bluuebunny/crossref_metadata_2025 huggingface dataset:
Soluble PD-L1 and Serum Vascular Endothelial Growth Factor-B May Independently Predict Prognosis in Patients with Advanced Non-Small Cell Lung Cancer Treated with Pembrolizumab
Authors: Kokkotou Eleni , Grapsa Dimitra , Papadopoulou Anna , Gaitanakis Stylianos , Bakakos Petros , Poulakou Garyfallia , Moutsatsou Paraskevi , Syrigos Konstantinos
Published: January 2025

Background: Previous preclinical data have shown that the dynamic cross-talk between abnormal tumor vasculature and immune cell factors in the tumor microenvironment may exert a critical role in the progression and treatment resistance of non-small cell lung cancer (NSCLC). In the clinical setting, a variety of blood-based angiogenesis- and immune-related factors are being increasingly investigated as potential biomarkers of prognosis or treatment response in immunotherapy-treated NSCLC. We herein aimed to evaluate the clinical relevance of the peripheral blood levels of vascular endothelial growth factor-A and -B (VEGF-A and VEGF-B, respectively), soluble programmed cell death-1 (sPD-1), and programmed cell death-ligand 1 (sPD-L1) in patients with advanced NSCLC treated with immune checkpoint inhibitors (ICIs). Methods: Consecutive patients with advanced-stage, non-oncogene-addicted NSCLC, eligible to receive ICIs at the Oncology Unit of Sotiria Athens General Hospital, were prospectively recruited. A group of sex- and age-matched healthy controls was also enrolled for the evaluation of the potential diagnostic significance of the examined biomarkers. Serum levels of all biomarkers were measured using ELISA, both before and after treatment, and were correlated with standard clinicopathological features of patients, treatment response, progression-free survival (PFS), and overall survival (OS). Results: A total of 55 patients and 16 healthy controls were included in the final analysis. The mean age of patients and controls was 66.5 years (SD = 8.0 years) and 65.4 years (SD = 9.1 years), respectively. The majority of patients (65.5%) received pembrolizumab in combination with chemotherapy, while the remaining patients received pembrolizumab monotherapy. ROC curve analysis showed that VEGFB and sPD-1 were the only markers with a significant diagnostic value. Higher pre-treatment values of sPD-L1 (HR = 1.68; p = 0.040) and sPD-1 (HR = 10.96; p = 0.037) as well as higher post-treatment values of VEGF-B (HR = 2.99; p = 0.049) were all significantly associated with a reduced OS in univariate Cox regression analysis. The adverse prognostic significance of higher pre-treatment values of sPD-L1 (HR = 2.10; p = 0.014) and higher post-treatment values of VEGFB (HR = 3.37; p = 0.032) was further confirmed in multivariate analysis. Conclusions: Our study results suggest that serum levels of sPD-L1 and VEGF-B may independently predict prognosis in ICI-treated advanced-stage NSCLC.
Metabolomic Exploration of Colorectal Cancer Through Amino Acids and Acylcarnitines Profiling of Serum Samples
Authors: Avram Lucreția , Crișan Dana , Moldovan Radu-Cristian , Bogos Luisa-Gabriela , Iuga Cristina-Adela , Andraș David , Crișan Sorin , Bodolea Constantin , Nemeş Andrada , Donca Valer
Published: January 2025

Background/Objectives: Colorectal cancer (CRC) represents one of the most prevalent forms of cancer, with high mortality rates. The aim of this study was to observe and understand the metabolic changes in CRC through targeted metabolomics. Methods: Samples collected from 58 CRC patients and 35 healthy individuals have been analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), targeting two classes of metabolites: amino acids and acylcarnitines. Results: Statistical analysis revealed 26 significantly modified (p-value < 0.01; |FC| > 1.2) metabolites in CRC patients compared to the control group and 22 between colon cancer and control, whereas 8 metabolites differed only significantly between rectal cancer and healthy patients. Some of these significantly modified metabolites characterize cancer-specific adaptations, such as increased energy demand, increased tumor invasiveness, capabilities to promote amino acid synthesis, and tumor resistance against acute immune response. Moreover, receiver operator characteristic (ROC) analysis revealed that a set of two acylcarnitines (C6DC and C4-OH) can differentiate between CRC patients and healthy individuals with a high degree of confidence (AUC 0.837). Conclusions: By implementing a metabolomics approach targeting amino acids and acylcarnitines, several metabolic alterations induced by CRC have been highlighted. Even though these modifications are not specific enough to act as disease markers, they might prove useful for evaluating patient status.
Correction: Bertuzzi et al. Microenvironmental Traits of Classical Hodgkin’s Lymphoma in Adolescents and Their Prognostic Impact. Cancers 2024, 16, 4210
Authors: Bertuzzi Clara , Righi Simona , Motta Giovanna , Rossi Maura , Carella Matteo , Gabrielli Giulia , Facchini Elena , Baldassarre Maurizio , Prete Arcangelo , Zinzani Pier Luigi , Mascolo Massimo , Agostinelli Claudio , Sabattini Elena
Published: January 2025

Massimo Mascolo was not included as an author in the original publication [...]
Improving Treatment Options for Patients with Double Refractory CLL
Authors: Jacobs Ryan , Wierda William
Published: January 2025

