Computer users at risk: Health disorders associated with prolonged computer use

By keeping in view the ISO standards which emphasize the assessment of use of a product, this research aims to assess the prolonged use of computers and their effects on human health. The objective of this study was to investigate the association between extent of computer use (per day) and carpal tunnel syndrome, computer stress syndrome, computer vision syndrome and musculoskeletal problems. The second objective was to investigate the extent of simultaneous occurrence of carpal tunnel syndrome, stress, computer vision syndrome and musculoskeletal disorders among computer users. The sample in this exploratory study consisted of 120 employees and students. Self administered questionnaire was used as an instrument in this field survey study. The findings confirmed that computer related health disorders such as carpal tunnel syndrome, stress, computer vision syndrome and musculoskeletal disorders occur simultaneously among prolonged computer users such as employees and students. The simultaneous occurrence of carpal tunnel syndrome, stress, computer vision syndrome and musculoskeletal disorders is more among employees than students and those who are both employees and students. Employees who use computer daily for more than four hours are more likely subjected to the risks of all these four health disorders. The study concludes that by observing some rules of using computer, minimizing and treating of these disorders are possibleKeywords: Computer, Prolonged use, Carpal Tunnel Syndrome, Computer Vision Syndrome, Health Disorders, Employees, Students.

Mainstreaming prevention: Prescribing fruit and vegetables as a brief intervention in primary care

This is the author's PDF version of an article published in Public health© 2005.This articles discusses a project at the Castlefields Health Centre in Halton whereby primary care professionals issue a prescription for discounts on fruit and vegetables. The prescription is explicitly linked to the five-a-day message

Convection of heat and thermodynamic irreversibilities in two-phase, turbulent nanofluid flows in solar heaters by corrugated absorber plates

The effects of simultaneous implementation of corrugated walls and nanoparticles upon the performance of solar heaters are investigated. Triangular and sinusoidal wall profiles along with varying concentration of nanoparticles are analyzed. The multi-phase mixture and the SST κ-ω models are used to simulate turbulent nanofluid flows inside the corrugated channels. The staggered computational grid is employed for storing the velocity and pressure terms at cell faces and cell center, respectively. The governing equations are first discretized by employing a second-order upwind differencing technique and are then solved by means of pressure-based finite volume approach. The convergence criterion is also presented for the validation of obtained results. The effects of wall profiles and nanoparticle concentration on the pertinent parameters including Nusselt number, pressure drop, performance evaluation criterion (PEC), and thermal and frictional irreversibilities are studied. This reveals that, in general, the triangular duct features superior heat transfer and inferior hydraulic characteristics in comparison with the sinusoidal duct. It is demonstrated that as long as the base fluid (water) is used the highest value of PEC corresponds to the straight duct. Yet, by introducing nanofluids the PEC values of the corrugated ducts exceed those of the straight duct. The analysis further shows that on the basis of the performance evaluation criterion, the sinusoidal duct appears to be a better choice in comparison with the triangular duct. However, the situation is reversed when thermodynamic irreversibilities are considered. It is argued that vortex formation in the two investigated wavy walls and shear layer developed in the triangular case are the essential physical reasons for the observed thermal, hydraulic and entropic behaviors

Diagnosis and monitoring of Alzheimer's patients using classical and deep learning techniques

Machine based analysis and prediction systems are widely used for diagnosis of Alzheimer's Disease (AD). However, lower accuracy of existing techniques and lack of post diagnosis monitoring systems limit the scope of such studies. In this paper, a novel machine learning based diagnosis and monitoring of AD-like diseases is proposed. The AD-like diseases diagnosis process is accomplished by analysing the magnetic resonance imaging (MRI) scans using deep learning and is followed by an activity monitoring framework to monitor the subjects’ activities of daily living using body worn inertial sensors. The activity monitoring provides an assistive framework in daily life activities and evaluates vulnerability of the patients based on the activity level. The AD diagnosis results show up to 82% improvement in comparison to well-known existing techniques. Moreover, above 95% accuracy is achieved to classify the activities of daily living which is quite encouraging in terms of monitoring the activity profile of the subject

An integrated decanter centrifuge-pitot pump

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1996.Includes bibliographical references.M. Farooq Ellahi.M.S

CuO–Water Nanofluid Magnetohydrodynamic Natural Convection inside a Sinusoidal Annulus in Presence of Melting Heat Transfer

Impact of nanofluid natural convection due to magnetic field in existence of melting heat transfer is simulated using CVFEM in this research. KKL model is taken into account to obtain properties of CuO–H2O nanofluid. Roles of melting parameter (δ), CuO–H2O volume fraction (ϕ), Hartmann number (Ha), and Rayleigh (Ra) number are depicted in outputs. Results depict that temperature gradient improves with rise of Rayleigh number and melting parameter. Nusselt number detracts with rise of Ha. At the end, a comparison as a limiting case of the considered problem with the existing studies is made and found in good agreement

