bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantifying Intermittent Flow Regimes in Ungauged Basins: Optimization of Remote Sensing Techniques for Ephemeral Channels Using a Flexible Statistical Classification
Authors: Davidson Lea J. , Milewski Adam M. , Holland Steven M.
Published: December 2023

Intermittent and ephemeral channels are a critical component of the global hydrologic network. The dominant feature in dryland environments, ephemeral channel transmission loss facilitates aquifer recharge. Characterizing flow intermittency improves groundwater storage estimates; however, limited gauging of intermittent systems impedes this understanding. This research develops an improved classification for surface flow, optimized for ephemeral systems using linear discriminant function analysis and remotely sensed imagery. It further applies this methodology to assess temporal and spatial flow patterns across the Souss channel, an ungauged, ephemeral system in central Morocco. Linear discriminant function analysis demonstrates high predictive accuracy for Landsat imagery, with significantly improved classification success as compared to the Modified Normalized Difference Water Index. Application to the Souss channel from 1984 to 2022 points to a decreasing trend in flow frequency. Despite this change, flow events remain concentrated within the wet season, critical for regional aquifer recharge. Spatial flow characteristics further support sustained infiltration, with the majority of events focused within the upstream channel section during both dry and wet seasons. Decreased occurrence moving downstream highlights the likely impact of additional factors such as transmission loss, evapotranspiration, and agricultural abstraction contributing to channel intermittency.
Bicycle Data-Driven Application Framework: A Dutch Case Study on Machine Learning-Based Bicycle Delay Estimation at Signalized Intersections Using Nationwide Sparse GPS Data
Authors: Yuan Yufei , Wang Kaiyi , Duives Dorine , Hoogendoorn Serge , Hoogendoorn-Lanser Sascha , Lindeman Rick
Published: December 2023

Data-driven approaches are helpful for quantitative justification and performance evaluation. The Netherlands has made notable strides in establishing a national protocol for bicycle traffic counting and collecting GPS cycling data through initiatives such as the Talking Bikes program. This article addresses the need for a generic framework to harness cycling data and extract relevant insights. Specifically, it focuses on the application of estimating average bicycle delays at signalized intersections, as this is an essential variable in assessing the performance of the transportation system. This study evaluates machine learning (ML)-based approaches using GPS cycling data. The dataset provides comprehensive yet incomplete information regarding one million bicycle rides annually across The Netherlands. These ML models, including random forest, k-nearest neighbor, support vector regression, extreme gradient boosting, and neural networks, are developed to estimate bicycle delays. The study demonstrates the feasibility of estimating bicycle delays using sparse GPS cycling data combined with publicly accessible information, such as weather information and intersection complexity, leveraging the burden of understanding local traffic conditions. It emphasizes the potential of data-driven approaches to inform traffic management, bicycle policy, and infrastructure development.
A Novel Lightweight Human Activity Recognition Method Via L-CTCN
Authors: Ding Xue , Li Zhiwei , Yu Jinyang , Xie Weiliang , Li Xiao , Jiang Ting
Published: December 2023

Wi-Fi-based human activity recognition has attracted significant attention. Deep learning methods are widely used to achieve feature representation and activity sensing. While more learnable parameters in the neural networks model lead to richer feature extraction, it results in significant resource consumption, rendering the model unsuitable for lightweight Internet of Things (IoT) devices. Furthermore, the sensing performance heavily relies on the quality and quantity of data, which is a time-consuming and labor-intensive task. Therefore, there is a need to explore methods that reduce the dependence on the quality and quantity of the dataset while ensuring recognition performance and decreasing model complexity to adapt to ubiquitous lightweight IoT devices. In this paper, we propose a novel Lightweight-Complex Temporal Convolution Network (L-CTCN) for human activity recognition. Specifically, this approach effectively combines complex convolution with a Temporal Convolution Network (TCN). Complex convolution can extract richer information from limited raw complex data, reducing the reliance on the quality and quantity of training samples. Based on the designed TCN framework with 1D convolution and residual blocks, the proposed model can achieve lightweight human activity recognition. Extensive experiments verify the effectiveness of the proposed method. We can achieve an average recognition accuracy of 96.6% with only 0.17 M parameter size. This method performs well under conditions of low sampling rates and a low number of subcarriers and samples.
A HOOI-Based Fast Parameter Estimation Algorithm in UCA-UCFO Framework
Authors: Wang Yuan , Wang Xianpeng , Su Ting , Guo Yuehao , Lan Xiang
Published: December 2023

In this paper, we introduce a Reduced-Dimension Multiple-Signal Classification (RD-MUSIC) technique via Higher-Order Orthogonal Iteration (HOOI), which facilitates the estimation of the target range and angle for Frequency-Diverse Array Multiple-Input–Multiple-Output (FDA-MIMO) radars in the unfolded coprime array with unfolded coprime frequency offsets (UCA-UCFO) structure. The received signal undergoes tensor decomposition by the HOOI algorithm to get the core and factor matrices, then the 2D spectral function is built. The Lagrange multiplier method is used to obtain a one-dimensional spectral function, reducing complexity for estimating the direction of arrival (DOA). The vector of the transmitter is obtained by the partial derivatives of the Lagrangian function, and its rotational invariance facilitates target range estimation. The method demonstrates improved operation speed and decreased computational complexity with respect to the classic Higher-Order Singular-Value Decomposition (HOSVD) technique, and its effectiveness and superiority are confirmed by numerical simulations.
Automatic Detection of Magnetic Disturbances in Magnetic Inertial Measurement Unit Sensors Based on Recurrent Neural Networks
Authors: Belalcazar-Bolaños Elkyn Alexander , Torricelli Diego , Pons José L.
Published: December 2023