The proliferation and survival of chronic lymphocytic leukemia (CLL) cells are heavily dependent on B-cell receptor (BCR) signaling and resistance to apoptosis. Approvals of multiple covalent Bruton’s tyrosine kinas inhibitors (cBTKis) as well as the B-cell lymphoma-2 inhibitor (BCL2i) venetoclax targeting these pathways have revolutionized the treatment of CLL and small lymphocytic lymphoma (SLL). The superiority of these treatments over chemoimmunotherapy has been proven in phase III studies in both treatment-naïve and relapsed refractory settings, leading to the majority of patients with CLL being treated sequentially with cBTKis and the BCL2i venetoclax as their first- and second-line therapies. While most patients with CLL respond for many years to these sequenced treatments, they are unfortunately not curative. There remains an unmet need for effective treatment options for patients who progressed after treatment with both cBTKis and BCL2i, also referred to as double refractory patients. Treatment options for double refractory CLL has improved recently with the approval of the non-covalent BTK inhibitor (ncBTKi) pirtobrutinib as well as the CD19 targeted chimeric antigen receptor T-cell (CAR T-cell) therapy lisocabtagene maraleucel (liso-cel). These recently approved treatment options for patients with CLL with at least two prior lines of therapy have fortunately demonstrated efficacy for double refractory CLL. Additionally, there are several novel treatment options in clinical development, including bi-specific antibodies, second-generation BCL2is, new ncBTKis, and BTK degraders. Understanding resistance mechanisms to existing cBTKis and venetoclax can potentially inform us of the best utilization of available treatment options for double refractory CLL and provide a personalized approach for these patients. In this review, a challenging example of a double refractory patient with CLL will serve as the basis for a review of available literature on the treatment of double refractory CLL/SLL.
Histopathological Features of Hepatocellular Carcinoma in Patients with Hepatitis B and D Virus Infection: A Single-Institution Study in Mongolia
Authors: Jargalsaikhan Orgil , Shao Wenhua , Ichimura-Shimizu Mayuko , Ishimaru Soichiro , Koma Takaaki , Nomaguchi Masako , Ogawa Hirohisa , Tachibana Shotaro , Chimeddorj Battogtokh , Batchuluun Khongorzul , Tseveenjav Anujin , Magvan Battur , Enkhbat Bayarmaa , Lkhagvadorj Sayamaa , Mendjargal Adilsaikhan , Ganbaatar Lkhagvadulam , Irahara Minoru , Akaike Masashi , Boldbaatar Damdindorj , Tsuneyama Koichi
Published: January 2025

Background: Viral hepatitis, particularly hepatitis B (HBV) and hepatitis C (HCV), is highly prevalent in Mongolia. Moreover, Mongolia has the highest prevalence of hepatitis delta virus (HDV) globally, with over 60% of HBV-infected individuals also co-infected with HDV. Since HBV/HDV infections accelerate liver disease progression more compared to HBV infection alone, urgent national health measures are required. Method: This study presents a clinicopathological analysis of 49 hepatocellular carcinoma cases surgically resected at the Mongolia–Japan Hospital of the Mongolian National University of Medical Sciences. Results: HBV infection was found in 27 (55.1%) cases of all HCC cases. Immunohistochemical staining of the liver revealed that 14 (28.6%) cases were HDV antigen-positive in the HCC cases. HDV-positive cases exhibited significantly higher inflammatory activity compared to HDV-negative cases, with lymphocytic infiltrates predominantly composed of CD4-positive cells. Furthermore, HDV-positive cells were spatially distinct from HBs antigen-positive cells, suggesting that HDV-infected cells may interfere with HBV replication. No significant differences in fibrosis or in tumor characteristics were observed between the HDV-positive and negative cases. Early diagnosis of HBV/HDV infections is essential for appropriate treatment and to prevent further domestic transmission of the virus. However, routine testing for HDV infection is rarely conducted in Mongolia. Since HDV-positive cells are morphologically indistinguishable from surrounding HDV-negative cells, routine histopathological analysis may not be sufficient enough to detect HDV infection. Conclusions: Based on this clinicopathological study, CD4 and CD8 immunostaining can be considered an adjunctive diagnostic tool in cases with significant lymphocytic infiltration and hepatocellular damage. Additionally, HDV screening using blood and tissue samples may be recommended to ensure accurate diagnosis.
Contribution of Rare and Common APOE Variants to Familial Hypercholesterolemia in Spanish Cohort
Authors: Vega-Prado Lorena M. , Vázquez-Coto Daniel , Villazón Francisco , Suárez-Gutiérrez Lorena , Martínez-Faedo Ceferino , Menéndez-Torre Edelmiro , Riestra María , González-Martínez Silvia , Gutiérrez-Buey Gala , García-Lago Claudia , Gómez Juan , Alvarez Victoria , Gil Helena , Lorca Rebeca , Coto Eliecer
Published: January 2025

