bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-UAV Autonomous Path Planning in Reconnaissance Missions Considering Incomplete Information: A Reinforcement Learning Method
Authors: Chen Yu , Dong Qi , Shang Xiaozhou , Wu Zhenyu , Wang Jinyu
Published: December 2022

Unmanned aerial vehicles (UAVs) are important in reconnaissance missions because of their flexibility and convenience. Vitally, UAVs are capable of autonomous navigation, which means they can be used to plan safe paths to target positions in dangerous surroundings. Traditional path-planning algorithms do not perform well when the environmental state is dynamic and partially observable. It is difficult for a UAV to make the correct decision with incomplete information. In this study, we proposed a multi-UAV path planning algorithm based on multi-agent reinforcement learning which entails the adoption of centralized training–decentralized execution architecture to coordinate all the UAVs. Additionally, we introduced a hidden state of the recurrent neural network to utilize the historical observation information. To solve the multi-objective optimization problem, We designed a joint reward function to guide UAVs to learn optimal policies under the multiple constraints. The results demonstrate that by using our method, we were able to solve the problem of incomplete information and low efficiency caused by partial observations and sparse rewards in reinforcement learning, and we realized kdiff multi-UAV cooperative autonomous path planning in unknown environment.
Strategic and Tactical Path Planning for Urban Air Mobility: Overview and Application to Real-World Use Cases
Authors: Causa Flavia , Franzone Armando , Fasano Giancarmine
Published: December 2022

Urban air mobility requires safe and efficient airspace management, as well as effective path planning and decision-making capabilities to enable access to the urban airspace, which is predicted to be very densely populated. This paper tackles the problem of strategic and tactical path planning by presenting a framework specifically designed for accounting for several constraints and issues of the urban environment. Multi-objective and multi-constraint planner algorithms are developed to this aim, along with an innovative method for information simplification and manipulation. Navigation-aware and optimized trajectories were retrieved from the strategic approach. Tactical path planning was developed using three approaches that react differently to unpredicted conditions. The entire strategic–tactical pipeline was tested in two real-world use cases, representing common missions in urban environments, such as medical delivery and short-range air taxi. The results demonstrate the effectiveness of the proposed methodology in generating the strategic path and show the different outcomes of the proposed tactical approaches, thus highlighting their advantages and drawbacks.
A Lightweight Uav Swarm Detection Method Integrated Attention Mechanism
Authors: Wang Chuanyun , Meng Linlin , Gao Qian , Wang Jingjing , Wang Tian , Liu Xiaona , Du Furui , Wang Linlin , Wang Ershen
Published: December 2022

Aiming at the problems of low detection accuracy and large computing resource consumption of existing Unmanned Aerial Vehicle (UAV) detection algorithms for anti-UAV, this paper proposes a lightweight UAV swarm detection method based on You Only Look Once Version X (YOLOX). This method uses depthwise separable convolution to simplify and optimize the network, and greatly simplifies the total parameters, while the accuracy is only partially reduced. Meanwhile, a Squeeze-and-Extraction (SE) module is introduced into the backbone to improve the model′s ability to extract features; the introduction of a Convolutional Block Attention Module (CBAM) in the feature fusion network makes the network pay more attention to important features and suppress unnecessary features. Furthermore, Distance-IoU (DIoU) is used to replace Intersection over Union (IoU) to calculate the regression loss for model optimization, and data augmentation technology is used to expand the dataset to achieve a better detection effect. The experimental results show that the mean Average Precision (mAP) of the proposed method reaches 82.32%, approximately 2% higher than the baseline model, while the number of parameters is only about 1/10th of that of YOLOX-S, with the size of 3.85 MB. The proposed approach is, thus, a lightweight model with high detection accuracy and suitable for various edge computing devices.
Blowing in the Wind: Using a Consumer Drone for the Collection of Humpback Whale (Megaptera novaeangliae) Blow Samples during the Arctic Polar Nights
Authors: Costa Helena , Rogan Andrew , Zadra Christopher , Larsen Oddbjørn , Rikardsen Audun , Waugh Courtney
Published: December 2022

Analysis of cetacean blow offers a unique potential for non-invasive assessments of their health. In recent years, the use of uncrewed aerial vehicles (UAVs) has revolutionized the way these samples are collected. However, the high cost and expertise associated with purpose-built waterproof UAVs, paired with the challenges of operating during difficult meteorological conditions, can be prohibitive for their standardized use worldwide. A pilot study was conducted in a Northern Norwegian fjord during winter, to assess the feasibility of using a minimally modified and affordable consumer drone to collect blow samples even during the polar nights’ challenging weather conditions. For each flight, six petri dishes were attached with velcro to a DJI Mavic 2 Pro. The flights were conducted under temperatures ranging from -1 to -18 degrees Celsius, wind speeds ranging from 9 to 31 km/h, and with the absence of the sun. During the 6-day-long boat survey, 16 blow samples were successfully collected from 11 distinct groups of humpback whales (Megaptera novaeangliae). With this study, we further validated the use of a consumer drone as a practical, affordable, and simplified tool for blow collection, functional under harsh meteorological conditions.
SIFT-CNN Pipeline in Livestock Management: A Drone Image Stitching Algorithm
Authors: Bouchekara Houssem R. E. H. , Sadiq Bashir O , O Zakariyya Sikiru , Sha’aban Yusuf A. , Shahriar Mohammad S. , Isah Musab M.
Published: December 2022

