bluuebunny/crossref_metadata_2025 huggingface dataset:
Peatland Hydro-Climatological Parameters Variability in Response to 2019–2022 Climate Anomalies in the OKI Regency
Authors: Irfan Muhammad , Khakim Mokhamad Yusup Nur , Mardiansyah Wijaya , Kurniawati Netty , Awaluddin  , Sulaiman Albertus , Iskandar Iskhaq , Suwignyo Rujito Agus , Yang Hyunyoung , Choi Eunho
Published: January 2025

Peatlands in OKI Regency are highly flammable during extreme dry seasons and experience flooding during extreme rainy seasons. Research related to peatlands is important to be carried out in disaster mitigation efforts on peatlands. In this study, we aimed to examine the impact of climate anomalies occurring between 2019 and 2022 on the Rainfall (RF), Groundwater Level (GWL), and Soil Moisture (SM) in this region. We analyzed data collected at the CJ2 station to understand the dynamics of these parameters throughout the occurrence of the ENSO and IOD phenomena in 2019–2022. The findings of this study indicate a positive correlation between RF and GWL. Specifically, a higher amount of RF resulted in a stronger correlation. Moreover, the rate of the GWL decline was 0.24 mm/d, while the rate of the SM decline was 0.06%/day. Furthermore, the soil moisture in CJ2 OKI must be maintained at a minimum of 20% to prevent fires. In addition, an empirical equation was derived to express the relationship between GWL (m) and SM (%) as SM = 49,044 GWL + 59,142. The findings of this study provide valuable in-sights for all stakeholders involved in efforts to mitigate the impact of natural disasters on peatlands.
An Overview of the Therapeutic Potential of Dimeric Flavonoids for Targeting Cancer Hallmarks
Authors: Lopes Inês , Meireles Isabel , Rocha Rafaela , Medeiros Rui , Cerqueira Fátima
Published: January 2025

Evidence found in the literature indicates that dimeric flavonoids constitute important therapeutic options against cancer. Using these molecules to prevent cancer progression might be a novel and promising therapeutic approach with advantages like fewer side effects, easy access in nature, overall health benefits and overcoming drug resistance. Cancer is a complex disease and still not understood, but there are some common mechanisms and biological characteristics underlying tumor progression that have been scrutinized over the years. This information was summarized in a conceptual framework designated as hallmarks of cancer. Dimeric flavonoids exert biological effects in several pathways involved in cancer hallmarks including cell growth, cell cycle, apoptosis, metastasis and metabolism.
Current Understanding on the Heterogenous Expression of Plastic Depolymerising Enzymes in Pichia pastoris
Authors: Wu Shuyan , Hooks David , Brightwell Gale
Published: January 2025

Enzymatic depolymerisation is increasingly recognised as a reliable and environmentally friendly method. The development of this technology hinges on the availability of high-quality enzymes and associated bioreaction systems for upscaling biodegradation. Microbial heterologous expression systems have been studied for meeting this demand. Among these systems, the Pichia pastoris expression system has emerged as a widely used platform for producing secreted heterologous proteins. This article provides an overview of studies involving the recombinant expression of polymer-degrading enzymes using the P. pastoris expression system. Research on P. pastoris expression of interested enzymes with depolymerising ability, including cutinase, lipase, and laccase, are highlighted in the review. The key factors influencing the heterologous expression of polymer-degrading enzymes in P. pastoris are discussed, shedding light on the challenges and opportunities in the development of depolymerising biocatalysts through the P. pastoris expression system.
Inferior Outcomes of Fludarabine–Cyclophosphamide–Rituximab Chemotherapy in Korean Chronic Lymphocytic Leukemia Patients with Concurrent Thrombocytopenia and Anemia
Authors: Kim Tong-Yoon , Min Gi-June , Jeon Young-Woo , Yahng Seung-Ah , Cho Seok-Goo , Lee Jong-Mi , Kim Myungshin , Eom Ki-Seong
Published: January 2025

Background/Objectives: Anti-CD20 monoclonal antibodies combined with alkylator-based chemotherapy enhance survival in chronic lymphocytic leukemia (CLL). However, the risks of infection and bone marrow suppression may mean that new, targeted therapies are more appropriate for some patients than fludarabine–cyclophosphamide–rituximab (FCR). In the Republic of Korea, where insurance limits coverage to novel agents, FCR therapy should be carefully considered for patients with CLL. Methods: Using clinical data from 144 FCR-treated patients with CLL, we retrospectively analyzed clinical characteristics impacting survival outcomes, the impact of cytopenia after FCR, and the durable remission status in terms of measurable residual disease (MRD). We compared the impact of bicytopenia with those of other hematologic conditions. Results: The 5-year overall survival (OS) and 5-year progression-free survival (PFS) for all patients were 84.4% and 68.3%, respectively. FCR-treated patients in the bicytopenia and TP53-positive groups exhibited poor OS and PFS; in particular, the bicytopenia group often experienced prolonged anemia and thrombocytopenia (6–12 months). The responder group achieved sustained remission for a median of 5 years for MRD negativity. Conclusions: In bicytopenia, FCR can induce prolonged cytopenia, making it difficult to switch to second-line therapy or complete cycles of chemoimmunotherapy, directly affecting poor survival outcomes. The cautious application of FCR therapy in CLL without bicytopenia or TP53 positivity can achieve long-term remission.
The Potential of Mesenchymal Stem Cell-Derived Exosomes to Treat Diabetes Mellitus
Authors: Kim Ju-El , Lee Jong-Won , Cha Gi Doo , Yoon Jeong-Kee
Published: January 2025

