bluuebunny/crossref_metadata_2025 huggingface dataset:
A Few-Shot Learning-Based Material Recognition Scheme Using Smartphones
Authors: Kim Yeonju , Yoon Jeonghyeon , Kim Seungku
Published: January 2025

This study proposes FSMR, a material recognition scheme designed to expand context information about locations in context recognition services. FSMR identifies the material in contact with the smartphone and determines the object based on this information to obtain location data. When the smartphone sends vibrations to the object it touches, the vibration signals change according to the unique properties of the material, and the reflected signals are measured using an accelerometer. Based on the fact that the measured sensor values have distinct characteristics for each material, deep learning techniques are applied to classify the material and determine the object. The existing research on material and object recognition using smartphone vibrations and accelerometers often requires vast amounts of training data for deep learning-based models, making it challenging to apply to real-world applications. To address this issue, this study employs few-shot learning and data augmentation to significantly reduce the amount of training data required. The evaluation results show that FSMR achieved classification accuracies of up to 72.03% and 83.63% when trained with data collected over 1 s and 5 s, respectively.
G&G Attack: General and Geometry-Aware Adversarial Attack on the Point Cloud
Authors: Chen Geng , Zhang Zhiwen , Peng Yuanxi , Li Chunchao , Li Teng
Published: January 2025

Deep neural networks have been shown to produce incorrect predictions when imperceptible perturbations are introduced into the clean input. This phenomenon has garnered significant attention and extensive research in 2D images. However, related work on point clouds is still in its infancy. Current methods suffer from issues such as generated point outliers and poor attack generalization. Consequently, it is not feasible to rely solely on overall or geometry-aware attacks to generate adversarial samples. In this paper, we integrate adversarial transfer networks with the geometry-aware method to introduce adversarial loss into the attack target. A state-of-the-art autoencoder is employed, and sensitivity maps are utilized. We use the autoencoder to generate a sufficiently deceptive mask that covers the original input, adjusting the critical subset through a geometry-aware trick to distort the point cloud gradient. Our proposed approach is quantitatively evaluated in terms of the attack success rate (ASR), imperceptibility, and transferability. Compared to other baselines on ModelNet40, our method demonstrates an approximately 38% improvement in ASR for black-box transferability query attacks, with an average query count of around 7.84. Comprehensive experimental results confirm the superiority of our method.
Retrofitting of a Multi-Span Simply Supported Bridge into a Semi-Integral Bridge
Authors: Xu Zhen , Luo Xiaoye , Sennah Khaled , Chen Baochun , Zhuang Yizhou
Published: January 2025

Thousands of multi-span, simply supported beam bridges with short or medium spans have been built in China. They often suffer from problems of cracks in the link slabs over piers, and the deterioration and damage of deck expansion joints at abutments. To address these problems, one approach is to retrofit them by converting the simply supported box beams into continuous structures over the piers and jointless bridges over the abutments. This paper discusses the design methodology and details for retrofitting the Jinpu Bridge in Zhangzhou, Fujian, China, from a simply supported bridge into a semi-integral bridge, in which semi-fixed dowel joints are used to connect the superstructure and the substructure, including piers and abutments. Simultaneously, the finite element software is used to calculate the internal forces and displacements of the structure. The analysis reveals an 11.1% reduction in the maximum positive moment at the midspan of the main beam in the semi-integral bridge compared to the simply supported bridge. However, the shear forces at the interior pier increase by 6.4%. According to the response spectrum analysis, the maximum longitudinal displacement of the semi-integral bridge’s main beam is 11.6 mm, reduced by 80.1% compared to the simply supported bridge under a dead load and earthquake effects. The maximum bending moment and shear force on the pier of the semi-integral bridge are 984.7 kN·m and 312.6 kN, respectively, both below their ultimate bearing capacities. The maximum displacement at the top of the pier is 7.7 mm, which is below the allowable 52.4 mm displacement. The calculated results conform to the design requirements specified by the code.
A Deep Learning-Based Mapping Model for Three-Dimensional Propeller RANS and LES Flow Fields
Authors: Jin Jianhai , Ye Yuhuang , Li Xiaohe , Li Liang , Shan Min , Sun Jun
Published: January 2025

In this work, we propose a deep learning-based model for mapping between the data of the flow field of the propeller generated by the Reynolds-averaged Navier–Stokes (RANS) and those generated by Large Eddy Simulation (LES). The goal of establishing the mapping model is to generate LES data, which needs higher computing power requirements, with the help of RANS data. The model utilizes a deep learning method for computer vision to handle three-dimensional data generated by RANS and those by LES. Firstly, the data samples of the RANS flow field and those of the LES flow field are processed to obtain their corresponding three-dimensional image data, respectively. Secondly, the two kinds of field flow images are used as the training data for constructing a mapping model between RANS flow field images and the corresponding LES flow field images. The obtained mapping model thus can be used to predict the LES flow field images. Thirdly, the regression module is employed to regress the three-dimensional LES image point-by-point to the velocities at the points of the LES flow field, thereby ultimately achieving the generation of LES flow field data from RANS data. The experimental results show that by applying this method to RANS data and LES data of propeller flow fields, the overall error rate of LES flow field prediction by this method is 17.68% compared to actual flow field data, which verifies the effectiveness and accuracy of the proposed model in LES flow field prediction.
Fuzzy Delphi and DEMATEL Approaches in Sustainable Wearable Technologies: Prioritizing User-Centric Design Indicators
Authors: Liao Chin-Wen , Yao Kai-Chao , Wang Ching-Hsin , Hsieh Hsi-Huang , Wang I-Chi , Ho Wei-Sho , Huang Wei-Lun , Huang Shu-Hua
Published: January 2025

