bluuebunny/crossref_metadata_2025 huggingface dataset:
Size-Exclusion Chromatography of Macromolecules: A Brief Tutorial Overview on Fundamentals with Computational Tools for Data Analysis and Determination of Structural Information
Authors: Hernández-Cifre José Ginés , Collado-González Mar , Díaz Baños Francisco Guillermo , García de la Torre José
Published: February 2025

Size-exclusion chromatography (SEC) is presently a widely used and very informative technique for the characterization of macromolecules in solution. Beyond the first implementations of SEC—which required cumbersome column calibrations and were mainly intended for the determination of molecular weights—the modern SEC approach involving multiple detectors (md-SEC) is based on solution properties such as intrinsic viscosity and light scattering. Thus, md-SEC enables the direct and more efficient determination of molecular weights, as well as the determination of relationships between property and molecular weight, which can be quite useful in structural studies. Here, we first present a review of the fundamental aspects of the dilute-solution properties of macromolecules—particularly the differential refractive index, intrinsic viscosity, and scattering-related properties—on which the various detectors involved in md-SEC are based. Then, we developed SECtools, a suite of public-domain, open-source computer programs, which allow for the full analysis of md-SEC chromatograms. These analyses range from just the recorded raw signals (mV) of the detectors to a full determination of molecular weight averages and distributions. The use of these programs is illustrated through experimental studies using various samples.
Novel Processes for the Production of Continuous Carbon Fiber-Reinforced Thermoplastic Polymers via Additive Manufacturing and Comparisons
Authors: Zeidler Simon , Matkovic Nikolas , Kößler Florian , Puchta Alexander , Fleischer Jürgen
Published: February 2025

Continuous fiber-reinforced polymer (CoFRP) parts offer significant potential for reducing future product consumption and CO2 emissions due to their high tensile properties and low density. Additive manufacturing enables the tool-free production of complex geometries with optimal material utilization, making it a promising approach for creating load-path-optimized CoFRP parts. Recent advancements have integrated continuous fibers into laser sintering processes, allowing for the support-free production of complex parts with improved material properties. However, additive manufacturing faces challenges such as long production times, small component dimensions, and defects like high void content. New processes, including Arburg Polymer Freeforming (APF), robotic direct extrusion (DES) and the integration of thermoplastic tapes, and laser sintering, have enabled the production of CoFRPs to address these issues. A comparison of these new processes with existing material extrusion methods is necessary to determine the most suitable approach for specific tasks. The fulfillment factor is used to compare composites with different matrix and fiber materials, representing the percentage of experimentally achieved material properties relative to the theoretical maximum according to the Voigt model. The fulfillment factor varies significantly across different processes and materials. For FFF processes, the fulfillment factor ranges from 20% to 77% for stiffness and 14% to 84% for strength, with an average of 52% and 37%, respectively. APF shows a high fulfillment factor for stiffness (94%) but is lower for strength (23%), attributed to poor fiber–matrix bonding and process-induced pores. The new DES process improves the fulfillment factor due to additional consolidation steps, achieving above-average values for strength (67%). The CoFRP produced by the novel LS process also shows a high fulfillment factor for stiffness (85%) and an average fulfillment factor for strength (39%), influenced by suboptimal process parameters and defects.
Enhanced Thermal Resistance and Mechanical Performance of Methyl Methacrylate-Based Pavement Coatings for Urban Heat Mitigation
Authors: Kim Kwan Kyu , Choi Yoon-Sang , Lee Hee Jun , Rodrigazo Shanelle Aira , Yeon Jaeheum
Published: February 2025

The urban heat island effect raises road surface temperatures, increasing energy demands and accelerating pavement deterioration. This study evaluates a polymer-based pavement system using methyl methacrylate (MMA) resin with aluminum silicate (AS), glass bubbles (GBs), and microencapsulated n-docosane phase-change material (PCM) to identify the most effective solution. Indoor laboratory tests determined AS as the optimal choice, balancing thermal insulation, workability, and mechanical strength. AS-containing mixtures reduced surface temperatures by ~10 °C and exhibited superior compressive strength (28.2 MPa at 6 wt%) compared to GB (23.7 MPa at 4 wt%) and PCM (27.2 MPa at 6 wt%). AS also maintained stable viscosity at ≤10 wt%, unlike GB and PCM, which became unworkable above 5 wt%. The AS-based system achieved high skid resistance (90.2 BPN), abrasion resistance (0.1% wear after 500,000 cycles), and low VOC emissions (69.64 g/L). Adjusting the resin-to-BPO ratio to 1:0.42 enabled a 30 min curing time at 25 °C, ensuring practical application. These findings highlight AS as the most effective filler for large-scale deployment. Future work should assess long-term durability and optimize formulations for broader adoption in heat-mitigating infrastructure.
Preparation and Performance Evaluation of High-Temperature Polymer Nano-Plugging Agents for Water-Based Drilling Fluids Systems Applicable to Unconventional Reservoirs
Authors: Yao Lei , Quan Xiaohu , Zhang Yongjie , Huang Shengming , Feng Qi , Zhang Xin
Published: February 2025

