The putative tumor suppressor gene on chromosome 5q for hepatocellular carcinoma is distinct from the MCC and APC genes

We have previously shown that the tumor suppressor gene for hepatocellular carcinoma (HCC) without cirrhosis may be located on chromosome 5q35-qter. In this study, we analyzed nine cases of primary HCC without cirrhosis using probes from the MCC and APC genes, which are in the region 5q21-22. None of the informative cases had allele loss detected by these probes, whereas the probe lambda MS8 for the region 5q35-qter showed allele loss in six out of six informative cases. The results confirm that the putative tumor suppressor gene for HCC without cirrhosis on chromosome 5q is distinct from the MCC and APC genes.     

Effects of the cryogenic cooling on the fatigue strength of the AISI 304 stainless steel ground components

For environmental considerations, the substitution of the conventionally used oil-based grinding fluids has nowadays become strongly recommended. Although several alternatives have been proposed, cryogenic cooling by liquid nitrogen is the non-polluting coolant that has been given relatively more attention because of its very low temperature. In this investigation, in order to contribute to developing this promising cooling mode, its beneficial effects on the ground surface integrity of the AISI 304 stainless steel and their consequences on the fatigue lifetime are explored. Results of this investigation show that grinding under cryogenic cooling mode generates surfaces with lower roughness, less defects, higher work hardening and less tensile residual stresses than those obtained on surfaces ground under oil-based grinding fluid. These surface enhancements result into substantial improvements in the fatigue behaviour of components ground under this cooling mode. An increasing rate of almost 15% of the endurance limit at 2 × 10⁶ cycles could be realized. SEM analyses of the fatigue fracture surfaces have shown that the fatigue cracks observed on the specimens ground under cryogenic cooling are shorter (i.e., 30-50 μm) than those generated under oil-based cooling mode (i.e., 150-200 μm). The realized improvements in the surface integrity and in the fatigue behaviour are thought to be related to the reduction of the grinding zone temperature observed under cryogenic cooling, as no significant differences between the grinding force components for both cooling modes have been observed.     

Erosion rate correlations of a pipe protruded in an abrupt pipe contraction

Erosion is one of the most serious problems in various gas and liquid flow passages such as flow in pipes, pumps, turbines, compressors and many other devices. Sand presence causes loss of pipe wall thickness that can lead to pipe erosion, frequent failures and loss of expensive production time. The importance of this problem is mainly due to many related engineering applications, viz. heat exchangers. In order to reduce the frequency of such pipe erosions, caps in the form of replaceable pipes are protruded in the sudden contraction regions which are exposed to most of the serious erosion rates. In the present work, numerical investigation of the erosion of a pipe protruded in a sudden contraction is presented. The turbulent, steady, 2-D axi-symmetric flow inside an axi-symmetric abrupt contraction pipe with a pipe protrusion embedded in it was solved by steady-state time averaged conservation equations of mass and momentum along with two equation model for turbulence. Particles are tracked using Lagrangian particle tracking. An erosion model was employed to investigate the erosion phenomena for the given geometry. The influence of the different parameters such as the inlet flow velocity (3–10 m/s), the particle diameter (10–400 μm), the protruded pipe geometry (thickness T=1–5 mm and depth H=2–5 mm) and the pipe contraction ratio (Cr=0.25–0.5) on the erosion of pipe protrusion was investigated. Correlations for the influence of inlet flow velocity, depth and thickness of the protruded pipe on the erosion rate are presented.     

TP63 Is Significantly Upregulated in Diabetic Kidney

The role of tumor protein 63 (TP63) in regulating insulin receptor substrate 1 (IRS-1) and other downstream signal proteins in diabetes has not been characterized. RNAs extracted from kidneys of diabetic mice (db/db) were sequenced to identify genes that are involved in kidney complications. RNA sequence analysis showed more than 4- to 6-fold increases in TP63 expression in the diabetic mice’s kidneys, compared to wild-type mice at age 10 and 12 months old. In addition, the kidneys from diabetic mice showed significant increases in TP63 mRNA and protein expression compared to WT mice. Mouse proximal tubular cells exposed to high glucose (HG) for 48 h showed significant decreases in IRS-1 expression and increases in TP63, compared to cells grown in normal glucose (NG). When TP63 was downregulated by siRNA, significant increases in IRS-1 and activation of AMP-activated protein kinase (AMPK (p-AMPK-Th¹⁷²)) occurred under NG and HG conditions. Moreover, activation of AMPK by pretreating the cells with AICAR resulted in significant downregulation of TP63 and increased IRS-1 expression. Ad-cDNA-mediated over-expression of tuberin resulted in significantly decreased TP63 levels and upregulation of IRS-1 expression. Furthermore, TP63 knockdown resulted in increased glucose uptake, whereas IRS-1 knockdown resulted in a decrease in the glucose uptake. Altogether, animal and cell culture data showed a potential role of TP63 as a new candidate gene involved in regulating IRS-1 that may be used as a new therapeutic target to prevent kidney complications in diabetes.     

