bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Groundwater Potential Using Aquifer Characteristics in Urambo District, Tabora Region, Tanzania
Authors: Yohana Athuman R. , Makoba Edikafubeni E. , Mussa Kassim R. , Mjemah Ibrahimu C.
Published: October 2023

In developing countries like Tanzania, groundwater studies are essential for water resource planning, development, and management. Limited hydrogeological information on groundwater occurrence, availability, and distribution in Urambo District is termed a key factor that hinders groundwater development. This research was aimed at the evaluation of groundwater potential zones in a granitic gneiss aquifer in Urambo District by integrating six indicators (transmissivity, specific capacity, static water level, yield, total dissolved solids, and geology) that were developed and applied in the study area. The indicators were further combined, and a groundwater potential index map (GWPIM) was prepared using relative weights derived from the analytical hierarchy process (AHP). The results show that 67% and 27% of the study area are categorized as moderate and high groundwater potential zones, respectively. Groundwater is controlled by both Quaternary sediments (sands and gravels) and weathered to fractured granitic gneiss. Quaternary sediments host the major shallow aquifers (<35 m) with relatively high transmissivity, specific capacity, and yield (1.5 m2/day, 16.36 m2/day, and 108 m3/day, respectively). Granitic gneiss is not strongly fractured/weathered and forms an aquifer with a relatively low yield of about 10.08 m3/day. The findings were validated using three boreholes, and the results are consistent with the developed GWPIM. Such findings are of great importance in groundwater development as the techniques applied can be extended to other areas in Tanzania as well as other countries that experience similar geological environments.
A Case Study on the Administrative Impacts of Different Engineering Capstone Teaching Modalities
Authors: Lapp Justin L. , Goupee Andrew , Friess Wilhelm A.
Published: October 2023

The capstone experience in engineering curriculums is a critical component focused on the unification of several years of student learning, but its unique nature can present challenges to engineering departments in faculty assignment and ensuring consistent, high-quality instruction. During a seven-year period, five instructional modalities, defining the interaction between students and faculty, were explored in capstone courses in the University of Maine Mechanical Engineering Department. By sharing the lessons learned from this case study, other engineering departments can make more informed decisions about how to operate capstone courses. We present the benefits and challenges of each modality and evaluate them for scalability, student satisfaction, project diversity, cost, and instructor workload. Annual data were collected on student, instructor, and project counts. Data from student evaluations and department budgets were used to evaluate student satisfaction and costs, respectively. Insights from the three authors, who were the primary capstone instructors during this study, are shared as part of the evaluations and lessons learned. Key results are that cost, student satisfaction, and project diversity did not depend strongly on the teaching modality. However, scalability and instructor workload were highly dependent on the teaching modality. The University of Maine Mechanical Engineering Department sees the most promise in a modality with multiple lead instructors who each oversee a portion of the teams, which provides scalability to add or remove instructors, and the ability for high-quality instruction through close coordination of a small instructor group.
Earning Your Way into General Education: Perceptions about Autism Influence Classroom Placement
Authors: Frake Emily , Dean Michelle , Huynh Linh N. , Iadarola Suzannah , Kasari Connie
Published: October 2023

The language used by teachers, school staff, and parents to talk about autistic students can send either positive or negative messages to other school staff, parents, and all students—with or without autism—about autistic students. Ultimately, these messages also extend to autistic people. Using qualitative focus group methods, we talked to parents, teachers, administrators, and other school staff to better understand how people speak about the inclusion of autistic students in general education classrooms in public schools. Overall, we found that many of our participants thought (1) autistic students need to earn their way into general education classrooms, unlike their peers without disabilities, (2) segregating students with disabilities away from their peers without disabilities is acceptable, and sometimes preferable, in school settings, and (3) there is power in inclusive education opportunities for students with and without disabilities in school settings. The findings from this study suggest that inclusive opportunities for autistic students were largely driven by stakeholder mindsets. These results should encourage school staff to think about and reflect on how they talk about autistic students in inclusive settings with the ultimate goal of creating more welcoming inclusive environments for autistic students.
Pricing Mechanism and Trading Strategy Optimization for Microgrid Cluster Based on CVaR Theory
Authors: Chen Wengang , Zhang Ying , Chen Jiajia , Xu Bingyin
Published: October 2023

