bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermal Analysis and Evaluation of Memristor-based Compute-in-Memory Chips
Authors: Ma Awang , Gao Bin , Yao Peng , Tang Jianshi , Qian He , Wu Huaqiang
Published: January 2025

The rapid advancement of artificial intelligence (AI) technologies has significantly increased the demand for high-performance computational hardware. Resistive Random-Access Memory (RRAM)-based Compute-in-Memory (CIM) technology shows great potential for addressing the data transfer bottleneck and supporting high-performance computing (HPC). In this paper, a multi-scale thermal model is developed to evaluate the temperature distribution in RRAM-based CIM chips and the influence of various factors on thermal behavior. The results indicate that hotspot temperatures can be mitigated by reducing the epoxy molding compound (EMC) thickness, increasing the substrate thickness, and lowering boundary thermal resistance. Moreover, optimizing the layout of analog computing circuits and digital circuits can reduce the maximum temperature by up to 4.04℃. Furthermore, the impact of temperature on the conductance of RRAM devices and the inference accuracy of RRAM-based CIM chips is analyzed. Simulation results reveal that thermal-induced accuracy loss in CIM chips is significant, but the computation correction method effectively reduces the accuracy loss from 66.4% to 1.4% at 85 ℃.
Metabolic Dysfunction-Associated Steatotic Liver Disease: Mechanisms Leading to Its Development with a Focus on Methylglyoxal and Counterbalancing Treatment Strategies—A Comprehensive Review
Authors: Berdowska Izabela , Matusiewicz Małgorzata , Fecka Izabela
Published: January 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a multifactorial disorder characterized by an excessive lipids accumulation in the liver which dysregulates this organ’s function. The key contributor to MASLD development seems to be insulin resistance (IR) which affects many organs (including adipose tissue, skeletal muscles and the liver), whereas the molecular background is associated with oxidative, nitrosative and carbonyl stress. Among molecules responsible for carbonyl stress effects, methylglyoxal (MGO) seems to play the major pathological function. MGO—a by-product of glycolysis, fructolysis and lipolysis (from glycerol and fatty acids-derived ketone bodies)—is implicated in hyperglycemia, hyperlipidemia, obesity, type 2 diabetes, hypertension and cardiovascular diseases. Its causative effect in the stimulation of prooxidative and proinflammatory pathways has been well documented. Since metabolic dysregulation leading to these pathologies underlies also MASLD, the role of MGO in MASLD is addressed in this review. Potential MGO participation in the mechanism of MASLD development is discussed in regard to its role in different signaling routes leading to pathological events accelerating the disorder. Moreover, treatment strategies including approved and potential therapies in MASLD are overviewed and discussed. Among them, medications aimed at attenuating MGO-induced pathological processes are addressed.
Etiopathogenic and Therapeutic Considerations in a Multiple Sclerosis Case with Acute Toxic Hepatitis
Authors: Dumitru-Martoiu Maria Melania , Petrescu Simona , Panea Cristina Aura
Published: January 2025

Background/Objectives: In multiple sclerosis (MS) there are many therapeutic options, most of the available drugs causing drug-induced liver injury, after the first infusions. A wide variety of other drugs may cause a spectrum of liver disease, from simple anti-pyretic drugs like paracetamol to multiple dietary herb supplements like Ashwagandha. Methods: 39 years female patient, diagnosed with MS, previously treated with Glatiramer Acetate, Interferon-beta, and current immunomodulatory treatment with Natalizumab (infusion no. 81), with recent history of an airway infection for which she took 4-5 capsules of Paracetamol per day for 7 days, and consumption of dietary supplement with Ashwagandha herbs, who presented with jaundice, pruritus, and lower limbs ecchymoses. Results: Laboratory results revealed higher aminotransferases levels, total bilirubin, and alkaline phosphatase. Screening for autoimmune and infectious hepatitis was negative. The scenario of a toxic hepatitis induced by recently used drugs (Ashwagandha dietary herb supplement and Paracetamol) made the medical team to start therapy with oral prednisone. The clinical and laboratory results progressively improved, with normal levels in liver enzymes and bilirubin, with no further increase after discontinuation of corticosteroid therapy and dietary herb supplement.  Conclusions: This case highlights the difficulty to establish the multiple etiologies and the management of an acute hepatitis in a MS patient with Natalizumab as immunomodulatory treatment, a drug that can induce liver injury after the first infusions, and with recent history of ingestion of toxic hepatic drugs.
Biological Evaluation of Water Quality with the BMWP Index in a Section of the Tlapaneco River Affected by Two Rural Communities in the Guerrero Mountains, Mexico
Authors: Pantiga-Tapia Aide , Rosas-Acevedo José Luis , Guzmán-Martínez María , Solis-Navarrete José Alberto , Bedolla-Solano Ramón , Anzaldúa-Soulé Karla Rosalba
Published: January 2025

