Discrete Behavior Research Articles

Employees’ views on empathic behavior in the workplace: a bottom-up approach to understanding empathy

AbstractAlthough the empathy concept is relevant across all domains of human relations, it is often used in a vague and poorly defined way that limits its utility both in science and in real-world applications. Research indeed suggests that behaviors considered “empathic” vary across individuals and according to context. This research looked at the organizational context, by (a) in two studies, asking employees in many different work settings to rate a diverse list of workplace behaviors for how much each is empathic to them, and (b) in a third study, analyzing employees’ messages describing instances of fellow employees’ empathic behavior posted to their companies’ rewards platform. In Study 1 (N = 318), employees in different companies responded to a list of 44 discrete behaviors, and in Study 2 (N = 234), employees responded to the same behaviors as well as 25 more. In both studies, two conceptually different, but empirically related, types of empathy emerged, which we labeled Emotional Sensitivity and Professionalism. In Study 3, we coded for these two dimensions in 1,497 messages sent by employees on a company rewards platform where they described “empathic” workplace behaviors by co-workers. Results of all three studies suggest that in the workplace, behavioral manifestations of “empathy” extend beyond conventional notions of personal responsiveness to include task functions, thus demonstrating that “empathy” in the real world covers surprisingly wide territory. The research shows that context matters in discussions of empathy and provides a concrete vocabulary for scholars and organizations to use in research on workplace culture.

Ethogram of the Domestic Cat

The existing domestic cat literature predominantly contains lists detailing its behaviour. However, these lists are neither specific enough for domestic cats nor general enough for all behaviours on a macro level of the domestic cat. Furthermore, the majority of studies lack illustrations. Therefore, we have developed a comprehensive ethogram of the domestic cat and scalable schematic representations of the behaviour units. We evaluated observational data from free-roaming cats and cats from private households using ad libitum and focal animal sampling (video material 55.31 h, n = 170 animals). In addition, we used the leading literature and detailed anatomical studies to create systematic categories and morphologically correct drawings. A total of 117 discrete behaviours were recorded and divided into 12 categories. The description of each behaviour includes a name, a word definition, an ethological classification and a schematic illustration (excluding the category devoted to vocalisations). An ethogram is needed to better understand the behavioural repertoire of healthy domestic cats and to facilitate the design phase of further investigations. This document can help to better distinguish species-appropriate behaviours and body postures from those behaviours and poses that indicate chronic pain, stress or discomfort.

Maximizing reachability probabilities in rectangular automata with random events

This paper introduces two stochastic variants of rectangular automata. First, rectangular automata with random events (RAE) are introduced, which semantically embed random events. Second, in rectangular automata with random clocks (RAC), the dynamics of random events are explicitly modeled as stopwatches which are called random clocks. We show that RAE can be transformed into RAC maintaining time- and jump-bounded reachability. Both modeling variants incorporate time-induced nondeterminism on discrete behavior and nondeterminism in the dynamic behavior. The difference between RAE and RAC lies in the modeling of the random events: while RAE semantically ensure that random events are correctly handled via stochastic guards, in RAC it is the responsibility of the modeler to ensure, e.g., that random clocks are enabled and disabled such that the resulting random delay correctly models the desired random event. However, the advantage of RAC is that existing methods for nonstochastic rectangular automata can directly be applied to RAC to compute the reachable state space. We then propose an algorithm to maximize reachability probabilities for RAC with history-dependent prophetic scheduling. Specifically, we use a backward refinement approach to identify the maximum prophetic scheduler and prove the correctness of the proposed method. The feasibility of the presented approach is illustrated on a scalable model and the results computed with our tool RealySt are validated against the tool ProHVer.

Economic mobility and parents’ opportunity hoarding

Creating opportunities for people to achieve socioeconomic mobility is a widely shared societal goal. Paradoxically, however, achieving this goal can pose a threat to high-socioeconomic-status (SES) people as they look to maintain their privileged positions in society for both them and their children. Two studies evaluate whether this threat manifests as "opportunity hoarding" in which high-SES parents adopt attitudes and behaviors aimed at shoring up their families' access to valuable educational and economic resources. The current paper provides converging evidence for this hypothesis across two studies conducted with 2,557 American parents. An initial correlational study demonstrated that believing that socioeconomic mobility is possible was associated with high-SES parents being more inclined to attempt to secure valuable educational and economic resources for their children, even when doing so came at the cost of low-SES families. Specifically, high-SES parents with stronger beliefs in socioeconomic mobility exhibited decreased support for redistributive policies and viewed engaging in discrete behaviors that would unfairly advantage their children (e.g., allowing them to misrepresent their identities on school and job applications) as more acceptable relative to both low-SES parents with similar beliefs and high-SES parents who were less optimistic about socioeconomic mobility. A subsequent experimental study established these relationships causally by comparing parents' responses to different types of socioeconomic mobility. Together, the current findings merge insights across psychology and economics to deepen understandings of the processes through which societal inequities emerge and persist, especially during times of apparently abundant opportunity.

