MFC-09-1: A New Forage Cowpea (\u3cem\u3eVigna unguiculata\u3c/em\u3e (L.) Walp) Variety for South Zone of India

Cowpea (Vigna unguiculata (L.) Walp) is a leguminous crop grown throughout West Africa, often in association with pearl millet and sorghum. Cowpea is well adapted to the harsh growing conditions, including low soil fertility, high temperatures, and drought. Cowpea can fix atmospheric nitrogen to improve soil fertility and cropping system productivity. Additionally, farmers feed cowpea fodder to livestock to increase income, and collect the manure produced for use in their fields thereby reduces farmers’ reliance on commercial fertilizers and sustains soil fertility. Previous studies with cowpea indicated that this legume improves soil fertility and enhances the intake and utilization of poor quality roughage consequently improving livestock production and productivity

Performance of Dual Purpose Pearl Millet Genotypes as Influenced by Cutting Management and Nitrogen Levels

Pearl millet (Pennisetum glaucum L.) is important minor millets cultivated both for food and fodder. The dual purpose nature of pearl millet has recently identified due to its profused tillering, repeated harvesting and absence of anti nutritional factor. In fodder crops, the production potential can be manipulated by fertilizer management and time of harvest. In this regard, peal millet no exception, scientific study on cutting and nitrogen management on green fodder yield, quality and grain yield is meagre. Therefore, the present investigation was under taken to study the influence of cutting management and nitrogen levels on green forage and grain yield of dual purpose pearl millet

RESPONSE OF DRILL SOWN FINGER MILLET [ELEUSINE CORACANA (L.)] TO PRE AND POST EMERGENT HERBICIDES

The predominant weed floras observed in the experimental plot were Eleusine indica (L.) Gaertn., Dactyloctenium aegyptium. Commelina benghalensis, Ageratum conyzoides, Croton bonplandianum, Celosia argentia, Ocimum canum and Cyperus rotundus. Among different herbicides pre-emergence application of bensulfuron methyl (0.6% G) + pretilachlor (6.0 % G) at 10 kg ha-1 recorded significantly lower weed population of 20.33 per 0.25 m2 and weed dry weight of 7.56 g per 0.25 m2 as compared to unweeded check (172.33 no. and 58.44 g per m2, respectively). However, the grain yield and straw yield (3291 and 5208 kg ha-1, respectively) were significantly higher with pre-emergence application of bensulfuron methyl (0.6 % G) + pretilachlor (6.0 % GR) at 7.5 kg/ha as compared to unweeded check (814 and 1373 kg ha-1, respectively). Finally it can be concluded that pre- emergence application of bensulfuron methyl (0.6 % G) + pretilachlor (6.0 % G) @ 7.5 kg ha-1 (pre mix formulation) resulted in higher grain yield

Enhancing Productivity of Guinea Grass Variety JHGG-08-1 through Agro-Techniques in Southern Dry Zone of Karnataka

Guinea grass (Panicum maximum) is a major pan tropical grass used throughout the tropics for pasture, cut-and-carry, silage and hay. It is a fast growing and leafy grass, which is palatable to livestock with a good nutritional value. However, it is generally recommended to supplement it with sources of protein in order to meet nutritional requirements or improve animal performance. It grows well on a wide variety of well drained soils of good fertility and it is a good vegetative barrier. It can survive quick moving fires which does not harm the underground roots and drought because of the deep, dense and fibrous root system. The potentiality of the varieties varies with agro climatic situation and soil type, keeping these things in view, the present investigation was undertaken to identify the optimum plant population and nutrient levels for enhancing the productivity and quality of guinea grass variety JHGG-08- in southern Zone of Karnataka

