bluuebunny/crossref_metadata_2025 huggingface dataset:
A customized convolutional neural network-based approach for weeds identification in cotton crops
Authors: Faisal Hafiz Muhammad , Aqib Muhammad , Mahmood Khalid , Safran Mejdl , Alfarhood Sultan , Ashraf Imran
Published: January 2025

Smart farming is a hot research area for experts globally to fulfill the soaring demand for food. Automated approaches, based on convolutional neural networks (CNN), for crop disease identification, weed classification, and monitoring have substantially helped increase crop yields. Plant diseases and pests are posing a significant danger to the health of plants, thus causing a reduction in crop production. The cotton crop, is a major cash crop in Asian and African countries and is affected by different types of weeds leading to reduced yield. Weeds infestation starts with the germination of the crop, due to which diseases also invade the field. Therefore, proper monitoring of the cotton crop throughout the entire phases of crop development from sewing to ripening and reaping is extremely significant to identify the harmful and undesired weeds timely and efficiently so that proper measures can be taken to eradicate them. Most of the weeds and pests attack cotton plants at different stages of growth. Therefore, timely identification and classification of such weeds on virtue of their symptoms, apparent similarities, and effects can reduce the risk of yield loss. Weeds and pest infestation can be controlled through advanced digital gadgets like sensors and cameras which can provide a bulk of data to work with. Yet efficient management of this extraordinarily bulging agriculture data is a cardinal challenge for deep learning techniques too. In the given study, an approach based on deep CNN-based architecture is presented. This work covers identifying and classifying the cotton weeds efficiently alongside a comparison of other already existing CNN models like VGG-16, ResNet, DenseNet, and Xception Model. Experimental results indicate the accuracy of VGG-16, ResNet-101, DenseNet-121, XceptionNet as 95.4%, 97.1%, 96.9% and 96.1%, respectively. The proposed model achieved an accuracy of 98.3% outperforming other models.
Genome-wide analysis of sugar transporter gene family in Erianthus rufipilus and Saccharum officinarum, expression profiling and identification of transcription factors
Authors: Akbar Sehrish , Hua Xuiting , Zhang Yingying , Liu Gang , Wang Tianyou , Shi Huihong , Li Zhen , Qi Yiying , Habiba Habiba , Yao Wei , Zhang Mu-Qing , Zhang Jisen
Published: January 2025

Sugar, the primary product of photosynthesis, is a vital requirement for cell activities. Allocation of sugar from source to sink tissues is facilitated by sugar transporters (ST). These STs belong to the Major Facilitator Superfamily (MFS), the largest family of STs in plants. In this study, we performed genome wide and gene expression data analysis to identify the putative ST genes in Erianthus rufipilus (E. rufipilus) and in Saccharum officinarum (S. officinarum). We identified 78 ST gene families in E. rufipilus and 86 ST gene families in S. officinarum. Phylogenetic analysis distributed the ST genes into eight distinct subfamilies (INT, MST, VGT, pGlcT, PLT, STP, SFP and SUT). Chromosomal distribution of ST genes clustered them on 10 respective chromosomes. Furthermore, synteny analysis with S. spontaneum and Sorghum bicolor (S. bicolor) revealed highly colinear regions. Synonymous and non-synonymous ratio (Ka/Ks) showed purifying selection in gene evolution. Promoter analysis identified several cis-regulatory elements, mainly associated with light responsiveness. We also examined the expression pattern of ST genes in different developing tissues (mature leaf, pre-mature stem, mature stem and seedling stem). Under sugar stress, we identified the significant ST genes showing differential expression patterns. Moreover, our yeast one-hybrid (Y1H) assays identified NAM, ATAF and CUC (NAC) and Lesion Simulating Disease (LSD) potential transcription factors (TFs) that may bind to the SUT1-T1 promoter in S. officinarum, showing negative correlation pattern with SUT1-T1. Our results deepen our understanding of ST gene evolution in Saccharum species and will facilitate the future investigation of functional analysis of the ST gene family.
Sustainable flavor, healthy future: toward a green transition of the UPV in the food sector
Authors: López López Rebeca , Picó Sirvent María Belén , Domingo-Calabuig Débora , Martínez-Monzó Javier , García-Segovia Purificación
Published: January 2025

Introduction

Due to the current climatic situation of the planet and the increase in concern for the environment, the Universitat Politècnica de València (UPV) aims to be a model for the university community in terms of the preservation of the ecosystem and prevention of the environmental impact caused by daily tasks; thus, aligning itself with the goals of the 2030 Agenda. For this reason, a project has been launched to carry out the green transformation of the UPV toward a university that prioritizes sustainability in all its areas.

Methods

As part of this project, a survey was conducted using anonymous online questionnaires for the student population and employees. The study aimed to gauge the perception of sustainability and campus food supply and included items related to waste management and public awareness. A total of 800 students and 100 employees from the three UPV campuses (Vera, Alcoy, and Gandía) participated, ranging from 17 to 66 years old.

