bluuebunny/crossref_metadata_2025 huggingface dataset:
Management of Patients with Hypersensitivity to Platinum Salts and Taxane in Gynecological Cancers: A Cross-Sectional Study by the European Network of Young Gynaecologic Oncologists (ENYGO)
Authors: Zwimpfer Tibor A. , Bilir Esra , Gasimli Khayal , Cokan Andrej , Bizzarri Nicolò , Razumova Zoia , Kacperczyk-Bartnik Joanna , Nikolova Tanja , Pletnev Andrei , Kahramanoglu Ilker , Shushkevich Alexander , Strojna Aleksandra , Theofanakis Charalampos , Cicakova Tereza , Vetter Marcus , Montavon Céline , Morgan Gilberto , Heinzelmann-Schwarz Viola
Published: March 2024

Platinum and taxane chemotherapy is associated with the risk of hypersensitivity reactions (HSRs), which may require switching to less effective treatments. Desensitization to platinum and taxane HSRs can be used to complete chemotherapy according to the standard regimen. Therefore, we aimed to investigate the current management of HSRs to platinum and/or taxane chemotherapy in patients with gynecologic cancers. We conducted an online cross-sectional survey among gynecological and medical oncologists consisting of 33 questions. A total of 144 respondents completed the survey, and 133 respondents were included in the final analysis. Most participants were gynecologic oncologists (43.6%) and medical oncologists (33.8%), and 77.4% (n = 103) were involved in chemotherapy treatment. More than 73% of participants experienced >5 HSRs to platinum and taxane per year. Premedication and a new attempt with platinum or taxane chemotherapy were used in 84.8% and 92.5% of Grade 1–2 HSRs to platinum and taxane, respectively. In contrast, desensitization was used in 49.4% and 41.8% of Grade 3–4 HSRs to platinum and taxane, respectively. Most participants strongly emphasized the need to standardize the management of platinum and taxane HSRs in gynecologic cancer. Our study showed that HSRs in gynecologic cancer are common, but management is variable and the use of desensitization is low. In addition, the need for guidance on the management of platinum- and taxane-induced HSRs in gynecologic cancer was highlighted.
Application of Nanoparticles for Magnetic Hyperthermia for Cancer Treatment—The Current State of Knowledge
Authors: Szwed Marzena , Marczak Agnieszka
Published: March 2024

Hyperthermia (HT) is an anti-cancer therapy commonly used with radio and chemotherapies based on applying heat (39–45 °C) to inhibit tumor growth. However, controlling heat towards tumors and not normal tissues is challenging. Therefore, nanoparticles (NPs) are used in HT to apply heat only to tumor tissues to induce DNA damage and the expression of heat shock proteins, which eventually result in apoptosis. The aim of this review article is to summarize recent advancements in HT with the use of magnetic NPs to locally increase temperature and promote cell death. In addition, the recent development of nanocarriers as NP-based drug delivery systems is discussed. Finally, the efficacy of HT combined with chemotherapy, radiotherapy, gene therapy, photothermal therapy, and immunotherapy is explored.
Biomarkers in the Diagnosis of Endometrial Precancers. Molecular Characteristics, Candidate Immunohistochemical Markers, and Promising Results of Three-Marker Panel: Current Status and Future Directions
Authors: Niu Shuang , Molberg Kyle , Castrillon Diego H. , Lucas Elena , Chen Hao
Published: March 2024

Endometrial carcinoma stands as the most prevalent gynecological cancer and the fourth most common cancer affecting women. The incidence of endometrial cancer has been steadily increasing over the past decade, posing a significant threat to public health. The early detection of its precancers remains a critical and evolving concern to reduce mortality associated with endometrial carcinoma. In the last decade, our understanding of endometrial carcinoma and its precancers has advanced through systematic investigations into the molecular genetics of endometrial carcinoma and its precancers. In this review, we focus on advances in precancers associated with the endometrioid subtype, by far the most common histologic variant of endometrial adenocarcinoma. Recent investigations have led to the identification of new biomarkers, and the proposed incorporation of these biomarkers or biomarker panels into the diagnostic framework of endometrial carcinoma precancers. Here, we review these recent advances and their relevance to the histopathologic diagnosis of endometrial carcinoma precancers.
Acute Promyelocytic Leukemia: Review of Complications Related to All-Trans Retinoic Acid and Arsenic Trioxide Therapy
Authors: Ghiaur Alexandra , Doran Cristina , Gaman Mihnea-Alexandru , Ionescu Bogdan , Tatic Aurelia , Cirstea Mihaela , Stancioaica Maria Camelia , Hirjan Roxana , Coriu Daniel
Published: March 2024

