A novel fuzzy programming approach for piece selection problem in P2P content distribution network.

Piece selection policy in dynamic P2P networks play crucial role and avoid the last piece problem. BitTorrent uses rarest-first piece selection mechanism to deal with this problem, but its efficacy is limited because each peer only has a local view of piece rareness. The problem of piece section is multiple objectives. A novel fuzzy programming approach is introduced in this article to solve the multiple objectives piece selection problem in P2P network, in which some of the factors are fuzzy in nature. Piece selection problem has been prepared as a fuzzy mixed integer goal programming piece selection problem that includes three primary goals such as minimizing the download cost, time, maximizing speed and useful information transmission subject to realistic constraints regarding peer's demand, capacity and dynamicity. The proposed approach has the ability to handle practical situations in a fuzzy environment and offers a better decision tool to each peer to select optimal pieces to download from other peers in dynamic P2P network. Extensive simulations are carried out to demonstrate the effectiveness of the proposed model. It is proved that proposed system outperforms existing with respect to download cost, time and meaningful exchange of useful information.

Preparedness of primary and secondary health facilities in India to address major noncommunicable diseases: results of a National Noncommunicable Disease Monitoring Survey (NNMS).

BACKGROUND: The monitoring framework for evaluating health system response to noncommunicable diseases (NCDs) include indicators to assess availability of affordable basic technologies and essential medicines to treat them in both public and private primary care facilities. The Government of India launched the National Program for Prevention and Control of Cancer, Diabetes, Cardiovascular diseases and Stroke (NPCDCS) in 2010 to strengthen health systems. We assessed availability of trained human resources, essential medicines and technologies for diabetes, cardiovascular and chronic respiratory diseases as one of the components of the National Noncommunicable Disease Monitoring Survey (NNMS - 2017-18). METHODS: NNMS was a cross-sectional survey. Health facility survey component covered three public [Primary health centre (PHC), Community health centre (CHC) and District hospital (DH)] and one private primary in each of the 600 primary sampling units (PSUs) selected by stratified multistage random sampling to be nationally representative. Survey teams interviewed medical officers, laboratory technicians, and pharmacists using an adapted World Health Organization (WHO) - Service Availability and Readiness Assessment (SARA) tool on handhelds with Open Data Kit (ODK) technology. List of essential medicines and technology was according to WHO - Package of Essential Medicines and Technologies for NCDs (PEN) and NPCDCS guidelines for primary and secondary facilities, respectively. Availability was defined as reported to be generally available within facility premises. RESULTS: Total of 537 public and 512 private primary facilities, 386 CHCs and 334 DHs across India were covered. NPCDCS was being implemented in 72.8% of CHCs and 86.8% of DHs. All essential technologies and medicines available to manage three NCDs in primary care varied between 1.1% (95% CI; 0.3-3.3) in rural public to 9.0% (95% CI; 6.2-13.0) in urban private facilities. In NPCDCS implementing districts, 0.4% of CHCs and 14.5% of the DHs were fully equipped. DHs were well staffed, CHCs had deficits in physiotherapist and specialist positions, whereas PHCs reported shortage of nurse-midwives and health assistants. Training under NPCDCS was uniformly poor across all facilities. CONCLUSION: Both private and public primary care facilities and public secondary facilities are currently not adequately prepared to comprehensively address the burden of NCDs in India.

Secondary transmission of SARS-CoV-2 through wastewater: Concerns and tactics for treatment to effectively control the pandemic.

The SARS-CoV-2 virus has spread globally and has severely impacted public health and the economy. Hand hygiene, social distancing, and the usage of personal protective equipment are considered the most vital tools in controlling the primary transmission of the virus. Converging evidence indicated the presence of SARS-CoV-2 in wastewater and its persistence over several days, which may create secondary transmission of the virus via waterborne and wastewater pathways. Although, researchers have started focusing on this mode of virus transmission, limited knowledge and societal unawareness of the transmission through wastewater may lead to significant increases in the number of positive cases. To emphasize the severe issue of virus transmission through wastewater and create societal awareness, we present a state of the art critical review on transmission of SARS-CoV-2 in wastewater and the potential remedial strategies to effectively control the viral spread and safeguard society. For low-income countries with high population densities, it is suggested to identify the virus in large scale municipal wastewater plants before following up with one-to-one testing for effective control of the secondary transmission. Ultrafiltration is an effective method for wastewater treatment and usually more than 4 logs of virus removal are achieved while safeguarding good protein permeability. Decentralized wastewater treatment facilities using solar-assisted disinfestation methods are most economical and can be effectively used in hospitals, isolation wards, and medical centers for reducing the risk of transmission from high local concentration sites, especially in tropical countries with abundant solar energy. Disinfection with chlorine, sodium hypochlorite, benzalkonium chloride, and peracetic acid have shown potential in terms of virucidal properties. Biological wastewater treatment using micro-algae will be highly effective in removal of virus and can be incorporated into membrane bio-reaction to achieve excellent virus removal rate. Though promising results have been shown by initial research for inactivation of SARS-CoV-2 in wastewater using physical, chemical and biological based treatment methods, there is a pressing need for extensive investigation of COVID-19 specific disinfectants with appropriate concentrations, their environmental implications, and regular monitoring of transmission. Effective wastewater treatment methods with high virus removal capacity and low treatment costs should be selected to control the virus spread and safeguard society from this deadly virus.

