Discrete Behavior Research Articles

Numerical reproduction and prediction of rock failure behavior: From short term to long term

Rock is a natural geological material; its time-dependent failure presents complex nonlinear and random characteristics under the interaction effects of various mechanisms. Previous research focuses on either short-term or long-term failure behavior. Here, we develop a new unified numerical model to address short-term and long-term rock failures in one framework. Viscoelastic, viscoplastic, and damage mechanisms are considered and integrated under thermodynamic consistency. The corresponding parameters feature definite physical meanings. Mean-field homogeneous (HO) analysis and mesoscale-based heterogeneous (HE) analysis are proposed. Numerical schemes are validated via several representative examples. In both short-term and long-term situations, the proposed model can reproduce and predict time-dependent failure behaviors (such as the failure mode, strength, and failure time). Rock failure is controlled by various energy dissipation components and exhibits prominent time-dependent characteristics at different time scales. The effect of mesoscopic details sustainably enlarges as time prolongs. Furthermore, the fluctuation in material properties at the mesoscale profoundly affects the macroscopic nonlinear, stochastic, and discrete behavior. Our research provides insights into time-dependent rock failure and catastrophe forecast.

Identifying Intraoperative Behaviors Associated With Surgical Resident Teachability

The resident-attending dyad influences the intraoperative training of surgery residents. To better understand the role of trainees within the dyad, we hypothesized there is a measurable concept of "teachability," a combination of the trainee's observed skills and behaviors with their performance. This study aims to define teachability and identify discrete intraoperative behaviors that contribute to this concept. We posit that residents who are active learners as demonstrated by asking questions, proposing next steps, and initiating purposeful actions have higher teachability. Previously recorded videos from 26 laparoscopic inguinal hernia repairs performed by two PGY-5 general surgery residents at a Midwest tertiary care center were qualitatively reviewed for intraoperative behaviors. A summative content analysis identified behaviors associated with increased teachability and improved operative performance assessment scores. Average frequencies of intraoperative behaviors for resident 1 and 2 (R1 and R2) were not significantly different, although R2 asked more medical knowledge and technical questions. While the rate of attending feedback was similar for both residents (x=3.82 vs 3.40, p=0.646), R1 consistently incorporated feedback (x=2.27 vs 0.40, p=0.001) whereas R2 needed frequent prompting (x=2.45 vs 1.55, p=0.239). R1 scored higher in all but one operative performance assessment category, including overall performance (x=4.17 vs 2.93, p=0.007), but R2 had a larger magnitude of overall improvement (+1 vs +2). Teachability is a dynamic component of the resident-attending dyad. While intraoperative active learning behaviors do not appear to be associated with teachability, asking questions may increase the magnitude of improvement in performance. Most importantly, the ability to incorporate intraoperative feedback in real time seems to be a critical aspect of teachability and warrants further research.

Parental Imitations and Expansions of Child Language Predict Later Language Outcomes of Autistic Preschoolers.

Both the amount and responsiveness of adult language input contribute to the language development of autistic and non-autistic children. From parent–child interaction footage, we measured the amount of adult language input, overall parent responsiveness, and six discrete parent responsive behaviours (imitations, expansions, open-ended questions, yes/no questions, comments and acknowledgements) to explore which types of responsiveness predicted autistic preschoolers’ language five months later, after controlling for adult language input. We found expansions and particularly imitations to be more important for later language than overall responsiveness. This study emphasises the need to capture what exactly about parent language input influences child language acquisition, and adds to the evidence that imitating and expanding early language might be particularly beneficial for autistic preschoolers.

