bluuebunny/crossref_metadata_2025 huggingface dataset:
Ezetimibe Anticancer Activity via the p53/Mdm2 Pathway
Authors: Twala Charmy , Malindisa Sibusiso , Munnik Chamone , Sooklal Selisha , Ntwasa Monde
Published: January 2025

Background: Ezetimibe is used to treat cardiovascular disease as it blocks the sterol transporter Niemann-Pick C1-Like 1 (NPC1CL1) protein. However, recent evidence indicates that Ezetimibe inhibits several cancers indirectly by reducing circulating cholesterol or via specific signalling pathways. Methods and Results: Our in silico studies indicate that Ezetimibe binds to the Tp53 binding domain in Mdm2, forming a more thermodynamically stable complex than nutlin3a. Furthermore, a docking study of the newly developed inhibitors—RG7388 and RG7112—was conducted. This further showed lower binding energies of −6.337 kcal/mol and −6.222 kcal/mol, respectively, when compared to the −7.919 kcal/mol exhibited by Ezetimibe. We show that Ezetimibe inhibits the growth of several cancer cell lines at concentrations that are not toxic to a normal cell line. Conclusions: Thus, Ezetimibe is probably active against cancers that overexpress Mdm2. Moreover, inhibitors of RBBP6 may be combined with Ezetimibe for effective anticancer activity. Due to poor oral bioavailability, Ezetimibe must be administered parenterally for cancer treatment.
Enhanced Polar Lights Optimization with Cryptobiosis and Differential Evolution for Global Optimization and Feature Selection
Authors: Gao Yang , Cheng Liang
Published: January 2025

Optimization algorithms play a crucial role in solving complex problems across various fields, including global optimization and feature selection (FS). This paper presents the enhanced polar lights optimization with cryptobiosis and differential evolution (CPLODE), a novel improvement upon the original polar lights optimization (PLO) algorithm. CPLODE integrates a cryptobiosis mechanism and differential evolution (DE) operators to enhance PLO’s search capabilities. The original PLO’s particle collision strategy is replaced with DE’s mutation and crossover operators, enabling a more effective global exploration and using a dynamic crossover rate to improve convergence. Furthermore, a cryptobiosis mechanism records and reuses historically successful solutions, thereby improving the greedy selection process. The experimental results on 29 CEC 2017 benchmark functions demonstrate CPLODE’s superior performance compared to eight classical optimization algorithms, with higher average ranks and faster convergence. Moreover, CPLODE achieved competitive results in feature selection on ten real-world datasets, outperforming several well-known binary metaheuristic algorithms in classification accuracy and feature reduction. These results highlight CPLODE’s effectiveness for both global optimization and feature selection.
The Impact of Courtyard Spatial Characteristics Across Historical Periods on Summer Microclimates: A Case Study from China
Authors: Zhang Qian , Ma Xuan , Xu Duo , Zhou Dian , Yang Yujun , Jiang Weile
Published: January 2025

This study investigates the impact of spatial changes over a 400-year period on the summer microclimate of a residential courtyard in China. Using ENVI-met simulations, we analyze how factors such as courtyard orientation, building height, and opening positions affect the thermal environment. The results show that east–west-oriented courtyards experienced 0.2–0.4 °C lower daytime temperatures compared to north–south ones. Additionally, taller surrounding buildings increased the courtyard’s average daytime temperature by approximately 0.3–0.5 °C, while courtyards with a single opening facing the prevailing wind maintained the lowest temperatures. These findings underscore the importance of historical spatial characteristics in shaping microclimates and offer key insights for contemporary urban planning. By incorporating design strategies based on these historical spatial features, such as optimizing courtyard orientation, enhancing building height variability, and creating appropriate openings for natural ventilation, urban planners can improve microclimate conditions, reduce reliance on mechanical cooling, and enhance energy efficiency. This approach not only contributes to lowering carbon emissions but also boosts resilience to extreme heat events in urban areas, especially in regions facing rapid urbanization and climate change challenges.
FS-DDPG: Optimal Control of a Fan Coil Unit System Based on Safe Reinforcement Learning
Authors: Li Chenyang , Fu Qiming , Chen Jianping , Lu You , Wang Yunzhe , Wu Hongjie
Published: January 2025

To optimize the control of fan coil unit (FCU) systems under model-free conditions, researchers have integrated reinforcement learning (RL) into the control processes of system pumps and fans. However, traditional RL methods can lead to significant fluctuations in the flow of pumps and fans, posing a safety risk. To address this issue, we propose a novel FCU control method, Fluctuation Suppression–Deep Deterministic Policy Gradient (FS-DDPG). The key innovation lies in applying a constrained Markov decision process to model the FCU control problem, where a penalty term for process constraints is incorporated into the reward function, and constraint tightening is introduced to limit the action space. In addition, to validate the performance of the proposed method, we established a variable operating conditions FCU simulation platform based on the parameters of the actual FCU system and ten years of historical weather data. The platform’s correctness and effectiveness were verified from three aspects: heat transfer, the air side and the water side, under different dry and wet operating conditions. The experimental results show that compared with DDPG, FS-DDPG avoids 98.20% of the pump flow and 95.82% of the fan flow fluctuations, ensuring the safety of the equipment. Compared with DDPG and RBC, FS-DDPG achieves 11.9% and 51.76% energy saving rates, respectively, and also shows better performance in terms of operational performance and satisfaction. In the future, we will further improve the scalability and apply the method to more complex FCU systems in variable environments.
Spatial Distribution of Tumor Cells in Clear Cell Renal Cell Carcinoma Is Associated with Metastasis and a Matrisome Gene Expression Signature
Authors: Bhat Prahlad , Tamboli Pheroze , Sircar Kanishka , Kannan Kasthuri
Published: January 2025

