bluuebunny/crossref_metadata_2025 huggingface dataset:
Binderless particleboards obtained 100% from winery by-products for the packaging industry
Authors: Fernandes Raquel A. , Lopes Sandro , Ferreira Nuno , Santos Jorge , Martins Jorge M. , Carvalho Luisa H.
Published: April 2024

The valorization of bioeconomy by-products holds immense significance in achieving sustainability goals and fostering resource efficiency, not only to reduce the amount of waste generated but also to significantly decrease the carbon footprint associated with several industrial fields, by promoting circular economy. The wine industry is not only one of the major contributors for world’s economy but also a great producer of by-products, with no valorization process associated. Grape stalks are a great source of chemical molecules, as polyphenols, that can be applied in the production of bio-adhesives. In the present work, grape stalk particles were used as raw material to obtain a highly rich extract with bonding properties through solid/liquid extraction. Different extraction agents were tested (water, NaOH, and Na2CO3) at varied concentrations (0.1%, 0.5%, and 1.0%, respectively). Additionally, extracts were chemically characterized, and the bonding capacity was also evaluated. Using NaOH 1.0%, an extraction efficiency of 8.9% and a total content of polyphenols of 1.4% were achieved. Moreover, all extracts presented an interesting bonding capacity (>1.0 MPa) by hot-press at 120°C for 120 s. The composite panel produced using grape stalk adhesive and vine strain particles fulfills the requirements for type P1 particleboards in terms of internal bond strength, reaching 0.66 MPa. The mechanical and wettability properties of composite material allow foreseeing a promising application in the food packaging industry.
Initial Impact of Different Feeding Methods on Feed Intake Time in Stabled Icelandic Horses
Authors: Ragnarsson Sveinn , Víkingsdóttir Sigríður Vaka , Stefánsdóttir Guðrún Jóhanna
Published: April 2024

The natural behaviour of horses is to spend the majority of their time on feed intake The feeding of stabled horses is, however, often far from that, as their feed intake is limited to their nutritional requirements. In order to approach their natural foraging time, it is important to extend the feed intake time of stabled horses. The aim of this study was to estimate if the feed intake time differs when feeding haylage in a haynet, hayball, metal corner manger, or from the box floor. The experimental design consisted of a Latin square, occurred across four days with four adult Icelandic horses and four treatments. Horses were stabled in individual boxes and fed 7 kg of high-energy haylage in two even meals while the intake time was recorded. The feed intake time per kg DM was shorter from the manger or the box floor than from a haynet or hayball (81 or 85 min versus 94 or 96 min; p < 0.05). It can be concluded that feeding haylage in a hayball or in a haynet can increase the feed intake time by 13% per day (12 min/kg DM/day) when compared to the more traditional methods. Thus, with simple alternatives, it is possible to extend the feed intake time of stabled horses.
Multilingual Hate Speech Detection: A Semi-Supervised Generative Adversarial Approach
Authors: Mnassri Khouloud , Farahbakhsh Reza , Crespi Noel
Published: April 2024

Social media platforms have surpassed cultural and linguistic boundaries, thus enabling online communication worldwide. However, the expanded use of various languages has intensified the challenge of online detection of hate speech content. Despite the release of multiple Natural Language Processing (NLP) solutions implementing cutting-edge machine learning techniques, the scarcity of data, especially labeled data, remains a considerable obstacle, which further requires the use of semisupervised approaches along with Generative Artificial Intelligence (Generative AI) techniques. This paper introduces an innovative approach, a multilingual semisupervised model combining Generative Adversarial Networks (GANs) and Pretrained Language Models (PLMs), more precisely mBERT and XLM-RoBERTa. Our approach proves its effectiveness in the detection of hate speech and offensive language in Indo-European languages (in English, German, and Hindi) when employing only 20% annotated data from the HASOC2019 dataset, thereby presenting significantly high performances in each of multilingual, zero-shot crosslingual, and monolingual training scenarios. Our study provides a robust mBERT-based semisupervised GAN model (SS-GAN-mBERT) that outperformed the XLM-RoBERTa-based model (SS-GAN-XLM) and reached an average F1 score boost of 9.23% and an accuracy increase of 5.75% over the baseline semisupervised mBERT model.
At the Intersection of Housing, Energy, and Mobility Poverty: Trapped in Social Exclusion
Authors: Großmann Katrin , Oettel Helene , Sandmann Leona
Published: April 2024

The individual debates on housing poverty, energy poverty, and mobility poverty for the most part overlook the interwoven nature of all three cost burdens, especially for low-income households. This study examines how the three cost factors interact on a household level, the consequences for those affected by cost burdens, and how they cope and negotiate their expenses. Our research comprises two sets of semi-structured interviews, one before and one during the energy crisis, to gain insight into household experiences and constraints. We found that the freedom to choose where and how to live largely determines how households heat their homes and organize their mobility. The housing crisis together with housing market mechanisms appears to be the main driver of this cost trap; and from here, a complex interplay of causal factors unfolds. Location, often conceived of in terms of an urban–rural divide, seems to be of secondary importance. The intersection of cost burdens results in stress, anxiety, and social exclusion, further limiting the capacity for coping.
Short-Term Load Forecasting Based on Optimized Random Forest and Optimal Feature Selection
Authors: Magalhães Bianca , Bento Pedro , Pombo José , Calado Maria do Rosário , Mariano Sílvio
Published: April 2024