DEM Investigation of Discrete Heat Transfer Behavior of the Grinding Media in Ball Mills

This study presented a numerical model for the quantitative assessment of the heat transfer behavior of grinding media inside a ball mill. Effects of various mill speeds, grinding media filling, and the number of lifters on heat transfer were studied and verified by comparing the experimental results and the numerical simulations calculated by DEM (Discrete Element Method). The results show that the heat transfer of grinding media has a strong sensitivity to the variation of the mill speed, grinding media filling, and the number of lifters. The optimum grinding conditions for heat transfer behavior can be determined in terms of the temperature field of the grinding media. The maximum temperature rise of grinding media occurs at a range from 70% to 80% of critical speed. The maximum average temperature of grinding media up to 295.057 K appears at the grinding media filling 25% and the number of lifters 12. Subsequently, validation experiments are carried out to validate the numerical simulation results. The experimental results are closer to the simulation results, indicating the reasonability of the heat transfer model.

Bias in measurement of autism symptoms by spoken language level and non-verbal mental age in minimally verbal children with neurodevelopmental disorders.

Increasing numbers of children with known genetic conditions and/or intellectual disability are referred for evaluation of autism spectrum disorder (ASD), highlighting the need to refine autism symptom measures to facilitate differential diagnoses in children with cognitive and language impairments. Previous studies have reported decreased specificity of ASD screening and diagnostic measures in children with intellectual disability. However, little is known about how cognitive and language abilities impact the measurement of specific ASD symptoms in this group. We aggregated a large sample of young children (N = 1196; aged 31–119 months) to examine measurement invariance of ASD symptoms among minimally verbal children within the context of the Autism Diagnostic Observation Schedule (ADOS) Module 1. Using confirmatory factor analysis (CFA) and moderated non-linear factor analysis (MNLFA), we examined how discrete behaviors were differentially associated with the latent symptom domains of social communication impairments (SCI) and restricted and repetitive behaviors (RRB) across spoken language levels and non-verbal mental age groupings. While the two-factor structure of SCI and RRB held consistently across language and cognitive levels, only partial invariance was observed for both ASD symptom domains of SCI and RRB. Specifically, four out of the 15 SCI items and one out of the three RRB items examined showed differential item functioning between children with “Few to No Words” and those with “Some Words”; and one SCI item and one RRB item showed differential item functioning across non-verbal mental age groups. Moreover, even after adjusting for the differential item functioning to reduce measurement bias across groups, there were still differences in ASD symptom domain scores across spoken language levels. These findings further underscore the influence of spoken language level on measurement of ASD symptoms and the importance of measuring ASD symptoms within refined spoken language levels, even among those with minimal verbal abilities.

Merging technologies and supervised classification methods to quantify capture behavior on hook-and-line

Animal behavior varies in response to capture between/within species and fisheries, and its expression may contribute to incidental mortality when behaviors result in physiological ramifications that cannot be resolved. However, this relationship between capture behavior and animal health is poorly understood, and it remains a logistical challenge to evaluate behavior during capture. We describe an experimental technique that characterizes and quantifies capture behavior in hook-and-line fisheries. This technique includes (1) simultaneously monitoring the behavioral response to capture with accelerometers and cameras, (2) characterizing behavior from video footage and linking discrete behaviors to acceleration data, and (3) predicting behavior based solely on acceleration data using an ensemble of supervised classification methods. We captured oceanic whitetip sharks, Carcharhinus longimanus, with experimental (hook-and-line) gear to test these techniques (n = 38 capture events), with capture durations ranging from 4 to 68 min. In all, 145,589 tri-axial acceleration observations were collected across these events, including simultaneous video footage (six hours total) from 10 capture events. Three discrete capture behaviors were characterized: steady swimming, a high-energy response consisting of thrashing and burst swimming, and a loss of body orientation while hanging motionless from the gear. The latter two behaviors can lead to physiological stress if exhibited for prolonged periods. Our trained ensemble of supervised classification methods successfully predicted behaviors from acceleration data with up to 95.2% accuracy. This technique provides a better understanding of the behavioral response to hook-and-line capture and, if paired with health or fate assessments, can characterize the influence of behavior on mortality. Our technique also provides a method for predicting behavior based on acceleration data alone, which can be more feasible to collect across the spectrum of fishing conditions and practices within a fishery. Such information will assist in understanding how species respond to capture on hook-and-line gear and in the formulation of species- and fishery-specific strategies for mitigating mortality.

