Reliable and Energy Efficient MLC STT-RAM Buffer for CNN Accelerators

We propose a lightweight scheme where the formation of a data block is changed in such a way that it can tolerate soft errors significantly better than the baseline. The key insight behind our work is that CNN weights are normalized between -1 and 1 after each convolutional layer, and this leaves one bit unused in half-precision floating-point representation. By taking advantage of the unused bit, we create a backup for the most significant bit to protect it against the soft errors. Also, considering the fact that in MLC STT-RAMs the cost of memory operations (read and write), and reliability of a cell are content-dependent (some patterns take larger current and longer time, while they are more susceptible to soft error), we rearrange the data block to minimize the number of costly bit patterns. Combining these two techniques provides the same level of accuracy compared to an error-free baseline while improving the read and write energy by 9% and 6%, respectively

Helicobacter pylori infection and insulin resistance in diabetic and nondiabetic population

Helicobacter pylori (HP) is a common worldwide infection with known gastrointestinal and nongastrointestinal complications. One of the gastrointestinal side effects posed for this organism is its role in diabetes and increased insulin resistance. The aim of this study was to evaluate the association between HP and insulin resistance in type 2 diabetic patients and nondiabetics. This cross-sectional study was carried out from May to December 2013 on 211 diabetic patients referred to diabetes clinic of Shahid Beheshti Hospital of Qom and 218 patients without diabetes. HP was evaluated using serology method and insulin resistance was calculated using HOMA-IR. The prevalence of H. pylori infection was 55.8% and 44.2% in diabetics and nondiabetics (P=0.001). The study population was divided into two HP positive and negative groups. Among nondiabetics, insulin resistance degree was 3.01±2.12 and 2.74±2.18 in HP+ and HP- patients, respectively P=0.704. Oppositely, insulin resistance was significantly higher in diabetic HP+ patients rather than seronegative ones (4.484±2.781 versus 3.160±2.327, P=0.013). In diabetic patients, in addition to higher prevalence of HP, it causes a higher degree of insulin resistance. © 2014 Jamshid Vafaeimanesh et al

Effect of different oxygen levels on growth performance, stress response and oxygen consumption in two weight groups of great sturgeon Huso huso

In the present study, different oxygen levels were examined in two weight groups of great sturgeon Huso huso including small size (with initial weight 280.9 ± 49.2 g) and large size (with initial weight 1217.9 ± 138.1 g). The fish were kept in hypoxia (2-3 mg/l), normoxia (5-6 mg/l) and hyperoxia (9-10 mg/l) conditions for 8 weeks and then were individually placed in the tanks with oxygen level of 6 mg/l to levels causing sedate fish and subsequently dissolved oxygen level in water was measured every 30 minutes. No significant effects on blood cortisol and glucose levels were observed after 8 weeks (P>0.05), but there were significant differences in cortisol concentrations between treatments (P0.05) in large size. There were no significant differences in oxygen consumption among treatments (P>0.05). Results revealed that dissolved oxygen had a significant effect on growth of H. huso and also a low level of oxygen accompanied by reduction in feed intake resulted in lower growth and changes in stress response

Camera calibration of long image sequences with the presence of occlusions

Camera calibration is a critical problem in applications such as augmented reality and image based model reconstruction. When constructing a 3D model of an object from an uncalibrated video sequence, large amounts of frames and self occlusions of parts of the object are common and difficult problems. In this paper we present a fast and robust algorithm that uses a divide and conquer strategy to split the video sequence into sub-sequences containing only the most relevant frames. Then a robust stratified linear based algorithm is able to calibrate each of the subsequences to a metric structure and finally the subsequences are merged together and a final non-linearoptimization refines the solution. Examples of real datareconstructions are presented.Postprint (author’s final draft

Effect of hypoxia, normoxia and hyperoxia conditions on gill histopathology in two weight groups of beluga (Huso huso)

The influence of dissolved oxygen concentration on gill histopathology of great sturgeon (Huso huso) was evaluated in two weight classes (initial weight 280.9±49.2 g and 1217.9±138.1 g respectively). Oxygen treatments included hypoxia (2-3 mg/l), normoxia (5-6 mg/l) and hyperoxia (9-10 mg/l). The fish were acclimated to experimental tanks for one week then randomly distributed into 9 tanks in each of the initial weight classes (3 and 6 fish per tank in higher and lower initial weight classes respectively) for 8 weeks. In order to find the histopathological changes, gill samples were collected, dehydrated through ethanol series, embedded in paraffin , sectioned at 7 µm thickness using a Leitz microtome and stained with H & E. No mortality was observed over the 8 weeks of the experimental period. There were significant differences in weight and feed intake between treatments in the both weight classes (P<0.05). Fork length showed significant differences in lower initial weight class (P<0.05). The main histopathological changes were observed in gills including: Hyperplasia, loss of secondary lamellae, hemorrhage and congestion in primary and secondary lamellae, lamellar fusion, epithelial lifting in secondary lamellae, clubbing of secondary lamellae, telangiectases, increase in melanin pigments and numerous vacuoles in primary and secondary lamellae (in hyperoxia treatment). All these lesions may reduce gill functional surface of gaseous exchange, impairing respiratory function