Short-term load forecasting (STLF) plays a vital role in ensuring the safe, efficient, and economical operation of power systems. Accurate load forecasting provides numerous benefits for power suppliers, such as cost reduction, increased reliability, and informed decision-making. However, STLF is a complex task due to various factors, including non-linear trends, multiple seasonality, variable variance, and significant random interruptions in electricity demand time series. To address these challenges, advanced techniques and models are required. This study focuses on the development of an efficient short-term power load forecasting model using the random forest (RF) algorithm. RF combines regression trees through bagging and random subspace techniques to improve prediction accuracy and reduce model variability. The algorithm constructs a forest of trees using bootstrap samples and selects random feature subsets at each node to enhance diversity. Hyperparameters such as the number of trees, minimum sample leaf size, and maximum features for each split are tuned to optimize forecasting results. The proposed model was tested using historical hourly load data from four transformer substations supplying different campus areas of the University of Beira Interior, Portugal. The training data were from January 2018 to December 2021, while the data from 2022 were used for testing. The results demonstrate the effectiveness of the RF model in forecasting short-term hourly and one day ahead load and its potential to enhance decision-making processes in smart grid operations.
Ramping-Up Electro-Fuel Production
Authors: Peters Ralf , Decker Maximilian , Breuer Janos Lucian , Samsun Remzi Can , Stolten Detlef
Published: April 2024

Future transport systems will rely on new electrified drives utilizing batteries and hydrogen-powered fuel cells or combustion engines with sustainable fuels. These systems must complement each other and should not be viewed as competing. Properties such as efficiency, range, as well as transport and storage properties will determine their use cases. This article looks at the usability of liquid electro-fuels in freight transport and analyzes the production capacities that will be necessary through 2050 in Germany. Different scenarios with varying market shares of electro-fuels are considered. A scenario with a focus on fuel cells foresees a quantity of 220 PJ of electro-fuels, i.e., 5.1 million tons, which reduces 80% of carbon dioxide emissions in LDV and HDV transport. A further scenario achieves carbon-neutrality and leads to a demand for nearly 17 million tons of e-fuel, corresponding to 640 PJ. Considering a final production rate of 5.1 million tons of electro-fuels per year leads to maximum investment costs of around EUR 350 million/year in 2036 during the ramp-up phase. The total investment costs for synthesis plants amount to EUR 4.02 billion. A carbon-neutrality scenario requires more than a factor 3 for investment for the production facilities of electro-fuels alone.
Optimizing Generative AI Chatbots for Net-Zero Emissions Energy Internet-of-Things Infrastructure
Authors: Matharaarachchi Amali , Mendis Wishmitha , Randunu Kanishka , De Silva Daswin , Gamage Gihan , Moraliyage Harsha , Mills Nishan , Jennings Andrew
Published: April 2024

Internet-of-Things (IoT) technologies have been steadily adopted and embedded into energy infrastructure following the rapid transformation of energy grids through distributed consumption, renewables generation, and battery storage. The data streams produced by such energy IoT infrastructure can be extracted, processed, analyzed, and synthesized for informed decision-making that delivers optimized grid operations, reduced costs, and net-zero carbon emissions. However, the voluminous nature of such data streams leads to an equally large number of analysis outcomes that have proven ineffective in decision-making by energy grid operators. This gap can be addressed by introducing artificial intelligence (AI) chatbots, or more formally conversational agents, to proactively assist human operators in analyzing and identifying decision opportunities in energy grids. In this research, we draw upon the recent success of generative AI for optimized AI chatbots with natural language understanding and generation capabilities for the complex information needs of energy IoT infrastructure and net-zero emissions. The proposed approach for optimized generative AI chatbots is composed of six core modules: Intent Classifier, Knowledge Extractor, Database Retriever, Cached Hierarchical Vector Storage, Secure Prompting, and Conversational Interface with Language Generator. We empirically evaluate the proposed approach and the optimized generative AI chatbot in the real-world setting of an energy IoT infrastructure deployed at a large, multi-campus tertiary education institution. The results of these experiments confirm the contribution of generative AI chatbots in simplifying the complexity of energy IoT infrastructure for optimized grid operations and net-zero carbon emissions.
Assessment of the Effect of Leonurine Hydrochloride in a Mouse Model of PCOS by Gene Expression Profiling
Authors: Wang Mengmeng , Yang Li , Sun Guojie , Shao Yongbin , Liu Yuran , Yang Huiying , Wang Yan , Zhang Mengyuan , Shang Yunxia , Gu Xinli
Published: April 2024

