bluuebunny/crossref_metadata_2025 huggingface dataset:
Data-Driven Dynamic Security Partition Assessment of Power Systems Based on Symmetric Electrical Distance Matrix and Chebyshev Distance
Authors: Qi Hang , Su Ruiyang , Sun Runjia , Yan Jiongcheng
Published: October 2024

A rapid dynamic security assessment (DSA) is crucial for online preventive and restoration decision-making. The deep learning-based DSA models have high efficiency and accuracy. However, the complex model structure and high training cost make them hard to update quickly. This paper proposes a dynamic security partition assessment method, aiming to develop accurate and incrementally updated DSA models with simple structures. Firstly, the power grid is self-adaptively partitioned into several local regions based on the mean shift algorithm. The input of the mean shift algorithm is a symmetric electrical distance matrix, and the distance metric is the Chebyshev distance. Secondly, high-level features of operating conditions are extracted based on the stacked denoising autoencoder. The symmetric electrical distance matrix is modified to represent fault locations in local regions. Finally, DSA models are constructed for fault locations in each region based on the radial basis function neural network (RBFNN) and Chebyshev distance. An online incremental updating strategy is designed to enhance the model adaptability. With the simulation software PSS/E 33.4.0, the proposed dynamic security partition assessment method is verified in a simplified provincial system and a large-scale practical system in China. Test results demonstrate that the Chebyshev distance can improve the partition quality of the mean shift algorithm by approximately 50%. The RBFNN-based partition assessment model achieves an accuracy of 98.96%, which is higher than the unified assessment with complex models. The proposed incremental updating strategy achieves an accuracy of over 98% and shortens the updating time to 30 s, which can meet the efficiency of online application.
Urban Emergency Evacuation Path Optimization Based on Uncertain Environments to Enhance Response for Symmetric and Asymmetric Evacuation Problems
Authors: Mao Jia , Zhou Yanzhi , Zhou Yu , Wang Xi
Published: October 2024

Background: Serious secondary disasters caused by extreme natural weather conditions occur frequently, making it essential to establish a scientific and efficient modern emergency management system to maximize life-saving efforts. Methods: This study focuses on the uncertain environment of urban road networks and employs fuzzy theory to construct a 0–1 integer programming model for emergency evacuation paths that minimizes the average expected travel time. Results: We enhanced the neighborhood search strategy of the traditional ACO_time by incorporating the 2-opt and 3-opt perturbation mechanisms from the SA algorithm. Additionally, we utilized improved ant-volume and ant-perimeter models, along with their combinations, in the pheromone-updating mechanism of the basic ACO. The heuristic principles of the A* algorithm were integrated, introducing the joint influence of path and time into the heuristic function of the ACO algorithm. Conclusions: The IACO3 algorithm was tested on the Sioux Falls network and the Berlin Heisenheimer Center network. The computation time of the improved IACO3 algorithm was reduced by up to 20% compared to the original IACO3 algorithm in relation to the SA algorithm, with only a 4–5% increase in computation time compared to the ACO_time algorithm, which translates to an increase of merely 4–5 s. This demonstrates the superior solution efficiency of the IACO3 algorithm.
Modeling Pollutant Diffusion in the Ground Using Conformable Fractional Derivative in Spherical Coordinates with Complete Symmetry
Authors: Kim Mintae , Mert Coskun Oya , Ordu Seyma , Mutlu Resat
Published: October 2024

The conformal fractional derivative (CFD) has become a hot research topic since it has a physical interpretation and is easier to grasp and apply to problems compared with other fractional derivatives. Its application to heat transfer, diffusion, diffusion-advection, and wave propagation problems can be found in the literature. Fractional diffusion equations have received great attention recently due to their applicability in physical, chemical, and biological processes and engineering. The diffusion of the pollutants within the ground, which is an important environmental problem, can be modeled with a diffusion equation. Diffusion in some porous materials or soil can be modeled more accurately with fractional derivatives or the conformal fractional derivative. In this study, the diffusion problem of a spilled pollutant leaking into the ground modeled with the conformal fractional time derivative in spherical coordinates has been solved analytically using the Fourier series for a constant mass flow rate and complete symmetry under the assumptions of homogeneous and isotropic soil, constant soil temperature, and constant permeability. The solutions have been simulated spatially and in time. A parametric analysis of the problem has been performed for several values of the CFD order. The simulation results are interpreted. It has also been suggested how to find the parameters of the soil to see whether the CFD can be used to model the soil or not. The approach described here can also be used for modeling pollution problems involving different boundary conditions.
Solving the Dual Generalized Commutative Quaternion Matrix Equation AXB = C
Authors: Shi Lei , Wang Qing-Wen , Xie Lv-Ming , Zhang Xiao-Feng
Published: October 2024

Dual generalized commutative quaternions have broad application prospects in many fields. Additionally, the matrix equation AXB=C has important applications in mathematics and engineering, especially in control systems, economics, computer science, and other disciplines. However, research on the matrix equation AXB=C over the dual generalized commutative quaternions remains relatively insufficient. In this paper, we derive the necessary and sufficient conditions for the solvability of the dual generalized commutative quaternion matrix equation AXB=C. Furthermore, we provide the general solution expression for this matrix equation, when it is solvable. Finally, a numerical algorithm and an example are provided to confirm the reliability of the main conclusions.
The Influencing Mechanism of Robustness of Emergency Medical Logistics: Mediating Role of Knowledge Integration
Authors: Zhang Jianhua , Cao Ziao , Zhou Xiaoqian , Liu Jinyan , Jia Hongyu
Published: October 2024

