bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Carbonization Pressure on CO2 Sequestration and Rheological Properties of Coal Gangue-Based Backfilling Slurry
Authors: Zhu Lei , Liu Zhicheng , Guo Qiang , Huo Binbin , Zhou Nan , Zhou Yuejin , Li Meng , Gu Wenzhe
Published: February 2025

The wet carbonation of coal gangue-based backfilling slurry (CGBS) is considered to be an effective method for the resource utilization of coal gangue solid waste and CO2 sequestration, but CO2 sequestration has a negative impact on the rheological properties of CGBS. This investigation explores the effect of carbonization pressure on the rheological properties and CO2 sequestration properties of CGBS by using a carbonization reactor, a rheometer, X-ray diffraction, a nitrogen adsorption–desorption instrument, a scanning electron microscope and other testing methods. The results show that increasing the carbonization pressure can increase the CO2 sequestration capacity of CGBS, and the carbonization products produced make the pores of CGBS smaller and the structure more compact; however, increasing the carbonization pressure will reduce the rheological properties of the slurry, and the optimal carbonization pressure is 0.7 MPa. At this time, the yield stress, plastic viscosity and hysteresis loop area of CGBS are 171.66 Pa, 0.0998 Pa·s and 1376 Pa/s, respectively. However, when the carbonization pressure is further increased, the CO2 sequestration capacity tends to remain unchanged. This is mainly because the carbonization pressure causes the carbonization reaction to intensify, forming a calcified layer on the particle surface, which hinders the penetration of CO2 into the particles. This study is of great significance for improving the utilization rate of gangue solid waste and CO2 sequestration.
Calibration and Compensation of Gyro Drift Errors Based on External Rotational Angle Comparison in a Rotational Inertial Navigation System
Authors: Li Wenqiang , Wen Zeyang , Yang Gongliu , Zhang Yanbei , Mo Haozhou , Peng Jincheng , Xiong Yuyu
Published: February 2025

The inertial navigation system (INS) is a robust and reliable navigation strategy to provide position, attitude and velocity information of a carrier with signal acquired from inertial sensors without external assistant. However, the lack of external correction information leads to the accumulation of navigation errors, thereby limiting the reliability and applicable range of INS. In a typical INS, the accuracy and robustness of INS are mainly hindered by sensor’s measuring accuracy, installation misalignments and navigation algorithm effectiveness. To address the limitations of navigation accuracy degradation caused by sensor measurement errors, a calibration and compensation method of the gyro bias was proposed to improve the navigation accuracy. Through analyzing the influence of individual navigation errors, we found that the bias noise of gyroscope is the dominant factor in degrading the navigation accuracy. Aiming to improve the performance of navigation, a rotational modulation method is employed to eliminate the influence of gyro bias drift. Specifically, the rotational modulation could average the gyro bias to zero through the periodic rotational mechanism. Furthermore, the rotational turntable output angle can be used to correct navigation-resolved attitude results, which has a highly precise angle and can be used to calibrate the gyro drift. By compensating for gyro bias in a navigation algorithm, the performance of the navigation results is improved by a matter of one order from 7 km to less than 1 km over a period of 6 h. Several individual navigation experiments were also conducted, and the results prove the effectiveness of our method. The theoretical and experimental results show that the proposed error analysis and the compensation method are feasible and can been applied to the practical navigation system.
Finite Element Modeling of Dynamic Response of RPC Columns and Frames Under Coupled Fire and Explosion
Authors: Rong Qin , Peng Chaochao , Hou Xiaomeng , Chang Yuan , Fan Tiancong
Published: February 2025

Reactive powder concrete (RPC) is widely used in ultra-high-rise buildings, hydropower stations, bridges, and other important infrastructures. To study the dynamic response and damage characteristics of RPC columns and frames considering coupled fire and explosions, an analytical model of RPC columns and frames with coupled fire and explosions was established by using ABAQUS (2021) finite element software. The dynamic response and damage degree of RPC columns under coupled fire and explosions were investigated to reveal the influence laws of parameters such as cross-section size, axial compression ratio, reinforcement rate, and fire duration on the dynamic response of RPC columns at high temperatures. The dynamic response of the frame structure was analyzed when the explosion load was applied to the bottom corner columns, side columns, and top beams, respectively. The results show that the fire severely weakened the blast resistance of RPC columns; the maximum mid-span deformation and residual deformation of RPC columns decreased with the increase in cross-section size and longitudinal bar reinforcement ratio and increased with the increase in fire duration and axial compression ratio. When the explosion load was applied to the corner columns of the bottom floor of the frame, the bottom corner columns were almost completely destroyed, and there was a significant risk of the structure collapsing. Based on the results of the data analysis, a method to enhance the explosion resistance of RC frame structures using RPC materials at high temperatures is proposed.
JLMS25 and Jiao-Liao Mandarin Speech Recognition Based on Multi-Dialect Knowledge Transfer
Authors: Li Xuchen , Wang Yiqun , Liu Xiaoyang , Su Kun , Li Zhaochen , Wang Yitian , Jiang Bin , Xie Kang , Liu Jie
Published: February 2025

Jiao-Liao Mandarin, a distinguished dialect in China, reflects the linguistic features and cultural heritage of the Jiao-Liao region. However, the labor-intensive and costly nature of manual transcription limits the scale of transcribed corpora, posing challenges for speech recognition. We present JLMS25, a transcribed corpus for Jiao-Liao Mandarin, alongside a novel multi-dialect knowledge transfer (MDKT) framework for low-resource speech recognition. By leveraging phonetic and linguistic knowledge from neighboring dialects, the MDKT framework improves recognition in resource-constrained settings. It comprises an acoustic feature extractor, a dialect feature extractor, and two modules—WFAdapter (weight decomposition adapter) and AttAdapter (attention-based adapter)—to enhance adaptability and mitigate overfitting. The training involves a three-phase strategy: multi-dialect AID-ASR multi-task learning in phase one, freezing the dialect feature extractor in phase two, and fine-tuning only the adapters in phase three. Experiments on the Jiao-Liao Mandarin subset of the KeSpeech dataset and JLMS25 dataset show that MDKT outperforms full-parameter fine-tuning, reducing Character Error Rate (CER) by 5.4% and 7.7% and Word Error Rate (WER) by 6.1% and 10.8%, respectively.
Prospective, Open-Label, Observational, Multicenter, Single Arm, Post-Marketing Study in Asthmatic Patients for Evaluation of Safety and Effectiveness of Indacaterol/Mometasone DPI (PROMISING-SHIFT)
Authors: Karmakar Saurabh , Singh Gajendra V. , Bhate Amit S. , Barge Vijaykumar , Mehrotra Bharat , Patel Chintan , Sinha Ekta , Bhagat Sagar , Patil Saiprasad , Barkate Hanmant
Published: February 2025

Background: Asthma significantly impacts global health, necessitating effective management strategies. A combination of inhaled corticosteroids (ICSs) and long-acting β2-agonists (LABA) is recommended for patients with inadequately controlled asthma. Method: This prospective, open-label, multicenter study (PROMISING-SHIFT) study evaluated the safety and efficacy of once-daily Indacaterol/Mometasone (IND/MF) dry powder inhaler (DPI) in Indian asthma patients (≥12 years), inadequately controlled with prior therapies. Patients received IND/MF DPI in three strengths (150/80 mcg, 150/160 mcg, 150/320 mcg) over 12 weeks. Results: The study included a total of 174 participants, and 27 adverse events (AEs) in 25 patients (14.37%) were reported, primarily mild to moderate, with no serious adverse events (SAEs). Drug-related treatment-emergent adverse events (TEAEs) were observed in 11 patients. Significant improvements were noted in the mean trough FEV1 and FVC, increasing from baseline to week 4 and week 12 (p < 0.001). The mean ACQ-5 score significantly decreased from 3.0 ± 0.73 baseline to 2.50 ± 0.53 (16.67%) at week 4 and further to 1.73 ± 0.35 at week 12, along with reduced exacerbations (p < 0.001). The need for rescue medication declined from 13.79% to 8.62%, and 96.55% of patients reported treatment satisfaction by study completion. Conclusion: Once-daily IND/MF DPI demonstrated a favorable safety profile with marked improvements in lung function, asthma control, and patient satisfaction, making it a promising option for long-term asthma management in Indian patients.
Physicochemical Characteristics of Individual Indoor Airborne Particles in the High Lung Cancer Rate Area in Xuanwei, China
Authors: Hu Ying , Shao Longyi , BéruBé Kelly , Wang Ningping , Hou Cong , Fan Jingsen , Jones Tim
Published: February 2025

Emissions from domestic coal burning are generally recognized as the cause of the lung cancer epidemic in Xuanwei City, Yunnan Province, China. To examine the physicochemical characteristics of airborne particles emitted from burning this locally sourced coal, PM2.5 samples were collected from Hutou village which has high levels of lung cancer, and Xize village located approximately 30 km from Hutou without lung cancer cases. Transmission Electron Microscopy-Energy Dispersive X-ray (TEM-EDX) analysis was employed to study the physiochemical features and chemistry of individual particles. Sulfur and silica are the most abundant elements found in the airborne particles in both of the two villages. Fewer elements in aerosol particles were found in Xize village compared with Hutou village. Based on the morphologies and chemical compositions, the particles in Xuanwei can be classified into five types including composite particles (38.6%); organic, soot, tar balls, and biologicals (28.3%); sulfate (14.1%); fly ash (9.8%); and minerals (9.2%). The particles in Hutou village are abundant in the size range of 0.4–0.8 μm while that in Xize is 0.7–0.8 μm. Composite particles are the most common types in all the size ranges. The percentage of composite particles shows two peaks in the small size range (0.1–0.2 μm) and the large size ranges (2–2.3 μm) in Hutou village while that shows an even distribution in all size ranges in Xize village. Core-shell particles are typical types of composite particles, with the solid ‘core’ consisting of materials such as fly ash or mineral grains, and the shell or surface layer being an adhering soluble compound such as sulfates or organics. The heterogeneous reactions of particles with acidic liquid layers produce the core-shell structures. Typically, the equivalent diameter of the core-shell particles is in the range of 0.5–2.5 μm, averaging 1.6 μm, and the core-shell ratio is usually between 0.4 and 0.8, with an average of 0.6. Regardless of the sizes of the particles, the relatively high core-shell ratios imply a less aging state, which suggests that the core-shell particles were relatively recently formed. Once the coal-burning particles are inhaled into the human deep lung, they can cause damage to lung cells and harm to human health.
The Fetal Effect of Maternal Caffeine Consumption During Pregnancy—A Review
Authors: Dube Rajani , Kar Subhranshu Sekhar , Bahutair Shadha Nasser Mohammed , Kuruba Manjunatha Goud Bellary , Shafi Shehla , Zaidi Huma , Garg Heena Chaitanya , Almas Yumna Mushrmita , Kidwai Alweena , Zalat Reem Ashraf Fathy , Sidahmed Omnia Elrasheid Babikir
Published: February 2025

Caffeine is commonly used to excess by the general public, and most pregnant women drink caffeine on a daily basis, which can become a habit. Maternal caffeine intake during pregnancy is associated with severe gestational outcomes. Due to its lipophilic nature, caffeine can cross the blood–brain barrier, placental barrier, and even amniotic fluid. It can be found in substantive amounts in breast milk and semen. There has been a reported drop in neonatal anthropometric measurements with increased caffeine consumption in some cohort studies. This narrative review using literature titles and abstracts from the electronic databases of PubMed, Embase, and Scopus investigates the data linking maternal caffeine use to unfavorable pregnancy outcomes. It also evaluates the validity of the recommendations made by health professionals on caffeine consumption by mothers from the available literature. The results of our comprehensive literature search of case–control studies, cohort studies, randomized control trials, and meta-analyses, imply that caffeine use during pregnancy is linked to miscarriage, stillbirth, low birth weight, and babies that are small for gestational age. It was also found that there may be effects on the neurodevelopment of the child and links to obesity and acute leukemia. These effects can even be seen at doses well below the daily advised limit of 200 mg. The genetic variations in caffeine metabolism and epigenetic changes may play a role in the differential response to caffeine doses. It is crucial that women obtain solid, evidence-based guidance regarding the possible risks associated with caffeine.
Intelligent Microfluidics for Plasma Separation: Integrating Computational Fluid Dynamics and Machine Learning for Optimized Microchannel Design
Authors: Manekar Kavita , Bhaiyya Manish L. , Hasamnis Meghana A. , Kulkarni Madhusudan B.
Published: February 2025

Efficient separation of blood plasma and Packed Cell Volume (PCV) is vital for rapid blood sensing and early disease detection, especially in point-of-care and resource-limited environments. Conventional centrifugation methods for separation are resource-intensive, time-consuming, and off-chip, necessitating innovative alternatives. This study introduces “Intelligent Microfluidics”, an ML-integrated microfluidic platform designed to optimize plasma separation through computational fluid dynamics (CFD) simulations. The trifurcation microchannel, modeled using COMSOL Multiphysics, achieved plasma yields of 90–95% across varying inflow velocities (0.0001–0.05 m/s). The input fluid parameters mimic the blood viscosity and density used with appropriate boundary conditions and fluid dynamics to optimize the designed microchannels. Eight supervised ML algorithms, including Artificial Neural Networks (ANN) and k-Nearest Neighbors (KNN), were employed to predict key performance parameters, with ANN achieving the highest predictive accuracy (R2 = 0.97). Unlike traditional methods, this platform demonstrates scalability, portability, and rapid diagnostic potential, revolutionizing clinical workflows by enabling efficient plasma separation for real-time, point-of-care diagnostics. By incorporating a detailed comparative analysis with previous studies, including computational efficiency, our work underscores the superior performance of ML-enhanced microfluidic systems. The platform’s robust and adaptable design is particularly promising for healthcare applications in remote or resource-constrained settings where rapid and reliable diagnostic tools are urgently needed. This novel approach establishes a foundation for developing next-generation, portable diagnostic technologies tailored to clinical demands.
The Inflammatory Mechanism of Parkinson’s Disease: Gut Microbiota Metabolites Affect the Development of the Disease Through the Gut–Brain Axis
Authors: Gao Ai , Lv Jiaqi , Su Yanwei
Published: February 2025

Parkinson’s disease is recognized as the second most prevalent neurodegenerative disorder globally, with its incidence rate projected to increase alongside ongoing population growth. However, the precise etiology of Parkinson’s disease remains elusive. This article explores the inflammatory mechanisms linking gut microbiota to Parkinson’s disease, emphasizing alterations in gut microbiota and their metabolites that influence the disease’s progression through the bidirectional transmission of inflammatory signals along the gut–brain axis. Building on this mechanistic framework, this article further discusses research methodologies and treatment strategies focused on gut microbiota metabolites, including metabolomics detection techniques, animal model investigations, and therapeutic approaches such as dietary interventions, probiotic treatments, and fecal transplantation. Ultimately, this article aims to elucidate the relationship between gut microbiota metabolites and the inflammatory mechanisms underlying Parkinson’s disease, thereby paving the way for novel avenues in the research and treatment of this condition.
Emerging Medications for Treatment-Resistant Depression: A Review with Perspective on Mechanisms and Challenges
Authors: Lucido Michael J. , Dunlop Boadie W.
Published: February 2025