With the increasing penetration rate of renewable energy generation, the uncertainty of renewable energy output in microgrid cluster (MGC) leads to significant fluctuations in transaction volume, which may lead to the risk of transaction default. This paper proposes a day-ahead two layer trading model for microgrid cluster based on price trading mechanism and Conditional value-at-risk (CVaR) theory. Firstly, the upper-layer establishes an objective to minimize the overall power fluctuation of the microgrid cluster using Demand response (DR) with a penalty mechanism. The microgrid cluster adopts an internal pricing mechanism and adjusts transaction prices based on internal supply-demand conditions to guide microgrids’ participation in intracluster trading, thereby encouraging the microgrid to use the flexible resources to reduce power fluctuation. Secondly, the lower-layer optimization establishes an optimization model with the objective of minimizing the comprehensive operating cost of the microgrid cluster. The model employs backward scenario reduction techniques to obtain multiple sets of typical scenarios for renewable energy generation, and the CVaR theory is introduced to quantify the potential risk of transaction default. Finally, the effectiveness of the proposed models is verified through case studies considering various application scenarios.
Substation Personnel Fall Detection Based on Improved YOLOX
Authors: Fan Xinnan , Gong Qian , Fan Rong , Qian Jin , Zhu Jie , Xin Yuanxue , Shi Pengfei
Published: October 2023

With the continuous promotion of smart substations, staff fall detection has become a key issue in automatic detection of substations. The injuries and safety hazards caused by falls among substation personnel are numerous. If a timely response can be made in the event of a fall, the injuries caused by falls can be reduced. In order to address the issues of low accuracy and poor real-time performance in detecting human falls in complex substation scenarios, this paper proposes an improved algorithm based on YOLOX. A customized feature extraction module is introduced to the YOLOX feature fusion network to extract diverse multiscale features. A recursive gated convolutional module is added to the head to enhance the expressive power of the features. Meanwhile, the SIoU(Soft Intersection over Union) loss function is utilized to provide more accurate position information for bounding boxes, thereby improving the model accuracy. Experimental results show that the improved algorithm achieves an mAP value of 78.45%, which is a 1.31% improvement over the original YOLOX. Compared to other similar algorithms, the proposed algorithm achieves high accuracy prediction of human falls with fewer parameters, demonstrating its effectiveness.
Legalized Routing Algorithm Based on Linear Programming
Authors: Chen Chuandong , Tong Xin , Liu Qinghai , Chen Jiarui , Lin Zhifeng
Published: October 2023

Legalized routing is an essential part of PCB automatic routing. It solves the problem of wiring conflicts and obtains routing results that comply with the constraints of design rules. Traditional legalized routing problems mostly use trial backtracking methods, but with increasing design complexity and design rules, avoiding wiring conflicts between networks has become increasingly challenging. This paper proposes a legalized routing algorithm based on linear programming to obtain the optimal wiring trajectory under specified topological constraints. First, the corresponding routing model was established based on numerous routing rules, and a routing grid diagram was found using obstacles as grid points. Secondly, a global routing algorithm was used to obtain the estimated wiring path, and integer linear programming was used to realize the mathematical modeling of the legalized routing problem. Finally, a multi-line simultaneous routing strategy was used to design and implement a detailed routing algorithm, optimizing the routing results. We use C++ to complete the coding work and thoroughly test the PCB use cases of different sizes. The experimental results show that our algorithm still maintains a 100% routing success rate, good time performance, and excellent routing quality with large-scale use cases compared with the trial backtracking method.
How Do Background and Remote User Representations Affect Social Telepresence in Remote Collaboration?: A Study with Portal Display, a Head Pose-Responsive Video Teleconferencing System
Authors: Kang Seongjun , Kim Gwangbin , Lee Kyung-Taek , Kim SeungJun
Published: October 2023

This study presents Portal Display, a screen-based telepresence system that mediates the interaction between two distinct spaces, each using a single display system. The system synchronizes the users’ viewpoint with their head position and orientation to provide stereoscopic vision through this single monitor. This research evaluates the impact of graphically rendered and video-streamed backgrounds and remote user representations on social telepresence, usability, and concentration during conversations and collaborative tasks. Our results indicate that the type of background has a negligible impact on these metrics. However, point cloud streaming of remote users significantly improves social telepresence, usability, and concentration compared with graphical avatars. This study implies that Portal Display can operate more efficiently by substituting the background with graphical rendering and focusing on higher-resolution 3D point cloud streaming for narrower regions for remote user representations. This configuration may be especially advantageous for applications where the remote user’s background is not essential to the task, potentially enhancing social telepresence.
The Analysis of Permanent Magnet Vernier Synchronous Machine Vibration and Noise
Authors: Yang Fan , Li Daolu , Zhang Yi , Wang Lijing , Ye Bitian , Zhang Fang
Published: October 2023

The permanent magnet vernier synchronous machine (PMVSM) has the characteristics of high torque density and high power density and has advantages in the field of low-speed and high-torque applications. The PMVSM utilizes rich harmonics for torque enhancement, but it can also cause an increase in radial electromagnetic force and vibration noise. In this paper, we take a 12-slot 10-pole PMVSM as an example to analyze the source of radial electromagnetic force, vibration and noise. The electromagnetic finite-element model and structural finite-element model of the PMVSM are established for calculation. Through the analysis and calculation of two-dimensional electromagnetic fields, the radial electromagnetic force distribution of the PMVSM is obtained. We derive the radial electromagnetic force formula of the PMVSM and verify the correctness of the formula through harmonic analysis of the radial electromagnetic force. The sources of radial electromagnetic forces at various orders and frequencies within the PMVSM are analyzed and summarized by coupling the radial electromagnetic force obtained from the electromagnetic finite-element model to the structural finite-element model and conducting electromagnetic vibration harmonic response analysis on the PMVSM. The measured acceleration spectrum of the prototype is compared with the finite-element method (FEM) results, verifying the correctness of the finite-element simulation results for electromagnetic vibration.
An On-Demand Partial Charging Algorithm without Explicit Charging Request for WRSNs
Authors: Gao Weixin , Li Yuxiang , Shao Tianyi , Lin Feng
Published: October 2023