On hybrid dynamical systems of differential–difference equations

In this paper, we define and study a class of linear hybrid dynamical systems characterized by differential–difference equations. We introduce two operators that facilitate the analysis of these systems and derive explicit formulas for their solutions. We examine the transfer function matrix and characteristic polynomial to assess stability. Our theoretical findings are supported by numerical examples, demonstrating their application in power systems stability analysis. Specifically, we substantiate our theory within the context of power systems stability analysis, incorporating elements of discrete behavior.

Classification of African ground pangolin behaviour based on accelerometer readouts: validation of bio-logging methods

BackgroundUnderstanding how free-ranging animals behave can help in the design of optimal management strategies to both conserve species and enable individuals to express natural behaviours, maximising welfare. Animal-borne accelerometers passively collect data on body acceleration which can be interpreted to quantify behaviour. Accelerometers are increasingly used in behavioural research, however validation of accelerometer readouts to enable classification of discrete behaviours is required for each species. Pangolins are a heavily trafficked clade of mammals, all of which are considered vulnerable to extinction. They are also under-researched, with little known about their behaviour in the wild. In this study, we present the first validation of behavioural classification based on accelerometer readouts for a pangolin species; the ground pangolin (Smutsia temminckii).ResultsWe present a standardised protocol for attaching accelerometers to pangolins to minimise the impact of devices on welfare. We match the readouts from accelerometers to behaviours defined through video observations. Using a random forest classification, we defined five discrete behaviours (walking, digging, feeding, investigating ground, and stationary, accuracy of 85%) and three activity levels (low, medium, and high, accuracy of 94%) from accelerometer readouts. We determine optimal sampling frequency and window length (50 Hz and five seconds for discrete behaviour, 10 Hz and seven seconds for activity level). We then deploy accelerometers and classify the behaviour of three free-ranging pangolins for between two and four days. We find considerable variation in peak daily activity between free-ranging pangolins with different individuals displaying nocturnal and crepuscular behaviour. We also find that pangolins spend the majority of their time (between 62 and 71%) at rest.ConclusionThe methods we present will enable the quantification of ground pangolin behaviour in the wild to improve our understanding of the species’ ecology and help inform conservation efforts. This will also help to improve our fundamental understanding of animal behaviour and ecology.

Computational engine for finite element digital twins of structural dynamics via motion data

Typical structural health monitoring systems employ limited numbers of sensors capable of measuring discrete local behaviours. However, practical challenges arise as these sensor arrays cannot cover all local areas of interest. To address this challenge, this article introduces a novel method for twinning structural dynamic behaviour by constructing a finite-element-model-based digital twin, enabling the observation of non-sensor positions crucial for downstream tasks. The approach utilises streaming monitoring data, e.g., displacement and acceleration, as external dynamic loads to reproduce the dynamic response of the entire physical structure. Subsequently, the dynamic behaviour of specific non-sensor locations can be extracted from the digital twin. The method is formulated as a local-global-local procedure. To validate the proposed approach, two virtual experiments were conducted on: 1) a simply supported Euler-Bernoulli beam subjected to static loads and 2) a high-fidelity finite element model of a composite bridge carrying dynamic traffic loads. The results demonstrate remarkable accuracy in reproducing both global and local behaviours, facilitating observations at non-sensor positions for downstream estimations.

A computable and compositional semantics for hybrid systems

Hybrid Systems are systems having a mixed discrete and continuous behaviour that cannot be characterised faithfully using either discrete or continuous models only.Due to the intrinsic complexity of hybrid systems, it is highly desirable to describe them compositionally, where large systems are seen as the composition of several simpler subparts that are studied independently. Furthermore, since several problems, including reachability, are undecidable for hybrid systems, the availability of approximate decision procedures is another important feature.In this paper, we propose a purely behavioural formalism for hybrid systems that is compositional and supports approximate decision procedures. The formalism is abstract and sufficiently general to subsume or be a semantic framework for most of the concrete formalisms or languages proposed in the literature.