Background/Objectives: Non-response to initial treatment options for major depressive disorder (MDD) is a common clinical challenge with profound deleterious impacts for affected patients. Few treatments have received regulatory approval for treatment-resistant depression (TRD). Methods: A systematic search of United States and European Union clinical trials registries was conducted to identify Phase II, III, or IV clinical trials, with a last update posted on or after 1 January 2020, that were evaluating medications for TRD. For both the US and EU registries, the condition term “treatment resistant depression” and associated lower-level terms (per registry search protocol) were used. For the US registry, a secondary search using the condition term “depressive disorders” and the modifying term “inadequate” was also performed to capture registrations not tagged as TRD. Two additional searches were also conducted in the US registry for the terms “suicide” and “anhedonia” as transdiagnostic targets of investigational medications. Trials were categorized based on the primary mechanism of action of the trial’s investigational medication. Results: Fifty clinical trials for TRD, 20 for anhedonia, and 25 for suicide were identified. Glutamate system modulation was the mechanism currently with the most compounds in development, including antagonists and allosteric modulators of NMDA receptors, AMPA receptors, metabotropic type 2/3 glutamate receptors, and intracellular effector molecules downstream of glutamate signaling. Psychedelics have seen the greatest surge among mechanistic targets in the past 5 years, however, with psilocybin in particular garnering significant attention. Other mechanisms included GABA modulators, monoamine modulators, anti-inflammatory/immune-modulating agents, and an orexin type 2 receptor antagonist. Conclusions: These investigations offer substantial promise for more efficacious and potentially personalized medication approaches for TRD. Challenges for detecting efficacy in TRD include the heterogeneity within the TRD population stemming from the presumed variety of biological dysfunctions underlying the disorder, comorbid disorders, chronic psychosocial stressors, and enduring effects of prior serotonergic antidepressant medication treatments.
Acute and Chronic Cardiovascular Adverse Events in Patients with Acute Myeloid Leukemia: A Systematic Review
Authors: Siaravas Konstantinos C. , Moula Amalia I. , Tzourtzos Ioannis S. , Ballas Christos E. , Katsouras Christos S.
Published: February 2025

Background/Objectives: Patients with acute myeloid leukemia (AML) have a higher propensity for adverse cardiovascular outcomes, primarily due to the toxic effects of chemotherapeutic agents. The purpose of this systematic review is to explore the association of acute myeloid leukemia treatment with adverse cardiovascular events. Methods: We systematically screened the literature for studies providing comparative data on cardiovascular toxicities in patients treated for acute myeloid leukemia. After the initial search, 3649 papers were screened and a final total number of 46 were included for the review process. Results: Common chemotherapeutic agents used in AML may cause cardiovascular (CV) toxicities. A plethora of pathophysiological mechanisms are incriminated for these effects. Drug combinations may increase the risk in a synergistic way. In addition, common mutations of AML, personal history of previous cardiovascular disease and impaired heart function carry an increased complication risk. Biomarkers, as well as multimodality imaging, may be used for the early detection of cardiovascular toxicities. Conclusions: Increased risks of CV toxicity and comorbidities are observed among AML patients. With all the available diagnostic modalities, early detection and CV prevention strategies can improve the patient’s prognosis and quality of life.
Regulatory Elements for Gene Therapy of Epilepsy
Authors: Chesnokova Ekaterina , Bal Natalia , Alhalabi Ghofran , Balaban Pavel
Published: February 2025

The problem of drug resistance in epilepsy means that in many cases, a surgical treatment may be advised. But this is only possible if there is an epileptic focus, and resective brain surgery may have adverse side effects. One of the promising alternatives is gene therapy, which allows the targeted expression of therapeutic genes in different brain regions, and even in specific cell types. In this review, we provide detailed explanations of some key terms related to genetic engineering, and describe various regulatory elements that have already been used in the development of different approaches to treating epilepsy using viral vectors. We compare a few universal promoters for their strength and duration of transgene expression, and in our description of cell-specific promoters, we focus on elements driving expression in glutamatergic neurons, GABAergic neurons and astrocytes. We also explore enhancers and some other cis-regulatory elements currently used in viral vectors for gene therapy, and consider future perspectives of state-of-the-art technologies for designing new, stronger and more specific regulatory elements. Gene therapy has multiple advantages and should become more common in the future, but there is still a lot to study and invent in this field.
The Effect of Glazing and Repeated Firing on Color, Translucency, and Flexural Strength of Different Types of Zirconia: An In Vitro Study
Authors: Alshali Ruwaida Z. , Awad Mohamed Abdelmageed , Assiri Amnah A. , Aljahdali Shahad A. , Babeer Walaa A. , Bukhary Dalea M. , Altassan Mosa M. , Al-Turki Lulwa E.
Published: February 2025

