bluuebunny/crossref_metadata_2025 huggingface dataset:
“Fading out” - genomic epidemiology of the last persistently infected BVDV cattle in Germany
Authors: Wernike Kerstin , Pfaff Florian , Beer Martin
Published: January 2024

Bovine viral diarrhea virus (BVDV) is one of the most important cattle pathogens worldwide, causing major economic losses and animal welfare issues. Disease eradication programs have been implemented in several countries, including Germany where an obligatory nationwide control program is in force since 2011. As molecular epidemiology has become an essential tool to understand the transmission dynamics and evolution of BVDV, 5′ untranslated region (UTR) sequences are generated from viruses present in persistently infected animals since the beginning of the BVDV control program. Here, we report the results of the sequence-based subtyping of BVDV strains found from 2018 through 2022 in calves born in Germany. In 2018, 2019 and 2020, BVDV-1d and-1b were the dominant subtypes and cases were spread throughout the area that was not yet officially declared BVDV-free at that time. In addition, BVDV–1a, −1e, −1f and -1h could rarely be detected. From 2021 onwards, subtype 1d clearly took over the dominance, while the other subtypes could be gradually nearly eliminated from the cattle population. The eradication success not only results in a drastic reduction of cases, but also in a marked reduction of strain diversity. Interestingly, before vaccination has been banned in regions and farms with a disease-free status, two live-vaccine virus strains were repeatedly detected in ear tissue samples of newborn calves (n = 14) whose mothers were immunized during gestation. The field-virus sequences are an important basis for molecular tracing and identification of potential relationships between the last outbreaks in the final phase of the German BVDV eradication program, thereby supporting classic epidemiological investigations. Furthermore, the monitoring of the composition of virus subtypes in the cattle population helps to maintain effective diagnostic methods and control measures and is an early warning system for the introduction of new pestiviruses in the naïve cattle population.
An Improved Analytical Model of a Thrust Stand with a Flexure Hinge Structure Considering Stiffness Drift and Rotation Center Offset
Authors: Chen Xingyu , Zhao Liye , Xu Jiawen , Liu Zhikang
Published: January 2024

Micro-newton thrust stands are widely used in thruster ground calibration procedures for a variety of space missions. The conventional analytical model does not consider the gravity-induced extension effect and systematic error in displacement for thrust stands consisting of hanging pendulums based on flexure hinge structures. This paper proposes an improved analytical model of a hanging pendulum for thrust measurement, where an elliptical notched flexure hinge is the key component. A parametric model of the bending stiffness of the flexure hinge is developed. Equally, both the bending stiffness shift under the gravity-induced extension effect and the systematic error in displacement due to the assumed rotational center offset of the hinge are investigated. The presented stiffness equations for elliptical notched hinges can be degenerated into stiffness equations for circular notched as well as leaf-type hinges. The improved model aims to evaluate and highlight the influence of the two considered factors for use in thrust stand parameter design and thrust analysis. A finite element modeling solution is proposed to validate the proposed analytical model. The results show that the proposed model can quantify the hinge bending stiffness shift, which also demonstrates that even a small bending stiffness shift may introduce great uncertainty into the thrust analysis.
Evaluating the Enzyme Activities and Soil Physicochemical Properties of Four Typical Halophytic Communities in Saline-Sodic Soil
Authors: Zhou Jie , Miao Yue , Guo Liangliang , Zhang Tieyi , Nie Zhaoyang , Luo Xuejiao , Yang Fan , Wang Zhichun
Published: January 2024

Four typical halophytic communities found in saline-sodic soil, including Phragmites australis, Suaeda glauca, Leymus chinensis, and Puccinellia parl, were investigated in this study. A comparison was made among the electrical conductivity (EC) value, pH value, soil organic carbon (SOC), and soil enzyme activity across various soil depths. The findings of this study indicate that the EC and pH levels of the soil at the 0–40 cm depth vary among the four communities, with Suaeda glauca having the highest values, followed by Puccinellia parl, Phragmites australis, and Leymus chinensis. The highest value of SOC among the four communities was observed in the Leymus chinensis community (0.85–0.94 g/kg), followed by the Phragmites australis community (0.50–0.77 g/kg), and the lowest levels were observed in the Puccinellia parl community (0.37–0.78 g/kg). As the soil depth increases, there is a decline in the amount of SOC. With an increase in soil depth, the content of SOC in the soil decreased, and the content of total nitrogen (TN) and the activity of six enzymes in the soil of each community increased. Furthermore, at the soil layer of 0–20 cm, the TN content in the soils was negatively correlated with pH and EC (p < 0.01), and so was the total phosphorus (TP). Additionally, the TP content is considerably positively connected with alkaline phosphatase (ALP) activity, whereas the TN content is significantly positively correlated with Soil Urease (S-UE) activity. Within the soil depth of 20–40 cm, the levels of TN, TP, and SOC exhibit a negative association with pH and EC. However, this link is weaker compared to that observed in the surface soil. A strong inverse correlation (p < 0.05) exists between the TP concentration and the ALP activity. The objective of this study was to investigate the use of halophytes in various saline-sodic soils for diverse avenues of restoration, and to establish a database on the role and efficacy of plant roots in enhancing saline-sodic soil.
Effects of Supplementing Drinking Water of Parental Pigeons with Enterococcus faecium and Bacillus subtilis on Antibody Levels and Microbiomes in Squabs
Authors: Ma Hui , Li Yunlei , Han Pengmin , Zhang Ran , Yuan Jingwei , Sun Yanyan , Li Jianhui , Chen Jilan
Published: January 2024