Our aim was to determine whether rare APOE pathogenic variants (PV) and the common e2/e3/e4 polymorphism were associated with the risk of familial hypercholesterolemia (FH). A total of 431 patients who met the inclusion criteria for FH were next-generation sequenced for the main candidate genes (LDLR, APOB, PCSK9, APOE, LDLRAP1). A total of 139 patients (32%) had a pathogenic variant, including 3 with APOE p.Leu167del. Among the PV-negatives (n = 292), one was homozygous for APOE-e2 and showed a combined phenotype of high low-density lipoprotein cholesterol (LDL-C) and triglycerides (TGs). A total of 165 population controls were also genotyped for the APOE polymorphism. PV-negative patients showed a significantly higher frequency of APOE-e3e4/e4e4 compared to PV-positives (p = 0.006) and to population controls (p = 0.0002, OR = 2.63, 95% CI = 1.57–4.40). APOE-e4e4 patients had significantly higher mean LDL-C compared to the other genotypes (p = 0.047). In conclusion, APOE pathogenic variants were a rare cause of FH in our population, and the APOE-e4 allele was a significant risk factor for being diagnosed with familial hypercholesterolemia in the absence of a pathogenic variant involved in FH. In particular, the APOE-e4e4 genotype was associated with higher LDL-C levels compared to the other genotypes.
Recent Advances in Transition Metal Chalcogenides Electrocatalysts for Oxygen Evolution Reaction in Water Splitting
Authors: Gao Honglin , Yang Ting , Dong Aiyi , Xing Yuliang , Liu Dajun , Ma Yinhua , Zhu Kaixin
Published: January 2025

Rapid industrial growth has overexploited fossil fuels, making hydrogen energy a crucial research area for its high energy and zero carbon emissions. Water electrolysis is a promising method as it is greenhouse gas-free and energy-efficient. However, OER, a slow multi-electron transfer process, is the limiting step. Thus, developing efficient, low-cost, abundant electrocatalysts is vital for large-scale water electrolysis. In this paper, the application and progress of transition metal chalcogenides (TMCs) as catalysts for the oxygen evolution reaction in recent years are comprehensively reviewed. The key findings highlight the catalytic mechanism and performance of TMCs synthesized using single or multiple transition metals. Notably, modifications through recombination, heterogeneous interface engineering, vacancy, and atom doping are found to effectively regulate the electronic structure of metal chalcogenides, increasing the number of active centers and reducing the adsorption energy of reaction intermediates and energy barriers in OER. The paper further discusses the shortcomings and challenges of TMCs as OER catalysts, including low electrical conductivity, limited active sites, and insufficient stability under harsh conditions. Finally, potential research directions for developing new TMC catalysts with enhanced efficiency and stability are proposed.
Sensitive Electrochemical Sensor Based on Amino-Functionalized Graphene Oxide/Polypyrrole Composite for Detection of Pb2+ Ions
Authors: Zine Priyanka C. , Narwade Vijaykiran N. , Patil Shubham S. , Qureshi Masira T. , Tsai Meng-Lin , Hianik Tibor , Shirsat Mahendra D.
Published: January 2025

In this work, an amino-functionalized graphene oxide/polypyrrole (AMGO/PPy) composite-based novel sensing platform was established to monitor lead ions (Pb2+) at high sensitivity. AMGO was synthesized through a hydrothermal process and later formed a composite with PPy at varying concentrations. A physicochemical investigation of the synthesized materials was carried out using various characterization tools, while the electrochemical properties were examined by cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS) methods. The AMGO/PPy composite was deposited on a glassy carbon electrode (GCE), which was used for the real-time electrochemical detection of Pb2+. The AMGO/PPy sensor exhibited lower limits of detection (LOD) of 0.91 nM. In addition, the developed Pb2+ sensor exhibited excellent reproducibility, repeatability, selectivity, sensitivity, and long-term stability for 25 days. The AMGO/PPy composite emerges as a ground-breaking material for the electrochemical detection of Pb2+, holding significant potential for environmental monitoring and the protection of human health.
Wearable Neurotechnology for the Treatment of Insomnia: The Study Protocol of a Prospective, Placebo-Controlled, Double-Blind, Crossover Clinical Trial of a Transcranial Electrical Stimulation Device
Authors: Caswell Keenan , Roe Grace , Odafe Emamoke , Arora Subodh , Motoni Caddie , Werner John Kent
Published: January 2025

Sleep disruption and deprivation are epidemic problems in the United States, even among those without a clinically diagnosed sleep disorder. Military service members demonstrate an increased risk of insomnia, which doubles after deployment. This study will investigate the ability of a translational device, Teledyne PeakSleep™ (Teledyne Scientific & Imaging, Durham, NC, USA), to reduce sleep onset latency and the time spent awake after sleep onset, with improvement in the subjective benefits of sleep for patients with insomnia by enhancing the brain rhythms within the frontal lobe implicated in slow wave generation. During this crossover trial, patients will use the wearable neurotechnology prototype headband, which delivers < 14 min of frontal short duration repetitive–transcranial electrical stimulation over a 30 min period immediately before trying to fall asleep. Using active stimulation versus a sham paradigm, we will compare actigraphy data, physiological data, and subjective sleep measures against a pre-treatment baseline in the same patient over the course of the 8-week study. If successful, PeakSleep™ could address the final common pathway in insomnia, namely the onset and maintenance of slow-wave sleep (SWS), and accordingly has the potential to enhance sleep onset in a wide range of individuals, most importantly warfighters in whom efficient sleep onset may be critical for operational success.
Flexible Electrospun Polyacrylonitrile/ZnO Nanofiber Membrane as Separator for Sodium-Ion Batteries with Cycle Stability
Authors: Mu Xin , Yin Xiangyu , Qi Meili , Yusuf Abdulla , Liu Shibin
Published: January 2025

