bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Impact of Public Health Emergencies on Urban Vitality Using a Difference-In-Difference Model
Authors: Chen Yuqiao , Li Bozhao , Liu Songcao , Cai Zhongliang
Published: May 2024

Urban vitality, a multifaceted construct, is influenced by economic conditions and urban structural characteristics, and can significantly be impacted by public health emergencies. While extensive research has been conducted on urban vitality, prevailing studies often rely on singular data sources, limiting the scope for holistic assessment. Moreover, there is a conspicuous absence of longitudinal analyses on urban vitality’s evolution and a dearth of quantitative causal evaluations of the effects of public health emergencies. Addressing these gaps, this study devises a comprehensive framework for evaluating urban vitality, assessing Wuhan’s vitality from 2018 to 2020 across economic, social, spatial, and ecological dimensions. Utilizing a Difference-In-Difference (DID) model, the impact of public health emergencies is quantified. The findings indicate pronounced spatial variations in Wuhan’s urban vitality, with a gradational decline from the city center; public health emergencies exhibit differential impacts across vitality dimensions, detrimentally affecting economic, social, and spatial aspects, while bolstering ecological vitality. Moreover, high population and high public budget revenue are identified as factors enhancing urban vitality and bolstering the city’s resilience against sudden adversities. This study offers valuable insights for geographers and urban planners, contributing to the refinement of urban development strategies.
Operational Forecasting of Global Ionospheric TEC Maps 1-, 2-, and 3-Day in Advance by ConvLSTM Model
Authors: Yang Jiayue , Huang Wengeng , Xia Guozhen , Zhou Chen , Chen Yanhong
Published: May 2024

In this paper, we propose a global ionospheric total electron content (TEC) maps (GIM) prediction model based on deep learning methods that is both straightforward and practical, meeting the requirements of various applications. The proposed model utilizes an encoder-decoder structure with a Convolution Long Short-Term Memory (ConvLSTM) network and has a spatial resolution of 5° longitude and 2.5° latitude, with a time resolution of 1 h. We utilized the Center for Orbit Determination in Europe (CODE) GIM dataset for 18 years from 2002 to 2019, without requiring any other external input parameters, to train the ConvLSTM models for forecasting GIM 1, 2, and 3 days in advance. Using the CODE GIM data from 1 January 2020 to 31 December 2023 as the test dataset, the performance evaluation results show that the average root mean square errors (RMSE) for 1, 2 and 3 days of forecasts are 2.81 TECU, 3.16 TECU, and 3.41 TECU, respectively. These results show improved performance compared to the IRI-Plas model and CODE’s 1-day forecast product c1pg, and comparable to CODE’s 2-day forecast c2pg. The model’s predictions get worse as the intensity of the storm increases, and the prediction error of the model increases with the lead time.
Refining ICESAT-2 ATL13 Altimetry Data for Improving Water Surface Elevation Accuracy on Rivers
Authors: Chen Yun , Liu Qihang , Ticehurst Catherine , Sarker Chandrama , Karim Fazlul , Penton Dave , Sengupta Ashmita
Published: May 2024

The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect solely with water. It is acknowledged that the ATL13 product has noise elevations of the adjacent land, resulting in biased high mean WSEs at VSs. Earlier studies have relied on human intervention or water masks to resolve this. Both approaches are unsatisfactory solutions for large river basins where the issue becomes pronounced due to many tributaries and meanders. There is no automated procedure to partition the truly representative water height from the totality of the along-track ICESAT-2 photon segments (portions of photon points along a beam) for increasing precision of the mean WSE at VSs. We have developed an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparing the ATL13-derived WSEs with direct water level observations at 10 different gauging stations on 37 different dates along the Lower Murray River, Australia. The concordance between the two datasets is significantly high and without detectable bias. In addition, we evaluated the effects of four methods for calculating the mean WSEs at VSs after auto-segmentation processing. Our results reveal that all methods perform almost equally well, with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189 m) and MAE (0.130–0.142 m). We also found that the R2, RMSE and MAE are better under the high flow condition (0.999, 0.124 and 0.111 m) than those under the normal-low flow condition (0.997, 0.208 and 0.160 m). Overall, our auto-segmentation method is an effective and efficient approach for deriving accurate mean WSEs at river VSs. It will contribute to the improvement of ICESAT-2 ATL13 altimetry data utility on rivers.
Envelope Extraction Algorithm for Magnetic Resonance Sounding Signals Based on Adaptive Gaussian Filters
Authors: Tian Baofeng , Duan Haoyu , Lin Yue-Der , Luan Hui
Published: May 2024

