Assessment of genetic diversity and identification of core collection in sandalwood germplasm using RAPDS

Sandalwood is an economically important aromatic tree belonging to the family Santalaceae. The trees are used mainly for their fragrant heartwood and oil that have immense potential for foreign exchange. Very little information is available on the genetic diversity in this species. Hence studies were initiated and genetic diversity estimated using RAPD markers in 51 genotypes of Santalum album procured from different geographcial regions of India and three exotic lines of S. spicatum from Australia. Eleven selected Operon primers (10mer) generated a total of 156 consistent and unambiguous amplification products ranging from 200bp to 4kb. Rare and genotype specific bands were identified which could be effectively used to distinguish the genotypes. Genetic relationships within the genotypes were evaluated by generating a dissimilarity matrix based on Ward's method (Squared Euclidean distance). The phenetic dendrogram and the Principal Component Analysis generated, separated the 51 Indian genotypes from the three Australian lines. The cluster analysis indicated that sandalwood germplasm within India constitutes a broad genetic base with values of genetic dissimilarity ranging from 15 to 91 %. A core collection of 21 selected individuals revealed the same diversity of the entire population. The results show that RAPD analysis is an efficient marker technology for estimating genetic diversity and relatedness, thereby enabling the formulation of appropriate strategies for conservation, germplasm management, and selection of diverse parents for sandalwood improvement programmes.

Identification of a core promoter and a novel isoform of the human TSCI gene transcript and structural comparison with mouse homolog

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder with loci on chromosome 9q34.12 (TSC1) and chromosome 16p13.3 (TSC2). Genes for both loci have been isolated and characterized. The promoters of both genes have not been characterized so far and little is known about the regulation of these genes. This study reports the characterization of the human TSC1 promoter region for the first time. We have identified a novel alternative isoform in the 5' untranslated region (UTR) of the TSC1 gene transcript involving exon 1. Alternative isoforms in the 5' UTR of the mouse Tsc1 gene transcript involving exon I and exon 2 have also been identified. We have identified three upstream open reading frames (uORFs) in the 5' UTR of the TSC1/Tsc1 gene. A comparative study of the 5' UTR of TSC1/Tsc1 gene has revealed that there is a high degree of similarity not only in the sequence but also in the splicing pattern of both human and mouse TSC1 genes. We have used PCR methodology to isolate approximately 1.6 kb genomic DNA 5' to the TSC1 cDNA. This sequence has directed a high level of expression of luciferase activity in both HeLa and HepG2 cells. Successive 5' and 3' deletion analysis has suggested that a -587 bp region, from position +77 to -510 from the transcription start site (TSS), contains the promoter activity. Interestingly, this region contains no consensus TATA box or CAAT box. However, a 521-bp fragment surrounding the TSS exhibits the characteristics of a CpG island which overlaps with the promoter region. The identification of the TSC1 promoter region will help in designing a suitable strategy to identify mutations in this region in patients who do not show any mutations in the coding regions. It will also help to study the regulation of the TSC1 gene and its role in tumorigenesis. (C) 2003 Elsevier B.V. All rights reserved.

Reducing Buffer Requirements in Core Routers using Dynamic Buffering

Earlier studies have exploited statistical multiplexing of flows in the core of the Internet to reduce the buffer requirement in routers. Reducing the memory requirement of routers is important as it enables an improvement in performance and at the same time a decrease in the cost. In this paper, we observe that the links in the core of the Internet are typically over-provisioned and this can be exploited to reduce the buffering requirement in routers. The small on-chip memory of a network processor (NP) can be effectively used to buffer packets during most regimes of traffic. We propose a dynamic buffering strategy which buffers packets in the receive and transmit buffers of a NP when the memory requirement is low. When the buffer requirement increases due to bursts in the traffic, memory is allocated to packets in the off-chip DRAM. This scheme effectively mitigates the DRAM access bottleneck, as only a part of the traffic is stored in the DRAM. We build a Petri net model and evaluate the proposed scheme with core Internet like traffic. At 77% link utilization, the dynamic buffering scheme has a drop rate of just 0.65%, whereas the traditional DRAM buffering has 4.64% packet drop rate. Even with a high link utilization of 90%, which rarely happens in the core, our dynamic buffering results in a packet drop rate of only 2.17%, while supporting a throughput of 7.39 Gbps. We study the proposed scheme under different conditions to understand the provisioning of processing threads and to determine the queue length at which packets must be buffered in the DRAM. We show that the proposed dynamic buffering strategy drastically reduces the buffering requirement while still maintaining low packet drop rates.

Multiclass Core Vector Machine

Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these approaches to handle large data sets still needs much of exploration. Core Vector Machine(CVM) is a technique for scaling up a two class SVM to handle large data sets. In this paper we propose a Multiclass Core Vector Machine(MCVM). Here we formulate the multiclass SVM problem as a Quadratic Programming(QP) problem defining an SVM with vector valued output. This QP problem is then solved using the CVM technique to achieve scalability to handle large data sets. Experiments done with several large synthetic and real world data sets show that the proposed MCVM technique gives good generalization performance as that of SVM at a much lesser computational expense. Further, it is observed that MCVM scales well with the size of the data set.

