bluuebunny/crossref_metadata_2025 huggingface dataset:
Proof-of-Concept for Long-Term Human Endometrial Epithelial Organoids in Modeling Menstrual Cycle Responses
Authors: Jiang Yanyu , Palomares Arturo Reyes , Munoz Patricia , Nalvarte Ivan , Acharya Ganesh , Inzunza Jose , Varshney Mukesh , Rodriguez-Wallberg Kenny Alexandra
Published: November 2024

Endometrial disorders, such as infertility and endometriosis, significantly impact reproductive health, thus necessitating better models to study endometrial function. Current in vitro models fail to replicate the complexity of the human endometrium throughout the entire menstrual cycle. This study aimed to assess the physiological response of human endometrial organoids (hEOs) to in vitro hormonal treatments designed to mimic the hormonal fluctuations of the menstrual cycle. Endometrial biopsies from three healthy women were used to develop hEOs, which were treated over 28 days with three hormonal stimulation strategies: (1) estrogen only (E) to mimic the proliferative phase, (2) the addition of progesterone (EP) to simulate the secretory phase, and (3) the further addition of cAMP (EPC) to enhance the secretory functions of hEOs. Gene and protein expression were analyzed using qPCR, IHC, and ELISA. The hEOs exhibited proliferation, gland formation, and appropriate expression of markers such as E-cadherin and Ki67. The hormonal treatments induced significant changes in PR, HSD17B1, PAEP, SPP1, and other genes relevant to endometrial function, closely mirroring in vivo physiological responses. The prominent changes were observed in EPC-treated hEOs (week 4) with significantly high expression of uterine milk components such as glycodelin (PAEP) and osteopontin (SPP1), reflecting mid- to late-secretory phase physiology. This model successfully recapitulates human menstrual cycle dynamics and offers a promising platform for studying endometrial disorders and advancing personalized treatments in gynecology.
The Crosstalk of Apoptotic and Non-Apoptotic Signaling in CD95 System
Authors: Seyrek Kamil , Espe Johannes , Reiss Elisabeth , Lavrik Inna N.
Published: November 2024

The mechanisms of CD95 (Fas/APO-1)-mediated extrinsic apoptotic pathway in cancer cells have been extensively studied. The majority of human cells express CD95, but not all these cells can induce extrinsic apoptosis. Accumulating evidence has shown that CD95 is a multifunctional protein, and its stimulation can also elicit non-apoptotic or even survival signals. It has become clear that under certain cellular contexts, due to the various checkpoints, CD95 activation can trigger both apoptotic and non-apoptotic signals. The crosstalk of death and survival signals may occur at different levels of signal transduction. The strength of the CD95 stimulation, initial levels of anti-apoptotic proteins, and posttranslational modifications of the core DISC components have been proposed to be the most important factors in the life/death decisions at CD95. Successful therapeutic targeting of CD95 signaling pathways will require a better understanding of the crosstalk between CD95-induced apoptotic and cell survival pathways. In this review, in order to gain a systematic understanding of the crosstalk between CD95-mediated apoptosis and non-apoptotic signaling, we will discuss these issues in a step-by-step way.
Correction: Svobodová Kovaříková et al. N6-Adenosine Methylation in RNA and a Reduced m3G/TMG Level in Non-Coding RNAs Appear at Microirradiation-Induced DNA Lesions. Cells 2020, 9, 360
Authors: Svobodová Kovaříková Alena , Stixová Lenka , Kovařík Aleš , Komůrková Denisa , Legartová Soňa , Fagherazzi Paolo , Bártová Eva
Published: November 2024

The affiliation number 1, “Institute of Biophysics of the Czech Academy of Sciences, Královopolská 135, 612 65 Brno, Czech Republic” changed its zip code to 612 00 [...]
Fish Cell Spheroids, a Promising In Vitro Model to Mimic In Vivo Research: A Review
Authors: Gómez-Mercader Antonio , Monzón-Atienza Luis , Montero Daniel , Bravo Jimena , Acosta Félix
Published: November 2024

In vitro cell culture systems serve as instrumental platforms for probing biological phenomena and elucidating intricate cellular mechanisms. These systems afford researchers the opportunity to scrutinize cellular responses within a regulated environment, thereby circumventing the ethical and logistical challenges associated with in vivo experimentation. Three-dimensional (3D) cell cultures have emerged as a viable alternative to mimic in vivo environments. Within this context, spheroids are recognized as one of the most straightforward and efficacious models, presenting a promising substitute for conventional monolayer cultures. The application of 3D cultures of fish cells remains limited, focusing mainly on physiological and morphological characterization studies. However, given the capacity of spheroids to emulate in vivo conditions, researchers are exploring diverse applications of these 3D cultures. These include eco-toxicology, immunology, drug screening, endocrinology, and metabolism studies, employing a variety of cell types such as fibroblasts, hepatocytes, embryonic cells, gonadal cells, gastrointestinal cells, and pituitary cells. This review provides a succinct overview, concentrating on the most frequently employed methods for generating fish cell spheroids and their applications to date. The aim is to compile and highlight the significant contributions of these methods to the field and their potential for future research.
Celastrol-Loaded Hyaluronic Acid/Cancer Cell Membrane Lipid Nanoparticles for Targeted Hepatocellular Carcinoma Prevention
Authors: He Peng , Zou Manshu , Zhang Chanjuan , Shi Yaning , Qin Li
Published: November 2024

