclerosis. Wobblers show spinal cord neurodegeneration associated with gliosis, neuroinflammation, and demyelination. Similar to human neurodegenerative diseases, Wobblers show high levels of corticosterone in blood and the nervous system. A role for glucocorticoids in neuropathology is suggested by the observation that pathological signs attenuate with treatment with glucocorticoid receptor (GR) antagonists/modulators. In the present study, we demonstrated in 5-month-old clinically afflicted Wobbler mice that the selective GR modulator CORT125329 decreased motoneuron degeneration, astro- and microgliosis, and levels of pro-inflammatory factors (HMGB1, toll-like receptor 4, tumor necrosis factorFα, and its receptor). In addition, CORT125329 increased the acetylcholine-producing enzyme choline acetyltransferase, the neurotrophin brain-derived neurotrophic factor, and their cellular colocalization. Furthermore, the increased oligodendrocyte number and a healthier myelin ultrastructure are consistent with the enhanced axonal myelination after CORT125329 treatment. Finally, the high expression of immunoreactive protein and mRNA levels of acquaporin4 in Wobblers was decreased by CORT125329 treatment, implying this water channel is a glucocorticoid target involved in neuropathology. The beneficial effects of CORT125329 correlated with enhanced motor behavioral performance and trophic changes of the forelimbs. In conclusion our results support further preclinical and clinical studies with GR modulators in sporadic amyotrophic lateral sclerosis.
Simulating surfing with optimal control: Sensorfusion for biomechanical analysis
Authors: Weiss Alexander , Lluch Èric , Masmoudi Ilias , Döllinger Michael , Heinrich Dieter , Koelewijn Anne 
Published: January 2025

Abstract

Currently, there is no established biomechanical model for surfing. Especially, musculoskeletal simulations can provide valuable insights for athletes to enhance performance and prevent injuries using quantitative data such as joint angles, joint moments, and muscle forces. The dynamic nature of surfing makes it difficult to assess biomechanics in a laboratory setting. Although inertial measurement units (IMUs) offer a potential solution, relying solely on IMU data in three-dimensional musculoskeletal models presents challenges. We hypothesize a multi-modal approach combining IMU data with deep learning-based human pose estimation to simulate surfing movements. We collected data from seven experienced surfers on a river wave, providing a semi-controlled environment. We placed IMUs on the participants’ bodies, and positioned cameras around the1wave. We defined an optimal control problem to drive three-dimensional biomechanical simulations. In addition, we used an adapted contact model to represent the interaction between feet, surfboard, and water surface. Consequently, we compared the kinematics and kinetics of the front and rear legs, and analyzed muscle forces, to demonstrate the potential of our approach. The study successfully minimized tracking errors and established the first biomechanical model for surfing. Differences between rear and front leg joint moments and angles of up to 47% were found, with muscle forces being higher in the front leg’s muscles, suggesting that the weight distribution in surfing comes mainly from the front leg muscles, while the higher rear leg moments come from stabilization. This showcases the high potential for further biomechanical analysis in surfing performance analysis using our approach.
A simple model approach for the desorption of DDT and related compounds from contaminated sediment to plastic polymers
Authors: Ricking Mathias , Kerndorff Alexander , Obermaier Nathan , Zhu Xiaojing , Bannick Claus Gerhard 
Published: January 2025

Abstract

Plastics including microplastic (MP) particles are widely distributed in the environment today. Microcontaminants - especially very persistent organic compounds and trace metals - are also detected to a large extent in the (aquatic) environment, which has led to a growing number of recent studies addressing interactions between organic contaminants and (micro)plastics in the environment. The background of these studies is the presumed function of plastic particles as vectors for biomagnification, leading to negative effects on the ecosystem. In the present work, interactions between two common plastic polymers, low-density polyethylene (LD-PE) and rigid polyvinyl chloride (H-PVC), and three organic persistent compounds, dichlorodiphenyltrichloroethane (DDT), methoxychlor (DMDT), and dicofol with different log Kow-values, were investigated using a sorption assay and desorption experiments. A new and innovative experimental approach based on a static system resembling burial in deeper sediment layers was investigated. The experimental setup used additive-free plastic containers, resulting in an easy-to-use experiment instead of MP sorption. It is assumed that the basic mechanisms of interaction are evaluated and are material specific. The present sorption experiment demonstrated adsorption/incorporation of contaminants into the two polymers. Differences between the two polymers are addressed. In the sorption experiments, all target substances were detected in agreement with their hydrophobicity. In the desorption experiments, diffusion of contaminants from a contaminated sediment to the polymers was detected. As expected, sorption by PE was significantly higher. The differences between the two polymers are based on the different glass transition temperatures (Tg) and polymer structure. A comparison with published data from the Pellet Watch project shows a sorption capacity in the same concentration range. The simple approach is easy to use and illustrates the limited sorption capacity of the two polymers studied. It eliminates possible sorption effects on glass walls and simulates the ecosystem situation of a multiple aged contaminant mixture, which is usually not represented in laboratory experiments. The same approach is applicable to polystyrene, polypropylene and polyethylene terephthalate beside other polymer containers.
Immune cell-mediated CETP gene and the causal relationship with ischemic stroke disease risk: Mendelian randomization analysis with mediation effect assessment
Authors: Yuan Hao , Feng Xin , Lin Jiancheng , Huang Chi , Huang Mengshi , Duan Chuanzhi 
Published: January 2025