In sodium-ion batteries, the research of electrode and separator materials must work in tandem. However, the existing separators still need to go through a drawn-out procedure in order to satisfy the engineering and technological standards of sodium-ion batteries. A new sodium-ion battery separator was created for this investigation. Electrostatic spinning was used to create polyacrylonitrile (PAN)/ZnO nanofiber films, and varying the ZnO nanoparticle doping level enhanced the nanofiber separator’s cyclic stability. A new flexible PAN separator for sodium-ion batteries is presented in this study. It has good commercial value and may find use in flexible, high safety sodium-ion battery systems. Additionally, it offers some theoretical direction for creating organic polymer separators with excellent safety.
Evaluating Pediatric NAFLD with Controlled Attenuation Parameter: A Comprehensive Narrative Review
Authors: Arteaga Ingrid , Chacón Carla , Martínez-Escudé Alba , Rojano Irene Ruiz , Diez-Fadrique Galadriel , Carmona-Cervelló Meritxell , Torán-Monserrat Pere
Published: January 2025

Non-alcoholic fatty liver disease (NAFLD) in the pediatric population has emerged as a significant health concern due to its alarming rise in prevalence. In children, the characteristics of the disease differ from those seen in adults. NAFLD may progress to more severe liver disease in children compared to adults with similar profiles. Liver biopsy remains the gold standard for diagnosis; its invasive nature and high cost limit its use as a first-line tool. Alternatively, magnetic resonance imaging (MRI) techniques, such as magnetic resonance imaging-estimated liver proton density fat fraction (MRI-PDFF), have shown a good correlation with the degree of histological steatosis, although their use is limited by high costs and limited accessibility. Controlled attenuation parameter (CAP), integrated with vibration-controlled transient elastography (VCTE) (FibroScan®), is a novel non-invasive, accessible, and effective method for diagnosing hepatic steatosis. In this article, we reviewed the existing literature on the diagnostic accuracy of CAP in pediatric NAFLD. The PubMed and EMBASE databases were searched. Seven relevant studies were identified, conducted in pediatric hospital populations with specific demographic characteristics. Two of these studies compared CAP with liver biopsy, one compared CAP with liver biopsy and MRI-PDFF, and the remaining four compared CAP with MRI. Overall, CAP proved to be accurate in detecting the presence or absence of fatty infiltration, positioning it as a promising tool to simplify the diagnosis of NAFLD in children. However, further studies in larger populations are needed to confirm these findings and facilitate its implementation in routine clinical practice.
Development and Validation of a Machine Learning Model for Early Prediction of Sepsis Onset in Hospital Inpatients from All Departments
Authors: Thiboud Pierre-Elliott , François Quentin , Faure Cécile , Chaufferin Gilles , Arribe Barthélémy , Ettahar Nicolas
Published: January 2025

Background: With 11 million sepsis-related deaths worldwide, the development of tools for early prediction of sepsis onset in hospitalized patients is a global health priority. We developed a machine learning algorithm, capable of detecting the early onset of sepsis in all hospital departments. Methods: Predictors of sepsis from 45,127 patients from all departments of Valenciennes Hospital (France) were retrospectively collected for training. The binary classifier SEPSI Score for sepsis prediction was constructed using a gradient boosted trees approach, and assessed on the study dataset of 5270 patient stays, including 121 sepsis cases (2.3%). Finally, the performance of the model and its ability to detect early sepsis onset were evaluated and compared with existing sepsis scoring systems. Results: The mean positive predictive value of the SEPSI Score was 0.610 compared to 0.174 for the SOFA (Sepsis-related Organ Failure Assessment) score. The mean area under the precision–recall curve was 0.738 for SEPSI Score versus 0.174 for the most efficient score (SOFA). High sensitivity (0.845) and specificity (0.987) were also reported for SEPSI Score. The model was more accurate than all tested scores, up to 3 h before sepsis onset. Half of sepsis cases were detected by the model at least 48 h before their medically confirmed onset. Conclusions: The SEPSI Score model accurately predicted the early onset of sepsis, with performance exceeding existing scoring systems. It could be a valuable predictive tool in all hospital departments, allowing early management of sepsis patients. Its impact on associated morbidity-mortality needs to be further assessed.
Novel Pathways of Oxidative and Nitrosative Inactivation of the Human MGMT Protein in Colon Cancer and Glioblastoma Cells: Increased Efficacy of Alkylating Agents In Vitro and In Vivo
Authors: Basak Debasish , Mostofa Agm , Madala Hanumantha Rao , Srivenugopal Kalkunte S.
Published: January 2025

Background: O6-Methylguanine-DNA methyltransferase (MGMT) is a unique antimutagenic DNA repair protein that plays a crucial role in conferring resistance to various alkylating agents in brain tumor therapy. In this study, we exploited the susceptibility of the active site Cys145 of MGMT for thiolation and nitrosylation, both of which inactivate the enzyme. Methods: We designed a redox perturbing glutathione mimetic, a platinated homoglutathione disulfide (hGTX) by adding small amounts of cisplatin (1000:10) and used a nitric oxide-donor spermine NONOate. N6022, a potent inhibitor of S-nitrosoglutathione reductase was used to extend the retention of nitrosylated MGMT in tumor cell culture and subcutaneous xenografts. Results: Both hGTX and spermine NONOate inhibited MGMT activity in HT29, SF188, T98G, and other brain tumor cells. There was a robust increase in the alkylation-induced DNA interstrand cross-linking, G2/M cell cycle arrest, cytotoxicity, and the levels of apoptotic markers when either of the agents was used with alkylating agents. In the nude mice bearing T98G and HT29-luc2 xenografts, combinations of hGTX and spermine NONOate with alkylating agents produced a marked reduction in MGMT protein and tumor growth delay and regressions. N6022 treatment increased the presence of nitrosylated MGMT for a longer time, thereby extending the DNA-repair deficient state both in cell culture and preclinical settings. Conclusions: Our findings highlight the options for redox-driven therapeutic strategies for MGMT and suggest that oxidative and/or nitrosative inactivation of DNA repair in combination with alkylating agents could be exploited.
Risk of Insulin Resistance in 44,939 Spanish Healthcare Workers: Association with Sociodemographic Variables and Healthy Habits
Authors: Tárraga Marcos Pedro Javier , López-González Ángel Arturo , Martínez-Almoyna Rifá Emilio , Paublini Oliveira Hernán , Martorell Sánchez Cristina , Tárraga López Pedro Juan , Ramírez-Manent José Ignacio
Published: January 2025