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide, and its prevention and treatment face severe challenges. It is crucial to improve the targeting of drugs on tumor cells and tissues. Celastrol (CeT), as an active ingredient of traditional Chinese medicine, possesses strong antitumor effects, especially in triggering apoptosis of HCC. However, due to its toxicity and lack of targeting, its application is greatly limited. HMCLPs, a nano-biomimetic platform carrying CeT with controllable drug release, enhanced targeting, and immunocompatibility, were developed for the first time, which can be used for the treatment of HCC. By utilizing homologous cell membranes and hyaluronic acid (HA), HMCLPs can precisely target tumor regions and release CeT in a controlled manner. Both in vitro and in vivo studies have demonstrated that HMCLPs loaded with CeT significantly increased the accumulation of reactive oxygen species (ROS), induced mitochondrial damage, and triggered apoptosis of HCC cells, resulting in effective treatment with minimal adverse reaction. The development of HMCLPs as a nanocarrier system for CeT delivery offers a promising therapeutic strategy for HCC. This innovative approach improves the targeted delivery and bioavailability of CeT, dramatically induces apoptosis in HCC cells, and exerts its powerful antitumor effects while minimizing systemic toxicity. The present study highlights the potential of combining innovative nanocarriers with powerful natural compounds such as CeT to enhance efficacy and reduce toxicity.
The Exposure Height of Silicon Particle with Round Edges Effect on the Tribological Property of Al-Si Alloy Cylinder Liner
Authors: Li Chengdi , Chen Xiao , Liu Hao , Dong Lianjie , Jian Huihua , Wang Jingsi , Du Fengming , Guan Yong
Published: November 2024

In order to improve the wear resistance of Al-Si alloy cylinder liners, surface treatment is usually used. The Al-Si alloy cylinder liner samples were prepared by mechanical grinding and laser finishing. The mechanical grinding samples were carried out by the independent design and development of a grinding machine. The laser finishing samples were laser-heated by a CO2 continuous transverse-flow laser. Both of the two surface treatments could provide the surfaces of protruding silicon particles with round edges to improve the wear resistance. However, in the exposure height of silicon particles with round edges, the study was lacking. The exposure height of silicon particles is important to the tribological properties of the Al-Si alloy cylinder liner, and should be analyzed in detail. The wear tests were completed by a contraposition reciprocating wear test rig under lubrication. It was found that when the silicon particles were exposed on the surface of the Al-Si alloy cylinder liner sample by 1.2 μm, the mechanical grinding samples and laser finishing samples all exhibited minimum friction coefficients and weight losses. This paper confirms that a suitable exposure height of silicon particles would reduce the probability of adhesion wear and abrasive wear of Al-Si alloy cylinder liners and increase the lubrication. It presents an excellent tribological property. However, when the exposure height of silicon particles is too high, the silicon particle is easily prone to plastic deformation or even falls off during the friction process due to the high stress and larger plastic contact index.
Performance Analysis of Wireless Sensor Networks Using Damped Oscillation Functions for the Packet Transmission Probability
Authors: Orea-Flores Izlian Y. , Rivero-Angeles Mario E. , Gonzalez-Ambriz Sergio-Jesus , Anaya Eleazar Aguirre , Saleem Sumera
Published: November 2024

Wireless sensor networks are composed of many nodes distributed in a region of interest to monitor different environments and physical variables. In many cases, access to nodes is not easy or feasible. As such, the system lifetime is a primary design parameter to consider in the design of these networks. In this regard, for some applications, it is preferable to extend the system lifetime by actively reducing the number of packet transmissions and, thus, the number of reports. The system administrator can be aware of such reporting reduction to distinguish this final phase from a malfunction of the system or even an attack. Given this, we explore different mathematical functions that drastically reduce the number of packet transmissions when the residual energy in the system is low but still allow for an adequate number of transmissions. Indeed, in previous works, where the negative exponential distribution is used, the system reaches the point of zero transmissions extremely fast. Hence, we propose different dampening functions with different decreasing rates that present oscillations to allow for packet transmissions even at the end of the system lifetime. We compare the system performance under these mathematical functions, which, to the best of our knowledge, have never been used before, to find the most adequate transmission scheme for packet transmissions and system lifetime. We develop an analytical model based on a discrete-time Markov chain to show that a moderately decreasing function provides the best results. We also develop a discrete event simulator to validate the analytical results.
Natural Resources of Rhaponticum carthamoides in the Tarbagatai State National Nature Park
Authors: Myrzagaliyeva Anar , Irsaliyev Serik , Tustubayeva Shynar , Samarkhanov Talant , Orazov Aidyn , Alemseitova Zhanylkan
Published: November 2024