The rapid advancement of intelligent technologies, including sensing devices, artificial intelligence, and the Internet of Things, has significantly accelerated the progress in industrial technology, particularly within the medical enterprise sector. Wearable innovations for health management have introduced novel approaches to physiological monitoring and early disease detection, contributing to an improved quality of life. In the context of sustainable development, wearable devices demonstrate considerable potential for supporting long-term healthcare solutions, particularly in the post-pandemic era, where the demand for smart health solutions continues to rise. This study aims to identify critical product design indicators for wearable devices that align with sustainable health management goals. Utilizing expert questionnaires and employing a combination of the Fuzzy Delphi Method and the DEMATEL-based Analytic Network Process (ANP), this research systematically evaluates the key factors influencing wearable device design. The findings highlight three primary aspects, six criteria, and 16 design indicators, with pivotal factors including “Compatibility”, “Foresight”, “Integration”, “Comfort”, “Appearance”, “Customization”, and “Intelligence”. These indicators provide a comprehensive framework for developing wearable devices that address diverse user needs while promoting individual well-being and sustainable health management. This study offers valuable insights into the design and development of wearable devices that support sustainable healthcare practices, advance social responsibility, and strengthen preventive care initiatives.
The Effect of Exercise Interventions on Sleep Quality and Weight Loss in Individuals with Obesity: A Systematic Review and Meta-Analysis of Randomized Control Trials
Authors: Ka Soonjo , Choe Yu Hyeon , Kim Young-Im , Kim Nahyun , Seo Minjae , Choi Youngju , Park Jonghoon
Published: January 2025

This study evaluated the effects of exercise interventions on sleep quality and weight loss through a systematic literature review and meta-analysis. A comprehensive literature search was conducted across PubMed, Embase, Web of Science, and the Cochrane Library for publications up to December 2022. Only randomized controlled trials (RCTs) were included in the analysis. The Risk of Bias was assessed using the Cochrane Risk of Bias 2 (ROB 2) tool, and disagreements were resolved by consensus. Data synthesis and meta-analysis were performed using Comprehensive Meta-Analysis Version 4 (CMA version 4) software, with outcomes expressed as pooled effect sizes, odds ratios (ORs), and 95% confidence intervals (CIs). Seven RCTs encompassing 908 participants were analyzed. The meta-analysis indicated a significant improvement in sleep outcomes (OR = 3.93, 95% CI [2.04, 7.56], p < 0.001). The combined aerobic and resistance exercise regimen showed the most substantial effects on sleep quality. Additionally, four of the seven RCTs included in the weight loss analysis indicated a significant improvement in weight loss (OR = 2.58, 95% CI [1.79, 3.71], p < 0.001). Exercise interventions have a strong potential for improving sleep quality and weight loss in adults with obesity. Future studies should focus on developing optimized targeted strategies for sleep enhancement.
Characterization of the Interaction of a Novel Anticancer Molecule with PMMA, PCL, and PLGA Polymers via Computational Chemistry
Authors: Montenegro Edwar D. , Nunes Jamylle M. , Ramos Igor F. S. , Almeida Renata G. , da Silva Júnior Eufrânio N. , Rizzo Márcia S. , da Silva-Filho Edson C. , Ribeiro Alessandra B. , Silva Heurison S. , Costa Marcília P.
Published: January 2025

The development of anticancer drugs is costly and time intensive. Computational approaches optimize the process by studying molecules such as naphthoquinones. This research explores the quantitative structure–activity relationship (QSPR) and molecular interactions among 2,2-dimethyl-3-((3-nitrophenyl)amino)-2,3-dihydronaphtho[1,2-b]furan-4,5-dione (QPhNO2), a Nor-β-Lapachone derivative with anticancer properties, and the following polymers for nanoencapsulation: polymethyl methacrylate (PMMA), polycaprolactone (PCL), and poly-lactic-co-glycolic acid (PLGA). Spartan 14 optimized the compounds using density functional theory (DFT), while ArgusLab performed docking, and Discovery Studio analyzed post-docking results. Simulations indicated that polymers with larger energy gaps are more stable and less prone to deformation than QPhNO2, facilitating interaction with polymer chains. The binding energies for PMMA/QPhNO2, PCL/QPhNO2, and PLGA/QPhNO2 interactions were −4.607, −4.437, and −1.814 kcal/mol, respectively. Docking analysis revealed non-bonded interactions between polymers and QPhNO2. These findings highlight the role of computational methods in nanoencapsulation and molecular characterization, guiding the development of future analogs and combinations.
Influence of the Oxide Layer Thickness on the Behavior of the Electrical Wheel–Rail Contact in Static Conditions
Authors: Haydar Luna , Loete Florent , Houzé Frédéric , Slimani Karim , Guiche Fabien , Testé Philippe
Published: January 2025