Background/Objectives: Predicting the behavior of clear cell renal cell carcinoma (ccRCC) is challenging using standard-of-care histopathologic examination. Indeed, pathologic RCC tumor grading, based on nuclear morphology, performs poorly in predicting outcomes of patients with International Society of Urological Pathology/World Health Organization grade 2 and 3 tumors, which account for most ccRCCs. Methods: We applied spatial point process modeling of H&E-stained images of patients with grade 2 and grade 3 ccRCCs (n = 72) to find optimum separation into two groups. Results: One group was associated with greater spatial randomness and clinical metastasis (p < 0.01). Notably, spatial analysis outperformed standard pathologic grading in predicting clinical metastasis. Moreover, cell-to-cell interaction distances in the metastasis-associated group were significantly greater than those in the other patient group and were also greater than expected by the random distribution of cells. Differential gene expression between the two spatially defined groups of patients revealed a matrisome signature, consistent with the extracellular matrix’s crucial role in tumor invasion. The top differentially expressed genes (with a fold change > 3) stratified a larger, multi-institutional cohort of 352 ccRCC patients from The Cancer Genome Atlas into groups with significant differences in survival and TNM disease stage. Conclusions: Our results suggest that the spatial distribution of ccRCC tumor cells can be extracted from H&E-stained images and that it is associated with metastasis and with extracellular matrix genes that are presumably driving these tumors’ aggressive behavior.
Analysis of TERT mRNA Levels and Clinicopathological Features in Patients with Peritoneal Mesothelioma
Authors: d’Amati Antonio , Serio Gabriella , Quaranta Andrea , Vimercati Luigi , De Giorgis Michelina , Lorusso Loredana , Errede Mariella , Longo Vito , Marzullo Andrea , Ribatti Domenico , Annese Tiziana
Published: January 2025

Background/Objectives: Telomerase reverse transcriptase (TERT) is the catalytic subunit of the telomerase enzyme responsible for telomere length maintenance and is an important cancer hallmark. Our study aimed to clarify the mRNA expression of TERT in peritoneal mesothelioma (PeM), and to explore the relationship between its expression and the clinicopathological parameters and prognosis of patients with PeM. Methods: In a cohort of 13 MpeM patients, we evaluated histotype, nuclear grade, mitotic count, necrosis, inflammation, Ki67, BAP1, MTAP and p16 expression by immunohistochemistry, p16/CDKN2A status by FISH and TERT mRNA expression by RNAscope. Results: Our results showed several statistical correlations between TERT mRNA-score and other investigated features: (i) a poor positive correlation with BAP1 score (r = 0.06340; p ≤ 0.0001); (ii) a moderate positive correlation with p16 FISH del homo (r = 0.6340; p ≤ 0.0001); (iii) a fair negative correlation with p16 FISH del hetero (r = −0.3965; p ≤ 0.0001); a negative poor correlation with MTAP (r = −0.2443; p ≤ 0.0001); and (iv) a negative fair correlation with inflammatory infiltrate (r = −0.5407; p = 0.0233). Moreover, patients survive for a significantly longer time if they have a low mitotic index adjusted (2–4 mitotic figures per 2 mm2) (p ≤ 0.0001), are male (p = 0.0152), lose BAP1 (p = 0.0152), are p16 positive and present no deletion or heterozygous for p16 (p ≤ 0.01). Conclusions: TERT is highly expressed in PeM, but it is not one of the crucial factors in evaluating the prognosis of patients. Nevertheless, the results validate the prognostic significance of the mitotic index, BAP1 loss and p16/CDKN2A status.
EIF4A3-Mediated circ_0008126 Inhibits the Progression and Metastasis of Gastric Cancer by Modulating the APC/β-Catenin Pathway
Authors: Wang Zeen , Chen Wenxing , Wang Ziwei , Dai Xinglong
Published: January 2025

