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The sulfuric acid-doping polyaniline (H-PANI-HSO4) are applied to conduct the electrochemical measurement and simulation calculation to investigate the capacitance, electronic structure and energy band properties. The H-PANI-HSO4 growing on graphite carbon paper (H-PANI-HSO4/GCP) is applied as an electroactive electrode to investigate electrochemical properties. The Faradaic capacitance of H-PANI-HSO4/GCP electrode is ascribed to the reversible redox reaction of bisulfate anion doping/dedoping protonated PANI (H-PANI). Cyclic voltammetry measurement at a scan rate of 5mVs−1 determines an equivalent mean response current of 0.64Ag−1 and a capacitance of 128.35Fg−1. Galvanostatic charge–discharge measurement determines specific capacitance from 129.06 to 116.88Fg−1 at current densities from 0.5 to 2.5Ag−1. Cyclic voltammetry-based capacitance at equivalent current density of 0.64Ag−1 is in accordance with galvanostatic charge–discharge-based capacitance at the current density of 0.57Ag−1. Electrochemical impedance spectrum measurements indicate that H-PANI-HSO4/GCP exhibits lower charge-transfer resistance, much lower Warburg resistance, higher quasicapacitance than H-PANI-HSO4 to approaching ideal capacitor. Density functional theory calculations indicate that H-PANI-HSO4 has a higher density of states (10.6 electron/eV) and lower bandgap energy (0.481eV) than H-PANI (5.24 electron/eV, 1.449eV), indicating its enhanced electronic conductivity. The electronic bandgap energy is accordingly decreased from 0.263eV for H-PANI-HSO4/GCP to 0 for H-PANI-HSO4/GCP. Electrochemical measurement and simulation calculation investigation proves that H-PANI-HSO4/GCP electrode with anion-doped and protonated state exhibits higher electronic conductivity and capacitance performance to act as superior electroactive material. [ABSTRACT FROM AUTHOR]

The Laser Interferometer Space Antenna (LISA) mission, scheduled for launch in the mid-2030s, is a gravitational wave space observatory designed to detect sources emitting in the millihertz band. LISA is an European Space Agency flagship mission, currently entering the Phase-B development phase. It is expected to help us improve our understanding of our Universe by measuring gravitational wave sources of different types, with some of the sources being at very high redshifts (z ∼ 2 0). On February 23, 2022, we organized the first LISA in Greece Workshop. This Workshop aimed to inform the Greek scientific and tech industry communities about the possibilities of participating in LISA science and the LISA mission, with the support of the Hellenic Space Center. In this White Paper, we summarize the outcomes of the Workshop, the most important aspect of it being the inclusion of 1 5 Greek researchers to the LISA Consortium, raising our total number to 2 2. At the same time, we present a road map with the future steps and actions of the Greek Gravitational Wave community with respect to the LISA mission. [ABSTRACT FROM AUTHOR]

The paper focuses on the cutting behavior of Glass Fiber Reinforced Polymer (GFRP) composites and GNP–GFRP composites that contain varying amounts of Graphene Nano Platelets (GNP). GFRP composites are increasingly being used in a variety of industrial applications due to their excellent mechanical properties, such as high strength, stiffness, and low weight. However, their machining and cutting behavior can be challenging due to the presence of the reinforcing fibers. Therefore, the study aims to investigate the machining behavior of GFRP composites and the effect of adding GNP on their cutting behavior. The effect of different parameters such as cutting speed, feed rate and reinforcement rate on cutting forces and delamination factor is investigated. In addition, the tensile strength and fatigue behavior of the composite materials with the best and worst delamination factors were also determined. Addition of up to 0.2 wt.% of GNP to GFRP composites resulted in an increase in cutting forces and delamination factor when drilling GFRP composites. While the cutting force and delamination factor decreased with the increase in cutting speed, the cutting force and delamination factor increased with the increase in the feed rate. Analysis of variance (ANOVA) was performed to determine the effects of drilling parameters and reinforcement ratio on cutting force and delamination factor according to full factorial experimental design. The most efficient factor on the cutting forces is found to be feed rate (84.97%), followed by the reinforced rate (6.48%) and cutting speed (6.13%). The most efficient factor on the delamination factor is determined to be feed rate for (44.49%), followed by the reinforced rate (29.20%) and cutting speed (21.73%). [ABSTRACT FROM AUTHOR]

The novel coronavirus disease — COVID-19 is a historic catastrophe that has caused many devastating impacts on human life and wellness. Researchers in academia and industry strive to understand the causes of this pandemic disease and find new therapeutics combating it. Consequently, the number of COVID-19 related publications increases rapidly, and it is too difficult for medical researchers and practitioners to keep up with the latest research and development. Literature filtering and categorization, and knowledge discovery can use text mining as a powerful tool. In this paper, we propose a text mining method to explore the categories of COVID-19 related themes and identify the standard methodologies that have been used. We discuss the potential limitations of this preliminary study and present future perspectives related to COVID-19 research. This paper provides an quantitative and qualitative mixed analysis example of using some research papers by data mining method to dig out several hidden information and set up a foundation for data scientists to develop more effective algorithms to deal with COVID-19 related problems. [ABSTRACT FROM AUTHOR]

