Why do some followers remain silent in response to abusive supervision? A system justification perspective

Copyright © 2023 The Authors. This study investigates how the system justification motive manifests in employees’ voice/silence behavior at the workplace. It also explores the moderating effects of system justification on the linkage between abusive supervision and voice/silence behavior for blue- and white-collar employees. The field study generated responses from 905 employees in Turkey. Multi-group analysis reveals that the moderating effect of system justification motives varies by occupational class. In particular, the impact of abusive supervision on silence becomes more salient when white-collar employees endorse higher system justification motives. However, in the blue-collar sample, the absence of a moderating effect could be attributed to the strong main effect of system justification motives. The current study adds to the extant literature by applying a system justification perspective to voice and silence behavior by collar differences at work. It also provides important implications for managers in dealing with workplace mistreatment affecting all occupational groups, mainly when blue-collar employee silence is endemic and regulatory policies are inadequate

Applying advanced data analytics and machine learning to enhance the safety control of dams

The protection of critical engineering infrastructures is vital to today’s so- ciety, not only to ensure the maintenance of their services (e.g., water supply, energy production, transport), but also to avoid large-scale disasters. Therefore, technical and financial efforts are being continuously made to improve the safety control of large civil engineering structures like dams, bridges and nuclear facilities. This con- trol is based on the measurement of physical quantities that characterize the struc- tural behavior, such as displacements, strains and stresses. The analysis of monitor- ing data and its evaluation against physical and mathematical models is the strongest tool to assess the safety of the structural behavior. Commonly, dam specialists use multiple linear regression models to analyze the dam response, which is a well- known approach among dam engineers since the 1950s decade. Nowadays, the data acquisition paradigm is changing from a manual process, where measurements were taken with low frequency (e.g., on a weekly basis), to a fully automated process that allows much higher frequencies. This new paradigm escalates the potential of data analytics on top of monitoring data, but, on the other hand, increases data quality issues related to anomalies in the acquisition process. This chapter presents the full data lifecycle in the safety control of large-scale civil engineering infrastructures (focused on dams), from the data acquisition process, data processing and storage, data quality and outlier detection, and data analysis. A strong focus is made on the use of machine learning techniques for data analysis, where the common multiple linear regression analysis is compared with deep learning strategies, namely recur- rent neural networks. Demonstration scenarios are presented based on data obtained from monitoring systems of concrete dams under operation in Portugal.info:eu-repo/semantics/acceptedVersio

Prevalence of Frailty in European Emergency Departments (FEED): an international flash mob study

Introduction Current emergency care systems are not optimized to respond to multiple and complex problems associated with frailty. Services may require reconfiguration to effectively deliver comprehensive frailty care, yet its prevalence and variation are poorly understood. This study primarily determined the prevalence of frailty among older people attending emergency care. Methods This cross-sectional study used a flash mob approach to collect observational European emergency care data over a 24-h period (04 July 2023). Sites were identified through the European Task Force for Geriatric Emergency Medicine collaboration and social media. Data were collected for all individuals aged 65 + who attended emergency care, and for all adults aged 18 + at a subset of sites. Variables included demographics, Clinical Frailty Scale (CFS), vital signs, and disposition. European and national frailty prevalence was determined with proportions with each CFS level and with dichotomized CFS 5 + (mild or more severe frailty). Results Sixty-two sites in fourteen European countries recruited five thousand seven hundred eighty-five individuals. 40% of 3479 older people had at least mild frailty, with countries ranging from 26 to 51%. They had median age 77 (IQR, 13) years and 53% were female. Across 22 sites observing all adult attenders, older people living with frailty comprised 14%. Conclusion 40% of older people using European emergency care had CFS 5 + . Frailty prevalence varied widely among European care systems. These differences likely reflected entrance selection and provide windows of opportunity for system configuration and workforce planning

Evaluation of acoustic emission activities in a steel fiber reinforced concrete beam by Ib value analysis [Çelik lifli betonarme kirişte akustik emisyon aktivitelerinin Ib değeri analizi ile değerlendirilmesi]

###EgeUn###There are numerous nondestructive testing methods that are used to determine damages within structures. Acoustic Emission (AE), being one of these methods makes it possible to obtain significant pieces of information such as origin time, location and type of damage formed in a material during loading by analyzing AE data using various algorithms. Ib value analysis is one of these algorithms which is based on AE signal and this analysis enables to have information on formation of new cracks or propagation of existing cracks by scaling the magnitude of AE activities. In this study, in order to investigate effect of the steel fiber in concrete matrix on Ib value, two reinforced concrete beams were tested under simple bending while one of them was the reference. Afterwards, AE parameters obtained were analyzed, Ib value analyses were applied to amplitude values and these parameters were associated to each other. Furthermore, effect of steel fiber existence on behavior of the beam and distribution of Ib value were examined. © 2019 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved.112M822 Türkiye Bilimsel ve Teknolojik Araştirma KurumuThe authors are thankful to the Scientific and Technological Research Council of Turkey for having supported this work (TUBITAK, Grant Number 112M822). -

Numerical simulation of flood wave propagation in two-dimensions in densely populated urban areas due to dam break

Dams are important structures having many functions such as water supply, flood control, hydroelectric power and recreation. Although dam break failures are very rare events, dams can fail with little warning and the damage at the downstream of the dam due to the flood wave can be catastrophic. During a dam failure, immense volume of water is mobilized at very high speed in a very short time. The momentum of the flood wave can turn to a very destructive impact force in residential areas. Therefore, from risk point of view, understanding the consequences of a possible dam failure is critically important. This study deals with the methodology utilized for predicting the flood wave occurring after the dam break and analyses the propagation of the flood wave downstream of the dam. The methodology used in this study includes creation of bathymetric, DEM and land use maps; routing of the flood wave along the valley using a 1D model; and two dimensional numerical modeling of the propagation and spreading of flood wave for various dam breaching scenarios in two different urban areas. Such a methodology is a vital tool for decision-making process since it takes into account the spatial heterogeneity of the basin parameters to predict flood wave propagation downstream of the dam. Proposed methodology is applied to two dams; Porsuk Dam located in Eskişehir and Alibey Dam located in Istanbul, Turkey. Both dams are selected based on the fact that they have dense residential areas downstream and such a failure would be disastrous in both cases. Model simulations based on three different dam breaching scenarios showed that maximum flow depth can reach to 5 m at the border of the residential areas both in Eskişehir and in Istanbul with a maximum flow velocity of 5 m/s and flood waves having 0.3 m height reach to the boundary of the residential area within 1 to 2 h. Flooded area in Eskişehir was estimated as 127 km2, whereas in Istanbul this area was 8.4 km2 in total

ABSTRACT Forecasting Using TES Processes

Forecasting is of prime importance for accuracy in decision-making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor forecasting. TES (Transform-Expand-Sample) is a class of stochastic processes to model empirical autocorrelated time series and is frequently used in Monte Carlo simulation. Its merit is to capture simultaneously both the empirical distribution function and the autocorrelation function of a stochastic process. In addition, its analytical background makes it a viable tool to forecast future values of time series data. In this paper, we utilize phase-type random variables as the innovation variable in the TES model fitting methodology. We investigate the forecasting performance of TES processes and 1 compare it to traditional auto regressive integrated moving average models. We find that TES models yield forecasts as accurate as time series models. KEY WORDS forecasting; TES processes; time series model