Twinning dynamics in nanoscale body-centered cubic tungsten

The non-planar core structure of screw dislocations in body-centered cubic (BCC) metals strongly influences its twinning dynamics, resulting in a minimum embryo size of six-layers {112} planes and discrete three-layers thickening behavior. By considering the energetically-stable three-layers “zonal dislocation” as a unit of twinning front, we rationalize such discrete twinning behavior to the two units for twin embryo and one unit for growth, in consistent with the description of classical twinning theory.

Long-Range Nonequilibrium Coherent Tunneling Induced by Fractional Vibronic Resonances.

We study the influence of a linear energy bias on a nonequilibrium excitation on a chain of molecules coupled to local vibrations (a tilted Holstein model) using both a random-walk rate kernel theory and a nonperturbative, massively parallelized adaptive-basis algorithm. We uncover structured and discrete vibronic resonance behavior fundamentally different from both linear response theory and homogeneous polaron dynamics. Remarkably, resonance between the phonon energy ℏω and the bias δϵ occurs not only at integer but also fractional ratios δϵ/(ℏω) = m/n, which effect long-range n-bond m-phonon tunneling. These observations are reproduced in a model calculation of a recently demonstrated Cy3 system, and the effect of dipole-dipole-type non-nearest-neighbor coupling and vibrationally relaxed initial states is also considered. Potential applications range from molecular electronics to optical lattices and artificial light harvesting via vibronic engineering of coherent quantum transport.

Reconfigurable multivalued memristor FPGA model for digital recognition

AbstractCompared with the traditional memristor, it's more significant to research the multivalued memristor in improving the stability and reliability of memristive neural networks. Developing some multivalued memristor emulators is highly attractive since the fabrication and integration of the memristor are not mature at present. This work presents a behavioral‐level model of a general multivalued memristor FPGA that exhibits continuous or discrete behavior, similar to electrochemical metallization memories. The proposed solution has been successfully synthesized and verified on a Xilinx ZYNQ‐7000 FPGA XQ7Z020 with less than 1% hardware utilization. Additionally, to test the synaptic function of the memristor model in artificial neural networks, this paper constructs a quantized artificial neural network based on eight‐valued memristors in FPGA. In the training of the neural network, the pixel values of the images and the network weights are quantized and then mapped to the input voltage and conductance respectively of the memristor during the forward propagation. The experimental results show that the memristive network circuit achieves 92.8% recognition accuracy for 10,000 MNIST images.

Experimental and theoretical study on horizontal flame spread through arrays of wooden dowels

AbstractFlame spread along discrete fuel element is of great interest for both fundamental science and fire prevention, whose combustion properties may be different from those of homogenous materials. It has been a long time for researchers in fire science to find a simple and effective method to construct a discrete flame spread model. This work was motivated by the research of 2‐D horizontal discrete flame spread behaviors with different spacings and rows, establishing the prediction model of ignition time and global mass loss rate (MLR). In this work, burning characteristics of the 2‐D discrete flame spread were experimentally studied with six different row numbers (1–11 with an interval of 2) of cylindrical dowels (birch wood, 3 mm diameter × 50 mm height) under three selected spacings (6, 7, and 8 mm). Based on the heat transfer model developed, the theoretical models of ignition time and MLR were obtained and validated. Moreover, combined with previous studies, the numerical correlation between dimensionless flame height and dimensionless heat release rate for the 2‐D horizontal discrete flame spread scenario was established. This study provided an insight into the horizontal discrete flame spread mechanism in the aspect of heat and mass transfer, which may be applied in the prediction and assessment of discrete fuel fires in reality.

Identifying critical thinking skills used by experts versus novices to construct argument maps in a computer-aided mapping tool

Research shows that using computer-aided mapping tools improves critical thinking skills, but prior research provides limited evidence to show how the use of specific critical thinking skills increases map quality. This qualitative study observed 4 experts and 5 novices use a computer-aided mapping tool to construct argument maps. The analysis of video recordings with think-aloud protocols and retrospective interviews revealed the use of a five-step argument mapping process (read claims, position conclusion, position claims, link claims, revise links) with the experts using a more sequential application of the five-step process and producing more accurate maps than novices. The novices showed the tendency to position and link claims as a joint action, making map revision more cumbersome. The experts exhibited the tendency to work backward from conclusion to claim while the novices exhibited the reverse tendency. This study’s findings identify processes that differentiate experts from novices and validate specific thinking skills that can be used to improve map quality, and how these processes can be operationalized in terms of discrete mapping behaviors performed on screen that can be mined and analyzed in mapping tools to assess and diagnose students’ mapping skills.

Atomic-scale friction between single-asperity contacts unveiled through in situ transmission electron microscopy

Friction and wear are detrimental to functionality and reduce the service life of products with mechanical elements. Here, we unveil the atomic-scale friction of a single tungsten asperity in real time through a high-resolution transmission electron microscopy investigation of a nanocontact in countermotion, induced through a piezo actuator. Molecular dynamics simulations provide insights into the sliding pathway of interface atoms and the dynamic strain/stress evolution at the interface. We observe a discrete stick-slip behaviour and an asynchronous process for the accumulation and dissipation of the strain energy together with the non-uniform motion of interface atoms. Our methodology allows for studying in situ atomic-friction phenomena and provides insights into friction phenomena at the atomic scale.

Finite-Time Pinning Synchronization Control for T-S Fuzzy Discrete Complex Networks with Time-Varying Delays via Adaptive Event-Triggered Approach.

This paper is concerned with the adaptive event-triggered finite-time pinning synchronization control problem for T-S fuzzy discrete complex networks (TSFDCNs) with time-varying delays. In order to accurately describe discrete dynamical behaviors, we build a general model of discrete complex networks via T-S fuzzy rules, which extends a continuous-time model in existing results. Based on an adaptive threshold and measurement errors, a discrete adaptive event-triggered approach (AETA) is introduced to govern signal transmission. With the hope of improving the resource utilization and reducing the update frequency, an event-based fuzzy pinning feedback control strategy is designed to control a small fraction of network nodes. Furthermore, by new Lyapunov–Krasovskii functionals and the finite-time analysis method, sufficient criteria are provided to guarantee the finite-time bounded stability of the closed-loop error system. Under an optimization condition and linear matrix inequality (LMI) constraints, the desired controller parameters with respect to minimum finite time are derived. Finally, several numerical examples are conducted to show the effectiveness of obtained theoretical results. For the same system, the average triggering rate of AETA is significantly lower than existing event-triggered mechanisms and the convergence rate of synchronization errors is also superior to other control strategies.

A novel quantum-behaved binary firefly algorithm with gravitational search algorithm to optimize the features for human activity recognition

This paper proposes a novel optimization approach of the quantum-behaved binary firefly algorithm with a gravitational search algorithm (QBFA-GSA) for discrete feature optimization, which is utilized for the application of human activity recognition. The firefly algorithm (FA) and gravitational search algorithm (GSA) are recently introduced meta-heuristic algorithms that are efficient for optimizing the continuous solution set. The binarized version of the proposed approach enables it to optimize the discrete features and quantum behavior ensures the better diversity of the final optimized features. In the proposed QBFA-GSA approach, the features are optimized by following the combined advantageous attributes of FA and GSA in which the search space is initially explored by firefly agents until the current firefly finds the brighter firefly and further these agents adapt the attributes of GSA to complete the process. These optimized features are passed to deep neural networks (DNN) for the classification of human activities. Here, DNN models of deep convolutional neural networks (DCNN) and DCNN extended with residual blocks (DCNN-RB) are incorporated. The evaluation experiments for human activity recognition are conducted on a benchmark dataset of UCF-101, which is a composition of 101 different activities. The experimental results of the proposed QBFA-GSA approach are superlative to state-of-art techniques, which indicate that the proposed approach is efficient to optimize the features.

Emergence and Dynamical Stability of a Charge Time-Crystal in a Current-Carrying Quantum Dot Simulator.

