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Tail suspension test (TST) and forced swimming test (FST) are widely used in basic research and pharmaceutical screening of potential antidepressant treatments in rodents. In both tests, the measurement of immobility behavior is the main parameter to assess the rats' depressive-like behavior. [Extracted from the article]

Expansive soils often pose as a potential geo-hazard for structures built on them due to the volumetric changes associated with moisture variation. Soil water characteristic curve (SWCC) is a direct representation of the pore and grain distribution of clays while the variation of in situ soil matric suction governs the hydration processes. In the present research, five natural expansive clays were studied at their 95% of maximum dry unit weight. Swell behavioral evaluations are conducted using standard test procedures. Both desorption and adsorption SWCC's were determined using pressure cell apparatus and filter paper method. Adsorption paths are utilized for analysis study as swelling behavior is the main scope of the research. A novel path traversed by the soil specimen on the void ratio-moisture content-log (soil suction) plot, and the corresponding slope, namely the modified specific moisture capacity, 'α', is identified as the main influential parameter. This modified specific moisture capacity exhibited direct relationship to swelling strains and swelling pressure of all five natural clays. A simple model for predicting one dimensional swell strain and swell pressure was established based on reliable predictions obtained using the modified specific moisture capacity of clays. [ABSTRACT FROM AUTHOR]

Purpose: Emotions and emotional contagion are being increasingly recognized as crucial variables influencing individual behavior and organizational functioning. This position paper serves the function as a ready reckoner by reviewing and consolidating existing literature in the field of emotional contagion. The review is categorized into three broad headings: (a) individual, (b) interpersonal, and (c) contextual factors, based on their relationship with emotional contagion. Design/Methodology/Approach: The article focuses on analyzing and critiquing studies of emotional contagion conducted in several streams such as psychological processes, personality, organizational behavior, marketing, and consumer behavior. A conceptual framework of emotional contagion is presented, supplemented with research propositions. Findings: The phenomenon of emotional contagion in workplace and its effects on personal and group outcomes has emerged as a critical area of research. It has been firmly established in literature that spread of emotions, if not properly managed, is bound to influence work effectiveness. Implications: Importance of understanding the effects of transfer of emotions, for both academicians and practicing managers is one of the critical take-aways of this article. Suitable interventions are the need of the hour in order to ensure proper management of emotions. Originality/Value: The contribution of the article is expected to be fourfold, in terms of: (a) presenting a structured and comprehensive review of literature on emotional contagion, (b) identifying gaps in the existing literature, (c) proposing a conceptual framework, and (d) developing propositions for future research. [ABSTRACT FROM AUTHOR]

Significant research has been carried out in the field of User Behavior Analysis, focused on understanding, modeling and predicting past, present and future behaviors of users. However, the heterogeneity of the approaches makes their comprehension very complicated. Thus, domain and Machine Learning experts have to work together to achieve their objectives. The main motivation for this work is to obtain an understanding of this field by providing a categorization of state-of-the-art works grouping them based on specific features. This paper presents a comprehensive survey of the existing literature in the areas of Cybersecurity, Networks, Safety and Health, and Service Delivery Improvement. The survey is organized based on four different topic-based features which categorize existing works: keywords, application domain, Machine Learning algorithm, and data type. This paper aims to thoroughly analyze the existing references, to promote the dissemination of state-of-the-art approaches discussing their strong and weak points, and to identify open challenges and prospective future research directions. In addition, 127 discussed papers have been scored and ranked according to relevance-based features: paper reputation, maximum author reputation, novelty, innovation and data quality. Both types of features, topic-based and relevance-based have been combined to build a similarity metric enabling a rich visualization of all considered publications. The obtained graphic representation provides a guide of recent advancements in User Behavior Analysis by topic, highlighting the most relevant ones. [ABSTRACT FROM AUTHOR]

The Repetitive Behaviours Questionnaire for Adults (RBQ-2A) measures two factors of restricted and repetitive behaviours (RRBs) associated with autism. However, the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) provides four criteria for RRBs: repetitive motor behaviours, insistence on sameness, restricted interests, and interest in sensory aspects of the environment (or atypical sensitivity). The current paper aimed to examine whether the RBQ-2A is a psychometrically sound measure of these four factors. Study 1 had university students (N = 368) complete the RBQ-2A and other related measures online and revealed that the RBQ-2A can assess the factors highlighted in the DSM-5 and that these four factors comprise a general RRB construct. Study 2 had individuals disclosing a diagnosis of autism (N = 283) complete the RBQ-2A and other related measures online and supported that this four-factor structure provided good psychometric properties. While the current paper provides findings for an online autistic population, further research is needed to generalize these findings to autistic individuals less likely to partake in online studies (e.g., those with intellectual or language disabilities). Overall, the results suggest that the RBQ-2A reliably and validly assesses RRBs. [ABSTRACT FROM AUTHOR]

The article discusses the 95th Transportation Research Board (TRB) Annual Meeting that was held in Washington D.C. on January 10-14, 2016, focusing on the model travel demand, initially with trip-based and tour-based models in the early 70s and 80s. Topics include the use of social media data to characterize the individual activities, the different individual behavioural attitudes in the formulation of activity-based models, and the dynamic network assignment and equilibrium models.