Wireless rechargeable sensor networks provide an effective solution to the energy limitation problem in wireless sensor networks by introducing chargers to recharge the nodes. On-demand charging algorithms, which schedule the mobile charger to charge the most energy-scarce node based on the node’s energy status, are one of the main types of charging scheduling algorithms for wireless rechargeable sensor networks. However, most existing on-demand charging algorithms require a predefined charging request threshold to prompt energy-starved nodes with energy levels lower than this threshold to submit an explicit charging request to the base station so that the base station can schedule the mobile charger to charge these nodes. These algorithms ignore the difference in importance of nodes in the network, and charging requests sent by nodes independently can interfere with the mobile charger’s globally optimal scheduling. In addition, forwarding charging requests in the network increases the network burden. In this work, aiming to maximize the network revenue and the charging efficiency, we investigate the problem of scheduling the mobile charger on-demand without depending on explicit charging requests from nodes (SWECR). We propose a novel on-demand partial charging algorithm that does not require explicit charging requests from nodes. Our algorithm accounts for the differences in importance between nodes and leverages the deep reinforcement learning technique to determine the target charging node and each node’s charging time. The simulation results demonstrate that the proposed algorithm significantly improves the charging performance and maximizes the network revenue and the charging efficiency.
A RAW Image Noise Suppression Method Based on BlockwiseUNet
Authors: Xu Jing , Liu Yifeng , Fang Ming
Published: October 2023

Given the challenges encountered by industrial cameras, such as the randomness of sensor components, scattering, and polarization caused by optical defects, environmental factors, and other variables, the resulting noise hinders image recognition and leads to errors in subsequent image processing. In this study, we propose a RAW image denoising method based on BlockwiseUNet. By enabling local feature extraction and fusion, this approach enhances the network’s capability to capture and suppress noise across multiple scales. We conducted extensive experiments on the SIDD benchmark (Smartphone Image Denoising Dataset), and the PSNR/SSIM value reached 51.25/0.992, which exceeds the current mainstream denoising methods. Additionally, our method demonstrates robustness to different noise levels and exhibits good generalization performance across various datasets. Furthermore, our proposed approach also exhibits certain advantages on the DND benchmark(Darmstadt Noise Dataset).
Review of Low-Temperature Performance, Modeling and Heating for Lithium-Ion Batteries
Authors: Sun Bingxiang , Qi Xianjie , Song Donglin , Ruan Haijun
Published: October 2023

Lithium-ion batteries (LIBs) have the advantages of high energy/power densities, low self-discharge rate, and long cycle life, and thus are widely used in electric vehicles (EVs). However, at low temperatures, the peak power and available energy of LIBs drop sharply, with a high risk of lithium plating during charging. This poor performance significantly impacts the application of EVs in cold weather and dramatically limits the promotion of EVs in high-latitude regions. This challenge recently attracted much attention, especially investigating the performance decrease for LIBs at low temperatures, and exploring the solutions; however, limited reviews exist on this topic. Here, we thoroughly review the state-of-the-arts about battery performance decrease, modeling, and preheating, aiming to drive effective solutions for addressing the low-temperature challenge of LIBs. We outline the performance limitations of LIBs at low temperatures and quantify the significant changes in (dis)charging performance and resistance of LIBs at low temperatures. The various models considering low-temperature influencing factors are also tabulated and summarized, with the modeling improvement for describing low-temperature performance highlighted. Furthermore, we categorize the existing heating methods, and the metrics such as heating rate, energy consumption, and lifetime impact are highlighted to provide fundamental insights into the heating methods. Finally, the limits of current research on low-temperature LIBs are outlined, and an outlook on future research direction is provided.
Transfer Learning Prediction Performance of Chillers for Neural Network Models
Authors: Dou Hongwen , Zmeureanu Radu
Published: October 2023

Building automation systems installed in large commercial buildings record sub-hourly measurements from hundreds of sensors. The use of such large datasets are challenging because of missing and erroneous data, which can prevent the development of accurate prediction models of the performance of heating, ventilation, and air-conditioning equipment. The use of the transfer learning (TL) method for building applications attracted researchers to solve the problems created by small and incomplete datasets. This paper verifies the hypothesis that the deep neural network models that are pre-trained for one chiller (called the source chiller) with a small dataset of measurements from July 2013 could be applied successfully, by using TL strategies, for the prediction of the operation performance of another chiller (called the target chiller) with different datasets that were recorded during the cooling season of 2016. Measurements from a university campus are used as a case study. The results show that the initial hypothesis of this paper is confirmed.
Comprehensive Characterization of Energy Saving and Environmental Benefits of Campus Photovoltaic Buildings
Authors: Yang Jie , Cai Baorui , Cao Jingyu , Wang Yunjie , Yang Huihan , Zhu Ping
Published: October 2023

The development of campus photovoltaic buildings is a promising way to solve the problem of high energy consumption in colleges and universities. However, comprehensive study on their energy saving and environmental benefits is still insufficient. In this study, a theoretical model of a photovoltaic building roof system was preliminarily built, and the main factors affecting the power generation of campus photovoltaic buildings were analyzed. Furthermore, an experimental test platform for the campus photovoltaic building system was built, and a dynamic grid-connected strategy of “spontaneous self-use, surplus electricity connected to the grid” was creatively proposed, which points out that the grid connection rate in winter and summer vacations are about 15% and over 40%, respectively, and the annual grid connection rate is 25%. The result shows that the electricity input of the campus photovoltaic building can bear nearly 30% of the school’s annual electricity supply, which reduces the comprehensive energy consumption per unit area and per capita comprehensive energy consumption of the campus by more than 20%. The economic and environmental benefits of the 130,000 square meter campus photovoltaic building in the article are 38.8 million CNY and 20.12 million CNY, respectively, and the static investment payback period is about 7 years. The results show considerable reference value to the upgrading of campus photovoltaic buildings.
A Study of Passenger Car Cabin Pre-Ventilation under the Sun
Authors: Zhang Yingchao , Li Ziqiao , Liu Shengda , Wang Guohua , Chang He
Published: October 2023

With the increasing intelligence of automobiles, vehicle pre-ventilation can be better controlled. In summer, cars parked in the open air are directly exposed to sunlight; thus, a high-temperature environment is formed in the occupant cabin, which seriously affects the passengers and driver’s riding and driving experience. Meanwhile, lowering the temperature of the passenger compartment from a very high temperature to a comfortable temperature consumes a lot of energy. Therefore, it is increasingly important to study the pre-ventilation of the cabin in order to improve the thermal comfort of the occupant cabin and reduce energy consumption. In this paper, a new theoretical model of a cabin temperature control system is proposed. To support the theoretical model, an outdoor parking temperature rise test was carried out. Environmental parameters were obtained and used as the boundary conditions of the subsequent simulation. Based on the mechanism of the cabin temperature rise, the convective heat transfer coefficient on the body surface, the equivalent heat transfer model of the cabin, the solar radiation model and the physical properties of the air, a computational simulation of the temperature rise in the occupant cabin was carried out, and a simulation of the temperature rise in the occupant cabin exposure was studied. The simulation results were compared with the experimental findings to verify the accuracy of the simulation, which provided a reference for the design of the pre-cooling function of the occupant cabin. This study revealed that the pre-ventilation model developed reduces the vehicle cabin temperature through optimal control of air supply volumes and air supply angles. Furthermore, the developed pre-ventilation model is capable of reducing energy consumption, thereby reducing greenhouse gas emissions.
Self-Directed Mobile Robot Navigation Based on Functional Firefly Algorithm (FFA)
Authors: Patle Bhumeshwar K. , Patel Brijesh , Jha Alok , Kashyap Sunil Kumar
Published: October 2023

This paper proposes an optimized mobile robot navigation strategy using a functional firefly algorithm (FFA) and choice function. This approach has two key advantages: first, the linear objective function performs efficiently with the single degree and finite-order polynomial time operation, and second, the cartesian constraint performs compactly with the chosen degree of freedom on the finite interval. This functional approach optimizes the size of operational parameters in context with key size, operation time, and a finite range of verification. The choice function achieves parameter order (size) reduction. The attraction characteristic of fireflies is represented by the choice function for optimizing the choice between low and high intensities of fireflies. In 2D and 3D environments, the proposed robot navigation performs well in an uncertain environment with static and dynamic obstacles. This efficiency includes the robot’s speed as determined by the choice function’s minimum path lengths. The collision-free path is achieved by the non-void family of non-void sets. The obtained results are optimal in terms of path length and navigational time. The proposed controller is also compared with the other existing controllers, and it is observed that the FFA gives the shortest path in less time for the same environmental condition.
Impact of Hydrocarbon Emissions from Oil and Gas Deposits on δ13C Variability in Pine Tree Rings from the Tatarstan Republic
Authors: Churakova (Sidorova) Olga V. , Batalin Georgii , Gareev Bulat , Mingazov Gazinur , Terekhin Andrey , Tishin Denis , Kuzina Dilyara , Nurgaliev Danis
Published: October 2023