Abstract

Background:
The advancement of cholesterol ester transfer protein inhibitors in the treatment of coronary heart disease (CHD) has thus far failed to produce approved therapeutic agents, despite Mendelian randomization (MR) studies establishing CETP gene as a viable target for CHD prevention. However, there is currently no empirical evidence supporting the role of CETP-related genes as potential therapeutic targets for ischemic stroke. Our study aims to delineate CETP gene as a novel key player in ischemic stroke pathogenesis, establish its causal association with ischemic stroke, and assess the potential mediating effect of immune cells in this process.
Methods
Using the expression quantitative trait loci (eQTL) database and a cross-ethnic cohort of 688807 Europeans and Asians, we conducted MR analysis to investigate the causal relationship between key genes and ischemic stroke. Additionally, we performed mediation analysis to examine the involvement of 731 immune phenotypes in these relationships.
Result
We confirmed that an increase in CETP gene expression is associated with an increased risk of ischemic stroke (OR 1.090, 95% CI : 1.033 to 1.151, p = 0.002), and 11 types of immune cells including IgD + CD24 + B cells mediate this causal relationship.
Conclusion
Increased CETP gene expression is closely associated with a high risk of ischemic stroke, and CETP inhibitors may serve as the next generation of drugs for ischemic stroke therapy.
Global-Local Context Enhanced YOLO for Small Object Detection in UAV Images
Authors: Wei Lixin , Han Kangshuai , Li Xin , Che Haijun , Hu Ziyu 
Published: January 2025

Abstract

Object detection using Unmanned Aerial Vehicles (UAVs) has emerged as a crit- ical application across diverse domains. However, the wide-angle views of drones often result in images containing a high density of small objects, posing chal- lenges for object detection such as few learnable features, significant occlusion, and an imbalanced distribution of positive and negative samples. To address these issues, this paper introduces AGLC-YOLO, an enhanced version of the YOLOv7 architecture specifically designed for detecting small objects in UAV images. AGLC-YOLO integrates global and local context information through a Attention guide Global-Local Context Information Extraction (AGLC) module. This module employs parallel dilated convolutions to capture local context infor- mation and a transformer-based structure to extract global dependencies, which are then fused using an improved attention mechanism. The network also adds an additional small object detection head to enrich the small object informa- tion in the model. Additionally, AGLC-YOLO utilizes an auxiliary bounding box in conjunction with the Inner-Wise Intersection over Union (Inner-WIoU) loss function to accelerate the bounding box regression process and improve detec- tion accuracy. Experimental results on the VisDrone and ManipalUav datasets demonstrate that AGLC-YOLO achieves significant improvements over the base- line YOLOv7 model, with an increase of 3% in AP50 and 2.7% in AP95 on the VisDrone dataset, and 1.9% in AP50 and 2% in AP95 on the ManipalUav dataset. Source code is released in https://github.com/hanks124/aglc.
An Automated Multimodal Medical Image Fusion Framework for Alzheimer Detection using Deep Learning
Authors: Beatrice S. , M Janaki Meena , Dhivviyanandnam I. 
Published: January 2025

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative condition that affects the elderly population. The early detection and diagnosis of AD is critical for achieving effective treatment, as it can greatly improve the patient experience. AD can be viewed through imaging techniques like MRI, PET, and SPECT, providing valuable information about structural and functional changes. These findings are important in understanding this area. However, each imaging modality offers a different perspective. This information can be better collected from several of the other modalities as well as from some others to improve accuracy and reliability in AD detection. By combining information from different imaging modalities, such as MRI, PET, DTI, and fMRI, automated multimodal medical image frameworks aim to create a fused representation that preserves the relevant features from each modality. Convolutional neural networks (CNNs) and generative adversarial networks (GANs), among other deep learning techniques, have been prevalent in these frameworks for learning discriminative and informative features from multi-modal data. In this paper, The Alzheimer's Disease Neuroimaging Initiative (ADNI) is used for experimental analysis. The proposed work gives 98.94% of accuracy and 1.06% of error which is greater than the existing approaches.
Artificial Intelligence in Computer-Aided Drug Design (CADD) Tools for the Finding of Potent Biologically Active Small Molecules: Traditional to
Modern Approach
Authors: Siddiqui Benjamin , Yadav Chandra Shekhar , Akil Mohd , Faiyyaz Mohd , Khan Abdul Rahman , Ahmad Naseem , Hassan Firoj , Azad Mohd. Irfan , Owais Mohammad , Nasibullah Malik , Azad Iqbal 
Published: January 2025