This paper proposes a new methodology for the automatic detection of magnetic disturbances from magnetic inertial measurement unit (MIMU) sensors based on deep learning. The proposed approach considers magnetometer data as input to a long short-term memory (LSTM) neural network and obtains a labeled time series output with the posterior probabilities of magnetic disturbance. We trained our algorithm on a data set that reproduces a wide range of magnetic perturbations and MIMU motions in a repeatable and reproducible way. The model was trained and tested using 15 folds, which considered independence in sensor, disturbance direction, and signal type. On average, the network can adequately detect the disturbances in 98% of the cases, which represents a significant improvement over current threshold-based detection algorithms.
Research on the Detection Method of Organic Matter in Tea Garden Soil Based on Image Information and Hyperspectral Data Fusion
Authors: Zhang Haowen , He Qinghai , Yang Chongshan , Lu Min , Liu Zhongyuan , Zhang Xiaojia , Li Xiaoli , Dong Chunwang
Published: December 2023

Soil organic matter is an important component that reflects soil fertility and promotes plant growth. The soil of typical Chinese tea plantations was used as the research object in this work, and by combining soil hyperspectral data and image texture characteristics, a quantitative prediction model of soil organic matter based on machine vision and hyperspectral imaging technology was built. Three methods, standard normalized variate (SNV), multisource scattering correction (MSC), and smoothing, were first used to preprocess the spectra. After that, random frog (RF), variable combination population analysis (VCPA), and variable combination population analysis and iterative retained information variable (VCPA-IRIV) algorithms were used to extract the characteristic bands. Finally, the quantitative prediction model of nonlinear support vector regression (SVR) and linear partial least squares regression (PLSR) for soil organic matter was established by combining nine color features and five texture features of hyperspectral images. The outcomes demonstrate that, in comparison to single spectral data, fusion data may greatly increase the performance of the prediction model, with MSC + VCPA-IRIV + SVR (R2C = 0.995, R2P = 0.986, RPD = 8.155) being the optimal approach combination. This work offers excellent justification for more investigation into nondestructive methods for determining the amount of organic matter in soil.
Efficient Internet-of-Things Cyberattack Depletion Using Blockchain-Enabled Software-Defined Networking and 6G Network Technology
Authors: Razaque Abdul , Yoo Joon , Bektemyssova Gulnara , Alshammari Majid , Chinibayeva Tolganay T. , Amanzholova Saule , Alotaibi Aziz , Umutkulov Dauren
Published: December 2023

Low-speed internet can negatively impact incident response by causing delayed detection, ineffective response, poor collaboration, inaccurate analysis, and increased risk. Slow internet speeds can delay the receipt and analysis of data, making it difficult for security teams to access the relevant information and take action, leading to a fragmented and inadequate response. All of these factors can increase the risk of data breaches and other security incidents and their impact on IoT-enabled communication. This study combines virtual network function (VNF) technology with software -defined networking (SDN) called virtual network function software-defined networking (VNFSDN). The adoption of the VNFSDN approach has the potential to enhance network security and efficiency while reducing the risk of cyberattacks. This approach supports IoT devices that can analyze large volumes of data in real time. The proposed VNFSDN can dynamically adapt to changing security requirements and network conditions for IoT devices. VNFSDN uses threat filtration and threat-capturing and decision-driven algorithms to minimize cyber risks for IoT devices and enhance network performance. Additionally, the integrity of IoT devices is safeguarded by addressing the three risk categories of data manipulation, insertion, and deletion. Furthermore, the prioritized delegated proof of stake (PDPoS) consensus variant is integrated with VNFSDN to combat attacks. This variant addresses the scalability issue of blockchain technology by providing a safe and adaptable environment for IoT devices that can quickly be scaled up and down to pull together the changing demands of the organization, allowing IoT devices to efficiently utilize resources. The PDPoS variant provides flexibility to IoT devices to proactively respond to potential security threats, preventing or mitigating the impact of cyberattacks. The proposed VNFSDN dynamically adapts to the changing security requirements and network conditions, improving network resiliency and enabling proactive threat detection. Finally, we compare the proposed VNFSDN to existing state-of-the-art approaches. According to the results, the proposed VNFSDN has a 0.08 ms minimum response time, a 2% packet loss rate, 99.5% network availability, a 99.36% threat detection rate, and a 99.77% detection accuracy with 1% malicious nodes.
Development and Validation of a Double-Sensor Hump Calibration Method for Articulated Vehicle Model Identification
Authors: Wu Yuhang , Li Yuanqi
Published: December 2023