To address the challenges of micro-fracture development in shale formations, frequent wellbore instability, and the limited plugging capability of water-based drilling fluids in unconventional reservoirs, a nano-plugging agent (NPA) was synthesized using emulsion polymerization. The synthesized NPA was characterized through thermogravimetric analysis (TGA) and transmission electron microscopy (TEM), revealing excellent high-temperature stability and a spherical or sub-spherical morphology, with particle diameters ranging from approximately 20 to 50 nm. The rheological, filtration, and plugging properties of NPA were systematically evaluated, and its sealing mechanism was analyzed. The results demonstrate that at a test temperature of 180 °C, the optimal NPA concentration in the drilling fluid base slurry is 1.5%, achieving a 60.5% reduction in HTHP (high-temperature high-pressure) sand disc filtration loss. Additionally, the API filtration loss and HTHP filtration loss reduction rates reached 58.1% and 50.3%, respectively, highlighting the remarkable filtration loss reduction and plugging efficiency of NPA under high-temperature conditions. After NPA treatment, the specific surface area and pore volume of shale cuttings decreased to 9.348 m2/g and 0.035 cm3/g, respectively, indicating effective surface plugging. The mechanism analysis suggests that due to its nanoscale size, NPA can penetrate deep into micro-pores and fractures within the shale, achieving deep-layer plugging. Furthermore, NPA forms a physical plugging barrier on the shale surface, effectively suppressing shale hydration and swelling. This study provides valuable insights and guidance for addressing wellbore instability and the insufficient plugging performance of drilling fluids in unconventional reservoir drilling operations.
Engineering Hydrogels with Enhanced Adhesive Strength Through Optimization of Poly(Ethylene Glycol) Molecular Weight
Authors: Yang Yin-An , Ni Yu-Feng , Chakravarthy Rajan Deepan , Wu Karl , Yeh Mei-Yu , Lin Hsin-Chieh
Published: February 2025

Hydrogels are extensively utilized in biomedical fields because of their remarkable properties, including biocompatibility, high water content, flexibility, and elasticity. However, despite substantial progress in hydrogel research, creating a hydrogel adhesive that integrates high stretchability, fatigue resistance, and reversible adhesion continues to pose significant challenges. In this study, we aimed to address these challenges by preparing hydrogels using a combination of acrylic acid, acrylamide, carboxymethylcellulose methacrylate, thiol-functionalized polyhedral oligomeric silsesquioxane, and poly(ethylene glycol) dimethacrylate (PEGDM). By systematically varying the molecular weight of PEG, we were able to precisely adjust the mechanical and adhesive properties of the hydrogels. Our research revealed that a PEG molecular weight of 2000 (resulting in P1 hydrogel) provided a notable adhesive strength of 717.2 kPa on glass surfaces. This performance is particularly impressive given the challenges associated with achieving high adhesive strength while maintaining other desirable hydrogel properties. Beyond its strong adhesive capabilities, the P1 hydrogel also demonstrated exceptional stretchability, support, and fatigue resistance. These characteristics are crucial for applications where the adhesive needs to endure repeated stress and deformation without losing effectiveness. The successful development of P1 hydrogel underscores its potential as a multifunctional adhesive material with a broad range of applications. The ability to tailor the properties of hydrogels through molecular weight adjustments offers a promising approach to creating advanced adhesive solutions that meet the demanding requirements of modern biomedical and industrial applications.
Inducing Osteogenesis in Human Pulp Stem Cells Cultured on Nano-Hydroxyapatite and Naringin-Coated 3D-Printed Poly Lactic Acid Scaffolds
Authors: Dawood Reem Mones , Mahdee Anas Falah
Published: February 2025

Background: Regeneration dentistry demonstrates significant challenges due to the complexity of different dental structures. This study aimed to investigate osteogenic differentiation of human pulp stem cells (hDPSCs) cultured on a 3D-printed poly lactic acid (PLA) scaffold coated with nano-hydroxyapatite (nHA) and naringin (NAR) as a model for a dental regenerative. Methods: PLA scaffolds were 3D printed into circular discs (10 × 1 mm) and coated with nHA, NAR, or both. Scaffolds were cultured with hDPTCs to identify cellular morphological changes and adhesion over incubation periods of 3, 7, and 21 days using SEM. Then, the osteogenic potential of PLA, PLA/nHA/NAR, or PLA scaffolds coated with MTA elutes (PLA/MTA scaffolds) were evaluated by measuring mineralized tissue deposition using calcium concentration assays and alizarin red staining (ARS). Also, immunofluorescence labelling of alkaline phosphatase (ALP) and dentine sialophosphoprotein (DSPP) within cultured cells were evaluated. Results: The highest cellular attachment was identified on the PLA/nHA/NAR scaffold, with morphological changes reflecting cellular differentiation. The highest calcium deposition and ARS were recognized in the PLA/nHA/NAR culture, with statistically significant difference (p < 0.05) compared to PLA/MTA. Also, ALP and DSPP markers showed statistically significantly higher (p < 0.05) immunoreactivity in cells cultured within PLA/nHA/NAR compared to PLA/MTA. Conclusions: The results confirm the osteogenic potential of PLA scaffolds coated with nHA/NAR for future animal and human investigations.
Nonlinear Viscoelasticity of and Structural Modulation in Guar Gum-Enhanced Triple-Network Hydrogels
Authors: Luo Yi , Pauer Werner , Luinstra Gerrit A.
Published: February 2025

