Behavior Characteristics Research Articles

Mechanical characterization of Al2219-SiC metal matrix composites

The present work conducted an experimental examination to assess the tensile behaviour and microstructural characteristics of Al2219 metal alloy reinforced with 4 and 8 wt. % of SiC composites. The investigation employed the liquid metallurgical method to fabricate composites of the Al2219 alloy including SiC particles at weight percentages of 4 and 8. This work employed supplementary methods, including scanning electron microscopy (SEM), to determine the microstructural characteristics. An investigation of the mechanical characteristics of Al2219 alloy with SiC reinforced composites is conducted in accordance with ASTM Standards. Furthermore, the incorporation of silicon carbide particles into aluminium 2219 demonstrates remarkable characteristics in the field of composite materials, therefore augmenting its potential for a broad spectrum of uses. Enhancements in hardness and tensile strengths of the composites were achieved by combining different materials. The fractured surfaces of the Al2219-SiC composites displayed both brittle and ductile fracture characteristics, as indicated by their tensile test results.

Enhanced analog switching and neuromorphic performance of ZnO-based memristors with indium tin oxide electrodes for high-accuracy pattern recognition.

This study systematically investigates analog switching and neuromorphic characteristics in a ZnO-based memristor by varying the anodic top electrode (TE) materials [indium tin oxide (ITO), Ti, and Ta]. Compared with the TE materials (Ti and Ta), memristive devices with TEs made of ITO exhibit dual volatile and nonvolatile switching behavior and multistate switching characteristics assessed based on reset-stop voltage and current compliance (ICC) responses. The polycrystalline structure of the ZnO functional layer sandwiched between ITO electrodes was confirmed by high-resolution transmission electron microscopy analysis. The current transport mechanism in the ZnO-based memristor was dominated by Schottky emission, with the Schottky barrier height modulated from 0.26 to 0.4V by varying the reset-stop voltage under different ICC conditions. The long-term potentiation and long-term depression synaptic characteristics were successfully mimicked by modulating the pulse amplitudes. Furthermore, a 90.84% accuracy was achieved using a convolutional neural network architecture for Modified National Institute of Standards and Technology pattern categorization, as demonstrated by the confusion matrix. The results demonstrated that the ITO/ZnO/ITO/Si memristor device holds promise for high-performance electronic applications and effective ITO electrode modeling.

Review of research on disaster mitigation emergency congregate shelter planning for vulnerable group

The elderly, including individuals with disabilities, women, and children, among other vulnerable evacuees, are the most fragile group during disasters. During major disasters, safely and rapidly transferring vulnerable evacuees to shelters that can meet their sheltering needs is crucial and challenging in emergency rescue work. This article systematically analyzes the sheltering behavior characteristics and sheltering needs of vulnerable evacuees based on relevant research at home and abroad. It also reviews the technical indicators and requirements for emergency shelter planning for vulnerable evacuees, and studies emergency shelter planning models from the perspective of vulnerable evacuees. Finally, it proposes prospects for emergency shelter planning indicators and models based on vulnerable evacuees, providing a reference and guidance for improving and enhancing emergency sheltering strategies for vulnerable evacuees.

Data-Driven Fault Detection and Diagnosis for UAV Swarm Systems

With the widely application and promotion of Unmanned aerial vehicle (UAV) technology, UAV swarms are widely used in military and civilian fields by taking advantage of group collaboration. It has huge economic and national defense value. The safety and reliability requirements of the UAV swarm system are extremely strict, and real-time fault detection and diagnosis is one of its important supporting technologies. In this paper, a fault diagnosis method based on statistical model and improved broad learning system (BLS) is proposed. The behavior characteristics of the UAV swarm system under normal and different failure modes are characterized by multivariate data statistical analysis, and the improved BLS model is adopted to achieve accurate and fast fault diagnosis. And a high-fidelity simulation verification platform is developed to verify the rationality and effectiveness of the proposed method.

