Quantitative Analysis Of Behavior Research Articles

Quantitative analysis of fluid heat transfer behavior in a proton exchange membrane water electrolysis cell

The development of heat transfer models for proton exchange membrane water electrolysis (PEMWE) cells is necessary to enhance their efficiency, durability, and safety. Although modeling efforts have indicated that the heat transfer to fluids is significant, the magnitude of the heat transfer and mechanism have not been adequately studied. To fill this knowledge gap, we quantified the amounts of heat transferred in a thermally insulated cell and associated system. We found that heat transfer to the inflow water accounted for the majority of heat transfer to the fluids, and the rise of the membrane (CCM + PTL) temperature was due mainly to deterioration of the distribution of water at high current density. The sensible heat transfer and the resistive heat were directly proportional to each other, and the quantity of latent heat transfer could be influenced by resistive heating and kinetic factors. This study was the first to provide detailed experimental insights into the factors that mainly affect heat transfer to fluids in PEM water electrolysis cells.

Bead‐to‐Bead Analysis: Introducing an Innovative Methodology for Accelerated Quantitative Analysis of the Welding Behavior of Bead Foams

ABSTRACTPerformant lightweight components made of bead foams are essential for a sustainable transformation of industry in multiple areas. An in‐depth understanding of the welding process is key in reaching maximum mechanical properties. This study presents the novel methodology of Bead‐to‐Bead analysis, providing a superior way in directly and quantitatively evaluating the welding behavior of bead foams compared with current approaches. Individual beads of expanded polystyrene (EPS) and expanded thermoplastic polyurethane (ETPU) are welded in a rheometer at defined parameters. A subsequent tensile test in combination with the analysis of the welded surface allows the evaluation of shrinkage/softening of the beads during welding and their tensile strength. For EPS, softening of the amorphous material is observed at the beginning of glass transition (~95°C) in addition to an increased welding quality. Residual stresses in ETPU lead to initial shrinkage followed by softening above 140°C. Welding of ETPU starts at 100°C and reaches a maximum at 140°C. The subsequent thermal analysis of the welded beads show the importance of recrystallization processes during cooling due to the formation of new crystalline domains across the bead interfaces. In the absence of such domains, sufficient bonding between beads is not possible.

ABNet: AI-Empowered Abnormal Action Recognition Method for Laboratory Mouse Behavior.

The automatic recognition and quantitative analysis of abnormal behavior in mice play a crucial role in behavioral observation experiments in neuroscience, pharmacology, and toxicology. Due to the challenging definition of abnormal behavior and difficulty in collecting training samples, directly applying behavior recognition methods to identify abnormal behavior is often infeasible. This paper proposes ABNet, an AI-empowered abnormal action recognition approach for mice. ABNet utilizes an enhanced Spatio-Temporal Graph Convolutional Network (ST-GCN) as an encoder; ST-GCN combines graph convolution and temporal convolution to efficiently capture and analyze spatio-temporal dynamic features in graph-structured data, making it suitable for complex tasks such as action recognition and traffic prediction. ABNet trains the encoding network with normal behavior samples, then employs unsupervised clustering to identify abnormal behavior in mice. Compared to the original ST-GCN network, the method significantly enhances the capabilities of feature extraction and encoding. We conduct comprehensive experiments on the Kinetics-Skeleton dataset and the mouse behavior dataset to evaluate and validate the performance of ABNet in behavior recognition and abnormal motion detection. In the behavior recognition experiments conducted on the Kinetics-Skeleton dataset, ABNet achieves an accuracy of 32.7% for the top one and 55.2% for the top five. Moreover, in the abnormal behavior analysis experiments conducted on the mouse behavior dataset, ABNet achieves an average accuracy of 83.1%.

