High slew-rate CMOS operational amplifier

A 0.8 /spl mu/m CMOS operational amplifier configuration with a slew rate in excess of 2 V/ns and a unity gain bandwidth of 55 MHz with a load capacitance of 15 pF is proposed. This employs a dynamic technique that turns on a large current source when the rate of change of input is larger than a pre-decided value.     

Control of polishing of diamond films using microactuation and an atmospheric pressure plasma

In this work, the diamond deposited by hot filament chemical vapor deposition (CVD) is polished using an atmospheric pressure plasma. In order to position the film relative to the plasma, a microactuator system is designed using a stack of domed piezoelectric actuators. A dynamic model based on the physical system is developed and the model parameters are measured experimentally. A system based on laser triangulation is used to measure the position of the diamond film relative to the plasma. Control techniques are used to reduce the oscillations during actuation and to eliminate the steady state positioning error. With the application of feedback control, the overshoot is reduced to 2% and the settling time is reduced to 0.3 s. A preliminary set of experiments is performed to relate process parameters to the final surface roughness of the diamond film. The parameters studied include the film's time of exposure to the plasma, the height of the film relative to the plasma, and the distance from the film to the center of the plasma. It is found that the optimum exposure time is 15 min and the reduction of surface roughness is greatest when the distance between the film and the plasma is at a minimum. The best results are obtained when the top of the film is even in elevation with the tip of the top electrode. The diamond film is translated laterally along the plasma. When feedback control is not used, there is no change in the surface roughness. With feedback control implemented, the surface roughness of the diamond film is reduced by 33%.     

A DNA-binding element for a steroid receptor-binding factor is flanked by dual nuclear matrix DNA attachment sites in the c-myc gene promoter

The receptor-binding factor (RBF) for the avian oviduct progesterone (Pg) receptor (PR) has previously been shown to be a unique 10-kDa nuclear matrix protein that generates high affinity PR-binding sites on avian DNA. This paper describes the use of Southwestern blot and DNA gel shift analyses with RBF protein to identify a minimal 54-base pair RBF-binding element in the matrix-associated region (MAR) of the Pg-regulated c-myc gene promoter. This element contains a 5'-GC-rich domain and a 3'-AT-rich domain, the latter of which has a homopurine/homopyrimidine structure. The gel shift assays required the generation of an RBF-maltose fusion protein (RBF-MBP), which specifically binds this element and is supershifted when the anti-RBF polyclonal antibody is added. Computer analysis of the full-length amino acid sequence for RBF predicts a DNA-binding motif involving a beta-sheet structure at the N-terminal domain. Southern blot analyses using nuclear matrix DNA suggests that there are dual MAR sites in the c-myc promoter, which flank an intervening domain containing the RBF element. The co-transfection of this MAR sequence, containing the RBF element and cloned into a luciferase reporter vector, together with an RBF expression vector construct, into steroid treated human MCF-7 cells, results in a decrease of the c-myc promoter activity relative to control transfections containing only the parent vector of the RBF expression construct. These data suggest that a unique chromatin/nuclear matrix structure, composed of the RBF-DNA element complex which is flanked by nuclear matrix attachment sites, serves to bind the PR and repress the c-myc promoter.     

Neuroanatomy in Rett syndrome: cerebral cortex and posterior fossa

Rett syndrome (RS), a neurodevelopmental disorder of unknown etiology occurring almost exclusively in females, is characterized by autistic-like behavior, motor dysfunction, loss of language skills, dementia, and microcephaly. This study is a follow-up and extension of a previously reported neuroimaging study of patients with RS. We replicated previously reported findings with a larger patient population, and the volumetric MRI analysis was extended to include an analysis of neuroanatomy of the posterior fossa. Twenty girls with RS were compared with individually age- and gender-matched normal controls. Patients with RS showed global reduction in gray- and white-matter volumes. The prefrontal, posterior-frontal, and anterior-temporal regions showed the largest bilateral decrease in gray-matter volume, whereas white-matter volume was uniformly reduced throughout the brain. We found confirmation for the preferential reduction in caudate nucleus volume. However, we observed no preferential reduction in midbrain volume despite a preferential reduction in the midsagittal area of this region. We also present an individual case comparison between monozygotic twins discordant for RS.     