The hallmark of acute promyelocytic leukemia (APL) is the presence of the characteristic fusion transcript of the promyelocytic leukemia gene with the retinoic acid receptor α gene (PML::RARA). The PML::RARA fusion is a molecular target for all-trans retinoic acid (ATRA) and arsenic trioxide (ATO). Therapies based on ATRA plus ATO have excellent outcomes in terms of complete remission rates, overall survival, and achievement of deep and durable molecular responses with a very low incidence of relapse. However, although the combination of ATRA and ATO has lower hematologic toxicity than standard chemotherapy, its use is associated with a spectrum of distinctive toxicities, such as differentiation syndrome, liver toxicity, QT interval prolongation, and neurotoxicity. Rigorous monitoring of patients’ clinical evolution is indispensable for identifying and addressing each complication. The objective is to maintain an equilibrium between treatment-induced adverse events and therapeutic efficacy. This paper focused on non-hematologic complications associated with the combination of ATRA and ATO. Additionally, we discuss late-onset complications of this therapy. In summary, the majority of treatment-related adverse events are manageable, self-limiting, and reversible. More so, there seems to be a lower incidence rate of secondary neoplasms compared to standard chemotherapy. However, further research is required to assess how the ATRA plus ATO regimen affects the emergence of additional comorbidities.
Patterns and Incidence of Pneumonitis and Initial Treatment Outcomes with Durvalumab Consolidation Therapy after Radical Chemoradiotherapy for Stage III Non-Small Cell Lung Cancer
Authors: Sato Mizuki , Odagiri Kazumasa , Tabuchi Yuya , Okamoto Hiroaki , Shimokawa Tsuneo , Nakamura Yukiko , Hata Masaharu
Published: March 2024

Durvalumab consolidation after chemoradiotherapy for stage III non-small cell lung cancer (NSCLC) has become the standard of care. Single-center results were examined for treatment outcomes and patterns of pneumonitis in clinical practice. Patients with stage III NSCLC who underwent chemoradiotherapy at our institution (n = 150) were included. The patients were treated with chemoradiotherapy and durvalumab consolidation (Group D, n = 69) or chemoradiotherapy alone (Group N, n = 81). The overall survival (OS), progression-free survival (PFS), and the incidence of and risk factors for 12-month pneumonitis grade ≥ 2 (G2) were investigated. Two-year OS rates were 71.6% in Group D and 52.7% in Group N (p = 0.052). Two-year PFS rates were 43.0% in Group D and 26.5% in Group N (p = 0.010), although a propensity score matched analysis showed no significant difference. The incidence of 12-month pneumonitis ≥ G2 tended to be higher in Group D than in Group N (41.9% vs. 26.3%, p = 0.080). However, there was no difference in pneumonitis ≥ G3 rates (10.5% vs. 12.6%, p = 0.657). A multivariate analysis showed that the lung volume spared from 5 Gy (VS5) < 1800 cm3 was a risk factor for pneumonitis ≥ G2 in Group D. Durvalumab consolidation showed the potential to prolong PFS without increasing the severity of pneumonitis.
Spain’s Rising Melanoma Threat: A Comprehensive 30-Year Analysis (1990–2019)
Authors: Cayuela Lucía , Pereyra-Rodríguez José-Juan , Hernández-Rodriguez Juan-Carlos , Cayuela Aurelio
Published: March 2024

Aim: This study aims to elucidate the factors driving melanoma incidence trends in Spain by analyzing the GBD-2019 dataset (1990–2019) and investigating the age-specific, birth cohort, and period effects on incidence rates. Materials and Methods: This study analyzed melanoma incidence trends in Spain from 1990 to 2019 using an ecological design. Data were sourced from the Global Burden of Disease Study 2019 and Spain’s National Statistics Institute. Age-standardized incidence rates (ASIRs) were calculated using joinpoint regression analysis, and age–period–cohort (A-P-C) modeling was employed to assess the effects of age, time period, and birth cohort on incidence rates. Results: Between 1990 and 2019, an estimated 147,823 melanoma cases were diagnosed in Spain. The ASIRs showed a steady increase for both sexes, with slightly higher rates observed in men. Both men (average annual percentage change (AAPC): 2.8%) and women (AAPC: 2.4%) showed a steady increase in the ASIR over the period. Joinpoint analysis revealed distinct periods of incidence rate changes, with significant upward trends in earlier years followed by stabilization in recent years. Incidence rates increased steadily with age, with the highest rates in the 80–84 age group. Women tended to have slightly higher rates in younger age groups, while men had higher rates in older age groups. Both men and women experienced a steady increase in relative risk of melanoma throughout the 30-year study period, with significant upward trends across birth cohorts. Conclusions: Despite limitations, this study provides valuable insights into factors influencing melanoma incidence in Spain. By understanding age, period, and cohort effects, effective prevention strategies can be developed to reduce melanoma incidence.
Recombinant Acetylcholine Receptor Immunization Induces a Robust Model of Experimental Autoimmune Myasthenia Gravis in Mice
Authors: Theissen Lukas , Schroeter Christina B. , Huntemann Niklas , Räuber Saskia , Dobelmann Vera , Cengiz Derya , Herrmann Alexander , Koch-Hölsken Kathrin , Gerdes Norbert , Hu Hao , Mourikis Philipp , Polzin Amin , Kelm Malte , Hartung Hans-Peter , Meuth Sven G. , Nelke Christopher , Ruck Tobias
Published: March 2024