Results

After the statistical analysis of the results, significant differences were identified in most of the questions of the different thematic blocks and, in some cases, in terms of gender and age group. In general, good knowledge about sustainability was observed, although participation in initiatives organized by the university was low in both population groups. On the other hand, as the age of the participants increased, a greater adoption of sustainable behaviors was observed, especially in buying and recycling habits. Regarding the food supply on university campuses, the need to improve it to promote healthier and more sustainable options is highlighted. This work investigates ways to improve the menu choices offered in university settings to promote healthier and more sustainable habits. Additionally, the study aims to identify potential obstacles within the university environment that may hinder these efforts, raise awareness, and encourage more environmentally friendly behaviors.

Discussion

The proposed improvements include: (i) increasing the variety of plant-based options, (ii) sourcing food locally to reduce its carbon footprint, and (iii) implementing a waste management system that encourages recycling.
Physicians’, pharmacists’, and nurses’ education of patients about antibiotic use and antimicrobial resistance in primary care settings: a qualitative systematic literature review
Authors: Balea Lavinia Bianca , Gulestø Ragnhild J. A. , Xu Hongxuan , Glasdam Stinne
Published: January 2025

Background

Patients’ adherence to antibiotic treatment and related prevention of AMR is significant. Understanding healthcare professionals’ strategies for advising and educating patients in primary care settings is crucial.

Aim

From the perspectives of professionals and patients, to explore how physicians, pharmacists, and nurses educate patients about antibiotic use and antimicrobial resistance in primary care settings.

Methods

A qualitative systematic literature review was conducted in MEDLINE, EMBASE, CINAHL Complete, Eric, SocINDEX, PsycInfo, Web of Science and Scopus. The study included 102 publications, followed PRISMA recommendations and was registered in PROSPERO (reg.no. CRD4202455761). The studies were screened and selected based on specific inclusion and exclusion criteria using Covidence. Quality appraisal followed the Critical Appraisal Skills Program (CASP) qualitative study checklist. Data were extracted, and the analysis consisted of a descriptive numerical summary analysis and a qualitative thematic analysis.

Results

The analyzed studies spanned multiple countries and settings and included perspectives of primary care physicians, pharmacists, nurses and patients. Two main themes emerged: (1) Relationships between professionals and patients influenced educational strategies, showing that trust and rapport between healthcare professionals and patients played a crucial role in shaping educational strategies around antibiotic use; (2) The organizational structures challenged professionals in guiding and educating patients, highlighting how limited resources, time constraints, and system-level pressures hindered healthcare professionals’ ability to provide consistent and effective education. Often, structural challenges led to not educating the patients on the risks of antibiotic misuse and antimicrobial resistance. The use of delayed prescriptions emerged as a strategy for improved AMR stewardship and to meet patients’ expectations for antibiotic treatment, though it raised concerns about undermining professional responsibility and authority in ensuring appropriate antibiotic use.

Conclusion

Healthcare professionals’ role in educating patients about antibiotic use and AMR in primary care settings was complex, with different challenges faced by nurses, pharmacists and primary care physicians. These challenges extended beyond the clinical level, including relational, social and structural factors. Power dynamics, trust issues, and time pressures often hindered effective education on antibiotic use. Addressing gaps in education on antibiotic use and AMR requires acknowledging these multifaceted challenges, with future efforts focusing on better supporting healthcare professionals in this context.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD4202455761.
The experience of Italian student athletes enrolled in a dual career university program: the challenges of employability
Authors: Belluzzi Mattia , Ferraboli Alessia , Gozzoli Caterina , D’Angelo Chiara
Published: January 2025

Introduction

In the so-called “new career era,” career transitions and employability have attracted growing attention. For elite athletes, the Dual Career experiences may be regarded as a protective factor during various career transitions, with the end-of-career transition being closely linked to employability. This contribution aims to explore the dual career paths of athletes through the lens of graduate employability, as perceived by the individuals themselves. Thus, employability can be considered as an important resource for athletes during the many transitions that characterize their sports careers.

Methodology

Study participants included 21 student-athletes participating in the first four editions of the Dual Career program at an Italian university. Using a phenomenological-interpretive approach, semi-structured interviews and focus groups were conducted with participants. A top-down and bottom-up content analysis was conducted using Nvivo software for qualitative analysis.

Results

The data derived from interviews and focus groups are presented with reference to four dimensions—Human Capital, Social Capital, Individual Behaviors, and Individual Attributes—that, according to Clarke's integrated model, impact perceived employability in graduate students, including student-athletes. The results highlight traits shared with classic university students while, at the same time, emphasizing peculiar sub-dimensions.