Background: Mounting evidence exhibits circRNAs as critical regulators in the progression of many tumors. The regulatory function and potential mechanism by which circ_0008126 in gastric cancer (GC) is unknown. Methods: To validate and analyze the expression levels and clinical values of circ_0008126 in GC patients, the biological phenotypes of circ_0008126 in GC were investigated in vitro and in vivo. The roles and effects of circ_0008126 on miR-502-5p, EIF4A3, and APC in GC cells were explored using rescue experiment, RNA stability assay, RNA pull-down, dual-luciferase reporter, RNA immunoprecipitation (RIP), RNA FISH, immunofluorescence (IF), and TOP/Flash and FOP/Flash assays. Results: Circ_0008126 expression levels were prominently down-regulated in GC tissues and cells. Importantly, low expression of circ_0008126 was relevant to the more lymphatic metastasis, advanced TNM stage, and poor survival period in patients with GC. Functionally, circ_0008126 inhibited GC cell proliferative activity, metastatic ability, and epithelial-mesenchymal transition (EMT) in vitro and vivo. Mechanistically, we verified that EIF4A3 can mediate the formation of circ_0008126, and circ_0008126 could competitively bind miR-502-5p and alleviate its role and effect on APC, thus inactivating the β-catenin pathway in GC. Additionally, circ_0008126 was determined to increase the stability of APC mRNA by interacting with cytoplasmic EIF4A3 protein and then enhancing the APC expression. Conclusions: These data demonstrate that EIF4A3-mediated circ_0008126 could regulate the APC expression and inactivate the β-catenin pathway partly by binding to miR-502-5p and EIF4A3, thus inhibiting the tumorigenesis and development of GC.
Plasmon-Enhanced CO2 Reduction to Liquid Fuel via Modified UiO-66 Photocatalysts
Authors: Elsafi Alaa , Theihmed Zeineb , Al-Yafei Amna , Alkhateeb Alaa , Abotaleb Ahmed , Anwar Muhammad , Mroue Kamal , Aissa Brahim , Sinopoli Alessandro
Published: January 2025

Metal–organic frameworks (MOFs) have emerged as versatile materials with remarkably high surface areas and tunable properties, attracting significant attention for various applications. In this work, the modification of a UiO-66 MOF with metal nanoparticles (NPs) is investigated for the purpose of enhancing its photocatalytic activity for CO2 reduction to liquid fuels. Several NPs (Au, Cu, Ag, Pd, Pt, and Ni) were loaded into the UiO-66 framework and employed as photocatalysts. The synergistic effects of plasmonic resonance and MOF characteristics were investigated to improve photocatalytic performance. The synthesized materials were characterized by X-ray powder diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS), confirming the successful integration of metal NPs onto the UiO-66 framework. Morphological analysis revealed distinct distributions and sizes of NPs on the UiO-66 surface for different metals. Photocatalytic CO2 reduction experiments demonstrated enhanced activity of plasmonic MOFs, yielding methanol and ethanol. The findings revealed by this study provide valuable insights into tailoring MOFs for improved photocatalytic applications through the incorporation of plasmonic metal nanoparticles.
Palladium-Catalyzed Cascade Reactions for Synthesis of Heterocycles Initiated by C(sp3)–H Functionalization
Authors: Yuan Dan , Xu Ziting , Zhou Yang , Herington Faith , Liu Chong , Yang Ke , Ge Haibo
Published: January 2025

Heterocycles are widely present in natural products, pharmaceuticals, and organic functional materials. In heterocycle synthesis, Pd-catalyzed cascade C–H functionalization has been regarded as one of the most powerful approaches due to its advantages in terms of high atom efficiency and readily available starting materials. In this review, we will briefly introduce the major advances in palladium-catalyzed cascade C(sp3)–H activation and annulation for constructing different types of heterocycles through inter- and intramolecular pathways from 2010 to 2023.
Recent Progress in Materials Design and Fabrication Techniques for Membrane Electrode Assembly in Proton Exchange Membrane Fuel Cells
Authors: Deng Xinhai , Ma Liying , Wang Chao , Ye Hao , Cao Lin , Zhan Xinxing , Tian Juan , Tong Xin
Published: January 2025

Proton Exchange Membrane Fuel Cells (PEMFCs) are widely regarded as promising clean energy technologies due to their high energy conversion efficiency, low environmental impact, and versatile application potential in transportation, stationary power, and portable devices. Central to the operation and performance of PEMFCs are advancements in materials and manufacturing processes that directly influence their efficiency, durability, and scalability. This review provides a comprehensive overview of recent progress in these areas, emphasizing the critical role of membrane electrode assembly (MEA) technology and its constituent components, including catalyst layers, membranes, and gas diffusion layers (GDLs). The MEA, as the heart of PEMFCs, has seen significant innovations in its structure and manufacturing methodologies to ensure optimal performance and durability. At the material level, catalyst layer advancements, including the development of platinum-group metal catalysts and cost-effective non-precious alternatives, have focused on improving catalytic activity, durability, and mass transport. Similarly, the evolution of membranes, particularly advancements in perfluorosulfonic acid membranes and alternative hydrocarbon-based or composite materials, has addressed challenges related to proton conductivity, mechanical stability, and operation under harsh conditions such as low humidity or high temperature. Additionally, innovations in gas diffusion layers have optimized their porosity, hydrophobicity, and structural properties, ensuring efficient reactant and product transport within the cell. By examining these interrelated aspects of PEMFC development, this review aims to provide a holistic understanding of the state of the art in PEMFC materials and manufacturing technologies, offering insights for future research and the practical implementation of high-performance fuel cells.
Role of tRNA-Derived Fragments in Protozoan Parasite Biology
Authors: Sharma Manu , Singh Upinder
Published: January 2025

