988 resultados para American Society for Metals
Resumo:
Autosomal recessive primary microcephaly (MCPH) is a genetic disorder that causes a reduction of cortical outgrowth without severe interference with cortical patterning. It is associated with mutations in a number of genes encoding protein involved in mitotic spindle formation and centrosomal activities or cell cycle control. We have shown previously that blocking vasoactive intestinal peptide (VIP) during gestation in mice by using a VIP antagonist (VA) results in microcephaly. Here, we have shown that the cortical abnormalities caused by prenatal VA administration mimic the phenotype described in MCPH patients and that VIP blockade during neurogenesis specifically disrupts Mcph1 signaling. VA administration reduced neuroepithelial progenitor proliferation by increasing cell cycle length and promoting cell cycle exit and premature neuronal differentiation. Quantitative RT-PCR and Western blot showed that VA downregulated Mcph1. Inhibition of Mcph1 expression led to downregulation of Chk1 and reduction of Chk1 kinase activity. The inhibition of Mcph1 and Chk1 affected the expression of a specific subset of cell cycle-controlling genes and turned off neural stem cell proliferation in neurospheres. Furthermore, in vitro silencing of either Mcph1 or Chk1 in neurospheres mimicked VA-induced inhibition of cell proliferation. These results demonstrate that VIP blockade induces microcephaly through Mcph1 signaling and suggest that VIP/Mcph1/Chk1 signaling is key for normal cortical development.
Resumo:
Earlier desinent cavitation studies on a 1/8 caliber ogive by one of the authors (J. W. H.) showed a sudden change in the magnitude of the desinent cavitation number at a critical velocity. In the present work it is shown by means of oil-film flow visualization that below the critical velocity a long laminar separation bubble exists whereas above the critical velocity the laminar separation bubble is short. Thus the desinent cavitation characteristics of a 1/8 caliber ogive are governed by the nature of the viscous flow around the body.
Resumo:
Dendritic cells (DCs) as sentinels of the immune system are important for eliciting both primary and secondary immune responses to a plethora of microbial pathogens. Cooperative stimulation of a complex set of pattern-recognition receptors, including TLR2 and nucleotide-binding oligomerization domain (NOD)-like receptors on DCs, acts as a rate-limiting factor in determining the initiation and mounting of the robust immune response. It underscores the need for ``decoding'' these multiple receptor interactions. In this study, we demonstrate that TLR2 and NOD receptors cooperatively regulate functional maturation of human DCs. Intriguingly, synergistic stimulation of TLR2 and NOD receptors renders enhanced refractoriness to TGF-beta- or CTLA-4-mediated impairment of human DC maturation. Signaling perturbation data suggest that NOTCH1-PI3K signaling dynamics assume critical importance in TLR2- and NOD receptor-mediated surmounting of CTLA-4- and TGF-beta -suppressed maturation of human DCs. Interestingly, the NOTCH1-PI3K signaling axis holds the capacity to regulate DC functions by virtue of PKC delta-MAPK-dependent activation of NF-kappa B. This study provides mechanistic and functional insights into TLR2-and NOD receptor-mediated regulation of DC functions and unravels NOTCH1-PI3K as a signaling cohort for TLR2 and NOD receptors. These findings serve in building a conceptual foundation for the design of improved strategies for adjuvants and immunotherapies against infectious diseases.
Resumo:
Uncertainties in complex dynamic systems play an important role in the prediction of a dynamic response in the mid- and high-frequency ranges. For distributed parameter systems, parametric uncertainties can be represented by random fields leading to stochastic partial differential equations. Over the past two decades, the spectral stochastic finite-element method has been developed to discretize the random fields and solve such problems. On the other hand, for deterministic distributed parameter linear dynamic systems, the spectral finite-element method has been developed to efficiently solve the problem in the frequency domain. In spite of the fact that both approaches use spectral decomposition (one for the random fields and the other for the dynamic displacement fields), very little overlap between them has been reported in literature. In this paper, these two spectral techniques are unified with the aim that the unified approach would outperform any of the spectral methods considered on their own. An exponential autocorrelation function for the random fields, a frequency-dependent stochastic element stiffness, and mass matrices are derived for the axial and bending vibration of rods. Closed-form exact expressions are derived by using the Karhunen-Loève expansion. Numerical examples are given to illustrate the unified spectral approach.
Resumo:
Mechanisms that control the volume changes behavior of foundation soils are well understood. The changes that occur in the behavior of soil due to migration of pollutants are not well understood. The extent of changes that occur in the presence of small concentration of contaminants can be predicted based on changes in the thickness of double layer and associated fabric changes. Interactions that occur with strong contaminants depends on the type of soil, type and concentration of contamination and duration of interaction etc It has been shown that different concentrations (1N and 4N) of sodium hydroxide solution causes abnormal changes on volume change behaviour of soil due to mineralogical changes. An attempt is made in this paper to stabilize contaminated soil using fly ash, after establishing its stability in alkali solutions. It was found that the effectiveness of fly ash to control the alkali induced heave increases with fly ash content incorporated into the soil. X-ray diffraction studies reveal that the mineralogical changes that occur in soil due to alkali interaction are inhibited by the presence of fly ash.
Resumo:
The paper brings out the role of calcium carbonate (CaCO3) on the volume change behaviour of natural black cotton soil with 1N sulfuric acid (H2SO4) as pore fluid. Natural black cotton soil contained predominantly montmorillonite [Ca0.2(Al,Mg)2Si4 O10 (OH)2 .4H2O] along with other minerals such as amesite [(Mg Fe)2 Al (Si Al)2 O5 (OH)4], kalsilite [KAlSiO4] and quartz [SiO2]. The calcitic soil, reacted with H2SO4 during consolidation testing, showed the presence of the new mineral yavapaiite [K Fe(SO4)2]. Consequently, the carbonate soil treated with 1N H2SO4 led to higher swell at seating load and more compression upon loading than the soil with no carbonate. The swelling increased with increase in the amount of carbonate present in the soil.
Resumo:
The transport processes of the dissolved chemicals in stratified or layered soils have been studied for several decades. In case of the solute transport through stratified layers, interface condition plays an important role in determining appropriate transport parameters. First‐ type and third‐ type interface conditions are generally used in the literature. A first‐type interface condition will result in a continuous concentration profile across the interface at the expense of solute mass balance. On the other hand, a discontinuity in concentration develops when a third‐ type interface condition is used. To overcome this problem, a combined first‐ and third‐ type condition at the interface has been widely employed which yields second‐ type condition. This results in a similar break‐through curve irrespective of the layering order, which is non‐physical. In this work, an interface condition is proposed which satisfies the mass balance implicitly and brings the distinction between the breakthrough curves for different layering sequence corroborating with the experimental observations. This is in disagreement with the earlier work by H. M. Selim and co‐workers but, well agreement with the hypothetical result by Bosma and van der Zee; and Van der Zee.
Resumo:
This paper presents the results of the detailed studies on stress - controlled cyclic triaxial tests on sandy soils from Ahmedabad, Gujarat, India subjected to a loading frequency of 0.1 Hz in cyclic triaxial equipment. Undrained stress controlled cyclic triaxial tests were carried out on cylindrical samples of size 50 mm diameter and height 100 mm with different cyclic stress ratios. Laboratory evaluations were carried out to compare the cyclic resistance of clean sand to that of sand with various fines contents at a constant gross void ratio. The gross void ratio considers the voids formed by sand particles and fines. The effects of gross void ratio with and without fines on pore water pressure build up and liquefaction potential of sandy soils in stress controlled tests are presented. The results obtained from this study provide direct evidence that the limiting silt content plays an important role in the cyclic resistance of sandy soils. Below the limiting silt content the cyclic resistance decreases until the limiting silt content is reached and then the cyclic resistance increases.