The European Water Framework Directive (WFD) is one of the most analyzed environmental legislations in the scientific literature, influencing the water management in some non-European countries. The WFD has the strong ambition of achieving a good ecological status of water bodies across all river basins in Europe. However, the advances towards sustainable management are falling far behind the planned schedule. The emphasis of the Directive is focused on water quality rather than on water quantity. The advances during the last quarter of the century since its inception have been strong on urban and industrial point pollution, but not on agricultural non-point pollution that remains high and even increases in major basins. Water quantity aspects have been mostly left aside in the Directive, despite the fact that water scarcity is a serious problem in Southern European countries, and will become more critical with climate change in most basins across Europe. Some policy measures of the WFD need to be reformed, in particular measures for abating agricultural pollution, and new measures for addressing water scarcity. The narrow focus of the WFD on water pricing to solve at the same time issues of financing, water allocation and efficiency, environment, opportunity costs and pollution abatement, should be broadened. The challenge is giving more emphasis to command & control and collective action instruments, and designing combinations of instruments adapted to sectoral and spatial locations in basins. This overhaul of the water policy instruments by the European Commission will be needed to advance in the sustainable management of river basins in Europe. [ABSTRACT FROM AUTHOR]

In this paper, an analysis of the precision of range sensors is presented. Light Detection and Ranging (LIDAR) data from three different sensors (HLS-LFCD-LDS, SICK TIM561, and Kinect V2), stereo data from the Realsense D435, and structured light data from both Kinect V1 for Xbox and the Xtion PRO Live were analyzed regarding the influence of range, incident angle to the surface, and surface material. In addition, a comparison with standard deviation models based on vendor-provided specifications was performed. We found that the vendor specifications are in general not specific enough to facilitate accurate sensor simulations. Therefore, we developed a data-driven model for range precision. Our model can be used to create realistic sensor simulations and to develop robot navigation algorithms weighing sensor range readings based on the precision. [ABSTRACT FROM AUTHOR]

This paper aims to comprehensively explore the pivotal role of simulation and modeling in the field of Artificial Intelligence (AI). It focuses on elucidating the diverse applications of simulation and modeling in training AI systems, optimizing algorithms, and enhancing decision-making processes. To achieve this objective, we conducted an extensive review of the literature from the Scopus database, employing a well-defined selection process. We utilized keywords such as "simulation," "modeling," "Artificial Intelligence," and related terms to identify relevant papers published within the last 10 years. The selection criteria included assessing the relevance, quality, contribution, and recent citations of the papers. After a rigorous screening process, we selected 40 papers with the highest overall scores for inclusion in our review. The selected papers encompass a wide range of domains where simulation and modeling play a vital role in advancing AI applications. These domains include manufacturing, healthcare, energy consumption prediction, public sector decision-making, education, environmental modeling, and more. Our review highlights how AI leverages simulation and modeling to improve predictive accuracy, optimize resource allocation, and enhance decision-making processes across diverse sectors. We also discuss the potential future directions in the integration of simulation and modeling with AI, emphasizing its significance in various fields. [ABSTRACT FROM AUTHOR]

How to improve the high resolution and remove the noise of composite infrared thermal wave detection image have become important research topics in machine vision. Therefore, this paper proposes a composite image enhancement algorithm based on edge adaptive total variation of direction. Using the improved adaptive directional total variation model to construct the guidance image of the guidance filter can provide better structural information for the guidance filter and conduct the guidance filter. This process is iterated to eliminate noise and ladder effect. Experimental results show that this algorithm is superior to other advanced methods in objective evaluation index and subjective vision. The algorithm proposed in this paper can not only effectively eliminate noise and ladder effect, but also highlight image details and structure information, which proves the effectiveness of this algorithm. Discover the cutting-edge algorithm for high-resolution improvement and noise elimination in infrared thermal wave detection images. Our innovative composite image enhancement technique, based on edge adaptive total variation, outperforms traditional methods. The improved directional model provides better structural information, optimizing the guidance filter process. Experimental results reveal its superiority in objective evaluation and subjective vision. This algorithm effectively eliminates noise and ladder effect while highlighting image details, validating its remarkable effectiveness. [ABSTRACT FROM AUTHOR]

The International Journal of Semantic Computing has published a special issue on Semantic Computing, which includes five selected papers from the 17th IEEE International Conference on Semantic Computing. Semantic Computing focuses on the derivation, description, integration, and use of semantics for various resources. The papers in the special issue cover topics such as intent detection, constructing probabilistic models from knowledge graphs, unsupervised estimation of subjective content descriptions, the influence of noisy labels on question answering systems, and automatic domain-adaptive sentiment analysis. Each paper presents innovative approaches and findings in their respective areas of research. [Extracted from the article]

