bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Story Volumetric Blocks Buildings with Lower Frame Floors
Authors: Teshev Ilia , Bespayev Aliy , Zhambakina Zauresh , Tamov Murat , Altigenov Ulan , Zhussupov Timur , Tolegenova Aigerim
Published: June 2024

This article presents the results of experimental studies of the stress–strain state of volumetric blocks based on the underlying frame structures. The aim of the research is to evaluate the stress–strain state and the nature of damage development as a result of an increase in the load up to a critical level. Based on the analysis of the nature of the damage, recommendations have been developed to strengthen the destruction zone. Data were collected on the redistribution of stresses and deformations, the formation of cracks and joint openings, the magnitude of horizontal displacements, and the failure mode of volumetric blocks and floor frames. Five full-scale volumetric blocks were tested under the loading of hydraulic jacks, differing in concrete type, reinforcement, presence of doors, and dimensions of the stylobate beams. When the volumetric modules were supported by a frame floor the results revealed that the maximum destructive load of 10,462 kN was observed in the first specimen; the horizontal displacements of the walls decreased by 13–18 mm, and there was a decrease in the crack opening width to 0.5 mm. The cracks decreased the strength of the walls, leading to a redistribution of the compressive stresses and their increase in the support zone. The most significant compressive strains in concrete in the corner parts of longitudinal walls were in the range of (600–620) × 10−6, and in the middle part of the walls, 370 × 10−6 were observed. Furthermore, the largest cracks caused significant horizontal displacements (deplanation) of the walls, which decreased the stiffness of the conjunction of longitudinal walls with the floor slab and created an additional eccentricity of the vertical force. Based on the findings, the correlation between the measured parameters of each specimen at all stages of vertical load increase is demonstrated and illustrated in graphs of the measured parameters. The importance of quantity compliance with the initial rigid connection between the longitudinal wall and ceiling plate has been estimated.
A Comparative Analysis of Machine Learning Algorithms in Predicting the Performance of a Combined Radiant Floor and Fan Coil Cooling System
Authors: Lu Shengze , Cui Mengying , Gao Bo , Liu Jianhua , Ni Ji , Liu Jiying , Zhou Shiyu
Published: June 2024

Machine learning algorithms have proven to be practical in a wide range of applications. Many studies have been conducted on the operational energy consumption and thermal comfort of radiant floor systems. This paper conducts a case study in a self-designed experimental setup that combines radiant floor and fan coil cooling (RFCFC) and develops a data monitoring system as a source of historical operational data. Seven machine learning algorithms (extreme learning machine (ELM), convolutional neural network (CNN), genetic algorithm-back propagation (GA-BP), radial basis function (RBF), random forest (RF), support vector machine (SVM), and long short-term memory (LSTM)) were employed to predict the behavior of the RFCFC system. Corresponding prediction models were then developed to evaluate operative temperature (Top) and energy consumption (Eh). The performance of the model was evaluated using five error metrics. The obtained results showed that the RF model had very high performance in predicting Top and Eh, with high correlation coefficients (>0.9915) and low error metrics. Compared with other models, it also demonstrated high accuracy in Eh prediction, yielding maximum reductions of 68.1, 82.4, and 43.2% in the mean absolute percentage error (MAPE), mean squared error (MSE), and mean absolute error (MAE), respectively. A sensitivity ranking algorithm analysis was also conducted. The obtained results demonstrated the importance of adjusting parameters, such as the radiant floor supply water temperature, to enhance the indoor comfort. This study provides a novel and effective method for evaluating the energy efficiency and thermal comfort of radiant cooling systems. It also provides insights for optimizing the efficiency and thermal comfort of RFCFC systems, and lays a theoretical foundation for future studies integrating machine learning algorithms in this field.
Three-Dimensional Discrete Element Analysis of Bearing Characteristics of Concrete–Cored Sand–Gravel Pile Composite Foundation under Cyclic Dynamic Load
Authors: Ma Binhui , Tang Wenbiao , Lan Tian , Deng Xu , Du Bicheng
Published: June 2024

Concrete-cored sand–gravel piles are a kind of composite pile formed by wrapping a concrete-cored pile with a sand–gravel shell, which has the advantages of both a rigid pile and bulk-material pile. The bearing characteristics of the concrete-cored sand–gravel pile composite foundation were investigated by establishing a three-dimensional discrete element numerical model for a cyclic dynamic loading test. The results show that the vertical stress of the core pile body fluctuates greatly at the beginning of loading, and the fluctuation amplitude decreases with the depth, and gradually tends to be stable in the middle and late stages, and the vertical-stress distribution is relatively uniform. The radial stress in the upper part of the core pile body fluctuates greatly, the fluctuation in the lower part is small, and the radial stress in each part of the core pile body gradually tends to be stable in the late-loading period. The radial stress factor of the core pile body reaches the stable speed with the foundation depth decreasing; the fluctuation amplitude of the pile-soil stress ratio decreases with the foundation depth and gradually tends to be stable with the increase in loading. The results of this study can provide a reference for the design and construction of a core sand pile composite foundation.
Prognostic Impact and Clinical Implications of Adverse Tumor Grade in Very Favorable Low- and Intermediate-Risk Prostate Cancer Patients Treated with Robot-Assisted Radical Prostatectomy: Experience of a Single Tertiary Referral Center
Authors: Porcaro Antonio Benito , Bianchi Alberto , Gallina Sebastian , Panunzio Andrea , Tafuri Alessandro , Serafin Emanuele , Orlando Rossella , Mazzucato Giovanni , Ornaghi Paola Irene , Cianflone Francesco , Montanaro Francesca , Artoni Francesco , Baielli Alberto , Ditonno Francesco , Migliorini Filippo , Brunelli Matteo , Siracusano Salvatore , Cerruto Maria Angela , Antonelli Alessandro
Published: June 2024

