bluuebunny/crossref_metadata_2025 huggingface dataset:
Dual Clustering-Based Method for Geospatial Knowledge Graph Partitioning
Authors: Chen Yuxuan , Ou Feifei , Liu Qiliang , Wu Gusheng , Chen Kaiqi , Deng Min , Chen Meihua , Xu Rui
Published: November 2024

Geospatial knowledge graphs provide critical technology for integrating geographic information and semantic knowledge, which are very useful for geographic data analysis. As the scale of geospatial knowledge graphs continues to grow, the distributed management of geospatial knowledge graphs is becoming an inevitable requirement. Geospatial knowledge graph partitioning is the core technology for the distributed management of geospatial knowledge graphs. To support geographic data analysis, spatial relationships between entities should be considered in the application of geospatial knowledge graphs. However, existing knowledge graph partitioning methods overlook the spatial relationships between entities, resulting in the low efficiency of spatial queries. To address this issue, this study proposes a geospatial knowledge graph partitioning method based on dual clustering which performs two different clustering methods step by step. First, the density peak clustering method (DPC) is used to cluster geographic nodes. The nodes within each cluster are merged into a super-node. Then, we use an efficient graph clustering method (i.e., Leiden) to identify the community structure of the graph. Nodes belonging to the same community are further merged to reduce the size of the graph. Finally, partitioning operations are performed on the compressed graph based on the idea of the Linear-Weighted Deterministic Greedy Policy (LDG). We construct a geospatial knowledge graph based on YAGO3 to evaluate the performance of the proposed graph partitioning method. The experimental results show that the proposed method outperforms ten comparison methods in terms of graph partitioning quality and spatial query efficiency.
The Impact of Objects with a Potential Odour Nuisance on the Life Comfort of the Urban Agglomeration Inhabitants
Authors: Wiśniewska Marta , Szyłak-Szydłowski Mirosław
Published: November 2024

Odour nuisance is one of the main causes of environmental complaints. People exposed to long-term odorants may experience headaches, nausea, difficulty concentrating, loss of appetite, stress, insomnia, and discomfort. Some chemical compounds, besides unpleasant odours, can cause adverse symptoms, diseases, and even death in human bodies. One of these compounds that make up BTEX (benzene, toluene, ethylbenzene, xylene) is benzene, which is present in the environment, mainly in the air, because of emissions from traffic, the petrochemical industry, and combustion processes. Factories, such as refineries and petrochemicals, that form part of some urban agglomerations constitute extensive industrial facilities. This paper presents the survey research results in an urban agglomeration, which enabled, among others, an indication of significant sources of odour nuisance and the areas most exposed to this nuisance. In addition, an analysis of residents’ complaints about odour nuisance over a 10-year period was carried out, which showed, on the one hand, the variability of the number of complaints and, on the other hand, the areas of the city where there were the most complaints. This work aims to evaluate the problem of odour nuisance in an urban agglomeration and to identify its causes through the analysis of residents’ complaints and the results of surveys.
Vehicle Motion Control for Overactuated Vehicles to Enhance Controllability and Path Tracking
Authors: Mandl Philipp , Edelmann Johannes , Plöchl Manfred
Published: November 2024

The motion control of vehicles poses distinct challenges for both vehicle stability and path tracking, especially under critical environmental and driving conditions. Overactuated vehicles can effectively utilize the available tyre–road friction potential by leveraging additional actuators, thus enhancing their stability and controllability even in challenging scenarios. This paper introduces a novel modular upstream control architecture for overactuated vehicles, integrating a fast and robust linear time-varying model predictive path and speed tracking controller with a model following approach and nonlinear control allocation to form a holistic vehicle motion controller. The architecture decouples the path and speed tracking task from the actuator allocation, where torque vectoring and rear-wheel steering are applied to achieve linear understeer reference vehicle behavior. It allows for the use of a simpler path tracking controller, enabling long preview horizons and enhanced computational efficiency. Nonlinearities, such as the mutual influence of lateral and longitudinal tyre forces, are accounted for within the control allocation. The simulation results demonstrate that the proposed control architecture and overactuation improve vehicle stability in critical driving conditions and reduce path tracking errors compared to a dual-motor vehicle.
Fast Type-II Hartley Transform Algorithms for Short-Length Input Sequences
Authors: Polyakova Marina , Cariow Aleksandr
Published: November 2024

This paper presents the type-II fast discrete Hartley transform (DHT-II) algorithms for input data sequences of lengths from 2 to 8. The starting point for developing the eight algorithms is the representation of DHT-II as a matrix–vector product. The underlying matrices usually have a good block structure. These matrices must then be successfully factorized to obtain a computational procedure that reduces the number of operations in computing the matrix–vector product. In some cases, it is necessary to pre-decompose the original matrices into submatrices and rearrange the rows and/or columns of the resulting matrices to find the factorizations that would substantially save the arithmetic operations. As a result of applying the pointed transformations, we synthesized the final algorithms with reduced computational complexity. The correctness of the obtained algorithmic solutions was theoretically justified using the rigorous mathematical background of each of them. Then, the complex algorithms were further tested using the MATLAB R2023b software to confirm their performance. Finally, an evaluation of the computational complexity for each obtained solution was compared with the computational complexity of the direct calculation of the matrix–vector product and existing fast DHT-II algorithms. The obtained factorizations of the DHT-II transformation matrices on average reduce the number of additions by 5% and the number of multiplications by 73% compared with the direct calculation of the matrix–vector product.
Cubic-like Features of I–V Relations via Classical Poisson–Nernst–Planck Systems Under Relaxed Electroneutrality Boundary Conditions
Authors: Li Hong , Li Zhantao , Pan Chaohong , Song Jie , Zhang Mingji
Published: November 2024