Anthropic activities as agriculture and livestock and wastewater discharges affect water quality in the Tlapaneco river in the Montaña region of the state of Guerrero, México, which is a tributary of the great Balsas River that flows from the Montaña and discharges into the Pacific Ocean; the water resource in the localities mentioned is used for agricultural work, recreation, and domestic tasks. The objective of the work was to evaluate quality of the water in the stretch of influence of two localities, Patlicha and Copanatoyac. The instrument used was the BMWP biotic index and some physicochemical parameters. Nine sampling sites were selected according to the perception of the local community with respect to disturbance; the study area was divided into three: high, medium and low. Twenty-seven collections of macroinvertebrates and water were analyzed, in dry and rainy seasons, through the presence-absence of these organisms and physicochemical analysis to evaluate water quality. The results showed that the conditions of the riverbed associated with daily activities and domestic discharges are important factors in the composition of the families. Water quality was very poor to fair according to the macroinvertebrate assemblages collected. The BMWP index with fair quality was when the families Leptohyphidae, Chironomidae, Hydropsychidae, Leptophlebiidae, Baetidae, Simuliidae, Veliidae, Corixidae, Hydrophylidae, Lestidae and Ephemerellidae were present; in sites with poor quality, the families Chironomidae, Leptophlebiidae, Veliidae, Corixidae, Hydropsychidae, Leptohyphidae, Hydrophilidae, Baetidae and Simuliidae were found, while in very poor quality the family present was Corixidae.
Subthreshold Autism and ADHD: A Brief Narrative Review for Frontline Clinicians
Authors: Ogundele Michael O , Morton Michael J S
Published: January 2025

Epidemiological studies have shown that Neurodevelopmental disorders (NDD) such as autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD) are more prevalent in the general childhood population, compared to cases that are formally diagnosed in clinical cohorts. This suggests that many children and youths have NDD which are never diagnosed clinically, causing impairments in some domains of their daily life. There is increasing recognition of the concept of ‘subthreshold’ condition, sometimes used to describe the presence of potentially impairing variations in the neurodevelopmental profile that do not meet criteria for a diagnosis. The aim of this narrative review is to appraise the published literature about common themes regarding subthreshold conditions in relation to Autism and ADHD, identifying any practical lessons that may be applicable to frontline neurodevelopmental clinicians; We searched electronic databases including PMC, Pubmed using various combinations of keywords: Subthreshold, subclinical, neurodevelopmental, childhood, ADHD and ASD; The identified themes include: Definitions, Prevalence, Assessment tools, Lifetime impairments, NDD classification models, Management, Raising public awareness, and Future research directions; The authors propose that a “subthreshold condition” should be recorded when NDD don’t meet the categorical DSM-5 or ICD-11 criteria if there is evidence of significant, persisting impairment in at least one setting.
Comparative Analysis of Pedicle Screw Fixation and Interspinous Devices in Lumbar Spinal Fusion: Clinical and Surgical Outcomes in Degenerative Spine Conditions
Authors: Orlando Vittorio , Galieri Gianluca , Mazzucchi Edoardo , Pignotti Fabrizio , Carcagnì Antonella , Bazzu Paola , Altieri Roberto , Barbarisi Manlio , Olivi Alessandro , Sabatino Giovanni , La Rocca Giuseppe
Published: January 2025

Background/Objectives: Degenerative lumbar spine conditions are a major cause of disability, particularly in elderly patients or those with comorbidities. Surgical treatment often combines decompression and stabilization to address pain and instability. Pedicle screws are the gold standard for stabilization but pose challenges in patients with compromised bone quality. Interspinous devices have emerged as a less invasive alternative, but comparative studies are limited. This study aimed to compare clinical and surgical outcomes of lumbar decompression with stabilization using pedicle screws versus interspinous devices. Methods: A retrospective cohort study was conducted on patients who underwent lumbar decompression with either pedicle screw fixation or interspinous device stabilization at Mater Olbia Hospital between February 2020 and February 2023. Outcomes were evaluated using VAS for back and leg pain, SF-36 for quality of life, EQ-5D, and SCL-90 for psychological factors. Statistical analysis included paired t-tests, chi-square tests, and multivariate regression. Results: A total of 728 patients were included. The interspinous device group consisted of older patients with higher comorbidity burdens (mean age: 68.4 vs. 59.2 years, p < 0.001). Surgical time and incision size were significantly shorter in the interspinous group (p < 0.001), and no postoperative complications were reported, compared to 3.5% in the pedicle screws group (p < 0.05). Both groups demonstrated significant improvements in pain (VAS), quality of life (SF-36, EQ-5D), and psychological outcomes (SCL-90). Somatization and paranoid ideation were significant predictors of worse postoperative pain, particularly in the pedicle screws group. No significant differences in quality-of-life improvements were observed between the groups. Conclusions: Both stabilization techniques are effective for lumbar spine surgery, with interspinous devices offering a safer and less invasive option for high-risk patients. Psychological factors significantly influence pain outcomes, underscoring the need for a comprehensive approach addressing both physical and psychological aspects to optimize patient recovery.
Effective Intramuscular Vitamin D2 in Patients with Systemic Sclerosis Non-Responding to Oral Supplementation; A Retrospective Observational Case Series
Authors: Aoun Maroun , Mallat Farid , Jabbour Rita , Hachem Samir , Soutou Boutros , Helou Josiane
Published: January 2025