Objectives: To assess the prognostic impact and predictors of adverse tumor grade in very favorable low- and intermediate-risk prostate cancer (PCa) patients treated with robot-assisted radical prostatectomy (RARP). Methods: Data of low- and intermediate PCa risk-class patients were retrieved from a prospectively maintained institutional database. Adverse tumor grade was defined as pathology ISUP grade group > 2. Disease progression was defined as a biochemical recurrence event and/or local recurrence and/or distant metastases. Associations were assessed by Cox’s proportional hazards and logistic regression model. Results: Between January 2013 and October 2020, the study evaluated a population of 289 patients, including 178 low-risk cases (61.1%) and 111 intermediate-risk subjects (38.4%); unfavorable tumor grade was detected in 82 cases (28.4%). PCa progression, which occurred in 29 patients (10%), was independently predicted by adverse tumor grade and biopsy ISUP grade group 2, with the former showing stronger associations (hazard ratio, HR = 4.478; 95% CI: 1.840–10.895; p = 0.001) than the latter (HR = 2.336; 95% CI: 1.057–5.164; p = 0.036). Older age and biopsy ISUP grade group 2 were independent clinical predictors of adverse tumor grade, associated with larger tumors that eventually presented non-organ-confined disease. Conclusions: In a very favorable PCa patient population, adverse tumor grade was an unfavorable prognostic factor for disease progression. Active surveillance in very favorable intermediate-risk patients is still a hazard, so molecular and genetic testing of biopsy specimens is needed.
Pt3Mn/SiO2 + ZSM-5 Bifunctional Catalyst for Ethane Dehydroaromatization
Authors: Jiang Shan , Chang Che-Wei , Swann William A. , Li Christina W. , Miller Jeffrey T.
Published: June 2024

Ethane dehydroaromatization (EDA) is a potentially attractive process for converting ethane to valuable aromatics such as benzene, toluene, and xylene (BTX). In this study, a Pt3Mn/SiO2 + ZSM-5 bifunctional catalyst was used to investigate the effect of dehydrogenation and the Brønsted acid catalyst ratio, hydrogen partial pressure, and reaction temperature on the product distributions for EDA. Pt3Mn/SiO2 + ZSM-5 with a 1/1 weight ratio showed the highest ethane conversion rate and BTX formation rate. Ethylene is initially formed by dehydrogenation by the Pt3Mn catalyst, which undergoes secondary reactions on ZSM-5, forming C3+ reaction intermediates. The latter form final products of CH4 and BTX. At conversions from 15 to 30%, the BTX selectivities are 82–90%. For all bifunctional catalysts, the ethane conversion significantly exceeds the ethane–ethylene equilibrium conversion due to reaction to secondary products. Low H2 partial pressures did not significantly alter the product selectivity or conversion. However, higher H2 partial pressures resulted in increased methane and decreased BTX selectivity. The excess hydrogen saturated the olefin intermediates to form alkanes, which produced methane by monomolecular cracking on ZSM-5. With an increasing reaction temperature from 550 °C to 650 °C, the benzene selectivity increased, while the highest BTX selectivity was obtained at 600 to 650 °C.
TiO2-Based Catalysts with Various Structures for Photocatalytic Application: A Review
Authors: Song Cheng , Xiao Lanqing , Chen Yan , Yang Fan , Meng Huiying , Zhang Wanying , Zhang Yifan , Wu Yang
Published: June 2024

TiO2-based catalysts with various surface heterostructures (0D, 1D, 2D, and 3D) have been widely researched owing to their cost-effectiveness, high stability, and environmentally friendly nature, and can be used for many applications in various fields, including hydrogen production and pollutant degradation. However, there are also many existing problems limiting their practical application, such as their large band gap and rapid electron–hole recombination rate. Owing to the abundance of recent achievements in materials science, we will summarize the recent structural engineering strategies which provide favorable photocatalytic activity enhancements, such as enhanced visible light absorption, stability, an increased charge–carrier separation rate and improved specific surface area. Among the various structural engineering methods in this review, we will introduce TiO2-based materials with different dimensional structures. Meanwhile, we also discuss recent achievements in synthesis methods and application of TiO2-based catalysts in various fields. We aim to display a comprehensive overview which can be a guide for the development of a new generation of TiO2-based catalysts according to their structural design for enhanced solar energy conversion.
Multiple Endocrine Neoplasia Type 1 Regulates TGFβ-Mediated Suppression of Tumor Formation and Metastasis in Melanoma
Authors: Boudreault Julien , Canaff Lucie , Ghozlan Mostafa , Wang Ni , Guarnieri Vito , Salcuni Antonio Stefano , Scillitani Alfredo , Goltzman David , Ali Suhad , Lebrun Jean-Jacques
Published: June 2024