Images taken by drones often must be preprocessed and stitched together due to the inherent noise, narrow imaging breadth, flying height, and angle of view. Conventional UAV feature-based image stitching techniques significantly rely on the quality of feature identification, made possible by image pixels, which frequently fail to stitch together images with few features or low resolution. Furthermore, later approaches were developed to eliminate the issues with conventional methods by using the deep learning-based stitching technique to collect the general attributes of remote sensing images before they were stitched. However, since the images have empty backgrounds classified as stitched points, it is challenging to distinguish livestock in a grazing area. Consequently, less information can be inferred from the surveillance data. This study provides a four-stage object-based image stitching technique that, before stitching, removes the background’s space and classifies images in the grazing field. In the first stage, the drone-based image sequence of the livestock on the grazing field is preprocessed. In the second stage, the images of the cattle on the grazing field are classified to eliminate the empty spaces or backgrounds. The third stage uses the improved SIFT to detect the feature points of the classified images to o8btain the feature point descriptor. Lastly, the stitching area is computed using the image projection transformation.
Analysis of Quantum Correlations Obtained Using Local Optimal Universal Asymmetric Cloners
Authors: Cîrneci Cătălina , Ghiu Iulia
Published: December 2022

We apply the local optimal universal asymmetric cloning machine on an initially pure entangled state of two qubits. As output, we obtain two final states which present quantum correlations. We analyze three types of quantum correlations among the final states, namely, concurrence, quantum discord, and consonance. A detailed comparison between concurrence, quantum discord, and consonance is made, and we find that consonance is greater than quantum discord, which is in turn greater than concurrence.
Self-Supervised Node Classification with Strategy and Actively Selected Labeled Set
Authors: Kang Yi , Liu Ke , Cao Zhiyuan , Zhang Jiacai
Published: December 2022

To alleviate the impact of insufficient labels in less-labeled classification problems, self-supervised learning improves the performance of graph neural networks (GNNs) by focusing on the information of unlabeled nodes. However, none of the existing self-supervised pretext tasks perform optimally on different datasets, and the choice of hyperparameters is also included when combining self-supervised and supervised tasks. To select the best-performing self-supervised pretext task for each dataset and optimize the hyperparameters with no expert experience needed, we propose a novel auto graph self-supervised learning framework and enhance this framework with a one-shot active learning method. Experimental results on three real world citation datasets show that training GNNs with automatically optimized pretext tasks can achieve or even surpass the classification accuracy obtained with manually designed pretext tasks. On this basis, compared with using randomly selected labeled nodes, using actively selected labeled nodes can further improve the classification performance of GNNs. Both the active selection and the automatic optimization contribute to semi-supervised node classification.
Enhanced Signed Graph Neural Network with Node Polarity
Authors: Chen Jiawang , Qiao Zhi , Yan Jun , Wu Zhenqiang
Published: December 2022

Signed graph neural networks learn low-dimensional representations for nodes in signed networks with positive and negative links, which helps with many downstream tasks like link prediction. However, most existing signed graph neural networks ignore individual characteristics of nodes and thus limit the ability to learn the underlying structure of real signed graphs. To address this limitation, a deep graph neural network framework SiNP to learn Signed network embedding with Node Polarity is proposed. To be more explicit, a node-signed property metric mechanism is developed to encode the individual characteristics of the nodes. In addition, a graph convolution layer is added so that both positive and negative information from neighboring nodes can be combined. The final embedding of nodes is produced by concatenating the outcomes of these two portions. Finally, extensive experiments have been conducted on four significant real-world signed network datasets to demonstrate the efficiency and superiority of the proposed method in comparison to the state-of-the-art.
Effects of in Utero SARS-CoV-2 Exposure on Newborn Health Outcomes
Authors: Kyle Margaret H. , Dumitriu Dani
Published: December 2022

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 600 million people worldwide, including millions of pregnant women. While newborns exposed to other viruses in utero are sometimes at high risk for vertical transmission, a substantial body of literature since early 2020 has demonstrated that vertical transmission of SARS-CoV-2 from infected mother to neonate is rare, and that newborns who do become infected with SARS-CoV-2 generally have favorable outcomes. In this review, the authors evaluate the existing literature on vertical transmission of SARS-CoV-2 and its potential mechanisms and discuss short- and long-term health outcomes in newborns who were exposed to SARS-CoV-2 in utero. The authors conclude that vertical transmission and adverse neonatal and infant/child outcomes are unlikely, but that neonates exposed to prenatal maternal SARS-CoV-2 infection may be at slightly higher risk for preterm birth, possibly related to increased risk of severe COVID-19 disease in pregnant women, placental changes, or infection timing. Ultimately, the need for additional and longer-term follow-up data in this population is highlighted.
Experimental Design for the Propagation of Smoldering Fires in Corn Powder and Cornflour
Authors: Rosa Ana C. , Teixeira Ivenio , Lacasta Ana M. , Haurie Laia , Soares Carlos A. P. , Tam Vivian W. Y. , Haddad Assed
Published: December 2022

