bluuebunny/crossref_metadata_2025 huggingface dataset:
A Prediction Model for the Unconfined Compressive Strength of Pervious Concrete Based on Mix Design and Compaction Energy Variables Using the Response Surface Methodology
Authors: Adresi Mostafa , Yamani Alireza , Tabarestani Mojtaba Karimaei , Nalon Gustavo Henrique
Published: September 2024

Pervious concrete is desirable for water drainage in building systems, but achieving both high strength and good permeability can be challenging. Also, the importance of compaction energy is significant in determining the efficiency of pervious concrete. However, research on the development of unconfined compressive strength (UCS) prediction models for pervious concrete materials that incorporate compaction energy parameters remains unexplored. Therefore, this study aimed to balance strength and permeability while optimizing the compaction energy required for concrete production. A Central Composite Design (CCD) was used to design experiments within the response surface methodology (RSM) and evaluate the UCS, the porosity and permeability of pervious concrete specimens produced with varying cement content (280.00–340.00 kg/m3), the water-to-cement ratio (0.27–0.33), the aggregate-to-cement ratio (4:1–4.5:1), and compaction energy (represented by VeBe compaction time, 13–82 s). A regression model with goodness of fit (R2adjusted > 0.87) was calibrated to estimate the UCS of pervious concrete as a function of mix design parameters and VeBe compaction time (Tvc). This model can potentially guide field practices by recommending compaction strategies and mix designs for pervious concrete, achieving a desirable balance between mechanical strength and hydraulic permeability for building construction applications.
Fibroblast Growth Factor 2 (FGF2) Activates Vascular Endothelial Growth Factor (VEGF) Signaling in Gastrointestinal Stromal Tumors (GIST): An Autocrine Mechanism Contributing to Imatinib Mesylate (IM) Resistance
Authors: Boichuk Sergei , Dunaev Pavel , Galembikova Aigul , Valeeva Elena
Published: September 2024

We showed previously that the autocrine activation of the FGFR-mediated pathway in GIST lacking secondary KIT mutations was a result of the inhibition of KIT signaling. We show here that the FGF2/FGFR pathway regulates VEGF-A/VEGFR signaling in IM-resistant GIST cells. Indeed, recombinant FGF2 increased the production of VEGF-A by IM-naive and resistant GIST cells. VEGF-A production was also increased in KIT-inhibited GIST, whereas the neutralization of FGF2 by anti-FGF2 mAb attenuated VEGFR signaling. Of note, BGJ 398, pan FGFR inhibitor, effectively and time-dependently inhibited VEGFR signaling in IM-resistant GIST T-1R cells, thereby revealing the regulatory role of the FGFR pathway in VEGFR signaling for this particular GIST cell line. This also resulted in significant synergy between BGJ 398 and VEGFR inhibitors (i.e., sunitinib and regorafenib) by enhancing their pro-apoptotic and anti-proliferative activities. The high potency of the combined use of VEGFR and FGFR inhibitors in IM-resistant GISTs was revealed by the impressive synergy scores observed for regorafenib or sunitinib and BGJ 398. Moreover, FGFR1/2 and VEGFR1/2 were co-localized in IM-resistant GIST T-1R cells, and the direct interaction between the aforementioned RTKs was confirmed by co-immunoprecipitation. In contrast, IM-resistant GIST 430 cells expressed lower basal levels of FGF2 and VEGF-A. Despite the increased expression VEGFR1 and FGFR1/2 in GIST 430 cells, these RTKs were not co-localized and co-immunoprecipitated. Moreover, no synergy between FGFR and VEGFR inhibitors was observed for the IM-resistant GIST 430 cell line. Collectively, the dual targeting of FGFR and VEGFR pathways in IM-resistant GISTs is not limited to the synergistic anti-angiogenic treatment effects. The dual inhibition of FGFR and VEGFR pathways in IM-resistant GISTs potentiates the proapoptotic and anti-proliferative activities of the corresponding RTKi. Mechanistically, the FGF2-induced activation of the FGFR pathway turns on VEGFR signaling via the overproduction of VEGF-A, induces the interaction between FGFR1/2 and VEGFR1, and thereby renders cancer cells highly sensitive to the dual inhibition of the aforementioned RTKs. Thus, our data uncovers the novel mechanism of the cross-talk between the aforementioned RTKs in IM-resistant GISTs lacking secondary KIT mutations and suggests that the dual blockade of FGFR and VEGFR signaling might be an effective treatment strategy for patients with GIST-acquired IM resistance via KIT-independent mechanisms.
Curcumin-Dichloroacetate Hybrid Molecule as an Antitumor Oral Drug against Multidrug-Resistant Advanced Bladder Cancers
Authors: Gupta Kunj Bihari , Taylor Truett L. , Panda Siva S. , Thangaraju Muthusamy , Lokeshwar Bal. L.
Published: September 2024