Introduction: Insulin resistance (IR) is a highly prevalent pathophysiological entity implicated in the development of a wide variety of metabolic, cardiovascular, and endocrine disorders. The aim of this study is to assess the association between sociodemographic variables and healthy habits with IR risk scales. Methodology: This dual study, incorporating both longitudinal-retrospective and cross-sectional designs, analyzed healthcare workers across four professional categories (physicians, nurses, healthcare technicians, and auxiliary personnel). It examined the association of age, sex, professional category, smoking status, physical activity, and adherence to the Mediterranean diet with elevated scores on insulin resistance risk scales. Results: All the variables analyzed were associated with the presence of elevated values of the IR scales, with age, sex, and physical activity showing the strongest association (reflected in the odds ratio values). Conclusions: The profile of an individual with a higher risk of presenting elevated values of the IR risk scales would be an elderly male auxiliary health worker who is a smoker and is physically inactive, with a low adherence to the Mediterranean diet.
A Metric for the Entropic Purpose of a System
Authors: Parker Michael C. , Jeynes Chris , Walker Stuart D.
Published: January 2025

Purpose in systems is considered to be beyond the purview of science since it is thought to be intrinsically personal. However, just as Claude Shannon was able to define an impersonal measure of information, so we formally define the (impersonal) ‘entropic purpose’ of an information system (using the theoretical apparatus of Quantitative Geometrical Thermodynamics) as the line integral of an entropic “purposive” Lagrangian defined in hyperbolic space across the complex temporal plane. We verify that this Lagrangian is well-formed: it has the appropriate variational (Euler-Lagrange) behaviour. We also discuss the teleological characteristics of such variational behaviour (featuring both thermodynamically reversible and irreversible temporal measures), so that a “Principle of Least (entropic) Purpose” can be adduced for any information-producing system. We show that entropic purpose is (approximately) identified with the information created by the system: an empirically measurable quantity. Exploiting the relationship between the entropy production of a system and its energy Hamiltonian, we also show how Landauer’s principle also applies to the creation of information; any purposive system that creates information will also dissipate energy. Finally, we discuss how ‘entropic purpose’ might be applied in artificial intelligence contexts (where degrees of system ‘aliveness’ need to be assessed), and in cybersecurity (where this metric for ‘entropic purpose’ might be exploited to help distinguish between people and bots).
An Online Evaluation Method for Random Number Entropy Sources Based on Time-Frequency Feature Fusion
Authors: Sun Qian , Ma Kainan , Zhou Yiheng , Wang Zhaoyuxuan , You Chaoxing , Liu Ming
Published: January 2025

Traditional entropy source evaluation methods rely on statistical analysis and are hard to deploy on-chip or online. However, online detection of entropy source quality is necessary in some applications with high encryption levels. To address these issues, our experimental results demonstrate a significant negative correlation between minimum entropy values and prediction accuracy, with a Pearson correlation coefficient of −0.925 (p-value = 1.07 × 10−7). This finding offers a novel approach for assessing entropy source quality, achieving an accurate rate in predicting the next bit of a random sequence using neural networks. To further improve prediction capabilities, we also propose a novel deep learning architecture, Fast Fourier Transform-Attention Mechanism-Long Short-Term Memory Network (FFT-ATT-LSTM), that integrates a simplified soft attention mechanism with Fast Fourier Transform (FFT), enabling effective fusion of time-domain and frequency-domain features. The FFT-ATT-LSTM improves prediction accuracy by 4.46% and 8% over baseline networks when predicting random numbers. Additionally, FFT-ATT-LSTM maintains a compact parameter size of 33.90 KB, significantly smaller than Temporal Convolutional Networks (TCN) at 41.51 KB and Transformers at 61.51 KB, while retaining comparable prediction performance. This optimal balance between accuracy and resource efficiency makes FFT-ATT-LSTM suitable for online deployment, demonstrating considerable application potential.
Enhancing Watershed Management Through the Characterization of the River Restoration Index (RRI): A Case Study of the Samian Watershed, Ardabil Province, Iran
Authors: Hazbavi Zeinab , Azizi Elham , Ghabelnezam Elnaz , Sharifi Zahra , Davudirad Aliakbar , Fathololoumi Solmaz
Published: January 2025