Diabetes mellitus (DM) is a fatal metabolic disease characterized by persistent hyperglycemia. In recent studies, mesenchymal stem cell (MSC)-derived exosomes, which are being investigated clinically as a cell-free therapy for various diseases, have gained attention due to their biomimetic properties that closely resemble natural cellular communication systems. These MSC-derived exosomes inherit the regenerative and protective effects from MSCs, inducing pancreatic β-cell proliferation and inhibiting apoptosis, as well as ameliorating insulin resistance by suppressing the release of various inflammatory cytokines. Consequently, MSC-derived exosomes have attracted attention as a novel treatment for DM as an alternative to stem cell therapy. In this review, we will introduce the potential of MSC-derived exosomes for the treatment of DM by discussing the studies that have used MSC-derived exosomes to treat DM, which have shown therapeutic effects in both type 1 and type 2 DM.
Development of a Cable-Driven Bionic Spherical Joint for a Robot Wrist
Authors: He Zixun , Ito Yutaka , Saito Shotaro , Narumi Sakura , Kang Yousun , Shin Duk
Published: January 2025

Wrist movements play a crucial role in upper-limb motor tasks. As prosthetic and robotic hand technologies have evolved, increasing attention has been focused on replicating the anatomy and functionality of the wrist. Closely imitating the biomechanics and movement mechanisms of human limbs is expected to enhance the overall performance of bionic robotic hands. This study presents the design of a tendon-driven bionic spherical robot wrist, utilizing two pairs of cables that mimic antagonist muscle pairs. The cables are actuated by pulleys driven by servo motors, allowing for two primary wrist motions: flexion–extension and ulnar–radial deviation. The performance Please confirm if the “1583 Iiyama” is necessary. Same as belowof the proposed robot wrist is validated through manipulation experiments using a prototype, demonstrating its capability to achieve a full range of motion for both ulnar and radial deviation. This wrist mechanism is expected to be integrated into robotic systems, enabling greater flexibility and more human-like movement capabilities.
Diagnosis of Cognitive and Mental Disorders: A New Approach Based on Spectral–Spatiotemporal Analysis and Local Graph Structures of Electroencephalogram Signals
Authors: Sanati Fahandari Arezoo , Moshiryan Sara , Goshvarpour Ateke
Published: January 2025

Background/Objectives: The classification of psychological disorders has gained significant importance due to recent advancements in signal processing techniques. Traditionally, research in this domain has focused primarily on binary classifications of disorders. This study aims to classify five distinct states, including one control group and four categories of psychological disorders. Methods: Our investigation will utilize algorithms based on Granger causality and local graph structures to improve classification accuracy. Feature extraction from connectivity matrices was performed using local structure graphs. The extracted features were subsequently classified employing K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost, and Naïve Bayes classifiers. Results: The KNN classifier demonstrated the highest accuracy in the gamma band for the depression category, achieving an accuracy of 89.36%, a sensitivity of 89.57%, an F1 score of 94.30%, and a precision of 99.90%. Furthermore, the SVM classifier surpassed the other machine learning algorithms when all features were integrated, attaining an accuracy of 89.06%, a sensitivity of 88.97%, an F1 score of 94.16%, and a precision of 100% for the discrimination of depression in the gamma band. Conclusions: The proposed methodology provides a novel approach for analyzing EEG signals and holds potential applications in the classification of psychological disorders.
In-Depth Analysis of Photovoltaic-Integrated Shading Systems’ Performance in Residential Buildings: A Prospective of Numerical Techniques Toward Net-Zero Energy Buildings
Authors: Baghdadi Ahmad , Abuhussain Maher
Published: January 2025

The three categories of energy scarcity, population growth and environmental concerns explain the need for new energy sources. Saudi Arabia has become one of the regions capable of using solar energy, particularly through the use of photovoltaic systems, thanks to Saudi Arabia’s excellent ability to effectively utilize the sunlight. This study examines the performance of photovoltaic-integrated shading systems (PVIS) in enhancing energy efficiency for residential buildings under the extreme climatic conditions of Riyadh and Abha in Saudi Arabia. The study advances the knowledge of PVIS applications by addressing the dual challenges of energy efficiency and sustainability in urban residential settings. Leveraging numerical simulations conducted with EnergyPlus, the research evaluates various shading configurations, including louvers, horizontal and sidefin canopies, to quantify their impact on cooling, heating, lighting demands and energy production. The annual efficiency of the proposed integrated systems to achieve sustainable and net-zero energy buildings (NZEBs) is a key metric evaluated in this study. The key findings highlight the effectiveness of horizontal PVIS in achieving the highest energy efficiency, with up to 27.19% in Abha and 24.72% in Riyadh, based on the ratio of annual available solar energy to PV energy production. The integration of PVIS not only reduces the cooling loads by optimizing shading but also contributes significantly to renewable energy production toward NZEBs. The lifecycle cost analysis (LCCA) identifies horizontal canopies as the most cost-effective configuration, with a payback period of 8.6 years in Abha and 10.2 years in Riyadh.
Properties of High-Strength Concrete Incorporating Calcined Diatomaceous Earth, Polypropylene, and Glass Fibers
Authors: Hasan Muttaqin , Alkhaly Yulius Rief , Hamzani  , Fikri Rijalul , Saidi Taufiq
Published: January 2025

