bluuebunny/crossref_metadata_2025_split huggingface dataset:
Paramedics and EMTs’ Perceptions of Geriatric Trauma Care in Saudi Arabia
Authors: Harthi Naif , Goodacre Steve , Sampson Fiona , Binhotan Meshary , Suhail Abdullah 
Published: November 2024

Abstract

Background
Saudi ambulance clinicians face ageing-related challenges and impacts of ageing changes while providing prehospital geriatric trauma care but little is known about their understanding of such care.
Methods
A qualitative study was conducted using a purposive sample of Saudi paramedics and ambulance technicians from Riyadh and Makkah using online semi-structured interviews and analysed using the framework method.
Results
The qualitative study recruited twenty participants and identified that they reported age-related challenges including physiological changes, polypharmacy, and communication difficulties. They all wanted training and guidelines to improve their knowledge. They reported struggling with communication difficulties, inaccurate adverse outcomes predictions, difficult intravenous cannulations, and cultural restrictions affecting care provision for female patients. We identified organisational barriers (e.g. lack of shared patient records and lack of guidelines) and cultural barriers (e.g. barriers to assessing women, attitudes towards older people, and attitudes towards paramedics) that influenced implementation of knowledge.
Conclusion
Ambulance clinicians in Saudi Arabia want guidelines and training in managing older trauma patients but these need to take into account the organisational and cultural barriers that we identified to facilitate implementing knowledge and changing practice to providing improved care.
Dynamic Response Analysis of Ancient Pagodas Under Rockfall Impact
Authors: Li XiaoPeng , He Qing , Ling Kangjie , Liu Dewen , Liu Yang 
Published: November 2024

Abstract

As a vital component of China's historical and cultural heritage, ancient pagodas hold significant value in the realms of architectural art and religious culture, and they provide precious information for the exploration of historical geography. However, pagodas located in mountainous areas are threatened by natural disasters such as landslides, debris flows, and rockfalls, with the latter being a particularly pressing issue due to the notable increase in accidents caused by rockfalls in China over recent decades. This study employs the ABAQUS finite element analysis software to simulate and analyze the response of ancient pagodas when subjected to rockfall impact loads. Detailed geometric modeling and material property assignment of the pagoda structure were conducted to establish the corresponding finite element model. Subsequently, the impact of rockfalls with varying velocities, radii, impact angles, and impact heights on the pagoda was simulated to assess its structural safety and stability. The results indicate that rockfall velocity, radius, impact angle, and impact height are key factors affecting the structural safety of ancient pagodas. This research aims to provide a theoretical basis for the protection against rockfall disasters of ancient pagodas, effectively safeguarding these precious cultural heritages.
Efficient Brain Tumor Detection Based on Channel Shuffling
Authors: Li Pei , Zhang Rong , Zhu Zhongjie , Zhang Lei , Bai Yongqiang 
Published: November 2024

Abstract

Brain tumor detection is crucial for early diagnosis and treatment planning, as it involves automatically identifying and localizing brain tumors. However, existing methods often lack accuracy in detecting highly heterogeneous brain tumors and struggle to balance detection speed. To alleviate these issues, a novel brain tumor detection method termed channel shuffling YOLO (CS-YOLO) has been proposed, which optimizes both accuracy and detection speed. First, a depthwise separable convolution with a channel shuffling RepVGG module is designed. This module combines efficient parameter computation with robust feature extraction. It extracts deep features from images, thereby enhancing both accuracy and speed of brain tumor detection. Second, to enhance the network's performance in perceiving complex brain tumor targets, a novel convolutional multi-head self-attention module is constructed. This module learns long-range dependencies at lower resolutions, thereby improving the model's capability to recognize highly heterogeneous brain tumors. Finally, a lightweight channel shuffling convolution is designed and used to construct a lightweight residual module. This module dramatically reduces the number of parameters and the computational complexity of the model by splitting and shuffling channels, thus improving the model's learning and generalization performance. Experimental results demonstrate that the proposed method surpasses YOLOv6-L, YOLOv7, YOLOv8-L, and the latest RCS-YOLO in terms of detection accuracy and speed on the Br35H dataset. Compared to the state-of-the-art methods, the proposed CS-YOLO significantly enhances brain tumor detection accuracy and speed. Specifically, network computation in GFLOPs is reduced by 41%, FPS is increased by 14%, and accuracy AP is improved by 0.8%, achieving advanced performance.
Spatial Distribution Characteristic of Vanadium in Typical Paddy Soils of Hunan Province, China
Authors: Yu Shu , Wan Da-Juan , Chen Jia-Qi , Yuan Teng-Yue , Wu Jue , Ouyang Ning-Xiang , Zhang Yang-Zhu , Tan Chang-Yin 
Published: November 2024

