Factors Affecting Quality of Sleep in Intensive Care Unit

Background: The etiology of sleep disruption in intensive care unit is poorly known and often ignored complication. It is caused by the environmental factors especially pain, noise, diagnostic testing and human interventions that cause sleep disruption. Light, medications and activities related to patient care interfere with patient's ability to have good sleep. There are multi-factorial environmental etiologies for disruption of sleep in ICU. Objective: The objective of this study was to evaluate the factors disturbing the sleep quality in intensive care unit (ICU) admitted patients. Methodology: A cross sectional study was designed involving 150 patients admitted in intensive care unit and high dependency unit of Gulab Devi Chest Hospital. The duration of study was from September 2015 to March 2016. The questionnaire was made and filled with the help of patients. The data was analyzed using SPSS version 16.00. Results: Mean age of patients was 50.46+10.96 with maximum age of 65 and minimum age of 30 years. There was 53.33% male patients and 46.67% females participating in this study. The sleep quality was significantly poor in ICU than at home. After analysis, 54.67% patients were with poor quality of sleep due to pain and 48.67% were due to noise of environmental stimuli. The other factors were alarms, light and loud talking. Conclusion: Current study shows that reduced sleep quality is a common problem in ICU with multi-factorial etiologies. Patient reported the poor sleep quality in ICU due to environmental issues that are potentially modifiable. Conclusion: Current study shows that reduced sleep quality is a common problem in ICU with multi-factorial etiologies. Patient reported the poor sleep quality in ICU due to environmental issues that are potentially modifiable

From Fiscal Decentralisation to Economic Growt The Role of Complementary Institutions

Decentralisation is theoretically expected to be a platform towards efficient provision of the local public goods and services. This is expected to boost economic growth due to efficient and effective utilisation of scarce fiscal resources. Nevertheless, the existing empirical studies present mixed results on this expected positive relationship among decentralisation and economic growth. Recently, the theories of fiscal federalism have also pressed upon the enabling environment for effective decentralisation; talking explicitly, an enabling institutional setup is required. The current study explores the complementarity between fiscal decentralisation and other institutions for stimulating growth and the study uses rich crosscountry panel data for the period 1984 to 2012, covering both the developing and developed countries of the world. The results suggest that positive relationship exist between fiscal decentralisation and economic growth for the developed countries while evidence was not found in the case of developing countries. Further, it was found that fiscal decentralisation and quality institutions are complementary for economic growth. JEL Classification: C22, H11, H77, O40 Keywords: Fiscal Decentralisation, Institutions, Economic Growth, Panel Data, unequally spaced panel dat

Enhancing quality-of-service conditions using a cross-layer paradigm for ad-hoc vehicular communication

The Internet of Vehicles (IoVs) is an emerging paradigm aiming to introduce a plethora of innovative applications and services that impose a certain quality of service (QoS) requirements. The IoV mainly relies on vehicular ad-hoc networks (VANETs) for autonomous inter-vehicle communication and road-traffic safety management. With the ever-increasing demand to design new and emerging applications for VANETs, one challenge that continues to stand out is the provision of acceptable QoS requirements to particular user applications. Most existing solutions to this challenge rely on a single layer of the protocol stack. This paper presents a cross-layer decision-based routing protocol that necessitates choosing the best multi-hop path for packet delivery to meet acceptable QoS requirements. The proposed protocol acquires the information about the channel rate from the physical layer and incorporates this information in decision making, while directing traffic at the network layer level. Key performance metrics for the system design are analyzed using extensive experimental simulation scenarios. In addition, three data rate variant solutions are proposed to cater for various application-specific requirements in highways and urban environments. © 2013 IEEE

EFFECT OF JOB STRESS ON JOB SATISFACTION OF PHYSICAL EDUCATION TEACHERS WORKING IN GOVERNMENT COLLEGES

The current research is an attempt to examine the effect of job stress on job satisfaction of physical education teachers working in government colleges, Khyber Pakhtunkhwa (KP), Pakistan. A cross-sectional research method was used to collect required data from a finite population N=170 (males=97; females=73). Self-made questionnaires namely, Job Stress Questionnaire (JSQ) and Job Satisfaction Questionnaire (JSQ) were developed and used for the collection of required data. A statistical package for social sciences (SPSS), version; 26 was used to analyze the collected data, revealing negligible and inverse correlation (-.887, -.633 & -.721). The study revealed a significant impact of job stressors on job satisfaction (p < .05). Additionally, male physical education teachers reported a higher mean score on various variables included in the study (p < .05). These findings help policymakers to devise a uniform human policy that could protect the interests of the physical education teachers to share responsibilities of carving out the future of the country.  Â