ARMAN: A Reconfigurable Monolithic 3D Accelerator Architecture for Convolutional Neural Networks

The Convolutional Neural Network (CNN) has emerged as a powerful and versatile tool for artificial intelligence (AI) applications. Conventional computing architectures face challenges in meeting the demanding processing requirements of compute-intensive CNN applications, as they suffer from limited throughput and low utilization. To this end, specialized accelerators have been developed to speed up CNN computations. However, as we demonstrate in this paper via extensive design space exploration, different neural network models have different characteristics, which calls for different accelerator architectures and configurations to match their computing demand. We show that a one-size-fits-all fixed architecture does not guarantee optimal power/energy/performance trade-off. To overcome this challenge, this paper proposes ARMAN, a novel reconfigurable systolic-array-based accelerator architecture based on Monolithic 3D (M3D) technology for CNN inference. The proposed accelerator offers the flexibility to reconfigure among different scale-up or scale-out arrangements depending on the neural network structure, providing the optimal trade-off across power, energy, and performance for various neural network models. We demonstrate the effectiveness of our approach through evaluations of multiple benchmarks. The results demonstrate that the proposed accelerator exhibits up to 2x, 2.24x, 1.48x, and 2x improvements in terms of execution cycles, power, energy, and EDP respectively, over the non-configurable architecture

Evaluating the effect of a herb on the control of blood glucose and insulin-resistance in patients with advanced type 2 diabetes (a double-blind clinical trial)

Background: Different benefits of various herbal medicines in decreasing blood sugar have been reported in different clinical trials so far. Considering the growing tendency toward these combinations and the booming market, inappropriate advice is growing accordingly. Hence, it is necessary to evaluate the effects and possible complications of such combinations on health status and blood glucose control. Methods: Two 38-subject groups were formed and a 12-week treatment program was administered for both groups. The inclusion criteria were failure to control blood glucose with two oral medicines, unwillingness to inject insulin. The medicine was prepared in capsules by Booali Company. Each capsule weighed 750 mg and contained nettle leaf 20 (w/w), berry leaf 10 (w/w), onion and garlic 20 (w/w), fenugreek seed 20 (w/w), walnut leaf 20 (w/w), and cinnamon bark 10 (w/w) all in powder. Results: At the beginning of the study, there was no significant difference between the subjects regarding the evaluated parameters, but after the intervention, the level of glucose was significantly lower in fasting (P=0.0001) and 2-hour postprandial (P=0.002) levels. The level of glycated hemoglobin A1c (HbA1c) (P=0.0001) also decreased from 0.33±9.72 to 0.20±8.39 . Finally, the level of insulin resistance reduced from 1.9±4.1 to 1.4±2.6 (P=0.001) after consuming herbal medicine. Conclusion: According to the results of the current study, the herbal combination was effective in controlling blood sugar, and considering the reduction of HbA1c by 1.31 , it seems that the herbal combination is an effective medicine to treat diabetes. © 2020 Babol University of Medical Sciences. All rights reserved

Fish and shrimp waste management at household and market in Bushehr, Iran

Abstract: The aim of this study was to investigate the estimation and management of fish and shrimp wastes in Bushehr province. Two-part questionnaire including the demographic information, and fish and shrimp waste disposal method were completed for 91 stores and 636 households. The quantity of generated wastes was estimated based on the 3 different Scenarios. In addition, the waste generation factor were calculated for common fish and shrimp species. Results showed the waste generation factor for fish and shrimp equal to 32.67 and 42%, respectively. The total quantity of fish- and shrimp-generated wastes in Bushehr province was estimated to be 29,388 tons per year, of which the quantity of generated waste by stores and by households was 3731 tons per year (16 ton per capita per year) and 8804 tons per year (34 kg per capita per year), respectively. The remaining quantity is related to other unaccounted sectors such as fish industries. Moreover, the biogas production potential from an anaerobic digestion were estimated 2,675,400 m3 per year, which is equivalent to 16,052 MWh. In addition, the biodiesel production potential was obtained equivalent to 19 kt, which is about 4.2% of the total diesel fuel requirement of the province in 2016. Graphic abstract: [Figure not available: see fulltext.