Drawing on the social capital theory, the research examines the impact of network size, network centrality, trust, and regulation on the knowledge integration and robustness of emergency medical logistics. Additionally, the research seeks to provide deeper insight into the link between the variables by studying how knowledge integration mediates the relationship between independent variables and the robustness of emergency medical logistics. The study utilized structural equation modeling to assess the underlying assumptions of the research model. A total of 465 valid questionnaires were collected from government departments, hospitals, social teams, and enterprises. The data processing and analysis were conducted using SPSS 23.0 and AMOS 24.0 software. The study’s outcome indicated that network size and network centrality have indirect effects on the robustness of emergency medical logistics through the intermediate variable of knowledge integration, but neither has a direct effect. Moreover, knowledge integration has a significant positive impact on the robustness of emergency medical logistics. Both trust and regulation have positive effects on the robustness of emergency medical logistics, and they also have positive effects on the robustness of emergency medical logistics through knowledge integration. This study is the inaugural exploration of the correlation between knowledge integration and the robustness of emergency medical logistics. It adds to the literature by providing evidence that knowledge integration is an essential emergency organization’s aide in promoting the robustness of emergency medical logistics. The findings of this study establish a strong theoretical foundation and practical significance for ensuring and improving the level of effectiveness in emergency medical logistics management.
The Impact of Artificial Intelligence Marketing on E-Commerce Sales
Authors: Madanchian Mitra
Published: October 2024

This review explores the influence of AI marketing on e-commerce sales, examining how AI-driven strategies affect key metrics such as customer acquisition and conversion rates. Given the growing importance of AI in online retail, this paper employs a critical review methodology, analyzing 50 documents from the Scopus database. The analysis reveals that AI tools like chatbots, personalization engines, and predictive analytics significantly enhance e-commerce performance. The study provides practical and theoretical contributions, offering recommendations for businesses and suggesting future research directions.
From Reactive to Proactive Infrastructure Maintenance: Remote Sensing Data and Practical Resilience in the Management of Leaky Pipes
Authors: Gahrn-Andersen Rasmus , Festila Maria
Published: October 2024

The introduction of remote sensing technologies, AI and big data analytics in the utility sector is warranted by the need to provide critical services with the least disruption to customers, but also to enable preventive maintenance, extend the life cycle of infrastructure components and reduce grid loss—or overall, to exhibit ‘durability’ and ‘resilience’ when faced with the certainty of breakage and decay. In this paper, we first explore the concept of ‘resilience’ and the nature of practice from a performativist perspective in order to set the scene for discussing the impact of ‘datafication’ on maintenance practices and infrastructure durability. We then describe an instance of introducing remote sensing technologies in district heating network surveillance and leak detection: drone-operated thermographic cameras and underground wire sensors. Based on insights from this case study, we discuss the specificity of data-driven infrastructure maintenance practices, and what it means to exhibit practical resilience in relation to how such practices unfold, interrelate and evolve over time. We reflect on how the use of remote sensing technologies and data analytics (1) potentially changes district heating workers’ epistemic worlds (i.e., how knowledge emerges, is negotiated and ordered in practice) and (2) provides opportunities for ‘messy’ pipe repair work to tacitly adopt proactive and preventive logics to meet continuously evolving organizational and societal needs.
Improvement of Sound-Absorbing Wool Material by Laminating Permeable Nonwoven Fabric Sheet and Nonpermeable Membrane
Authors: Sakamoto Shuichi , Sato Kodai , Muroi Gaku
Published: October 2024

Thin sound-absorbing materials are particularly desired in space-constrained applications, such as in the automotive industry. In this study, we theoretically analyzed the structure of relatively thin glass wool or polyester wool laminated with a nonpermeable polyethylene membrane and a permeable nonwoven fabric sheet. We also measured and compared the sound-absorption coefficients of these samples between experimental and theoretical values. The sound-absorption coefficient was derived using the transfer matrix method. The Rayleigh model was applied to describe the acoustic behavior of glass wool and nonwoven sheet, while the Miki model was used for polyester wool. Mathematical formulas were employed to model an air layer without damping and a vibrating membrane. These acoustic components were integrated into a transfer matrix framework to calculate the sound-absorption coefficient. The sound-absorption coefficients of glass wool and polyester wool were progressively enhanced by sequentially adding suitable nonwoven fabric and PE membranes. A sample approximately 10 mm thick, featuring permeable and nonpermeable membranes as outer layers of porous sound-absorbing material, achieved a sound-absorption coefficient equivalent to that of a sample occupying 20 mm thickness (10 mm of porous sound-absorbing material with a 10 mm back air layer).
Introducing Digitized Cultural Heritage to Wider Audiences by Employing Virtual and Augmented Reality Experiences: The Case of the v-Corfu Project
Authors: Komianos Vasileios , Tsipis Athanasios , Kontopanagou Katerina
Published: October 2024

