Workload, Work Stress, Role Conflict, and Workplace Deviant Behaviour in Banks: an Empirical Analysis

This study identifies and explains the relationship between workload, work stress, role conflict, and workplace deviant behaviour. This study uses the Affective Events Theory (AET) as a foundation to test a proposed model. All Data were gathered using self-administered questionnaires from a sample of 125 bank employees who work in banks around Faisalabad. Descriptive analysis, correlation analysis, and multiple regression analysis were used in this study. The findings demonstrate a low level of workplace deviant behaviour. The results showed a significant relationship between workload, work stress, role conflict and workplace deviant behavior. The role conflict was the major contributor to workplace deviant behaviour. This study has practical implications where the bank should take initiatives within banks provided

Workload, Work Stress, Role Conflict, and Workplace Deviant Behaviour in Banks: an Empirical Analysis

This study identifies and explains the relationship between workload, work stress, role conflict, and workplace deviant behaviour. This study uses the Affective Events Theory (AET) as a foundation to test a proposed model. All Data were gathered using self-administered questionnaires from a sample of 125 bank employees who work in banks around Faisalabad. Descriptive analysis, correlation analysis, and multiple regression analysis were used in this study. The findings demonstrate a low level of workplace deviant behaviour. The results showed a significant relationship between workload, work stress, role conflict and workplace deviant behavior. The role conflict was the major contributor to workplace deviant behaviour. This study has practical implications where the bank should take initiatives within banks provided

A digital twin (DT) approach to narrow-band Internet of things (NB-IoT) wireless communication optimization in an industrial scenario

The pervasive realization of virtual replication of physical entities termed Digital Twin (DT) has been utilized in this paper to optimize the wireless communication of the Narrowband Internet of Things (NB-IoT) in an industrial scenario. This optimization is exclusively achieved through DT approach. NB-IoT is a Low-Powered Wide Area Network (LPWAN) standardized by 3GPP and leverages Long Term Evolution (LTE) technology. The Amplify-and-Forward (AF) optimization technique is used to improve the performance of some notably poor-performing terminals in the scenario. Bit-Error-Rate (BER) tests show the terminals’ overall performance before and after optimization. An improvement of 17% is achieved in BER. The signal quality of the channels is analyzed as well as the Cumulative Distribution Function (CDF) is used to showcase the effective throughput performance of the NB-IoT terminals

Towards the Digital Twin (DT) of narrow-band Internet of Things (NBIoT) wireless communication in industrial indoor environment

A study of the behavior of NB-IoT wireless communication in an industrial indoor environment was conducted in this paper. With Wireless Insite software, a scenario in the industrial sector was simulated and modeled. Our research examined how this scenario or environment affected the communication parameters of NB-IoT’s physical layer. In this context, throughput levels among terminals as well as between terminals and transceiver towers, the power received at signal destination points, signal-to-noise ratios (SNRs) in the environment, and distances between terminals and transceivers are considered. These simulated results are also compared with the calculated or theoretical values of these parameters. The results show the effect of the industrial setting on wireless communication. The differences between the theoretical and simulated values are also established

Suitability of NB-IoT for indoor industrial environment: a survey and insights

The Internet of Things (IoT) and its applications in industrial settings are set to bring in the fourth industrial revolution. The industrial environment consisting of high profile manufacturing plants and a variety of equipment is inherently characterized by high reflectiveness, causing significant multi-path components that affect the propagation of wireless communications—a challenge among others that needs to be resolved. This paper provides a detailed insight into Narrow-Band IoT (NB-IoT), Industrial IoT (IIoT), and Wireless Sensor Networks (WSN) within the context of indoor industrial environments. It presents the applications of NB-IoT for industrial settings, such as the challenges associated with these applications. Furthermore, future research directions were put forth in the areas of NB-IoT network management using self-organizing network (SON) technology, edge computing for scalability enhancement, security in NB-IoT generated data, and proposing a suitable propagation model for reliable wireless communications

In Vitro Supplementation of Glycine Improves Quality of Cryopreserved Bull Semen

The extender supplementation of glycine on quality of cryopreserved bull sperm was reported in current study. Three adult Sahiwal bulls was used for semen collection by artificial vagina having 42°C (three weeks) (replicates; n=18)). Collected semen was quickly shifted to laboratory for initial evaluation. Qualified semen ejaculates (>60% motility, >1mL volume, >0.5billion/mL cons.) was diluted in tris extender having 0 (control), 5, 10 and 15 and 20mM of glycine. Cooling of extended semen to (4℃) was done in 2 hours and kept for 4 hours for equilibration. French straws were used for filling at (4℃), liquid nitrogen used for freezing. Highest percentages of post thaw sperm progressive motility and acrosome integrity were observed in extender containing 5mM of glycine compared to other treatments and control (P<0.05). However, glycine supplementation in extender didn’t affect viability, chromatin integrity and plasma membrane integrity of bull sperm. In conclusion, glycine addition at 5 mM in extender improves quality of cryopreserved bull semen