Myasthenia gravis (MG) is a prototypical autoimmune disease of the neuromuscular junction (NMJ). The study of the underlying pathophysiology has provided novel insights into the interplay of autoantibodies and complement-mediated tissue damage. Experimental autoimmune myasthenia gravis (EAMG) emerged as a valuable animal model, designed to gain further insight and to test novel therapeutic approaches for MG. However, the availability of native acetylcholine receptor (AChR) protein is limited favouring the use of recombinant proteins. To provide a simplified platform for the study of MG, we established a model of EAMG using a recombinant protein containing the immunogenic sequence of AChR in mice. This model recapitulates key features of EAMG, including fatigable muscle weakness, the presence of anti-AChR-antibodies, and engagement of the NMJ by complement and a reduced NMJ density. Further characterization of this model demonstrated a prominent B cell immunopathology supported by T follicular helper cells. Taken together, the herein-presented EAMG model may be a valuable tool for the study of MG pathophysiology and the pre-clinical testing of therapeutic applications.
The Potential of Mushroom Extracts to Improve Chemotherapy Efficacy in Cancer Cells: A Systematic Review
Authors: Fonseca Jéssica , Vaz Josiana A. , Ricardo Sara
Published: March 2024

Chemoresistance is a challenge in cancer treatment, limiting the effectiveness of chemotherapy. Mushroom extracts have shown potential as treatments for cancer therapies, offering a possible solution to overcome chemoresistance. This systematic review aimed to explore the role of mushroom extracts in enhancing chemotherapy and reversing chemoresistance in cancer cells. We searched the PubMed, Web of Science and Scopus databases, following the PRISMA guidelines, and registered on PROSPERO. The extracts acted by inhibiting the proliferation of cancer cells, as well as enhancing the effect of chemotherapy. The mechanisms by which they acted included regulating anti-apoptotic proteins, inhibiting the JAK2/STAT3 pathway, inhibiting the ERK1/2 pathway, modulating microRNAs and regulating p-glycoprotein. These results highlight the potential of mushroom extracts to modulate multiple mechanisms in order to improve the efficacy of chemotherapy. This work sheds light on the use of mushroom extracts as an aid to chemotherapy to combat chemoresistance. Although studies are limited, the diversity of mushrooms and their bioactive compounds show promising results for innovative strategies to treat cancer more effectively. It is crucial to carry out further studies to better understand the therapeutic potential of mushroom extracts to improve the efficacy of chemotherapy in cancer cells.
Recent Research Trends in Neuroinflammatory and Neurodegenerative Disorders
Authors: Cohen Jessica , Mathew Annette , Dourvetakis Kirk D. , Sanchez-Guerrero Estella , Pangeni Rajendra P. , Gurusamy Narasimman , Aenlle Kristina K. , Ravindran Geeta , Twahir Assma , Isler Dylan , Sosa-Garcia Sara Rukmini , Llizo Axel , Bested Alison C. , Theoharides Theoharis C. , Klimas Nancy G. , Kempuraj Duraisamy
Published: March 2024

Neuroinflammatory and neurodegenerative disorders including Alzheimer’s disease (AD), Parkinson’s disease (PD), traumatic brain injury (TBI) and Amyotrophic lateral sclerosis (ALS) are chronic major health disorders. The exact mechanism of the neuroimmune dysfunctions of these disease pathogeneses is currently not clearly understood. These disorders show dysregulated neuroimmune and inflammatory responses, including activation of neurons, glial cells, and neurovascular unit damage associated with excessive release of proinflammatory cytokines, chemokines, neurotoxic mediators, and infiltration of peripheral immune cells into the brain, as well as entry of inflammatory mediators through damaged neurovascular endothelial cells, blood–brain barrier and tight junction proteins. Activation of glial cells and immune cells leads to the release of many inflammatory and neurotoxic molecules that cause neuroinflammation and neurodegeneration. Gulf War Illness (GWI) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are chronic disorders that are also associated with neuroimmune dysfunctions. Currently, there are no effective disease-modifying therapeutic options available for these diseases. Human induced pluripotent stem cell (iPSC)-derived neurons, astrocytes, microglia, endothelial cells and pericytes are currently used for many disease models for drug discovery. This review highlights certain recent trends in neuroinflammatory responses and iPSC-derived brain cell applications in neuroinflammatory disorders.
CaH2-Assisted Molten Salt Synthesis of Zinc-Rich Intermetallic Compounds of RhZn13 and Pt3Zn10 for Catalytic Selective Hydrogenation Application
Authors: Kobayashi Yasukazu , Yamamoto Koharu , Shoji Ryo
Published: March 2024

Zinc-included intermetallic compound catalysts of RhZn, PtZn, and PdZn with a molar ration of Zn/metal = 1/1, which are generally prepared using a hydrogen reduction approach, are known to show excellent catalytic performance in some selective hydrogenations of organic compounds. In this study, in order to reduce the incorporated mounts of the expensive noble metals, we attempted to prepare zinc-rich intermetallic compounds via a CaH2-assisted molten salt synthesis method with a stronger reduction capacity than the common hydrogen reduction method. X-ray diffraction results indicated the formation of RhZn13 and Pt3Zn10 in the samples prepared by the reduction of ZnO-supported metal precursors. In a hydrogenation reaction of p-nitrophenol to p-aminophenol, the ZnO-supported RhZn13 and Pt3Zn10 catalysts showed a higher selectivity than the RhZn/ZnO and PtZn/ZnO catalysts with the almost similar conversions. Thus, it was demonstrated that the zinc-rich intermetallic compounds of RhZn13 and Pt3Zn10 could be superior selective hydrogenation catalysts compared to the conventional intermetallic compound catalysts of RhZn and PtZn.
Perivascular Epithelioid Cell Tumor with Uncertain Malignant Potential Arising in the Round Ligament
Authors: Badlaeva Alina , Tregubova Anna , Kruglyak Diana , Luzhina Irina , Asaturova Aleksandra
Published: March 2024