In recent years, cultural projects utilizing digital applications and immersive technologies (VR, AR, MR) have grown significantly, enhancing cultural heritage experiences. Research emphasizes the importance of usability, user experience, and accessibility, yet holistic approaches remain underexplored and many projects fail to reach their audience. This article aims to bridge this gap by presenting a complete workflow including systematic requirements analysis, design guidelines, and development solutions based on knowledge extracted from previous relevant projects. The article focuses on virtual museums covering key challenges including compatibility, accessibility, usability, navigation, interaction, computational performance and graphics quality, and provides a design schema for integrating virtual museums into such projects. Following this approach, a number of applications are presented. Their performance with respect to the aforementioned key challenges is evaluated. Users are invited to assess them, providing positive results. To assess the virtual museum’s ability to attract a broader audience beyond the usual target group, a group of underserved minorities are also invited to use and evaluate it, generating encouraging outcomes. Concluding, results show that the presented workflow succeeds in yielding high-quality applications for cultural heritage communication and attraction of wider audiences, and outlines directions for further improvements in digitized heritage applications.
Primary Sequence and Three-Dimensional Structural Comparison between Malanin and Ricin, a Type II Ribosome-Inactivating Protein
Authors: Yuan Yan , Wu Shuxiao , Day Philip J. R.
Published: October 2024

Malanin is a new type II ribosome-inactivating protein (RIP) purified from Malania oleifera, a rare, endangered tree is only found in the southwest of Guangxi Province and the southeast of Yunnan Province, China. The gene coding sequence of malanin was found from the cDNA library of M. oleifera seeds by employing the ten N-terminal amino acid sequences of malanin, DYPKLTFTTS for chain-A and DETXTDEEFN (X was commonly C) for chain-B. The results showed a 65% amino acid sequence homology between malanin and ricin by DNAMAN 9.0 software, the active sites of the two proteins were consistent, and the four disulfide bonds were in the same positions. The primary sequence and three-dimensional structures of malanin and ricin are likely to be very similar. Our studies suggest that the mechanism of action of malanin is expected to be analogous to ricin, indicating that it is a member of the type II ribosome-inactivating proteins. This result lays the foundation for further study of the anti-tumor activities of malanin, and for the application of malanin as a therapeutic agent against cancers.
Field-Applicable Loop-Mediated Isothermal Amplification for the Detection of Seven Common Human Papillomavirus Subtypes
Authors: Li Hongyi , Tan He , Lv Xiaona , Han Zhiqiang , Wang Yuxin , Gao Shijue , Zhang Ruiqin , Shen Xinxin , Ma Xuejun , Tie Yanqing
Published: October 2024

Persistent HPV infection is a major risk factor for the subsequent development of cervical cancer. LAMP is simple and suitable for field detection in the resource-limited settings. In this study, hydroxy naphthol blue (HNB)-based visual LAMP and evagreen-based fluorescent LAMP coupled with a microfluidic chip (LAMP-chip) were established for the field detection of seven subtypes of HPV. The analytical sensitivity was 19–233 copies/reaction. The overall clinical sensitivity was 97.35% for visual LAMP and 98.23% for LAMP-chip. Both LAMP assays exhibited 100% specificity and were completed in less than 50 min. Additionally, both assays did not require complicated nucleic acid extraction and purification steps. A complete quality control monitoring system (including internal control, positive quality control and negative control) in the LAMP assays further ensured the credibility of the results. Our findings demonstrated that the proposed LAMP assays have the potential to be applied in the testing of common HPV DNA in field investigations (visual LAMP) or within communities and primary health centers (LAMP-chip).
Galaxy Classification Using EWGC
Authors: Nie Yunyan , Pan Zhiren , Zhou Jianwei , Qiu Bo , Luo A-Li , Luo Chong , Luan Xiaodong
Published: October 2024

The Enhanced Wide-field Galaxy Classification Network (EWGC) is a novel architecture designed to classify spiral and elliptical galaxies using Wide-field Infrared Survey Explorer (WISE) images. The EWGC achieves an impressive classification accuracy of 90.02%, significantly outperforming the previously developed WGC network and underscoring its superior performance in galaxy morphology classification. Remarkably, the network demonstrates a consistent accuracy of 90.02% when processing both multi-target and single-target images. Such robustness indicates the EWGC’s versatility and potential for various applications in galaxy classification tasks.
Replication Characteristics of African Swine Fever Virus (ASFV) Genotype I E70 and ASFV Genotype II Belgium 2018/1 in Perivenous Macrophages Using Established Vein Explant Model
Authors: Han Shaojie , Oh Dayoung , Balmelle Nadège , Cay Ann Brigitte , Ren Xiaolei , Droesbeke Brecht , Tignon Marylène , Nauwynck Hans
Published: October 2024

