Behavioral Parameter Field for Human Abnormal Behavior Recognition in Low-Resolution Thermal Imaging Video

In recent years, thermal imaging cameras are widely used in the field of intelligent surveillance because of their special imaging characteristics and better privacy protection properties. However, due to the low resolution and fixed location for current thermal imaging cameras, it is difficult to effectively identify human behavior using a single detection method based on skeletal keypoints. Therefore, a self-update learning method is proposed for fixed thermal imaging camera scenes, called the behavioral parameter field (BPF). This method can express the regularity of human behavior patterns concisely and directly. Firstly, the detection accuracy of small targets under low-resolution video is improved by optimizing the YOLOv4 network to obtain a human detection model under thermal imaging video. Secondly, the BPF model is designed to learn the human normal behavior features at each position. Finally, based on the learned BPF model, we propose to use metric modules, such as cosine similarity and intersection over union matching, to accomplish the classification of human abnormal behaviors. In the experimental stage, the living scene of the indoor elderly living alone is applied as our experimental case, and a variety of detection models are compared to the proposed method for verifying the effectiveness and practicability of the proposed behavioral parameter field in the self-collected thermal imaging dataset for the indoor elderly living alone.

Temporal Behavioral Parameters of On-Going Gaze Encounters in a Virtual Environment

To navigate the social world, humans heavily rely on gaze for non-verbal communication as it conveys information in a highly dynamic and complex, yet concise manner: For instance, humans utilize gaze effortlessly to direct and infer the attention of a possible interaction partner. Many traditional paradigms in social gaze research though rely on static ways of assessing gaze interaction, e.g., by using images or prerecorded videos as stimulus material. Emerging gaze contingent paradigms, in which algorithmically controlled virtual characters can respond flexibly to the gaze behavior of humans, provide high ecological validity. Ideally, these are based on models of human behavior which allow for precise, parameterized characterization of behavior, and should include variable interactive settings and different communicative states of the interacting agents. The present study provides a complete definition and empirical description of a behavioral parameter space of human gaze behavior in extended gaze encounters. To this end, we (i) modeled a shared 2D virtual environment on a computer screen in which a human could interact via gaze with an agent and simultaneously presented objects to create instances of joint attention and (ii) determined quantitatively the free model parameters (temporal and probabilistic) of behavior within this environment to provide a first complete, detailed description of the behavioral parameter space governing joint attention. This knowledge is essential to enable the modeling of interacting agents with a high degree of ecological validity, be it for cognitive studies or applications in human-robot interaction.

Fear response-based prediction for stress susceptibility to PTSD-like phenotypes

Most individuals undergo traumatic stresses at some points in their life, but only a small proportion develop stress-related disorders such as anxiety diseases and posttraumatic stress disorder (PTSD). Although stress susceptibility is one determinant of mental disorders, the underlying mechanisms and functional implication remain unclear yet. We found that an increased amount of freezing that animals exhibited in the intertrial interval (ITI) of a stress-enhanced fear learning paradigm, predicts ensuing PTSD-like symptoms whereas resilient mice show ITI freezing comparable to that of unstressed mice. To examine the behavioral features, we developed a systematic analytical approach for ITI freezing and stress susceptibility. Thus, we provide a behavioral parameter for prognosis to stress susceptibility of individuals in the development of PTSD-like symptoms as well as a new mathematical means to scrutinize freezing behavior.

Parallel Hydrological Model Parameter Uncertainty Analysis Based on Message-Passing Interface

Parameter uncertainty analysis is one of the hot issues in hydrology studies, and the Generalized Likelihood Uncertainty Estimation (GLUE) is one of the most widely used methods. However, the scale of the existing research is relatively small, which results from computational complexity and limited computing resources. In this study, a parallel GLUE method based on a Message-Passing Interface (MPI) was proposed and implemented on a supercomputer system. The research focused on the computational efficiency of the parallel algorithm and the parameter uncertainty of the Xinanjiang model affected by different threshold likelihood function values and sampling sizes. The results demonstrated that the parallel GLUE method showed high computational efficiency and scalability. Through the large-scale parameter uncertainty analysis, it was found that within an interval of less than 0.1%, the proportion of behavioral parameter sets and the threshold value had an exponential relationship. A large sampling scale is more likely than a small sampling scale to obtain behavioral parameter sets at high threshold values. High threshold values may derive more concentrated posterior distributions of the sensitivity parameters than low threshold values.

Fear response-based prediction for stress susceptibility to PTSD-like phenotypes

Most individuals undergo traumatic stresses at some points in their life, but only a small proportion develop stress-related disorders such as anxiety diseases and posttraumatic stress disorder (PTSD). Although stress susceptibility is one determinant of mental disorders, the underlying mechanisms and functional implication remain unclear yet. We found that an increased amount of freezing that animals exhibited in the intertrial interval (ITI) of a stress-enhanced fear learning paradigm, predicts ensuing PTSD-like symptoms whereas resilient mice show ITI freezing comparable to that of unstressed mice. To examine the behavioral features, we developed a systematic analytical approach for ITI freezing and stress susceptibility. Thus, we provide a behavioral parameter for prognosis to stress susceptibility of individuals in the development of PTSD-like symptoms as well as a new mathematical means to scrutinize freezing behavior.