The mountainous Samian Watershed hosts important rivers recently, significantly triggered by fast and unplanned urbanization, population growth, environmentally hazardous industrialization, and inappropriate dam construction. Nonetheless, this watershed has not yet been evaluated through the lens of river restoration. Therefore, this study aims (1) to apply the River Restoration Index (RRI), (2) to assess the significance of each river restoration criterion and sub-index, and (3) to identify priority hotspots for immediate restoration efforts across 27 sub-watersheds in this case study. First, we built a database containing meteorological, hydrological, land use, physiographic, soil, and economic data. Then, we calculated the general state of the watershed (GSW), connectivity (Con), riverbank conditions (RbC), and hydraulic risk reduction (HRR) sub-indices to develop a multi-domain RRI. Finally, the MEREC-ORESTE hybrid method supported sustainable government planning. The findings reveal significant environmental issues, notably in sanitation conditions, transversal connectivity, and urban encroachment on riverbanks. Sanitation risks were high throughout the watershed, while other eco-environmental risks varied across regions. The weights of 0.36, 0.16, 0.32, and 0.16 were assigned for GSW, Con, RbC, and HRR, respectively, highlighting the importance of GSW and RbC in river restoration activities. Priority management areas (with RRI below 0.50) cover 78% of the watershed.
Exploring ChatGPT’s Role in Higher Education: Perspectives from Pakistani University Students on Academic Integrity and Ethical Challenges
Authors: Alghazo Runna , Fatima Ghulam , Malik Misbah , Abdelhamid Sherif E. , Jahanzaib Muhammad , Nayab Dur e , Raza Ayesha
Published: January 2025

This study investigates the perceptions of university students in Pakistan on the use of ChatGPT in learning. It aims to understand the students’ views on the benefits, challenges, and overall impact of ChatGPT on their academic experiences. A quantitative approach was employed, collecting data from 400 students across various universities in Pakistan through a structured questionnaire. The validity and reliability of the questionnaire were ensured through pilot testing and statistical analysis. The study found that while most students perceive ChatGPT as a beneficial tool for improving their learning, significant concerns remain about academic integrity, over-reliance on artificial intelligence (AI), and the accuracy of information provided by ChatGPT. The findings suggest that perceptions vary across demographic factors such as age, gender, and type of university. These findings can benefit policymakers and educational institutions in effectively integrating AI tools such as ChatGPT into educational systems, ensuring that the value is maximized while addressing potential disadvantages. The study contributes to the existing body of knowledge on AI utilization in education, particularly within the context of developing countries.
Exploring Factors Influencing Depression: Socioeconomic Perspectives Using Machine Learning Analytics
Authors: Kim Cheong
Published: January 2025

Depression is a widespread mental health disorder with significant societal impacts, and while socioeconomic status (SES) is a well-established determinant, limited research has explored the unique factors influencing depression in South Korea, such as educational pressure, long working hours, and traditional gender roles. Using data from the Korean National Health and Nutrition Examination Survey (KNHANES) collected in 2014, 2016, 2018, 2020, and 2022, this study analyzed 24,308 participants to examine the relationship between SES and depression. Depression was measured using the Patient Health Questionnaire-9 (PHQ-9), and twelve socioeconomic variables, including income, education, marital status, and working hours, were assessed using logistic regression models. The findings revealed that monthly income, age, marital status, and weekly working hours were significant predictors of depression, with higher income levels unexpectedly associated with greater depression scores, potentially due to increased stress. Gender, household size, and educational attainment were also notable contributors. This study underscores the complex interplay of SES factors and depression in South Korea’s distinct sociocultural context and highlights the need for mental health policies addressing both economic and psychological stressors, particularly for higher income individuals and women. Future research should further explore these dynamics to develop culturally sensitive mental health interventions.
Enhancing Real-Time Video Streaming Quality via MPT-GRE Multipath Network
Authors: Al-Imareen Naseer , Lencse Gábor
Published: January 2025

The demand for real-time 4K video streaming has introduced technical challenges due to the high bandwidth, low latency, and minimal jitter required for high-quality user experience. Traditional single-path networks often fail to meet these requirements, especially under network congestion and packet loss conditions, which degrade video quality and disrupt streaming stability. This study evaluates Multipath tunnel- Generic Routing Encapsulation (MPT-GRE), a technology designed to address these challenges by enabling simultaneous data transmission across multiple network paths. By aggregating bandwidth and adapting dynamically to network conditions, MPT-GRE enhances resilience, maintains quality during network disruptions, and offers throughput nearly equal to the sum of its physical paths’ throughput. This feature ensures that even if one path fails, the technology seamlessly continues streaming through the remaining path, significantly reducing interruptions. We measured key video quality metrics to assess MPT-GRE’s performance: Structural Similarity Index Measure (SSIM), Mean Squared Error (MSE), and Peak Signal-to-Noise Ratio (PSNR). Our results confirm that the MPT-GRE tunnel effectively improves SSIM, PSNR, and reduces MSE compared to single-path streaming, offering a more stable, high-quality viewing experience. Our results indicate that analyzing the SSIM, MSE, and PSNR values for 4K video streaming using the MPT tunnel demonstrates a significant performance improvement compared to a single path. The improvement percentages of the SSIM and PSNR values for the MPT tunnel are (29.05% and 29.04%) higher than that of the single path, while MSE is reduced by 81.17% compared to the single path.
Design Strategies for BCAT Structures: Enhancing DRAM Reliability and Mitigating Row Hammer Effect
Authors: Im Jisung , Kim Hansol , Kim Hyungjin , Woo Sung Yun
Published: January 2025