tRNA molecules are among the most fundamental and evolutionarily conserved RNA types, primarily facilitating the translation of genetic information from mRNA into proteins. Beyond their canonical role as adaptor molecules during protein synthesis, tRNAs have evolved to perform additional functions. One such non-canonical role for tRNAs is through the generation of tRNA-derived fragments via specific cleavage processes. These tRNA-derived small RNAs (tsRNAs) are present across all three domains of life, including in protozoan parasites. They are formed through the cleavage of the parent tRNA molecules at different sites, resulting in either tRNA halves or smaller fragments. The precise mechanisms underlying the synthesis of various tRNA-derived fragments, including the specific RNases involved, as well as their distinct functions and roles in parasite physiology, are not yet fully understood and remain an active area of ongoing research. However, their role in modulating gene expression, particularly during stress responses, is becoming increasingly evident. In this context, we discuss recent findings on the roles of tRNA-derived small RNA in various protozoan parasites. Furthermore, we investigate how these tsRNAs either modulate gene expression within the parasite itself or are packaged into extracellular vesicles to alter host gene expression, thereby promoting parasite survival and adaptation.
GLI1-Rearranged Enteric Tumors: Updates on Clinicopathologic and Molecular Genetics Features
Authors: Younes Ahmed I. , Mejbel Haider A.
Published: January 2025

Recent advances in molecular genetics, particularly in identifying and characterizing genetic abnormalities within mesenchymal neoplasms, have led to a more comprehensive and evolving classification system. Modern technological developments in cytogenetics and next-generation sequencing have enabled the analysis of small clinical samples, expanded our understanding of tumor biology, and improved the diagnostic, prognostic, and predictive precision by identifying targeted genetic alterations, confirming the presence of fusion transcripts, and/or revealing the overexpression of specific genes and their targets. In this review, we focus specifically on the GLI1-rearranged enteric tumor, a recent clinicopathological entity that has emerged within the expanding classification of mesenchymal tumors. Herein, we aim to explore the histopathological features, molecular genetic characteristics, and clinical outcomes in these tumors. Due to their rarity and the extensive overlapping in their histopathological and molecular features with other neoplasms, continued research and systematic documentation of GLI1-rearranged enteric tumors is necessary to better understand their biological behavior, develop more accurate prognostic indicators, and establish optimal treatment strategies.
Survey of Aconitum Alkaloids to Establish an Aconitum carmichaeli (Fu-Zi) Processing Procedure and Quality Index
Authors: Wang Kun-Teng , Lee Ming-Chung , Chuang Wu-Chang
Published: January 2025

Processed Fu-Zi (the lateral roots of Aconitum carmichaeli) is beneficial for the cardiac system, but, because it contains toxins, raw Fu-Zi produces arrhythmia and breathing difficulties. C19 diester diterpenoid alkaloids (DDAs), including aconitine, mesaconitine, and hypaconitine, are toxic Aconitum alkaloids found in Fu-Zi and can be hydrolyzed to nontoxic monoester diterpenoid alkaloids (MDAs), including benzoylaconine, benzoylmesaconine, and benzoylhypaconine. In this study, six processed Fu-Zi decoction pieces and herbal medicines were analyzed. The highest DDA contents were found in Shengfupian, the raw Fu-Zi samples. A processing quality index (Grades A to D) was established to evaluate the processing quality of Fu-Zi. The data demonstrated that few Fu-Zi decoction pieces did not conform to the government regulation. The results of testing the inorganic elements showed that the calcium content increased by approximately 5 to 30 fold compared to raw Fu-Zi due to substances assisting with processing. Raw Fu-Zi processed by boiling, without additional substances, may have a decreased DDA content. This study provides a method of determining the quality status of pieces of Fu-Zi decoction and establishes a processing quality index for pieces of Fu-Zi decoction and herbal medicine. Furthermore, our results suggest that it is not necessary to use additional substance to assist with the processing of Fu-Zi. Through the established processing quality index, Fu-Zi may be used more safely and may demonstrate a greater consistency in quality.
The Impact of a Music- and Movement-Based Intervention on Motor Competence, Social Engagement, and Behavior in Children with Autism Spectrum Disorder
Authors: Kanzari Chayma , Hawani Aymen , Ayed Karim Ben , Mrayeh Maher , Marsigliante Santo , Muscella Antonella
Published: January 2025

Background/Objectives: The main objective of this manuscript is to evaluate the effects of training, music, and movement intervention on motor functions, social engagement, and behaviors in autistic children. Methods: Twenty-one children with a diagnosis of mild autism spectrum disorder (ASD), with an age range of 5-to-13 years, were divided into two groups: the experimental group (n = 10) and the control group (n = 11). All participants were examined before (T0) and after the intervention (T1) to evaluate their motor functions (Bruininks–Oseretsky Motor Performance Test (BOT-2)), maladaptive behavior (RCS (Response to Challenge Scale)), and enjoyment and engagement (PACES (Physical Activity Enjoyment Scale)). Results: Statistical analysis showed that music and movement intervention significantly improved motor functions such as balance and bilateral coordination (p < 0.0001), social engagement (p = 0.002), and adaptive behaviors (p = 0.005) in children with ASD. Our research supports the feasibility of music and movement intervention and documents the interest in participating in children with ASD. Conclusions: This study demonstrates the benefits of movement and music interventions and can be considered a useful way to manage autism spectrum disorders in the future.
The Relevance of the Virchow Node and Virchow Triad in Renal Cancer Diagnosis
Authors: Dorobantu-Lungu Luiza-Roxana , Dinca Viviana , Gegiu Andrei , Spataru Dan , Toma Andreea , Welt Luminita , Badea Mihaela Florentina , Caruntu Constantin , Scheau Cristian , Savulescu-Fiedler Ilinca
Published: January 2025