A significant proportion of malaria infections in humans exhibit no symptoms, but it is a reservoir for maintaining malaria transmission. A time periodic reaction-diffusion model for malaria spread is introduced in this paper, incorporating spatial heterogeneity, incubation periods, symptomatic and asymptomatic carriers. This paper introduces the concept of the basic reproduction number R 0 , which is defined as the spectral radius of the next generation operator, and we present some preliminary results by elementary analysis. The threshold dynamic behavior analysis shows that when R 0 < 1 , the disease is extinct, and when R 0 > 1 , the disease is persistent. We investigate the case of constant system parameters, focusing on the global asymptotic stability of the disease-free steady state when R 0 = 1 . In the numerical simulation section, we validate the theoretical results obtained, and then use elasticity analysis methods to explore the influence of parameters on the output solution. In addition, sensitivity analysis of the basic reproduction number under homogeneous conditions indicates direction of controlling malaria transmission. And several control measures are evaluated in the following steps. [ABSTRACT FROM AUTHOR]

This special issue aims to bring together the latest advancements in human-centric intelligent multimedia understanding, diving deeper into human-centered behavior understanding tasks. However, there are still various open questions in improving the robustness, explainability, and accuracy of human-centric multimedia understanding approaches, while large-scale benchmark datasets and effective methods on these tasks are yet to be explored. From another perspective, human behavior understanding from multimedia contents is a fundamental driving force for related artificial intelligence applications such as smart city, medical image understanding, and human behavior analysis. [Extracted from the article]

The recent series of papers between Sampaio and Haydu (Behavior and Social Issues 32(1):115–133, 2023a; Behavior and Social Issues 32(1):141–146, 2023b) and Ardila-Sánchez and Hayes (Behavior and Social Issues 32(1):134–140, 2023) on the cultural milieu construct is of critical import for culturo-behavior science. By constructing a revised version of Houmanfar and colleagues' (Ardila-Sánchez et al., Behavior and Social Issues 28(1):298–315, 2019: Houmanfar, Ardila-Sánchez, & Alavosius, Behavior science perspectives on culture and community, pp. 151–170, Springer, 2020: Houmanfar & Rodrigues, Behavior and Social Issues, 15(1):13–30, 2006: Houmanfar, Rodrigues, & Ward, Behavior and Social Issues 19(1):78–103, 2010) elaborated metacontingency model, Sampaio and Haydu address confusion inherent in the concept of the cultural milieu by separating it into two different components—cultural antecedents and selecting environment variables—with different functional properties. This allows the cultural milieu to be conceptualized more coherently within a behavior-analytic framework, a framework into which the cultural milieu does not quite fit when described in interbehavioral terms. However, given differences in integrated field and contingency logic, an interbehaviorally conceptualized cultural milieu does not belong in any metacontingency model, elaborated or otherwise. The purpose of this paper is to address this issue—the elephant in the field—and confusing aspects of the cultural milieu that Sampaio and Haydu do not address when one considers the elaborated metacontingency model from an interbehavioral perspective. In doing so, I discuss issues with the model warranting attention and the prospect of a unified culturo-behavior science. [ABSTRACT FROM AUTHOR]

Due to the digitization of data and the dynamic requirements of the users, cloud computing is one of the most used technologies in the present scenario. Cloud computing provides a platform to store, process, and share data remotely for heterogeneous users and provides services according to the requests generated by those users. However, its rapid growth has led to one of the major challenges in the environment; the security and privacy of the data. To address the security and privacy concerns, in this paper, our major contribution is a trusted computing framework namely Secure Framework using Behavior and Role Analysis (SFBRA) for cloud data security. The framework utilizes user log monitoring data, pattern recognition algorithms, and role-based access mechanisms to detect malicious and suspicious activities of different users. Our proposed framework provides two levels of security for cloud users. In Level-1, we calculate the trust value of the logged-in users by analyzing the existing log table and pattern of request access. In Level-2, we calculate the trust of the request (storage, processing, sharing) data packet using behavior analysis of the user and a role-based access mechanism and finally detect the malicious activities. The efficacy of our proposed framework is demonstrated through experimentation, where we compare our framework with existing research works. The results show 95% accuracy in potential attack detection and prevention,approximately 8 Mbps throughput, and 0.003% packet drop on average. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing the lack of Braille-embossed labels in Chinese pharmaceutical product packaging. To this end, this study constructs an evolutionary game model of multi-participant behaviour in drug production regulation and conducts simulation based on the perspective of stakeholders in order to study the evolutionary steady state of regulatory authorities, pharmaceutical companies, and visually impaired individuals and the influence of each parameter variable on the choice of strategic behaviour of the participants. The simulation results show that in the legal framework of China, administrative penalties, the production subsidy rate, and the Basic Medical Insurance (BMI) reimbursement rate are the main drivers of the system's evolution towards a steady state. Reduced costs of drugs with Braille-embossed packaging is a prerequisite for the visually impaired to purchase such drugs, and the key for the whole system to converge to a stable state therefore lies in the BMI reimbursement rate for drugs with Braille-embossed packaging. This paper suggests that the Chinese government should improve the law enforcement mechanism for the regulation of the production of drugs with Braille-embossed packaging; increase the type and intensity of administrative penalties as well as production subsidies, tax incentives, and compliance incentives for pharmaceutical companies; and provide higher BMI reimbursement rates for the visually impaired. The results of the study provide valuable insights to improve accessibility to drugs and build a barrier-free environment for ensuring medication safety in China and other developing countries. [ABSTRACT FROM AUTHOR]

The world is witnessing the fast replacement of fossil-fuelled vehicles by environment-friendly electric vehicles (EVs). This unprecedented growth of EVs is expected to burden the material resource consumption of batteries constituting metals from the earth. However, circular economy in the electric vehicle battery (EVB) ecosystem can provide a sustainable solution to resource management. This has triggered the need to understand and analyse the EVB ecosystem players. Long-term analyses of behaviours of the different variables under dynamic and complex systems are best carried out by the application of system dynamics (SD)—a continuous simulation methodology. This research paper has contributed in developing an interactive SD-based model for the circular production and consumption flow of EVBs to analyse the behavioural dynamics of the different variables involved. Five scenarios have been simulated for the analyses. The behaviour trends of the variables obtained from the SD-based simulation model have provided useful insights and five recommendations for resource sustainability. The recommendations are: the necessity for adopting Industry-4.0 in EVB manufacturing, awareness creation of circular thinking amongst all stakeholders, enhanced end-of-life (EOL) period of EVB, compelling need for high EVB recollection efficiency after EOL, and improvement in the reprocessing technology of EOL batteries. [ABSTRACT FROM AUTHOR]

