DeepMotions : A Deep Learning System for Path Prediction Using Similar Motions

Trajectory prediction techniques play a serious role in many location-based services such as mobile advertising, carpooling, taxi services, traffic management, and routing services. These techniques rely on the object’s motion history to predict the future path(s). As a consequence, these techniques fail when history is unavailable. The unavailability of history might occur for several reasons such as; history might be inaccessible, a recently registered user with no preceding history, or previously logged data is preserved for confidentiality and privacy. This paper presents a Bi-directional recurrent deep-learning based prediction system, named DeepMotions , to predict the future path of a query object without any prior knowledge of the object historical motions. The main idea of DeepMotions is to observe the moving objects in the vicinity that have similar motion patterns of the query object. Then use those similar objects to train and predict the query object’s future steps. To compute similarity, we propose a similarity function that is based on the KNN algorithm. Extensive experiments conducted on real data sets confirm the efficient performance and the quality of prediction in DeepMotions with up to 96% accuracy

Identification and determination of antibiotic resistance of pathogenic bacteria Isolated from Septic Wounds

Wound infection is a global cause of morbidity and mortality across all wound types. Therefore, efficient diagnosis and treatment of wound infection are essential. This study was carried out to identify the pathogenic bacteria in infected wounds of the patient’s attending Sebha city hospitals (Libya) and to determine their resistance profile to the most common antibiotics used in therapy. A total of sixty wound swab specimens were collected and cultured, of which 39 samples showed bacterial growth. Three different species of bacteria were isolated. Staphylococcus aureus 21 (53.9%) were the most common organisms followed by Pseudomonas aeruginosa 10 (25.6%) and Staphylococcus epidermidis 8 (20.5%). The antibiotic susceptibility test of the bacterial isolate was performed by Kirby-Bauer disk diffusion method. Results showed that 90.5% of the Staphylococcus aureus isolates were resistant to vancomycin, 61.9% to tetracycline, 57.1% to amoxicillin, 52.4 % to methicillin, 42.9 to erythromycin and 23.8% to streptomycin. 87.5% of the Staphylococcus epidermidis isolates were resistant to vancomycin, 75% to methicillin, 62.5% to tetracycline, 50% to streptomycin 37.5% to amoxicillin, and erythromycin. All the Pseudomonas aeruginosa isolates were sensitive to ciprofloxacin and highly resistant 90-100% to other antibiotics tested Amoxicillin, Nalidixic acid, Streptomycin, and Tetracycline. The high rate of multiple antibiotic resistance was observed in all bacterial species recovered

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Health in times of uncertainty in the eastern Mediterranean region, 1990�2013: a systematic analysis for the Global Burden of Disease Study 2013

Background The eastern Mediterranean region is comprised of 22 countries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the United Arab Emirates, and Yemen. Since our Global Burden of Disease Study 2010 (GBD 2010), the region has faced unrest as a result of revolutions, wars, and the so-called Arab uprisings. The objective of this study was to present the burden of diseases, injuries, and risk factors in the eastern Mediterranean region as of 2013. Methods GBD 2013 includes an annual assessment covering 188 countries from 1990 to 2013. The study covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Our GBD 2013 analyses included the addition of new data through updated systematic reviews and through the contribution of unpublished data sources from collaborators, an updated version of modelling software, and several improvements in our methods. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically. Findings The leading cause of death in the region in 2013 was ischaemic heart disease (90·3 deaths per 100�000 people), which increased by 17·2 since 1990. However, diarrhoeal diseases were the leading cause of death in Somalia (186·7 deaths per 100�000 people) in 2013, which decreased by 26·9 since 1990. The leading cause of disability-adjusted life-years (DALYs) was ischaemic heart disease for males and lower respiratory infection for females. High blood pressure was the leading risk factor for DALYs in 2013, with an increase of 83·3 since 1990. Risk factors for DALYs varied by country. In low-income countries, childhood wasting was the leading cause of DALYs in Afghanistan, Somalia, and Yemen, whereas unsafe sex was the leading cause in Djibouti. Non-communicable risk factors were the leading cause of DALYs in high-income and middle-income countries in the region. DALY risk factors varied by age, with child and maternal malnutrition affecting the younger age groups (aged 28 days to 4 years), whereas high bodyweight and systolic blood pressure affected older people (aged 60�80 years). The proportion of DALYs attributed to high body-mass index increased from 3·7 to 7·5 between 1990 and 2013. Burden of mental health problems and drug use increased. Most increases in DALYs, especially from non-communicable diseases, were due to population growth. The crises in Egypt, Yemen, Libya, and Syria have resulted in a reduction in life expectancy; life expectancy in Syria would have been 5 years higher than that recorded for females and 6 years higher for males had the crisis not occurred. Interpretation Our study shows that the eastern Mediterranean region is going through a crucial health phase. The Arab uprisings and the wars that followed, coupled with ageing and population growth, will have a major impact on the region's health and resources. The region has historically seen improvements in life expectancy and other health indicators, even under stress. However, the current situation will cause deteriorating health conditions for many countries and for many years and will have an impact on the region and the rest of the world. Based on our findings, we call for increased investment in health in the region in addition to reducing the conflicts. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

Simulation of CO2 and attribution analysis at six European peatland sites using the ECOSSE model

In this study, we simulated heterotrophic CO2 (Rh) fluxes at six European peatland sites using the ECOSSE model and compared them to estimates of Rh made from eddy covariance (EC) measurements. The sites are spread over four countries with different climates, vegetation and management. Annual Rh from the different sites ranged from 110 to 540 g C m−2. The maximum annual Rh occurred when the water table (WT) level was between −10 and −25 cm and the air temperature was above 6.2 °C. The model successfully simulated seasonal trends for the majority of the sites. Regression relationships (r 2) between the EC-derived and simulated Rh ranged from 0.28 to 0.76, and the root mean square error and relative error were small, revealing an acceptable fit. The overall relative deviation value between annual EC-derived and simulated Rh was small (−1 %) and model efficiency ranges across sites from −0.25 to +0.41. Sensitivity analysis highlighted that increasing temperature, decreasing precipitation and lowering WT depth could significantly increase Rh from soils. Thus, management which lowers the WT could significantly increase anthropogenic CO2, so from a carbon emissions perspective, it should be avoided. The results presented here demonstrate a robust basis for further application of the ECOSSE model to assess the impacts of future land management interventions on peatland carbon emissions and to help guide best practice land management decisions