Enterococcus faecium (E. faecium) and Bacillus subtilis (B. subtilis) are widely used as probiotics to improve performance in animal production, but there have been few reports of their impacts on pigeon milk. In this study, twenty-four pairs of parental pigeons were randomly divided into four groups, with six replicates, and each pair feeding three squabs. The control group drank normal water. The E. faecium group, B. subtilis group, and mixed group drank water supplemented with 3 × 106 CFU/mL E. faecium, 2 × 107 CFU/mL B. subtilis, and a mixture of these two probiotics, respectively. The experiment lasted 19 days. The results demonstrated that the IgA and IgG levels were significantly higher in the milk of Group D pigeons than in the other groups. At the phylum level, Fimicutes, Actinobacteria, and Bacteroidetes were the three main phyla identified. At the genus level, Lactobacillus, Bifidobacterium, Veillonella, and Enterococcus were the four main genera identified. In conclusion, drinking water supplemented with E. faecium and B. subtilis could improve immunoglobulin levels in pigeon milk, and this could increase the ability of squabs to resist disease. E. faecium and B. subtilis could be used as probiotics in the pigeon industry.
Research on VVC Intra-Frame Bit Allocation Scheme Based on Significance Detection
Authors: Jin Xuesong , Sun Huiyuan , Zhang Yuhang
Published: January 2024

This research is based on an intra-frame rate control algorithm based on the Versatile Video Coding (VVC) standard, considering that there is the phenomenon of over-allocating the bitrate of the end coding tree units (CTUs) in the bit allocation process, while the front CTUs are not effectively compressed. Fusing a Canny-based edge detection algorithm, a color contrast-based saliency detection algorithm, a Sum of Absolute Transformed Differences (SATD) based CTU coding complexity measure, and a Partial Least Squares (PLS) regression model, this paper proposes a CTU-level bit allocation improvement scheme for intra-mode code rate control of the VVC standard. First, natural images are selected to produce a lightweight dataset. Second, different metrics are utilized to obtain the significance and complexity values of each coding unit, the relatively important coding units in the whole frame are selected, which are adjusted with different weights, and the optimal adjustment multiplicity is supplemented into the dataset. Finally, the PLS regression model was used to obtain regression equations to refine the weights for adjusting the bit allocation. The proposed bit allocation scheme improves the average rate control accuracy by 0.453%, Y-PSNR by 0.05 dB, BD-rate savings by 0.33%, and BD-PSNR by 0.03 dB compared to the VVC standard rate control algorithm.
Efficient Diagnosis of Autism Spectrum Disorder Using Optimized Machine Learning Models Based on Structural MRI
Authors: Bahathiq Reem Ahmed , Banjar Haneen , Jarraya Salma Kammoun , Bamaga Ahmed K. , Almoallim Rahaf
Published: January 2024

Autism spectrum disorder (ASD) affects approximately 1.4% of the population and imposes significant social and economic burdens. Because its etiology is unknown, effective diagnosis is challenging. Advancements in structural magnetic resonance imaging (sMRI) allow for the objective assessment of ASD by examining structural brain changes. Recently, machine learning (ML)-based diagnostic systems have emerged to expedite and enhance the diagnostic process. However, the expected success in ASD was not yet achieved. This study evaluates and compares the performance of seven optimized ML models to identify sMRI-based biomarkers for early and accurate detection of ASD in children aged 5 to 10 years. The effect of using hyperparameter tuning and feature selection techniques are investigated using two public datasets from Autism Brain Imaging Data Exchange Initiative. Furthermore, these models are tested on a local Saudi dataset to verify their generalizability. The integration of the grey wolf optimizer with a support vector machine achieved the best performance with an average accuracy of 71% (with further improvement to 71% after adding personal features) using 10-fold Cross-validation. The optimized models identified relevant biomarkers for diagnosis, lending credence to their truly generalizable nature and advancing scientific understanding of neurological changes in ASD.
Alignment of Unsupervised Machine Learning with Human Understanding: A Case Study of Connected Vehicle Patents
Authors: Bridgelall Raj
Published: January 2024

As official public records of inventions, patents provide an understanding of technological trends across the competitive landscape of various industries. However, traditional manual analysis methods have become increasingly inadequate due to the rapid expansion of patent information and its unstructured nature. This paper contributes an original approach to enhance the understanding of patent data, with connected vehicle (CV) patents serving as the case study. Using free, open-source natural language processing (NLP) libraries, the author introduces a novel metric to quantify the alignment of classifications by a subject matter expert (SME) and using machine learning (ML) methods. The metric is a composite index that includes a purity factor, evaluating the average ML conformity across SME classifications, and a dispersion factor, assessing the distribution of ML assigned topics across these classifications. This dual-factor approach, labeled the H-index, quantifies the alignment of ML models with SME understanding in the range of zero to unity. The workflow utilizes an exhaustive combination of state-of-the-art tokenizers, normalizers, vectorizers, and topic modelers to identify the best NLP pipeline for ML model optimization. The study offers manifold visualizations to provide an intuitive understanding of the areas where ML models align or diverge from SME classifications. The H-indices reveal that although ML models demonstrate considerable promise in patent analysis, the need for further advancements remain, especially in the domain of patent analysis.
Analysis of a Wind-Driven Power Generation System with Root Slapping Mechanism
Authors: Wang Yi-Ren , Chang Jin-Wei , Lin Chen-Yu
Published: January 2024