Discussion

This study integrates the constructs of employability and career transitions in the target group of university athletes. Through the Clarke's model, which offers a complex and multidimensional definition of employability, this research explores why the dual career pathway represents a resource for athletes during transitions. The results can serve as a first step in developing good practices for supporting and guiding student-athletes enrolled in Dual Career programs, by addressing aspects recognized in the scientific literature as practical implications for supporting employability development.
Applying the socio-ecological systems framework to assess the sustainability of tropical cattle ranching in Mexico
Authors: Figueroa Daniela , Galicia Leopoldo , Ávila Foucat Véronique Sophie , Díaz-Morales Benito
Published: January 2025

The conceptual framework of socio-ecological systems (SES) has been used to redirect resource management practices towards more sustainable scenarios. Utilizing surveys conducted with 350 producers of a silvopastoral cattle network in southern Mexico, the structure and interactions of cattle SES were characterized. Furthermore, based on information derived from a workshop with producers, the framework was operationalized through variables representing action situations and generating outcomes in terms of management, organizational issues, and ecosystem services. This participatory exercise allowed for the identification of locally relevant sustainability components and ranges that can be generalized to other similar SES in Latin America, specific socio-ecological challenges, and potential actions leading to maximizing the sustainability of silvopastoral ranches in the tropics. Challenges include an excessive number of intermediaries, labor conditions accentuating poverty, marketing chains inaccessible to small scale producers, and low diversification. These issues can be addressed within the cattle SES through technical and financial support from involved governmental institutions and strengthening the local governance system. This work bridges gaps in cattle research by highlighting that sustainable intensification through the establishment of silvopastoral systems is possible within specific ranges, and sustainability can be defined, understood, and built by producers from the territories.
Evaluation of equine perineural anesthesia simulators with integrated success control for veterinary education
Authors: Chodzinski Anna , Wissing Sandra , Tipold Andrea , Geburek Florian
Published: January 2025

The skills necessary to perform diagnostic perineural anesthesia in equids belongs to one of the Day One Competences of a veterinarian, so every veterinary graduate should be able to perform them correctly. For logistical, hygienic and ethical reasons, practical exercises on cadaver limbs are not accessible to all students. Two equine distal limb simulators were developed and evaluated as an additional instructional tool to train the required skills. Both simulators were designed and built with an integrated success control, with Simulator I (S1) designed to be a simplified anatomical model and Simulator II (S2), a more realistic model. The simulators were tested by 68 students in the 5th year who were divided into two groups. Thirty-four students received a training session using the simplified anatomical model (S1) and the other 34 students one on cadaver limbs, the usual instructional tool. The practical learning success of both groups was validated using S2. Additionally, data on self-efficacy were collected. The results show that the two groups did not differ significantly in their practical learning success, whereas self-efficacy of both groups increased significantly after the sessions. An evaluation performed by 7 veterinarians and 49 students of the 5th year indicate that the simulators are suitable for teaching perineural anesthesia in the equine distal limb. However, S2 could be more realistic. The simulators will be used as a supplement to exercises on cadaver limbs to enable all students to practice perineural anesthesia.
Endovascular Preparation With Innovative Custom-Made Stent-Graft Before Kidney Transplantation: The Solution for Patients With Hostile Iliac Calcification
Authors: Arsicot Matthieu , Ammollo Raffaele Pio , Bordet Marine , Dehina-Khenniche Leila , Thaunat Olivier , Della Schiava Nellie , Millon Antoine , Seizilles De Mazancourt Emilien , Badet Lionel , Matillon Xavier
Published: January 2025

The increasing age of patients with end-stage renal disease raises the issue of hostile arterial access for transplantation, with technical difficulties associated with clamping and suturing the iliac artery. Some of these patients - who theoretically represent those who would benefit the most from transplantation in terms of mortality - are contraindicated because of anatomical and medical issues. In this context, a specific endovascular device called EndoPreKiT (Endovascular Preparation for Kidney Transplantation) has been designed, enabling arterial access for transplantation via a mini-invasive procedure. It consists of a woven Dacron supported by self-expanding nitinol rings, ensuring anchorage and allowing arterial clamping. The middle part of the anterior face of the device is stentless, enabling the anastomosis directly onto the Dacron once the calcified artery wall has been removed. After a cadaveric study validating its technical feasibility, such device was successfully implanted in 10 patients considered unfit for transplantation due to severe wall calcification. Two of them have been successfully transplanted with excellent outcomes after 13 and 3 months of follow-up. EndoPreKiT device may be a significant breakthrough in transplant surgery, that could expand the horizon of eligibility to include even the most fragile patients with challenging arterial access.
Winglet Design for Aerodynamic and Performance Optimization of UAVs via Surrogate Modeling
Authors: Nikolaou Eleftherios , Kilimtzidis Spyridon , Kostopoulos Vassilis
Published: January 2025

