bluuebunny/crossref_metadata_2025 huggingface dataset:
Protection Conferred by Gallid Alphaherpesvirus 2 Vaccines Against Immunosuppression Induced by Very Virulent Plus (vv+) Marek’s Disease Virus Strains in Commercial Meat Type Chickens
Authors: Khaled Nagwa , Gaghan Carissa , Fares Abdelhamid M. , Goodell Christa , Stanley William , Kulkarni Raveendra R. , Gimeno Isabel M.
Published: January 2025

Very virulent plus Marek’s disease virus (vv+MDV) induces severe immunosuppression in commercial chickens. In this study, we evaluated how three Gallid alphaherpesvirus 2 (GaHV-2) vaccines (CVI-988, rMd5-BAC∆Meq, and CVI-LTR) protected against two negative outcomes of vv+MDV infection: (1) reduced viability and frequency of immune cells in the spleen and (2) decreased efficacy of the CEO (chicken embryo origin) vaccine against infectious laryngotracheitis challenge. At 25 days post-infection with vv+MDV 686, all vaccines are protected against the reduced viability of splenocytes. However, there were differences in the frequency of splenic immunophenotypes among groups. Compared to the uninfected control, the frequency of B cells was reduced in the CVI-988/686 group but not in the rMd5-BAC∆Meq/686 and CVI-LTR/686 groups. T cell subset frequencies showed no difference between the negative controls and CVI-988/686; however, there was a reduction in activated CD4+ T cells in the rMd5-BAC∆Meq/686 group and in activated CD4+, activated CD8+, and γδ+ T cells in the CVI-LTR/686 group. We also demonstrated that the three vaccines protected against MDV-induced tumors, but only rMd5-BAC∆Meq and CVI-LTR protected against the negative impact of vv+MDV 648A strain on CEO vaccine efficacy. Our findings demonstrate important differences in the biology and/or mechanisms of protection of these vaccines.
Salt Stress Enhanced Bioactivity of Quinoa Leaf Extracts: An In Vitro and In Silico Study of Acetylcholinesterase and Tyrosinase Inhibition for Sustainable Drug Development
Authors: Slimani Narmine , Arraouadi Soumaya , Hajlaoui Hafedh , Cid-Samamed Antonio , Borgi Mohamed Ali , Snoussi Mejdi
Published: January 2025

Background: Quinoa is recognized for its nutritional and pharmacological properties. This study aims to investigate the impact of salt stress induced by varying concentrations of sodium chloride (NaCl) on the production of phenolic compounds and their biological activities in different quinoa accessions. Method: Leaves from three quinoa accessions (Q4, Q24, and Q45) cultivated under increasing NaCl treatments were subjected to chemical analysis using ethanol and water extract. The concentrations of various phenolic compounds, including polyphenols, tannins, anthocyanins, and flavonoids, were quantified. HPLC-DAD-ESI-MS/MS was employed to identify the major compounds in the water extract. Additionally, antioxidants (ABTS and FRAP), anti-tyrosinase, and anti-acetylcholinesterase effects were assessed using in vitro and in silico approaches. Results: NaCl treatment significantly increased the levels of phenolic compounds across all quinoa accessions. The Q45 accession exhibited the highest accumulation of these compounds, particularly in the aqueous extracts at the 200 mM NaCl concentration. Increases were observed in flavonoids (144%), anthocyanins (125%), tannins (89%), and total polyphenols (65%) relative to controls. HPLC-DAD-ESI-MS/MS analysis corroborated these findings, showing that the main compounds also increased with higher NaCl concentrations. Furthermore, the biological efficacy tests revealed that the IC50 values for both tyrosinase and acetylcholinesterase activities decreased with greater salt stress, indicating enhanced enzyme inhibition. The antioxidant activity of these extracts also showed a significant increase as the salt stress levels rose. Conclusions: Salt stress not only promotes the production of bioactive phenolic compounds in quinoa leaves but also enhances their inhibitory effects on key enzymes associated with neurodegenerative and pigmentary disorders. These findings suggest that quinoa may serve as a valuable resource for therapeutic applications, particularly under increased salinity conditions.
Evaluation of Five Ready-to-Use Bases for the Topical Administration of Propranolol Hydrochloride to Treat Infantile Hemangioma
Authors: Lacassia Chiara , Cutrignelli Annalisa , la Forgia Flavia Maria , Fontana Sergio , Lopalco Antonio , Denora Nunzio , Lopedota Angela Assunta
Published: January 2025