Tumor cells produce excessive reactive oxygen species (ROS) but cannot detoxify ROS if they are due to an external agent. An agent that produces toxic levels of ROS, specifically in tumor cells, could be an effective anticancer drug. CMC-2 is a molecular hybrid of the bioactive polyphenol curcumin conjugated to dichloroacetate (DCA) via a glycine bridge. The CMC-2 was tested for its cytotoxic antitumor activities and killed both naïve and multidrug-resistant (MDR) bladder cancer (BCa) cells with equal potency (<1.0 µM); CMC-2 was about 10–15 folds more potent than curcumin or DCA. Growth of human BCa xenograft in mice was reduced by >50% by oral gavage of 50 mg/kg of CMC-2 without recognizable systemic toxicity. Doses that used curcumin or DCA showed minimum antitumor effects. In vitro, the toxicity of CMC-2 in both naïve and MDR cells depended on increased intracellular ROS in tumor cells but not in normal cells at comparable doses. Increased ROS caused the permeabilization of mitochondria and induced apoptosis. Further, adding N-Acetyl cysteine (NAC), a hydroxyl radical scavenger, abolished excessive ROS production and CMC-2’s cytotoxicity. The lack of systemic toxicity, equal potency against chemotherapy -naïve and resistant tumors, and oral bioavailability establish the potential of CMC-2 as a potent drug against bladder cancers.
Cellular and Microbial In Vitro Modelling of Gastrointestinal Cancer
Authors: Žukauskaitė Kristina , Li Melissa , Horvath Angela , Jarmalaitė Sonata , Stadlbauer Vanessa
Published: September 2024

Human diseases are multifaceted, starting with alterations at the cellular level, damaging organs and their functions, and disturbing interactions and immune responses. In vitro systems offer clarity and standardisation, which are crucial for effectively modelling disease. These models aim not to replicate every disease aspect but to dissect specific ones with precision. Controlled environments allow researchers to isolate key variables, eliminate confounding factors and elucidate disease mechanisms more clearly. Technological progress has rapidly advanced model systems. Initially, 2D cell culture models explored fundamental cell interactions. The transition to 3D cell cultures and organoids enabled more life-like tissue architecture and enhanced intercellular interactions. Advanced bioreactor-based devices now recreate the physicochemical environments of specific organs, simulating features like perfusion and the gastrointestinal tract’s mucus layer, enhancing physiological relevance. These systems have been simplified and adapted for high-throughput research, marking significant progress. This review focuses on in vitro systems for modelling gastrointestinal tract cancer and the side effects of cancer treatment. While cell cultures and in vivo models are invaluable, our main emphasis is on bioreactor-based in vitro modelling systems that include the gut microbiome.
The Real-World Efficacy and Safety of Direct-Acting Antivirals for Chronic Hepatitis C in Patients Active Malignancies
Authors: Dąbrowska Maria , Jaroszewicz Jerzy , Sitko Marek , Janocha-Litwin Justyna , Zarębska-Michaluk Dorota , Janczewska Ewa , Lorenc Beata , Tudrujek-Zdunek Magdalena , Parfieniuk-Kowerda Anna , Klapaczyński Jakub , Berak Hanna , Socha Łukasz , Dobracka Beata , Dybowska Dorota , Mazur Włodzimierz , Ważny Łukasz , Flisiak Robert
Published: September 2024

Background: Over the past years, the introduction of direct-acting antivirals (DAAs) revolutionized chronic hepatitis C treatment. We aimed to characterize and assess treatment efficacy in three specific groups of patients treated with DAAs: those with active solid malignant tumors (SMTs), hematological diseases (HDs) and hepatocellular carcinomas (HCCs). Methods: A total of 203 patients with active oncological disease (SMT n = 61, HD = 67, HCC n = 74) during DAA treatment in 2015–2020 selected from the EpiTer-2 database were analyzed retrospectively and compared to 12,983 patients without any active malignancy. Results: Extrahepatic symptoms were more frequent in HD patients (17.2% vs. SMT = 10.3%, HCC = 8.2%, without = 7.8%, p = 0.004). HCC patients characterized with the highest ALT activity (81 IU/L vs. SMT = 59.5 IU/L, HD = 52 IU/L, without = 58 IU/L, p = 0.001) more often had F4 fibrosis as well (86.11% vs. SMT = 23.3%, HD = 28.8%, controls = 24.4%, p = 0.001). A significant majority of subjects in HCC, HD and SMT populations completed the full treatment plan (HCC = 91%; n = 67, HD = 97%; n = 65, SMT = 100%; n = 62). Concerning the treatment efficacy, the overall sustained virologic response, excluding non-virologic failures, was reported in 93.6% HD, 90.16% SMT and 80.6% in HCC patients. Conclusions: As presented in our study, DAA therapy has proven to be highly effective and safe in patients with active SMTs and HDs. However, therapy discontinuations resulting from liver disease progression remain to be the major concern in HCC patients.
Clinical Interest in Exome-Based Analysis of Somatic Mutational Signatures for Non-Small Cell Lung Cancer
Authors: Peroz Morgane , Mananet Hugo , Roussot Nicolas , Kaderbhai Courèche Guillaume , Derangère Valentin , Truntzer Caroline , Ghiringhelli François
Published: September 2024