This study was aimed at determining the hardened and fresh properties as well as the high-temperature resistance of high-strength concrete (HSC) produced by incorporating diatomaceous earth, polypropylene, and glass fibers. CDE (calcined diatomaceous earth) was employed as a 10% cement replacement, while polypropylene and glass fibers were added separately to the mixtures at 0.2, 0.4, 0.6, 0.8, and 1.0% volumetric contents. Moreover, the mixtures without using CDE and fibers were used as references. The concrete mixtures were fabricated, followed by the determination of the fresh concrete flow, the absorption capacity, and the flexural, compressive, and splitting tensile strengths of hardened concrete. Furthermore, the specimens fabricated for the hardened concrete were exposed to temperatures of 400 °C, 500 °C, and 600 °C, and the remaining compressive strength was examined. The findings suggested that the incorporation of polypropylene and glass fibers in HSC with CDE enhanced the compressive, flexural, and splitting tensile strengths by 23.4 and 32.6%, 70.0 and 83.5%, and 18.9 and 17.9%, respectively. Moreover, the inclusion of polypropylene and glass fibers reduced the absorption of hardened concrete. Meanwhile, the inclusion of CDE lowered the strengths and increased the absorption. It was further identified that the incorporation of CDE enhanced the resistance of HSC to high temperatures, while polypropylene and glass fibers lowered the resistance. The incorporation of CDE, polypropylene, and glass fibers also lowered the flow of fresh concrete.
Damage Evolution Characteristics of Steel-Fiber-Reinforced Cellular Concrete Based on Acoustic Emission
Authors: Huang Hu , Chen Feihao , Cao Kelei , Zhang Xiancai , Li Ruihang
Published: January 2025

In order to investigate the steel fiber parameters on the damage characteristics and crack evolution of cellular concrete materials, uniaxial compression–acoustic emission combined tests were carried out on steel-fiber-reinforced cellular concrete (SFRCC) with different steel fiber contents (0%, 0.5%, 1%, 1.5%, and 2%) and different porosities (10% and 20%). The material damage evolution characteristics were analyzed by acoustic emission parameters and IB values, and the crack types were identified using Gaussian mixture clustering method (GMM) pairs. The results show the following: the inclusion of steel fibers increased the compressive strength of cellular concrete by 19.8~46.3% at 10% porosity, and by 37.1~102.2% at 20% porosity; the addition of steel fibers significantly increased the density and intensity of the acoustic emission signals; the decreasing tendency of the IB value at the peak stress slowed down with the increase in the amount of steel fibers, and the steel fibers could effectively inhibit the crack development; crack classification results show that the proportion of shear cracks in all stages of cellular concrete increased significantly after the addition of steel fibers.
Dynamic Multilevel Regulation of EGFR, KRAS, and MYC Oncogenes: Driving Cancer Cell Proliferation Through (Epi)Genetic and Post-Transcriptional/Translational Pathways
Authors: Seres Mario , Spacayova Katarina , Sulova Zdena , Spaldova Jana , Breier Albert , Pavlikova Lucia
Published: January 2025

The epidermal growth factor receptor (EGFR) regulates gene expression through two primary mechanisms: as a growth factor in the nucleus, where it translocates upon binding its ligand, or via its intrinsic tyrosine kinase activity in the cytosol, where it modulates key signaling pathways such as RAS/MYC, PI3K, PLCγ, and STAT3. During tumorigenesis, these pathways become deregulated, leading to uncontrolled proliferation, enhanced migratory and metastatic capabilities, evasion of programmed cell death, and resistance to chemotherapy or radiotherapy. The RAS and MYC oncogenes are pivotal in tumorigenesis, driving processes such as resistance to apoptosis, replicative immortality, cellular invasion and metastasis, and metabolic reprogramming. These oncogenes are subject to regulation by a range of epigenetic and post-transcriptional modifications. This review focuses on the deregulation of EGFR, RAS, and MYC expression caused by (epi)genetic alterations and post-translational modifications. It also explores the therapeutic potential of targeting these regulatory proteins, emphasizing the importance of phenotyping neoplastic tissues to inform the treatment of cancer.
Mebendazole Exerts Anticancer Activity in Ovarian Cancer Cell Lines via Novel Girdin-Mediated AKT/IKKα/β/NF-κB Signaling Axis
Authors: Gupta Rahul , Roy Dipanjan , Ghosh Arijit , Begum Yasmin , Ghosh Dipanjan , Swarnakar Snehasikta
Published: January 2025