The study of medicinal plants and having a protected status is an urgent issue for the conservation of biodiversity in Kazakhstan. Rhaponticum carthamoides (Willd.) Ilijn is a medicinal plant, and its excessive harvesting and destruction of habitats, as well as its conservation status, are of concern. We conducted a study to assess the ecological characteristics of the habitat of the species in the Tarbagatai National Natural Park, calculate the amount of medicinal raw materials, calculate both aboveground and underground phytomass, and calculate biological and operational reserves. A map has been developed to show the distribution of the species and potential harvest sites. In addition, a correlation analysis was performed to understand how population size affects productivity. The results highlight the need for continuous monitoring and protection of endangered species. The conservation of Rhaponticum carthamoides in the Tarbagatai State National Nature Park is currently ensured by its protected status. However, the study emphasizes the importance of developing a sustainable use regime to effectively manage plant resources and ensure their preservation for future generations.
Using Key Predictors in an SVM Model for Differentiating Spinal Fractures and Herniated Intervertebral Discs in Preoperative Anesthesia Evaluation
Authors: Yang Shih-Ying , Hsu Shih-Yen , Su Yi-Kai , Lu Nan-Han , Liu Kuo-Ying , Chen Tai-Been , Chiu Kon-Ning , Huang Yung-Hui , Yeh Li-Ren
Published: November 2024

Background/Objectives: Spinal conditions, such as fractures and herniated intervertebral discs (HIVDs), are often challenging to diagnose due to overlapping clinical symptoms and the difficulty in assessing their functional impact. Accurate differentiation between these conditions is crucial for effective treatment, particularly in the context of preoperative anesthesia evaluation, where understanding the underlying condition can influence anesthesia planning and pain management. Methods and Materials: This study presents a Support Vector Machine (SVM) model designed to distinguish between spinal fractures and HIVDs using key clinical predictors, including age, gender, preoperative Visual Analog Scale (VAS) pain scores, and the number of spinal fractures. A retrospective analysis was conducted on a dataset of 199 patients diagnosed with these conditions. The SVM model, using a radial basis function (RBF) kernel, classified the conditions based on the selected predictors. Model performance was evaluated using precision, recall, accuracy, and the Kappa index, with Leave-One-Out (LOO) cross-validation applied to ensure robust results. Results: The SVM model achieved a precision of 92.1% for fracture cases and 91.2% for HIVDs, with recall rates of 98.1% for fractures and 70.5% for HIVDs. The overall accuracy was 92%, and the Kappa index was 0.76, indicating substantial agreement. The analysis revealed that age and VAS pain scores were the most critical predictors for accurately diagnosing these conditions. Conclusions: These results highlight the potential of the SVM model with an RBF kernel to reliably differentiate between spinal fractures and HIVDs using routine clinical data. Future work could enhance model performance by incorporating additional clinical parameters relevant to preoperative anesthesia evaluation.
Molecular Imaging Biomarkers for Early Cancer Detection: A Systematic Review of Emerging Technologies and Clinical Applications
Authors: Malik Maajid Mohi Ud Din , Alqahtani Mansour M. , Hadadi Ibrahim , Kanbayti Ibrahem , Alawaji Zeyad , Aloufi Bader A.
Published: November 2024

Background: Early cancer detection is crucial for improving patient outcomes. Molecular imaging biomarkers offer the potential for non-invasive, early-stage cancer diagnosis. Objectives: To evaluate the effectiveness and accuracy of molecular imaging biomarkers for early cancer detection across various imaging modalities and cancer types. Methods: A comprehensive search of PubMed/MEDLINE, Embase, Web of Science, Cochrane Library, and Scopus was performed, covering the period from January 2010 to December 2023. Eligibility criteria included original research articles published in English on molecular imaging biomarkers for early cancer detection in humans. The risk of bias for included studies was evaluated using the QUADAS-2 tool. The findings were synthesized through narrative synthesis, with quantitative analysis conducted where applicable. Results: In total, 50 studies were included. Positron emission tomography (PET)-based biomarkers showed the highest sensitivity (mean: 89.5%, range: 82–96%) and specificity (mean: 91.2%, range: 85–100%). Novel tracers such as [68Ga]-PSMA for prostate cancer and [18F]-FES for breast cancer demonstrated promising outcomes. Optical imaging techniques showed high specificity in intraoperative settings. Conclusions: Molecular imaging biomarkers show significant potential for improving early cancer detection. Integration into clinical practice could lead to earlier interventions and improved outcomes. Further research is needed to address standardization and cost-effectiveness.
Principals in Preschool Management and Leadership: A Necessary Combination to Ensure That Preschool Teachers Are Given Conditions to Be Responsible for Teaching in Preschool
Authors: Öqvist Anna , Cervantes Sara
Published: November 2024