Bonica's (Am J Polit Sci 58(2):367–386, 2014) campaign finance-based ideology scores, or CFscores, create an ideological common space that allows researchers to compare a wide variety of actors. Because relatively few citizens donate to candidates, however, the public is not well represented in this common space. This paper addresses that gap. It uses random forest machine learning on data from the 2012 Cooperative Congressional Election Study to impute CFscores for respondents who did not donate to candidates, based on how their policy views compared to those who did. These new scores are robust to differences in issue importance between donors and non-donors, and they outperform other ideological measures in predicting vote choice. The scores are then applied to a substantive exercise. Past research shows that extreme candidates for governor are penalized more by voters than those in lower-profile races. The implied mechanism—that vote choice for governor is more ideologically-driven—can be directly tested with imputed CFscores, since they uniquely allow comparisons between voters and candidates across races. An analysis of voting behavior in 2012 confounds expectations. Ideology appears to factor no more into vote choice for governor than for US House. These novel findings underscore the value of extending CFscores to non-donating survey respondents, and while current efforts are limited by data availability, this study offers encouragement and a roadmap to that end. [ABSTRACT FROM AUTHOR]

Hygroscopic properties of wood have been utilized in adaptive façades to respond to variation in humidity levels. Shape-shifting materials have been developed to replace mechanical actuators that respond to climatic variation with zero-energy consumption. This paper presents a systematic review of the literature on the use of hygromorphic behaviour in developing adaptive architectural façades, with the primary focus of identifying the venues of implementation of hygroscopic actuation in adaptive facades. The paper triangulates the intersection between hygroscopic design parameters with manufacturing strategies and their application as a passive motion mechanism in adaptive facades. This review focuses on state-of-the-art experimental work in hygroscopic design, with specific interest in manufacturing methods of hygromorphic adaptive façades, response motion behaviour evaluation and tracking, analysis of the current applications of hygromorphic design in real weather conditions, and performance prediction. Results reveal that most of the studied papers focus on the response behaviour of programmable materials to variation in moisture content and the implementation of hygroscopic design in adaptive façades. From the literature analysis, it was shown that programming the response behaviour of hygroscopic materials mainly takes place through variation in fabrication methods, followed by passive layer configurations, which act as actuators that are controlled by differences in layer properties. [ABSTRACT FROM AUTHOR]

This paper presents an approach to analyzing consumers' e-commerce site usage and browsing motifs through pattern mining and surfing behavior. User-generated clickstream is first stored in a client site browser. We build an ingestion pipeline to capture the high-velocity data stream from a client-side browser through Apache Storm, Kafka, and Cassandra. Given the consumer's usage pattern, we uncover the user's browsing intent through n-grams and Collocation methods. An innovative clustering technique is constructed through the Expectation-Maximization algorithm with Gaussian Mixture Model. We discuss a framework for predicting a user's clicks based on the past click sequences through higher order Markov Chains. We developed our model on top of a big data Lambda Architecture which combines high throughput Hadoop batch setup with low latency real-time framework over a large distributed cluster. Based on this approach, we developed an experimental setup for an optimized Storm topology and enhanced Cassandra database latency to achieve real-time responses. The theoretical claims are corroborated with several evaluations in Microsoft Azure HDInsight Apache Storm deployment and in the Datastax distribution of Cassandra. The paper demonstrates that the proposed techniques help user experience optimization, building recently viewed products list, market-driven analyses, and allocation of website resources. [ABSTRACT FROM AUTHOR]

This paper summarizes the results of a series of experimental studies on the emotional responses of American and French viewers to televised excerpts of their leaders' facial displays. Using a combination of ethological and social-psychological theory it develops an explanation of such emotional responses. [ABSTRACT FROM AUTHOR]

The lot-sizing and cutting-stock problems arise, in general, in manufacturing industries as subsequent processes. Many authors have addressed these problems separately; however, some studies have considered integrated approaches to these problems in recent practical applications. This paper aims to introduce a new model for integrated lot-sizing, one-dimensional cutting-stock and two-dimensional cutting-stock problems. This integrated model can be used to address the papermaking process as a three-phase subsequent process, which starts from the production of jumbos and ends with the paper sheets used in daily life. The first phase of the process is modeled according to a lot-sizing problem, where the quantities of jumbos are determined to meet the demand of the entire planning horizon. The second phase is modeled as a one-dimensional cutting-stock problem, where the jumbos are cut into smaller reels. The reels are used as raw material for the third phase of the process, where they are cut again into sheets employing a two-dimensional cutting-stock problem. A heuristic algorithm that uses the column generation and relax-and-fix techniques is applied to evaluate the proposed model from a series of experiments. Gains of up 16.5% were observed compared to the solution obtained with no integration among the production phases. Additional analyses of the model behavior under multiple scenarios resulted in significant findings, as the increasing costs' reduction as more product types are considered and the use of more efficient cutting patterns resulting in reduced material waste. [ABSTRACT FROM AUTHOR]

A flexible drilling tool is a special drilling tool for ultrashort-radius radial horizontal wells. This tool is composed of many parts and has the characteristics of a multibody system. In this paper, a numerical method for the dynamic analysis of flexible drilling tools is proposed. The flexible drill tool is discretized into spatial beam elements, while the multilayer contact of the flexible drilling tool is represented by the multilayer dynamic gap element, and the dynamic model of the multibody system for the flexible drilling tool's multilayer contact is established, considering the interaction force between the drill bit and the rock. The nonlinear dynamic equation is solved using the Newmark method and Newton–Raphson method. An analysis of the dynamic behavior of a flexible drilling tool is conducted. The results indicate that the flexible drilling tool experiences vortex formation due to the interaction between the flexible drilling pipe and the guide pipe, leading to increased friction and wear. This situation hinders safe drilling operations with flexible drilling tools. The collision force of the flexible drilling tool near the bottom of the hole is more severe than that of the other tool types, which may lead to failure of the connection. [ABSTRACT FROM AUTHOR]