Objective: To assess the response to intramuscular vitamin D in patients not respond-ing to oral supplementation. Methods: A retrospective series included patients, with systemic sclerosis and a history of subclinical poor vitamin D status that was resistant to at least 6 months of oral supplementation, to whom intramuscular vitamin D2 was administered. Results: Twelve patients were identified, with a mean age of 47.8 years. All were women. Five had diffuse systemic sclerosis and seven had localized systemic sclerosis. The mean duration of the disease was 17.9 years, with a mean modified Rod-nan skin score of 14.9. All patients were twice injected, at a 15-day interval, 300,000 IU of ergocalciferol into the anterior gluteus muscle. The mean serum level of 25(OH)D increased from 12.9 ng/mL before the first injection, to 23 ng/mL two weeks after the first injection, and 37.1 ng/mL four weeks after the second injection (p<0.001). No side effects were observed. Conclusion: It is the first report of safely normalizing vitamin D levels with intramuscular ergocalciferol in patients with systemic sclerosis.
Equity and Ethics in Telerehabilitation: Toward Personalized Approaches in Physiotherapy and Occupational Therapy
Authors: Veras Mirella , Sigouin Jennifer , Auger Claudine , Auger Louis-Pierre , Ahmed Sarah , Boychuck Zachary , Cavallo Sabrina , Lévesque Martine , Lovo Stacey , Miller William C , Nelson Michelle , Norouzi-Gheidarii Nahid , O'Neil Jennifer , Perreault Kadija , Urbanowski Reg , Sheehy Lisa , Singh Hardeep , Vincent Claude , Wang Rosalie , Zidarov Diana , Hudon Anne , Kairy Dahlia
Published: January 2025

Introduction: The rapid adoption of telerehabilitation in physiotherapy and occupational therapy has transformed healthcare delivery, offering new opportunities for patient-centered care. However, its implementation raises critical ethical and equity-related questions that must be addressed to ensure fair and responsible practices. This review examines how ethical disparities and equity-related challenges are reflected in the existing literature on telerehabilitation.
Objective: To investigate the presence of ethical-disparity and equity-related aspects in the provision of telerehabilitation in physiotherapy and occupational therapy as reflected in the literature.
Methods: A rapid review methodology was employed to explore ethical and equity-related challenges in telerehabilitation. The search included articles published in English and French between 2010 and 2020 from the Medline and Embase databases. Articles were selected based on their relevance to ethical and equity considerations in telerehabilitation. A total of 1,556 sources were initially identified, with 57 articles meeting the eligibility criteria for inclusion in this review. Data were extracted based on variables such as age, gender, ethnicity, morbidity, cost, privacy, confidentiality, and autonomy. The data extraction and analysis were guided by the Progress Plus and Metaverse Equitable Rehabilitation Therapy frameworks. A narrative synthesis approach was used to analyze and discuss the findings. The results highlighted key ethical considerations, including adverse events, patient autonomy, and privacy issues. Equity-related aspects were examined with a significant focus on age demographics, access to rehabilitation services, and gender considerations. Disparities in technology access, socioeconomic status, and ethnicity were also identified.
Conclusions: The review underscores the importance of addressing ethical and equity-related issues in telerehabilitation to ensure a socially just, responsible, and inclusive approach to care. Additionally, it highlights the potential for telerehabilitation to offer personalized interventions that cater to individual patient needs, further advancing equitable and patient-centered rehabilitation practices.
Leveraging Data Science for Enhanced Academic Outcomes: Insights from the Student Performance Dataset
Authors: Juhardeen Hammad Ruxshan , Amin Noor Ul , Said Omar Swafa Salim , Meena Sakina Hussein
Published: January 2025

The present work applies techniques of data science to the "Student Performance Dataset" in finding factors that could predict academic achievement of secondary school students in Portugal. Based on demographics, study habits, parental education, and schools, this research searches for the performance trend and patterns of students. Specific techniques applied for this study were EDA and correlation analysis, predictive modeling of results, therefore, giving actionable insight into how individualized learning strategies could best be improved upon. It is noted that the study time, absenteeism, parents' education, and final grades are all highly correlated. Further, different predictive models on student performance were developed using Linear Regression, Support Vector Regression, and Decision Tree Regression, while the best results in light of R-squared and Mean Squared Error metrics came out for Linear Regression. The hidden message from this study is that interventions should be tailored in education, with data-driven approaches being the need of the hour to increase academic performance. Dealing with outliers, optimization of feature selection, and using a robust preprocessing technique are in tune with the broader objective of equitable and effective educational systems. These findings have practical implications for policymakers, educators, and institutions seeking to implement evidence-based strategies for academic excellence.
Special Zero Gravity Theory
Authors: Cuesta Gutierrez Francisco Javier
Published: January 2025

This paper has been renamed as “Special Zero Gravity Theory” because it preceds to another one called “General Zero Gravity Theory” of a different scope. A Theory strictly deduced from Einstein’s General Relativity Theory [1] is introduced in this paper. This Theory is also based in the premise “Gravity is an expression of the state of balance reached by matter in space-time” (from Artificial BioIntelligence Theory [5] by this same author, Amazon November 2023). Its mathematicals basis are deduced from [1] and exposed in detail. We prove that speed in its different forms (translation or rotation) is able to counteract the concavity created by the Gravity, creating at last instance a “Zero Gravity” effect. The relation between such effect with speed and altitude is shown through different sample graphs. We discuss the conditions that must be fulfilled for appying the theory in the case of spinning objects, showing some graphs for different altitudes, rotation speeds and diameters of objects (disks). Although such theoretical objects are supposed to have all their mass concentrated in their periphery, an “equivalent radius”(Re) is calculated for an object with shape of compact disc. The way for extrapolating Re to any kind of objects with other shapes is shown. The “partial Zero Gravity effect” is also calculated, showing that a partial effect can be reached for different speeds and altitudes. We also discuss the relation among the Zero Gravity effect and the energy conservation principle, between gravitational potential energy and kinetic energy. Finally we show the relation with the metric tensor of Einstein.
Comparative Study of Inregrated Learning for Dynamic State Estimation of Power System Considering Data Dropout
Authors: Wang Yuefan , Luo Zhiyuan , Feng Ruikai , Zeng Qi
Published: January 2025

