Abusive Supervision and Workplace Deviance: The Moderating Role of Power Distance

The aim of this paper is to examine the association of abusive supervision with workplace deviance, for instance supervisory directed deviance, non-supervisory directed deviance, and emotional exhaustion. Further, in this paper we examine how power distance moderates these relationships. Cross-sectional data was collected through self administrated questionnaire from banking sectors in Lahore, Pakistan. To test the hypothesis, structural equation-modeling (SEM) technique is used; moreover, for moderation test hierarchical regression is applied. The finding suggests that abusive supervision is positively associated with supervisory directed deviance, non-supervisory directed deviance, and emotional exhaustion. In moderation test, the individual power distance influences the relationships between abusive supervision and supervisory directed deviance as well as emotional exhaustion. However, it has not affected the relationship among abusive supervision and non-supervisory directed deviance. The results indicate that mostly mistreated employees involved in negative reactions and these reactions are not only contained deviating behavior, it also influences them emotionally. By addressing abusive supervision issues, this research has key implication for abusive supervision practically. In practical terms, „Policy makers‟ can also take benefit from this research by considering how abusive supervision can influence the employees‟ wellbeing in organizations while making organizational polices

Evaluating TCP Performance of Routing Protocols for Traffic Exchange in Street-parked Vehicles based Fog Computing Infrastructure

As most vehicles remain parked 95% of its time, this suggests that leveraging the use of On-board Units (OBUs) in parked vehicles would provide communication and computation services to other mobile and fixed nodes for de- livery of services such as multimedia streaming, data storage and data processing. The nearby vehicles can form an infrastructure using IEEE 802.11p communication interface, facilitating communication, computation and storage services to the end users. We refer to this as a Vehicular Fog Computing (VFC) infrastructure. In this study, using NS-2 simulator, we investigate how six routing protocols consisting of two proactive routing protocols, Destination Sequence Destination Vector (DSDV) and Fisheye State Routing (FSR); two reactive routing protocols, Ad Hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR); and two geographic routing protocols, Distance Routing Effect Algorithm for Mobility (DREAM) and Location Aided Routing (LAR) perform when forwarding TCP traffic among the parked vehicles that form a VFC infrastructure in an urban street parking scenario. In order to reflect an urban street parking scenario, we consider a traffic mobility traces that are generated using SUMO in our simulation. To the best of our knowledge, this work is the first effort to understand how vehicle density, vehicle speed and parking duration can influence TCP in an urban street parking scenario when packet forwarding decision is made using proactive, reactive and geographic routing protocols. In our performance evaluation, positive results are observed on the influence of parking duration in parked vehicles as TCP performance in all routing protocols increases with longer parking duration. However, variable speed in parked vehicles and moving vehicles in an urban street parking scenario may not have significant influence on TCP performance, especially in case of reactive and proactive routing protocols. Further, our findings reveal that vehicle density in a VFC infrastructure can noticeably influence TCP performance. Towards the end of the paper, we delineate some important future research issues in order to improve routing performance in a street-parked vehicle based VFC infrastructure

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Abusive supervision and workplace deviance: The moderating role of power distance

The aim of this paper is to examine the association of abusive supervision with workplace deviance, for instance supervisory directed deviance, non-supervisory directed deviance, and emotional exhaustion. Further, in this paper we examine how power distance moderates these relationships. Cross-sectional data was collected through self-administrated questionnaire from banking sectors in Lahore, Pakistan. To test the hypothesis, structural equation-modeling (SEM) technique is used; moreover, for moderation test hierarchical regression is applied. The finding suggests that abusive supervision is positively associated with supervisory directed deviance, non-supervisory directed deviance, and emotional exhaustion. In moderation test, the individual power distance influences the relationships between abusive supervision and supervisory directed deviance as well as emotional exhaustion. However, it has not affected the relationship among abusive supervision and non-supervisory directed deviance. The results indicate that mostly mistreated employees involved in negative reactions and these reactions are not only contained deviating behavior, it also influences them emotionally. By addressing abusive supervision issues, this research has key implication for abusive supervision practically. In practical terms, "Policy makers&#x201f; can also take benefit from this research by considering how abusive supervision can influence the employees&#x201f; well-being in organizations while making organizational polices

Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence

Precisely measuring the work area of agriculture farm machinery is important for performing the authentication of machinery usage, better allocation of resources, measuring the effect of machinery usage on the yield, usage billing and driver’s behaviour. The manual measurement, which is a common practice is an error-prone and time-consuming process. The irregular fields make it even more difficult to calculate the work area. An automatic solution that uses smart technology and algorithms to precisely calculate the work area is crucial for the advancement of agriculture. In this work, we have developed a smart system that utilizes the Internet of Things (IoT), Global Positioning System (GPS) and Artificial Intelligence (AI) that records the movement of agriculture machinery and use it to measure the precise work area of its usage. The system couples the nearest neighbourhood algorithms with Contact-based mechanisms to find the precise work area for different shaped fields and activities. The system was able to record the movement of machinery and calculate its work area, regardless of how many times the machinery runs through a particular field. Our evaluation shows that the system was able to precisely find the work boundaries and calculate the area with a maximum of 9% error for irregular shapes.</jats:p

Determining the Precise Work Area of Agriculture Machinery Using Internet of Things and Artificial Intelligence

Precisely measuring the work area of agriculture farm machinery is important for performing the authentication of machinery usage, better allocation of resources, measuring the effect of machinery usage on the yield, usage billing and driver&rsquo;s behaviour. The manual measurement, which is a common practice is an error-prone and time-consuming process. The irregular fields make it even more difficult to calculate the work area. An automatic solution that uses smart technology and algorithms to precisely calculate the work area is crucial for the advancement of agriculture. In this work, we have developed a smart system that utilizes the Internet of Things (IoT), Global Positioning System (GPS) and Artificial Intelligence (AI) that records the movement of agriculture machinery and use it to measure the precise work area of its usage. The system couples the nearest neighbourhood algorithms with Contact-based mechanisms to find the precise work area for different shaped fields and activities. The system was able to record the movement of machinery and calculate its work area, regardless of how many times the machinery runs through a particular field. Our evaluation shows that the system was able to precisely find the work boundaries and calculate the area with a maximum of 9% error for irregular shapes

Kinetics and mechanism of rhenium-ethylenediaminetetraacetic acid (Re(IV)-EDTA) complex degradation; For 99Tc-EDTA degradation in the natural environment

© 2022 The Author(s)Mechanism and kinetics of Rhenium complexes as a surrogate of Technetium-99 (99Tc) is worthy of study from radioactive waste safe disposal perspective. Re(IV)-EDTA was synthesized via the reduction of Re(VII) with Sn(II) in the presence of Ethylenediaminetetraacetic acid (EDTA). The Re(IV)-EDTA was then degraded by H2O2 (7%–30%) at pH of 3–11 in ionic strength I = 0–2 M solution. The Re-EDTA was observed to degrade more rapidly at pH of ≤ 3–4 than one of ≥ 10–11 and remained stable at pH = 7–9. The Re-EDTA was degraded in accordance with the H+ addition mechanism in the acidic range and ligand charge transfer in the alkaline region. Complex degradation followed the zero-order rate kinetics for the H+ and Re-EDTA parameters, apart from a pH of 3, for which degradation was a better fit to first order kinetics. A higher Re(IV)-EDTA stability at a pH of 7–9 demonstrated that Re(IV)-EDTA (or 99Tc(IV)-EDTA) tends to be more persistent in natural environments similar to the pH range of 7–9.11Nsciescopu