Traditional requirement verification methods often fail to fully consider the modeling of time-dependent behaviors during system execution, which may lead to inconsistent system requirements, thereby compromise software reliability and correctness. To address this limitation, this paper proposes the Scenario-Specific Verification Method for System Requirements Consistency via Time Modeling. The Scenario-Specific Verification Method converts use case descriptions and problem graphs into Clock Constraint Specification Language (CCSL) constraints, transformed into clock graphs for verifying requirement consistency. The resulting constraints are solved with the Z3 solver to validate correctness, thereby enhancing system reliability. The novel time modeling approach provides techniques for verifying temporal dependencies in requirements. A case study demonstrates the efficiency and accuracy of the Scenario-Specific Verification Method in detecting inconsistencies. The main contributions include that a technique is demonstrated to formalize use case descriptions as CCSL constraints, improving on natural language and a method is presented utilizing CCSL time modeling and clock graphs to analyze requirements for consistency. Overall, an innovative solution for requirement verification using time modeling is offered by this paper, contributing to the enhancement of system development process reliability and correctness. [ABSTRACT FROM AUTHOR]

Amid the pandemic infection, people are bound to use contactless mobile payment (M-Payment) services. M-Payment is a payment method using an application in a mobile device, such as a mobile phone, and gadget. Owing to the convenience, reliability and contact-free feature of M-Payment, it has been diffusely adopted to reduce the direct and indirect contacts in transactions, allowing social distancing to be maintained and facilitating the stabilization of the social economy. Consequently, it has become one of the day's most important topics. Therefore, the purpose of this study is to provide a systematic literature review (SLR) on the applications of M-payment services in financial strategies, focusing on the pandemic crisis. 19 papers were collected and divided into three groups for further analysis. The results showed that M-Payments applications in financial strategies during the pandemic crisis could help reduce the spread of infection risks by hastening the transition to touchless habits. [ABSTRACT FROM AUTHOR]

In recent years, the concurrent occurrences of the COVID-19 pandemic and the Russian invasion of Ukraine have led to global disruptions in supply chains and a surge in commodity prices. Major advanced economies have experienced an increase in inflation rates and a decline in economic activity. Against this economic backdrop, this paper aims to address the strained condition of supply chains by employing the Global Supply Chain Pressure Index (GSCPI) alongside commodity price indices. Furthermore, it seeks to examine how fluctuations in these variables affect Japan's macroeconomic landscape through local projection and structural Vector Autoregression (VAR). In the local projection analysis, it has been observed that the strain on supply chains induces sustained increases in consumer and producer prices, further contributing to long-term declines in production. Within the structural VAR model framework, the identification of structural shocks is conducted through sign restrictions, affirming the significance of supply chain shocks and energy and food price shocks as crucial factors contributing to recent price increases. This confirmation is supported by variance decomposition and historical decomposition analyses. [ABSTRACT FROM AUTHOR]

The global financial crisis that followed Lehman Brothers' declaration of bankruptcy in September 2008 critically highlighted the significance of research on systemic risk and macro-prudential supervision. Accordingly, this paper mainly analyzed the relationship between financial crises and the article output in financial crisis research through the application of bibliometrics. The occurrence of a financial crisis leads to changes in the output of articles on crisis and risks. Hence, we focused on bibliographic coupling (e.g., co-authorship, co-occurrence), data classification by risk type in this study (e.g., market risk, credit risk) and citation analysis (e.g., top 1% cited paper). Meanwhile, the analysis indicated the most relevant disciplines in financial crisis research. For example, the number of top 1% cited articles and citations, MARKET RISK documents and citations published the most papers. In other words, the market risk is valued in the financial risk literature. [ABSTRACT FROM AUTHOR]

Unreliable suppliers may pose a substantial threat to supply chains, especially when they hold private information of their reliability. We consider a dyadic supply chain where the information of supplier reliability (in the form of random production yield) is asymmetric. We propose a new mechanism-design model and derive the buyer's optimal procurement contract menu offered to suppliers with private information. We prove that the contract menu is as simple as offering two different inflated order amounts and setting the procuring price sufficiently low to let the suppliers earn zero reservation profits. These results are derived analytically under uniform distribution. We test them numerically under beta distribution and find them hold as well. However, the informational rent will become positive when the supplier's reservation profit is positive. Positive informational rent is also found when we consider another structure of the supplier's production cost. This paper provides some new insights into supply chain management under asymmetric information of uncertain supply. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on topics including water-related ecosystem services, plastic pollution abatement willingness, and water user fees' impact on pollution reduction, among other related topics.

An introduction is presented in which the editor discusses articles in the issue on topics including breast cancer image classification, intelligent engineering management with data mining, and identifying optimal methods for power grid error parameters.

The paper examines various properties of D T - k -subgroup structures and addresses an open problem on the existence of topological group structures on the n -dimensional Khalimsky (K -, for brevity) topological space and Marcus–Wyse (M -, for short) topological plane. In particular, we obtain many types of totally k -disconnected or k -connected subgroups of a k -connected D T - k -group. Besides, we prove that each of the n -dimensional K -topological space and the M -topological plane cannot be a typical topological group. Unlike an existence of a D T - k -group structure of (S C k n , l , ∗) (see Proposition 4.7), we prove that neither of (S C K n , l , ∗) and (S C M l , ∗) is a topological group, where S C K n , l (respectively, S C M l ) is a simple closed K - (respectively, M -) topological curve with l elements in ℤ n (respectively, ℤ 2 ) and the operation "∗" is a special kind of binary operation for establishing a group structure of each of S C K n , l and S C M l . Finally, given a D T - k -group structure of (S C k 1 n 1 , l 1 × S C k 2 n 2 , l 2 , ∗) , we find several types of D T - k -subgroup structures of it (see Theorem 5.7). [ABSTRACT FROM AUTHOR]

