Empirical models for net-length probability distribution and applications

In this paper, we propose a novel, empirical, and parameterizable model for estimating the probability distribution of wire length for each net in a placed netlist. The model is simple and fast to compute. We did extensive experimentation with state-of-the-art commercial (Cadence) and academic (Parquet and Labyrinth) tools and validated our model. Our distribution model was around three times more accurate than assuming half-perimeter bounding box as the fixed net-length estimate. Since the model is parameterizable it can be easily tailored for different routing tools and benchmarks. This model would be very useful in defining a full fledged probabilistic design automation methodology in which various design metrics are optimized from a probabilistic point of view. We also discuss the application of our model in a novel probabilistic approach to the buffer insertion problem.     

Influence of dietary iron deficiency on acute metal intoxication

The frequent difficulties encountered in the diagnosis of pediatric sarcomas, caused by the lack of observable differentiation at the light microscopic level, has led to the routine use of immunohistochemistry in pediatric surgical pathology. To a large degree the advent of this staining technique has led to the correct assessment of many perplexing lesions that previously would have been given inconclusive diagnoses. However, with increased usage and testing, it has become apparent that there are few, if any, "magic bullets" in immunohistochemistry for pediatric pathologists. Thus, it behooves diagnosticians to be careful in the usage of this technique, to be aware of possible discrepancies in its results, and to remember the ancillary nature of its application. The following article will review selected markers commonly used in pediatric surgical pathology, from both previous reports and the author's perspective, and will briefly consider several new phenotypic markers which have potential utility with childhood sarcomas.     

A Quadratic Modeling-Based Framework for Accurate Statistical Timing Analysis Considering Correlations

The impact of parameter variations on timing due to process variations has become significant in recent years. In this paper, we present a statistical timing analysis (STA) framework with quadratic gate delay models that also captures spatial correlations. Our technique does not make any assumption about the distribution of the parameter variations, gate delays, and arrival times. We propose a Taylor-series expansion-based quadratic representation of gate delays and arrival times which are able to effectively capture the nonlinear dependencies that arise due to increasing parameter variations. In order to reduce the computational complexity introduced due to quadratic modeling during STA, we also propose an efficient linear modeling driven quadratic STA scheme. We ran two sets of experiments assuming the global parameters to have uniform and Gaussian distributions, respectively. On an average, the quadratic STA scheme had 20.5times speedup in runtime as compared to Monte Carlo simulations with an rms error of 0.00135 units between the two timing cummulative density functions (CDFs). The linear modeling driven quadratic STA scheme had 51.5times speedup in runtime as compared to Monte Carlo simulations with an rms error of 0.0015 units between the two CDFs. Our proposed technique is generic and can be applied to arbitrary variations in the underlying parameters under any spatial correlation model     

Optimization of nitrilase production from a new thermophilic isolate

A new thermostable nitrilase‐producing isolate identified as Streptomyces sp. MTCC 7546 has been studied extensively for the optimization of enzyme production operating in batch mode. The benzonitrile was observed as inducer of nitrilase production. The isolate showed maximum nitrilase production after 24 h of incubation at optimal conditions. The strain grows well on a variety of carbon sources and produces the nitrilase that catalyses the hydrolysis of nitriles to acids without formation of amides. The enzyme is mostly active against mono‐ and di‐aliphatic nitriles (10 mmol L^?1) at pH of 7.4 and at a temperature of 50 °C. Copyright © 2007 Society of Chemical Industry     

Targeting Efficiency and Biodistribution of Zoledronate Conjugated Docetaxel Loaded Pegylated PBCA Nanoparticles for Bone Metastasis