We focus on higher-order matched asymptotic expansions of a one-dimensional classical Poisson–Nernst–Planck system for ionic flow through membrane channels with two oppositely charged ion species under relaxed electroneutrality boundary conditions. Of particular interest are the current–voltage (I–V) relations, which are used to characterize the two most relevant biological properties of ion channels—permeation and selectivity—experimentally. Our result shows that, up to the second order in ε=λ/r, where λ is the Debye length and r is the characteristic radius of the channel, the cubic I–V relation has either three distinct real roots or a unique real root with a multiplicity of three, which sensitively depends on the boundary layers because of the relaxation of the electroneutrality boundary conditions. This indicates more rich dynamics of ionic flows under our more realistic setups and provides a better understanding of the mechanism of ionic flows through membrane channels.
Spectral Properties of the Laplace Operator with Variable Dependent Boundary Conditions in a Disk
Authors: Dukenbayeva Aishabibi , Sadybekov Makhmud
Published: November 2024

In this work, we study the spectral properties of the Laplace operator with variable dependent boundary conditions in a disk. The boundary conditions include periodic and antiperiodic boundary conditions as well as the generalized Samarskii–Ionkin-type boundary conditions. We show eigenfunctions and eigenvalues of these problems in an explicit form. Moreover, the completeness of their eigenfunctions is investigated.
Some Theorems of Uncertain Multiple-Delay Differential Equations
Authors: Gao Yin , Tang Han
Published: November 2024

Uncertain differential equations with a time delay, called uncertain-delay differential equations, have been successfully applied in feedback control systems. In fact, many systems have multiple delays, which can be described by uncertain differential equations with multiple delays. This paper defines uncertain differential equations with multiple delays, which are called uncertain multiple-delay differential equations (UMDDEs). Based on the linear growth condition and the Lipschitz condition, the existence and uniqueness theorem of the solutions to the UMDDEs is proven. In order to judge the stability of the solutions to the UMDDEs, the concept of the stability in measure for UMDDEs is presented. Moreover, two theorems sufficient for use as tools to identify the stability in measure for UMDDEs are proved, and some examples are also discussed in this paper.
Extension of an Eighth-Order Iterative Technique to Address Non-Linear Problems
Authors: Ramos Higinio , Argyros Ioannis K. , Behl Ramandeep , Alshehri Hashim
Published: November 2024

The convergence order of an iterative method used to solve equations is usually determined by using Taylor series expansions, which in turn require high-order derivatives, which are not necessarily present in the method. Therefore, such convergence analysis cannot guarantee the theoretical convergence of the method to a solution if these derivatives do not exist. However, the method can converge. This indicates that the most sufficient convergence conditions required by the Taylor approach can be replaced by weaker ones. Other drawbacks exist, such as information on the isolation of simple solutions or the number of iterations that must be performed to achieve the desired error tolerance. This paper positively addresses all these issues by considering a technique that uses only the operators on the method and Ω-generalized continuity to control the derivative. Moreover, both local and semi-local convergence analyses are presented for Banach space-valued operators. The technique can be used to extend the applicability of other methods along the same lines. A large number of concrete examples are shown in which the convergence conditions are fulfilled.
Assessment of a Top and Bottom Cooling Strategy for Prismatic Lithium-Ion Cells Intended for Automotive Use
Authors: Madaoui Said , Guzowski Bartlomiej , Gozdur Roman , Dimitrova Zlatina , Audiot Nicolas , Sabatier Jocelyn , Vinassa Jean-Michel , Guillemard Franck
Published: November 2024

