Performance of Coloured Bell Pepper in Naturally-Ventilated Polyhouse under Mid-Hill Conditions of Himachal Pradesh

Bell pepper is highly susceptible to water stagnation and excess moisture. Therefore, cultivation of this vegetable under protected structures can prove to be a boon, ensuring higher yields and quality produce. Farmers are mainly concentrating on cultivation of coloured varieties, viz., Orobelle and Bomby, under these structures. Therefore, on-farm trials were laid out during the year 2007 in farmers' fields, with six hybrids of bell pepper (Orobelle, Bomby, Mahabharath, Tanvi, Tanvi Plus and US-26) replicated thrice in RBD at four locations. The aim was to provide a suitable substitute for the existing varieties. On studies revealed that Tanvi (yellow-fruited) and Tanvi Plus (red-fruited) were the best yielders when compared to varieties being grown by the farmers. Average plant height ranged from 100 to 160cm, fruit weight ranged from 205 to 280g/fruit and number of marketable fruits per plant varied from 11 to 23. Yield and (Benefit:Cost) B:C ratio for the two best hybrids, i.e., Tanvi and Tanvi Plus were 140.5t&127.3t ha-1, and 2.37&2.06, respectively

Loss Guided Activation for Action Recognition in Still Images

One significant problem of deep-learning based human action recognition is that it can be easily misled by the presence of irrelevant objects or backgrounds. Existing methods commonly address this problem by employing bounding boxes on the target humans as part of the input, in both training and testing stages. This requirement of bounding boxes as part of the input is needed to enable the methods to ignore irrelevant contexts and extract only human features. However, we consider this solution is inefficient, since the bounding boxes might not be available. Hence, instead of using a person bounding box as an input, we introduce a human-mask loss to automatically guide the activations of the feature maps to the target human who is performing the action, and hence suppress the activations of misleading contexts. We propose a multi-task deep learning method that jointly predicts the human action class and human location heatmap. Extensive experiments demonstrate our approach is more robust compared to the baseline methods under the presence of irrelevant misleading contexts. Our method achieves 94.06\% and 40.65\% (in terms of mAP) on Stanford40 and MPII dataset respectively, which are 3.14\% and 12.6\% relative improvements over the best results reported in the literature, and thus set new state-of-the-art results. Additionally, unlike some existing methods, we eliminate the requirement of using a person bounding box as an input during testing.Comment: Accepted to appear in ACCV 201

The general dielectric tensor for bi-kappa magnetized plasmas

In this paper we derive the dielectric tensor for a plasma containing particles described by an anisotropic superthermal (bi-kappa) velocity distribution function. The tensor components are written in terms of the two-variables kappa plasma special functions, recently defined by Gaelzer and Ziebell [Phys. Plasmas 23, 022110 (2016)]. We also obtain various new mathematical properties for these functions, which are useful for the analytical treatment, numerical implementation and evaluation of the functions and, consequently, of the dielectric tensor. The formalism developed here and in the previous paper provides a mathematical framework for the study of electromagnetic waves propagating at arbitrary angles and polarizations in a superthermal plasma.Comment: Accepted for publication in Physics of Plasma

Oxygen isotope effect on the superconductivity and stripe phase in La1.6−x_{1.6-x}Nd0.4_{0.4}Srx_{x}CuO4_4

The oxygen isotope effect on the superconductivity, stripe phase and structure transition is systematically investigated in La$_{1.6-x}$Nd$_{0.4}$Sr$_{x}$CuO$_4$ with static stripe phase. Substitution of $^{16}$O by $^{18}$O leads to a decrease in superconducting transition temperature T$_C$, while enhances the temperature of the structural transition from low-temperature-orthorhombic (LTO) phase to low-temperature-tetragonal (LTT) phase. Compared to the Nd free sample, a larger isotope effect on $T_C$ is observed in La$_{1.6-x}$Nd$_{0.4}$Sr$_{x}$CuO$_4$. These results indicate that the distortion of CuO$_2$ plane suppresses the superconductivity, giving a direct evidence for the competing of stripe phase and superconductivity because the distortion of CuO$_2$ plane enhances the stripe phase.Comment: 4 pages, 5 figure

