Immigrating and vicinity are not risk factors in the prevalence and transmission rate of human T-lymphotropic virus type 1: A Survey in an endemic region of Iran and Afghan refugees.

Human T-lymphotropic virus type 1 (HTLV-1) is a retrovirus associated with two life-threatening diseases; HAM/TSP and ATLL. Due to the slow-growing HTLV-1 infection worldwide, WHO urged for elimination. A large border with Afghanistan, northeast Iran is an endemic region for HTLV-1 infection. Historically, Afghanistan has common sociocultural similarities to Persian peoples. This study was conducted to evaluate HTLV-1 prevalence in Afghan refugees. Also, the HTLV-1 transmission rate and understanding of whether or not the Silk Road has been the route of HTLV-1 infection to Iran were investigated. This case-control study was conducted in a rural area of Fariman city, with Afghan residents who migrated around 165 years ago, from 1857, the Treaty of Paris at the end of the Anglo-Persian war, and a refugee camp in Torbat-e-Jam city. These populations in HTLV-1 endemic area were compared to a segregated population of Afghan refugees in Semnan, the centre of Iran. Blood samples of 983 volunteers were assessed with the ELISA method for the presence of HTLV-1 antibodies and then confirmed by PCR technique. All samples from Afghan refugee camps, Semnan and Torbat-e-Jam, were negative for HTLV-1 infection. However, the prevalence of HTLV-1 infection in Fariman, a rural population of Afghan origin, was approximately 2.73%. The results showed that HTLV-1 is not endemic in Afghanistan, a war-stricken region with refugees distributed worldwide. The land Silk Road has not been the route of HTLV-1 transmission to Northeastern Iran. Importantly, HTLV-1 endemicity might occur during a long time of living in an endemic area.

Estimation of Fractional Photosynthetically Active Radiation From a Canopy 3D Model; Case Study: Almond Yield Prediction.

Canopy-intercepted light, or photosynthetically active radiation, is fundamentally crucial for quantifying crop biomass development and yield potential. Fractional photosynthetically active radiation (PAR) (fPAR) is conventionally obtained by measuring the PAR both below and above the canopy using a mobile lightbar platform to predict the potential yield of nut crops. This study proposed a feasible and low-cost method for accurately estimating the canopy fPAR using aerial photogrammetry-based canopy three-dimensional models. We tested up to eight different varieties in three experimental almond orchards, including California's leading variety of 'Nonpareil'. To extract various canopy profile features, such as canopy cover and canopy volume index, we developed a complete data collection and processing pipeline called Virtual Orchard (VO) in Python environment. Canopy fPAR estimated by VO throughout the season was compared against midday canopy fPAR measured by a mobile lightbar platform in midseason, achieving a strong correlation (R 2) of 0.96. A low root mean square error (RMSE) of 2% for 'Nonpareil'. Furthermore, we developed regression models for predicting actual almond yield using both measures, where VO estimation of canopy fPAR, as a stronger indicator, achieved a much better prediction (R 2 = 0.84 and RMSE = 195 lb acre-1) than the lightbar (R 2 = 0.70 and RMSE = 266 lb acre-1) for 'Nonpareil'. Eight different new models for estimating potential yield were also developed using temporal analysis from May to August in 2019 by adjusting the ratio between fPAR and dry kernel yield previously found using a lightbar. Finally, we compared the two measures at two different spatial precision levels: per-row and per-block. fPAR estimated by VO at the per-tree level was also assessed. Results showed that VO estimated canopy fPAR performed better at each precision level than lightbar with up to 0.13 higher R 2. The findings in this study serve as a fundamental link between aerial-based canopy fPAR and the actual yield of almonds.

Estimation of the camera spectral sensitivity function using neural learning and architecture.

In this paper, we propose a robust method to estimate the camera spectral sensitivity function using a neural-network-based model and a custom learning algorithm. A new and specially designed architecture for training our neural network model is presented to estimate the spectral sensitivity as a function of wavelength. The sensitivity function is modeled as the sum of a few Gaussian functions, and a radial basis function neural network is trained to approximate this function over the visual wavelengths. No constraints are imposed on the illumination distribution or spectral sensitivity, as similar methods usually do. Experimental results show that the proposed method produces superior results with much lower root mean square error compared to the methods using basis functions or constraint optimization approaches. Study of the reproduced colors also verifies the accuracy of our method.

Sensitivity Comparison of the Skin Prick Test and Serum and Fecal Radio Allergosorbent Test (RAST) in Diagnosis of Food Allergy in Children.

BACKGROUND: Diagnosis of food allergy is difficult in children. Food allergies are diagnosed using several methods that include medical histories, clinical examinations, skin prick and serum-specific immunoglobulin E (IgE) tests, radio-allergosorbent test (RAST), food challenge, and supervised elimination diets. In this study we evaluated allergies to cow's milk, egg, peanut, and fish in children with suspected food allergies with skin prick tests and serum and feces RAST. METHODS: Forty-one children with clinical symptoms of food allergies were enrolled in the study. Skin prick tests and serum and fecal RAST were performed and compared with challenge tests. RESULTS: The most common sites of food allergy symptoms were gastrointestinal (82.9%) and skin (48.8%). 100% of the patients responded to the challenge tests with cow's milk, egg, peanut, and fish. 65% of the patients tested positive with the skin prick test, 12.1% tested positive with serum RAST, and 29.2% tested positive with fecal RAST. CONCLUSION: The skin prick test was more sensitive than serum or fecal RAST, and fecal RAST was more than twice as sensitive as serum RAST.