In contemporary vehicle applications, lithium-ion batteries have become a leading option among the diverse array of battery technologies available. This preference is attributed to their advantageous properties, which include low self-discharge rates and no memory effect. Despite these benefits, lithium-ion batteries are not without their challenges. The key issues include a restricted driving range, concerns regarding longevity, safety risks, and prolonged charging durations. Efforts aimed at minimizing the charging duration frequently entail the introduction of elevated currents into the battery, a practice that can significantly elevate its temperature and, in turn, diminish its operational lifespan. Generally, battery packs in electric vehicles are equipped with flat cooling plates located on their side or bottom surfaces, which also serve the dual purpose of providing heating in colder conditions. Nevertheless, this cooling configuration faces difficulties during fast charging and may not efficiently heat or cool the batteries. In this work, a novel thermal management approach is proposed, in which a battery module is cooled not only with a bottom cooling plate but also using another cooling plate in contact with the busbars, located on the top of the battery module. The simulations and experimental tests show that this new configuration demonstrates significant improvements. The thermal time constant is reduced by 47%, enabling faster cooling of the module. Additionally, the maximum temperature reached by the battery during charging with dual cooling is lowered by 6 °C compared to the conventional approach. In this configuration, the top cooling plate acts as a thermal bridge. This is a key advantage that promotes temperature homogenization within the battery module. As a result, it supports an even aging process of batteries, ensuring their longevity and optimal performance.
Efficacy of High-Definition Transcranial Alternating Current Stimulation (HD-tACS) at the M1 Hotspot Versus C3 Site in Modulating Corticospinal Tract Excitability
Authors: Meng Hao , Houston Michael , Dias Nicholas , Guo Chen , Francisco Gerard , Zhang Yingchun , Li Sheng
Published: November 2024

Previous studies have shown that beta-band transcranial alternating current stimulation (tACS) applied at the M1 hotspot can modulate corticospinal excitability. However, it remains controversial whether tACS can influence motor unit activities at the spinal cord level. This study aims to compare the efficacy of applying tACS over the hotspot versus the conventional C3 site on motor unit activities and subsequent behavioral changes. This study used a randomized crossover trial design, where fifteen healthy participants performed a paced ball-squeezing exercise while receiving high-definition tACS (HD-tACS) at 21 Hz and 2 mA for 20 min. HD-tACS targeted either the flexor digitorum superficialis (FDS) hotspot or the C3 site, with the order of stimulation randomized for each participant and a 1-week washout period between sessions. Motor unit activities were recorded from the FDS. HD-tACS intervention significantly reduced the variability of motor unit firing rates and increased force variability during isometric force production. The significant modulation effects were seen only when the intervention was applied at the hotspot, but not at the C3 site. Our findings demonstrate that HD-tACS significantly modulates motor unit activities and force variability. The results indicate that cortical-level entrainment by tACS can lead to the modulation of spinal motor neuron activities. Additionally, this study provides further evidence that the C3 site may not be the optimal target for tACS intervention for hand muscles, highlighting the need for personalized neuromodulation strategies.
Prognostic Significance and Immune Landscape of a Cuproptosis-Related LncRNA Signature in Ovarian Cancer
Authors: Zhou Min , Tang Jianming , Huang Guotao , Hong Li
Published: November 2024

Background: Cuproptosis is a copper-induced mitochondrial cell death, and regulating cuproptosis is becoming a rising cancer treatment modality. Here, we attempted to establish a cuproptosis-associated lncRNAs (CRLs) signature (CRlncSig) to predict the survival, immune landscape, and treatment response in ovarian cancer (OC) patients. Methods: A series of statistical analyses were used to identify the key CRLs that are closely related to the prognosis, and a prognostic CRlncSig was constructed. The predictive accuracy of the CRlncSig was further validated in an independent Gene Expression Omnibus (GEO) set. Then, we compared the immune cell infiltration, immune checkpoints, tumor microenvironment (TME), tumor mutational burden (TMB), drug sensitivity, and efficacy of immunotherapy between the two subgroups. We further built a nomogram integrating the CRlncSig and different clinical traits to enhance the clinical application of the CRlncSig. Results: Nine hub CRLs, namely RGMB-AS1, TYMSOS, DANCR, LINC00702, LINC00240, LINC00996, DNM1P35, LINC00892, and TMEM254-AS1, were correlated with the overall survival (OS) of OC and a prognostic CRlncSig was established. The CRlncSig classified OC patients into two risk groups with strikingly different survival probabilities. The time-dependent ROC (tdROC) curves demonstrated good predictive ability in both the training cohort and an independent validation cohort. Multivariate analysis confirmed the independent predictive performance of the CRlncSig. We constructed a nomogram based on the CRlncSig, which can predict the prognosis of OC patients. The high-risk score was characterized by decreased immune cell infiltration and activation of stroma, while activation of immunity was observed in the low-risk subgroup. Moreover, patients in low-risk subgroups had more Immunophenoscore (IPS) and fewer immune escapes compared to high-risk subgroups. Finally, an immunotherapeutic cohort confirmed the value of the CRlncSig in predicting immunotherapy outcomes. Conclusions: The developed CRlncSig may be promising for the clinical prediction of OC patient outcomes and immunotherapeutic responses.
Kallikrein-Related Peptidase 6 Contributes to Murine Intestinal Tumorigenesis Driven by a Mutant Adenomatous polyposis coli Gene
Authors: Georgieva Teodora G. , Darmoul Dalila , Chen Hwudaurw , Cui Haiyan , Rice Photini F. S. , Barton Jennifer K. , Besselsen David G. , Ignatenko Natalia A.
Published: November 2024