Fuzzy Expert System based on a Novel Hybrid Stem Cell (HSC) Algorithm for Classification of Micro Array Data.

In the growing scenario, microarray data is extensively used since it provides a more comprehensive understanding of genetic variants among diseases. As the gene expression samples have high dimensionality it becomes tedious to analyze the samples manually. Hence an automated system is needed to analyze these samples. The fuzzy expert system offers a clear classification when compared to the machine learning and statistical methodologies. In fuzzy classification, knowledge acquisition would be a major concern. Despite several existing approaches for knowledge acquisition much effort is necessary to enhance the learning process. This paper proposes an innovative Hybrid Stem Cell (HSC) algorithm that utilizes Ant Colony optimization and Stem Cell algorithm for designing fuzzy classification system to extract the informative rules to form the membership functions from the microarray dataset. The HSC algorithm uses a novel Adaptive Stem Cell Optimization (ASCO) to improve the points of membership function and Ant Colony Optimization to produce the near optimum rule set. In order to extract the most informative genes from the large microarray dataset a method called Mutual Information is used. The performance results of the proposed technique evaluated using the five microarray datasets are simulated. These results prove that the proposed Hybrid Stem Cell (HSC) algorithm produces a precise fuzzy system than the existing methodologies.

Road Accident Prevention with Instant Emergency Warning Message Dissemination in Vehicular Ad-Hoc Network.

A Road Accident Prevention (RAP) scheme based on Vehicular Backbone Network (VBN) structure is proposed in this paper for Vehicular Ad-hoc Network (VANET). The RAP scheme attempts to prevent vehicles from highway road traffic accidents and thereby reduces death and injury rates. Once the possibility of an emergency situation (i.e. an accident) is predicted in advance, instantly RAP initiates a highway road traffic accident prevention scheme. The RAP scheme constitutes the following activities: (i) the Road Side Unit (RSU) constructs a Prediction Report (PR) based on the status of the vehicles and traffic in the highway roads, (ii) the RSU generates an Emergency Warning Message (EWM) based on an abnormal PR, (iii) the RSU forms a VBN structure and (iv) the RSU disseminates the EWM to the vehicles that holds the high Risk Factor (RF) and travels in High Risk Zone (HRZ). These vehicles might reside either within the RSU's coverage area or outside RSU's coverage area (reached using VBN structure). The RAP scheme improves the performance of EWM dissemination in terms of increase in notification and decrease in end-to-end delay. The RAP scheme also reduces infrastructure cost (number of RSUs) by formulating and deploying the VBN structure. The RAP scheme with VBN structure improves notification by 19 percent and end-to-end delay by 14.38 percent for a vehicle density of 160 vehicles. It is also proved from the simulation experiment that the performance of RAP scheme is promising in 4-lane highway roads.

An Efficient Framework for Large Scale Multimedia Content Distribution in P2P Network: I2NC.

Network coding (NC) makes content distribution more effective and easier in P2P content distribution network and reduces the burden of the original seeder. It generalizes traditional network routing by allowing the intermediate nodes to generate new coded packet by combining the received packets. The randomization introduced by network coding makes all packets equally important and resolves the problem of locating the rarest block. Further, it reduces traffic in the network. In this paper, we analyze the performance of traditional network coding in P2P content distribution network by using a mathematical model and it is proved that traffic reduction has not been fully achieved in P2P network using traditional network coding. It happens due to the redundant transmission of noninnovative information block among the peers in the network. Hence, we propose a new framework, called I2NC (intelligent-peer selection and incremental-network coding), to eliminate the unnecessary flooding of noninnovative coded packets and thereby to improve the performance of network coding in P2P content distribution further. A comparative study and analysis of the proposed system is made through various related implementations and the results show that 10-15% of traffic reduced and improved the average and maximum download time by reducing original seeder's workload.