Polycystic ovary syndrome (PCOS) is an endocrine disease commonly associated with metabolic disorders in females. Leonurine hydrochloride (Leo) plays an important role in regulating immunity, tumours, uterine smooth muscle, and ovarian function. However, the effect of Leo on PCOS has not been reported. Here, we used dehydroepiandrosterone to establish a mouse model of PCOS, and some mice were then treated with Leo by gavage. We found that Leo could improve the irregular oestros cycle of PCOS mice, reverse the significantly greater serum testosterone (T) and luteinising hormone (LH) levels, significantly reduce the follicle-stimulating hormone (FSH) level, and significantly increase the LH/FSH ratio of PCOS mice. Leo could also change the phenomenon of ovaries in PCOS mice presented with cystic follicular multiplication and a lacking corpus luteum. Transcriptome analysis identified 177 differentially expressed genes related to follicular development between the model and Leo groups. Notably, the cAMP signalling pathway, neuroactive ligand-receptor interactions, the calcium signalling pathway, the ovarian steroidogenesis pathway, and the Lhcgr, Star, Cyp11a, Hsd17b7, Camk2b, Calml4, and Phkg1 genes may be most related to improvements in hormone levels and the numbers of ovarian cystic follicles and corpora lutea in PCOS mice treated by Leo, which provides a reference for further study of the mechanism of Leo.
Ten Traps for Non-Representational Theory in Human Geography
Authors: Torrens Paul M.
Published: April 2024

Non-Representational Theory (NRT) emphasizes the significance of routine experience in shaping human geography. In doing so, the theory largely eschews traditional approaches that have offered area-based, longitudinal, and synoptic formalisms for geographic inquiry. Instead, NRT prioritizes the roles of individualized and often dynamic lived geographies as they unfold in the moment. To date, NRT has drawn significant inspiration from the synergies that it shares with philosophy, critical geography, and self-referential ethnography. These activities have been tremendous in advancing NRT as a concept, but the theory’s strong ties to encounter and experience invariably call for practical exposition. Alas, applications of NRT to concrete examples at scales beyond small case studies often prove challenging, which we argue artificially constrains further development of the theory. In this paper, we examine some of the thorny problems that present in applying NRT in practical terms. Specifically, we identify ten traps that NRT can fall into when moving from theory to actuality. These traps include conundrums of small geographies, circularity in representation, cognitive traps, issues of mustering and grappling with detail, access issues, limitations with empiricism, problems of subjectivity, methodological challenges, thorny issues of translation, and the unwieldy nature of process dynamics. We briefly demonstrate a novel observational instrument that can sidestep some, but not all, of these traps.
Exploring Current Molecular Targets in the Treatment of Neovascular Age-Related Macular Degeneration toward the Perspective of Long-Term Agents
Authors: Fragiotta Serena , Bassis Lorena , Abdolrahimzadeh Barmak , Marino Alessandra , Sepe Massimiliano , Abdolrahimzadeh Solmaz
Published: April 2024

Long-lasting anti-vascular endothelial growth factor (anti-VEGF) agents have become an option to reduce treatment frequency, with ongoing research exploring optimal responses and safety profiles. This review delves into molecular targets, pharmacological aspects, and strategies for achieving effective and enduring disease control in neovascular age-related macular degeneration (AMD). The molecular pathways involved in macular neovascularization, including angiogenesis and arteriogenesis, are explored. VEGF, PlGF, Ang-1, and Ang-2 play crucial roles in regulating angiogenesis, influencing vessel growth, maturation, and stability. The complex interplay of these factors, along with growth factors like TGFβ and bFGF, contributes to the pathogenesis of neovascular membranes. Current anti-VEGF therapies, including bevacizumab, ranibizumab, aflibercept, brolucizumab, and faricimab, are discussed with a focus on their pharmacokinetics and clinical applications. Strategies to achieve sustained disease control in AMD involve smaller molecules, increased drug dosages, and novel formulations. This narrative review provides a comprehensive overview of the molecular targets and pharmacological aspects of neovascular AMD treatment.
IGF-1 Genome-Edited Human MSCs Exhibit Robust Anti-Arthritogenicity in Collagen-Induced Arthritis
Authors: Chae Dong-Sik , Han Seongho , Kim Sung-Whan
Published: April 2024

Stem cell therapy stands out as a promising avenue for addressing arthritis treatment. However, its therapeutic efficacy requires further enhancement. In this study, we investigated the anti-arthritogenic potential of human amniotic mesenchymal stem cells (AMM) overexpressing insulin-like growth factor 1 (IGF-1) in a collagen-induced mouse model. The IGF-1 gene was introduced into the genome of AMM through transcription activator-like effector nucleases (TALENs). We assessed the in vitro immunomodulatory properties and in vivo anti-arthritogenic effects of IGF-1-overexpressing AMM (AMM/I). Co-culture of AMM/I with interleukin (IL)-1β-treated synovial fibroblasts significantly suppressed NF-kB levels. Transplantation of AMM/I into mice with collagen-induced arthritis (CIA) led to significant attenuation of CIA progression. Furthermore, AMM/I administration resulted in the expansion of regulatory T-cell populations and suppression of T-helper-17 cell activation in CIA mice. In addition, AMM/I transplantation led to an increase in proteoglycan expression within cartilage and reduced infiltration by inflammatory cells and also levels of pro-inflammatory factors including cyclooxygenase-2 (COX-2), IL-1β, NF-kB, and tumor necrosis factor (TNF)-α. In conclusion, our findings suggest that IGF-1 gene-edited human AMM represent a novel alternative therapeutic strategy for the treatment of arthritis.
Genomic Insights into Cyanide Biodegradation in the Pseudomonas Genus
Authors: Sáez Lara P. , Rodríguez-Caballero Gema , Olaya-Abril Alfonso , Cabello Purificación , Moreno-Vivián Conrado , Roldán María Dolores , Luque-Almagro Víctor M.
Published: April 2024