Following the educational reforms of 2010 and the revision of the curriculum in 2018, Swedish preschool principals have a special responsibility for ensuring that preschool teachers have the necessary conditions to assume their responsibility for the teaching and to lead the work team. This indicates that integrating leadership with management is essential for a sustainable and successful preschool education. This study explores this assumption. Building on the concepts of management and leadership, with a qualitative research design, this study analyses data from seven interviews with preschool principals. The results showed a lack of a combination of management and leadership among the principals in relation to their special responsibility of ensuring that preschool teachers are given conditions necessary to be responsible for teaching in the preschool. The principals either lacked both management and leadership or focused on management only with a lack of leadership. Our findings suggest the necessity for principals to combine management and leadership and move from a previous flat organisational structure towards a focus on increasing preschool teachers’ responsibilities and leadership within the work team. Support for principals is needed to be able to perform a combination of management and leadership when their mission is complex and time-consuming.
The Nexus Between Digital Technology, Innovation, Entrepreneurship Education, and Entrepreneurial Intention and Entrepreneurial Motivation: A Systematic Literature Review
Authors: Udekwe Emmanuel , Iwu Chux Gervase
Published: November 2024

Entrepreneurship Education (EE) is renowned for developing students’ managerial aptitudes, skills, and ideas for self-reliance. The inclusion of digital technology and innovation in EE is necessary to enhance Entrepreneurial Intention (EI) and Entrepreneurial Motivation (EM) for technological revolution and economic development. The aim of the systematic literature review is to (i) identify the current study on digital technologies, innovation, EE, EI, and EM, (ii) highlight how digital technology and innovation shape EE to achieve EI and motivation among students, and (iii) offer new advice on the future EE in a digital era. A search strategy was instituted to ascertain the required publications from Scopus, Web of Science, DOAJ, IEEE, ProQuest, SAGE Journals, Taylor & Francis, and Wiley. The publications were between 2010 and 2024, with no language restrictions. Out of the 108 identified publications from the search, 69 publications representing 54 separate papers were used in the review. Digital transformation in EE requires significant studies to determine its role in economic development and job creation. This review identified several themes in the publications, such as innovation, motivation, skills development, digital technology, EE’s impact, and factors of EE. The sustainability and future expectations of EE through digital technology and innovation are highlighted in the review. The study identified several findings, such as factors depriving EE, such as experience, investment, teachers, infrastructure, technology, market size, government, competition, culture, and funds. Further findings are a strategic vision of EE through policies to embrace innovation and digital technology practices and to achieve EM and EI. Also, the selected papers for the review are current publications at 61.1%, the quantitative method at 42.3% and journal articles at 88.9%. It is prudent to review EE’s appropriateness in a digital and innovative environment and to identify the impact on EM and EI among students.
Prospective Teachers’ Conceptions of Area
Authors: McNeal Betsy , Ghosh Hajra Sayonita , Battista Michael , Ozturk Ayse
Published: November 2024

This study explored 10 prospective teachers’ (PTs’) understanding of the area of a rectangular region using square and non-square rectangular area-units. In an hour-long interview, each PT was first asked to explain how they would find the area of a given rectangular region in terms of a non-square notecard. For several PTs, this task prompted discussion of a square unit defined by the edge of the notecard. In a second task, PTs were presented with a rectangular array of squares and were asked to explain to a fictional child why multiplying length times width does not count the top left corner square twice. An analysis of transcripts of the interview suggested three conceptual components to understanding the area of a rectangular region—area-units, multiplication, and their connection to the length times width formula. Based on the PTs’ responses, we propose multi-tiered levels of reasoning. Each new level of understanding was built on the prior level in a hierarchical fashion. Juxtaposing tasks involving different area-units revealed PTs’ thinking about non-square and square area-units and how these related to the formula “L × W”.
An Automated Penetration Testing Framework Based on Hierarchical Reinforcement Learning
Authors: Liu Hongri , Liu Chuhan , Wu Xiansheng , Qu Yun , Liu Hongmei
Published: November 2024

Given the large action space and state space involved in penetration testing, reinforcement learning is widely applied to enhance testing efficiency. This paper proposes an automatic penetration testing scheme based on hierarchical reinforcement learning to reduce both action space and state space. The scheme includes a network intelligence responsible for specifying the penetration host and a host intelligence designated to perform penetration testing on the selected host. Specifically, within the network intelligence, an action-masking mechanism is adopted to shield unenabled actions, thereby reducing the explorable action space and improving the penetration testing efficiency. Additionally, the host intelligence employs an invalid discrimination mechanism, terminating testing after actions that do not alter system states, thereby preventing sudden increases in the number of neural network training steps for an action. An optimistic estimation mechanism is also introduced to select penetration strategies suited to various hosts, preventing training crashes due to value confusion between different hosts. Ablation experiments demonstrate that the host intelligence can learn different penetration strategies for varying penetration depths without significant fluctuations in training steps, and the network intelligence can coordinate with the host intelligence to perform network penetration steadily. This hierarchical reinforcement learning framework can detect network vulnerabilities more quickly and accurately, significantly reducing the cost of security policy updates.
Current Compensation for Faulted Grid-Connected PV Arrays Using a Modified Voltage-Fed Quasi-Z-Source Inverter
Authors: Al-Saloli Abdullah Abdurrahman , Alfaris Faris E.
Published: November 2024