Mebendazole (MBZ), a benzimidazole anthelmintic and cytoskeleton-disrupting compound, exhibits antitumor properties; however, its action on ovarian cancer (OC) is not clearly understood. This study evaluates the effect of MBZ on OC cell lines OVCAR3 and OAW42, focusing on cell proliferation, migration, invasion, and cancer stemness. The underlying mechanisms, including cytoskeletal disruption, epithelial–mesenchymal transition (EMT), and signaling pathways, were explored. MBZ inhibited OVCAR3 and OAW42 cell proliferation in a dose- and time-dependent manner. Additionally, MBZ significantly impedes migration, spheroid invasion, colony formation, and stemness. In addition, it reduced actin polymerization and down-regulated CSC markers (e.g., CD24, CD44, EpCAM). Moreover, MBZ suppressed MMP-9 activity and inhibited the EMT marker as judged by decreased N-Cadherin and Vimentin and increased E-Cadherin. Furthermore, MBZ induced G2/M cell cycle arrest by modulating Cyclin B1, CDC25C, and WEE1. Also, it triggered apoptosis by disrupting mitochondrial membrane potential. Mechanistic studies revealed a significant downregulation of Girdin, an Akt modulator, along with reduced p-Akt, p-IKKα/β, and p-NF-κB, indicating MBZ’s novel mechanism of action through the Girdin-mediated Akt/IKKα/β/NF-κB signaling axis. Thus, by targeting Girdin, MBZ presents a promising repurposed therapeutic strategy to inhibit cancer cell proliferation and metastasis in ovarian cancer.
Impact of Aggregate Characteristics on Frictional Performance of Asphalt-Based High Friction Surface Treatments
Authors: Roshan Alireza , Abdelrahman Magdy
Published: January 2025

High Friction Surface Treatments (HFST) are recognized for their effectiveness in enhancing skid resistance and reducing road accidents. While Epoxy-based HFSTs are widely applied, they present limitations such as compatibility issues with existing pavements, high installation and removal costs, and durability concerns tied to substrate quality. As an alternative to traditional Epoxy-based HFSTs, this study investigated the effects of aggregate gradation as designated by agencies on the performance of asphalt-based HFST. Various aggregate types were assessed to evaluate friction performance and the impact of polishing cycles on non-Epoxy HFST. It was found that adjustments in aggregate size and gradation may be necessary when transitioning to asphalt-based HFSTs, given the different nature of asphalt as more temperature susceptible compared to Epoxy. Various asphalt binder grades were considered in this study. A series of tests, including the British Pendulum Test (BPT), Dynamic Friction Tester (DFT), Circular Track Meter (CTM), Micro-Deval (MD), and Aggregate Imaging Measurement System (AIMS), were conducted to measure Coefficient of Friction (COF), Mean Profile Depth (MPD), texture, and angularity before and after polishing cycles. The results showed that the COF in asphalt-based slabs decreased more significantly than in Epoxy-based slabs as polishing cycles increased for HFST and medium gradations. However, in coarse gradation, the COF of slabs using asphalt-based binder matched or even surpassed that of Epoxy after polishing. Notably, the PG88-16 binder for Calcined Bauxite (CB) had the smallest reduction in COF after 140K polishing cycles, with only a 19% decrease compared to a 23% reduction for Epoxy.
Barriers and Factors Affecting Nursing Communication When Providing Patient Care in Jeddah
Authors: Alharazi Ruba M. , Abdulrahim Rahaf J. , Mazuzah Alhanouf H. , Almutairi Reem M. , Almutary Hayfa , Alhofaian Aisha
Published: January 2025

Background/Objectives: Effective communication between nurses and patients plays a crucial role in the delivery of quality healthcare services, especially when caring for patients from diverse cultural backgrounds. It fosters trust, understanding, and collaboration and contributes to better health outcomes and satisfactory nurse–patient relationships. The aim of the study is to assess the factors and barriers affecting nurses’ communication when providing care for patients from diverse cultural backgrounds in Jeddah, Saudi Arabia. Methods: A cross-sectional quantitative descriptive design is used with an online survey instrument. The study involved registered nurses employed in Jeddah’s hospitals. The study utilized a convenience sample for data collection and used the latest version of the statistical package for the social sciences (SPSS version 21) for data entry and analysis. Results: A study of 367 participants found significant barriers to nurse–patient communication, with a mean score of 2.84 on a three-point scale. Key challenges included language differences between nurses and patients with a mean score of 2.87, and cultural and religious differences with a mean score of 2.83 and 2.81, as well as nurses’ communication skills, attitudes, and self-confidence and patients’ awareness, attitudes, and resistance to communication. The multifaceted nature of these barriers emphasizes the need for targeted interventions to improve nurse–patient interactions and enhance care quality. Conclusions: The study highlights the impact of various factors on effective communication between nurses and patients, emphasizing the need for nurses to develop their communication skills and to receive adequate training from nursing officials.
Facile Synthesis of Iron Phosphide Nanoparticles in 3D Porous Carbon Framework as Superior Anodes for Sodium-Ion Batteries
Authors: Yan Jian , Lin Sheng , Xia Yongji , Zhou Zhidong , Li Jintang , Yue Guanghui
Published: January 2025