The aerodynamic performance of an aircraft can be significantly enhanced by incorporating wingtip devices, such as winglets, which primarily reduce lift-induced drag caused by wingtip vortices. This study introduces a comprehensive optimization framework for designing winglets on a Class I fixed-wing mini-UAV, aiming to maximize aerodynamic efficiency and operational performance. Using surrogate-based optimization (SBO) techniques, this research developed winglet geometries with varying geometric parameters such as length, cant angle, and sweep angle with their performance being evaluated through high-fidelity Computational Fluid Dynamics (CFD) simulations. These simulations utilized Reynolds-Averaged Navier–Stokes (RANS) equations coupled with the Spalart–Allmaras turbulence model to capture the intricate flow dynamics around the UAV in different flight phases. The integration of SBO techniques allowed for an efficient exploration of the design space while reducing computational costs associated with iterative high-fidelity simulations. In particular, the proposed SBO framework optimized the UAV’s aerodynamic characteristics, including lift-to-drag ratio and drag reduction, followed by a stability and control analyses to ensure balanced performance for the optimal configurations. Dynamic stability evaluations revealed improved flight characteristics, maintaining control across operational envelopes. The results demonstrated a significant improvement in aerodynamic coefficients, range, endurance, and reduction in battery consumption throughout the entire UAV operational envelope, underscoring the potential of innovative winglet designs to enhance UAV performance across diverse mission profiles.
A Channel Attention-Driven Optimized CNN for Efficient Early Detection of Plant Diseases in Resource Constrained Environment
Authors: Parez Sana , Dilshad Naqqash , Lee Jong Weon
Published: January 2025

Agriculture is a cornerstone of economic prosperity, but plant diseases can severely impact crop yield and quality. Identifying these diseases accurately is often difficult due to limited expert availability and ambiguous information. Early detection and automated diagnosis systems are crucial to mitigate these challenges. To address this, we propose a lightweight convolutional neural network (CNN) designed for resource-constrained devices termed as LeafNet. LeafNet draws inspiration from the block-wise VGG19 architecture but incorporates several optimizations, including a reduced number of parameters, smaller input size, and faster inference time while maintaining competitive accuracy. The proposed LeafNet leverages small, uniform convolutional filters to capture fine-grained details of plant disease features, with an increasing number of channels to enhance feature extraction. Additionally, it integrates channel attention mechanisms to prioritize disease-related features effectively. We evaluated the proposed method on four datasets: the benchmark plant village (PV), the data repository of leaf images (DRLIs), the newly curated plant composite (PC) dataset, and the BARI Sunflower (BARI-Sun) dataset, which includes diverse and challenging real-world images. The results show that the proposed performs comparably to state-of-the-art methods in terms of accuracy, false positive rate (FPR), model size, and runtime, highlighting its potential for real-world applications.
Physicochemical Differences in the Leaves of the Two Agave salmiana Subspecies Grown in Different Regions
Authors: Campos-Herrera Oscar , González-Cruz Leopoldo , Silva-Martínez Guillermo Antonio , Flores-Martínez Norma Leticia , Ortíz-Basurto Rosa Isela , Bernardino-Nicanor Aurea
Published: January 2025

The domestication process of agaves has allowed this plant to adapt to different environmental conditions, which has led to the emergence of subspecies of the same species with altered morphological characteristics. This may lead to differences in their nutritional properties. For this reason, the aim of this study was to determine the differences in the physiochemical properties of two subspecies of Agave salmiana (crassispina and salmiana) grown in regions with different environmental characteristics. Although both regions have clay soils, some differences in cation exchange capacity (CEC) and nutrient concentration were found, which may have induced changes in leaf size in Agave during the adaptation process. Slight differences were observed in the thickness of the cuticle membrane in both agaves, but significant differences were found between the adaxial and abaxial sides. Moreover, only some macronutrients were significantly different in both agaves, so the subspecies and the development zone apparently have no influence on their composition. No significant differences were found in the color of the leaves based on the growing region of the agaves. However, the removal of the cuticle affects color perception, with significant differences observed between leaves with and without cuticles. According to the results obtained, the growing region of the Agave subspecies has a drastic effect on plant size and some nutritional traits and pigments but a lesser effect on overall coloration. The two subspecies of Agave salmiana, crassispina and salmiana, have different characteristics that enable them to adapt efficiently.
Analysis of Viability as Readout of Lymphocyte Transformation Test in Drug Hypersensitivity Diagnostics
Authors: Gyovai András , Metzler Gabriella , Papp Krisztián , Prechl József
Published: January 2025

In vitro tests of cellular activity form part of the diagnostic algorithm of drug hypersensitivity reactions. Because of the wide range of pharmacological mechanisms, clinical symptoms, genetic components, and laboratory tests involved, it is important to know how a particular test performs in the diagnostic procedure. We carried out a detailed retrospective analysis of more than 6000 measurements of numerous drug compounds tested in 738 serum samples over the past 6 years. Our cell viability-based lymphocyte transformation had a coefficient of variation of 10% and showed similar performance over the whole range of tested ages. With an adequate number of parallel measurements, the test can identify modest increases in stimulation indices with high confidence. Similar percentages of analytically positive responses (11.4%, 13.5%, and 9.7%) were observed for the three most frequently tested drug groups, namely, antibiotics, non-steroid anti-inflammatory agents, and anesthetics. These results confirm that cell viability tests are suitable alternatives for proliferation assays in drug allergy testing.
Chitosan-Based Semen Extenders: An Approach to Antibiotic-Free Artificial Insemination in Rabbit
Authors: Marco-Jiménez Francisco , Ferriz-Nuñez Celia , Viudes-de-Castro Maria Pilar , Vicente José Salvador , Lorenzo-Rebenaque Laura
Published: January 2025