The effect of the presence of guar gum (0–0.75 wt%) in a thermo-responsive triple-network (TN) PVA/TA/PVA-MA-g-PNIPAAm hydrogel (PVA: polyvinyl alcohol; MA: methacrylate, PNIPAAm: poly-N-isopropyl acryl amide; TA: tannic acid) with respect to the structural, mechanical, and viscoelastic properties was mapped. A comprehensive analysis, using large-amplitude oscillatory shear (LAOS), SEM imaging, XRD, and mechanical analysis revealed that guar enhances hydrogel crystallinity (up to 30% at 0.75 wt%), which goes along with a strain hardening. The hydrogel achieved superior mechanical performance at a gum concentration of 0.5 wt% with a 40% increase in shear-thickening, an enhanced strain tolerance in nonlinear regimes, and a good mechanical robustness (maximum elongation to break of 500% and stress of 620 kPa). The hydrogel with 0.5 wt% guar exhibited also a good thermal response (equilibrium swelling ratio changed from 8.4 at 5 °C to 2.5 at 50 °C) and an excellent thermal cycling dimensional stability. Higher guar concentrations reduce structural resilience, leading to brittle hydrogels with lower extensibility and viscoelastic stability.
Low-Alpha-Cellulose-Based Membranes
Authors: Makarov Igor , Shambilova Gulbarshin , Bukanova Aigul , Kairliyeva Fazilat , Bukanova Saule , Kadasheva Zhanar , Gainutdinov Radmir , Koksharov Alexander , Komarov Ivan , Song Junlong , Legkov Sergey , Nebesskaya Alexandra
Published: February 2025

Depending on the method of cellulose production, the proportion of alpha fraction in it can vary significantly. Paper pulp, unlike dissolving cellulose, has an alpha proportion of less than 90%. The presence of cellulose satellites in the system does not impede the formation of concentrated solutions of N-methylmorpholine-N-oxide (NMMO). In the current study, spinning solutions based on cellulose with a low alpha fraction (up to 90%) (pulp cellulose) are investigated. The morphological features and rheological behavior of such solutions are examined. It is suggested to roll the obtained solutions in order to obtain cellulose membranes. X-ray diffraction, IR spectroscopy, AFM and SEM were used to investigate the resulting structure and morphology of the obtained membranes. It is shown that the degree of crystallinity for the membranes varies based on the impurity content in the sample. The morphology of the films is characterized by a dense texture and the absence of vacuoles. The highest strength and elastic modulus were found for membranes made of bleached hardwood sulfate cellulose, 5.7 MPa and 6.4 GPa, respectively. The maximum values of the contact angle (48°) were found for films with a higher proportion of lignin. The presence of lignin in the membranes leads to an increase in rejection for the anionic dyes Orange II and Remazol Brilliant Blue R.
Recent Advances in Polymer Recycling: A Review of Chemical and Biological Processes for Sustainable Solutions
Authors: Peti Damián , Dobránsky Jozef , Michalík Peter
Published: February 2025

Plastics, particularly synthetic organic polymers, have become indispensable in modern life, yet their large-scale production has led to significant environmental challenges due to persistent waste. Traditional mechanical recycling methods have proven insufficient in addressing these issues. This review explores recent advancements in polymer recycling, focusing on chemical and biological processes, such as pyrolysis, depolymerization, and enzyme-based degradation, which offer more efficient and sustainable alternatives. Within the framework of a circular economy, the review also examines strategies like closed-loop and circular plastic economies. These developments represent critical steps toward creating more sustainable plastic recycling practices. The final chapter includes the Quarterly Report 2024 on recycling plastics, providing an up-to-date overview of the current state of plastic recycling and its recent trends.
Analysis and Optimization of Thermal Storage Performance of Thermocline Storage Tank with Different Water Distribution Structures
Authors: Wang Xinwei , Duan Longbin , Gao Genying , Zheng Weibo , Sun Dong , Li Jinyu , Fu Jing , Lin Riyi
Published: February 2025

Energy storage is essential for solar energy utilization, and thermocline storage tanks are commonly used. To improve temperature stratification and storage efficiency, we investigated the effect of different water distributor configurations on tank stratification. We numerically analyzed the heat storage processes in hot water tanks with three water distribution configurations: star, antenna, and octagonal. Temperature stratification was evaluated based on thermocline thickness and storage efficiency. Thermal storage efficiency improves by 0.45% when the outlet direction of the water distributor matches the fluid’s motion direction during natural stratification. The energy storage process is categorized into three stages based on efficiency changes, with different factors affecting efficiency at each stage. In the initial stage, antenna-type and octagonal water distribution improve temperature uniformity along the axial section, reduce thermocline thickness, and enhance stratification. Final efficiency during this stage is primarily influenced by energy loss resulting from the mixing of hot and cold water. In the development stage, energy storage efficiency decreases mainly because the lower boundary of the thermocline reaches the exit, causing partial discharge of hot water. Among the three configurations, the octagonal water distribution exhibits the lowest energy loss, 6.4% lower than that of the star-type distribution.
TopADDPi: An Affordable and Sustainable Raspberry Pi Cluster for Parallel-Computing Topology Optimization
Authors: Zhang Zhi-Dong , Yu Dao-Yuan , Ibhadode Osezua , Meng Liang , Gao Tong , Zhu Ji-Hong , Zhang Wei-Hong
Published: February 2025