Human-caused anthropogenic greenhouse emissions impact the climate globally. In this pilot study, we aim to reveal the influence of hydrocarbon emissions on pine forests by applying a stable carbon isotope analysis in pine tree rings (δ13Cptrw). Our study was conducted in an industrial giant oil field reservoir (UVRT) and natural reserve (Raifa) sites, the Tatarstan Republic, Russia. Our results show a decreasing δ13Cptrw at the UVRT site in 1943, when oil extraction started, and in 1970, when it reached maximum production. We found that the δ13Cptrw from UVRT indicates developing unfavourable drier conditions and a suppressed tree growth caused by both human-induced oil and deposit infrastructures and natural processes compared to the undisturbed Raifa site. A 5-year running correlation analysis showed a significant difference between the sites in 1965 over the period of 1930 to 2021. The δ13Cptrw values from Raifa are more negative compared to UVRT, which can be explained by a higher forest sensitivity to human-induced impacts. From an eco-physiological point of view, the decreasing of intercellular (ci)-to-ambient (ca) CO2 concentration ratios at the leaf level and the increasing of intrinsic water-use efficiency (iWUE) along with a decreasing of tree-ring widths at the UVRT site (1970–2021) indicate the development of drought conditions.
Research on Gluing Properties of Thick Bamboo-Wood-Oriented Strand Boards
Authors: Yang Bajin , Guo Xu , Chen Wu , Wang Xingyu , Du Guanben , Dong Chunlei
Published: October 2023

This study investigated the effects of adhesive resination and bamboo strand content on the physical and mechanical properties of thick Bamboo-Wood-oriented strand board (BWOSB), such as the air dry density (ADD), internal bond strength (IB), water absorption thickness swelling (TS), modulus of rupture (MOR), modulus of elasticity (MOE), and gluing properties. The raw materials used included large strands prepared from Chinese fir (Cunninghamia lanceolata), bamboo (Phyllostachys edulis), and modified isocyanate resin (PMDI). In this study, BWOSB specimens with different adhesive resination and bamboo strand content were fabricated, and their physical–mechanical properties were examined. It was found that the physical and mechanical properties of BWOSB with 8% PMDI resination were better than those with 5%, and their gluing damage was mostly in the form of the tearing of the raised vascular bundles of bamboo strands and the wood-breaking damage of wood strands. With the increase in the proportion of bamboo strands, the internal bonding strength and the short-span shear strength of BWOSB showed a tendency to decrease at first and then increase. The swelling rate of the water absorption thickness showed a tendency to decrease, and the other properties of BWOSB did not show a clear correlation with the change in the proportion of bamboo strands. The unique gluing interface between the bamboo and wood strands, which either used the “keyway” type of gluing effect or the “nail” type of gluing effect, determined the gluing performance of BWOSB, and the proportion of bamboo and wood strands influenced the gluing interface and gluing type of BWOSB, which ultimately affected the gluing performance of BWOSBs. The proportion of bamboo and wood strands also affected the gluing properties of BWOSBs by influencing the gluing interface and gluing type. This study provides a reference for the development of the production process of thick BWOSB and its application in the field of heavy load construction.
Thinning Combined with Prescribed Burn Created Spatially Heterogeneous Overstory Structures in Contemporary Dry Forests: A Comparison Using LiDAR (2016) and Field Inventory (1934) Data
Authors: Nepal Sushil , Eskelson Bianca N. I. , Ritchie Martin W. , Gergel Sarah E.
Published: October 2023

Restoring current ponderosa pine (Pinus ponderosa Dougl. Ex P. and C. Laws)-dominated forests (also known as “dry forests”) to spatially resilient stand structures requires an adequate understanding of the overstory spatial variation of forests least impacted by Euro-American settlers (also known as “reference conditions”) and how much contemporary forests (2016) deviate from reference conditions. Because of increased tree density, dry forests are more spatially homogeneous in contemporary conditions compared to reference conditions, forests minimally impacted by Euro-American settlers. Little information is available that can be used by managers to accurately depict the spatial variation of reference conditions and the differences between reference and contemporary conditions. Especially, forest managers need this information as they are continuously designing management treatments to promote contemporary dry forest resiliency against fire, disease, and insects. To fill this knowledge gap, our study utilized field inventory data from reference conditions (1934) along with light detection and ranging and ground-truthing data from contemporary conditions (2016) associated with various research units of Blacks Mountain Experimental Forest, California, USA. Our results showed that in reference conditions, above-ground biomass—a component of overstory stand structure—was more spatially heterogeneous compared to contemporary forests. Based on semivariogram analyses, the 1934 conditions exhibited spatial variation at a spatial scale < 50 m and showed spatial autocorrelation at shorter ranges (150–200 m) compared to those observed in contemporary conditions (>250 m). In contemporary conditions, prescribed burn with high structural diversity treatment enhanced spatial heterogeneity as indicated by a greater number of peaks in the correlograms compared to the low structural diversity treatment. High structural diversity treatment units exhibited small patches of above-ground biomass at shorter ranges (~120 to 440 m) compared to the low structural diversity treatment units (~165 to 599 m). Understanding how spatial variation in contemporary conditions deviates from reference conditions and identifying specific management treatments that can be used to restore spatial variation observed in reference conditions will help managers to promote spatial variation in stand structure that has been resilient to wildfire, insects, and disease.
Blockchain Technology for Secure Communication and Formation Control in Smart Drone Swarms
Authors: Koulianos Athanasios , Litke Antonios
Published: October 2023