Magnetic resonance sounding is a geophysical method for quantitatively determining the state for groundwater storage that has gained international attention in recent years. However, the practical acquisition of magnetic resonance sounding signals, which are on the nanovolt scale, is susceptible to various types of interference, such as power-line harmonics, random noise, and spike noise. Such interference can degrade the quality of magnetic resonance sounding signals and, in severe cases, be completely drowned out by noise. This paper introduces an adaptive Gaussian filtering algorithm that is well-suited for handling intricate noise signals due to its adaptive solving characteristics and iterative sifting approach. Notably, the algorithm can process signals without relying on prior knowledge. The adaptive Gaussian filtering algorithm is applied for the envelope extraction of noisy magnetic resonance sounding signals, and the reliability and effectiveness of the method are rigorously validated. The simulation results reveal that, even under strong noise interference (with original signal-to-noise ratios ranging from −7 dB to −25 dB), the magnetic resonance sounding signal obtained after algorithmic processing is compared to the ideal signal, with 16 sets of data statistics, and the algorithm ensures an initial amplitude uncertainty within 4nV and restricts the uncertainty of the relaxation time within a 6 ms range. The signal-to-noise ratio can be boosted by up to 53 dB. The comparative assessments with classical algorithms such as empirical mode decomposition and the harmonic modeling method confirm the superior performance of the adaptive Gaussian filtering algorithm. The processing of the field data also fully proved the practical application effects of the algorithm.
Arctic Winds Retrieved from FY-3D Microwave Humidity Sounder-II 183.31 GHz Brightness Temperature Using Atmospheric Motion Vector Method
Authors: Li Bingxu , Guo Xi , Liu Hao , Han Donghao , Li Gang , Wu Ji
Published: May 2024

In this study, we develop an Atmospheric Motion Vector (AMV)-based method for retrieving wind vectors using 183.31 GHz water-vapor absorption channels. The method involves tracking water-vapor features from image triplets and subsequently deriving wind fields from motion vectors. The height of the derived wind for each channel is determined by calculating the weighing function peak using monthly averaged ERA5 reanalysis data. By utilizing Microwave Humidity Sounder-II (MWHS-II) brightness temperatures from the five channels centered around 183.31 GHz, wind vectors are retrieved within the Arctic region for the entire year of 2022. The retrieval quality is evaluated through comparative analysis with ERA5 reanalysis data and the Visible Infrared Imaging Radiometer Suite (VIIRS) wind product. The resultant vector root mean square errors (RMSEs) are approximately 4.5 m/s for the three lower-height channels and 5.5 m/s for the two upper-height channels. These findings demonstrate a wind retrieval performance comparable to the existing methods, highlighting its potential for augmenting wind availability at lower height levels.
Fire Vulnerability, Resilience, and Recovery Rates of Mediterranean Pine Forests Using a 33-Year Time Series of Satellite Imagery
Authors: Peña-Molina Esther , Moya Daniel , Marino Eva , Tomé José Luis , Fajardo-Cantos Álvaro , González-Romero Javier , Lucas-Borja Manuel Esteban , de las Heras Jorge
Published: May 2024

The modification of fire regimes and their impact on vegetation recovery, soil properties, and fuel structure are current key research areas that attempt to identify the thresholds of vegetation’s susceptibility to wildfires. This study aimed to evaluate the vulnerability of Mediterranean pine forests (Pinus halepensis Mill. and Pinus pinaster Aiton) to wildfires, analyzing two major forest fires that occurred in Yeste (Spain) in 1994 and 2017, affecting over 14,000 and 3200 hectares, respectively. Four recovery regions were identified based on fire severity—calculated using the delta Normalized Burn Ratio (dNBR) index—and recurrence: areas with high severity in 2017 but not in 1994 (UB94-HS17), areas with high severity in 1994 but not in 2017 (HS94-UB17), areas with high severity in both fires (HS94-HS17), and areas unaffected by either fire (UB94-UB17). The analysis focused on examining the recovery patterns of three spectral indices—the Normalized Difference Vegetation Index (NDVI), Normalized Moisture Index (NDMI), and Normalized Burn Ratio (NBR)—using the Google Earth Engine platform from 1990 to 2023. Additionally, the Relative Recovery Indicator (RRI), the Ratio of Eighty Percent (R80P), and the Year-on-Year average (YrYr) metrics were computed to assess the spectral recovery rates by region. These three spectral indices showed similar dynamic responses to fire. However, the Mann–Kendall and unit root statistical tests revealed that the NDVI and NDMI exhibited distinct trends, particularly in areas with recurrence (HS94-HS17). The NDVI outperformed the NBR and NDMI in distinguishing variations among regions. These results suggest accelerated vegetation spectral regrowth in the short term. The Vegetation Recovery Capacity After Fire (VRAF) index showed values from low to moderate, while the Vulnerability to Fire (V2FIRE) index exhibited values from medium to high across all recovery regions. These findings enhance our understanding of how vegetation recovers from fire and how vulnerable it is to fire.
Efficient Structure from Motion for Large-Size Videos from an Open Outdoor UAV Dataset
Authors: Xiang Ruilin , Chen Jiagang , Ji Shunping
Published: May 2024