Immersive gaze sharing for enhancing education: An exploration of user experience and future directions

Gaze sharing (GS) technology enhances communication between human interlocutors. Essentially, GS consists of sharing information regarding one's visual attention with another person, by automatically marking one's current point of interest on a digital display. The benefits of this technology for education have been demonstrated by researchers. However, since most GS systems relay gaze information using flat monitors, they impede natural communication between interlocutors who are co-located (as glancing at the display diverts their attention from the physical space). Acknowledging this limitation, immersive gaze sharing (IGS) systems have been recently developed. IGS systems utilize the power of Extended Reality (XR) technology to superimpose gaze information directly onto one's visual environment, and are therefore a promising tool for enhancing human communication in education. Currently, we know little regarding how users experience IGS, to guide its development. To bridge this gap, we have executed an exploratory user study of IGS with learners and instructors, using Mixed Reality (MR) technology. A quantitative and qualitative analysis of users' feedback and behavior has shed light on the differences between instructors and learners in terms of their needs, abilities and preferences. On this basis, guidelines for developing IGS systems are proposed, towards their integration into our future educational practices.

Quantitative analysis of the micromechanical behavior and work hardening in Fe-0.1C–10Mn steel via in-situ high-energy X-ray diffraction

In the current work, the micromechanical behavior and work hardening behavior of Fe-0.1C–10Mn (in wt.%) steel deformed at 100, 63, 25 and −50 °C were investigated via in-situ high-energy X-ray diffraction (HE-XRD) technique. As the deformation temperature decreased, the yield strength (YS) and ultimate tensile strength (UTS) increased, while the total elongation (TE) reached a maximum value at 25 °C. The transformation kinetics of retained austenite (RA) was fitted by the Olson and Cohen (OC) model. The phase stress and flow stress contributed by the constituent phases were obtained based on the lattice strain and the volume fraction of the corresponding phase. The work hardening rate was decomposed into four contributors related to the TRIP effect and load partitioning, ie., the austenite phase stress, load partitioning between austenite and martensite, martensitic formation rate and load partitioning between ferrite and austenite. The influence of each contributor on the work hardening behavior was quantitatively evaluated and stacked, the stacked results agreed reasonably well with the experimental work hardening rate obtained from the true stress-strain curve. Finally, the volume fraction of austenite to martensite transformation promoted by the Lüders band (LB) and the stacking fault energy (SFE) of RA were found to be highly temperature-dependent. A linear relationship was revealed between the volume fraction of austenite to martensite transformation during the LB propagation and the SFE of RA. These findings offer insights into the TRIP effect and the LB propagation in medium-Mn steels.

Quantitative analysis of grain boundary segregation and fracture behavior in Ca-doped magnesium aluminate spinel

Quantitative analysis of grain boundary segregation and fracture behavior in Ca-doped magnesium aluminate spinel

Solvent effect, spectral (SERS and UV-Vis) and adsorption analysis of Gliadel (GL) anticancer drug with Ag/Au loaded silica nanocomposites

Drug delivery devices reduce drug molecule toxicity and nanostructure can be used to targeted drug delivery. A quantitative analysis of the interaction behavior of Gliadel (GL) with Ag/Au…SiO2 presented in this study in order to minimize drug molecule toxicity. The stabilized structure with the lowest energy conformer of GL in both the gas/water phases has been examined using potential energy surface (PES) analysis, after which the structure was optimized. In the reactivity study, silver/gold loaded silica nanocomposites formed by GL exhibit an increasing electrophilicity index, giving a characteristic to the systems. UV–Vis. analysis was studied to assess the excited state of the investigated complexes using time-dependent density function theory (TD-DFT) in both gas and water phases. The electron transfer within a molecule is determined by Frontier Molecular Orbitals, or FMOs. The charge distribution within the molecule was examined using a color-coded graphic representation of the molecular electrostatic potential (MEP) map. To the extent that to sort out whether a molecule was desirable for use as a medicine, the drug delivery procedure took into account its absorption, distribution, metabolism, and excretion (ADME) qualities. Finally, molecular docking with the selected proteins was examined using the complexes and pure.

The scientist/practitioner in behavior analysis: A case study.