Background: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality. This study investigates the clinical interest of whole exome sequencing (WES) for analyzing somatic mutational signatures in patients with advanced or metastatic NSCLC treated with the current standard of care. Methods: Exome sequencing data and clinical characteristics from 132 patients with advanced or metastatic NSCLC were analyzed. Somatic mutational signatures including single base substitutions (SBSs), double base substitutions (DBSs), and copy number signatures were evaluated. Structural variations including tumor mutational burden (TMB), the number of neoantigens, TCR clonality, homologous recombination deficiency (HRD), copy number alterations (CNAs), and microsatellite instability (MSI) score were determined. The association between these genomic features, NSCLC subtypes, and patient outcomes (progression-free and overall survival) was evaluated. Conclusions: Exome sequencing offers valuable insights into somatic mutational signatures in NSCLC. This study identified specific signatures associated with a poor response to immune checkpoint inhibitor (ICI) therapy and chemotherapy, potentially aiding treatment selection and identifying patients unlikely to benefit from these approaches.
Set When the Sun Rises, Rise When the Sun Sets: Climate Impact on Health, Safety, and Wellbeing of Smallholder Farmers in Vietnam
Authors: Dally Miranda , Tran Thuy Thi Thu , Nguyen Thanh Le Nhat , Nguyen Quynh , Newman Lee S. , Van Dyke Mike , Tamayo-Ortiz Marcela , Crooks James , Krisher Lyndsay , Cherewick Megan
Published: September 2024

Vietnam is a country most at risk for experiencing climate change effects, especially increasing temperatures. Agricultural production is one of the biggest contributors to Vietnam’s economy. Recent research has explored how climate change will impact agriculture in Vietnam. However, the impact of climate change to the health, safety, and wellbeing of Vietnamese farmers is often overlooked. In this study, we conducted five focus groups with 46 farmers representing three provinces of Vietnam. We used a convergent mixed-methods design and a Total Worker Health® framework to assess how farmers in Vietnam experience climate-change-related hazards and describe how famers associate these hazards with impacts to their health, safety, and wellbeing. Multi-dimensional scaling suggests farmers conceptualize hazards separately from health, safety, and wellbeing outcomes, but a thematic analysis of our data indicated that farmers perceive both direct and indirect impacts of climate change to their health, safety, and wellbeing. Direct impacts of climate change described included physical health effects such as heat stress. Indirect impacts included mental health stressors due to productivity demands. Gaps in available health and safety trainings for farmers were also identified. This project demonstrates the need to co-develop safety and health trainings with farmers. System-level approaches both at the societal and community levels are needed. The local governments, cooperatives, Women’s Unions, and Farmers’ Unions are trusted sources of information that could implement and disseminate these trainings.
Study of Properties of Water-Dispersion Paint and Varnish Compositions with the Content of Modified Mineral Filler
Authors: Nurlybayev Ruslan E. , Kuldeyev Erzhan I. , Altayeva Zaure N. , Zhumadilova Zhanar O. , Yestemessova Axaya S. , Orynbekov Yelzhan S.
Published: September 2024

This article presents the results of research work devoted to improving the characteristics of paint and varnish coatings based on aqueous dispersions of polyacrylates; it is proposed to modify them by introducing mineral raw materials as fillers and hydrated lime, with subsequent processing in a vortex layer apparatus. The introduction of activated diatomite does not cause the deterioration of covering power, adhesion or an increase in the porosity of the paint material. The modification of coatings contributes to an increase in their operational properties, which can be associated with a reduction in the free volume in the composite and the formation of polymer boundary layers with modified physical and chemical properties. The aim of this study is to obtain a water-dispersion paint and varnish composition containing modified diatomite on a polyacrylate basis and, subsequently, study its main physical and mechanical parameters. The work has been carried out by the following method: determination of porosity, adhesion, elasticity and covering power of the control composition; determination of porosity, adhesion, elasticity and covering power of the obtained composites using modified filler; investigation of the influence of radiation on the infrared spectrum of the paint coating surface using a FLIRB620 thermal imager. As a result of this research work, it was noticed that the modification of water dispersions with silica-activated diatomite helps to eliminate the main disadvantages of materials and coatings based on acrylate binders—low water resistance and low physical and mechanical characteristics. The introduction of modified diatomite into water-emulsion paint on an acrylate base does not lead to the deterioration of the main performance characteristics of paint coatings—porosity, adhesion, elasticity and covering.
Preparation of Robust Superhydrophobic Coatings Using Hydrophobic and Tough Micro/Nano Particles
Authors: Feng Tianyi , Liu Yifan , Ye Siyan , Sheng Liping , Wu Binrui , Huang Lingcai
Published: September 2024

Superhydrophobic nanocomposite coatings, prepared using adhesive and fillers, offer advantages including ease of fabrication and suitability for large-scale applications, but compared with other types of artificial superhydrophobic surfaces, poor durability still limits these surfaces from practical applications. The utilization of micro/nanoscale particles with both intrinsic hydrophobicity and robust mechanical properties to prepare coatings should significantly contribute to enhanced durability. Herein, rough and hydrophobic particles with micro/nano hierarchical structures were prepared at first, and robust superhydrophobic surfaces were fabricated using the prepared particles and additional nanoparticles. The initially prepared particles formed a rough framework of the coating, while additional nanoparticles provided inevitable nanoscale structures. A series of mechanical tests were carried out to validate the durability, and the surface with 20 wt.% NPs exhibited the best performance, withstanding 30 tape peeling tests, a 2.47 m sandpaper rubbing test (at a pressure of 5 kPa), the impact of 200 g of grit dropped from a height of 20 cm, and a 2 h acidic immersion. These appealing materials may attract attention for self-cleaning, high-speed water impact resistance, anti-icing, and anti-fouling applications in the coatings industry.
Integration of Self-Assembled Monolayers for Cobalt/Porous Low-k Interconnects
Authors: Cheng Yi-Lung , Kao Joe , Zhang Hao-Wei , Liao Bo-Jie , Chen Giin-Shan , Fang Jau-Shiung
Published: September 2024