Molecular studies about cyanide biodegradation have been mainly focused on the hydrolytic pathways catalyzed by the cyanide dihydratase CynD or the nitrilase NitC. In some Pseudomonas strains, the assimilation of cyanide has been linked to NitC, such as the cyanotrophic model strain Pseudomonas pseudoalcaligenes CECT 5344, which has been recently reclassified as Pseudomonas oleovorans CECT 5344. In this work, a phylogenomic approach established a more precise taxonomic position of the strain CECT 5344 within the species P. oleovorans. Furthermore, a pan-genomic analysis of P. oleovorans and other species with cyanotrophic strains, such as P. fluorescens and P. monteilii, allowed for the comparison and identification of the cioAB and mqoAB genes involved in cyanide resistance, and the nitC and cynS genes required for the assimilation of cyanide or cyanate, respectively. While cyanide resistance genes presented a high frequency among the analyzed genomes, genes responsible for cyanide or cyanate assimilation were identified in a considerably lower proportion. According to the results obtained in this work, an in silico approach based on a comparative genomic approach can be considered as an agile strategy for the bioprospection of putative cyanotrophic bacteria and for the identification of new genes putatively involved in cyanide biodegradation.
PPARs as Key Transcription Regulators at the Crossroads of Metabolism and Inflammation
Authors: Vázquez-Carrera Manuel , Wahli Walter
Published: April 2024

The metabolic and immune systems are complex networks of organs, cells, and proteins that are involved in the extraction of energy from food; this is to run complex cellular processes and defend the body against infections while protecting its own tissues, respectively [...]
Electrochemical Characterization of Diffusion in Polymeric vs. Monomeric Solvents
Authors: Porat Ze’ev
Published: April 2024

Polymer electrolyte was used as a medium for testing the performance of microband electrodes under conditions of linear diffusion. Cyclic voltammetry (CV) and chronoamperometry (CA) experiments were performed in a highly viscous medium, where diffusion rates are much slower than in fluid solutions. The log i vs. log v (CV) or log i vs. log t (CA) relationships with the current equation confirmed the existence of such conditions, yielding slope values that were lower than the expected 0.5. This could indicate an impure linear diffusion profile, i.e., some contribution from radial diffusion (edge effects). However, the desired value of 0.5 was obtained when performing these tests in monomeric solvents of similar viscosities, such as glycerol or propylene glycol. These results led to the conclusion that the current equations, which are based on Fick’s laws, may not be applicable for polymer electrolytes, where various obstructions to free diffusion result in a more complicated process than for monomeric solvents.
The Effect of Internal Gas Pressure on the Compression Properties of Natural Rubber Foams
Authors: Heydari Amirhosein , Rodrigue Denis
Published: April 2024

This study explores the effect of internal gas pressure (P) on closed-cell natural rubber (NR) foams. Three key factors are analyzed using a 3D model during uniaxial compression: (1) the initial gas pressure (P0 = 1, 2, and 3 atm) inside the cells, (2) different cell sizes (D = 0.1, 0.2, 0.3, and 0.4 mm in diameter), and (3) the presence of defects (holes in the cell walls) in terms of their sizes (d = 0.07 to 0.1 mm). The findings reveal a negative relationship between the initial gas pressure and the relative internal gas pressure (α = P/P0) and a direct correlation with stress during compression. For instance, a change from 1 to 3 atm of the initial internal gas pressure results in a 158% decrease in α with only a 3% increase in stress. Larger cell sizes contribute to higher α but lower stress levels during compression. Changing the cell size from 0.1 to 0.4 mm generates a 27% increase in α but a 45% drop in stress. An analysis of hole sizes (cell connection) indicates that larger holes result in higher relative internal gas pressure, while smaller holes lead to higher stress levels because of more flow restriction. For example, increasing the hole size from 0.07 to 0.1 mm leads to an 8% higher α but a 32% stress reduction. These findings highlight the significant effect of the internal gas pressure inside the cells in determining the mechanical properties of rubber foams, which are generally neglected. The results also provide useful insights for better material design and different industrial applications. This study also generates predictive models to understand the relationships between stress, strain, initial gas pressure, cell size, and defects (holes/connections), enabling the production of tailor-made rubber foams by controlling their mechanical behavior.
Comparison of the Magnetic and Structural Properties of MnFePSi Microwires and MnFePSi Bulk Alloy
Authors: Salaheldeen Mohamed , Zhukova Valentina , Rosero James , Salazar Daniel , Ipatov Mihail , Zhukov Arcady
Published: April 2024

