Formant extraction from linear-prediction phase spectra

Extraction of formant information from linear-prediction phase spectra is proposed. It is shown that the derivative of phase spectrum gives reliable formant information. Since the phase spectra for several resonators in cascade are additive, the resonance peaks are additive in the derivative of the phase spectrum unlike in the magnitude spectrum and hence the problem of identifying merged peaks is very easily solved by this method. Application of the method is illustrated through examples of linear-prediction spectra obtained for simulated models and for actural speech segments.

Karnaugh map synthesis of multigate threshold networks

It has been shown in an earlier paper that I-realizability of a unate function F of up to six variables corresponds to ' compactness ' of the plot of F on a Karnaugh map. Here, an algorithm has been presented to synthesize on a Karnaugh map a non-threahold function of up to Bix variables with the minimum number of threshold gates connected in cascade. Incompletely specified functions can also be treated. No resort to inequalities is made and no pre-processing (such as positivizing and ordering) of the given switching function is required.

A simple method for potential flow simulation of cascades

A simple method using a combination of conformal mapping and vortex panel method to simulate potential flow in cascades is presented. The cascade is first transformed to a single body using a conformal mapping, and the potential flow over this body is solved using a simple higher order vortex panel method. The advantage of this method over existing methodologies is that it enables the use of higher order panel methods, as are used to solve flow past an isolated airfoil, to solve the cascade problem without the need for any numerical integrations or iterations. The fluid loading on the blades, such as the normal force and pitching moment, may be easily calculated from the resultant velocity field. The coefficient of pressure on cascade blades calculated with this methodology shows good agreement with previous numerical and experimental results.

Cascades of Selective Pulses on Connected Single-Quantum Transitions Leading to the Selective Excitation of Multiple-Quantum Coherences

A symmetric cascade of selective pulses applied on connected transitions leads to the excitation of a selected multiple-quantum coherence by a well-defined angle. This cascade selectively operates on the subspace of the multiple-quantum coherence and acts as a generator of rotation selectively on the multiple-quantum subspace. Single-transition operator algebra has been used to explain these experiments. Experiments have been performed on two- and three-spin systems. It is shown that such experiments can be utilized to measure the relaxation times of selected multiple-quantum coherences or of a specifically prepared initial longitudinal state of the spin system.

Cytochrome P4504f, a potential therapeutic target limiting neuroinflammation

Inflammatory processes are involved in the pathogenesis and/or progression of acute central nervous system (CNS) infection, traumatic brain injury and neurodegenerative disorders among others indicating the need for novel strategies to limit neuroinflammation. Eicosanoids including leukotrienes, particularly leukotriene B-4 (LTB4) are principle mediator(s) of inflammatory response, initiating and amplifying the generation of cytokines and chemokines. Cytochrome P450 (Cyp), a family of heme proteins mediate metabolism of xenobiotics and endogenous compounds, such as eicosanoids and leukotrienes. Cytochrome P4504F (Cyp4f) subfamily includes five functional enzymes in mouse. We cloned and expressed the mouse Cyp4f enzymes, assayed their relative expression in brain and examined their ability to hydroxylate the inflammatory cascade prompt LTB4 to its inactive 20-hydroxylated product. We then examined the role of Cyp4fs in regulating inflammatory response in vitro, in microglial cells and in vivo, in mouse brain using lipopolysacharide (LPS), as a model compound to generate inflammatory response. We demonstrate that mouse brain Cyp4fs are expressed ubiquitously in several cell types in the brain, including neurons and microglia, and modulate inflammatory response triggered by LPS, in vivo and in microglial cells, in vitro through metabolism of LTB4 to the inactive 20-hydroxy LTB4. Chemical inhibitor or shRNA to Cyp4fs enhance and inducer of Cyp4fs attenuates inflammatory response. Further, induction of Cyp4f expression lowers LTB4 levels and affords neuroprotection in microglial cells or mice exposed to LPS. Thus, catalytic activity of Cyp4fs is a novel target for modulating neuroinflammation through hydroxylation of LTB4. (C) 2011 Elsevier Inc. All rights reserved.

