bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Antimicrobial Stewardship in the Management of Vertebral Osteomyelitis: Analysis of Decade-long Data from a Central Taiwan Tertiary Teaching Hospital
Authors: Chen Chang-Hua , Kor Chew-Teng , Chang Ing-Lin , Chen Yu-Min , Kuo Su-Feng , Cheng Yeh Hua 
Published: November 2024

Abstract

Background: Vertebral osteomyelitis (VO) is associated with high morbidity rates[A1] . We conducted a retrospective observational cohort study to evaluate the effects of appropriate antibacterial therapies on the clinical outcomes of patients with VO. This study compared the outcomes of proper and empirical therapies to determine whether empirical antibiotic treatment versus targeted treatment based on microbial culture results leads to different long-term prognoses regarding complications and sequelae in [E2] patients with VO.
Methods: Patients diagnosed with VObetween January 2011 and February 2022 were selected from the Changhua Christian Hospital Clinical Research Database. The diagnosis of VO primarily relied on magnetic resonance imaging reports. We defined the microbiological relevance in patients with VO and identified the types of VO-related sequelae and complications in this cohort. This[A3] cohort was categorized into appropriate antibiotics(AA) and empirical therapy (ET).
Results: This cross-sectional cohort study collected data over ten years. In total, 230 patients with VO were included in our study. The mean age was 64.7 years, and 110 participants were men (30.8 %). [A4] Most of the participants had underlying diseases. Overall, 33.9 % of patients experienced complications[A5] , with a mortality rate of 4 %. The AA group had a significantly lower incidence of chronic low back pain than the ET group (6.9 % vs. 20.7 %, p=0.031).
Conclusions: Inappropriate antibiotic use in patients with VO has been associated with reduced symptomatic relief, highlighting the importance of antimicrobial stewardship. The symptoms improved with appropriate antibiotic therapy. Severe illness, rapid diagnosis, and early appropriate treatment are crucial for treating VO. This study emphasizes optimizing VO management within antimicrobial stewardship to enhance outcomes and reduce healthcare burden. Patients requiring surgery often experience spinal instability, severe nerve compression, or related complications. Severe lower back pain is joint, and appropriate antibiotics significantly alleviate this symptom compared with[E6] empirical therapy. Identifying the causative pathogens of targeted therapy is essential for better long-term outcomes.
Laboratory-scale system for developing in-service pipeline welding under oil flow at 300°C
Authors: Miná Émerson Mendonça , Franco Marília Ferreira , Marinho Ricardo Repold , Silva Yuri Cruz , Dalpiaz Giovani , Paes Marcelo Torres Piza , Zumpano Petrônio , Motta Marcelo Ferreira , Silva Cleiton Carvalho , Miranda Hélio Cordeiro 
Published: November 2024

Abstract

The oil and gas industry often faces the need to halt the transportation and production of its products for repair operations or to bypass flowlines, resulting in unwanted costs. These costs can be avoided by employing a specialized welding procedure performed during service. However, executing such a technique requires great care due to the presence of flammable fluids and high-temperature gases flowing through pipelines. To address this challenge, the Welding Research and Technology Laboratory at the Universidade Federal do Ceará has developed a system for heating and flowing oil along a pipeline, enabling in-service welding procedures on a laboratory scale. This system has the capability to adjust the oil flow rate (up to 140 l/min), oil temperature (up to 300°C), welding angle (0° to 45°), and positioning of different materials with varying thicknesses. The system was evaluated in terms of maximum fluid flow rate by experiments. It was also assessed the effect of sieves placed into the pipe sample on velocity of fluid distribution for different levels of flow rate (30 l/min, 60 l/min, 90 l/min and 140 l/min) by numerical simulation. An in-service welding method was proposed to achieve data from in-service welding flowing flammable heated fluid to keep safety. The method proposed was assessed using a pipe and sleeve of 316L stainless steel with 7.1 mm. The results obtained showed that initial steps of the method proposed showed to be conservative enough to put the welder and engineering staff in safe during in-service welding with heated oil flowing during welding experiments. The simulations predicted the inner temperature of the pipe with reasonable accuracy.
Comparative analysis and directed protein evolution yield an improved degron technology with minimal basal degradation, rapid inducible depletion, and faster recovery of target proteins.
Authors: Adli Mazhar , Xing De , Bai Tao , Neyisci Ozlem , Paylakhi Seyedehzahra , Duval Alexander , Tekin Yasemin 
Published: November 2024