To manage and ensure the safety of traffic on rail networks, trains need to be reliably located at all times. This is achieved in many countries by electrically detecting their presence using so-called “track circuits” installed at regular intervals on each track, designed to detect when the wheels and axles of a train are shunting the two rails and to act accordingly on the signaling system. Such a detection principle is highly dependent on the quality of the electrical contacts between rails and wheels; the occurrence of high wheel–rail contact resistances can induce malfunctions known as “deshunting”, when the system is unable to judge the presence or absence of a train on a section of track. This type of potentially risky event must obviously be avoided at all costs. In this article, we focus on wheel–rail contact degradation resulting from steel oxidation, using a home-made, scaled-down test bench that reproduces real contact in the laboratory under controlled conditions. Given the complexity of the topic, the investigations are focused on static contact characterizations involving different degrees of rail oxidation and slow, stepwise variations in DC intensity.
Development and Evaluation of Customized Bike Saddle Pads Using Innovative Design for AM Approaches and Suitable Additive Manufacturing Processes
Authors: Geyer Sebastian , Schwemmer Jonas , Hölzl Christian
Published: January 2025

Design for additive manufacturing (DfAM) has made significant advancements in recent years, with development focusing on pivotal aspects such as topology optimization (TO), generative design (GD), lattice structures, and AI-based algorithms. This paper puts forth a proposed methodology for the development of customizable bike saddle pads for manufacturing with AM. The approach entails the selection of appropriate AM processes and materials, the evaluation of material properties through compression testing, an initial saddle pressure mapping and bike fitting, the design and AM of bespoke saddle pads based on the initial measurements, and a validation pressure mapping and bike fitting. The investigation yielded clear findings regarding improvements in both pressure distribution and the change in pressure peaks, as well as an improvement in riding comfort. The findings indicate that although the overall process is innovative, improvements are required to streamline the measuring, modeling, and manufacturing workflow.
Understanding the Seismic Resilience of Metallic Cylindrical Tanks Through Parametric Analysis
Authors: Brunesi Emanuele , Nascimbene Roberto , Beilic Dumitru
Published: January 2025

This research investigates the seismic behavior of rigid and flexible cylindrical steel tanks, focusing on tanks with an open top and fully anchored at the base. The primary objective is to evaluate the hydrodynamic pressures exerted by the fluid on the tank walls during seismic excitation. Three widely recognized design approaches—New Zealand NZSEE recommendations, European code UNI EN 1998-4:2006 (CEN, 2006), and American Water Works Association AWWA D100-05 standard (ANSI/AWWA, 2005)—were implemented and compared with high-definition finite element models and then validated against the experimental results. Nonlinear fluid–structure interaction (FSI) was modeled using an Arbitrary Lagrangian–Eulerian (ALE) formulation with the Navier–Stokes equations governing the fluid motion and material and geometric nonlinearities considered in the tank walls. Parametric analyses were conducted to investigate the impact of tank geometry, specifically height-to-radius and radius-to-thickness ratios, on seismic response, identifying a transition between rigid and flexible behavior. The study also examined the influence of seismic input using a set of ten displacement spectrum-compatible ground motions. The findings contribute to a better understanding of the seismic resilience of cylindrical steel tanks, offering valuable insights for improving design standards and safety in earthquake-prone regions where these systems may abound.
Exploring Surface-Driven Mechanisms for Low-Temperature Sintering of Nanoscale Copper
Authors: Li Jingyan , Song Zixian , Liu Zhichao , Xie Xianli , Guan Penghui , Zhu Yiying
Published: January 2025

As the density of electronic packaging continues to rise, traditional soldering techniques encounter significant challenges, leading to copper–copper direct bonding as a new high-density connection method. The high melting point of copper presents difficulties for direct diffusion bonding under standard conditions, thus making low-temperature copper–copper bonding a focal point of research. In this study, we examine the sintering process at various temperatures by constructing models with multiple nanoparticles and sintering them under different conditions. Our findings indicate that 600 K is a crucial temperature for direct copper–copper sintering. Below this threshold, sintering predominantly depends on structural adjustments driven by residual stresses and particle contact. Conversely, at temperatures of 600 K and above, the activation of rapid surface atomic motion enables further structural adjustments between nanoparticles, leading to a marked decrease in porosity. Mechanical testing of the sintered samples corroborated the structural changes at different temperatures, demonstrating that the surface dynamic motion of atoms inherent in low-temperature sintering mechanisms significantly affects the mechanical properties of nanomaterials. These findings have important implications for developing high-performance materials that align with the evolving requirements of modern electronic devices.
A Method of Selecting Automated Driving Service Sections Considering Spatial Influence Factors
Authors: Kim Tagyoung , Kang Kyeong-pyo
Published: January 2025