In an attempt to improve tumor localization of docetaxel (DTX)‐loaded nanoparticles (NPs), zoledronic acid (ZOL) is used as a ligand to target bone metastasis. DTX‐loaded ZOL‐conjugated polyethylene glycol (PEG)ylated polybutyl cyanoacrylate (PBCA) NPs are prepared using an anionic polymerization technique. PBCA‐PEG‐ZOL NPs are subjected to cytotoxic assay in both BO2 and MCF‐7 cell lines. Cell cycle arrest and apoptosis induced by the PBCA‐PEG‐ZOL NPs are studied. Quantitative cellular uptake, NP uptake route characterization, confocal microscopy and IPP/ApppI levels are performed. PBCA‐PEG‐ZOL NPs show an enhanced cytotoxic effect in both BO2 as well as MCF‐7 cell lines due to higher uptake following ZOL‐mediated endocytosis. The molecular basis of apoptosis reveals the involvement of a cytoplasmic protein in activating the programmed cell death pathway. Route characterization studies reveal that PBCA‐PEG‐ZOL NPs uptake is not completely blocked even by using both inhibitors (genistein and phenyl arsinoxide) simultaneously, conferring that uptake is not entirely based upon clathrin or caveolae. PBCA‐PEG‐ZOL NPs showed 7 and 5.3 times increase in IPP and ApppI production, in comparison to ZOL treatment, and 138 times higher than the control group in MCF‐7 cell line. In BO2 cell line, after treatment with NPs, IPP was 5.35 times higher than ZOL solution. No ApppI in BO2 cell line after treatment with NPs and ZOL solution was found. NP distribution in tumor infected bone is also significantly high in comparison to the normal bone at any time point. It is concluded that ZOL‐conjugated NPs provide an efficient and targeted delivery of DTX, with synergistic effects. Thus, these NPs present a promising treatment in the near future, by actively targeting metastatic tumor.     

Recent Developments in Integrated Solar Combined Cycle Power Plants

Global concern for depleting fossil fuel reserves have been compelling for evolving power generation options using renewable energy sources. The solar energy happens to be a potential source for running the power plants among renewable energy sources. Integrated Solar Combined Cycle(ISCC) power plants have gained popularity among the thermal power plants. Traditional ISCC power plants use Direct Steam Generation(DSG) approach. However, with the DSG method, the ISCC plant’s overall thermal effici...     

Gurson model parameters for ductile fracture simulation in ASTM A992 steels

This study is concerned with the modelling the ductile fracture in ASTM A992 steels using the Gurson‐Tvergaard‐Needleman (GTN) model for high stress triaxiality regime. The GTN model for ASTM A992 structural steels is calibrated from the experiments performed on axisymmetrically notched tensile specimens. The experiments are designed to obtain a range of stress triaxiality and different fracture initiation locations. The non‐uniqueness in the constitutive parameters of the GTN model is illustrated in this study. The choice of a unique set of GTN constitutive parameters is made by choosing the nucleation strain (?_N) as a material constant. The process of estimating this material specific nucleation strain is provided. All the other GTN model parameters corresponding to the material specific nucleation strain (?_N) are evaluated to best fit the experimental results. The calibrated GTN model is shown to predict the load displacement behaviour, ductility and fracture initiation locations in the notched specimens. The calibrated GTN parameters are used to successfully predict the ductility of structural components: (a) bars with a hole; (b) plate with reduced section and (c) plate with holes; that are typically found in structural engineering applications.     

Pushdown resistance as a measure of robustness in progressive collapse analysis

This paper presents a technique termed ‘pushdown analysis’ that can be used to investigate the robustness of building systems by computing residual capacity and establishing collapse modes of a damaged structure. The proposed method is inspired by the pushover method commonly used in earthquake engineering. Three variants of the technique, termed uniform pushdown, bay pushdown and incremental dynamic pushdown, are suggested and exercised using nonlinear analysis on 10-story steel moment frames designed for moderate and high levels of seismic risk. Simulation results show that the frame designed for high seismic risk is more robust than the corresponding one designed for moderate seismic risk. The improved performance is attributed to the influence of seismic detailing, specifically, the presence of reduced beam sections and stronger columns. It is shown that the dynamic impact factors associated with column removal are significantly lower than the commonly used value of 2.0 and are in line with lower values in the guidelines recently proposed by the US Department of Defense. The study suggests that seismic ‘fuses’ can play a role in the design for robustness and a discussion of the implications of this observation is provided.