Abstract

Biological mechanisms are inherently dynamic, requiring precise and rapid gene manipulation for effective characterization. Traditional genetic perturbation tools such as siRNA and CRISPR knockout operate on timescales that render them unsuitable for exploring dynamic processes or studying essential genes, where chronic depletion can lead to cell death. Here, we compared four major inducible degron systems—dTAG, HaloPROTAC, and two auxin-inducible degron (AID) tools—in human pluripotent stem cells. We evaluated basal degradation levels, inducible degradation kinetics, and recovery dynamics for endogenously tagged genes. While the AID 2.0 system is the most efficient for rapid protein degradation, it exhibited higher basal degradation and slower recovery after ligand washout. To address these challenges, we applied directed protein evolution, incorporating base-editing-mediated mutagenesis and iterative functional selection and screening. We discovered novel OsTIR1 variants, including S210A, with significantly enhanced overall degron efficiency. The resulting system, designated as AID 3.0, demonstrates minimal basal degradation and rapid and effective target protein depletion and substantially rescues the cellular and molecular phenotypes due to basal degradation or slow target protein recovery in previous systems. We conclude that AID 3.0 represents a superior degron technology, offering a valuable tool for studying gene functions in dynamic biological contexts and exploring therapeutic applications. Additionally, the research strategy used here could be broadly applicable for improving other degron and biological tools.
Improving Intrusion Detection Systems' Resilience to Adversarial Attacks through Feature Engineering and Hybrid Metaheuristic Algorithms
Authors: Giri Kanak , Dadheech Pankaj , Gupta Mukesh Kumar 
Published: November 2024

Abstract

Intrusion Detection Systems (IDS) are essential for securing computer networks against malicious activities. However, the rise of adversarial attacks seriously threatens the robustness and efficacy of IDS models. With the increasing prevalence of adversarial attacks on intrusion detection systems (IDS), it has become crucial to develop robust defence mechanisms to make sure the integrity and reliability of these systems. This paper presents a novel approach that combines Particle Swarm Optimization (PSO), Gradient Boosting Machines (GBM), genetic operators, and deep neural networks (DNN) with defence mechanisms to improve the resilience of IDS in order to stop adversarial attacks. The proposed approach starts with a feature engineering stage, where PSO and GBM are utilised to select and optimise the most informative features from the input dataset. Genetic operators are then employed to refine the feature selection process further, ensuring the creation of robust and discriminative feature subsets. In the subsequent stage, a deep neural network model is constructed with defence mechanisms, including adversarial training, input perturbation, and ensemble learning. These defence mechanisms work synergistically to monitor and improve the IDS's capacity to find and classify normal and adversarial network traffic accurately. The well-known NSL-KDD dataset is utilised to assess how successful the suggested method is. Experimental findings show that the integrated framework outperforms current techniques. Additionally, the system shows increased resistance to various adversarial techniques, such as evasion, poisoning, and adversarial samples. Overall, this study bridges the gap between adversarial attacks and intrusion detection, offering a powerful defence framework that can be integrated into existing IDS architectures to extenuate the consequence of adversarial threats and ensure the integrity and reliability of network security systems.
DNAHLM - DNA sequence and Human Language mixed large language Model
Authors: Wang Liang 
Published: November 2024