This study introduces a groundbreaking slap-type Vibration Energy Harvesting (VEH) system, leveraging a rotating shaft with magnets to induce vibrations in an adjacent elastic steel sheet through magnetic repulsion. This unique design causes the elastic sheet to vibrate, initiating the oscillation of a seesaw-type rigid plate lever. The lever then slaps a piezoelectric patch (PZT) at the elastic steel sheet’s root, converting vibrations into electrical energy. Notably, the design enables the PZT to withstand deformation and flapping forces simultaneously, enhancing power conversion efficiency. The driving force for the rotating shaft is harnessed from the downstream flow field generated by moving objects like rotorcraft, fixed-wing aircraft, motorcycles, and bicycles. Beyond conventional vibration energy harvesting, this design taps into additional electric energy generated by the PZT’s slapping force. This study includes mathematical modeling of nonlinear elastic beams, utilizing the Method of Multiple Scales (MOMS) for in-depth vibration mode analysis. Experimental validation ensures the convergence of theory and practice, confirming the feasibility and superior voltage generation efficiency of this slap-type VEH concept compared to traditional VEH systems.
Application of a Hybrid Model in Landslide Susceptibility Evaluation of the Western Tibet Plateau
Authors: Yang Yongpeng , Guo Ya , Chen Hao , Tang Hao , Li Meng , Sun Ang , Bian Yu
Published: January 2024

The evaluation of landslide susceptibility plays a crucial role in preventing the risks associated with landslides and debris flows, providing valuable insights for the effective prevention and mitigation of geological hazards. However, there is limited research on high-altitude areas. Therefore, this study chose the western Tibetan Plateau as the study area, a representative area known for its susceptibility to landslides and high attitudes. In this study, seven factors were identified based on research objectives. Information value (IVM), weight of evidence (WOE), information value logistic regression (IVM-LR), weight of evidence logistic regression (WOE-LR), information value multi-layer perceptron (IVM-MLP) and weight of evidence multi-layer perceptron (WOE-MLP) were selected and compared for landslide susceptibility. The percentage of disaster area included in each risk level, the AUC value and the ROC curve were used to evaluate the accuracy of the results. The ROC curves of the results were close to the upper–left corner and the AUC values exceeded 0.85, an indication that all results were highly accurate. Moreover, the percentage of disaster area included for each risk showed an upward trend regarding susceptibility. The results indicated that the hybrid model exhibited superior performance in assessing landslide susceptibility at high altitudes. Overall, the results showed great significance regarding disaster prevention and mitigation measures of local governments.
FedNow: An Efficiency-Aware Incentive Mechanism Enables Privacy Protection and Efficient Resource Utilization in Federated Edge Learning
Authors: Lu Jianfeng , Yuan Wenxuan , Cao Shuqin , Zhou Pan
Published: January 2024

Federated edge learning (FEL) has recently attracted great interest due to its real-time response and energy-efficient characteristics. Most existing work focuses on designing algorithms to improve model performance, ignoring the malicious behavior and personal decision-making of self-interested edge servers. Although some efforts have been devoted to incentivizing honest edge server engagement by compensating training costs, this rarely considers resource efficiency and often assumes that edge servers provide complete information to the platform, which may lead to the risk of private attribute leakage. Hence, we aim to achieve an incentive mechanism that promotes secure and efficient model training between the platform and edge servers. However, edge servers’ multi-dimensional private attributes and training strategies make the optimization problem nonconvex, and incomplete information further increases the complexity of the analysis. In order to address these challenges and by integrating contract theory and exponential mechanism, we propose an efficiency-aware incentive mechanism, FedNow, which enables edge servers to personally determine their local training rounds while motivating their participation without giving access to their true training strategies and private attributes. Specifically, we enabld edge servers to add noise to their submitted training strategy to hide their true training rounds; then, we carefully designed an efficiency score function to select honest and efficient edge servers without disclosing their private attributes. In order to demonstrate that FedNow strictly outperforms existing schemes in terms of total costs, we theoretically derived sufficient conditions for making the total costs of FedNow lower than existing schemes and designed a greedy algorithm that uses the Monte Carlo method to find feasible near-optimal solutions in polynomial time. Our extensive experimental assessment using synthetic and real datasets shows the superiority of FedNow.
Metabolomics, Transcriptome and Single-Cell RNA Sequencing Analysis of the Metabolic Heterogeneity between Oral Cancer Stem Cells and Differentiated Cancer Cells
Authors: Miao Yuwen , Wang Pan , Huang Jinyan , Qi Xin , Liang Yingjiqiong , Zhao Wenquan , Wang Huiming , Lyu Jiong , Zhu Huiyong
Published: January 2024

