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

R-PEKS: RBAC Enabled PEKS for Secure Access of Cloud Data

In the recent past, few works have been done by combining attribute-based access control with multi-user PEKS, i.e., public key encryption with keyword search. Such attribute enabled searchable encryption is most suitable for applications where the changing of privileges is done once in a while. However, to date, no efficient and secure scheme is available in the literature that is suitable for these applications where changing privileges are done frequently. In this paper our contributions are twofold. Firstly, we propose a new PEKS scheme for string search, which, unlike the previous constructions, is free from bi-linear mapping and is efficient by 97% compared to PEKS for string search proposed by Ray et.al in TrustCom 2017. Secondly, we introduce role based access control (RBAC) to multi-user PEKS, where an arbitrary group of users can search and access the encrypted files depending upon roles. We termed this integrated scheme as R-PEKS. The efficiency of R-PEKS over the PEKS scheme is up to 90%. We provide formal security proofs for the different components of R-PEKS and validate these schemes using a commercial dataset

Dichromacy: Color Vision Impairment and Consanguinity in Heterogenous Population of Pakistan

Background and Objectives: Dichromacy, an X-linked recessive disorder is identified worldwide, more in males than females. In European Caucasians, its incidence is 8% in males and 0.5% in females. In India, it is 8.73% in males and 1.69% in females, and in Iran, it is 8.18% in males and 0.43% in females. Population based epidemiological data about dichromacy in different ethnic groups in Pakistan is not available. The aim of this study was to find out the population prevalence of inherited red-green dichromacy in a heterogenous population of the district of Chiniot, Punjab, Pakistan, and to determine the impact of consanguinity and ethnicity. Methods: In this cross-sectional study, boys and girls of the higher secondary schools were examined in the three tehsils of district Chiniot. Pseudoisochromatic Ishihara Test has been employed for detection of dichromacy in the study population. The sample size was calculated statistically as 260, which was expanded to 705 and divided by population density of the three tehsils. Results: Screening of 359 males and 346 females revealed 19 (5.29%) dichromat males and only 2 (0.58%) females. The study population belonged to 23 castes / isonym groups. The consanguinity found in the district of Chiniot is 84.82% and in the dichromat families, it is 85.71%, of which 52.37% are first cousin. Interpretation & Conclusion: The study has shown that the incidence of dichromacy could be reduced through genetic counselin

Risk Factors of Diarrhoea in Malnourished Children Under Age of 5 Years

Background: Acute infectious enteritis remains one of the commonest causes of death among infants and children in developing countries. Acute enteritis is defined as a loss of stool consistency with pasty or liquid stools, and/or an increase in stool frequency to more than three stools in 24 hours with or without fever or vomiting. Human survival depends on the secretion and reabsorption of fluid and electrolytes in the intestinal tract. The objective of the study is to evaluate the risk factors of diarrhoea in children under age of 5 years. Methodology: It was an observational study. Study was completed in about six months. Non-probability purposive sampling technique was used. In this study, 270 samples were taken from Diarrheal ward of The Children Hospital Lahore, Pakistan. Results: In this study, out of 270 patients, 58.52% were males and 41.48% were females. 90.37% patients were vaccinated. 54.81% had weaning history. 91.85% patients had feeding history. 29.26% had blood in stool. 96.67% patients were dehydrated. 95.56% patients had loose watery diarrhoea. 62.96% patients used boiled water. 58.52% patients consumed less than half litre of water, 30.00% patients consumed 1 litre of water and 11.48% patients consumed > 1 litre of water. 49.18% patients had proper hygiene. 38.15% mothers of patients were well educated. 40.37% patients had model household condition. 57.41% patients lived in rural area and 42.59% patients lived in urban area. Conclusion: The variation in the level of diarrheal morbidity was well explained by maternal education, income, personal hygiene, refuse disposal system and the effect of health extension programme

On the Complexity of Average Path length for Biological Networks and Patterns

Path length calculation is a frequent requirement in studies related to graph theoretic problems such as genetics. Standard method to calculate average path length of a graph requires traversing all nodes in the graph repeatedly, which is computationally expensive for graphs containing large number of nodes. We propose a novel method to calculate average path length for graphs commonly required in the studies of genetics. The proposed method is computationally less expensive and less time consuming compared to standard method. In this paper, a mathematical formulation is provided that calculates Average Path Length for graphs commonly present in biological networks, at the cost of uniform time complexity, for different size of networks

Full-field and anomaly initialization using a low-order climate model: a comparison and proposals for advanced formulations

Initialization techniques for seasonal-to-decadal climate predictions fall into two main categories; namely full-field initialization (FFI) and anomaly initialization (AI). In the FFI case the initial model state is replaced by the best possible available estimate of the real state. By doing so the initial error is efficiently reduced but, due to the unavoidable presence of model deficiencies, once the model is let free to run a prediction, its trajectory drifts away from the observations no matter how small the initial error is. This problem is partly overcome with AI where the aim is to forecast future anomalies by assimilating observed anomalies on an estimate of the model climate. The large variety of experimental setups, models and observational networks adopted worldwide make it difficult to draw firm conclusions on the respective advantages and drawbacks of FFI and AI, or to identify distinctive lines for improvement. The lack of a unified mathematical framework adds an additional difficulty toward the design of adequate initialization strategies that fit the desired forecast horizon, observational network and model at hand. Here we compare FFI and AI using a low-order climate model of nine ordinary differential equations and use the notation and concepts of data assimilation theory to highlight their error scaling properties. This analysis suggests better performances using FFI when a good observational network is available and reveals the direct relation of its skill with the observational accuracy. The skill of AI appears, however, mostly related to the model quality and clear increases of skill can only be expected in coincidence with model upgrades. We have compared FFI and AI in experiments in which either the full system or the atmosphere and ocean were independently initialized. In the former case FFI shows better and longer-lasting improvements, with skillful predictions until month 30. In the initialization of single compartments, the best performance is obtained when the stabler component of the model (the ocean) is initialized, but with FFI it is possible to have some predictive skill even when the most unstable compartment (the extratropical atmosphere) is observed. Two advanced formulations, least-square initialization (LSI) and exploring parameter uncertainty (EPU), are introduced. Using LSI the initialization makes use of model statistics to propagate information from observation locations to the entire model domain. Numerical results show that LSI improves the performance of FFI in all the situations when only a portion of the system's state is observed. EPU is an online drift correction method in which the drift caused by the parametric error is estimated using a short-time evolution law and is then removed during the forecast run. Its implementation in conjunction with FFI allows us to improve the prediction skill within the first forecast year. Finally, the application of these results in the context of realistic climate models is discussed

