442 research outputs found

    Air born dust particles effects on microwave propagation in arid-area

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    Dust storms can degrade visibility and increase atmospheric attenuation. Therefore, microwave (MW) propagation is severely affected by dust storms in many parts of the world. Air-born dust particles may affect electromagnetic waves during a dust storm. In this paper air- born dust particles effects are studied based on measured visibility. Recent analytical and numerical models results are compared to the measured at 14 GHz. Consequently, measured attenuation is significantly greater than the predicted using recent analytical and numerical models. Dust storms can degrade visibility and increase atmospheric attenuation. Therefore, microwave (MW) propagation is severely affected by dust storms in many parts of the world. Air-born dust particles may affect electromagnetic waves during a dust storm. In this paper air- born dust particles effects are studied based on measured visibility. Recent analytical and numerical models results are compared to the measured at 14 GHz. Consequently, measured attenuation is significantly greater than the predicted using recent analytical and numerical models

    Effect of dust storm intensity variations on total path attenuation prediction

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    This paper proposes a novel dust-storm total path attenuation prediction model. This model is formulated as a function of specific attenuation (dB/km) and the effective distance, which considers the non-uniform dust storm intensity variations throughout the link. The effective distance is obtained as a combination of the total link distance and the reduction factor. The reduction factor is developed based on the modeled 2-D structure of the observed dust storm characteristics. A measurement campaign of atmospheric characteristics, their properties, and effects on several microwave links operated in Khartoum-Sudan was conducted. In an earlier report, an empirical dust storm attenuation prediction model was proposed based on short-distance links by assuming uniform dust storm intensity variations. However, it was observed that the dust intensity varies with the distance, which affects total attenuation, and this issue is not addressed yet. One year measurement on the 6.2 km and 7.6 km long microwave links operating at 21.2 GHz and 14.5 GHz are used to validate the proposed dust storm total path attenuation model

    Energy harvesting effect on prolonging low-power lossy networks lifespan

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    Low-power lossy networks performance relies heavily on the wireless node battery status. Furthermore, Routing Protocol for Low-Power and Lossy Network routing protocol was not optimally designed with sustainable energy consumption in mind to suit these networks. Prolonging the lifespan of these networks is of utmost priority. This article introduces a solar energy harvesting module to power energy-constrained network devices and quantifies the effect of using harvested energy on prolonging their network lifetime when Routing Protocol for Low-Power and Lossy Network routing protocol is used. Simulation of the new developed module is conducted in three different scenarios using Contiki Cooja simulator sporting Zolertia Z1 motes. Furthermore, the harvested energy used was fed from a Cooja-based Simulation model of actual PV supercapacitor circuit design. All battery levels were set to 1% of their total capacity for all nodes in the network to speed up observing the energy harvesting effect. The performance evaluation results showed that the network with no-energy harvesting operated for time duration of 4:08:04 time units (i.e. hour:minute:second) with a dramatic decrease in connection between nodes in the network. However, the same network, when using the harvested energy to back up the battery operation, lasted for 6:40:01 in time units with improved connectivity, a total extended network lifetime of 2:31:97-time units. Furthermore, for the Routing Protocol for Low-Power and Lossy Network routing metrics, OF0 outperformed ETX in term of throughput, packet delivery ratio, energy consumption, and network connectivity. Results indicate that the developed harvested energy module fits perfectly for any Cooja-based simulation and mimics actual photovoltaic-based supercapacitor battery. It should also help researchers introduce and quantify accurately new energy consumption-based routing metrics for Routing Protocol for Low-Power and Lossy Network

    Thermal-based early breast cancer detection using inception V3, inception V4 and modified inception MV4

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    Breast cancer is one of the most significant causes of death for women around the world. Breast thermography supported by deep convolutional neural networks is expected to contribute significantly to early detection and facilitate treatment at an early stage. The goal of this study is to investigate the behavior of different recent deep learning methods for identifying breast disorders. To evaluate our proposal, we built classifiers based on deep convolutional neural networks modelling inception V3, inception V4, and a modified version of the latter called inception MV4. MV4 was introduced to maintain the computational cost across all layers by making the resultant number of features and the number of pixel positions equal. DMR database was used for these deep learning models in classifying thermal images of healthy and sick patients. A set of epochs 3–30 were used in conjunction with learning rates 1 9 10–3, 1 9 10–4 and 1 9 10–5, Minibatch 10 and different optimization methods. The training results showed that inception V4 and MV4 with color images, a learning rate of 1 9 10–4, and SGDM optimization method, reached very high accuracy, verified through several experimental repetitions. With grayscale images, inception V3 outperforms V4 and MV4 by a considerable accuracy margin, for any optimization methods. In fact, the inception V3 (grayscale) performance is almost comparable to inception V4 and MV4 (color) performance but only after 20–30 epochs. inception MV4 achieved 7% faster classification response time compared to V4. The use of MV4 model is found to contribute to saving energy consumed and fluidity in arithmetic operations for the graphic processor. The results also indicate that increasing the number of layers may not necessarily be useful in improving the performance

    Inflammatory, Hemostatic, and Other Novel Biomarkers for Diabetic Retinopathy: The Multi-Ethnic Study of Atherosclerosis