African Swine Fever Virus (ASFV), resulting in strain-dependent vascular pathology, leading to hemorrhagic fever, is an important pathogen in swine. The pathogenesis of ASFV is determined by the array and spatial distribution of susceptible cells within the host. In this study, the replication characteristics of ASFV genotype I E70 (G1-E70) and ASFV genotype II Belgium 2018/1 (G2-B18) in the environment of small veins were investigated in an established vein explant model. Immunofluorescence staining analysis revealed that perivenous macrophages (CD163+ cells) were widely distributed in the explant, with most of them (approximately 2–10 cells/0.03 mm2) being present close to the vein (within a radius of 0–348 µm). Upon inoculation with G1-E70 and G2-B18, we observed an increase in the quantity of cells testing positive for viral antigens over time. G1-E70 replicated more efficiently than G2-B18 in the vein explants (7.6-fold for the ear explant at 72 hpi). The majority of ASFV+ cells were CD163+, indicating that macrophages are the primary target cells. Additional identification of cells infected with ASFV revealed the presence of vimentin+, CD14+, and VWF+ cells, demonstrating the cellular diversity and complexity associated with ASFV infection. By the use of this new vein explant model, the susceptibility of vascular and perivascular cells to an ASFV infection was identified. With this model, it will be possible now to conduct more functional analyses to get better insights into the pathogenesis of ASFV-induced hemorrhages.
Strain- and Subtype-Specific Replication of Genotype 3 Hepatitis E Viruses in Mongolian Gerbils
Authors: Li Tiancheng , Sakai Yusuke , Ami Yasushi , Suzaki Yuriko , Isogawa Masanori
Published: October 2024

Since Mongolian gerbils are broadly susceptible to hepatitis E virus (HEV), including genotypes 1, 4, 5, and 8 (HEV-1, HEV-5, HEV-5, and HEV-8) and rat HEV, they are a useful small animal model for HEV. However, we have observed that the subtypes HEV-3k and HEV-3ra in genotype 3 HEV (HEV-3) were not infected efficiently in the gerbils. A small-animal model for HEV-3 is also needed since HEV-3 is responsible for major zoonotic HEV infections. To investigate whether gerbils can be used as animal models for other subtypes of HEV-3, we injected gerbils with five HEV-3 subtypes (HEV-3b, -3e, -3f, -3k, and -3ra) and compared the infectivity of the subtypes. We detected viral RNA in the gerbils’ feces. High titers of anti-HEV IgG antibodies in serum were induced in all HEV-3b/ch-, HEV-3f-, and HEV-3e-injected gerbils. Especially, the HEV-3e-injected animals released high levels of viruses into their feces for an extended period. The virus replication was limited in the HEV-3b/wb-injected and HEV-3k-injected groups. Although viral RNA was detected in HEV-3ra-injected gerbils, the copy numbers in fecal specimens were low; no antibodies were detected in the sera. These results indicate that although HEV-3′s infectivity in gerbils depends on the subtype and strain, Mongolian gerbils have potential as a small-animal model for HEV-3. A further comparison of HEV-3e with different genotype strains (HEV-4i and HEV-5) and different genera (rat HEV) revealed different ALT elevations among the strains, and liver damage occurred in HEV-4i- and HEV-5-infected but not HEV-3e- or rat HEV-infected gerbils, demonstrating variable pathogenicity across HEVs from different genera and genotypes in Mongolian gerbils. HEV-4i- and HEV-5-infected Mongolian gerbils might be candidate animal models to examine HEV’s pathogenicity.
Comparison of Predictive Factors of Flu Vaccine Uptake Pre- and Post-COVID-19 Using the NIS-Teen Survey
Authors: Skyles Ty J. , Stevens Harlan P. , Davis Spencer C. , Obray Acelan M. , Miner Dashiell S. , East Matthew J. , Davis Tyler , Hoelzer Haley , Piccolo Stephen R. , Jensen Jamie L. , Poole Brian D.
Published: October 2024

Background: Seasonal influenza vaccination rates are very low among teenagers. Objectives: We used publicly available data from the NIS-Teen annual national immunization survey to explore factors that influence the likelihood of a teen receiving their seasonal flu shot. Methods: Traditional stepwise multivariable regression was used in tandem with machine learning to determine the predictive factors in teen vaccine uptake. Results and Conclusions: Age was the largest predictor, with older teens being much less likely to be vaccinated than younger teens (97.48% compared to 41.71%, p < 0.0001). Provider participation in government programs such as Vaccines for Children and the state vaccine registry positively impacts vaccine uptake (p < 0.0001). Identifying as non-Hispanic Black was a small, negative predictor of teen vaccine uptake (78.18% unvaccinated compared to 73.78% of White teens, p < 0.0001). The state quartile for COVID-19 vaccine uptake also strongly predicted flu vaccine uptake, with the upper quartile of state COVID-19 vaccine uptake being significantly more likely to also get vaccinated for influenza (76.96%, 74.94%, 74.55%, and 72.97%, p < 0.0001). Other significant factors are the number of providers, education of the mother, poverty status, and having a mixed provider facility type. Additionally, the multivariable regression analysis revealed little difference in the predictive factors of vaccine uptake between pre- and post-pandemic datasets.
Does the Vaccination against Tick-Borne Encephalitis Offer Good Value for Money for Incidence Rates below the WHO Threshold for Endemicity? A Case Study for Germany
Authors: Müller Malina , Lintener Hannah , Henkel Vivien , Pilz Andreas , Halsby Kate , Malerczyk Claudius , Madhava Harish , Moïsi Jennifer C. , Yu Holly , Schley Katharina
Published: October 2024