Corn is an example of an agricultural grain with a specific combustibility level and can promote smoldering fires during storage. This paper conducts an experimental design to numerically evaluate how three parameters, namely particle size, moisture, and air ventilation, influence the smoldering velocity. The work methodology is based on Minitab’s experimental design, which defined the number of experiments. First, a pile of corn is heated by a hot plate and a set of thermocouples registers all temperature variations. Then, a full-factorial experiment is implemented in Minitab to analyze the smoldering, which provides a mathematical equation to represent the smoldering velocity. The results indicate that particle size is the most influential factor in the reaction, with 35% and 45% variation between the dried and wet samples. Moreover, comparing the influence of moisture between corn flour and corn powder samples, a variation of 19% and 31% is observed; additionally, analyzing the ventilation as the only variant, we noticed variations of 15% and 17% for dried and wet corn flour, and 27% and 10% for dried and wet corn powder. Future studies may use the experimental design of this work to standardize the evaluation methodology and more effectively evaluate the relevant influencing factors.
Assessment of Artificial Neural Network through Drought Indices
Authors: Doshi Smit Chetan , Shanmugam Mohana Sundaram , Akib Shatirah
Published: December 2022

Prediction of potential evapotranspiration (PET) using an artificial neural network (ANN) with a different network architecture is not uncommon. Most researchers select the optimal network using statistical indicators. However, there is still a gap to be filled in future applications in various drought indices and of assessment of location, duration, average, maximum and minimum. The objective was to compare the performance of PET computed using ANN to the Penman–Monteith technique and compare drought indices standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), using two different computed PET for the durations of 1, 3, 6, 9, and 12–months. Statistical performance of predicted PET shows an RMSE of 9.34 mm/month, RSR of 0.28, R2 of 1.00, NSE of 0.92, and PBIAS of −0.04. Predicted PET based on ANN is lower than that the Penman–Monteith approach for maximum values and higher for minimum values. SPEI–Penman–Monteith and SPI have a monthly correlation of greater than 0.95 and similar severity categories, but SPEI is lower than SPI. The average monthly index values for SPEI prediction show that SPEI–ANN captures drought conditions with higher values than SPEI–Penman–Monteith. PET–based ANN, performs robustly in prediction, fails by a degree of severity classification to capture drought conditions when utilized.
Current Status and Prospects of Valorizing Organic Waste via Arrested Anaerobic Digestion: Production and Separation of Volatile Fatty Acids
Authors: Giduthuri Anthony T. , Ahring Birgitte K.
Published: December 2022

Volatile fatty acids (VFA) are intermediary degradation products during anaerobic digestion (AD) that are subsequently converted to methanogenic substrates, such as hydrogen (H2), carbon dioxide (CO2), and acetic acid (CH3COOH). The final step of AD is the conversion of these methanogenic substrates into biogas, a mixture of methane (CH4) and CO2. In arrested AD (AAD), the methanogenic step is suppressed to inhibit VFA conversion to biogas, making VFA the main product of AAD, with CO2 and H2. VFA recovered from the AAD fermentation can be further converted to sustainable biofuels and bioproducts. Although this concept is known, commercialization of the AAD concept has been hindered by low VFA titers and productivity and lack of cost-effective separation methods for recovering VFA. This article reviews the different techniques used to rewire AD to AAD and the current state of the art of VFA production with AAD, emphasizing recent developments made for increasing the production and separation of VFA from complex organic materials. Finally, this paper discusses VFA production by AAD could play a pivotal role in producing sustainable jet fuels from agricultural biomass and wet organic waste materials.
Fire-Resistance Testing Procedures for Construction Elements—A Review
Authors: Chaturvedi Shashikant , Vedrtnam Ajitanshu , Youssef Maged A. , Palou Martin T. , Barluenga Gonzalo , Kalauni Kishor
Published: December 2022

