Digital stress: Concept, structure, and development of a digital stress scale

People suffer from stress or digital stress when using information communication technology. However, few tools have been developed to capture this phenomenon. The concept of digital stress has remained controversial. This preregistered study aims to reflect and clarify the concept of digital stress and to develop a digital stress scale for adolescents. This study integrated qualitative and quantitative approaches to explore the structure of digital stress and develop a digital stress scale. First, we theoretically proposed the digital stress item pool based on current theories of digital stress and the definition of digital stress. Then, we conducted focus groups and in-depth interviews (N=41) to revise the items in the item pool. Lastly, we finalized the scale based on the data collected from three independent samples of adolescents (Nsample1=1088, Nsample2=879, Nsample3=176). The results revealed six dimensions of digital stress among adolescents: unsatisfactory information and communication, unmet recreational motivation, online learning burden, social concerns, useless and overloaded notifications, and online verbal attacks. The scale showed robust reliability (2=.851 to .959), stability (test-retest reliability =.717 to .681, p < .001), and validity (construct validity: X2= 2107.978, df = 387, CFI = .932, TLI = .923, RMSEA = .064; correlation with anxiety and depression is .431 to .462, p < .001). The developed scale is reliable in measuring digital stress in adolescents, especially when few measures exist. Limitations, implications, and guidance for future research are discussed.

Structural reliability under uncertainty in moments: distributionally-robust reliability-based design optimization

This study considers structural optimization under a reliability constraint, in which the input distribution is only partially known. Specifically, when it is only known that the expected value vector and the variance-covariance matrix of the input distribution belong to a given convex set, it is required that the failure probability of a structure should be no greater than a specified target value for any realization of the input distribution. We demonstrate that this distributionally-robust reliability constraint can be reduced equivalently to deterministic constraints. By using this reduction, we can handle a reliability-based design optimization problem under the distributionally-robust reliability constraint within the framework of deterministic optimization; in particular, nonlinear semidefinite programming. Two numerical examples are solved to demonstrate the relation between the optimal value and either the target reliability or the uncertainty magnitude.

Reliability Analysis Based on a Gamma-Gaussian Deconvolution Degradation Modeling with Measurement Error

In most degradation tests, the measuring processes is affected by several conditions that may cause variation in the observed measures. As the measuring process is inherent to the degradation testing, it is important to establish schemes that define a certain level of permissible measurement error such that a robust reliability estimation can be obtained. In this article, an approach to deal with measurement error in degradation processes is proposed, the method focuses on studying the effect of such error in the reliability assessment. This approach considers that the true degradation is a function of the observed degradation and the measurement error. As the true degradation is not directly observed it is proposed to obtain an estimate based on a deconvolution operation, which considers the subtraction of random variables such as the observed degradation and the measurement error. Given that the true degradation is free of measurement error, the first-passage time distribution will be different from the observed degradation. For the establishment of a control mechanism, these two distributions are compared using different indices, which account to describe the differences between the observed and true degradation. By defining critical levels of these indices, the reliability assessment may be obtained under a known level of measurement error. An illustrative example based on a fatigue-crack growth dataset is presented to illustrate the applicability of the proposed scheme, the reliability assessment is developed, and some important insights are provided.

Operational Aftershock Forecasting for 2017-2018 Seismic Sequence in Western Iran

<p>On Sunday November 12, 2017, at 18:18:16 UTC, (21:48:16 local time), a strong earthquake with Mw7.3 occurred in western Iran in the border region between Iran and Iraq in vicinity of the Sarpol-e Zahab town. Unfortunately, this catastrophic seismic event caused 572 causalities, thousands of injured and vast amounts of damage to the buildings, houses and infrastructures in the epicentral area. The mainshock of this seismic sequence was felt in the entire western and central provinces of Iran and surrounding areas. The main event was preceded by a foreshock with magnitude 4.5 about 43 minutes before the mainshock that warned the local residence to leave their home and possibly reduced the number of human casualties. More than 2500 aftershocks with magnitude greater than 2.5 have been reported up to January 2019 with the largest registered aftershock of Mw6.4. A novel and fully-probabilistic procedure is adopted for providing spatio-temporal predictions of aftershock occurrence in a prescribed forecasting time interval (in the order of hours or days). The procedure aims at exploiting the information provided by the ongoing seismic sequence in quasi-real time. The versatility of the Bayesian inference is exploited to adaptively update the forecasts based on the incoming information as it becomes available. The aftershock clustering in space and time is modelled based on an Epidemic Type Aftershock Sequence (ETAS). One of the main novelties of the proposed procedure is that it considers the uncertainties in the aftershock occurrence model and its model parameters. This is done by moving within a framework of robust reliability assessment which enables the treatment of uncertainties in an integrated manner. Pairing up the Bayesian robust reliability framework and the suitable simulation schemes (Markov Chain Monte Carlo Simulation) provides the possibility of performing the whole forecasting procedure with minimum (or no) need of human interference. The fully simulation-based procedure is examined for both Bayesian model updating of ETAS spatio-temporal model and robust operational forecasting of the number of events of interest expected to happen in various time intervals after main events within the sequence. The seismicity is predicted within a confidence interval from the mean estimate.</p>