Tick-borne encephalitis (TBE) is a viral infection affecting the central nervous system (CNS) with potential long-term consequences including neurological sequelae. Vaccination is critical to reduce TBE morbidity and mortality, as no antiviral treatment is available. The World Health Organization (WHO) defines areas with an incidence of ≥5 cases/100,000 PPY as highly endemic and recommends that vaccination is offered to all individuals in these areas. However, access to TBE vaccination depends on recommendations and funding by national or subnational decision-makers. We assessed if TBE vaccination could offer good value for money at incidences below this threshold. Methods: A closed-cohort Markov model was developed to estimate the cost-effectiveness of TBE vaccination. We compared primary vaccination applied to the whole population (aged above 1 year) and to a subpopulation aged between 60 and 85 years to a scenario without vaccination. Since TBE incidence is often underestimated, we included under-ascertained TBE cases and non-CNS TBE infections. Germany was used as a case study due to the availability of detailed incidence data. Results: Our incidence threshold analysis showed that TBE vaccination offers good value for money well below the WHO threshold in most of the analyzed scenarios. Conclusions: Our results support a recommendation for TBE vaccination even in settings with low numbers of reported cases, especially for older patients. Furthermore, this analysis identified major research gaps regarding the costs, utilities, and clinical progression of TBE.
The Recent Research Progress of the Tumor mRNA Vaccine
Authors: Zhao Hao , Li Miying , Zhou Jiaren , Hu Lidan , Lu Shaohong , Li Pan
Published: October 2024

Tumors have long posed a significant threat to human life and health, and the messenger ribonucleic acid (mRNA) vaccine is seen as an attractive approach for cancer immunotherapy due to its developmental simplicity, rapid manufacture, and increased immune safety and efficiency. In this review, we have summarized details of the developmental history of mRNA vaccines, discussed the basic molecular structure and the effect on the stable and translation level of mRNA, analyzed the underlying immune efficiency and mechanisms on tumors, and assessed the current status of clinical research. We explored the treatment and application prospects of mRNA vaccines, aiming to provide perspectives on the future of mRNA tumor vaccines for ongoing clinical research.
Groundwater Potential Zone Delineation through Analytical Hierarchy Process: Diyala River Basin, Iraq
Authors: Mohammed Ruqayah , Scholz Miklas
Published: October 2024

Groundwater recharge zone identification is vital for managing water resources, particularly in semi-arid and dry climates. Accurate and quantifiable assessment is necessary for the sustainable management of groundwater resources, and it is possible to carry this method out using modern techniques and technical standards. To identify likely groundwater locations in the Diyala River Catchment, Iraq, which serves as an example study basin, the current research examines a new methodology that employs a geographic information system, and an Analytical Hierarchy Process connected with remote sensing data. The technique of ArcGIS was employed to generate spatially distributed thematic layers of rainfall, lithology, slope, drainage density, land use/land cover, relief and soil. The raster data from these layers were then converted and categorized. The weights assigned to thematic strata depended on their significance relative to groundwater occurrence. A pairwise judgement matrix for the Analytical Hierarchy Process was used, with the categorized ranking, to assess the standardized weights of the layers under consideration. The layers for the formation of groundwater zones have then been placed using the overlay-weighted summation approach. Three regions, which are classed as excellent, good and moderate, have been identified on the resulting groundwater potential zones map, representing roughly 29, 69 and 2% of the basin’s total area, respectively. The study’s conclusions indicate that, in such a climate, the adopted strategy would produce favourable results to promote the organizing of opinions and the sustainable use of groundwater resources.
Sustainable Wastewater Treatment Strategies in Effective Abatement of Emerging Pollutants
Authors: Ahmad Hafiz Waqas , Bibi Hafiza Aiman , Chandrasekaran Murugesan , Ahmad Sajjad , Kyriakopoulos Grigorios L.
Published: October 2024

The fundamental existence of any living organism necessitates the availability of pure and safe water. The ever-increasing population has led to extensive industrialization and urbanization, which have subsequently escalated micropollutants and water contamination. The environmental impact on various life forms poses a dire need for research in effective environmental management. Versatile technologies involving multiple approaches, including physiochemical and biological bioremediation strategies, draw insights from environmental biology. Metabolic annihilation mediated by microbes shows significant potential in the bioconversion of toxic micropollutants to tolerable limits. Environmentally friendly, cost-effective, and sustainable strategies are envisaged for efficient environmental protection. Phytoremediation technology, especially floating wetland treatments, facilitates micropollutant elimination, landscape management, ecosystem conservation, and aesthetic enhancement in diverse environments. The incorporation of nanomaterials in the bioremediation of toxic micropollutants augments novel and innovative strategies for water pollution abatement. This paper offers a novel strategy that combines nanomaterials to improve micropollutant degradation with bioremediation techniques, particularly the creative application of phytoremediation technologies like floating wetlands. Combining these techniques offers a novel viewpoint on long-term, affordable approaches to reducing water pollution. Additionally, the review proposes a forward-looking strategic framework that addresses the accumulation and refractory nature of micropollutants, which has not been thoroughly explored in previous literature.
Combining Activated Carbon Adsorption and CO2 Carbonation to Treat Fly Ash Washing Wastewater and Recover High-Purity Calcium Carbonate
Authors: Chen Weifang , Chen Yifan , Wang Yegui , Zhao Na
Published: October 2024