The findings of this study underscore the efficacy of integrating the time modelling capability of LSTM with the robustness of integrated methods to enhance the stability and operational reliability of the power grid. This study has contributed to the development of elastic DSE technology that can adapt to the complexity challenges of modern power grids.
Artificial Liver Classifier: A New Alternative to Conventional Machine Learning Models
Authors: Jumaah Mahmood A. , Ali Yossra H. , Rashid Tarik A.
Published: January 2025

Supervised machine learning classifiers often encounter challenges related to performance, accuracy, and overfitting. This paper introduces the Artificial Liver Classifier (ALC), a novel supervised learning classifier inspired by the human liver’s detoxification function. The ALC is characterized by its simplicity, speed, hyperparameters-free, ability to reduce overfitting, and effectiveness in addressing multi-classification problems through straightforward mathematical operations. To optimize the ALC’s parameters, an improved FOX optimization algorithm (IFOX) is employed as the training method. The proposed ALC was evaluated on five benchmark machine learning datasets: Iris Flower, Breast Cancer Wisconsin, Wine, Voice Gender, and MNIST. The results demonstrated competitive performance, with the ALC achieving 100% accuracy on the Iris dataset, surpassing logistic regression, multilayer perceptron, and support vector machine. Similarly, on the Breast Cancer dataset, it achieved 99.12% accuracy, outperforming XGBoost and logistic regression. Across all datasets, the ALC consistently exhibited lower overfitting gaps and loss compared to conventional classifiers. These findings highlight the potential of leveraging biological process simulations to develop efficient machine learning models and open new avenues for innovation in the field.
Tuning BMI.NTf2 Ionic Liquid Concentration in Dental Adhesives Towards a Rational Design of Antibacterial Materials
Authors: Garcia Isadora Martini , Simionato Andressa , Souza Virgínia Serra de , Melo Mary , Scholtene Jackson Damiani , Collares Fabrício Mezzomo
Published: January 2025

1-Butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (BMI.NTf2) is a hydrophobic ionic liquid with potential antibacterial properties for dental materials. This study aimed to (1) incorporate different mass fractions of BMI.NTf2 into a dental adhesive and (2) assess its impact on physical and chemical properties. Adhesive resins were prepared with 1 (G1%), 2.5 (G2.5%), and 5 wt.% (G5%) BMI.NTf2, with a control group (GCTRL) lacking the ionic liquid. Evaluations included polymerization kinetics, degree of conversion (DC), softening in solvent (ΔKHN%), and ultimate tensile strength (UTS). Groups with BMI.NTf2 showed accelerated polymerization kinetics, with G5% achieving a higher DC and ΔKHN% compared to GCTRL (p<0.05). Lower concentrations (1% and 2.5%) did not affect ΔKHN%, and no significant differences were found in UTS across groups (p>0.05). Notably, 2.5 wt.% of BMI.NTf2 increased the DC without affecting other properties, indicating optimal polymerization rates and handling characteristics. These results support the development of BMI.NTf2-based antibacterial adhesives to may assist preventing secondary caries in restorative dentistry.
Effects of High-Dose Prednisone on the Gastrointestinal Microbiota of Healthy DogsEffects of High-Dose Prednisone on the Gastrointestinal Microbiota of Healthy Dogs
Authors: Garrity Sarah , Whittemore Jacqueline C. , Sahoo Dipak Kumar , Morgan Shannon , Lingreen Emily , VanDeWalle Sarah , Suchodolski Jan S. , Jergens Albert E.
Published: January 2025

The effects of high-dose glucocorticoids on the gastrointestinal microbiota of healthy dogs are unknown. This study’s aim was to investigate the effects of immunosuppressive doses of prednisone on the fecal microbiota and the gastric and duodenal mucosal microbiota in healthy dogs. Twelve healthy adult dogs were enrolled into a randomized, double-blinded, placebo-controlled trial. Dogs were evaluated on days 0, 14, and 28 following treatments with either prednisone (2 mg/kg/d) or placebo. Outcome measures included: 1) composition and abundance of the fecal microbiota (via high throughput sequencing of the 16S rRNA gene and qPCR-based dysbiosis index [DI]) and 2) spatial distribution of the gastric and duodenal mucosal microbiota using fluorescence in situ hybridization (FISH). No significant difference in alpha and beta diversity or amplicon sequence variants of the fecal microbiota was observed between treatment groups. Blautia spp. concentrations via qPCR were significantly decreased between prednisone group timepoints 2 and 3. Compared to placebo group dogs, prednisone group dogs showed significantly increased gastric mucosal helicobacters and increased mucosal associated total bacteria and Bacteroides in duodenal biopsies over the treatment period. Results indicate that immunosuppressive dosages of prednisone alter the mucosal microbiota of healthy dogs in a time-dependent manner which may disrupt mucosal homeostasis.
Drifting Impact: A Comprehensive Review of Floating Debris
Authors: Błotnicki Jan , Buta Bogna , Głowski Robert , Jarzembowski Paweł
Published: January 2025