Fire accidents are a significant risk to human life and civil infrastructure. As a countermeasure, the regulatory bodies of different countries have established standards for evaluating the performance of construction elements during fire exposure. ISO 834 is the globally accepted fire-resistance testing standard. Other standards include ASTM E119, BS 476, IS 3809, JIS A 1304, AS 1503, EN 1363, and GB/T 9978, which are utilized by the US, Britain, India, Japan, Australia, Europe, and China, respectively. This article presents a summary and comparison of the fire-resistance testing standards. In reality, standard tests for isolated structural members may not efficiently portray realistic fire scenarios due to the fire location, its intensity, etc. Thus, researchers have utilized a variety of specialized setups and full-scale non-standard fire tests to fulfill their research objectives. The article includes a summary of selected full-scale, ad hoc, and specialized setups that were reported in the literature. The article highlights the need for timely updates of fire standards to accommodate the testing of newly developed construction materials, structural systems, and possible regional fire scenarios. The article also identifies the research areas that require significant focus in experimental structural fire-resistant testing.
Vulnerability of the Small-Scale Fishery to Climate Changes in the Northern-Central Adriatic Sea (Mediterranean Sea)
Authors: Cavraro Francesco , Anelli Monti Marco , Matić-Skoko Sanja , Caccin Alberto , Pranovi Fabio
Published: December 2022

Climate change is altering the functioning of ecosystems and species distribution worldwide, with negative impacts on human activities, including fisheries. The Adriatic Sea is an extremely productive area for fisheries, due to the strong outflow of nutrients from rivers and the periodic mixing of nutrients from the Mediterranean. However, the Adriatic Sea is also a semi-closed basin, where species do not have the ability to move to higher latitudes to avoid warming of the waters. Climate change acts on biodiversity in a variety of ways, such as causing changes in the trophic network—favoring the intake of thermophilic alien species, often in competition with local species—and altering the biological cycles of acclimatized marine species to temperate–cold climates. These problems become critical factors for the survival of species and for fisheries relying on these resources. Within this context, to have estimates of possible modifications of the nektonic community in the near future could be quite useful for preparing adaptation plans. In this paper, using Maximum Entropy models under RCP 4.5 and 8.5 scenarios, we estimated the future habitat suitability for a set of marine nektonic species of different thermal affinity (e.g., cold, temperate and warm species) within GSA17 (Northern and Central Adriatic Sea), among the most productive—and most exploited—areas of the Mediterranean Sea. This study shows how, at the current pace, climate change could modify marine ecosystems to the extent that future habitat suitability will decrease for nearly half of the species considered, with a decrease in landings from 13.5 to 86.9%, depending on the scenario. Only for the blue crab Callinectes sapidus has an increase in habitat suitability been observed. For most of the species considered, temperature was the most important variable to explain the probability of relative presence within the GSA17. On the other hand, GSA17 climatic conditions in the near future under the tested scenarios could become a suitable environment for tropical species, which could find here a suitable habitat, at least in terms of thermal features. Results of the present study can help the management of fishery resources and local markets in the near future, providing information to predict changes in the composition of the aquatic community and draw up management plans that take into account the effects of climate change.
Spawning Phenology and Early Growth of Japanese Anchovy (Engraulis japonicus) off the Pacific Coast of Japan
Authors: Zhu Qinghuan , Wu Rui , Masuda Yoshio , Takahashi Yutaro , Okabe Kyu , Koizumi Koji , Iida Atsuko , Katayama Satoshi
Published: December 2022

The reproduction and early growth of fish are essential elements that affect recruitment and provide breakthrough points for understanding population fluctuations. In this study, larval and juvenile Japanese anchovy (Engraulis japonicus) were collected from five coastal waters off the Pacific coast of Japan in 2020 and 2021 to gain more insight into life history traits such as reproduction and early growth of this species on the basis of otolith microstructure analysis. The spawning period appeared to be related to temperature and chlorophyll-a concentrations, showing latitudinal gradient variation among fishing areas. We detected a significant positive allometric growth pattern between standard length and body weight. The Gompertz model best fits the growth of standard length, showing an initial stage of growth that was quick and accelerating. The mean daily growth rate for standard length was 0.64 ± 0.09 mm per day. A series of mixed-effect models was constructed to investigate the sources of differences in the mean growth rates among individuals. The results revealed regional variability in fish growth, with individuals in the central Pacific stock growing faster. Individuals that grew slower were heavier than those of the same length, indicating a trade-off between length growth and weight growth. The mean growth of individual fish was positively influenced by environmental factors (surface water temperature and chlorophyll-a concentration), and individuals within the same school of fish displayed a striking homogeneity of growth. Our research demonstrates the significance of including both physiological characteristics and environmental influences in early growth studies on fish.
Distinct Stocks of the Redtail Scad Decapterus kurroides Bleeker, 1855 (Perciformes: Carangidae) from the Northern Sulu and Southern Sibuyan Seas, Philippines Revealed from Otolith Morphometry and Shape Analysis
Authors: Barnuevo Kyle Dominic E. , Morales Christian James C. , Calizo Jenylle Kate S. , Delloro Emmanuel S. , Añasco Cherry Pilapil , Babaran Ricardo P. , Lumayno Sanny David P.
Published: December 2022