Currently, the level of automated driving technology is level 3 service in Korea, and the level 4 service has been launched overseas and is reaching the stage of commercialization. For commercialization, it is necessary not only to stabilize automated driving technology but also to prepare for service applications. To apply and expand automated driving services, it is most urgent to secure the safety of automated driving technology, and it is necessary to prepare for efficient procedures and methods suitable for automated driving services. In this study, considering the two aspects of AV manufacturer and service provider, the spatial factors affecting the safety of ADS are estimated using disengagement information in the level 3 service field data in Korea, and the method is proposed to select the automated driving service sections using spatial information analysis. To validate the method, the matching rate is compared and analyzed by applying it to the other testbed, which is currently being prepared for the level 4 car sharing service. According to validation results, it judged that the proposed method could be used to select the automated driving service section efficiently in the planning stage before deploying AVs and providing services.
Ambient Backscatter- and Simultaneous Wireless Information and Power Transfer-Enabled Switch for Indoor Internet of Things Systems
Authors: Sooriarachchi Vishalya P. , Perera Tharindu D. Ponnimbaduge , Jayakody Dushantha Nalin K.
Published: January 2025

Indoor Internet of Things (IoT) is considered as a crucial component of Industry 4.0, enabling devices and machine to communicate and share sensed data leading to increased efficiency, productivity, and automation. Increased energy efficiency is a significant focus within Industry 4.0, as it offers numerous benefits. To support this focus, we developed a hybrid switching mechanism to switch between energy harvesting techniques, ambient backscattering and Simultaneous Wireless Information and Power Transfer (SWIPT), which can be utilized within cooperative communications. To implement the proposed switching mechanism, we consider an indoor warehouse environment, where the moving sensor node transmits sensed data to the fixed relay located on the roof, which is then transmitted to an IoT gateway. The relay is equipped with the proposed switch to energize its communication capabilities while maintaining the expected quality of service at the IoT gateway. Simulation results illustrate the improved energy efficiency within the indoor communication setup while maintaining QoS at varying signal-to-noise (SNR) conditions.
Multi-Level Feature Dynamic Fusion Neural Radiance Fields for Audio-Driven Talking Head Generation
Authors: Song Wenchao , Liu Qiong , Liu Yanchao , Zhang Pengzhou , Cao Juan
Published: January 2025

Audio-driven cross-modal talking head generation has experienced significant advancement in the last several years, and it aims to generate a talking head video that corresponds to a given audio sequence. Out of these approaches, the NeRF-based method can generate videos featuring a specific person with more natural motion compared to the one-shot methods. However, previous approaches failed to distinguish the importance of different regions, resulting in the loss of information-rich region features. To alleviate the problem and improve video quality, we propose MLDF-NeRF, an end-to-end method for talking head generation, which can achieve better vector representation through multi-level feature dynamic fusion. Specifically, we designed two modules in MLDF-NeRF to enhance the cross-modal mapping ability between audio and different facial regions. We initially developed a multi-level tri-plane hash representation that uses three sets of tri-plane hash networks with varying resolutions of limitation to capture the dynamic information of the face more accurately. Then, we introduce the idea of multi-head attention and design an efficient audio-visual fusion module that explicitly fuses audio features with image features from different planes, thereby improving the mapping between audio features and spatial information. Meanwhile, the design helps to minimize interference from facial areas unrelated to audio, thereby improving the overall quality of the representation. The quantitative and qualitative results indicate that our proposed method can effectively generate talk heads with natural actions and realistic details. Compared with previous methods, it performs better in terms of image quality, lip sync, and other aspects.
Multi-Criteria Decision Analysis in Drug Discovery
Authors: Bachorz Rafał A. , Lawless Michael S. , Miller David W. , Jones Jeremy O.
Published: January 2025

Drug discovery is inherently a multi-criteria optimization problem. In the first instance, it involves a tremendously large chemical space, where each compound can be characterized by multiple molecular and biological properties. Modern computational approaches try to efficiently explore the chemical space in search of molecules with the desired combination of properties. For example, Pareto optimizers identify a so-called “Pareto front”, a set of non-dominated solutions. From a qualitative perspective, all solutions on the front are potentially equally desirable, each expressing a trade-off between the goals. However, often there is a need to weight the objectives differently, depending on their perceived importance. To address this, we recently implemented a new Multi-Criteria Decision Analysis (MCDA) method as part of the AI-powered Drug Design (AIDDTM) technology initiative. This allows the user to weight various objective functions differently, which, in turn, efficiently directs the generative chemistry process toward the desired areas in chemical space.
Rainfall and PM Removal on Tree Leaves: A Study of Santiago, Chile’s Native Species
Authors: Préndez Margarita , Corada Karina , Navarrete Ignacio , Vera Javier , Wyss Zilera
Published: January 2025

