bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Long-Term Influence of Proppant Optimization on the Production of Deep Shale Gas Fractured Horizontal Well
Authors: Chen Siyuan , Wei Shiming , Jin Yan , Xia Yang
Published: February 2025

As shale gas development gradually advances to a deeper level, the economic exploitation of deep shale gas has become one of the key technologies for sustainable development. Large-scale, long-term and effective hydraulic fracturing fracture networks are the core technology for achieving economic exploitation of deep shale gas. Due to the high-pressure and high-temperature characteristics of deep shale gas reservoirs, traditional seepage models cannot effectively simulate gas flow in such environments. Therefore, this paper constructs a fluid–solid–thermal coupling model, considering the creep characteristics of deep shale, the effects of proppant embedment and deformation on fracture closure, and deeply analyzes the effects of proppant parameters on the shale gas production process. The results show that factors such as proppant concentration, placement, mechanical properties and particle size have a significant effect on fracture width, fracture surface seepage characteristics and final gas production. Specifically, an increase in proppant concentration can expand the fracture width but has limited effect on increasing gas production; uneven proppant placement will significantly reduce the fracture conductivity, resulting in a significant decrease in gas production; proppants with smaller sizes are more suitable for deep shale gas fracturing construction, which not only reduces construction costs but also improves gas seepage capacity. This study provides theoretical guidance for proppant optimization in deep shale gas fracturing construction.
Lateral Displacement and Distance of Vehicles in Freeway Overtaking Scenario Based on Naturalistic Driving Data
Authors: Pan Cunshu , Zhang Yuhao , Zhang Heshan , Xu Jin
Published: February 2025

The design of passenger-dedicated lane width is essential for freeway reconstruction and expansion projects. However, the technical standard of lane width established in China is based on trucks. This study aims to propose a passenger-dedicated lane width calculation method for freeways based on overtaking behavior. Computer vision technology was used to extract vehicle trajectories and dimensions from videos captured by an unmanned aerial vehicle (UAV). Statistical methods such as cumulative frequency statistics, typical percentile statistics and regression analysis were employed to elaborate on the lateral displacement and distance of vehicles during overtaking. The results show that vehicles’ lateral displacements are mainly related to behaviors such as lane changing, lateral distance maintenance and lane keeping. The body width sum of parallel vehicles has little effect on the geometric center distance but significantly reduces the wheel distance when increasing. The general value of the passenger-dedicated lane width on freeways is recommended to be 3.5 m, and the limit value is 3.25 m. Compared with existing lane width calculation methods, this study pays more attention to the relationship between vehicle width and lateral distance, which can better cope with the challenges caused by vehicle diversity in lane width design.
The Influence of Ultraviolet Radiation, Ozonation, and Ultrasonic Field on the Effectiveness of Dye Removal from Aqueous Solutions
Authors: Kida Małgorzata , Ziembowicz Sabina
Published: February 2025

This study presents an analysis of the effectiveness of the removal of three dyes, Indigo Carmine, Tartrazine, and Allura Red AC, using advanced oxidation methods. The research showed low efficiency in removing these dyes using acoustic waves. Neither the addition of hydrogen peroxide to assist the process nor increasing the intensity of the acoustic waves improved the degradation of the analyzed dyes. However, when ozone was applied, a 91% removal efficiency of Indigo Carmine was achieved after 30 min, while the other two dyes were resistant to degradation by ozone. The introduction of an additional amount of oxidant in the form of hydrogen peroxide and waste catalyst (steel shavings) resulted in an increased efficiency of removing all dyes and a shortening of the degradation process time. Ultraviolet radiation in the presence of a TiO2 catalyst was also effective only for Indigo Carmine. After 30 min, the removal efficiency of this dye reached 95%. It was also demonstrated that the catalyst dose affected the rate constant of the reaction. Kinetic studies revealed that the degradation of Indigo Carmine in an aqueous solution through advanced oxidation processes followed the first-order reaction kinetics. Energy demand calculations confirmed that the most effective Indigo Carmine removal process is the one using ozone with the addition of a catalyst and an oxidizer at pH = 3.
Experimental Study of a Novel Prototype of Dual-Cycle Two-Phase Cooling System for a Data Cabinet
Authors: Cheng Hao , Yang Tongzhi , Zhao Yifan , Wang Leixin , Yuan Weixing , Ren Kexian
Published: February 2025