Large-scale photovoltaic (PV) systems are being widely deployed to meet global environmental goals and renewable energy targets. Advances in PV technology have driven investment in the electric sector. However, as the size of PV arrays grows, more obstacles and challenges emerge. The primary obstacles are the occurrence of direct current (DC) faults and shading in a large array of PV panels, where any malfunction in a single panel can have a detrimental impact on the overall output power of the entire series-connected PV string and therefore the PV array. Due to the abrupt and frequent fluctuations in power, beside the low-PV systems’ moment of inertia, various technical problems may arise at the point of common coupling (PCC) of grid-connected PV generations, such as frequency and voltage stability, power efficiency, voltage sag, harmonic distortion, and other power quality factors. The majority of the suggested solutions were deficient in several crucial transient operating features and cost feasibility; therefore, this paper introduces a novel power electronic DC–DC converter that seeks to mitigate these effects by compensating for the decrease in current on the DC side of the system. The suggested solution was derived from the dual-source voltage-fed quasi-Z-source inverter (VF-qZSI), where the PV generation power can be supported by an energy storage element. This paper also presents the system architecture and the corresponding power switching control. The feasibility of the proposed method is investigated with real field data and the PSCAD simulation platform during all possible weather conditions and array faults. The results demonstrate the feasibility and capability of the proposed scheme, which contributes in suppressing the peak of the transient power-to-time variation (dP/dt) by 72% and reducing its normalized root-mean-square error by about 38%, with an AC current total harmonic distortion (THD) of only 1.04%.
Impact of Air Gaps Between Microstrip Line and Magnetic Sheet on Near-Field Magnetic Shielding
Authors: Park Hyun Ho , Song Eakhwan , Kim Jiseong , Kim Cheolsoo
Published: November 2024

This study experimentally analyzed the impact of air gaps between a magnetic sheet and a test board with a microstrip line, which is used to measure the near-field magnetic shielding effectiveness (NSE) of magnetic sheets made of metallic powder. To conduct the measurements, a material fixture equipped with a microstrip line to generate the near magnetic field, a rectangular loop probe, and an automatic probe positioning system capable of moving the loop probe along three axes were designed and fabricated. In addition, to systematically vary the thickness of the gaps, three paper spacers with a thickness of 0.11 mm per paper were used, and a 1.0 mm thick acrylic sheet, along with a specially designed material fixture, was used to press down the magnetic sheets during measurement. The magnetic shielding properties were measured and compared under various air gap conditions using a near-field magnetic loop probe. The effect of the gaps on the shielding performance of the magnetic sheets was quantitatively evaluated for three different magnetic sheets. The experimental results showed that as the gap thickness increased, NSE tended to improve up to a frequency around 1 GHz, while in the higher frequency range of a few GHz, NSE tended to decrease. The physical background of this phenomenon was explained using an equivalent magnetic circuit represented by reluctances for the structure, where the magnetic sheet is placed above the microstrip line with an air gap. This model helps to elucidate how the presence of the air gap affects the near-field magnetic shielding performance.
Capacity Optimization of Wind–Solar–Storage Multi-Power Microgrid Based on Two-Layer Model and an Improved Snake Optimization Algorithm
Authors: Zhao Mintong , He Yuling , Tian Yunfeng , Sun Kai , Jiao Lingyu , Wang Haipeng
Published: November 2024

A two-layer optimization model and an improved snake optimization algorithm (ISOA) are proposed to solve the capacity optimization problem of wind–solar–storage multi-power microgrids in the whole life cycle. In the upper optimization model, the wind–solar–storage capacity optimization model is established. It takes wind–solar power supply and storage capacity as decision variables and the construction cost of the whole life cycle as the objective function. At the lower level, the optimal scheduling model is established, considering the output characteristics of various types of power supplies and energy storage, microgrid sales, and purchases of power as constraints. At the same time, the model considers constraints, such as the power balance, the operating state of the energy storage system, the power sales and purchases, and the network fluctuations, to ensure the system operates efficiently. Taking a microgrid in South China as an application scenario, the model is solved and the optimal capacity allocation scheme of the microgrid is obtained. Meanwhile, the demand response mechanism and the influence of planning years are introduced to further optimize the configuration scheme, and the impact of different rigid–flexible load ratios and various planning horizons on microgrid capacity optimization is analyzed, respectively, by a numerical example. The comparison shows that the ISOA has better optimization performance in solving the proposed two-layer model.
Adaptive Weighted Particle Swarm Optimization for Controlling Multiple Switched Reluctance Motors with Enhanced Deviatoric Coupling Control
Authors: Zhang Tianyu , Xu Xianglian , Zhang Fangqing , Gu Yifeng , Deng Kaitian , Xu Yuli , Xie Tunzhen , Song Yuanqing
Published: November 2024