Since the emergence of big data, the popularity of deep learning models has increased and they are being implemented in a wide range of applications, including people detection and counting in congested environments. Detecting and counting people for human behavior analysis in retail stores is a challenging research problem due to the congested and crowded environment. This paper proposes a deep learning approach for detecting and counting people in the presence of occlusions and illuminance variation in a crowded retail environment, utilizing deep CNNs (DCNNs) for semantic segmentation of top-view depth visual data. Semantic segmentation has been implemented using (DCNNs) in recent years since it is a powerful approach. The objective of this paper is to design a novel architecture that consists of an encoder–decoder architecture. We were motivated to use transfer learning to solve the problem of insufficient training data. We used ResNet50 for the encoder, and we built the decoder part as a novel contribution. Our model was trained and evaluated on the TVHeads dataset and the people counting dataset (PCDS) that are available for research purposes. It consists of depth data of people captured from a top-view RGB-D sensor. The segmentation results indicate high accuracy and demonstrate that the proposed model is robust and accurate. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an R package that performs automated photo editing effects. Specifically, it is an R implementation of an image-processing algorithm proposed by Boyadzhiev et al. (2015). The software allows the user to manipulate the appearance of objects in photographs, such as emphasizing facial blemishes and wrinkles, smoothing the skin, or enhancing the gloss of fruit. It provides a reproducible method to quantitatively control specific surface properties of objects (e.g., gloss and roughness), which is useful for researchers interested in topics related to material perception, from basic mechanisms of perception to the aesthetic evaluation of faces and objects. We describe the functionality, usage, and algorithm of the method, report on the findings of a behavioral evaluation experiment, and discuss its usefulness and limitations for psychological research. The package can be installed via CRAN, and documentation and source code are available at https://github.com/tsuda16k/materialmodifier. [ABSTRACT FROM AUTHOR]

In this study, geomechanical behavior of fractures and faults in rocks as a saturated deformable discrete fracture-porous medium has been evaluated using coupled fluid flow-geomechanics numerical modeling. The purpose of this paper is to observe and evaluate the effects of fractures and faults on the pore pressures during fluid flow through reservoirs. This issue involves solving the equations that have been derived from the Biot consolidation theory such as fluid mass balance equation, Darcy law and momentum balance equations. Govern coupled equations were solved using the standard Galerkin finite element method for continuous porous medium. Elements called "zero-thickness elements" were also used to discretize the fault as a discontinuous part of the porous medium. In compared with the previous and similar methods, the method introduced in this paper, made modifications in either the choice of the element and the method of solving the governing equations. The main advantage of this paper is providing clear precise formulations of the double node zero-thickness element in hydro-mechanical modeling of fractures and faults. Verification of the proposed process and models presented in this paper were done by providing three index problems which their analytical and numerical solutions are available. The results of our model provide a good agreement to these reference solutions which indicates the accuracy of the method presented in this paper. [ABSTRACT FROM AUTHOR]

Any organism in nature will inevitably be affected by uncertain factors. The deterministic model and stochastic model are no longer suitable for population dynamics analysis under uncertain noise environment. In order to simulate these problems more reasonably, we propose an uncertain logistic population model with Allee effect, which describes the population dynamic behavior through uncertain differential equation. In this paper, the solution and α -path of the uncertain Logistic population model with Allee effect are given, and the behavior analysis of the solution is also discussed. Besides, some numerical examples are put forward to illustrate the conclusions obtained in the paper. [ABSTRACT FROM AUTHOR]

Technological and industrial developments have impacted every aspect of human life, making it convenient, resourceful, advanced, and fast paced. However, this advancement along with population growth is also translating negatively to humongous levels of waste generation globally. "Throw away culture" has further worsened the situation. Every year, billions of tonne solid waste is created, most of which is poorly managed, dumped, or burned, harming the environment, climate, and natural resources and disrupting the ecological balance. The generation of waste cannot be stopped, but it can surely be recycled or reused judicially in order to mitigate the harmful effects. In recent years, many researchers have investigated the feasibility of waste utilization in varied sectors. The building industry is one sector where many sorts of waste materials can be used in large quantities. This paper critically reviews the current state of research and knowledge in utilizing waste materials for manufacturing of bricks. Detailed review on variety of wastes (fly ash, plastic waste, construction and demolition waste, agricultural waste, glass, ceramic, and rubber and paper and pulp industry waste) used in bricks and their impact on the strength behaviour, water absorption, porosity, thermal conductivity, etc. has been presented. The highlight of our observations is that the firing and cementing methods for producing bricks from waste materials still have the same drawbacks as traditional brick production methods in terms of high energy utilization. Analysis shows superior strength properties of bricks containing fly ash, plastic waste, and construction and demolition waste over other types of wastes. Comparison of the properties of non-fired bricks using different wastes shows that the bricks prepared by geo-polymerization of fly ash exhibit higher energy efficiency and sustainability. [ABSTRACT FROM AUTHOR]

Customer behaviour analysis in a telecom market is a challenging task in the customer relationship management area. In this paper, we propose a customer behaviour recognition model that combines unsupervised classification and supervised classification methods. First, considering the complexity and uncertainty of consumption behaviour, a hybrid model of K-means clustering, the entropy method and customer portrait analysis is applied to segment customers. Second, the segmentation results are subsequently incorporated into the proposed multi-head self-attention-based nested long short-term memory classifier to evaluate the performance of customer behaviour recognition. Third, the proposed framework is applied to a real case obtained from the China telecom market. The results indicate that our model is significantly superior to other traditional customer behaviour classification models. In addition, medium-value customers will make full use of the mobile traffic packet, and the package utilization rate of high-value groups is lower, which may benefit the precision marketing of telecom companies. [ABSTRACT FROM AUTHOR]

