SEMANTIC BASED E-LEARNING RECOMMENDER SYSTEM

Introduction of new technologies in the last few decades have brought about some innovative methods in web-based education. However many of these online courses provide universal static solution which do not cater the individual needs of the learner. Recommender system has been successfully recommending items such as books, movies, news articles etc however recommendation techniques applied in the e-learning domain are relatively new. Many of the techniques applied in the e-learning domain are generic and usually derived from other domains. This paper will present semantic based recommender system for e-learner to facilitate effective learning. We use a novel alternative to conventional recommendation techniques by considering a social network tool such as twitter which is popular for information sharing. Relevant tweets are recommended to the learner as per the current learning topic of the learner

Effect of COVID-19 on Clinical Spectrum of patients presenting to the Dermatology Outpatient Department of a Tertiary Care Hospital in Rawalpindi

Introduction: COVID-19 has significantly decreased the influx of patients presenting with dermatologic diseases at hospitals due to lockdown and restrictions pertaining to stop the spread of COVID-19. Objective: To describe the effect of changes of COVID-19 on the clinical spectrum of patients presenting in dermatology OPD at a tertiary care unit in Rawalpindi, Pakistan. Method: A comparison of the census of the dermatology outpatient department of three corresponding months before and after COVID-19 was done. During the pandemic year (2020) a significant decrease in patients visiting the dermatology outpatient department was observed. Results: This reduction was much more prominent for the extreme of ages i.e. children and elderly. Infections and infestations were the predominant causes of presentation of patients at our dermatology outpatient department in pre-COVID-19 as well as during the pandemic. Patients with serious dermatologic conditions (e.g., pemphigus vulgaris, erythroderma, and cellulitis), however, had significantly fewer visits during the pandemic as compared to Pre COVID-19 era. In contrast, patients suffering from eczema constituted a significantly higher rate of outpatient visits during the pandemic. Conclusion: Patients with serious dermatologic conditions (e.g., pemphigus vulgaris, erythroderma, and cellulitis), had significantly fewer visits during the pandemic as compared to the Pre COVID-19 era. In contrast, patients suffering from eczema constituted a significantly higher rate of outpatient visits during the pandemic

Comparative Antibacterial Analysis of Four Different Medicinal Plants Against Human Skin Flora

Background: As we are facing continuously increasing antibiotic resistance, increased infections, diseases and pandemics, the researching community is turning to find the solutions from nature and plants play a vital role in this scenario. Pakistan due to its unique geography and a variety of climatic zones harbors a huge floral diversity.Methods: In this study extracts of four plants of Pakistan namely Azadirachta indica, Curcuma longa, Moringa oleifera and Eucalyptus camaldulensis prepared by Aqueous. Ethanol and Methanol extract preparation methods were examined for their phytochemical content by employing various reagents and methods like foam test for saponins, xanthoprotein test for proteins, Braemar’s test for tannins etc. Antibacterial activity against stored human skin flora samples was performed using the agar well diffusion assay and statistical analysis was performed using ANOVA one way analysis on Microsoft Excel 2010.Result: Each plant extract exhibited antibacterial activity and statistical analysis performed for extracts of each plant showed p value for A. indica as 0.36 (P > 0.05), for C. longa as 0.09 (P > 0.05), for M. oleifera as 0.67 (P > 0.05) and for E. camaldulensis as 0.02 (P < 0.05), which indicates significant antibacterial activity of E. camaldulensis depending on the size of zones of inhibition produced by it. Conclusion: All the extracts prepared from selected plants showed some degree of antibacterial activity against the human skin flora that can also act as opportunistic pathogen. This supports the use of traditionally used plants and herbs for fighting present day soaring health related issues as antimicrobial resistance. Study also suggests further investigations for estimating exact concentrations of extracts to be used that work efficiently in relevant cases and molecular mechanism of action of these extracts.Keywords: Skin Flora; Antibiotic Resistant; Plant Extract; Antibacterial Activity, Medicinal plants   

An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm

Natural scene text classification is considered to be a challenging task because of diversified set of image contents, presence of degradations including noise, low contrast/resolution and the random appearance of foreground (font, style, sizes and orientations) and background properties. Above all, the high dimension of the input image's feature space is another major problem in such tasks. This work is aimed to tackle these problems and remove redundant and irrelevant features to improve the generalization properties of the classifier. In other words, the selection of a qualitative and discriminative set of features, aiming to reduce dimensionality that helps to achieve a successful pattern classification. In this work, we use a biologically inspired genetic algorithm because crossover employed in such algorithm significantly improve the quality of multimodal discriminative set of features and hence improve the classification accuracy for diversified natural scene text images. The Support Vector Machine (SVM) algorithm is used for classification and the average F-Score is used as fitness function and target condition. First after preprocessing input images, the whole feature space (population) is built using a multimodal feature representation technique. Second, a feature level fusion approach is used to combine the features. Third, to improve the average F-score of the classifier, we apply a meta-heuristic optimization technique using a GA for feature selection. The proposed algorithm is tested on five publically available datasets and the results are compared with various state-of-the-art methods. The obtained results proved that the proposed algorithm performs well while classifying textual and non-textual region with better accuracy than benchmark state-of-the-art algorithms.Qatar University [QUHI-CBE-21/22-1]