Dynamically Reconfigurable Regular Expression Matching Architecture

Regular Expressions are generic representations for a string or a collection of strings. This paper focuses on implementation of a regular expression matching architecture on reconfigurable fabric like FPGA. We present a Nondeterministic Finite Automata based implementation with extended regular expression syntax set compared to previous approaches. We also describe a dynamically reconfigurable generic block that implements the supported regular expression syntax. This enables formation of the regular expression hardware by a simple cascade of generic blocks as well as a possibility for reconfiguring the generic blocks to change the regular expression being matched. Further,we have developed an HDL code generator to obtain the VHDL description of the hardware for any regular expression set. Our optimized regular expression engine achieves a throughput of 2.45 Gbps. Our dynamically reconfigurable regular expression engine achieves a throughput of 0.8 Gbps using 12 FPGA slices per generic block on Xilinx Virtex2Pro FPGA.

Nature's Swiss Army Knives: Ovipositor Structure Mirrors Ecology in a Multitrophic Fig Wasp Community

Background: Resource partitioning is facilitated by adaptations along niche dimensions that range from morphology to behaviour. The exploitation of hidden resources may require specially adapted morphological or sensory tools for resource location and utilisation. Differences in tool diversity and complexity can determine not only how many species can utilize these hidden resources but also how they do so. Methodology and Principal Findings: The sclerotisation, gross morphology and ultrastructure of the ovipositors of a seven-member community of parasitic wasps comprising of gallers and parasitoids developing within the globular syconia (closed inflorescences) of Ficus racemosa (Moraceae) was investigated. These wasps also differ in their parasitism mode (external versus internal oviposition) and their timing of oviposition into the expanding syconium during its development. The number and diversity of sensilla, as well as ovipositor teeth, increased from internally ovipositing to externally ovipositing species and from gallers to parasitoids. The extent of sclerotisation of the ovipositor tip matched the force required to penetrate the syconium at the time of oviposition of each species. The internally ovipositing pollinator had only one type of sensillum and a single notch on the ovipositor tip. Externally ovipositing species had multiple sensilla types and teeth on their ovipositors. Chemosensilla were most concentrated at ovipositor tips while mechanoreceptors were more widely distributed, facilitating the precise location of hidden hosts in these wasps which lack larval host-seeking behaviour. Ovipositor traits of one parasitoid differed from those of its syntopic galler congeners and clustered with those of parasitoids within a different wasp subfamily. Thus ovipositor tools can show lability based on adaptive necessity, and are not constrained by phylogeny. Conclusions/Significance: Ovipositor structure mirrored the increasingly complex trophic ecology and requirements for host accessibility in this parasite community. Ovipositor structure could be a useful surrogate for predicting the biology of parasites in other communities.