Modern UAVs (unmanned aerial vehicles) equipped with video cameras can provide large-scale high-resolution video data. This poses significant challenges for structure from motion (SfM) and simultaneous localization and mapping (SLAM) algorithms, as most of them are developed for relatively small-scale and low-resolution scenes. In this paper, we present a video-based SfM method specifically designed for high-resolution large-size UAV videos. Despite the wide range of applications for SfM, performing mainstream SfM methods on such videos poses challenges due to their high computational cost. Our method consists of three main steps. Firstly, we employ a visual SLAM (VSLAM) system to efficiently extract keyframes, keypoints, initial camera poses, and sparse structures from downsampled videos. Next, we propose a novel two-step keypoint adjustment method. Instead of matching new points in the original videos, our method effectively and efficiently adjusts the existing keypoints at the original scale. Finally, we refine the poses and structures using a rotation-averaging constrained global bundle adjustment (BA) technique, incorporating the adjusted keypoints. To enrich the resources available for SLAM or SfM studies, we provide a large-size (3840 × 2160) outdoor video dataset with millimeter-level-accuracy ground control points, which supplements the current relatively low-resolution video datasets. Experiments demonstrate that, compared with other SLAM or SfM methods, our method achieves an average efficiency improvement of 100% on our collected dataset and 45% on the EuRoc dataset. Our method also demonstrates superior localization accuracy when compared with state-of-the-art SLAM or SfM methods.
A Sensorized 3D-Printed Knee Test Rig for Preliminary Experimental Validation of Patellar Tracking and Contact Simulation
Authors: Michaud Florian , Mouzo Francisco , Dopico Daniel , Cuadrado Javier
Published: May 2024

Experimental validation of computational simulations is important because it provides empirical evidence to verify the accuracy and reliability of the simulated results. This validation ensures that the simulation accurately represents real-world phenomena, increasing confidence in the model’s predictive capabilities and its applicability to practical scenarios. The use of musculoskeletal models in orthopedic surgery allows for objective prediction of postoperative function and optimization of results for each patient. To ensure that simulations are trustworthy and can be used for predictive purposes, comparing simulation results with experimental data is crucial. Although progress has been made in obtaining 3D bone geometry and estimating contact forces, validation of these predictions has been limited due to the lack of direct in vivo measurements and the economic and ethical constraints associated with available alternatives. In this study, an existing commercial surgical training station was transformed into a sensorized test bench to replicate a knee subject to a total knee replacement. The original knee inserts of the training station were replaced with personalized 3D-printed bones incorporating their corresponding implants, and multiple sensors with their respective supports were added. The recorded movement of the patella was used in combination with the forces recorded by the pressure sensor and the load cells, to validate the results obtained from the simulation, which was performed by means of a multibody dynamics formulation implemented in a custom-developed library. The utilization of 3D-printed models and sensors facilitated cost-effective and replicable experimental validation of computational simulations, thereby advancing orthopedic surgery while circumventing ethical concerns.
Parkinson’s Kinetigraph for Wearable Sensor Detection of Clinically Unrecognized Early-Morning Akinesia in Parkinson’s Disease: A Case Report-Based Observation
Authors: Poplawska-Domaszewicz Karolina , Limbachiya Naomi , Lau Yue Hui , Chaudhuri Kallol Ray
Published: May 2024

Early-morning off periods, causing early-morning akinesia, can lead to significant motor and nonmotor morbidity in levodopa-treated fluctuating Parkinson’s disease (PD) cases. Despite validated bedside scales in clinical practice, such early-morning off periods may remain undetected unless specific wearable technologies, such as the Parkinson’s KinetiGraph™ (PKG) watch, are used. We report five PD cases for whom the PKG detected early-morning off periods that were initially clinically undetected and as such, untreated. These five cases serve as exemplars of this clinical gap in care. Post-PKG assessment, clinicians were alerted and targeted therapies helped abolish the early-morning off periods.
Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress Detection
Authors: Lange Lucas , Wenzlitschke Nils , Rahm Erhard
Published: May 2024

Smartwatch health sensor data are increasingly utilized in smart health applications and patient monitoring, including stress detection. However, such medical data often comprise sensitive personal information and are resource-intensive to acquire for research purposes. In response to this challenge, we introduce the privacy-aware synthetization of multi-sensor smartwatch health readings related to moments of stress, employing Generative Adversarial Networks (GANs) and Differential Privacy (DP) safeguards. Our method not only protects patient information but also enhances data availability for research. To ensure its usefulness, we test synthetic data from multiple GANs and employ different data enhancement strategies on an actual stress detection task. Our GAN-based augmentation methods demonstrate significant improvements in model performance, with private DP training scenarios observing an 11.90–15.48% increase in F1-score, while non-private training scenarios still see a 0.45% boost. These results underline the potential of differentially private synthetic data in optimizing utility–privacy trade-offs, especially with the limited availability of real training samples. Through rigorous quality assessments, we confirm the integrity and plausibility of our synthetic data, which, however, are significantly impacted when increasing privacy requirements.
Research on a Corrosion Detection Method for Oil Tank Bottoms Based on Acoustic Emission Technology
Authors: Hua Weixing , Chen Yan , Zhao Xiang , Yang Jiping , Chen Han , Wu Zhaojie , Fang Gang
Published: May 2024

