bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Long-Term Skid Resistance of Asphalt Pavement
Authors: Chen Yuanfeng , Li Zhitang , Wang Yuankuo , Liang Guoxi , Yang Xiaolong
Published: February 2025

This study aims to gain an in-depth understanding of the research trends in the field of the long-term skid resistance (L-TSR) of asphalt pavement (AP). In this paper, the detection method, decay model, influence factors, and prediction model of the L-TSR of AP are summarized. This paper quantitatively analyzes the skid resistance mechanism of the pavement and elucidates the existing problems and future development directions of the L-TSR of AP. The research indicates that digital image methods and intelligent sensor detection methods are important methods for the skid resistance detection of AP in the future. The indoor test can provide detailed data of material properties and can effectively evaluate the performance of anti-sliding materials under different environmental conditions by simulating the actual road conditions. A quantitative analysis of the skid mechanism of AP can better reflect the actual contact characteristics of the pavement. The combined prediction model combining multiple single models can not only correct the shortcomings of a single model but also greatly improve the calculation accuracy. At present, the research on the L-TSR of AP is insufficient in the aspects of the tire–pavement interaction mechanism, evaluation index, decay model, and combined prediction model, which needs to be further studied from quantitative, time-varying, unified, and innovative aspects.
Chemical Composition, Antibacterial Activity, and Food Application of Sprouts from Fabaceae and Brassicaceae Species
Authors: (Neagu) Dragomir Christine , Misca Corina Dana , Dossa Sylvestre , Jianu Călin , Radulov Isidora , Negrea Monica , Paven Loredana , Alexa Ersilia
Published: February 2025

The aim of this paper is to evaluate, from a chemical and antibacterial point of view, sprouts from species of Fabaceae and Brassicaceae families, to establish a correlation between analyzed parameters and to test the possibility of using these functional compounds in the flour food industry. The material used was lentil sprouts (LS), pea sprouts (PS), bean sprouts (BS), and radish sprouts (RS), which were chemically analyzed by determining the content of total and individual polyphenols and macro- and microelements. The antimicrobial potential of the sprout extracts obtained was tested using the disk diffusion method on five bacterial strains: Escherichia coli, Proteus mirabilis, Klebsiella pneumoniae, Enterococcus faecalis, and Staphylococcus aureus. In order to capitalize on the flour food industry, the sprouts were introduced in the recipes for the manufacture of some cookies, and sensory analysis was performed. The results obtained indicated that LS are the sprouts with the highest content of TPC (524.130 mg/100 g) and highest content for Ni, Cu, Zn, Fe, Mn, and Mg, while the highest values for Ca were recorded in the case of PS (256.575 ± 2.23 mg/kg), and for K in the case of the BS sample (4819.450 ± 1.1 mg/kg). The RS extract has been shown to be effective against E. faecalis (MIC-70 µL/mL), S. aureus (MIC 50 µL/mL), and PS against S. aureus (MIC 70 µL/mL). Regarding the sensory analysis of cookies, the panelists participating in the study preferred products based on BS and PS in a percentage of 2.5%.
A Multiscale Mixed-Graph Neural Network Based on Kinematic and Dynamic Joint Features for Human Motion Prediction
Authors: Zhao Rongyong , Wei Bingyu , Han Lingchen , Cai Yuxin , Ma Yunlong , Li Cuiling
Published: February 2025

Predicting human future motion holds significant importance in the domains of autonomous driving and public safety. Kinematic features, including joint coordinates and velocity, are commonly employed in skeleton-based human motion prediction. Nevertheless, most existing approaches neglect the critical role of dynamic information and tend to degrade as the prediction length increases. To address the related constraints due to single-scale and fixed-joint topological relationships, this study proposes a novel method that incorporates joint torques estimated via Lagrangian equations as dynamic features of the human body. Specifically, the human skeleton is modeled as a multi-rigid body system, with generalized joint torques calculated based on the Lagrangian formula. Furthermore, to extract both kinematic and dynamic joint information effectively for predicting long-term human motion, we propose a Multiscale Mixed-Graph Neural Network (MS-MGNN). MS-MGNN can extract kinematic and dynamic joint features across three distinct scales: joints, limbs, and body parts. The extraction of joint features at each scale is facilitated by a single-scale mixed-graph convolution module. And to effectively integrate the extracted kinematic and dynamic features, a KD-fused Graph-GRU (Kinematic and Dynamics Fused Graph Gate Recurrent Unit) predictor is designed to fuse them. Finally, the proposed method exhibits superior motion prediction capabilities across multiple motions. In motion prediction experiments on the Human3.6 dataset, it outperforms existing approaches by decreasing the average prediction error by 9.1%, 12.2%, and 10.9% at 160 ms, 320 ms, and 400 ms for short-term prediction and 7.1% at 560 ms for long-term prediction.
Does Mental Imagery Influence Muscles Activity? A Proof of Concept Study on Franklin Method® Effectiveness in Dance Training
Authors: Gorwa Joanna , Fryzowicz Anna
Published: February 2025

