Attention Limitations in the Detection and Identification of Alarms in Close Temporal Proximity

Objective The aim of this study was to establish the effects of simultaneous and asynchronous masking on the detection and identification of visual and auditory alarms in close temporal proximity. Background In complex and highly coupled systems, malfunctions can trigger numerous alarms within a short period of time. During such alarm floods, operators may fail to detect and identify alarms due to asynchronous and simultaneous masking. To date, the effects of masking on detection and identification have been studied almost exclusively for two alarms during single-task performance. This research examines 1) how masking affects alarm detection and identification in multitask environments and 2) whether those effects increase as a function of the number of alarms. Method Two experiments were conducted using a simulation of a drone-based package delivery service. Participants were required to ensure package delivery and respond to visual and auditory alarms associated with eight drones. The alarms were presented at various stimulus onset asynchronies (SOAs). The dependent measures included alarm detection rate, identification accuracy, and response time. Results Masking was observed intramodally and cross-modally for visual and auditory alarms. The SOAs at which asynchronous masking occurred were longer than reported in basic research on masking. The effects of asynchronous and, even more so, simultaneous masking became stronger as the number of alarms increased. Conclusion Masking can lead to breakdowns in the detection and identification of alarms in close temporal proximity in complex data-rich domains. Application The findings from this research provide guidance for the design of alarm systems.

How Subsistence Communities Reconfigure Livelihood Systems in Response to Climate Change: A Coupled-Systems Perspective

A defining societal challenge in the era of climate change is ensuring consumption adequacy in subsistence communities. To understand the intricacies of this challenge, we have conducted an ethnographic study of a low-income community that relies on subsistence fishing to maintain consumption adequacy. Based on our data analysis, we advance a conceptualization of subsistence livelihood systems that models the tight coupling among its three constituent subsystems: the market system, the social system, and the environmental system. These three subsystems are highly interdependent and operate in concert to maintain consumption adequacy. We then show how climate change-induced environmental disruptions threaten consumption adequacy by disequilibrating livelihood systems in subsistence settings, as well as unpack the self-directed adaptation and mitigation strategies employed by the community in response to the threat of consumption inadequacy. These response strategies create feedback loops to either preserve or attenuate the tight coupling among the three subsystems.

Memristive Structure-Based Chaotic System for PRNG

This paper suggests an approach to generate pseudo-random sequences based on the discrete-time model of the simple memristive chaotic system. We show that implementing Euler’s and Runge–Kutta’s methods for the simulation solutions gives the possibility of obtaining chaotic sequences that maintain general properties of the original chaotic system. A preliminary criterion based on the binary sequence balance estimation is proposed and applied to separate any binary representation of the chaotic time sequences into random and non-random parts. This gives us the possibility to delete obviously non-random sequences prior to the post-processing. The investigations were performed for arithmetic with both fixed and floating points. In both cases, the obtained sequences successfully passed the NIST SP 800-22 statistical tests. The utilization of the unidirectional asymmetric coupling of chaotic systems without full synchronization between them was suggested to increase the performance of the chaotic pseudo-random number generator (CPRNG) and avoid identical sequences on different outputs of the coupled systems. The proposed CPRNG was also implemented and tested on FPGA using Euler’s method and fixed-point arithmetic for possible usage in different applications. The FPGA implementation of CPRNG supports a generation speed up to 1.2 Gbits/s for a clock frequency of 50 MHz. In addition, we presented an example of the application of CPRNG to symmetric image encryption, but nevertheless, one is suitable for the encryption of any binary source.