Parallel-Computing Topology Optimization (PCTO) has gained importance, especially with the advancement of additive manufacturing (AM), due to its ability to tackle high-dimensional, high-resolution challenges. PCTO is highly relevant to sustainable manufacturing processes and technologies, enabling resource-efficient designs, reduced emissions, and advancements in Industry 4.0 integration. However, PCTO poses difficulties for newcomers or researchers, mainly because of its reliance on non-traditional computing environments and the limited availability of high-performance computing (HPC) resources. Addressing this, the study introduces TopADDPi, a Raspberry Pi-based cluster system, which has been purpose-built to facilitate learning and research in PCTO. It provides detailed instructions for assembling and configuring a Raspberry Pi cluster, with a focus on cost-effectiveness and ease of use. The study thoroughly investigates how different hardware and software configurations affect computing efficiency. In addition, through extensive numerical testing, the performance, energy consumption, and environmental impact of the Raspberry Pi cluster are benchmarked against conventional computing systems. The findings demonstrate the cluster’s advantages in handling parallel computing, its indispensable role in debugging, its remarkable energy efficiency, and its significantly reduced carbon footprint compared to conventional systems. These attributes establish the Raspberry Pi cluster as an invaluable tool for both educational and research applications in structural engineering, offering an affordable, sustainable, and indispensable solution for PCTO.
The Effect of Activated Carbon Support on Ru/AC Catalysts Used for the Catalytic Decomposition of Hydroxylamine Nitrate and Hydrazine Nitrate
Authors: Cao Zhi , Yu Deyan , He Tiansheng , Li Tianchi , Zuo Chen , Li Baole , Lv Hongbin , Yan Taihong , Zheng Weifang
Published: February 2025

Hydroxylamine nitrate (HAN) and hydrazine nitrate (HN) are commonly found in radioactive waste solutions in nuclear fuel reprocessing, and their efficient removal is essential for waste treatment processes. In this study, six activated carbon carriers were selected to prepare Ru/AC catalysts for the simultaneous catalytic decomposition of HAN and HN, with the aim of exploring the effect of carrier properties on catalytic performance. The catalyst’s activity was evaluated in a batch reaction unit, and its structural properties were characterized using N2 physical adsorption, XRD, SEM, and TEM techniques. The results revealed that the catalyst’s activity was primarily determined by the carrier’s particle size and specific surface area. Additionally, corrosion-induced damage to the pore structure and Ru loss were identified as the main factors responsible for catalyst deactivation. This study highlights the importance of optimizing carrier structure to enhance the activity and stability of Ru/AC catalysts.
Does Vitamin D Deficiency Increase the Risk of Autism Spectrum Disorder? Linking Evidence with Theory—A Narrative Review
Authors: Sultan Sadia , Alhejin Noor , Serafi Raed , Abu Alrahi Manar , Afifi Gehad , Al-Adawi Layan , Serafi Mohammed , El Madhoun Nada
Published: February 2025

Introduction: Vitamin D plays a crucial role in brain health by providing antioxidant, anti-inflammatory, and neuroprotective benefits. It regulates neurotransmitters and neurotrophins that are essential for the development, maintenance, and functioning of the nervous system. Deficiency in vitamin D during pregnancy and early childhood can disrupt neurodevelopment, potentially contributing to autism spectrum disorder (ASD). The aim of this narrative review was to analyze the potential link between vitamin D deficiency and the development of ASD, as well as to explore the therapeutic benefits of vitamin D supplementation. Method: We performed a literature search across PubMed, EMBASE, Web of Science, and the Cochrane Library databases, reviewing observational studies, randomized controlled trials (RCTs), and meta-analyses for evidence of an association between vitamin D deficiency and ASD. Results: The results were mixed but promising, with most observational studies suggesting a positive link between vitamin D deficiency and ASD, though these findings were not consistently replicated in prospective studies or RCTs. In conclusion, the available data are insufficient to establish vitamin D deficiency as a definitive cause of ASD. Further RCTs, particularly during pregnancy and infancy, are needed to better understand the role of vitamin D in the etiology of ASD and its potential as a therapeutic intervention. Conclusions: The current available data are insufficient to support vitamin D deficiency as a definitive factor in the etiology of autism spectrum disorders. To translate this hypothesis into clinical practice, additional randomized controlled trials, particularly during pregnancy and early infancy, are needed.
Assessment of the Mechanical Properties of Soft Tissue Phantoms Using Impact Analysis
Authors: Bouffandeau Arthur , Poudrel Anne-Sophie , Brossier Chloé , Rosi Giuseppe , Nguyen Vu-Hieu , Flouzat-Lachaniette Charles-Henri , Meningaud Jean-Paul , Haïat Guillaume
Published: February 2025