The realistic simulation of the dynamic responses of a moving articulated vehicle has attracted considerable attention in various disciplines, with the identification of the vehicle model being the prerequisite. To this end, a double-sensor hump calibration method (DHCM) was developed to identify both unladen and laden vehicle models, consisting of a sensor layout optimization step and a system identification step. The first step was to optimize the number and position of sensors via parameter sensitivity analysis; the second was to inversely identify the vehicle system based on sensor responses. For comparison, the DHCM and the existing single-sensor hump calibration method (SHCM) were used to calibrate a small-sized vehicle model and a multi-axle articulated vehicle model. Vertical accelerations of the vehicle models were then simulated and characterized by power spectral densities (PSDs). Validation against experimental measurements indicated that the PSDs of the models identified with the DHCM matched the measured PSDs better than those of the SHCM, i.e., the DHCM-identified model accurately simulated the dynamic response of an articulated vehicle with relative errors below 16% in the low-frequency range. Therefore, the DHCM could identify models of small-sized vehicles and multi-axle articulated vehicles, while the SHCM was only suitable for the former.
Measuring System for Synchronous Recording of Kinematic and Force Data during Handover Action of Human Dyads
Authors: Kutz Dieter F. , Kopnarski Lena , Püschel Jochen , Rudisch Julian , Voelcker-Rehage Claudia
Published: December 2023

Handover actions are joint actions between two people in which an object is handed over from a giver to a receiver. This necessitates precise coordination and synchronization of both the reach and grasp kinematics and the scaling of grip forces of the actors during the interaction. For this purpose, a measurement object is presented that records the grip forces of both actors on the instrument and allows synchronous measurement of the kinematic data of both actors and the position and orientation of the instrument in space using an optical motion capture system. Additionally, the object allows one to alter its weight in a covert fashion so that it cannot be anticipated by the actors. It is shown that the four phases of a handover, (1) reach and grasp, (2) object transport, (3) object transfer, and (4) end of handover, can be clearly identified with the described measurement system. This allows the user to measure movement kinematics and grip forces during the individual phases with high precision and therefore systematically investigate handover actions. Using exemplary data, we demonstrate in this study how movement kinematics and grip forces during a handover depend on the characteristics of the object to be measured (i.e., its size or weight).
Effects of Artificially Induced Leg Length Discrepancy on Treadmill-Based Walking and Running Symmetry in Healthy College Students: A Lab-Based Experimental Study
Authors: Korontzi Maria , Kafetzakis Ioannis , Mandalidis Dimitris
Published: December 2023

Leg length discrepancy (LLD) is a common postural deviation of musculoskeletal origin, which causes compensatory reactions and often leads to injury. The aim of the study was to investigate the effect of artificially induced LLD on gait symmetry by means of the spatiotemporal gait parameters and ground reaction forces (GRFs) using a treadmill equipped with capacitive sensors (instrumented) as well as the EMG activity of trunk and hip muscles during walking and running. Twenty-six healthy male and female college students were required to perform two sets of four 2.5-min walking and running trials on an instrumented treadmill at 5.6 and 8.1 km·h−1, respectively, without (0) and with 1, 2, and 3 cm LLD implemented by wearing a special rubber shoe. Statistical analysis was performed using one-way repeated measures or a mixed-design ANOVA. Most spatiotemporal gait parameters and GRFs demonstrated an increase or decrease as LLD increased either on the short-limb or the long-limb side, with changes becoming more apparent at ≥1 cm LLD during walking and ≥2 cm LLD during running. The EMG activity of trunk and hip muscles was not affected by LLD. Our findings showed that gait symmetry in terms of treadmill-based spatiotemporal parameters of gait and GRFs is affected by LLD, the magnitude of which depends on the speed of locomotion.
An Improved Multimodal Biometric Identification System Employing Score-Level Fuzzification of Finger Texture and Finger Vein Biometrics
Authors: Haider Syed Aqeel , Ashraf Shahzad , Larik Raja Masood , Husain Nusrat , Muqeet Hafiz Abdul , Humayun Usman , Yahya Ashraf , Arfeen Zeeshan Ahmad , Khan Muhammad Farhan
Published: December 2023

This research work focuses on a Near-Infra-Red (NIR) finger-images-based multimodal biometric system based on Finger Texture and Finger Vein biometrics. The individual results of the biometric characteristics are fused using a fuzzy system, and the final identification result is achieved. Experiments are performed for three different databases, i.e., the Near-Infra-Red Hand Images (NIRHI), Hong Kong Polytechnic University (HKPU) and University of Twente Finger Vein Pattern (UTFVP) databases. First, the Finger Texture biometric employs an efficient texture feature extracting algorithm, i.e., Linear Binary Pattern. Then, the classification is performed using Support Vector Machine, a proven machine learning classification algorithm. Second, the transfer learning of pre-trained convolutional neural networks (CNNs) is performed for the Finger Vein biometric, employing two approaches. The three selected CNNs are AlexNet, VGG16 and VGG19. In Approach 1, before feeding the images for the training of the CNN, the necessary preprocessing of NIR images is performed. In Approach 2, before the pre-processing step, image intensity optimization is also employed to regularize the image intensity. NIRHI outperforms HKPU and UTFVP for both of the modalities of focus, in a unimodal setup as well as in a multimodal one. The proposed multimodal biometric system demonstrates a better overall identification accuracy of 99.62% in comparison with 99.51% and 99.50% reported in the recent state-of-the-art systems.
SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam
Authors: Xie Weiguo , Wu Jianhua , Gao Hua , Chen Jiehong , He Yufeng
Published: December 2023