Mental imagery influences the body, movement, and technical skills of the dancer. The aim of this study was to identify the influence of dance imagery on the electromyographic parameters of selected muscles in a professional ballet dancer during three ballet tasks: parallel position, demi pointe relevé, and demi plié. Five mental imageries according to the Franklin Method® were used: foot dome, the wheelbarrow, pushing the toes, space behind the kneecap, and the kneecap float. Electromyographic signals were recorded bilaterally for lumbar erector spinae, rectus abdominis, vastus medialis, long head of biceps femoris, lateral head of gastrocnemius, tibialis anterior, and fibularis longus. All of the mental imageries resulted in increased activity (above 20% compared with no-imagery performance) of the selected muscles in the studied classical dance positions and tasks. Overall, the ankle muscles were influenced the most. This study indicates that mental images effectively influence a physiological parameter, as indicated by an electromyographic signal.
Shifting Paradigms in Spinal Infection Management: The Rising Role of Spine Endoscopy—A Systematic Review and Case Series Analysis
Authors: Łątka Kajetan , Kołodziej Waldemar , Domisiewicz Kacper , Pawuś Dawid , Klepinowski Tomasz , Tanaka Masato , Łabuz-Roszak Beata , Łątka Dariusz
Published: February 2025

The management of spinal infections, such as spondylodiscitis, remains a complex challenge. With advancements in technology, spinal endoscopy has emerged as a promising minimally invasive approach. This systematic review and case series aims to evaluate the efficacy of endoscopic techniques in treating primary and post-operative spinal infections. A comprehensive literature review was conducted using databases such as PubMed, MEDLINE, and Cochrane Library, focusing on studies from 2000 to 2023. Our case series included patients treated with endoscopy for spinal infections in our institution between 2020 and 2023. The findings suggest that endoscopic techniques are associated with reduced tissue trauma, shorter hospital stays, and faster recovery, while maintaining comparable clinical outcomes to traditional open surgery. Despite the relatively high pathogen identification rates and favorable clinical outcomes, complications such as residual infection and the need for re-operations were noted. These results emphasize the need for further research to optimize endoscopic procedures in spinal infection management, potentially paving the way for this technique to become a standard treatment option.
Event-Triggered MFAILC Bipartite Formation Control for Multi-Agent Systems Under DoS Attacks
Authors: Li Han , Fu Lixia , Wu Wenchao
Published: February 2025

For multi-input multi-output (MIMO) nonlinear discrete-time bipartite formation multiagent systems (BFMASs) performing trajectory tracking tasks with unknown dynamics, a dynamic event-triggered model-free adaptive iterative learning control (DET-MFAILC) algorithm is proposed to address periodic denial-of-service (DoS) attacks. First, using the pseudo-partial derivative, a compact format dynamic linearization (CFDL) method is employed to construct an equivalent CFDL data model for the MIMO multi-agent system. A DoS attack model and its corresponding compensation algorithm are developed, while a dynamic event-triggered condition is designed considering both the consensus error and the tracking error. Subsequently, the proposed DoS attack compensation algorithm and the dynamic event-triggered mechanism are integrated with the model-free adaptive iterative learning control algorithm to design a controller, which is further extended from fixed-topology systems to time-varying topology systems. The convergence of the control system is rigorously proven. Finally, simulation experiments are conducted on bipartite formation multi-agent systems (BFMASs) under fixed and time-varying communication topologies. The results demonstrate that the proposed algorithm effectively mitigates the impact of DoS attacks, reduces controller updates, conserves network resources, and ensures that both the tracking error and consensus error converge to an ideal range close to zero within a finite number of iterations while maintaining a good formation shape.
Teenagers and Young Adults with Cochlear Implants: A Multidisciplinary Follow-Up Study Approach and Baseline Characteristics
Authors: Löfkvist Ulrika , Dahlby-Skoog Malin , Persson Anna , Asp Filip , Verrecchia Luca , Gripenberg Susanne , Karpeta Niki , Eklöf Martin , Karltorp Eva
Published: February 2025

Background/Objectives: Early pediatric cochlear implantation positively impacts early language outcomes. The Teenager and Young Adults Cochlear Implant (TAYACI) study investigates the long-term outcomes of early implantation and factors influencing variability among cochlear implant (CI) users. This article outlines participants’ background, early language outcomes, and multidisciplinary study protocol. Methods and Materials: Individuals aged 12–22 received CIs before 30 months of age, followed-up at the same hearing implant center, and adhered to a standard school curriculum were invited to participate. Out of 109 eligible CI users, 50 participated; 46 agreed to undergo clinical assessments, while four completed questionnaires only. Results: The mean age at the first CI was 15.63 months (SD = 6.0). All but one communicated with spoken language(s). Participants attended mainstream schools and had highly educated parents. Over half (56%) had received Auditory Verbal Therapy in early childhood. Earlier implantation correlated with better language understanding one year post-CI. Conclusions: Earlier implantation was associated with better early language outcomes, with parental education level and early family-centered intervention likely contributing. Future sub-studies will investigate multidisciplinary long-term effects of pediatric cochlear implantation in adolescents.
Optimization of Size and Operation of Stand-Alone Renewable-Based Systems with Diesel and Hybrid Pumped Hydro Storage–Battery Storage Considering Uncertainties
Authors: Dufo-López Rodolfo , Lujano-Rojas Juan M.
Published: February 2025