Background/Objectives: The objective of this study was to assess the role of a secreted serine protease, kallikrein-related peptidase 6 (KLK6), during colorectal tumorigenesis driven by a mutant Adenomatous polyposis coli (APC) tumor suppressor gene. A first analysis of KLK6 expression in the intestinal tract of Apc-mutant multiple intestinal neoplasia (ApcMin/+) mice revealed up to four-fold induction of Klk6 mRNA levels in adenomas relative to its level in the adjacent mucosa. Methods and Results: The presence of KLK6 protein in the adenomatous areas was confirmed by immunohistochemistry and optical coherence tomography/laser-induced fluorescence (OCT/LIF) imaging. To assess the contribution of the KLK6 expression on the Apc-mutant intestinal and colon tumorigenesis, we engineered a mouse with floxed alleles of the Klk6 gene (Klk6lox/lox) and crossed it with a mouse expressing the truncated APC protein under control of the intestinal tract-specific human CDX2P9.5-NLS Cre transgene (CPC;Apcfl/fl;Klk6+/+). We found that CPC;Apcfl/fl mice with disrupted Klk6 gene expression (CPC;Apcfl/fl;Klk6fl/fl) had a significantly smaller average size of the small intestinal and colon crypts (p < 0.001 and p = 0.04, respectively) and developed a significantly fewer adenomas (p = 0.01). Moreover, a decrease in high-grade adenomas (p = 0.03) and adenomas with a diameter above 2 mm (p < 0.0001) was noted in CPC;Apcfl/fl;Klk6fl/fl mice. Further molecular analysis showed that Klk6 gene inactivation in the small intestine and colon tissues of CPC;Apcfl/fl;Klk6fl/fl mice resulted in a significant suppression of transforming growth factor β2 (TGF-β2) protein (p ≤ 0.02) and mitogen-activated protein kinase (MAPK) phosphorylation (p ≤ 0.01). Conclusions: These findings demonstrate the oncogenic role of KLK6 in the mutant Apc-mediated intestinal tumorigenesis and suggest the utility of KLK6 for early diagnosis of colorectal tumors.
SLFN12 Expression Significantly Effects the Response to Chemotherapy Drugs in Triple-Negative Breast Cancer
Authors: Brown Savannah R. , Vomhof-DeKrey Emilie Erin , Al-Marsoummi Sarmad , Beyer Trysten , Lauckner Bo , Samson Mckenzie , Sattar Sarah , Brown Nicholas D. , Basson Marc D.
Published: November 2024

Background/Objectives: Schlafen12 (SLFN12) is an intermediate human Schlafen protein shown to correlate with survivability in triple-negative breast cancer (TNBC). SLFN12 causes differential expressions of significant cancer genes, but how they change in response to chemotherapy remains unknown. Our aim is to identify the effect of chemotherapy on genes that improve TNBC outcomes and other SLFN family members following SLFN12 knockout or overexpression. Methods: We overexpressed SLFN12 using a lentiviral vector and knocked out SLFN12 (AdvShSLFN12) using a hairpin adenovirus in MDA-MB-231 TNBC cells. Cells were treated with camptothecin, paclitaxel, zoledronic acid, or carboplatin to evaluate the SLFN12 signature cancer genes associated with improved TNBC outcomes using qPCR. Additionally, cells were treated alone and in combination with AdvShSLFN12, IFN-α2 (known SLFN12 stimulator), carboplatin, and paclitaxel. After treatment, the viable cell numbers were analyzed utilizing a colorimetric crystal violet assay for cell viability. Results: The SLFN family and SLFN12 cancer signature gene mRNA expressions were analyzed by RT-qPCR. Treating SLFN12-overexpressing TNBC cells with chemotherapy agents resulted in the differential expressions of eight cancer-related genes. Notably, GJB3 was downregulated following treatment with each chemotherapeutic drug. Inducing SLFN12 with IFN-α2 resulted in decreased cell viability and increased SLFN12 mRNA levels following treatment with paclitaxel or carboplatin. Conclusions: These results suggest that SLFN12 overexpression significantly affects the expressions of genes driving phenotypic changes in response to chemotherapy and influences additional SLFN family members following IFN-α2 treatment. This may contribute to improving the survival of patients with SLFN12 overexpression. Additionally, patient SLFN12 levels can be used as a factor when pursuing personalized chemotherapy treatments.
Psychological Interventions for Insomnia in Patients with Cancer: A Scoping Review
Authors: Gonzalez Alyssa Alinda , Jimenez-Torres Gladys Janice , Rozman de Moraes Aline , Geng Yimin , Pawate Varsha , Khan Rida , Narayanan Santhosshi , Yennurajalingam Sriram
Published: November 2024