Abstract

Considering the paddy soil developed from six major soil parent materials in Hunan Province as the research subject, 63 paddy soil profiles were collected to determine soil vanadium content in paddy soil and study the distribution and migration characteristics of V in it.The results showed that: (1) The V content of paddy soil in Hunan Province was 67.84 ± 31.23 mg / kg, with a range of 4.84 ~ 150.96 mg / kg, and the high and extremely high value points mainly appeared in eastern part of Hunan. (2) There was a certain correlation of V content between each soil layers, with higher levels in the deeper soil,and the vertical distribution characteristics of V generally showed a gradual increase in content with increasing depth. (3) There was significant downward migration of V in most paddy soil profiles, with greater downward leaching amount of V in the 0 ~ 20 cm and the 20 ~ 40 cm soil layer. (4) The overall V content of soil developed in different soil parent materials were in the following order from high to low: Quaternary red clay > River and lake sediment > Limestone weathered material > Slate shale weathered material > Purple sand shale weathered material > Granite weathered material
Mitochondria- and Anaerobic Glycolysis- Targeted Self-Assembled Copper Complex Nanoparticles for Boosting Cuproptosis- Immunotherapy
Authors: Zhang Hanyu , Xia Jing , Xie Lingling , Hao Meng , Wang Sizhang , Dong Xiao , Li Yongxin , Mu Qiang 
Published: November 2024

Abstract

Cuproptosis is an emerging regulated cell death that depends on the intracellular copper ion and mitochondrial respiration, showing great potential in cancer treatment. However, increasing the specific accumulation of copper ions in mitochondria while simultaneously enhancing mitochondrial respiration are highly needed and still a major challenge to promote cuproptosis. Herein, the lactate dehydrogenase (LDH) inhibitor galloflavin (GF) self-assembles with the copper ionophore elesclomol (ES) through copper ion-driven cooperative coordination to form GF/CuES nanoparticles, synergistically targeting mitochondria and anaerobic glycolysis to boost cuproptosis-immunotherapy. After cellular internalization, the GF/CuES nanoparticles responsively dissociate to release Cu2+ and ES, co-transporting into mitochondria to collaboratively trigger cuproptosis, which subsequently evokes immunogenic cell death (ICD). Notably, the liberated GF leads to effective LDH suppression, which not only further amplifies cuproptosis via disrupting anaerobic glycolysis and enhancing mitochondrial respiration but also reduces lactate production, thus alleviating the immunosuppressive tumor microenvironment and augmenting anti-tumor immunity driven by ICD. Thus, the GF/CuES nanoparticles exhibit strong antitumor effects through cooperatively targeting glycolysis, cuproptosis and immunotherapy, offering a unique opportunity to enhance cancer treatment strategies.
Lignin-based plugging hydrogel with high-temperature resistance and adjustable gelation
Authors: Liu Haibo , Li Xiaomeng , Pan Zheng , Dai Lin , Zhang Meng , Sheng Feng , Si Chuanling 
Published: November 2024