A 12-year-old adolescent was diagnosed with a right-sided solid mass in the round ligament of the uterus. The chief complaints were abdominal pain and pelvic discomfort. She underwent laparoscopic tumor resection. Histological examination demonstrated a trabecular growth pattern of epithelioid cells with mitotic activity (3 per 50 HPF), which expressed melanocytic and myoid markers. Due to aforementioned findings, a final diagnosis of perivascular epithelioid cell tumor (PEComa) with uncertain malignant potential was made. To the best of our knowledge, this localization of PEComa is considered to be infrequent with only occasionally reported cases.
Differential Effects of a Telemonitoring Platform in the Development of Chemotherapy-Associated Toxicity: A Randomized Trial Protocol
Authors: Martínez Felipe , Taramasco Carla , Espinoza Manuel , Acevedo Johanna , Goic Carolina , Nervi Bruno
Published: March 2024

Chemotherapy requires careful monitoring, but traditional follow-up approaches face significant challenges that were highlighted by the COVID-19 pandemic. Hence, exploration into telemonitoring as an alternative emerged. The objective is to assess the impact of a telemonitoring platform that provides clinical data to physicians overseeing solid tumor patients, aiming to enhance the care experience. The methodology outlines a parallel-group randomized clinical trial involving recently diagnosed patients with solid carcinomas preparing for curative intent chemotherapy. Eligible adult patients diagnosed with specific carcinoma types and proficient in Spanish, possessing smartphones, will be invited to participate. They will be randomized using concealed allocation sequences into two groups: one utilizing a specialized smartphone application called Contigo for monitoring chemotherapy toxicity symptoms and accessing educational content, while the other receives standard care. Primary outcome assessment involves patient experience during chemotherapy using a standardized questionnaire. Secondary outcomes include evaluating severe chemotherapy-associated toxicity, assessing quality of life, and determining user satisfaction with the application. The research will adhere to intention-to-treat principles. This study has been registered at ClinicalTrials.gov (NCT06077123).
DengueFog: A Fog Computing-Enabled Weighted Random Forest-Based Smart Health Monitoring System for Automatic Dengue Prediction
Authors: Kukkar Ashima , Kumar Yugal , Sandhu Jasminder Kaur , Kaur Manjit , Walia Tarandeep Singh , Amoon Mohammed
Published: March 2024

Dengue is a distinctive and fatal infectious disease that spreads through female mosquitoes called Aedes aegypti. It is a notable concern for developing countries due to its low diagnosis rate. Dengue has the most astounding mortality level as compared to other diseases due to tremendous platelet depletion. Hence, it can be categorized as a life-threatening fever as compared to the same class of fevers. Additionally, it has been shown that dengue fever shares many of the same symptoms as other flu-based fevers. On the other hand, the research community is closely monitoring the popular research fields related to IoT, fog, and cloud computing for the diagnosis and prediction of diseases. IoT, fog, and cloud-based technologies are used for constructing a number of health care systems. Accordingly, in this study, a DengueFog monitoring system was created based on fog computing for prediction and detection of dengue sickness. Additionally, the proposed DengueFog system includes a weighted random forest (WRF) classifier to monitor and predict the dengue infection. The proposed system’s efficacy was evaluated using data on dengue infection. This dataset was gathered between 2016 and 2018 from several hospitals in the Delhi-NCR region. The accuracy, F-value, recall, precision, error rate, and specificity metrics were used to assess the simulation results of the suggested monitoring system. It was demonstrated that the proposed DengueFog monitoring system with WRF outperforms the traditional classifiers.
Restoring the Fluctuation–Dissipation Theorem in Kardar–Parisi–Zhang Universality Class through a New Emergent Fractal Dimension
Authors: Gomes-Filho Márcio S. , de Castro Pablo , Liarte Danilo B. , Oliveira Fernando A.
Published: March 2024

The Kardar–Parisi–Zhang (KPZ) equation describes a wide range of growth-like phenomena, with applications in physics, chemistry and biology. There are three central questions in the study of KPZ growth: the determination of height probability distributions; the search for ever more precise universal growth exponents; and the apparent absence of a fluctuation–dissipation theorem (FDT) for spatial dimension d>1. Notably, these questions were answered exactly only for 1+1 dimensions. In this work, we propose a new FDT valid for the KPZ problem in d+1 dimensions. This is achieved by rearranging terms and identifying a new correlated noise which we argue to be characterized by a fractal dimension dn. We present relations between the KPZ exponents and two emergent fractal dimensions, namely df, of the rough interface, and dn. Also, we simulate KPZ growth to obtain values for transient versions of the roughness exponent α, the surface fractal dimension df and, through our relations, the noise fractal dimension dn. Our results indicate that KPZ may have at least two fractal dimensions and that, within this proposal, an FDT is restored. Finally, we provide new insights into the old question about the upper critical dimension of the KPZ universality class.
Magnetic Black Hole Thermodynamics in an Extended Phase Space with Nonlinear Electrodynamics
Authors: Kruglov Sergey Il’ich
Published: March 2024