We provide comparative studies of the structural, morphological, microstructural, and magnetic properties of MnFePSi-glass-coated microwires (MnFePSi-GCMWs) and bulk MnFePSi at different temperatures and magnetic fields. The structure of MnFePSi GCMWs prepared by the Taylor–Ulitovsky method consists of the main Fe2P phase and secondary impurities phases of Mn5Si3 and Fe3Si, as confirmed by XRD analysis. Additionally, a notable reduction in the average grain size from 24 µm for the bulk sample to 36 nm for the glass-coated microwire sample is observed. The analysis of magnetic properties of MnFePSi-glass-coated microwires shows different magnetic behavior as compared to the bulk MnFePSi. High coercivity (450 Oe) and remanence (0.32) are observed for MnFePSi-GCMWs compared to low coercivity and remanent magnetization observed for bulk MnFePSi alloy. In addition, large irreversibility at low temperatures is observed in the thermal dependence of magnetization of microwires. Meanwhile, the bulk sample shows regular ferromagnetic behavior, where the field cooling and field heating magnetic curves show a monotonic increase by decreasing the temperature. The notable separation between field cooling and field heating curves of MnFePSi-GCMWs is seen for the applied field at 1 kOe. Also, the M/M5K vs. T for MNFePSi-GCMWs shows a notable sensitivity at a low magnetic field compared to a very noisy magnetic signal for bulk alloy. The common features for both MnFePSi samples are high Curie temperatures above 400 K. From the experimental results, we can deduce the substantial effect of drawing and quenching involved in the preparation of glass-coated MnFePSi microwires in modification of the microstructure and magnetic properties as compared to the same bulk alloy. The provided studies prove the suitability of the Taylor–Ulitovsky method for the preparation of MnFePSi-glass-coated microwires.
A New Method for Ground-Based Optical Polarization Observation of the Moon
Authors: Wang Weinan , Ping Jinsong , Zhang Wenzhao , Wang Mingyuan , Ye Hanlin , Han Xingwei , Kou Songfeng
Published: April 2024

As a natural satellite of the Earth, the moon is a prime target for planetary remote sensing exploration. However, lunar polarization studies are not popular in the planetary science community. Polarimetry of the lunar surface had not been carried out from a spacecraft until the Korean lunar exploration program was initiated. In previous polarization observations of the moon, images of different polarization states were obtained by a rotating linear polarizer. This method is not well suited for future polarization observations from space-based spacecraft. To this end, we present a new kind of polarized observation of the moon using a division of a focal-plane polarization camera and propose a pipeline on the processing method of the polarization observation of the moon. We obtain a map of the degree of white-light polarization on the nearside of the moon through polarization observation, data processing, and correction. The observation and data processing methods presented in this study have the potential to serve as a reference for analyzing polarization observation data from future orbiting spacecraft. These are expected to lead to new discoveries in the fields of astronomy and planetary science.
Real-Time 3D Tracking of Multi-Particle in the Wide-Field Illumination Based on Deep Learning
Authors: Luo Xiao , Zhang Jie , Tan Handong , Jiang Jiahao , Li Junda , Wen Weijia
Published: April 2024

In diverse realms of research, such as holographic optical tweezer mechanical measurements, colloidal particle motion state examinations, cell tracking, and drug delivery, the localization and analysis of particle motion command paramount significance. Algorithms ranging from conventional numerical methods to advanced deep-learning networks mark substantial strides in the sphere of particle orientation analysis. However, the need for datasets has hindered the application of deep learning in particle tracking. In this work, we elucidated an efficacious methodology pivoted toward generating synthetic datasets conducive to this domain that resonates with robustness and precision when applied to real-world data of tracking 3D particles. We developed a 3D real-time particle positioning network based on the CenterNet network. After conducting experiments, our network has achieved a horizontal positioning error of 0.0478 μm and a z-axis positioning error of 0.1990 μm. It shows the capability to handle real-time tracking of particles, diverse in dimensions, near the focal plane with high precision. In addition, we have rendered all datasets cultivated during this investigation accessible.
ST-TGR: Spatio-Temporal Representation Learning for Skeleton-Based Teaching Gesture Recognition
Authors: Chen Zengzhao , Huang Wenkai , Liu Hai , Wang Zhuo , Wen Yuqun , Wang Shengming
Published: April 2024

Teaching gesture recognition is a technique used to recognize the hand movements of teachers in classroom teaching scenarios. This technology is widely used in education, including for classroom teaching evaluation, enhancing online teaching, and assisting special education. However, current research on gesture recognition in teaching mainly focuses on detecting the static gestures of individual students and analyzing their classroom behavior. To analyze the teacher’s gestures and mitigate the difficulty of single-target dynamic gesture recognition in multi-person teaching scenarios, this paper proposes skeleton-based teaching gesture recognition (ST-TGR), which learns through spatio-temporal representation. This method mainly uses the human pose estimation technique RTMPose to extract the coordinates of the keypoints of the teacher’s skeleton and then inputs the recognized sequence of the teacher’s skeleton into the MoGRU action recognition network for classifying gesture actions. The MoGRU action recognition module mainly learns the spatio-temporal representation of target actions by stacking a multi-scale bidirectional gated recurrent unit (BiGRU) and using improved attention mechanism modules. To validate the generalization of the action recognition network model, we conducted comparative experiments on datasets including NTU RGB+D 60, UT-Kinect Action3D, SBU Kinect Interaction, and Florence 3D. The results indicate that, compared with most existing baseline models, the model proposed in this article exhibits better performance in recognition accuracy and speed.
Improving Graph Convolutional Network with Learnable Edge Weights and Edge-Node Co-Embedding for Graph Anomaly Detection
Authors: Tan Xiao , Yang Jianfeng , Zhao Zhengang , Xiao Jinsheng , Li Chengwang
Published: April 2024