Currently, the electrical supply in stand-alone systems is usually composed of renewable sources with fossil-fuel generators and battery storage. This study shows a novel model for the metaheuristic–stochastic optimization (minimization of the net present cost, and NPC) of sizing and energy management for stand-alone photovoltaic (PV)–wind–diesel systems with hybrid pumped hydro storage (PHS)–battery storage systems. The model is implemented in C++ programming language. To optimize operations—thus reducing PHS losses and increasing battery lifetimes—optimal energy management can optimize the power limits of using the PHS or battery to supply or store energy. The probabilistic approach considers the variability of wind speed, irradiation, temperature, load, and diesel fuel price inflation. The variable efficiencies of the components and losses and advanced models for battery degradation are considered. This methodology was applied to Graciosa Island (Portugal), showing that, compared with the current system, the optimal system (with a much higher renewable power and a hybrid PHS–battery storage) can reduce the NPC by half, reduce life cycle emissions to 14%, expand renewable penetration to 96%, and reduce the reserve capacity shortage to zero.
Review on Advancements in Carbon Nanotubes: Synthesis, Purification, and Multifaceted Applications
Authors: Madikere Raghunatha Reddy Anil Kumar , Darwiche Ali , Reddy Mogalahalli Venkatashamy , Zaghib Karim
Published: February 2025

Since their discovery over two decades ago, carbon nanotubes (CNTs) have captivated researchers due to their exceptional electrical, optical, mechanical, and thermal properties, making them versatile candidates for various advanced applications. CNTs have transformed numerous scientific domains, including nanotechnology, electronics, materials science, and biomedical engineering. Their applications range from nanoelectronics, robust nanocomposites, and energy storage devices to innovative materials, sensors, conducting polymers, field emission sources, and Li-ion batteries. Furthermore, CNTs have found critical roles in biosensing, water purification, bone scaffolding, and targeted gene and drug delivery. The chemical reactivity and functional versatility of CNTs are profoundly influenced by their structural and physicochemical properties, such as surface area, surface charge, size distribution, surface chemistry, and purity. This review comprehensively explores the current state of CNT research, focusing on widely used synthesis, purification, and characterization techniques alongside emerging applications. By highlighting recent advancements and addressing unresolved challenges, it aims to present a novel perspective on the transformative potential of CNTs, fostering innovation across diverse scientific and technological fields.
Comparative Analysis of Synthesis Routes and Aluminum Doping Effects on Nickel-Manganese-Cobalt Type Cathode Material
Authors: Chen Yu-Sheng , Tchernychova Elena , Hočevar Samo , Dominko Robert , Wieczorek Władysław
Published: February 2025

This study presents a comprehensive analysis of the synthesis techniques and the effects of aluminum doping on nickel-manganese-cobalt (NMC) 811 cathode materials. Our research focuses on the comparison of two different synthesis methods. Hydroxide co-precipitation is followed by solid-state calcination for polycrystalline (PC) cathodes and molten salt calcination for single-crystalline (SC) cathodes. In addition, the study systematically integrates aluminum dopants at different stages of these processes. This study aims to examine how various doping methods affect the structural characteristics, morphological features, and electrochemical performance of NMC cathodes.This investigation employs a thorough characterization approach, utilizing techniques such as X-ray diffraction (XRD), various microscopy methods, and galvanostatic cycling tests, our results illustrate the complexity of the synthesis parameters that influence the capacity retention and performance of the samples produced.
Lab-Scale X-Ray Exposure Has No Measurable Impact on Lithium-Ion Battery Performance and Lifetime
Authors: Min Jinhong , Condon Amariah , Attia Peter M.
Published: February 2025

X-ray characterization is broadly used in battery research, development, manufacturing, and quality control. However, the impact of lab-scale X-ray exposure on battery performance and lifetime is not well understood. In this work, we evaluate the impact of lab-scale X-rays on battery performance and lifetime. We tested groups of cylindrical 18,650 cells using 2 min and 60 min X-ray imaging conditions; the performance and lifetime of these cells were identical to a control group without X-ray exposure. These results suggest that lab-scale X-ray characterization is safe for lithium-ion batteries.
Integrated Omics Approaches to Explore a New System of Genetic Control of Dibenzothiophene Desulfurization and Aromatic Ring Cleavage by Gordonia alkanivorans Strain 135
Authors: Frantsuzova Ekaterina , Bogun Alexander , Vetrova Anna , Kazakova Elizaveta , Kusainova Tomiris , Tarasova Irina , Pozdnyakova-Filatova Irina , Delegan Yanina
Published: February 2025