Background/Objectives: Insomnia is a frequent and distressing symptom with limited treatment in patients with cancer. Among the available treatments for insomnia, psychological interventions are some of the most assessed. While studies and reviews show promise of interventions improving insomnia in patients with cancer, inconsistent approaches to operationalizing and measuring insomnia combined with the heterogeneity of available treatments render comparisons and synthetization difficult. This review sought to rigorously synthesize psychological interventions for patients with cancer and insomnia by describing current therapies, identifying gaps in the literature, and offering supportive interventions. Methods: A comprehensive search of five databases—Ovid MEDLINE, Ovid Embase, Ovid PsycInfo, EBSCO CINAHL Plus with Full Text, and Cochrane Library—was conducted through 1 August 2024. The review included randomized trials and non-inferiority trials evaluating psychological interventions for patients with various types of cancers. Twenty-one studies were included, and study quality ranged from good to excellent, according to the PEDro scale. Results: The current evidence supports the use of cognitive behavioral therapy (CBT) to treat insomnia over and above psychoeducation alone, mindfulness-based stress reduction, Brief Behavioral Therapy, the Benson Relaxation Technique, progressive muscle relaxation, mindfulness meditation, mind-body bridging, and home-based psychological nursing. Digital, minimal, and internet-based intervention modalities are effective, though professional-delivered CBT proved most effective. Conclusions: CBT remains the most effective psychological intervention for insomnia in this population. Challenges exist regarding the implementation of CBT, so further research is warranted to identify the best psychological interventions for specific settings and subsets of patients with cancer.
Peptide-Functionalized Gold Nanoparticles as Organocatalysts for Asymmetric Aldol Reactions
Authors: Peme Thabo , Brady Dean , Shumbula Ndivhuwo P. , Machumele Khanani , Moloto Nosipho , Adams Taryn , Makatini Maya M.
Published: November 2024

The use of high catalyst loading is required for most of the organocatalyzed asymmetric aldol reactions in organic synthesis, and this often presents challenges during purification and difficulties in catalyst recovery from the reaction mixture. The immobilization of the catalyst onto gold nanoparticles (AuNPs) can change the structural conformations of the catalyst, thereby improving its catalytic activity and reusability. Herein we report on the synthesis of aldolase mimetic peptide coupled to gold nanoparticles (AuNPs) as efficient organocatalysts for asymmetric aldol reaction. AuNPs were synthesized using the Turkevich method. The conjugation of the peptide to AuNPs was characterized using surface plasmon resonance (SPR), Raman and X-ray photoelectron spectroscopy, and transmission electron microscopy (TEM) was used for particle size determination. The produced nanoparticles, whose sizes depended on the reduction method, were quasi-spherical with a relatively narrow size distribution. The peptide–AuNP conjugates were evaluated for aldol reaction catalytic activity between carbonyls p-nitrobenzaldehyde and cyclohexanone. The products were obtained with good yields (up to 85%) and enantioselectivity (up to 94%). The influence of organic solvents, pH and buffer solutions was also investigated. The results showed that the buffer solutions regulated the colloidal stability of AuNPs, resulting in a significant enhancement in the catalytic rate of the peptide–AuNP conjugate.
Fabrication of Two-Dimensional B-Doped C3N4 Nanosheet-Encapsulated One-Dimensional Rod-like Mo-MOF-Derived MoS2 Heterojunctions for Enhanced Photocatalytic Ethanol Conversion and Synergistic Hydrogen Production
Authors: Zhang Caili , Wang Jian , Wang Li
Published: November 2024

The photocatalytic conversion of ethanol and the simultaneous development of hydrogen technology play a role in solving the energy crisis and reducing environmental pollution. In this research, rod-like M-MoS2 serves as a channel for charge transfer, leading to superior photocatalytic activity compared to H-MoS2. Further, two-dimensional (2D) B-doped C3N4 (BCN) nanosheets were anchored on the one-dimensional (1D) rod-like M-MoS2 surface to form a 1D/2D heterojunction, with M-MoS2/BCN-0.08 (mass ratio of M-MoS2:BCN of 0.08:1) exhibiting the highest photocatalytic performance. Under visible light irradiation, the ethanol conversion rate reached 1.79% after 5 h of photocatalytic reaction per gram of catalyst, while generating 421 μmol of 2,3-butanediol (2,3-BDO), 5460 μmol of acetaldehyde (AA), and 5410 μmol of hydrogen gas (H2). This different characterization provides evidence that a significant amount of photoinduced electrons generated in BCN under illumination conditions rapidly transfer to the conduction band (CB) of M-MoS2 through the rod-like structure of M-MoS2, and finally transfer to Pt to promote the production of hydrogen gas. The photoinduced holes in the valence band (VB) of M-MoS2 are rapidly consumed by ethanol upon transferring to BCN, effectively separating the photoinduced electron–hole pairs and resulting in superior photocatalytic performance.
Data Analysis and Prediction for Emergency Supplies Demand Through Improved Dynamics Model: A Reflection on the Post Epidemic Era
Authors: Zhuang Weiqing , Wu Qiong , Wang Morgan C.
Published: November 2024