The era of Industry 4.0 is gradually transforming our society into a data-driven one, which can help us uncover valuable information from accumulated data, thereby improving the level of social governance. The detection of anomalies, is crucial for maintaining societal trust and fairness, yet it poses significant challenges due to the ubiquity of anomalies and the difficulty in identifying them accurately. This paper aims to enhance the performance of the current Graph Convolutional Network (GCN)-based Graph Anomaly Detection (GAD) algorithm on datasets with extremely low proportions of anomalous labels. This goal is achieved through modifying the GCN network structure and conducting feature extraction, thus fully utilizing three types of information in the graph: node label information, node feature information, and edge information. Firstly, we theoretically demonstrate the relationship between label propagation and feature convolution, indicating that the Label Propagation Algorithm (LPA) can serve as a regularization penalty term for GCN, aiding in training and enabling learnable edge weights, providing a basis for incorporating node label information into GCN networks. Secondly, we introduce a method to aggregate node and edge features, thereby incorporating edge information into GCN networks. Finally, we design different GCN trainable weights for node features and co-embedding features. This design allows different features to be projected into different spaces, greatly enhancing model expressiveness. Experimental results on the DGraph dataset demonstrate superior AUC performance compared to baseline models, highlighting the feasibility and efficacy of the proposed approach in addressing GAD tasks in the scene with extremely low proportions of anomalous data.
Long-Term Coherent Integration Algorithm for High-Speed Target Detection
Authors: He Yao , Zhao Guanghui , Xiong Kai
Published: April 2024

Long-term coherent integration (CI) can effectively improve the radar detection capability for high-speed targets. However, the range walk (RW) effect caused by high-speed motion significantly degrades the detection performance. To improve detection performance, this study proposes an improved algorithm based on the modified Radon inverse Fourier transform (denoted as IMRIFT). The proposed algorithm uses parameter searching for velocity estimation, designs a compensation function based on the relationship between velocity and distance walk and Doppler ambiguity terms, and performs CI based on the compensated signal. IMRIFT can achieve RW correction, avoid the blind-speed sidelobe (BSSL) effect caused by velocity mismatch, and improve detection performance, while ensuring low computational complexity. In addition, considering the relationship between energy concentration regions and bandwidth in the 2D frequency domain, a fast method based on IMIRFT is proposed, which can balance computational cost and detection capacity. Finally, a series of comparative experiments are conducted to demonstrate the effectiveness of the proposed algorithm and the fast method.
α-Fe2O3/TiO2/Ti3C2Tx Nanocomposites for Enhanced Acetone Gas Sensors
Authors: Zhao Zhihua , Lv Zhenli , Chen Zhuo , Zhou Baocang , Shao Zhigang
Published: April 2024

Metal oxide semi-conductors are widely applied in various fields due to their low cost, easy processing, and good compatibility with microelectronic technology. In this study, ternary α-Fe2O3/TiO2/Ti3C2Tx nanocomposites were prepared via simple hydrothermal and annealing treatments. The composition, morphology, and crystal structure of the samples were studied using XPS, SEM, EDS, XRD, and multiple other testing methods. The gas-sensing measurement results suggest that the response value (34.66) of the F/M-3 sensor is 3.5 times higher than the pure α-Fe2O3 sensor (9.78) around 100 ppm acetone at 220°C, with a rapid response and recovery time (10/7 s). Furthermore, the sensors have an ultra-low detection limit (0.1 ppm acetone), excellent selectivity, and long-term stability. The improved sensitivity of the composites is mainly attributed to their excellent metal conductivity, the unique two-dimensional layered structure of Ti3C2Tx, and the heterojunction formed between the nanocomposite materials. This research paves a new route for the preparation of MXene derivatives and metal oxide nanocomposites.
Mit den Deutschen oder gegen sie? Eine politische Entscheidung – eine kulturelle Entscheidung? Die dynastische Frage in Rumänien in den Jahren 1916-1918
Authors:   Fakultät für Geschichte der Universität Alexandru Ioan
Cuza Iași, Buruianã Ovidiu
Published: April 2024

This study tackles the political and cultural dispute regarding Romania’s participation in the world
war that began in 1914. Seen as an opportunity to achieve the political objective of the 19th century—namely, the unification of the Romanians—the conflict posed a civilizational dilemma for
the elites of the Old Kingdom, who had to choose which side the country should join. Although
the Romanian state and society after 1878 owed much of their political, cultural, academic and
economic transformation to Germany, the majority decided in favor of the Entente Powers. In
the present text we attempt to answer two questions: what were the insidious cultural mechanisms
that supported, between 1914 and 1916, the prevalent political decision, which in the context
of war breaking out in Europe leaned towards the Entente instead of the Central Powers? Additionally, we analyze the reasoning behind the choice for Transylvania and the Romanians living
there to the detriment of Bessarabia. Also discussed is the manner in which the aversion towards
Germany and the German culture/civilization came to be in the public space of the time (a phenomenon extended to the historiographic field). Furthermore, in the present study we look at the
positioning of the German dynasty in Romania at the center of the political and symbolic debates
regarding the salvation of the nation and the reconstruction of the state
THE DEVELOPMENT OF THE AGRO-INDUSTRIAL COMPLEX OF THE MUNICIPAL DISTRICT AS A FACTOR IN ENSURING THE COUNTRY'S FOOD SECURITY
Authors: Podmolodina Irina , Davydenko I.
Published: April 2024