Background/Objectives: Since 2008, following clinical studies conducted on children that revealed the ability of the β-adrenergic antagonist propranolol to inhibit capillary growth in infantile hemangiomas (IHs), its oral administration has become the first-line treatment for IHs. Although oral propranolol therapy at a dosage of 3 mg/kg/die is effective, it can cause systemic adverse reactions. This therapy is not necessarily applicable to all patients. Topical skin applications could help maintain a high drug concentration at local sites and also represent a characteristically easy method of administration for pediatric patients. Because no topical propranolol dosage forms are commercially available, such formulations may be prepared at hospitals and pharmacies. Methods: In the present study, we identified a simple method for preparing topical propranolol hydrochloride formulations at 1% w/w with five commercial ready-to-use bases and evaluated the pharmaceutical profiles. The physical stability of the extemporaneous formulations was predicted by performing an accelerated centrifuge test and assessed by visual inspection after one month storage at 25 °C. The chemical stability of the drug in the five formulations was assessed by using a high-performance liquid chromatography (HPLC) method. In vitro drug-release and permeability experiments were conducted through synthetic membranes and the outer pavilion of a pig’s ear by utilizing Franz-type diffusion cells. Results: The results indicated that the release of the drug was significantly influenced by the internal structure and physicochemical properties of each base. Conclusions: Specifically, the formulations prepared with the hydrophilic bases could be easily prepared and yield satisfactory results, representing a potential effective therapy for IHs in pediatric patients.
Plant Adaptation and Soil Shear Strength: Unraveling the Drought Legacy in Amorpha fruticosa
Authors: Jiang Hao , Chen Xiaoqing , Xu Gang , Chen Jiangang , Song Dongri , Lv Ming , Guo Hanqing , Chen Jingyi
Published: January 2025

Climate change has led to an increasing frequency of droughts, potentially undermining soil stability. In such a changing environment, the shallow reinforcement effect of plant roots often fails to meet expectations. This study aims to explore whether this is associated with the alteration of plant traits as a response to environmental change. Focusing on Amorpha fruticosa, a species known for its robust root system that plays a crucial role in soil consolidation and slope stabilization, thereby reducing soil and water erosion, we simulated a drought-rewetting event to assess the legacy effects of drought on the soil shear strength and the mechanical and hydrological traits associated with the reinforcement provided by A. fruticosa. The results show that the legacy effect of drought significantly diminishes the soil shear strength. Pretreated with drought, plant roots undergo morphological alterations such as deeper growth, yet the underground root biomass and diameter decline, thereby influencing mechanical reinforcement. Chemical composition analysis indicates that the plant’s adaptation to drought modifies the intrinsic properties of the roots, with varying impacts on different root types and overall reinforcement. Concurrently, the stomatal conductance and transpiration rate of leaves decrease, weakening the capacity to augment soil matric suction through transpiration and potentially reducing hydrological reinforcement. Although rewetting treatments aid in recovery, drought legacy effects persist and impact plant functional attributes. This study emphasizes that, beyond soil matric suction, plant adaptive mechanisms in response to environmental changes may also contribute significantly to reduced soil shear strength. Consequently, ecological restoration strategies should consider plant trait adaptations to drought, enhancing root systems for soil conservation and climate resilience.
Development and Characterization of Hyaluronic Acid Graft-Modified Polydopamine Nanoparticles for Antibacterial Studies
Authors: Li Shu , Li Jia , Xing Jun , Li Ling , Wang Long , Wang Cai
Published: January 2025

The problem of antibiotic abuse and drug resistance is becoming increasingly serious. In recent years, polydopamine (PDA) nanoparticles have been recognized as a potential antimicrobial material for photothermal therapy (PTT) due to their excellent photothermal conversion efficiency and unique antimicrobial ability. PDA is capable of rapidly converting light energy into heat energy under near-infrared (NIR) light irradiation to kill bacteria efficiently. In order to solve the problem of PDA’s tendency to aggregate and precipitate, this study improved its stability by grafting hyaluronic acid (HA) onto the surface of PDA. Using dopamine and hyaluronic acid as raw materials, hyaluronic acid (HA) was grafted onto polydopamine (PDA) nanoparticles via self-polymerization and Michael addition reactions under alkaline conditions to obtain PDA-HA-modified nanoparticles. We confirmed the successful grafting of hyaluronic acid via scanning electron microscopy (SEM), Fourier infrared spectroscopy (FTIR), nuclear magnetic hydrogen spectroscopy (¹H NMR), ultraviolet–visible spectroscopy (UV–vis), Raman spectroscopy (Raman), and dynamic light scattering (DLS) methods. Scanning electron microscopy (SEM) was used to observe the surface morphology and nanostructure of the grafted materials, providing information on the morphology and size distribution of the materials. Near-infrared performance experiments showed that the temperature of the PDA-HA solution increased rapidly under near-infrared light irradiation, demonstrating an excellent photothermal conversion performance. Antimicrobial properties were assessed via the colony counting method, and typical Gram-positive bacteria S. aureus and Gram-negative bacteria E. coli were selected as model strains. The experimental groups were tested under dark conditions and near-infrared (NIR) light irradiation. PDA/HA showed significant photothermal properties under NIR light irradiation, resulting in a rapid increase in the surrounding temperature to a level sufficient to kill bacteria. Under NIR light irradiation, PDA/HA exhibited 100% antimicrobial efficacy against both S. aureus and E. coli, while antimicrobial efficacy was limited under dark conditions. This indicates that the antibacterial activity of PDA/HA is highly dependent on NIR light activation.
A Fast Calculation Method for Economic Dispatch of Electro-Thermal Coupling System Considering the Dynamic Process of Heat Transfer
Authors: Chen Jingyan , Lin Qinting , Yang Zilong , Liu Qingming , Zou Hongbo
Published: January 2025

The dynamic spatial and temporal characteristics of heat transfer within heating network pipelines are important factors affecting the accuracy of economic dispatch decision-making results of electro-thermal coupling systems. However, the pipeline heat transmission process is described by partial differential equations, which makes it difficult to solve quickly. Therefore, this study introduces a model for calculating the economic dispatch of the electro-thermal coupling system (EDETCS) that takes into account the pipeline transmission process. Firstly, based on the implicit upwind difference method, a two-port model of branch heat transfer dynamics is established. Secondly, the general term formula of the two-port model is derived. Finally, the established two-port model is applied to the EDETCS. The findings from the example analysis indicate that, in contrast to the conventional calculation method, the proposed model improves the calculation speed while ensuring the accuracy of the solution.
Research on Modifying the Development Plan to Enhanced Oil Recovery in the Middle and Late Stages of Water Flooding in Deep Clastic Rock Reservoirs
Authors: Song Fuquan , Tian Lu , Li Hui
Published: January 2025

The exploitation of Block L within the Tarim Basin oilfield commenced in 1989 and it has transitioned from the natural energy development stage to the current water injection development stage. Despite this, the efficacy of water flooding remains suboptimal, with the low degree of control, uneven utilization of reserves, and subpar mining outcomes. The block still contains substantial remaining oil resources, necessitating continued extraction. Notably, the primary oil produced in this block is condensate oil, which commands a high economic value. To enhance the oil recovery efficiency of the block reservoir, a development plan employing alternating and water-natural gas flooding has been proposed. The objective of this study is to evaluate the feasibility of the proposed alternating displacement scheme involving natural gas and water in this reservoir. The specific steps include PVT fitting, historical matching, residual oil evaluation, and the optimization of gas injection parameters. Results show that for this reservoir the water-natural gas flooding (WAG) is the optimal option. And this article has the application of WAG flooding simulation, simulating 15 years of operation. Compared with the original development scheme of the original well pattern, the recovery of this reservoir is increased by 12.05%, which provided a reference basis for the on-site application of WAG in this reservoir.
Modeling and Evaluation of Attention Mechanism Neural Network Based on Industrial Time Series Data
Authors: Zhou Jianqiao , Wang Zhu , Liu Jiaxuan , Luo Xionglin , Chen Maoyin
Published: January 2025

Chemical process control systems are complex, and modeling the controlled object is the first task in automatic control and optimal design. Most chemical process modeling experiments require test signals to be applied to the process, which may lead to production interruptions or cause safety accidents. Therefore, this paper proposes an improved transformer model based on a self-attention mechanism for modeling industrial processes. Then, an evaluation mechanism based on root mean square error (RMSE) and Kullback–Leibler divergence (KLD) metrics is designed to obtain more appropriate model parameters. The Variational Auto-Encoder (VAE) network is used to compute the associated KLD. Finally, a real nonlinear dynamic process in the petrochemical industry is modeled and evaluated using the proposed methodology to predict the time series data of the process. This study demonstrates the validity of the proposed transformer model and illustrates the versatility of using an integrated modeling, evaluation, and prediction scheme for nonlinear dynamic processes in process industries. The scheme is of great importance for the field of industrial soft measurements as well as for deep learning-based time series prediction. In addition, the issue of a suitable time domain for the prediction is discussed.
A Sentinel-2-Based System to Detect and Monitor Oil Spills: Demonstration on 2024 Tobago Accident
Authors: D’Ugo Emilio , Kallikkattilkuruvila Ashish , Giuseppetti Roberto , Carvajal Alejandro , Diouf Abdou Mbacke , Tucci Matteo , Aulenta Federico , Ursi Alessandro , Sacco Patrizia , Tapete Deodato , Laneve Giovanni , Magurano Fabio
Published: January 2025

In this paper, we analyze the serious environmental accident caused by a massive oil spill on 7 February 2024, off the island of Tobago, using two separate algorithms, namely, the established visible near-red index (VNRI) algorithm and the novel IVI visible reflectance ratio index (IVI), both applied to Sentinel-2 satellite images. These algorithms were specifically designed to monitor oil spills in inner waters. In this paper, where the IVI is presented for the first time, its effectiveness in the open sea is also showcased allowing the identification and subsequent monitoring over time of the oily masses that threaten the coral reef of the island. The analysis suggests that with sufficient cloud-free conditions, high temporal revisit multispectral optical satellites could support the timely detection and tracking of oil masses during environmental incidents near natural sanctuaries.
Multi-Criteria Assessment of Urban Thermal Hotspots: A GIS-Based Remote Sensing Approach in a Mediterranean Climate City
Authors: Sola-Caraballo Javier , Serrano-Jiménez Antonio , Rivera-Gomez Carlos , Galan-Marin Carmen
Published: January 2025