Long-time properties of generic Floquet systems are approximately periodic with the driving period

A Floquet quantum system is governed by a Hamiltonian that is periodic in time. Consider the space of piecewise time-independent Floquet systems with (geometrically) local interactions. We prove that for all but a measure zero set of systems in this space, starting from a random product state, many properties (including expectation values of observables and the entanglement entropy of a macroscopically large subsystem) at long times are approximately periodic with the same period as the Hamiltonian. Thus, in almost every Floquet system of arbitrarily large but finite size, discrete time-crystalline behavior does not persist to strictly infinite time.

Female oviposition preferences and larval behavior of the Aedes aegypti mosquito (Linnaeus, 1762) exposed to predator cues (Odonata: Libellulidae)

The reproductive success of mosquitoes is heavily influenced by females' ability to select suitable oviposition sites for the proper development of their offspring. Many of these potential habitats may harbor predators, and the detection of these predators is crucial for assessing the risk of predation, which can, in turn, influence the behavior of the prey. However, there are often trade-offs to consider, which can impact the life history of these organisms. In our study, we investigated the oviposition preferences and larval behavioral responses of the Aedes aegypti mosquito when exposed to cues from predators and the actual presence of predation by Libellulidae (Odonata) larvae. We observed the mosquito's choices regarding oviposition with and without predation cues for a duration of ten weeks, following 48 hours of exposure. Additionally, we measured larval behavior across various treatments, including those with predation cues, predator cues, the presence of larvae, and controls with only water. Our findings revealed that the highest preference for oviposition occurred in containers with high organic matter content, regardless the presence of both predator cues and actual predators. Furthermore, we noted significant changes in larval behavior in response to predation cues, including evasive behaviors. When facing the risk of predation, larvae spent more time near the container's edges and exhibited discrete feeding behaviors or avoidance of the risk of predation. Conversely, in the absence of predation risk, larvae explored the entire container, swimming vigorously. These results highlight the significance of anti-predatory behaviors triggered by the recognition of predation cues in the context of Ae. aegypti's reproductive success.

Emergence of collective behaviours from local Voronoi topological perception.

This article addresses how diverse collective behaviours arise from simple and realistic decisions made entirely at the level of each agent's personal space in the sense of the Voronoi diagram. We present a discrete-time model in two dimensions in which individual agents are aware of their local Voronoi environment and may seek static target locations. In particular, agents only communicate directly with their Voronoi neighbours and make decisions based on the geometry of their own Voronoi cells. With two effective control parameters, it is shown numerically to capture a wide range of collective behaviours in different scenarios. Further, we show that the Voronoi topology facilitates the computation of several novel observables for quantifying discrete collective behaviours. These observables are applicable to all agent-based models and to empirical data.

Artificial neural network-based sequential approximate optimization of metal sheet architecture and forming process

Abstract This paper introduces a sequential approximate optimization method that combines the finite element method (FEM), dynamic differential evolution (DDE), and artificial neural network (ANN) surrogate models. The developed method is applied to address two optimization problems. The first involves metamaterial design optimization for metal sheet architecture with binary design variables. The second pertains to optimizing process parameters in multi-stage metal forming, where the discrete nature arises owing to changing tool geometries across stages. This process is highly nonlinear, accumulating contact, geometric, and material nonlinear effects discretely through forming stages. The efficacy of the proposed optimization method, utilizing ANN surrogate models, is compared with traditionally used polynomial response surface (PRS) surrogate models, primarily based on low-order polynomials. Efficient learning of ANN surrogate models is facilitated through the FEM and Python integration framework. Initial data for surrogate model training is collected via Latin hypercube sampling and FEM simulations. DDE is employed for sequential approximate optimization, optimizing ANN or PRS surrogate models to determine optimal design variables. PRS surrogate models encounter challenges in dealing with nonlinear changes in sequential approximate optimization concerning discrete characteristics such as binary design variables and discrete nonlinear behavior found in multi-stage metal forming processes. Owing to the discrete nature, PRS surrogate models require more data and iterations for optimal design variables. In contrast, ANN surrogate models adeptly predict nonlinear behavior through the activation function's characteristics. In the optimization problem of Metal Sheet Architecture for design target C, the ANN surrogate model required an average of 4.6 times fewer iterations to satisfy stopping criteria compared to the PRS surrogate model. Furthermore, in the optimization of multi-stage deep drawing processes, the ANN surrogate model required an average of 6.1 times fewer iterations to satisfy stopping criteria compared to the PRS surrogate model. As a result, the sequential global optimization method utilizing ANN surrogate models achieves optimal design variables with fewer iterations than PRS surrogate models. Further confirmation of the method's efficiency is provided by comparing Pearson correlation coefficients and locus plots.