Background/Objectives: The use of antibiotics in livestock contributes to antimicrobial resistance, highlighting the need for alternative solutions. Among these, chelating agents, like ethylenediaminetetraacetic acid (EDTA) and Chitosan, have shown potential in reducing bacterial contamination in seminal doses used in artificial insemination (AI), while preserving sperm quality. The objective of this study was to evaluate the potential use of EDTA and Chitosan as alternatives to antibiotics for the liquid storage of rabbit seminal AI doses. Methods: EDTA (20 mM) and Chitosan (0.05%) were tested both individually and in combination, by adding them to the semen extender, and their effects were compared with extenders containing antibiotics or none. The extenders were evaluated for microbial resistance and their ability to maintain sperm quality in vitro during refrigeration at 16 ± 1 °C for 72 h. To assess antimicrobial efficacy, Enterococcus faecalis was used. Seminal doses stored for 24 h were used for insemination under commercial conditions, and fertility rate and total kits born were evaluated. Results: Adding 0.05% Chitosan to the extender resulted in sperm parameters and bacterial load comparable to those achieved with antibiotics during refrigerated storage, yielding similar fertility rate and total kits born outcomes 24 h post-storage. In contrast, the use EDTA alone or in combination with Chitosan was less effective at controlling Enterococcus faecalis than the antibiotic extenders, which also resulted in a reduction of sperm total motility over storage period (0–72 h) and negatively impacted fertility rate and total kits born. Conclusions: Chitosan’s protective effect on sperm function, combined with its antimicrobial activity, makes it a promising alternative antimicrobial agent for the liquid storage of rabbit seminal AI doses.
Harnessing Non-Antibiotic Strategies to Counter Multidrug-Resistant Clinical Pathogens with Special Reference to Antimicrobial Peptides and Their Coatings
Authors: Mishra Shyam Kumar , Akter Tanzina , Urmi Umme Laila , Enninful George , Sara Manjulatha , Shen Jiawei , Suresh Dittu , Zheng Liangjun , Mekonen Elias Shiferaw , Rayamajhee Binod , Labricciosa Francesco M. , Sartelli Massimo , Willcox Mark
Published: January 2025

Antimicrobial resistance is a critical global challenge in the 21st century, validating Sir Alexander Fleming’s warning about the misuse of antibiotics leading to resistant microbes. With a dwindling arsenal of effective antibiotics, it is imperative to concentrate on alternative antimicrobial strategies. Previous studies have not comprehensively discussed the advantages and limitations of various strategies, including bacteriophage therapy, probiotics, immunotherapies, photodynamic therapy, essential oils, nanoparticles and antimicrobial peptides (AMPs) within a single review. This review addresses that gap by providing an overview of these various non-antibiotic antimicrobial strategies, highlighting their pros and cons, with a particular emphasis on antimicrobial peptides (AMPs). We explore the mechanism of action of AMPs against bacteria, viruses, fungi and parasites. While these peptides hold significant promise, their application in mainstream drug development is hindered by challenges such as low bioavailability and potential toxicity. However, advancements in peptide engineering and chemical modifications offer solutions to enhance their clinical utility. Additionally, this review presents updates on strategies aimed at improving the cost, stability and selective toxicity of AMPs through the development of peptidomimetics. These molecules have demonstrated effective activity against a broad range of pathogens, making them valuable candidates for integration into surface coatings to prevent device-associated infections. Furthermore, we discuss various approaches for attaching and functionalising these peptides on surfaces. Finally, we recommend comprehensive in vivo studies to evaluate the efficacy of AMPs and their mimetics, investigate their synergistic combinations with other molecules and assess their potential as coatings for medical devices.
The Role of ChatGPT and AI Chatbots in Optimizing Antibiotic Therapy: A Comprehensive Narrative Review
Authors: Antonie Ninel Iacobus , Gheorghe Gina , Ionescu Vlad Alexandru , Tiucă Loredana-Crista , Diaconu Camelia Cristina
Published: January 2025

Background/Objectives: Antimicrobial resistance represents a growing global health crisis, demanding innovative approaches to improve antibiotic stewardship. Artificial intelligence (AI) chatbots based on large language models have shown potential as tools to support clinicians, especially non-specialists, in optimizing antibiotic therapy. This review aims to synthesize current evidence on the capabilities, limitations, and future directions for AI chatbots in enhancing antibiotic selection and patient outcomes. Methods: A narrative review was conducted by analyzing studies published in the last five years across databases such as PubMed, SCOPUS, Web of Science, and Google Scholar. The review focused on research discussing AI-based chatbots, antibiotic stewardship, and clinical decision support systems. Studies were evaluated for methodological soundness and significance, and the findings were synthesized narratively. Results: Current evidence highlights the ability of AI chatbots to assist in guideline-based antibiotic recommendations, improve medical education, and enhance clinical decision-making. Promising results include satisfactory accuracy in preliminary diagnostic and prescriptive tasks. However, challenges such as inconsistent handling of clinical nuances, susceptibility to unsafe advice, algorithmic biases, data privacy concerns, and limited clinical validation underscore the importance of human oversight and refinement. Conclusions: AI chatbots have the potential to complement antibiotic stewardship efforts by promoting appropriate antibiotic use and improving patient outcomes. Realizing this potential will require rigorous clinical trials, interdisciplinary collaboration, regulatory clarity, and tailored algorithmic improvements to ensure their safe and effective integration into clinical practice.
Unseen Enemy: Mechanisms of Multidrug Antimicrobial Resistance in Gram-Negative ESKAPE Pathogens
Authors: Sakalauskienė Giedrė Valdonė , Malcienė Lina , Stankevičius Edgaras , Radzevičienė Aurelija
Published: January 2025