A recent study was performed to assess the morphometric variation of otoliths of the Decapterus kurroides collected in the northern Sulu and southern Sibuyan seas in delineating fish stocks. Seven of the otolith morphometric descriptors (otolith length, OL; otolith height, OH; otolith weight OW; otolith area, OA; otolith perimeter, OP; ellipticity, EL; and aspect ratio, AR) demonstrated a significant positive correlation with fish length and six (rectangularity, RE; squareness, SQ; roundness, RO; circularity, CI; compactness, CO; and form factor, FF) demonstrated a significant negative correlation. In terms of intraspecific comparisons, almost all the otolith morphometric descriptors were significantly different between the two sites (except RE and OH). Further, principal component (PC) analysis showed that direct otolith morphometric descriptors such as OL, OH, OW, OA, and OP explained 61.71% of the differences (PC1). In contrast, derived otolith descriptors such as EL, AR, and CO explained 22.00% of the variations (PC2) for a total of 83.71% explained variations with the eight otolith morphometric descriptors. Statistics reveal that D. kurroides from the Sibuyan Sea have significantly larger, heavier, and more elliptical otoliths than those from the Sulu Sea. Results suggested that the D. kurroides from Sulu and Sibuyan seas are two different phenotypic stocks. Further studies such as otolith microchemistry, genetics, other life history-based studies, and present exploitation levels should be carried out to supplement the results of this study to fully establish the D. kurroides stock structures within Philippine waters.
CFD Analysis of a Hydrostatic Pressure Machine with an Open Source Solver
Authors: Pienika Rodolfo , Cataldo José , Ramos Helena M.
Published: December 2022

The open source and freely available fluid flow solver named caffa3d was adapted to simulate the performance of a medium-scale Hydrostatic Pressure Machine (HPM) with straight radial blades, which had been previously tested in a laboratory facility. A fully detailed explanation of the code caffa3d is not intended to be included in this paper, but some of its main characteristics are mentioned for completeness. In addition, convergence and grid sensitivity analysis were performed in order to assess the adequacy of the model. Evolution of instantaneous power over a few turns of the HPM shows typical blade pass frequency for all operating discharges and another oscillatory phenomena at rotating frequency for higher discharges. The Power—Discharge and Efficiency—Discharge curves obtained from the simulations present a good correlation with the experimental curves, up to the discharge value corresponding to the maximum power of the HPM. The comparison error in power and efficiency remained below 6% for discharge lower than 97.8 L/s. For higher discharge, the flow through the HPM becomes very unsteady, with big eddy structures, underfilling of the buckets and recirculation down to the entry of the channel, significantly reducing the generated power. This behaviour was also observed during the previous experiments. In the present work, the foundations for the study of other types of turbines with caffa3d are laid.
Constructing Analytical Solutions of the Fractional Riccati Differential Equations Using Laplace Residual Power Series Method
Authors: Burqan Aliaa , Sarhan Aref , Saadeh Rania
Published: December 2022

In this article, a hybrid numerical technique combining the Laplace transform and residual power series method is used to construct a series solution of the nonlinear fractional Riccati differential equation in the sense of Caputo fractional derivative. The proposed method is implemented to construct analytical series solutions of the target equation. The method is tested for eminent examples and the obtained results demonstrate the accuracy and efficiency of this technique by comparing it with other numerical methods.
New Analytical Solutions for Time-Fractional Stochastic (3+1)-Dimensional Equations for Fluids with Gas Bubbles and Hydrodynamics
Authors: Alhamud Mohammed , Elbrolosy Mamdouh , Elmandouh Adel
Published: December 2022

This paper explores the effects of spatial fractional derivatives and the multiplicative Wiener process on the analytical solutions for (3+1)-dimensional fractional stochastic equations for fluids with gas bubbles. We study the bifurcation of the analytical solutions and introduce new fractional stochastic solutions. We also discuss how the solutions differ depending on the initial conditions. The new solutions are notably more beneficial and impactful for understanding various, significant, and incredibly hard physical phenomena due to the significance of the modified fractional stochastic (3+1)-dimensional equations for fluids with gas bubbles and hydrodynamics. We also discuss the effects of the fractional order and the Wiener process on the obtained analytical solutions.
The Stability of Set-Valued Differential Equations with Different Initial Time in the Sense of Fractional-like Hukuhara Derivatives
Authors: Wang Peiguang , Bi Jiahui
Published: December 2022

This paper investigates set-valued differential equations with fractional-like Hukuhara derivatives. Firstly, a novel comparison principle is given by introducing the upper quasi-monotone increasing functions. Then, the stability criteria of Lipschitz stability and practical stability of such equations with different initial time are obtained via the new comparison principle and vector Lyapunov functions.
Adaptive Quantized Synchronization of Fractional-Order Output-Coupling Multiplex Networks
Authors: Bai Yunzhan , Yu Juan , Hu Cheng
Published: December 2022