Background: The purpose of this article is to overview the clinical significance of left supraclavicular adenopathy and review the etiology of inferior vena cava (IVC) thrombosis, starting from a presentation of a rare case of renal cell carcinoma (RCCs) with Xp11.2 translocation involving TFE3 gene fusion. This article also aims to review the literature to understand the characteristics of this rare type of renal tumor. Renal cell carcinoma (RCC) associated with Xp11.2 translocation/gene fusion TFE3 is a rare subtype of kidney cancer that was classified in 2016 as belonging to the family of renal carcinomas with MiT gene translocation (microphthalmia-associated transcription factor). The prognosis for these kidney cancers is poorer compared to other types. Methods: We present a case of a 66-year-old man with Virchow–Troisier adenopathy during physical examination, which raises the suspicion of infra-diaphragmatic tumor. The echocardiography highlighted a heterogeneous mass in the right cardiac cavities, and the abdominal ultrasound exam revealed a solid mass at the upper pole of the left kidney. Results: Following computed tomography, magnetic resonance imaging, PET-CT, and histopathological and immunohistochemical examinations, the patient was diagnosed with renal carcinoma with Xp11.2 translocation and TFE3 gene fusion. Conclusions: IVC thrombosis is often associated with neoplastic disease due to the procoagulant state of these patients, the most common malignancies related to IVC thrombosis being represented by RCCs (38%), genitourinary cancers (25%), bronchus and lung cancers, retroperitoneal leiomyosarcoma, and adrenal cortical carcinoma. Imaging methods play a crucial role in differential diagnosis, allowing for the localization of the primary tumor and assessment of its characteristics.
Durable Textile Dyeing/Printing Using Natural Indigo Dyes and Leaves, and Mayan-Inspired Blue Indigo Pigments
Authors: Behary Nemeshwaree , Volle Nicolas
Published: January 2025

Indigo leaves from various plant species are sources of dyes/pigments, not fully exploited for making sustainable textiles. Blue indigo vat dye extracted from indigo leaves yields high wash color fastness but fades slowly with light, and is not easily used for direct printing. Indigo leaves can be used to produce textiles of various color shades, while light-resistant Mayan-inspired hybrid pigments have not yet been used for textile coloring. Using blue indigo dyes from three plant species, with exhaustion dyeing, intense wash-resistant blue-colored textiles are produced, and in the case of Indigofera Persicaria tinctoria, textiles have antibacterial activity against S. epidermis and E. coli. A 100% natural Mayan-inspired blue indigo pigment, made from sepiolite clay and natural indigo dye, was used both in powdered and paste forms to perform pigment textile dyeing by pad cure process, and direct screen printing on textiles. A water-based bio-binder was used efficiently for both padding and printing. Bio-based Na Alginate thickener allowed to produce prints with good color-fastness on both polyester and cotton fabrics, while bio-based glycerin produced excellent print color fastness on polyester only: wash fastness (5/5), dry and wet rub fastness (5/5) and light fastness (7/8).
Spiradenoma: A Case Report and Review of the Literature
Authors: Chang Jia-Ying , Chen Yen-Chang , Ding Dah-Ching
Published: January 2025

Background and Clinical Significance: Spiradenoma is a rare benign skin adnexal tumor with unknown incidence and prevalence, typically affecting young to middle-aged adults without a sexual predilection. Case Presentation: A 59-year-old woman presented with a palpable lesion in the suprapubic region that had been there for 20 years and had become enlarged over the past 2 months. Physical examination revealed a firm, non-tender, subcutaneous mass, approximately 2 cm in size, in the right pubic region. Ultrasound revealed a hypoechoic, heterogeneous lesion with a well-defined border, measuring 2.37 × 0.94 × 1.67 cm, without hypervascularity. Therefore, the patient underwent excision of the subcutaneous tumor. The pathology report confirmed the diagnosis of spiradenoma of the pubis. Histochemistry showed that the inner luminal cells were positive for CK7, and the outer basaloid cells were positive for p63. CD56 and CD117 were focally positive. Conclusions: With an accurate diagnosis and appropriate surgical excision, the prognosis for spiradenoma is generally excellent. However, a long-term follow-up is advisable.
Quantitative Changes in Vascular and Neural Fibers Induced by Subretinal Fluid Excluding the Peripapillary Region in Patients with Chronic Central Serous Chorioretinopathy
Authors: Kızıldağ Özbay Esra , Sabancı Şenol , Küçük Mehmet Fatih , Erol Muhammet Kazım
Published: January 2025