A fear conditioned cue orchestrates a suite of behaviors in rats.

Pavlovian fear conditioning has been extensively used to study the behavioral and neural basis of defensive systems. In a typical procedure, a cue is paired with foot shock, and subsequent cue presentation elicits freezing, a behavior theoretically linked to predator detection. Studies have since shown a fear conditioned cue can elicit locomotion, a behavior that - in addition to jumping, and rearing - is theoretically linked to imminent or occurring predation. A criticism of studies observing fear conditioned cue-elicited locomotion is that responding is non-associative. We gave rats Pavlovian fear discrimination over a baseline of reward seeking. TTL-triggered cameras captured 5 behavior frames/s around cue presentation. Experiment 1 examined the emergence of danger-specific behaviors over fear acquisition. Experiment 2 examined the expression of danger-specific behaviors in fear extinction. In total, we scored 112,000 frames for nine discrete behavior categories. Temporal ethograms show that during acquisition, a fear conditioned cue suppresses reward seeking and elicits freezing, but also elicits locomotion, jumping, and rearing - all of which are maximal when foot shock is imminent. During extinction, a fear conditioned cue most prominently suppresses reward seeking, and elicits locomotion that is timed to shock delivery. The independent expression of these behaviors in both experiments reveals a fear conditioned cue to orchestrate a temporally organized suite of behaviors.

Machine Learning Methods and Visual Observations to Categorize Behavior of Grazing Cattle Using Accelerometer Signals.

Accelerometers worn by animals produce distinct behavioral signatures, which can be classified accurately using machine learning methods such as random forest decision trees. The objective of this study was to identify accelerometer signal separation among parsimonious behaviors. We achieved this objective by (1) describing functional differences in accelerometer signals among discrete behaviors, (2) identifying the optimal window size for signal pre-processing, and (3) demonstrating the number of observations required to achieve the desired level of model accuracy,. Crossbred steers (Bos taurus indicus; n = 10) were fitted with GPS collars containing a video camera and tri-axial accelerometers (read-rate = 40 Hz). Distinct behaviors from accelerometer signals, particularly for grazing, were apparent because of the head-down posture. Increasing the smoothing window size to 10 s improved classification accuracy (p < 0.05), but reducing the number of observations below 50% resulted in a decrease in accuracy for all behaviors (p < 0.05). In-pasture observation increased accuracy and precision (0.05 and 0.08 percent, respectively) compared with animal-borne collar video observations.

An algebraic approach to simulation and verification for cyber-physical systems with shared-variable concurrency

Cyber-Physical systems (CPS), containing discrete behaviors of the cyber and continuous behaviors of the physical, have gained wide applications in many fields. Since CPS subsume the intersection of cyber systems and physical processes, the traditional modeling languages which merely include discrete variables are no longer applicable to CPS. Accordingly, a shared variable language called CPSLsc was proposed to specify CPS. In this paper, we elaborate the algebraic semantics for this language, so that every program of CPSLsc can be converted into a unified form called guarded choice form and the sequentialization of parallel programs is achieved. Additionally, we formalize the algebraic semantics in the rewriting engine Real-Time Maude. With the algebraic laws constructed, for every program specified with CPSLsc, we can simulate its execution step by step. Furthermore, automatic transformation and execution are attained. As a consequence, if the program and its initial data state are provided, the corresponding trace of data states during execution can be generated. In the light of the generated trace, automatic verification can be carried out as well.

Examining Congestion Pricing Scheme Effectiveness Using the Travel Time Congestion Index

This study investigated the effectiveness of congestion pricing (CP) using the travel time congestion index (TTCI), a congestion assessment tool, in Hyderabad, India. Initially, a set of hypothetical mode choice scenarios under the CP scheme were designed to collect car users’ perceptions based on a stated preference (SP) experiment. Based on the SP survey data, discrete travel behavior models were developed to estimate the probable modal trade-off among cars, two-wheelers, and public buses under the generated CP scenarios. Using the existing traffic, geometric, and land-use data from the most congested corridors of the study city, TTCI values were estimated for the base and future conditions, followed by commuter volume estimation for the different conditions using vehicle occupancy factors. Further, the commuter volume derived from modal trade-off under CP scenarios was converted into traffic volume for the identified congested corridors. Finally, the TTCI values were re-estimated using the final traffic volume and compared across worst, best-worst (intermediate), and best case CP scenarios for the base and future years. An annual average growth of 5% in traffic volume was considered. The results show a significant improvement in TTCI values across all identified corridors under CP implementation, indicating its effectiveness toward congestion alleviation. Such demonstration of CP effectiveness could play a major role in making CP a successful travel demand management measure for cities burdened with congestion.