This study investigates the impact of four parameters—gate angles, fin height controlled through gate overlaps and the distance from fin to source/drain, and substrate bottom doping concentration—on the row hammer effect (RHE) in DRAM cells. The influence of adjacent and passing gates on the DRAM cell body potential was identified as a key factor in D0 and D1 failures. The tolerance for D1 and D0 failures was analyzed, defined as the threshold number of pulses required to induce a 0.6 V change in the storage node voltage (from 1.2 V to 0.6 V for a D1 failure or from 0 V to 0.6 V for a D0 failure). D1 (D0) failure tolerances with the slope from the top of the top gate (θangle) of 3°, the height of the TiN gate covering the fin (Hfin_overlap) of 12.5 nm, and the height of the fin (Hfin) of 12.5 nm are 1.26 × 106 (4.8 × 106), 1.14 × 106 (4 × 107), and 7.5 × 105 (4.8 × 105), respectively. Higher θangles and smaller fin heights generally result in higher RHE tolerances. Although decreasing the fin height reduced the RHE, it also decreased the on-current and resulted in an increase in the threshold voltage (VT) and the subthreshold swing (SS). In addition, by increasing the substrate bottom doping concentration (Pdop_bot), we improve RHE tolerance twice its original level without reducing the on-current. Therefore, designing a buried channel array transistor (BCAT) structure requires careful consideration of these trade-offs, and a thorough understanding of the underlying mechanism is crucial to devising strategies that reduce RHE tolerance. The findings of this study are expected to contribute significantly to the development of next-generation DRAM architectures, enhancing stability and performance. By addressing the reliability challenges posed by advanced scaling, this study paves the way for the ongoing advancement of DRAM technology for high-density and high-performance applications.
MSQuant: Efficient Post-Training Quantization for Object Detection via Migration Scale Search
Authors: Jiang Zhesheng , Li Chao , Qu Tao , He Chu , Wang Dingwen
Published: January 2025

YOLO (You Only Look Once) has become the dominant paradigm in real-time object detection. However, deploying real-time object detectors on resource-constrained platforms faces challenges due to high computational and memory demands. Quantization addresses this by compressing and accelerating CNN models through the representation of weights and activations with low-precision values. Nevertheless, the quantization difficulty between weights and activations is often imbalanced. In this work, we propose MSQuant, an efficient post-training quantization (PTQ) method for CNN-based object detectors, which balances the quantization difficulty between activations and weights through migration scale. MSQuant introduces the concept of migration scales to mitigate this disparity, thereby improving overall model accuracy. An alternating search method is employed to optimize the migration scales, avoiding local optima and reducing quantization error. We select YOLOv5 and YOLOv8 models as the PTQ baseline, followed by extensive experiments on the PASCAL VOC, COCO, and DOTA datasets to explore various combinations of quantization methods. The results demonstrate the effectiveness and robustness of MSQuant. Our approach consistently outperforms other methods, showing significant improvements in quantization performance and model accuracy.
Sales Forecasting for New Products Using Homogeneity-Based Clustering and Ensemble Method
Authors: Hwang Seongbeom , Lee Yuna , Jeon Byoung-Ki , Oh Sang Ho
Published: January 2025

Accurate sales forecasting for new products is critical in industries characterized by intense competition, rapid innovation, and short product life cycles, such as the smartphone market. This study proposes a data-driven framework that enhances prediction accuracy by combining homogeneity-based clustering with an ensemble learning approach. Unlike traditional methods that depend on product-specific attributes, our approach utilizes historical sales data from similar products, overcoming attribute dependency. Using K-means clustering, the training data are segmented into homogeneous groups, and tailored ensemble forecasting models are developed for each cluster by combining five machine learning models: Random Forest, Extra Tree, XGBoost, LightGBM, and TabNet. When tested on South Korean smartphone sales data, the framework achieves superior performance, with the optimal ensemble model using four clusters delivering an MAPE of 8.3309% and an RMSPE of 7.8360%, significantly outperforming traditional single-cluster models. These findings demonstrate the effectiveness of leveraging data homogeneity and ensemble methods, offering a scalable and adaptable solution for accurate sales forecasting of new products.
Quantitative Analysis Method of Conversion of Type of Microscopic Remaining Oil Based on CT Technology
Authors: Feng Chun , Sun Linghui , Yang Zhengming
Published: January 2025

The distribution and mutual conversion of remaining oil during the process of oilfield development constitute an important basis for guiding the exploitation of remaining oil potential. Based on the visual core displacement method of CT scanning technology, CT scanning images of the oil–water phase in core models at different displacement stages were obtained, and the remaining oil types were classified. On this basis, image segmentation technology was employed to establish the transformation analysis method of remaining oil types, and the mutual transformation of microscopic remaining oil types at different displacement stages was clarified. The ability of displacement media to utilize various remaining oils was further clarified. The results demonstrate that there are significant differences in the distribution of remaining oil after the injection of different displacement media. The displacement media can not only spread the continuous-phase oil in large pores to varying degrees but also transform the discontinuous oil into continuous-phase oil in some small pore tubes, showing a “converging” transformation law, thereby enhancing the utilization degree of various remaining oils. Additionally, the surfactant’s unique capabilities of “micellar solubilization, emulsification, and oil carrying” have good adaptability to the discontinuous oil phase and can transform the discontinuous-phase remaining oil into continuous-phase remaining oil, namely columnar–film–cluster–recovery.
Collaborative Control and Intelligent Optimization of a Lead–Bismuth Cooled Reactor Based on a Modified PSO Method
Authors: Yan Shoujun , Zhou Lijie , Song Lifeng , Guo Huiyu , Wu Junliang , Luo Run , Zhao Fuyu
Published: January 2025