This study evaluated the impact of glazing and multiple firing on the flexural strength, translucency, and color stability of three types of zirconia: 3 mol% yttria-stabilized tetragonal zirconia polycrystals (3Y-TZP), 4 mol% yttria partially stabilized zirconia (4Y-PSZ), and 5 mol% yttria partially stabilized zirconia (5Y-PSZ). A total of 120 samples were categorized into four groups: polishing only (P), polishing + glazing (PG), polishing + glazing + one glaze firing (PGF), and polishing + glazing + two glaze firings (PGFF). A three-point bending test was used for assessing flexural strength and a spectrophotometer analysis for assessing color difference (ΔE*ab) and translucency parameter (TP). Statistical analysis included one-way ANOVA and Kruskal–Wallis tests, with significance set at α = 0.05. The type 3Y-TZP showed the highest flexural strength (918.46 MPa) and lowest translucency (TP = 4.32), while 5Y-PSZ exhibited the lowest strength (401.58 MPa, p < 0.001) and highest translucency (TP = 6.26, p ≤ 0.012). Heat treatment resulted in a significant reduction in the flexural strength of 5Y-PSZ (p = 0.002), followed by 3Y-TZP (p = 0.04). The type 5Y-PSZ exhibited significant change in translucency (p = 0.003) and unacceptable variations in color (ΔE*ab: 1.49–9.6). The type 4Y-PSZ exhibited the highest stability in flexural strength, translucency, and color under multiple treatments. In conclusion, while glazing and firing significantly compromised 5Y-PSZ’s flexural strength and altered its color and translucency, 4Y-PSZ demonstrated the highest stability.
Emotional Reactivity and Behavioral Problems in Preschoolers: The Interplay of Parental Stress, Media-Related Coping, and Child Screen Time
Authors: Jusienė Roma , Breidokienė Rima , Baukienė Edita , Rakickienė Lauryna
Published: February 2025

Background/Objectives: Excessive screen time has been linked to poorer developmental outcomes in preschool years, with the impact depending on context. Parents of emotionally reactive children, in particular, may use screens to manage their child’s emotions, especially when experiencing distress themselves. This reliance on screens can hinder the development of self-regulation, leading to behavioral difficulties. Our study aimed to explore how emotional reactivity, parental distress, screen time, and media-related coping interact while contributing to externalizing (behavioral) problems in preschool-aged children. Methods: The study included 754 children (49.1% girls), aged 2–5 years (M = 44.6 months, SD = 13.7). Parents reported children’s emotional reactivity and externalizing problems using the Child Behavior Checklist and provided data on daily screen time and media-related coping behaviors. Bivariate correlations, group comparisons, and structural equation modeling were employed to analyze the data. Results: Children averaged 111.86 min of daily screen time (SD = 83.94), with 35.2% of parents using screens as a coping strategy. Emotional reactivity was the strongest predictor of externalizing problems, while the role of screen time was weak, yet significant. Parental distress was positively associated with child emotional reactivity and screen time. Structural equation modeling showed that child emotional reactivity related to behavioral problems both directly and indirectly via parental distress, media-related coping, and increased screen time. Conclusions: The findings highlight emotional reactivity as a key factor in child behavioral problems, emphasizing the cumulative risks posed by parental distress and screen use. The results suggest interventions promoting healthier screen habits and supporting parental well-being.
Intravenous Sodium Ferric Gluconate Complex for Hospitalized Pediatric Patients with Iron Deficiency Anemia
Authors: White Felicia , Polakowski Noelle , Merlington Elena , Leimanis Mara , Dudick Brooke , Parker Jessica , Jousma Ashley , Loji Alexander , Hanson Jeffrey , Arney Monica , Boville Brian
Published: February 2025

Background/Objectives: Iron deficiency anemia is common in the pediatric population. Red blood cell transfusions, a common acute treatment, pose well-recognized risks including lung injury, circulatory overload, and immune dysfunction. Intravenous iron, specifically sodium ferric gluconate complex (SFGC), is a potential alternative, however investigation on its use in hospitalized children is lacking. This study aims to describe the physiologic response via change in hematologic values to cumulative dose of SFGC, investigate the effect of cumulative dosing on the amount of RBC transfusions received, and comment on its safety. Methods: This is a retrospective investigation of pediatric patients with iron deficiency who received SFGC during their admission to the Helen DeVos Children’s Hospital between 2016 and 2018 (N = 85). Results: A total of 258 doses of intravenous SFGC were provided to 85 patients. The average pre-treatment serum hemoglobin was 8.73 ± 1.33, and 7 days post-treatment this increased to 10.41 ± 1.43. Mean corpuscular volume, ferritin, serum ion, total iron binding capacity, reticulocyte percentage, and reticulocyte hemoglobin all increased 7 days post-treatment, as would be suspected, but without any statistically significant difference between hematologic outcomes and cumulative dose of SFGC. Our study did not reveal any correlation between the cumulative dose of SFGC administered and the amount of RBC transfusions received. Only one adverse event was recorded. Conclusions: Our results complement the trend of increased use and emerging evidence of favorable safety profiles of IV iron in the pediatric population. This descriptive investigation revealed that administering higher cumulative doses of SFGC provided no further benefits in terms of hematologic response or RBC transfusion administration.
Improvement of Surface Properties of 30CrNi2MoVA Steel with Ultrasonic Composite Strengthening Modification
Authors: Liu Dan , Ke Yinglin , Huang Hongsheng , Tan Changsheng , Xu Qiang , Li Huanbin
Published: February 2025