The No.4 tailings pond of the Dexing Copper Mine is the second largest in Asia. The tailing pond is a dangerous source of man-made debris flow with high potential energy. In view of the lack of effective and low-cost global safety monitoring means in this region, in this paper, the time-series InSAR technology is innovatively introduced to monitor the deformation of tailings dam and significant key findings are obtained. First, the surface deformation information of the tailings pond and its surrounding areas was extracted by using SBAS-InSAR technology and Sentinel-1A data. Second, the cause of deformation is explored by analyzing the deformation rate, deformation accumulation, and three typical deformation rate profiles of the representative observation points on the dam body. Finally, the power function model is used to predict the typical deformation observation points. The results of this paper indicated that: (1) the surface deformation of the tailings dam can be categorized into two directions: the upper portion of the dam moving away from the satellite along the Line of Sight (LOS) at a rate of −40 mm/yr, whereas the bottom portion approaching the satellite along the LOS at a rate of 8 mm/yr; (2) the deformation of the dam body is mainly affected by the inventory deposits and the construction materials of the dam body; (3) according to the current trend, deformation of two typical observation points in the LOS direction will reach the cumulative deformation of 80 mm and −360 mm respectively. The research results can provide data support for safety management of No.4 tailings dam in the Dexing Copper Mine, and provide a method reference for monitoring other similar tailings dams.
Design of a Remote, Multi-Range Conductivity Sensor
Authors: Dima Georgiana , Radkovskaya Anna , Stevens Christopher J. , Solymar Laszlo , Shamonina Ekaterina
Published: December 2023

So far, research on remote conductivity detection has primarily focused on large conductivities. This paper examines the entire conductivity range, proposing a method that can be adapted to the desired application. The optimization procedure for the different regions is presented and discussed. Specific interest is given to the low-conductivity range, below 10 S/m, which covers human body tissues. This could lead to applications in body imaging, especially for induction tomography. Conductivities below 12.5 S/m are extracted experimentally with an error below 10%.
Study on Enhancement of Denitrification Performance of Alcaligenes faecalis
Authors: Luo Zicheng , Hu Shugen , Zhang Yameng , Yu Guanlong , Yang Yunhe , Li Qing , Duan Peng
Published: December 2023

Nitrogen pollution in water bodies presents a serious threat to ecosystems due to its role in eutrophication. In this study, the aerobic denitrifying bacterium Alcaligenes faecalis was used as a model microorganism to investigate the optimal operating conditions for nitrogen removal from nitrogen-containing wastewater by Alcaligenes faecalis under different aeration modes, microbial dosages and C/N ratios. The results showed that the optimal aeration mode for efficient bacterial denitrification was 10 min of aeration with a 30 min interval, and the total nitrogen removal reached 87.82%. At different bacterial doses, NO3−–N was completely denitrified and NO2−–N accumulation levels were reduced, all of which resulted in significant denitrification, and the final total nitrogen removal efficiencies reached 86.39–98.50%. With an increase in the C/N ratio, the pollutant removal performance of denitrifying bacteria increased. When the C/N ratio was 17, the final rates of NO3−–N, TN and COD removal were 100%, 98.50% and 96.13%, respectively. At lower C/N ratios, the growth and metabolism of microorganisms were inhibited and fewer electron acceptors were available during the denitrification process, which seriously affected denitrification performance. In this study, the denitrification performance of aerobic denitrifying bacterium Alcaligenes faecalis was explored in experiments using changes in aeration mode, microbial dosage and C/N ratio, and the optimal operating conditions of Alcaligenes faecalis for treating nitrogenous wastewater were indicated. This provides technical support for Alcaligenes faecalis in improving the remediation effect of nitrogenous wastewater and provides a theoretical basis for further in-depth research on the performance of Alcaligenes faecalis in the future.
A Decade of Climate Action and the Mission towards Climate Neutrality and Adaptation in European Cities: Delivering Urban Transformations?
Authors: Corrêa do Lago Ana , Sánchez Chaparro Teresa , Lumbreras Julio
Published: December 2023

Climate action in cities is increasingly recognized as of strategic importance to accomplish the global governance of climate change. In Europe, cities are adopting a “mission approach” to accelerate urban transformations and reach climate neutrality targets by 2030. While the “Mission” unfolds, it is worth acknowledging that in the last decade, cities in Europe have engaged in climate action. Through a selection of empirical case studies, this review examines the main governance approaches that have been used to analyze the implementation of transformative adaptation and mitigation measures in the Global North. This approach aims to respond to the gap between policy rhetoric of urban transformations and the realities of on-the-ground implementation. This systematic literature review asks the following question: what are the challenges and key success factors amongst the governance approaches that have informed the implementation of transformative climate agendas in cities of the Global North? The findings cover conceptual approaches to analyze the governance of urban transformations, and cases illustrate the challenges in mainstreaming climate action, even in cities that are environmental champions. The need to strengthen collaborations to deliver transformative interventions is raised, while the authors also caution about power imbalances in network governance.
Methodology for Assessing Power Needs for Onshore Power Supply in Maritime Ports
Authors: Amaral Marcelo , Amaro Nuno , Arsénio Pedro
Published: December 2023