The integration of self-assembled monolayers (SAM) into cobalt (Co)/porous low-dielectric-constant (low-k) dielectric interconnects is studied in terms of electrical characteristics and reliability in this work. Experimental results indicated that SAM derived from 3-aminopropyltrimethoxysilane (APTMS) improved breakdown field, time-dependent dielectric breakdown, and adhesion for Co/porous low-k integrated interconnects. However, the improvement magnitude was not large as compared to SAM in the Cu/porous low-k integration. Therefore, the integration of SAM into Co/porous low-k interconnects has a positive effect; however, in order to further promote the efficiency of SAM for Co/porous low-k interconnects, the option of precursors for the growth of SAM is required.
SLACPSS: Secure Lightweight Authentication for Cyber–Physical–Social Systems
Authors: Abed Ahmed Zedaan M. , Abdelkader Tamer , Hashem Mohamed
Published: September 2024

The concept of Cyber–Physical–Social Systems (CPSSs) has emerged as a response to the need to understand the interaction between Cyber–Physical Systems (CPSs) and humans. This shift from CPSs to CPSSs is primarily due to the widespread use of sensor-equipped smart devices that are closely connected to users. CPSSs have been a topic of interest for more than ten years, gaining increasing attention in recent years. The inclusion of human elements in CPS research has presented new challenges, particularly in understanding human dynamics, which adds complexity that has yet to be fully explored. CPSSs are a base class and consist of three basic components (cyberspace, physical space, and social space). We map the components of the metaverse with that of a CPSS, and we show that the metaverse is an implementation of a Cyber–Physical–Social System (CPSS). The metaverse is made up of computer systems with many elements, such as artificial intelligence, computer vision, image processing, mixed reality, augmented reality, and extended reality. It also comprises physical systems, controlled objects, and human interaction. The identification process in CPSSs suffers from weak security, and the authentication problem requires heavy computation. Therefore, we propose a new protocol for secure lightweight authentication in Cyber–Physical–Social Systems (SLACPSSs) to offer secure communication between platform servers and users as well as secure interactions between avatars. We perform a security analysis and compare the proposed protocol to the related previous ones. The analysis shows that the proposed protocol is lightweight and secure.
Crystal Growth of LiNa5Mo9O30 Crystals of High Optical Quality
Authors: Khokhlov Nikolai , Grishchenko Ivan , Shevelkina Ekaterina , Bindyug Denis , Barkanova Ekaterina , Denisov Dmitry , Demushkin Dmitry , Telegin Ivan , Yezhikova Ekaterina , Avetissov Igor , Avetisov Roman , Konyashkin Alexey , Ryabushkin Oleg
Published: September 2024

The bulk of the LiNa5Mo9O30 (LNM) crystals were successfully grown in the [010] and [001] directions without internal inclusions and cracks, using the Czochralski method with a low temperature gradient. The crystal grown in the [010] direction showed a tendency to twinning. The crystal grown in the [001] direction demonstrated high structural perfection (FWHM = 13″) for the (001) plane and high optical quality Δn ≈ 2 × 10−5. The laser-induced damage threshold was measured along a, b and c axes and was 12.2, 27.0 and 27.5 J/cm2, respectively. The thermo-optical coefficient dn/dT was measured for the main crystallographic axes, which was −5.75 × 10−6, −20.2 × 10−6 and 3.65 × 10−6 K−1 along the a, b and c axes, respectively. The second harmonic generation (SHG) was conducted in the crystalline LNM sample. The maximum efficiency value of 3.5% at a pump power of 12 W was achieved.
Current and Future Distribution of the Cataglyphis nodus (Brullé, 1833) in the Middle East and North Africa
Authors: Kalarikkal Remya Kottarathu , Park Hotaek , Georgiadis Christos , Guénard Benoit , Economo Evan P. , Kim Youngwook
Published: September 2024

Climate change is a major threat to the Middle East and North Africa (MENA) region, which can cause significant harm to its plant and animal species. We predicted the habitat distribution of Cataglyphis nodus (Brullé, 1833) in MENA using MaxEnt models under current and future climate conditions. Our analysis indicates that the cooler regions of the MENA are projected to experience temperature increases of 1–2 °C by 2040 and 2–4 °C by the 2070s. Similarly, the warmer regions may anticipate rises of 0.5–2 °C by 2040 and 2–4 °C by the 2070s. MaxEnt model results for the current climate show good agreement with observations (mean area under the curve value of 0.975 and mean true statistical skill value of 0.8), indicating good potential habitat suitability for C. nodus. Significant factors affecting habitat suitability are elevation, mean monthly precipitation of the coldest quarter, temperature seasonality, and precipitation amount of the driest month. The research predicts that under Shared Socioeconomic Pathway (SSP) 1.2.6, the habitat suitability area may increase by 6% in 2040, while SSP 3.7.0 (0.3%) and SSP 5.8.5 (2.6%) predict a decrease. For 2070, SSP 5.8.5 predicts a 2.2% reduction in habitat suitability, while SSP 1.2.6 (0.4%) and SSP 3.7.0 (1.3%) predict slight increases. The results provide insight into the potential impacts of climate change on the species and regional biodiversity changes associated with the projected species distribution.
Can Selected Parameters of Brain Injury Reflect Neuronal Damage in Smoldering Multiple Sclerosis?
Authors: Niedziela Natalia , Nowak-Kiczmer Maria , Malciene Lina , Stasiołek Mariusz , Zalejska-Fiolka Jolanta , Czuba Zenon P. , Niedziela Jacek T. , Szczygieł Jarosław , Lubczyński Michał , Adamczyk-Sowa Monika
Published: September 2024