Iron phosphide (FeP) represents a promising anode material for sodium-ion batteries, attributed to its significant theoretical capacity, moderate operating potential, and natural abundance. However, due to the low conductivity and significant volume expansion of FeP electrodes, their specific capacity and cycle life decrease rapidly during charging and discharging. In this study, we synthesized FeP nanoparticles supported on a three-dimensional porous carbon framework composite (FeP@PCF) using a straightforward colloidal blow molding method, employing iron nitrate nonahydrate and polyvinylpyrrolidone as raw materials. The nanoscale size of the FeP particles, along with the abundant mesopores and high specific surface area of the 3D porous carbon framework, contribute to the impressive sodium storage performance of FeP@PCF. It is revealed that FeP@PCF achieves a remarkable capacity of 196.6 mA h g−1 at a current density of 1.0 A g−1. Furthermore, after 800 cycles at this current density, it retains a capacity of 172.4 mA h g−1, demonstrating excellent cycling performance. Kinetic and dynamic studies indicate that this exceptional performance is largely attributed to the well-designed FeP@PCF, which exhibits a high capacitive contribution of 88.3% at a scan rate of 1 mV s−1.
Polydispersity and Composition Stability in a Long-Term Follow-Up of Palmarosa (Cymbopogon Martini) and Tea Tree (Melaleuca Alternifolia) O/W Nanoemulsions for Antibacterial Use
Authors: Sánchez-Gaitán Erick , González-López Vianney , Delgado Francisco
Published: January 2025

There is a growing focus on the design of nanoemulsions because of their valuable properties as an enhanced vehicle for interaction with cells and resistant bacteria. Their potential applications in the health and food industry are numerous. Although they are considered unstable because of flocculation and coalescence, they are still efficient resources for antibacterial inhibition due to their droplet size. Studies on the interactions between essential oils and an aqueous medium are increasing, in order to efficiently formulate them at the nanometric scale using surfactants, thereby providing them with long-lived droplet size stability. This study used the ultrasonication method for fabrication and Eumulgin as a surfactant to achieve nanometric droplet sizes using two noble essential oils, palmarosa and tea tree. A follow-up for one year tracked a stable droplet size and sustained polydispersity in those emulsions as the most valuable outcome. Moreover, the insights of a thermoresponsive study have been included, also showing a strong stability. The antibacterial properties of the essential oils considered became enhanced, at a comparable scale of an antibiotic, on Salmonella spp. and Bacillus subtilis depending on the nanoscale droplet size. The outcomes suggest the importance of deepening parametric studies of these nanoformulations in terms of concentrations and temperature changes, characterizing their remarkable properties and durability.
Design and Synthesis of Crystalline Al-Doped TiO2 Buffer Layers for Enhancing Energy Conversion Efficiency of New Photovoltaic Devices
Authors: Kim Dongin , Lee Jiwon , Jeong Rakhyun , Hwang Ki-Hwan , Boo Jin-Hyo
Published: January 2025

Perovskite solar cells (PSCs) characterized by high energy conversion efficiency (ECE) and low manufacturing costs, exhibit promising potential for commercialization in the near term. For commercialization, it is very important to prevent the decomposition of perovskite by ultraviolet (UV) radiation in the air environment. Also, the mesoscopic architecture of PSCs presents considerable opportunities for the solar cell industry, offering potential for recycling of spent photocatalytic materials such as TiO2, and exploration of new energy resources. To solve these problems, therefore, this study introduces a strategy to mitigate these challenges using a crystalline Al-doped TiO2 buffer layer as the electron transport layer (ETL) in conjunction with a mesoporous TiO2 layer in the fabrication of PSCs. Among various Al concentrations in the crystalline Al-doped TiO2 buffer layer fabricated via spin-coating, an optimum concentration of 7 mol% Al yielded the highest cell performance in the specific perovskite solar cell structure. These solar cells exhibited an impressive ECE of 11.87%, representing a substantial enhancement of nearly double the ECE (6.37%) achieved with the conventional ETL. This remarkable improvement can be attributed to the passivation effect of the newly developed ETL, which combines a crystalline Al-doped TiO2 buffer layer with a mesoporousTiO2 layer. Electrochemical impedance spectroscopy (EIS) analysis was performed in conjunction with theoretical calculations of charge transport parameters to substantiate this claim.
A Vermetid Bioconstruction at the Adriatic Coast of Apulia (Italy)
Authors: Mercurio Maria , Coccia Isabella , Marra Manuel , Lazic Tamara , Corriero Giuseppe , Gravina Maria Flavia
Published: January 2025

This study presents the first comprehensive data on a vermetid formation along the Apulian coast of the Adriatic Sea, representing one of the northernmost records in the Mediterranean. Surveys along the Brindisi coastline employed visual inspection to map the bioconstruction’s distribution and extension. Detailed data on the bioconstruction inner and the outer edge length, thickness, width, slope and topographic complexity were collected at three selected sites. Moreover, photographic replicates were used to assess shell aperture density and diameters of Dendropoma sp. Associated fauna was studied using two quantitative sampling squares in each transect. The results showed that the vermetid bioconstruction consisted of a thin, encrusted monolayer (thickness < 1.5 cm) that extended for 3.273 linear kilometers, covering 17.23% of the investigated area; it had an average width of 0.5 m, with a mean density of Dendropoma sp. at 2.52 ind/cm2. The associated fauna was composed of 47 taxa dominated by crustaceans, mollusks and annelids. Species richness was correlated with the bioconstruction’s thickness and complexity. These findings underline the ecological importance of vermetid bioconstructions as biodiversity hotspots. The lack of massive mortality events along the Apulian coast, in contrast to other Mediterranean vermetid bioconstructions, underscores the necessity for targeted conservation measures.
A Framework for Developing Biodiversity Conservation Networks Based on Morphological Spatial Pattern Analysis and the Maximum Entropy Model: A Case Study of the Jianghan Plain, China
Authors: Guo Xiaohua , Liu Chang , Bi Shibo , Zhang Xuewen
Published: January 2025