Dibenzothiophene (DBT) is a widespread environmental pollutant. The most common metabolic pathway for DBT degradation by Gordonia strains is the 4S pathway, which is under the control of the dsz operon. The ability to utilize DBT as the sole source of sulfur in Gordonia alkanivorans strain 135 has been revealed. The dsz operon was not detected in the genome of strain 135. In this work, using genomic, transcriptomic, and proteomic data of strain 135, it was shown that an alternative pathway of DBT transformation is possible in non-dsz Gordonia; the sfnB and tauD genes and two acyl-dehydrogenase genes are significantly involved in the desulfurization process.
TRPC6-Mediated Zn2+ Influx Negatively Regulates Contractile Differentiation of Vascular Smooth Muscle Cells
Authors: Su Chenlin , Mi Xinya , Ito Tomoya , Kato Yuri , Nishimura Akiyuki , Nagata Ryu , Mori Yasuo , Nishida Motohiro
Published: February 2025

Vascular smooth muscle cells (VSMCs) can dynamically change their phenotype between contractile and synthetic forms in response to environmental stress, which is pivotal in maintaining vascular homeostasis and mediating pathological remodeling of blood vessels. We previously reported that suppression of canonical transient receptor potential 6 (TRPC6) channel-mediated cation entry sustains VSMCs contractile phenotype and promotes the blood flow recovery after hindlimb ischemia in mice. We also reported that Zn2+, a metal biomolecule mobilized by TRPC6 channel activation, exerts potential beneficial effects on cardiac contractility and remodeling. Therefore, we hypothesized that TRPC6-mediated Zn2+ influx participates in phenotype switching of VSMCs and vascular remodeling. We established rat aortic smooth muscle cells (RAoSMCs) stably expressing wild type (WT) and Zn2+ only impermeable TRPC6 (KYD) mutant. Although the resting phenotypes were similar in both RAoSMCs, pharmacological TRPC6 activation by PPZ2 prevented the transforming growth factor (TGF) β-induced reduction in the intracellular Zn2+ amount and contractile differentiation in RAoSMCs (WT), but failed to prevent them in RAoSMCs (KYD). There were no significant differences in TRPC6-dependent cation currents among all RAoSMCs pretreated with or without TGFβ and/or PPZ2, suggesting that TRPC6 channels are functionally expressed in RAoSMCs regardless of their phenotype. Treatment of mice with PPZ2 attenuated the progression of vascular remodeling caused by chronic angiotensin II infusion. These results suggest that Zn2+ influx through TRPC6 channels negatively regulates the TGFβ-induced contractile differentiation of VSMCs and the progression of vascular remodeling in rodents.
Sesquiterpene Lactones as Promising Phytochemicals to Cease Metastatic Propagation of Cancer
Authors: Mehdikhani Fatemeh , Hajimehdipoor Homa , Tansaz Mojgan , Maresca Marc , Rajabi Sadegh
Published: February 2025

Cancer metastasis remains the most challenging issue in cancer therapy. Recent reports show that cancer metastasis accounts for over 90% of cancer-associated deaths in the world. Metastasis is a multi-step process by which cancer cells spread to distant tissues and organs beyond the primary site. The metastatic propagation of different cancers is under the surveillance of several regulating processes and factors related to cellular signaling pathways. Plant-derived phytochemicals are bioactive components of plants with a variety of biological and medicinal activities. Several phytochemicals have been shown to target various molecular factors in cancer cells to tackle metastasis. Sesquiterpene lactones, as a diverse group of plant-derived phytochemicals with a variety of biological activities, have been shown to suppress the promotion and progression of different cancer types by acting on multiple cell-signaling pathways. This review article briefly describes the process of metastasis and its components. Then, sesquiterpene lactones with the ability to target and inhibit invasion, migration, and metastasis along with the molecular mechanisms of their effects on different cancers are described in detail.
Everolimus in the Treatment of Neuroendocrine Tumors: Lights and Shadows
Authors: Medici Bianca , Caffari Eugenia , Maculan Yuri , Benatti Stefania , Piacentini Federico , Dominici Massimo , Gelsomino Fabio
Published: February 2025

Neuroendocrine tumors (NETs) comprise a heterogeneous group of neoplasms that originate from neuroendocrine cells, characterized by their ability to secrete hormones and peptides. Once considered rare, the incidence of NETs has steadily increased due to improved diagnostic modalities. The therapeutic landscape is multifaceted, ranging from surgery for localized disease to pharmacological interventions for advanced cases. However, the absence of robust predictive biomarkers precludes patient stratification and optimization of therapy. Everolimus, an oral mTOR inhibitor, has emerged as a key therapeutic agent due to its dual role in inhibiting cell proliferation and angiogenesis. Nevertheless, challenges such as resistance mechanisms, toxicity and optimal treatment sequencing remain unresolved. This article provides a comprehensive review of the role of everolimus in the management of NETs, focusing in particular on unresolved issues, from the absence of predictive biomarkers to the unavailability of defined guidelines for determining the correct therapeutic sequence.
The Tight Relationship Between the Tumoral Microenvironment and Radium-223
Authors: Conte Miriam , Tomaciello Miriam , De Feo Maria Silvia , Frantellizzi Viviana , Marampon Francesco , De Cristofaro Flaminia , De Vincentis Giuseppe , Filippi Luca
Published: February 2025