This article is a transcription of Murray Sidman's presentation at the annual meeting of the Society for the Quantitative Analysis of Behavior in May 1998. It describes the development (from 1965 to 1975) of behavior-change programs implemented outside the animal laboratory to benefit humans before such application was established formally as an entity derived from the experimental analysis of behavior. The presentation illustrates the use of an inductive method in practice, where working with a fluid behavior stream entails making intervention decisions on the spot. Examples include fading and backward-chaining procedures in the establishment and stimulus control of novel actions. Sidman also discusses the certification of practitioners and the interaction between client and therapist and between basic and applied endeavors. The latter define what is contemporaneously described as translational intervention. It is noteworthy that Sidman's presentation was at a meeting attended by both practitioners and scientists.

Online Room Booking System for HotelVilla18

ABSTRACT: The hospitality industry has undergone a significant transformation with the advent of online booking platforms, reshaping the way travelers search for and book hotel accommodations. This research paper investigates the role of hotel booking web development in enhancing user experience and business efficiency within the hospitality sector. The study focuses on evaluating the user interface, usability, real-time availability, pricing transparency, secure payment processing, and booking management systems of hotel booking websites or applications. A mixed-method approach is employed, combining quantitative analysis of user behavior and system performance metrics with qualitative insights from user surveys, interviews with industry experts, and case studies of successful booking platforms. The findings contribute to understanding best practices, user preferences, technological advancements, and business strategies in hotel booking web development. The outcomes of this study are valuable for hoteliers, web developers, policymakers, and researchers aiming to optimize the online booking experience, drive customer satisfaction, and achieve business success in the digital era. Keywords– Online Room Booking, Hotel Reservation System, Instant Hotel Booking, Secure Hotel Booking.

Quantitative Assessment and Analysis of Fish Behavior in Closed Systems Using Information Entropy

This study introduces a method for quantitatively assessing the complexity and predictability of fish behavior in closed systems through the application of information entropy, offering a novel lens through which to understand how fish adapt to environmental changes. Utilizing simulations rooted in a random walk model for fish movement, we delve into entropy fluctuations under varying environmental conditions, including responses to feeding and external stimuli. Our findings underscore the utility of information entropy in capturing the intricacies of fish behavior, particularly highlighting the synchrony in collective actions and adaptations to environmental shifts. This research not only broadens our comprehension of fish behavior but also paves the way for its application in fields like aquaculture and resource management. Through our analysis, we discovered that smaller grid sizes in simulations capture detailed local fluctuations, while larger grids elucidate general trends, pinpointing a 2.5 grid as optimal for our study. Moreover, changes in swimming speeds and behavioral adaptations during feeding were quantitatively analyzed, with results illustrating significant behavior modifications. Additionally, employing a Gaussian mixture model helped to clarify the nuanced changes in fish behavior in response to altered light conditions, demonstrating the layered complexity of fish responses to environmental stimuli. This investigation confirms the efficacy of information entropy as a robust metric for evaluating fish shoal behavior, offering a fresh methodology for ecological and environmental studies, with promising implications for sustainable management practices.

Ecotoxicological evaluation and regeneration impairment of planarians by dibutyl phthalate

Commonly utilized as a plasticizer in the food and chemical sectors, Dibutyl phthalate (DBP) poses threats to the environment and human well-being as it seeps or moves into the surroundings. Nevertheless, research on the harmfulness of DBP to aquatic organisms is limited, and its impact on stem cells and tissue regeneration remains unidentified. Planarians, recognized for their robust regenerative capabilities and sensitivity to aquatic pollutants, are emerging animal models in toxicology. This study investigated the comprehensive toxicity effects of environmentally relevant levels of DBP on planarians. It revealed potential toxicity mechanisms through the use of immunofluorescence, chromatin dispersion assay, Western blot, quantitative real-time fluorescence quantitative PCR (qRT-PCR), chromatin behavioral and histological analyses, immunofluorescence, and terminal dUTP nickel-end labeling (TUNEL). Findings illustrated that DBP caused morphological and motor abnormalities, tissue damage, regenerative inhibition, and developmental neurotoxicity. Further research revealed increased apoptosis and suppressed stem cell proliferation and differentiation, disrupting a balance of cell proliferation and death, ultimately leading to morphological defects and functional abnormalities. This was attributed to oxidative stress and DNA damage caused by excessive release of reactive oxygen species (ROS). This exploration furnishes fresh perspectives on evaluating the toxicity peril posed by DBP in aquatic organisms.