Comprehensive performance modeling and analysis of multicasting in optical networks

Multicasting is becoming increasingly important in today's networks. In optical networks, optical splitters facilitate the multicasting of optical signals. By eliminating the transmission of redundant traffic over certain links, multicasting can improve network performance. However, in a wavelength-division multiplexed (WDM) optical network, the lack of wavelength conversion necessitates the establishment of a single multicast circuit (light-tree) on a single wavelength. On the other hand, establishing several unicast connections (lightpaths) to satisfy a multicast request, while requiring more capacity, is less constrained in terms of wavelength assignment. The objective of the paper is to evaluate the tradeoff between capacity and wavelength continuity in the context of optical multicasting. To this end, we develop accurate analytical models with moderate complexity for computing the blocking probability of multicast requests realized using light-trees, lightpaths, and combinations of light-trees and lightpaths. Numerical results indicate that a suitable combination of light-trees and lightpaths performs best when no wavelength conversion is present.     

Model-based test generation using extended symbolic grammars

A novel, model-based test case generation approach for validating reactive systems, especially those supporting richly structured data inputs and/or interactions, is presented. Given an executable system model and an extended symbolic grammar specifying plausible system inputs, the approach performs a model-based simulation to (i) ensure the consistency of the model with respect to the specified inputs, and (ii) generate corresponding test cases for validating the system. The model-based simulation produces a state transition diagram (STD) automatically justifying the model runtime behaviors within the test case coverage. The STD can further be transformed to produce an evolved symbolic grammar, which can then be used to incrementally generate a refined set of test cases. As a case study, we present a live sequence chart (LSC) model-based test generator, named LCT in short, for LSC simulation and consistency testing. The evolved symbolic grammar produced by the simulator can either be used to generate practical test cases for software testing, or be further refined by applying our model-based test generation approach again with additional test coverage criteria. We further show that LSCs can also be used to specify and test certain temporal system properties during the model simulation. Their satisfaction, reflected in the STD, can either be served as a directive for selective test generation, or a basis for further temporal property model checking.     

Thermal and flow properties of oils from salmon heads

Thermal and flow properties of unrefined oils from the heads of red or pink salmon were evaluated. Major thermal degradation of the salmon oils occurred between 200 and 450°C. Red and pink salmon oils were completely decomposed at 533 and 668°C, respectively. The phase transition of salmon oils occurred over a wide range of temperatures. The melting points of −69.6 to −0.36°C and −64.7 to 20.8°C were observed for red and pink salmon oils, respectively. The enthalpy was 40 j/g for red salmon oil and 39 j/g for pink salmon oil. Specific heat capacity ranges of 0.8 to 1.6 and 1.3 to 2.3 j/g/°C were observed for red and pink salmon oils, respectively. Both salmon oils exhibited Newtonian flow behavior. Red salmon oil required higher magnitudes of energy (kj·mol⁻¹) to flow than pink salmon oil. The viscosity of salmon oils was temperature-dependent and could be predicted by the Arrhenius equation.     