As Information Technology continues to rapidly evolve, the scale and energy consumption of data centers have seen a significant surge. Traditional air-cooling systems in data centers are notably energy intensive. This study proposes an innovative dual-cycle two-phase cooling system (DTCS) for retrofitting existing server cabinets. The system integrates the two synergistic subsystems of a pump-driven chip-level two-phase cooling system (PCTCS) and a pump-driven backplane-level two-phase cooling system (PBTCS). The PCTCS provides year-round natural cooling of high-power chips, and experimental results indicate that even under extreme outdoor conditions of up to 42 °C, the PCTCS can maintain the chip temperature at 76 °C. At the same time, the PBTCS effectively cools all components in the cabinet except the high-power chips. By efficiently controlling the chip temperature through the PCTCS, the novel DTCS ensures stable operation at data room temperatures up to 33 °C, thereby significantly reducing the energy consumption of the cooling system. The average annual pPUE of the cooling system is 1.078 at the test site in Xiangyang, Hubei province in China. The DTCS could perform well across various Chinese cities even under severe hot and moist conditions, with the average annual pPUE consistently below 1.1.
Towards a Heat-Resistant Tethered Micro-Aerial Vehicle for Structure Fire Sensing
Authors: Aláez Daniel , Prieto Manuel , Villadangos Jesús , Astrain José Javier
Published: February 2025

The collapse of structures during firefighter intervention is one of the greatest risks that firefighters must face when entering buildings. To reduce these risks, situational awareness is key. Although many advances have already been developed in wildland and outdoor fires, there is still room for improvement in structure fires. The development of a heat-resistant micro-aerial vehicle for indoor fires poses a series of challenges such as component cooling, battery management, and protection from impacts. In this paper, a heat-resistant tethered micro-aerial vehicle is designed, modeled through thermal analysis, and successfully tested in real-world conditions. This platform has been equipped with a micro-sized thermal sensing camera and first-person-view (FPV) camera, optimized for thermal management, to allow for situational awareness in structure fires.
Scaling Torsional Drilling Vibrations: A Simulation-Based Comparison of Downscale and Upscale Drill Strings Under Varying Torque Conditions
Authors: Ejike Chinedu , Abid Khizar , Teodoriu Catalin
Published: February 2025

Torsional vibrations pose a serious challenge in drilling operations and can lead to effects such as stick-slip phenomena, tool wear, and reduced drilling efficiency. While previous research has been conducted on torsional vibrations, there is a notable gap in comparative studies that assess the scalability of downscale models to real-world drilling conditions. This study fills this gap by systematically comparing torsional vibrations in downscale and upscale drill strings under different torque conditions at three different depths, shedding light on scaling effects in drilling vibrations. Numerical simulation was carried out taking into account non-linear interactions, damping effects, and torque variations. The laboratory set-up was for a well length of 15 m and was geometrically scaled to represent an upscale well of 450 m. Certain operational parameters such as rotation speed, torque, density, and friction coefficients were modified to keep realistic dynamic behavior, and all models were run at an identical speed of rotation to enforce consistency. The results show that both the upscale and downscale models exhibited stick-slip behavior, but differences in vibration intensity and stabilization trends point out how scaling affects torsional dynamics. Notably, the upscale bit first faced higher torsional oscillation than the set rotation speed after overcoming stick-slip before stabilizing, whereas the downscale bit went through prolonged stick-slip instability before synchronization. This study enhances the understanding of scaling effects in torsional drilling vibrations, offering a foundation for optimizing experimental setups and improving predictive modeling in drilling operations.
Study on Flow and Settlement Performance Evaluation and Optimization of Coal Gangue Slurry Filling Material Based on Fractal Gradation
Authors: Shao Xiaoping , Wang Wei , Zhao Bingchao , Ning Jianbo , Wang Zhengchun , Zhang Yibo , Du Xing , Tang Renlong
Published: February 2025

Coal gangue slurry filling technology is an effective way of utilizing coal gangue solid waste resources rationally, and its fluidity and sedimentation behavior have an essential influence on filling performance. However, evaluation and optimization methods for the fluidity and sedimentation performance of coal gangue slurry filling materials (CSFMs) are still scarce. In order to solve this problem, based on the fractal grading theory, this paper carried out an experimental study on the influence of the fractal dimension on the flow characteristics of CSFMs, revealed the impact of the fractal dimension on the flow performance of slurry, and constructed a CSFM flow performance evaluation and optimization model based on the fractal dimension. At the same time, the influence of the fractal dimension on solid mass fraction and particle distribution in the CSFM sedimentation process was analyzed using a sedimentation experiment. Combined with fitting analysis and model construction, a CSFM sedimentation performance evaluation method based on fractal dimension D was proposed. The results show that (1) the slump, expansion, and yield stress of CSFMs increased first and then decreased with the increase in the fractal dimension, and the bleeding rate of CSFMs decreased with the rise in the fractal dimension. The analysis of the consistency coefficient of CSFMs shows that the increase in the proportion of fine particles will increase the consistency coefficient. (2) The fitting analysis indicates that the fractal dimension D of CSFMs is negatively correlated with the sedimentation performance PS. The change in D is most significant in the range of 2.3 to 2.4, where the slurry’s stability is poor. When D exceeds 2.5, the slurry’s stability improves significantly. (3) Based on the evaluation of flow performance and settlement performance, the flow performance and settlement performance of CSFMs with fractal dimensions between 2.50 and 2.59 achieve the best balance, which ensures the reliability of long-distance transportation and construction quality. The research results can provide a reference for the pipeline transportation of whole gangue slurry and have important practical significance for realizing the large-scale disposal of gangue solid waste and green mining of coal mines.
Refactoring for Java-Structured Concurrency
Authors: Zhang Yang , Shen Gaojie , Zhang Liyan , Zheng Meiyan , Zheng Kun
Published: February 2025

Structured concurrency treats multiple tasks running in different threads as a single unit, thereby improving reliability and enhancing observability. The existing IDE (Integrated Development Environment) does not provide sufficient support to leverage such an advanced structure and conduct refactoring automatically. Manual refactoring is tedious and error prone. There is an urgent need to provide adequate support to perform automatic refactoring. To this end, this paper proposes ReStruct, an automatic refactoring approach to transform unstructured concurrency to structured concurrency. ReStruct first employs visitor pattern analysis to acquire the target code for refactoring and then performs a precondition to filter out the code that meets the refactoring criteria. Subsequently, it performs scope analysis to guide the refactoring process. Finally, ReStruct performs refactoring on the AST of the source program. ReStruct is implemented as an Eclipse plugin and is evaluated in seven real-world projects via the number of refactorings and changes to LOCs (lines of code), time, and performance after refactoring. The experimental results illustrate that a total of 82 unstructured codes are refactored, with an average of 27.3 s per project. Furthermore, the performances of these refactored projects are improved by an average of 6.5%, demonstrating its effectiveness.
Predicting the Unsaturated Hydraulic Conductivity of Compacted Polyurethane–Clay Using the Filter Paper Method
Authors: Adajar Mary Ann , Frianeza Cielo
Published: February 2025

Sanitary landfill covers are exposed to varying environmental conditions; hence, the state of the clay layer also changes from saturated to unsaturated. The study aimed to predict the unsaturated hydraulic conductivity of the locally available compacted clay and clay with polyurethane to determine their behavior as they change from wet to dry using matric suction and empirical models proposed through other studies. The specimens underwent three wet–dry cycles wherein the matric suction was determined for several moisture content levels as the specimen dried using the filter paper method or ASTM D5298. The results showed that the factors affecting the soil structure, such as grain size difference between clay and polyurethane–clay, varying initial void ratios, and degradation of the soil structure due to the wet–dry cycles, did not affect the matric suction at the higher suction range; however, these factors had an effect at the lower suction range. The matric suction obtained was then used to establish the best fit water retention curve (WRC) or the relationship between the matric suction and moisture content. The WRC was used to predict the unsaturated hydraulic conductivity and observe the soil–water interaction. The study also observed that the predicted unsaturated hydraulic conductivity decreases as the compacted specimen moves to a drier state.
Augmented Reality’s Impact in Industry—A Scoping Review
Authors: Fernández-Moyano Jon A. , Remolar Inmaculada , Gómez-Cambronero Águeda
Published: February 2025

This scoping review investigates the integration of augmented reality within Industry 4.0 and Industry 5.0, focusing on its applications across various industrial sectors. The study analyzes 74 relevant articles published since 2014, coinciding with the emergence of Industry 4.0. Since the introduction of the Industry 5.0 concept in 2021, there has been a noticeable increase in publications, reflecting a shift toward applications that prioritize personalization, sustainability, and human-centric innovations. The findings highlight the versatility of augmented reality in enhancing productivity, efficiency, safety, and work quality across industries such as robotics, automotive, education, and construction. However, the implementation of artificial intelligence within augmented reality applications remains limited, revealing a significant opportunity for future research to optimize their integration and functionality. The review emphasizes the importance of developing augmented reality solutions tailored to specific industrial needs, aligned with the principles of Industry 5.0, and leveraging versatile, cost-effective hardware like mobile devices and smartglasses to ensure accessibility and scalability.
Enhancing Small Language Models for Graph Tasks Through Graph Encoder Integration
Authors: Oh Dongryul , Kang Sujin , Kim Heejin , Oh Dongsuk
Published: February 2025

Small language models (SLMs) are increasingly utilized for on-device applications due to their ability to ensure user privacy, reduce inference latency, and operate independently of cloud infrastructure. However, their performance is often limited when processing complex data structures such as graphs, which are ubiquitous in real-world datasets like social networks and system interactions. Graphs inherently encode intricate structural dependencies, requiring models to effectively capture both local and global relationships. Traditional language models, designed primarily for text data, struggle to address these requirements, leading to suboptimal performance in graph-related tasks. To overcome this limitation, we propose a novel graph encoder-based prompt tuning framework which integrates a graph convolutional network (GCN) with a graph transformer. By leveraging the complementary strengths of the GCN for local structural modeling and the graph transformer for capturing global relationships, our method enables SLMs to effectively process graph data. This integration significantly enhances the ability of SLMs to handle graph-centric tasks while maintaining the efficiency required for resource-constrained devices. The experimental results show that our approach not only improves the performance of SLMs on various graph benchmarks but also achieves results which closely approach the performance of a large language model (LLM). This work highlights the potential of extending SLMs for graph-based applications and advancing the capabilities of on-device artificial intelligence.
Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management
Authors: Nomura Yusuke , Liu Ziang , Nishi Tatsushi
Published: February 2025

