Rolling of Al-SiC_p Composites

Aluminum based metal matrix composites are offering o utstanding properties in a number of automotive and aircraft components and body structures. The major advantages of these composite materials are their high st rength to weight ratio, high stiffness, high hardness, wear resistance, low coef ficient of thermal expansion, superior dimensional stability and versatility to designer. In addition to these their isotropic properties, good forming characte ristics, easy availability of cheaper reinforcements...     

Excretion of acid hydrolases during molting inPhilosamia ricini

Summary The level of the acid hydrolases -glucuronidase (EC 3.2.3.11), acid phosphatase (EC 3.1.3.2) and acid protease (EC 3.4.4) was studied during larval growth and molting inP. ricini. The level of activity of these enzymes remained low during larval growth; however, the level increased sharply at the time of molting and declined sharply thereafter in the newly ecdysed insect. Interestingly, the diminished activity of these enzymes was almost quantitatively recovered in the cast-off cuticle. The excretion of acid hydrolases through the cast-off cuticle has hitherto not been reported in insects during molting.     

Effect of molasses binder on the physical and mechanical properties

Molasses was used as an alternative binder to the bentonite binder. The change in moisture absorption by pellets prepared with different iron ores and different molasses contents were investigated. Iron ore properties exerted the major effect on pellet behavior and final pellet quality. The absorbed moisture content of pellets prepared without binder, bentonite-added pellets, and molasses-added pellets were in the range of 7.72%–9.95%, 9.62%–10.84%, and 6.14%-6.69%, respectively. The wet pellet compressive strength of molasses-added pellets(43–230 N/pellet) was superior to that of bentonite-added pellets(9.47–11.92 N/pellet). The compressive strength of dried molasses-modified pellets increased to 222–394 N/pellet, which is currently the highest value achieved for dried pellets.     

Formalising and Detecting Community Structures in Real World Complex Networks

Community structure is an integral characteristic of real world networks whichever processes or areas they emerge from. This paper addresses the problem of community structure detection theoretically as well as computationally. The authors introduce a number of concepts such as the neighbourhood and strength of a subgraph, p-community, local maximal p-community, hubs, and outliers that play elemental role in formalising the concept of community structure in complex networks. A few preliminary results have been derived that lead to the development of an algorithm for community structure detection in undirected unweighted networks. The algorithm is based on a local seed expansion strategy that uses the concept of interaction coefficient. The authors have analysed the algorithm on a number of parameters such as accuracy, stability, and quality on synthetic and real world networks from different areas.     

Optimal sampling frequency for volatility forecast models for the Indian stock markets

This paper evaluates the performance of conditional variance models using high‐frequency data of the National Stock Index (S&P CNX NIFTY) and attempts to determine the optimal sampling frequency for the best daily volatility forecast. A linear combination of the realized volatilities calculated at two different frequencies is used as benchmark to evaluate the volatility forecasting ability of the conditional variance models (GARCH (1, 1)) at different sampling frequencies. From the analysis, it is found that sampling at 30 minutes gives the best forecast for daily volatility. The forecasting ability of these models is deteriorated, however, by the non‐normal property of mean adjusted returns, which is an assumption in conditional variance models. Nevertheless, the optimum frequency remained the same even in the case of different models (EGARCH and PARCH) and different error distribution (generalized error distribution, GED) where the error is reduced to a certain extent by incorporating the asymmetric effect on volatility. Our analysis also suggests that GARCH models with GED innovations or EGRACH and PARCH models would give better estimates of volatility with lower forecast error estimates. Copyright © 2008 John Wiley & Sons, Ltd.     

Common variants on 1p36 and 1q42 are associated with cutaneous basal cell carcinoma but not with melanoma or pigmentation traits

To search for new sequence variants that confer risk of cutaneous basal cell carcinoma (BCC), we conducted a genome-wide SNP association study of 930 Icelanders with BCC and 33,117 controls. After analyzing 304,083 SNPs, we observed signals from loci at 1p36 and 1q42, and replicated these associations in additional sample sets from Iceland and Eastern Europe. Overall, the most significant signals were from rs7538876 on 1p36 (OR = 1.28, P = 4.4 x 10(-12)) and rs801114 on 1q42 (OR = 1.28, P = 5.9 x 10(-12)). The 1p36 locus contains the candidate genes PADI4, PADI6, RCC2 and ARHGEF10L, and the gene nearest to the 1q42 locus is the ras-homolog RHOU. Neither locus was associated with fair pigmentation traits that are known risk factors for BCC, and no risk was observed for melanoma. Approximately 1.6% of individuals of European ancestry are homozygous for both variants, and their estimated risk of BCC is 2.68 times that of noncarriers.     

Identification of renal Cd36 as a determinant of blood pressure and risk for hypertension

To identify renally expressed genes that influence risk for hypertension, we integrated expression quantitative trait locus (QTL) analysis of the kidney with genome-wide correlation analysis of renal expression profiles and blood pressure in recombinant inbred strains derived from the spontaneously hypertensive rat (SHR). This strategy, together with renal transplantation studies in SHR progenitor, transgenic and congenic strains, identified deficient renal expression of Cd36 encoding fatty acid translocase as a genetically determined risk factor for spontaneous hypertension.     

miR-1, miR-10b,miR-155, and miR-191 are novel regulators of BDNF

Brain-derived neurotrophic factor (BDNF) is a secreted protein of the neurotrophin family that regulates brain development, synaptogenesis, memory and learning, as well as development of peripheral organs, such as angiogenesis in the heart and postnatal growth and repair of skeletal muscle. However, while precise regulation of BDNF levels is an important determinant in defining the biological outcome, the role of microRNAs (miRs) in modulating BDNF expression has not been extensively analyzed. Using in silico approaches, reporter systems, and analysis of endogenous BDNF, we show that miR-1, miR-10b, miR-155, and miR-191 directly repress BDNF through binding to their predicted sites in BDNF 3′UTR. We find that the overexpression of miR-1 and miR-10b suppresses endogenous BDNF protein levels and that silencing endogenous miR-10b increases BDNF mRNA and protein levels. Furthermore, we show that miR-1/206 binding sites within BDNF 3′UTR are used in differentiated myotubes but not in undifferentiated myoblasts. Finally, our data from two cell lines suggest that endogenous miR-1/206 and miR-10 family miRs act cooperatively in suppressing BDNF through their predicted sites in BDNF 3′UTR. In conclusion, our results highlight miR-1, miR-10b, miR-155, and miR-191 as novel regulators of BDNF long and short 3′UTR isoforms, supporting future research in different physiological and pathological contexts.