Performance of Guinea Grass Variety JHGG-08-1 in Southern Region of Karnataka

Guinea grass (Panicum maximum) is native to Africa but this grass was introduced to almost all tropical countries as a source of animal forage. It grows well on a wide variety of well drained soils of good fertility and it is suitable for vegetative barrier and conservation of soil. It can survive quick moving fires which does not harm the underground roots and drought because of the deep, dense and fibrous root system. The Potentiality of the varieties varies with agro climatic situation and soil type. Keeping these things in view, the present investigation was taken up to study the performance of Guinea grass varieties in southern dry zone of Karnataka under protective irrigation

Understanding Electricity-Theft Behavior via Multi-Source Data

Electricity theft, the behavior that involves users conducting illegal operations on electrical meters to avoid individual electricity bills, is a common phenomenon in the developing countries. Considering its harmfulness to both power grids and the public, several mechanized methods have been developed to automatically recognize electricity-theft behaviors. However, these methods, which mainly assess users' electricity usage records, can be insufficient due to the diversity of theft tactics and the irregularity of user behaviors. In this paper, we propose to recognize electricity-theft behavior via multi-source data. In addition to users' electricity usage records, we analyze user behaviors by means of regional factors (non-technical loss) and climatic factors (temperature) in the corresponding transformer area. By conducting analytical experiments, we unearth several interesting patterns: for instance, electricity thieves are likely to consume much more electrical power than normal users, especially under extremely high or low temperatures. Motivated by these empirical observations, we further design a novel hierarchical framework for identifying electricity thieves. Experimental results based on a real-world dataset demonstrate that our proposed model can achieve the best performance in electricity-theft detection (e.g., at least +3.0% in terms of F0.5) compared with several baselines. Last but not least, our work has been applied by the State Grid of China and used to successfully catch electricity thieves in Hangzhou with a precision of 15% (an improvement form 0% attained by several other models the company employed) during monthly on-site investigation.Comment: 11 pages, 8 figures, WWW'20 full pape

Sex differences in the effect of chronic delivery of the buprenorphine analogue BU08028 on heroin relapse and choice in a rat model of opioid maintenance

Background and Purpose: Maintenance treatment with opioid agonists (buprenorphine, methadone) decreases opioid use and relapse. We recently modelled maintenance treatment in rats and found that chronic delivery of buprenorphine or the μ opioid receptor partial agonist TRV130 decreased relapse to oxycodone seeking and taking. Here, we tested the buprenorphine analogue BU08028 on different heroin relapse-related measures and heroin versus food choice. Experimental Approach: For relapse assessment, we trained male and female rats to self-administer heroin (6 h·day−1, 14 days) in Context A and then implanted osmotic minipumps containing BU08028 (0, 0.03 or 0.1 mg·kg−1·d−1). Effects of chronic BU08028 delivery were tested on (1) incubation of heroin-seeking in a non-drug Context B, (2) extinction responding reinforced by heroin-associated discrete cues in Context B, (3) reinstatement of heroin-seeking induced by re-exposure to Context A and (4) re-acquisition of heroin self-administration in Context A. For choice assessment, we tested the effect of chronic BU08028 delivery on heroin versus food choice. Key Results: Chronic BU08028 delivery decreased incubation of heroin seeking. Unexpectedly, BU08028 increased re-acquisition of heroin self-administration selectively in females. Chronic BU08028 had minimal effects on context-induced reinstatement and heroin versus food choice in both sexes. Finally, exploratory post hoc analyses suggest that BU08028 decreased extinction responding selectively in males. Conclusions and Implications: Chronic BU08028 delivery had both beneficial and detrimental, sex-dependent, effects on different triggers of heroin relapse and minimal effects on heroin choice in both sexes. Results suggest that BU08028 would not be an effective opioid maintenance treatment in humans.</p

Enhanced Disease Susceptibility 1 and Salicylic Acid Act Redundantly to Regulate Resistance Gene-Mediated Signaling