Today, intelligent drone technology is rapidly expanding, particularly in the defense industry. A swarm of drones can communicate, share data, and make the best decisions on their own. Drone swarms can swiftly and effectively carry out missions like surveillance, reconnaissance, and rescue operations, without exposing military troops to hostile conditions. However, there are still significant problems that need to be resolved. One of them is to protect communications on these systems from threat actors. In this paper, we use blockchain technology as a defense mechanism against such issues. Drones can communicate data safely, without the need for a centralized authority (ground station), when using a blockchain to facilitate communication between them in a leader–follower hierarchy structure. Solidity has been used to create a compact, lightweight, and effective smart contract that automates the process of choosing a position in a certain swarm formation structure. Additionally, a mechanism for electing a new leader is proposed. The effectiveness of the presented model is assessed through a simulation that makes use of a DApp we created and Gazebo software. The purpose of this work is to develop a reliable and secure UAV swarm communication system that will enable widespread global adoption by numerous sectors.
Wildfire-Residential Risk Analysis Using Building Characteristics and Simulations to Enhance Structural Fire Resistance in Greece
Authors: Menemenlis Dimitrios , Palaiologou Palaiologos , Kalabokidis Kostas
Published: October 2023

Urban areas adjacent to wildlands are very dangerous zones for residents and their properties during a wildfire event. We attempted to connect wildfire simulations with field inventories and surveys to create a framework that can be used to enhance the fire resistance of residential structures located in the wildland-urban interface (WUI). Legal restrictions and the lack of economic incentives for WUI residents greatly limit the potential to appropriately intervene to enhance their property’s fire resistance. By studying in situ the resilience of building materials and combining them with exposure metrics produced from wildfire simulations, we created an index that helps to assess fire risk at the property level. The proposed index can support property owners to optimally manage the vegetation near or inside their property. State agencies can use our proposed index to estimate with a consistent methodology which properties are more exposed and with higher risk from fire damage so that specific fuel and vegetation management practices on and around them can be suggested or enforced.
Equilibrium Problem for the Stochastic Multi-Weighted Urban Public Transportation System with Time Delay: A Graph-Theoretic Method
Authors: Yang Hui , Zhang Chunmei , Li Ran , Chen Huiling
Published: October 2023

This paper focuses on the equilibrium problem of an urban public transportation system with time delay. Time delay, multi-weights, and stochastic disturbances are considered in the urban public transportation system. Hence, one can regard the urban public transportation system as a stochastic multi-weighted delayed complex network. By combining graph theory and the Lyapunov method, the global Lyapunov function is constructed indirectly. Moreover, the response system can realize synchronization with the drive system under the adaptive controller. In other words, the urban public transportation system is balanced in the actual running traffic network. Finally, numerical examples about the Chua system and small-world network are presented to confirm the accuracy and validity of the theoretical results.
Mandelbrot and Julia Sets of Transcendental Functions Using Picard–Thakur Iteration
Authors: Bhoria Ashish , Panwar Anju , Sajid Mohammad
Published: October 2023

The majority of fractals’ dynamical behavior is determined by escape criteria, which utilize various iterative procedures. In the context of the Julia and Mandelbrot sets, the concept of “escape” is a fundamental principle used to determine whether a point in the complex plane belongs to the set or not. In this article, the fractals of higher importance, i.e., Julia sets and Mandelbrot sets, are visualized using the Picard–Thakur iterative procedure (as one of iterative methods) for the complex sine Tc(z)=asin(zr)+bz+c and complex exponential Tc(z)=aezr+bz+c functions. In order to obtain the fixed point of a complex-valued sine and exponential function, our concern is to use the fewest number of iterations possible. Using MATHEMATICA 13.0, some enticing and intriguing fractals are generated, and their behavior is then illustrated using graphical examples; this is achieved depending on the iteration parameters, the parameters ‘a’ and ‘b’, and the parameters involved in the series expansion of the sine and exponential functions.
Quantifying Aboveground Grass Biomass Using Space-Borne Sensors: A Meta-Analysis and Systematic Review
Authors: Maake Reneilwe , Mutanga Onisimo , Chirima George , Sibanda Mbulisi
Published: October 2023