This paper presents an acoustic emission (AE) detection method for refined oil storage tanks which is aimed towards specialized places such as oil storage tanks with high explosion-proof requirements, such as cave oil tanks and buried oil tanks. The method utilizes an explosion-proof acoustic emission instrument to detect the floor of a refined oil storage tank. By calculating the time difference between the defective acoustic signal and the speed of acoustic wave transmission, a mathematical model is constructed to analyze the detected signals. An independent channel AE detection system is designed, which can store the collected data in a piece of independent explosion-proof equipment, and can analyze and process the data in a safe area after the detection, solving the problems of a short signal acquisition distance and the weak safety protection applied to traditional AE instruments. A location analysis of the AE sources is conducted on the bottom plate of the tank, evaluating its corrosion condition accurately. The consistency between the evaluation and subsequent open-tank tests confirms that using AE technology effectively captures corrosion signals from oil storage tanks’ bottoms. The feasibility of carrying out online inspection under the condition of oil storage in vertical steel oil tanks was verified through a comparison with open inspections, which provided a guide for determining the inspection target and opening order of large-scale oil tanks.
Dual-Message QR Codes
Authors: Chou Kuo-Chien , Wang Ran-Zan
Published: May 2024

A novel dual-message QR code is proposed for carrying two individual messages that can be read by standard QR code readers: one from a close range and the other from a large distance. By exploring the module value determining the rule of typical QR code readers, we designed two-state module blocks that can be recognized as different module values through changing the distance from which the QR code is scanned, and applied them to construct the proposed dual-message QR code. Experiments were conducted to test the readability of the two messages within a dual-message QR code, with the results demonstrating the high feasibility of the proposed method. The dual-message QR code can be applied for designing creative applications. For example, an interactive wedding card that can access the growing film of the groom and that of the bride interchangeably, which bring the viewers a higher-quality experience.
Novel Approach Combining Shallow Learning and Ensemble Learning for the Automated Detection of Swallowing Sounds in a Clinical Database
Authors: Kimura Satoru , Emoto Takahiro , Suzuki Yoshitaka , Shinkai Mizuki , Shibagaki Akari , Shichijo Fumio
Published: May 2024

Cervical auscultation is a simple, noninvasive method for diagnosing dysphagia, although the reliability of the method largely depends on the subjectivity and experience of the evaluator. Recently developed methods for the automatic detection of swallowing sounds facilitate a rough automatic diagnosis of dysphagia, although a reliable method of detection specialized in the peculiar feature patterns of swallowing sounds in actual clinical conditions has not been established. We investigated a novel approach for automatically detecting swallowing sounds by a method wherein basic statistics and dynamic features were extracted based on acoustic features: Mel Frequency Cepstral Coefficients and Mel Frequency Magnitude Coefficients, and an ensemble learning model combining Support Vector Machine and Multi-Layer Perceptron were applied. The evaluation of the effectiveness of the proposed method, based on a swallowing-sounds database synchronized to a video fluorographic swallowing study compiled from 74 advanced-age patients with dysphagia, demonstrated an outstanding performance. It achieved an F1-micro average of approximately 0.92 and an accuracy of 95.20%. The method, proven effective in the current clinical recording database, suggests a significant advancement in the objectivity of cervical auscultation. However, validating its efficacy in other databases is crucial for confirming its broad applicability and potential impact.
Enhancing the Responsiveness of Thermoelectric Gas Sensors with Boron-Doped and Thermally Annealed SiGe Thin Films via Low-Pressure Chemical Vapor Deposition
Authors: Shin Woosuck , Nishibori Maiko , Itoh Toshio , Izu Noriya , Matsubara Ichiro
Published: May 2024

Thermoelectric gas sensor (THGS) devices with catalysts and Si0.8Ge0.2 thin films of different boron doping levels of 1018, 1019, and 1020 cm−3 were fabricated, and their transport properties are investigated. SiGe films were deposited on Si3N4/SiO2 multilayers on Si substrates using low-pressure chemical vapor deposition (LPCVD) and thermally annealed at 1050 °C. The Seebeck coefficients of the SiGe films were increased after thermal annealing, ranging from 191 to 275 μV/K at temperatures of 74 to 468 °C in air, and reaching the highest power factor of 6.78 × 10−4 W/mK2 at 468 °C. The thermal conductivity of the SiGe films varied from 2.4 to 3.0 W/mK at 25 °C. The THGS detection performance was tested for the H2 gas in air from 0.01 to 1.0%, and compared to the thermoelectric properties of the SiGe films. The high-temperature annealing treatment process was successful in enhancing the thermoelectric performance of both the SiGe films and sensor devices, achieving the best THGS performance with the sensor device fabricated from the annealed SiGe film with 1018 cm−3 boron-doped Si0.8Ge0.2.
High-Voltage Cable Buffer Layer Ablation Fault Identification Based on Artificial Intelligence and Frequency Domain Impedance Spectroscopy
Authors: Liu Jiajun , Ma Mingchao , Liu Xin , Xu Haokun
Published: May 2024