Background: This study aims to evaluate the quantitative changes in retinal nerve fiber layer (RNFL) thickness and radial peripapillary capillary (RPC) vessel density in patients with chronic central serous chorioretinopathy (CSCR), specifically excluding the peripapillary region. Methods: A prospective case–control study was conducted at the Antalya Training and Research Hospital, Health Sciences University, involving 65 patients with chronic CSCR. Participants were categorized into two groups based on the presence or regression of subretinal fluid (SRF). A control group of age- and sex-matched healthy individuals was also included. Optical coherence tomography angiography (OCTA) was used to assess RNFL thickness and RPC vessel density. Statistical analyses were conducted using SPSS, with non-parametric tests employed for between-group comparisons. Results: Patients with persistent SRF exhibited significant increases in RNFL thickness in the inferior and nasal quadrants compared to healthy controls (p = 0.003 and p = 0.014, respectively). Additionally, RPC vessel density in the small vessel disc area (%) was significantly lower in the persistent SRF group compared to controls (p = 0.021). A significant negative correlation was found between nasal quadrant RNFL thickness and small vessel disc area (p = 0.014, r = −0.306). Conclusions: Chronic SRF in CSCR patients, even when not involving the peripapillary region, leads to significant structural changes in both the neural and vascular components of the retina. These findings suggest that SRF contributes to broader retinal alterations and supports the need for early detection and management of CSCR to prevent long-term visual impairment.
The Future of Last-Mile Delivery: Lifecycle Environmental and Economic Impacts of Drone-Truck Parallel Systems
Authors: Bao Danwen , Yan Yu , Li Yuhan , Chu Jiajun
Published: January 2025

With rapid advancements in unmanned aerial vehicle (UAV) technology, its integration into logistics operations has emerged as a promising solution for improving efficiency and sustainability. Among the emerging solutions, a collaborative delivery model involving drones and trucks addresses last-mile delivery challenges by leveraging the complementary strengths of both modes of transport. However, evaluating the environmental and economic impacts of this transportation mode requires a systematic framework to capture its unique characteristics and minimize environmental impacts and costs. This paper investigates the Parallel Drone Scheduling Traveling Salesman Problem (PDSTSP) to evaluate the environmental and economic sustainability of a collaborative drone-truck delivery system. Specifically, a mathematical model for this delivery system is developed to optimize joint delivery operations. Environmental impacts are assessed using a comprehensive Life Cycle Assessment (LCA), including emissions and operational noise, while a Life Cycle Cost Analysis (LCCA) quantifies economic performance across five cost dimensions. Sensitivity analysis explores factors such as delivery density, traffic congestion, and wind conditions. Results show that, compared to the electric vehicle fleet, the proposed model achieves an approximate 20% reduction in carbon emissions, while delivering a 20–30% cost reduction relative to the fuel truck fleet. Drones’ efficiency in short-distance deliveries alleviates trucks’ load, cutting environmental and operational costs. This study offers practical insights and recommendations for implementing drone-truck parallel delivery systems, particularly in high-demand density areas.
VFL-Cafe: Communication-Efficient Vertical Federated Learning via Dynamic Caching and Feature Selection
Authors: Zhou Jiahui , Liang Han , Wu Tian , Zhang Xiaoxi , Jiang Yu , Tan Chee Wei
Published: January 2025

Vertical Federated Learning (VFL) is a promising category of Federated Learning that enables collaborative model training among distributed parties with data privacy protection. Due to its unique training architecture, a key challenge of VFL is high communication cost due to transmitting intermediate results between the Active Party and Passive Parties. Current communication-efficient VFL methods rely on using stale results without meticulous selection, which can impair model accuracy, particularly in noisy data environments. To address these limitations, this work proposes VFL-Cafe, a new VFL training method that leverages dynamic caching and feature selection to boost communication efficiency and model accuracy. In each communication round, the employed caching scheme allows multiple batches of intermediate results to be cached and strategically reused by different parties, reducing the communication overhead while maintaining model accuracy. Additionally, to eliminate the negative impact of noisy features that may undermine the effectiveness of using stale results to reduce communication rounds and incur significant model degradation, a feature selection strategy is integrated into each round of local updates. Theoretical analysis is then conducted to provide guidance on cache configuration, optimizing performance. Finally, extensive experimental results validate VFL-Cafe’s efficacy, demonstrating remarkable improvements in communication efficiency and model accuracy.
Shannon Entropy Computations in Navier–Stokes Flow Problems Using the Stochastic Finite Volume Method
Authors: Kamiński Marcin , Ossowski Rafał Leszek
Published: January 2025

The main aim of this study is to achieve the numerical solution for the Navier–Stokes equations for incompressible, non-turbulent, and subsonic fluid flows with some Gaussian physical uncertainties. The higher-order stochastic finite volume method (SFVM), implemented according to the iterative generalized stochastic perturbation technique and the Monte Carlo scheme, are engaged for this purpose. It is implemented with the aid of the polynomial bases for the pressure–velocity–temperature (PVT) solutions, for which the weighted least squares method (WLSM) algorithm is applicable. The deterministic problem is solved using the freeware OpenFVM, the computer algebra software MAPLE 2019 is employed for the LSM local fittings, and the resulting probabilistic quantities are computed. The first two probabilistic moments, as well as the Shannon entropy spatial distributions, are determined with this apparatus and visualized in the FEPlot software. This approach is validated using the 2D heat conduction benchmark test and then applied for the probabilistic version of the 3D coupled lid-driven cavity flow analysis. Such an implementation of the SFVM is applied to model the 2D lid-driven cavity flow problem for statistically homogeneous fluid with limited uncertainty in its viscosity and heat conductivity. Further numerical extension of this technique is seen in an application of the artificial neural networks, where polynomial approximation may be replaced automatically by some optimal, and not necessarily polynomial, bases.
Putting Inclusion into Practice: Five Commitments Toward Equity in Teaching
Authors: DeKorver Brittland
Published: January 2025