Switched reluctance motors (SRMs) are widely used in industrial applications due to their advantages. Multi-motor synchronous control systems are crucial in modern industry, as their control strategies significantly impact synchronization performance. Traditional deviation coupling control structures face limitations during the startup phase, leading to excessive tracking errors and exacerbated by uneven load distribution, resulting in desynchronized motor acceleration and increased speed synchronization errors. This study proposes a modified deviation coupling control method based on an adaptive weighted particle swarm optimization (PSO) algorithm to enhance multi-motor synchronization performance. Traditional deviation coupling control applies equal reference torque inputs to each motor’s current loop, failing to address uneven load distribution and causing inconsistent accelerations. To resolve this, a gain equation based on speed deviation is introduced, incorporating self-tracking error and gain coefficients for dynamic synchronization error compensation. The gain coefficients are optimized using the adaptive weighted PSO algorithm to improve system adaptability. A simulation model of a synchronization control system for three SRMs was developed in the Matlab/Simulink R2023b environment. This model compares the synchronization performance of traditional deviation coupling, Fuzzy-PID improved structure, and adaptive PSO improved structure during motor startup, sudden speed increases, and load disturbances. The validated deviation coupling control structure achieved the initial set speed in approximately 0.236 s, demonstrating faster convergence and a 6.35% reduction in settling time. In both the motor startup and sudden speed increase phases, the two optimized methods outperformed the traditional structure in dynamic performance and synchronization accuracy, with the adaptive PSO structure improving synchronization accuracy by 54% and 37.17% over the Fuzzy-PID structure, respectively. Therefore, the PSO-optimized control system demonstrates faster convergence, improved stability, and enhanced synchronization performance.
Conditional Community Search Based on Weight Information
Authors: Wang Mengxiang , Ma Dong , Fu Qiang , Zong Chuanyu
Published: November 2024

Community search aims to identify cohesive subgraphs containing user-given query nodes in social networks. As information technology develops, user demands for community search have become increasingly sophisticated. The searched communities must not only meet the structural cohesiveness requirements but also adhere to some complex search conditions based on Boolean expressions. For example, certain desired nodes should be contained in the communities, while certain undesired nodes cannot exist in the communities, which is called conditional community search. However, existing solutions for conditional community search often introduce some undesired nodes into the identified communities and exhibit relatively low search efficiency. To overcome these drawbacks, therefore, this paper investigates the problem of conditional community search based on weight information. First, we refine the original problem definition of conditional community search and outline the need for an improved algorithm for calculating the weights of the nodes. Then, we explore two novel algorithms for searching conditional communities based on calculated weight information. Finally, we conduct extensive experiments on several real-world datasets to verify the accuracy and efficiency of our proposed searching algorithms.
Fake Review Detection Model Based on Comment Content and Review Behavior
Authors: Sun Pengfei , Bi Weihong , Zhang Yifan , Wang Qiuyu , Kou Feifei , Lu Tongwei , Chen Jinpeng
Published: November 2024

With the development of the Internet, services such as catering, beauty, accommodation, and entertainment can be reserved or consumed online. Therefore, consumers increasingly rely on online information to choose merchants, products, and services, with reviews becoming a crucial factor in their decision making. However, the authenticity of reviews is highly debated in the field of Internet-based process-of-life service consumption. In recent years, due to the rapid growth of these industries, the detection of fake reviews has gained increasing attention. Fake reviews seriously mislead customers and damage the authenticity of online reviews. Various fake review classifiers have been developed, taking into account the content of the reviews and the behavior involved in the reviews, such as rating, time, etc. However, there has been no research considering the credibility of reviewers and merchants as part of identifying fake reviews. In order to improve the accuracy of existing fake review classification and detection methods, this study utilizes a comment text processing module to model the content of reviews, utilizes a reviewer behavior processing module and a reviewed merchant behavior processing module to model consumer review behavior sequences that imply reviewer credibility and merchant review behavior sequences that imply merchant credibility, respectively, and finally merges the two features for fake review classification. The experimental results show that, compared to other models, the model proposed in this paper improves the classification performance by simultaneously modeling the content of reviews and the credibility of reviewers and merchants.
BTIP: Branch Triggered Instruction Prefetcher Ensuring Timeliness
Authors: Lin Wenhai , Lin Yiquan , Chen Yiquan , Cai Shishun , Jin Zhen , Xu Jiexiong , Zhang Yuzhong , Chen Wenzhi
Published: November 2024