Background: Inflammatory demyelination and impaired recovery processes result in permanent neurodegeneration and neurological disability in patients with multiple sclerosis (MS). In terms of smoldering MS, chronic neuroinflammation develops in the early period of the disease and leads to confirmed disability accumulation. There is a great need to identify biomarkers of neurodegeneration and disease progression. Methods: A single-center prospective observational study was performed. The median age of the patients was 40 (31–52) years. Women comprised 64% of the study population. We evaluated the concentrations of the parameters of brain injury (NF-H, GFAP, S100B and UCHL1) in the cerebrospinal fluid (CSF) and the selected interleukins (ILs) in serum of 123 relapsing–remitting MS (RRMS) and 88 progressive MS (PMS) patients. Results: The levels of GFAP, S100B and UCHL were higher in the PMS group than the RRMS group, in contrast to the levels of NF-H. We observed a positive correlation between the selected pro-inflammatory cytokines and the parameters of brain injury. The Expanded Disability Status Scale (EDSS) score increased with GFAP and NF-H levels and was correlated with the selected ILs. The concentrations of S100B, UCHL1 and NF-H reflected the duration of MS symptoms. Conclusions: The levels of brain injury parameters in the CSF and the selected serum ILs in MS patients seem to be promising biomarkers to determine neurodegeneration and neuroinflammation in smoldering MS. Further studies are warranted in this respect.
Optical Methods for Optimizing Fluorescence Imaging Field of View and Image Quality in Surgical Guidance Procedures
Authors: Seo Jeongmin , Park Jina , Yoon Kicheol , Lee Sangyun , Kim Minchan , Ryu Seung Yeob , Kim Kwang Gi
Published: September 2024

Cancer surgery is aimed at complete tumor resection and accurate lymph node detection. However, numerous blood vessels are distributed within the tumor, and the colors of the tumor, blood vessels, and lymph nodes are similar, making observations with the naked eye difficult. Therefore, tumors, blood vessels, and lymph nodes can be monitored via color classification using an operating microscope to induce fluorescence emission. However, as the beam width of the LED required to induce fluorescence emission is narrow and the power loss of the beam is significant at a certain working distance, there are limitations to inducing fluorescence emission, and light reflection occurs in the observation image, obstructing the view of the observation area. Therefore, the removal of reflected light is essential to avoid missing the diagnosis of the lesion under observation. This paper proposes the use of a beam mirror and polarizing filter to increase the beam width and beam intensity. The refraction and reflection effects of the beam were utilized using the beam mirror, and the rotation angle of the polarizing filter was adjusted to remove light reflection. Consequently, the minimum beam power using the beam mirror was 10.9 mW, the beam width was doubled to 40.2°, and more than 98% of light reflection was removed at 90° and 270°. With light reflection effectively eliminated, clear observation of lesions is possible. This method is expected to be used effectively in surgical, procedural, and diagnostic departments.
Drone-Assisted Multimodal Logistics: Trends and Research Issues
Authors: Kim Kyunga , Kim Songi , Kim Junsu , Jung Hosang
Published: September 2024

This study explores the evolving trends and research issues in the field of drone-assisted multimodal logistics over the past two decades. By employing various text-mining techniques on related research publications, we identify the most frequently investigated topics and research issues within this domain. Specifically, we utilize titles, abstracts, and keywords from the collected studies to perform both Latent Dirichlet Allocation techniques and Term Frequency-Inverse Document Frequency analysis, which help in identifying latent topics and the core research themes within the field. Our analysis focuses on three primary categories of drone-assisted logistics: drone–truck, drone–ship, and drone–robot systems. The study aims to uncover which latent topics have been predominantly emphasized in each category and to highlight the distinct differences in research focuses among them. Our findings reveal specific trends and gaps in the existing literature, providing a clear roadmap for future research directions in drone-assisted multimodal logistics. This targeted analysis not only enhances our understanding of the current state of the field but also identifies critical areas that require further investigation to advance the application of drones in logistics.
Achieving Robust Learning Outcomes in Autonomous Driving with DynamicNoise Integration in Deep Reinforcement Learning
Authors: Shi Haotian , Chen Jiale , Zhang Feijun , Liu Mingyang , Zhou Mengjie
Published: September 2024