DNA amplified fingerprinting, a useful tool for determination of genetic origin and diversity analysis in Citrus

We used three short repetitive nucleotide sequences [(GTG)5, (TAC)5, and (GACA)4] either as radiolabeled probes for hybridization with restricted Citrus DNA or as single primers in polymerase chain reaction amplification experiments with total genomic DNA. We tested the ability of the sequences to discriminate between seedlings of zygotic or nuclear origin in the progeny of a Volkamer lemon #Citrus volkameriana# Ten. & Pasq.) tree. The genetic variability within two species [#Citrus sinensis# (L.) Osbeck (sweet oranges) and #Citrus reticulata# Blanco and relatives (mandarins)] was evaluated. DNA amplified figerprinting with single primers was the more successful technique for discriminating between nucellular and zygotic seedlings. Although we were not able to distinguish among 10 cultivars of #C. sinensis#, all 10 #C. reticulata# cultivars tested were distinguishable. However, it still is difficult to identify the putative parents of a hybrid plant when the two parental genomes are closely related. (Résumé d'auteur

Enhanced Version of Multi-algorithm Genetically Adaptive for Multiobjective optimization

Abstract: Multi-objective EAs (MOEAs) are well established population-based techniques for solving various search and optimization problems. MOEAs employ different evolutionary operators to evolve populations of solutions for approximating the set of optimal solutions of the problem at hand in a single simulation run. Different evolutionary operators suite different problems. The use of multiple operators with a self-adaptive capability can further improve the performance of existing MOEAs. This paper suggests an enhanced version of a genetically adaptive multi-algorithm for multi-objective (AMAL-GAM) optimisation which includes differential evolution (DE), particle swarm optimization (PSO), simulated binary crossover (SBX), Pareto archive evolution strategy (PAES) and simplex crossover (SPX) for population evolution during the course of optimization. We examine the performance of this enhanced version of AMALGAM experimentally over two different test suites, the ZDT test problems and the test instances designed recently for the special session on MOEA?s competition at the Congress of Evolutionary Computing of 2009 (CEC?09). The suggested algorithm has found better approximate solutions on most test problems in terms of inverted generational distance (IGD) as the metric indicator. - See more at: http://thesai.org/Publications/ViewPaper?Volume=6&Issue=12&Code=ijacsa&SerialNo=37#sthash.lxkuyzEf.dpu

Enhanced Arabic disaster data classification using domain adaptation

Natural disasters, like pandemics and earthquakes, are some of the main causes of distress and casualties. Governmental crisis management processes are crucial when dealing with these types of problems. Social media platforms are among the main sources of information regarding current events and public opinion. So, they have been used extensively to aid disaster detection and prevention efforts. Therefore, there is always a need for better automatic systems that can detect and classify disaster data of social media. In this work, we propose enhanced Arabic disaster data classification models. The suggested models utilize domain adaptation to provide state-of-the-art accuracy. We used a standard dataset of Arabic disaster data collected from Twitter for testing the proposed models. Experimental results show that the provided models significantly outperform the previous state-of-the-art results

Frequency of Clinical Symptoms of Gastroesophageal Reflux Disease in Asthmatic Patients

Background: Gastroesophageal reflex is known as an acid reflex, is long term condition where stomach contents back into the oesophagus resulting in either symptoms or complications. GERD disease is caused by weakness or failure of the lower oesophageal sphincter. Symptoms include the acidic taste behind the mouth, heart burn, chest pain, difficult breathing and vomiting. Complication includes esophagitis, oesophageal strictures and barrettes oesophagus. Objective: The aim of this research was to introduce the symptoms of GERD disease in asthmatic patients and how these symptoms worsen the symptoms of asthma disease and what clinical pictures present with the asthmatic disease. Methodology: A designed performa was used to collect the data and after filling the performa, results were drawn and conclusion through the facts and the information given by patients. Results: In the present study among all 164 asthmatic patients, 70 (42.7%) patients showed dyspepsia, 58 (35.4%) were with chest burning, 23 (14%) were asking about chest pain, with acidic mouth taste were 39 (23.8%), 22 (13.4%) were feeling sore throat and 44 (26.8%) showed regurgitation reflex. Among these 164 patients 16 (9.8%) were smokers and 148 (90.2 %) were non-smokers. 47 (28.7%) were males and 117 (71.3%) were females. Conclusion: It is concluded that gastroesophageal reflux disease in asthmatic patients present symptoms of acidic mouth taste, chest burning, chest pain, dyspepsia, regurgitation reflex and sore throat