In CPU microarchitecture, caches store frequently accessed instructions and data by exploiting their locality, reducing memory access latency and improving application performance. However, contemporary applications with large code footprints often experience frequent Icache misses, which significantly degrade performance. Although Fetch-Directed Instruction Prefetching (FDIP) has been widely adopted in commercial processors to reduce Icache misses, our analysis reveals that FDIP still suffers from Icache misses caused by branch mispredictions and late prefetch, leaving considerable opportunity for performance optimization. Priority-Directed Instruction Prefetching (PDIP) has been proposed to reduce Icache misses caused by branch mispredictions in FDIP. However, it neglects Icache misses due to late prefetch and suffers from high storage overhead. In this paper, we proposed a branch-triggered instruction prefetcher (BTIP), which aims to prefetch Icache lines that FDIP cannot efficiently handle, including the Icache misses due to branch misprediction and late prefetch. We also introduce a novel Branch Target Buffer (BTB) organization, BTIP BTB, which stores prefetch metadata and reuses information from existing BTB entries, effectively reducing storage overhead. We implemented BTIP on the Champsim simulator and evaluated BTIP in detail using traces from the 1st Instruction Prefetching Championship (IPC-1). Our evaluation shows that BTIP outperforms both FDIP and PDIP. Specifically, BTIP reduces Icache misses by 38.0% and improves performance by 5.1% compared to FDIP. Additionally, BTIP outperforms PDIP by 1.6% while using only 41.9% of the storage space required by PDIP.
Evolving Transparent Credit Risk Models: A Symbolic Regression Approach Using Genetic Programming
Authors: Sotiropoulos Dionisios N. , Koronakos Gregory , Solanakis Spyridon V.
Published: November 2024

Credit scoring is a cornerstone of financial risk management, enabling financial institutions to assess the likelihood of loan default. However, widely recognized contemporary credit risk metrics, like FICO (Fair Isaac Corporation) or Vantage scores, remain proprietary and inaccessible to the public. This study aims to devise an alternative credit scoring metric that mirrors the FICO score, using an extensive dataset from Lending Club. The challenge lies in the limited available insights into both the precise analytical formula and the comprehensive suite of credit-specific attributes integral to the FICO score’s calculation. Our proposed metric leverages basic information provided by potential borrowers, eliminating the need for extensive historical credit data. We aim to articulate this credit risk metric in a closed analytical form with variable complexity. To achieve this, we employ a symbolic regression method anchored in genetic programming (GP). Here, the Occam’s razor principle guides evolutionary bias toward simpler, more interpretable models. To ascertain our method’s efficacy, we juxtapose the approximation capabilities of GP-based symbolic regression with established machine learning regression models, such as Gaussian Support Vector Machines (GSVMs), Multilayer Perceptrons (MLPs), Regression Trees, and Radial Basis Function Networks (RBFNs). Our experiments indicate that GP-based symbolic regression offers accuracy comparable to these benchmark methodologies. Moreover, the resultant analytical model offers invaluable insights into credit risk evaluation mechanisms, enabling stakeholders to make informed credit risk assessments. This study contributes to the growing demand for transparent machine learning models by demonstrating the value of interpretable, data-driven credit scoring models.
An Energy Management System for Distributed Energy Storage System Considering Time-Varying Linear Resistance
Authors: Fan Yuanliang , Li Zewen , Huang Xinghua , Luo Dongtao , Lin Jianli , Chen Weiming , Li Lingfei , Yang Ling
Published: November 2024

As the proportion of renewable energy in energy use continues to increase, to solve the problem of line impedance mismatch leading to the difference in the state of charge (SOC) of each distributed energy storage unit (DESU) and the DC bus voltage drop, a distributed energy storage system control strategy considering the time-varying line impedance is proposed in this paper. By analyzing the fundamental frequency harmonic components of the pulse width modulation (PWM) signal carrier of the converter output voltage and output current, we can obtain the impedance information and, thus, compensate for the bus voltage drop. Then, a novel, droop-free cooperative controller is constructed to achieve SOC equalization, current sharing, and voltage regulation. Finally, the validity of the system is verified by a hardware-in-the-loop experimental platform.
Implementation of the Deposit System in Poland as a Tool for Implementing the Circular Economy
Authors: Zarębski Andrzej , Zarębska Joanna , Marosek Konrad
Published: November 2024

The circular economy (CE) poses major challenges to the citizens of European countries. Proper waste management is a priority here. Poland is one of the countries that has been trying for many years to meet the requirements to achieve an appropriate level of recovery as well as the recycling of municipal and packaging waste. In order to achieve appropriate levels of packaging waste recycling, it was planned to implement an otherwise refundable deposit system starting in January 2023. Currently, work is still underway to implement this system starting in January 2025. The aim of the study is to describe the current work of the ministry, entrepreneurs and recovery organizations in this area and, on this basis, to indicate the barriers and uncertainties encountered in the implementation of this system. The authors want to answer the question of what barriers and benefits can be expected after the implementation of the deposit system. The implementation of the system has been postponed many times (for several years). The current involvement of various organizations (large cities, chain stores and recovery organizations) indicates that the system will be implemented on 1 January 2025. Based on the example of other EU countries, what estimated benefits can be expected after implementing the system in Poland? An extensive literature review and survey research indicate that Polish society views the deposit system favorably and Poland is ready to implement it. Specific regulations from the Minister of Climate and Environment need to be implemented as well as special machine need to be put in stores to start the deposit system. Examples of ongoing efforts to create appropriate infrastructure also show that Poland is on track to join the deposit system from January 2025. The deposit system will be continuously improved and expanded with more packages. Currently, it is planned to be introduced only for selected packages.
A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices
Authors: Xiang Hui , Liao Xiao , Wang Yanjie , Cao Hui , Zhong Xianjing , Guan Qingshu , Ru Weiyun
Published: November 2024