Maritime ports represent an important ecosystem for pollutant emissions and, considering the ongoing energy transition, need to adopt new solutions to mitigate current emission levels. These emissions are partially avoidable if ships and vessels docked at the port use electric energy to feed their power needs instead of using their internal combustion engines. In Europe, there is an ongoing discussion on including such emissions in the European Union Emissions Trading System, which will represent added costs for maritime operators. Onshore power supply systems can contribute to the ongoing energy transition by allowing the use of electric power to feed docked ships. As a first step to contribute to the development of onshore power supply solutions, it is necessary to evaluate the added power needs that these systems would represent for the port. This paper presents a methodology that allows port operators to verify, straightforwardly and transparently, their power needs for onshore power supply applications. The methodology is based on the historical data of docked ships at the port or quay level and provides an energy analysis of each type of vessel to determine the power to be installed at the port so that it is possible to supply energy to different types of ships and vessels simultaneously. Additionally, the implemented methodology provides economic and technical decision support factors by comparing the fuel costs with electric power costs, assessing the potential for this transition to onshore power supply. The methodology is validated using a real case study for the Port of Lisbon, and obtained results demonstrate the potential for the installation of an onshore power supply in medium- to large-dimension maritime ports.
Examining the Impact of Market Segmentation on Carbon Emission Intensity in China
Authors: Guo Tianmiao , Li Jian , Gao Fengyue , Zhang Shuhua
Published: December 2023

Market segmentation behavior has led to environmental issues, notably, carbon emissions, during China’s economic transformation, posing a significant challenge to ongoing economic progress. This study builds upon the existing literature and empirical analyses on market segmentation and carbon emissions, establishing a theoretical framework to understand the relationship between market segmentation and carbon emission intensity. Using a panel dataset covering Chinese provinces from 2003 to 2020, we systematically examined the impact and transmission mechanisms of market segmentation on carbon emission intensity. This study revealed the following findings: (1) there is a significant positive correlation between market segmentation and carbon emission intensity, which remains true after a series of robustness tests; (2) the promoting effect of market segmentation on carbon emission intensity in the eastern region is significantly lower than that in the central and western regions and, as time goes by, the promoting effect of market segmentation on carbon emission intensity becomes smaller and smaller; (3) resource mismatch and industrial structure are two important transmission channels through which market segmentation affects carbon emission intensity; (4) market segmentation demonstrated a distinct positive spatial contagion impact on carbon emission intensity. This study provides valuable policy recommendations to align with China’s ‘dual carbon goals’ by supporting a unified market and fostering low-carbon development. These recommendations aim to steer China’s economy toward a greener and low-carbon transformation.
Dyonic Black Holes in Kaluza–Klein Theory with a Gauss–Bonnet Action
Authors: Mignemi Salvatore
Published: December 2023

Kaluza–Klein theory attempts a unification of gravity and electromagnetism through the hypothesis that spacetime has five dimensions, of which only four are observed. The original model gives rise to the standard Einstein–Maxwell theory after dimensional reduction. However, in five dimensions, the Einstein–Hilbert action is not unique, and one can add to it a Gauss–Bonnet term, giving rise to nonlinear corrections in the dimensionally reduced action. We consider such a model, which reduces to Einstein gravity nonminimally coupled to nonlinear electrodynamics. The black hole solutions of the four-dimensional model modify the Reissner–Nordström solutions of general relativity. We show that in the modified solutions, the gravitational field presents the standard singularity at r=0, while the electric field can be regular everywhere if the magnetic charge vanishes.
Gene-Editing and RNA Interference in Treating Hepatitis B: A Review
Authors: Kasianchuk Nadiia , Dobrowolska Krystyna , Harkava Sofiia , Bretcan Andreea , Zarębska-Michaluk Dorota , Jaroszewicz Jerzy , Flisiak Robert , Rzymski Piotr
Published: December 2023