The surface roughness, surface hardness, tensile properties and friction-wear properties were characterized, in comparison with those of the traditional turned cutting, electropulsing treatment (EP) and ultrasonic surface-rolling process (USRP) sample. The surface microstructure was obviously refined after USRP and EP-USRP, with a fine-grain depth of 60 μm and 100 μm, respectively. The surface roughness significantly decreases at first, and then gradually increases after surface-strengthening modification. The lowest roughness of 0.035 μm and 0.040 μm is obtained for the USRP and EP-USRP samples, respectively, which is about 12 times less than that of the turning surface roughness of 0.421 μm. The surface hardness increases from 280 HV to 360 HV after strengthening modification. The super tensile property of 30CrNi2Mo steel is obtained for the USRP, for which the yield strength, tensile strength, elongation and yield-to-strength ratio are 743 MPa, 961 MPa, 11% and 0.773, respectively. The friction coefficients in the turning state, USRP and EP-USRP are 0.37, 0.35 and 0.4, respectively. Ultrasonic composite-strengthening modification can increases the surface hardness, and obtains gradient microstructure on the material surface, which endows the material with better surface properties.
Experimental Study on Shear Thickening Polishing of ZnS Glass
Authors: Zhang Xueliang , Ke Mingfeng , Chen Yuyang , Shao Lanying , Wang Jiahuan , Yuan Julong , Lyu Binghai
Published: February 2025

Zinc sulfide (ZnS) is extensively utilized in various applications due to its exceptional optical transmittance across numerous spectral bands. To achieve ultra-high surface quality ZnS optical components, shear thickening polishing (STP) is employed to reduce roughness. A comparison between traditional fixed abrasive polishing (FAP) and STP for ZnS glass showed that FAP results in poor surface quality due to its low removal efficiency and uneven abrasive exposure, while STP provides better surface quality due to its flexible removal process, proving its feasibility and advancement. The Taguchi method was used to study the impact of three key polishing parameters on surface roughness (Ra) and the material removal rate (MRR), finding that polishing angle most influenced roughness and speed most influenced MRR. With optimal parameters, ZnS glass surface roughness was reduced from 110 ± 15 nm to 8.85 ± 0.5 nm, with an MRR of 32.5 nm/min. Scanning electron microscope (SEM) images further confirmed STP’s effectiveness in removing microdefects and smoothing the ZnS glass surface, offering a new method for the efficient, high-quality polishing of chalcogenide glasses without surface damage.
Tunable Group Delay of Reflected Beam in Multilayered Structures with Antisymmetric Graphene via Magnetic Control
Authors: Wu Xinghua , Guo Yanyan , Wang Qingkai
Published: February 2025

In this paper, we demonstrate the magnetic field-adjustable group delay of the reflected beam in the terahertz frequency range, using a multilayer architecture incorporating three layers of antisymmetric graphene. The observed enhancement in group delay results from localized field amplification, which occurs due to the excitation of surface plasmon polaritons on the graphene at the interface between two dielectric layers. By considering the quantum mechanical response of graphene, the polarity of the group delay can be reversed by exploiting the antisymmetric conductivity characteristics of graphene. Furthermore, the group delay can be dynamically modulated either by varying the external magnetic field or by adjusting the structural parameters. The achieved enhancement and tunability of the group delay offer significant potential for the development of graphene-based terahertz modulation devices and other optical delay applications.
Research on the Circuit Breaker State Judgment Method Based on Ant Colony Optimization Dempster-Shafer Evidence Theory
Authors: Zhang Qian , Liu Zhi , Zhang Zhilan , Guo Lei , Wang Yan , Peng Runze , Liu Jiaqi
Published: February 2025

The paper proposes a method for circuit breaker state judgment based on ant colony algorithm-optimized Dempster-Shafer evidence theory.It can improve the accuracy and robustness of state judgment. As a key device in the power system, the state judgment of circuit breakers is crucial for the safety and stability of the power grid. Existing methods have limitations in handling conflicts and uncertainties of multi-source data, and a single model is difficult to meet the needs of complex data fusion. Therefore, the paper applies the ant colony algorithm to optimize the basic probability assignment in Dempster-Shafer evidence theory to improve the fusion effect of multi-source data. The ant colony algorithm, through its global search and adaptive characteristics, can effectively optimize evidence combination and enhance the accuracy of the fusion results. The experiment used a support vector machine model based on current signals and a decision tree model based on vibration signals for data fusion and discrimination. The results showed that the Dempster-Shafer evidence theory model optimized by the ant colony algorithm achieved a discrimination accuracy of 75% under various circuit breaker conditions. Compared to the Dempster-Shafer evidence theory fusion model, it improved by approximately 8.3%, and compared to the current research’s Dempster-Shafer evidence theory and neural network methods, it improved by 5%.. This method has broad application prospects in enhancing the operational stability of power grid equipment and improving fault detection efficiency.
DGMT: A Fully Dynamic Group Signature from Symmetric-Key Primitives
Authors: Fadavi Mojtaba , Karati Sabyasachi , Erfanian Aylar , Safavi-Naini Reihaneh
Published: February 2025