Abstract

Lost circulation is a prevalent and intricate phenomenon in the domain of oil and gas drilling, which has resulted in significant economic losses for the global oil industry. Common gel lost circulation materials have been observed to exhibit deficiencies in temperature resistance and gel strength. In this study, a lignin-based plugging hydrogel (Lig-plugel) was prepared for lost circulation plugging using a simple method. The hydrogel employed the self-crosslinking mechanism of lignin in a high-temperature environment, which reduced the quantity of crosslinker, achieved the objective of regulating gelation time, and enhanced its mechanical properties. The maximum compressive strain of Lig-plugel synthesised at 200°C with a 25 wt% crosslinker amount reached 76.83%, and the compressive strength and compressive toughness reached 1.85 MPa and 276.13 KJ/m3, respectively. Furthermore, Lig-plugel exhibits excellent heat resistance. It demonstrates minimal mass loss during thermal decomposition in high-temperature environments below 220°C, which is sufficient for high-temperature applications. Additionally, the simulated plugging experiments indicate that Lig-plugel has an effective plugging effect and is adaptable. This study presents an environmentally friendly and sustainable solution to the lost circulation problem and has a broad application prospect in the field of oil and gas drilling.
3D K-space sphere analysis enables Cascaded Wave-Guide (CWG)
Authors: Zhang Shanwen , Qin Jiajia , Xie Yongfang , Wang Jin , Song Qiang , Wang Jing , Cheng Zhiming , Hu Dejiao , Duan Huigao , zhou changhe 
Published: November 2024

Abstract

Optical waveguide combiner is regarded as the most promising solution in the augmented reality community, because of its slim form factor, wide FOV, and large eye-box. Although the surface relief grating-based wave-guide exhibits challenges in single-layer full-color display with two-dimensional (2D) exit pupil expansion due to poor color uniformity and low optical efficiency, the geometrical reflective lightguide, utilizing two sets of cascaded embedded partially reflective mirrors, increases the probability of stray light and degrades image quality. In this work, we propose a reflective-diffractive cascaded waveguide (CWG) to address these issues by using a unique combination of a pair of gratings and a set of cascaded embedded partially reflecting mirrors. A three-dimensional (3D) k-space sphere as a novel analytical method is presented for investigating the light propagation in CWG to prevent additional distortion aberration. To achieve the optimal imaging result of CWG, we have developed a home-build auto-layout and multidimensional ray-field tracing program. CWG is designed with a total thickness of 1.5 mm, a diagonal FOV of 30°, an eye-box of 12 mm × 10 mm, and an optical efficiency of 4.5% higher than any other recorded for a 2D EPE optical wave-guide. Our model and analysis method made up of CWG and a home-build ray-field tracing program would be instructive and improved for advancing research fields concerned with optical wave-guide design.
Assessment of Pesticide Residue Practices and Public Health Implications in Agro-Pastoral Communities of Niger State, Nigeria
Authors: Haruna Aliyu Evuti , Alhaji Nma Bida , Adama John Yisa , Onakpa Monday , Muhammed Hadiza Lami , Makun Hussaini Anthony 
Published: November 2024

Abstract

Pesticide residues in agricultural practices pose significant risks to public health, particularly in agro-pastoral communities where knowledge of pesticide usage is often limited. This study assesses pesticide residue practices among agro-pastoralists in Niger State, Nigeria, and examines the associated public health implications. A cross-sectional survey was conducted across three agro-ecological zones (A, B, and C) using structured questionnaires. The survey targeted nomadic and sedentary pastoral cattle herds to gather data on pesticide usage, exposure, and risk factors. Results revealed widespread pesticide misuse, largely driven by poor regulatory enforcement, low educational levels, and increasing demand for agricultural productivity. Additionally, significant variations were observed in pesticide knowledge and practices between the zones. This study highlights the urgent need for targeted interventions, stricter regulatory controls, and educational programs to mitigate health risks and enhance compliance with international safety standards.
XOR-Based Visual Cryptography Scheme for Securing Color Image Sharing Using Three Shares
Authors: Nujumudeen Faizal , Hussain Tarak , Mubarak Muhammad Noorul 
Published: November 2024

Abstract

This paper introduces a novel XOR-based visual cryptography scheme designed to increase the security and efficiency of color image sharing by dividing them into three distinct shares, ensuring confidentiality and enabling flawless reconstruction. This method guarantees flawless image reconstruction by utilizing the reversible nature of the XOR operation when all three shares are combined. Our approach improves upon conventional (n, n) threshold visual cryptography techniques by reducing the number of shares and the complexity of the share generation and image reconstruction. Each share is created by manipulating pixels at random, which guarantees its uniqueness and unreadability. The original image is reconstructed by performing a pixel-by-pixel XOR operation across all three shares, ensuring complete and lossless image recovery. The method offers a blend of robust security and computational efficiency, making it ideal for applications requiring secure image transmission and storage. Furthermore, the scheme's versatility extends to both grayscale and RGB images, broadening its applicability across a wide range of visual media formats. The experimental results confirm the method's robustness, demonstrating precise reconstruction even with diverse image resolutions. This solution offers a secure and practical approach to visual data encryption, which is especially beneficial for scenarios demanding high confidentiality, such as military imaging, biometric data exchange, and secure multimedia transmission.
New formulation to characterize chip behaviour geometry during a metal cutting process using an analogy with a beam
Authors: Valera Juan Armando Ortiz , Armendariz Víctor Hugo Jacobo , Alcántara Carlos Gabriel Figueroa , Prado Armando Ortiz 
Published: November 2024

