Large negative magnetoresistance in a ferromagnetic shape memory alloy : Ni_{2+x}Mn_{1-x}Ga

5% negative magnetoresistance (MR) at room temperature has been observed in bulk Ni_{2+x}Mn_{1-x}Ga. This indicates the possibility of using Ni_{2+x}Mn_{1-x}Ga as magnetic sensors. We have measured MR in the ferromagnetic state for different compositions (x=0-0.2) in the austenitic, pre-martensitic and martensitic phases. MR is found to increase with x. While MR for x=0 varies almost linearly in the austenitic and pre-martensitic phases, in the martensitic phase it shows a cusp-like shape. This has been explained by the changes in twin and domain structures in the martensitic phase. In the austenitic phase, which does not have twin structure, MR agrees with theory based on s-d scattering model.Comment: 3 pages, 3 figures, Appl. Phys. Lett 86, 202508 (2005

VideoCapsuleNet: A Simplified Network for Action Detection

The recent advances in Deep Convolutional Neural Networks (DCNNs) have shown extremely good results for video human action classification, however, action detection is still a challenging problem. The current action detection approaches follow a complex pipeline which involves multiple tasks such as tube proposals, optical flow, and tube classification. In this work, we present a more elegant solution for action detection based on the recently developed capsule network. We propose a 3D capsule network for videos, called VideoCapsuleNet: a unified network for action detection which can jointly perform pixel-wise action segmentation along with action classification. The proposed network is a generalization of capsule network from 2D to 3D, which takes a sequence of video frames as input. The 3D generalization drastically increases the number of capsules in the network, making capsule routing computationally expensive. We introduce capsule-pooling in the convolutional capsule layer to address this issue which makes the voting algorithm tractable. The routing-by-agreement in the network inherently models the action representations and various action characteristics are captured by the predicted capsules. This inspired us to utilize the capsules for action localization and the class-specific capsules predicted by the network are used to determine a pixel-wise localization of actions. The localization is further improved by parameterized skip connections with the convolutional capsule layers and the network is trained end-to-end with a classification as well as localization loss. The proposed network achieves sate-of-the-art performance on multiple action detection datasets including UCF-Sports, J-HMDB, and UCF-101 (24 classes) with an impressive ~20% improvement on UCF-101 and ~15% improvement on J-HMDB in terms of v-mAP scores

CDM afforestation and reforestation baseline methodologies: An analysis of the submission and approval process

Afforestation and Reforestation (A/R), also widely termed LULUCF have been an important field of conflict in the Clean Development Mechanism (CDM) of the Kyoto Protocol. The first methodology for A/R projects has been submitted only by October 2004 and the first project was registered only in November 2006, two years after the first project in the energy sector. Like energy efficiency and transportation methodologies, A/R methodologies also suffer high rejection rate. 20 A/R CDM methodologies evaluated by the CDM Executive Board have been analyzed in this paper with respect to their approval history. On an average it took 4-5 months for approval of A/R methodologies in contrast to the long approval time taken in case of other methodologies (9-10 months). Most methodologies has been rejected because of not properly defining land eligibility, incomplete baseline scenario selection, lack of methods to prove additionality and insufficient treatment of uncertainties. --

Ethnobotanical Studies on Dental Hygiene in District Hamipur, Himachal Pradesh (H.P.), India

The present study was carried out to assess and document ethnobotanical knowledge of plants of District Hamirpur (H.P.) used for dental care, as the area has diverse flora and high ethnobotanical potential. It was found that 32 different plant species belonging to 24 families are used for dental hygiene. The studies reveal the use of 18 trees, 9 shrubs, 2 under-shrubs and 5 herbs for dental hygiene

Ethnobotanical Studies on Dental Hygiene in District Hamirpur, Himachal Pradesh (H.P.), India

The present study was carried out to assess and document ethnobotanical knowledge of plants of District Hamirpur (H.P.) used for dental care, as the area has diverse flora and high ethnobotanical potential. It was found that 32 different plant species belonging to 24 families were used for dental hygiene. The studies reveal the use of 18 trees, 9 shrubs, 2 under-shrubs and 5 herbs for dental hygiene