Perishable goods have a limited shelf life, and inventory should be discarded once it exceeds its shelf life. Finding optimal inventory management policies is essential since inefficient policies can lead to increased waste and higher costs. While many previous studies assume the perishable inventory is processed following the First In, First Out rule, it does not reflect customer purchasing behavior. In practice, customers’ preferences are influenced by the shelf life and price of products. This study optimizes inventory and pricing policies for a perishable inventory management problem considering age-dependent probabilistic demand. However, introducing dynamic pricing significantly increases the complexity of the problem. To tackle this challenge, we propose eliminating irrational actions in dynamic programming without sacrificing optimality. To solve this problem more efficiently, we also implement a deep reinforcement learning algorithm, proximal policy optimization, to solve this problem. The results show that dynamic programming with action reduction achieved an average of 63.1% reduction in computation time compared to vanilla dynamic programming. In most cases, proximal policy optimization achieved an optimality gap of less than 10%. Sensitivity analysis of the demand model revealed a negative correlation between customer sensitivity to shelf lives or prices and total profits.
Optimal Seismic Retrofit Alternative for Shear Deficient RC Beams: A Multiple Criteria Decision-Making Approach
Authors: Villalba Paola , Guaygua Byron , Yepes Víctor
Published: February 2025

The vulnerability of existing buildings to recent earthquakes underscores the critical need to explore effective retrofit solutions thoroughly. This study presents a comprehensive methodology for ranking seismic retrofit alternatives for reinforced concrete beams with shear deficiencies. It evaluates five alternatives to ensure a 50-year service life, meeting current seismic standards and incorporating specific preventive maintenance measures for each option. A cradle-to-grave life cycle assessment was used to analyze the impacts associated with the sustainability of each alternative. Hybridization of emerging multi-criteria decision-making methods was applied for criteria weighting and final ranking, and a hierarchical model including economic, environmental, social, and functional criteria was developed. The results highlight carbon fiber reinforcements and steel plates with epoxy adhesives as optimal solutions due to their lower environmental and social impact, along with improvements in execution time and minimal architectural impact. This study underscores the necessity of a comprehensive approach to identifying optimal retrofitting alternatives, demonstrating the imperative to complement the conventional structural engineering objective of ensuring safety while minimizing investment.
Performance Analysis of Scandium-Doped Aluminum Nitride-Based PMUTs Under High-Temperature Conditions
Authors: Lyu Haochen , Safari Ahmad
Published: February 2025

PMUTs have been widely studied in recent years, particularly those based on the SOI (silicon-on-insulator) process, which have been partially commercialized and are extensively used in advanced applications such as ultrasonic ranging and spatial positioning. However, there has been little research on their high-temperature reliability, a critical area for their use in extreme environmental conditions. In this study, we investigate the high-temperature characteristics of air-coupled PMUTs based on SOI under various structural conditions, employing both finite element analysis (FEA) and experimental validation. We assess the performance of PMUTs at elevated temperatures by examining key parameters such as resonant frequency, the electromechanical coupling coefficient, mechanical amplitude, and warpage, all analyzed as functions of temperature. The experimental results show that temperature-induced drift becomes more significant as the back cavity size increases and the top silicon layer thickness decreases. These findings are consistent with the trends observed in the finite element analysis. Specifically, a PMUT with a back cavity diameter of 1000 μm and a top silicon thickness of 4 μm exhibits a temperature drift rate of up to 47.3% when the operating temperature rises from room temperature to 200 °C. Furthermore, at elevated temperatures, the maximum electromechanical coupling coefficient improves by 68.6%, and the mechanical amplitude increases by 66.1%. Heating experiments using a 3D profiler reveal that warpage increases from 0.3 μm to 2.15 μm as the temperature reaches 150 °C. These findings offer important theoretical insights into the temperature-induced drift behavior of PMUTs under high-temperature conditions. This study provides a comprehensive understanding of the performance variations of PMUTs, including changes in electromechanical coupling, mechanical amplitude, and structural warpage, which are critical for their reliable operation in extreme environments. The results presented here can serve as a foundation for the design and optimization of PMUTs in applications that require high-temperature stability, ensuring their enhanced reliability and performance in such demanding conditions.
Application of Quantum Key Distribution to Enhance Data Security in Agrotechnical Monitoring Systems Using UAVs
Authors: Bakyt Makhabbat , La Spada Luigi , Zeeshan Nida , Moldamurat Khuralay , Atanov Sabyrzhan
Published: February 2025