Accelerator-driven subcritical (ADS) reactors with lead–bismuth eutectic (LBE) coolants are some of the Gen-IV nuclear energy systems that can generate clean electricity and potentially transmute spent fuel. The dynamic characteristics and control strategy of an ADS reactor are substantially different from those of traditional nuclear reactors. In this paper, a new collaborative control strategy is proposed using an accelerator beam and a control rod, and the control system’s parameters are optimized using a modified particle swarm optimization (PSO) method. To test the control performance, a simulation platform is developed with a nonlinear reactor dynamic model, a power compensation control system and a coolant temperature control system. Four typical control transients are used, including a ±10% full-power (FP) step change load and a ±5% FP/min linear variable load. The simulation results show that the collaborative control strategy has a better load tracking capability and a higher power control accuracy than the beam single-control strategy and the rod single-control strategy. The results also show that the performance of the collaborative control system in terms of the reactor’s power and coolant temperature is significantly improved based on the modified PSO parameter optimization.
How Does the Interplay Between Banking Performance, Digitalization, and Renewable Energy Consumption Shape Sustainable Development in European Union Countries?
Authors: Manta Alina Georgiana , Gherțescu Claudia , Bădîrcea Roxana Maria , Manta Liviu Florin , Popescu Jenica , Lăpădat Cătălin Valentin Mihai
Published: January 2025

In the context of current global challenges, the integration of digitalization, financial performance, and renewable energy is pivotal in fostering sustainable and resilient economic development. The aim of this paper is to explore the interplay between banking performance, digitalization, and renewable energy consumption in the context of the European Union (EU), with a focus on sustainable economic development. This study examines the extent to which the digitalization and efficiency of the banking sector influence the uptake of renewable energy considering the EU’s environmental and economic priorities. The methodology used involves an econometric analysis based on statistical data from EU countries, using Fully Modified Ordinary Least Squares (FMOLS) to assess causal relationships between variables, complemented by Vector Autoregression (VAR) models and Granger causality tests to further investigate the dynamic interactions among the variables. The data were analyzed to examine the correlation between banking performance, digitalization, and renewable energy consumption levels. The results reveal a positive correlation between greater digitalization in the banking sector, stronger financial performance, and higher investments in renewable energy sources. These factors also support the transition to a green economy, but the effect varies between EU countries depending on national policies and existing digital infrastructure. Recommendations for policymakers include stimulating digitalization in the financial sector, creating a regulatory framework to encourage green energy investments, and strengthening collaboration between financial institutions and the energy sector to facilitate the transition to renewables. This paper also suggests a fiscal policy conducive to technological innovation and digitalization to accelerate the uptake of renewable energy.
Research on Equalization Strategy of Lithium-Ion Battery Based on Temperature and SOC Adaptive Fuzzy Control
Authors: Su Xingyang , Zou Guoping , An Siguang , Zou Hongliang , Wang Xueyan
Published: January 2025

To enhance equalization efficiency and address the issue of traditional equalization methods overlooking temperature factors, this paper proposes a multilayer equalization circuit for both intra-group and inter-group balancing. The traditional Buck-Boost equalization topology between groups is improved by incorporating a two-way interleaved inductor structure, which helps reduce equalization idle time. An adaptive fuzzy control equalization strategy for multiple objectives is applied to the topology. The state of charge (SOC) and temperature of the battery are used as key variables for equalization, with the equalization current dynamically adjusted based on changes in the SOC and temperature. This approach improves the balance between equalization speed and temperature control, reducing equalization time while limiting battery temperature rise. A simulation model is developed using MATLAB/Simulink. The simulation results demonstrate that, compared to the traditional Buck-Boost equalization topology, the proposed topology reduces equalization time by 15.1%. Additionally, under three different operating conditions, the equalization cotnrol strategy designed in this paper improves time efficiency by over 14% compared to traditional methods, while also reducing both the maximum temperature and temperature difference.
A Review of Diagnostic Methods for Yaw Errors in Horizontal Axis Wind Turbines
Authors: Li Qian , Chen Danyang , Lin Hangbing , Yang Xiaolei
Published: January 2025

Yaw errors occur in wind turbines either during the installation stage or because of the aging of devices. It reduces the wind speed in the rotor axial direction and increases the structural loads in the lateral direction. Diagnosing yaw error rapidly and accurately is crucial for avoiding the introduced under-performance. In this review paper, we first introduce the fundamental concepts and principles of wind turbine yaw control strategies, and we discuss two types of yaw errors (i.e., the static yaw error and the dynamic yaw error) with their corresponding causes. Subsequently, we outline the existing yaw error diagnostic methods, which are based on the LiDAR (light detection and ranging) data, the SCADA (supervisory control and data acquisition) data, or a combination of the two, and we discuss the advantages and disadvantages of various methods. At last, we emphasize that the diagnostic performance can be improved via the combination of the LiDAR data and the SCADA data, and it benefits from an in-depth understanding of the salient features and influential factors associated with the yaw error. Meanwhile, the potential of intelligent clusters and digital twins for detecting yaw errors is discussed.