Over the past few decades, the worldwide incidence of cutaneous melanoma, a malignant neoplasm arising from melanocytes, has been increasing markedly, leading to the highest rate of skin cancer-related deaths. While localized tumors are easily removed by excision surgery, late-stage metastatic melanomas are refractory to treatment and exhibit a poor prognosis. Consequently, unraveling the molecular mechanisms underlying melanoma tumorigenesis and metastasis is crucial for developing novel targeted therapies. We found that the multiple endocrine neoplasia type 1 (MEN1) gene product Menin is required for the transforming growth factor beta (TGFβ) signaling pathway to induce cell growth arrest and apoptosis in vitro and prevent tumorigenesis in vivo in preclinical xenograft models of melanoma. We further identified point mutations in two MEN1 family members affected by melanoma that led to proteasomal degradation of the MEN1 gene product and to a loss of TGFβ signaling. Interestingly, blocking the proteasome degradation pathway using an FDA-approved drug and RNAi targeting could efficiently restore MEN1 expression and TGFβ transcriptional responses. Together, these results provide new potential therapeutic strategies and patient stratification for the treatment of cutaneous melanoma.
Specific Cell Targeting by Toxoplasma gondii Displaying Functional Single-Chain Variable Fragment as a Novel Strategy; A Proof of Principle
Authors: Aljieli Muna , Rivière Clément , Lantier Louis , Moiré Nathalie , Lakhrif Zineb , Boussemart Anne-France , Cnudde Thomas , Lajoie Laurie , Aubrey Nicolas , Ahmed Elhadi M. , Dimier-Poisson Isabelle , Di-Tommaso Anne , Mévélec Marie-Noëlle
Published: June 2024

Toxoplasma gondii holds significant therapeutic potential; however, its nonspecific invasiveness results in off-target effects. The purpose of this study is to evaluate whether T. gondii specificity can be improved by surface display of scFv directed against dendritic cells’ endocytic receptor, DEC205, and immune checkpoint PD-L1. Anti-DEC205 scFv was anchored to the T. gondii surface either directly via glycosylphosphatidylinositol (GPI) or by fusion with the SAG1 protein. Both constructs were successfully expressed, but the binding results suggested that the anti-DEC-SAG1 scFv had more reliable functionality towards recombinant DEC protein and DEC205-expressing MutuDC cells. Two anti-PD-L1 scFv constructs were developed that differed in the localization of the HA tag. Both constructs were adequately expressed, but the localization of the HA tag determined the functionality by binding to PD-L1 protein. Co-incubation of T. gondii displaying anti-PD-L1 scFv with tumor cells expressing/displaying different levels of PD-L1 showed strong binding depending on the level of available biomarker. Neutralization assays confirmed that binding was due to the specific interaction between anti-PD-L1 scFv and its ligand. A mixed-cell assay showed that T. gondii expressing anti-PD-L1 scFv predominately targets the PD-L1-positive cells, with negligible off-target binding. The recombinant RH-PD-L1-C strain showed increased killing ability on PD-L1+ tumor cell lines compared to the parental strain. Moreover, a co-culture assay of target tumor cells and effector CD8+ T cells showed that our model could inhibit PD1/PD-L1 interaction and potentiate T-cell immune response. These findings highlight surface display of antibody fragments as a promising strategy of targeting replicative T. gondii strains while minimizing nonspecific binding.
Emerging Treatments Targeting the Tumor Microenvironment for Advanced Chondrosarcoma
Authors: Ingangi Vincenzo , De Chiara Annarosaria , Ferrara Gerardo , Gallo Michele , Catapano Antonio , Fazioli Flavio , Di Carluccio Gioconda , Peranzoni Elisa , Marigo Ilaria , Carriero Maria Vincenza , Minopoli Michele
Published: June 2024

Chondrosarcoma (ChS), a malignant cartilage-producing tumor, is the second most frequently diagnosed osseous sarcoma after osteosarcoma. It represents a very heterogeneous group of malignant chemo- and radiation-resistant neoplasms, accounting for approximately 20% of all bone sarcomas. The majority of ChS patients have a good prognosis after a complete surgical resection, as these tumors grow slowly and rarely metastasize. Conversely, patients with inoperable disease, due to the tumor location, size, or metastases, represent a great clinical challenge. Despite several genetic and epigenetic alterations that have been described in distinct ChS subtypes, very few therapeutic options are currently available for ChS patients. Therefore, new prognostic factors for tumor progression as well as new treatment options have to be explored, especially for patients with unresectable or metastatic disease. Recent studies have shown that a correlation between immune infiltrate composition, tumor aggressiveness, and survival does exist in ChS patients. In addition, the intra-tumor microvessel density has been proven to be associated with aggressive clinical behavior and a high metastatic potential in ChS. This review will provide an insight into the ChS microenvironment, since immunotherapy and antiangiogenic agents are emerging as interesting therapeutic options for ChS patients.
Regulator of Lipid Metabolism NHR-49 Mediates Pathogen Avoidance through Precise Control of Neuronal Activity
Authors: Kwon Saebom , Park Kyu-Sang , Yoon Kyoung-hye
Published: June 2024