Instructors make day-to-day decisions grounded in their own experiences, and this practice may be appropriate for the students who share similar experiences and backgrounds. But for students who come from a different socioeconomic status, nationality, racial or ethnic identity, gender or sexual identity, or ability status, the instructor’s experiences may be insufficient to provide guidance for how to create an inclusive space for all learners. This manuscript describes interviews collected with students with disabilities regarding their experiences having their disability accommodations implemented in their courses. From these interviews and personal reflections on teaching, the author piloted and refined several teaching practices to improve the accessibility and inclusion in her own classroom. The author summarizes the principles underlying these pedagogical decisions as five commitments toward equity in teaching.
Ultra-Short-Term Photovoltaic Power Prediction Based on BiLSTM with Wavelet Decomposition and Dual Attention Mechanism
Authors: Liu Mingyang , Wang Xiaohuan , Zhong Zhiwen
Published: January 2025

Photovoltaic power generation relies on sunlight conditions, and traditional prediction models find it difficult to capture the deep features of power data, resulting in low prediction accuracy. In addition, there are problems such as outliers and missing values in the data collected on site. This article proposes an ultra-short-term photovoltaic power generation prediction model based on wavelet decomposition, a dual attention mechanism, and a bidirectional long short-term memory network (W-DA-BiLSTM), aiming to address the limitations of existing deep learning models in processing nonlinear data and automatic feature extraction and optimize for the common problems of outliers and missing values in on-site data collection. This model uses the quartile range method for outlier detection and multiple interpolation methods for missing value completion. In the prediction section, wavelet decomposition is used to effectively handle the volatility and nonlinear characteristics of photovoltaic power generation data, while the bidirectional long short-term memory network (LSTM) structure and dual attention mechanism enhance the model’s comprehensive learning ability for time series data. The experimental results show that compared with the SOTA method, the model proposed in this paper has higher accuracy and efficiency in predicting photovoltaic power generation and can effectively address common random fluctuations and nonlinear problems in photovoltaic power generation.
Multiscale Convolution-Based Efficient Channel Estimation Techniques for OFDM Systems
Authors: Kwon Nahyeon , Yoon Bora , Kim Junghyun
Published: January 2025

With the advancement of wireless communication technology, the significance of efficient and accurate channel estimation methods has grown substantially. Recently, deep learning-based methods are being adopted to estimate channels with higher precision than traditional methods, even in the absence of prior channel statistics. In this paper, we propose two deep learning-based channel estimation models, CAMPNet and MSResNet, which are designed to consider channel characteristics from a multiscale perspective. The convolutional attention and multiscale parallel network (CAMPNet) accentuates critical channel characteristics by utilizing parallel multiscale features and convolutional attention, while the multiscale residual network (MSResNet) integrates information across various scales through cross-connected multiscale convolutional structures. Both models are designed to perform robustly in environments with complex frequency domain information and various Doppler shifts. Experimental results demonstrate that CAMPNet and MSResNet achieve superior performance compared to existing channel estimation methods within various channel models. Notably, the proposed models show exceptional performance in high signal-to-noise ratio (SNR) environments, achieving up to a 48.98% reduction in mean squared error(MSE) compared to existing methods at an SNR of 25dB. In experiments evaluating the generalization capabilities of the proposed models, they show greater stability and robustness compared to existing methods. These results suggest that deep learning-based channel estimation models have the potential to overcome the limitations of existing methods, offering high performance and efficiency in real-world communication environments.
Highly Robust Active Damping Approach for Grid-Connected Current Feedback Using Phase-Lead Compensation
Authors: Guo Ang , Tian Yizhi , Zhao Haikun
Published: January 2025

The grid-current-feedback active damping (GCFAD) strategy has been widely utilized in LCL-type cascaded H-bridge static var generator (SVG) systems. Although digital control in GCFAD enhances sampling accuracy, it introduces delays in the subsequent calculation and execution processes, thereby reducing the effective damping region and weakening the robustness of the LCL-type cascaded H-bridge SVG system under a broad domain of grid impedance changes. This paper expands the effective damping area from (0, fR) (fR ∈ (fs/6, fs/3)) to (0, 0.45fs) by introducing a phase-lead compensator into the active damping feedback loop to reduce the delay. This reduces the negative effect of the digital control on the system’s effective damping region and significantly enhances its robustness under an extensive domain of grid impedance variations. The improved GCFAD is employed to establish the system’s discrete domain model and the controller parameters are adjusted in conjunction with the mentioned model. Simulation outcomes indicate the efficiency of the presented approach.
Analysis and Applications of Magnetically Coupled Resonant Circuits
Authors: Hałgas Stanisław , Hausman Sławomir , Jopek Łukasz
Published: January 2025