Ensuring secure data transmission in agrotechnical monitoring systems using unmanned aerial vehicles (UAVs) is critical due to increasing cyber threats, particularly with the advent of quantum computing. This study proposes the integration of Quantum Key Distribution (QKD), based on the BB84 protocol, as a secure key management mechanism to enhance data security in UAV-based geographic information systems (GIS) for monitoring agricultural fields and forest fires. QKD is not an encryption algorithm but a secure key distribution protocol that provides information-theoretic security by leveraging the principles of quantum mechanics. Rather than replacing traditional encryption methods, QKD complements them by ensuring the secure generation and distribution of encryption keys, while AES-128 is employed for efficient data encryption. The QKD framework is optimized for real-time operations through adaptive key generation and energy-efficient hardware, alongside Lempel–Ziv–Welch (LZW) compression to improve the bandwidth efficiency. The simulation results demonstrate that the proposed system achieves secure key generation rates up to 50 Mbps with minimal computational overhead, maintaining reliability even under adverse environmental conditions. This hybrid approach significantly improves data resilience against both quantum and classical cyber-attacks, offering a comprehensive and robust solution for secure agrotechnical data transmission.
Performance Analysis of Solar Collector Integrated with Porous Metallic Foam
Authors: Kulkarni Vismay , Kashyap Abhishek Singh , Pal Mayur , Tyagi Himanshu
Published: February 2025

The use of solar energy is a promising solution to reduce dependence on fossil fuels. Flat-plate collectors (FPCs) are commonly employed to harness solar energy, but their performance is often limited by thermal resistance, surface deterioration, and inefficient heat dissipation. This study investigates the performance enhancement of an FPC integrated with porous copper foam through numerical simulations. The porous foam increases surface area and improves heat transfer by creating a complex flow path for the working fluid. Key parameters such as the porous foam height ratio (S), Darcy number (Da), and volumetric flow rate (V˙) are analysed to determine their impact on thermal performance. The results indicate that a maximum Nusselt number (Nu) of 28.85 and an outlet temperature of 306.81 K is obtained for S = 1. A decrease in Da from 10−2 to 10−6 and an increase in V˙ from 0.25 L/min to 1 L/min enhance the Nu by 5.7% and 8.8%, respectively. The friction factor (f) increases with increases in S, a decrease in Da and an increase in V˙. The performance evaluation criteria (PEC) are obtained to be maximum at S = 0.4, Da = 10−2 and V˙ = 0.25 L/min. These findings demonstrate the potential of porous copper foam in improving FPC efficiency.
Land Cover Changes and Land Surface Temperature Dynamics in the Rohingya Refugee Area, Cox Bazar, Bangladesh: An Analysis from 2013 to 2024
Authors: Karmakar Sourav , Rahman Mizanur , Meng Lei
Published: February 2025

The rapid expansion of refugee settlements has caused significant environmental changes, particularly in regions experiencing forced displacement. The Rohingya refugee crisis in Cox’s Bazar, Bangladesh, has led to extensive deforestation and land transformation, affecting local climate conditions. While urbanization’s impact on land surface temperature (LST) is well-documented, the environmental consequences of unplanned refugee settlements remain understudied. This study investigates land cover changes and LST dynamics from 2013 to 2024, offering a novel perspective on refugee-induced environmental changes. Using Landsat 8 imagery, four key land cover categories (built-up, mixed forest, water bodies, and barren land) were classified through a Support Vector Machine (SVM) approach. The temporal change in these key land cover categories was examined. The surface temperature product (Band 10) from Landsat 8 Collection 2 Level 2 (C2 L2) was applied to derive LST, while Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI) were used to assess vegetation and urbanization trends. Findings reveal a 97% decline in forest cover and a 161.78% increase in built-up areas between 2013 and 2018, leading to substantial LST increases. Statistical analyses confirm strong correlations between LST and multispectral indices, with vegetation and water bodies acting as cooling agents, while urban areas amplify heat stress. This study underscores the urgent need for sustainable land management and reforestation efforts to mitigate environmental degradation. It also highlights the importance of global cooperation in balancing humanitarian needs with environmental sustainability, providing insights for policymakers and urban planners to enhance climate resilience in vulnerable regions.
IAEA Safety Guides vs. Actual Challenges for Design and Conduct of Indoor Radon Surveys
Authors: Tsapalov Andrey , Kovler Konstantin , Kiselev Sergey , Yarmoshenko Ilia , Bobkier Robert , Miklyaev Petr
Published: February 2025

An analysis of the international radon regulatory framework identified actual challenges for the design and conduct of indoor radon surveys, though there is little discussion on this issue in the radon community. The main challenges hindering the development of radon regulation on an international scale, particularly in indoor radon surveys include the following: (i) responsibility for indoor radon testing and mitigation, (ii) excessive focus on Radon Priority Areas, (iii) the role of temporal uncertainty in indoor radon testing, (iv) the standardization of indoor radon measurements, and (v) the standardization of thoron EEC measurements and indoor testing. To address these gaps and inconsistencies, actual needs for design and conduct of indoor radon surveys are proposed, covering the aforementioned challenges. The needs statement, including a discussion of solutions, addresses the following key aspects of radon regulation: (1) legislation, (2) radon measurements, (3) awareness, and (4) building protection. The focus remains on the radon measurement aspect, detailing the strategy and tools for conducting indoor radon surveys within a rational approach. This includes the main research activities necessary for the sustainable development of global radon regulation. The final part of the article presents a Rational Method (protocol) of indoor radon measurements serving as a detailed guideline for standardizing indoor radon testing at the international level. This ensures the decision-making reliability of at least 95% and harmonizes relevant national approaches considering traditional measurement protocols using both short-term and long-term measurements. The proposed solutions aim to achieve the goal of a modern design and conduct of indoor radon surveys that are consistent with large-scale (mass) testing and effectively identify hazardous buildings. These solutions are based on a rational approach with convenient tools and active voluntary participation of the population to be implemented within the framework of national radon regulation.
Isoprene Emissions, Oxidation Chemistry and Environmental Impacts
Authors: Khan M. Anwar H. , Holland Rayne , Mould Charlotte , Bacak Asan , Percival Carl J. , Shallcross Dudley E.
Published: February 2025