The advancement of autonomous driving technology is becoming increasingly vital in the modern technological landscape, where it promises notable enhancements in safety, efficiency, traffic management, and energy use. Despite these benefits, conventional deep reinforcement learning algorithms often struggle to effectively navigate complex driving environments. To tackle this challenge, we propose a novel network called DynamicNoise, which was designed to significantly boost the algorithmic performance by introducing noise into the deep Q-network (DQN) and double deep Q-network (DDQN). Drawing inspiration from the NoiseNet architecture, DynamicNoise uses stochastic perturbations to improve the exploration capabilities of these models, thus leading to more robust learning outcomes. Our experiments demonstrated a 57.25% improvement in the navigation effectiveness within a 2D experimental setting. Moreover, by integrating noise into the action selection and fully connected layers of the soft actor–critic (SAC) model in the more complex 3D CARLA simulation environment, our approach achieved an 18.9% performance gain, which substantially surpassed the traditional methods. These results confirmed that the DynamicNoise network significantly enhanced the performance of autonomous driving systems across various simulated environments, regardless of their dimensionality and complexity, by improving their exploration capabilities rather than just their efficiency.
Is the Nexus between Gender Diversity and Firm Financial Distress Moderated by CEO Duality?
Authors: Khan Muhammad Tahir , Ahmad Waqar , Khan Sajjad Nawaz , Antohi Valentin Marian , Fortea Costinela , Zlati Monica Laura
Published: September 2024

This study examines the impact of gender diversity in the positions of board commissioners, executive directors, and audit committee members on the financial performance of firms experiencing financial trouble. It also evaluates whether the presence of a CEO with multiple responsibilities moderates this relationship. The analysis encompassed 224 publicly traded companies from the non-financial sector, spanning the years 2012 to 2021. The study employed the dynamic panel model system GMM to address issues of endogeneity, simultaneity, and heterogeneity in the data. The findings indicate that the presence of women on supervisory boards and in senior positions has a substantial impact. Companies with a higher number of female board members have reduced financial hardship among Malaysian listed enterprises. Female directors exhibit a greater level of caution and risk aversion while participating in management choices, which is a significant conclusion. Research indicates that the majority of financial variables are inherently endogenous, so dynamic models are better suited for analyzing the interaction between these variables. This study also presents the notable correlation between gender diversity on boards of management, CEO duality, and financial difficulty.
Exploring a Synchronous Hybrid Observation Approach for Supporting Student Teachers during School Placements
Authors: Agnew Annie , Kearney Matthew , Ó Grádaigh Seán , Mac Mahon Brendan , Connolly Cornelia
Published: September 2024

This article presents findings from an international study examining a synchronous hybrid approach for observing and supporting student teachers on their school placement. This novel approach emerged from previous studies conducted during the COVID-19 pandemic and involves university tutors synchronously supervising student teachers from two locations: one tutor face-to-face in a school-based classroom and another virtually, from a remote setting such as a university campus. The qualitative case study adopts a focus group method to explore the views of participating school placement tutors from universities in Ireland and Australia about the benefits and challenges of this approach. Findings suggest that this new approach enhances supervisors’ observation and feedback practices and enables enriched collaboration and professional dialogue between student teachers and their tutors. Future research directions are also shared to advance the field.
A New Cascaded Multilevel Inverter for Modular Structure and Reduced Passive Components
Authors: Das Durbanjali , Mahato Bidyut , Chandan Bikramaditya , Joshi Hitesh , Mahto Kailash Kumar , Das Priyanath , Fotis Georgios , Vita Vasiliki , Mann Michael
Published: September 2024

In high-power applications, achieving adequate power quality in power converter design is accomplished by utilizing multilevel inverters instead of using two-level and three-level inverters. The device generates a sinusoidal output voltage, which results in reduced total harmonic distortion and lower voltage stress on the switches and leads to lower electromagnetic interference, making it suitable for use in renewable energy applications. However, to illustrate the advantages mentioned above, a significant number of switching devices and DC sources are necessary while raising the voltage levels. This article proposes an asymmetrical voltage generation method, which operates in a ratio of 1:5 and generates 25 levels using 11 power switches. The topology is modular in structure, and each module has a lower component count, which significantly reduces the overall cost. The proposed topology is capable of generating negative output voltage levels without the use of an H-bridge configuration, where only three switches are used to generate any voltage levels. The functionality of the developed module is amended by fixing different voltage values in DC sources. This article also presents a comprehensive examination of the circuit and the functioning of various voltage levels. The advantages of the proposed inverter have been demonstrated by comparative research with the currently existing MLI topologies. Ultimately, both the simulation and experimental findings validated the practical capabilities.
Enhancing Linux System Security: A Kernel-Based Approach to Fileless Malware Detection and Mitigation
Authors: Wu Min-Hao , Hsu Fu-Hau , Huang Jian-Hung , Wang Keyuan , Hwang Yan-Ling , Wang Hao-Jyun , Chen Jian-Xin , Hsiao Teng-Chuan , Yang Hao-Tsung
Published: September 2024