One of the most significant urban challenges focuses on addressing the effects of urban overheating as a consequence of climate change. Several methods have been developed to characterize urban heat islands (UHIs); however, the most widely used involve complex planning, huge time consumption, and substantial human and technical resources on field monitoring campaigns. Therefore, this study aims to provide an easily accessible and affordable remote sensing method for locating urban hotspots and addresses a multi-criteria assessment of urban heat-related parameters, allowing for a comprehensive city-wide evaluation. The novelty is based on leveraging the potential of the last Landsat 9 satellite, the application of kernel spatial interpolation, and GIS open access data, providing very high-resolution land surface temperature images over urban spaces. Within GIS workflow, the city is divided into LCZs, thermal hotspots are detected, and finally, it is analyzed to understand how urban factors, such as urban boundaries, building density, and vegetation, affect urban scale LST, all using graphical and analytical cross-assessment. The methodology has been tested in Seville, a representative warm Mediterranean city, where variations of up to 10 °C have been found between homogeneous residential areas. Thermal hotspots have been located, representing 11% of the total residential fabric, while results indicate a clear connection between the urban factors studied and overheating. The conclusions support the possibility of generating a powerful affordable tool for future research and the design of public policy renewal actions in vulnerable areas.
Effective First-Break Picking of Seismic Data Using Geometric Learning Methods
Authors: Wen Zhongyang , Ma Jinwen
Published: January 2025

Automatic first-break(FB) picking is a key task in seismic data processing, with numerous applications in the field. Over the past few years, both unsupervised and supervised learning algorithms have been applied to 2D seismic arrival time picking and obtained good picking results. In this paper, we introduce a strategy of optimizing certain geometric properties of the target curve for first-break picking which can be implemented in both unsupervised and supervised learning modes. Specifically, in the case of unsupervised learning, we design an effective curve evolving algorithm according to the active contour(AC) image segmentation model, in which the length of the target curve and the fitting region energy are minimized together. It is interpretable, and its effectiveness and robustness are demonstrated by the experiments on real world seismic data. We further investigate three schemes of combining it with human interaction, which is shown to be highly useful in assisting data annotation or correcting picking errors. In the case of supervised learning especially for deep learning(DL) models, we add a curve loss term based on the target curve geometry of first-break picking to the typical loss function. It is demonstrated by various experiments that this curve regularized loss function can greatly enhance the picking quality.
Assessing the Air Quality Impact of Train Operation at Tokyo Metro Shibuya Station from Portable Sensor Data
Authors: Agarwal Deepanshu , Trinh Xuan Truong , Takeuchi Wataru
Published: January 2025

Air pollution remains a critical global health concern, with 91% of the world’s population exposed to air quality exceeding World Health Organization (WHO) standards and indoor pollution causing approximately 3.8 million deaths annually due to incomplete fuel combustion. Subways, as major public transportation modes in densely populated cities, can exhibit fine particulate matter (PM) levels that surpass safety limits, even in developed countries. Contributing factors include station location, ambient air quality, train frequency, ventilation efficiency, braking systems, tunnel structure, and electrical components. While elevated PM levels in underground platforms are recognized, the vertical and horizontal variations within stations are not well understood. This study examines the vertical and horizontal distribution of PM2.5 and PM10 levels at Shibuya Station, a structurally complex hub in the Tokyo Subway System. Portable sensors were employed to measure PM concentrations across different platform levels—both above and underground—and at various locations along the platforms. The results indicate that above-ground platforms have significantly lower PM2.5 and PM10 levels compared to underground platforms (17.09 μg/m3 vs. 22.73 μg/m3 for PM2.5; 39.54 μg/m3 vs. 56.98 μg/m3 for PM10). Notably, the highest pollution levels were found not at the deepest platform but at the one with the least effective ventilation. On the same platform, PM levels varied by up to 63.72% for PM2.5 and 120.23% for PM10, with elevated concentrations near the platform extremities compared to central areas. These findings suggest that ventilation efficiency plays a more significant role than elevation in vertical PM variation, while horizontal differences are likely influenced by piston effects from moving trains. This study underscores the risk of exposure to unsafe PM2.5 levels in underground platforms, particularly at platform extremities, highlighting the need for improved ventilation strategies to enhance air quality in subway environments.
The Impact of Spatial Dynamic Error on the Assimilation of Soil Moisture Retrieval Products
Authors: Bai Xuesong , Qin Zhengkun , Li Juan , Zhang Shupeng , Wang Lili
Published: January 2025

Soil moisture is a key factor affecting the exchange of heat and water between the land and the atmosphere. Land data assimilation (LDA) methods that leverage the strengths of both models and observations can generate more accurate initial conditions. However, soil moisture exhibits significant spatial heterogeneity, implying strong local characteristics for both observational and background errors. To elucidate the impact of error localization on LDA, we constructed a land data assimilation system (LDAS) suitable for the Common Land Model (CoLM), based on the simplified extended Kalman filter (SEKF) method. Through practical assimilation experiments using soil moisture retrieval products from the Soil Moisture Active Passive (SMAP) and Fenyun-3D (FY3D) satellites, we investigated the influence of spatial static and dynamic observational and background errors on LDA. The results indicate that by incorporating dynamic errors that account for the spatial heterogeneity of soil, LDAS can adaptively absorb observational information, thereby significantly enhancing assimilation impact and subsequent model forecast accuracy. Compared to experiments applying static errors, dynamic errors increased the spatial correlation coefficients by 17.4% and reduced the root mean square error (RMSE) by 11.2%. The results clearly demonstrate that for soil variable assimilation studies with strong spatial heterogeneity, progressively refined dynamic error estimation is a crucial direction for improving land surface assimilation performance.
The Design and Validation of an Open-Palm Data Glove for Precision Finger and Wrist Tracking
Authors: Hosie Olivia , Isaksson Mats , McCormick John , Tirosh Oren , Hensman Chrys
Published: January 2025

Wearable motion capture gloves enable the precise analysis of hand and finger movements for a variety of uses, including robotic surgery, rehabilitation, and most commonly, virtual augmentation. However, many motion capture gloves restrict natural hand movement with a closed-palm design, including fabric over the palm and fingers. In order to alleviate slippage, improve comfort, reduce sizing issues, and eliminate movement restrictions, this paper presents a new low-cost data glove with an innovative open-palm and finger-free design. The new design improves usability and overall functionality by addressing the limitations of traditional closed-palm designs. It is especially beneficial in capturing movements in fields such as physical therapy and robotic surgery. The new glove incorporates resistive flex sensors (RFSs) at each finger and an inertial measurement unit (IMU) at the wrist joint to measure wrist flexion, extension, ulnar and radial deviation, and rotation. Initially the sensors were tested individually for drift, synchronisation delays, and linearity. The results show a drift of 6.60°/h in the IMU and no drift in the RFSs. There was a 0.06 s delay in the data captured by the IMU compared to the RFSs. The glove’s performance was tested with a collaborate robot testing setup. In static conditions, it was found that the IMU had a worst case error across three trials of 7.01° and a mean absolute error (MAE) averaged over three trials of 4.85°, while RFSs had a worst case error of 3.77° and a MAE of 1.25° averaged over all five RFSs used. There was no clear correlation between measurement error and speed. Overall, the new glove design proved to accurately measure joint angles.
Analysis of the Effect of Skin Pigmentation and Oxygen Saturation on Monte Carlo-Simulated Reflectance Photoplethysmography Signals
Authors: Al-Halawani Raghda , Qassem Meha , Kyriacou Panicos A.
Published: January 2025

The effect of skin pigmentation on photoplethysmography and, specifically, pulse oximetry has recently received a significant amount of attention amongst researchers, especially since the COVID-19 pandemic. With most computational studies observing overestimation of arterial oxygen saturation (SpO2) in individuals with darker skin, this study seeks to further investigate the root causes of these discrepancies. This study analysed intensity changes from Monte Carlo-simulated reflectance PPG signals across light, moderate, and dark skin types at oxygen saturations of 70% and 100% in MATLAB R2024a. With simulated intensity reflecting PPG amplitude, the results showed that systolic intensity decreased by 3–4% as pigmentation increased at 660 nm. It was also shown that the impact at 940 nm is minimal (<0.2%), indicating that the increased absorption of red light by melanin has a greater effect on the ratio of ratios calculations. These results suggest that in-built adjustments may be required for data collected from red-light sources in pulse oximeters that do not currently have the necessary post-processing algorithms to account for this difference between diverse skin populations.
Research on End-Effector Position Error Compensation of Industrial Robotic Arm Based on ECOA-BP
Authors: Xiang Wenping , Chen Junhua , Li Hao , Chai Zhiyuan , Lou Yinghou
Published: January 2025

Industrial robotic arms are often subject to significant end-effector pose deviations from the target position due to the combined effects of nonlinear deformations such as link flexibility, joint compliance, and end-effector load. To address this issue, a study was conducted on the analysis and compensation of end-position errors in a six-degree-of-freedom robotic arm. The kinematic model of the robotic arm was established using the Denavit–Hartenberg (DH) parameter method, and a rigid–flexible coupled virtual prototype model was developed using ANSYS and ADAMS. Kinematic simulations were performed on the virtual prototype to analyze the variation in end-effector position errors under rigid–flexible coupling conditions. To achieve error compensation, an approach based on an Enhanced Crayfish Optimization Algorithm (ECOA) optimizing a BP neural network was proposed to compensate for position errors. An experimental platform was constructed for error measurement and validation. The experimental results demonstrated that the positioning accuracy after compensation improves by 75.77%, fully validating the effectiveness and reliability of the proposed method for compensating flexible errors.
Analysis of GNSS-RTK Monitoring Background Noise Characteristics Based on Stability Tests
Authors: Qi Wencong , Li Feilong , Yu Lina , Fan Lilong , Zhang Kai
Published: January 2025