High-resolution, high-throughput analysis of Drosophila geotactic behavior.

Drosophila innate response to gravity, geotaxis, has been previously used to assess the impact of aging and disease on motor performance. Despite its rich history, fly geotaxis continues to be largely measured manually and assessed through simplistic metrics. The manual nature of this assay introduces substantial experimental variability while simplistic metrics provide limited analytic insights into the behavior. To address these shortcomings, we have constructed a fully automated, programable apparatus, and developed a multi-object tracking software capable of following sub-second movements of individual flies, thus allowing reproducible, detailed, and quantitative analysis of geotactic behavior. The apparatus triggers and monitors geotaxis of 10 fly cohorts simultaneously, with each cohort consisting of up to 7 flies. The tracking program isolates cohorts and records individual fly coordinate outputs allowing for simultaneous multi-group, multi-fly tracks per experiment, greatly improving throughput and resolution. The algorithm tracks individual flies during the entire run with ~97% accuracy, yielding detailed climbing curve, speed, and movement direction with 1/30 second resolution. Our tracking also allows the construction of multi-variable metrics and the detection of transitory movement phenotypes, such as slips and falls, which have thus far been neglected in geotaxis studies due to limited spatio-temporal resolution. Through a combination of automation and robust tracking, the platform is therefore poised to advance Drosophila geotaxis assay into a comprehensive assessment of locomotor behavior.

The evolution of olfactory sensitivity, preferences, and behavioral responses in Mexican cavefish is influenced by fish personality.

Animals are adapted to their natural habitats and lifestyles. Their brains perceive the external world via their sensory systems, compute information together with that of internal states and autonomous activity, and generate appropriate behavioral outputs. However, how do these processes evolve across evolution? Here, focusing on the sense of olfaction, we have studied the evolution in olfactory sensitivity, preferences, and behavioral responses to six different food-related amino acid odors in the two eco-morphs of the fish Astyanax mexicanus. To this end, we have developed a high-throughput behavioral setup and pipeline of quantitative and qualitative behavior analysis, and we have tested 489 six-week-old Astyanax larvae. The blind, dark-adapted morphs of the species showed markedly distinct basal swimming patterns and behavioral responses to odors, higher olfactory sensitivity, and a strong preference for alanine, as compared to their river-dwelling eyed conspecifics. In addition, we discovered that fish have an individual 'swimming personality', and that this personality influences their capability to respond efficiently to odors and find the source. Importantly, the personality traits that favored significant responses to odors were different in surface fish and cavefish. Moreover, the responses displayed by second-generation cave × surface F2 hybrids suggested that olfactory-driven behavior and olfactory sensitivity is a quantitative genetic trait. Our findings show that olfactory processing has rapidly evolved in cavefish at several levels: detection threshold, odor preference, and foraging behavior strategy. Cavefish is therefore an outstanding model to understand the genetic, molecular, and neurophysiological basis of sensory specialization in response to environmental change.