Floating debris (FD), encompassing both woody and anthropogenic materials, disrupts fishway hydraulics and ecological efficiency. Despite frequent usage in scientific literature, the term remains ambiguous. Motivated by the need to enhance fishway performance, this study examines the concept of FD. A substantial review of environmental, economic, and safety impacts was conducted, focusing on marine debris, microplastics, and woody debris. Additionally, a systematic analysis of 560 articles published from 2018 to 2023 assessed how FD is described across diverse contexts. Through an elimination process, 55 papers underwent detailed manual analysis. FD was categorized into natural floating debris (NFD) and anthropogenic floating debris (AFD), a distinction crucial for engineering and scientific applications. This classification supports fishway management by facilitating the identification and monitoring of debris accumulation, thus enabling strategies to mitigate hydraulic and ecological consequences. While FD poses risks such as habitat disruption and pollutant bioaccumulation, natural FD also provides potential ecological benefits, including habitat creation. To address these challenges, the study advocates innovative waste management strategies informed by concepts like the doughnut economy and ecological economics. These approaches aim to reconcile ecological sustainability with economic activities, reducing anthropogenic FD while leveraging the advantages of NFD.
Efficacy of Three Dimension Curved Angle Plate Versus Two Miniplates in Mandibular Angle Fracture Fixation
Authors: Amer Ahmed abdul-motamed , Abdullah Abdel Aziz Baiomy , Makhlouf Ahmed Omar Ahmed Abdelrahman
Published: January 2025

The present study proposed to determine the superiority between using 3D and two miniplates fixation methods in the mandibular angle fractures. The aim of this study was evaluate the efficacy of three dimension curved angle strut plate versus two miniplates in mandibular angle fracture fixation. Sixteen patients requiring internal fixation of the mandibular angle fractures divided into two groups eight in each group, group I was treated with using 3D curved angle strut plate. Group II was treated using two 2-mm miniplates. The results of this study suggested that there are statistically significant in time elapsed between plate adaptation and definitive fixation (min) between two groups. Conclusions: 3D curved angle plate has relatively less or no postoperative complications compared with other techniques.
Enhancing Particle Breakage and Energy Utilization in Ball Mills: An Integrated DEM and SPH Approach
Authors: Soares Wallace Santos , dos Santos Magalhães Elisan , Govender Nicolin
Published: January 2025

This study examines the conversion of an overflow ball mill into a new energy-efficient discharge system via Discrete Element Method (DEM) and Smoothed Particle Hydro-dynamics (SPH) simulations. The research evaluates milling charge dynamics, empha-sizing the impact of liner geometry and operational variables such as charge filling and ball size. Our methodology integrates SPH to assess effects of the slurry on energy dissipation, power loss, breakage rates, and material transport. Our findings highlight significant operational inefficiencies in the overflow setup, notably extensive dead zones and excessive charge volume that hinder milling efficiency by limiting slurry in-teraction and reducing energy for comminution. Additionally, slurry pooling shifts the center of gravity, causing torque losses and direct material bypass to the discharge zone. Our simulations replicate these challenges and benchmark them against indus-trial-scale operations, identifying critical charge excesses that constrain throughput and elevate power consumption. The new discharge system decouples the filling charge from the evacuation mechanism, further than tackling common issues in the traditional grate discharge setups like backflow and carry-over. This approach substantially improves grinding efficiency, as demonstrated by enhanced breakage rates and diminished specific energy consumption. The results provide a robust framework for mill design and operational optimization, underscoring the value of integrated slurry behavior analysis in mill performance enhancement.
Pioneering Fuzzy-Based Energy-Efficient Routing for Underwater Sensor Networks
Authors: Tarif Mehran , Homaei MohammadHossein , Mosavi Amir
Published: January 2025

Underwater Wireless Sensor Networks (UWSNs) have garnered significant attention due to their potential in oceanographic research, seismic monitoring, environmental protection, and seabed mapping applications. However, these networks face unique challenges, such as high interference, long propagation times, reduced bandwidth, and dynamic network topologies. Routing protocols play a critical role in overcoming these issues. This paper proposes an enhanced fuzzy-based routing protocol, UWF-RPL, which optimizes decision-making through dynamic path selection and distributed traffic balancing. Our approach builds on the RPL framework, incorporating fuzzy logic to evaluate parameters such as depth, energy consumption, RSSI/ETX ratio, and latency. Simulation results demonstrate that the proposed protocol significantly outperforms existing methods, offering improved energy efficiency, higher packet delivery rates, reduced delay, and minimized queue overflows. The protocol also ensures greater scalability and resilience in dynamic underwater environments, contributing to the efficient operation and extended lifetime of UWSNs.
Profiling Indigenous Cultural Preservation Efforts of the Blaan Tribe in Kiblawan, Philippines
Authors: Fajinmi John , Oloyede Joseph
Published: January 2025