Skin physiopathological conditions have a strong influence on its biomechanical properties. However, it remains difficult to accurately assess the surface stiffness of soft tissues. The aim of this study was to evaluate the performances of an impact-based analysis method (IBAM) and to compare them with those of an existing digital palpation device, MyotonPro®. The IBAM is based on the impact of an instrumented hammer equipped with a force sensor on a cylindrical punch in contact with agar-based phantoms mimicking soft tissues. The indicator Δt is estimated by analyzing the force signal obtained from the instrumented hammer. Various phantom geometries, stiffnesses and structures (homogeneous and bilayer) were used to estimate the performances of both methods. Measurements show that the IBAM is sensitive to a volume of interest equivalent to a sphere approximately twice the punch diameter. The sensitivity of the IBAM to changes in Young’s modulus is similar to that of dynamic mechanical analysis (DMA) and significantly better compared to MyotonPro. The axial (respectively, lateral) resolution is two (respectively, five) times lower with the IBAM than with MyotonPro. The present study paves the way for the development of a simple, quantitative and non-invasive method to measure skin biomechanical properties.
AIPI: Network Status Identification on Multi-Protocol Wireless Sensor Networks
Authors: Jiang Peng , Feng Xinglin , Feng Renhai , Cui Junpeng
Published: February 2025

Topology control is important for extending networks lifetime and reducing interference. The accuracy of topology identification plays a crucial role in topology control. Traditional passive interception can only identify the connectivity among cooperative sensor networks with known protocol. This paper proposes a novel method called Active Interfere and Passive Interception (AIPI) to identify the topology of non-cooperative sensor networks by using both active and passive interceptions. Active interception uses full duplex sensors to disrupt communication until frequency hopped to acquire distance information, and thus, infer their connectivity and calculate the location after modifying error in a non-cooperative sensor network. Passive interception uses Granger causality to infer the connectivity between two communication nodes after getting the time frame structure in physical layer. Passive interception is applied to conserve power consumption after obtaining physical information via active interception. Simulation results indicate that AIPI can identify the topology of non-cooperative sensor networks with a higher accuracy than traditional method.
A Compact Orthosis Compliance Monitoring Device Using Pressure Sensors and Accelerometers: Design and Proof-of-Concept Testing
Authors: Devanand Devi Baruni , Gardiner Matthew D. , Kedgley Angela E.
Published: February 2025

Monitoring orthosis compliance using patient diaries is subjective, as patients can overestimate their levels of device use. An objective way to monitor compliance is required because if an orthotic prescription is not followed, the orthosis will not work as intended. This study aimed to develop and validate a device that monitors orthosis compliance objectively using pressure and acceleration. Fifteen participants were recruited to test the device’s ability to estimate wear time during the performance of several grip patterns and whilst completing selected activities of daily living. Sensor threshold values were used to discern whether users were wearing their orthosis or not. No differences between pressure sensor and accelerometer-based wear time estimations were found. The device’s pressure-based wear time estimations were found to have a specificity of 92.7 ± 16.4% and sensitivity of 74.0 ± 41.3%, whilst accelerometer-based wear time estimates had a specificity of 66.1 ± 34.7% and sensitivity of 86.2 ± 8.0%. This study successfully demonstrated the feasibility of monitoring hand orthosis compliance using pressure or acceleration. This device has the potential to provide insight into the effectiveness of both existing and novel orthotics, benefitting both clinical practice and research.
Altered Directed-Connectivity Network in Temporal Lobe Epilepsy: A MEG Study
Authors: Zhang Chen , Hu Wenhan , Wu Yutong , Li Guangfei , Yang Chunlan , Wu Ting
Published: February 2025

Temporal lobe epilepsy (TLE) is considered a network disorder rather than a localized lesion, making it essential to study the network mechanisms underlying TLE. In this study, we constructed directed brain networks based on clinical MEG data using the Granger Causality Analysis (GCA) method, aiming to provide new insights into the network mechanisms of TLE. MEG data from 13 lTLE and 21 rTLE patients and 14 healthy controls (HCs) were analyzed. The preprocessed MEG data were used to construct directed brain networks using the GCA method and undirected brain networks using the Pearson Correlation Coefficient (PCC) method. Graph theoretical analysis extracted global and local topologies from the binary matrix, and SVM classified topologies with significant differences (p < 0.05). Comparative studies were performed on connectivity strengths, graph theory metrics, and SVM classifications between GCA and PCC, with an additional analysis of GCA-weighted network connectivity. The results show that TLE patients showed significantly increased functional connectivity based on GCA compared to the control group; similarities of the hub brain regions between lTLE and rTLE patients and the cortical–limbic–thalamic–cortical loop were identified; TLE patients exhibited a significant increase in GCA-based Global Clustering Coefficient (GCC) and Global Local Efficiency (GLE); most brain regions with abnormal local topological properties in TLE patients overlapped with their hub regions. The directionality of brain connectivity has played a significantly more pivotal role in research on TLE. GCA may be a potential tool in MEG analysis to distinguish TLE patients and HC effectively.
Overcoming Challenges in Video-Based Health Monitoring: Real-World Implementation, Ethics, and Data Considerations
Authors: Ferreira Simão , Marinheiro Catarina , Mateus Catarina , Rodrigues Pedro Pereira , Rodrigues Matilde A. , Rocha Nuno
Published: February 2025