In recent years, the occurrence of high-voltage cable buffer layer ablation faults has become frequent, posing a serious threat to the safe and stable operation of cables. Failure to promptly detect and address such faults may lead to cable breakdowns, impacting the normal operation of the power system. To overcome the limitations of existing methods for identifying buffer layer ablation faults in high-voltage cables, a method for identifying buffer layer ablation faults based on frequency domain impedance spectroscopy and artificial intelligence is proposed. Firstly, based on the cable distributed parameter model and frequency domain impedance spectroscopy, a mathematical model of the input impedance of a cable containing buffer layer ablation faults is derived. Through a simulation, the input impedance spectroscopy at the first end of the cables under normal conditions, buffer layer ablation, local aging, and inductive faults is performed, enabling the identification of inductive and capacitive faults through a comparative analysis. Secondly, the frequency domain amplitude spectroscopy of the buffer layer ablation and local aging faults are used as datasets and are input into a neural network model for training and validation to identify buffer layer ablation and local aging faults. Finally, using multiple evaluation metrics to assess the neural network model validates the superiority of the MLP neural network in cable fault identification models and experimentally confirms the effectiveness of the proposed method.
Extended-Aperture Shape Measurements Using Spatially Partially Coherent Illumination (ExASPICE)
Authors: Agour Mostafa , Falldorf Claas , Bergmann Ralf B.
Published: May 2024

We have recently demonstrated that the 3D shape of micro-parts can be measured using LED illumination based on speckle contrast evaluation in the recently developed SPICE profilometry (shape measurements based on imaging with spatially partially coherent illumination). The main advantage of SPICE is its improved robustness and measurement speed compared to confocal or white light interferometry. The limited spatial coherence of the LED illumination is used for depth discrimination. An electrically tunable lens in a 4f-configuration is used for fast depth scanning without mechanically moving parts. The approach is efficient, takes less than a second to capture required images, is eye-safe and offers a depth of focus of a few millimeters. However, SPICE’s main limitation is its assumption of a small illumination aperture. Such a small illumination aperture affects the axial scan resolution, which dominates the measurement uncertainty. In this paper, we propose a novel method to overcome the aperture angle limitation of SPICE by illuminating the object from different directions with several independent LED sources. This approach reduces the full width at half maximum of the contrast envelope to one-eighth, resulting in a twofold improvement in measurement accuracy. As a proof of concept, shape measurements of various metal objects are presented.
RBS and ABS Coordinated Control Strategy Based on Explicit Model Predictive Control
Authors: Chu Liang , Li Jinwei , Guo Zhiqi , Jiang Zewei , Li Shibo , Du Weiming , Wang Yilin , Guo Chong
Published: May 2024

During the braking process of electric vehicles, both the regenerative braking system (RBS) and anti-lock braking system (ABS) modulate the hydraulic braking force, leading to control conflict that impacts the effectiveness and real-time capability of coordinated control. Aiming to enhance the coordinated control effectiveness of RBS and ABS within the electro-hydraulic composite braking system, this paper proposes a coordinated control strategy based on explicit model predictive control (eMPC-CCS). Initially, a comprehensive braking control framework is established, combining offline adaptive control law generation, online optimized control law application, and state compensation to effectively coordinate braking force through the electro-hydraulic system. During offline processing, eMPC generates a real-time-oriented state feedback control law based on real-world micro trip segments, improving the adaptiveness of the braking strategy across different driving conditions. In the online implementation, the developed three-dimensional eMPC control laws, corresponding to current driving conditions, are invoked, thereby enhancing the potential for real-time braking strategy implementation. Moreover, the state error compensator is integrated into eMPC-CCS, yielding a state gain matrix that optimizes the vehicle braking status and ensures robustness across diverse braking conditions. Lastly, simulation evaluation and hardware-in-the-loop (HIL) testing manifest that the proposed eMPC-CCS effectively coordinates the regenerative and hydraulic braking systems, outperforming other CCSs in terms of braking energy recovery and real-time capability.
Semi-TSGAN: Semi-Supervised Learning for Highlight Removal Based on Teacher-Student Generative Adversarial Network
Authors: Zheng Yuanfeng , Yan Yuchen , Jiang Hao
Published: May 2024

Despite recent notable advancements in highlight image restoration techniques, the dearth of annotated data and the lightweight deployment of highlight removal networks pose significant impediments to further advancements in the field. In this paper, to the best of our knowledge, we first propose a semi-supervised learning paradigm for highlight removal, merging the fusion version of a teacher–student model and a generative adversarial network, featuring a lightweight network architecture. Initially, we establish a dependable repository to house optimal predictions as pseudo ground truth through empirical analyses guided by the most reliable No-Reference Image Quality Assessment (NR-IQA) method. This method serves to assess rigorously the quality of model predictions. Subsequently, addressing concerns regarding confirmation bias, we integrate contrastive regularization into the framework to curtail the risk of overfitting on inaccurate labels. Finally, we introduce a comprehensive feature aggregation module and an extensive attention mechanism within the generative network, considering a balance between network performance and computational efficiency. Our experimental evaluations encompass comprehensive assessments on both full-reference and non-reference highlight benchmarks. The results demonstrate conclusively the substantive quantitative and qualitative enhancements achieved by our proposed algorithm in comparison to state-of-the-art methodologies.
Lower Limb Motion Recognition with Improved SVM Based on Surface Electromyography
Authors: Tu Pengjia , Li Junhuai , Wang Huaijun
Published: May 2024