Efficient interest prediction for social networks is critical for both users and service providers for behavior analysis and a series of extension services. However, most existing approaches are inefficient, incomplete or isolated. In this paper, we propose combination of Gaussian and Markov approaches (namely, GAM) as typical soft computing technology for interest prediction of social intelligent multimedia systems. GAM model considers "the number of posted messages" as the only parameter, and defines selection logic to implement either Gaussian or Markov based approaches. Our proposed solution takes the advantage of Gaussian model in prediction accuracy and computation complexity, and advantage of Markov model in high availability. Further experiments illustrate that our solution achieves higher prediction accuracy of 94.3% (without considering the influence of swing users), with the best result achieved ever. [ABSTRACT FROM AUTHOR]

To improve the scientificity and reliability of medical behavior analysis, this paper combines machine learning and wireless sensor technology to construct an intelligent data mining system that can be used for medical behavior analysis and uses association rules to analyze and mine the implicit relationships between structural monitoring parameters. Moreover, this paper establishes strong association rules between different monitoring variables based on historical monitoring data under normal structural conditions to predict whether the structural conditions are normal. In addition, this paper constructs a system function module according to actual needs, obtains the overall system architecture, and implements the system function module in combination with algorithms. Finally, this paper designs experiments to verify the performance of the system constructed in this paper and discusses the experimental results through mathematical graph analysis methods. From the research point of view, it can be observed that the system constructed in this paper has a specific effect. [ABSTRACT FROM AUTHOR]

In this paper, effect of surface, including its elasticity, residual stress and density is investigated on the nano-beam stiffness and mass analytically. To this aim, the governing equation of the nano-beam dynamic behavior is extracted utilizing Gurtin–Murdoch's theory and Euler–Bernoulli hypothesis which incorporates the surface effects. Effect of surface parameters on nano-beam lumped mass and stiffness is investigated parametrically and necessary conditions for hardening and softening behavior are presented based on the surface stress and elasticity for both clamped–clamped and clamped-free nano-beams. The performed analysis revealed that surface may have different effects on similar nano-beams with only different boundary conditions. The obtained results in this paper can be utilized in analysis and design of nano-systems. [ABSTRACT FROM AUTHOR]

Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors and activities. Machine Learning (ML)-based behavior analysis within the IDS has considerable potential for detecting dynamic cyber threats, identifying abnormalities, and identifying malicious conduct within the network. However, as the number of data grows, dimension reduction becomes an increasingly difficult task when training ML models. Addressing this, our paper introduces a novel ML-based network intrusion detection model that uses Random Oversampling (RO) to address data imbalance and Stacking Feature Embedding based on clustering results, as well as Principal Component Analysis (PCA) for dimension reduction and is specifically designed for large and imbalanced datasets. This model's performance is carefully evaluated using three cutting-edge benchmark datasets: UNSW-NB15, CIC-IDS-2017, and CIC-IDS-2018. On the UNSW-NB15 dataset, our trials show that the RF and ET models achieve accuracy rates of 99.59% and 99.95%, respectively. Furthermore, using the CIC-IDS2017 dataset, DT, RF, and ET models reach 99.99% accuracy, while DT and RF models obtain 99.94% accuracy on CIC-IDS2018. These performance results continuously outperform the state-of-art, indicating significant progress in the field of network intrusion detection. This achievement demonstrates the efficacy of the suggested methodology, which can be used practically to accurately monitor and identify network traffic intrusions, thereby blocking possible threats. [ABSTRACT FROM AUTHOR]

Purpose: The paper's aim is to use the dynamic theory of multi-rigid body systems to establish a dynamic model of the ammunition belt for the gas-operated machine gun. Then, an experimental study is also carried out on the PKMS Kalashnikov 7.62 mm machine gun to verify the reliability of the proposed model. Method: A multi-body mechanical model for dynamic analysis of the ammunition belt is proposed to serve as a foundation for the theoretical calculation problem. In addition, a set of experimental procedures for the PKMS Kalashnikov 7.62 mm machine gun is carried out dynamic analysis problem. Results: The calculation results are compared with the experimental results, including the motion, displacement, and velocity of the ammunition belt and the interaction force between two link joints to confirm the suitability of the proposed model. From here, it can be asserted that our model is an effective one and should be encouraged in research into the dynamics of the automatic machine and the design of the gas-operated machine gun. [ABSTRACT FROM AUTHOR]

This paper presents a system integration of a sense-based user interface (SUI) platform, comprised of flexible pressure and humidity sensor arrays with a commercial inertial measurement unit (IMU), to analyze behavioral patterns of young children. The pressure sensors utilize a sensor array created using flexible inkjet printing, with each sensor using a piezoresistive sensing layer. The humidity sensors employ an interdigitated capacitive sensor based on a polyimide humidity-sensitive layer and are also manufactured using the flexible inkjet printing technique. To achieve a wide measurement area, both the pressure and humidity sensors are expanded into 5 × 5 and 5 × 10 sensor arrays, respectively. Also, commercial IMU, including accelerometer/gyroscope sensors, is employed. Finally, the SUI platform is in the form of a cuboidal block model, with an IMU and circuits embedded within the block. Multilayered pressure and humidity sensor arrays are installed on the external surface of the block. Collected data from each sensor are visualized through heatmaps and 3D motion representation to create a platform that integrates fine-grained behavior as well as global behavior information of young children. This research would provide a foundation for the development of SUI technology, especially aimed at individuals who have difficulty with conventional forms of input–output devices. [ABSTRACT FROM AUTHOR]

This paper reviews the impact dust accumulation for long-term on the performance of photovoltaic (PV) modules. It examines accumulation impact on the PV efficiency, their solar energy production, and their lifetime. The paper also discusses the various strategies for preventing dust accumulation, such as waterproof coatings, hydrophobic coatings, and anti-static coatings. Finally, the paper provides a comprehensive review in dust control and highlights potential future research directions. This review provides an in-depth analysis of PV behavior and its effect by dust accumulation and provides useful information for researchers and practitioners in the solar industry. [ABSTRACT FROM AUTHOR]