Biomonitoring of Lotic habitats through Diatoms

Freshwater ecosystems vary in size and composition and contain a wide range of organisms which interact with each other and with the environment. These interactions are between organisms and the environment as nutrient cycling, biomass formation and transfer, maintenance of internal environment and interactions with the external environment. The range of organisms present in aquatic communities decides the generation and transfer function of biomass, which defines and characterises the system. These organisms have distinct roles as they occupy particular trophic levels, forming an interconnected system in a food chain. Availability of resources and competition would primarily determine the balance of individual species within the food web, which in turn influences the variety and proportions of the different organisms, with important implications for the overall functioning of the system. This dynamic and diverse relationship decides the physical, chemical and biological elements across spatial and temporal scales in the aquatic ecosystem, which can be recorded by regular inventorying and monitoring to maintain the integrity and conserve the ecosystem. Regular environmental monitoring, particularly water quality monitoring allows us to detect, assess and manage the overall impacts on the rivers. The appreciation of water quality is in constant flux. Water quality assessments derived through the biotic indices, i.e. assessments based on observations of the resident floral and faunal communities has gained importance in recent years. Biological evaluations provide a description of the water quality that is often not achievable from elemental analyses alone. A biological indicator (or bioindicator) is a taxon or taxa selected based on its sensitivity to a particular attribute, and then assessed to make inferences about that attribute. In other words, they are a substitute for directly measuring abiotic features or other biota. Bioindicators are evaluated through presence or absence, condition, relative abundance, reproductive success, community structure (i.e. composition and diversity), community function (i.e. trophic structure), or any combination thereof.Biological communities reflect the overall ecological integrity by integrating various stresses, thus providing a broad measure of their synergistic impacts. Aquatic communities, both plants and animals, integrate and reflect the effects of chemical and physical disturbances that occur over extended periods of time. Monitoring procedures based on the biota measure the health of a river and the ability of aquatic ecosystems to support life as opposed to simply characterising the chemical and physical components of a particular system. This is the central purpose of assessing the biological condition of aquatic communities of a river.Diatoms (Bacillariophyceae), blue green algae (Cyanophyceae), green algae (Chlorophyceae), and red algae (Rhodphyceae) are the main groups of algae in flowing water. These organisms are widely used as biological indicators of environmental health in the aquatic ecosystem because algae occupy the most basic level in the transfer of energy through natural aquatic systems. The distribution of algae in an aquatic ecosystem is directly related to the fundamental factors such as physical, chemical and biological constituents. Soft algae (all the algal groups except diatoms) have also been used as indicators of biological integrity, but they may have less efficiency than diatoms in this respect due to their highly variable morphology. The diatoms (Bacillariophyceae) comprise a ubiquitous, highly successful and distinctive group of unicellular algae with the most obvious distinguishing characteristic feature being siliceous cell walls (frustules). The photosynthetic organisms living within its photic zone are responsible for about one-half of global primary productivity. The most successful organisms are thought to be photosynthetic prokaryotes (cyanobacteria and prochlorophytes) and a class of eukaryotic unicellular algae known as diatoms. Diatoms are likely to have arisen around 240 million years ago following an endosymbiotic event between a red eukaryotic alga and a heterotrophic flagellate related to the Oomycetes.The importance of algae to riverine ecology is easily appreciated when one considers that they are primary producers that convert inorganic nutrients into biologically active organic compounds while providing physical habitat for other organisms. As primary producers, algae transform solar energy into food from which many invertebrates obtain their energy. Algae also transform inorganic nutrients, such as atmospheric nitrogen into organic forms such as ammonia and amino acids that can be used by other organisms. Algae stabilises the substrate and creates mats that form structural habitats for fish and invertebrates. Algae are a source of organic matter and provide habitat for other organisms such as non-photosynthetic bacteria, protists, invertebrates, and fish. Algae's crucial role in stream ecosystems and their excellent indicator properties make them an important component of environmental studies to assess the effects of human activities on stream health. Diatoms are used as biological indicators for a number of reasons: 1. They occur in all types of aquatic ecosystems. 2. They collectively show a broad range of tolerance along a gradient of aquatic productivity, individual species have specific water chemistry requirements. 3. They have one of the shortest generation times of all biological indicators (~2 weeks). They reproduce and respond rapidly to environmental change and provide early measures of both pollution impacts and habitat restoration. 4. It takes two to three weeks before changes are reflected to a measurable extent in the assemblage composition.

Model for Predicting the Mean Drop Size in Effervescent Sprays

This paper is focused on the development of a model for predicting the mean drop size in effervescent sprays. A combinatorial approach is followed in this modeling scheme, which is based on energy and entropy principles. The model is implemented in cascade in order to take primary breakup (due to exploding gas bubbles) and secondary breakup (due to shearing action of surrounding medium) into account. The approach in this methodology is to obtain the most probable drop size distribution by maximizing the entropy while satisfying the constraints of mass and energy balance. The comparison of the model predictions with the past experimental data is presented for validation. A careful experimental study is conducted over a wide range of gas-to-liquid ratios, which shows a good agreement with the model predictions: It is observed that the model gives accurate results in bubbly and annular flow regimes. However, discrepancies are observed in the transitional slug flow regime of the atomizer.

Support Vector Machine Approach to Downscale Precipitation in Climate Change Scenarios

Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.

Dynamic Multiscaling in Two-Dimensional Fluid Turbulence

We obtain, by extensive direct numerical simulations, time-dependent and equal-time structure functions for the vorticity, in both quasi-Lagrangian and Eulerian frames, for the direct-cascade regime in two-dimensional fluid turbulence with air-drag-induced friction. We show that different ways of extracting time scales from these time-dependent structure functions lead to different dynamic-multiscaling exponents, which are related to equal-time multiscaling exponents by different classes of bridge relations; for a representative value of the friction we verify that, given our error bars, these bridge relations hold.