Recently, the move from cost-tied to open-access data has led to the mushrooming of research in pursuit of algorithms for estimating the aboveground grass biomass (AGGB). Nevertheless, a comprehensive synthesis or direction on the milestones achieved or an overview of how these models perform is lacking. This study synthesises the research from decades of experiments in order to point researchers in the direction of what was achieved, the challenges faced, as well as how the models perform. A pool of findings from 108 remote sensing-based AGGB studies published from 1972 to 2020 show that about 19% of the remote sensing-based algorithms were tested in the savannah grasslands. An uneven annual publication yield was observed with approximately 36% of the research output from Asia, whereas countries in the global south yielded few publications (<10%). Optical sensors, particularly MODIS, remain a major source of satellite data for AGGB studies, whilst studies in the global south rarely use active sensors such as Sentinel-1. Optical data tend to produce low regression accuracies that are highly inconsistent across the studies compared to radar. The vegetation indices, particularly the Normalised Difference Vegetation Index (NDVI), remain as the most frequently used predictor variable. The predictor variables such as the sward height, red edge position and backscatter coefficients produced consistent accuracies. Deciding on the optimal algorithm for estimating the AGGB is daunting due to the lack of overlap in the grassland type, location, sensor types, and predictor variables, signalling the need for standardised remote sensing techniques, including data collection methods to ensure the transferability of remote sensing-based AGGB models across multiple locations.
Distinctive Accumulation Patterns of Trace Elements in Sediments of Bedrock Rivers (Miño River, NW Iberian Peninsula)
Authors: Álvarez-Vázquez Miguel Ángel , De Uña-Álvarez Elena , Ramírez-Pérez Alexandra María , de Blas Esther , Prego Ricardo
Published: October 2023

Sediment compositions and enrichment patterns are investigated in an urban reach of a bedrock river, the Miño River passing through Ourense City, Spain. This study focuses on the trace element distribution in different fractions to gain insights into trace element enrichment. To assess enrichment, a context-specific approach was employed, based on the mean, the standard deviation of the estimated background, and the empirical rule, avoiding the pitfalls of general and arbitrary thresholds. Notably, the <0.063 mm and <2 mm fractions showed differential accumulation patterns. Both fractions serve to detect enrichments that can be indicative of contamination, but they measure different things, the maturity of sediments and postdepositional processes being key factors in understanding the sediment composition and enrichments. These findings also highlight the role of rock cavities, particularly those hosting permanent deposits, as traps for trace elements and their potential significance in assessing environmental enrichment. This work contributes to understanding sediment compositions and enrichment dynamics in bedrock rivers. It also underscores the significance of considering site-specific approaches for enrichment assessment and the necessity for further research to unravel the mechanisms driving differential accumulation within distinct depositional environments.
Thermal Conductivity Variations in Frozen Hydrate-Bearing Sand upon Heating and Dissociation of Pore Gas Hydrate
Authors: Chuvilin Evgeny , Davletshina Dinara , Bukhanov Boris , Grebenkin Sergey , Pankratova Elena
Published: October 2023

High-latitude permafrost, including hydrate-bearing frozen ground, changes its properties in response to natural climate change and to impacts from petroleum production. Of special interest is the behavior of thermal conductivity, one of the key parameters that control the thermal processes in permafrost containing gas hydrate accumulations. Thermal conductivity variations under pressure and temperature changes were studied in the laboratory through physical modeling using sand sampled from gas-bearing permafrost of the Yamal Peninsula (northern West Siberia, Russia). When gas pressure drops to below equilibrium at a constant negative temperature (about −6 °C), the thermal conductivity of the samples first becomes a few percent to 10% lower as a result of cracking and then increases as pore gas hydrate dissociates and converts to water and then to ice. The range of thermal conductivity variations has several controls: pore gas pressure, hydrate saturation, rate of hydrate dissociation, and amount of additionally formed pore ice. In general, hydrate dissociation can cause up to 20% thermal conductivity decrease in frozen hydrate-bearing sand. As the samples are heated to positive temperatures, their thermal conductivity decreases by a magnitude depending on residual contents of pore gas hydrate and ice: the decrease reaches ~30% at 20–40% hydrate saturation. The thermal conductivity decrease in hydrate-free saline frozen sand is proportional to the salinity and can become ~40% lower at a salinity of 0.14%. The behavior of thermal conductivity in frozen hydrate-bearing sediments under a pressure drop below the equilibrium and a temperature increase to above 0 °C is explained in a model of pore space changes based on the experimental results.
Retrospective Analysis of Nosocomial SARS-CoV-2 Infections in Orthopedic and Traumatological Inpatients
Authors: Dankl Lukas , Crepaz-Eger Ulrich , Arora Rohit , Schneider Friedemann
Published: October 2023