We study Einstein’s gravity coupled to nonlinear electrodynamics with two parameters in anti-de Sitter spacetime. Magnetically charged black holes in an extended phase space are investigated. We obtain the mass and metric functions and the asymptotic and corrections to the Reissner–Nordström metric function when the cosmological constant vanishes. The first law of black hole thermodynamics in an extended phase space is formulated and the magnetic potential and the thermodynamic conjugate to the coupling are obtained. We prove the generalized Smarr relation. The heat capacity and the Gibbs free energy are computed and the phase transitions are studied. It is shown that the electric fields of charged objects at the origin and the electrostatic self-energy are finite within the nonlinear electrodynamics proposed.
CNN-HT: A Two-Stage Algorithm Selection Framework
Authors: Xu Siyi , Liu Wenwen , Wu Chengpei , Li Junli
Published: March 2024

The No Free Lunch Theorem tells us that no algorithm can beat other algorithms on all types of problems. The algorithm selection structure is proposed to select the most suitable algorithm from a set of algorithms for an unknown optimization problem. This paper introduces an innovative algorithm selection approach called the CNN-HT, which is a two-stage algorithm selection framework. In the first stage, a Convolutional Neural Network (CNN) is employed to classify problems. In the second stage, the Hypothesis Testing (HT) technique is used to suggest the best-performing algorithm based on the statistical analysis of the performance metric of algorithms that address various problem categories. The two-stage approach can adapt to different algorithm combinations without the need to retrain the entire model, and modifications can be made in the second stage only, which is an improvement of one-stage approaches. To provide a more general structure for the classification model, we adopt Exploratory Landscape Analysis (ELA) features of the problem as input and utilize feature selection techniques to reduce the redundant ones. In problem classification, the average accuracy of classifying problems using CNN is 96%, which demonstrates the advantages of CNN compared to Random Forest and Support Vector Machines. After feature selection, the accuracy increases to 98.8%, further improving the classification performance while reducing the computational cost. This demonstrates the effectiveness of the first stage of the CNN-HT method, which provides a basis for algorithm selection. In the experiments, CNN-HT shows the advantages of the second stage algorithm as well as good performance with better average rankings in different algorithm combinations compared to the individual algorithms and another algorithm combination approach.
Exploration of Resonant Modes for Circular and Polygonal Chladni Plates
Authors: Val Baker Amira , Csanad Mate , Fellas Nicolas , Atassi Nour , Mgvdliashvili Ia , Oomen Paul
Published: March 2024

In general, sound waves propagate radially outwards from a point source. These waves will continue in the same direction, decreasing in intensity, unless a boundary condition is met. To arrive at a universal understanding of the relation between frequency and wave propagation within spatial boundaries, we explore the maximum entropy states that are realized as resonant modes. For both circular and polygonal Chladni plates, a model is presented that successfully recreates the nodal line patterns to a first approximation. We discuss the benefits of such a model and the future work necessary to develop the model to its full predictive ability.
Technological Tools in Higher Education: A Qualitative Analysis from the Perspective of Students with Disabilities
Authors: Fernández-Cerero José , Cabero-Almenara Julio , Montenegro-Rueda Marta
Published: March 2024

The integration of information and communication technologies (ICT) in education has emerged as a transformative element, contributing significantly to the establishment of more inclusive educational environments. In this context, understanding the impact of technological tools becomes crucial to identifying the opportunities and limitations that students encounter when incorporating these resources in university classrooms. The main objective of this research is to analyse the impact of ICT use in higher education, with a specific focus on the perceptions of students with disabilities. Information was collected through interviews with university students with disabilities. The results reveal both advantages and difficulties and underline the importance of designing and implementing technologies in an inclusive way. Key issues relating to accessibility and participation are addressed, providing valuable insights for improving inclusive higher education in the digital age.
Students’ Motivation and Engagement in the Implementation of Individual Development Plan for Underrepresented Minority (URM) Students in Undergraduate STEM Training Programs
Authors: Edwards Nishika , Goodwin Richard L. , Khalil Mohammed K. , Fowler Lauren A. , Nathaniel Thomas
Published: March 2024

Despite recent progress, statistics show an urgent need for growth in the numbers of underrepresented minority (URM) students in STEM fields. An individual development plan (IDP) has been used to assist Ph.D. trainees in exploring career paths, developing short- and long-term career goals, and creating action plans to achieve these goals. The National Institutes of Health (NIH) and many institutions require the completion of the IDP by graduate students, postdoctoral researchers, and junior faculty mentees to enhance career development. However, little information exists regarding how motivated and behaviorally engaged undergraduate URM undergraduate students are in using IDP as a tool to develop their STEM career pathway. In this study, researchers present data from the motivation levels and behavioral engagement factors that are associated with the effectiveness of the IDP with 20 URM students recruited for the REP Summer program. A total of 85% of students strongly agreed that the IDP was most effective in assessing and reflecting on their academic and professional goals. The mentorship needs were met by 80% of the students, while 75% of the students agreed that the IDP was very effective in helping to identify short-term and long-term goals for their undergraduate studies. Moreover, 70% of the students were satisfied with the IDP in developing an action plan, identifying short-term and long-term goals for their professional careers, and assessing their scientific skills, interests, and values. URM students are intrinsically and extrinsically motivated to implement the IDP and pursue careers in STEM. Findings suggest that URM students’ motivation and behavioral engagement levels impact the effectiveness of the implemented IDP with these students. There is a need to identify factors that enhance the effectiveness of the IDP to determine how to maximize the career development of URM students in STEM programs.
A Memorable Communication Method Based on Cryptographic Accumulator
Authors: Jiang Wenbao , Wang Yongpan , Ye Shuai
Published: March 2024