This study investigates the indigenous cultural preservation efforts of the Blaan tribe in Kiblawan, Davao del Sur, Philippines, highlighting their practices, challenges, and strategies for safeguarding their cultural heritage. Employing a qualitative approach, the research involves in-depth interviews, focus group discussions, and participatory observations with tribal elders, cultural practitioners, and community leaders. Key findings reveal that the Blaan tribe actively preserves their traditions through oral storytelling, ritual ceremonies, traditional crafts, and indigenous knowledge systems. Despite these efforts, challenges such as modernization, land disputes, and limited government support pose threats to their cultural identity. The study underscores the significance of community-driven initiatives, external support from stakeholders, and policy interventions to ensure the sustainability of Blaan cultural heritage. By documenting these practices, this research contributes to a deeper understanding of indigenous cultural preservation and provides actionable insights for fostering cultural resilience in the face of contemporary challenges.
EQLC-EC: An Efficient Voting Classifier for 1D Mass Spectrometry Data Classification
Authors: Guo Lin , Wang Yinchu , Liu Zilong , Xiong Xingchuang , Zhang Fengyi
Published: January 2025

Mass spectrometry (MS) data presents challenges for machine learning (ML) classification due to its high dimensionality, complex feature distributions, batch effects, and intensity discrepancies, often hindering model generalization and efficiency. To address these issues, this study introduces the Efficient Quick 1D Lite CNN Ensemble Classifier (EQLC-EC), integrating 1D convolutional networks with reshape layers and dual voting mechanisms for enhanced feature representation and classification performance. Validation was performed on five publicly available MS datasets, each featured in high-impact publications. EQLC-EC underwent comprehensive evaluation against classical machine learning (ML) models (e.g., support vector machine [SVM], random forest) and the leading deep learning methods reported in these studies. EQLC-EC demonstrated dataset-specific improvements, including enhanced classification accuracy (1%-5% increase) and reduced standard deviation (1%-10% reduction). Performance differences between soft and hard voting mechanisms were negligible (<1% variation in accuracy and standard deviation). EQLC-EC presents a powerful and efficient tool for MS data analysis with potential applications across metabolomics and proteomics.
River Restoration Units: Riverscape Units for European Freshwater Ecosystem Management
Authors: Duarte Gonçalo , Peponi Angeliki , Segurado Pedro , Leite Tamara , Borgwardt Florian , Funk Andrea , Birk Sebastian , Ferreira Maria Teresa , Branco Paulo
Published: January 2025

Freshwater habitats and biota are among the most threatened worldwide. In Europe, significant efforts are being taken to counteract detrimental human impacts on nature. In line with these efforts, the MERLIN project funded by the H2020 program focuses on mainstreaming ecosystem restoration for freshwater-related environments at the landscape scale. Additionally, the Dammed Fish project focuses on one of the main threats affecting European Networks – river artificial fragmentation. Meeting the objectives of both projects to work on a large, pan-European scale we developed a novel spatial database for river units. These spatial units, named River Restoration Units (R2U), abide by river network functioning while creating the possibility of aggregating multiple data sources with varying resolutions to comparable units. To create the R2U, we set a methodological framework that departs from the Catchment Characterisation and Modelling – River and Catchment Database v2.1 (CCM2) - together with the capabilities of the River Network Toolkit software (RivTool) to implement a 7-step methodological procedure. This enabled the creation of 11 557 R2U units in European sea outlet river basins along with their attributes. Procedure outputs were associated with spatial layers and then reorganised to create a relational database with normalised data. Under the MERLIN project, R2U have been used as the spatial analysis unit for a large-scale analysis using multiple input datasets (e.g., ecosystem services, climate, European Directive reporting data). This database will be valuable for river management and conservation planning, being particularly well suited for large-scale restoration planning in abidance with European Nature legislation. This database is publicly available via Zenodo (DOI: 10.5281/zenodo.10753900) and Open Science Framework (https://osf.io/mk6ed/).
Observations of the Microphysics of Wintertime Mixed Phase Precipitation and Type, and Instrument Comparisons at Sorel, Quebec, Canada.
Authors: Boudala Faisal S. , Lachapelle Mathieu , Isaac George A. , Milbrandt Jason A. , Michelson Daniel , Reed Robert , Holden Stephen
Published: January 2025