Constructing ecological networks in urban areas improves ecosystem stability and biodiversity protection. However, most studies focus on optimizing ecological environments through objective assessments, often neglecting species diversity. This study developed a biodiversity grading framework for the Jianghan Plain using species observation and ecosystem diversity data. Supported by ArcGIS, ecological sources were identified via MSPA and graded using the Guidelines and MaxEnt model. The MCR model was used to simulate connectivity barriers between ecological sources and calculate the minimum cumulative resistance distance, thereby generating corridors and ultimately constructing a hierarchical biodiversity conservation network for the Jianghan Plain. Our findings indicated the following: (1) The Jianghan Plain hosts 21 major ecological sources, primarily natural water bodies at the plain’s edge, which can be classified into five primary and 16 secondary sources based on biodiversity grades. (2) The recessive corridors, comprising 10 primary and 95 secondary ones, are mainly concentrated in the central Jianghan Plain, with primary corridors located centrally and westward, characterized by a large overall span. (3) Changhu Lake and Honghu Lake, two critical water bodies with high-quality habitats and significant biodiversity, were identified as key ecological nodes from the ecological sources, bridging and guiding the central and southern corridors. (4) Based on the ecological network distribution and key nodes and corridors, a “three zones, three belts, and two points” strategy was proposed for optimizing the Jianghan Plain’s ecological network. This study provides a novel framework and theoretical support for regional habitat, biodiversity conservation, and sustainable development.
Credit Evaluation of Technology-Based Small and Micro Enterprises: An Innovative Weighting Method Based on Machine Learning and AHP
Authors: Wu Bingya , Hu Zhihui , Gu Zhouyi , Zheng Yuxi , Lv Jiayan
Published: January 2025

Technology-based small and micro enterprises play a crucial role in national economic and social development. Managing their credit risk effectively is key to ensuring their healthy growth. This study is based on corporate credit management theory and Wu’s three-dimensional credit theory. It clarifies the credit concept and measurement logic of these enterprises, considering their unique development characteristics in China. A credit evaluation system is constructed, and an innovative method combining machine learning with comprehensive evaluation is proposed. This approach aims to assess the credit status of technology-based small and micro enterprises in a thorough and objective manner. The study finds that, first, the credit level of these enterprises is currently moderate, with little variation. Second, financial information remains a key factor in credit evaluation. Third, the ML-AHP (Machine Learning-Analytic Hierarchy Process) combined weighting method effectively integrates subjective experience with objective data, providing a more rational assessment. The findings provide theoretical references and practical guidance for the healthy development of technology-based small and micro enterprises, early credit risk warning, and improved financing efficiency.
An Efficient 3D Convolutional Neural Network for Dose Prediction in Cancer Radiotherapy from CT Images
Authors: Hien Lam Thanh , Hieu Pham Trung , Toan Do Nang
Published: January 2025

Introduction: Cancer is a highly lethal disease with a significantly high mortality rate. One of the most commonly used methods for treatment is radiation therapy. However, cancer treatment using radiotherapy is a time-consuming process that requires significant manual work from planners and doctors. In radiation therapy treatment planning, determining the dose distribution for each of the regions of the patient’s body is one of the most difficult and important tasks. Nowadays, artificial intelligence has shown promising results in improving the quality of disease treatment, particularly in cancer radiation therapy. Objectives: The main objective of this study is to build a high-performance deep learning model for predicting radiation therapy doses for cancer and to develop software to easily manipulate and use this model. Materials and Methods: In this paper, we propose a custom 3D convolutional neural network model with a U-Net-based architecture to automatically predict radiation doses during cancer radiation therapy from CT images. To ensure that the predicted doses do not have negative values, which are not valid for radiation doses, a rectified linear unit (ReLU) function is applied to the output to convert negative values to zero. Additionally, a proposed loss function based on a dose–volume histogram is used to train the model, ensuring that the predicted dose concentrations are highly meaningful in terms of radiation therapy. The model is developed using the OpenKBP challenge dataset, which consists of 200, 100, and 40 head and neck cancer patients for training, testing, and validation, respectively. Before the training phase, preprocessing and augmentation techniques, such as standardization, translation, and flipping, are applied to the training set. During the training phase, a cosine annealing scheduler is applied to update the learning rate. Results and Conclusions: Our model achieved strong performance, with a good DVH score (1.444 Gy) on the test dataset, compared to previous studies and state-of-the-art models. In addition, we developed software to display the dose maps predicted by the proposed model for each 2D slice in order to facilitate usage and observation. These results may help doctors in treating cancer with radiation therapy in terms of both time and effectiveness.
Challenges in Science, Technology, Engineering, Arts, and Mathematics Education in Cape Verde: A Study of a Mathematics Teacher Training Project
Authors: Dos Santos José Manuel Dos Santos , Silveira Astrigilda Pires Rocha , Breda Ana Maria Reis d’Azevedo , Lavicza Zsolt
Published: January 2025