The evolution of olfactory sensitivity, preferences, and behavioral responses in Mexican cavefish is influenced by fish personality

Animals are adapted to their natural habitats and lifestyles. Their brains perceive the external world via their sensory systems, compute information together with that of internal states and autonomous activity, and generate appropriate behavioral outputs. However, how do these processes evolve across evolution? Here, focusing on the sense of olfaction, we have studied the evolution in olfactory sensitivity, preferences, and behavioral responses to six different food-related amino acid odors in the two eco-morphs of the fish Astyanax mexicanus. To this end, we have developed a high-throughput behavioral setup and pipeline of quantitative and qualitative behavior analysis, and we have tested 489 six-week-old Astyanax larvae. The blind, dark-adapted morphs of the species showed markedly distinct basal swimming patterns and behavioral responses to odors, higher olfactory sensitivity, and a strong preference for alanine, as compared to their river-dwelling eyed conspecifics. In addition, we discovered that fish have an individual ‘swimming personality’, and that this personality influences their capability to respond efficiently to odors and find the source. Importantly, the personality traits that favored significant responses to odors were different in surface fish and cavefish. Moreover, the responses displayed by second-generation cave × surface F2 hybrids suggested that olfactory-driven behavior and olfactory sensitivity is a quantitative genetic trait. Our findings show that olfactory processing has rapidly evolved in cavefish at several levels: detection threshold, odor preference, and foraging behavior strategy. Cavefish is therefore an outstanding model to understand the genetic, molecular, and neurophysiological basis of sensory specialization in response to environmental change.

Quantitative Analysis of Lithium-Ion Battery Eruption Behavior in Thermal Runaway

With the widespread adoption of battery technology in electric vehicles, there has been significant attention drawn to the increasing frequency of battery fire incidents. However, the jetting behavior and expansion force during the thermal runaway (TR) of batteries represent highly dynamic phenomena, which lack comprehensive quantitative description. This study addresses this gap by employing an enhanced experimental setup that synchronizes the video timing of cameras with a signal acquisition system, enabling the multidimensional quantification of signals, such as images, temperature, voltage, and pressure. It also provides a detailed description of the jetting behavior and expansion force characteristics over time for Li(Ni0.8Co0.1Mn0.1)O2 batteries undergoing thermal runaway in an open environment. The results from three experiments effectively identify key temporal features, including the timing of the initial jetting spark, maximum jetting velocity, jetting duration, explosion duration, and patterns of flame volume variation. This quantitative analytical approach proves effective across various battery types and conditions. The findings could offer scientific foundations and experimental strategies for parameter identification in fire prevention and thermal runaway model development.

Phase Transition Heat Transfer Enhancement of a Graphene-Coated Microporous Copper Surface Using Two-Step Electrodeposition Method

Abstract Owing to their exceptionally high thermal conductivity, there is a growing demand for graphene nanoparticles in phase transition heat transfer applications. This research delves into the exploration of various critical phenomena within the realm of surface science, specifically focusing on interactions at solid-liquid and liquid-liquid interfaces. In this work, graphene nanoparticles at varying concentrations are subject to electrochemical deposition on a microporous copper substrate to form graphene coated over microporous copper (GCOMC). The study encompasses a comprehensive analysis of surface characteristics, such as porosity, roughness, and wettability. Furthermore, the study involves the calculation of two key heat transfer metrics, the critical heat flux (CHF) and the boiling heat transfer coefficient (BHTC), through the execution of pool boiling experiments. The findings of this research underscore the remarkable superiority of GCOMC surfaces over their uncoated copper counterparts in terms of boiling performance. Particularly, the GCOMC surface showcases an impressive 87.5% enhancement in CHF and a 233% increase in BHTC compared to the bare copper surface. Furthermore, this investigation delves into a detailed quantitative analysis of bubble behavior, encompassing parameters such as bubble departure diameter, bubble departure frequency, and nucleation site density, employing high-speed camera techniques to comprehensively understand the underlying processes.

Dimensionality of locomotor behaviors in developing C. elegans.