Abstract

There are already many DNA large language models, but most of them still follow traditional uses, such as extracting sequence features for classification tasks. More innovative applications of large language models, such as prompt engineering, RAG, and zero-shot or few-shot prediction, remain challenging for DNA-based models. The key issue lies in the fact that DNA models and human natural language models are entirely separate; however, techniques like prompt engineering require the use of natural language, thereby significantly limiting the application of DNA large language models. This paper introduces a pre-trained model trained on the GPT-2 network, combining DNA sequences and English text, and uses a unified BPE tokenization method. We then convert classification and other downstream tasks into Alpaca format instruction data, and perform instruction fine-tuning on this pre-trained model to create a fine-tuned model capable of handling multiple tasks. The model has demonstrated its effectiveness in DNA related zero-shot prediction and multitask application. This research provides a highly promising direction for building a unified DNA sequence task framework.
Co-infection status of PCV2 and PRRSV with other pathogens in Porcine Circovirus Associated Disease and Porcine Respiratory Disease Complex
Authors: Xie Chang-zhan , Zhang Ping , Tao Yi-mo , Fan Qian-xi , Wang Zheng , Shang Wei-ping , Nan Fu-long , Zhang He , Jin Ning-yi. , Lu Hui-jun. 
Published: November 2024

Abstract

PCV2 and PRRSV are involved in a variety of disease syndromes, collectively referred to as Porcine Circovirus Associated Disease (PCVAD) and Porcine Respiratory Disease Complex (PRDC). To explore the effects of other pathogens on porcine PCVAD and PRDC. This study firstly conducted an epidemiological investigation on PPV, confirmed the prevalence of PPV sub-types in China; We then determined that other pathogens were more common in POS-PCV2 (PCV2 positive other pathogen detection rate) than NEG-PCV2 (other pathogen detection rate PCV2 negative); however, in POS-PRRSV (PRRSV positive other pathogen detection rate), the detection rate was lower than that of NEG-PRRSV (other pathogens were negative for PRRSV). To study the effect of PPV2, PPV3, PPV4, PPV5, PPV6, PPV7, PRRSV, PCV2, PCV3, TTsuV1, and TTsuV2 co-infection on PCV2-associated disease (PCVAD) and porcine respiratory disease complex (PRDC), we used a logit-link and a generalized linear model (GLM) of the binomial error distribution and compute the predictions. PCV3 (P < 0.001***), PRRSV (P < 0.001***), and TTsuV2 (P < 0.001***) were predicted to be the most significant factors associated with PCV2 in PCVAD and PRDC, PCV2 (P < 0.001***), PCV3 (P < 0.001***) and TTsuV2 (P = 0.003**) were the most significant factors associated with PRRSV in PCVAD and PRDC. These findings determine that PPV2, PPV3, PPV4, PPV5, PPV6, PPV7, PRRSV, PCV2, PCV3, TTsuV1, and TTsuV2 viruses are statistically associated as co-infectors frequency with PCV2 in PRDC and PRRSV in PCVAD diseased pigs through logit-link and a generalized linear model (GLM) of the binomial error distribution.
AFF-LightNet: Attentional Feature Fusion Based Lightweight Network for Ship Detection
Authors: Yuan yingxiu , Yu Xiaoyan , Rong Xianwei , Wang Xiaozhou 
Published: November 2024

Abstract

Efficient mobile detection equipment plays a vital role in ensuring maritime safety, and accurate ship identification is crucial for maritime traffic. Recently, advanced learning-based methods boost the accuracy of ship detection, but face challenges on mobile devices due to size and computation. Thus, we propose a lightweight ship detection network based on feature fusion, called AFF-LightNet. We introduce iterative attentional feature fusion (IAFF) into the proposed neck network, improving the efficiency of feature fusion by introducing a multi-scale channel attention module. Also, Conv is replaced by DCNv2 in the backbone network to further improve the detection accuracy of the proposed network. DCNv2 enhances the spatial sampling position in convolution and Rol pooling by introducing offsets. Moreover, a lightweight convolution GhostConv was introduced into the head network to reduce the number of parameters and computation cost. Last, SIOU was leveraged to improve the convergence speed of the model. We conduct extensive experiments on the publicly available dataset SeaShips and compare it with existing methods. The experimental results show that compared with the standard YOLOv8n, the improved network has an average accuracy of 98.8%, an increase of 0.4%, a reduction of 1.9 G in computational complexity, and a reduction of 0.19 M in parameter count.
Dynamics Analytical Calculation Model for Seismic Response of Rocking Steel Piers
Authors: Zhuge Hanqing , Jia Zhenlei , Han Qiang , Du Rui , Niu Chenpeng 
Published: November 2024