Periodically driven open quantum systems that never thermalize exhibit a discrete time-crystal behavior, a nonequilibrium quantum phenomenon that has shown promise in quantum information processing applications. Measurements of time-crystallinity are currently limited to (magneto-) optical experiments in atom-cavity systems and spin-systems making it an indirect measurement. We theoretically show that time-crystallinity can be measured directly in the charge-current from a spin-less Hubbard ladder, which can be simulated on a quantum-dot array. We demonstrate that one can dynamically tune the system out and then back on a time-crystal phase, proving its robustness against external forcings. These findings motivate further theoretical and experimental efforts to simulate the time-crystal phenomena in current-carrying nanoscale systems.

An improved real-time collision-avoidance algorithm based on Hybrid A* in a multi-object-encountering scenario for autonomous surface vessels

Collision-avoidance algorithms for maritime autonomous surface vessels are increasingly being analyzed for challenging scenarios. However, the trade-off between the computation’s effectiveness and efficiency is always an intractable problem, especially in complex, multi-object-encountering cases. This paper proposes an improved Hybrid A* algorithm that searches a node map with discrete control behaviors as ‘movement options’. The real-time performance in maritime, multi-object- encountering scenarios is improved by narrowing the search space with the proposed pre-processing method, i.e., the collision velocity check (CVC). The following is incorporated within the mentioned approach: the compliance of the relevant rules in International Regulations for Preventing Collisions at Sea and the dynamics of the ship. A comparative study with various multi-target scenarios is conducted with a baseline method. Simulation results show the effectiveness of the proposed method. The use of the CVC significantly reduces the time of the computation with little reduction in the solution’s accuracy. Additionally, the proposed method is applied within a real-time simulation environment, which is fed by logged data collected during an actual sea trial.

Inconsistent response of biophysical characteristics in the western Bay of Bengal associated with positive Indian Ocean dipole

The Bay of Bengal (BoB) is known to have high primary productivity at its western margin during the Indian summer monsoon season (June–September). This higher coastal productivity is mainly caused due to the near-surface nutrient availability maintained by the local coastal upwelling process. The surface winds in the Indian Ocean significantly vary during El-Niño/La-Niña and Indian Ocean dipole (IOD). The current study examines the sea surface temperature (SST) and Chlorophyll-a (Chl-a) anomalies in the western BoB for the period of 18 years (2000 to 2017), using a coupled regional ocean biophysical model. All considered positive IOD (pIOD) years show discrete behavior of biophysical features in the western BoB. The co-occurrence years of pIOD and El-Niño modes are associated with contrast biophysical anomalies. In the analyzed pIOD events, the years 2006 and 2012 show an enhancement in the Chl-a anomalies whereas, the other two years (2015 and 2017) experience Chl-a decrement. The western BoB was anomalously warmer during the 2015 and 2017 pIOD years compared to the other two pIOD years (2006, 2012). This inconsistent response of biophysical features associated with pIOD years is investigated in terms of local surface flux (momentum, heat, and freshwater) changes over the western BoB. The combined impact of local surface flux changes during the individual years remains the major contributing factor affecting the upper-ocean stratification. Ultimately, the stratification changes are responsible for the observed inconsistent response of biophysical features by significantly altering the upper-ocean mixing, upwelling, and nutrient availability in the western BoB.

The initial response of females towards congeneric males matches the propensity to hybridise in Ophthalmotilapia