Optimization for Die Attach Film Delamination on Nickel-Palladium-Gold Die Pad

In the Semiconductor Industry, the delamination performance of integrated circuit packaging is being aggressively improved. However, this task is complicated and difficult, as the defective failure is highly dependent on the compatibility of the material characteristics that may affect the entire Integrated Circuit package system under certain stress levels, both mechanical and thermal. This research work aims to study Die Attach process optimization in DAF adhesive for Nickel-Palladium-Gold Die Pad leadframe to achieve maximum reliability performance under IPC / JEDEC Moisture Sensitivity Level 1 (MSL1) at 260°C reflow. Strategic optimization of the Die Attach process is needed to ensure robust reliability. And one of the solutions is to apply the Scrubbing method, which is a machine feature used at a constant temperature to aid in the wetting of adhesives and the removal of voids.

Validation of the Greek version of Tinnitus Handicap Inventory

Purpose: The purpose of this study was to validate the Greek version of the Tinnitus Handicap Inventory. Method: Eighty-six adult patients with chronic tinnitus participated in the study. Sociodemographic data and medical history were recorded during the interview. The patients underwent audiological examination and they were asked to fill in three questionnaires: the Greek version of the THI (THI-GR), the Greek version of the State-Trait Anxiety Inventory (STAI) and the brief Tinnitus Severity Scale Questionnaire (TSSQ). Results: The THI-GR showed good internal consistency, comparable to the original version. Cronbach’s alpha was equal to 0.92, which suggests a robust reliability. All THI-GR subscales along with total score were significantly and positively correlated with the TSSQ grade and the audiogram results indicating the existence of convergent validity. Furthermore, THI-GR's subscales were significantly correlated with both State and Trait subscales, which indicates a correlation between tinnitus and stress. Conclusions: This study highlighted the high reliability and validity of the THI-GR as a self-report measure for the evaluation of tinnitus-related annoyance and psychological distress in clinical practice.

Operational Aftershock Forecasting for Mw7.3 Sarpol-e Zahab (2017) Earthquake in Western Iran

<p><strong>Methodology:</strong></p><p>The implementation of short-term forecasts for emergency response management in the immediate aftermath of a seismic event, and in the presence of an ongoing seismic sequence, requires two basic components: scientific advisories expressed in terms of risk assessment, and protocols that establish how the scientific results can be translated into decisions/actions for risk mitigation. The operational earthquake forecasting framework is geared towards providing scientific advisories in the form of time-dependent probabilities expressing seismicity, hazard and risk that can be practically translated into decisions. Considering the triggered sequence of aftershocks in the process of post-event decision-making and prioritization of emergency operations still seems to need and to deserve much more attention. To this end, the adopted novel and fully-probabilistic procedure succeeds in providing spatio-temporal predictions of aftershock occurrence in a prescribed forecasting time interval (in the order of hours or days). The procedure aims at exploiting the information provided by the ongoing seismic sequence in quasi-real time considering the time needed for registering and transmitting the data. The versatility of the Bayesian inference is exploited to adaptively update the forecasts based on the incoming information as it becomes available. The aftershock clustering in space and time is modelled based on an Epidemic Type Aftershock Sequence (ETAS). One of the main novelties of the proposed procedure is that it considers the uncertainties in the aftershock occurrence model and its model parameters. This is done by moving within a framework of robust reliability assessment which enables the treatment of uncertainties in an integrated manner. Pairing up the Bayesian robust reliability framework and the suitable simulation schemes (Markov Chain Monte Carlo Simulation) provides the possibility of performing the whole forecasting procedure with minimum (or no) need of human interference.</p><p><strong>Application:</strong></p><p>This procedure is demonstrated through a retrospective application to early forecasting of seismicity associated with the 2017 Sarpol-e Zahab seismic sequence activities. On Sunday November 12, 2017, at 18:18:16 UTC, (21:48:16 local time), a strong earthquake with Mw7.3 occurred in western Iran in the border region between Iran and Iraq in vicinity of the Sarpol-e Zahab town. Unfortunately, this catastrophic seismic event caused 572 causalities, thousands of injured and vast amounts of damage to the buildings, houses and infrastructures in the epicentral area. The mainshock of this seismic sequence was felt in the entire western and central provinces of Iran and surrounding areas. The main event was preceded by a foreshock with magnitude 4.5 about 43 minutes before the mainshock that warned the local residence to leave their home and possibly reduced the number of human casualties. More than 2500 aftershocks with magnitude greater than 2.5 have been reported up to January 2019 with the largest registered aftershock of Mw6.4. The fully simulation-based procedure is examined for both Bayesian model updating of ETAS spatio-temporal model and robust operational forecasting of the number of events of interest expected to happen in various time intervals after main events within the sequence. The seismicity is predicted within a confidence interval from the mean estimate.</p>