During robot-assisted rehabilitation, failure to recognize lower limb movement may efficiently limit the development of exoskeleton robots, especially for individuals with knee pathology. A major challenge encountered with surface electromyography (sEMG) signals generated by lower limb movements is variability between subjects, such as motion patterns and muscle structure. To this end, this paper proposes an sEMG-based lower limb motion recognition using an improved support vector machine (SVM). Firstly, non-negative matrix factorization (NMF) is leveraged to analyze muscle synergy for multi-channel sEMG signals. Secondly, the multi-nonlinear sEMG features are extracted, which reflect the complexity of muscle status change during various lower limb movements. The Fisher discriminant function method is utilized to perform feature selection and reduce feature dimension. Then, a hybrid genetic algorithm-particle swarm optimization (GA-PSO) method is leveraged to determine the best parameters for SVM. Finally, the experiments are carried out to distinguish 11 healthy and 11 knee pathological subjects by performing three different lower limb movements. Results demonstrate the effectiveness and feasibility of the proposed approach in three different lower limb movements with an average accuracy of 96.03% in healthy subjects and 93.65% in knee pathological subjects, respectively.
Aluminum Removal from Rare Earth Chloride Solution through Regulated Hydrolysis via Electrochemical Method
Authors: Zhu Yaoyao , Li Jian , Xie Dongyue , Zhang Hui , Li Man , Xu Binfeng , Zhang Xuxia , Xie Yangyang , Qi Tao
Published: May 2024

Due to the coexistence of Al3+ and RE3+ and their similar properties, the separation of aluminum from rare earths is difficult. In this study, selective precipitation was used to separate aluminum from rare earth chloride solution via electrochemical regulated hydrolysis. By controlling the current density and electrolytic time, the rate of hydroxyl ion production was regulated, and the selective separation of rare earth and aluminum was realized according to the different precipitation sequences. By altering the temperature, current density, pH value, and other parameters, the separation performance of aluminum from rare earth in mixed rare earth chloride systems was systematically investigated. The removal rate of aluminum reached 88.35%, and the loss rate of rare earth was only 5.99% under optimized conditions. Compared with traditional neutralization hydrolysis, the new process showed higher efficiency and lower rare earth loss rate. Furthermore, a kinetic analysis of aluminum precipitation revealed that the reaction adhered to pseudo-first order kinetics. Additionally, the precipitate obtained via separation and filtration was amorphous alumina hydroxide with a small amount of rare earth attached. No reagent was consumed for the new process, which was more efficient and cleaner, providing a new idea for removing aluminum impurities from rare earth solutions.
Assessing the Impact of Fencing on Postural Parameters: Observational Study Findings on Elite Athletes
Authors: Di Martino Giulia , Centorbi Marco , Buonsenso Andrea , Fiorilli Giovanni , della Valle Carlo , Iuliano Enzo , Calcagno Giuseppe , di Cagno Alessandra
Published: May 2024

The aim of the study was to evaluate whether the static stabilometric parameters among elite fencers, were affected by prolonged, asymmetric training regimen. A sample of 26 elite fencers of both genders, aged 19.15 ± 2.24 years, practising one of the three disciplines foil, épée, or sabre, was recruited for the study. Anthropometric measurements including thigh and calf circumferences and postural assessment based on the weight distribution on a stabilimeter platform were performed. Postural tone, as indicated by measures such as sway length and sway area ratio was calculated.. No notable anthropometric asymmetries were detected within the examined group The weight distribution patterns on the support quadrants in static stabilometric measurements did not suggest clinically significant issues. There were no significant differences among subgroups based on gender and lower limb dominance for both anthropometric and stabilimeter variables. However, 30.8% of participants showed anomalies in postural tone (hypertonic and hypotonic condition). Five out of eight athletes found with abnormal postural tone were foil fencers, suggesting a potential discipline-specific effect. Individual adjustments were found in foil fencers. These findings provide insights into the potential effects of fencing training on postural parameters among elite athletes.
Waiting Strategy for the Dynamic Meal Delivery Routing Problem with Time-Sensitive Customers Using a Hybrid Adaptive Genetic Algorithm and Adaptive Large Neighborhood Search Algorithm
Authors: Wang Wenjie , Gao Shen
Published: May 2024

In this paper, we study the dynamic meal delivery routing problem (MDRP) with time-sensitive customers. The multi-objective MDRP optimization model is developed to maximize customer satisfaction and minimize delay penalty cost and riding cost. To solve the dynamic MDRP, a novel waiting strategy is proposed to divide the dynamic problem into a series of static subproblems. This waiting strategy utilizes the decision threshold to determine rerouting points based on the number of dynamic meal orders. Meanwhile, time-sensitive priority is introduced to accelerate assignment and routing decisions for orders from customers with high time sensitivity. For each static subproblem, a hybrid AGA–ALNS algorithm that incorporates the adaptive genetic algorithm and adaptive large neighborhood search is developed to improve both the global and local search capabilities of the genetic algorithm. We validate the performance of the proposed waiting strategy and the AGA–ALNS algorithm through numerical instances. In addition, managerial insights are obtained from sensitivity analysis experiments.
The Impact and Spatial Spillover Effects of Tourism Development on Urban Welfare: Empirical Evidence from the Yangtze River Delta in China
Authors: Chen Gong , Hu Meijuan , Li Zaijun , Kang Lexin
Published: May 2024