Radium-223 (223Ra) was the first radioactive isotope approved for treating castration-resistant prostate cancer (CRPC) with symptomatic bone metastases without visceral metastatic disease. To better understand the action of 223Ra, its role in the tumor microenvironment represents a crucial aspect. A literature search was conducted using the PubMed/MEDLINE database and studies regarding the relationship between 223Ra and the tumoral microenvironment were considered. The tumoral microenvironment is a complex setting in which complex interactions between cells and molecules occur. Radium-223, as an alpha-emitter, induces double-stranded DNA breaks; to potentiate this effect, it could be used in patients with genetic instability but also in combination with therapies which inhibit DNA repair, modulate the immune response, or control tumor growth. In conclusion, a few studies have taken into consideration the tumoral microenvironment in association with 223Ra. However, its understanding is a priority to better comprehend how to effectively exploit 223Ra and its action mechanism.
Understanding the Impact of Synthetic Hematocrit Levels and Biomimetic Channel Widths on Bubble Parameters in Vascular Systems on a Chip
Authors: Baassiri Karine , Nicolau Dan V.
Published: February 2025

Gas embolism is a rare but life-threatening process characterized by the presence of gas bubbles in the venous or arterial systems. These bubbles, if sufficiently large or numerous, can block the delivery of oxygen to critical organs, in particular the brain, and subsequently they can trigger a cascade of adverse biochemical reactions with severe medical outcomes. Despite its critical nature, gas embolism remains poorly understood, necessitating extensive investigation, particularly regarding its manifestations in the human body and its modulation by various biological conditions. However, given its elusive nature, as well as potential lethality, gas embolism is extremely difficult to study in vivo, and nearly impossible to be the subject of clinical trials. To this end, we developed a microfluidic device designed to study in vitro the impact of blood properties and vascular geometries on the formation and evolution of gas bubbles. The system features a biomimetic vascular channel surrounded by two pressure chambers, which induce the genesis of bubbles under varying circumstances. The bubble parameters were correlated with different input parameters, i.e., channel widths, wall thicknesses, viscosities of the artificial blood, and pressure levels. Smaller channel widths and higher equivalent hematocrit concentrations in synthetic blood solutions increased the nucleation density and bubble generation frequencies. Small channel widths were also more prone to bubble formation, with implications for the vulnerability of vascular walls, leading to increased risks of damage or compromise to the integrity of the blood vessels. Larger channel widths, along with higher equivalent hematocrit concentrations, translated into larger bubble volumes and decreased bubble velocities, leading to an increased risk of bubble immobilization within the blood vessels. This biomimetic approach provides insights into the impact of patient history and biological factors on the incidence and progression of gas embolism. Medical conditions, such as anemia, along with anatomical features related to age and sex—such as smaller blood vessels in women and children or larger vascular widths in adult men—affect the susceptibility to the initiation and progression of gas embolism, explored here in vitro through the development of a controlled, physiological-like environment. The analysis of the videos that recorded gas embolism events in vitro for systems where pressure is applied laterally on the microvasculature with thin walls, i.e., 50 μm or less, suggests that the mechanism of gas transfer for the pressure area to the blood is based on percolation, rather than diffusion. These findings highlight the importance of personalized approaches in the management and prevention of gas embolism.
A Scale-Invariant Looming Detector for UAV Return Missions in Power Line Scenarios
Authors: Zhao Jiannan , Zhao Qidong , Wu Chenggen , Li Zhiteng , Shuang Feng
Published: February 2025

Unmanned aerial vehicles (UAVs) offer an efficient solution for power grid maintenance, but collision avoidance during return flights is challenged by crossing power lines, especially for small drones with limited computational resources. Conventional visual systems struggle to detect thin, intricate power lines, which are often overlooked or misinterpreted. While deep learning methods have improved static power line detection in images, they still struggle with dynamic scenarios where collision risks are not detected in real time. Inspired by the hypothesis that the Lobula Giant Movement Detector (LGMD) distinguishes sparse and incoherent motion in the background by detecting continuous and clustered motion contours of the looming object, we propose a Scale-Invariant Looming Detector (SILD). SILD detects motion by preprocessing video frames, enhances motion regions using attention masks, and simulates biological arousal to recognize looming threats while suppressing noise. It also predicts impending collisions during high-speed flight and overcomes the limitations of motion vision to ensure consistent sensitivity to looming objects at different scales. We compare SILD with existing static power line detection techniques, including the Hough transform and D-LinkNet with a dilated convolution-based encoder–decoder architecture. Our results show that SILD strikes an effective balance between detection accuracy and real-time processing efficiency. It is well suited for UAV-based power line detection, where high precision and low-latency performance are essential. Furthermore, we evaluated the performance of the model under various conditions and successfully deployed it on a UAV-embedded board for collision avoidance testing at power lines. This approach provides a novel perspective for UAV obstacle avoidance in power line scenarios.
Long Short-Term Memory-Enabled Electromyography-Controlled Adaptive Wearable Robotic Exoskeleton for Upper Arm Rehabilitation
Authors: Samarakoon S. M. U. S. , Herath H. M. K. K. M. B. , Yasakethu S. L. P. , Fernando Dileepa , Madusanka Nuwan , Yi Myunggi , Lee Byeong-Il
Published: February 2025