Wintertime mixed-phase precipitation (P) impacts transportation, electric power grids, and homes. Forecasting winter precipitation such as freezing precipitation (ZP), freezing rain (ZR), freezing drizzle (ZL), ice pellets (IP), and the snow (S) and rain (R) boundary remains challenging due to the complex cloud microphysical and dynamical processes involved, which are difficult to predict in current numerical weather prediction (NWP) models. Understanding these processes based on observations is crucial for improving NWP models. To aid this effort, Environment and Climate Change Canada deployed specialized instruments such as the Vaisala FD71P and OTT PARSIVEL disdrometers, which measure P type (PT), particle size distribution (N(D)), and fall velocity (V). The liquid water content (LWC) and mean mass weighted diameter ( D_m ) were derived based on the PARSIVEL data during the ZP events. Additionally, a Micro Rain Radar (MRR) and an OTT Pluvio2 P gauge were used as part of the Winter Precipitation Type Research Multi-Scale Experiment project at Sorel, Quebec. The dataset included manual measurements of snow water equivalent (SWE), PT, and radiosonde profiles. Analysis revealed that the FD71P and PARSIVEL instruments generally agreed in detecting P and snow events. However, the FD71P tended to overestimate ZR and underestimate IP, while the PARSIVEL showed superior detection of R, ZR, and S. Conversely, the FD71P performed better in identifying ZL These discrepancies may stem from uncertainties in the velocity-diameter (V-D) relationship used to diagnose ZR and IP. Observations from the MRR, radiosondes, and surface data linked ZR and IP events to melting layers (ML). IP events were associated with colder surface temperatures (T) compared to ZP events. Most ZR and ZL occurrences were characterized by light P with low LWC and specific intensity and D_m thresholds. Additionally, snow events were more common at warmer T compared to liquid P under low surface relative humidity conditions. The Pluvio2 gauge significantly underestimated snowfall compared to optical probes and manual measurements. However, snowfall estimates derived from PARSIVEL data, adjusted for snow density to account for riming effects, closely matched measurements from the FD71P and manual observations.
GO/Alg/PRP Regulates Oxidative Stress Through the p38MAPK/NF-κB Pathway on Ischemic Reperfusion Pressure Injury in Mice
Authors: Yan Shuang , Wang Siqing , Chen Ningjie , Chai Doudou , Wang Haitao , Yang Jincun , Xu Qingpeng , Fu Shengyao
Published: January 2025

Pressure injury（PI） are localized damages to the skin or underlying soft tissues typically caused by intense and/or prolonged pressure, shearing, friction, or combination of these factors. The wound is difficult to heal and easily leads to infection and other complications. The repair of PI has become a global health problem. This paper describes the preparation and characterization of Graphene Oxide (GO)/Alginate (Alg) gel-loaded Platelet-Rich Plasma (PRP), and the effects of GO/Alg/PRP on cell proliferation and angiogenesis have been evaluated by cell experiments. The effect of GO/Alg/PRP on PI model in mice was evaluated and the relationship between oxidative stress and p38 Mitogen-Activated Protein Kinase (P38MAPK)/ Nuclear Factor-κB (NF-κB) pathway was investigated. We established cell models and animal models damaged by oxidative stress, and detected the proliferation and migration of cells, the ability of angiogenesis and the degree of peroxide damage through cytological experiments, the degree of skin pathology, immunohistochemical staining and peroxide damage in mice through histological experiments, and the protein expression of stress-related pathways through Western blot. Under Scanning Electron Microscopy (SEM), GO/Alg/PRP presents a three-dimensional mesh-like structure, with fibrin connected between the fold walls of GO/Alg, making the mesh structure denser. The addition of PRP provides more growth factors, and the slow-release effect of GO/Alg ensures that the growth factors continue to promote wound healing. In vitro, GO/Alg, PRP and GO/Alg/PRP all promote cell proliferation, migration, angiogenesis, wound healing, collagen deposition and epithelial regeneration, and reduce oxidative stress damage of cells and tissues. Among these, GO/Alg/PRP plays the most significant role. We also found a relationship between oxidative stress and the p38MAPK/NF-κB pathway. The high level of Reactive Oxygen Species (ROS) produced by immune cells in the wound activated the p38MAPK/NF-κB pathway and significantly increased the expression of inflammatory mediators. GO/Alg/PRP gel inhibited the stress response, apoptosis degree and inflammatory response of cells, and reduced the oxidative stress damage caused by p38MAPK/NF-κB signaling pathway on the wound. In this study, we investigated the effects of GO/Alg/PRP on reducing inflammatory cell infiltration and inflammatory factors to prevent tissue damage and promote wound healing. We also explored the role of the p38MAPK/NF-κB pathway in regulating oxidative stress in the context of Ischemic Reperfusion (I/R) injuries in mice. Our findings suggest that GO/Alg/PRP could be an effective strategy for the treatment of I/R injuries and may serve as a basis for the development of novel PRP-based bioactive wound dressings.
Forecasting Oak Diameter Using an LSTM Neural Network in the Missouri State of USA
Authors: Chakraborty Sounak , Bardhan Sougata , Gullapalli SaiTeja , Khadka Saaruj
Published: January 2025

Accurately predicting tree growth is crucial for sustainable forest management and addressing climate-related impacts on ecosystems. This study explores the use of Long Short-Term Memory (LSTM) neural networks to forecast the Diameter at Breast Height (DIA) for white oak and red oak trees in Missouri, USA, which is a key indicator of tree health, growth, and timber value. Using historical data from 1999 to 2020 for training and 2021 data for validation, the model demonstrated its capability to capture growth patterns effectively. Results revealed that the LSTM model achieved higher predictive accuracy for white oak, attributed to its more consistent growth trends, whereas red oak predictions were influenced by greater sensitivity to environmental variability. These findings emphasize the potential of LSTM models in forestry analytics providing detailed insights into species-specific growth dynamics and supporting enhanced forest resource monitoring and management. The study contributes to advancing machine learning applications in forestry by showcasing how LSTM networks can address challenges in predicting tree growth across diverse species and environmental conditions. This research highlights the transformative role of data-driven models in fostering sustainable forest management practices and improving decision-making processes in the face of ecological and climate uncertainties.
Trends in Efficacy Endpoints in Phase II Glioblastoma Trials: A Regulatory Science Analysis (FY2020–FY2022)
Authors: Watanabe Shinya , Maeda Makoto , Sugii Narushi , Yamada Masanobu , Arakawa Yoshihiro , Nakamura Kimika , Hashimoto Koichi , Ishikawa Eiichi
Published: January 2025