The traditional Internet has many security problems. It is difficult to guarantee the authenticity, integrity, and synchronization of message transmission, and it lacks a message-traceability mechanism, which is caused by its performance-oriented design. To address these problems, this paper proposes a memorable communication method based on cryptographic accumulators. In this method, both parties in the communication can verify the message data sent and received arbitrarily by virtue of the memory value. As long as a simple memory value comparison is performed, the strong consistency of all message data can be ensured. This method has the security advantages of synchronization, verification, traceability, and non-tamperability, as well as the performance advantages brought by batch signature and verification. In this paper, the memorable communication model, the memory function, and the memorable communication process are designed, and theoretical analysis shows that the memorable communication method has synchronization and traceability and can realize batch signature and authentication. In addition, a chain-key can be constructed based on a memory value to achieve key per-packet updating. Comparative analysis shows the transmission efficiency, traceability efficiency, and security performance of the memorable communication method.
Development of Autonomous Mobile Robot with 3DLidar Self-Localization Function Using Layout Map
Authors: Sasaki Minoru , Tsuda Yuki , Matsushita Kojiro
Published: March 2024

In recent years, there has been growing interest in autonomous mobile robots equipped with Simultaneous Localization and Mapping (SLAM) technology as a solution to labour shortages in production and distribution settings. SLAM allows these robots to create maps of their environment using devices such as Lidar, radar, and sonar sensors, enabling them to navigate and track routes without prior knowledge of the environment. However, the manual operation of these robots for map construction can be labour-intensive. To address this issue, this research aims to develop a 3D SLAM autonomous mobile robot system that eliminates the need for manual map construction by utilizing existing layout maps. The system includes a PC for self-position estimation, 3DLidar, a camera for verification, a touch panel display, and the mobile robot itself. The proposed SLAM method extracts stable wall point cloud information from 3DLidar, matches it with the wall surface information in the layout map, and uses a particle filter to estimate the robot’s position. The system also includes features such as route creation, tracking, and obstacle detection for autonomous movement. Experiments were conducted to compare the proposed system with conventional 3D SLAM methods. The results showed that the proposed system significantly reduced errors in self-positioning and enabled accurate autonomous movement on specified routes, even in the presence of slight differences in layout maps and obstacles. Ultimately, this research demonstrates the effectiveness of a system that can transport goods without the need for manual environment mapping, addressing labour shortages in such environments.
A Distributed Multi-Timescale Dispatch Strategy for a City-Integrated Energy System with Carbon Capture Power Plants
Authors: Liu Huanan , Lu Ruoci , Dou Zhenlan , Zhang Chunyan , Wang Songcen
Published: March 2024

In city-integrated energy systems containing electric–thermal multi-energy sources, the uncertainty of renewable energy sources and the fluctuation of loads challenge the safe, efficient, economic and stable operation of the integrated energy systems. This paper introduces a novel approach for the operation of a carbon capture plant/CHP with PV accommodation within a city-integrated energy system. The proposed strategy aims to maximize the utilization of photovoltaic (PV) power generation and carbon capture equipment, addressing issues related to small-scale CHP climbing constraints and short-term output regulation. Additionally, this paper presents a multi-timescale optimal scheduling strategy, which effectively addresses deviations caused by PV fluctuations and load changes. This was achieved through a detailed analysis of the CHP climbing constraints, carbon capture equipment operation and real-time characteristics of PV power generation. This paper introduces a fully distributed neural dynamics-based optimization algorithm designed to address multi-timescale optimization challenges. Utilizing rolling cycles, this algorithm computes both day-ahead and real-time scheduling outcomes for urban integrated energy systems. Theoretical analyses and numerical simulations were conducted to validate the precision and efficacy of the proposed model and algorithm. These analyses quantitatively evaluate the scheduling performance of PV power generation and carbon capture CHP systems across various timescales.
Efficient Framework to Manipulate Data Compression and Classification of Power Quality Disturbances for Distributed Power System
Authors: Syamsudin Mariana , Chen Cheng-I , Berutu Sunneng Sandino , Chen Yeong-Chin
Published: March 2024

There is some risk of power quality disturbances at many stages of production, transformation, distribution, and energy consumption. The cornerstone for dealing with power quality problems is the characterization of power quality disturbances (PQDs). However, past research has focused on a narrow topic: noise disruption, overfitting, and training time. A new strategy is suggested to address this problem that combines efficient one-dimensional dataset compression with the convolutional neural network (CNN) classification algorithm. First, three types of compression algorithms: wavelet transform, autoencoder, and CNN, are proposed to be evaluated. According to the IEEE-1159 standard, the synthetic dataset was built with fourteen different PQD types. Furthermore, the PQD classification procedure integrated compressed data with the CNN classification algorithm. Finally, the suggested method demonstrates that combining CNN compression and classification methods can efficiently recognize PQDs. Even in noisy environments, PQD signal processing achieved up to 98.25% accuracy and managed the overfitting.
Transient Synchronous Stability Analysis of Grid-Forming Photovoltaic Grid-Connected Inverters during Asymmetrical Grid Faults
Authors: He Wenwen , Yao Jun , Xu Hao , Zhong Qinmin , Xu Ruilin , Liu Yuming , Li Xiaoju
Published: March 2024

