The availability of source code in relation to timely response to security vulnerabilities

Once a vulnerability has been found in an application or service that runs on a computer connected to the Internet, fixing that exploit in a timely fashion is of the utmost importance. There are two parts to fixing vulnerability: a party acting on behalf of the application's vendor gives instructions to fix it or makes a patch available that can be downloaded; then someone using that information fixes the computer or application in question. This paper considers the effects of proprietary software versus non-proprietary software in determining the speed with which a security fix is made available, since this can minimize the amount of time that the computer system remains vulnerable.     

A probabilistic framework for specular shape-from-shading

One of the problems that hinders conventional methods for shape-from-shading is the presence of local specularities which may be misidentified as high curvature surface features. In this paper we address the problem of estimating the proportions of Lambertian and specular reflection components in order to improve the quality of surface normal information recoverable using shape-from-shading. The framework for our study is provided by the iterated conditional modes algorithm. We develop a maximum a posteriori probability (MAP) estimation method for estimating the mixing proportions for Lambertian and specular reflectance, and also, for recovering local surface normals. The MAP estimation scheme has two model ingredients. First, there are separate conditional measurement densities which describe the distributions of surface normal directions for the Lambertian and specular reflectance components. We experimentally compare three different models for the specular component. The second ingredient is a smoothness prior which models the distribution of surface normal directions over local image regions. We demonstrate the utility of method on real-world data. Ground truth data is provided by imagery obtained with crossed polaroid filters. This reveals not only that the method accurately estimates the proportion of specular reflection, but that it also results in good surface normal reconstruction in the proximity of specular highlights.     

Application of ion-engineered Persian Gulf seawater in EOR:effects of different ions on interfacial tension,contact angle,zeta potential,and oil recovery

In this study,we initially performed interfacial tension(IFT)tests to investigate the potential of using the Persian Gulf sea-water(PGSW)as smart water with dif...     

Scattering of elastic P- and SV-waves by a circular coated nanofiber based on Gurtin–Murdoch model of surface elasticity: Scattering cross section results

In this article, an analytical study of elastic P- and SV-wave scattering by a circular nanofiber is presented. The nanofiber is assumed to be surrounded by an inhomogeneous interphase layer, and Gurtin–Murdoch's model of surface elasticity is utilized to study the surface/interface effects in the regions between the fiber and interphase and also interphase and matrix. The simultaneous effects of surface elasticity and interphase inhomogeneity are considered here; by taking the inhomogeneous interphase to be composed of several sublayers, a transfer matrix approach is used to find the unknown field variables and, consequently, the scattering cross sections. The results indicate that considering the effects of surface elasticity and interphase inhomogeneity has a considerable impact on the calculated scattering cross sections.     

Automatic image‐based stress analysis by the scaled boundary finite element method

Digital imaging technologies such as X‐ray scans and ultrasound provide a convenient and non‐invasive way to capture high‐resolution images. The colour intensity of digital images provides information on the geometrical features and material distribution which can be utilised for stress analysis. The proposed approach employs an automatic and robust algorithm to generate quadtree (2D) or octree (3D) meshes from digital images. The use of polygonal elements (2D) or polyhedral elements (3D) constructed by the scaled boundary finite element method avoids the issue of hanging nodes (mesh incompatibility) commonly encountered by finite elements on quadtree or octree meshes. The computational effort is reduced by considering the small number of cell patterns occurring in a quadtree or an octree mesh. Examples with analytical solutions in 2D and 3D are provided to show the validity of the approach. Other examples including the analysis of 2D and 3D microstructures of concrete specimens as well as of a domain containing multiple spherical holes are presented to demonstrate the versatility and the simplicity of the proposed technique. Copyright © 2016 John Wiley & Sons, Ltd.     

A platform for electrochemical sensing of biomolecules based on Europia/reduced graphene oxide nanocomposite

This study aimed at preparing and evaluating the europium oxide–reduced graphene oxide (rGO) composites. Inorganic nanoparticles anchored onto rGO sheets through a facile sonochemical method. The resultant products were characterized by FT-IR, XRD, SEM. Their activity in biomolecules’ analysis were examined by cyclic voltammetry. The rectified electrodes revealed an incredibly electroactive manner. The obtained progress provided excellent materials for scrutiny of biomolecules. The linear relationship was used in the region of 100–1500 µM ascorbic acid (AA), 50–600 µM dopamine (DA), and 10–700 µM uric acid (UA), between current intensities and concentrations. The detection restrictions (LOD) (S/N?=?3) decreased to 8 µM, 1.1 µM and 0.085 µM for AA, DA and UA respectively by differential pulse voltammetry (DPV).     