Precise control of neuronal activity is crucial for the proper functioning of neurons. How lipid homeostasis contributes to neuronal activity and how much of it is regulated by cells autonomously is unclear. In this study, we discovered that absence of the lipid regulator nhr-49, a functional ortholog of the peroxisome proliferator-activated receptor (PPAR) in Caenorhabditis elegans, resulted in defective pathogen avoidance behavior against Pseudomonas aeruginosa (PA14). Functional NHR-49 was required in the neurons, and more specifically, in a set of oxygen-sensing body cavity neurons, URX, AQR, and PQR. We found that lowering the neuronal activity of the body cavity neurons improved avoidance in nhr-49 mutants. Calcium imaging in URX neurons showed that nhr-49 mutants displayed longer-lasting calcium transients in response to an O2 upshift, suggesting that excess neuronal activity leads to avoidance defects. Cell-specific rescue of NHR-49 in the body cavity neurons was sufficient to improve pathogen avoidance, as well as URX neuron calcium kinetics. Supplementation with oleic acid also improved avoidance behavior and URX calcium kinetics, suggesting that the defective calcium response in the neuron is due to lipid dysfunction. These findings highlight the role of cell-autonomous lipid regulation in neuronal physiology and immune behavior.
Voice as a Biomarker of Pediatric Health: A Scoping Review
Authors: Rogers Hannah Paige , Hseu Anne , Kim Jung , Silberholz Elizabeth , Jo Stacy , Dorste Anna , Jenkins Kathy
Published: June 2024

The human voice has the potential to serve as a valuable biomarker for the early detection, diagnosis, and monitoring of pediatric conditions. This scoping review synthesizes the current knowledge on the application of artificial intelligence (AI) in analyzing pediatric voice as a biomarker for health. The included studies featured voice recordings from pediatric populations aged 0–17 years, utilized feature extraction methods, and analyzed pathological biomarkers using AI models. Data from 62 studies were extracted, encompassing study and participant characteristics, recording sources, feature extraction methods, and AI models. Data from 39 models across 35 studies were evaluated for accuracy, sensitivity, and specificity. The review showed a global representation of pediatric voice studies, with a focus on developmental, respiratory, speech, and language conditions. The most frequently studied conditions were autism spectrum disorder, intellectual disabilities, asphyxia, and asthma. Mel-Frequency Cepstral Coefficients were the most utilized feature extraction method, while Support Vector Machines were the predominant AI model. The analysis of pediatric voice using AI demonstrates promise as a non-invasive, cost-effective biomarker for a broad spectrum of pediatric conditions. Further research is necessary to standardize the feature extraction methods and AI models utilized for the evaluation of pediatric voice as a biomarker for health. Standardization has significant potential to enhance the accuracy and applicability of these tools in clinical settings across a variety of conditions and voice recording types. Further development of this field has enormous potential for the creation of innovative diagnostic tools and interventions for pediatric populations globally.
Electronic Heart (ECG) Monitoring at Birth and Newborn Resuscitation
Authors: Mende Sarah , Ahmed Syed , DeShea Lise , Szyld Edgardo , Shah Birju A.
Published: June 2024

Background: Approximately 10% of newborns require assistance at delivery, and heart rate (HR) is the primary vital sign providers use to guide resuscitation methods. In 2016, the American Heart Association (AHA) suggested electrocardiogram in the delivery room (DR-ECG) to measure heart rate during resuscitation. This study aimed to compare the frequency of resuscitation methods used before and after implementation of the AHA recommendations. Methods: This longitudinal retrospective cohort study compared a pre-implementation (2015) cohort with two post-implementation cohorts (2017, 2021) at our Level IV neonatal intensive care unit. Results: An initial increase in chest compressions at birth associated with the introduction of DR-ECG monitoring was mitigated by focused educational interventions on effective ventilation. Implementation was accompanied by no changes in neonatal mortality. Conclusions: Investigation of neonatal outcomes during the ongoing incorporation of DR-ECG may help our understanding of human and system factors, identify ways to optimize resuscitation team performance, and assess the impact of targeted training initiatives on clinical outcomes.
Cobalt Ion-Modified Titanium Oxide Nanorods: A Promising Approach for High-Performance Electrochromic Application
Authors: Morankar Pritam J. , Amate Rutuja U. , Teli Aviraj M. , Beknalkar Sonali A. , Jeon Chan-Wook
Published: June 2024

The development of novel cathodic materials with tailored nanostructures is crucial for the advancement of electrochromic devices. In this study, we synthesized cobalt-doped titanium dioxide (Ti-Co) thin films using a facile hydrothermal method to investigate the effects of cobalt doping on their structural, morphological, and electrochromic properties. Comprehensive characterization techniques, including X-ray diffraction and Raman analysis, confirmed the highly crystalline nature of the Ti-Co thin films, with specific Raman bands indicating distinct modifications due to cobalt incorporation. The TiO2 nanorods, optimally doped with cobalt (TC-3), demonstrated enhanced charge transport and mobility, significantly improving the electrochromic performance. Among the various compositions studied, the TC-3 sample exhibited superior lithium-ion accommodation, achieving an optical modulation of 73.6% and a high coloration efficiency of 81.50 cm2/C. It also demonstrated excellent electrochromic stability, maintaining performance for up to 5000 s of coloring/bleaching cycles. These results confirm the beneficial impact of cobalt doping on the structural and functional properties of the host material. Furthermore, the practical effectiveness of the TC-3 thin film was validated through the fabrication of an electrochromic device, which showed efficient coloration and bleaching capabilities. This comprehensive research enhances the understanding and functionality of Ti-Co nanorod architectures, highlighting their promising potential for advanced electrochromic applications.
Effects of Ti/Nb Dual-Element Addition on the Microstructure and Properties of Tungsten Carbide-Reinforced Laser Cladding Coatings
Authors: Li Jianfeng , Gao Xue , Dong Kewei , Liu Jinfu
Published: June 2024

