Yield and fibre quality components analysis in upland cotton (Gossypium hirsutum L.) under salinity

Cotton being an important cash crop of India plays a distinguished role in energizing the economy of the country by fetching appreciable amount of foreign exchange annually. The cotton production of country is improving significantly but the yield per unit area is still lower than that of the other countries due to some biotic and abiotic factors. Amongst the abiotic stresses, salinity is a serious threat next to drought. Keeping in view, the present study was conducted to assess the salt tolerance of 32 popular upland varieties released for general cultivation between 1980 and 2001 in India. The study was carried out in normal as well as saline-alkaline condition; in which salinity were created using bore well water irrigation and the average electrical conductivity level of bore well water is 3.10 ds/m. The 32 upland cotton genotypes under both salinity and normal conditions revealed high GCV and genetic gain for number of bolls per plant, boll weight, lint yield per plant, 2.5 per cent span length, leaf area index, Na-K ratio and seed cotton yield and these traits could be improved by simple selection. Correlation and path analysis studies revealed that the seed cotton yield was highly influenced by lint yield per plant in both normal and salinealkaline condition. Significant positive correlations exists between Bartlett's rate index with uniformity ratio, 2.5 per cent span length with bundle strength, uniformity ratio with micronaire and elongation percent, specific leaf area with leaf area index. These results clearly indicated that selection for any one of these traits might lead to concurrent improvement of other traits as well as seed cotton yield. The characters boll weight (-0.347), ginning out turn (-0.528), 2.5% span length (-0.312) and uniformity ratio (-0.440) registered high order negative direct effect on seed cotton yield. This result further confirms the negative association between the quality and yield

Distant Pedestrian Detection in the Wild using Single Shot Detector with Deep Convolutional Generative Adversarial Networks

In this work, we examine the feasibility of applying Deep Convolutional Generative Adversarial Networks (DCGANs) with Single Shot Detector (SSD) as data-processing technique to handle with the challenge of pedestrian detection in the wild. Specifically, we attempted to use in-fill completion to generate random transformations of images with missing pixels to expand existing labelled datasets. In our work, GAN's been trained intensively on low resolution images, in order to neutralize the challenges of the pedestrian detection in the wild, and considered humans, and few other classes for detection in smart cities. The object detector experiment performed by training GAN model along with SSD provided a substantial improvement in the results. This approach presents a very interesting overview in the current state of art on GAN networks for object detection. We used Canadian Institute for Advanced Research (CIFAR), Caltech, KITTI data set for training and testing the network under different resolutions and the experimental results with comparison been showed between DCGAN cascaded with SSD and SSD itself

Targeting Mycobacterium tuberculosis CoaBC through Chemical Inhibition of 4'-Phosphopantothenoyl-l-cysteine Synthetase (CoaB) Activity.

Coenzyme A (CoA) is a ubiquitous cofactor present in all living cells and estimated to be required for up to 9% of intracellular enzymatic reactions. Mycobacterium tuberculosis (Mtb) relies on its own ability to biosynthesize CoA to meet the needs of the myriad enzymatic reactions that depend on this cofactor for activity. As such, the pathway to CoA biosynthesis is recognized as a potential source of novel tuberculosis drug targets. In prior work, we genetically validated CoaBC as a bactericidal drug target in Mtb in vitro and in vivo. Here, we describe the identification of compound 1f, a small molecule inhibitor of the 4'-phosphopantothenoyl-l-cysteine synthetase (PPCS; CoaB) domain of the bifunctional Mtb CoaBC, and show that this compound displays on-target activity in Mtb. Compound 1f was found to inhibit CoaBC uncompetitively with respect to 4'-phosphopantothenate, the substrate for the CoaB-catalyzed reaction. Furthermore, metabolomic profiling of wild-type Mtb H37Rv following exposure to compound 1f produced a signature consistent with perturbations in pantothenate and CoA biosynthesis. As the first report of a direct small molecule inhibitor of Mtb CoaBC displaying target-selective whole-cell activity, this study confirms the druggability of CoaBC and chemically validates this target

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model

Sorghum improvement (1980–2010): Status and way forward

Sorghum (Sorghum bicolor) is the fifth most important cereal crop globally and is the dietary staple of more than 500 million people in over 90 countries, primarily in the developing world (Reddy et al. 2010). With its C4 photosynthetic pathway, it is adapted to a wide range of environmental conditions. It has multiple uses as a food, feed, fodder, fuel and fiber crop (Paterson et al. 2009). More than 35 percent of world sorghum production is going for food consumption (Awika and Rooney 2004) by the poorest of the poor in the largely low-income deficit countries. Worldwide, it is grown on about 40 million ha, of which about 9 million ha are cultivated in Asia; of this the largest area is in India (7.53 milion ha) which has a production of 7.25 million t (FAOSTAT 2011)