Green infrastructure, such as street trees, can help improve air quality, but the role of rainfall in cleaning total particulate matter (TPM) from tree leaves is not well understood, especially in cities like Santiago, Chile. This study measured TPM deposited on leaves and its elemental composition of two native tree species, Quillaja saponaria and Schinus molle, by five independent rainfall episodes. The results showed significant differences in how each tree species responded to rainfall. The total amount of TPM finally removed or retained at the leaf level in the five rainfall events studied was 4.72 and 8.43 mg/gldw for Q. saponaria and S. molle, respectively. Q. saponaria decreased TPM levels after rainfall, while S. molle exhibited mixed responses, increasing or decreasing TPM accumulation on leaves after different intensities of rainfalls. Elemental analysis revealed metals such as lithium and nickel—potentially linked to electric vehicle batteries—and tin and antimony–potentially linked to industrial processes. Rainfall benefited air quality by removing heavy metals from the atmosphere and aiding plant recovery from TPM accumulation. However, further research is needed on metal speciation in TPM and its foliar uptake by plants. This study provides some insights into the complex interactions between trees leaves, TPM deposition, and rainfall.
Cantelli’s Bounds for Generalized Tail Inequalities
Authors: Apollonio Nicola
Published: January 2025

Let X be a centered random vector in a finite-dimensional real inner product space E. For a subset C of the ambient vector space V of E and x,y∈V, write x⪯Cy if y−x∈C. If C is a closed convex cone in E, then ⪯C is a preorder on V, whereas if C is a proper cone in E, then ⪯C is actually a partial order on V. In this paper, we give sharp Cantelli-type inequalities for generalized tail probabilities such as PrX⪰Cb for b∈V. These inequalities are obtained by “scalarizing” X⪰Cb via cone duality and then by minimizing the classical univariate Cantelli’s bound over the scalarized inequalities. Three diverse applications to random matrices, tails of linear images of random vectors, and network homophily are also given.
Isolation of Actinobacteria from Date Palm Rhizosphere with Enzymatic, Antimicrobial, Antioxidant, and Protein Denaturation Inhibitory Activities
Authors: Smati Maria , Bramki Amina , Makhlouf Fatima Zohra , Djebaili Rihab , Farda Beatrice , Abdelhadi Fatima Zohra , Abdelli Nahla , Kitouni Mahmoud , Pellegrini Marika
Published: January 2025

Arid ecosystems constitute a promising source of actinobacteria producing new bioactive molecules. This study aimed to explore different biological activities of actinomycetes isolated from the rhizosphere of Phoenix dactylifera L. in the Ghardaia region, Algeria. A total of 18 actinobacteria were isolated and studied for their enzymatic and antimicrobial activities. All isolates shared cellulase and catalase activity; most of them produced amylase (94%), esterase (84%), lecithinase and lipoproteins (78%), caseinase (94%), and gelatinase (72%). The isolates could coagulate (56%) or peptonize (28%) skim milk. Overall, 72% of the isolates exhibited significant antibacterial activity against at least one test bacteria, while 56% demonstrated antifungal activity against at least one test fungi. Based on enzyme production and antimicrobial activity, isolate SGI16 was selected for secondary metabolite extraction by ethyl acetate. The crude extract of SGI16 was analyzed using DPPH and BSA denaturation inhibition tests, revealing significant antioxidant power (IC50 = 7.24 ± 0.21 μg mL−1) and protein denaturation inhibitory capacity (IC50 = 492.41 ± 0.47 μg mL−1). Molecular identification based on 16S rDNA analysis showed that SGI16 belonged to the genus Streptomyces. The findings highlight that date palms’ rhizosphere actinobacteria are a valuable source of biomolecules of biotechnological interest.
Unraveling the Genetic Heartbeat: Decoding Cardiac Involvement in Duchenne Muscular Dystrophy
Authors: Novelli Valeria , Canonico Francesco , Laborante Renzo , Manzoni Martina , Arcudi Alessandra , Pompilio Giulio , Mercuri Eugenio , Patti Giuseppe , D’Amario Domenico
Published: January 2025

Cardiomyopathy represents the most important life-limiting condition of Duchenne muscular dystrophy (DMD) patients after the age of 20. Genetic alterations in the DMD gene result in the absence of functional dystrophin protein, leading to skeletal/cardiac muscle impairment. The DMD incidence is one in 5000 live male births. Identifying the genetic background, in addition to DMD disease-causing variants, is one of the unmet needs in understanding the cardiac disease’s pathogenetic mechanisms and its prognostic implications. The clinical scenario is made even more intricate by the difficulty in predicting the onset and progression of cardiomyopathy, as no clear genotype/phenotype correspondence has been found thus far. The evaluation of genes involved in the onset of primary cardiomyopathies could explore the hypothesis that changes in cytoskeletal and sarcomeric protein function are the modulators of ventricular dysfunction in DMD patients. In the last decade, with the advent of next-generation sequencing (NGS) technology, many disease-causing genes and modifiers have been identified. Assessing the genetic origin of the phenotypic variability of the disease in both the onset and progression of cardiomyopathy in DMD would be extremely helpful in managing these patients. This review article aims to spotlight the genetic background associated with Cardiomyopathy in DMD patients toward a more predictive personalized model of care.
MicroRNAs Expression Profile in MN1-Altered Astroblastoma
Authors: Gianno Francesca , Miele Evelina , Sabato Claudia , Ferretti Elisabetta , Minasi Simone , Buttarelli Francesca Romana , Salerno Debora , Pediconi Natalia , Pascucci Giuseppe Rubens , Guerrieri Francesca , Ciolfi Andrea , Pizzi Simone , Massimino Maura , Biassoni Veronica , Schiavello Elisabetta , Gessi Marco , Asioli Sofia , Mastronuzzi Angela , d’Amati Antonio , Catanzaro Giuseppina , Viscardi Elisabetta , Capper David , Giangaspero Felice , Antonelli Manila
Published: January 2025

