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The growing use of digital technologies (DTs) has a myriad of implications to socio-technical systems, which are not yet fully recognised. This paper investigates the contributions and drawbacks of DTs to resilient performance (RP), an aspect that so far has received less attention in comparison to others such as efficiency. To this end, a survey questionnaire was applied to 79 academics and practitioners linked to resilience engineering. Data analysis involved descriptive statistics and a thematic analysis of the open-text responses to the survey. Mixed impacts were identified, with 10 themes related to contributions and 16 to drawbacks. Regarding the contributions, the results highlighted the use of DTs for monitoring and anticipating system performance. Machine learning seems to be the most promising approach for this purpose. A key drawback is the need for developing new skills across the workforce so that they can make sense of the outputs of DTs and are aware of their strengths and weaknesses. The human role is expected to remain crucial for RP, which makes the current coordination difficulties with DTs even more important to address. A research agenda composed of five topics is proposed, encompassing description, prescription, and assessment. The agenda emphasizes the need for mapping the attributes or functionalities of DTs onto resilience concepts, models, and frameworks. [ABSTRACT FROM AUTHOR]

Paroxysmal atrial fibrillation (PAF) is a cardiac arrhythmia which is often challenging to diagnose because patients may be asymptomatic, and episodes are usually intermittent. In this paper we describe a method for identifying patients with a history of PAF using electrocardiogram (ECG) recordings during sinus rhythm. We analyzed, on a beat-to-beat basis, the P-waves in the sinus rhythm ECGs of 69 patients with a history of PAF and 59 healthy individuals. From each subject's P-waves, we calculated key electrocardiographic metrics, including some which are proposed here for the first time. Using means testing and feature selection methods, we discerned the features which were most useful for classification, and trained a Random Forest which identified PAF patients. Our approach achieved a 93.45% accuracy, sensitivity of 95.21%, and specificity of 91.40% using P-wave integral and novel amplitude and slope-based features which ranked highest in importance compared to other metrics from the literature. In particular, descriptive statistics of P-wave amplitudes, slopes, and integrals, were effective for identifying subjects with PAF history vs. healthy individuals. Our method has a high sensitivity and discrimination ability, with an AUC=0.9669 which is superior to others', and can thus be potentially valuable for the early identification of patients who are prone to episodes of PAF, even as part of the standard cardiological checkup that most adults undergo periodically. • Early identification of PAF during sinus rhythm with high accuracy. • P-wave signal metrics on a beat-to-beat basis are proposed. • P-wave amplitude, integral and slope features were ranked as the most important. • A RF classifier distinguishes PAF from healthy subjects with a state-of-the-art AUC. [ABSTRACT FROM AUTHOR]

• The first review article summarizes 30 years of the TSLP studies. • A comprehensive review of the problem literature with a new classification system. • Detailed descriptive statistics for the literature. • New directions for future research are given. Traffic flow data is a decisive element in transportation planning and traffic management. Over time, traffic sensors have been recognized as sources of such data. Despite their outstanding capabilities in measuring different traffic flow information types, they are not practical to apply across all transportation network streets or intersections. Thus, the traffic sensor location problem (TSLP) has emerged to answer two typical questions: how many sensors are needed, and what are the best locations for their deployment. This paper reviews the TSLP classes that have been extensively examined in the literature over the last three decades. This study tries to fulfill two major gaps in the existing literature. First, this is the only review article that summarizes the contributions made toward solving the TSLP spanning nearly 30 years. Second, it presents a comprehensive review and analysis of most TSLP studies with a new categorization system. This contribution clarifies the progress made and provides recommendations for further research. [ABSTRACT FROM AUTHOR]