Abstract:
Computer-Aided Drug Design (CADD) entails designing molecules that could potentially
interact with a specific biomolecular target and promising their potential binding. The stereo-
arrangement and stereo-selectivity of small molecules (SMs)--based chemotherapeutic
agents significantly influence their therapeutic potential and enhance their therapeutic advantages.
CADD has been a well-established field for decades, but recent years have observed a
significant shift toward acceptance of computational approaches in both academia and the pharmaceutical
industry. Recently, artificial intelligence (AI), bioinformatics, and data science have
played a significant role in drug discovery to accelerate the development of effective treatments,
reduce expenses, and eliminate the need for animal testing. This shift can be attributed to the
availability of extensive data on molecular properties, binding to therapeutic targets, and their 3D
structures. Increasing interest from legislators, pharmaceutical companies, and academic and industrial
scientists is evidence that AI is reshaping the drug discovery industry. To achieve success
in drug discovery, it is necessary to optimize pharmacodynamic, pharmacokinetic, and clinical
outcome-related properties. Moreover, the advent of on-demand virtual libraries containing
billions of drug-like SMs, coupled with abundant computing capacities, has further facilitated
this transition. To fully capitalize on these resources, rapid computational methods are needed for
effective ligand screening. This includes structure-based virtual screening (SBVS) of vast chemical
spaces, aided by fast iterative screening approaches. At the same time, advances in deep
learning (DL) predictions of ligand properties and target activities have become very helpful, as
they no longer need information about the structure of the receptor. This study examines recent
progress in the drug discovery and development (DDD) approach, their potential to reshape the
entire DDD process, and the challenges they face. This review examines the role of artificial intelligence
as a fundamental component in drug discovery, particularly focusing on small molecules.
It also discusses how AI-driven approaches can expedite the identification of diverse, potent,
target-specific, and drug-like ligands for protein targets. This advancement has the potential
to make drug discovery more efficient and cost-effective, ultimately facilitating the development
of safer and more effective therapeutics.
“Skin Whitening Creams: Cosmetovigilance.”
Authors: Agarwal Saloni , Mazhar Mohd , Saha Hiranmoy , Khan Simra , Ibrahim Mohammad , Chhabra Charu 
Published: January 2025

Abstract:
Cosmeceutical products such as skin-lightening agents have been used globally to
enhance skin tone and obtain a magnificent outward appearance. The pigment known as melanin,
produced by melanocytes, imparts skin color. The Cosmetic Europe survey testifies that
most people believe that cosmetics enhance one's quality of life. The most in-demand in the
cosmetics industry are skin-whitening agents. Heavy metals and dangerous substances like lead
and mercury are present in these skin-brightening cosmetics, which have a long-term effect on
important organs and begin asymptomatic. Despite these negative consequences, there is a sizable
market for these products due to the desire for fairer skin tones. Cosmetovigilance studies
determine the of heavy metals in these preparations, which need to be monitored regularly. This
article discusses the toxicity of heavy metals such as nickel, mercury, arsenic, lead, cobalt, and
others found in skin-lightening formulas. The acceptable limit for these toxic agents is recognized
by several healthcare organizations worldwide.
Recent Advances in Nanocarrier-mediated Combination Drug Therapy for Tackling Solid-resistant Tumors
Authors: Rafiya Km , Awasthi Sakshi , Qureshi Saba Asif , Hasan Nazeer , Ahmad Farhan Jalees 
Published: January 2025

Abstract:
Cancer is a group of dynamic diseases characterized by uncontrollable growth and spread
of cells. The heterogenic nature of cancer hinders the abolishment of cancer resulting in a narrow
therapeutic index, the capacity of drug efflux, multidrug resistance, and unacceptable side effects.
The major challenge in the treatment of malignancies is multidrug resistance (MDR). A novel platform,
nanoscale delivery system, concluding desirable applications for the treatment of cancer with
targeted and controlled release of drugs, reducing the number of side effects and systemic toxicity.
Recent studies emphasize that combining 2 or more nanocarrier-mediated therapies may produce
complementary therapeutic effects, perhaps resulting in improved outcomes of cancer current therapies
like deterioration of drug resistance. Therefore, in this article, we scrutinize the recent advancement
addressing combination therapy by combining nanoparticles with anticancer drugs. It briefly
concludes a thorough overview of cancer, tumor or solid resistant tumors, the mechanism of resistant
tumors, current therapies for the treatment of solid tumors, and their challenges. It also covers various
types of nanoparticles used in cancer treatment, the usage of nanocarriers in resistant tumors, and
nanocarrier-based combinatorial therapy for the treatment of resistant tumors as well as its benefits.
However, this approach still needs to be improved for clinical applications.