Background/Objectives: Astroblastoma is a rare glial neoplasm more frequent in young female patients, with unclear clinical behaviors and outcomes. The diagnostic molecular alteration is a rearrangement of the Meningioma 1 (MN1) gene. MicroRNAs (miRNAs) are important gene expression regulators with strong implications in biological processes. Here, we investigated microRNA expression, regulation, and biological processes correlated to target genes of deregulated miRNAs in MN1-altered astroblastoma. Methods: A cohort of 14 tumor samples, histologically classified as astroblastoma, was retrospectively collected and analyzed through their DNA methylation profiles. MiRNA expression profiles were then detected on MN1-altered astroblastomas (n = 8) and normal brain controls (n = 2) by Nanostring technology and validated by RT-qPCR; then, the expression of deregulated miRNAs was correlated with clinical-pathological characteristics. Subsequently, the methylation status of promoters of deregulated miRNAs was investigated through a methylation profiling microarray. Finally, bioinformatics analysis was conducted to explore the biological processes (BPs) and target genes of differentially expressed miRNAs. Results: Eight MN-altered astroblastoma were identified. Thirty-nine miRNAs were deregulated in tumor samples compared to normal brain tissue. Downregulated microRNAs exhibited an association with an increased risk of recurrence. The promoter methylation status was investigated in 32/39 miRNAs: 14/32 were epigenetically deregulated. None of them were genetically regulated. Conclusions: MN1-altered astroblastomas have an miRNA expression signature that identifies specific BPs and pathways. Our findings suggested that the involved pathways could be associated with clinical and pathological characteristics of MN1-altered astroblastomas. Also, the biology of this rare tumor could have potential implications on prognostic markers and therapy.
Evaluation of Sericin/Polyvinyl Alcohol Mixtures for Developing Porous and Stable Structures
Authors: Arango Maria C. , Vásquez Vásquez Leander , Parra Akemy Carolina Homma , Rueda-Mira Santiago , Jaramillo-Quiceno Natalia , Cerisuelo Josep Pasqual , Cháfer Amparo , Álvarez-López Catalina
Published: January 2025

Fibrous by-products, including defective or double cocoons, are obtained during silk processing. These cocoons primarily contain fibroin and sericin (SS) proteins along with minor amounts of wax and mineral salts. In conventional textile processes, SS is removed in the production of smooth, lustrous silk threads, and is typically discarded. However, SS has garnered attention for its antioxidant, antibacterial, biocompatible, and anticancer properties as well as its excellent moisture absorption, making it a promising polymer for biomedical applications. Owing to its functional groups (carboxyl, amino, and hydroxyl), SS can blend and crosslink with other polymers, thereby improving the mechanical properties of sericin-based materials. This study explored the effects of different SS/polyvinyl alcohol (PVA) ratios on porous scaffolds fabricated via freeze-drying, focusing on the mechanical stability, water absorption, and protein release in phosphate-buffered saline (PBS). The scaffold morphology revealed reduced porosity with higher SS content, while increased PVA content led to material folding and layering. A greater PVA content enhanced water absorption, mechanical properties, and thermal stability, although SS release decreased. These results demonstrate that scaffold properties can be tailored by optimizing the SS/PVA ratio to suit specific biomedical applications.
Neuroscience Literacy and Academic Outcomes: Insights from a University Student Population
Authors: Almarzouki Abeer F. , Alqahtani Arzan I. , Baessa Jumana K. , Badaood Dhuha K. , Nujoom Rwdyn R. , Malibari Raneem W. , Aljared Elaf M. , Alghamdi Reema S.
Published: January 2025