Understanding the distinct metabolic characteristics of cancer stem cells (CSC) may allow us to better cope with the clinical challenges associated with them. In this study, OSCC cell lines (CAL27 and HSC3) and multicellular tumor spheroid (MCTS) models were used to generate CSC-like cells. Quasi-targeted metabolomics and RNA sequencing were used to explore altered metabolites and metabolism-related genes. Pathview was used to display the metabolites and transcriptome data in a KEGG pathway. The single-cell RNA sequencing data of six patients with oral cancer were analyzed to characterize in vivo CSC metabolism. The results showed that 19 metabolites (phosphoethanolamine, carbamoylphosphate, etc.) were upregulated and 109 metabolites (2-aminooctanoic acid, 7-ketocholesterol, etc.) were downregulated in both MCTS cells. Integration pathway analysis revealed altered activity in energy production (glycolysis, citric cycle, fatty acid oxidation), macromolecular synthesis (purine/pyrimidine metabolism, glycerophospholipids metabolism) and redox control (glutathione metabolism). Single-cell RNA sequencing analysis confirmed altered glycolysis, glutathione and glycerophospholipid metabolism in in vivo CSC. We concluded that CSCs are metabolically inactive compared with differentiated cancer cells. Thus, oral CSCs may resist current metabolic-related drugs. Our result may be helpful in developing better therapeutic strategies against CSC.
A Comprehensive Analysis of Tn and STn Antigen Expression in Esophageal Adenocarcinoma
Authors: Mercanoglu Baris , Karstens Karl-Frederick , Giannou Anastasios D. , Meiners Jan , Lücke Jöran , Seeger Philipp , Brackrock Vera , Güngör Cenap , Izbicki Jakob R. , Bockhorn Maximilian , Hackert Thilo , Melling Nathaniel , Wolters-Eisfeld Gerrit
Published: January 2024

Differential glycosylation, marked by the presence of truncated O-glycans, is a distinctive feature of epithelial-derived cancers. However, there is a notable gap in research regarding the expression of Tn and STn antigens in esophageal adenocarcinoma (EAC). To address this, we employed commercially available antibodies, previously validated for Tn and STn antigens, to analyze two cohorts of EAC tissues. Initially, large-area tissue sections from formalin-fixed paraffin-embedded (FFPE) EAC and corresponding healthy tissues were subjected to immunohistochemistry (IHC) staining and scoring. Subsequently, we evaluated the RNA expression levels of crucial O-glycosylation related genes—C1GALT1 and C1GALT1C1—using a quantitative real-time polymerase chain reaction (qRT-PCR). In a comprehensive analysis, a substantial cohort of EAC tissues (n = 311 for Tn antigen, n = 351 for STn antigen) was investigated and correlated with clinicopathological data. Our findings revealed that Tn and STn antigens are highly expressed (approximately 71% for both) in EAC, with this expression being tumor-specific. Notably, Tn antigen expression correlates significantly with the depth of tumor cell infiltration (p = 0.026). These antigens emerge as valuable markers and potential therapeutic targets for esophageal adenocarcinoma.
A High-Protein Diet Promotes Atrial Arrhythmogenesis via Absent-in-Melanoma 2 Inflammasome
Authors: Song Jia , Wu Jiao , Robichaux Dexter J. , Li Tingting , Wang Shuyue , Arredondo Sancristobal Maria J. , Dong Bingning , Dobrev Dobromir , Karch Jason , Thomas Sandhya S. , Li Na
Published: January 2024

High-protein diets (HPDs) offer health benefits, such as weight management and improved metabolic profiles. The effects of HPD on cardiac arrhythmogenesis remain unclear. Atrial fibrillation (AF), the most common arrhythmia, is associated with inflammasome activation. The role of the Absent-in-Melanoma 2 (AIM2) inflammasome in AF pathogenesis remains unexplored. In this study, we discovered that HPD increased susceptibility to AF. To demonstrate the involvement of AIM2 signaling in the pathogenesis of HPD-induced AF, wildtype (WT) and Aim2−/− mice were fed normal-chow (NC) and HPD, respectively. Four weeks later, inflammasome activity was upregulated in the atria of WT-HPD mice, but not in the Aim2−/−-HPD mice. The increased AF vulnerability in WT-HPD mice was associated with abnormal sarcoplasmic reticulum (SR) Ca2+-release events in atrial myocytes. HPD increased the cytoplasmic double-strand (ds) DNA level, causing AIM2 activation. Genetic inhibition of AIM2 in Aim2−/− mice reduced susceptibility to AF, cytoplasmic dsDNA level, mitochondrial ROS production, and abnormal SR Ca2+-release in atrial myocytes. These data suggest that HPD creates a substrate conducive to AF development by activating the AIM2-inflammasome, which is associated with mitochondrial oxidative stress along with proarrhythmic SR Ca2+-release. Our data imply that targeting the AIM2 inflammasome might constitute a novel anti-AF strategy in certain patient subpopulations.
High Stretch Modulates cAMP/ATP Level in Association with Purine Metabolism via miRNA–mRNA Interactions in Cultured Human Airway Smooth Muscle Cells
Authors: Luo Mingzhi , Wang Chunhong , Guo Jia , Wen Kang , Yang Chongxin , Ni Kai , Liu Lei , Pan Yan , Li Jingjing , Deng Linhong
Published: January 2024