In the late 20th century, computer viruses emerged as powerful malware that resides permanently in target hosts. For a virus to function, it must load into memory from persistent storage, such as a file on a hard drive. Due to the significant destructive potential of viruses, numerous defense measures have been developed to protect computer systems. Among these, antivirus software is one of the most recognized and widely used. Typically, antivirus solutions rely on static analysis (signature-based) technologies to detect infections in files stored on permanent storage devices, such as hard drives or USB (Universal Serial Bus) flash drives. However, a new breed of malware, fileless malware, has been designed to evade detection and enhance durability. Fileless malware resides solely in the memory of the target hosts, circumventing traditional antivirus software, which cannot access or analyze processes executed directly from memory. This study proposes the Check-on-Execution (CoE) kernel-based approach to detect fileless malware on Linux systems. CoE intervenes by suspending code execution before a program executes code from a process’s writable and executable memory area. To prevent the execution of fileless malware, CoE extracts the code from memory, packages it with an ELF (Executable and Linkable Format) header to create an ELF file, and uses VirusTotal for analysis. Experimental results demonstrate that CoE significantly enhances a Linux system’s ability to defend against fileless malware. Additionally, CoE effectively protects against shell code injection attacks, including buffer and memory overflows, and can handle packed malware. However, it is important to note that this study focuses exclusively on fileless malware, and further research is needed to address other types of malware.
Improved Plasma Etch Endpoint Detection Using Attention-Based Long Short-Term Memory Machine Learning
Authors: Kim Ye Jin , Song Jung Ho , Cho Ki Hwan , Shin Jong Hyeon , Kim Jong Sik , Yoon Jung Sik , Hong Sang Jeen
Published: September 2024

Existing etch endpoint detection (EPD) methods, primarily based on single wavelengths, have limitations, such as low signal-to-noise ratios and the inability to consider the long-term dependencies of time series data. To address these issues, this study proposes a context of time series data using long short-term memory (LSTM), a kind of recurrent neural network (RNN). The proposed method is based on the time series data collected through optical emission spectroscopy (OES) data during the SiO2 etching process. After training the LSTM model, the proposed method demonstrated the ability to detect the etch endpoint more accurately than existing methods by considering the entire time series. The LSTM model achieved an accuracy of 97.1% in a given condition, which shows that considering the flow and context of time series data can significantly reduce the false detection rate. To improve the performance of the proposed LSTM model, we created an attention-based LSTM model and confirmed that the model accuracy is 98.2%, and the performance is improved compared to that of the existing LSTM model.
State-of-the-Art Electric Vehicle Modeling: Architectures, Control, and Regulations
Authors: Hussein Hossam M. , Ibrahim Ahmed M. , Taha Rawan A. , Rafin S. M. Sajjad Hossain , Abdelrahman Mahmoud S. , Kharchouf Ibtissam , Mohammed Osama A.
Published: September 2024

The global reliance on electric vehicles (EVs) has been rapidly increasing due to the excessive use of fossil fuels and the resultant CO2 emissions. Moreover, EVs facilitate using alternative energy sources, such as energy storage systems (ESSs) and renewable energy sources (RESs), promoting mobility while reducing dependence on fossil fuels. However, this trend is accompanied by multiple challenges related to EVs’ traction systems, storage capacity, chemistry, charging infrastructure, and techniques. Additionally, the requisite energy management technologies and the standards and regulations needed to facilitate the expansion of the EV market present further complexities. This paper provides a comprehensive and up-to-date review of the state of the art concerning EV-related components, including energy storage systems, electric motors, charging topologies, and control techniques. Furthermore, the paper explores each sector’s commonly used standards and codes. Through this extensive review, the paper aims to advance knowledge in the field and support the ongoing development and implementation of EV technologies.
Research on Wind Turbine Fault Detection Based on CNN-LSTM
Authors: Qi Lin , Zhang Qianqian , Xie Yunjie , Zhang Jian , Ke Jinran
Published: September 2024

With the wide application of wind energy as a clean energy source, to cope with the challenge of increasing maintenance difficulty brought about by the development of large-scale wind power equipment, it is crucial to monitor the operating status of wind turbines in real time and accurately identify the specific location of faults. In this study, a CNN-LSTM-based wind motor fault detection model is constructed for four types of typical faults, namely gearbox faults, electrical faults, yaw faults, and pitch faults of wind motors, combining CNN’s advantages of excelling in feature extraction and LSTM’s advantages of dealing with long-time sequence data, to achieve the simultaneous detection of multiple fault types. The accuracy of the CNN-LSTM-based wind turbine fault detection model reaches 90.06%, and optimal results are achieved for the effective discovery of yaw system faults, pitch system faults, and gearbox faults, obtaining 94.09%, 96.46%, and 97.39%, respectively. The CNN-LSTM wind turbine fault detection model proposed in this study improves the fault detection effect, avoids the further deterioration of faults, provides direction for preventive maintenance, reduces downtime loss due to restorative maintenance, and is essential for the sustainable use of wind turbines and maintenance of wind turbine service life, which helps to improve the operation and maintenance level of wind farms.
Power Dispatching Strategy Considering the Health Status of Multi-Energy Conversion Equipment in Highway Power Supply Systems
Authors: Hou Xianhong , Wang Jiao , Guo Shaoyong , Liu Ketian
Published: September 2024