Fly ash washing wastewater was carbonated with carbon dioxide (CO2) to remove calcium (Ca) by forming a calcium carbonate (CaCO3) precipitate. An investigation of the factors affecting carbonation showed that Ca removal was highly dependent on the initial pH of the wastewater. The Ca removal was 10%, 61%, 91% and more than 99% at initial wastewater pH levels of 11.8, 12.0, 12.5 and 13.0, respectively. The optimal conditions for carbonation were initial pH of 13.0, carbonation time of 30 min and CO2 flow rate of 30 mL/min. The Ca concentration in the wastewater decreased to <40 mg/L, while 73 g of CaCO3 precipitate was produced per liter of wastewater. However, heavy metals, specifically Pb and Zn, co-precipitated during carbonation, which resulted in a CaCO3 product that contained as much as 0.61 wt% of Pb and 0.02 wt% of Zn. Activated carbon modified by a quaternary ammonium salt was used to selectively adsorb the Pb and Zn first. The Pb- and Zn-free water was then carbonated. By combining adsorption with carbonation, the Ca concentration in the treated wastewater was decreased to about 28 mg/L, while the Na, Cl and K were retained. The wastewater thus treated was ready for NaCl and KCl recovery. In addition, the precipitate had a Ca content of more than 38 wt% and almost no heavy metals. The average particle size of the precipitate was 47 μm, with a uniform cubic shape. The quality of the precipitate met the requirements for the industrial reuse of CaCO3. In summary, adsorption and carbonation combined were able to remove pollutants from wastewater while recovering useful resources.
The Degradation of Rhodamine B by an Electro-Fenton Reactor Constructed with Gas Diffusion Electrode and Heterogeneous CuFeO@C Particles
Authors: Li Shuo , Gu Siyang , Jia Xiaotong , Su Xin , Li Yifan , Zhang Yang , Du Yunmei , Ding Yuanhong
Published: October 2024

Compared with conventional Fenton processes, the electro-Fenton process consumes fewer chemicals and produces less sludge, as it can generate the required Fenton’s reagents in situ. In this work, an electro-Fenton reactor was constructed to treat synthetic rhodamine B (Rh B) wastewater, in which a gas diffusion electrode (GDE) was used as a cathode to produce H2O2, and heterogeneous CuFeO@C particles were used to generate Fe2+ in situ. The results indicated that the gas diffusion electrode made of elements N-S-B and r-graphene oxide (NSB-r-GO) composites produced more H2O2 than the one made from r-graphene oxide (r-GO), under the conditions of 0.1 mol ·L−1 Na2SO4 electrolyte, 10 mA·cm−2 current density, and 1.0 L·min−1 O2 flow rate, with the accumulated H2O2 production reaching 105.43 mg·L−1. Additionally, different iron morphologies, including octahedral Fe (II), octahedral Fe (III), and tetrahedral Fe (III), were found in the calcined CuFeO@C particles, approximately 1.0 mg·L−1 of iron ions dissolved in the electrolyte was detected, which worked simultaneously as conductive electrodes in a conceptual three-dimensional electrochemical reactor consisting of a gas diffusion electrode cathode, Ti/RuSn anode, and CuFeO@C particle electrodes. No external Fenton reagents were necessary.
Assessing Trade-Offs and Synergies in Ecosystem Services within the Tianshan Mountainous Region
Authors: Li Hui , Cui Shichao , Zhao Chengyi , Zhang Haidong
Published: October 2024

In managing ecosystem services (ESs), it is vital to understand and effectively regulate the trade-offs and synergies (ToSs) involved. This study investigates the Tianshan Mountains (TSMs), utilizing the InVEST (Integrated Valuation of ESs and Tradeoffs) model to evaluate ecosystem service changes from 2000 to 2020, while employing univariate linear regression to examine their spatiotemporal dynamics. Pearson correlation analysis was also conducted to assess how climatic variables (temperature and precipitation) and vegetation indicators (NDVI, normalized difference vegetation index) influence the overall ecosystem service benefits. The findings reveal notable spatial heterogeneity and dynamic shifts in ESs across the TSMs, with strong synergies observed between carbon storage (CS) and other services (such as habitat quality, HQ; soil conservation, SC; and water yield, WY), especially in areas experiencing increased vegetation. However, the connection between HQ and WY was comparatively weaker and occasionally exhibited negative correlations during specific periods, highlighting the intricate trade-offs among various services. The correlation analysis further showed that climate and vegetation changes significantly impact ecosystem service benefits, with declining precipitation and rising temperatures reducing these benefits, whereas higher NDVI was associated with improved service functions. Ultimately, this study emphasizes the necessity of recognizing and managing ToSs in ESs to promote sustainable regional ecosystem development.
Study of Flooding Behavior and Discharge from Karot Dam in the Event of a Possible Breach by Using the Hydrodynamic Model
Authors: Momburi Lilian Thomas , Li Changwen , Masami Frank N. M. , Ren Minglei , Otoo Isaac
Published: October 2024

This study utilizes the MIKE 11 hydrodynamic model developed by the Danish Hydraulic Institute to simulate flood behavior downstream of Karot Dam under multi-year in-flow conditions. The key parameters analyzed include breach characteristics, flood duration, water depth, flow velocity, discharge rate, and downstream distance. After dam failure, the peak discharge reaches 33,171 m3/s, exceeding the 10,000-year recurrence peak flow of 32,300 m3/s, with a breach duration of 2 h. The estimated peak discharge after simulation using empirical equations and comparative analyses showed maximum flood discharges of 28,187 m3/s, 28,922 m3/s, and 29,769 m3/s, with breach widths of 181 m, 256 m, and 331 m, respectively. The peak discharge predicted to reach the outlet with travel time ranging from 4 h 25 min to 4 h 40 min. Under multi-year average inflow conditions, Mangla Dam faces no risk of failure, with a maximum outflow of 12,097 m3/s and a spillway capacity of 30,147 m3/s. The model accurately predicted discharge values, with a strong correlation coefficient of R2 = 0.9653, indicating strong agreement between the actual water level data and predicted discharge. These insights are essential for developing effective emergency response strategies to mitigate the risks associated with dam failure.
Temporal Variability of Hydroclimatic Extremes: A Case Study of Vhembe, uMgungundlovu, and Lejweleputswa District Municipalities in South Africa
Authors: Botai Christina M. , de Wit Jaco P. , Botai Joel O.
Published: October 2024