Resistance (R) protein–associated pathways are well known to participate in defense against a variety of microbial pathogens. Salicylic acid (SA) and its associated proteinaceous signaling components, including enhanced disease susceptibility 1 (EDS1), non–race-specific disease resistance 1 (NDR1), phytoalexin deficient 4 (PAD4), senescence associated gene 101 (SAG101), and EDS5, have been identified as components of resistance derived from many R proteins. Here, we show that EDS1 and SA fulfill redundant functions in defense signaling mediated by R proteins, which were thought to function independent of EDS1 and/or SA. Simultaneous mutations in EDS1 and the SA–synthesizing enzyme SID2 compromised hypersensitive response and/or resistance mediated by R proteins that contain coiled coil domains at their N-terminal ends. Furthermore, the expression of R genes and the associated defense signaling induced in response to a reduction in the level of oleic acid were also suppressed by compromising SA biosynthesis in the eds1 mutant background. The functional redundancy with SA was specific to EDS1. Results presented here redefine our understanding of the roles of EDS1 and SA in plant defense

SAG101 Forms a Ternary Complex with EDS1 and PAD4 and Is Required for Resistance Signaling against Turnip Crinkle Virus

EDS1, PAD4, and SAG101 are common regulators of plant immunity against many pathogens. EDS1 interacts with both PAD4 and SAG101 but direct interaction between PAD4 and SAG101 has not been detected, leading to the suggestion that the EDS1-PAD4 and EDS1-SAG101 complexes are distinct. We show that EDS1, PAD4, and SAG101 are present in a single complex in planta. While this complex is preferentially nuclear localized, it can be redirected to the cytoplasm in the presence of an extranuclear form of EDS1. PAD4 and SAG101 can in turn, regulate the subcellular localization of EDS1. We also show that the Arabidopsis genome encodes two functionally redundant isoforms of EDS1, either of which can form ternary complexes with PAD4 and SAG101. Simultaneous mutations in both EDS1 isoforms are essential to abrogate resistance (R) protein-mediated defense against turnip crinkle virus (TCV) as well as avrRps4 expressing Pseudomonas syringae. Interestingly, unlike its function as a PAD4 substitute in bacterial resistance, SAG101 is required for R-mediated resistance to TCV, thus implicating a role for the ternary complex in this defense response. However, only EDS1 is required for HRT-mediated HR to TCV, while only PAD4 is required for SA-dependent induction of HRT. Together, these results suggest that EDS1, PAD4 and SAG101 also perform independent functions in HRT-mediated resistance

Machine Learning Approach for Cardiovascular Risk and Coronary Artery Calcification Score

Coronary artery calcification (CAC) could assist in the discovery of new risk elements for coronary artery disorder. CAC evaluation, on the other hand, is difficult due to the wide range of CAC in the populations. As a reason, evaluating and analysing data among research have become complicated. In the Research of Inherited Risk Factors for Coronary Atherosclerosis, we used CAC information to test the effects of different analytical methodologies on the correlation with recognized cardiovascular risk elements in asymptomatic patients. Cardiac computed tomography (CT) is also seeing an increase in examinations, and machine learning (ML) could assist with the growing amount of extracted data. Furthermore, there are other sectors in cardiac CT where machine learning could be crucial, including coronary calcium scoring, perfusion, and CT angiography. The establishment of risk evaluation algorithms based on information from CAC utilizing machine learning could assist in the categorization of patients undergoing cardiovascular into distinct risk groups and effectively adapt their treatments to their unique situations. Our findings imply that for forecasting CVD occurrences in asymptomatic people, age-sex segmentation by CAC percentile rank is as effective as absolute CAC scoring. Longitudinal population-based investigations are currently underway and would offer further definitive findings. While machine learning is a strong technology with a lot of possibilities, its implementations in the domain of cardiac CAC are generally in the early stages of development and are not currently commonly accessible in medical practise because of the requirement for substantial verification. Enhanced machine learning will, however, have a significant effect on cardiovascular and coronary artery calcification in the upcoming years