This paper is devoted to investigating the synchronization of fractional-order output-coupling multiplex networks (FOOCMNs). Firstly, a type of fractional-order multiplex network is introduced, where the intra-layer coupling and the inter-layer coupling are described separately, and nodes communicate with each other by their outputs, which is more realistic when the node states are unmeasured. By using the Lyapunov method and the fractional differential inequality, sufficient conditions are provided for achieving asymptotic synchronization based on the designed adaptive control, where the synchronized state of each layer is different. Furthermore, a quantized adaptive controller is developed to realize the synchronization of FOOCMNs, which effectively reduces signal transmission frequency and improves the effective utilization rate of network resources. Two numerical examples are given at last to support the theoretical analysis.
Fractional Order Model Identification of a Person with Parkinson’s Disease for Wheelchair Control
Authors: Ivanescu Mircea , Dumitrache Ioan , Popescu Nirvana , Popescu Decebal
Published: December 2022

The paper focuses on the design of an intelligent interface that compensates for the incapacity of a person with Parkinson’s disease to drive a wheelchair. The fractional order model that defines a person with Parkinson’s disease is investigated. An identification technique based on the analysis of the frequency behavior of the movement of a wheelchair driven by a with Parkinson’s disease person on the test trajectory is proposed and a delay time crossover model with fractional order exponent β=1.5 is inferred. The fractional dynamic model of the “disabled man-wheelchair” system is discussed and a control system is proposed to compensate for the inability of the wheelchair driver. The conditions that ensure the stability of the closed loop control system are inferred. An experimental technique for analyzing movement performance is developed and a quality index is proposed to evaluate these experiments. The values of this index on the tests performed on Parkinson’s patients are analyzed and discussed.
A Self-Healing Gel Polymer Electrolyte, Based on a Macromolecule Cross-Linked Chitosan for Flexible Supercapacitors
Authors: Xue Xiaoyuan , Wan Long , Li Wenwen , Tan Xueling , Du Xiaoyu , Tong Yongfen
Published: December 2022

Gel polymer electrolytes with a satisfied ionic conductivity have attracted interest in flexible energy storage technologies, such as supercapacitors and rechargeable batteries. However, the poor mechanical strength inhibits its widespread application. One of the most significant ways to avoid the drawbacks of the gel polymer electrolytes without compromising their ion transportation capabilities is to create a self−healing structure with the cross−linking segment. Herein, a new kind of macromolecule chemical cross−linked network ionic gel polymer electrolyte (MCIGPE) with superior electrochemical characteristics, a high flexibility, and an excellent self−healing ability were designed, based on chitosan and dibenzaldehyde−terminated poly (ethylene glycol) (PEGDA) via dynamic imine bonds. The ionic conductivity of the MCIGPE−65 can achieve 2.75 × 10−2 S cm−1. A symmetric all−solid−state supercapacitor employing carbon cloth as current collectors, activated a carbon film as electrodes, and MCIGPE−65 as a gel polymer electrolyte exhibits a high specific capacitance of 51.1 F g−1 at 1 A g−1, and the energy density of 7.1 Wh kg−1 at a power density of 500.2 W kg−1. This research proves the enormous potential of incorporating, environmentally and economically, chitosan into gel polymer electrolytes for supercapacitors.
Recent Advances and Progress of Conducting Polymer-Based Hydrogels in Strain Sensor Applications
Authors: Tran Vinh Van , Lee Kyungjun , Nguyen Thanh Ngoc , Lee Daeho
Published: December 2022

Conducting polymer-based hydrogels (CPHs) are novel materials that take advantage of both conducting polymers and three-dimensional hydrogels, which endow them with great electrical properties and excellent mechanical features. Therefore, CPHs are considered as one of the most promising platforms for employing wearable and stretchable strain sensors in practical applications. Herein, we provide a critical review of distinct features and preparation technologies and the advancements in CPH-based strain sensors for human motion and health monitoring applications. The fundamentals, working mechanisms, and requirements for the design of CPH-based strain sensors with high performance are also summarized and discussed. Moreover, the recent progress and development strategies for the implementation of CPH-based strain sensors are pointed out and described. It has been surmised that electronic skin (e-skin) sensors are the upward tendency in the development of CPHs for wearable strain sensors and human health monitoring. This review will be important scientific evidence to formulate new approaches for the development of CPH-based strain sensors in the present and in the future.
Communication Ecology Model of Successful Aging in Indonesian Context
Authors: Irwansyah Irwansyah
Published: December 2022

The communication ecology model of successful aging (CEMSA) as a part of aging studies from a communication perspective was replicated in the Indonesian context. The CEMSA provided a specific perspective from communication scholars about the successful aging process. The study of CEMSA has grown significantly to demonstrate the importance of the interactive-communication process to propagate and enhance aging studies. However, there has been no specific aging study from a communication perspective, especially from communication scholars in the Indonesian context. This study applied all concepts, variables, measurements, and analyses from the replicated study. The result showed that seven domains of communication about aging may be relevant to predict successful aging from a negative effect and positive effect, and efficacy toward aging. The model showed that the uncertainty and combination of a negative and positive effect in seven domains of communication about aging could construct the efficacy and success of the aging process. The model with seven domains of communication about aging could be proved while the data were gathered not by self-report.
Incongruent Views of Functioning between Patients and Gastroenterologists: A Mixed Methods Study
Authors: Eiroa-Orosa Francisco José , Georghiades Alicia , Rodriguez-Urrutia Amanda , Accarino Anna
Published: December 2022