The hepatitis B virus (HBV) continues to cause substantial health and economic burdens, and its target of elimination may not be reached in 2030 without further efforts in diagnostics, non-pharmaceutical prevention measures, vaccination, and treatment. Current therapeutic options in chronic HBV, based on interferons and/or nucleos(t)ide analogs, suppress the virus replication but do not eliminate the pathogen and suffer from several constraints. This paper reviews the progress on biotechnological approaches in functional and definitive HBV treatments, including gene-editing tools, i.e., zinc-finger proteins, transcription activator-like effector nucleases, and CRISPR/Cas9, as well as therapeutics based on RNA interference. The advantages and challenges of these approaches are also discussed. Although the safety and efficacy of gene-editing tools in HBV therapies are yet to be demonstrated, they show promise for the revitalization of a much-needed advance in the field and offer viral eradication. Particular hopes are related to CRISPR/Cas9; however, therapeutics employing this system are yet to enter the clinical testing phases. In contrast, a number of candidates based on RNA interference, intending to confer a functional cure, have already been introduced to human studies. However, larger and longer trials are required to assess their efficacy and safety. Considering that prevention is always superior to treatment, it is essential to pursue global efforts in HBV vaccination.
Preliminary Study on the Efficacy of a Recombinant, Subunit SARS-CoV-2 Animal Vaccine against Virulent SARS-CoV-2 Challenge in Cats
Authors: Morozov Igor , Gaudreault Natasha N. , Trujillo Jessie D. , Indran Sabarish V. , Cool Konner , Kwon Taeyong , Meekins David A. , Balaraman Velmurugan , Artiaga Bianca Libanori , Madden Daniel W. , McDowell Chester , Njaa Bradley , Retallick Jamie , Hainer Nicole , Millership Jason , Wilson William C. , Tkalcevic George , Vander Horst Hanne , Burakova Yulia , King Vickie , Hutchinson Kendra , Hardham John M. , Schwahn Denise J. , Kumar Mahesh , Richt Juergen A.
Published: December 2023

The objective of this work was to evaluate the safety and efficacy of a recombinant, subunit SARS-CoV-2 animal vaccine in cats against virulent SARS-CoV-2 challenge. Two groups of cats were immunized with two doses of either a recombinant SARS-CoV-2 spike protein vaccine or a placebo, administered three weeks apart. Seven weeks after the second vaccination, both groups of cats were challenged with SARS-CoV-2 via the intranasal and oral routes simultaneously. Animals were monitored for 14 days post-infection for clinical signs and viral shedding before being humanely euthanized and evaluated for macroscopic and microscopic lesions. The recombinant SARS-CoV-2 spike protein subunit vaccine induced strong serologic responses post-vaccination and significantly increased neutralizing antibody responses post-challenge. A significant difference in nasal and oral viral shedding, with significantly reduced virus load (detected using RT-qPCR) was observed in vaccinates compared to mock-vaccinated controls. Duration of nasal, oral, and rectal viral shedding was also significantly reduced in vaccinates compared to controls. No differences in histopathological lesion scores were noted between the two groups. Our findings support the safety and efficacy of the recombinant spike protein-based SARS-CoV-2 vaccine which induced high levels of neutralizing antibodies and reduced nasal, oral, and rectal viral shedding, indicating that this vaccine will be efficacious as a COVID-19 vaccine for domestic cats.
Evaluation of Water Resources Carrying Capacity of Zhangye City Based on Combined Weights and TOPSIS Modeling
Authors: Yang Mingyue , Qu Deye , Shen Yue , Yang Shanquan , Liu Bin , Lu Wenjing
Published: December 2023

According to the natural condition of water resources and the economic, social, and ecological environment status of Zhangye City, the water resources carrying capacity of Zhangye City is evaluated by using the water resources carrying capacity Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model with combination assignment. The results show that: (1) From 2010 to 2020, the water resources carrying capacity of Zhangye City was generally stable at the macro level, ranking at grades III and IV. However, from the micro level, the water resources carrying capacity fluctuates to a certain extent and shows an increasing trend year by year. (2) The steady improvement of economic and social conditions is the main driving force for the improvement of the comprehensive water resources carrying capacity of Zhangye City, and the changes in the ecological environment are also important factors affecting the carrying capacity of water resources. The results provided a decision basis for future comprehensive development and utilization of water resources in Zhangye City and a reference for water resource carrying capacity and water resource security assessment in other arid and semi-arid areas in our country.
A High-Precision Car-Following Model with Automatic Parameter Optimization and Cross-Dataset Adaptability
Authors: Qin Pinpin , Bin Shenglin , Pang Yanzhi , Li Xing , Wu Fumao , Liu Shiwei
Published: December 2023

Despite the significant impact of network hyperparameters on deep learning car-following models, there has been relatively little research on network hyperparameters of deep learning car-following models. Therefore, this study proposes a car-following model that combines particle swarm optimization (PSO) and gated recurrent unit (GRU) networks. The PSO-GRU car-following model is trained and tested using data from the natural driving database. The results demonstrate that compared to the intelligent driver model (IDM) and the GRU car-following model, the PSO-GRU car-following model reduces the mean squared error (MSE) for the speed simulation of following vehicles by 88.36% and 72.92%, respectively, and reduces the mean absolute percentage error (MAPE) by 64.81% and 50.14%, respectively, indicating a higher prediction accuracy. Dataset 3 from the drone video trajectory database of Southeast University and NGSIM’s I-80 dataset are used to study the car-following model’s cross-dataset adaptability, that is, to verify its transferability. Compared to the GRU car-following model, the PSO-GRU car-following model reduces the standard deviation of the test results by 60.64% and 32.89%, highlighting its more robust prediction stability and better transferability. Verifying the ability of the car-following model to produce the stop-and-go phenomenon can evaluate its transferability more comprehensively. The PSO-GRU car-following model outperforms the GRU car-following model in creating stop-and-go sensations through platoon simulation tests, demonstrating its superior transferability. Therefore, the proposed PSO-GRU car-following model has higher prediction accuracy and cross-dataset adaptability compared to other car-following models.
THE IMAGES OF NATURE AS A MANNER OF AUTHOR'S SELF-IDENTITY EXPRESSION INJ. FOWLES' NOVEL "AMAGGOT"
Authors:   Orel State University, GOLBAN O.S.
Published: December 2023

There is a review of the images of nature and the peculiarities of their functioning in the novel «A Maggot» by John Fowles in the context of the problem of expression of authorial self-identity in the work. The images of nature in the artistic reality of the analyzed novel reveal the infinite mobility of the world and contrast it with the limitations of a dogmatic worldview, thus complementing the author’s idea of the need to overcome the dominance of generally accepted truths in the name of genuine humanity.
CONCEPT’ SONG TN POETICS OF R.I. ROZHDESTVENSKY
Authors:   Federal Guard Service Academy of Russia, MARTYNOVA E.M.
Published: December 2023

The study is focused on the realization of the concept “Song”in the poems of R.I. Rozhdestvensky. The concepts “Human Being”, “Life”, “Homeland”, “Love”interconnected with itare revealed. The representatives of song types, the most important of which being lullaby and memorial, are analyzed.
ON THE EDUCATIONAL ENVIRONMENT OF THE UNIVERSITY AS A SPACE FOR THE FORMATION OF THE COMMUNICATIVE TOLERANCE OF STUDENTS
Authors:   Orel State Agrarian University Named After N.V. Parakhin, AKHINKO N.N. , BURKO N.V. ,   Orel State Agrarian University Named After N.V. Parakhin, OREKHOVA M.V. ,   Orel State Agrarian University Named After N.V. Parakhin, SHITAKOVA N.I. ,   Orel State Agrarian University Named After N.V. Parakhin
Published: December 2023

In this paper, the authors talk about the organic relationship between classroom and extracurricular activities for the formation and development of a number of universal competencies among students. They consider the educational environment of the university as a space for the effective formation of students' communicative tolerance.
POLITICAL DISCUSSIONS IN ALL-UNION COMMUNIST PARTY (BOLSHEVIKS) IN 1923-1924 AND HIGHER SCHOOL OF PETROGRAD
Authors:   St. Petersburg Institute of History of the Russian Academy of Sciences, BARINOV D.A.
Published: December 2023

The article presents an analysis of the course of the party discussion of the RCP (b) in the university cells of Petrograd (based on the materials of the archives of the CGAIPD St. Petersburg and RGASPI). The history of the discussion of the programs of the left opposition in the student environment allows us to trace the roots of the subsequently created myth about the opposition as a youth, student movement. The author also demonstrates the methods of conducting the discussion, reveals the numerous manipulations and violations committed by the supporters of the majority of the Central Committee who opposed L.D. Trotsky and T.V. Sapronov. The voting methods, the nature of the reports, and the organization of the meetings of the cells led to the fact that the official statistics, which testified to the complete defeat of the opposition, hardly adequately reflected the real popularity of its ideas.
CHARITY AND CHARITY AS A SOCIO-CULTURAL PHENOMENON IN THE EDUCATIONAL SPACE OF RUSSIA: A RETROSPECTIVE ANALYSIS
Authors:   Moscow International Academy, PAVLOVA V.A.
Published: December 2023

This article discusses the definitions of the terms «charity», «philanthropy». Interest in charity and philanthropy in Russia especially attracts the population of the country, since there is a constant need to search for and improve non-state forms andfind ways to support. The article is devoted to the cultural and historical aspect and retrospective analysis in the educational space of Russia, the problem of the implementation of charitable assistance and the development ofpatronage in Russia from the past period to the present day.
IMPLEMENTATION OF THE MODEL OF THE METHODOLOGICAL SYSTEM FOR TEACHING STUDENTS OF PHYSICAL AND MATHEMATICAL AREAS OF TRAINING IN THE BASICS OF CORRELATION ANALYSIS
Authors:   Orel State University, SELYUTIN V.D.
Published: December 2023

A theoretical model of a methodological system for teaching students of physical and mathematical areas of training in correlation analysis and its implementation on the basis of pedagogical requirements formulated in the Federal State Educational Standard of Higher Education is considered. Specific examples show the features of the created educational and methodological complex.
GOVERNMENT SUPPORT FOR SMALL AND MEDIUM-SIZED BUSINESSES IN THE UK DURING THE COVID-19 PANDEMIC
Authors:   Orel State University, GELLA T.N. , ANTONOVA A.E. ,   Orel State University
Published: December 2023

The article is devoted to the economic policy of the United Kingdom in the context of the spread of the COVID-19 pandemic. The pandemic has affected many aspects of public life. The sphere of economy turned out to be the most sensitive to these changes. The article analyzes the first reactions of government structures to the spread of the pandemic in early 2020. The main focus is on the consideration of state anti-crisis programs to support small and medium-sized businesses adopted and implemented by the conservative government of B. Johnson in response to the coronavirus in 2020. In general, the British strategy to combat the pandemic was situational in nature, and anti-crisis programs were reduced to providing financial advantages: budget loans and guarantees, subsidies; delays in paying taxes and other mandatory payments.
Estilos de enseñanza y competencias matemáticas: una propuesta de mejora
Authors: Rosales Cruz Jorge Luís , Cervera Cajo Luz Emérita , Querebalú Galán Mercedes Teófila , Sandoval Garabito Flora Elena , Martínez Melgarejo Luz Madeleine , Jaramillo Soto Manuel Wilder
Published: December 2023