Postrainy season sorghum: Constraints and breeding approaches

Sorghum (Sorghum bicolor) is the fifth most important cereal crop in the world. Different types of sorghum are recognized. These are: grain sorghum, dual purpose (grain and fodder) sorghum, fodder sorghum, forage sorghum and sweet stalk sorghum. Also two types of sorghums are noted based on the season of adaptation; these are rainy (wet) season or postrainy (dry) season sorghum. There are two distinct sorghum growing seasons in India, kharif (rainy season; June–October) and rabi (postrainy season; October–January). In India, the grain productivity is about 1.2 t ha-1 in the rainy season, and about 0.8 t ha-1 in the postrainy season whereas the global grain productivity of sorghum is 1.4 t ha-1 (FAOSTAT 2011). The grain sorghum requirements for these two seasonal adaptations are quite diverse due to different agroclimatic conditions (Rana et al. 1997). There has been a significant decline in area under grain and dual purpose sorghum during the rainy season due to grain molds, but the area has remained stable in the postrainy season where mostly dual purpose sorghums are cultivated

Using Barkhausen Noise to Measure Coating Depth of Coated High-Speed Steel

Coated high-speed steel tools are widely used in machining processes as they offer an excellent tool life to cost ratio, but they quickly need replacing once the coated layer is worn away. It would be therefore useful to be able to measure the tool life remaining non-destructively and cheaply. To achieve this, the work presented here aims to measure the thickness of the coated layer of high-speed cutting tools by using Barkhausen noise (BHN) techniques. Coated high-speed steel specimens coated with two different materials (chromium nitride (CrN), titanium nitride (TiN)) were tested using a cost-effective measuring system developed for this study. Sensory features were extracted from the signal received from a pick-up coil and the signal features, Root mean square, peak count, and signal energy, were successfully correlated with the thickness of the coating layer on high-speed steel (HSS) specimens. The results suggest that the Barkhausen noise measuring system developed in this study can successfully indicate the different thickness of the coating layer on CrN/TiN coated HSS specimens

MGEx-Udb: A Mammalian Uterus Database for Expression-Based Cataloguing of Genes across Conditions, Including Endometriosis and Cervical Cancer

Gene expression profiling of uterus tissue has been performed in various contexts, but a significant amount of the data remains underutilized as it is not covered by the existing general resources.). The database can be queried with gene names/IDs, sub-tissue locations, as well as various conditions such as the cervical cancer, endometrial cycles and disorders, and experimental treatments. Accordingly, the output would be a) transcribed and dormant genes listed for the queried condition/location, or b) expression profile of the gene of interest in various uterine conditions. The results also include the reliability score for the expression status of each gene. MGEx-Udb also provides information related to Gene Ontology annotations, protein-protein interactions, transcripts, promoters, and expression status by other sequencing techniques, and facilitates various other types of analysis of the individual genes or co-expressed gene clusters.In brief, MGEx-Udb enables easy cataloguing of co-expressed genes and also facilitates bio-marker discovery for various uterine conditions

2-Mercapto-Quinazolinones as Inhibitors of Type II NADH Dehydrogenase and Mycobacterium tuberculosis:Structure-Activity Relationships, Mechanism of Action and Absorption, Distribution, Metabolism, and Excretion Characterization

<i>Mycobacterium tuberculosis</i> (<i>MTb</i>) possesses two nonproton pumping type II NADH dehydrogenase (NDH-2) enzymes which are predicted to be jointly essential for respiratory metabolism. Furthermore, the structure of a closely related bacterial NDH-2 has been reported recently, allowing for the structure-based design of small-molecule inhibitors. Herein, we disclose <i>MTb</i> whole-cell structure–activity relationships (SARs) for a series of 2-mercapto-quinazolinones which target the <i>ndh</i> encoded NDH-2 with nanomolar potencies. The compounds were inactivated by glutathione-dependent adduct formation as well as quinazolinone oxidation in microsomes. Pharmacokinetic studies demonstrated modest bioavailability and compound exposures. Resistance to the compounds in <i>MTb</i> was conferred by promoter mutations in the alternative nonessential NDH-2 encoded by <i>ndhA</i> in <i>MTb</i>. Bioenergetic analyses revealed a decrease in oxygen consumption rates in response to inhibitor in cells in which membrane potential was uncoupled from ATP production, while inverted membrane vesicles showed mercapto-quinazolinone-dependent inhibition of ATP production when NADH was the electron donor to the respiratory chain. Enzyme kinetic studies further demonstrated noncompetitive inhibition, suggesting binding of this scaffold to an allosteric site. In summary, while the initial <i>MTb</i> SAR showed limited improvement in potency, these results, combined with structural information on the bacterial protein, will aid in the future discovery of new and improved NDH-2 inhibitors

Altitudinal variation in soil organic carbon stock in coniferous subtropical and broadleaf temperate forests in Garhwal Himalaya

<p>Abstract</p> <p>Background</p> <p>The Himalayan zones, with dense forest vegetation, cover a fifth part of India and store a third part of the country reserves of soil organic carbon (SOC). However, the details of altitudinal distribution of these carbon stocks, which are vulnerable to forest management and climate change impacts, are not well known.</p> <p>Results</p> <p>This article reports the results of measuring the stocks of SOC along altitudinal gradients. The study was carried out in the coniferous subtropical and broadleaf temperate forests of Garhwal Himalaya. The stocks of SOC were found to be decreasing with altitude: from 185.6 to 160.8 t C ha^-1and from 141.6 to 124.8 t C ha^-1in temperature (<it>Quercus leucotrichophora</it>) and subtropical (<it>Pinus roxburghii</it>) forests, respectively.</p> <p>Conclusion</p> <p>The results of this study lead to conclusion that the ability of soil to stabilize soil organic matter depends negatively on altitude and call for comprehensive theoretical explanation</p