Cichlid radiations often harbour closely related species with overlapping niches and distribution ranges. Such species sometimes hybridise in nature, which raises the question how they can coexist. This also holds for the Tanganyika mouthbrooders Ophthalmotilapia ventralis and O. nasuta. Earlier studies found indications of asymmetrical hybridisation with females of O. ventralis accepting males of O. nasuta, but not the other way around. We hypothesised that this was due to differences in the capacity for species recognition. Given the higher propensity of O. ventralis females towards hybridisation, we expect a reduced ability for species recognition in O. ventralis females, compared to O. nasuta females. We staged two experiments, one focusing on 22 female O. nasuta and one on 21 female O. ventralis. These fish were placed in one half of a tank and briefly exposed to a conspecific or a heterospecific male, a conspecific female, or nothing (control). Female response was evaluated by scoring six tracking parameters and by noting the occurrence of ten discrete behaviours before and during the encounter. Females always responded to the presence of another fish by approaching it. Remarkably, for both O. nasuta and O. ventralis, we did not find a different response between encounters with conspecific males and females. However, in agreement with our hypothesis, females of O. nasuta behaved differently towards conspecific or heterospecific males, whereas females of O. ventralis did not. When presented with a heterospecific male, females of O. nasuta performed a lower number of ‘ram’ behaviours. Additionally, they never displayed the ‘flee’ behaviour, a component of the species’ mating repertoire that was seen in all but one of the presentations with a conspecific male. Our findings show that differences in species recognition at first encounter predict to a large degree the outcome of the mating process, even in the absence of mating behaviour.

A Framework for Identification and Validation of Affine Hybrid Automata from Input-Output Traces

Automata-based modeling of hybrid and cyber-physical systems (CPS) is an important formal abstraction amenable to algorithmic analysis of its dynamic behaviors, such as in verification, fault identification, and anomaly detection. However, for realistic systems, especially industrial ones, identifying hybrid automata is challenging, due in part to inferring hybrid interactions, which involves inference of both continuous behaviors, such as through classical system identification, as well as discrete behaviors, such as through automata (e.g., L*) learning. In this paper, we propose and evaluate a framework for inferring and validating models of deterministic hybrid systems with linear ordinary differential equations (ODEs) from input/output execution traces. The framework contains algorithms for the approximation of continuous dynamics in discrete modes, estimation of transition conditions, and the inference of automata mode merging. The algorithms are capable of clustering trace segments and estimating their dynamic parameters, and meanwhile, deriving guard conditions that are represented by multiple linear inequalities. Finally, the inferred model is automatically converted to the format of the original system for the validation. We demonstrate the utility of this framework by evaluating its performance in several case studies as implemented through a publicly available prototype software framework called HAutLearn and compare it with a membership-based algorithm.

Discrete twinning dynamics and size-dependent dislocation-to twin transition in body-centred cubic tungsten

• We present a direct visualization of twinning dynamics in BCC W nanowires, with a discrete behaviour at atomic level. • Quantitative experimental studies directly demonstrate that deformation twins in W nanowires have a minimum size of six-layers and grow in increments of approximately three-layers, in contrast to the layer-by-layer growth of deformation twins in FCC. • These discrete twinning dynamics are generally applicable to different BCC metals across different length scales, which can help interpret the major twinning characteristics observed in previous and current studies of bulk BCC metals. • These findings not only advance the understanding of size-dependent dislocation-twinning competition in BCC nanocrystals, but also stimulate the investigation of plasticity in a broad class of small-volume BCC metals and alloys. Body-centred cubic (BCC) metals are known to have unstable intrinsic stacking faults and high resistance to deformation twinning, which can strongly influence their twinning behaviour. Though twinning mechanisms of BCC metals have been investigated for more than 60 years, the atomistic level dynamics of twinning remains under debate, especially regarding its impact on competition between twinning and slip. Here, we investigate the atomistic level dynamics of twinning in BCC tungsten (W) nanowires using in situ nanomechanical testing. Quantitative experimental studies directly visualize that deformation twins in W nanowires have a minimum size of six-layers and grow in increments of approximately three-layers at a time, in contrast to the layer-by-layer growth of deformation twins in face-centred cubic metals. These unique twinning dynamics induces a strong competition with ordinary dislocation slip, as exhibited by a size-dependent dislocation-to-twin transition in W nanowires, with a transition size of ∼40 nm. Our work provides physical insight into the dynamics of twinning at the atomic level, as well as a size-dependent dislocation-twinning competition, which have important implications for the plastic deformation in a broad class of BCC metals and alloys.