INTERFERON REGULATORY FACTOR -2 REGULATES HEMATOPOIETIC STEM CELLS

The concept of a hematopoietic niche was first proposed in 1978, and the overall concept of a stem cell niche was first demonstrated in Drosophila gonads (1–3). Within mammalian bone marrow, hematopoietic stem and progenitor cells (HSPCs) interact with a variety of cells and signals, which constitute their niche or microenvironment. Cells of the microenvironment, through either direct contact or through secreted factors, can influence HSPC behaviour in the marrow. These micro environmentally imposed signals can regulate stem cell fate decisions, self-renewal, and residence in the marrow and are critical to maintaining the stem cell pool. Disruption of these signals in the microenvironment can lead to stem cell depletion, altered haematopoiesis, and malignancy. Over the past 10 years, numerous cell types and molecules of the HSPC niche have been identified and are discussed in several comprehensive reviews. Our research will focus on the cellular components of the hematopoietic stem cell (HSC) niche that are targets for hormonal signals (specifically, mesenchymal stem cells [MSCs] and the osteoblastic lineage as well as adipocytes) and how hormonal signals and signalling pathways are integrated in the bone marrow microenvironment

Machine Learning Techniques for 5G and beyond

Wireless communication systems play a very crucial role in modern society for entertainment, business, commercial, health and safety applications. These systems keep evolving from one generation to next generation and currently we are seeing deployment of fifth generation (5G) wireless systems around the world. Academics and industries are already discussing beyond 5G wireless systems which will be sixth generation (6G) of the evolution. One of the main and key components of 6G systems will be the use of Artificial Intelligence (AI) and Machine Learning (ML) for such wireless networks. Every component and building block of a wireless system that we currently are familiar with from our knowledge of wireless technologies up to 5G, such as physical, network and application layers, will involve one or another AI/ML techniques. This overview paper, presents an up-to-date review of future wireless system concepts such as 6G and role of ML techniques in these future wireless systems. In particular, we present a conceptual model for 6G and show the use and role of ML techniques in each layer of the model. We review some classical and contemporary ML techniques such as supervised and un-supervised learning, Reinforcement Learning (RL), Deep Learning (DL) and Federated Learning (FL) in the context of wireless communication systems. We conclude the paper with some future applications and research challenges in the area of ML and AI for 6G networks. © 2013 IEEE

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Hospital-based ultra-sonographic prevalence and spectrum of thyroid incidentalomas in Pakistani population

Introduction: Thyroid incidentalomas (TIs) are clinically asymptomatic nodules found accidentally during imaging studies ordered for some other reasons. Being easily accessible, non-invasive, and inexpensive, thyroid ultrasound (US) is a key investigation in the management of thyroid nodules.Methods: This ultrasound-based cross-sectional study was performed in the radiology department of a major tertiary care hospital. Every second patient visiting the emergency department was a potential candidate for a thyroid ultrasound. Patients having ages greater than 20 years were included in the study.Results: A total of 250 patients were included in the study. Out of these, 175 were female and 75 were male. The majority (54.80%) were in the age group 21-30 years. Nodules were found in 65 (26%) patients and in the majority of cases (67.7%) they were multiple in number. Associated lymphadenopathy was seen in only one patient. Thyroid nodules were more common in females as compared to males (75.38% versus 24.62%). According to Thyroid Imaging and Reporting Data System (TI-RADS) classification, the majority of the nodules were falling in TI-RADS 1 (74%) followed by TI-RADS 3 (9.60%) and 4A (8.80%).Conclusion: The thyroid nodules are more commonly seen in females as compared to males. A significant association is seen between the frequency of thyroid nodules and increasing age. The majority of thyroid nodules fall in TI-RADS 1 category followed by TI-RADS 3 and 4A