Isoprene emissions can affect the oxidizing capacity of the atmosphere and are likely to increase with an increase in the world’s biomass. The emission of isoprene is strongest in tropical forested regions, suggesting a major portion of tropospheric chemistry occurs in the tropics. As well as deforestation and reforestation having a direct impact on the world’s climate through land cover, there is also an indirect environmental impact (e.g., global warming, air pollution) through the resulting change in isoprene emissions. Previously, incomplete understanding of isoprene oxidation chemistry caused a model-measurement breakdown for concentrations of HOx radicals observed over certain low-NOx regions, such as the pristine Amazon rainforest. Over the last decade, however, understanding of isoprene oxidation chemistry has been vastly improved. Numerous research studies have provided evidence for the involvement of 1,6-H and 1,5-H shift reactions in the isoprene oxidation mechanism, which increases the level of HOx recycling that occurs. As well as helping to reduce the model-measurement breakdown observed, the updated isoprene oxidation mechanism affects the tropospheric burdens of other species, including carbon monoxide (CO), methane (CH4), ozone (O3), organic peroxides (ROOH), secondary organic aerosol (SOA), and organic nitrates (RONO2). There are still gaps in the understanding of the impacts and oxidation chemistry of isoprene emissions, which this literature review identifies and discusses. In the future, there is still much scope for further research, including modeling future reforestation scenarios with isoprene emissions and their impacts on both global and regional scales.
Temporal Profiles of Volatile Organic Compounds near the Houston Ship Channel, Texas
Authors: Guagenti Meghan , Shrestha Sujan , Mehra Manisha , Yoon Subin , Ramirez Mackenzie T. S. , Flynn James H. , Usenko Sascha
Published: February 2025

Houston, Texas, with its large-scale industrial activities, serves as a national hub for petrochemical processing and chemical feedstock production, making it a unique emission region for volatile organic compounds (VOCs) and production-related emissions. These emissions can be associated with industrial activities, including solvent usage and production to manufacture consumer products such as volatile chemical products. To support the Houston-based Dept. of Energy’s Atmospheric Measurement Radiation program-led Tracking Aerosol Convection ExpeRiment (TRACER) projects, VOCs were measured at the San Jacinto Battleground State Historic Site during September 2021 and 2022. The observed VOC mixing ratios reveal unique emission signatures for select VOCs, including benzene, toluene, acetone, and isoprene. Routine nighttime enhancements of these compounds exceeded the urban background, with mixing ratios increasing by up to 20 ppbv per hour and persisting for up to 6 h, suggesting that emissions from local industrial activities near the Houston Ship Channel (HSC) are impacting the site. For example, mixing ratios exceeding 15 ppbv for at least one VOC were observed on 58% of nights (n = 32 nights), with 19 nights (~35%) having two or more VOCs with mixing ratios above 15 ppbv. For select peak emission events, the NOAA dispersion model estimated plume transport across parts of the urban system, suggesting that VOCs from the HSC may impact local air quality. This study highlights the importance of VOC-related emissions from industrial production and supply chains in contributing to total VOC emissions in urban areas like Houston, Texas.
Assessing AgERA5 and MERRA-2 Global Climate Datasets for Small-Scale Agricultural Applications
Authors: Soulis Konstantinos , Dosiadis Evangelos , Nikitakis Evangelos , Charalambopoulos Ioannis , Kairis Orestis , Katsogiannou Aikaterini , Palli Gravani Stergia , Kalivas Dionissios
Published: February 2025

AgERA5 (ECMWF) is a relatively new climate dataset specifically designed for agricultural applications. MERRA-2 (NASA) is also used in agricultural applications; however, it was not specifically designed for this purpose. Despite the proven value of these datasets in assessing global climate patterns, their effectiveness in small-scale agricultural contexts remains unclear. This research aims to fill this gap by assessing the suitability and performance of AgERA5 and MERRA-2 in precision irrigation management, which is crucial for regions with limited ground data availability. The wine-making region of Nemea, Greece, with its complex and challenging terrain is used as a characteristic case study. The datasets are assessed for key weather variables and for irrigation planning, using detailed local meteorological station data as a reference. The results reveal that both products have serious limitations in small scale irrigation scheduling applications in contrast to what was reported in previous studies for other regions. The uneven performance of global datasets in different regions due to lack of sufficient observation data for reanalysis data calibration was also indicated. Comparing the two datasets, AgERA5 outperforms MERRA-2, especially in precipitation and reference evapotranspiration. MERRA-2 shows comparable potential in irrigation planning, as it occasionally matches or exceeds AgERA5’s performance. The study findings underscore the importance of evaluating metanalysis datasets in the application area before their use for precision agriculture, particularly in regions with complex topography.
Exponential Stability for a Degenerate/Singular Beam-Type Equation in Non-Divergence Form
Authors: Akil Mohammad , Fragnelli Genni , Sbai Amine
Published: February 2025