The enhanced power graph of a group G is a simple undirected graph with vertex set G and two vertices are adjacent if they belong to the same cyclic subgroup. In this paper, we obtain the Laplacian spectrum of the enhanced power graph of certain non-abelian groups, viz. semidihedral, dihedral and generalized quaternion. Also, we obtained the metric dimension and the resolving polynomial of the enhanced power graphs of these groups. At the final part of this paper, we study the distant properties and the detour distant properties, namely: closure, interior, distance degree sequence, eccentric subgraph of the enhanced power graph of semidihedral group, dihedral group and generalized quaternion group, respectively. [ABSTRACT FROM AUTHOR]

Numerical unsteady approach based on Galerkin method with the inclusion of adaptive mesh was executed in this paper to simulate the freezing of water within a container. The domain has two triangular and trapezoidal cold surfaces and two adiabatic walls. The governing equations show the domination of conduction and transient source term has been involved. Galerkin method for modeling was applied and good accommodation has been reported based on comparison with previous data. Adding nano-powders makes the amount of heat to be released with stronger conduction and freezing time decreases about 26.76% when m = 8. 6. Augmenting the fraction of powders can make the rate of process increase. For the greatest fraction of powders, an augmenting shape factor can enhance the speed of process about 6.95%. [ABSTRACT FROM AUTHOR]

The diversity, infinity, and nonuniform description of human motion make it challenging for computers to understand human activities. To explore and reuse captured human motion data, this work defines a more comprehensive hierarchical theoretical model of human motion and proposes a standard human posture encoding scheme. We construct a domain knowledge graph (DKG) named the human motion encoding knowledge graph (HME-KG) based on posture codes and action labels. Community detection, similarity analysis, and centrality analysis are used to explore the potential value of motion data. This paper conducts an evaluation and visualization of HME-KG. [ABSTRACT FROM AUTHOR]

Modular robots carry the unique advantage of changing their shape according to different tasks and environments. In order to study the lightweight and flexible combination characteristics of modular robots, this paper presents a two-degree-of-freedom pluggable modular robot and its simulation method, named SnackBot. SnackBot is composed of several independently operating modules. Each module contains a control unit, a micro battery, and two DC motors that drive the module joints. In order to predict robot actions and monitor the state of the robot, the simulation model of SnackBot is built and a virtual environment is established in Ignition Gazebo. The virtual robot and physical robot are synchronously controlled in the environment of the Robot Operating System 2 (ROS2). Finally, experimental results verify the feasibility of the SnackBot. [ABSTRACT FROM AUTHOR]

Milk is considered to be one of the most perfect natural foods for human beings. The analysis of effective components and determination of important components in milk is an important practical work. Based on the previous measurement data of fat volume concentration and refractive index of milk in the market, this paper forms a fitting formula through mathematical fitting, which can solve the corresponding relationship between nonmeasurement points of milk concentration and refractive index. Because the actual measurement points are limited, its practical application is not convenient. However, fitting formulas can calculate the corresponding values of infinitely many points, which can be easily applied. However, judging from the goodness of fit of the fitting formula, a theoretically good fitting formula may produce underfitting and overfitting in practical application. Through the analysis of the first-order to sixth-order fitting formulas of milk concentration and refractive index, this paper tells us that the fitting formula with high goodness of fit is not necessarily a good formula. The specific problems should be analyzed in the application process to make the theory more consistent with the actual situation. From the calculation and analysis in this paper, it can be seen that the fitted sixth-order formula has the best effect when the fat volume concentration of milk is 0–10%. When considering a fat volume concentration of 0–34% in milk, the fitted second-order formula performs better. [ABSTRACT FROM AUTHOR]

The Second Issue of Volume 10 of Water Economics and Policy (WEP) features five research papers that examine various water management challenges at different spatial scales. The papers cover topics such as game theory applied to aquifer sub-basin management in Spain, benefit-cost analysis of river bank erosion investments in Serbia, flood damage assessment models in Turkey, the impact of agricultural production on groundwater depletion in India, and the water footprint and vulnerability of China's provincial energy sector. These studies provide valuable insights into water management challenges and offer potential policy implications for addressing these issues. [Extracted from the article]

This article explores the properties of 2D defective Mo1.33C MXene, a material that shows promise in electromagnetic interference (EMI) shielding. The researchers tested a defect-containing Mo1.33C MXene "paper" and found positive results compared to other MXene and graphene-based materials. The article provides information on the preparation of the MXene and the experimental methods used for characterization and testing. The research suggests that Mo-based defective MXene could have applications in EMI shielding. [Extracted from the article]

