An integrated photonic neural network is proposed based on on-chip cascaded one-dimensional (1D) metasurfaces. High-contrast transmitarray metasurfaces, termed as metalines in this paper, are defined sequentially in the silicon-on-insulator substrate with a distance much larger than the operation wavelength. Matrix-vector multiplications can be accomplished in parallel and with low energy consumption due to intrinsic parallelism and low-loss of silicon metalines. The proposed on-chip whole-passive fully-optical meta-neural-network is very compact and works at the speed of light, with very low energy consumption. Various complex functions that are performed by digital neural networks can be implemented by our proposal at the wavelength of 1.55 µm. As an example, the performance of our optical neural network is benchmarked on the prototypical machine learning task of classification of handwritten digits images from the Modified National Institute of Standards and Technology (MNIST) dataset, and an accuracy comparable to the state of the art is achieved.
BackgroundPrevalence of chronic pain and its association with demographic characteristics have been reported by different studies from different geographical regions in the world. However, data from many Middle East countries including Iran (especially southern Iran) are scare. The aim of the present study was to demonstrate the prevalence of chronic pain and its association with demographic, psychological and socioeconomic factors in an Iranian population.MethodsIn this population-based survey, the target population was comprised of subjects aged 20 to 85 years residing in Jahrom, southern Iran during 2009-2011. All eligible subjects were invited to participate in the study. Before a detailed questionnaire was given; face to face interviews were done for each individual.ResultsThere were 719 men and 874 women with an average age of 40.5 years at the onset of the study. Among the study population, 38.9% (620/1,593) complained of chronic pain, of whom 40.8% (253/620) were men and 59.2% (367/620) were women. Foot and joint pain were observed in 31.9%. Hip and spine pain, migraine and tension headaches, heart pain, and abdomen pain were observed in 21.5%, 15.5%, 9.5%, and 8.0% of chronic pain cases, respectively. There was a significant association among the covariables age, sex, overweight, educational level, income, and type of employment with chronic pain as the dependent variable (P < 0.0001).ConclusionsOur findings show the prevalence of chronic pain and its association with demographic, psychological and socioeconomic factors. Individuals with low incomes and less education became accustomed to pain due to a lack of knowledge.
ObjectiveTo compare the blood glucose levels, insulin concentrations, and insulin resistance during the two phases of the menstrual cycle between healthy women and patients with premenstrual syndrome (PMS).MethodsFrom January of 2011 to the August of 2012, a descriptive cross-sectional study was performed among students in the School of Medicine of Jahrom University of Medical Sciences. We included 30 students with the most severe symptoms of PMS and 30 age frequency-matched healthy controls. We analyzed the serum concentrations of glucose, insulin, and insulin resistance by using the glucose oxidase method, radioimmunometric assay, and homeostasis model assessment of insulin resistance equation, respectively.ResultsNo significant differences between the demographic data of the control and PMS groups were observed. The mean concentrations of glucose of the two study groups were significantly different during the follicular and luteal phases (p=0.011 vs. p<0.0001, respectively). The amounts of homeostasis model assessment of insulin resistance of the two study groups were significantly different in the luteal phase (p=0.0005).ConclusionThe level of blood glucose and insulin resistance was lower during the two phases of the menstrual cycle of the PMS group than that of the controls.
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