Metal-ceramic composite coatings are produced on the surface of equipment components by laser cladding, improving the abrasive wear resistance of components and extending their service life. However, defects such as brittleness and cracks limit the wide application of metal-ceramic clad coatings in the field of construction machinery. In the present study, a dual-element (Ti/Nb) alloying method is innovatively adopted to regulate the microstructure and mechanical properties of tungsten carbide (WC)-reinforced clad coatings. Experimental results show that with the introduction of Ti/Nb, novel reinforcements are in-situ synthesized in the cladding coatings with two different kinds of morphologies: one is a core-shell carbide with the core of pure TiC and a shell of (Ti,Nb,W)C multiple carbide; the other is a (Ti,Nb,W)C multiple carbide. With 8 wt.% Ti/Nb addition, the newly formed multiple carbides with the appropriate content are well-dispersed and distributed in the clad coating, which effectively transfers load, inhibits the initiation and expansion of micro-cracks, and resists the wear damage of hard abrasive particles, solving the technical problems of the simultaneous improvement of toughness and abrasive wear resistance of metal-ceramic laser cladding coatings.
Helix Formation from Hydrogen Bond Kinetics in Alanine Homopeptides
Authors: Kuczera Krzysztof , Jas Gouri S. , Szoszkiewicz Robert
Published: June 2024

We present an analysis of α-helix folding in the coarse-grained coordinate of number of formed helical hydrogen bonds (NHBs) for four alanine peptides (ALA)n, with n = 5, 8, 15, and 21 residues. Starting with multi-microsecond all-atom molecular dynamics trajectories in aqueous solution, we represent the system dynamics in a space of between four (for ALA5) and twenty (for ALA21) hydrogen-bonding microstates. In all cases, transitions changing the hydrogen bond count by 1–2 dominate and the coil formation, NHB 1 → 0, is the fastest process. The calculation of global maximum weight paths shows that, when analyzed at a sufficiently long lag time, folding in the NHB coordinate is consecutive, with direct folding, 0 → 3, for ALA5 and bottlenecks at transitions 4 → 6 for ALA8, 0 → 5 for ALA15, and 0 → 9 for ALA21. Further coarse-graining to 2–4 dimensions was performed with the optimal dimensionality reduction method, allowing the identification of crucial folding intermediates and time scales of their formation in ALA8, ALA15, and ALA21. The detailed analysis of hydrogen bonding patterns revealed that folding is initiated preferentially at both peptide termini. The kinetic model was also used to estimate diffusion and friction coefficients for helix propagation. The description of the helix formation process in the hydrogen bonding coordinate NHB was in good general agreement with the experimental data and qualitatively similar to previous kinetic models of higher dimensions based on structural clustering. Use of the low-dimensional hydrogen bonding picture thus provides a different, complementary way of describing the complex and fascinating mechanism of helix formation.
Evaluation of Bitemark Analysis’s Potential Application in Forensic Identification: A Systematic Review
Authors: Christoloukas Nikolaos , Mitsea Anastasia , Rontogianni Aliki , Papadakis Evangelos , Angelopoulos Christos
Published: June 2024

Bitemark analysis involves the examination of both patterned injuries and contextual circumstances, combining morphological and positional data. Considering the uniqueness of human dentition, bitemarks caused by teeth on skin or impressions on flexible surfaces could assist in human identification. Aims: to investigate the available literature systematically and evaluate the scientific evidence published over the past decade concerning the potential application of bitemark analysis in forensic identification. Methods: Two researchers meticulously searched electronic databases from January 2012 to December 2023, including Scopus, PubMed, Web of Science, and the Cochrane Library. Adhering to the PRISMA statement guidelines, this review employed appropriate medical subject headings (MeSHs) and free-text synonyms. Strict inclusion and exclusion criteria were applied during article retrieval. Results: The findings yielded controversial outcomes. Approximately two-thirds of the articles concluded that bitemark analysis is useful in forensic identification, while the remaining articles did not report statistically significant outcomes and cautioned against relying solely on bitemark analysis for identification. Conclusions: The authors assert that bitemark analysis can be a reliable and complementary method for forensic identification, contingent upon the establishment and adoption of a universally accepted global protocol for data collection, processing, and interpretation. Undoubtedly, recent years have witnessed a notable increase in research focused on bitemark identification, driven by the goal of achieving quantitative, objective, reproducible, and accurate results.
Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection
Authors: Syed Asif Hassan , Abujabal Hamza Ali S. , Ahmad Shakeel , Malebary Sharaf J. , Alromema Nashwan
Published: June 2024