Rough Core Vector Clustering

Support Vector Clustering has gained reasonable attention from the researchers in exploratory data analysis due to firm theoretical foundation in statistical learning theory. Hard Partitioning of the data set achieved by support vector clustering may not be acceptable in real world scenarios. Rough Support Vector Clustering is an extension of Support Vector Clustering to attain a soft partitioning of the data set. But the Quadratic Programming Problem involved in Rough Support Vector Clustering makes it computationally expensive to handle large datasets. In this paper, we propose Rough Core Vector Clustering algorithm which is a computationally efficient realization of Rough Support Vector Clustering. Here Rough Support Vector Clustering problem is formulated using an approximate Minimum Enclosing Ball problem and is solved using an approximate Minimum Enclosing Ball finding algorithm. Experiments done with several Large Multi class datasets such as Forest cover type, and other Multi class datasets taken from LIBSVM page shows that the proposed strategy is efficient, finds meaningful soft cluster abstractions which provide a superior generalization performance than the SVM classifier.

Health Monitoring Of Composite Structures Based On Acoustic Wave Sensing Using Fiber Optic Sensors

Structural Health Monitoring has gained wide acceptance in the recent past as a means to monitor a structure and provide an early warning of an unsafe condition using real-time data. Utilization of structurally integrated, distributed sensors to monitor the health of a structure through accurate interpretation of sensor signals and real-time data processing can greatly reduce the inspection burden. The rapid improvement of the Fiber Optic Sensor technology for strain, vibration, ultrasonic and acoustic emission measurements in recent times makes it feasible alternative to the traditional strain gauges, PVDF and conventional Piezoelectric sensors used for Non Destructive Evaluation (NDE) and Structural Health Monitoring (SHM). Optical fiber-based sensors offer advantages over conventional strain gauges, and PZT devices in terms of size, ease of embedment, immunity from electromagnetic interference (EMI) and potential for multiplexing a number of sensors. The objective of this paper is to demonstrate the acoustic wave sensing using Extrinsic Fabry-Perot Interferometric (EFPI) sensor on a GFRP composite laminates. For this purpose experiments have been carried out initially for strain measurement with Fiber Optic Sensors on GFRP laminates with intentionally introduced holes of different sizes as defects. The results obtained from these experiments are presented in this paper. Numerical modeling has been carried out to obtain the relationship between the defect size and strain.

Behavior of Sandwich Beams With Functionally Graded Rubber Core in Three Point Bending

The three-point bending behavior of sandwich beams made up of jute epoxy skins and piecewise linear functionally graded (FG) rubber core reinforced with fly ash filler is investigated. This work studies the influence of the parameters such as weight fraction of fly ash, core to thickness ratio, and orientation of jute on specific bending modulus and strength. The load displacement response of the sandwich is traced to evaluate the specific modulus and strength. FG core samples are prepared by using conventional casting technique and sandwich by hand layup. Presence of gradation is quantified experimentally. Results of bending test indicate that specific modulus and strength are primarily governed by filler content and core to sandwich thickness ratio. FG sandwiches with different gradation configurations (uniform, linear, and piecewise linear) are modeled using finite element analysis (ANSYS 5.4) to evaluate specific strength which is subsequently compared with the experimental results and the best gradation configuration is presented. POLYM. COMPOS., 32:1541-1551, 2011. (C) 2011 Society of Plastics Engineers

Hexa-arm star shaped hydrazone derivatives from hexakis(4-formylphenoxy)-cyclotriphosphazene core

A series of novel hexasubstituted cyclophosphazene hydrazones [N(3)P(3)(-OC(6)H(4)-p-CH=N-NH-C(O)-C(6)H(4)-p-X)(6)] (X = H, Br, Cl, F, OH, OCH(3), CH(3), NO(2), NH(2)) were prepared by a sixfold condensation reaction of [N(3)P(3)(-OC(6)H(4)-p-CHO)(6)] with para-substituted benzoic hydrazides [NH(2)-NH-C(O)-C(6)H(4)-p-X] with excellent yields (91-98%). The structures of the compounds were confirmed by elemental analysis, FT-IR, (1)H, (13)C, (31)P, 2D-HSQC NMR and mass spectrometry (MALDI-TOF). All the synthesized cyclophosphazene hydrazones exhibit high thermal stability. The crystal structure of a homogeneously substituted hexakis(4-formylphenoxy)-cyclotriphosphazene was determined by X-ray diffraction analysis. The compound crystallizes in the monoclinic system, space group P2(1)/n with a = 16.558(3) angstrom, b = 10.250(2) angstrom, c = 23.429(5) angstrom, alpha = gamma = 90.00 degrees, beta = 90.461(4)degrees, V = 3976.5(14) angstrom(3) and Z = 4. The R value is 0.0823 for 4290 observed reflections. The conformations of the 4-formylphenoxy-groups are different at the three phosphorus atoms. (C) 2011 Elsevier B.V. All rights reserved.