SARS-CoV-2 has had a measurable impact on the field of orthopedic and traumatological surgery. To date, scarce data on intramural SARS-CoV-2 infections in orthopedic and traumatological patients have been reported. Therefore, the aim of our study was to investigate the effect of nosocomial SARS-CoV-2 infections in orthopedic and traumatological inpatients regarding symptoms of infection, mortality, duration of hospitalization, and other relevant patient-dependent factors. Patients admitted to hospital for an orthopedic or traumatological indication were screened retrospectively for nosocomial SARS-CoV-2 infections and included in this study. An age-, sex-, and ICD 10-matched control group was assigned and demographic data, clinical symptoms of a SARS-CoV-2 infection as well as mortality, length of hospital stays, time to surgery, pre-existing conditions, LKF-points representing the financial effort, and the Charlson Comorbidity Index were collected. A significantly higher length of stay was observed in the SARS-CoV-2 group (25 days; 4–60; SD 12.5) when compared to the control group (11 days; 2–36; SD 7; p < 0.05). LKF points were significantly higher in the SARS-CoV-2 group (13,939 points vs. 8542 points). No significant difference in mortality could be observed. An infection with SARS-CoV-2 in inpatients significantly increases length of hospital stay and cost of treatment. Although no significant difference in mortality was found, care should be taken to avoid intramural SARS-CoV-2 infections, resulting in prolonged hospitalization, higher costs, and potentially further individual risks.
Geomatic Sensors for Heritage Documentation: A Meta-Analysis of the Scientific Literature
Authors: Agapiou Athos , Skarlatos Dimitrios
Published: October 2023

This review paper aims to provide a meta-analysis of the scientific literature for heritage documentation and monitoring using geo-information sensors. The study initially introduces the main types of geomatic sensors that are currently widely used for heritage studies. Although the list provided here is indicative rather than exhaustive, it provides a general overview of the variety of sensors used for different observation scales. The study next focuses on the existing literature, based on published documents. Targeted queries were implemented to the Scopus database to extract the relevant information. Filtering was then applied to the results so as to limit the analysis on the specific thematic sub-domains that is applied for heritage documentation and monitoring. These domains include, among other close-range and underwater photogrammetry, Terrestrial Laser Scanner, Unmanned Aerial Vehicles platforms, and satellite observations. In total, more than 12,000 documents were further elaborated. The overall findings are summarized and presented here, providing further insights into the current status of the domain.
Hydrogen Storage as a Key Energy Vector for Car Transportation: A Tutorial Review
Authors: Dragassi Marie-Charlotte , Royon Laurent , Redolfi Michaël , Ammar Souad
Published: October 2023

Hydrogen storage is a key enabling technology for the extensive use of hydrogen as energy carrier. This is particularly true in the widespread introduction of hydrogen in car transportation. Indeed, one of the greatest technological barriers for such development is an efficient and safe storage method. So, in this tutorial review the existing hydrogen storage technologies are described with a special emphasis on hydrogen storage in hydrogen cars: the current and the ongoing solutions. A particular focus is given on solid storage and some of the recent advances on plasma hydrogen ion implantation, which should allow not only the preparation of metal hydrides, but also the imagination of a new refluing circuit. From hydrogen discovery to its use as an energy vector in cars, this review wants to be as exhaustive as possible, introducing the basics of hydrogen storage, and discussing the experimental practicalities of car hydrogen fuel. It wants to serve as a guide for anyone wanting to undertake such a technology and to equip the reader with an advanced knowledge on hydrogen storage and hydrogen storage in hydrogen cars to stimulate further researches and yet more innovative applications for this highly interesting field.
Simple and Cost-Effective Method for Reliable Indirect Determination of Field Capacity
Authors: Almaz Cansu , Miháliková Markéta , Báťková Kamila , Vopravil Jan , Matula Svatopluk , Khel Tomáš , Kara Recep Serdar
Published: October 2023

This study introduces a simple and cost-effective method for the indirect determination of field capacity (FC) in soil, a critical parameter for soil hydrology and environmental modeling. The relationships between FC and soil moisture constants, specifically maximum capillary water capacity (MCWC) and retention water capacity (RWC), were established using undisturbed soil core samples analyzed via the pressure plate method and the “filter paper draining method”. The aim was to reduce the time and costs associated with traditional FC measurement methods, as well as allowing for the use of legacy databases containing MCWC and RWC values. The results revealed the substantial potential of the “filter paper draining method” as a promising approach for indirect FC determination. FC determined as soil water content at −33 kPa can be effectively approximated by the equation FC33 = 1.0802 RWC − 0.0688 (with RMSE = 0.045 cm3/cm3 and R = 0.953). FC determined as soil water content at −5 or −10 kPa can be effectively approximated by both equations FC5 = 1.0146 MCWC − 0.0163 (with RMSE = 0.027 cm3/cm3 and R = 0.961) and FC10 = 1.0152 MCWC − 0.0275 (with RMSE = 0.033 cm3/cm3 and R = 0.958), respectively. Historical pedotransfer functions by Brežný and Váša relating FC to fine particle size fraction were also evaluated for practical application, and according to the results, they cannot be recommended for use.