The article presents an analysis of the development of the agro-industrial complex of the Voronezh region and the Khokholsky municipal district of the Voronezh region, which allowed us to conclude about a stable trend in the development of the main branches of the agro-industrial complex of the Khokholsky district. However, in some positions, the Khokholsky district is lagging behind the regional average indicators of agricultural development. The necessity of further development of the agro-industrial complex of the Khokholsky district is substantiated and its directions are determined taking into account the use of modern technologies.
Challenges and Barriers in Implementing Inclusive Education Policies
Authors: Ratheeswari K. , Nallathambi K.
Published: April 2024

The noble concept of inclusive education seeks to give all students, regardless of their aptitudes, disabilities, or individual characteristics, high-quality educational experiences. It encourages the establishment of learning settings that value each student’s holistic development and embrace diversity. Even though inclusive education has many supporters and proponents, there are several obstacles that must be overcome before it can be successfully implemented. This summary offers a concise synopsis of the difficulties and roadblocks related to inclusive education policies, illuminating issues with funding, opposition to change, teacher readiness, assessment, social inclusion, diversity, legal loopholes, and community involvement. As they collaborate to realise the goal of education, stakeholders in the field—from legislators to teachers and families—must have a thorough understanding of these obstacles of inclusive education Finding long-term solutions that support inclusive and equitable learning environments begins with acknowledging these challenges. The examination of the complexities of inclusive education difficulties in this article provides insights into the subtleties of this important sector and establishes the groundwork for thoughtful conversations and strategic planning targeted at resolving these obstacles. In the end, overcoming these obstacles will help to realise the fundamental goal of inclusive education, which is to give every student an equal chance to succeed both academically and personally.
The Influence of Cultural Differences on Customer Satisfaction: The Case of Amman Airport (QAIA)
Authors: Alhmoud Murad , Kuşak Sümeyye
Published: April 2024

Cultural differences between airport employees and passengers can substantially impact how those passengers evaluate and judge the quality of services provided to them at airports. In this regard, the present study aims to investigate whether the differences in cultural backgrounds between customers and airport employees affect the customers' comfortability and satisfaction while using Amman Airport. The data was collected via a questionnaire to measure customer satisfaction and comfortability. In addition, demographic factors, like age, gender and education, were also taken into consideration. The study sample includes purposively selected 100 passengers. For data analysis, SPSS 22.0 software was used. While customer satisfaction and comfortability vary with education and nationality, they do not show significant differences based on gender and age. However, there is a significant impact of cultural comfortability of passengers on their satisfaction.
PRELIMINARY RESEARCHES ON SOME TECHNICAL-FUNCTIONAL PARAMETERS OF AN EXPERIMENTAL MODEL OF CONVECTIVE DRYER WITH TOTAL ENERGY INDEPENDENCE
Authors: SORICĂ Cristian , PĂTRUȚ Andrei , ȘOVĂIALĂ Gheorghe , SORICĂ Elena , VLĂDUȚOIU Laurențiu , CRISTEA Mario , MATACHE Gabriela , PAVEL Ioan
Published: April 2024

In order to be consumed whole year at a nutritional value close to the freshly picked product, seasonal vegetal products (vegetables, fruits, aromatic and medicinal plants, seeds, berries, mushrooms etc.) are preserved by artificial dehydration. Unlike other preservation methods and techniques, dehydration leads to obtaining products with a weight 8-10 times reduced and a volume 3-4 times smaller, a fact that contributes to the reduction of the spaces required for storage and the substantial reduction of handling and transport costs, compared to those for fresh vegetal products. Taking into account the general context related to global warming, as well as the need to reduce energy consumption from fossil fuels, the paper approaches the preliminary experimental research of a small capacity convective dryer, with total energy independence from the electricity network, intended for small agricultural producers from isolated hill and mountain areas. The technical equipment consists of a thermal generator operating on TLUD principle, which utilizes existing biomass at the local level, a high-efficiency air-air heat exchanger and a drying room with trays. The aim was to determine some important technical-functional parameters in the working process of the equipment, such as: the temperature of the burnt gases, the biomass loading capacity of the gasification reactor, the capacity to regulate the air flow required for the thermo-chemical processes, the temperature at various keypoints inside equipment etc. Following the analysis of the experimental data, there were highlighted quantitative values useful for estimating the inputs required for a normal operation of the equipment.
Effect of Transformational Leadership and Work Stress on Organizational Citizenship Behavior with Organizational Commitment as an Intervening Variable
Authors: Arrozi Muhammad Fachruddin , Tirtayasa Charli Otman , Nofiarni Nofiarni
Published: April 2024