The ultimate goal of China’s tourism industry is to create a flourishing sector that brings happiness. It is of immense theoretical and practical importance to investigate the impact of tourism development (TD) on urban welfare (UW) and uncover its spatial spillover characteristics from a macro perspective. Utilizing panel data from 41 cities in the Yangtze River Delta region from 2000 to 2021, this study applies the spatial panel Durbin model to explore the direct and spillover effects of TD on UW. The results show that TD significantly boosts UW in both local and neighboring areas, with the spillover effects taking a dominant position in the total effects. Examining the sub-dimensions of UW, the local welfare effects of TD primarily stem from economic welfare, whereas the spillover effects are characterized by the “three-wheel drive” of economic, social, and environmental welfare. This study can provide practical insights into the coordinated and sustainable development of the regional tourism industry.
Stress Responses and Ammonia Nitrogen Removal Efficiency of Oocystis lacustris in Saline Ammonium-Contaminated Wastewater Treatment
Authors: Zhu Yuqi , Zhang Yili , Chen Hui , Zhang Lisha , Shen Chensi
Published: May 2024

The increasing concern over climate change has spurred significant interest in exploring the potential of microalgae for wastewater treatment. Among the various types of industrial wastewaters, high-salinity NH4+-N wastewater stands out as a common challenge. Investigating microalgae’s resilience to NH4+-N under high-salinity conditions and their efficacy in NH4+-N utilization is crucial for advancing industrial wastewater microalgae treatment technologies. This study evaluated the effectiveness of employing nitrogen-efficient microalgae, specifically Oocystis lacustris, for NH4+-N removal from saline wastewater. The results revealed Oocystis lacustris’s tolerance to a Na2SO4 concentration of 5 g/L. When the Na2SO4 concentration reached 10 g/L, the growth inhibition experienced by Oocystis lacustris began to decrease on the 6th day of cultivation, with significant alleviation observed by the 7th day. Additionally, the toxic mechanism of saline NH4+-N wastewater on Oocystis lacustris was analyzed through various parameters, including chlorophyll-a, soluble protein, oxidative stress indicators, key nitrogen metabolism enzymes, and microscopic observations of algal cells. The results demonstrated that when the Oocystis lacustris was in the stationary growth phase with an initial density of 2 × 107 cells/L, NH4+-N concentrations of 1, 5, and 10 mg/L achieved almost 100% removal of the microalgae on the 1st, 2nd, and 4th days of treatment, respectively. On the other hand, saline NH4+-N wastewater minimally impacted photosynthesis, protein synthesis, and antioxidant systems within algal cells. Additionally, NH4+-N within the cells was assimilated into glutamic acid through glutamate dehydrogenase-mediated pathways besides the conventional pathway involving NH4+-N conversion into glutamine and assimilation amino acids.
Migration Patterns and Potential Risk Assessment of Trace Elements in the Soil–Plant System in the Production Area of the Chinese Medicinal Herb Scrophularia ningpoensis Hemsl.
Authors: Gong Yufeng , Ren Wei , Zhang Zhenming
Published: May 2024

Scrophularia ningpoensis Hemsl. holds a prominent place among Chinese medicinal herbs. Assessing the soil–plant system of its origin is crucial for ensuring medication safety. Although some trace elements are essential for the normal functioning of living organisms, exposure to higher concentrations is harmful to humans, so in order to assess the possible health risk of trace elements in the soil–plant system of Scrophularia ningpoensis Hemsl. origin for human assessment, we used non-carcinogenic risk (HI) and carcinogenic risk (CR) for their evaluation. In this paper, the following trace elements were studied in the soil–Scrophularia ningpoensis Hemsl. system: manganese (Mn), iron (Fe), cobalt (Co), zinc (Zn), selenium (Se), molybdenum (Mo), arsenic (As) and lead (Pb). Correlation and structural equation analyses showed that the effect of soil in the root zone on the plant was much greater than the effect of soil in the non-root zone on the plant. The single-factor pollution index (Pi) showed that the soil in the production area of Scrophularia ningpoensis Hemsl. was polluted to a certain extent, notably with Pb showing the highest average Pi values of 0.94 and 0.89 in the non-root and root zones, respectively. Additionally, the Nemerow composite pollution indices (PN) for both zones indicated an alert range. Regarding health risks, exposure to soil in the non-root zone posed higher non-carcinogenic risk (HI) and carcinogenic risk (CR) compared to the root zone, although neither zone presented a significant carcinogenic risk. The potential non-carcinogenic risk (HI) and carcinogenic risk (CR) from consuming Scrophularia ningpoensis Hemsl. leaves and stems were more than ten times higher than that of roots. However, the carcinogenic risk (CR) values for both the soil and plant of interest in the soil– Scrophularia ningpoensis Hemsl. system did not exceed 10−4, and therefore no significant carcinogenic risk existed.
Pulmonary Thromboembolism following Russell’s Viper Bites
Authors: Senthilkumaran Subramanian , Sampath Sasikumar , Almeida José R. , Williams Jarred , Williams Harry F. , Patel Ketan , Thirumalaikolundusubramanian Ponniah , Vaiyapuri Sakthivel
Published: May 2024