Emergency Situation Prediction Mechanism: A Novel Approach for Intelligent Transportation System Using Vehicular Ad Hoc Networks.

In Indian four-lane express highway, millions of vehicles are travelling every day. Accidents are unfortunate and frequently occurring in these highways causing deaths, increase in death toll, and damage to infrastructure. A mechanism is required to avoid such road accidents at the maximum to reduce the death toll. An Emergency Situation Prediction Mechanism, a novel and proactive approach, is proposed in this paper for achieving the best of Intelligent Transportation System using Vehicular Ad Hoc Network. ESPM intends to predict the possibility of occurrence of an accident in an Indian four-lane express highway. In ESPM, the emergency situation prediction is done by the Road Side Unit based on (i) the Status Report sent by the vehicles in the range of RSU and (ii) the road traffic flow analysis done by the RSU. Once the emergency situation or accident is predicted in advance, an Emergency Warning Message is constructed and disseminated to all vehicles in the area of RSU to alert and prevent the vehicles from accidents. ESPM performs well in emergency situation prediction in advance to the occurrence of an accident. ESPM predicts the emergency situation within 0.20 seconds which is comparatively less than the statistical value. The prediction accuracy of ESPM against vehicle density is found better in different traffic scenarios.

Study of morbidity profile of a rural population in Tamil Nadu.

OBJECTIVE: To identify the reported morbidity profile of people according to age, gender and organ system affected using International Classification of Diseases (ICD) coding, in a demographically defined area in Tamil Nadu in order to identify their health care needs and to plan appropriate interventions strategies. MATERIALS AND METHODS: This is a-cross sectional study using a convenience sample of 12308 persons sceened from the 41 panchayat units of the Kattankulathur block, comprising 90 villages with a population of about 2,00,890, over a period of one year. Diagnosis made were coded using ICD 10 version and data collected was analysed by appropriate statistical methods to explain the distribution of morbidity profile among the study population. RESULT: Out of total, 38.1% screened were males and 61.9% were females. Underfives were 5.3%, school going children 43.3%, adults 39.2% and elderly 12.3%. Majority had illness affecting respiratory system (20%), 'symptoms and signs' (19%), musculo-skeletal system (16.1%) and digestive system(11.9%). 'Symptoms and signs' classification, is a group of conditions which is of nonspecific diseases, signs, symptoms, abnormal findings and complaints, apart from the system specific conditions diagnosed properly and not elsewhere classified, More males were affeced with respiratory, digestive and illnesses with 'symptoms and signs' while more women were affected with musculo-skeletal problems. Only 9.7 % of patients reported with non-communicable diseases. Among them, 55 % women and 42.3 % men had osteoarthritis and 15.7 % women and 21.3 % men had cataract. About 15.8 % women and 18.1 % men had hypertension and other heart diseases while 9.7 % women and 8.4 % men had diabetes and 10.0 % men and 3.9 % women had chronic respiratory diseases. CONCLUSION: School going children and adults have higher levels of morbidity when compared to elderly and under five children. More females reported with illness but morbidity was found to be higher among males. The burden of illness increased with age. Acute ailments were responsible for high morbidity among children, while chronic ailments caused high morbidity among the elderly.

Epidemiological and clinical pattern of dermatomycoses in rural India.

Superficial fungal infections are most common in tropical and subtropical countries. In this study, 297 suspected superficial fungal infection cases were identified among 15,950 patients screened. The collected samples (skin, nail, and hair) were subjected to direct microscopy with potassium hydroxide and cultured on Sabourauds dextrose agar to identify the fungal species. The prevalence of superficial fungal infection was 27.6% (82/297), dermatophytosis was 75.6% (62/82), and non-dermatophytosis was 24.4% (20/82). Among the isolated dermatophytes, Trichophyton rubrum was the commonest species (79%) and Candida (60%) the commonest non-dermatophytic species. Tinea corporis was the commonest (78%) clinical presentation.

Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.