Multidrug antimicrobial resistance (AMR) represents a formidable challenge in the therapy of infectious diseases, triggered by the particularly concerning gram-negative Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. (ESKAPE) pathogens. Designated as a “priority” in 2017, these bacteria continue to pose a significant threat in 2024, particularly during the worldwide SARS-CoV-2 pandemic, where coinfections with ESKAPE members contributed to worsened patient outcomes. The declining effectiveness of current treatments against these pathogens has led to an increased disease burden and an increase in mortality rates globally. This review explores the sophisticated mechanisms driving AMR in gram-negative ESKAPE bacteria, focusing on Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterobacter spp. Key bacterial mechanisms contributing to resistance include limitations in drug uptake, production of antibiotic-degrading enzymes, alterations in drug target sites, and enhanced drug efflux systems. Comprehending these pathways is vital for formulating innovative therapeutic strategies and tackling the ongoing threat posed by these resistant pathogens.
Concatenated Attention: A Novel Method for Regulating Information Structure Based on Sensors
Authors: Zhang Zeyu , Chen Tianqi , Todo Yuki
Published: January 2025

This paper addresses the challenges of limited training data and suboptimal environmental conditions in image processing tasks, such as underwater imaging with poor lighting and distortion. Neural networks, including Convolutional Neural Networks (CNNs) and Transformers, have advanced image analysis but remain constrained by computational demands and insufficient data. To overcome these limitations, we propose a novel split-and-concatenate method for self-attention mechanisms. By splitting Query and Key matrices into submatrices, performing cross-multiplications, and applying weighted summation, the method optimizes intermediate variables without increasing computational costs. Experiments on a real-world crack dataset demonstrate its effectiveness in improving network performance.
Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture
Authors: Katı Bekir Eray , Küçüksille Ecir Uğur , Sarıman Güncel
Published: January 2025

The widespread use of the internet, coupled with the increasing production of digital content, has caused significant challenges in information security and manipulation. Deepfake detection has become a critical research topic in both academic and practical domains, as it involves identifying forged elements in artificially generated videos using various deep learning and artificial intelligence techniques. In this dissertation, an innovative model was developed for detecting deepfake videos by combining the Quantum Transfer Learning (QTL) and Class-Attention Vision Transformer (CaiT) architectures. The Deepfake Detection Challenge (DFDC) dataset was used for training, and a system capable of detecting spatiotemporal inconsistencies was constructed by integrating QTL and CaiT technologies. In addition to existing preprocessing methods in the literature, a novel preprocessing function tailored to the requirements of deep learning models was developed for the dataset. The advantages of quantum computing offered by QTL were merged with the global feature extraction capabilities of the CaiT. The results demonstrated that the proposed method achieved a remarkable performance in detecting deepfake videos, with an accuracy of 90% and ROC AUC score of 0.94 achieved. The model’s performance was compared with other methods evaluated on the DFDC dataset, highlighting its efficiency in resource utilization and overall effectiveness. The findings reveal that the proposed QTL-CaiT-based system provides a strong foundation for deepfake detection and contributes significantly to the academic literature. Future research should focus on testing the model on real quantum devices and applying it to larger datasets to further enhance its applicability.
Transmission Lines Insulator State Detection Method Based on Deep Learning
Authors: Tan Xu , Hou Shiying , Yang Fan , Li Zhimin
Published: January 2025

Aerial images are commonly used for detecting insulators in transmission lines to ensure their safe operation. However, each capture session generates thousands of insulator images, requiring manual collection, organization, and analysis. Therefore, to achieve automation in insulator state detection, this paper proposes a method based on deep learning for insulator state detection in transmission lines. Firstly, an insulator state detection model is built based on YOLOv7, and the model is improved using a bi-level routing attention mechanism and a content-aware up-sampling operator. Then, combined with dataset augmentation, including cropping, flipping, rotating, scaling, and splicing and a bounding box loss function incorporating a dynamic non-monotonic focus mechanism, 4000 visible images from different voltage levels of transmission lines are used for training. Finally, using a confusion matrix combined with comparative and ablation experiments, the results of insulator state detection are analyzed. Experimental results show that the proposed method achieves a detection accuracy of 97.1%. The detection accuracies for insulators exhibiting self-explosion, damage, flashover, and insulator strings are 93.5%, 98.6%, 97.5%, and 98.9%, respectively. Analysis results demonstrate that the proposed method can effectively realize insulator status detection.
Study on the Stability and Control of Gob-Side Entry Retaining in Paste Backfill Working Face
Authors: Xu Changtao , Wang Xiangyu , Chen Dingchao , Wang Guanghui , Niu Zhenpeng , Lu Huixing
Published: January 2025