High stretch (>10% strain) of airway smooth muscle cells (ASMCs) due to mechanical ventilation (MV) is postulated to contribute to ventilator-induced lung injury (VILI), but the underlying mechanisms remain largely unknown. We hypothesized that ASMCs may respond to high stretch via regulatory miRNA–mRNA interactions, and thus we aimed to identify high stretch-responsive cellular events and related regulating miRNA–mRNA interactions in cultured human ASMCs with/without high stretch. RNA-Seq analysis of whole genome-wide miRNAs revealed 12 miRNAs differentially expressed (DE) in response to high stretch (7 up and 5 down, fold change >2), which target 283 DE-mRNAs as identified by a parallel mRNA sequencing and bioinformatics analysis. The KEGG and GO analysis further indicated that purine metabolism was the first enriched event in the cells during high stretch, which was linked to miR-370-5p–PDE4D/AK7. Since PDE4D/AK7 have been previously linked to cAMP/ATP metabolism in lung diseases and now to miR-370-5p in ASMCs, we thus evaluated the effect of high stretch on the cAMP/ATP level inside ASMCs. The results demonstrated that high stretch modulated the cAMP/ATP levels inside ASMCs, which could be largely abolished by miR-370-5p mimics. Together, these findings indicate that miR-370-5p–PDE4D/AK7 mediated high stretch-induced modulation of cAMP and ATP synthesis inside ASMCs. Furthermore, such interactive miRNA–mRNA pairs may provide new insights for the discovery of effective biomarkers/therapeutic targets for the diagnosis and treatment of VILI and other MV-associated respiratory diseases.
Effect of Blending of Shellac, Carbonyl Iron Powder, and Carbonyl Iron Powder/Carbon Nanotube Microcapsules on the Properties of Coatings
Authors: Zhu Ye , Li Wenbo , Xia Yongxin , Hang Jingyi , Yan Xiaoxing , Li Jun
Published: January 2024

Nine sets of orthogonal experimental samples were prepared by examining four factors: shellac microcapsules, carbonyl iron powder (CIP) microcapsules, CIP/ carbon nanotube (CNT) microcapsules, and primer coating thickness. By testing the morphology and performance of the coating and using the fracture elongation of the coating as an orthogonal experimental analysis, the maximum factor affecting the fracture elongation of shellac, CIP, and CIP/CNT microcapsule coatings was determined. The first two factors that had a significant impact on the fracture elongation of the coating were the content of CIP/CNT microcapsules and shellac microcapsules. In order to further optimize the coating performance, important factor experiments were conducted, using the content of CIP/CNT microcapsules and shellac microcapsules as variables. It was found that the coating had the best performance when the content of CIP/CNT microcapsules was 7.0% and the content of shellac microcapsules was 4.0%. The optical properties of coatings with added shellac, CIP, and CIP/CNT microcapsules were tested, and the color difference and glossiness of the coatings showed little change. The mechanical properties of coatings with added shellac, CIP, and CIP/CNT microcapsules were tested. The blending of the three types of microcapsules enhanced the toughness of the coating to a certain extent, and suppressed the generation of micro-cracks, demonstrating a good self-healing effect. The electromagnetic-absorption performance of coatings with added shellac, CIP, and CIP/CNT microcapsules was tested. The blending of shellac, CIP, and CIP/CNT microcapsules exhibited two effective bands of electromagnetic absorption and a good absorption performance at a relatively wide frequency range. The combination of shellac, CIP, and CIP/CNT microcapsules endows the fiberboard surface with self-healing and electromagnetic-absorption functions, while maintaining the original performance of the water-based coating. The results can be used for application of surface coatings on wooden materials with dual functions of self-healing and electromagnetic absorption.
Review on Lymph Node Metastases, Sentinel Lymph Node Biopsy, and Lymphadenectomy in Sarcoma
Authors: Chmiel Paulina , Krotewicz Maria , Szumera-Ciećkiewicz Anna , Bartnik Ewa , Czarnecka Anna M. , Rutkowski Piotr
Published: January 2024

Soft tissue sarcomas (STS) originating from connective tissue rarely affect the lymph nodes. However, involvement of lymph nodes in STS is an important aspect of prognosis and treatment. Currently, there is no consensus on the diagnosis and management of lymph node metastases in STS. The key risk factor for nodal involvement is the histological subtype of sarcoma. Radiological and pathological evaluation seems to be the most effective method of assessing lymph nodes in these neoplasms. Thus, sentinel lymph node biopsy (SLNB), which has been shown to be valuable in the management of melanoma or breast cancer, may also be a beneficial diagnostic option in some high-risk STS subtypes. This review summarizes data on the risk factors and clinical characteristics of lymph node involvement in STS. Possible management and therapeutic options are also discussed.
Diet Supplementation with Rosemary (Rosmarinus officinalis L.) Leaf Powder Exhibits an Antidiabetic Property in Streptozotocin-Induced Diabetic Male Wistar Rats
Authors: Kabubii Zelipha N. , Mbaria James M. , Mathiu Peter Mbaabu , Wanjohi John M. , Nyaboga Evans N.
Published: January 2024

Diabetes mellitus is a metabolic disorder that has a high global health burden and causes high mortality and morbidity in humans. Medicinal herbs and plants offer a promising alternative to conventional therapies for the management of diabetes. Rosemary (Rosmarinus officinalis L.) is a traditional medicinal herb that has been used for the management of several diseases. Therefore, the present study investigates the antidiabetic properties of diets supplemented with R. officinalis leaf powder on streptozotocin-induced diabetic Wistar rats. First, the phytochemicals and 2,2-dephenyl-1-picrylhydrazyl (DPPH) free-radical scavenging activity of aqueous R. officinalis leaf extract were determined. Streptozotocin-induced diabetic male Wistar rats were fed a diet supplemented with R. officinalis leaf powder (ROP) at 3%, 6%, and 12%, respectively, for 6 weeks. Investigations of food intake, body weight, rat relative organ weights, blood glucose, lipid profiles, creatinine, bilirubin, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were estimated according to standard procedures. The results show that ROP aqueous extract contains significant amounts of phenolics, flavonoids, and tannins, which exhibit in vitro DPPH free-radical scavenging activity. Based on an in vivo study, ROP reduced blood glucose levels in streptozotocin-induced diabetic animals (p < 0.05). Dietary supplementation with ROP in diabetic rats significantly (p < 0.05) lowered ALT, AST, bilirubin, creatinine, total triglyceride (TG), total cholesterol (TC), and low-density lipoprotein (LDL) levels while increasing high-density lipoproteins (HDLs) when compared with the diabetic control group. Our findings demonstrate that a diet supplemented with R. officinalis leaf powder exhibits an antidiabetic potential with improved health outcomes, as demonstrated by the improved lipid and liver profile enzymes in our animal model.
The Influence of Gender and Age on the Open-Mindedness of University Students
Authors: Caballero-García Presentación Ángeles , Sánchez Ruiz Sara
Published: January 2024

Open-mindedness (OM) is one of the select groups of 21st-century soft skills that are lacking in the university curricula. Our aim was to analyse the OM level of our university students and study the influence of gender and age on OM. To do so, we used an ex post facto experimental design, a snowball sampling technique, an OM questionnaire administered to 493 students and statistical techniques of data mining and multiple linear regression. The results show medium–low levels of OM and higher scores in those below 49 years of age and female gender. The variable that most influenced the variability of OM was age (82%), compared to gender (18%). The practical implications of these results aim to promote a more inclusive, active and higher-quality university education that integrates OM, together with other competencies, to make our students more competitive academically and favour their entry into the labour market.
Exploring Style-Robust Scene Text Detection via Style-Aware Learning
Authors: Cai Yuanqiang , Zhou Fenfen , Yin Ronghui
Published: January 2024

Although current scene text detectors achieve remarkable accuracy across different and diverse styles of datasets by fine-tuning models multiple times, these approaches are time-consuming and hinder model generalization. As such, exploring a training strategy that only requires training once on all datasets is a promising solution. However, the text-style mismatch poses challenges to accuracy in such an approach. To mitigate these issues, we propose a style-aware learning network (SLNText) for style-robust text detection in the wild. This includes a style-aware head to distinguish the text styles of images and a dynamic selection head to realize the detection of images with different text styles. SLNText is only trained once, achieving superior performance by automatically learning from multiple text styles and overcoming the style mismatch issue inherent in one-size-fits-all approaches. By using only one set of network parameters, our method significantly reduces the training consumption while maintaining a satisfactory performance on several styles of datasets. Our extensive experiments demonstrate that SLNText achieves satisfactory performance in several styles of datasets, showcasing its effectiveness and efficiency as a promising solution to style-robust scene text detection.
A Low-Cost Test Platform for Performance Analysis of Phasor Measurement Units
Authors: Kunac Antonijo , Petrović Goran , Despalatović Marin , Jurčević Marko
Published: January 2024

In this paper, a customizable low-cost voltage waveform generator based on a real-time desktop PC and embedded data acquisition card synchronized with Coordinated Universal Time (UTC) is presented. A software approach to phase-locked loop synchronization with an external Global Positioning System (GPS) pulse signal is utilized to achieve a time uncertainty of ±1μs. This avoids expensive hardware modules for synchronization and timing purposes, which are commonly presented in literature. Besides the application for controlling the test platform, our own phasor data concentrator (PDC) application is running concurrently on the host PC. The latter is used for collecting and comparing the syncrophasor data from the test platform against the syncrophasor data measured by phasor measurement units (PMUs) under the test. The paper describes all procedures for generating reference test signals. Numerous case studies were performed, and experimental results for steady-state compliance as well as frequency ramp and phase modulation tests for dynamic compliance are presented in detail. All tests confirm that customizable test platform meets the requirements of IEEE/IEC standards. Compared to other calibrators, the cost as well as the specifications and point-by-point concept of data processing makes the described test platform suitable for performance analysis of PMU algorithms implemented on various development boards.
Learning the Frequency Domain Aliasing for Real-World Super-Resolution
Authors: Hao Yukun , Yu Feihong
Published: January 2024

Most real-world super-resolution methods require synthetic image pairs for training. However, the frequency domain gap between synthetic images and real-world images leads to artifacts and blurred reconstructions. This work points out that the main reason for the frequency domain gap is that aliasing exists in real-world images, but the degradation model used to generate synthetic images ignores the impact of aliasing on images. Therefore, a method is proposed in this work to assess aliasing in images undergoing unknown degradation by measuring the distance to their alias-free counterparts. Leveraging this assessment, a domain-translation framework is introduced to learn degradation from high-resolution to low-resolution images. The proposed framework employs a frequency-domain branch and loss function to generate synthetic images with aliasing features. Experiments validate that the proposed domain-translation framework enhances the visual quality and quantitative results compared to existing super-resolution models across diverse real-world image benchmarks. In summary, this work offers a practical solution to the real-world super-resolution problem by minimizing the frequency domain gap between synthetic and real-world images.
Frequency Modulation Scheme for CCM Boost PFC Converter to Improve THD in Light-Load Condition
Authors: Han Jung-Kyu
Published: January 2024

This study proposes a novel frequency modulation scheme for a continuous conduction mode (CCM) boost power factor correction (PFC) converter. The aim is to improve the total harmonic distortion (THD) under light-load conditions. Boost converters are widely utilized with CCM control for the PFC stage owing to their ability to achieve high efficiency with minimal components. In addition, they have a high power factor (PF) and low THD. However, despite being designed for CCM operation, the boost PFC converter transitions into discontinuous conduction mode (DCM) as the output load decreases. This mode, known as mixed conduction mode, degrades the PF and THD of the PFC converter. To address these issues, we propose a novel frequency modulation scheme. The CCM boost PFC converter adopts frequency variation to reduce the DCM region. To validate the feasibility of the proposed concept, a prototype with a 60 Hz/230 Vac input and 850 W/380 V output was utilized. Consequently, the boost PFC converter attains a high PF and low THD with simplified circuits.
Experimental Study of Evaporation Characteristics of Acoustically Levitated Fuel Droplets at High Temperatures
Authors: Pang Bin , Yang Guangcan , Liu Xiaoxin , Huang Yu , Li Wanli , He Yongqing , Shi Zhongyuan , Yang Zhaochu , Dong Tao
Published: January 2024

Examining fuel droplet evaporation is crucial for enhancing fuel engine efficiency, conserving energy, and reducing emissions. This study utilizes experimental methods involving ultrasonic standing wave levitation and high-speed cameras to investigate the impact of temperatures and droplet properties, including initial diameter and composition, on the evaporation process. The evaporation behaviors of fuel droplets, like hexadecane and diesel, are documented across a temperature spectrum spanning 150 °C to 550 °C, with an initial droplet equivalent diameter ranging from 0.10 to 0.30 mm. The evaporation rate positively correlates with temperature and may vary by 15% to 71% between hexadecane and diesel droplets.
Exploring the User Adoption Mechanism of Green Transportation Services in the Context of the Electricity–Carbon Market Synergy
Authors: Pan Dong , Wang Bao , Li Jun , Wu Fei
Published: January 2024

Promoting green transportation development in the context of electric–carbon market synergy can help promote sustainable transport and tackle climate change. The sharing economy has given rise to innovative and successful business models in recent years. To occupy current and potential markets, many enterprises that participate in sharing economy activities have engaged in a fiercely competitive environment. It is an important way for enterprises to generate profits and improve competitiveness by encouraging consumers’ continuous consumption or stimulating repurchase intentions. This study investigates the effects of consumer satisfaction on consumer repurchase intention (CRI) and how such effects are moderated by the consumer’s risk perception and sustainability awareness in the case of ride-sharing services, which are viewed as a mode of green transportation service. The results of a survey of 358 Chinese consumers who have used ride-sharing services suggest that transaction-based and experience-based satisfaction have positive and significant effects on the CRI of ride-sharing services. Moreover, the results indicate that consumer risk perception negatively moderates the relationships between satisfaction and CRI, while consumer sustainability awareness plays different roles depending on the type of satisfaction (transaction-based versus experience-based). Finally, implications and suggestions for future studies are discussed.
Improving Thermal Energy Storage in Solar Collectors: A Study of Aluminum Oxide Nanoparticles and Flow Rate Optimization
Authors: Hamdan Mohammad , Abdelhafez Eman , Ajib Salman , Sukkariyh Mustafa
Published: January 2024

Solar thermal energy storage improves the practicality and efficiency of solar systems for space heating by addressing the intermittent nature of solar radiation, leading to enhanced energy utilization, cost reduction, and a more sustainable and environmentally friendly approach to meeting heating needs in residential, commercial, and industrial settings. In this study, an indoor experimental setup was employed to investigate the impact of a water-based Al2O3 nanofluid on the storage capacity of a flat plate solar collector under varying flow rates of the heat transfer fluid. The nanofluid, introduced at specific concentrations, was incorporated into a water-contained storage tank through which the hot heat transfer fluid circulated within a heat exchanger. This process resulted in the storage of thermal energy for future applications. The research identified that the optimal flow rate of the heat transfer fluid, corresponding to the maximum storage temperature, was 15 L per hour, and the ideal nanofluid concentration, associated with the maximum specific heat capacity of the storage medium, was 0.6%. Furthermore, the introduction of nanoparticles into the storage tank led to a significant increase in the specific heat of the water, reaching a maximum of 19% from 4.18 to 5.65 kJ/(kg·°C).
Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection
Authors: Bustamante-Mesa Santiago , Gonzalez-Sanchez Jorge W. , Saldarriaga-Zuluaga Sergio D. , López-Lezama Jesús M. , Muñoz-Galeano Nicolás
Published: January 2024