Adult animals display robust locomotion, yet the timeline and mechanisms of how juvenile animals acquire coordinated movements and how these movements evolve during development are not well understood. Recent advances in quantitative behavioral analyses have paved the way for investigating complex natural behaviors like locomotion. In this study, we tracked the swimming and crawling behaviors of the nematode Caenorhabditis elegans from postembryonic development through to adulthood. Our principal component analyses revealed that adult C. elegans swimming is low dimensional, suggesting that a small number of distinct postures, or eigenworms, account for most of the variance in the body shapes that constitute swimming behavior. Additionally, we found that crawling behavior in adult C. elegans is similarly low dimensional, corroborating previous studies. Further, our analysis revealed that swimming and crawling are distinguishable within the eigenworm space. Remarkably, young L1 larvae are capable of producing the postural shapes for swimming and crawling seen in adults, despite frequent instances of uncoordinated body movements. In contrast, late L1 larvae exhibit robust coordination of locomotion, while many neurons crucial for adult locomotion are still under development. In conclusion, this study establishes a comprehensive quantitative behavioral framework for understanding the neural basis of locomotor development, including distinct gaits such as swimming and crawling in C. elegans.

Effect of Gas Environment on Metal‐Support Interactions of Supported Metal Catalysts

AbstractSupported‐metal catalysts, pivotal for industrial applications, have their catalytic properties affected by metal‐support interactions (MSIs), which notably influence both their electronic and geometric characteristics. Therefore, understanding internal and external factors that influence MSIs is crucial for the rational design of catalysts. Our minireview focuses on the effects of the gas environment on the MSIs, particularly the morphological changes in metal nanoparticles, the migrating behavior of reducible supports (strong metal‐support interaction), and the compositional rearrangement of the catalysts (reactive metal‐support interaction). Future directions are suggested to elucidate the fundamental aspects of gas environment induced structural reconstruction of catalysts, including the quantitative analysis of dynamic behavior of both the surface and interface, atomic‐level insights into the structures of the metal, support, and interface under pertinent conditions through advanced in situ/operando characterization, and the in situ manipulation of structural reconstruction.

Tensile deformation behavior of triple heterogeneous microstructure comprising fine equiaxed/coarse equiaxed/columnar grains in AlCu/AlMgSc bimetal fabricated via dual-wire arc direct energy deposition

In this study, an AlCu/AlMgSc bimetallic alloy is prepared using a dual-wire arc direct energy deposition method and a triple heterogeneous microstructure (fine/coarse equiaxed grains/columnar grains) is constructed. Additionally, a quantitative comparative analysis of the deformation behavior of triple and dual heterogeneous microstructures during interrupted tensile testing is conducted, with emphasis on the effects of grain morphology and size on the tensile deformation mechanisms in the heterogeneous microstructure. Compared with the AlCu alloy with a double heterogeneous microstructure (equiaxed/columnar grain), the AlCu/AlMgSc bimetallic alloy exhibits a higher ultimate tensile strength of 301.4 ± 7.9 MPa, a yield strength of 181.3 ± 1.4 MPa, and an elongation of 9.7 % ± 1.3 %, which correspond to increases by 19.4 %, 21.2 %, and 24.4 %, respectively. Interrupted tensile testing is performed and a quasi-in-situ approach is employed to investigate the plastic deformation mechanisms of the triple heterogeneous microstructure during tensile deformation. The density of geometrically necessary dislocations (GNDs) in the fine equiaxed grains and the rate of GND accumulation during deformation, surpassed those observed in coarse equiaxed and columnar grains. Furthermore, in micrometer-sized equiaxed grains, the ability to accumulate GNDs decreases as the equiaxed grain size increases, and the equiaxed grains exhibit a higher capacity to accumulate GNDs compared with columnar grains. The triple heterogeneous microstructure provides a more favorable environment for trapping GNDs, thus resulting in enhanced strength and plastic deformation capabilities. This study offers guidance for the formulation and engineering application of heterogeneous microstructure alloys with diverse grain morphologies and multiple length scales. Additionally, novel approaches are introduced to enhance the strength and ductility of Al alloys.

Quantitative Analysis of Codeformation Behavior of Ceramic and Metallic Particle System

Quantitative Analysis of Codeformation Behavior of Ceramic and Metallic Particle System