Due to the poor stability of the roof and floor of the roadway in the 3-1 coal seam of Chahasu Coal Mine, traditional gob-side entry retaining (GER) methods fail to meet the production safety requirements. To address this, a GER technology using paste backfill was proposed. This study reveals the stability mechanism of the surrounding rock in GER with paste backfill through theoretical analysis, numerical simulation, and industrial experiments. First, theoretical analysis was conducted to determine the overburden movement characteristics under varying backfill ratios. Uniaxial compressive tests on the paste material demonstrated that its bearing capacity reaches a relatively stable state after 14–28 days of curing. Second, numerical simulations were performed to study the deformation patterns of the surrounding rock and mine pressure characteristics under backfill ratios of 65%, 75%, 85%, and 95%. The Strain-Softening model was used to calibrate the backfill material parameters. The results showed that as the backfill ratio increased, the support provided by the backfill material improved, leading to enhanced bearing capacity of the overlying strata, reduced mine pressure intensity, significantly decreased deformation of the roadway, and substantially improved stability of the surrounding rock. Third, under a backfill ratio of 95%, the evolution of the abutment stress during face advancement was investigated. It was found that as the working face advanced, the backfill material and the overlying strata gradually formed a stable composite structure, with the abutment stress in the mining area stabilizing over time. Finally, to address the issue of insufficient initial strength and limited support capacity of the paste backfill material, a comprehensive control system for surrounding rock stability was proposed. This system integrates a basic bolt-mesh-cable support structure with localized reinforcement using portal hydraulic supports. Field industrial practices demonstrated that after applying this comprehensive control technology, the convergence of roof and floor was approximately 190 mm and the convergence of two ribs was about 140 mm, effectively ensuring the stability of surrounding rock in GER with paste backfill working face.
The Effect of Whole-Body Vibration on Upper Extremity Function in Children with Cerebral Palsy: A Pilot Study
Authors: Kelaiditi Marianna , Lepoura Alexandra , Christakou Anna , Chrysagis Nikolaos , Sakellari Vasiliki
Published: January 2025

Cerebral palsy (CP) is the leading cause of lifelong physical disability, affecting approximately 17 million individuals worldwide. Upper extremity dysfunction, alongside spasticity and coordination challenges, significantly impacts independence in daily activities. Whole-Body Vibration (WBV) has been proposed as a therapeutic modality to improve functionality in neurological populations, though its effects on upper extremity function in children with CP remain relatively unclear. This pilot study assessed the feasibility and preliminary efficacy of Upper Extremity Vibration Therapy using a Whole-Body Vibration Platform (UEVT-WBV) combined with conventional physiotherapy, in enhancing upper extremity function and reducing spasticity in children with CP. Ten children aged 4.5–18 years with upper extremity dysfunction due to CP were randomly assigned to either an intervention group receiving UEVT-WBV alongside conventional physiotherapy or a control group receiving only conventional physiotherapy. Both interventions were implemented over eight weeks. Assessments were conducted at baseline, week 4, and week 8 using the Modified Ashworth Scale (MAS) (spasticity), ABILHAND (manual ability), and a quality-of-life questionnaire. Both groups demonstrated significant reductions in spasticity and improvements in upper extremity function over time, as measured by MAS and ABILHAND, respectively. However, no statistically significant differences were found between groups, indicating comparable outcomes between UEVT-WBV and conventional physiotherapy alone. While hemiplegic participants achieved greater functional gains than those with quadriplegia regardless of intervention, quality-of-life improvements were minor and limited to emotional well-being and pain reduction in the intervention group. This pilot study highlights the feasibility of UEVT-WBV as an adjunct therapy in pediatric CP rehabilitation, providing foundational data for future studies. Further studies are needed to isolate the effects of UEVT-WBV and to identify its potential in targeted subpopulations.
Approximate and Sample Entropy of the Center of Pressure During Unperturbed Tandem Standing: Effect of Altering the Tolerance Window
Authors: Wesley Jayla , Rhodes Samhita , Zeitler David W. , Alderink Gordon
Published: January 2025