Gastrointestinal patients, especially those diagnosed with functional digestive disorders (FGIDs), usually present a complex clinical picture that poses a challenge for their management in primary care. The main objective of the current research was to examine the relationship of the congruence of the perception of severity and quality of life between gastroenterologists and their patients with psychological distress and the helping attitude experienced by the latter attended in primary care centres. Additionally, we wanted to explore patients’ and practitioners’ perceptions. We performed a cross-sectional study with a total of 2261 patients (1562 analysed) that attended three primary care centres. Patients completed questionnaires that measured physical functioning, distress, and perception of helping attitude. Gastroenterologists registered the functional status of each participating patient. Patients were then invited to take part in the qualitative part of the study if they were considered to have incongruent views on their functioning with their gastroenterologist. In total, 52 patients took part in one of eight focus groups. Additionally, four individual interviews were carried out with three gastroenterologists and one consultation-liaison psychiatrist specialised in FGIDs. Both incongruence and functional diagnosis correlated with distress. However, incongruent views between patients and gastroenterologists explained more variance. Statistically significant differences in patients’ helping attitude perception were detected between diagnostic but no incongruence groups. In the second stage of the study, a total of five themes were identified from the patient focus groups and the gastroenterologist interviews: illness-emotional and personal problems, disease-health system interaction, health system, intervention, and patients. The current research allowed us to confirm that incongruence in the perception of severity and quality of life between gastroenterologists and patients is related to psychological distress and that this occurs in a multifactorial context where the characteristics of the disorder interact with those of the health system.
Epidemiology of Healthcare-Associated Infections and Adherence to the HAI Prevention Strategies
Authors: Alrebish Saleh A. , Yusufoglu Hasan S. , Alotibi Reem F. , Abdulkhalik Nawal S. , Ahmed Nehad J. , Khan Amer H.
Published: December 2022

Healthcare-associated infections are widely considered one of the most common unfavorable outcomes of healthcare delivery. Ventilator-associated pneumonia, central line-associated bloodstream infections, and catheter-associated urinary tract infections are examples of healthcare-associated infections. The current study was a retrospective study conducted at a public hospital in Unaizah, Saudi Arabia, to investigate the frequency of healthcare-associated illnesses and adherence to healthcare-associated infection prevention techniques in the year 2021. Surgical site infections occurred at a rate of 0.1%. The average number of catheter-associated urinary tract infections per 1000 catheter days was 0.76. The average number of central line-associated bloodstream infections per 1000 central line days was 2.6. The rate of ventilator-associated pneumonia was 1.1 per 1000 ventilator days on average. The average number of infections caused by multidrug-resistant organisms per 1000 patient days was 2.8. Compliance rates were 94%, 100%, 99%, and 76% for ventilator-associated pneumonia, central line-associated bloodstream infections, catheter-associated urinary tract infections, and hand hygiene bundles, respectively. It is critical to participate in more educational events and workshops, particularly those that emphasize hand cleanliness and personal safety equipment.
Analysing Objects to Tailor Environmental Preventive Conservation
Authors: Thickett David , Emmerson Nicola , Larsen Rene , Odlyha Marianne , Watkinson David
Published: December 2022

This work explores the potential of analyzing individual objects to improve their preventive conservation. Previously, environmental recommendations have been based on an average or worst response of material groups. Cultural heritage objects are extremely variable and within a group such as archaeological iron a very wide range of responses are shown. Characterizing a single object’s response allows its environment to be tailored to its requirements and can enable significant resource and carbon footprint savings. Three main approaches are considered with a material explored in detail including preventive conservation ramifications. Composition analysis is investigated through the stability of limestones. The critical concentrations of soluble salts causing surface deterioration in one environment has been explored. A more rapid method of analyzing clays in acid insoluble fractions from drillings and undertaking that analysis non-invasively has been developed. Measuring deterioration rates is explored through oxygen consumption analyses of archaeological iron. The distributions of previously published data are explored and the changes in rates examined. A scheme for parchment based on shrinkage temperatures and observations is presented for the first time and its use illustrated with a newly acquired letter. The type of work required to produce these schemes is explored with leather.
Intraperitoneally Delivered Umbilical Cord Lining Mesenchymal Stromal Cells Improve Survival and Kidney Function in Murine Lupus via Myeloid Pathway Targeting
Authors: Chua Alvin Wen Choong , Guo Dianyang , Tan Jia Chi , Lim Frances Ting Wei , Ong Chee Tian , Masilamani Jeyakumar , Lim Tony Kiat Hon , Hwang William Ying Khee , Lim Ivor Jiun , Chen Jinmiao , Phan Toan Thang , Fan Xiubo
Published: December 2022