This study, utilizing high-throughput technologies and Machine Learning (ML), has identified gene biomarkers and molecular signatures in Inflammatory Bowel Disease (IBD). We could identify significant upregulated or downregulated genes in IBD patients by comparing gene expression levels in colonic specimens from 172 IBD patients and 22 healthy individuals using the GSE75214 microarray dataset. Our ML techniques and feature selection methods revealed six Differentially Expressed Gene (DEG) biomarkers (VWF, IL1RL1, DENND2B, MMP14, NAAA, and PANK1) with strong diagnostic potential for IBD. The Random Forest (RF) model demonstrated exceptional performance, with accuracy, F1-score, and AUC values exceeding 0.98. Our findings were rigorously validated with independent datasets (GSE36807 and GSE10616), further bolstering their credibility and showing favorable performance metrics (accuracy: 0.841, F1-score: 0.734, AUC: 0.887). Our functional annotation and pathway enrichment analysis provided insights into crucial pathways associated with these dysregulated genes. DENND2B and PANK1 were identified as novel IBD biomarkers, advancing our understanding of the disease. The validation in independent cohorts enhances the reliability of these findings and underscores their potential for early detection and personalized treatment of IBD. Further exploration of these genes is necessary to fully comprehend their roles in IBD pathogenesis and develop improved diagnostic tools and therapies. This study significantly contributes to IBD research with valuable insights, potentially greatly enhancing patient care.
Engagement in Youth Athletes as a Positive Experience in Sport: Implications of Gender, Age, and Competitive Level
Authors: Raimundi María Julia , Celsi Ignacio , Pérez-Gaido Mauro , Schmidt Vanina , Castillo Isabel , Alvarez Octavio
Published: June 2024

The aim of this study was to examine athlete engagement and its relationships with indicators of the quality of the athlete’s sport experience, exploring potential differences according to gender, age, and competitive level. Furthermore, this study validated the Athlete Engagement Questionnaire (AEQ) in young athletes and confirmed its factor structure. A total of 1188 athletes (43.90% girls) from Argentina participated in the study, with a mean age of 15.92 (SD = 2.50). The participants completed the AEQ along with other measures of athletes’ quality of experience, such as motivation, enjoyment, and burnout. This study confirmed the multidimensional nature of engagement, showing positive associations with high-quality athlete experiences and revalidating the inverse relationship with burnout. Moreover, the study found differences in engagement dimensions (i.e., confidence, vigor, dedication, and enthusiasm) based on the interplay of gender, age, and competitive level. In general, male athletes, younger athletes, and those with a higher competitive level showed more engagement and interactions between these sociodemographic variables. The Argentinian version of AEQ exhibited optimal fit and reliability and good indexes of measurement invariance across gender, age, and competitive level. These findings validate the AEQ as a reliable tool for evaluating sport engagement among adolescents in Argentina. Engagement constitutes an indicator of an optimal experience linked to positive youth development through sports participation.
Impact of Solder Voids on IGBT Thermal Behavior: A Multi-Methodological Approach
Authors: Alavi Omid , De Ceuninck Ward , Daenen Michaël
Published: June 2024

This study investigates the thermal behavior of Insulated Gate Bipolar Transistors (IGBTs) with a focus on the influence of solder voids within the device. Utilizing a combination of Finite Element Method (FEM) simulations, X-ray imaging, and SEM-EDX analysis, we accurately modeled the internal structure of IGBTs to assess the impact of void characteristics on thermal resistance. The findings reveal that the presence and characteristics of solder voids—particularly their size, number, and distribution—significantly affect the thermal resistance of IGBT devices. Experimental measurements validate the FEM model’s accuracy, confirming that voids disrupt the heat flow path, which can lead to increased thermal resistance and potential device failure. Five regression models, including Gaussian process regression (GPR) and neural networks, were employed to predict the thermal resistance based on void characteristics, with the GPR models demonstrating superior performance. The optimal GPR RQ model consistently provided accurate predictions with an RMSE of 0.0050 and R2 of 0.9728. Using the void percentage as the only input parameter for the regression models significantly impacted the prediction accuracy, showing the importance of the void extraction method. This study shows the necessity of minimizing solder voids and offers a robust methodological framework for a better prediction of the reliability of IGBTs.
A Simple Thermal Model for Junction and Hot Spot Temperature Estimation of 650 V GaN HEMT during Short Circuit
Authors: Palazzo Simone , Sanseverino Annunziata , Canale Parola Giovanni , Martano Emanuele , Velardi Francesco , Busatto Giovanni
Published: June 2024

Temperature is a critical parameter for the GaN HEMT as it sharply impacts the electrical characteristics of the device more than for SiC or Si MOSFETs. Either when designing a power converter or testing a device for reliability and robustness characterizations, it is essential to estimate the junction temperature of the device. For this aim, manufacturers provide compact models to simulate the device in SPICE-based simulators. These models provide the junction temperature, which is considered uniform along the channel. We demonstrate through two-dimensional numerical simulations that this approach is not suitable when the device undergoes high electrothermal stress, such as during short circuit (SC), when the temperature distribution along the channel is strongly not uniform. Based on numerical simulations and experimental measurements on a 650 V/4 A GaN HEMT, we derived a thermal network suitable for SPICE simulations to correctly compute the junction temperature and the SC current, even if not providing information about the possible failure of the device due to the formation of a local hot spot. For this reason, we used a second thermal network to estimate the maximum temperature reached inside the device, whose results are in good agreement with the experimental observed failures.
Design and Analysis of a High-Gain, Low-Noise, and Low-Power Analog Front End for Electrocardiogram Acquisition in 45 nm Technology Using gm/ID Method
Authors: Emon Md. Zubair Alam , Salim Khosru Mohammad , Chowdhury Md. Iqbal Bahar
Published: June 2024

In this work, an analog front-end (AFE) circuit for an electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using an advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter—all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the gm/ID methodology. Both the pre-layout and post-layout simulation are carried out. The layout consumes an area of 0.00628 mm2 without the resistors and capacitors. Analysis of various simulation results are carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz, with a variable gain between 44 and 58 dB, a notch depth of −56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of −59.65 dB (less than 1%), an input-referred noise spectral density of <34 μVrms/Hz at the pass-band, a dynamic range of 52.71 dB, and a total power consumption of 10.88 μW with a supply of ±0.6 V. Hence, the AFE exhibits the promise of high-quality signal acquisition capability required for portable ECG detection systems in modern healthcare.
Speech Emotion Recognition Using Dual-Stream Representation and Cross-Attention Fusion
Authors: Yu Shaode , Meng Jiajian , Fan Wenqing , Chen Ye , Zhu Bing , Yu Hang , Xie Yaoqin , Sun Qiurui
Published: June 2024

Speech emotion recognition (SER) aims to recognize human emotions through in-depth analysis of audio signals. However, it remains challenging to encode emotional cues and to fuse the encoded cues effectively. In this study, dual-stream representation is developed, and both full training and fine-tuning of different deep networks are employed for encoding emotion patterns. Specifically, a cross-attention fusion (CAF) module is designed to integrate the dual-stream output for emotion recognition. Using different dual-stream encoders (fully training a text processing network and fine-tuning a pre-trained large language network), the CAF module is compared to other three fusion modules on three databases. The SER performance is quantified with weighted accuracy (WA), unweighted accuracy (UA), and F1-score (F1S). The experimental results suggest that the CAF outperforms the other three modules and leads to promising performance on the databases (EmoDB: WA, 97.20%; UA, 97.21%; F1S, 0.8804; IEMOCAP: WA, 69.65%; UA, 70.88%; F1S, 0.7084; RAVDESS: WA, 81.86%; UA, 82.75.21%; F1S, 0.8284). It is also found that fine-tuning a pre-trained large language network achieves superior representation than fully training a text processing network. In a future study, improved SER performance could be achieved through the development of a multi-stream representation of emotional cues and the incorporation of a multi-branch fusion mechanism for emotion recognition.
An Improved YOLOv5s Model for Building Detection
Authors: Zhao Jingyi , Li Yifan , Cao Jing , Gu Yutai , Wu Yuanze , Chen Chong , Wang Yingying
Published: June 2024

With the continuous advancement of autonomous vehicle technology, the recognition of buildings becomes increasingly crucial. It enables autonomous vehicles to better comprehend their surrounding environment, facilitating safer navigation and decision-making processes. Therefore, it is significant to improve detection efficiency on edge devices. However, building recognition faces problems such as severe occlusion and large size of detection models that cannot be deployed on edge devices. To solve these problems, a lightweight building recognition model based on YOLOv5s is proposed in this study. We first collected a building dataset from real scenes and the internet, and applied an improved GridMask data augmentation method to expand the dataset and reduce the impact of occlusion. To make the model lightweight, we pruned the model by the channel pruning method, which decreases the computational costs of the model. Furthermore, we used Mish as the activation function to help the model converge better in sparse training. Finally, comparing it to YOLOv5s (baseline), the experiments show that the improved model reduces the model size by 9.595 MB, and the mAP@0.5 reaches 82.3%. This study will offer insights into lightweight building detection, demonstrating its significance in environmental perception, monitoring, and detection, particularly in the field of autonomous driving.
Shaping Tomorrow: Anticipating Skills Requirements Based on the Integration of Artificial Intelligence in Business Organizations—A Foresight Analysis Using the Scenario Method
Authors: Bobitan Nicolae , Dumitrescu Diana , Popa Adriana Florina , Sahlian Daniela Nicoleta , Turlea Ioan Codrut
Published: June 2024

This study examines the impact of artificial intelligence (AI) on workforce skill requirements as AI becomes increasingly integrated into business operations. Using foresight analysis and scenario-based methods, we anticipate the necessary skills for future AI-integrated workplaces. A SWOT analysis evaluates three potential paths for AI adoption—gradual, aggressive, and selective—to project the evolving skills needed for employee success in changing business environments. The findings emphasize the critical need for both enhanced technical proficiency and soft skills, such as creative problem-solving and interpersonal abilities, across all AI adoption scenarios. The study highlights the importance of strategic reskilling and continuous learning to align employee skills with the new business paradigms shaped by AI. It provides a roadmap for businesses, educators, and policymakers to collaboratively develop a resilient and adaptable workforce for an AI-enhanced future.
Metaverse and Fashion: An Analysis of Consumer Online Interest
Authors: Ruiz Viñals Carmen , Gil Ibáñez Marta , Del Olmo Arriaga José Luis
Published: June 2024

