Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

Structural properties of inorganic materials: tungsten bronze SBN ceramics

Rare-earth doped strontium barium niobates were synthesized using usual ceramic technique. The dopants are La, Ce, Gd, Sm and Nd. The materials were characterized by XRD and density measurements. The grain sizes were determined from SEM analysis. Lattice parameters changed uniformly with rare-earth dopants in unfilled structures. Density measurements and SEM analysis confirmed only minute changes in the densities of the ceramics.     

Design considerations for high performance avalanche photodiodemultiplication layers

We have studied the effect of the thickness of the multiplication region on the noise performance characteristics of avalanche photodiodes (APD's). Our simulation results are based on a full band Monte Carlo model with anisotropic threshold energies for impact ionization. Simulation results suggest that the well known McIntyre expression for the excess noise factor is not directly applicable for devices with a very thin multiplication region. Since the number of ionization events is drastically reduced when the multiplication layer is very thin, the “ionization coefficient” is not a good physical parameter to characterize the process. Instead “effective quantum yield,” which is a measure of the total electron-hole pair generation in the device, is a more appropriate parameter to consider. We also show that for the device structure considered here, modeling the excess noise factor using a “discrete Bernoulli trial” model as opposed to the conventional “continuum theory” produces closer agreement to experimental measurements. Our results reinforce the understanding that impact ionization is a strong function of carrier energy and the use of simplified field-dependent models to characterize this high energy process fails to accurately model this phenomenon     

Optimisation of solar photovoltaic (PV) parameters using meta-heuristics

Microsystem Technologies - This paper presents a critical analysis of the meta-heuristic techniques used in various researches on the optimisation of photovoltaic (PV) parameters, which involves...     

Radiation-Induced Senescence Reprograms Secretory and Metabolic Pathways in Colon Cancer HCT-116 Cells

Understanding the global metabolic changes during the senescence of tumor cells can have implications for developing effective anti-cancer treatment strategies. Ionizing radiation (IR) was used to induce senescence in a human colon cancer cell line HCT-116 to examine secretome and metabolome profiles. Control proliferating and senescent cancer cells (SCC) exhibited distinct morphological differences and expression of senescent markers. Enhanced secretion of pro-inflammatory chemokines and IL-1, anti-inflammatory IL-27, and TGF-β1 was observed in SCC. Significantly reduced levels of VEGF-A indicated anti-angiogenic activities of SCC. Elevated levels of tissue inhibitors of matrix metalloproteinases from SCC support the maintenance of the extracellular matrix. Adenylate and guanylate energy charge levels and redox components NAD and NADP and glutathione were maintained at near optimal levels indicating the viability of SCC. Significant accumulation of pyruvate, lactate, and suppression of the TCA cycle in SCC indicated aerobic glycolysis as the predominant energy source for SCC. Levels of several key amino acids decreased significantly, suggesting augmented utilization for protein synthesis and for use as intermediates for energy metabolism in SCC. These observations may provide a better understanding of cellular senescence basic mechanisms in tumor tissues and provide opportunities to improve cancer treatment.     

Perceiving,learning, and exploiting object affordances for autonomous pile manipulation

Autonomous manipulation in unstructured environments will enable a large variety of exciting and important applications. Despite its promise, autonomous manipulation remains largely unsolved. Even the most rudimentary manipulation task—such as removing objects from a pile—remains challenging for robots. We identify three major challenges that must be addressed to enable autonomous manipulation: object segmentation, action selection, and motion generation. These challenges become more pronounced when unknown man-made or natural objects are cluttered together in a pile. We present a system capable of manipulating unknown objects in such an environment. Our robot is tasked with clearing a table by removing objects from a pile and placing them into a bin. To that end, we address the three aforementioned challenges. Our robot perceives the environment with an RGB-D sensor, segmenting the pile into object hypotheses using non-parametric surface models. Our system then computes the affordances of each object, and selects the best affordance and its associated action to execute. Finally, our robot instantiates the proper compliant motion primitive to safely execute the desired action. For efficient and reliable action selection, we developed a framework for supervised learning of manipulation expertise. To verify the performance of our system, we conducted dozens of trials and report on several hours of experiments involving more than 1,500 interactions. The results show that our learning-based approach for pile manipulation outperforms a common sense heuristic as well as a random strategy, and is on par with human action selection.     

Effect of dietary fat on diabetes-induced changes in liver microsomal fatty acid composition and glucose-6-phosphatase activity in rats

Experimental diabetes may manifest itself in a defect in liver microsomal fatty acid desaturation and increased activity of glucose-6-phosphatase (G-6-Pase). The present study was designed to determine whether these changes could be normalized by a change in the dietary fat consumed. Control and streptozotocin-induced diabetic rats were fed nutritionally adequate diets which varied in fatty acid composition. Fatty acid analysis of liver microsomal phospholipids revealed that non-diabetic control animals fed saturated fat (beef tallow) or a diet high in ω3 fatty acids (fish oil) exhibited a significantly higher level of 18∶2ω6 and a lower level of 20∶4ω6 in the phosphatidylcholine and phosphatidylethanolamine fractions compared with diabetic animals. Control and diabetic animals fed the high linoleic acid diet had similar levels of 18∶2ω6 in the microsomal phosphatidylcholine and phosphatidylserine fractions. Microsomal G-6-Pase activity was higher in diabetic than in control animals. Activity of G-6-Pase was lower in microsomes of control animals fed the soybean oil or the fish oil diet, but was not significantly reduced in diabetic animals fed high polyunsaturated fats. Blood glucose levels were similar in control groups fed the different diets, but the plasma hemoglobin A1c level was lower in diabetic animals fed the soybean oil diet. Cholesterol and triglyceride levels were lower in diabetic animals fed the fish oil-based diet. The results suggest that dietary fat manipulation has the potential to change at least some of the abnormalities in the microsomal membrane in experimental diabetes.