Career goals of trainee physicians in internal medicine

OBJECTIVE: To survey Internal Medicine trainees\u27 future career choices and factors influencing their decision-making. DESIGN: Cross-sectional study. PLACE AND DURATION OF STUDY: The Aga Khan University Hospital, Karachi, from November 2006 to January 2007. SUBJECTS AND METHODS: A standard questionnaire was administered to the residents and Interns working in the Department of Internal Medicine of The Aga Khan University Hospital. The questionnaire covered demographic details, specialty choice, work-time distribution and factors influencing career choice. Descriptive statistics were applied. RESULTS: A total of 49 doctors participated with 57% females; and 43% males, having 33% interns and 67% residents. A minority (22%) opted for internal medicine, while 78% selected sub-specialties with cardiology (20%) being the most sought- after sub-specialty. Majority (69%) wanted to spend more time in clinical activities compared to administration (18%) or research (13%). Majority (92%) wanted to work in an academic setting. Availability of a structured training program (61%), ability to practice broad area of medicine (41%) and prestige of the specialty (41%) highly influenced their career choices. Forty one (82%) wanted to proceed abroad for further training and 80% wanted to eventually practice in Pakistan. CONCLUSION: Most of the interviewed under-training physicians wanted to pursue sub-specialty. Clinical work was more attractive compared to research. A structured training program was detrimental in affecting their choices. Majority wanted further training abroad but eventual settlement in Pakistan. The study results can help us create the basis for reforming the current training programs

Mobility management-based autonomous energy-aware framework using machine learning approach in dense mobile networks

A paramount challenge of prohibiting increased CO2 emissions for network densification is to deliver the Fifth Generation (5G) cellular capacity and connectivity demands, while maintaining a greener, healthier and prosperous environment. Energy consumption is a demanding consideration in the 5G era to combat several challenges such as reactive mode of operation, high latency wake up times, incorrect user association with the cells, multiple cross-functional operation of Self-Organising Networks (SON), etc. To address this challenge, we propose a novel Mobility Management-Based Autonomous Energy-Aware Framework for analysing bus passengers ridership through statistical Machine Learning (ML) and proactive energy savings coupled with CO2 emissions in Heterogeneous Network (HetNet) architecture using Reinforcement Learning (RL). Furthermore, we compare and report various ML algorithms using bus passengers ridership obtained from London Overground (LO) dataset. Extensive spatiotemporal simulations show that our proposed framework can achieve up to 98.82% prediction accuracy and CO2 reduction gains of up to 31.83%

Chitosan/poly vinyl alcohol/graphene oxide based ph-responsive composite hydrogel films: drug release, anti-microbial and cell viability studies

The composite hydrogels were produced using the solution casting method due to the non-toxic and biocompatible nature of chitosan (CS)/polyvinyl alcohol (PVA). The best composition was chosen and crosslinked with tetraethyl orthosilicate (TEOS), after which different amounts of graphene oxide (GO) were added to develop composite hydrogels. Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), atomic force microscopy (AFM) and contact angle was used to analyze the hydrogels. The samples were also evaluated for swelling abilities in various mediums. The drug release profile was studied in phosphate-buffered saline (PBS) at a pH of 7.4. To predict the mechanism of drug release, the data were fitted into kinetic models. Finally, antibacterial activity and cell viability data were obtained. FTIR studies revealed the successful synthesis of CS/PVA hydrogels and GO/CS/PVA in hydrogel composite. SEM showed no phase separation of the polymers, whereas AFM showed a decrease in surface roughness with an increase in GO content. 100 µL of crosslinker was the critical concentration at which the sample displayed excellent swelling and preserved its structure. Both the crosslinked and composite hydrogel showed good swelling. The most acceptable mechanism of drug release is diffusion-controlled, and it obeys Fick’s law of diffusion for drug released. The best fitting of the zero-order, Hixson-Crowell and Higuchi models supported our assumption. The GO/CS/PVA hydrogel composite showed better antibacterial and cell viability behaviors. They can be better biomaterials in biomedical applications

Edge intelligence in private mobile networks for next generation railway systems

The integration of Private Mobile Networks (PMN) with edge intelligence is expected to play an instrumental role in realizing the next generation of industry applications. This combination collectively termed as Intelligent Private Networks (IPN) deployed within the scope of specific industries such as transport systems can unlock several use-cases and critical applications that in turn can address rising business demands. This article presents a conceptual IPN that hosts intelligence at the network edge employing emerging technologies that satisfy a number of Next Generation Railway System (NGRS) applications. NGRS use-cases along with their applications and respective beyond 5G (B5G) enabling technologies have been discussed along with possible future research and development directions that will allow these promising technologies to be used and implemented widely