In this paper, a new detection method of pin defects based on image segmentation and ResNe-50 is proposed, which realizes the defect detection of faulty pins in many aviation connectors. In this paper, a new dataset image segmentation method is used to segment many aviation connectors in a single image to generate a dataset, which reduces the tedious work of manually labeling the dataset. In the defect detection model, based on ResNet-50, a ResNet-B residual structure is introduced to reduce the loss of features during information extraction; a continuously differentiable CELU is used as the activation function to reduce the neuron death problem of ReLU; a new deformable convolution network (DCN v2) is introduced as the convolution kernel structure of the model to improve the recognition of aviation connectors with prominent geometric deformation pin recognition. The improved model achieved 97.2% and 94.4% accuracy for skewed and missing pins, respectively, in the experiments. The detection accuracy improved by 1.91% to 96.62% compared to the conventional ResNet-50. Compared with the traditional model, the improved model has better generalization ability. [ABSTRACT FROM AUTHOR]

The application of the combination of unmanned aerial vehicles (UAVs) and artificial intelligence is a hot topic in the intelligent inspection of substations, and meter reading is a very challenging task. This paper proposes a method based on the combination of YOLOv6n object detection and Deeplabv3 + image segmentation and performs post-processing on the segmented images to obtain meter readings. First, YOLOv6n is used to detect the meter area of the aerial image and classify the meters. Second, the detected meter images are fed into the image segmentation model. The backbone network of the Deeplabv3 + algorithm is improved by using the MobileNetv3 network, which not only effectively extracts pointers and scales, but also makes the model more lightweight. Third, License Plate Recognition Network (LPRNet) is used to recognize digital meter images. In order to solve the problem of inaccurate pointer meter readings, to begin with, the segmented image is corroded; in addition, the circular dial area is flattened into a rectangular area by concentric circle sampling method. Finally, the meter reading is calculated by the position of the pointer, the scale and the total range of the meter. The post-processing part uses numba to optimize the inference speed. The experimental results show that in two datasets, The mean average precision of 50 (mAP50) accuracy of the YOLOv6n model using this method reached 99.71% and 98.60%, respectively, and the inference speed of a single image was 17.1 ms and 13.2 ms, respectively. The mean intersection over union (mIoU) of the image segmentation model reached 82.00%, 74.73%, 73.50%, 82.26% and 73.20%, respectively, and the single segmentation speed reached 33.7 ms. The LPRNet model has a recognition accuracy of 99.17% and a single image inference speed of 14.7 ms. At the same time, several mainstream object detection and semantic segmentation algorithms are compared. The experimental results show that the method in this paper greatly improved the accuracy and efficiency of intelligent inspection of substation meter readings. [ABSTRACT FROM AUTHOR]

The focus of this paper is impulse noise reduction in digital color images. The most popular noise reduction schemes are the vector median filter and its many variants that operate by minimizing the aggregate distance from one pixel to every other pixel in a chosen window. This minimizing operation determines the most confirmative pixel based on its similarity to the chosen window and replaces the central pixel of the window with the determined one. The peer group filters, unlike the vector median filters, determine a set of pixels that are most confirmative to the window and then perform filtering over the determined set. Using a set of pixels in the filtering process rather than one pixel is more helpful as it takes into account the full information of all the pixels that seemingly contribute to the signal. Hence, the peer group filters are found to be more robust to noise. However, the peer group for each pixel is computed deterministically using thresholding schemes. A wrong choice of the threshold will easily impair the filtering performance. In this paper, we propose a peer group filtering approach using principles of Bayesian probability theory and clustering. Here, we present a method to compute the probability that a pixel value is clean (not corrupted by impulse noise) and then apply clustering on the probability measure to determine the peer group. The key benefit of this proposal is that the need for thresholding in peer group filtering is completely avoided. Simulation results show that the proposed method performs better than the conventional vector median and peer group filtering methods in terms of noise reduction and structural similarity, thus validating the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the notion of a newly derived signed graph called a coset component graph, based on cosets of subgroups of a group is introduced. Let G be a group and H be its subgroup. Then, the coset component graph of H in G , denoted by Γ cc , is a simple graph with the vertex set consisting of elements of G and two vertices say, a , b ∈ Γ cc are adjacent if either a H = b H or H a = H b. A coset component signed graph of H in G is a signed graph whose edges get the sign in accordance with their inclusion in the edge set of the corresponding coset component graph. The structure and important properties of the coset component signed graphs are determined in this paper. [ABSTRACT FROM AUTHOR]

Traditional two-color lights out games and their solutions have been studied extensively. This paper focuses on the existence, or lack there of, of solutions in more general lights out games, which take on a prime number of color states. The result in this paper generalizes the existence of solutions in the family of lights out games on a (p + 1) × n grid with p -colors where n ∈ N and p. [ABSTRACT FROM AUTHOR]

In this paper, a new delayed fractional-order model including susceptible migratory birds, infected migratory birds and predators is proposed to discuss the spread of diseases among migratory birds. Fear of predators is considered in the model, as fear can reduce the reproduction rate and disease transmission rate among prey. First, some basic mathematical results of the proposed model are discussed. Then, time delay is regarded as a bifurcation parameter, and the delay-induced bifurcation conditions for such an uncontrolled system are established. A novel periodic pulse feedback controller is proposed to suppress the bifurcation phenomenon. It is found that the control scheme can successfully suppress the bifurcation behavior of the system, and the pulse width can be arbitrarily selected on the premise of ensuring the control effect. Compared with the traditional time-delay feedback controller, the control scheme proposed in this paper has more advantages in practical application, which not only embodies the advantages of low control cost and easy operation but also caters to the periodic changes of the environment. The proposed control scheme, in particular, remains effective even after the system has been disrupted by a constant. Numerical simulation verifies the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper develops a queueing system model to analyze the operations of a hierarchical healthcare system consisting of general hospitals (GHs) and community healthcare centers (CHCs). GHs typically provide a higher level of health care service than CHCs, and thus are preferred choices for many patients' healthcare service needs. Consequently, GHs are often heavily congested and patients often incur excessive waiting time. In contrast, CHCs are often idle and resources are underutilized. To help balance the utilization of resources in GHs and CHCs, a congestion-based information guidance policy is proposed in this paper to inform patients in the GH service queue about the anticipated delay. Upon being informed the delay for GH service, patients may balk, remain in queue for GH service, or switch to receive service at CHCs. This policy is thus expected to relieve the congestion at GHs and promote CHC usage. To study the effects of the proposed policy, a hierarchical healthcare system is modeled as a queueing system with strategic patients. Stationary performance measures of the system are analytically characterized using a Markov chain model. Stochastic and numerical analyses provide insights on how to design information guidance policy that would help improve overall health care service quality under different scenarios. [ABSTRACT FROM AUTHOR]

With a numerical method, the discharging process within a container with a double complex cold surface has been scrutinized in this paper. The inherent process makes conduction as the main mechanism and the temperature equation includes three terms and two of them are time-dependent which was discretized by means of implicit technique. Adding nanoparticles within water can enhance the rate of heat release and concentration of powders and their shapes can affect the properties of nanomaterial. Single phases for estimating the features of nanomaterial were applied. The maximum period of process takes 326.95 s which is 1.36 times lower than the case of pure water. Increasing the shape factor can enhance the speed of process and its impact is less than concentration of additives. [ABSTRACT FROM AUTHOR]

Considerations on the current status of the theory of superconductivity, the bibliometric H-index, and H. C. Andersen's tale about the emperor's new clothes. First appeared in the APS Forum on Physics and Society quarterly newsletter, January 2020. [ABSTRACT FROM AUTHOR]

The leisure agriculture in suburban towns provides important space for citizens to carry out leisure activities. This paper takes Xinkou town in Tianjin city as an example to analyze the development efficiency of leisure agriculture in suburban towns. On the premise of establishing the indicators for evaluating the development efficiency of leisure agriculture in Xinkou town, this paper first uses the data envelopment analysis (DEA) to measure the input and output indicators of leisure agriculture in 18 natural villages in Xinkou town, and calculates the comprehensive technical efficiency, target values, redundancy and returns to scale of leisure agriculture, and then evaluates the development efficiency of leisure agriculture in Xinkou town. Furthermore, by using the high/low clustering tool under the ArcGIS spatial statistics module, this paper conducts a high/low clustering analysis of the development efficiency of leisure agriculture in 18 natural villages of Xinkou town, and figures out the reasons for the high/low clustering of natural villages in Xinkou town spatially. After the research and analysis, the following conclusions are drawn: From the input–output perspective, except for Zhengzhuangzi village, Diliubu village, Yuejiakai village, and Dangcheng village, the development efficiency of leisure agriculture in other villages is relatively low due to their poor resource foundations, or deficiencies in management experience and transportation location. The development of leisure agriculture in Xinkou town is unbalanced, showing a pattern of polarized clusters: Diliubu village and Shuigaozhuang village form the most obvious high-value cluster, while Xiaoshawo village, Bijia village and Xuanjiayuan village form the most obvious low-value cluster, where the southeast corner of Xinkou town registers the lowest development efficiency value of leisure agriculture because it is far away from the town center and the main transportation arteries, and falls short of high-quality pastoral scenery. For the future development of leisure agriculture in Xinkou town, it is supposed to optimize the land use policy, provide active support to the competitive industrial and commercial capital, non-governmental capital, rural collective economic organizations, farmers' cooperatives, and family farms, strengthen the in-depth integration of industries, improve the support system for new-type leisure agriculture, and build leisure agriculture brands with local features. [ABSTRACT FROM AUTHOR]

In view of the problems of high production cost, scarcity and lack of diversity of 3D face datasets, this paper designs an end-to-end self-supervised learning 3D face reconstruction algorithm with a single 2D face image as input, which only uses 2D face datasets to complete model training. First, the improved ResNet module is introduced to preprocess the input face image. The deep residual neural network has strong feature extraction and characterization ability for the image, which can provide rich high-level semantic feature maps for the subsequent subnetwork. Then, add transformer module completely based on self-attention mechanism to the parameter prediction subnetwork, which can make different parameters of the subnetwork focus on self-related feature map information and avoid interference from invalid feature map information, so as to further improve the parameter prediction accuracy of the subnetwork. Next, training, ablation and comparison experiments were conducted on CelebA, BFM and Photoface datasets, and the combined function of pixel loss function and perceptual loss function was selected as the loss function. The experimental results show that: compared with the historical optimal results of the same network structure, the scale-invariant depth error (SIDE) and mean angle deviation (MAD) are improved by 5.9% and 10.8%, respectively, which strongly proves the effectiveness of the algorithm. Finally, in order to verify the actual effect of the 3D face reconstruction algorithm, examples are selected in this paper for reconstruction. The 3D faces generated by the algorithm all have a good sense of reality, which intuitively and effectively proves the advancement of the algorithm. [ABSTRACT FROM AUTHOR]

This research paper investigates the behavior of optical fiber pulses by studying the solitary wave solutions of the perturbed Chen–Lee–Liu (CLL) equation. The perturbed CLL equation is derived from the perturbed Schrödinger equation. Two analytical approaches for obtaining the innovative soliton-wave solutions are presented in this paper, and their reliability is examined by using a well-established numerical method. The accuracy of pulse wave analysis in an optical cable is demonstrated through a series of graphical representations. Our study introduces scientific novelty, as evidenced by the comparative analysis of our data with those of previous research papers. This research contributes to enhancing the understanding of the kinetics and physical behavior of pulses in optical fibers, which holds implications for the advancement of optical communication technologies. [ABSTRACT FROM AUTHOR]

In this paper, we consider self-similar solutions of the r -mean curvature flow into the (n + 1) -dimensional Euclidean space. By employing some general maximum principles as the main tool, we characterize some self-similar solutions of the r -mean curvature flow under some suitable geometric constraints. [ABSTRACT FROM AUTHOR]

This paper deals with the host–parasitoid model, where the logistic equation governs the host population growth, and a proportion of the host population can find refuge. The equilibrium points' existence, number, and local character are discussed. Taking the parameter regulating the parasitoid's growth as a bifurcation parameter, we prove that Neimark–Sacker and period-doubling bifurcations occur. Despite the complex behavior, it can be proved that the system is permanent, ensuring the long-term survival of both populations. Furthermore, it was observed that the presence of the proportional refuge does not significantly influence the system's behavior compared to the system without a proportional refuge. [ABSTRACT FROM AUTHOR]

This work investigates a prey–predator model featuring a Holling-type II functional response, in which the fear effect of predation on the prey species, as well as prey refuge, are considered. Specifically, the model assumes that the growth rate of the prey population decreases as a result of the fear of predators. Moreover, the detection of the predator by the prey species is subject to a delay known as the fear response delay, which is incorporated into the model. The paper establishes the preliminary conditions for the solution of the delayed model, including positivity, boundedness and permanence. The paper discusses the existence and stability of equilibrium points in the model. In particular, the paper considers the discrete delay as a bifurcation parameter, demonstrating that the system undergoes Hopf bifurcation at a critical value of the delay parameter. The direction and stability of periodic solutions are determined using central manifold and normal form theory. Additionally, the global stability of the model is established at axial and positive equilibrium points. An extensive numerical simulation is presented to validate the analytical findings, including the continuation of the equilibrium branch for positive equilibrium points. [ABSTRACT FROM AUTHOR]

The influence of conjugate heat transfer based on radiation and magnetohydrodynamic utilization is an attractive research area, with progressive features; it has many applications in thermal engineering, heat exchangers, cooling phenomenon, magnetic cell separation, energy production, hyperthermia, etc. Following the motivating significances of the current research topic, this paper explores the influences of an electrically conducting and radiating fluid with internal friction, heat generation and thermal radiation embedded in a porous medium past a flat permeable plate. The boundary layer equations are dimensionally transformed and solved numerically using implicit finite difference technique called the Keller-box method. The effect of various fluid obeying parameters such as magnetic field, viscous dissipation and heat generation on the flow factors such as velocity and temperature are graphed and discussed in this paper. Growing heat source, energy inside the fluid boosts, thereby increasing the energy of the flow. Increase in generation of energy reduces the viscosity of the flow reduces thereby increasing the velocity of the flow particles. [ABSTRACT FROM AUTHOR]

In this paper, the influence of velocity slip and the Newtonian heating parameters on Williamson Nanofluid across a variable stretching sheet is studied. The basic fluid flow equations are turned into a system of coupled ordinary differential equations with appropriate conditions, which are solved numerically with the Keller-box approach. The outcomes show that, increasing Williamson parameter, due to the viscosity velocity of the fluid slowdown. As a result, it is noticed that the velocity slip parameter reduces Williamson Nanofluid velocity, while increasing shear stress, according to the results. Furthermore, it has been discovered that unlike velocity profiles, the slip influence is more pronounced on temperature and concentration profiles. Furthermore, the Newtonian heating parameter may be shown to have rising functions for velocity and dimensionless temperature. Newtonian heating has uses in the petroleum industry, heat exchangers, conjugate heat transfer around fins and solar radiation. It is discovered that the Joule heating parameter improves the thermal boundary layer thickness and slows down the velocity of the fluid, which aids in maintaining system temperature. Additionally, it has been found that the temperature profile exhibits a stronger slip effect compared with the velocity profile. To prepare toffee, chocolate and other delicacies as efficiently as possible, it is crucial to investigate the flow of Williamson fluids (such as drilling muds, clay coatings, various suspensions and some lubricating oils, thermoplastic melts, and a variety of colloids) in the incidence of heat transfer. The novelty of this paper is the effect of joule heating, Newtonian heating parameter and velocity slip on Williamson fluid velocity and temperature gradient. Furthermore, the heat and mass transfer rates are calculated for various parameters numerically and shown in tabular form. [ABSTRACT FROM AUTHOR]