Abstract

The prestressed self-centering rocking steel bridge pier with external energy-dissipating devices has excellent seismic and economic performance and broad application prospects. This paper establishes a prediction model for the height of the compression zone at the pier bottom based on the existing statics analytical model of the rocking steel bridge piers under the horizontal cyclic load. Furthermore, based on the dynamics Lagrange’s equation and the conservation theorem of angular momentum before and after the impact, a dynamics analytical calculation method for the rocking steel pier structural system is proposed, which considers the energy dissipation in the plastic hinge zone at the pier bottom and the collaborative work of multiple components under horizontal ground motions. Compared with the calculation results of the static and dynamic refined finite element models, for rocking steel piers with different structural parameters, the statics analytical method can obtain accurate load–displacement hysteresis curves. Moreover, the displacement time history results and restoring force–displacement curves of the proposed dynamics analytical model are quite accurate. The dynamics analytical calculation method proposed in this paper can provide an important support for the establishment of seismic design method of the rocking steel pier.
LMS-Res-YOLOv8: Lightweight and Multi-scaleCucumber Detection Model with Residual Blocks
Authors: Li Bo , Zhong Guangjin , Ke Wei 
Published: November 2024

Abstract

Timely and efficient detection of greenhouse cucumbers is critical to improving agricultural production efficiency. Sincecucumber grows in complex environments, it is quite challenging to achieve high identification accuracy. Aiming to improvedetection accuracy and facilitate practical application, we proposed the LMS-Res-YOLOv8 (Lightweight Multi-Scale featurefusion module with Residual blocks) cucumber detection model. Firstly, we replace the C2f module with the HEU (High-Efficiency Unit with residual blocks) to enhance the multi-scale representation of features and effectively improve detectionaccuracy. Secondly, YOLOv8_n’s head is replaced with the DE-HEAD (Decoupled and Efficient detection HEAD) to decreasethe model’s parameters, floating-point operation, and size. Finally, the ordinary convolution in YOLOv8_n’s backbone and neckare replaced with the KernelWarehouse dynamic convolution proposed by Intel in 2023 to achieve a better balance betweenparameter efficiency and representation capability. The experimental results show that our model has improved mAP@0.5to 97.9% on the cucumber dataset we constructed, a 0.7% increase over the benchmark model YOLOv8_n. More stringentmAP@0.5:0.95 reaches 87.8%, showing an increase of 2.3%. The FLOPs decreased from 8.1G to 5.4G, representing a33.3% drop. The learnable parameters decrease from 3.01M to 2.43M, representing a 19.3% reduction. It proves that ourLMS-Res-YOLOv8 achieves a good balance between detection performance and model complexity, with potential applicationsin edge devices for cucumber detection.
WITHDRAWN: The Impact of Artificial Intelligence-Powered Writing Assistance Systems on Metacognitive Writing Strategies
Authors: Berk Ece Hatice , Aydin Selami 
Published: November 2024

Abstract

The full text of this preprint has been withdrawn by the authors as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Sensitivity Analysis of the Kinematic Parameters During the Industrial Polishing Process of Ceramic Floor Tiles
Authors: Sousa Fabio J. P. , Wagner Marcel , Gonçalves Rennáh , Halla Ricardo , Klar Matthias , Aurich Jan C. 
Published: November 2024