Background. Organizational citizenship behavior (OCB) is defined as behavior that goes beyond formally defined roles and is not stated in the job description. Objective: The study aimed to examine the effect of Organizational Citizenship Behavior (OCB) that are influenced by the Transformational Leadership of the Head of the Inpatient Room, work stress, and nurse organizational commitment simultaneously. Method: This research uses a survey method with an explanatory causality approach. Data was collected by using a questionnaire and tested using Multiple Linear Regression Analysis. Result: Transformational leadership, job stress, and organizational commitment significantly affect organizational citizenship behavior simultaneously. Transformational leadership is the biggest factor. Organizational commitment can mediate the effect of Transformational Leadership and work stress on Organizational Citizenship Behavior. Transformational leadership significantly affects Organizational Commitment, Work Stress significantly affects Organizational Commitment, Organizational Commitment significantly affects Organizational Citizenship Behavior, and Transformational Leadership significantly affects Organizational Citizenship Behavior. Work stress significantly affects Organizational Citizenship Behavior. Implication: This study helps hospital management to promote a more effective work culture through Transformational Leadership training, Organizational Citizenship Behavior of Heads of Inpatient rooms, and a new method of selecting new nurses recruitment by HRD and long-term prosocial improvement for senior employees
Factors Associated with the Incidence of Diabetic Ulcers in Clients with Diabetes Mellitus at Labuang Baji Hospital Makassar
Authors: Nusdin Nusdin , Awaluddin Achmad Indra
Published: April 2024

Background: Diabetes Mellitus is classified into a group of metabolic diseases with specific characteristics of increased blood sugar levels or hyperglycemia. Clients with Diabetes Mellitus have the potential for 15-25% to experience diabetic foot ulcers caused by the factors of cholesterol, use of footwear, and self-management of diabetes mellitus. Objectives: This study aims to determine factors associated with the incidence of diabetic ulcers in clients with diabetes mellitus at Labuang Baji Hospital Makassar. Methods: The type of research used was quantitative with a cross-sectional design. The number of samples used was 50 respondents by using accidental sampling. The research instrument used a questionnaires and Standard Operating Procedures for cholesterol examination. Result: The study results using the Spearman Correlation Testshowed a relationship between cholesterol and the incidence of diabetic ulcers in clients with Diabetes Mellitus with the p-value = 0.001 (p <0.05). There is a relationship between footwear usage and the incidence of diabetic ulcers in clients with diabetes mellitus with the p-value = 0.001 (p < 0.05) and there is a relationship between Self Management Diabetes Mellitus (SMDM) with the incidence of diabetic ulcers in clients with diabetes mellitus with p-value = 0.001 (p<0.05). Conclusion: Cholesterol, footwear usage, and Diabetes Mellitus Self Management (SMDM) are the factors of Diabetic ulcers in clients with diabetes mellitus. Recommendation: This study could be an adjunct for further systemic review and expected for further study to research about the other factor or the effect of treatment sequacity on diabetic ulcer recovery
The Influence of Workload, Knowledge, Motivation on Medical Record Quality Through Doctor Compliance
Authors: Arrandhikasari Devina , Pamungkas Rian Adi , Saptaningsih Agusdini Banun
Published: April 2024

Background. Medical records are records and documents containing the patient's identity, examination, treatment, actions and other services that have been provided to patients. Medical records are said to be of high quality if the data and information are complete and can be read by those entitled to it from time to time as a continuous communication tool. Objective: The study aimed to analyze the effect of workload, knowledge and motivation through doctor compliance that can improve the medical record quality. Method: This study uses a quantitative approach with a causal design research using SPSS-Path Analysis. Result: There was no effect of workload on the quality of medical records through doctor's compliance, there was an influence of knowledge on the quality of medical records through doctor's compliance and there was an influence of motivation on the quality of medical records through doctor's compliance. Implication: This study proves that the amount of doctor's compliance is able to mediate the effect of knowledge and motivation which can improve the quality of medical records. Hospital management is expected to be able to motivate doctors to understand changes in the current digitalization era and to improve the level of awareness of doctors to work in an orderly administration.

 

 

Keywords: Compliance, Knowledge, Medical Record Quality, Motivation, Workload
Role Ambiguity, Workload, and Work Motivation Influenced the Turnover Intention among Employees at Mother and child hospital
Authors: Palili Mohammad Ridwan , Hasyim Hasyim , Pamungkas Rian Adi
Published: April 2024

Background: Human resources play an essential role in achieving the success and goals of the hospital. Thereby, to connect all scopes of human resources, there needs to be good management. Objective: This study aims to analyze the effect of role ambiguity and workload and work motivation on employee turnover intention at Mother and Child Vitalaya Hospital. Method: A correlation study with a cross-sectional approach was applied in this study. Result: Multiple linear regression tests show that the coefficient of determination R square is 0.735. This indicates that role ambiguity, workload, and work motivation simultaneously contribute 74% to turnover intention. However, partially only work motivation influences employee turnover intention at Mother and Child Vitalaya Hospital. Conclusion: role ambiguity and workload were strong predictors of employee turnover intention. Recommendation: The human resource unit must consider those factors to prevent employee turnover. Further studies need to test other elements with a broad population to ensure the role of factors in avoiding turnover intention