Language independent unsupervised learning of short message service dialect

Noise in textual data such as those introduced by multilinguality, misspellings, abbreviations, deletions, phonetic spellings, non-standard transliteration, etc. pose considerable problems for text-mining. Such corruptions are very common in instant messenger and short message service data and they adversely affect off-the-shelf text mining methods. Most techniques address this problem by supervised methods by making use of hand labeled corrections. But they require human generated labels and corrections that are very expensive and time consuming to obtain because of multilinguality and complexity of the corruptions. While we do not champion unsupervised methods over supervised when quality of results is the singular concern, we demonstrate that unsupervised methods can provide cost effective results without the need for expensive human intervention that is necessary to generate a parallel labeled corpora. A generative model based unsupervised technique is presented that maps non-standard words to their corresponding conventional frequent form. A hidden Markov model (HMM) over a “subsequencized” representation of words is used, where a word is represented as a bag of weighted subsequences. The approximate maximum likelihood inference algorithm used is such that the training phase involves clustering over vectors and not the customary and expensive dynamic programming (Baum–Welch algorithm) over sequences that is necessary for HMMs. A principled transformation of maximum likelihood based “central clustering” cost function of Baum–Welch into a “pairwise similarity” based clustering is proposed. This transformation makes it possible to apply “subsequence kernel” based methods that model delete and insert corruptions well. The novelty of this approach lies in that the expensive (Baum–Welch) iterations required for HMM, can be avoided through an approximation of the loglikelihood function and by establishing a connection between the loglikelihood and a pairwise distance. Anecdotal evidence of efficacy is provided on public and proprietary data.     

Evaluation of potential anti‐cancer activity of cationic liposomal nanoformulated Lycopodium clavatum in colon cancer cells

Research dealing with early diagnosis and efficient treatment in colon cancer to improve patient''s survival is still under investigation. Chemotherapeutic agent result in high systemic toxicity due to their non‐specific actions on DNA repair and/or cell replication. Traditional medicine such as Lycopodium clavatum (LC) has been claimed to have therapeutic potentials against cancer. The present study focuses on targeted drug delivery of cationic liposomal nanoformulated LC (CL‐LC) in colon cancer cells (HCT15) and comparing the efficacy with an anti‐colon cancer drug, 7‐ethyl‐10‐hydroxy‐camptothecin (SN38) along with its nanoformulated form (CL‐SN38). The colloidal suspension of LC was made using thin film hydration method. The drugs were characterised using ultraviolet, dynamic light scattering, scanning electron microscopy, energy, dispersive X‐ray spectroscopy. In vitro drug release showed kinetics of 49 and 89% of SN38 and LC, whereas CL‐SN38 and CL‐LC showed 73 and 74% of sustained drug release, respectively. Studies on morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis of Bcl‐2, Bax, p53 by real‐time polymerase chain reaction and western blot analysis of Bad and p53 protein were performed. Nanoformulated LC significantly inhibited growth and increased the apoptosis of colon cancer cells indicating its potential anti‐cancer activity against colon cancer cells.Inspec keywords: cancer, biological organs, cellular biophysics, drug delivery systems, drugs, nanomedicine, genetics, DNA, molecular biophysics, biochemistry, lipid bilayers, toxicology, suspensions, colloids, light scattering, X‐ray chemical analysis, solvation, enzymes, nanostructured materialsOther keywords: energy dispersive X‐ray spectroscopy, in vitro drug release, morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis, Bcl‐2, Bax, real‐time polymerase chain reaction, western blot analysis, Bad protein, p53 protein, scanning electron microscopy, dynamic light scattering, ultraviolet scattering, thin film hydration method, colloidal suspension, nanoformulated form CL‐SN38, 7‐ethyl‐10‐hydroxy‐camptothecin, anticolon cancer drug, colon cancer cells HCT15, cationic liposomal nanoformulated LC, targeted drug delivery, therapeutic potentials, Lycopodium clavatum, traditional medicines, cell replication, DNA repair, nonspecific actions, high systemic toxicity, chemotherapeutic agents, patient survival, colon cancer treatment, colon cancer diagnosis, CL‐LC, potential anticancer activity     

Classification of speech signal based on gender: a hybrid approach using neuro-fuzzy systems

One of the most important processes in speech processing is gender classification. Generally gender classification is done by considering pitch as feature. In general the pitch value of female is higher than the male. In some cases, pitch value of male is higher and female is low, in that cases this classification will not obtain the exact result. By considering this drawback here proposed a gender classification method which considers three features and uses fuzzy logic and neural network to identify the given speech signal belongs to which gender. For training fuzzy logic and neural network, training dataset is generated by considering the above three features. After completion of training, a speech signal is given as input, fuzzy and neural network gives an output, for that output mean value is taken and this value gives the speech signal belongs to which gender. The result shows the performance of our method in gender classification.