GNSS-RTK offers numerous advantages and broad prospects in structural dynamic monitoring in civil engineering. However, in practical applications, GNSS-RTK accuracy is susceptible to the monitoring environments, causing actual monitoring accuracy to fall below its calibrated accuracy. This study investigates the monitoring accuracy and spectral characteristics of GNSS-RTK based on stability tests under different environments related to reflection and obstruction conditions (i.e., concrete, grass, an obstructed balcony, and a water area). The findings indicate that in open environments of grass, concrete, and water, the standard deviation (STD) of GNSS-RTK monitored displacement is below 8 mm, its accuracy meeting the specifications of structural health monitoring. In the obstructed balcony environments, GNSS-RTK signals exhibit amplitude jumps, resulting in lower accuracy; however, during non-jump intervals, the STD of monitored displacement is below 10 mm, satisfying the structural health monitoring accuracy requirements. Moreover, the amplitudes of GNSS-RTK displacements in the concrete, grass, and water areas are basically consistent with the calibration accuracy of ±10 mm in the horizontal direction and ±20 mm in the elevation direction, while the amplitudes of GNSS-RTK displacements in the obstructed balcony condition are far greater than the calibration accuracy. The spectral analysis of GNSS-RTK signals reveals that multipath errors in concrete, grass, and obstructed balcony environments are primarily concentrated in the low-frequency range within 0.04 Hz, while the internal white noise of the instrument is widely and evenly distributed across the whole frequency domain. Based on these findings, adaptive methods, such as filter methods and multipath error correction techniques, are proposed for the de-noising of GNSS-RTK background noise.
Energy-Efficient Aerial STAR-RIS-Aided Computing Offloading and Content Caching for Wireless Sensor Networks
Authors: Yang Xiaoping , Wang Quanzeng , Yang Bin , Cao Xiaofang
Published: January 2025

Unmanned aerial vehicle (UAV)-based wireless sensor networks (WSNs) hold great promise for supporting ground-based sensors due to the mobility of UAVs and the ease of establishing line-of-sight links. UAV-based WSNs equipped with mobile edge computing (MEC) servers effectively mitigate challenges associated with long-distance transmission and the limited coverage of edge base stations (BSs), emerging as a powerful paradigm for both communication and computing services. Furthermore, incorporating simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) as passive relays significantly enhances the propagation environment and service quality of UAV-based WSNs. However, most existing studies place STAR-RISs in fixed positions, ignoring the flexibility of STAR-RISs. Some other studies equip UAVs with STAR-RISs, and UAVs act as flight carriers, ignoring the computing and caching capabilities of UAVs. To address these limitations, we propose an energy-efficient aerial STAR-RIS-aided computing offloading and content caching framework, where we formulate an energy consumption minimization problem to jointly optimize content caching decisions, computing offloading decisions, UAV hovering positions, and STAR-RIS passive beamforming. Given the non-convex nature of this problem, we decompose it into a content caching decision subproblem, a computing offloading decision subproblem, a hovering position subproblem, and a STAR-RIS resource allocation subproblem. We propose a deep reinforcement learning (DRL)–successive convex approximation (SCA) combined algorithm to iteratively achieve near-optimal solutions with low complexity. The numerical results demonstrate that the proposed framework effectively utilizes resources in UAV-based WSNs and significantly reduces overall system energy consumption.
Survey of Autonomous Vehicles’ Collision Avoidance Algorithms
Authors: Hamidaoui Meryem , Talhaoui Mohamed Zakariya , Li Mingchu , Midoun Mohamed Amine , Haouassi Samia , Mekkaoui Djamel Eddine , Smaili Abdelkarim , Cherraf Amina , Benyoub Fatima Zahra
Published: January 2025

Since the field of autonomous vehicles is developing quickly, it is becoming increasingly crucial for them to safely and effectively navigate their surroundings to avoid collisions. The primary collision avoidance algorithms currently employed by self-driving cars are examined in this thorough survey. It looks into several methods, such as sensor-based methods for precise obstacle identification, sophisticated path-planning algorithms that guarantee cars follow dependable and safe paths, and decision-making systems that allow for adaptable reactions to a range of driving situations. The survey also emphasizes how Machine Learning methods can improve the efficacy of obstacle avoidance. Combined, these techniques are necessary for enhancing the dependability and safety of autonomous driving systems, ultimately increasing public confidence in this game-changing technology.
Separation Process for Methanol–Methylal–Methyl Formate Multicomponent System in Polyformaldehyde Production Waste Liquid: Modeling and Techno-Economic Analysis
Authors: Liu Huajie , Fan Jun , Liu Weiping , Wang Yong , Ai Qiuhong , Li Yonglin
Published: January 2025

The vapor–liquid equilibrium (VLE) data of the ternary system methanol–methyl formate–methylal was measured at atmospheric pressure using a modified Rose equilibrium kettle with vapor–liquid double circulation method. The experiment data were correlated with the NRTL, UNIQUAC, and Wilson activity coefficient model equations. The results shown that the root mean square deviation (RMSD) between the calculated and simulated values of the three models followed the order: UNIQUAC ≈ NRTL < Wilson, and except for the RMSD (T) in the range of 0.4–0.5, the others are less than 0.01. In addition, the NRTL model was selected to link with Aspen Plus software to simulate the separation process of polyformaldehyde (POM) waste liquid. The simulation results show that the methyl formate in POM waste stream can be purified by simple distillation, while the methylal separated from the POM waste liquid, which was affected by factors like the azeotropic behavior of binary components, necessitates a complex distillation process. Under optimal operating conditions, the recovery yield of methyl formate through direct distillation can reach 99.7%, with an economic benefit of 6960.1 CNY per ton of waste liquid. Although the economic benefit of the multi-component distillation reach 7281.2 CNY, the increase in the number of equipment and the complexity of the process have negative impacts.
Frequency-Domain Characterization of Finite Sample Linear Systems with Uniform Window Inputs
Authors: Zhou Qihou
Published: January 2025