Background/Objectives: In clinical trials for glioblastoma, efficacy evaluation often deviates from the standard Response Evaluation Criteria in Solid Tumors (RECIST) due to the unique characteristics of brain tumors. This study aimed to analyze recent trends in efficacy endpoint settings for Phase II glioblastoma trials conducted during fiscal years (FY) 2020–2022 and compared them with trials from FY2017–2019. Methods: Using Clarivate’s Cortellis™ Clinical Trial Intelligence database, 116 Phase II glioblastoma trials initiated between April 2020 and March 2023 were identified. After applying exclusion criteria, 88 trials were analyzed. Trial characteristics, primary endpoints (PEs), secondary endpoints (SEs), and efficacy designs were summarized and compared to prior data. Results: Among the 88 included trials, approximately half targeted newly diagnosed glioblastoma patients, and the majority tested pharmaceutical products. Progression-free survival (PFS), overall survival (OS), and PFS rate were the most common PEs, whereas OS and quality of life dominated SEs. Time-to-event outcomes were employed in approximately 75% of the trials, whereas objective response rate (ORR) was used as a PE in only 8%, significantly less than in FY2017–2019 (p = 0.022). Randomized, double-blind trials tended to have more PEs but fewer SEs. Conclusions: The diversity of efficacy endpoint settings increased in recent glioblastoma trials, with reduced reliance on ORR as a PE compared to earlier periods. These trends reflect evolving strategies to address the unique challenges of glioblastoma treatment and evaluation.
Advances in Understanding and Mitigating Risks in Dental X-Ray Imaging: A Comprehensive Review — “Safer Smiles: Innovating Dental Radiography for Tomorrow”
Authors: Alsuraifi Ali , Husam Yousef , R. Mohammed Noor Alhuda , Kareem Sarah , I. Al-Essa Umalbaneen , Alshakhs Ibrahim , Ayad Abdullah
Published: January 2025

Background: Dental radiography has undergone a profound transformation, evolving from rudimentary techniques with high radiation exposure and limited clarity to advanced digital modalities prioritizing diagnostic precision and patient safety. Innovations such as digital imaging, three-dimensional visualization, and artificial intelligence (AI) have revolutionized diagnostics, enabling faster, more accurate imaging with significantly reduced radiation doses. Understanding these advancements is crucial for enhancing patient care and minimizing occupational risks for dental professionals. Main Body: This comprehensive review traces the historical development of dental radiography, highlighting key milestones from the first dental X-rays to the advent of digital sensors and cone-beam computed tomography (CBCT). It examines recent technological advancements, including the shift to digital radiography, which has improved image quality and eliminated the need for chemical processing. The integration of AI is explored, emphasizing its role in autonomously detecting dental anomalies, streamlining diagnostic workflows, and facilitating early intervention.A critical analysis compares radiation exposure levels between traditional and modern imaging techniques, underscoring the importance of minimizing exposure through technological innovations and adherence to the ALARA (As Low As Reasonably Achievable) principle. The biological effects of ionizing radiation on tissues, cells, and DNA are discussed, highlighting the necessity for rigorous safety measures.Protective strategies for patients and dental professionals are detailed, including the use of lead aprons, thyroid collars, and proper shielding techniques. The review emphasizes implementing radiation safety protocols in dental practices to mitigate occupational risks. Emerging trends such as portable X-ray units have expanded access to imaging services, benefiting geriatric and homebound patients. Additionally, the integration of automation and robotics, along with the development of novel materials for radiation attenuation, points toward a future of safer, more efficient dental radiography. Conclusion: The evolution of dental radiography reflects a dynamic interplay between technological innovation and a steadfast commitment to safety. Advancements in imaging technology and radiation protection measures have significantly enhanced diagnostic capabilities while reducing radiation risks. The ongoing integration of AI and cutting-edge technologies heralds a new era in dental care, promising improved diagnostic accuracy, streamlined workflows, and better safeguarding of both patients and practitioners.
Self‐Organizing Maps as a Way to Evaluate Optimal Strategies for Balancing Binary Class Distributions: A Methodological Approach
Authors: Nogales Alberto , Guadalupe Diego , García Tejedor Álvaro José
Published: January 2025

Given that Machine Learning algorithms are data-driven, the way datasets are collected significantly impacts their performance. Data must be gathered methodically to avoid missing values or class imbalance, but sometimes the inherent nature of the data tends to lead to such imbalances. An unbalanced dataset can lead to biased models whose predictions are influenced by the majority class. To avoid this problem, balancing strategies can be used to equalize the instances of each class. In this paper, we propose a methodology to evaluate which balancing strategies, depending on the dataset, yield the best results. We leverage Self-Organizing Maps, an unsupervised neural network model, to identify which strategy generates the most suitable balanced synthetic data. By considering their topological structure, we also propose a metric that uses the trained map to measure changes between the original dataset and the same dataset after applying the different strategies.