The bioconvective flows are truly connected to real-life and engineering development. So, the models of biomicrosystems and biocells are considered for the technical analysis in this paper. Our intention for the current analysis was to theoretically examine electrical conduction flow into mass and heat transfer by an extensive gyrotactic microorganism into an inclined magnetic field toward a vertical stretching sheet with nonlinear solar radiation with different solar thermal appliances. The effect on velocity slip and Joule heating was again studied in detail. This classical problem on Navier Stokes equations to the current imitation was decreased to ordinary differential equations by applying the comparison method. The numerical solutions were changed by boundary value problem (BVP) to clarify the subject into finite difference numerical scheme by applying MATLAB. The important results show that the density of motile microorganisms reduces to the bioconvection Lewis number and Peclet number, although reverse performance was noticed for the bioconvection Rayleigh number. Further, solar radiation fosters heat transport. In this paper, complete analysis is provided for potential functions of solar thermoelectric cells, solar ponds, solar thermal power fabrication, etc. [ABSTRACT FROM AUTHOR]

As greenhouse production is considered the most water-conservative solution in the agricultural sector, greenhouse technology has become an integral approach for modern crop production methods. Different types of greenhouse structures are used to produce crops, and each type has advantages for a particular application, having been designed to meet multiple and specific requirements. This paper introduces a quality function deployment (QFD) framework to select two optimal greenhouse types (single-span and multi-span). This study aims to demonstrate greenhouse management and practices and review the development efforts during the last two decades. A market survey, focus group discussion, and personal interviews revealed nine key performance indicators (KPIs) (cost, wind loads, crop loads, roof slope, light transmission, flexibility, maintainability, rapid spread/ease of control, and heating and ventilation). Then, the participating decision-makers identified nine functional requirements, which, if fulfilled, would boost client satisfaction. The framework designed in this paper was developed to select and analytically investigate the optimal system for greenhouse microclimate control based on the retrieved KPIs and functional requirements for client satisfaction. This QFD framework can assist decision-makers, in the preliminary phase, in selecting optimal systems for greenhouse microclimate control based on their individualized situations. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive exploration of physics-informed neural networks and their core features. It delves into their role in tackling inverse problems inherent in ordinary differential equation-based models. Within this context, we introduce a two-group epidemiological model, elucidating its fundamental attributes. The central objective of this research is to accurately estimate the model parameters for both groups in the epidemiological model. We offer a detailed exposition of the adopted methodology, providing insights into the algorithm and the techniques employed for its implementation. Through this analysis, we illuminate the complexities of our study, contributing to the growing body of knowledge in this field, which intersects epidemiology and neural network-based parameter estimation for an enriched understanding of infectious disease dynamics. [ABSTRACT FROM AUTHOR]

This research paper develops an algorithm to solve a neutrosophic linear fractional optimization problem, where the cost of the objective functions, the technology coefficients, and the resources are neutrosophic numbers (triangular and trapezoidal numbers). Two defuzzification methods are used here to convert the neutrosophic linear fractional optimization problem into a multi-objective linear fractional optimization problem (MOLFOP). The fractional objective function is defuzzified using the component-wise optimization method, and the linear constraints are defuzzified using the aggregation ranking function strategy. Hence, the MOLFOP is then solved using the fuzzy goal programming method. In order to further explain our suggested algorithm, two numerical examples are solved at the end, and the outcomes obtained by our method are compared with the outcomes obtained using the other algorithm. [ABSTRACT FROM AUTHOR]

This research paper aims to study the impact of COVID-19 on the economy, where we have extended the standard epidemiological model, the Susceptible–Infected–Recovered (SIR) model. In the economy's dynamics, we have incorporated aggregate demand and aggregate supply and further set up a system of three-dimensional nonlinear differential equations, which is more likely the Labor–Infected–Quarantine (LIQ) model, an extension of the SIR model. Here, we have derived the steady-state condition and analyzed the model's stability. In addition, we have done a comparative static analysis of parameters with some policy implications. We aim to achieve the twin objective, i.e., controlling the pandemic and reviving the economy under the set of the policy mix. [ABSTRACT FROM AUTHOR]

For the charged-particle dynamics under a strong and constant magnetic field, we consider and analyze exponential integrators in this paper. We derive two kinds of exponential integrators and study their long-time behavior by using the technique of modulated Fourier expansions. It is shown that a symmetric two-stage exponential integrator and some one-stage symplectic exponential integrators approximately conserve the energy and magnetic moment of the charged-particle dynamics over long times. [ABSTRACT FROM AUTHOR]

The new regulation was introduced to the franchise market of South Korea in that an applicant who wants to be a franchiser must set up direct retail stores and run them for at least one year before recruiting franchisees. Considering the purpose of the regulation, it is inferred that once franchisers run their own stores, their franchisees would be better off than otherwise. This paper addresses one reason that the Korea Fair Trade Commission has no choice but to introduce the regulation. Along the line, this paper investigates whether franchisees would have a more likelihood to make profit in case of franchisers operating their own stores. The result demonstrates that this case could be true since the operation of franchiser-owned stores could be helpful in reducing the cost of franchisees. [ABSTRACT FROM AUTHOR]