This study investigates strategies to empower Cape Verdean mathematics teachers in adopting Science, Technology, Engineering, Arts, and Mathematics (STEAM) methodologies, focusing on mathematics education. Using an interactive, reflective continuous professional development (CPD) model—including teaching simulations, classroom practice, and structured reflection—qualitative research was conducted via thematic analysis of published data over two project-training cycles. In the first cycle, 27 teachers participated, with 24 later acting as trainers in the second cycle, which involved 44 non-higher education teachers. The project, a collaboration between institutions in Cape Verde, Portugal, and Austria, was guided by Rogers’ Diffusion of Innovations theory and the Technological Pedagogical Content Knowledge (TPACK) framework. GeoGebra software was employed to support STEAM adoption. Results indicate significant advancements in teachers’ technological and pedagogical skills, leading to improved student engagement and understanding. However, challenges remain, especially in integrating STEAM across disciplines due to limited resources and a lack of systemic CPD. The study concludes that sustained support is essential for fully embedding STEAM in Cape Verde’s education system.
Delving into the Design and Implementation of Specifications Grading Systems in Higher Education
Authors: Howitz William J. , McKnelly Kate J. , Link Renée D.
Published: January 2025

Specifications grading is an alternative grading system that has been used with increasing frequency in higher education. Since first introduced by Linda Nilson in 2014, more than 90 publications on the design and implementation of specifications grading systems have been published. This work presents a systematic review of the current literature to analyze the variety of ways specifications grading systems are executed, including the diverse design and implementation considerations, as well as to present and discuss emergent themes. We analyzed 90 publications and present their relevant findings in the results. The following databases were last searched on 5 October 2024 for publications: IEEE Xplore, ACS Publications, ASEE PEER, PER, Scopus, ERIC, ACM, ScienceDirect, and Web of Science. All peer-reviewed journal articles, conference proceedings, and book chapters that implemented at least two structural features of specifications grading in an undergraduate or graduate course were included in this review. Theses, dissertations, conference abstracts, posters, workshops, blogs, opinion pieces, social media exchanges, and content provided on websites were not included. Additionally, reports of specifications grading systems in K-12 courses or those that only presented the design and/or implementation of less than two structural features of the grading system were similarly excluded. Our findings from the literature reveal that the following themes emerge from educators who use specifications grading: instructor commentary on time investment, academic performance, and student reactions to specifications grading. This review provides a resource for those interested in exploring this alternative grading system, and the emergent themes indicate that there are ripe opportunities for future study.
A Fusion Algorithm of Robot Path Planning Based on Improved Gray Wolf Algorithm and Dynamic Window Approach
Authors: Liu Fei , Wu Xiankun , Ma Li , You Dazhang
Published: January 2025

To tackle the problems of sluggish convergence rates, low precision, and limited applicability to static settings, a fusion algorithm of the improved Gray Wolf Algorithm and the improved Dynamic Window Approach is proposed. With regard to the Gray Wolf Algorithm, an adjustable nonlinear convergence factor is used to search and optimize the balance of the algorithm in the initial phase of the iteration process, and the candidate wolves are accepted through a simulated annealing operation in the late stage of iteration to prevent local optima and achieve the global path planning. With regard to the Dynamic Window Approach, an adaptive weight is introduced to safely control the speed for passing obstacles and an offset evaluation function is enrolled to prevent excessive local path deviation. Then, the algorithm extracts key waypoints from the global path for detailed local planning, so that the initial orientation angle succeeds the orientation angle that attained the local target point on the previous occasion and generate the shortest and smooth path from the start point to the target point. Finally, the algorithm is applied to various test scenarios for path planning simulation tests, demonstrating that the proposed algorithm is feasible and possesses superior exploration capabilities.
A Multi-Regime Car-Following Model Capturing Traffic Breakdown
Authors: Li Zhenhua , Wang Zuojun , Liu Yanyue
Published: January 2025

Traffic breakdown refers to the first-order transition from free flow to synchronized flow. It is characterized by a rapid decrease in speed, suddenly increasing density, and abruptly plummeting capacity in most of the relevant observations. To understand its cause and model its empirical observations, a multi-regime car-following model is proposed, which classifies the car-following state into four regimes, i.e., Free driving, High-speed following, Low-speed following, and Emergency. Simulation results demonstrate that traffic breakdown and spontaneous jam formation can be reproduced simultaneously by the new model. Experimental verification has shown that the new model can successfully simulate the observed concave growth pattern of traffic oscillations.
Dynamic Ensemble Learning with Gradient-Weighted Class Activation Mapping for Enhanced Gastrointestinal Disease Classification
Authors: Tsai Chih Mao , Lee Jiann-Der
Published: January 2025