Compared with the traditional grid-following photovoltaic grid-connected converter (GFL-PGC), the grid-forming photovoltaic grid-connected converter (GFM-PGC) can provide voltage and frequency support for power systems, which can effectively enhance the stability of power electronic power systems. Consequently, GFM-PGCs have attracted great attention in recent years. When an asymmetrical short-circuit fault occurs in the power grid, GFM-PGC systems may experience transient instability, which has been less studied so far. In this paper, a GFM-PGC system is investigated under asymmetrical short-circuit fault conditions. A novel Q-V droop control structure is proposed by improving the traditional droop control. The proposed control structure enables the system to accurately control the positive- and negative-sequence reactive current without switching the control strategy during the low-voltage ride-through (LVRT) period so that it can meet the requirements of the renewable energy grid code. In addition, a dual-loop control structure model of positive- and negative-sequence voltage and current is established for the GFM-PGC system under asymmetrical short-circuit fault conditions. Based on the symmetrical component method, the composite sequence network of the system is obtained under asymmetrical short-circuit fault conditions, and positive- and negative-sequence power-angle characteristic curves are analyzed. The influence law of system parameters on the transient synchronous stability of positive- and negative-sequence systems is quantitatively analyzed through the equal area criterion. Finally, the correctness of the theoretical analysis is verified by simulation and hardware-in-the-loop experiments.
Advances in Wastewater Treatment, 2024
Authors: Ugrina Marin , Milojković Jelena
Published: March 2024

Water is undoubtedly the most important and invaluable natural resource that humans utilize [...]
Debt Sustainability Assessment in the Biogas Sector: Application of Interest Coverage Ratios in a Sample of Agricultural Firms in Italy
Authors: Iotti Mattia , Manghi Elisa , Bonazzi Giuseppe
Published: March 2024

The biogas sector in Europe and Italy is attracting growing investment, combining agricultural activity, the circular economy, and renewable energy production. Firms in the sector widely use debt capital and, for this reason, there is a need to evaluate the structure of investments, financing, and debt service capacity calculated by applying interest coverage ratios (ICRs). ICRs are widely used by banks in granting loans, and calculation of ICRs allows managers and policy makers to correctly evaluate firms’ performance in the sector. In this research, based on a sample of 160 observations, the structure of investments and sources of financing of firms in the biogas sector, operating in northern Italy, are analyzed. ICRs are calculated with different approaches to establish which ICRs provide the most reliable results in the application. The research analyzes the correlations and highlights significant differences between ICRs. The research highlights some important findings: (a) the NWC is negative in 109 out of 160 observations and, therefore, constitutes a source of financing in the majority of observations; (b) ICRs based on EBITDA and CF are above the threshold value of “1” in 143 and 145 observations, respectively, while ICRs based on EBIT, OCF, and UFCF are above the threshold value of “1” in 132, 133, and 122 observations, respectively. The research allows the conclusion that the ICRs based on EBITDA and CF tend to overestimate results; ICRs based on EBIT, OCF and UFCF are preferable, and can therefore be applied by managers, banks, and policy makers and be used as debt covenants. For the calculation of the repayment of the NFP, the research has highlighted that ICRs in which the cost of the debt is deducted from the numerator are preferable. The research can thus be usefully applied and expanded to other territories, or by considering a larger sample with the aim of inferring conclusions of general validity.
Modelling Public Intentions to Use Innovative EV Chargers Employing Hybrid Energy Storage Systems: A UK Case Study Based upon the Technology Acceptance Model
Authors: Jones Christopher R. , Elgueta Herman , Chudasama Nikita , Kaklamanou Daphne , East Duncan , Cruden Andrew J.
Published: March 2024

The current study investigates public intentions to use an innovative, off-grid renewably powered EV charging technology called FEVER (Future Electric Vehicle Energy networks supporting Renewables). We report the findings of a questionnaire-based survey (QBS) conducted at a zoo in the south of England, exploring the prospect of demonstrating FEVER. The QBS was designed around a context-specific technology acceptance model (TAM) and administered both face-to-face (n = 63) and online (n = 158) from April to May 2023. The results indicate that most participants were willing to pay to use FEVER, particularly where revenue would benefit the zoo. The participants agreed they intended to use the chargers, and that they would be useful and easy to use. The participants agreed that there would be normative pressure to use the chargers, but that their use would be enjoyable. Of greatest concern was that the chargers would be blocked by others. The participants were ambivalent about concerns over charging duration and charge sufficiency. Structural equation modelling confirmed that the context-specific TAM explained 58% of people’s use intentions. The core relationships of the TAM were confirmed, with ‘perceived usefulness’ additionally predicted by subjective norms and ‘perceived ease of use’ additionally predicted by anticipated enjoyment. Of the other variables, only concern that the chargers would be blocked was retained as a marginal predictor of ‘perceived ease of use’. The implications of these findings for the co-design and demonstration of FEVER are discussed.
Editorial: Advances in Nuclear Fusion Energy and Cross-Cutting Technologies
Authors: Palermo Iole
Published: March 2024

The current energy model, which is based largely on the use of fossil fuels and has a direct influence on global warming and climate change, presents serious problems of unsustainability in the long term [...]
Fuzzy Super-Twisting Sliding Mode Controller for Switched Reluctance Wind Power Generator in Low-Voltage DC Microgrid Applications
Authors: Touati Zeineb , Mahmoud Imed , Araújo Rui Esteves , Khedher Adel
Published: March 2024

There is limited research focused on achieving optimal torque control performance of Switched Reluctance Generators (SRGs). The majority of existing studies tend to favor voltage or power control strategies. However, a significant drawback of SRGs is their susceptibility to high torque ripple. In power generation systems, torque ripple implicates fluctuations in the generated power of the generator. Moreover, high torque ripple can lead to mechanical vibrations and noise in the powertrain, impacting the overall system performance. In this paper, a Torque Sharing Function (TSF) with Indirect Instantaneous Torque Control (IITC) for SRG applied to Wind Energy Conversion Systems (WECS) is proposed to minimize torque ripple. The proposed method adjusts the shared reference torque function between the phases based on instantaneous torque, rather than the existing TSF methods formulated with a mathematical expression. Additionally, this paper introduces an innovative speed control scheme for SRG drive using a Fuzzy Super-Twisting Sliding Mode Command (FSTSMC) method. Notably robust against parameter uncertainties and payload disturbances, the proposed scheme ensures finite-time convergence even in the presence of external disturbances, while effectively reducing chattering. To assess the effectiveness of the proposed methods, comprehensive comparisons are made with traditional control techniques, including Proportional–Integral (PI), Integral Sliding Mode Control (ISMC), and Super-Twisting Sliding Mode Control (STSMC). The simulation results, obtained using MATLAB®/SIMULINK® under various speeds and mechanical torque conditions, demonstrate the superior performance and robustness of the proposed approaches. This study presents a thorough experimental analysis of a 250 W four-phase 8/6 SRG. The generator was connected to a DC resistive load, and the analysis focuses on assessing its performance and operational characteristics across different rotational speeds. The primary objective is to validate and confirm the efficacy of the SRG under varying conditions.
Optimizing Peer-to-Peer Energy Transactions: Determining the Allowable Maximum Trading Power for Participants
Authors: Angaphiwatchawal Pikkanate , Chaitusaney Surachai
Published: March 2024

This paper presents a comprehensive study on the impacts of peer-to-peer (P2P) energy markets on distribution systems, specifically focusing on voltage, power loss, and congestion. While P2P energy markets create opportunities for direct trading between prosumers and consumers, ensuring compliance with distribution system constraints remains a challenge. This paper proposes an iterative method and graphical interpretation in order to assess complex interactions, addressing the persistent issue of network constraints. Additionally, this paper proposes a method to determine distribution locational marginal prices (DLMPs) for real-time traditional energy markets. This ensures effective coordination among sellers, buyers, and the distribution system operator. The proposed method aims to prevent negative impacts on distribution system operation via the determination of the allowable maximum trading power (MTP), ensuring empirical validity and practical implementation via operating conditions and forecast errors, thus distinguishing it from prior studies. This paper also establishes a model for P2P energy market interactions, utilizing linear estimations for efficient DLMP updates. The contributions of this paper enhance the understanding and operation of P2P energy markets, and is supported by simulation results validating the proposed method.
Cooperative Application of Onboard Energy Storage and Stationary Energy Storage in Rail Transit Based on Genetic Algorithm
Authors: Kong Deshi , Miyatake Masafumi
Published: March 2024

The transition towards environmentally friendly transportation solutions has prompted a focused exploration of energy-saving technologies within railway transit systems. Energy Storage Systems (ESS) in railway transit for Regenerative Braking Energy (RBE) recovery has gained prominence in pursuing sustainable transportation solutions. To achieve the dual-objective optimization of energy saving and investment, this paper proposes the collaborative operation of Onboard Energy-Storage Systems (OESS) and Stationary Energy-Storage Systems (SESS). In the meantime, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied to optimize the ESS capacity and reduce its redundancy. The simulation is programmed in MATLAB. The results show that the corporation of OESS and SESS offers superior benefits (70 kWh energy saving within 30 min operation) compared to using SESS alone. Moreover, the OESS plays a significant role, emphasizing its significance in saving energy and investment, therefore presenting a win–win scenario. It is recommended that the capacity of OESS be designed to be two to three times that of SESS. The findings contribute to the ongoing efforts in developing more sustainable and energy-efficient transportation solutions, with implications for the railway industry’s investment and broader initiatives in energy saving for sustainable urban mobility.
New Aspects of the Pulse Combustion Process
Authors: Gieras Marian , Trzeciak Adrian Marek
Published: March 2024

Pulse combustion is an attractive yet still little-known form of combustion that can be successfully used in many industrial applications. Experimental studies show that the course of the combustion process in the valveless pulse combustion chamber is conditioned by the process of creating a well-mixed fuel–air mixture inside the chamber. In the paper, numerical calculations were carried out for selected operating conditions of the pulse chamber and compared with experimental results. This allowed for a better understanding and interpretation of the course of the pulsating combustion process itself. The role and importance of the rate of changes in the volume of the combustible mixture zone in the process of improving the efficiency of the combustion process were determined, and the reasons for changes in the pulsation frequency of the combustion process were also explained.