The advancement of hydrogen technology and rising environmental concerns have shifted research toward renewable energy for green hydrogen production. This study introduces a novel tri-level transaction methodology for microgrid clusters, addressing uncertainties and price fluctuations in hydrogen. We establish a comprehensive microgrid topology with distributed power generation and hydrogen production facilities. A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. We integrate a sophisticated demand response model for hydrogen loading, capturing users’ behavior in response to price changes, thereby improving renewable energy utilization and supporting economically viable management practices. Additionally, we propose a tri-level game-theoretic framework for analyzing stakeholder interactions in microgrid clusters, incorporating supply–demand dynamics and a master–slave structure for microgrids and users. A distributed algorithm, “KKT & supply-demand ratio”, solves large-scale optimization problems by integrating Karush–Kuhn–Tucker conditions with a heuristic approach. Our simulations validate the methodology, demonstrating that accounting for uncertainties and dynamic hydrogen prices enhances renewable energy use and economic efficiency, optimizing social welfare for operators and economic benefits for microgrids and users.
A Design and Safety Analysis of the “Electricity-Hydrogen-Ammonia” Energy Storage System: A Case Study of Haiyang Nuclear Power Plant
Authors: Shi Lingyue , Ye Cheng , Huang Hong , He Qinglun
Published: November 2024

With the development of modernization, traditional fossil energy reserves are decreasing, and the power industry, as one of the main energy consumption forces, has begun to pay attention to increasing the proportion of clean energy generation. With the deepening of electrification, the peak-valley difference of residential electricity consumption increases, but photovoltaic and wind power generation have fluctuations and are manifested as reverse peak regulation. Thermal power plants as the main force of peak regulation gradually reduce the market share, making nuclear power plants bear the heavy responsibility of participating in peak regulation. The traditional method of adjusting operating power by inserting and removing control rods has great safety risks and wastes resources. Therefore, this paper proposes a new energy storage system that can keep the nuclear power plant running at full power and produce hydrogen to synthesize ammonia from excess power. A comprehensive evaluation model of energy storage based on z-score data standardization and objective parameter assignment AHP (analytic hierarchy process) analysis method was established to evaluate energy storage systems according to a multi-index system. With an AP1000 daily load tracking curve as the input model, the simulation model built by Aspen Plus V14 was used to calculate the operating conditions of the system. In order to provide a construction basis for practical engineering use, Haiyang Nuclear Power Plant in Shandong Province is taken as an example. The system layout scheme is proposed according to the local environmental conditions. The accident tree analysis method is combined with ALOHA 5.4.1.2 (Areal Locations of Hazardous Atmospheres) hazardous chemical analysis software and MARPLOT 5.1.1 geographic information technology. A qualitative and quantitative assessment of risk factors and the consequences of leakage, fire, and explosion accidents caused by hydrogen and ammonia storage processes is carried out to provide guidance for accident prevention and emergency rescue. The design of an “Electric-Hydrogen-Ammonia” energy storage system proposed in this paper provides a new idea for zero-carbon energy storage for the peak shaving of nuclear power plants and has a certain role in promoting the development of clean energy.
Research on a New Method of Water Recovery from Biogas Plant Digestate
Authors: Nowak Mateusz , Czekała Wojciech , Bojarski Wiktor , Dach Jacek
Published: November 2024

Digestate is a product with valuable fertilizing properties, remaining after the anaerobic fermentation process. An essential feature of the substance in question is its high water content of up to 97%. To improve the fertilizer value of the digestate, it is necessary to dehydrate it to produce a concentrated product. This paper determined the possibility of dewatering the digestate using an innovative reactor design. The study, conducted on a laboratory scale, used digestate from a Polish biogas plant. The dewatering technique described in the paper is based on the evaporation and condensation of water vapor on the inner surface of the reactor dome. The condensate accumulated on the leach trough and was directed to a storage tank. During the weeks of testing, 11.5 kg of condensate was separated from the initial weight of the digestate (32 kg), with a dry weight of 6.11%. The resulting condensate from dehydration had an average pH value of 9.0 and an average ammonium nitrogen content of 2.07 g∙kg−1. The economic calculations made in the paper allowed for estimating the expected savings associated with the management of digestate in Poland. The research showed the proposed technology’s high potential for dewatering digestate under laboratory conditions.