Snakebite envenoming and its resulting complications are serious threats to the health of vulnerable people living in rural areas of developing countries. The knowledge of the heterogeneity of symptoms associated with snakebite envenoming and their management strategies is vital to treat such life-threatening complications to save lives. Russell’s viper envenomation induces a diverse range of clinical manifestations from commonly recognised haemotoxic and local effects to several rare conditions that are often not reported. The lack of awareness about these unusual manifestations can affect prompt diagnosis, appropriate therapeutic approaches, and positive outcomes for patients. Here, we report pulmonary thromboembolism that developed in three patients following Russell’s viper envenomation and demonstrate their common clinical features and diagnostic and therapeutic approaches used. All patients showed clinical signs of local (oedema) and systemic (blood coagulation disturbances) envenomation, which were treated using polyvalent antivenom. They exhibited elevated heart rates, breathlessness, and reduced oxygen saturation, which are non-specific but core parameters in the diagnosis of pulmonary embolism. The recognition of pulmonary embolism was also achieved by an electrocardiogram, which showed sinus tachycardia and computed tomography and echocardiogram scans further confirmed this condition. Anti-coagulant treatment using low-molecular-weight heparin offered clinical benefits in these patients. In summary, this report reinforces the broad spectrum of previously unreported consequences of Russell’s viper envenomation. The constant updating of healthcare professionals and the dissemination of major lessons learned in the clinical management of snakebite envenoming through scientific documentation and educational programs are necessary to mitigate the adverse impacts of venomous snakebites in vulnerable communities.
Intramuscular Botulinum Neurotoxin Serotypes E and A Elicit Distinct Effects on SNAP25 Protein Fragments, Muscular Histology, Spread and Neuronal Transport: An Integrated Histology-Based Study in the Rat
Authors: Martin Vincent , Carre Denis , Bilbault Heloise , Oster Sebastien , Limana Lorenzo , Sebal Florian , Favre-Guilmard Christine , Kalinichev Mikhail , Leveque Christian , Boulifard Virginie , George Catherine , Lezmi Stephane
Published: May 2024

Botulinum neurotoxins E (BoNT/E) and A (BoNT/A) act by cleaving Synaptosome-Associated Protein 25 (SNAP25) at two different C-terminal sites, but they display very distinct durations of action, BoNT/E being short acting and BoNT/A long acting. We investigated the duration of action, spread and neuronal transport of BoNT/E (6.5 ng/kg) and BoNT/A (125 pg/kg) after single intramuscular administrations of high equivalent efficacious doses, in rats, over a 30- or 75-day periods, respectively. To achieve this, we used (i) digit abduction score assay, (ii) immunohistochemistry for SNAP25 (N-ter part; SNAP25N-ter and C-ter part; SNAP25C-ter) and its cleavage sites (cleaved SNAP25; c-SNAP25E and c-SNAP25A) and (iii) muscular changes in histopathology evaluation. Combined in vivo observation and immunohistochemistry analysis revealed that, compared to BoNT/A, BoNT/E induces minimal muscular changes, possesses a lower duration of action, a reduced ability to spread and a decreased capacity to be transported to the lumbar spinal cord. Interestingly, SNAP25C-ter completely disappeared for both toxins during the peak of efficacy, suggesting that the persistence of toxin effects is driven by the persistence of proteases in tissues. These data unveil some new molecular mechanisms of action of the short-acting BoNT/E and long-acting BoNT/A, and reinforce their overall safety profiles.
Evaluating the Efficacy of a Peripheral Nerve Simulator-Guided Brachial Plexus Block in Rabbits Undergoing Orthopaedic Surgery Compared to Systemic Analgesia
Authors: Mead Sophie A. , Allen Matthew J. , Elsayed Sara Ahmed Hassouna , Gittel Claudia S.
Published: May 2024

Locoregional anaesthetic techniques are invaluable for providing multimodal analgesia for painful surgical procedures. This prospective, randomised study describes a nerve stimulator-guided brachial plexus blockade (BPB) in rabbits undergoing orthopaedic surgery in comparison to systemic lidocaine. Premedication was provided with intramuscular (IM) medetomidine, fentanyl, and midazolam. Anaesthesia was induced (propofol IV) and maintained with isoflurane. Nine rabbits received a lidocaine BPB (2%; 0.3 mL kg−1), and eight received a lidocaine constant rate infusion (CRI) (2 mg kg−1 IV, followed by 100 µg kg−1 min−1). Rescue analgesia was provided with fentanyl IV. Carprofen was administered at the end of the surgery. Postoperative pain was determined using the Rabbit Grimace Scale (RGS) and a composite pain scale. Buprenorphine was administered according to the pain score for two hours after extubation. Rabbits were filmed during the first two hours to measure distance travelled and behaviours. Food intake and faeces output were compared. Every rabbit in CRI required intraoperative rescue analgesia compared to none in BPB. However, rabbits in both groups had similar pain scores, and there was no difference in the administration of postoperative analgesia. There were no significant differences in food intake or faeces production over 18 h, and no significant differences in distance travelled or behaviours examined during the first two hours. BPB seems superior for intraoperative analgesia. Postoperatively, both groups were comparable.