In order to extend the service life of a highway power supply system and the level of new energy consumption, a power dispatching strategy considering the health status of multi-energy conversion equipment is proposed in this paper. Firstly, the energy and load forms of the highway power supply system are introduced, and the structure of the multi-energy conversion equipment, the topological structures of the DC–DC and DC–AC modules, and the operating characteristics are analyzed. Secondly, the module temperatures and output voltages are used as main parameters to establish the health indexes of DC–DC and DC–AC modules, and then the health index of the multi-energy conversion equipment is further calculated. Thirdly, the new energy consumption index is defined, and a multi-objective optimization model for power dispatching of highway power supply systems is established with the goal of improving the health index of multi-energy conversion equipment and the new energy consumption index. The case study shows that the power dispatching strategy in this paper can better control the temperature of each module, improve the health status of multi-energy conversion equipment, and have a high level of new energy consumption.
New Zero-Carbon Wooden Building Concepts: A Review of Selected Criteria
Authors: Starzyk Agnieszka , Rybak-Niedziółka Kinga , Nowysz Aleksandra , Marchwiński Janusz , Kozarzewska Alicja , Koszewska Joanna , Piętocha Anna , Vietrova Polina , Łacek Przemysław , Donderewicz Mikołaj , Langie Karol , Walasek Katarzyna , Zawada Karol , Voronkova Ivanna , Francke Barbara , Podlasek Anna
Published: September 2024

A Carbon Footprint (CF) is defined as the total emissions of greenhouse gases, primarily carbon dioxide, methane, and nitrous oxide, and is a specific type of Environmental Footprint that measures human impact on the environment. Carbon dioxide emissions are a major contributor to anthropogenic greenhouse gases driving climate change. Wood, as a renewable and ecological material, has relatively low carbon emissions. The study aimed to review and analyze the criteria influencing the feasibility of constructing modern zero-carbon wooden buildings. The review was conducted in two phases: (i) a literature review and (ii) an assessment of existing buildings. The preliminary research led to (i) narrowing the focus to the years 2020–2024 and (ii) identifying key criteria for analysis: sustainable material sourcing, carbon sequestration, energy efficiency, life cycle assessment (LCA), and innovative construction practices. The study’s findings indicate that all these criteria play a vital role in the design and construction of new zero-carbon wooden buildings. They highlight the significant potential of wood as a renewable material in achieving zero-carbon buildings (ZCBs), positioning it as a compelling alternative to traditional construction materials. However, the research also underscores that despite wood’s numerous potential benefits, its implementation in ZCBs faces several challenges, including social, regulatory, and financial barriers.
A Review of Flow Field and Heat Transfer Characteristics of Jet Impingement from Special-Shaped Holes
Authors: Xu Liang , Hu Naiyuan , Lin Hongwei , Xi Lei , Li Yunlong , Gao Jianmin
Published: September 2024

The jet impingement cooling technique is regarded as one of the most effective enhanced heat transfer techniques with a single-phase medium. However, in order to facilitate manufacturing, impingement with a large number of smooth circular hole jets is used in engineering. With the increasing maturity of additive technology, some new special-shaped holes (SSHs) may be used to further improve the cooling efficiency of jet impingement. Secondly, the heat transfer coefficient of the whole jet varies greatly on the impact target surface. The experiments with a large number of single smooth circular hole jets show that the heat transfer coefficient of the impact target surface will form a bell distribution—that is, the Nusselt number has a maximum value near the stagnation region, and then rapidly decreases exponentially in the radial direction away from the stagnation region. The overall surface temperature distribution is very uneven, and the target surface will form an array of cold spots, resulting in a high level of thermal stress, which will greatly weaken the structural strength and life of the equipment. Establishing how to ensure the uniformity of jet impingement cooling has become a new problem to be solved. In order to achieve uniform cooling, special-shaped holes that generate a swirling flow may be a solution. This paper presents a summary of the effects of holes with different geometrical features on the flow field and heat transfer characteristics of jet impingement cooling. In addition, the effect of jet impingement cooling with SSHs in different array methods is compared. The current challenges of jet impingement cooling technology with SSHs are discussed, as well as the prospects for possible future advances.
Breaking the CO2 Gridlock: Can Renewables Lead the Way for the OECD?
Authors: Jie Wang , Khan Rabnawaz
Published: September 2024

The use of low-carbon energy in power grids is essential for minimizing negative effects on the environment. Energy consumption causes environmental damage to the OECD’s economy. This study aims to investigate the effect of energy consumption, population, and GDP on CO2 emissions using panel data from 17 OECD countries over the period 2000–2023. We use regression approaches, such as partial least squares and principal components, to study the effects of GDP, urban and total population, oil and nuclear use, renewable energy, and industrialization on CO2 emissions. The regression process in this study reduces the data to a two-dimensional representation using a stochastic model and estimation techniques. The findings of this empirical investigation indicate that the United States, Canada, France, Germany, Italy, Korea, Mexico, and the United Kingdom exhibit higher levels of primary energy consumption in comparison to value-added sectors, renewable–geothermal energy, and nuclear energy. We determined the effects of CO2 emissions, GDP, and energy consumption by considering these as the most significant elements. This has made it possible to reduce CO2 emissions by focusing one’s attention and energy on the development of novel technologies, the use of renewable energy sources, and the execution of strategic plans. Attracting increasing attention are technological shifts that deliver enormous quantities of clean energy to combat climate change. Findings from this study can help environmentalists and policymakers better understand the role of structural change and energy consumption processes in the globalization process.