Fear response-based prediction for stress susceptibility to PTSD-like phenotypes

Most individuals undergo traumatic stresses at some points in their life, but only a small proportion develop stress-related disorders such as anxiety diseases and posttraumatic stress disorder (PTSD). Although stress susceptibility is one determinant of mental disorders, the underlying mechanisms and functional implication remain unclear yet. We found that an increased amount of freezing that animals exhibited in the intertrial interval (ITI) of a stress-enhanced fear learning paradigm, predicts ensuing PTSD-like symptoms whereas resilient mice show ITI freezing comparable to that of unstressed mice. To examine the behavioral features, we developed a systematic analytical approach for ITI freezing and stress susceptibility. Thus, we provide a behavioral parameter for prognosis to stress susceptibility of individuals in the development of PTSD-like symptoms as well as a new mathematical means to scrutinize freezing behavior.

ERP Correlates of Performance Monitoring: a Mouse-Tracking Study

Performance monitoring involves detection of action outcomes and initiation of appropriate behavioral adaptations. Psychophysiological mechanisms of performance monitoring remain largely understudied in the context of uncertainty that arises at the stage of stimulus identification and decision making, as well as in the context of inhibition/correction of the motor response. In the current study, we investigate relations between behavioral performance measures and several ERP components: N2, ERN/CRN and Pe. Participants performed a condensation task and made their responses by moving mouse cursor. Response registration using mouse tracking allowed us to obtain two independent behavioral measures: mouse movement initiation time and movement duration. Amplitude of N2 and CRN was dependent on movement initiation time: N2 was increased and CRN was decreased for ‘late’ correct responses compared with ‘early’ correct ones; this finding is compatible with the explanation that ‘late’ responses involve higher pre-response conflict and higher uncertainty compared with ‘early’ ones. Movement duration time was a novel independent behavioral parameter, that cannot be measured using traditional keystrokes. This behavioral measure was related to the early Pe: its amplitude was more positive for ‘long’ responses compared with ‘short’ ones. This finding may be explained by mechanisms of an ongoing response inhibition. We suggest that this effect is linked to response stopping, which may be related to outcome awareness.

An Evaluation of Catchment Transit Time Model Parameters: A Comparative Study between Two Stable Isotopes of Water

Using δ18O and δ2H in mean transit time (MTT) modeling can ensure the verifiability of results across catchments. The main objectives of this study were to (i) evaluate the δ18O- and δ2H-based behavioral transit time distributions and (ii) assess if δ18O and δ2H-based MTTs can lead to similar conclusions about catchment hydrologic functioning. A volume weighted δ18O (or δ2H) time series of sampled precipitation was used as an input variable in a 50,000 Monte Carlo (MC) time-based convolution modeling process. An observed streamflow δ18O (or δ2H) time series was used to calibrate the model to obtain the simulated time series of δ18O (or δ2H) of the streamflow within a nested system of eight Prairie catchments in Canada. The model efficiency was assessed via a generalized likelihood uncertainty estimation by setting a minimum Nash–Sutcliffe Efficiency threshold of 0.3 for behavioral parameter sets. Results show that the percentage of behavioral parameter sets across both tracers were lower than 50 at the majority of the studied outlets; a phenomenon hypothesized to have resulted from the number of MC runs. Tracer-based verifiability of results could be achieved within five of the eight studied outlets during the model process. The flow process in those five outlets were mainly of a shallow subsurface flow as opposed to the other three outlets, which experienced other additional flow dynamics. The potential impacts of this study on the integrated use of δ18O and δ2H in catchment water storage and release dynamics must be further investigated in multiple catchments within various hydro-physiographic settings across the world.

Music Festival Makes Hedgehogs Move: How Individuals Cope Behaviorally in Response to Human-Induced Stressors

Understanding the impact of human activities on wildlife behavior and fitness can improve their sustainability. In a pilot study, we wanted to identify behavioral responses to anthropogenic stress in an urban species during a semi-experimental field study. We equipped eight urban hedgehogs (Erinaceus europaeus; four per sex) with bio-loggers to record their behavior before and during a mega music festival (2 × 19 days) in Treptower Park, Berlin. We used GPS (Global Positioning System) to monitor spatial behavior, VHF (Very High Frequency)-loggers to quantify daily nest utilization, and accelerometers to distinguish between different behaviors at a high resolution and to calculate daily disturbance (using Degrees of Functional Coupling). The hedgehogs showed clear behavioral differences between the pre-festival and festival phases. We found evidence supporting highly individual strategies, varying between spatial and temporal evasion of the disturbance. Averaging the responses of the individual animals or only examining one behavioral parameter masked these potentially different individual coping strategies. Using a meaningful combination of different minimal-invasive bio-logger types, we were able to show high inter-individual behavioral variance of urban hedgehogs in response to an anthropogenic disturbance, which might be a precondition to persist successfully in urban environments.