Abstract

This work is focused on the industrial polishing process of ceramic floor tiles. The main goal is to estimate the impact of small deviations between nominal and actual values of three operational parameters on the glossiness of polished surfaces. These operating parameters are the most important kinematic variables that can be selected in industrial systems to control the movement of the grinding tools. Computational simulations were used to determine the abrasive trajectories so that the polishing uniformity could be quantified. Based on the simulated values the sensitivity of the polishing quality against kinematic deviations was quantitatively obtained. Such results are intended to support the daily tasks of operators as well as further research on process optimization.
LOROS: Laboratory Simulations of the Optical RadiOmeter composed of CHromatic Imagers (OROCHI) Experiment of the Martian Moons eXploration (MMX) Mission
Authors: Stabbins Roger , Kameda Shingo 
Published: November 2024

Abstract

The Laboratory OROCHI Simulator (LOROS) is an emulator of the Optical RadiOmeter composed of CHromatic Imagers (OROCHI), a multispectral and multiview imaging system for the Japan Aerospace Exploration Agency (JAXA) Martian Moons eXploration (MMX) spacecraft, that will study Phobos and Deimos with the objective of determining their origin. OROCHI consists of 8 visible/near-infrared (390-950 nm) spectral channels, hosted on 8 separate camera systems, arranged in a 3x3 grid (with an empty central site) with 10 cm spacing. Prior to completion of the OROCHI Flight Model it is important to demonstrate the ability of the cameras to resolve the subtle spectral features expected at Phobos and Deimos, and to investigate the implications of the multiview configuration when performing near-field imaging on the Phobos surface. LOROS provides a robust and portable emulator of the OROCHI Flight Model, composed of commercial off-the-shelf components and materials compliant with the ISO-6 restrictions of the JAXA Extraterrestrial Sample Curation Centre. Here we describe the configurations of the components and control software that we have developed and present the results of a series of calibration experiments, demonstrating the comparable performance of the two systems. We achieve agreement within 3% across sensor performance metrics of read noise, saturation capacity and sensitivity, and demonstrate the measurement of the reflectance of a dark diffuse reflector reference standard with a mean temporal signal-to-noise ratio of 120.
Automating Quality Assurance: The Role of Error Detection and Logging Algorithms in Multi- Environment Applications
Authors: Mukkamala Hema Sai , Tadipatti Vijayalakshmi , Vemula Vaishnavi , Tirumare Kavya Sri , Gopi Arepalli 
Published: November 2024

Abstract

The study's primary focus is the quality of cross-platform application development. As the demand for apps grows, ensuring that they perform properly across all platforms and operating systems is more critical than ever. This study focuses on five essential quality criteria: scalability, performance, security, maintainability, and usability. It emphasizes developers' distinct concerns, such as device fragmentation, performance differences, and testing challenges. The article discusses recommended practices for improving application quality, such as CI/CD methodologies, dependable testing techniques, and sound design concepts. The essay forecasts future improvements impacting cross-platform programming and presents real-world examples to demonstrate effective implementation.
Studying the characteristics of physical development of young athletes
Authors: Rylova N. V. 
Published: November 2024

Medical and biological support for the training of young athletes is a separate specific part of medical science and practice. This area of medicine includes determining the health and physical development of athletes, as well as diagnosing, treating and preventing diseases and injuries associated with physical education and sports. The main goal of medical and biological support for children’s and youth sports is the harmonious development of the child within the chosen sport, taking into account his age characteristics, functionality, physical development, including puberty.Objective. The purpose of the study is to investigate the characteristics of the physical development of young athletes of various specializations.Materials and methods: 102 young teenage athletes took part in the study. The control group consisted of 28 schoolchildren who were not involved in sports professionally. The first group of the study included 35 young athletes from the «Children and Youth Sports School of Swimming». The second group of the study consisted of 47 teenagers, students of a specialized children’s and youth sports school of the Olympic reserve in field hockey. The third group of the study included 20 young athletes, students of a specialized children’s and youth sports school of Olympic reserve fencing.Results: In terms of physical development parameters, young athletes have indicators above the average values of children in the control group. The percentage of body fat in boys and girls in the control group was significantly higher than in young athletes. At the same time, the level of muscle mass of boys who do not engage in sports is lower than that of the group of athletes.Conclusions: Based on the results of the work, it was established that the physical development of young athletes has significant differences from their peers who do not play sports professionally.