Hierarchical MPC-based authority allocation strategy for human–machine shared vehicles considering human–machine conflict

The uncertainty of driver behavior is an important factor affecting the safety of human–machine co-driving vehicles. Traditional rule-based models often fail to capture the nonlinear and complex characteristics of human steering behavior. To overcome this, we propose a data network-driven approach utilizing gated recurrent unit (GRU) neural networks to accurately predict driver steering behavior. The GRU-based driver model is integrated with vehicle dynamics to construct a control-oriented driver–vehicle model. Considering that human–machine conflict may cause vehicle instability, an exponential function combining proportional–integral–derivative is proposed to quantify the human–machine conflict level based on steering difference. To reasonably allocate human–computer permissions based on human–machine interaction, a hierarchical authority allocation framework is proposed. The upper layer provides a reference authority allocation via an exponential function, while the lower layer employs a real-time model predictive control (MPC) optimizer to track this reference, ensuring optimal vehicle path tracking and stability. The proposed system’s effectiveness is validated through driver-in-the-loop testing, demonstrating significant improvements in safety and performance. The results show that in the human–machine conflict scenario, the proposed authority allocation strategy can still ensure the path tracking and safety of the vehicle.

Bilateral Turing Test: Assessing machine consciousness simulations

Recent advancements in Artificial Intelligence (AI) have brought discussions on machine consciousness back to the forefront. However, methodologies for assessing machine consciousness simulations remain highly constrained and lack consensus. This study introduces the Bilateral Turing Test, a thought experiment to assess machine consciousness simulations based on a functionalist perspective, focusing on external behavior and cognitive characteristics associated with consciousness. The test involves both machines and humans participating as judges in an enhanced Turing Test, and compares the external behavior of machine-simulated consciousness with the behavior of human consciousness. We derive the experimental principles via three theoretical propositions reflecting the human–machine cognitive relationship and elucidate the basic conditions and procedures of the thought experiment. A systematic measure is employed to evaluate emulation against human benchmarks, and we establish a statistical threshold for successful consciousness simulations. Our study provides a comprehensive framework for redefining machine consciousness simulations and enhancing interdisciplinary conversations across computer science, neuroscience, and philosophy. This framework also advances bottom-up approaches for assessing machine consciousness simulations and provides pivotal insights into human–machine interaction dynamics.

Acoustic waves propagating through a fluid area containing randomly distributed coated cylinders

The research investigates acoustic wave propagation through a fluid region containing randomly arranged cylinders coated in identical materials, resulting in multiple scattering and the emergence of an effective wave. It examines the impact of the coating's viscoelasticity, cylinder material, and scatterer volume fraction on this wave. Additionally, it analyzes dispersion and attenuation as acoustic waves interact with the fluid region containing scatterers, particularly emphasizing normal incidence. This comprehensive study advances the understanding of wave scattering in random media, shedding light on this complex phenomenon. By delving into the complex interplay between wave behavior and material characteristics, the research provides valuable insights that can inform various acoustics and materials science applications, contributing to advancements in these fields.

Comprehensive transcriptomic analysis identifies three distinct subtypes of pituitary adenomas: insights into tumor behavior, prognosis, and stem cell characteristics

BackgroundPituitary adenomas (PAs) are the second most common intracranial tumor. While current diagnostic practices rely primarily on histological testing, they often fail to capture the molecular complexities of pituitary adenomas, underscoring the need for a molecular-based classification to refine therapeutic strategies and prognostic assessments. This study aims to provide a molecularly unbiased classification of pituitary adenomas and explore their unique gene expression patterns and clinical features.MethodsWe performed unsupervised hierarchical clustering of the gene expression profiles of 117 PA samples to identify three distinct molecular subtypes. Subsequently, we analyzed the compiled transcriptomic profiles of each individual subtype for pathway enrichment. We also validated the new classification with a validation set containing 158 PAs and 24 pituitary adenoma stem cells (PASCs).ResultsConsensus clustering of transcriptomic data from 117 pituitary adenoma (PA) samples identified three distinct molecular subtypes, each showing unique gene expression patterns and associated biological processes: Group I is enriched in signaling pathways, such as the cAMP signaling pathway and the calcium signaling pathway. Group II is primarily related to metabolic processes, including nitrogen metabolism and arginine biosynthesis in cancer. Group III predominantly shows enrichment in immune responses and potential malignant transformation of the disease, especially through cancer-related pathways such as the JAK–STAT signaling pathway and the PI3K–Akt signaling pathway. The immune profiling revealed distinct patterns for each subtype: Group I had higher dendritic cells and fewer CD8+ T cells, Group II had more monocytes and macrophages, and Group III had elevated levels of T cells. Additionally, there were differences in clinical characteristics and prognosis among the subtypes, with Group III having a worse prognosis, despite the smaller tumor size compared to other groups. Notably, differences in PASCs correlated with the molecular subtypes, with Group III stem cells being enriched in tumorigenesis pathways, PI3K–Akt signaling pathway and Ras signaling pathway.ConclusionOur study introduces a novel molecular classification for pituitary adenomas, independent of traditional histological methods. Each subtype features distinct genetic, molecular, and immunological profiles. We have isolated pituitary adenoma stem-like cells (PASCs), pairing them with tumor tissues for detailed transcriptomic analysis. These PASCs exhibit diverse molecular traits consistent with the new classification.