Resumo:
In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.
Resumo:
Feature selection is an important first step in regional hydrologic studies (RHYS). Over the past few decades, advances in data collection facilities have resulted in development of data archives on a variety of hydro-meteorological variables that may be used as features in RHYS. Currently there are no established procedures for selecting features from such archives. Therefore, hydrologists often use subjective methods to arrive at a set of features. This may lead to misleading results. To alleviate this problem, a probabilistic clustering method for regionalization is presented to determine appropriate features from the available dataset. The effectiveness of the method is demonstrated by application to regionalization of watersheds in conterminous United States for low flow frequency analysis. Plausible homogeneous regions that are formed by using the proposed clustering method are compared with those from conventional methods of regionalization using L-moment based homogeneity tests. Results show that the proposed methodology is promising for RHYS.
Resumo:
Antibodies specific for the modified nucleoside N6-(delta 2-isopentenyl) adenosine (i6A) were employed to identify the tRNAs containing i6A from an unfractionated tRNA mixture by a nitrocellulose filter binding assay. When radioactive aminoacyl-tRNAs were incubated with i6A-specific antibodies and filtered through nitrocellulose membrane filters, the tRNAs possessing i6A (tRNAtyr and tRNAser) remained on the filters. tRNAarg and tRNAlys which do not contain i6A showed no binding. This finding will be useful as a very simple and rapid assay of such RNAs under a variety of conditions. Purification of i6A containing tRNAs from an unfractionated tRNA mixture was achieved by affinity chromatography of the tRNAs on an i6A antibody-Sepharose column. Nonspecific binding of tRNAs to the column was avoided by the use of purified antibodies.
Resumo:
Cavitation inception measurements are reported for flow past a downstream facing step with the height of the step varying from about 0.4 to 5 percent of the forebody diameter. The forebody was a 49 mm hemispherical nose and sigmai values were found to be very strong function of the height of the step. In addition, sigmai values were found to depend on whether the boundary layer approaching the step was laminar or turbulent. Generally sigmai values for turbulent case were lower.
Resumo:
In this paper the use of probability theory in reliability based optimum design of reinforced gravity retaining wall is described. The formulation for computing system reliability index is presented. A parametric study is conducted using advanced first order second moment method (AFOSM) developed by Hasofer-Lind and Rackwitz-Fiessler (HL-RF) to asses the effect of uncertainties in design parameters on the probability of failure of reinforced gravity retaining wall. Totally 8 modes of failure are considered, viz overturning, sliding, eccentricity, bearing capacity failure, shear and moment failure in the toe slab and heel slab. The analysis is performed by treating back fill soil properties, foundation soil properties, geometric properties of wall, reinforcement properties and concrete properties as random variables. These results are used to investigate optimum wall proportions for different coefficients of variation of φ (5% and 10%) and targeting system reliability index (βt) in the range of 3 – 3.2.
Resumo:
Clustering techniques are used in regional flood frequency analysis (RFFA) to partition watersheds into natural groups or regions with similar hydrologic responses. The linear Kohonen's self‐organizing feature map (SOFM) has been applied as a clustering technique for RFFA in several recent studies. However, it is seldom possible to interpret clusters from the output of an SOFM, irrespective of its size and dimensionality. In this study, we demonstrate that SOFMs may, however, serve as a useful precursor to clustering algorithms. We present a two‐level. SOFM‐based clustering approach to form regions for FFA. In the first level, the SOFM is used to form a two‐dimensional feature map. In the second level, the output nodes of SOFM are clustered using Fuzzy c‐means algorithm to form regions. The optimal number of regions is based on fuzzy cluster validation measures. Effectiveness of the proposed approach in forming homogeneous regions for FFA is illustrated through application to data from watersheds in Indiana, USA. Results show that the performance of the proposed approach to form regions is better than that based on classical SOFM.