In the context of evolving healthcare technologies, this study investigates the application of AI and machine learning in video-based health monitoring systems, focusing on the challenges and potential of implementing such systems in real-world scenarios, specifically for knowledge workers. The research underscores the criticality of addressing technological, ethical, and practical hurdles in deploying these systems outside controlled laboratory environments. Methodologically, the study spanned three months and employed advanced facial recognition technology embedded in participants’ computing devices to collect physiological metrics such as heart rate, blinking frequency, and emotional states, thereby contributing to a stress detection dataset. This approach ensured data privacy and aligns with ethical standards. The results reveal significant challenges in data collection and processing, including biases in video datasets, the need for high-resolution videos, and the complexities of maintaining data quality and consistency, with 42% (after adjustments) of data lost. In conclusion, this research emphasizes the necessity for rigorous, ethical, and technologically adapted methodologies to fully realize the benefits of these systems in diverse healthcare contexts.
Towards Automatic Expressive Pipa Music Transcription Using Morphological Analysis of Photoelectric Signals
Authors: Wang Yuancheng , Li Xuanzhe , Zhang Yunxiao , Wang Qiao
Published: February 2025

The musical signal produced by plucked instruments often exhibits non-stationarity due to variations in the pitch and amplitude, making pitch estimation a challenge. In this paper, we assess different transcription processes and algorithms applied to signals captured by optical sensors mounted on a pipa—a traditional Chinese plucked instrument—played using a range of techniques. The captured signal demonstrates a distinctive arched feature during plucking. This facilitates onset detection to avoid the impact of the spurious energy peaks within vibration areas that arise from pitch-shift playing techniques. Subsequently, we developed a novel time–frequency feature, known as continuous time-period mapping (CTPM), which contains pitch curves. The proposed process can also be applied to playing techniques that mix pitch shifts and tremolo. When evaluated on four renowned pipa music pieces of varying difficulty levels, our fully time-domain-based onset detectors outperformed four short-time methods, particularly during tremolo. Our zero-crossing-based pitch estimator achieved a performance comparable to short-time methods with a far better computational efficiency, demonstrating its suitability for use in a lightweight algorithm in future work.
Enhancing Maritime Safety: Estimating Collision Probabilities with Trajectory Prediction Boundaries Using Deep Learning Models
Authors: Jurkus Robertas , Venskus Julius , Markevičiūtė Jurgita , Treigys Povilas
Published: February 2025

We investigate maritime accidents near Bornholm Island in the Baltic Sea, focusing on one of the most recent vessel collisions and a way to improve maritime safety as a prevention strategy. By leveraging Long Short-Term Memory autoencoders, a class of deep recurrent neural networks, this research demonstrates a unique approach to forecasting vessel trajectories and assessing collision risks. The proposed method integrates trajectory predictions with statistical techniques to construct probabilistic boundaries, including confidence intervals, prediction intervals, ellipsoidal prediction regions, and conformal prediction regions. The study introduces a collision risk score, which evaluates the likelihood of boundary overlaps as a metric for collision detection. These methods are applied to simulated test scenarios and a real-world case study involving the 2021 collision between the Scot Carrier and Karin Hoej cargo ships. The results demonstrate that CPR, a non-parametric approach, reliably forecasts collision risks with 95% confidence. The findings underscore the importance of integrating statistical uncertainty quantification with deep learning models to improve navigational decision-making and encourage a shift towards more proactive, AI/ML-enhanced maritime risk management protocols.
Trends and Advances in Wearable Plasmonic Sensors Utilizing Surface-Enhanced Raman Spectroscopy (SERS): A Comprehensive Review
Authors: Khonina Svetlana N. , Kazanskiy Nikolay L.
Published: February 2025

Wearable sensors have appeared as a promising solution for real-time, non-invasive monitoring in diverse fields, including healthcare, environmental sensing, and wearable electronics. Surface-enhanced Raman spectroscopy (SERS)-based sensors leverage the unique properties of SERS, such as plasmonic signal enhancement, high molecular specificity, and the potential for single-molecule detection, to detect and identify a wide range of analytes with ultra-high sensitivity and molecular selectivity. However, it is important to note that wearable sensors utilize various sensing mechanisms, and not all rely on SERS technology, as their design depends on the specific application. This comprehensive review highlights the recent trends and advancements in wearable plasmonic sensing technologies, focusing on their design, fabrication, and integration into practical wearable devices. Key innovations in material selection, such as the use of nanomaterials and flexible substrates, have significantly enhanced sensor performance and wearability. Moreover, we discuss challenges such as miniaturization, power consumption, and long-term stability, along with potential solutions to address these issues. Finally, the outlook for wearable plasmonic sensing technologies is presented, emphasizing the need for interdisciplinary research to drive the next generation of smart wearables capable of real-time health diagnostics, environmental monitoring, and beyond.
DVF-NET: Bi-Temporal Remote Sensing Image Registration Network Based on Displacement Vector Field Fusion
Authors: Xue Mingliang , Zhang Yiming , Jia Shucai , Cao Chong , Feng Lin , Liu Wanquan
Published: February 2025

Accurate image registration is essential for various remote sensing applications, particularly in multi-temporal image analysis. This paper introduces DVF-NET, a novel deep learning-based framework for dual-temporal remote sensing image registration. DVF-NET integrates two displacement vector fields to address nonlinear distortions caused by significant variations between images, enabling more precise image alignment. A key innovation of this method is the incorporation of a Structural Attention Module (SAT), which enhances the model’s ability to focus on structural features, improving the feature extraction process. Additionally, we propose a novel loss function design that combines multiple similarity metrics, ensuring more comprehensive supervision during training. Experimental results on various remote sensing datasets indicate that the proposed DVF-NET outperforms the existing methods in both accuracy and robustness, particularly when handling images with substantial geometric distortions such as tilted buildings. The results validate the effectiveness of our approach and highlight its potential for various remote sensing tasks, including change detection, land cover classification, and environmental monitoring. DVF-NET provides a promising direction for the advancement of remote sensing image registration techniques, offering both high precision and robustness in complex real-world scenarios.
Use of Smartphone-Based Experimental Data for the Calibration of Biodynamic Spring-Mass-Damper (SMD) Pedestrian Models
Authors: Bedon Chiara , Sciomenta Martina , Mazelli Alessandro
Published: February 2025

In practice, the structural analysis and design of pedestrian systems subjected to human-induced vibrations is often based on simplified biodynamic models that can be used in place of even more complex computational strategies to describe Human-Structure Interaction (HSI) phenomena. Among various walking features, the vertical reaction force that a pedestrian transfers to the supporting structure during motion is a key input for design, but results from the combination of multiple influencing parameters and dynamic interactions. Robust and practical strategies to support a realistic HSI description and analysis have hence been the object of several studies. Following earlier research efforts, this paper focuses on the optimised calibration of the input parameters for the consolidated Spring-Mass-Damper (SMD) biodynamic model, which reduces a single pedestrian to an equivalent SDOF (with body mass m, spring stiffness k, and viscous damping coefficient c) and is often used for vibration serviceability purposes. In the present study, this calibration process is carried out with smartphone-based acquisitions and experimental records from the Centre of Mass (CoM) of each pedestrian to possibly replace more complex laboratory configurations and devices. To verify the potential and accuracy of such a smartphone-based approach, different pedestrians/volunteers and substructures (i.e., a rigid concrete slab or a timber floor prototype) are taken into account, and a total of 145 original gaits are post-processed for SMD modelling purposes. The analysis of the experimental results shows a rather close match with previous findings in terms of key pedestrian parameters. This outcome poses the basis for a more generalised application of the smartphone-based strategy to a multitude of similar applications and configurations of practical interest. The validity of calibration output and its possible sensitivity are further assessed in terms of expected effects on substructures, with a critical discussion of the most important results.
Resilience in STEM: The Role of Well-Being Against Media’s Unrealistic Body Ideals
Authors: Gonta Iulia , Tripon Cristina
Published: February 2025

Despite the growing influence of social media on both professional and personal lives, there is a noticeable lack of research on media literacy related to the perception of body image. This study aims to fill that gap by exploring well-being and the factors that support it. The sample included 520 students from both STEM (science, technology, engineering, and mathematics) and non-STEM fields. We utilized adapted psychometric scales to measure attitudes towards physical appearance (SATAQ), body shape dissatisfaction (BSQ), and psychological well-being (PWB). The procedure involved assessing well-being and media exposure, and completing questionnaires designed to measure the impact of media exposure. The findings revealed that both STEM and non-STEM students with higher well-being reported significantly lower negative effects from exposure to idealized body images compared to those with lower well-being. Additionally, greater self-acceptance, a stronger sense of purpose in life, and better environmental mastery were associated with a lower negative impact on body image. Comparing the groups, STEM students exhibited higher resilience to the negative effects of idealized body images. These insights highlight key protective factors critical for developing interventions and strategies for student resilience.
Wood Gasification Biochar as an Effective Biosorbent for the Remediation of Organic Soil Pollutants
Authors: Loffredo Elisabetta , Denora Nicola , Vona Danilo , Gelsomino Antonio , Porfido Carlo , Colatorti Nicola
Published: February 2025