This paper presents a finite element method (FEM) analysis of the flexural behavior of the circumferential joints in a large-diameter tunnel. The bending rigidity of these joints is calculated and compared based on the linear or nonlinear material properties of the connecting bolts. The results indicate that the nonlinear material properties of the bolts play a major role in determining the flexural rigidity of the joints. This flexural rigidity is also dependent on the tilt angle and the strength grade of the connecting bolts. The results presented in this paper may serve as guide for the design of similar tunnels. [ABSTRACT FROM AUTHOR]

Open data sharing is critical for scientific progress. Yet, many authors refrain from sharing scientific data, even when they have promised to do so. Through a preregistered, randomized audit experiment (N = 1,634), we tested possible ethnic, gender and status-related bias in scientists' data-sharing willingness. 814 (54%) authors of papers where data were indicated to be 'available upon request' responded to our data requests, and 226 (14%) either shared or indicated willingness to share all or some data. While our preregistered hypotheses regarding bias in data-sharing willingness were not confirmed, we observed systematically lower response rates for data requests made by putatively Chinese treatments compared to putatively Anglo-Saxon treatments. Further analysis indicated a theoretically plausible heterogeneity in the causal effect of ethnicity on data-sharing. In interaction analyses, we found indications of lower responsiveness and data-sharing willingness towards male but not female data requestors with Chinese names. These disparities, which likely arise from stereotypic beliefs about male Chinese requestors' trustworthiness and deservingness, impede scientific progress by preventing the free circulation of knowledge. [ABSTRACT FROM AUTHOR]

Automated crowd behaviour analysis and monitoring is a challenging task due to the unpredictable nature of the crowd within a particular scene and across different scenes. The prior knowledge of the type of scene under consideration is a crucial mid-level information, which could be utilized to develop robust crowd behaviour analysis systems. In this paper, we propose an approach to automatically detect the type of a crowded scene based on the global motion patterns of the objects within the scene. Three different types of scenes whose global motion pattern characteristics vary from uniform to non-uniform are considered in this work, namely structured, semi-structured, and unstructured scenes, respectively. To capture the global motion pattern characteristics of an input crowd scene, we first extract the motion information in the form of trajectories using a key-point tracker and then compute the average angular orientation feature of each trajectory. This paper utilizes these angular features to introduce a novel feature vector, termed as Histogram of Angular Deviations (HAD), which depicts the distribution of the pair-wise angular deviation values for each trajectory vector. Since angular deviation information is resistant to changes in scene perspectives, we consider it as a key feature for distinguishing the scene types. To evaluate the effectiveness of the proposed HAD-based feature vector in classifying the crowded scenes, we build a crowd scene classification model by training the classical machine learning algorithms on the publicly available Collective Motion Database. The experimental results demonstrate the superior crowd classification performance of the proposed approach as compared to the existing methods. In addition to this, we propose a technique based on quantizing the angular deviation values to reduce the feature dimension and subsequently introduce a novel crowd scene structuredness index to quantify the structuredness of an input crowded scene based on its HAD. [ABSTRACT FROM AUTHOR]

Giant African snail has been considered as the most challenging and evolving pest all over the world. This Pest is recognized as one of the topmost 100 destructive species in the world. This Snail is an agricultural pest devours only vegetables, fruits and sometimes sand. It also disturbs the households. It has the capacity to transmit both human and plant pathogens. This snail feeds on the stem, leaves, and flower of the cauliflower. This paper gives the brief study of various behavior of Giant African snail in acoustic environment. The Signals of various behavior of snails are recorded and analyzed using a MATLAB 2019 software. The time domain specification and frequency domain specification of pest Snails are done. Eradication of snail from its habitat is the tedious process. The eradication of snail is quite simple when it is detected automatically. This paper also suggests the identification of snails automatically by its acoustic signals and uses Machine Learning algorithm for effective detection. Added to above, the addition of the 5% of AgNP nanoparticles eliminated the presence of Giant African snail in the agricultural fields. [ABSTRACT FROM AUTHOR]

The evaluation of groupware has a long history; several researchers have investigated this research area and made attempts to develop evaluation methods. This paper aims to make a contribution to this research topic by introducing a groupware evaluation method called Team Usability Testing. The goal of this method is to evaluate the usability of real-time distributed groupware. The Team Usability Test consists of a combination of questionnaires, on-screen behaviour recordings and interviews. The data analysis is based on the mechanics of collaboration theoretical framework and involves communication analysis, behaviour analysis, and analysis of post-experiment interviews. A laboratory experiment and a field study constitute the two main phases of the creation of the usability testing method. In this paper, the results of the laboratory experiment and its implications for the field study will be discussed. According to the results, the Team Usability Test is able to explore team-level usability problems and contextual problems. The paper ends with the discussion of future field research considerations related to the possible application of the Team Usability Test in real-life work settings. [ABSTRACT FROM AUTHOR]

The enormous amount of data generated by sensors and other data sources in modern grid management systems requires new infrastructures, such as IoT (Internet of Things) and Big Data architectures. This, in combination with Data Mining techniques, allows the management and processing of all these heterogeneous massive data in order to discover new insights that can help to reduce the energy consumption of the building. In this paper, we describe a developed methodology for an Internet of Things (IoT) system based on a robust big data architecture. This innovative approach, combined with the power of Spark algorithms, has been proven to uncover rules representing hidden connections and patterns in the data extracted from a building in Bucharest. These uncovered patterns were essential for improving the building's energy efficiency. [ABSTRACT FROM AUTHOR]