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    Objective— There are conflicting data regarding relationships of systemic biomarkers of inflammation, hemostasis, and homocysteine with diabetic retinopathy. We examined these relationships in the Multi-Ethnic Study of Atherosclerosis. Research design and methods— A total of 921 participants with diabetes were included. Diabetic retinopathy was graded from retinal photographs. We defined two outcomes: any diabetic retinopathy and vision-threatening diabetic retinopathy (severe nonproliferative diabetic retinopathy or worse). Systemic markers analyzed were C-reactive protein, homocysteine, fibrinogen, plasmin- 2-antiplasmin complex (PAP), interleukin-6, D-dimer, factor VIII, serum creatinine, and urinary albumin-to-creatinine (UAC) ratio. Results— Prevalence of diabetic retinopathy was 33.2% and vision-threatening diabetic retinopathy 7.1%. After adjusting for established risk factors (diabetes duration, A1C, systolic blood pressure, waist-to-hip ratio, and use of diabetes medications), fibrinogen (odds ratio 1.14 [95% CI 1.01–1.32], P 0.05) and PAP (1.25 [1.05–1.50], P0.01) were associated with any diabetic retinopathy, while PAP (1.54 [1.13–2.11], P 0.007) and homocysteine (1.57 [1.16– 2.11], P 0.003) were associated with vision-threatening diabetic retinopathy. Only PAP remained significant after additional adjustment for serum creatinine and UAC ratio. Area under receiver-operator characteristic curve (AUROC) for diabetic retinopathy was constructed for established and novel risk factors. Established risk factors accounted for a 39.2% increase of the AUROC, whereas novel markers (fibrinogen, PAP, homocysteine, serum creatinine, and UAC ratio) only accounted for an additional 2.2%. Conclusions— There were few associations of novel markers of inflammation, hemostasis, and homocysteine with diabetic retinopathy after controlling for established risk factors. These data suggest that there is limited clinical use of these biomarkers for prediction of diabetic retinopathy

    Towards a greater dialogue on disability between Muslims and Christians

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    Attitudes to disability and disabled people by Muslims – focusing on attitudes in the Middle East and North Africa - and Christians – focusing on the West (here taken to mean Europe, North America and Australasia) - were examined through a grounded theory literature search, with the study being divided into three phases of reading and analysis. The aims of study were to develop a dialogue on disability between the two cultures, to inform an understanding of the attitudes to disability in the two cultures, and to inform cultural practice in promoting support and equality in both cultures. The study finds that Islam and Christianity have much in common and are a force for good in promoting and developing disability equality in both Muslim and Christian cultures

    Association of respiratory symptoms and lung function with occupation in the multinational Burden of Obstructive Lung Disease (BOLD) study

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    Background Chronic obstructive pulmonary disease has been associated with exposures in the workplace. We aimed to assess the association of respiratory symptoms and lung function with occupation in the Burden of Obstructive Lung Disease study. Methods We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income. Results Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19–1.94), wheeze (OR 1.37, 95% CI 1.16–1.63) and dyspnoea (OR 1.83, 95% CI 1.53–2.20), but not lower FVC (β=0.02 L, 95% CI −0.02–0.06 L) or lower FEV1/FVC (β=0.04%, 95% CI −0.49–0.58%). Some findings differed by sex and gross national income. Conclusion At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.publishedVersio

    Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA

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    Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis

    Multiplicity dependence of inclusive J/psi production at midrapidity in pp collisions at root s=13 TeV

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    Measurements of the inclusive J/psi yield as a function of charged-particle pseudorapidity density dN(ch)/d eta in pp collisions at root s = 13 TeV with ALICE at the LHC are reported. The J/psi meson yield is measured at midrapidity (vertical bar y vertical bar <0.9) in the dielectron channel, for events selected based on the charged-particle multiplicity at midrapidity (vertical bar eta vertical bar <1) and at forward rapidity (-3.7 <eta <-1.7 and 2.8 <eta <5.1); both observables are normalized to their corresponding averages in minimum bias events. The increase of the normalized J/psi yield with normalized dN(ch)/d eta is significantly stronger than linear and dependent on the transverse momentum. The data are compared to theoretical predictions, which describe the observed trends well, albeit not always quantitatively. (C) 2020 European Organization for Nuclear Research. Published by Elsevier B.V.Peer reviewe

    (Anti-)deuteron production in pp collisions at 1as=13TeV

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    The study of (anti-)deuteron production in pp collisions has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high-energy hadronic collisions. In this paper the production of (anti-)deuterons is studied as a function of the charged particle multiplicity in inelastic pp collisions at s=13 TeV using the ALICE experiment. Thanks to the large number of accumulated minimum bias events, it has been possible to measure (anti-)deuteron production in pp collisions up to the same charged particle multiplicity (d Nch/ d \u3b7 3c 26) as measured in p\u2013Pb collisions at similar centre-of-mass energies. Within the uncertainties, the deuteron yield in pp collisions resembles the one in p\u2013Pb interactions, suggesting a common formation mechanism behind the production of light nuclei in hadronic interactions. In this context the measurements are compared with the expectations of coalescence and statistical hadronisation models (SHM)
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