The current study investigated hydroclimatic extremes in Vhembe, Lejweleputswa, and uMgungundlovu District Municipalities based on streamflow data from 21 river gauge stations distributed across the study site for the period spanning 1985–2023. Statistical metrics such as the annual mean and maximum streamflow, as well as trends in annual, maximum, seasonal, and high/low flow, were used to evaluate the historical features of streamflow in each of the three district municipalities. Moreover, the Standardized Streamflow Index (SSI) time series computed from streamflow observations at 3- and 6-month accumulation periods were used to assess hydroclimatic extremes, including drought episodes, proportion of wet/dry years and trends in SSI, drought duration (DD), and drought severity (DS). The results indicate that the three district municipalities have experienced localized and varying degrees of streamflow levels and drought conditions. The uMgungundlovu District Municipality in particular has experienced a significant decline in annual and seasonal streamflow as well as an increase in drought conditions during the 38-year period of analysis. This is supported by the negative trends observed in most of the assessed metrics (e.g., annual, maximum, seasonal, low/high flow, and SSI), whereas DD and DS showed positive trends in all the stations, suggesting an increase in prolonged duration and severity of drought. The Lejweleputswa District Municipality depicted positive trends in most of the assessed metrics, suggesting that streamflow increased, whereas drought decreased in the region over the 38-year period of study. Moreover, the Vhembe District Municipality experienced both negative and positive trends, suggesting localized variations in dry and wet conditions. The results presented in this study contribute towards drought monitoring and management efforts in support of policy- and decision-making that aim to uplift water resources management and planning at local and district municipality levels.
Simulation and Experimental Study on Heat Transfer Performance of Bionic Structure-Based Battery Liquid Cooling Plate
Authors: Wang Zhizhong , Liu Dinghong , Li Zhaoyang , Qi Xin , Wan Chaoyi
Published: October 2024

This study presents a bionic structure-based liquid cooling plate designed to address the heat generation characteristics of prismatic lithium-ion batteries. The size of the lithium-ion battery is 148 mm × 26 mm × 97 mm, the positive pole size is 20 mm × 20 mm × 3 mm, and the negative pole size is 22 mm × 20 mm × 3 mm. Experimental testing of the Li-ion battery’s heat generation model parameters, in conjunction with bionic structure and micro-channel features, has led to the development of this innovative cooling system. The traditional bionic liquid cooling plate’s structure is often singular; however, the flow path of the liquid cooling plate designed in this paper is based on the combination of the distribution of human blood vessel branches and the structure of insect wing veins. The external dimension of the liquid cooling plate is 152 mm × 100 mm × 6 mm (length × width × height). Utilizing numerical simulation and thermodynamic principles, we analyzed the heat transfer efficacy of the bionic liquid cooling module for power batteries. Specifically, we investigated the impact of varying coolant flow rates and the contact radius between flow channels on the thermal performance of the bionic battery modules. Our findings indicate that a liquid flow rate of 0.6 m/s achieves a stable maximum surface temperature and temperature differential across the bionic battery liquid cooling module, with a relatively low overall system power consumption, suggesting room for further enhancement of heat transfer performance. By augmenting the contact radius between flow channels, we observed an initial increase in the maximum surface temperature, temperature differential, and inlet–outlet pressure differential at a flow rate of 0.2 m/s. However, at flow rates equal to or exceeding 0.4 m/s, these parameters stabilized across different design Scenarios. Notably, the pump power consumption remained consistent across various scenarios and flow rates. This study’s outcomes offer valuable insights for the development of liquid-cooled battery thermal management systems that are energy-efficient and offer superior heat transfer capabilities.
Lateral-Stability-Oriented Path-Tracking Control Design for Four-Wheel Independent Drive Autonomous Vehicles with Tire Dynamic Characteristics under Extreme Conditions
Authors: Yu Zhencheng , Zhao Rongchen , Yuan Tengfei
Published: October 2024

This paper proposes a lateral-stability-oriented path-tracking controller for four-wheel independent drive (4WID) autonomous vehicles. The proposed controller aims to maintain vehicle stability under extreme conditions while minimizing lateral deviation. Firstly, a tiered control framework comprising upper-level and lower-level controllers is introduced. The upper-level controller is a lateral stability path-tracking controller that incorporates tire dynamic characteristics, developed using model predictive control (MPC) theory. This controller dynamically updates the tire lateral force constraints in real time to account for variations in tire dynamics under extreme conditions. Additionally, it enhances lateral stability and reduces path-tracking errors by applying additional yaw torque based on minimum tire utilization. The lower-level controllers execute the required steering angles and yaw moments through the appropriate component equipment and torque distribution. The joint simulation results from CarSim and MATLAB/Simulink show that, compared to the traditional MPC controller with unstable sideslip, this controller can maintain vehicle lateral stability under extreme conditions. Compared to the MPC controller, which only considers lateral force constraints, this controller can significantly reduce lateral tracking errors, with an average yaw rate reduction of 31.62% and an average sideslip angle reduction of 40.21%.
Two-Stage Multiple-Vector Model Predictive Control for Multiple-Phase Electric-Drive-Reconstructed Power Management for Solar-Powered Vehicles
Authors: Zhu Qingyun , Zhang Zhen , Zhu Zhihao
Published: October 2024