Throughout history, humanity has grappled with infectious diseases that pose serious risks to health and life. The COVID-19 pandemic has profoundly impacted society, prompting significant reflection on preparedness and response strategies. In the future, humans may face unexpected disasters or crises, making it essential to learn from the COVID-19 experience, especially in ensuring adequate emergency supplies and mobilizing resources effectively in times of need. Efficient emergency medical management is crucial during sudden outbreaks, and the preparation and allocation of medical supplies are vital to safeguarding lives, health, and safety. However, the unpredictable nature of epidemics, coupled with population dynamics, means that infection rates and supply needs within affected areas are uncertain. By studying the factors and mechanisms influencing emergency supply demand during such events, materials can be distributed more efficiently to minimize harm. This study enhances the existing dynamics model of infectious disease outbreaks by establishing a demand forecasting model for emergency supplies, using Hubei Province in China as a case example. This model predicts the demand for items such as masks, respirators, and food in affected regions. Experimental results confirm the model’s effectiveness and reliability, providing support for the development of comprehensive emergency material management systems. Ultimately, this study offers a framework for emergency supply distribution and a valuable guideline for relief efforts.
Corrosion Inhibition of PAAS/ZnO Complex Additive in Alkaline Al-Air Battery with SLM-Manufactured Anode
Authors: Peng Guangpan , Geng Yuankun , Niu Chenhao , Yang Hanqian , Duan Weipeng , Cao Shu
Published: November 2024

In order to improve the electrochemical activity and discharge performance of aluminum–air batteries and to reduce self-corrosion of the anode, an SLM-manufactured aluminum alloy was employed as the anode of the Al-air battery, and the influence of PAAS and ZnO inhibitors taken separately or together on the self-corrosion rate and discharge performance of the Al-air battery in a 4 M NaOH solution were investigated. The experimental result indicated that the effect of a composite corrosion inhibitor was stronger than that of a single corrosion inhibitor. The addition of the compound inhibitor not only promoted the activation of the anode but also formed a more stable composite protective film on the surface of the anode, which effectively slowed down the self-corrosion and improved the utilization rate of the anode. In NaOH/PAAS/ZnO electrolytes, the dissolution of the Al6061 alloy was mainly controlled by the diffusion of the electric charge in the corrosion products or the zinc salt deposition layer. Meanwhile, for the Al-air battery, the discharge voltage, specific capacity, and specific energy increased by 21.74%, 26.72%, and 54.20%, respectively. In addition, the inhibition mechanism of the composite corrosion inhibitor was also expounded. The excellent discharge performance was due to the addition of the composite corrosion inhibitor, which promoted the charge transfer of the anode reaction, improved the anode’s activity, and promoted the uniform corrosion of the anode. This study provides ideas for the application of aluminum–air batteries in the field of new energy.
Rough Draft Math as an Evolving Practice: Incremental Changes in Mathematics Teachers’ Thinking and Instruction
Authors: Jansen Amanda , Botello Megan , Silla Elena M.
Published: November 2024

This paper presents exploratory findings suggesting that mathematics teachers can implement Rough Draft Math (RDM) by making small, incremental changes that align with their current practices and local contexts, including curriculum materials, with minimal support. Following a conference presentation and/or reading a book about pedagogy, teachers reported shifts in their thinking that facilitated their interest in enacting RDM and small changes they made to their teaching. The flexibility of RDM, as a general concept rather than a set of prescribed practices, allowed teachers to incorporate RDM to meet their own teaching goals. We propose that this adaptability enables teachers to incorporate RDM into their classrooms incrementally, reflecting their existing objectives for their students.
Research on the Quality Grading Method of Ginseng with Improved DenseNet121 Model
Authors: Gu Jinlong , Li Zhiyi , Zhang Lijuan , Yin Yingying , Lv Yan , Yu Yue , Li Dongming
Published: November 2024

Ginseng is an important medicinal plant widely used in traditional Chinese medicine. Traditional methods for evaluating the visual quality of ginseng have limitations. This study presents a new method for grading ginseng’s appearance quality using an improved DenseNet121 model. We enhance the network’s capability to recognize various channel features by integrating a CA (Coordinate Attention) mechanism. We also use grouped convolution instead of standard convolution in dense layers to lower the number of model parameters and improve efficiency. Additionally, we substitute the ReLU (Rectified Linear Unit) activation function with the ELU (Exponential Linear Unit) activation function, which reduces the problem of neuron death related to ReLU and increases the number of active neurons. We compared several network models, including DenseNet121, ResNet50, ResNet101, GoogleNet, and InceptionV3, to evaluate their performance against our method. Results showed that the improved DenseNet121 model reached an accuracy of 95.5% on the test set, demonstrating high reliability. This finding provides valuable support for the field of ginseng grading.
Optimization Strategy for Integrated Energy Microgrids Based on Shared Energy Storage and Stackelberg Game Theory
Authors: Yin Zhilong , Wang Zhiguo , Yu Feng , Wang Dong , Li Na
Published: November 2024

The implementation of community power generation technology not only increases the flexibility of electricity use but also improves the power system’s load distribution, increases the overall system efficiency, and optimizes energy allocation. This article first outlines the operational context of the system and analyzes the roles and missions of the various participants. Subsequently, optimization models are developed for microgrid operators, community power storage facility service providers and load aggregators. Next, the paper explores the game relationship between microgrid operators and load aggregators, proposing a model based on the Stackelberg game theory and proving the presence and singularity of the Stackelberg equilibrium solution. Finally, simulations are conducted using Yalmip tools and the CPLEX solution on the MATLAB R2023a software platform. A combination of heuristic algorithms and solver methods is employed to optimize the strategies of microgrid operators and load aggregators. The research findings show that the proposed framework is not only able to achieve an effective balance of interests between microgrid operators and load aggregators but also creates a win–win situation between load aggregators and shared energy storage operators. Additionally, the solution algorithms used ensure the protection of data privacy.
Hybrid Control Strategy for LLC Converter Based on Improved Fruit Fly Optimization Algorithm
Authors: Xue Qitong , Zhi Pengfei , Zhu Wanlu , Wei Haifeng , Zhang Yi , Cui Jia
Published: November 2024