Background/Objectives: There is growing interest in neuroscience-informed education, as well as neuroscience-derived strategies that maximise learning. Studies on neuroscience literacy and neuromyths, i.e., understandings or misconceptions about the brain, have primarily focused on their prevalence in educators, and few studies have examined their impact on students’ study habits or academic performance. Methods: To address this gap, we surveyed 576 university students in different academic programmes to investigate the relationship between neuromyths and academic outcomes in university students. In this quantitative, cross-sectional study design, we used a validated neuroscience knowledge survey and the Revised Two-factor Study Process (R-SPQ-2F) Questionnaire. We also inquired about students’ interest in, exposure to, and awareness of neuroscience, as well as their academic grades. Results: Students showed significant awareness of and interest in neuroscience; this was highest among students in health science programmes and lowest among students in computer and engineering programmes. The most common sources of general neuroscience knowledge were internet articles. Higher neuroscience literacy was associated with higher interest in neuroscience and having taken more neuroscience courses. Neuromyth scores were also better among those with higher neuroscience literacy scores. Higher neuroscience literacy scores were significantly associated with higher grades, higher surface strategy scores, and lower surface motive study habits. Conclusions: Our study sheds light on the variations in foundational neuroscience literacy among students in different academic programmes. It also provides insight into how this foundation affects academic performance and study habits. This insight may help guide educational policymakers to adopt neuroscience-based strategies that may be beneficial for learning.
Exploring Employee Perspectives on Workplace Technology: Usage, Roles, and Implications for Satisfaction and Performance
Authors: Barbu Andreea , Ichimov Mirona Ana Maria , Costea-Marcu Iustina Cristina , Militaru Gheorghe , Deselnicu Dana Corina , Moiceanu Georgiana
Published: January 2025

In a dynamic context, where market requirements and needs change often, it is important for companies to adapt to new demands as quickly as possible to continue to be successful. To be able to face numerous challenges, however, organizations need to focus on the needs of their employees, with their satisfaction being an intermediate objective in achieving performance. Since technology is a pillar of each business field, the aim of this study is to explore employees’ perspectives on the use of technology at work, analyzing its main roles within the company, the benefits it provides from the employees’ viewpoint and its implications for satisfaction and performance. To achieve this objective, the authors used existing results in the literature that indicated several methods for the analysis of this subject, and continued with qualitative focus group research that involved six employees working both in hybrid and remote setups, within companies providing services in the engineering area. Thus, in this qualitative study, the needs and preferences of engineering employees are analyzed towards the efficiency of work activities, the improvement of team collaboration, as well as the role of digital technologies in facilitating communication and collecting feedback. Also, the research results address the support of personal and professional development and emphasize the importance of balance between personal and professional life through workplace flexibility—an aspect relatively unexplored in the specialized literature. Apart from the theoretical contributions that the study offers for the development of the literature, the results of this research offer a practical perspective for companies in the field of engineering, suggesting future research directions and recommendations for optimizing performance and increasing the level of employee satisfaction through the implementation of appropriate and personalized digital solutions.
Preventive Conservation of Vernacular Adobe Architecture at Seismic Risk: The Case Study of a World Heritage Historical City
Authors: Haji Sadeghi Neda , Azizi-Bondarabadi Hamed , Correia Mariana
Published: January 2025

Heritage is strengthened through proactive actions, known as preventive conservation, that are considered before earthquakes, rather than reactive actions addressed when the emergency situation occurs. Considering that there are several regions around the world with very active seismicity, conservation interventions should guarantee human safety and the improvement of the inhabitant’s living conditions while keeping alive the earthen fabric and adobe buildings, thus preserving the lives of the residents but also preserving cultural heritage in the face of earthquakes. The main aim of this paper is to define a comprehensive conservation procedure addressing the preventive conservation of vernacular adobe vaulted houses in Yazd, an Iranian World Heritage property, since 2017. The fundamental phases of this procedure, which this paper’s structure is based on, include introducing the case study and addressing the conservation objectives, the assessment of significance and value, the seismic criteria, the conservation strategies, seismic safety assessment, and decision-making on interventions. The comprehensive preventive conservation procedure presented in this paper was determined by relevant conservation criteria, which contributed to an adequate seismic-retrofitted intervention design. This conservation approach requires evaluation of the seismic performance and the buildings’ safety, through which the decision regarding intervention could be made. Accordingly, this research also dealt with the seismic safety assessment of an adobe building through numerical research work performed using the software HiStrA Ver.2022.1.6. Based on the numerical results, decisions on the need and on the extent of intervention techniques were addressed. In addition, a comparative study was performed on different seismic strengthening techniques available in the literature to define fundamental conservation criteria. In this way, there are more chances for human lives to be preserved if an earthquake occurs.
Effects of Post-Fire Rehydration on the Mechanical Properties of Slag-Modified Concrete
Authors: Teixeira Guilherme Palla , Ribeiro José Carlos Lopes , Pedroti Leonardo Gonçalves , Nalon Gustavo Henrique
Published: January 2025