Three-part superposition quasi-static stress model for PTFE across a broad low-temperature range based on ZWT and higher-order stress corrections

The widespread application of cryogenic liquid fuels in aerospace necessitates an accurate description of the mechanical properties of sealing materials such as Polytetrafluoroethylene (PTFE) at low temperatures. This study aims to develop a stress prediction model to describe the tensile stress response of PTFE across a broad low-temperature range. Quasi-static tensile tests on PTFE samples were conducted to obtain the uniaxial tensile properties of PTFE in the low-temperature range. Data fitting revealed significant errors and a loss of physical significance in the classical Zhu–Wang–Tang (ZWT) constitutive model and its modified versions when describing PTFE's mechanical response at low temperatures or large strains. Based on these theoretical models, a three-part superposition (TPS) model, incorporating asymptotic growth, linear growth, and exponential growth terms, is proposed. The TPS model demonstrates excellent predictive accuracy for PTFE's mechanical response from 77 K to 293 K, and from initial strain to fracture. Additionally, the physical connections and interpretations between the three parts of the TPS model and the macroscopic mechanical behavior and microscopic crystalline characteristics of semi-crystalline polymers are analyzed, providing a unified description and a comprehensive understanding of PTFE's mechanical behavior over this temperature range.

AstroSat’s view of 4U 1735−44: spectral, temporal, and type I X-ray burst studies

ABSTRACT This study utilizes the simultaneous broad-band observations of 4U 1735−44 from AstroSat, offering enhanced spectral and temporal resolution, to investigate its spectral properties, temporal behaviour, and burst characteristics. Spectral, type I X-ray burst, and temporal analyses on 4U 1735−44 were performed using AstroSat/Soft X-ray Telescope and Large Area X-ray Proportional Counter (LAXPC) observations. The hardness–intensity diagram from LAXPC-20 showed a positive correlation between hardness and intensity, with a pattern resembling the banana branch typical of atoll sources. Spectral analysis carried out in the 0.7–20.0 keV energy range, using the model combination – $\tt {constant}$$\times$$\tt {tbabs}$ ($\tt {nthcomp}$$+$$\tt {diskbb}$$+$$\tt {bbodyrad}$), suggested a cool accretion disc truncated at a large distance from the neutron star in the system. Time-resolved spectral studies of two type I X-ray bursts detected from the source revealed evidence of photospheric radius expansion, allowing for an estimation of the source distance. Temporal analysis showed the presence of low-frequency quasi-periodic oscillation at $\sim$69 Hz (3.3$\sigma$ significance with more than 99 per cent confidence) and prominent noise features below 30 Hz.

Intelligent monitoring of marine vessel dynamics based on data mining

This study explores vessel navigation's universal characteristics and individual anomaly behavior from dispatch to destination. With the help of information technology, it introduces big data and machine learning technologies into the work of vessel traffic management and conducts statistical analysis and monitoring studies of vessel behavior from a data-driven perspective. The study was conducted by modeling vessel speed, position, course, and other navigational characteristics behavior through comprehensive statistical analysis of vessel AIS, radar, and VTS data. The study was based on the monitoring methods for anomalous behavior of vessel speed, position, and heading inconsistencies with the expected behavior identified by the model.

Aggregation Behavior of CHR-bis(BODIPY) Bichromophores in THF-water Mixtures: Effect of Linking Positions and Aryl-spacer Substituents.