Metallo-organic deposition of tungsten oxide films from alkylammonium tungstate solutions

This paper describes a simple and inexpensive metallo-organic deposition (MOD) process for forming electrochromic tungsten oxide (WO₃) films on glass. The thin films of WO₃ were made by air firing (500–700°C) films from xylene/2-propanol solutions of bis-(di-n-octylammonium) tetratungstate, [(n-C₈H₁₇)₂NH₂]₂[W₄O₁₃]. The process coats glass with undoped films ranging in colour from faint yellow to dark brown, and can be used to make gradients of these colours. The colour is determined by the firing parameters and results from residual carbon and tungsten suboxides in the film due to incomplete firing. Increased firing temperatures or longer firing times removes the carbon and produces films with higher crystallinity. Electrochemical doping with acid (H⁺) switches the colour gradient films to a uniformly blue colour.     

An economic and sensitive method for extracting chromium speciation in airborne inhalable dust,using a green sample treatment coupled with electrothermal atomic absorption

ABSTRACT

A new approach of cloud point extraction CPE procedure is optimized for hexavalent chromium determination in airborne dusts. Triton X-114 is used as a surfactant and 1-(2-pyridylazo)-2-naphthol as a specific complexing agent for the trivalent chromium’s removal from the aqueous phase to isolate hexavalent chromium compounds. The parameters influencing the extraction protocol (pH, surfactant concentration, and temperature are optimized. The obtained detection and quantification limits are 0.1 and 0.4 μg/L, respectively. The linearity is verified, with a regression coefficient close to 0.999 and the extraction recovery exceeds 99%. The method was successfully applied to analyze airborne samples collected from workplaces.     

Sensor Fault Diagnosis and Unknown Disturbances Estimation of High Switching Frequency Single-phase PWM Rectifier

International Journal of Control, Automation and Systems - The fault and disturbances estimation has an important role in the modern traction railway system. This paper proposes a unique method for...     

Evolutionary forwarding games in delay tolerant networks: Equilibria,mechanism design and stochastic approximation

In this paper, we apply evolutionary games to non-cooperative forwarding control in Delay Tolerant Networks (DTNs). The main focus is on mechanisms to rule the participation of the relays to the delivery of messages in DTNs. Thus, we express the success probability as a function of the competition that takes place within a large population of mobiles, and we characterize the effect of reward-based mechanisms on the performance of such systems. Devices acting as active relays, in fact, sacrifice part of their batteries in order to support message replication and thus increase the probability to reach the destination. In our scheme, a relay can choose the strategy by which they participate to the message relaying. A mobile that participates receives a unit of reward based on the reward mechanism selected by the network. A utility function is introduced as the difference between the expected reward and the energy cost, i.e., the cost spent by the relay to sustain forwarding operations. We show how the evolution dynamics and the equilibrium behavior (called Evolutionary Stable Strategy – ESS) are influenced by the characteristics of inter contact time, energy expenditure and pricing characteristics.We extend our analysis to mechanisms that the system can introduce in order to have the message delivered to the destination with high probability within a given deadline and under energy constraints which bound the number of released copies per message. Finally, we apply our findings in order to devise decentralized forwarding algorithms that are rooted in the theory of stochastic approximations. Thus, we demonstrate that the ESS can be attained without complete knowledge of the system state and letting the source monitor number of released copies per message only. We provide extensive numerical results to validate the proposed scheme.     

Toward an efficient and scalable feature selection approach for internet traffic classification

There is significant interest in the network management and industrial security community about the need to identify the “best” and most relevant features for network traffic in order to properly characterize user behaviour and predict future traffic. The ability to eliminate redundant features is an important Machine Learning (ML) task because it helps to identify the best features in order to improve the classification accuracy as well as to reduce the computational complexity related to the construction of the classifier. In practice, feature selection (FS) techniques can be used as a preprocessing step to eliminate irrelevant features and as a knowledge discovery tool to reveal the “best” features in many soft computing applications. In this paper, we investigate the advantages and disadvantages of such FS techniques with new proposed metrics (namely goodness, stability and similarity). We continue our efforts toward developing an integrated FS technique that is built on the key strengths of existing FS techniques. A novel way is proposed to identify efficiently and accurately the “best” features by first combining the results of some well-known FS techniques to find consistent features, and then use the proposed concept of support to select a smallest set of features and cover data optimality. The empirical study over ten high-dimensional network traffic data sets demonstrates significant gain in accuracy and improved run-time performance of a classifier compared to individual results produced by some well-known FS techniques.