In this paper, I investigated whether the sustainability attitudes and behaviour of young people are similar to those of the older generation. Furthermore, I examined to which extent today's parents play a role as socialization agents in shaping the broader sustainability attitudes and behaviour of their children by investigating whether specific family characteristics are important to explain this association. The research questions were analysed by using data from a Belgian study conducted among Flemish pupils from 47 primary and secondary schools and one of their parents (n = 880). I found that children's attitudes towards sustainability are higher compared to those of the older generation (e.g. their parents) but that the older generation, on the contrary, act more sustainably. Furthermore, there were small but positive correlations within the family for sustainability attitudes and behaviour. Finally, the results showed that increased intrafamily discussions are associated with more sustainable attitudinal parent–child congruence. However, the results did not provide evidence in support of behavioural congruence. It was concluded that the transmission of sustainability attitudes and behaviour is not limited to the classic top-down approach where parents influence children's attitudes and behaviour and children are considered as passive recipients. [ABSTRACT FROM AUTHOR]

While integrative data analysis (IDA) presents great opportunity, it also necessitates a myriad of methodological decisions related to harmonizing disparate measures collected across multiple studies. There is a lack of step-by-step methodological guidance for harmonizing disparate measures of latent constructs differently conceptualized or operationalized across studies, such as social, emotional, and behavioral constructs often utilized in prevention science. The current paper addressed this gap by providing methodological guidance and a case illustration focused on harmonizing measures of disparately conceptualized and operationalized constructs. We do so by outlining a five-phased harmonization approach paired with an illustrative example of the approach as applied to harmonization of broadband latent emotional and behavioral health constructs assessed with different measures across studies. This approach builds on and expands upon procedures currently recommended in the IDA literature with parallels to best practices in test development procedures. The illustrative example of our phased approach is drawn from an IDA study of 11 randomized controlled trials of Coping Power (Lochman & Wells, 2004), an evidence-based preventive intervention. We demonstrate the harmonization of two constructs, internalizing and externalizing problems, as harmonized across the teacher-reported scales of the Achenbach System of Empirically Based Assessment (Achenbach, 1991a) and the Behavior Assessment System for Children (Reynolds & Kamphaus, 2004). Finally, we consider the potential strengths and limitations of this phased approach, underscoring areas for future methodological research and conclude with some recommendations. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, dynamic behavior of a rotor system with an elliptical breathing crack that simulates the real shape of the crack front is investigated. Methods: A finite element model of the cracked rotor system is developed. The crack breathing mechanism is modelled based on an improved breathing model which considers the inclination of the neutral axis of the cracked element cross-section during shaft rotation. Harmonic balance method is used to solve the equations of motion of the rotor system for steady-state response characteristics. The effect of some parameters such as crack depth, crack shape factor and the spinning speed is investigated. Results and conclusions: The results show that the unique whirl orbits behavior during passage through the subcritical speeds serve as a key indicator of crack presence in the shaft. The effects of the crack front curvature and the breathing model are revealed. The value of shape factor affects the whirl orbit characteristics such as size of the inner or outer loops and the amount by which the orbits rotate while crossing the subcritical speeds. The presented model considering the real crack front shape may contribute towards improved modelling of cracked rotors and better interpretation of measured vibration response. [ABSTRACT FROM AUTHOR]

The classic deformation known as simple shear has been investigated within the framework of nonlinear elasticity for isotropic incompressible hyperelastic materials in a large variety of contexts. For example, this deformation has been widely used in recent years in the analysis of the mechanical behaviour of biological soft matter. In this paper, we compare two different representations for the shear stress response that arise in the context of simple shearing: the first is the response arising in the classical strain or displacement based formulation while the second is the response arising in the stress or traction based formulation where the only nonzero stress is the shear stress. The former is also called a state of pure shear stretch where one stretch ratio is fixed at unity so that the other two principal stretches are a reciprocal of one another while the latter is a state of pure shear stress. Two different representations for the shear stress versus maximum stretch are obtained. The results are illustrated on using specific strain-energy densities for homogeneous isotropic incompressible hyperelastic materials. [ABSTRACT FROM AUTHOR]

A pilot's control behavior has a direct impact on aviation safety. To adapt to new flight training reforms, a competency-based assessment method is proposed in this paper. First, assessment scenarios, key competencies and observable behaviours were determined. Then, observable behavior assessment indexes were developed based on standard operating procedures and practical examination standards. Flight training data were analyzed based on curve similarity theory and a time series fast retrieval algorithm, and the assessment indexes were scored. The competency assessment method was established by quantifying "HOW MANY" and "HOW OFTEN" observable behaviors according to the assessment indexes score results. Finally, the fuzzy C-means clustering algorithm was used to classify the assessment values, and assessment results were obtained. A teardrop pattern procedure was used to test the reliability of the assessment method. The results indicate that the correlation coefficient between the model evaluation and the expert evaluation is 0.947 with a significance level of 0.01, reliably and objectively quantifying manual flight performance and improving the scientific nature of manual flight performance assessment methods. Flight training institutions can use this method to establish diverse assessment scenarios and formulate corresponding assessment indexes based on the characteristics of each pilot to reasonably evaluate the manual flight performance of pilot. Targeted training methods can then be adopted for pilot with different performance levels to improve their competency. [ABSTRACT FROM AUTHOR]

Considering the ever-increasing size and complexity of social networks, developing methods to extract meaningful knowledge and information from users' vast amounts of data is crucial. Identifying influencers on social networks is one of the essential investigations on these networks and has many applications in marketing, advertising, sociology, behavior analysis, and security issues. In recent years, many studies have been conducted on analyzing and identifying influencers on social networks. Therefore, in this article, a Systematic Literature Review (SLR) has been performed on previous studies about the methods of identifying influencers. To this end, we review the definitions of influencers, the datasets used for evaluation purposes, the methods of identifying influencers, and the evaluation techniques. Furthermore, the quality assessment of the recently published papers also has been performed in different aspects to find whether research about identifying influencers has progressed. Finally, trends and opportunities for future studies about influencers' identification are presented. The result of this SLR shows that the quantity and quality of articles in the field of identifying influencers in social networks are growing and progressive, which shows this field is a dynamic and active area of research. [ABSTRACT FROM AUTHOR]