Healthcare decisions for individual patients and for public health policies should be informed by the best available research evidence. The practice of evidence-based medicine is the integration of individual clinical expertise with the best available external clinical evidence from systematic research and patient's values and expectations. Primary care physicians need evidence for both clinical practice and for public health decision making. The evidence comes from good reviews which is a state-of-the-art synthesis of current evidence on a given research question. Given the explosion of medical literature, and the fact that time is always scarce, review articles play a vital role in decision making in evidence-based medical practice. Given that most clinicians and public health professionals do not have the time to track down all the original articles, critically read them, and obtain the evidence they need for their questions, systematic reviews and clinical practice guidelines may be their best source of evidence. Systematic reviews aim to identify, evaluate, and summarize the findings of all relevant individual studies over a health-related issue, thereby making the available evidence more accessible to decision makers. The objective of this article is to introduce the primary care physicians about the concept of systematic reviews and meta-analysis, outlining why they are important, describing their methods and terminologies used, and thereby helping them with the skills to recognize and understand a reliable review which will be helpful for their day-to-day clinical practice and research activities.

Prevalence of overweight/obesity among the medical students, Malaysia.

BACKGROUND: Overweight and obesity are defined as abnormal or excessive fat accumulation that may impair health. Body mass index is a simple index of weight-for-height that is commonly used in classifying overweight and obesity in adult populations and individuals. OBJECTIVES: A study was conducted to screen the medical students of AIMST University for overweight/obesity using Body Mass Index(BMI) and to determine the prevalence among them. MATERIALS AND METHODS: This is an institution based cross sectional study was conducted among 290 medical students using a pre-tested questionnaire and measured their Body Mass Index (BMI). Data obtained was analyzed statistically by calculating proportions. RESULTS: Out of 290 students who participated in the study, 45.2% were males. In the study, 14.8% were found to be overweight (BMI 23-24.9 kg/m2); 13.7% of males and 15.7% of females. Pre-obese students (BMI 25-29kg/m2) accounted for 15.9% of the total (males 18.3% and females 13.8%). 5.2% were found to be obese (BMI > 30 kg/m2): males 9.2% and females 1.9%. Also 14.8% were found to be underweight (males 12.2% and females 17.0%). The study group consisted of 63.8% Indian, 32.4% Chinese and 3.8% Malay students. CONCLUSIONS: The study reveals that the prevalence of overweight and obesity among the medical students of AIMST University is on the high, which is comparable to the findings of earlier studies conducted in Malaysia, reinforcing the need to encourage healthy lifestyle, healthy food habits and a physically active daily routine, among the adolescents and youth of this country.

Evaluation of computer usage in healthcare among private practitioners of NCT Delhi.

OBJECTIVES: 1. To evaluate the usage and the knowledge of computers and Information and Communication Technology in health care delivery by private practitioners. 2. To understand the determinants of computer usage by them. METHODS: A cross sectional study was conducted among the private practitioners practising in three districts of NCT of Delhi between November 2007 and December 2008 by stratified random sampling method, where knowledge and usage of computers in health care and determinants of usage of computer was evaluated in them by a pre-coded semi open ended questionnaire. RESULTS: About 77% of the practitioners reported to have a computer and had the accessibility to internet. Computer availability and internet accessibility was highest among super speciality practitioners. Practitioners who attended a computer course were 13.8 times [OR: 13.8 (7.3 - 25.8)] more likely to have installed an EHR in the clinic. Technical related issues were the major perceived barrier in installing a computer in the clinic. CONCLUSION: Practice speciality, previous attendance of a computer course, age of started using a computer influenced the knowledge about computers. Speciality of the practice, presence of a computer professional and gender were the determinants of usage of computer.

Methotrexate loaded solid lipid nanoparticles (SLN) for effective treatment of carcinoma.

Solid Lipid Nanoparticles (SLN) containing Methotrexate (MTX), an anticancer drug for intravenous administration was formulated and characterized. The SLN dispersions with MTX, stearic acid, and soya lecithin in the ratio of 1:4:1, 1:4:1.5, and 1:4:2, sodium taurodeoxycholate and distilled water were prepared by micro emulsification solidification method. The results show that the prepared MTX-SLN particles (with MTX-Stearic acid-Soya lecithin--1:4:2) have an average size of 270 nm with 51.3% drug entrapment. The in-vitro release was attained up to 15th h. The pharmacokinetic study reveals that the half-life and MRT of SLNs were higher than MTX solution. The life span of EAC (Ehrlich Ascite Carcinoma) bearing mice was increased when treated with MTX-SLNs (Methotrexate nanoparticles). These results clearly indicate that SLNs are a promising sustained release drug targeting system for lipophilic antitumour drugs.