Los estilos de enseñanza permiten optimizar el aprendizaje de los estudiantes logrando que puedan ser capaces de desenvolverse en las competencias, capacidades y habilidades de acuerdo a las necesidades que se establecen en el sistema educativo. Por tal razón, el objetivo de este estudio es determinar la relación de los estilos de enseñanza y las competencias matemáticas en una institución educativa pública del distrito de Ventanilla. La metodología tuvo un enfoque cuantitativo con diseño no experimental, de análisis correlacional. La muestra estuvo conformada por 61 estudiantes de 4to grado de primaria. Como instrumento fueron usados dos cuestionarios que fueron validados por expertos, acerca de la variable estilos de enseñanza con 4 dimensiones, y la variable competencias matemáticas. como resultado de la relación directa y positiva entre los estilos de enseñanza y las competencias matemáticas en el Rho = 0.620 lo que indica que se obtuvo un nivel positivo considerable presentando una p= 0.000 (muy significativo). De esta manera, se concluyó que los docentes deben considerar los estilos de aprendizaje que tienen sus estudiantes para así mejorar las competencias matemáticas
Gestión pedagógica y actividades extracurriculares en una institución educativa de Huaral, Perú
Authors: La Rosa Gallardo Luis Arturo
Published: December 2023

Los vertiginosos cambios a nivel de modelo educativo y gestión pedagógica que vienen suscitándose en los últimos años, suponen un interés por encontrar la metodología pedagógica más adecuada para desarrollar el mayor número de competencias en los alumnos. En esa línea, el presente estudio pretende determinar la relación entre la gestión pedagógica y sus dimensiones con las actividades extracurriculares de una institución educativa de Huaral. El enfoque es cuantitativo, de tipo descriptivo y explicativo, con un diseño transversal, no experimental y correlacional causal. La técnica usada para la recopilación fue la encuesta, así mismo como instrumentos se usaron 2 cuestionarios en escala de Likert, validados mediante juicio de expertos sobre la población de docentes se observa que el coeficiente de Spearman entre las variables gestión pedagógica y actividades extracurriculares fue de 0.751. Los resultados indica que existe un grado de correlación alta y positiva entre estas variables. Además, el nivel de significancia (p) es de 0.000, el cual al ser menor que el alfa (0.05) indicaría que la correlación es de tipo significativa; concluyendo que existe una correlación alta en la gestión pedagógica y las actividades curriculares.
La place du pouvoir judiciaire indien, au-delà du classicisme, un pouvoir atypique influent
Authors: Barrué-Belou Rémi
Published: December 2023

Le système judiciaire indien repose sur la Constitution de 1949 (entrée en vigueur en 1950) mettant en place une nouvelle organisation à la suite de l’indépendance acquise vis-à-vis du Royaume-Uni. Malgré un texte constitutionnel relativement développé, le pouvoir judiciaire s’est développé par opposition à la place détenue par les pouvoirs exécutif et législatif au fil des ans. Cette place s’est avant tout construite par la défense des droits de l’Homme et des droits fondamentaux. La Cour suprême a ainsi joué un rôle moteur et s’est alors située en véritable contre-pouvoir vis-à-vis de l’exécutif et du législatif fédéraux. La conséquence de cette montée en puissance et de cette volonté de constituer un contrepoids a été celle d’un isolement, tant politique que démocratique. C’est la construction de ce champ d’action que cet article souhaite analyser ainsi que les conséquences qui en ont résulté.
La consolidation de l’État de droit aux couleurs chinoises
Authors: Dolais Y.
Published: December 2023

La Chine est entrée dans une phase de consolidation de son système juridique illustrée symboliquement par l’adoption complète du premier code civil depuis 1949 mais aussi marquée par le souci d’une plus grande effectivité du droit en renforçant le rôle de la justice avec la publication désormais des jugements des tribunaux, la multiplication de tribunaux spécialisés, et la mise en place du système des cas directeurs ainsi que parallèlement avec le fort développement de l’arbitrage commercial national et international. Cependant cette consolidation est enfermée dans des caractéristiques chinoises réaffirmées avec force depuis l’arrivée au pouvoir de XI Jinping qui attestent de l’émergence d’un modèle chinois et des limites de l’État de droit.
La responsabilité extracontractuelle dans les projets du Code civil chinois
Authors: Li Bei
Published: December 2023

Le futur Code civil Chinois, phénomène historique, consacrera un Livre spécial à la responsabilité extracontractuelle. Sur un plan méthodologique, ce Livre adopte la méthode de la codification à droit constant, tout en introduisant quelques innovations intéressantes afin de moderniser et moraliser des règles juridiques. Sur un plan comparatiste, cette Partie du Code présente nombreuses particularités vis-à-vis du droit français, qui touche les faits générateurs (responsabilité équitable), les causes d’exonération et d’exclusion de la responsabilité (acceptation des risques), ainsi que le régime de la réparation des préjudices (place marginale du principe de la réparation intégrale).