The paper deals with the stability of a degenerate/singular beam equation in non-divergence form. In particular, we assume that the degeneracy and the singularity are at the same boundary point and we impose clamped conditions where the degeneracy occurs and dissipative conditions at the other endpoint. Using the energy method, we provide some conditions to obtain the stability for the considered problem.
The Calculus of Names—The Legacy of Jan Łukasiewicz
Authors: Pietruszczak Andrzej
Published: February 2025

With his research on Aristotle’s syllogistic, Jan Łukasiewicz initiates the branch of logic known as the calculus of names. This field deals with axiomatic systems that analyse various fragments of the logic of names, i.e., that branch of logic that studies various forms of names and functors acting on them, as well as logical relationships between sentences in which these names and functors occur. In this work, we want not only to present the genesis of the calculus of names and its first system created by Łukasiewicz, but we also want to deliver systems that extend the first. In this work, we will also show that, from the point of view of modern logic, Łukasiewicz’s approach to the syllogistic is not the only possible one. However, this does not diminish Łukasiewicz’s role in the study of syllogism. We believe that the calculus of names is undoubtedly the legacy of Łukasiewicz.
A Web-Based Platform for Hand Rehabilitation Assessment
Authors: Soumis Dimitrios N. , Tselikas Nikolaos D.
Published: February 2025

Hand impairment affects millions of people. There are multiple factors that cause deficits, varying from physical injuries to neurological disorders. Upper-limb patients face significant difficulties in daily life. Rehabilitation aims at supporting them to regain functionality and increasing their independence and quality of life. Assessment is key to therapy, as it offers an evaluation of the condition of patients, leading to suitable treatments. Unfortunately, rehabilitation relies on clinical resources, making it expensive and time-consuming. Digital technology can provide solutions that make treatments more flexible and affordable. With the use of computer vision, we created an online platform that includes several exercises and serious games, based on movements and gestures performed in real-world treatments. Difficulty levels vary, and therapists can monitor these procedures remotely, while performance can be stored and tracked over time, identifying improvement. There is no need for any special equipment, as the platform can be accessed like a common website and all its applications require only a simple computer camera and stable Internet connection. In this article, we present our research approach, we analyze the development of the platform, and we provide a brief demonstration of its use in practice. Furthermore, we address some technical challenges and we share the results derived from preliminary test phases, concluding by outlining future plans.
Correction: Pettenuzzo et al. Mechanical Behaviour of Plantar Adipose Tissue: From Experimental Tests to Constitutive Analysis. Bioengineering 2024, 11, 42
Authors: Pettenuzzo Sofia , Belluzzi Elisa , Pozzuoli Assunta , Macchi Veronica , Porzionato Andrea , Boscolo-Berto Rafael , Ruggieri Pietro , Berardo Alice , Carniel Emanuele Luigi , Fontanella Chiara Giulia
Published: February 2025

In the original publication [...]
Neural Network-Based Mammography Analysis: Augmentation Techniques for Enhanced Cancer Diagnosis—A Review
Authors: Blahová Linda , Kostolný Jozef , Cimrák Ivan
Published: February 2025

Application of machine learning techniques in breast cancer detection has significantly advanced due to the availability of annotated mammography datasets. This paper provides a review of mammography studies using key datasets such as CBIS-DDSM, VinDr-Mammo, and CSAW-CC, which play a critical role in training classification and detection models. The analysis of the studies produces a set of data augmentation techniques in mammography, and their impact and performance improvements in detecting abnormalities in breast tissue are studied. The study discusses the challenges of dataset imbalances and presents methods to address this issue, like synthetic data generation and GAN augmentation as potential solutions. The work underscores the importance of dataset design dedicated for experiments, detailed annotations, and the usage of machine learning models and architectures in improving breast cancer screening models, with a focus on BI-RADS classification. Future directions include refining augmentation methods, addressing class imbalance, and enhancing model interpretability through tools like Grad-CAM.
Immunohistochemical Evaluation of Bone Remodeling Following Compressive Force on Mandibular Condyle
Authors: Lyros Ioannis , Tsolakis Ioannis A. , Kotantoula Georgia , Tosios Konstantinos , George Vilaras , Nikitakis Nikolaos , Ferdianakis Efstratios , Lykogeorgos Theodoros , Fora Eleni , Tsolakis Apostolos I.
Published: February 2025