Aggregation-caused quenching effect (ACQ) greatly limits the practical use of many organic luminophores in biomedicine, optics and electronics. The comparative analysis of aggregation characteristics of CHR-bis(BODIPY) bichromophores 1-6 with R = H, Ph, MeOPh and various linking positions (α,α-; α,β-; β,β- and β',β'-) in THF-water mixtures with different water fractions or dye concentrations is first presented in this article. Both the linking style 1-4 and the arylation of the spacer with phenyl (Ph-) 5 or methoxyphenyl (MeOPh-) 6 substituents strongly affect the formation of luminophore aggregated forms in binary THF-water mixtures. The α,α-and β,β-isomers (1 and 3) form non-fluorescent H-type aggregates in THF-water mixtures with fw > 70%. The α,β-; β',β'-isomers (2, 4) and the MeOPh-substituted β,β-bichromophore 6 are characterized by predominant formation fluorescent aggregates. All bichromophores are characterized by the presence of residual amounts of non-aggregated forms in binary mixtures with maximum water content. The results are useful for controlling the aggregation behavior and spectral characteristics of CHR-bis(BODIPY) bichromophores in aqueous-organic media, which is important in the development of biomarkers and PDT agents.

Enhancing behavior classification of children in dynamic interaction scenes through improved DCNN model

The rapid development of society makes people pay more attention to the quality of the environment for children’s growth. However, due to the differences of young children, different environments are often needed for cultivation in dynamic interaction scenarios. Therefore, the authors propose an environment creation method for children’s behavior classification to improve the quality of children’s growth environment. Taking the video data of children for a period of time as input, the encoder and decoder are designed to classify children’s behavior and obtain behavior characteristics. After the input image is processed by the backbone network DCNN, two outputs are obtained, which are four times of shallow features and 16 times of high-level features. Aiming at the semantic gap between environmental features and children’s behavior features, the DenseNet model is used to remove the semantic difference between children’s behavior features and environmental features, and the similarity between the two features is fitted as much as possible. The dense blocks obtained by different expansion factors of the network are used for feature connection, so that the model is suitable for feature similarity calculation of different modes. The experimental results show that this method can accurately classify children’s behavior, and the F value is more than 70%, which can provide prerequisites for children’s environment creation. This environment creation model can clearly point out the suitable environment for children and provide a guarantee for children’s growth.

The Correlation of Maternal Behavior in Toddlers Breastfeeding with Wasting Prevention in Pidie

Besides children, teenagers also suffer from malnutrition due to certain factors. The development of wasting is considered related to mothers’ behavior during breastfeeding times. However, it has big impact towards the quality of breastfeeding. According to data from World Health Organization, 45.4 million children under the age of five were underweight in 2020, while the highest infant wasting rate nationally was 11.9% in several districts and cities from 33 provinces in Indonesia. Globally, 149.2 million children under the age five suffer from stunting, while its distribution of region in Indonesia is in Maluku and Aceh. Aceh is in fourth place of stunting with a percentage of 11.3% nationally. Based on the data related to wasting using the ratio of children’s weight to height, Pidie regency ranks third in Aceh as a whole with ratio of 15.3%. This study used a cross-sectional research with sample of 332 toddlers selected as the research object using Slovin formula. The sample data of this study was determined randomly and was taken from Pidie Regency Health Center which had a population of 1979 toddlers listed. SPSS 23 statistical software with Chisquare was used as a tool for data analysis. The findings of this study came from a bivariate statistical analysis test using the chisquare test at a confidence level of 95%, resulting in a p-value of 0.042 (p<; 0.05). This shows that the variable of maternal knowledge has an influence in keeping toddlers from experiencing wasting. The results of the chisquare test at the 95% confidence level in the bivariate statistical analysis test with p= 0.021 (p<; 0.05) showed that the maternal attitude variable had an influence on the ability of toddlers to avoid wasting. The results of the chisquare test for bivariate statistical analysis are at a confidence level of 95%: p = 0.024 (p<; 0.05). Characteristics of maternal behavior and prevention of wasting have a close correlation. Mothers' attitudes, knowledge, and behaviors towards wasting prevention are influenced by their breastfeeding practices. The best way to prevent wasting is to encourage mothers to breastfeed. The researchers stated that the increasing knowledge and attitudes of mothers in breastfeeding also improved their behavior, especially in terms of preventing wasting while breastfeeding. Supervision of health workers is expected to increase the knowledge and attitude of mothers and improve the prevention of wasting

Personalized Health Management Strategies Based on Deep Reinforcement Learning in the Network Environment

In order to study the optimal personalized motion push target, the author proposes a personalized health managementstrategy based on deep reinforcement learning in the network environment. Firstly, the research problem is defined, and a real-time interactive personalized motion target decision-making model is constructed; Subsequently, in response to the uncertain characteristics of user behavior in the problem, a deep reinforcement learning algorithm was adopted, combined with the departure strategy temporal difference learning method and neural network nonlinear fitting method, in order to learn strategies from user historical data; Finally, the effectiveness of the proposed method was validated using a real dataset from Fitbit. The research results indicate that personalized motion goal push services based on deep reinforcement learning can help users cultivate a healthy lifestyle and improve their personal health management level by analyzing user behavior data in real-time, providing scientific guidance and timely incentives.