Genetska raznolikost Mareecha i Barela pasmina jednogrbih deva iz Pakistana na temelju mikrosatelitskih markera

The genetic diversity of Pakistani dromedary camels is poorly documented. The present study evaluated the genetic variations of two well-known Pakistani camel breeds, Mareecha and Barela, that are well-adapted to the Cholistan desert climate. Camel can serve as a beneficial participant in the food supply chain by providing milk, meat and other food products for the livelihood of pastoral peoples. To explore a new world of resources, greater attention to needed to create standard procedures to genetically characterize, classify and identify camel breeds in the country. For this purpose, 66 unrelated animals of the Mareecha (n=35) and Barela (n=31) breeds were genotyped using a set of 12 labelled microsatellite loci. DNA fragment sizes were determined in an ABI 3130 Genetic Analyzer. All microsatellite markers were successfully amplified and exhibited a polymorphic nature, with an average Polymorphic Information Content (PIC) of 0.72 and 0.70 in Mareecha and Barela, respectively. A total of 107 alleles with an average of 8.91 alleles per locus were identified by these markers in both breeds. CMS15 was highly polymorphic with 13 alleles, while VOLP-032 was the lowest with two loci. The Fit and Fis values were low but high population differentiation (17%) was observed in both breeds, due to the migrations of pastoral people to different remote areas during climate fluctuations.Genetska raznolikost pakistanskih jednogrbih deva slabo je dokumentirana. Ova studija procijenila je genetske varijacije dviju dobro poznatih pasmina pakistanskih deva - mareecha i barela - koje su vrlo dobro prilagođene klimi pustinje Cholistan. Deva može poslužiti kao koristan sudionik u lancu opskrbe hranom, osiguravajući mlijeko, meso i druge prehrambene proizvode za život pastira. Da bi se istražio novi svijet resursa, potrebno je više pozornosti za obavljanje standardnih postupaka za genetsku karakterizaciju, razvrstavanje i identifikaciju pasmina deva u zemlji. U tu svrhu, ukupno 66 životinja koje nisu u srodstvu pasmine mareecha (n=35) i barela (n=31) genotipizirane su uporabom 12 označenih mikrosatelitskih lokusa. Veličine fragmenata DNK određene su u ABI 3130 genetskom analizatoru. Svi mikrosatelitski markeri uspješno su pojačani i pokazali su polimorfnu narav s prosječnim sadržajem polimorfnih informacija (PIC) od 0,72 i 0,70 za mareecha, odnosno barela pasminu. Ukupno 107 alela s prosječno 8,91 alelom po lokusu u obje pasmine identificirano je tim markerima. CMS15 bio je vrlo polimorfan s 13 alela dok je VOLP-032 bio najniži s 2 lokusa. Fit i Fis vrijednosti bile su niske, ali je uočena velika diferencijacija populacije (17 %) za obje pasmine koje su posljedica migracije pastira u različite udaljene krajeve tijekom promjena klime

Diagnosis and monitoring of Alzheimer's patients using classical and deep learning techniques

Machine based analysis and prediction systems are widely used for diagnosis of Alzheimer's Disease (AD). However, lower accuracy of existing techniques and lack of post diagnosis monitoring systems limit the scope of such studies. In this paper, a novel machine learning based diagnosis and monitoring of AD-like diseases is proposed. The AD-like diseases diagnosis process is accomplished by analysing the magnetic resonance imaging (MRI) scans using deep learning and is followed by an activity monitoring framework to monitor the subjects’ activities of daily living using body worn inertial sensors. The activity monitoring provides an assistive framework in daily life activities and evaluates vulnerability of the patients based on the activity level. The AD diagnosis results show up to 82% improvement in comparison to well-known existing techniques. Moreover, above 95% accuracy is achieved to classify the activities of daily living which is quite encouraging in terms of monitoring the activity profile of the subject

Dietary Calcium Intake, Vitamin D Status, and Bone Health in Postmenopausal Women in Rural Pakistan

The high prevalence of osteoporosis in Pakistan is of public-health concern. However, there is a paucity of information regarding nutrition and bone density in rural communities. The purpose of this study was to evaluate the dietary and lifestyle factors that impact bone health in Nahaqi. Data were collected from 140 postmenopausal women using an interviewer-administered 24-hour dietary recall questionnaire. Bone mineral density was estimated using the quantitative ultrasound index (QUI). Serum 25(OH)D was measured in fasting blood samples. The QUI scores revealed that 42% and 29% of the women had T-scores, indicative of osteopaenia and osteoporosis respectively. The mean calcium intake was 346 mg/d, which is less than 50% of the recommended daily intake. The QUI correlated with 25(OH)D after controlling for age (p=0.021, r=0.41, r2=0.168). Vitamin D deficiency and low intake of dietary calcium are two key factors contributing to poor bone health in this population