Excessive mandibular growth is largely affected by genetic factors and its orthodontic management is challenging. The present study utilized histophotometry and aimed to investigate immunohistochemical alterations in rat condyles following posterior mandibular displacement using a fixed intraoral functional appliance. Seventy-two male Wistar rats were divided into two equal groups, experimental and control, each consisting of three equal subgroups. The animals were sacrificed after 30, 60, and 90 days, and their condyles were isolated and examined microscopically for potential immunohistochemical changes. Statistically significant differences in RANKL appeared at days 30 and 60, while noteworthy changes regarding TRAP were evidenced at days 30 and 90. In the experimental group, RANKL decreased statistically significantly between days 60 and 90, while in the control group, the RANKL measured significantly increased at day 90 compared to days 30 and 60 alike. In the experimental group, TRAP appeared significantly decreased at day 60 vs. 30, while at day 90 vs. 60, it was found to be significantly increased. In the control group, there were no significant changes in TRAP. Posterior mandibular displacement may cause immunohistochemical changes in the rat condylar bone, and such outcomes should be considered when planning similar procedures in humans.
VPS25 Promotes an Immunosuppressive Microenvironment in Head and Neck Squamous Cell Carcinoma
Authors: Chen Li-Guo , Fang Yu-Han , Wang Kui-Ming , Zhang Wei , Chen Gang
Published: February 2025

The ESCRT (endosomal sorting complex required for transport) machinery is essential for various cellular processes, yet its role in head and neck squamous cell carcinoma (HNSCC) is poorly understood. We utilized The Cancer Genome Atlas (TCGA) datasets to analyze the expression of ESCRT genes. Bulk RNA-sequencing data and HNSCC tissue microarrays (TMAs) were used to evaluate VPS25 expression and its clinical significance. Single-cell RNA sequencing of tumor tissues and VPS25 knockdown experiments in CAL27 cells were used to investigate its biological functions. Immunohistochemistry, spatial transcriptomics, and immunotherapy datasets highlighted the involvement of VPS25 in immune suppression and its potential as a predictive biomarker. The results demonstrated significant VPS25 overexpression in HNSCC tissues, which correlated with poor clinical outcomes. It promoted tumor cell proliferation and migration while reducing immune cell infiltration in the tumor microenvironment (TME). Additionally, by upregulating PVR expression in tumor cells, VPS25 activated the immunosuppressive PVR-TIGIT signaling axis, thereby facilitating immune evasion. Furthermore, VPS25 emerged as a potential biomarker for predicting immunotherapy response. These findings highlight VPS25 as a pivotal regulator of tumor progression and immune evasion in HNSCC and a promising target for therapeutic strategies.
FOP: From Biomolecules to Hope
Authors: Kaplan Frederick S. , Pignolo Robert J.
Published: February 2025

In the introduction to his 1970 textbook BIOCHEMISTRY, Albert Lehninger wrote “Living things are composed of lifeless molecules [...]
Sensory Dysfunction in ALS and Other Motor Neuron Diseases: Clinical Relevance, Histopathology, Neurophysiology, and Insights from Neuroimaging
Authors: Kleinerova Jana , Chipika Rangariroyashe H. , Tan Ee Ling , Yunusova Yana , Marchand-Pauvert Véronique , Kassubek Jan , Pradat Pierre-Francois , Bede Peter
Published: February 2025

Background: The clinical profiles of MNDs are dominated by inexorable motor decline, but subclinical proprioceptive, nociceptive and somatosensory deficits may also exacerbate mobility, dexterity, and bulbar function. While extra-motor pathology and frontotemporal involvement are widely recognised in motor neuron diseases (MNDs), reports of sensory involvement are conflicting. The potential contribution of sensory deficits to clinical disability is not firmly established and the spectrum of sensory manifestations is poorly characterised. Methods: A systematic review was conducted to examine the clinical, neuroimaging, electrophysiology and neuropathology evidence for sensory dysfunction in MND phenotypes. Results: In ALS, paraesthesia, pain, proprioceptive deficits and taste alterations are sporadically reported and there is also compelling electrophysiological, histological and imaging evidence of sensory network alterations. Gait impairment, impaired dexterity, and poor balance in ALS are likely to be multifactorial, with extrapyramidal, cerebellar, proprioceptive and vestibular deficits at play. Human imaging studies and animal models also confirm dorsal column-medial lemniscus pathway involvement as part of the disease process. Sensory symptoms are relatively common in spinal and bulbar muscular atrophy (SBMA) and Hereditary Spastic Paraplegia (HSP), but are inconsistently reported in primary lateral sclerosis (PLS) and in post-poliomyelitis syndrome (PPS). Conclusions: Establishing the prevalence and nature of sensory dysfunction across the spectrum of MNDs has a dual clinical and academic relevance. From a clinical perspective, subtle sensory deficits are likely to impact the disability profile and care needs of patients with MND. From an academic standpoint, sensory networks may be ideally suited to evaluate propagation patterns and the involvement of subcortical grey matter structures. Our review suggests that sensory dysfunction is an important albeit under-recognised facet of MND.