Trackable CEMB-Klean Cotton Transgenic Technology: Affordable Climate Neutral Agri-biotech Industrialization for Developing Countries

Background: Transgenic technology reflects the incorporation of novel useful traits in crop plants like cotton for economic benefits by overcoming the problems including insects’ pests and weeds in special. The present study is the success story of the continuous effort of CEMB team started back in the 1990s.Methods: This study includes characterization of a large number of Bacillus thuringiensis (Bt) strains taken from local soil and subjected to direct transformation of isolated BT genes into local cotton cultivars. Protocols for transformation into cotton plants were optimized and validated by the development of double gene codon optimized (Cry1Ac and Cry2A) transgenic cotton varieties.Results: The resulting GMOs in the form of CEMB-33, CA-12, CEMB-66 have been approved by Punjab Seed Council in 2013 and 2016 respectively. Double Bt and weedicide resistant cotton harboring CEMB-Modified and codon optimized cp4EPSPS (GTGene). These varieties can tolerate glyphosate spray @ 1900ml per acre without the appearance of necrotic spots/shedding and complete removal of all surrounding weeds in the cotton field is a significant advance to boost cotton production without spending much on insecticides and herbicides.Conclusion: In the current report, two unique sets of primers which amplify 1.1 Kb for CEMB-double Bt genes and 660 bp product for CEMB-Modified cp4EPSPS (GTGene) were tested. CEMB cotton variety CKC-01 is specially designed as low cost and easy to use by local farmer’s technology has the potential to revolutionize the cotton growing culture of the country.Keywords: Event detection; Bt Cotton; CEMB transgenic technology; GTGen

Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.

Traumatic brain injury (TBI) and spinal cord injury (SCI) are increasingly recognised as global health priorities in view of the preventability of most injuries and the complex and expensive medical care they necessitate. We aimed to measure the incidence, prevalence, and years of life lived with disability (YLDs) for TBI and SCI from all causes of injury in every country, to describe how these measures have changed between 1990 and 2016, and to estimate the proportion of TBI and SCI cases caused by different types of injury. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016 to measure the global, regional, and national burden of TBI and SCI by age and sex. We measured the incidence and prevalence of all causes of injury requiring medical care in inpatient and outpatient records, literature studies, and survey data. By use of clinical record data, we estimated the proportion of each cause of injury that required medical care that would result in TBI or SCI being considered as the nature of injury. We used literature studies to establish standardised mortality ratios and applied differential equations to convert incidence to prevalence of long-term disability. Finally, we applied GBD disability weights to calculate YLDs. We used a Bayesian meta-regression tool for epidemiological modelling, used cause-specific mortality rates for non-fatal estimation, and adjusted our results for disability experienced with comorbid conditions. We also analysed results on the basis of the Socio-demographic Index, a compound measure of income per capita, education, and fertility. FINDINGS: In 2016, there were 27·08 million (95% uncertainty interval [UI] 24·30-30·30 million) new cases of TBI and 0·93 million (0·78-1·16 million) new cases of SCI, with age-standardised incidence rates of 369 (331-412) per 100 000 population for TBI and 13 (11-16) per 100 000 for SCI. In 2016, the number of prevalent cases of TBI was 55·50 million (53·40-57·62 million) and of SCI was 27·04 million (24·98-30·15 million). From 1990 to 2016, the age-standardised prevalence of TBI increased by 8·4% (95% UI 7·7 to 9·2), whereas that of SCI did not change significantly (-0·2% [-2·1 to 2·7]). Age-standardised incidence rates increased by 3·6% (1·8 to 5·5) for TBI, but did not change significantly for SCI (-3·6% [-7·4 to 4·0]). TBI caused 8·1 million (95% UI 6·0-10·4 million) YLDs and SCI caused 9·5 million (6·7-12·4 million) YLDs in 2016, corresponding to age-standardised rates of 111 (82-141) per 100 000 for TBI and 130 (90-170) per 100 000 for SCI. Falls and road injuries were the leading causes of new cases of TBI and SCI in most regions. INTERPRETATION: TBI and SCI constitute a considerable portion of the global injury burden and are caused primarily by falls and road injuries. The increase in incidence of TBI over time might continue in view of increases in population density, population ageing, and increasing use of motor vehicles, motorcycles, and bicycles. The number of individuals living with SCI is expected to increase in view of population growth, which is concerning because of the specialised care that people with SCI can require. Our study was limited by data sparsity in some regions, and it will be important to invest greater resources in collection of data for TBI and SCI to improve the accuracy of future assessments

Burden of injury along the development spectrum : associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017

Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm-the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.Peer reviewe

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions