A new multiscale Bayesian algorithm for speckle reduction in medical ultrasound images

This paper introduces a new multiscale speckle reduction method based on the extraction of wavelet interscale dependencies to visually enhance the medical ultrasound images and improve clinical diagnosis. The logarithm of the image is first transformed to the oriented dual-tree complex wavelet domain. It is then shown that the adjacent subband coefficients of the log-transformed ultrasound image can be successfully modeled using the general form of bivariate isotropic stable distributions, while the speckle coefficients can be approximated using a zero-mean bivariate Gaussian model. Using these statistical models, we design a new discrete bivariate Bayesian estimator based on minimizing the mean square error (MSE). To assess the performance of the proposed method, four image quality metrics, namely signal-to-noise ratio, MSE, coefficient of correlation, and edge preservation index, were computed on 80 medical ultrasound images. Moreover, a visual evaluation was carried out by two medical experts. The numerical results indicated that the new method outperforms the standard spatial despeckling filters, homomorphic Wiener filter, and new multiscale speckle reduction methods based on generalized Gaussian and symmetric alpha-stable priors.     

Novel extracellular hyper acidophil and thermostable α‐amylase from Micrococcus sp.NS 211

Among several bacteria examined in this study, a hyper acidophil and thermostable Micrococcus sp.NS 211 designated as M.Amy NS 211 was selected for production of amylase using starch agar plates with following incubation at 85°C. Identification by 16SrRNA on selected bacterium disclosed the highest similarity for protean regions of this gene, 27 F and 1492R as Micrococcus sp.NS 211. Although activity of M.Amy NS 211 was established at temperatures between 70 and 110°C and pH ranges 1.2–8.0, the optimum temperature and pH was achieved at 85°C and 3.5 in sodium citrate buffer system respectively. Two‐step chromatography was performed using (CM Bio‐Gel A) and (Bio‐Gel A‐150) columns to purify 84 kDa hyper acidophil and thermostable α‐amylase. SDS‐PAGE analysis showed molecular mass and amylolytic activity as single band. Enhancement of enzyme activity was obtained in presence of 5 mM MnCl₂ (298%), CaCl₂ (347%), FeCl₂ (211%), MgCl₂ (253%), ZnCl₂ (146%), NiCl (142%), NaCl (141%), Na‐sulfate (153%) while inhibition was observed with (5 mM) EDTA, PMSF (3 mM), urea (8 M), and SDS (1%) at 143, 134, 43, and 119%, respectively. M.Amy NS 211 can be applied in laundry detergents, textile, and modern relevant industrial processes at extreme temperatures and under acidic conditions.     

Optimisation of a pilot‐scale spray drying process for probiotic yoghurt,using response surface methodology

The influence of drying air temperatures, drying air flow rate and feed flow rate on percentage survival rate (% SR) of starter and probiotic bacteria, moisture content, water activity and colour of probiotic yoghurt powder produced using a pilot‐scale spray dryer was investigated. Optimisation of spray drying conditions was achieved based on the desirability value. Results showed that inlet air temperature, drying air flow rate, feed flow rate and outlet air temperature of 150 °C, 478 m³/h, 2 L/h and 63.3 °C, respectively, were optimal conditions to produce powder that meets quality specifications and with a satisfactory% SR.     

A multi-stage stochastic programming approach for production planning with uncertainty in the quality of raw materials and demand

Motivated by the challenges encountered in sawmill production planning, we study a multi-product, multi-period production planning problem with uncertainty in the quality of raw materials and consequently in processes yields, as well as uncertainty in products demands. As the demand and yield own different uncertain natures, they are modelled separately and then integrated. Demand uncertainty is considered as a dynamic stochastic data process during the planning horizon, which is modelled as a scenario tree. Each stage in the demand scenario tree corresponds to a cluster of time periods, for which the demand has a stationary behaviour. The uncertain yield is modelled as scenarios with stationary probability distributions during the planning horizon. Yield scenarios are then integrated in each node of the demand scenario tree, constituting a hybrid scenario tree. Based on the hybrid scenario tree for the uncertain yield and demand, a multi-stage stochastic programming (MSP) model is proposed which is full recourse for demand scenarios and simple recourse for yield scenarios. We conduct a case study with respect to a realistic scale sawmill. Numerical results indicate that the solution to the multi-stage stochastic model is far superior to the optimal solution to the mean-value deterministic and the two-stage stochastic models.     

Synthesis and characterization of conductive neural tissue engineering scaffolds based on urethane-polycaprolactone

Polymeric biomaterials play a key role in enhancement of lengthy nerve regeneration and various types of scaffolds were used to pave the way for nerve regeneration. Electrospun fibrous scaffolds have special potential applicability in controlling the cell behaviors such as adhesion, growth, proliferation and function. This study attempted to design a conductive and porous fibrous scaffold containing polycaprolactone (PCL) and polyaniline (PANI) with controllable degradation rate by adding urethane groups in scaffold structures. FTIR and NMR analysis was used to characterize the chemical bonds. Morphology, porosity, conductivity and degradation rate of scaffolds were also evaluated. To assess the cell–scaffold interaction, PC-12 cell line was cultured on the scaffolds. Results showed that the degradation rate of composite samples significantly increased in 50 time period. It seems that these results suggest that the composite fibrous scaffolds having proportions of UPCL/PCL/PANI45:20:35 exhibit the most balanced properties that meet all of the required specifications for neural cells and possess a potential application in neural tissue engineering.     

Role of turmeric in oxidative modulation in end‐stage renal disease patients

Oxidative stress is considered as a major player in uremia‐associated morbidity and mortality in hemodialysis (HD) patients. The aim of this study was to evaluate the effects of turmeric on oxidative stress markers in HD patients. This study was a prospective and double‐blind randomized clinical trial. Fifty HD patients aged 18–60 years were recruited after fulfilling the inclusion criteria. Patients were randomly categorized into 2 groups: trial group received turmeric and control group received placebo for 8 weeks. Each patient in the trial group received turmeric, whereas the control group received starch for the same 8 weeks. Plasma malondialdehyde (MDA), red blood cell (RBC) antioxidant enzyme activities as glutathione peroxidase (GPX), glutathione reductase (GR), and catalase (CAT), cholesterol, high‐density lipoprotein‐cholesterol, low‐density lipoprotein‐cholesterol, triglyceride, albumin, and hemoglobin were also measured before and after study. Although MDA level was reduced in both groups, the ratio of decrease was significantly higher in the turmeric group (0.2 vs. 0.1, P = 0.040). Three enzymes of GPX, GR, and CAT levels were increased in both groups; the ratio of increased was significantly higher in the turmeric group for the CAT enzyme (0.73 vs. 0.54; P = 0.02). Also, significant elevation of albumin level in the turmeric group compared with the control group was observed (P = 0.001). Regular ingestion of turmeric reduces plasma MDA and increases RBC CAT activity and plasma albumin levels in HD patients. Turmeric showed no adverse effects.     

Properties of Nafion Under Uniaxial Loading at Different Temperatures: A Molecular Dynamics Study

Nafion membrane encounters many different thermal conditions and mechanical loadings because of its wide range of applications as a proton exchange membrane (PEM). Molecular dynamics simulation of hydrated Nafion at different temperatures is carried out to investigate the alteration of the physical properties of Nafion under uniaxial loading over a wide range of temperatures. According to the simulation results, increase of the temperature reduces the yield stress. The results also show that the polymer chains ordering increases the glass transition temperature and enhances the self-diffusion coefficient of water in hydrated Nafion. Comparisons show that the elastic modulus and viscosity coefficient obtained from the simulations at different temperatures are qualitatively in agreement with the measured values from experiments.     

Deep convolution network for surveillance records super-resolution

Multimedia Tools and Applications - The aim of image super resolution (SR) is to recover low resolution (LR) input image or video to a visually desirable high-resolution (HR) one. The task of...     

Deep semantic preserving hashing for large scale image retrieval

Multimedia Tools and Applications - Hashing approaches have got a great attention because of its efficient performance for large-scale images. This paper, aims to propose a deep hashing method...