Association between antiinflammatory cytokine,IL‐10, and sleep quality in patients on maintenance hemodialysis

Elevated proinflammatory cytokines have been attributed to poor sleep quality in patients receiving hemodialysis. This is the first investigation about the relationship between sleep quality and circulating levels of antiinflammatory markers in these patients. A total of 72 patients who were receiving maintenance hemodialysis were enrolled in this cross‐sectional study. The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality. Patients were divided into two groups: good sleepers (PSQI score < 5) and poor sleepers (PSQI score ≥ 5). Assessments were made for serum biochemical parameters (albumin, parathyroid hormone), inflammatory (interleukin [IL]‐6, tumor necrosis factor‐alpha [TNF‐α], and high‐sensitivity c‐reactive protein [hs‐CRP] ) and antiinflammatory (IL‐10) markers. Fifty‐four patients (75%) were classified as poor sleepers. Poor sleepers showed significantly lower levels of serum IL‐10 and higher serum triglyceride and parathyroid hormone concentrations. These patients were more likely to have more comorbidities. The global PSQI score was significantly correlated with serum IL‐10 (p = 0.03) and triglyceride levels (p = 0.01). Multivariate logistic regression analysis showed a direct correlation between PSQI and having comorbidities (p = 0.011, odds ratio [OR] = 3.918; confidence interval 95% [CI] = 2.742–19.031), between PSQI and serum triglyceride (p = 0.027, OR = 1.027 [95% CI = 1.007–1.048] ), and an inverse correlation between PSQI and serum IL‐10 level (p = 0.021, OR = 0.424 [95% CI = 0.195–0.922]). Reduced circulating levels of the antiinflammatory cytokine IL‐10 were significantly associated with poor sleep quality in hemodialysis patients. Factors including serum IL‐10 and triglyceride concentrations and having comorbidities may predict patients prone to poor sleep quality.     

Optimal pixel aspect ratio for enhanced 3D TV visualization

In multiview 3D TV, a pair of corresponding pixels in adjacent 2D views contributes to the reconstruction of voxels (3D pixels) in the 3D scene. We analyze this reconstruction process and determine the optimal pixel aspect ratio based on which the estimated object position can be improved given specific imaging or viewing configurations and constraints. By applying mathematical modeling, we deduce the optimal solutions for two general stereo configurations: parallel and with vergence. We theoretically show that for a given total resolution a finer horizontal resolution, compared to the usual uniform pixel distribution, in general, provides a better 3D visual experience for both configurations. The optimal value may vary depending on different configuration parameter values. We validate our theoretical results by conducting subjective studies using a set of simulated non-square discretized red–blue stereo pairs and show that human observers indeed have a better 3D viewing experience with an optimized vs. a non-optimized representation of 3D-models.     

Selective Recovery of Cadmium,Cobalt, and Nickel from Spent Ni–Cd Batteries Using Adogen® 464 and Mesoporous Silica Derivatives

Spent Ni–Cd batteries are now considered an important source for many valuable metals. The recovery of cadmium, cobalt, and nickel from spent Ni–Cd Batteries has been performed in this study. The optimum leaching process was achieved using 20% H₂SO₄, solid/liquid (S/L) 1/5 at 80 °C for 6 h. The leaching efficiency of Fe, Cd, and Co was nearly 100%, whereas the leaching efficiency of Ni was 95%. The recovery of the concerned elements was attained using successive different separation techniques. Cd(II) ions were extracted by a solvent, namely, Adogen^® 464, and precipitated as CdS with 0.5% Na₂S solution at pH of 1.25 and room temperature. The extraction process corresponded to pseudo-2nd-order. The prepared PTU-MS silica was applied for adsorption of Co(II) ions from aqueous solution, while the desorption process was performed using 0.3 M H₂SO₄. Cobalt was precipitated at pH 9.0 as Co(OH)₂ using NH₄OH. The kinetic and thermodynamic parameters were also investigated. Nickel was directly precipitated at pH 8.25 using a 10% NaOH solution at ambient temperature. FTIR, SEM, and EDX confirm the structure of the products.     

Protein–Protein Interaction Prediction for Targeted Protein Degradation

Protein–protein interactions (PPIs) play a fundamental role in various biological functions; thus, detecting PPI sites is essential for understanding diseases and developing new drugs. PPI prediction is of particular relevance for the development of drugs employing targeted protein degradation, as their efficacy relies on the formation of a stable ternary complex involving two proteins. However, experimental methods to detect PPI sites are both costly and time-intensive. In recent years, machine learning-based methods have been developed as screening tools. While they are computationally more efficient than traditional docking methods and thus allow rapid execution, these tools have so far primarily been based on sequence information, and they are therefore limited in their ability to address spatial requirements. In addition, they have to date not been applied to targeted protein degradation. Here, we present a new deep learning architecture based on the concept of graph representation learning that can predict interaction sites and interactions of proteins based on their surface representations. We demonstrate that our model reaches state-of-the-art performance using AUROC scores on the established MaSIF dataset. We furthermore introduce a new dataset with more diverse protein interactions and show that our model generalizes well to this new data. These generalization capabilities allow our model to predict the PPIs relevant for targeted protein degradation, which we show by demonstrating the high accuracy of our model for PPI prediction on the available ternary complex data. Our results suggest that PPI prediction models can be a valuable tool for screening protein pairs while developing new drugs for targeted protein degradation.