Electrochemical Aspects of Electroosmotic Dewatering of Clay Suspensions

An attempt is made to elucidate the electrochemical aspects of the electroosmotic dewatering (EOD) of clays as reported in some recent work, especially that on interrupted DC power electroosmotic dewatering published by Rabie, Mujumdar and Weber (2). These authors showed that the dewatering by EOD stops after the DC power has been on for several minutes or hours; on interruption of their power and on short-circuiting of the electrodes, conditions can be created again for some further dewatering by DC power EOD. This discovery, of Rabie et al. is interpreted as a fuel cell effect and it is shown that it affords clues to several other electrochemical strategies for the possible enhancement of the efficiency of the EOD by DC power.

Further, the open circuit potentials observed by Rabie et al. (2) on the interruption of DC power are given an electrochemical interpretation which leads to quantitative estimates in agreement with the experimental values.     

Properties and Performance of Cation-Doped Ceria Electrolyte Materials in Solid Oxide Fuel Cell Applications

Cation-doped CeO₂ electrolyte has been evaluated in single-cell and short-stack tests in solid oxide fuel cell environments and applications. These results, along with conductivity measurements, indicate that an ionic transference number of ∼0.75 can be expected at 800°C. Single cells have shown a power density >350 mW/cm². Multicell stacks have demonstrated a peak performance of >100 mW/cm² at 700°C using metallic separators.     

A novel dynamic pricing scheme for contributing peers in the VoD system

In this paper we have proposed a dynamic pricing scheme for the contributing peers in the Video on Demand (VoD) system. The scheme provides an effective mechanism to maximize the profit through the residual resources of the contributing peers. A utilization function is executed for each contributing peer to estimate the utility factor based on the parameters such as initial setup cost, holding cost, chaining cost and salvage cost. In this paper, we urge an effective dynamic pricing algorithm that efficiently utilizes a range of parameters with a varying degree of complexity. The key findings of the algorithm are (i) each contributing peers are benefitted by the monetary based on its resource contributions to the VoD system and (ii) a high degree of social optimum is established by proficiently aggregating the contributing peer’s resources with the overall resources of the VoD system. We validate our claim by simulating the proposed dynamic pricing scheme with other standard pricing schemes such as altruism, cost model and game theory perspective. The result of our dynamic pricing scheme shows the best utility factor than other standard pricing schemes.     

Formation of Nanocrystalline Calcia by the Decomposition of Calcite

Formation of nanocrystalline calcia from calcite has been studied in situ via transmission electron microscopy. The crystallographic transformation occurred via two mechanisms: the first is by distortion of the cleaved rhombohedron of calcite, formed by {104} planes in hexagonal coordinates, into a cube. This produced a microstructure of oriented, elongated nanocrystals of calcia with planar boundaries. In the second mechanism, the micrometer-sized parent calcite particles broke up into nano-sized grains as the decomposition began, leading to irregularly shaped, randomly oriented nanocrystals of calcia.     

Low cycle fatigue,fatigue crack propagation and substructures in a series of polycrystalline Cu-Al alloys

Low Cycle Fatigue (LCF) on smooth hour glass specimens and Fatigue Crack Propagation (FCP) studies on Single Edge Notch (SEN) specimens were carried out at room temperature on four Cu-Al polycrystalline alloys to investigate the effects of Stacking Fault Energy (SFE) and mechanical property variations on fatigue characteristics. Significant improvements in fatigue properties were observed for alloys of low SFE. A microhardness technique was used to delineate the fatigue plastic zone ahead of stopped cracks at several stress intensity ranges for all the alloys. Planar slip was associated with a less than a second power dependence of plastic zone size on the stress intensity range. Transmission Electron Microscopy (TEM) was used to observe the substructures that developed both in LCF at different strain ranges and also ahead of fatigue cracks at different stress intensity ranges. Fractography was carried out to study the micromechanisms of crack propagation using a two stage replication technique. The experimental results were in good agreement with a theoretical model for FCP developed previously by the authors which incorporates mechanical and microstructural variables.     

Classification of heart rate data using artificial neural network and fuzzy equivalence relation

The electrocardiogram is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, etc. may contain useful information about the nature of disease afflicting the heart. However, these subtle details cannot be directly monitored by the human observer. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the signal parameters, extracted and analysed using computers, are highly useful in diagnostics. This paper deals with the classification of certain diseases using artificial neural network (ANN) and fuzzy equivalence relations. The heart rate variability is used as the base signal from which certain parameters are extracted and presented to the ANN for classification. The same data is also used for fuzzy equivalence classifier. The feedforward architecture ANN classifier is seen to be correct in about 85% of the test cases, and the fuzzy classifier yields correct classification in over 90% of the cases.     

Truncated O-Glycan-Bearing MUC16 Enhances Pancreatic Cancer Cells Aggressiveness via α4β1 Integrin Complexes and FAK Signaling

Elevated levels of Mucin-16 (MUC16) in conjunction with a high expression of truncated O-glycans is implicated in playing crucial roles in the malignancy of pancreatic ductal adenocarcinoma (PDAC). However, the mechanisms by which such aberrant glycoforms present on MUC16 itself promote an increased disease burden in PDAC are yet to be elucidated. This study demonstrates that the CRISPR/Cas9-mediated genetic deletion of MUC16 in PDAC cells decreases tumor cell migration. We found that MUC16 enhances tumor malignancy by activating the integrin-linked kinase and focal adhesion kinase (ILK/FAK)-signaling axis. These findings are especially noteworthy in truncated O-glycan (Tn and STn antigen)-expressing PDAC cells. Activation of these oncogenic-signaling pathways resulted in part from interactions between MUC16 and integrin complexes (α4β1), which showed a stronger association with aberrant glycoforms of MUC16. Using a monoclonal antibody to functionally hinder MUC16 significantly reduced the migratory cascades in our model. Together, these findings suggest that truncated O-glycan containing MUC16 exacerbates malignancy in PDAC by activating FAK signaling through specific interactions with α4 and β1 integrin complexes on cancer cell membranes. Targeting these aberrant glycoforms of MUC16 can aid in the development of a novel platform to study and treat metastatic pancreatic cancer.     

Design and development of a machine vision system using artificial neural network-based algorithm for automated coal characterization

Coal is heterogeneous in nature,and thus the characterization of coal is essential before its use for a specific purpose.Thus,the current study aims to develop ...     

A stable energy efficient clustering protocol for wireless sensor networks

Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.