Recent studies have demonstrated the value that the Internet and web applications bring to businesses. Among other tools are those that enable the analysis and monitoring of searches, such as Google Trends, which is currently used by the fashion industry to guide experiential practices in a context of augmented reality and/or virtual reality, and even to predict purchasing behaviours through the metaverse. Data from this tool provide insight into fashion consumer search patterns. Understanding and managing this digital tool is an essential factor in rethinking businesses’ marketing strategies. The aim of this study is to analyse online user search behaviour by analysing and monitoring the terms “metaverse” and “fashion” on Google Trends. A quantitative descriptive cross-sectional method was employed. The results show that there is growing consumer interest in both concepts on the Internet, despite the lack of homogeneity in the behaviour of the five Google search tools.
Untargeted Metabolomics Analysis Based on LC-QTOF-MS to Investigate the Phenolic Composition of Red and White Wines Elaborated from Sonicated Grapes
Authors: Martínez-Moreno Alejandro , Pérez-Porras Paula , Bautista-Ortín Ana Belén , Gómez-Plaza Encarna , Vallejo Fernando
Published: June 2024

Ultrasounds are considered an emerging technology in the wine industry. Concretely, in 2019, the International Organization of Vine and Wine (OIV) officially approved their use for the treatment of crushed grapes to increase the level of phenolic compound extraction. The main objective of this study was to validate an untargeted metabolomics approach as an analytical tool for identifying novel markers associated with sonication. To do so, the influence of a sonication treatment on the metabolic profile was studied in four typically commercial varietal wines, i.e., two red wines from ‘Syrah’ and ‘Cabernet Sauvignon’ grapes and two white wines from ‘Macabeo’ and ‘Airén’ grapes. A robust classification and prediction model was created employing supervised techniques such as partial least-squares discriminant analysis (PLS-DA). The findings indicated that the grapes subjected to high-power ultrasound conditions experienced cell wall disruption due to the cavitation phenomenon, resulting in significant changes in various phenolic compounds (including hydroxycinnamic acids and flavonoids) present in these wines compared to wines from non-sonicated grapes. Additionally, new metabolites were tentatively identified through untargeted metabolomics techniques. This study represents the successful application of the untargeted metabolomics approach employing a UHPLC-QTOF system to discern how grape sonication affects bioactive secondary metabolites in wines.
Improvement of Theaflavins on Glucose and Lipid Metabolism in Diabetes Mellitus
Authors: Xu Shiyu , Chen Ying , Gong Yushun
Published: June 2024

In diabetes mellitus, disordered glucose and lipid metabolisms precipitate diverse complications, including nonalcoholic fatty liver disease, contributing to a rising global mortality rate. Theaflavins (TFs) can improve disorders of glycolipid metabolism in diabetic patients and reduce various types of damage, including glucotoxicity, lipotoxicity, and other associated secondary adverse effects. TFs exert effects to lower blood glucose and lipids levels, partly by regulating digestive enzyme activities, activation of OATP-MCT pathway and increasing secretion of incretins such as GIP. By the Ca2+-CaMKK ꞵ-AMPK and PI3K-AKT pathway, TFs promote glucose utilization and inhibit endogenous glucose production. Along with the regulation of energy metabolism by AMPK-SIRT1 pathway, TFs enhance fatty acids oxidation and reduce de novo lipogenesis. As such, the administration of TFs holds significant promise for both the prevention and amelioration of diabetes mellitus.
Detection of Salt Content in Canned Tuna by Impedance Spectroscopy: A Feasibility Study for Distinguishing Salt Levels
Authors: Zabala Inés , Merino Santos , Eletxigerra Unai , Ramiro Jorge , Burguera Miren , Aranzabe Estibaliz
Published: June 2024

The electrical impedance of dilute aqueous solutions containing extracts from five brands of canned tuna is analyzed using impedance spectroscopy in order to analyze their salt content and detect the potential presence of other salts beyond the well-stated NaCl. A complex electrical impedance is modeled with an equivalent electrical circuit, demonstrating good agreement with experimental data. This circuit accounts for the contribution of ions in the bulk solution, as well as those contributing to electrode polarization. The parameters describing the equivalent circuits, obtained through fitting data to the electrical impedance, are discussed in terms of the various ion contributions to both the electrical double layer at the electrode interface and the electrical conductivity of each solution. The ionic contribution to the electrical impedance is compared with that of a pure NaCl solution at the same concentration range. This comparison, when extended to real samples, allows for the development of a model to estimate the electrical conductivity of canned tuna samples, thereby determining the salt concentration in tuna. The model enables differentiation among the various samples of tuna studied. Subsequently, the potential presence of other ions besides Na+ and Cl− and their contribution to the electrical properties of each canned tuna extract is considered, especially for samples with a higher ratio of the sum of K+ and phosphates to Na+ concentration. This analysis shows the potential of impedance spectroscopy for on-site and rapid analysis of salt content and/or detection of additives in canned tuna fish.