Under-frequency load shedding (UFLS) schemes are the latest safety measures applied for safeguarding the integrity of the grid against abrupt frequency imbalances. The overall inertia of electrical power systems is expected to decrease with an increased penetration of renewable energy as well as elements connected through power electronic interfaces. However, voltage source converter-based high voltage direct current (VSC-HVDC) links can provide virtual inertia through a control loop that allows for a reaction to occur at certain frequency fluctuations. This paper evaluates a UFLS scheme that considers the injection of virtual inertia through a VSC-HVDC link. A genetic algorithm (GA) is used to determine the location of the UFLS relays, the activation threshold of each stage, the delay time and the percentage of load shedding at each stage. It was found that the virtual inertia causes the nadir to delay and sometimes reach a greater depth. Furthermore, the implemented GA approximates the frequency response to the limits set with the constraints, reducing the load shedding but achieving a steeper nadir and a lower steady-state frequency level than traditional UFLS. The simulations were performed using the IEEE 39-bus test system.
Investigating the Role of Byproduct Oxygen in UK-Based Future Scenario Models for Green Hydrogen Electrolysis
Authors: Campbell-Stanway Cameron , Becerra Victor , Prabhu Shanker , Bull James
Published: January 2024

Water electrolysis for hydrogen production with renewable electricity is regularly studied as an option for decarbonised future energy scenarios. The inclusion of byproduct electrolytic oxygen capture and sale is of interest for parallel decarbonisation efforts elsewhere in the industry and could contribute to reducing green hydrogen costs. A deterministic hydrogen electrolysis system model is constructed to compare oxygen inclusion/exclusion scenarios. This uses wind and solar-PV electricity generation timeseries, a power-dependent electrolysis model to determine the energy efficiency of gas yield, and power allocation for gas post-processing energy within each hourly timestep. This maintains a fully renewable (and therefore low/zero carbon) electricity source for electrolysis and gas post-processing. The model is validated (excluding oxygen) against an existing low-cost GW-scale solar-hydrogen production scenario and an existing hydrogen production costs study with offshore wind generation at the multi-MW scale. For both comparisons, oxygen inclusion is then evaluated to demonstrate both the benefits and drawbacks of capture and utilisation, for different scenario conditions, and high parameter sensitivity can be seen regarding the price of renewable electricity. This work subsequently proposes that the option for the potential utilisation of byproduct oxygen should be included in future research to exemplify otherwise missed benefits.
Heat Transfer Mechanisms and Contributions of Wearable Thermoelectrics to Personal Thermal Management
Authors: Enescu Diana
Published: January 2024

Thermoelectricity can assist in creating comfortable thermal environments through wearable solutions and local applications that keep the temperature comfortable around individuals. In the analysis of an indoor environment, thermal comfort depends on the global characteristics of the indoor volume and on the local thermal environment where the individuals develop their activity. This paper addresses the heat transfer mechanisms that refer to individuals, which operate in their working ambient when wearable thermoelectric solutions are used for enhancing heating or cooling within the local environment. After recalling the characteristics of the thermoelectric generators and illustrating the heat transfer mechanisms between the human body and the environment, the interactions between wearable thermoelectric generators and the human skin are discussed, considering the analytical representations of the thermal phenomena. The wearable solutions with thermoelectric generators for personal thermal management are then categorized by considering active and passive thermal management methods, natural and assisted heat exchange, autonomous and nonautonomous devices, and direct or indirect contact with the human body.
A Fast Dynamic Simulation Method of an Active Distribution Network with Distributed Generations Based on Decomposition and Coordination
Authors: Liu Keyan , Ye Xueshun , Kang Tianyuan , Li Zhao , Jia Dongli
Published: January 2024

With the penetration of distributed resources into power distribution networks, power distribution networks are transforming into active distribution networks with a high proportion of distributed generations and power electronic equipment. Efficient modeling and simulation methods are essential to perform dynamic response analysis. In order to satisfy the fast/steady/slow multiple time-scale simulation requirements of active distribution networks, a fast/medium/slow time partition model and a network decoupling method for short line characteristic lines is proposed in this paper. Through the decomposition coordination simulation method, the network is decomposed into multiple regions that can be simulated in parallel. Based on the interconnection of fiber optic network cards, a multi-rate parallel simulation and synchronization strategy is proposed, which significantly improves the simulation speed of active distribution networks while ensuring simulation accuracy. The numerical experiments have been conducted based on a modified IEEE 33-bus and a PG&E 69-bus, and simulation results show the feasibility of the proposed method. The verification results of the example show that using adaptive variable-step-size multi-rate parallel simulation technology can increase the subnet computation-time balance rate and simulation acceleration ratio to 119.90% and 121.31% in the same rate-parallel mode.