To determine the therapeutic efficacy of human umbilical cord lining mesenchymal stromal cells (CL-MSCs) (US Patent number 9,737,568) in lupus-prone MRL/lpr (Faslpr) mice and elucidate its working mechanisms. A total of 4 doses of (20–25) × 106 cells/kg of CL-MSCs was given to 16-week-old female Faslpr mice by intraperitoneal injection. Three subsequent doses were given on 17 weeks, 18 weeks, and 22 weeks, respectively. Six-week-old Faslpr mice were used as disease pre-onset controls. Mice were monitored for 10 weeks. Mouse kidney function was evaluated by examining complement component 3 (C3) deposition, urinary albumin-to-creatinine ratio (ACR), and lupus nephritis (LN) activity and chronicity. Working mechanisms were elucidated by flow cytometry, Luminex/ELISA (detection of anti-dsDNA and isotype antibodies), and RNA sequencing. CL-MSCs improved mice survival and kidney function by reducing LN activity and chronicity and lymphocyte infiltration over 10 weeks. CL-MSCs also reduced urinary ACR, renal complement C3 deposition, anti-dsDNA, and isotype antibodies that include IgA, IgG1, IgG2a, IgG2b, and IgM. Immune and cytokine profiling demonstrated that CL-MSCs dampened inflammation by suppressing splenic neutrophils and monocytes/macrophages, reducing plasma IL-6, IL-12, and CXCL1 and stabilizing plasma interferon-γ and TNF-α. RNA sequencing further showed that CL-MSCs mediated immunomodulation via concerted action of pro-proinflammatory cytokine-induced chemokines and production of nitric oxide in macrophages. CL-MSCs may provide a novel myeloid (neutrophils and monocytes/macrophages)-targeting therapy for SLE.
Immune Modulatory Effects of Ketogenic Diet in Different Disease Conditions
Authors: Srivastava Shivani , Pawar Vishakha , Tyagi Anuradha , Sharma Kanti , Kumar Vinay , Shukla Surendra
Published: December 2022

Interceding nutrients have been acquiring increased attention and prominence in the field of healing and deterrence of various disorders. In this light, the present article encompasses several facets of ketogenic diet as an immunomodulator with respect to its expansive clinical applications. Accordingly, several scientific records, models, and case histories, including viral infections, cancer, chronic diseases, e.g., cardiovascular diseases, epilepsy, as well as numerous other neuro-disorders, are assembled, revealing a profound influence of KD in favor of improvement in the patient’s condition. We accentuate possible manifold mechanisms of KD that require further exploration.
Development of Solutions for Increasing the Combustion Efficiency of Hydrogen in Water Vapor in a Hydrogen-Oxygen Steam Superheater
Authors: Rogalev Andrey , Rogalev Nikolay , Kharlamova Daria , Shcherbatov Ivan , Karev Timofey
Published: December 2022

The study is aimed at revealing the specific features of the burning of hydrogen with oxygen in a water-vapor atmosphere. The purpose of the study is to define the optimal values for diluting the burning mixture with water vapor in the active burnout zone, providing the minimal values of incomplete combustion. Modeling of burning processes was carried out with the use of kinetic mechanisms in the Ansys Chemkin-Pro software. The result of the study was the definition of critical water vapor content in a burning mixture as 60% fraction of total mass with, obtaining dependencies of key parameters of the burning process within a wide range. The mechanism of chemical kinetics was selected for further modeling in a three-dimensional setting, and tasks for the formulation of requirements and methods for the design of efficient hydrogen combustion chambers were set up for 500 MW gas turbine plants at a supercritical pressure of 20 MPa or higher.
An Investigation to Detect Banking Malware Network Communication Traffic Using Machine Learning Techniques
Authors: Kazi Mohamed Ali , Woodhead Steve , Gan Diane
Published: December 2022

Banking malware are malicious programs that attempt to steal confidential information, such as banking authentication credentials, from users. Zeus is one of the most widespread banking malware variants ever discovered. Since the Zeus source code was leaked, many other variants of Zeus have emerged, and tools such as anti-malware programs exist that can detect Zeus; however, these have limitations. Anti-malware programs need to be regularly updated to recognise Zeus, and the signatures or patterns can only be made available when the malware has been seen. This limits the capability of these anti-malware products because they are unable to detect unseen malware variants, and furthermore, malicious users are developing malware that seeks to evade signature-based anti-malware programs. In this paper, a methodology is proposed for detecting Zeus malware network traffic flows by using machine learning (ML) binary classification algorithms. This research explores and compares several ML algorithms to determine the algorithm best suited for this problem and then uses these algorithms to conduct further experiments to determine the minimum number of features that could be used for detecting the Zeus malware. This research also explores the suitability of these features when used to detect both older and newer versions of Zeus as well as when used to detect additional variants of the Zeus malware. This will help researchers understand which network flow features could be used for detecting Zeus and whether these features will work across multiple versions and variants of the Zeus malware.