A group signature scheme allows a user to sign a message anonymously on behalf of a group and provides accountability by using an opening authority who can “open” a signature and reveal the signer’s identity. Group signature schemes have been widely used in privacy-preserving applications, including anonymous attestation and anonymous authentication. Fully dynamic group signature schemes allow new members to join the group and existing members to be revoked if needed. Symmetric-key based group signature schemes are post-quantum group signatures whose security rely on the security of symmetric-key primitives, and cryptographic hash functions. In this paper, we design a symmetric-key based fully dynamic group signature scheme, called DGMT, that redesigns DGM (Buser et al. ESORICS 2019) and removes its two important shortcomings that limit its application in practice: (i) interaction with the group manager for signature verification, and (ii) the need for storing and managing an unacceptably large amount of data by the group manager. We prove security of DGMT (unforgeability, anonymity, and traceability) and give a full implementation of the system. Compared to all known post-quantum group signature schemes with the same security level, DGMT has the shortest signature size. We also analyze DGM signature revocation approach and show that despite its conceptual novelty, it has significant hidden costs that makes it much more costly than using the traditional revocation list approach.
Harnessing Artificial Intelligence in Obesity Research and Management: A Comprehensive Review
Authors: Azmi Sarfuddin , Kunnathodi Faisal , Alotaibi Haifa F. , Alhazzani Waleed , Mustafa Mohammad , Ahmad Ishtiaque , Anvarbatcha Riyasdeen , Lytras Miltiades D. , Arafat Amr A.
Published: February 2025

Purpose: This review aims to explore the clinical and research applications of artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), in understanding, predicting, and managing obesity. It assesses the use of AI tools to identify obesity-related risk factors, predict outcomes, personalize treatments, and improve healthcare interventions for obesity. Methods: A comprehensive literature search was conducted using PubMed and Google Scholar, with keywords including “artificial intelligence”, “machine learning”, “deep learning”, “obesity”, “obesity management”, and related terms. Studies focusing on AI’s role in obesity research, management, and therapeutic interventions were reviewed, including observational studies, systematic reviews, and clinical applications. Results: This review identifies numerous AI-driven models, such as ML and DL, used in obesity prediction, patient stratification, and personalized management strategies. Applications of AI in obesity research include risk prediction, early detection, and individualization of treatment plans. AI has facilitated the development of predictive models utilizing various data sources, such as genetic, epigenetic, and clinical data. However, AI models vary in effectiveness, influenced by dataset type, research goals, and model interpretability. Performance metrics such as accuracy, precision, recall, and F1-score were evaluated to optimize model selection. Conclusions: AI offers promising advancements in obesity management, enabling more personalized and efficient care. While technology presents considerable potential, challenges such as data quality, ethical considerations, and technical requirements remain. Addressing these will be essential to fully harness AI’s potential in obesity research and treatment, supporting a shift toward precision healthcare.
Optimizing Cancer Treatment: Exploring the Role of AI in Radioimmunotherapy
Authors: Azadinejad Hossein , Farhadi Rad Mohammad , Shariftabrizi Ahmad , Rahmim Arman , Abdollahi Hamid
Published: February 2025

Radioimmunotherapy (RIT) is a novel cancer treatment that combines radiotherapy and immunotherapy to precisely target tumor antigens using monoclonal antibodies conjugated with radioactive isotopes. This approach offers personalized, systemic, and durable treatment, making it effective in cancers resistant to conventional therapies. Advances in artificial intelligence (AI) present opportunities to enhance RIT by improving precision, efficiency, and personalization. AI plays a critical role in patient selection, treatment planning, dosimetry, and response assessment, while also contributing to drug design and tumor classification. This review explores the integration of AI into RIT, emphasizing its potential to optimize the entire treatment process and advance personalized cancer care.
Critical Relaxation in the Quantum Yang–Lee Edge Singularity
Authors: Sun Yue-Mei , Wang Xinyu , Zhai Liang-Jun
Published: February 2025

We study the relaxation dynamics near the critical points of the Yang–Lee edge singularities (YLESs) in the quantum Ising chain in an imaginary longitudinal field with a polarized initial state. We find that scaling behaviors are manifested in the relaxation process after a non-universal transient time. We show that for the paramagnetic Hamiltonian, the magnetization oscillates periodically with the period being inversely proportional to the gap between the lowest energy level; for the ferromagnetic Hamiltonian, the magnetization decays to a saturated value; while for the critical Hamiltonian, the magnetization increases linearly. A scaling theory is developed to describe these scaling properties. In this theory, we show that for a small- and medium-sized system, the scaling behavior is described by the (0+1)-dimensional YLES.
Mean Field Initialization of the Annealed Importance Sampling Algorithm for an Efficient Evaluation of the Partition Function Using Restricted Boltzmann Machines
Authors: Prat Pou Arnau , Romero Enrique , Martí Jordi , Mazzanti Ferran
Published: February 2025

