Connected Weak Edge Detour Number of a Graph

Certain general properties of the detour distance, weak edge detour set, connected weak edge detour set, connected weak edge detour number and connected weak edge detour basis of graphs are studied in this paper. Their relationship with the detour diameter is discussed. It is proved that for each pair of integers k and n with 2 <= k <= n, there exists a connected graph G of order n with cdnw(G)=k. It is also proved that for any three positive integers R,D,k such that k >= D and R < D <= 2R, there exists a connected graph G with radD (G) = R, diamD G = D and cdnw(G)=k

Enzyme changes during seed storage in groundnut (Arachis hypogaea L.)

A change in enzyme activity in seeds due to ageing is a topic of scientific importance. Vigour is essentially a physiological phenomenon influenced by the reserved metabolites, enzyme activities and growth regulators. The exact cause of loss of seed vigour and viability is still unknown as deterioration of seed is a complex process. In the presence of oxygen, ageing of seed can lead to peroxidative changes in polyunsaturated fatty acids. The free radical -induced non-enzymatic peroxidation, which has the potential to damage membrane, is likely to be a primary cause of deterioration of stored seeds. Certain anabolic enzymes help in maintaining viability while some catabolic enzymes decrease viability. The seed catalase and peroxidase activity seem to be decreased during storage. The results revealed that the peroxidase enzyme activity decreased from 0.236 to 0.444 OD 10 min-1 when storage period increased. A decrease in catalase activity from 0.454 to 0.444 ?g H2O2 mg-1 min-1 followed by a small increase from 0.434 to 0.452 ?g H2O2 mg-1 min-1 was observed during storage. But the activity of lipase enzyme increased from 0.236 to 0.231 meq min-1g-1 of sample when the storage period was increased. The study would help to know the deterioration pattern of stored groundnut seeds

A PIPELINED APPROACH FOR FPGA IMPLEMENTATION OF BI MODAL BIOMETRIC PATTERN RECOGNITION

ABSTRACT A Biometric system is essentially a pattern recognition system that makes use of biometric traits to recognize individuals. Systems which are built upon multiple sources of information for establishing identity which are known as multimodal biometric systems can overcome some of the limitations like noisy captured data, intra class variations etc… In this paper a Bi modal biometric system of iris and palm print based on Wavelet Packet Transform (WPT), gabor filters and a neural classifier implemented in FPGA is described. Iris is the unique observable visible feature present in the detailed texture of each eye. Palmprint is referred to the textural data like principal lines wrinkles and ridges present in the palm. The visible texture of a person's iris and palm print is encoded into a compact sequence of 2-D wavelet packet coefficients constituting a biometric signature or a feature vector code. In this paper, a novel multi-resolution approach based on WPT for recognition of iris and palmprint is proposed. With an adaptive threshold, WPT sub image coefficients are quantized into 1, 0 or -1 as biometric signature resulting in the size of biometric signature as 960 bits. The combined pattern vector of palm print features and iris features are formed using fusion at feature level and applied to the pattern classifier. The Learning Vector Quantization neural network is used as pattern classifier and a recognition rate of 97.22% is obtained. A part of the neural network is implemented for input data of 16 dimensions and 12 input classes and 8 output classes, using virtex-4 xc4vlx15 device. This system can complete recognition in 3.25 microseconds thus enabling it being suitable for real time pattern recognition tasks

Characterization of polyxylylenes with solid state {sup 13}C nuclear magnetic resonance spectroscopy

Polyxylylenes are thermoplastics used as encapsulants for electronic devices. Five polyxylylenes were prepared by pyrolysis of [2.2]paracyclophanes and characterized by solid state {sup 13}C NMR spectroscopy. The chemical shift data, in combination with interrupted decoupling experiments, allowed assignment of resonances to their carbon sources in the polymers. This confirmed the integrity of the xylylene building block in the polymers and is consistent with linear polymers. No crosslinking could be detected within the NMR sensitivity limits. Residual paracyclophane was detected by {sup 13}C CP MAS NMR spectroscopy in the polyxylylene samples prepared at room temperature; however discrete {sup 13}C resonances due to amorphous and crystalline phases in the polymers were not resolved

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7–40.7 Mb) and on chromosome 8 (20.3–21.9 Mb). Across experiments, the soil type/ growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions

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