Abstract

In this study, the behaviour of a chip during metal cutting processes is analysed using the analogy that the chip behaves mechanically like a beam. This representation simplifies the modelling of the machining process and is used to perform an analysis through basic physical concepts, representing the chip as cyclical formations of small beams, instead of relying on statistical regressions and adjustments that require experimental data. The force components exerted on the chip were determined via Merchant’s force circle. These forces create compression and cause bending, inducing fractures between the work material and the layer to be removed, which shapes and subsequently deforms the chip. Initially, the chip is approximated as a Euler–Bernoulli beam, enabling the quantification of the chip fragment’s length, as well as the forces and deformations involved in its formation. The model results were compared with those from trials reported in the literature, and an excellent approximation was achieved.
Efficient Beam Search For SatelliteCommunications On The Move Systems
Authors: Wei Ziping , Chen Yongchun , Guo Kaiqi , Liu Bingsen , Liu Yue , Li Yihuan 
Published: November 2024

Abstract

Satellite Communication on the Move (SOTM) is essential for dynamic environments, such as military operations and disaster relief. Conventionalsystems with parabolic reflector antennas suffer from slow mechanical scanningand reduced tracking efficiency, especially for low Earth orbit (LEO) satellites,while phased array antennas offer faster, more precise tracking but remain underutilized. A key challenge in SOTM is achieving precise beam alignment betweenthe satellite and moving terminals, which directly impacts tracking accuracy.Several traditional existing beam alignment techniques are computationallyexpensive and impractical for real-time use. In this work, we propose a novel andefficient beam alignment algorithm that exploits the inherent low-rank structureof the beamspace energy matrix. By modeling the alignment process as amaximization problem with non-convex constraints, we leverage randomizedmatrix approximation to reconstruct a low-rank representation of the beamspace.This allows us to identify a subspace containing the optimal beam direction. Wethen use Particle Swarm Optimization (PSO) to refine the beam directionestimate. As illustrated in the numerical simulations, our approach improvesbeam alignment accuracy while reducing computational complexity comparing totraditional methods. This advancement has broad implications for enhancing theperformance of SOTM systems in dynamic environments.
An Efficient Multimodel Sentimental Analysis Using a Joint Representation With an Optimized Transformer
Authors: Vasanthi P , Viswanatham Madhu 
Published: November 2024

Abstract

Multimodal content on the Internet has exponentially grown with the proliferation of online video publishing. Using multimodal data for research purposes, sentiment analysis, and emotion classification in conversations have become topical research areas in recent years. Therefore, in this paper, automatic multimodal sentimental analysis is developed. To achieve this concept, joint representation with an optimized transformer is presented. The proposed approach consists of three main stages namely, multimodal feature extraction, Joint Representation Translator, and optimized transformer-based prediction. At first, we extract the features from each modality namely, text, audio, and video. After feature extraction, joint representations of bimodality are captured using a joint representation translator (JRT). Utilising an optimised Transformer, complementarity between modalities is further examined after acquiring the joint representations. The adaptive dragonfly optimization (ADO) technique is used to select the transformer's parameters optimally to improve performance. Based on comprehensive tests performed on the CMU-MOSI datasets, the proposed architecture performs better than the state-of-the-art techniques.
Turkish Adaptation Study Of Fear Of Water Assessment Scale And Its Analysis In Terms Of Various Variables
Authors: Hassani Fahimeh , Mutlu Ecem 
Published: November 2024