Nonthermal-Plasma-Promoted Catalysis for the Removal of NOx From a Stationary Diesel-Engine Exhaust

A detailed study on the removal of oxides of nitrogen (NOx) from the exhaust of a stationary diesel engine was carried out using nonthermal-plasma (pulsed electrical-discharge plasma)-promoted catalytic process. In this paper, the filtered exhaust from the diesel engine is made to pass through a combination of nonthermal plasma reactor and a catalytic reactor connected in series. This combination is referred to as cascade. Two types of cascaded systems were studied. In one type, the plasma treating filtered exhaust was cascaded with a reduction catalyst V2O5/TiO2 using ammonia as reducing agent, and in the other type, the plasma treating filtered exhaust was cascaded with activated-alumina catalyst without any additive. Improved NOx-removal performance of both the cascaded processes and the role of nonthermal plasma in promoting catalysis are explained. Along with the NOx, total hydrocarbon and aldehydes were also removed. Furthermore, experiments were conducted at different temperatures and engine-loading conditions.

Glycodelin-A interferes with IL-2/IL-2R signalling to induce cell growth arrest, loss of effector functions and apoptosis in T-lymphocytes

The progesterone-regulated glycoprotein glycodelin-A (GdA), secreted by the decidualized endometrium at high concentrations in primates, inhibits the maternal immune response against fetal antigens and thereby contributes to the tolerance of the semi-allogenic fetus during a normal pregnancy. Our earlier studies demonstrated the ability of GdA to induce an intrinsic apoptotic cascade in CD4 T-lymphocytes and suppress the cytolytic effector function of CD8 T-lymphocytes. In this report, we investigated further into the mechanism of action of GdA controlling perforin and granzyme B expression in CD8 T-lymphocytes and the mechanism of action of GdA leading to lymphocyte death. Flow cytometry analysis was performed to check for the surface expression of interleukin-2 receptor (IL-2R) and intracellular eomesodermin (Eomes) in activated T-lymphocytes, whereas quantitative RTPCR analysis was used to find out their mRNA profile upon GdA treatment. Western analysis was carried out to confirm the protein level of Bax and Bcl-2. GdA reduces the surface expression of the high-affinity IL-2R complex by down-regulating the synthesis of IL-2R (CD25). This disturbs the optimal IL-2 signalling and decreases the Eomes expression, which along with IL-2 directly regulates perforin and granzymes expression. Consequently, the CD8 T-lymphocytes undergo growth arrest and are unable to mature into competent cytotoxic T-lymphocytes. In the CD4 T-lymphocytes, growth factor IL-2 deprivation leads to proliferation inhibition, decreased Bcl-2/enhanced Bax expression, culminating in mitochondrial stress and cell death. GdA spurs cell cycle arrest, loss of effector functions and apoptosis in different T-cell subsets by making T-lymphocytes unable to respond to IL-2.

Silencing of toxic gene expression by Fis

Bacteria and bacteriophages have evolved DNA modification as a strategy to protect their genomes. Mom protein of bacteriophage Mu modifies the phage DNA, rendering it refractile to numerous restriction enzymes and in turn enabling the phage to successfully invade a variety of hosts. A strong fortification, a combined activity of the phage and host factors, prevents untimely expression of mom and associated toxic effects. Here, we identify the bacterial chromatin architectural protein Fis as an additional player in this crowded regulatory cascade. Both in vivo and in vitro studies described here indicate that Fis acts as a transcriptional repressor of mom promoter. Further, our data shows that Fis mediates its repressive effect by denying access to RNA polymerase at mom promoter. We propose that a combined repressive effect of Fis and previously characterized negative regulatory factors could be responsible to keep the gene silenced most of the time. We thus present a new facet of Fis function in Mu biology. In addition to bringing about overall downregulation of Mu genome, it also ensures silencing of the advantageous but potentially lethal mom gene.

Cascaded walks in protein sequence space: use of artificial sequences in remote homology detection between natural proteins

Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.