Magnetically coupled resonant circuits have been utilized in radio engineering for many years. Recently, these circuits have found new applications, particularly in supplying low- and medium-power devices through medium-range wireless power transmission technology based on magnetic resonance coupling. There is also a growing need to analyze magnetically coupled resonant circuits in the design of metamaterials, which exhibit specific electromagnetic properties within certain frequency bands. This paper provides a coherent and concise overview of the phenomena associated with magnetically coupled resonant circuits. The results encompass numerous established relations as well as new ones. They can be helpful in the design phase of magnetically coupled resonant circuits. The outcomes include equations for determining the coupling resonant frequencies and some parameters of resonance curves. These analytical results are accompanied by 3D and cross-sectional (contour) graphs for better visualization. Moreover, a lumped-element circuit model that includes magnetically coupled resonant circuits is proposed for the resonators used in metamaterials. Formulas for resonant frequencies are derived in the specific case of exciting such resonators. To validate the accuracy of the derived equations, the analytical results are compared with simulations from SPICE (IsSPICE4 ver. 8.1) and COMSOL 5.4 software, which are widely used tools for circuit analysis and electromagnetic simulations. The results of these comparative analyses indicate that the assumptions employed in the analytical solutions introduce only tiny errors.
TCAD-Based Analysis on the Impact of AlN Interlayer in Normally-off AlGaN/GaN MISHEMTs with Buried p-Region
Authors: Hamady Saleem , Beydoun Bilal , Morancho Frédéric
Published: January 2025

With the growing demand for more efficient power conversion and silicon reaching its theoretical limit, wide bandgap semiconductor devices are emerging as a potential solution. For instance, Gallium Nitride (GaN)-based high-electron-mobility transistors (HEMTs) are getting more attention, and several structures for the normally off operation have been proposed. Adding an AlN interlayer in conventional AlGaN/GaN normally on HEMT structures is known to enhance the current density. In this work, the effect of an AlN interlayer in the normally off AlGaN/GaN MISHEMT with a buried p-region was investigated using a TCAD simulation from Silvaco. The added AlN interlayer increases the two-dimensional electron gas density, requiring a higher p-doping concentration to achieve the same threshold voltage. The simulation results show that the overall effect is a reduction in the device’s current density and peak transconductance by 21.83% and 44.4%, respectively. Further analysis of the current profile shows that because of the buried p-region and at high gate voltages, the current flows near the AlGaN/GaN interface and along the insulator/AlGaN interface. Adding an AlN interface blocks the migration of channel electrons to the insulator/AlGaN interface, resulting in a lower current density.
Features of Hydrogen-Enriched Methane–Air Flames Propagating in Hele-Shaw Channels
Authors: Yakush Sergey , Rashkovskiy Sergey , Alexeev Maxim , Semenov Oleg
Published: January 2025

Mixtures of hydrogen with common hydrocarbon fuels are considered viable for reducing carbon footprint in modern industry, power production, and transportation. The addition of hydrogen alters the kinetics and thermophysical properties of the mixtures, as well as the composition and properties of combustion products, requiring detailed research into the features of flame propagation in hydrogen-enriched hydrocarbon–air mixtures. Of particular interest are also the safety aspects of such fuels. In this paper, experimental results are presented on the premixed laminar flame propagation in channels formed by two closely spaced plates (Hele-Shaw cell), with the internal straight walls forming a diverging (diffuser) channel with the opening angles between 5 and 25 degrees. Methane–hydrogen–air mixtures with the hydrogen relative contents of 0%, 25%, and 50% and global equivalence ratio of unity were ignited by a spark near the closed narrow end of the channel. Experiments were performed with the gap width of 3.5 mm; video recordings were processed in order to determine the quantitative features of the flame front propagation (leading and trailing point coordinate, coordinates of the cusps, cell sizes and shapes). The main features of flame propagation (fast initial expansion, development of cellular flame, self-induced longitudinal oscillations) are obtained and compared to clarify the effect of hydrogen contents in the fuel and channel geometry (gap width, opening angle).
Sensors on Flapping Wings (SOFWs) Using Complementary Metal–Oxide–Semiconductor (CMOS) MEMS Technology
Authors: Yang Lung-Jieh , Wang Wei-Cheng , Tasupalli Chandrashekhar , Esakki Balasubramanian , Shaik Mahammed Inthiyaz
Published: January 2025

This article presents a framework of using MEMS sensors to investigate unsteady flow speeds of a flapping wing or the new concept of sensors on flapping wings (SOFWs). Based on the implemented self-heating flow sensor using U18 complementary metal–oxide–semiconductor (CMOS) MEMS foundry provided by the Taiwan Semiconductor Research Institute (TSRI), the compact sensing region of the flow sensor was incorporated for in situ diagnostics of biomimetic flapping issues. The sensitivity of the CMOS MEMS flow sensor, packaged with a parylene coating of 10 μm thick to prolong the lifetime, was observed as −3.24 mV/V/(m/s), which was below the flow speed of 6 m/s. A comprehensive investigation was conducted on integrating CMOS MEMS flow sensors on the leading edge of the mean aerodynamic chord (m.a.c.) of the flexible 70-cm-span flapping wings. The interpreted flow speed signals were checked and demonstrated similar behavior with the (net) thrust force exerted on the flapping wing, as measured in the wind tunnel experiments using the force gauge. The experimental results confirm that the in situ measurements using the concept of SOFWs can be useful for measuring the aerodynamic forces of flapping wings effectively, and it can also serve for future potential applications.