Evaluation of Onion Varieties under Low Hill Conditions of Himachal Pradesh

An experiment was conducted to identify promising varieties of onion suited for cultivation under low hill conditions of Himachal Pradesh. Ten varieties were evaluated at Research Farm of the Institute of Biotechnology and Environmental Science, Dr. Y.S. Parmar University of Horticulture and Forestry, Neri, Hamirpur, for two consecutive seasons (2010- 2011 and 2011-2012). The farm is located at an altitude of 620m above mean sea level, with average mean maximum and minimum temperatures of 31.3°C and 12.4°C, respectively, and is a representative site of the low hill region of Himachal Pradesh. Standard package of practices was followed for raising the crop as recommended by the University. Observations were recorded on various horticultural traits, viz., plant height, number of leaves per plant, days to harvest, neck thickness, bulb diameter, bulb weight, TSS, and total yield. In addition, all the varieties were screened for resistance against purple blotch disease. Maximum days to harvest (129.33 days) were seen in the variety Holland Louis, while, variety Agrifound Rose showed minimum number of days (109). Varieties Palam Lohit, Nasik Red, N-53 and Agrifound Dark Red recorded significantly higher bulb yield (275.00, 240.67, 239.25 and 232.37 q/ha, respectively) than the other varieties evaluated. None of the varieties was able to resist the disease totally; however, 'Agrifound Dark Red' was moderately resistant, exhibiting just 13.78% disease incidence. Varieties Palam Lohit, Nasik Red and Agrifound Dark Red had medium bulb size and higher yield. These can be advocated for commercial cultivation under low hill conditions of Himachal Pradesh

Studies on Training Systems and NAA Application on Bell Pepper Production in Polyhouse

Capsicum (Capsicum annuum L.) is an important off-season vegetable crops grown in the mid-hills of Himachal Pradesh. Production and productivity of this crop is low because of high flower and fruit drop. The present investigation was carried out to find out the best training system and an appropriate concentration of naphthalene acetic acid (NAA). Two-stem training system was the best for most traits except, number of flowers per plant and days to first picking which were best under control, i.e., on plants not trained at all. Two sprays of NAA @ 15 ppm proved best for plant height, total number of flowers per plant, per cent flower drop, per cent fruit set, days to first picking, number of fruits per plant, fruit weight and total yield per plant

Effect of Age of Transplants on Fruit and Seed Yield of Tomato (Solanum lycopersicum L.)

Tomato is a major cash crop of the mid-hill regions of Himachal Pradesh. Among various factors that affect its growth and yield, age of the transplant - an important factor - is generally ignored by farmers. Therefore, the present investigation was undertaken at Vegetable Research Farm, Department of Vegetable Science, Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan, Himachal Pradesh, during the summer of 2008 and 2009 to ascertain optimum age of transplants for maximizing fruit and seed yield in tomato var. Solan Vajr. The experiment was laid out in RBD, with 3 replications. Age of the transplant starting with 15 days, and with subsequent gaps of 3 days each (upto 42 days, i.e., 10 stages) comprised different treatments. Among the various treatments imposed, 33-day old (middleaged) transplants performed best with respect to fruit and seed yield than younger or older transplants. This treatment also gave the best results for number of fruits per plant, fruit yield per plot (kg), seed recovery (%), seed yield per plot (g), and germination percentage

Path Planning of an Autonomous Surface Vehicle based on Artificial Potential Fields in a Real Time Marine Environment

With growing advances in technology and the everyday dependence on oceans for resources, the role of unmanned marine vehicles has increased many a fold. Extensive operations having naval, civil and scientific applications are being undertaken and demands are being placed on them to increase their flexibility and adaptability. A key factor for such vehicles is the requirement for them to possess a path planning subsystem. Most path planning techniques are implemented in self-simulated environments. This study accounts for use of artificial potential field in path planning of an autonomous surface vehicle (ASV) in a real time marine environment. Path cost, path length and computational time are described to ensure the effectiveness of the motion planning

Towards use of Dijkstra Algorithm for Optimal Navigation of an Unmanned Surface Vehicle in a Real-Time Marine Environment with Results from Artificial Potential Field

The growing need of ocean surveying and exploration for scientific and industrial application has led to the requirement of routing strategies for ocean vehicles which are optimal in nature. Most of the optimal path planning for marine vehicles had been conducted offline in a self‐made environment. This paper takes into account a practical marine environment, i.e. Portsmouth Harbour, for finding an optimal path in terms of computational time between source and end points on a real time map for an USV. The current study makes use of a grid map generated from original and uses a Dijkstra algorithm to find the shortest path for a single USV. In order to benchmark the study, a path planning study using a well‐known local path planning method artificial path planning (APF) has been conducted in a real time marine environment and effectiveness is measured in terms of path length and computational time