We discuss determining a finite sample linear time-invariant (FS-LTI) system’s impulse response function, h[n], in the frequency domain when the input testing function is a uniform window function with a width of L and the output is limited to a finite number of effective samples, M. Assuming that the samples beyond M are all zeros, the corresponding infinite sample LTI (IS-LTI) system is a marginally stable system. The ratio of the discrete Fourier transforms (DFT) of the output to input of such an FS-LTI system, H0[k], cannot be directly used to find h[n] via inverse DFT (IDFT). Nevertheless, H0[k] contains sufficient information to determine the system’s impulse response function (IRF). In the frequency-domain approach, we zero-pad the output array to a length of N. We present methods to recover h[n] from H0[k] for two scenarios: (1) N≥max(L,M+1) and N is a coprime of L, and (2) N≥L+M+1. The marginal stable system discussed here is an artifact due to the zero-value assumption on unavailable samples. The IRF obtained applies to any LTI system up to the number of effective data samples, M. In demonstrating the equivalence of H0[k] and h[n], we derive two interesting DFT pairs. These DFT pairs can be used to find trigonometric sums that are otherwise difficult to prove. The frequency-domain approach makes mitigating the effects of interferences and random noise easier. In an example application in radar remote sensing, we show that the frequency-domain processing method can be used to obtain finer details than the range resolution provided by the radar system’s transmitter.
Yam Nematodes as Production Constraints in Ghana: A Socio-Economic Perspective
Authors: Whedie Boafo Osei , Yami Gurmu Mesay , Nyaku Seloame Tatu , Brentu Collison Francis , Ankrah Daniel , Dzidzienyo Daniel , Bhattacharjee Ranjana
Published: January 2025

Yam (Dioscorea spp.) has been a prominent food and cash crop for most farmers in the yam production areas of Ghana, with the sales of yam in both domestic and international markets contributing significantly to the economy of the country. However, yam production by smallholder farmers is constrained by several challenges, including postharvest loss resulting from yam nematodes. This study conducted field surveys across seven districts across Ghana to collect data from randomly selected 150 yam farmers to investigate the status of nematode infestation, management practices and other socio-economic factors contributing to yam production in the country. The most common farm size for yam production from 2019 to 2022 was between 0.4 and 0.8 hectares. The majority of the farmers (56%) have been farming for over 15 years, with 6–10 years of experience in yam production, and preferred to use their own planting materials every year. Although most farmers (97.99%) experienced pests and diseases, most of them (77.33%) had no knowledge about nematode infestations in their farm causing damage to the tubers. Although yam farmers experienced yield losses, farmers were unable to manage nematode infestations in their farms. Twelve (12) genera of nematodes were identified in soils of yam rhizosphere across the seven districts. Tylenchus spp. (35.5%) and Scutellonema spp. (92.8%) were the most abundant nematode in soil samples and tuber peels, respectively while the second highest nematode in tuber peels was Meloidogyne spp. (4.0%). The presence of these parasitic nematodes in yam farms across Ghana suggests serious threats to the growth and yield of yams, although their presence is either not known or is usually neglected. Our result also confirmed the correlation between farmer storage practices and the management of nematodes, suggesting some storage practices such as barns may be effective in controlling nematodes. On the other hand, we find no association between pest occurrence in the field and nematode management. The lack of an association could be an indication that pest management in the field and nematode management in storage are separate activities and this underlines the importance of providing tailored postharvest training for smallholder farmers in effectively managing nematodes. It was therefore necessary to undertake this study and establish knowledge on the species as well as their prevalence in the farms across Ghana, contributing towards enhanced farmers’ understanding on nematode management and effective storage of yams to prevent losses caused by nematode infestation.
The Impact of the Convergence of Advanced Manufacturing and Modern Services on Green Innovation Efficiency
Authors: Zhang Hongying , Nie Song , Wan Liyang
Published: January 2025