Sponge City Public Private Partnership (PPP) project is a significant step to promote the construction of resilient city and sustainable development. Private companies take advantage of information asymmetry and regulatory loopholes to take opportunistic behavior, which affects the project delivery quality and public interests. In order to reveal the decision-making mechanism of the main stakeholders, this paper constructs an evolutionary game model of private companies, citizens and the government from a fresh perspective of perceived value. First, the traditional payoff matrix is modified by combining Prospect Theory and Mental Accounting. Next, this paper analyzes the strategic evolution law and stability conditions of game players by replicated dynamic equation. Finally, Nanganqu project is used for empirical simulation to verify the effectiveness of this model. Results indicate that, (1) due to the complexity of the project and the bounded rationality of the participants, there is no evolutionary stable strategy in this game system. (2) The behavioral decision of participants is affected by perceived incomes and perceived costs. (3) Government punishment and reputation loss can effectively curb the opportunistic behavior. All above studies are expected to improve the management of Sponge City PPP projects, providing theoretical guidance for the government to make scientific decisions. [ABSTRACT FROM AUTHOR]

This paper describes a strategic science of teaching (SST) and its application to effective education as a form of social justice. SST is grounded in the Comprehensive Application of Behavior Analysis to Schooling (CABAS®), a system-wide approach to teaching. The Accelerated Independent Learner (AIL) model stems from the CABAS® system but operates within public schools and general education classrooms where the science of behavior is applied to establish academic, social, and self-management repertoires for all students. In the AIL model, data from the student's progress drives instruction. The arrangement of the classroom includes classroom management, instructional presentations, curriculum-based measurement, visual displays of individual student mastery of curricular objectives, the interaction between verbal development and what to teach, and acquisition of learning cusps. Another critical aspect of these classrooms includes teacher measures and teacher education. All these components are used to collectively accelerate student learning. Using this model, we attempt to remove the barrier to a one-size-fits-all education system, thus creating a more just educational system for all children. [ABSTRACT FROM AUTHOR]

Many Australian students fail to meet an acceptable standard of reading proficiency. This can negatively impact their academic progress, social, and emotional well-being, and increase their risk of developing challenging behaviors. These risks and challenges have been found to compound over the lifetime of the learner. Unfortunately, the proportion of Australian students who fail to meet reading proficiency standards increases as they move through their years of schooling, and reading difficulties disproportionately affect historically marginalized groups. This has raised concerns about the effectiveness of instructional approaches used within the Australian education system, particularly in reading, and prompted discussions of reform. The purpose of this review paper was to examine the contributions of the science of reading and science of behavior to our collective knowledge regarding reading development and effective reading instruction, and how this knowledge is currently being used in the Australian context. We provide a discussion on the current state of reading instruction and achievement in Australia by considering national trends, inequities, and systemic challenges. Implications and recommendations to address inequities in reading outcomes, using both the science of reading and science of behavior, are discussed. [ABSTRACT FROM AUTHOR]

We study the autowave front propagation in a medium with discontinuous characteristics and the conditions for its stabilization to a stationary solution with a large gradient at the interface between media in the one-dimensional case. The asymptotic method of differential inequalities, based on constructing an asymptotic approximation of the solution, is the main method of study. We develop an algorithm for constructing such an approximation for the solution of the moving front form in a medium with discontinuous characteristics. The application of such an algorithm requires a detailed analysis of the behavior of the solution in neighborhoods of two singular points: the front localization point and the medium discontinuity point. As a result, we obtain a system of equations for the front propagation speed; this distinguishes this paper from the previously published ones. The developed algorithm can be used to describe autowave propagation in layered media. The results can also be extended to the multidimensional case. [ABSTRACT FROM AUTHOR]

This paper plans to propose a general numerical model for investigating the free and forced vibration behaviors of the multi-stepped functionally graded porous graphene platelet-reinforced composite (FGP-GPLRC) curved beam with various boundary conditions based on the first-order shear deformation Timoshenko beam theory by employing Rayleigh–Ritz method in conjunction with Jacobi polynomials. Different porosity and GPL distribution types are considered. The general boundary conditions of the multi-stepped FGP-GPLRC curved beam and connecting conditions of the FGP-GPLRC curved beam elements are simulated by employing boundary springs and connecting springs, respectively. The convergence and validation of the proposed numerical model are demonstrated by comparing the proposed results with the corresponding results which come from open literature and finite element software ABAQUS. The free and forced vibration behavior analysis of multi-stepped FGP-GPLRC curved beam is carried out by investigating the influences of material property and geometric parameters on the natural frequency and displacement response in the frequency and time domains of multi-stepped FGP-GPLRC curved beam structure. The investigation results can offer the technique guidance for the design and manufacture of the multi-stepped FGP-GPLRC curved beam. [ABSTRACT FROM AUTHOR]

The intelligent recognition of human behavior and action in massive video data is the key application direction in the field of artificial intelligence. With the development of intelligent communication network, multimedia communication has become a hot spot in the field of video analysis. 3D convolution is an efficient deep learning model. It can learn the temporal and spatial features of target images at the same time. A 3D max residual feature map convolution network (3D-MRCNN) is proposed in this paper. Problems can be solved by the proposed model that the deficiencies of the network degradation and gradient disappearance caused by convolution calculation. The proposed model is preprocessed by 2D convolution firstly. A learning network including 3D-max feature map (3D-MFM) and residual structure is established after the convolution splitting is completed. Finally, the output vectors corresponding to the two different inputs are connected and fused into the support vector machine (SVM) classification. The accuracy of 3D-MRCNN can achieve 85.7% by experimenting on the representative UCF101 data set. And it has higher accuracy and operating efficiency compared with the models which have strong correlation with 3D-MRCNN. [ABSTRACT FROM AUTHOR]