Although previous research has examined the mechanical properties of concrete exposed to high temperatures, further investigation is needed into the effects of post-fire curing on the recovery of strength and stiffness of sustainable concretes produced with slag-modified cement. This study conducted an experimental analysis of the residual compressive strength and modulus of elasticity of different types of concrete (20 MPa or 30 MPa) exposed to varying maximum temperature levels (200 °C, 400 °C, 600 °C, 800 °C) and post-fire treatments (with or without rehydration). The concrete specimens were produced using Portland cement CP II-E-32. The rehydration method involved one day of water curing, followed by 14 days of air curing. Statistical analyses revealed potential improvements in the mechanical properties of concretes produced with slag-modified cement due to rehydration processes after exposure to different temperatures levels. The highest values of the relative residual strength factor (Φc) were observed in specimens exposed to a maximum temperature of 600 °C, ranging from 0.862 to 0.905. The highest values of the relative residual elastic modulus factor (ψc) were verified for a maximum temperature of 200 °C, ranging from 0.720 to 0.778. The experimental results were compared with strength and stiffness predictions of design codes. The inclusion of slag in concrete reduced microcracking during the rehydration process due to the reduced amount of calcium hydroxide in the cementitious matrix, increasing the concrete’s relative residual strength and stiffness after post-fire curing.
Review of Prediction Models for Chloride Ion Concentration in Concrete Structures
Authors: Ma Jiwei , Yang Qiuwei , Wang Xinhao , Peng Xi , Qin Fengjiang
Published: January 2025

Chloride ion concentration significantly impacts the durability of reinforced concrete, particularly regarding corrosion. Accurately assessing how this concentration varies with the age of structures is crucial for ensuring their safety and longevity. Recently, several predictive models have emerged to analyze chloride ion concentration over time, classified into empirical models and machine learning models based on their data processing techniques. Empirical models directly relate chloride ion concentration to the age of concrete through specific functions. Their primary advantage lies in their low data requirements, making them convenient for engineering use. However, these models often fail to account for multiple influencing factors, which can limit their accuracy. Conversely, machine learning models can handle various factors simultaneously, providing a more detailed understanding of how chloride concentration evolves. When adequately trained with sufficient experimental data, these models generally offer superior prediction accuracy compared to mathematical models. The downside is that they necessitate a larger dataset for training, which can complicate their practical application. Future research could focus on combining machine learning and empirical models, leveraging their respective strengths to achieve a more precise evaluation of chloride ion concentration in relation to structural age.
Exploring the Role of Symptom Diversity in Facial Basal Cell Carcinoma: Key Insights into Preoperative Quality of Life and Disease Progression
Authors: Stundys Domantas , Kučinskaitė Alvija , Gervickaitė Simona , Grigaitienė Jūratė , Tutkuvienė Janina , Jančorienė Ligita
Published: January 2025

Facial basal cell carcinoma (BCC) is the most common skin cancer, yet delays in diagnosis and treatment persist. These delays affect quality of life (QoL), advance disease progression, and increase healthcare burden. This study explores the relationship between symptom diversity, QoL, and care-seeking behaviors, focusing on the impact of symptoms on clinical outcomes and consultation timing. A total of 278 adults with histologically confirmed facial BCC underwent surgical treatment at Vilnius University Hospital from November 2022 to April 2024. The data collected included demographics, tumor characteristics, and self-reported symptoms (pain, bleeding, itching, tumor presence, discomfort, and erosion). Disease-specific QoL was assessed using the Skin Cancer Index. ANCOVA compared QoL across symptom groups, multiple regression analyzed symptom effects on QoL, and logistic regression evaluated care-seeking behavior over time. Cox regression assessed symptom associations with time to medical consultation. The mean time from symptom onset to consultation was 21 months. Tumor presence (27%), erosion (18%), and discomfort (17%) were the most reported symptoms. Discomfort significantly reduced QoL in emotional, social, and appearance domains (p < 0.05). Logistic regression showed tumor presence and pain were associated with earlier care-seeking within 12 months (p < 0.05). Other symptoms, such as bleeding, itching, and erosion, did not significantly influence consultation timing. The findings highlight the need for public education and proactive patient counseling to promote timely intervention and reduce the disease progression.
Maxillectomy Guided by 3D Printing Versus Conventional Surgery for Patients with Head and Neck Cancer
Authors: Park Sung Yool , Jung Sung Ha , Seo Anna , Noh Hakjong , Lee Hwansun , Kim Hyo Jun , Kim Younghac , Chung Man Ki , Jeong Han-Sin , Baek Chung-Hwan , Son Young-Ik , Choi Nayeon
Published: January 2025

Background: This study evaluates the impact of three-dimensional (3D) printing-guided maxillectomy compared with conventional maxillectomy on surgical precision and oncological outcomes in patients with head and neck cancer. Materials and Methods: A retrospective analysis was conducted on 42 patients undergoing maxillectomy (16 in a 3D printing-guided group and 26 in a conventional group). Patient demographics, tumor characteristics, and outcomes were compared. Survival outcomes were analyzed using the Kaplan–Meier method. Results: The 3D printing group showed higher rates of negative resection margins (81.3% vs. 76.9%) compared with the conventional group and a trend toward improved 5-year local recurrence-free survival (87.5% vs. 58.7%, respectively) and overall survival (84.4% vs. 70.1%, respectively). However, the differences were not statistically significant. Conclusions: Maxillectomy guided by 3D printing may offer enhanced surgical precision and improved local control in patients undergoing head and neck cancer surgeries. Further research with larger cohorts is necessary to confirm these findings.