Electric-drive-reconstructed onboard chargers (EDROCs), also known as electric-drive-reconstructed power management systems, are a promising alternative to conventional onboard chargers due to their characteristics of low cost and high power density. The model predictive control offers a fast dynamic response, simple implementation, and the ability to control multiple targets simultaneously. In this paper, a two-stage multi-vector model predictive current control (MPCC) of a six-phase EDROC for solar-powered electric vehicles (EVs) is proposed. Firstly, the topology for the EDROC incorporating a six-phase symmetrical permanent magnet synchronous machine (PMSM) is introduced, and the operation principles of the DC charge mode, the drive mode, and, especially, the in-motion charge mode are analyzed in detail. After that, a two-stage multi-vector MPCC method is proposed by using the multi-vector MPC technique and designing a two-stage MPC structure to eliminate the regulation of the weighting factor of the MPC. Finally, the effectiveness of the proposed method is verified on a self-designed 2 kW EDROC platform.
Enhanced Vehicle Logo Detection Method Based on Self-Attention Mechanism for Electric Vehicle Application
Authors: Yang Shuo , Liu Yisu , Liu Ziyue , Xu Changhua , Du Xueting
Published: October 2024

Vehicle logo detection plays a crucial role in various computer vision applications, such as vehicle classification and detection. In this research, we propose an improved vehicle logo detection method leveraging the self-attention mechanism. Our feature-sampling structure integrates multiple attention mechanisms and bidirectional feature aggregation to enhance the discriminative power of the detection model. Specifically, we introduce the multi-head attention for multi-scale feature fusion module to capture multi-scale contextual information effectively. Moreover, we incorporate the bidirectional aggregation mechanism to facilitate information exchange between different layers of the detection network. Experimental results on a benchmark dataset (VLD-45 dataset) demonstrate that our proposed method outperforms baseline models in terms of both detection accuracy and efficiency. Our experimental evaluation using the VLD-45 dataset achieves a state-of-the-art result of 90.3% mAP. Our method has also improved AP by 10% for difficult samples, such as HAVAL and LAND ROVER. Our method provides a new detection framework for small-size objects, with potential applications in various fields.
Research on Performance of Interior Permanent Magnet Synchronous Motor with Fractional Slot Concentrated Winding for Electric Vehicles Applications
Authors: Xi Zhiqiang , Niu Lianbo , Yan Xianghai , Xu Liyou
Published: October 2024

The fractional-slot, concentrated-winding, interior permanent magnet synchronous motor (FSCW IPMSM) has advantages, such as reducing motor copper consumption, improving flux-weakening capability, and motor fault tolerance, and has certain development potential in application fields such as electric vehicles. However, fractional-slot concentrated-winding motors often contain rich harmonic components due to their winding characteristics, leading to increased motor losses and back electromotive force harmonics, thereby affecting the efficiency and constant power speed regulation range of the motor. Based on this, this article first uses the winding function method to explore the inductance and saliency ratio of the interior permanent magnet synchronous motor with different slot pole combinations in the fractional-slot concentrated- winding of electric vehicles. Secondly, this article will establish a 2D finite element parameterized model to analyze and compare the performance of fractional-slot concentrated-winding motors with different slot pole combinations, including air gap magnetic density, back electromotive force distortion rate, overload multiple, and torque. The structural parameters of the motor were optimized with the objective of minimizing the torque ripple under the constraint of minimizing the average torque reduction. The motor slot width, permanent magnet angle, and permanent magnet pole arc angle were analyzed and optimized. The simulation results showed that 12 slots and 8 poles were the optimal design schemes, providing a theoretical basis for the selection of slot pole coordination in the fractional-slot concentrated-winding interior permanent magnet synchronous motor for electric vehicles.
Implementasi Decision Tree untuk Prediksi Kelahiran Bayi Prematur
Authors: Rosida Putri Lailatul , Nurmalasari Mieke , Hosizah Hosizah , Krismawati Dewi
Published: October 2024

The early birth of baby in Indonesia is a case that has a very high incidence rate. According to data from the Ministry of Health in 2021, the presentation of premature babies in Indonesia is 84%. The number of infant deaths in Indonesia is still relatively high compared to other ASEAN countries. The purpose of this study was to predict the birth of premature babies with the implementation of decision tree, with this type of predictive analysis research. The population in this study is pregnant women patients with a sample of 350 pregnant women patient data covering the variables studied Age, BMI, Vaginal Discharge, History of Miscarriage, History of Prematurity and Pregnancy Spacing. The prediction was made by halving the training data by 245 and the testing data by 105. The results obtained are the variable Body Mass Index (BMI) is the riskiest factor for premature birth The decision tree model yields an AUC of 91.7%, it can be concluded that the decision tree has a good classification accuracy value.