Abstract

Fear of water is the main indicator of a lack of weakness of swimming ability. Some people cannot learn how to swim because they avoid water completely, while others might have difficulty learning because they may not relax their bodies while swimming. Thus, it is necessity to recognize these individuals and develop effective teaching strategies for them. Teachers and swim coaches need an assessment tool to help them identify individuals who are afraid of water. The aim of this study was to adapt the Fear of Water Assessment Questionnaire (FWAQ) developed by Misimi and co-worker (2020) into Turkish. For adaptation, the original scale was translated into Turkish. 146 males (54.5%) and 122 females (45.5%), participated in the study. The FWAQ consists of 20 items and three subscales: contact with the water environment, the natural power of water, and the values of movement control in water. Cronbach's alpha, interclass correlation coefficient (ICC), confirmatory and exploratory factor analysis was used to determine the internal consistency of subscales, temporal reliability, construct validity of the scale respectively. Also, the results of the calculations performed to estimate the reliability of the scale factors show that the value of the Cronbach's alpha coefficient and interclass correlation coefficient (ICC) are good enough and considering that the internal consistency coefficients and temporal reliability of the components of the list are reasonable and appropriate, the reliability of the scale is confirmed. The results revealed that FWAQ showed relatively acceptable construct validity and acceptable internal consistency and test-retest reliability. The results of this study support the preliminary validity and reliability of the FWAQ for use in academic sport contexts.
A general machine-learning framework for high-throughput screening for stable and efficient RuO2-based acidic oxygen evolution reaction catalysts
Authors: Shang Zhe , Dang Qian , Wang Fengmei , Sun Xiaoming , Li Hui 
Published: November 2024

Abstract

Doping guest elements is an effective way to increase activity and stability of RuO2 catalysts in acidic oxygen evolution reaction (OER). However, due to the vastness of doping space, it is challenging for either high-cost experiments or density functional theory (DFT) calculations to screen out the doped structures with the optimized catalytic performance. Herein, we reported a machine-learning (ML) framework that aims to realize high-throughput screening for both stability and activity of doped-RuO2 acidic OER catalysts from mono-doping to triple-doping at a low level of computational cost. Compared to the d-band theory and some other previous models, our ML model was constructed based on more general input features and realized higher prediction accuracy with mean absolute errors (MAEs) of 0.074, 0.142 and 0.082 eV for *OH, *O and *OOH adsorption, respectively. Through the ML models, three doping structures, Ru41Zn7O96, Ru41Zn4Fe3O96, and Ru39Zn4Cu4Co1O96 were found to possess the extraordinarily high stability and comparable or higher activity than the previously reported OER catalysts. This work provided an efficient study paradigm in fields of material screening and a useful guide for experimental synthesis.
Photoelectrochemical immunosensor for chloramphenicol detection based on cation exchange reaction-mediacted photocurrent enhancement of ZnIn2S4/TiO2/Ti3C2 MXene coupled with controlled-release strategy
Authors: Zheng Mengqin , Lin Huizi , Li Suhua , Huang Shuoying , Huang Jiangwei , Lai Wenqiang , Tang Dianping , Lin Youxiu 
Published: November 2024

Abstract

Herein, we developed a photocurrent enhancing photoelectrochemical (PEC) immunosensor for chloramphenicol (CAP) detection based on cation exchange reaction. The efficient split-type PEC immunosensor combimed with controlled release strategy was established using the ZnIn2S4/TiO2/Ti3C2 MXene (ZIS/T/M) composite as the photoactive material and CuO as the signal response probes. In the presence of target CAP, CuO-labeled CAP antibody (CuO-mAb) was introduced onto the microplate via a competitive-type immunoassay. Under acidic conditions, a large amount of Cu2+ released from CuO-mAb, which could trigger a cation exchange reaction with the Zn2+ in ZIS/T/M-modified photoelectrode to generate CuxS, resulting in a photocurrent enhancing. As a results, the quantitative detection of CAP was achieved by detecting the photocurrent change. Under optimized conditions, the linear range of the sensor was 1 pg/mL to 50 ng/mL and the detection limit was 0.24 pg/mL. The excellent PEC behavior of ZIS/T/M composite could be attributed to that heterojunction formation improved the migration and separation of photocarrier. Additionally, by virtue of the photocurrent enhancing strategy via cation exchange reaction and the controlled releasing signal amplification method of ion, the PEC immunosensor have high sensitivity and satisfactory accuracy, offering great potential applications in the analysis of CAP.