Approximate entropy (ApEn) and sample entropy (SampEn) are statistical indices designed to quantify the regularity or predictability of time-series data. Although ApEn has been a prominent choice in analyzing non-linear data, it is currently unclear which method and parameter selection combination is optimal for its application in biomechanics. This research aimed to examine the differences between ApEn and SampEn related to center-of-pressure (COP) data during tandem standing balance tasks, while also changing the tolerance window, r. Six participants completed five, 30 s trials, feet-together and tandem standing with eyes open and eyes closed. COP data (fs = 60 Hz, downsampled from 1200 Hz) from ground reaction force platforms were collected. ApEn and SampEn were calculated using a constant vector length, i.e., m = 2, but differing values of r (tolerance window). For each of the participants, four separate one-way analysis of variance analyses (ANOVA) were conducted for ApEn and SampEn along the anterior–posterior (AP) and medial–lateral (ML) axes. Dunnett’s intervals were applied to the one-way ANOVA analyses to determine which tandem conditions differed significantly from the baseline condition. ApEn and SampEn provided comparable results in the predictability of patterns for different stability conditions, with increasing instability, i.e., tandem eyes closed postures, being associated with greater unpredictability. The selection of r had a relatively consistent effect on mean ApEn and SampEn values across r = 0.15 × SD to r = 0.25 × SD, where both entropy methods tended to decrease as r increased. Mean SampEn values were generally lower than ApEn values. The results suggest that both ApEn and SampEn indices demonstrated relative consistency and were equally effective in quantifying the level of the center-of-pressure signal regularity during quiet tandem standing postural balance tests.
Queering Militarism in Israeli Photography
Authors: Gal Nissim
Published: January 2025

This article, Queering Militarism in Israeli Photography, examines Adi Nes’s Soldiers series, a body of work that interrogates the intersections of queerness, militarism, and nationalism within Israeli society. By employing a distinctive “military circus” aesthetic, Nes challenges the rigid heteronormative and hyper-masculine archetypes embedded in Israeli military identity. His staged photographs depict soldiers in circus-inspired performative poses, blending military discipline with elements of the carnivalesque to subvert conventional representations of military masculinity. This approach creates spaces where queerness, vulnerability, and fluid identity defy the rigid confines of nationalist narratives. Using queer studies frameworks, performance theory, and postcolonial critique, this article analyzes Nes’s depiction of soldiers as both military subjects and circus performers, examining how these representations disrupt the “naturalness” of gender, power, and identity within the Israeli national ethos. Through a close reading of key images—such as the fire-breathing soldier, the acrobat on a tightrope, and the strongman figure—this article argues that Nes critiques homonationalism and exposes the co-optation of LGBTQ+ identities into militaristic frameworks. His images juxtapose exaggerated masculinity with homoerotic and introspective vulnerability, positioning the queer body as both a participant in and a subverter of the national narrative. Drawing on contemporary queer theory—including José Esteban Muñoz’s concept of “disidentification”, Eve Kosofsky Sedgwick’s theories of queer shame and performativity, and perspectives on temporality, failure, and counterpublics following Elizabeth Freeman, Jack Halberstam, Michael Warner, and Sara Ahmed—this article frames queerness as an active site of resistance and creative transformation within the Israeli military complex. The analysis reveals how Nes’s work disrupts Zionist masculinities and traditional militaristic structures through a hybrid aesthetic of military and circus life. By reimagining Israeli identity as an inclusive, multi-dimensional construct, Nes expands queer possibilities beyond heteronormative confines and homonationalist alignments. This merging of critical queer perspectives—from the destabilizing of discipline and shame to the public visibility of non-normative bodies—posits that queer identities can permeate and reshape state power itself, challenging not only the norms of militaristic nationalism but also the boundaries of Israeli selfhood.
Assessing the Impact of Climate Change on Intensity-Duration-Frequency (IDF) Curves for the Qassim Region, Saudi Arabia
Authors: ALRakathi Mohammed , Alodah Abdullah
Published: January 2025

Climate change has the potential to significantly impact various aspects of Earth’s climate systems, including precipitation patterns, necessitating region-specific action plans. This study examines the Wadi Al Rummah region in Qassim province, Saudi Arabia, by analyzing Intensity-Duration-Frequency (IDF) curves across six locations, utilizing observed daily precipitation data from 1986 to 2014. The nonparametric quantile mapping method was employed to adjust the outputs of eight Regional Climate Models (RCMs) within the CMIP6 ensemble. These models were evaluated under four Shared Socioeconomic Pathways (SSPs), ranging from a stringent mitigation scenario to one with very high greenhouse gas emissions. Also, two statistical tests, namely the Kolmogorov-Smirnov and Chi-Square tests, were used to assess the best-fitting distribution to estimate the maximum rainfall values. Temporal disaggregation of daily precipitation data was performed using the K-nearest neighbors (KNN) method. The IDF curves were generated for both historical and three projected future periods using Gumbel distribution, which proved to be the best-fitting statistical model, using six return periods: 2, 5, 10, 25, 50, and 100 years. Results indicate that high-emission scenarios and longer timeframes exhibit greater uncertainty in IDF projections. Additionally, rainfall intensity is expected to increase over shorter durations, with significant increases observed in Buriydah and Nabhaniyah under SSP 8.5. In contrast, Al Rass, Badayea, and Al Mithnab show mixed trends, while Unaizah shows little to no significant change. These findings emphasize the need for sustainable development and adaptive strategies to mitigate risks in Qassim province, as climate impacts are projected to intensify, particularly in the short to long term.