Characteristics of Dietary Behaviors and Effects of Dietary Acculturation in East African Immigrants Living in the San Diego Area: Preliminary Insights from the HAWAASH2 Study

Characteristics of Dietary Behaviors and Effects of Dietary Acculturation in East African Immigrants Living in the San Diego Area: Preliminary Insights from the HAWAASH2 Study

Characteristics of light emission and wear behaviour of a reinforced composite material made of basalt and jute for optimum parameters

Characteristics of light emission and wear behaviour of a reinforced composite material made of basalt and jute for optimum parameters

Analysis of consumer behavior of tourism products

The research of the tourism phenomenon reveals that its main characteristic is the orientation towards consumption. One of the purposes of such research is to identify the characteristics of the consumer’s behavior, which is particularly important for determining the type and frequency of accessing tourist products and services by consumers, the formation of the tourist offer, the evaluation of the level of utility of the consumption of tourist products and services. The purpose of the present study was to identify the characteristics of consumer behavior in the tourist services market according to several factors. As the main research method, the online survey method was used in which 100 respondents participated. The questionnaire included questions aimed at identifying the following aspects: age category, social status, household size, income, frequency of accessing tourist services, type of tourist products accessed, national affiliation of the tourist products accessed and the level of utility recorded.

Deformation ability of modular gymnasium steel inner sleeve all-bolt cross connection joint based on 3D-DIC method

Immense roof loads present a significant hurdle for the functionality of continuously supported modular connection joints in movable modular gymnasium structures. Consequently, we introduced leveraging inner sleeves and bolts to interconnect the modular units of the upper and lower columns, aiming to bolster the strength of inter-unit connections. Despite its noteworthy benefits, the deformation behavior and force distribution characteristics of this novel design remain underexplored. Hence, our study employs three-dimensional digital image correlation (3D-DIC) measurement to precisely capture the full-field displacement and strain distributions within the core area of this joint. Four distinct joint specimens were designed, and conducted comprehensive static tests, encompassing variables such as the inclusion or exclusion of inner sleeves, reinforcing ribs, and diverse loading directions. 3D-DIC detected subtle deformations and local buckling phenomena, undetectable by the naked eye, and revealed their occurrence patterns. Furthermore, the detections underscore the critical role of weld quality between beams and columns in ensuring the overall safety of the joints. The joint exhibited earlier yielding in beam bending compared to column bending. To delve deeper into this joint, we generated moment-rotation curves leveraging DIC results, deducing that this joint exhibits rigid-joint characteristics. The specimens primarily showed damage modes such as beam-root fractures or member buckling, while the core area remained intact. This observation reinforces the classification of the joint as a full-strength entity. These insights enrich our comprehension of this novel joint and serve as invaluable references and aids for designers.

Al‐doped Mixed Transition Metal Ferrites Synthesis and Application in Adsorption of Dyes

AbstractThis paper presents the preparation of Al‐doped mixed transition metal ferrite (AlxCo0.7Mn0.3Fe2−xO4 where x=0.1, 0.3, 0.5, 0.7 and 0.9) via a solution combustion method, followed by an application for the removal of dyes from aqueous solution. Various physicochemical techniques were employed to determine the morphological, structural, magnetic behaviour and adsorption characteristics of the synthesized ferrites by through Scanning Electron Microscope (SEM), X‐ray powder Diffraction (XRD), Fourier Transform Infra‐Red spectroscopy (FT‐IR), Vibrating Sample Magnetometer (VSM), and Brunauer‐Emmett‐Teller (BET) analysis. Furthermore, the as‐synthesized ferrite materials were utilized for adsorbing dyes (Methylene blue (MB), Crystal violet (CV), Methyl orange (MO), and Congo red (CR)) from aqueous solutions, with the results reported using UV‐visible spectroscopy. The findings indicate that Al‐doped mixed transition metal ferrites serve as potential adsorbents for dye removal.