This paper presents a hybrid control strategy for the LLC resonant converter in X-ray machines, addressing the limitations of voltage gain range under Pulse Frequency Modulation (PFM) and dynamic response under Phase Shift Modulation (PSM). The strategy employs an improved fruit fly optimization algorithm (IFOA) to optimize PI control and integrate Hybrid Phase-Shifted and Frequency-Modulated control. It dynamically adjusts the switching frequency and phase shift angle to maintain output stability and efficiency, ensuring optimal operation under rated conditions. A Matlab-based system simulation model confirmed the stability and accuracy of the IFOA in controlling the converter. Subsequent prototype testing validated the strategy’s effectiveness in reducing conduction losses, enhancing overall efficiency, and demonstrating practical feasibility and superiority.
Artificial Intelligence Signal Control in Electronic Optocoupler Circuits Addressed on Industry 5.0 Digital Twin
Authors: Massaro Alessandro
Published: November 2024

The paper is focused on the modeling of a digital twin (DT) through a circuit simulation and artificial intelligence (AI) analysis to determine the effects of disturbances and noise in optocoupler devices integrated into programmable logic controller (PLC) systems. Specifically, the DT analyzes the parametric and the predicted simulations about the sensitivity of the optocouplers versus noise and interference to provide possible corrective actions, compensating for the distortion of the output signal. The model is structured into two main data processing steps: the first is based on the circuit simulation of the optocoupler noise coupling by highlighting the time-domain sensitivity aspects and the frequency behavior of the coupled signals; the second one estimates the predicted disturbed signal by means of supervised random forest (RF) and unsupervised K-Means algorithms to provide further elements to prevent corrective solutions by means of risk maps. This work is suitable for Industry 5.0 scenarios involving machine control supported by AI-based DT platforms. The innovative elements of the proposed model are the DT features of scalability and modularity; the spatial multidimensionality, able to couple the effects of different undesired signals; and the possibility to simulate the whole PLC system, including its control circuits.
An Optimization Strategy for Unit Commitment in High Wind Power Penetration Power Systems Considering Demand Response and Frequency Stability Constraints
Authors: Qian Minhui , Wang Jiachen , Yang Dejian , Yin Hongqiao , Zhang Jiansheng
Published: November 2024

To address the issue of accommodating large-scale wind power integration into the grid, a unit commitment model for power systems based on an improved binary particle swarm optimization algorithm is proposed, considering frequency constraints and demand response (DR). First, incentive-based DR and price-based DR are introduced to enhance the flexibility of the demand side. To ensure the system can provide frequency support, the unit commitment model incorporates constraints such as the rate of change of frequency, frequency nadir, steady-state frequency deviation, and fast frequency response. Next, for the unit commitment planning problem, the binary particle swarm optimization algorithm is employed to solve the mixed nonlinear programming model of unit commitment, thus obtaining the minimum operating cost. The results show that after considering DR, the load becomes smoother compared to the scenario without DR participation, the overall level of load power is lower, and the frequency meets the safety constraint requirements. The results indicate that a comparative analysis of unit commitment in power systems under different scenarios verifies that DR can promote rational allocation of electricity load by users, thereby improving the operational flexibility and economic efficiency of the power system. In addition, the frequency variation considering frequency safety constraints has also been significantly improved. The improved binary particle swarm optimization algorithm has promising application prospects in solving the accommodation problem brought by large-scale wind power integration.
Study on the Effect of Coal Grain Size on the Morphology of Soot Generated During Combustion
Authors: Liu Jiani , Si Mengting , Zhang Yindi , Liu Bing , Shi Changqian
Published: November 2024

This study performed an experimental exploration to analyze the influence of different grain sizes of coal on the nanostructure and morphological parameters of soot generated during combustion. Initially, primary and mature soot samples were gained from the combustion flames of two different grain sizes of coal (less than 150 μm, named sample #1, and 6–8 mm, named sample #2) by using thermophoresis sampling technology. Subsequently, the transmission electron microscopy (TEM) and scanning electron microscopy (SEM) were employed to investigate and analyze the soot samples, with the aim of obtaining their morphological parameters and nanostructure characteristics. The TEM images indicate that the nascent soot produced during the flame formed by small-sized coal is relatively uniform, with individual particles 8–14 nm in size. The grain size of the nascent soot produced by large-sized coal is much larger, within a wide range of 50–350 nm. Additionally, the nanostructures of the nascent soot particles produced by samples #1 and #2 mainly consist of upright parallel crystal stripes. The crystal stripes of the soot particles formed by sample #1 have obvious microcrystalline structures, whereas only a small amount of microcrystalline structure is found at the edge of sample #2. Compared with sample #2, the soot formed during the combustion of sample #1 exhibits a denser crystalline structure. The SEM results indicate that the mature soot agglomerates formed in sample #2 are larger and more in quantity compared to sample #1. Furthermore, the mature soot agglomerates formed in sample #2 have a stronger coagulation performance and a more compact structure than that formed in sample #1.
Modelling an Influence of Solar Cells’ Connection Manner in Silicon Photovoltaic Modules on Their Characteristics with Partial Shading
Authors: Górecki Krzysztof , Krac Ewa , Dąbrowski Jacek
Published: November 2024

