Random Feature Maps via a Layered Random Projection (LaRP) Framework for Object Classification

The approximation of nonlinear kernels via linear feature maps has recently gained interest due to their applications in reducing the training and testing time of kernel-based learning algorithms. Current random projection methods avoid the curse of dimensionality by embedding the nonlinear feature space into a low dimensional Euclidean space to create nonlinear kernels. We introduce a Layered Random Projection (LaRP) framework, where we model the linear kernels and nonlinearity separately for increased training efficiency. The proposed LaRP framework was assessed using the MNIST hand-written digits database and the COIL-100 object database, and showed notable improvement in object classification performance relative to other state-of-the-art random projection methods.Comment: 5 page

Sternal nonunion on bone scintigraphy: A case report

Sternal non-union is a severe complication of sternotomy closure following open heart surgeries. Healing problems typically occur in 0.3% to 5% of patients. Technetium-99m methylene diphosphonate (99mTc-MDP) bone scintigraphy has been used to assess bone nonunion to predict the healing response for proper management. In this report, we present the case of a marked sternal nonunion following coronary artery bypass graft (CABG), using radionuclide bone scintigraphy

Pulmonary tuberculosis and some underlying conditions in Golestan Province of Iran, during 2001-2005

Context: Pulmonary tuberculosis has been a major health problem in Golestan province of Iran. Aims: This descriptive cross-sectional study was performed to evaluate the frequency of coexisting medical conditions and their effects on some epidemiologic factors in patients with pulmonary tuberculosis. Setting and Design: This was a descriptive cross-sectional study. Methods and Material: Demographic information, time of admission in the hospital and coexisting medical conditions (diabetes, chronic renal failure/hemodyalysis, corticosteroids consumption and malignancies) were extracted from the patient's file. Statistical analysis used: Chi-square test was used to assess the relationship between variables. Results: Two hundred forty three patients with pulmonary tuberculosis during 5 years were studied. Out of all, 162 cases (66.7%) did not have any co-morbidities. Diabetes mellitus was found to be the most prevalent condition (23.05%) followed by chronic renal failure, corticosteroid consumption and malignancy ranking second, third and forth in the list (5.8%, 2.5% and 2 respectively). The mean age of the patients was 50.15±19 years old. In the group without co morbidities, male/ female ratio was 1.41/1, but co morbidity with diabetes was significantly more prevalent in females (p<0.05). Conclusions: We suggest screening of tuberculosis in patients with chronic renal failure and diabetes mellitus in our area. Also for patients with pulmonary tuberculosis, diabetes screening should be considered essential

Bell's Theorem and Chemical Potential

Chemical potential is a property which involves the effect of interaction between the components of a system, and it results from the whole system. In this paper, we argue that for two particles which have interacted via their spins and are now spatially separated, the so-called Bell's locality condition implies that the chemical potential of each particle is an individual property. Here is a point where quantum statistical mechanics and the local hidden variable theories are in conflict. Based on two distinct concepts of chemical potential, the two theories predict two different patterns for the energy levels of a system of two entangled particles. In this manner, we show how one can distinguish the non-separable features of a two-particle system.Comment: 11 pages,1 figure, To appear in J. Phy. A: Math. Gen., Special Issue: Foundations of Quantum Theor

Stochastic Receptive Fields in Deep Convolutional Networks

Deep convolutional neural networks (ConvNets) have rapidly grownin popularity due to their powerful capabilities in representing andmodelling the high-level abstraction of complex data. However,ConvNets require an abundance of data to adequately train networkparameters. To tackle this problem, we introduce the conceptof stochastic receptive fields, where the receptive fields arestochastic realizations of a random field that obey a learned distribution.We study the efficacy of incorporating layers of stochasticreceptive fields to a ConvNet to boost performance without theneed for additional training data. Preliminary results showing animprovement in accuracy ( 2% drop in test error) was achieved byadding a layer of stochastic receptive fields to a ConvNet comparedto adding a layer of fully-trained receptive fields, when training witha small training set consisting of 20% of the STL-10 dataset

Squeezed vacuum states from a whispering gallery mode resonator

Squeezed vacuum states enable optical measurements below the quantum limit and hence are a valuable resource for applications in quantum metrology and also quantum communication. However, most available sources require high pump powers in the milliwatt range and large setups, which hinders real world applications. Furthermore, degenerate operation of such systems presents a challenge. Here, we use a compact crystalline whispering gallery mode resonator made of lithium niobate as a degenerate parametric oscillator. We demonstrate about 1.4 dB noise reduction below the shot noise level for only 300 $\mu\text{W}$ of pump power in degenerate single mode operation. Furthermore, we report a record pump threshold as low as 1.35 $\mu\text{W}$. Our results show that the whispering gallery based approach presents a promising platform for a compact and efficient source for nonclassical light.Comment: $\copyright$ 2019 Optical Society of America. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserve

Consequences of AphanizomenonFlos-aquae(AFA) extract (StemtechTM) on metabolic profile of patients with type 2 diabetes

Background: Blue- green algae is one of the most nutrient dense foods which is rich in substances that have useful effects on human health. The purpose of this study was to evaluate the effectiveness of a water- soluble extract of the cyanophyta Aphanizomenon Flos-aquae (StemtechTM) as a functional supplement on CD markers, lipid profile, glucose levels as well as its side effects in Iranian patients with type 2 diabetes. Methods: During this randomized, double-blind, placebo-controlled trial 49 type 2 diabetic patients, aged between 20 and 60years with a HbA1C�7.5, were allocated. Patients were divided into two groups of placebo and treated with an equal ratio 1:1. The subjects in StemtechTM group received one capsule of StemFlo (508mg) before breakfast and two capsules of StemEnhance (500mg) after each meal for a period of 12weeks, and placebo group was instructed to take placebo with the same pattern. During the intervention period, subjects were asked to keep usual diet and prohibited to take any functional foods or dietary supplements. Metabolic panel has been measured as the primary outcome of study at the beginning and end of the intervention period via blood sampling. Results: StemtechTM supplementation for 12weeks decreased fasting blood glucose (FBG) and Glycatedhemoglobin (HbA1c). Mean serum chemistry parameters (Triglyceride, Total Cholesterol, LDL, HDL, CRP, AST, ALT, BUN and Creatinine) as well as CD 34+, IL-6, TNF-aα in treated and control groups before and after the study showed no considerable dissimilarities. Conclusion: StemtechTM intervention brought in positive consequence on blood glucose levels in Iranian patients with type 2 diabetes, consequently suggests the StemtechTM as a functional food for the management of diabetes. © 2015 Sanaei et al