Restoring strength, function, and mobility following an illness, accident, or surgery is the primary goal of upper arm rehabilitation. Exoskeletons offer adaptable support, enhancing patient engagement and accelerating recovery. This work proposes an adjustable, wearable robotic exoskeleton powered by electromyography (EMG) data for upper arm rehabilitation. Three activation levels—low, medium, and high—were applied to the EMG data to forecast the Pulse Width Modulation (PWM) based on the range of motion (ROM) angle. Conventional machine learning (ML) models, including K-Nearest Neighbor Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were compared with neural network approaches, including Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) to determine the best ML model for the ROM angle prediction. The LSTM model emerged as the best predictor with a high accuracy of 0.96. The system achieved 0.89 accuracy in exoskeleton control and 0.85 accuracy in signal categorization. Additionally, the proposed exoskeleton demonstrated a 0.97 performance in ROM correction compared to conventional methods (p = 0.097). These findings highlight the potential of EMG-based, LSTM-enabled exoskeleton systems to deliver accurate and adaptive upper arm rehabilitation, particularly for senior citizens, by providing personalized and effective support.
A New Conceptual Design of Twisting Morphing Wing
Authors: Kumkam Noppawit , Suratemeekul Napat , Sleesongsom Suwin
Published: February 2025

This research aims to enhance the performance of unmanned aerial vehicles (UAVs) by investigating the impact of twisting wingtip (TWT) on UAVs’ wing aeroelastic and structural behavior using MATLAB and ANSYS simulations. The study focuses on a simplified twisting wingtip design and its aeroelastic effect. This study includes both static and dynamic aeroelastic phenomena. Previous research has primarily focused on only flutter speed while neglecting divergence speed and lift-effectiveness in design results. Numerical and experimental validation underscores the model’s fidelity and its practical applicability. The TWT is designed to exhibit a predominant torsional mode using a guide mode preference technique. The design results reveal that the twist morphing wing improves structural and aeroelastic performance due to its unique twisting deformation capabilities. Furthermore, this research contributes fundamental insights into a specific twist morphing wing concept, highlighting its potential to enhance UAV performance through twisting wingtip technologies. The torsional mode can be predetermined using the guide mode preference technique. Notably, the divergence speed analysis confirms that the twisting shaft position should not exceed the aerodynamic center, which is located at 0.2103 of the chord length. This serves as the theoretical foundation for the TWT design in this study. The adjustment of the TWT’s twisting angle is confirmed to provide optimal divergence speed improvement within a range of 0% to 27.7%. Additionally, the relative aeroelastic efficiencies indicate that the highest lift effectiveness is 0.68% at a twisting angle of 30°, following an exponential relationship, which can be further extended to aircraft control laws. However, the relative efficiency of flutter speed is not significantly improved by the TWT, showing only a marginal improvement of 0% to 1.84% when twisting up and down, in accordance with previous research findings.
Yeast-Based Direct Catalytic Ethanol Fuel Cell Biosensors: A Batch Analysis Apparatus Combined with Chemometrics for Qualitative Carbohydrate Detection
Authors: Tomassetti Mauro , Marini Federico , Di Natale Corrado , Castrucci Mauro , Campanella Luigi
Published: February 2025

A novel strategy for the qualitative analysis of carbohydrates is developed, utilizing a direct catalytic fuel cell (DCFC) as a sensor, combined with chemometric tools for processing the resulting response curves. Specifically, carbohydrate solutions were incubated with yeast to produce alcohol, and the corresponding current decay trends were measured using a direct catalytic fuel cell designed for ethanol detection. Multiple data processing approaches were then evaluated. Initially, the entire set of data points from the response curves was analyzed using principal component analysis (PCA). To reduce analysis time, chemometric processing was subsequently restricted to the initial portion of the response curves. Finally, to enhance the results, the current decay curves were analyzed in conjunction with the linear fitting parameters derived from the quasi-linear region of the initial response curves, utilizing the common dimension (ComDim) algorithm.
Bioinformatics Tools for NGS-Based Identification of Single Nucleotide Variants and Large-Scale Rearrangements in Mitochondrial DNA
Authors: Barresi Marco , Dal Santo Giulia , Izzo Rossella , Zauli Andrea , Lamantea Eleonora , Caporali Leonardo , Ghezzi Daniele , Legati Andrea
Published: February 2025

The unique features of mitochondrial DNA (mtDNA), including its circular and multicopy nature, the possible coexistence of wild-type and mutant molecules (i.e., heteroplasmy) and the presence of nuclear mitochondrial DNA segments (NUMTs), make the diagnosis of mtDNA diseases particularly challenging. The extensive deployment of next-generation sequencing (NGS) technologies has significantly advanced the diagnosis of mtDNA-related diseases. However, the vast amounts and diverse types of sequencing data complicate the interpretation of these variants. From sequence alignment to variant calling, NGS-based mtDNA sequencing requires specialized bioinformatics tools, adapted for the mitochondrial genome. This study presents the use of new bioinformatics approaches, optimized for short- and long-read sequencing data, to enhance the accuracy of mtDNA analysis in diagnostics. Two recent and emerging free bioinformatics tools, Mitopore and MitoSAlt, were evaluated on patients previously diagnosed with single nucleotide variants or large-scale deletions. Analyses were performed in Linux-based environments and web servers implemented in Python, Perl, Java, and R. The results indicated that each tool demonstrated high sensitivity and specific accuracy in identifying and quantifying various types of pathogenic variants. The study suggests that the integrated and parallel use of these tools offers a significant advantage over traditional methods in interpreting mtDNA genetic variants, reducing the computational demands, and provides an accurate diagnostic solution.
The Moderating Effect of Self-Construal on the Relationship Between Mindfulness and Forgiveness
Authors: Guo Zhiruo , Xu Ting , Li Haijiang
Published: February 2025

The extant literature has established an association between mindfulness, forgiveness, and self-construal; however, the mechanisms underlying these relationships are not yet clear. The present study aims to explore the potential moderating role of self-construal between mindfulness and forgiveness. Four hundred and nineteen participants were recruited and asked to complete measures of mindfulness, self-construal, state, and trait forgiveness. The results showed that mindfulness was positively correlated with state and trait forgiveness. The present study investigated the association between mindfulness and state forgiveness, as well as trait forgiveness, and how this was moderated by self-construal. The findings indicated that for participants who identified with interdependent self-construal, both associations increased, while for those who identified with independent self-construal, the relationship decreased or became non-significant. These results align with previous research and suggest that the mechanisms identified may be applicable to psychological education. The results of this study suggest the presence of a potential underlying mechanism between mindfulness and forgiveness through self-construal. The findings of the research have guiding significance for the design and implementation of psychological interventions, providing evidence that mindfulness training may promote forgiveness by affecting self-construal. These findings have the potential to enhance interpersonal relationships, promote cross-cultural communication and international cooperation, and cultivate students’ mindfulness, empathy, and forgiveness, thereby supporting the creation of a more harmonious and supportive learning environment.
Innovative Prefabricated Wall Panel for Solar Utilization and Energy Efficiency: Building-Integrated Heat Pipe-Embedded System for Cooling-Dominant Zones
Authors: Long Hui , Xu Yangguang
Published: February 2025

Buildings are major contributors to carbon emissions, emphasizing the need for energy efficiency. However, existing solar-integrated building façades often face integration and adaptability challenges. The aim of this study is to propose and evaluate an innovative building-integrated heat pipe-embedded (BiHPe) prefabricated wall panel for sustainable building design. By embedding heat pipes into concrete walls, the system transfers solar energy to domestic water. The performance of the system is evaluated using a comprehensive approach that integrates dynamic modeling, experimental validation, parametric analysis, and a case study. A dynamic energy balance model was developed and experimentally validated, identifying key factors affecting system performance, such as heat pipe spacing, absorber material, and heat pipe placement and configuration. Parametric analysis was conducted to assess the impact of these variables. Simulation results from a case study in Hong Kong show that the system reduces wall heat transmission to 76.1%, achieves a water gain efficiency of 16.7%, and saves 162 kWh/m2 of electricity annually. Additionally, the system stabilizes indoor temperatures, improving thermal comfort. The BiHPe panel offers a multifunctional solution that combines energy efficiency, thermal comfort, and water heating, demonstrating exceptional adaptability and performance in cooling-dominant zones, making it a promising option for sustainable building design.
Identification of Key Drivers and Path Transmission of Carbon Emissions from Prefabricated Buildings: Based on System Dynamics
Authors: Cheng Jing , Li Liping , Zhang Rui , Tian Liang , Liu Yanhui
Published: February 2025

In order to achieve the ‘dual carbon’ goal, based on the DEMATEL-ISM model, 19 main factors affecting the carbon emissions of prefabricated buildings were preliminarily identified from five dimensions, including government decision-making, technical environment, social economy, energy consumption, and market supply and demand. The logical relationship, hierarchical structure, and importance between the factors were clarified, and finally, the four influencing factors were determined. According to the causal feedback relationship between the above four factors in the system flow from 2010 to 2030, eight different control scenarios were proposed, and the impact and change trend of each control scenario on the reduction of carbon emissions of prefabricated buildings were analyzed. The research results show that the key factors for carbon emissions from prefabricated buildings include 14 outcome factors and 5 cause factors, and that the causal factors are key drivers. They are the standard specification system, the incremental cost of prefabricated buildings, investment in scientific and technological innovation, and the level of prefabricated integrated technology. The key factors were structurally stratified from the essential level to the superficial level in four tiers. The first tier of the standard specification system is the surface causal factor affecting carbon emissions from prefabricated buildings. Investment in scientific and technological innovation in the second and third tiers, and the level of prefabricated integrated technology are the causes of the transition. The incremental cost of prefabricated buildings at the fourth level is the essential causal factor. Finally, based on the data related to carbon emissions of prefabricated buildings in Yunnan, China, and verified in eight regulatory scenarios, the results of the study can effectively reveal the carbon emission reduction transmission path of prefabricated buildings, which can provide a reference for the development of prefabricated buildings and carbon emission reduction strategies.
Cooling Heritage Scenarios: Transforming Historic Squares for Thermal Comfort
Authors: Rezaie Pegah , Lopez-Cabeza Victoria Patricia , Sola-Caraballo Javier , Galan-Marin Carmen
Published: February 2025

Urban squares in historic neighborhoods are vital public spaces, often the only nearby option available for an aging population. However, these spaces face increasing thermal discomfort exacerbated by urban heat island (UHI) effects. This research focuses on improving thermal comfort for two case studies located in Seville’s high-density and historically rich Casco Antiguo neighborhood. Although their significance and social value make them central meeting points for locals and visitors, these squares face major challenges regarding thermal comfort, mainly due to a lack of greenery or adequate shading. This study examines the conditions by conducting in-person monitoring and simulations, identifying factors contributing to discomfort. On the basis of this, the research proposes mitigation strategies to address these issues. These solutions include the installation of green walls, the addition of canopies, and the application of specific surface materials to improve the conditions of these squares. Canopies provided the most significant cooling, reducing universal thermal climate index (UTCI) values by up to 6.5 °C. Green walls delivered localized cooling, lowering the mean radiant temperature (MRT) by up to 5 °C. The results reveal how these approaches can bring about changes in thermal comfort in a way that benefits historic city environments.
Asymmetric Effect of Airline Customer Opinions for Service Quality Attributes: Text Mining Approach
Authors: Eum Seong-Won , Leem Byunghak
Published: February 2025

The purpose of this study is to identify airline asymmetric attributes that affect customer satisfaction based on the three-factor theory and to build an Asymmetric Impact-Sentiment Analysis (AISA) for resource allocation prioritization. We identified food and beverage service as a basic factor; inflight service as a one-dimensional factor; and seat comfort, ground service, and airline seat class as attractive factors. AISA analysis results showed that food and beverage services should be prevented from falling into customer dissatisfaction through Urgent Action (cell II), and in-flight services should be improved continuously to increase satisfaction (cell IV). Low-priority improvement is required for seat comfort, which is an attractive factor (cell VI), and strong maintenance is required for ground service and airline seat class as strength factors (cell V). The first contribution, the asymmetric relationship between customer opinions for service attributes and satisfaction, was verified. Second, this paper extended the IPA to the text mining-based asymmetric AISA.
Implications of Fumarate Hydratase Deficiency (FHD) and Cancer Risk: A Window into the Clinical and Oncological Implications of a Rare Disorder in Gynecology
Authors: D’Indinosante Marco , Lardino Sara , Bruno Matteo , Stabile Guglielmo , Pavone Matteo , Giannone Gaia , Lombardi Pasquale , Daniele Gennaro , Fanfani Francesco , Ciccarone Francesca , Scambia Giovanni
Published: February 2025

Fumarate hydratase (FH) deficiency is a rare, yet impactful metabolic disorder caused by mutations in the FH gene, affecting the Krebs cycle, leading to the accumulation of fumarate and pseudohypoxic states. This metabolic shift promotes cell signaling alterations that can drive tumorigenesis, as heterozygous germline mutations in the FH gene, resulting in hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome. FH-deficient uterine leiomyomas show peculiar histological features that may lead to misdiagnosis STUMP (smooth muscle tumor of uncertain malignant potential) and uLMS (uterine leiomyosarcoma). Definitive diagnosis involves clinical evaluation, imaging, and histopathological examination, with immunohistochemistry for FH protein being a key diagnostic tool. Management of FH-deficient leiomyomas may involve conventional treatments like surgery and hormonal therapy but also requires careful monitoring and genetic counseling for associated malignancies. High-intensity focused ultrasound (HIFU) has emerged as a promising treatment option for fibroids, although long-term efficacy remains a concern also because of its inability to obtain tissue for a pathological diagnosis. Fumarate hydratase deficiency (FHD) represents a significant challenge in gynecologic oncology due to its association with an increased risk of hereditary leiomyomatosis and renal cell carcinoma. Nevertheless, to the best of our knowledge, there is a lack of studies demonstrating the potential role of FH deficiency in increased risk of leiomyosarcomatosus transformation. Early detection, genetic screening, and personalized treatment approaches are critical for improving patient outcomes. The aim of this review is to develop a narrative overview of the implications of FHD in gynecological diseases and its correlation with cancer risk. For the first time, this review offers an overview of the necessity for studies to address the possible correlation between FH deficiency and the risk of developing leiomyosarcoma, focusing on new perspectives that can be explored in the field of better FH deficiency knowledge and cancer risk.