Practical stability for fractional impulsive control systems with noninstantaneous impulses on networks

This paper investigates practical stability for a class of fractional-order impulsive control coupled systems with noninstantaneous impulses on networks. Using graph theory and Lyapunov method, new criteria for practical stability, uniform practical stability as well as practical asymptotic stability are established. In this paper, we extend graph theory to fractional-order system via piecewise Lyapunov-like functions in each vertex system to construct global Lyapunov-like functions. Our results are generalization of some known results of practical stability in the literature and provide a new method of impulsive control law for impulsive control systems with noninstantaneous impulses. Examples are given to illustrate the effectiveness of our results

Метод определения характеристик перемежающейся обобщенной синхронизации, основанный на вычислении вероятности наблюдения синхронного режима

Method to define the characteristic phases in the behavior of unidirectionally coupled systems being near the boundary of the generalized chaotic synchronization regime onset, based on calculation of the probability of the synchronous regime observation in ensemble of coupled systems is proposed. Using the example of unidirectionally coupled Rössler systems in the band chaos regime we show its efficiency in comparison with the other known methods for detection the characteristics of intermittent generalized synchronization.

Abstractions and Automated Algorithms for Mixed Domain Finite Element Methods

Mixed dimensional partial differential equations (PDEs) are equations coupling unknown fields defined over domains of differing topological dimension. Such equations naturally arise in a wide range of scientific fields including geology, physiology, biology, and fracture mechanics. Mixed dimensional PDEs are also commonly encountered when imposing non-standard conditions over a subspace of lower dimension, e.g., through a Lagrange multiplier. In this article, we present general abstractions and algorithms for finite element discretizations of mixed domain and mixed dimensional PDEs of codimension up to one (i.e., n D- m D with |n-m| ≤ 1). We introduce high-level mathematical software abstractions together with lower-level algorithms for expressing and efficiently solving such coupled systems. The concepts introduced here have also been implemented in the context of the FEniCS finite element software. We illustrate the new features through a range of examples, including a constrained Poisson problem, a set of Stokes-type flow models, and a model for ionic electrodiffusion.

Synchronization in Dynamically Coupled Fractional-Order Chaotic Systems: Studying the Effects of Fractional Derivatives

This study presents the effectiveness of dynamic coupling as a synchronization strategy for fractional chaotic systems. Using an auxiliary system as a link between the oscillators, we investigate the onset of synchronization in the coupled systems and we analytically determine the regions where both systems achieve complete synchronization. In the analysis, the integration order is considered as a key parameter affecting the onset of full synchronization, considering the stability conditions for fractional systems. The local stability of the synchronous solution is studied using the linearized error dynamics. Moreover, some statistical metrics such as the average synchronization error and Pearson’s correlation are used to numerically identify the synchronous behavior. Two particular examples are considered, namely, the fractional-order Rössler and Chua systems. By using bifurcation diagrams, it is also shown that the integration order has a strong influence not only on the onset of full synchronization but also on the individual dynamic behavior of the uncoupled systems.

Directing Min protein patterns with advective bulk flow

We theoretically predict and experimentally show that the propagation direction of in vitro Min protein patterns can be controlled by a hydrodynamic flow of the bulk solution. We find downstream propagation of Min wave patterns relative to the bulk flow direction for low MinE:MinD concentration ratios, but upstream propagation for large MinE:MinD ratios, with multistability of both propagation directions in between. A theoretical model for the Min system reveals the mechanism underlying the upstream propagation and links it to the fast conformational switching of MinE in the bulk. For high MinE:MinD ratios, upstream propagation can be reproduced by a reduced model in which increased MinD bulk concentrations on the upstream side promote protein attachment and hence, propagation in that direction. For low MinE:D ratios, downstream propagation is described by the minimal model, as additionally confirmed by experiments with a non-switching MinE mutant. No advection takes place on the membrane surface where the protein patterns form, but advective bulk flow shifts the protein-concentration profiles in the bulk relative to the membrane-bound pattern. From a broader perspective, differential flows in a bulk volume relative to a surface are a relevant general feature in bulk-surface coupled systems. Our study shows how such a differential flow can control surface-pattern propagation and demonstrates how the global pattern's response may depend on specific molecular features of the reaction kinetics.