Discrete energy behavior of Timoshenko system with Cattaneo’s law

Discrete energy behavior of Timoshenko system with Cattaneo’s law

Experimental and numerical study of photocatalysis in Taylor photoreactors with carbon-quantum-dots/BiOCl as catalysts

A comprehensive CFD model considering the photo radiation, discrete phase dispersion, flow behaviors and photoreactions was built for Taylor‐Couette reactors (TCRs). The carbon quantum dots (CQDs) modified BiOCl composites which were responsive to visible light were synthesized and used as the catalysts for photodegradation of organic pollutants. The degradation kinetic parameters were obtained experimentally. The validated model was used to investigate the effects of the key parameters of TCRs such as rotation speed, light intensity and catalyst properties. The interactions among the photo radiation field, catalyst distribution, flow field, and degradation efficiency were discussed. The results showed the addition of 8 ωt % CQDs/BiOCl enhanced the degradation efficiency to 97% as compared to pure BiOCl, while the catalyst dosage had a limited impact on degradation performance. This work provides engineering insights in the CQDs-based photocatalysis, and the proposed model can serve as an effective tool for the design and scale-up of the TCRs.

The discrete and continuum behaviour of railway ballast

The mechanics of coarse-grained geomaterials have traditionally been examined from a continuum mechanics standpoint, but this has led to ever more complex constitutive models as an increasing number of novel aspects of behaviour are investigated. For this reason, there is a tendency to move towards discrete approaches. Such approaches require accurate definition and modelling of the particle shapes, for which considerable progress has been made, and also the contact mechanics between particles, about which little is known. For very coarse materials such as railway ballast, our understanding at the continuum scale has been hampered further by the technical difficulties in the laboratory testing so that the very small strain behaviour has been difficult to define with accuracy. New apparatus and techniques will be described to test ballast at both the continuum and particulate scales. These allow the small strain stiffness to be defined with accuracy in triaxial tests and to carry out precise particle-to-particle contact tests. At the particle contact scale, the behaviour is dominated by the roughness of the particles and their relatively sharp contacts, so that plasticity and particle wear predominate, which both change the contact properties significantly. It is the contact plasticity that then controls the decay in continuum stiffness with strain. The work emphasises the inadequacy of using simple linear and/or elastic DEM models calibrated from macro-scale tests rather than deriving the correct contact behaviour directly.

SysML4GDPSim: A SysML Profile for Modeling Geometric Deviation Propagation in Multistage Manufacturing Systems Simulation

In recent years, paradigms like production quality or zero-defect manufacturing have emerged, highlighting the need to improve quality and reduce waste in manufacturing systems. Although quality can be analyzed from various points of view during different stages of a manufacturing system’s lifecycle, this research focuses on a multidomain simulation model definition oriented toward the analysis of productivity and geometric quality during early design stages. To avoid inconsistencies, the authors explored the definition of descriptive models using system modeling language (SysML) profiles that capture domain-specific semantics defining object constraint language (OCL) rules, facilitating the assurance of model completeness and consistency regarding this specific knowledge. This paper presents a SysML profile for the simulation of geometric deviation propagation in multistage manufacturing systems (SysML4GDPSim), containing the concepts for the analysis of two data flows: (a) coupled discrete behavior simulation characteristic of manufacturing systems defined using discrete events simulation (DEVS) formalism; and (b) geometric deviation propagation through the system based on the geometrical modeling of artifacts using concepts from the topologically and technologically related surfaces (TTRS) theory. Consistency checking for this type of multidomain simulation model and the adoption of TTRS for the mathematical analysis of geometric deviations are the main contributions of this work, oriented towards facilitating the collaboration between design and analysis experts in the manufacturing domain. Finally, a case study shows the application of the proposed profile for the simulation model of an assembling line, including the model’s transformation to Modelica and some experimental results of this type of analysis.