A biochar (BC) generated by the pyrogasification of wood chips from authorized forestry cuts was extensively characterized and evaluated for its efficacy in retaining/releasing two agrochemicals, namely the fungicide penconazole (PEN), the herbicide S-metolachlor (S-MET), and the xenoestrogen bisphenol A (BPA) widely present in industrial effluents. The elemental composition of BC was evaluated using CN elemental analysis and total reflection X-ray fluorescence (TXRF) spectroscopy which showed the abundance of elements typically found in BCs (Ca, K, P) along with essential trace elements such as Fe and Mn. Scanning electron microscopy coupled with energy-dispersive X-ray analysis (SEM-EDX) described the surface features of BC along with the major surface elements, while Brunauer–Emmett–Teller (BET) analysis revealed, as expected, a large specific surface area (366 m2 g−1). High porosity (0.07 cm3 g−1) was demonstrated by the density functional theory (DFT) method, while Fourier transform infrared (FT-IR) spectroscopy highlighted the presence of a prominent aromatic structure and the abundance of reactive functional groups responsible for the binding of the compounds. The sorption/desorption capacity of BC was studied by means of sorption kinetics and isotherms in batch trials, and by modeling the experimental data with various theoretical equations. All compounds reached sorption equilibrium on BC very rapidly, following preferentially pseudo-second-order kinetics. Freundlich adsorption constants of PEN, S-MET, and BPA were 37.3, 13.2, and 11.6 L g−1, respectively, thus demonstrating the great affinity of BC for hydrophobic pollutants. The adsorption process was hysteretic as only a small fraction of each compound was slowly desorbed from BC. The overall results obtained highlighted the great potential of BC of acting as a biosorbent of contaminants, which is of great importance for the containment of pollution in agricultural soils and for limiting the entry of toxic compounds into the human and animal food chain.
Impact of Land Use Dynamics on Ecological Sensitivity and Soil Erosion in Typical Ecological Restoration Areas of the Loess Plateau
Authors: Li Huajie , Zhao Binhua , Li Zhanbin , Ma Junjie , Gao Bei , Li Muyan
Published: February 2025

This study aims to explore the impact of land use changes on ecological sensitivity and soil erosion in the ecological restoration areas of the Loess Plateau in Yulin City, Shaanxi Province, China. By analyzing land use changes from 2014 to 2022 and integrating an ecological sensitivity assessment model, this study systematically evaluates the effects of different land use types on the regional ecological environment. An analysis of variance (ANOVA) and structural equation modeling (SEM) were employed to investigate significant differences in the effects of various land use types on ecological sensitivity and soil erosion. The results indicate the following: (1) Croplands and grasslands in the study area exhibit higher ecological sensitivity, and the risk of soil erosion has increased annually since 2022, especially when grasslands are converted into croplands, leading to a significant intensification of soil erosion. (2) Different land use types have significant differential impacts on ecological sensitivity and soil erosion. (3) The direct effect of land use changes on soil erosion is close to significance, and ecological sensitivity has a significant positive effect on soil erosion (path coefficient = 0.958, p-value < 0.001). This study also provides a new perspective for examining the relationship between ecological sensitivity and soil erosion. The findings demonstrate the importance of land use changes in explaining soil erosion, offering a theoretical basis for understanding the multivariate relationships within complex ecosystems.
Policy Adjustments: Their Dual Impacts and Sustainability Assessment on Heavy Metal Concentration in Topsoil of Nantong City, China
Authors: Xu Yuchen , Zheng Jianan , Cao Yuhan , Jiang Qingfeng
Published: February 2025

Soil heavy metal pollution has emerged as a substantial threat to environmental quality and human health. The pollution levels of heavy metals in soil are significantly influenced by human activities, rendering it one of the most crucial topics for the sustainable development of soils. This study analyzed the data of surface soil heavy metal concentration in Nantong from 2008 to 2018 to explore the impact of policy adjustments on concentration levels. The results revealed that over the past decade, the overall content of Pb in the topsoil of Nantong decreased by 32.41%, presumably attributed to the widespread use of unleaded petrol. This suggests that policy adjustments can effectively regulate heavy metal pollution levels. However, the average concentration of Cr increased by 68.03%, and the high-concentration center shifted from the southwestern to the northeastern part of Nantong. The large-scale relocation of factories from riverside to coastal areas in Nantong likely contributed to this phenomenon. Evidently, the changes in heavy metal concentration in surface soils clearly exhibited policy-driven characteristics. Therefore, it is recommended that when formulating or adjusting relevant policies, it is imperative to comprehensively consider their potential impacts on soil heavy metal contamination. This is crucial for ensuring the overall effectiveness of the policies in terms of the sustainability of the soil environment. This article provides valuable insights for understanding heavy metal accumulation in Nantong and offers guidance for promoting future industrial upgrading and strategic planning, which is of great significance in guiding the improvement in soil quality and ensuring its sustainable use.
Impact of Industrial Symbiotic Agglomeration on Energy Efficiency: Analysis Using Time-Varying Difference-in-Difference Model
Authors: Liu Jun , Shen Hengxu , Li Yuexing , Yin Tianci
Published: February 2025

Industrial symbiotic agglomeration (ISA) is a new type of circular spatial agglomeration that is favorable towards energy efficiency (EE) improvement. Based on the notion of ISA, this research explores the influence of ISA on EE: (i) This research explores the mechanism of ISA’s influence on EE from the viewpoints of recycling and green technology innovation, and verifies it via a mechanism test, based on the features of ISA. (ii) To quantify the whole factor EE, including undesirable output, and analyze its characteristics, we use the super efficiency slack-based model based on the undesirable output and the Malmquist–Luenberger index. (iii) By using the multi-time point differences-in-differences method (time-varying DID) for benchmark regression, it is found that ISA significantly improves EE, and the results are still significant after the endogenous test and robustness test. And (iv) from the perspective of urban resource endowment and geographical location, it was discovered that the influence of ISA on EE is stronger in non-resource-based cities than in resource-based cities, and that the impact is greater in western and central China than in eastern China.