The article considers the problem of an influence of partial shading on the characteristics of photovoltaic modules (PV modules). Different manners of connections of silicon solar cells contained in such modules are considered, e.g., classical PV modules (I and II generation of modules) and modules made using half-cut technology (III generation of modules). A model of PV modules was proposed. This model has the form of a network for the SPICE program and takes into account the influence of partial shading of the PV module caused by clouds or terrain and architectural obstacles on its current and voltage. The form of the model was described, and the DC characteristics of the considered classical and half-cut modules, calculated using the formulated model, were compared to the measurement results under different shading conditions. Some calculations using the proposed model were performed for different methods to connect solar cells in PV modules. The obtained results were discussed.
An Approach for Detecting Faulty Lines in a Small-Current, Grounded System Using Learning Spiking Neural P Systems with NLMS
Authors: Hu Yangheng , Wu Yijin , Yang Qiang , Liu Yang , Wang Shunli , Dong Jianping , Zeng Xiaohua , Zhang Dapeng
Published: November 2024

Detecting faulty lines in small-current, grounded systems is a crucial yet challenging task in power system protection. Existing methods often struggle with the accurate identification of faults due to the complex and dynamic nature of current and voltage signals in these systems. This gap in reliable fault detection necessitates more advanced methodologies to improve system stability and safety. Here, a novel approach, using learning spiking neural P systems combined with a normalized least mean squares (NLMS) algorithm to enhance faulty line detection in small-current, grounded systems, is proposed. The proposed method analyzes the features of current and voltage signals, as well as active and reactive power, by separately considering their transient and steady-state components. To improve fault detection accuracy, we quantified the likelihood of a fault occurrence based on feature changes and expanded the feature space to higher dimensions using an ascending dimension structure. An adaptive learning mechanism was introduced to optimize the convergence and precision of the detection model. Simulation scheduling datasets and real-world data were used to validate the effectiveness of the proposed approach, demonstrating significant improvements over traditional methods. These findings provide a robust framework for faulty-line detection in small-current, grounded systems, contributing to enhanced reliability and safety in power system operations. This approach has the potential to be widely applied in power system protection and maintenance, advancing the broader field of intelligent fault diagnosis.
Evaluating Energy Efficiency Parameters of Municipal Wastewater Treatment Plants in Terms of Management Strategies and Carbon Footprint Reduction: Insights from Three Polish Facilities
Authors: Kłosok-Bazan Iwona , Rak Adam , Boguniewicz-Zabłocka Joanna , Kuczuk Anna , Capodaglio Andrea G.
Published: November 2024

Water management in cities is a critical factor for sustainable growth and development. Satisfying the current needs with respect for the future is not possible without properly managed water and wastewater systems. An essential element of wastewater systems is the wastewater treatment plant (WWTP). The nexus between wastewater treatments and energy demand is a well-known problem. In times of energy crisis, effective energy management in this critical infrastructure is a key task. The purpose of this article is to analyze WWTPs’ energy consumption with regard to proposed management strategies for managers, designers and decision makers. A detailed analysis of WWTP operational parameters and a proposal of improvement actions will be useful for applicability and benchmarking studies. Estimating the carbon footprint (CF) of selected WWTPs considering the indirect emissions due to energy consumption is an important step for developing energy neutrality of WWTPs. Due to the desire to deepen research in the area of a complex phenomenon, which is the energy management system in WWTPs, the research undertaken herein is based on the case study method of three water and sewage companies operating southwestern Poland. Each urban area has different specificities, natural conditions and needs. The presented results of the analyses may be the basis for developing directions for changes in national policy, other benchmarking studies, and improving the energy management system in WWTPs.
An ANN-Based Method for On-Load Tap Changer Control in LV Networks with a Large Share of Photovoltaics—Comparative Analysis
Authors: Janiga Klara , Miller Piotr , Małkowski Robert , Izdebski Michał
Published: November 2024

The paper proposes a new local method of controlling the on-load tap changer (OLTC) of a transformer to mitigate negative voltage phenomena in low-voltage (LV) networks with a high penetration of photovoltaic (PV) installations. The essence of the method is the use of the load compensation (LC) function with settings determined via artificial neural network (ANN) algorithms. The proposed method was compared with other selected local methods recommended in European regulations, in particular with those currently required by Polish distribution system operators (DSOs). Comparative studies were performed using the model of the 116-bus IEEE test network, taking into account the unbalance in the network and the voltage variation on the medium voltage (MV) side.