Probabilistic models in physics often require the evaluation of normalized Boltzmann factors, which in turn implies the computation of the partition function Z. Obtaining the exact value of Z, though, becomes a forbiddingly expensive task as the system size increases. A possible way to tackle this problem is to use the Annealed Importance Sampling (AIS) algorithm, which provides a tool to stochastically estimate the partition function of the system. The nature of AIS allows for an efficient and parallel implementation in Restricted Boltzmann Machines (RBMs). In this work, we evaluate the partition function of magnetic spin and spin-like systems mapped into RBMs using AIS. So far, the standard application of the AIS algorithm starts from the uniform probability distribution and uses a large number of Monte Carlo steps to obtain reliable estimations of Z following an annealing process. We show that both the quality of the estimation and the cost of the computation can be significantly improved by using a properly selected mean-field starting probability distribution. We perform a systematic analysis of AIS in both small- and large-sized problems, and compare the results to exact values in problems where these are known. As a result, we propose two successful strategies that work well in all the problems analyzed. We conclude that these are good starting points to estimate the partition function with AIS with a relatively low computational cost. The procedures presented are not linked to any learning process, and therefore do not require a priori knowledge of a training dataset.
Game-Based Learning to Promote Clinical Reasoning: An Innovative Educational Proposal in Pediatric Dentistry
Authors: Zerman Nicoletta , Silva Roberta , Bonfadelli Elisa , Puecher Susanna , Marogna Gianna , De’Manzoni Rachele , Beccherle Marinella , Mortari Luigina
Published: February 2025

Pediatric dentistry requires different professional knowledge and skills, including technical and analytical thinking skills, essential for deep clinical reasoning. To analyze the students’ awareness of their cognitive processes when solving clinical problems, a qualitative and inductive study with second and fifth year students in the Degree Course in Dentistry and Dental Prosthetics at the University of Verona was conducted. Adopting a phenomenological approach, it focused on participants’ lived experiences, gathering their reflections on solving clinical problems through two structured questions. The data, analyzed using content analysis, revealed that sometimes students focused on operational steps rather than reflecting on them, and underscored the necessity of innovating university teaching methods to enhance reflective moments. To respond to this need, a literature review was conducted, underscoring the value of active learning in innovating dentistry education. Accordingly, a game-based learning activity was elaborated: a dental-themed adaptation of the games where you guess an image without using certain predetermined words. Its goal is to create an interactive and engaging environment that facilitates sharing and reflection, challenging students to apply their competencies to practical scenarios. Finally, our research identified students’ educational needs to develop teaching strategies that shape their reflective process in clinical reasoning so as to be more deliberate and conscious.
Social and Emotional Learning: Easing the Transition to High School for 2e Learners
Authors: Willis Charles , Fugate C. Matthew
Published: February 2025

The transition from middle school to high school can be difficult for students as they navigate new environments and teacher expectations. This transition can be particularly difficult for twice-exceptional students who often struggle with the necessary executive functioning skills needed to meet these expectations, as well as their own self-awareness, self-efficacy, and the self-advocacy skills they need to help ease this transition. In this article, we discuss a unique pilot seminar program by the teachers and counselors at a school for twice exceptionality that helps students develop skills and a sense of self that will be beneficial to them, not only during their high school years, but also for their future lives and careers.
The Implications and Applications of Developmental Spelling After Phonics Instruction
Authors: Templeton Shane
Published: February 2025

Examining spelling from a developmental perspective began in the 1970s and has broadened over the years. This research has informed understanding of the nature and development of spelling or orthographic knowledge in children and older students and the role of orthographic knowledge in reading and writing. Based on analyses of the errors that students make in their writing and on spelling assessments, developmental spelling has documented the acquisition and integration of progressively more complex spelling patterns that represent both sound and meaning and illuminated how this information supports students’ ability to read as well as to write words. Intended for researchers, teacher educators, and teachers of students in grades 3–12, this article describes the layers of the spelling system that developmental spelling research has investigated, and their progressive integration in learners, including those who struggle, from the intermediate through the middle and secondary grades. It addresses the implications of developmental spelling research for assessment and instruction in spelling, word analysis, vocabulary, and the more specific implications of developmental spelling research for aligning instruction across spelling, word analysis, vocabulary, morphology, and etymology.
A Performance Analysis of You Only Look Once Models for Deployment on Constrained Computational Edge Devices in Drone Applications
Authors: Rey Lucas , Bernardos Ana M. , Dobrzycki Andrzej D. , Carramiñana David , Bergesio Luca , Besada Juan A. , Casar José Ramón
Published: February 2025

Advancements in embedded systems and Artificial Intelligence (AI) have enhanced the capabilities of Unmanned Aircraft Vehicles (UAVs) in computer vision. However, the integration of AI techniques o-nboard drones is constrained by their processing capabilities. In this sense, this study evaluates the deployment of object detection models (YOLOv8n and YOLOv8s) on both resource-constrained edge devices and cloud environments. The objective is to carry out a comparative performance analysis using a representative real-time UAV image processing pipeline. Specifically, the NVIDIA Jetson Orin Nano, Orin NX, and Raspberry Pi 5 (RPI5) devices have been tested to measure their detection accuracy, inference speed, and energy consumption, and the effects of post-training quantization (PTQ). The results show that YOLOv8n surpasses YOLOv8s in its inference speed, achieving 52 FPS on the Jetson Orin NX and 65 fps with INT8 quantization. Conversely, the RPI5 failed to satisfy the real-time processing needs in spite of its suitability for low-energy consumption applications. An analysis of both the cloud-based and edge-based end-to-end processing times showed that increased communication latencies hindered real-time applications, revealing trade-offs between edge (low latency) and cloud processing (quick processing). Overall, these findings contribute to providing recommendations and optimization strategies for the deployment of AI models on UAVs.