Cross-region and cross-industry cooperation has become a key driver of industrial transformation. Advanced manufacturing is boosting the modern service industry and fostering innovation and development, while the modern service industry is promoting advanced manufacturing and stimulating the market demand. The convergence of advanced manufacturing and modern services (CAMMS) is a key driver of environmental innovation in China’s modern economy. This study explores the impact of CAMMS on green innovation efficiency and its spatial correlations. Employing a two-way fixed-effect model, along with the mediating-effect model and the spatial Durbin model (SDM), we analyze Chinese provincial panel data from 2006 to 2021 to explore the effects of CAMMS on green innovation efficiency and its spatial spillover effects. Our findings reveal the following: (1) CAMMS significantly enhances green innovation efficiency. (2) Optimizing industrial structure and improving factor allocation are the primary mechanisms through which CAMMS promotes green innovation efficiency. (3) The CAMMS mechanism positively influences spatial spillover effects on green innovation efficiency, with these effects becoming more pronounced in the eastern region and after 2011. (4) Finally, due to increasing information transmission costs and local protectionism, the “spillover effect” of CAMMS on green innovation efficiency has geographical boundaries. This study contributes to the literature by providing valuable insights for future practices in CAMMS and green innovation strategies in China. This also provides strong support for the local economy to achieve green transformation and sustainable development.
Determination of the Key Factors to Uncover the True Benefits of Embracing Climate-Resilient Napier Grass Among Dairy Farmers in Southern India
Authors: Dey Shiladitya , Abbhishek Kumar , Saraswathibatla Suman , Das Debabrata , Rongali Hari Babu
Published: January 2025

Insufficient access to high-quality feed in sufficient amounts is hindering the sustainable growth of the Indian cattle sector. The feed supply is negatively impacted by increased cropping intensity, limited grazing land, and the effects of climate change. Therefore, developing cost-effective methods to improve feed availability year-round is crucial. Improved planted forages, such as Napier grass, are recommended to address feed shortages in semi-arid agroecological regions in India. The study, using the PSM approach, investigates the socioeconomic factors that impact Napier adoption, its influence on enhanced milk output, time saved in livestock farming, farmers’ well-being, and livestock health. This study employed a multistage sampling method to choose 309 participants for the questionnaire survey. Our analysis shows that Napier adoption resulted in a 24.6% rise in daily milk output/cow and a 61.2% overall improvement in total milk production/year/cow when compared with baseline data. Napier’s adoption decreased livestock farming times by 30 min/cow. Additionally, women’s involvement in livestock farming improved with Napier farming, and farmers who have switched to Napier have seen a remarkable increase in their net income, with a monthly boost of Rs. 2044–2555 per cow. Additionally, daily milk consumption has also skyrocketed, with a remarkable enhancement of 143–153 mL per person daily. Our study highlights that the farmer’s age, education level, livestock unit, and land holding play a crucial role. Additionally, the availability of extension services and farmer group participation can further impact the adoption process. Furthermore, our study explores how these factors shape the decision-making process and drive the successful integration of Napier grass into farming practices. However, considering the spatial limitations and reliance on self-reported data in this study, we suggest future research examining the long-term effects of Napier grass adoption on climate-smart agricultural practices, soil moisture, and socioeconomic benefits, involving field experiments, modeling, and farmer participation.
Quantitative Analysis of ESG Information Value and Policy Uncertainty
Authors: Lee Ming-Fang , Shih Kuang-Hsun , Wang Yi-Hsien , Lai Fu-Ming
Published: January 2025

This study examines the impact of ESG rating disclosures on the stock performance of highly rated semiconductor companies in Taiwan from 2017 to 2023. The findings reveal significant abnormal returns surrounding ESG rating releases, with positive returns before the event reflecting investor optimism and negative returns afterward indicating market reassessment. The analysis highlights varied effects of ESG dimensions: environmental performance benefits lower-performing firms, social initiatives show negative impacts on high-performing firms, and governance practices demonstrate both short-term costs and long-term benefits. Policy continuity emerges as a critical factor in moderating the financial impacts of ESG performance. Stable and supportive policies enhance the positive effects of ESG initiatives, while inconsistent frameworks exacerbate inefficiencies. These results emphasize the importance of aligning ESG strategies with consistent policy environments to maximize shareholder wealth, offering valuable insights for investors, corporate managers, and policymakers.
Promoting Youth Mental Health in Spiritual Tourism Through Service Design
Authors: Dong Haoyu , Zhang Jun , Tang Tang
Published: January 2025

Youth are society’s vital asset, and their mental health is a priority for global public health. Spiritual tourism, through the integration of cultural and spiritual elements, promotes travelers’ mental health and has emerged as a new model of service that complements traditional mental health treatments; however, this model lacks a focus on the specific characteristics and needs of the youth demographic, as well as a design perspective, which may contribute to the inability to provide long-term mental health support for youth due to insufficient social support. Therefore, this paper explores the ways in which service design can foster long-term mental health support for youth in spiritual tourism services. The paper begins with a theoretical analysis to identify the key characteristics and limitations of current spiritual tourism services while also addressing the principles of service design and the rationale for incorporating suburban experiential lodging as a case. Subsequently, qualitative methods, including ethnographic observations, demographic surveys, and in-depth interviews, were employed with eleven youth participants and three staff members to gather insights into their experiences and needs. The findings indicate that current spiritual tourism services are hindered by issues such as low accessibility, inadequate follow-up support, and design shortcomings. Furthermore, spiritual tourism services can be designed to systematically integrate the needs for natural environments, psychological identification, and social interaction, enhancing long-term mental health support for youth.