Gastrointestinal (GI) disease classification through endoscopic images is a critical yet challenging task, due to inter-class variability and subtle feature overlaps. This study introduces a novel ensemble learning framework that combines case-specific dynamic weighting with Gradient-weighted Class Activation Mapping (Grad-CAM) to enhance both accuracy and interpretability. Three state-of-the-art convolutional neural networks (DenseNet201, InceptionV3, and VGG19) were fine-tuned on the Kvasir v2 dataset and integrated using optimized weights (0.4, 0.4, and 0.2, respectively). The ensemble achieved an accuracy of 0.91, outperforming individual models, particularly in complex classes such as Esophagitis and Normal-Z-Line. Grad-CAM visualizations confirmed the ensemble’s focus on clinically relevant features, highlighting its potential to improve diagnostic interpretability. While the dynamic ensemble approach significantly enhanced classification performance, further refinement is needed to address subtle and ambiguous cases. These results underscore the promise of dynamic ensemble learning as an explainable and clinically applicable tool in medical imaging.
Versatile LCL Inverter Model for Controlled Inverter Operation in Transient Grid Calculation Using the Extended Node Method
Authors: Vorwerk Daniela , Schulz Detlef
Published: January 2025

Due to increasing decentralized power applications, power electronics are gaining importance, also in distribution grids. Since their scope of investigation is diverse, their versatile models and their use in grid calculations are important. In this work, a three-phase grid-synchronous inverter with an LCL filter is considered. It is defined as a component of the “Extended Node Method” to make it applicable in this node-based transient grid calculation method. Because the component stucture always looks the same and the construction of the grid system of equations always follows the same, straightforward process, the model can be applied easily and several times to large network calculations. Furthermore, an approach is developed for how inverter control algorithms are interconnected with the method’s results in the time domain. This allows for the fast analysis of converter control schemes in different grid topologies. To evaluate its accuracy, the developed approach is compared to equivalent calculations with Simulink and shows very good agreement, also for steep transients. In the long term, this model is intended to bridge the gap to other DC systems like electrochemical components and to gas and heating networks with the Extended Node Method.
Question–Answer Methodology for Vulnerable Source Code Review via Prototype-Based Model-Agnostic Meta-Learning
Authors: Corona-Fraga Pablo , Hernandez-Suarez Aldo , Sanchez-Perez Gabriel , Toscano-Medina Linda Karina , Perez-Meana Hector , Portillo-Portillo Jose , Olivares-Mercado Jesus , García Villalba Luis Javier
Published: January 2025

In cybersecurity, identifying and addressing vulnerabilities in source code is essential for maintaining secure IT environments. Traditional static and dynamic analysis techniques, although widely used, often exhibit high false-positive rates, elevated costs, and limited interpretability. Machine Learning (ML)-based approaches aim to overcome these limitations but encounter challenges related to scalability and adaptability due to their reliance on large labeled datasets and their limited alignment with the requirements of secure development teams. These factors hinder their ability to adapt to rapidly evolving software environments. This study proposes an approach that integrates Prototype-Based Model-Agnostic Meta-Learning(Proto-MAML) with a Question-Answer (QA) framework that leverages the Bidirectional Encoder Representations from Transformers (BERT) model. By employing Few-Shot Learning (FSL), Proto-MAML identifies and mitigates vulnerabilities with minimal data requirements, aligning with the principles of the Secure Development Lifecycle (SDLC) and Development, Security, and Operations (DevSecOps). The QA framework allows developers to query vulnerabilities and receive precise, actionable insights, enhancing its applicability in dynamic environments that require frequent updates and real-time analysis. The model outputs are interpretable, promoting greater transparency in code review processes and enabling efficient resolution of emerging vulnerabilities. Proto-MAML demonstrates strong performance across multiple programming languages, achieving an average precision of 98.49%, recall of 98.54%, F1-score of 98.78%, and exact match rate of 98.78% in PHP, Java, C, and C++.
Impact of Rock Cuttings on Downhole Fluid Movement in Polycrystalline Diamond Compact (PDC) Bits, Computational Fluid Dynamics, Simulation, and Optimization of Hydraulic Structures
Authors: Wei Lihong , Honra Jaime
Published: January 2025

The flow occurring at the bottom of a polycrystalline diamond compact (PDC) drill bit involves a complex process made up of drilling fluid and the drilled rock cuttings. A thorough understanding of the bottom-hole flow conditions is essential for accurately evaluating and optimizing the hydraulic structure design of the PDC drill bit. Based on a comprehensive understanding of the hydraulic structure and fluid flow characteristics of PDC drill bits, this study integrates computational fluid dynamics (CFD) with rock-breaking simulation methods to refine and enhance the numerical simulation approach for the liquid–solid two-phase flow field of PDC drill bits. This study further conducts a comparative analysis of simulation results between single-phase and liquid–solid two-phase flows, highlighting the influence of rock cuttings on flow dynamics. The results reveal substantial differences in flow behavior between single-phase and two-phase conditions, with rock cuttings altering the velocity distribution, flow patterns, and hydraulic performance near the bottom-hole region of the drill bit. The two-phase flow simulation results demonstrate higher accuracy and provide a more detailed depiction of the bottom-hole flow, facilitating the identification of previously unrecognized issues in the hydraulic structure design. These findings advance the methodology for multiphase flow simulation in PDC drill bit studies, providing significant academic and engineering value by offering actionable insights for optimizing hydraulic structures and extending bit life.