Neutrinos in IceCube/KM3NeT as probes of Dark Matter Substructures in Galaxy Clusters

Galaxy clusters are one of the most promising candidate sites for dark matter annihilation. We focus on dark matter with mass in the range 10 GeV - 100 TeV annihilating to muon pairs, neutrino pairs, top pairs, or two neutrino pairs, and forecast the expected sensitivity to the annihilation cross section into these channels by observing galaxy clusters at IceCube/KM3NeT. Optimistically, the presence of dark matter substructures in galaxy clusters is predicted to enhance the signal by 2-3 orders of magnitude over the contribution from the smooth component of the dark matter distribution. Optimizing for the angular size of the region of interest for galaxy clusters, the sensitivity to the annihilation cross section of heavy DM with mass in the range 300 GeV - 100 TeV will be of the order of 10^{-24} cm^3 s^{-1}, for full IceCube/KM3NeT live time of 10 years, which is about one order of magnitude better than the best limit that can be obtained by observing the Milky Way halo. We find that neutrinos from cosmic ray interactions in the galaxy cluster, in addition to the atmospheric neutrinos, are a source of background. We show that significant improvement in the experimental sensitivity can be achieved for lower DM masses in the range 10 GeV - 300 GeV if neutrino-induced cascades can be reconstructed to approximately 5 degrees accuracy, as may be possible in KM3NeT. We therefore propose that a low-energy extension "KM3NeT-Core", similar to DeepCore in IceCube, be considered for an extended reach at low DM masses.Comment: v2: 17 pages, 5 figures. Neutrino spectra corrected, dependence on dark matter substructure model included, references added. Results unchanged. Accepted in PR

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

Analysis of the Wicking and Thin-film Evaporation Characteristics of Microstructures

The topology and geometry of microstructures play a crucial role in determining their heat transfer performance in passive cooling devices such as heat pipes. It is therefore important to characterize microstructures based on their wicking performance, the thermal conduction resistance of the liquid filling the microstructure, and the thin-film characteristics of the liquid meniscus. In the present study, the free-surface shapes of the static liquid meniscus in common microstructures are modeled using SURFACE EVOLVER for zero Bond number. Four well-defined topologies, viz., surfaces with parallel rectangular ribs, horizontal parallel cylinders, vertically aligned cylinders, and spheres (the latter two in both square and hexagonal packing arrangements), are considered. Nondimensional capillary pressure, average distance of the liquid free-surface from solid walls (a measure of the conduction resistance of the liquid), total exposed area, and thin-film area are computed. These performance parameters are presented as functions of the nondimensional geometrical parameters characterizing the microstructures, the volume of the liquid filling the structure, and the contact angle between the liquid and solid. Based on these performance parameters, hexagonally-packed spheres on a surface are identified to be the most efficient microstructure geometry for wicking and thin-film evaporation. The solid-liquid contact angle and the nondimensional liquid volume that yield the best performance are also identified. The optimum liquid level in the wick pore that yields the highest capillary pressure and heat transfer is obtained by analyzing the variation in capillary pressure and heat transfer with liquid level and using an effective thermal resistance model for the wick

Galactic Center Radio Constraints on Gamma-Ray Lines from Dark Matter Annihilation

Recent evidence for one or more gamma-ray lines at ~ 130 GeV in the Fermi-LAT data from the Galactic Center has been interpreted as a hint for dark matter annihilation to Z{\gamma} or H{\gamma} with an annihilation cross section, ~ 10^{-27} cm^3 s^{-1} . We test this hypothesis by comparing synchrotron fluxes due to the electrons and positrons from the decay of the Z or the H boson only in the Galactic Center against radio data from the same region in the Galactic Center. We find that the radio data from single dish telescopes marginally constrain this interpretation of the claimed gamma lines for a contracted NFW profile. Already-operational radio telescopes such as LWA, VLA-Low and LOFAR, and future radio telescopes like SKA, which are sensitive to annihilation cross sections as small as 10^{-28} cm^3 s^{-1}, can confirm or rule out this scenario very soon. We discuss the assumptions on the dark matter profile, magnetic fields, and background radiation density profiles, and show that the constraints are relatively robust for any reasonable assumptions. Independent of the above said recent developments, we emphasize that our radio constraints apply to all models where dark matter annihilates to Z{\gamma} or H{\gamma}.Comment: v3: 18 pages, 7 figures. Minor changes. Published in Phys. Rev.

Effects of resveratrol on oxidative stress in high fat diet /streptozocin induced diabetic wistar albino rats

Background: Diabetes mellitus is a common chronic disease. One of the pathophysiology is found to be oxidative stress. This study aims to evaluate the effect of resveratrol on oxidative stress in high fat diet (HFD)/streptozotocin induced diabetic rats.Methods: Wistar albino rats, fed with HFD rendered diabetic with streptozotocin, were divided into 6 groups, namely the diabetic control treated with vehicle (DC), standard control which received metformin (SC), test groups treated with 5,10, and 20 mg/kg b.w. of resveratrol and combination of half dose of metformin and resveratrol (10 mg/kg)(TC). A group of six normal animals served as normal control (NC), another six as HFD control. Fasting blood glucose, lipid profile and serum MDA and SOD were measured one week after induction of diabetes. The animals were then treated orally for 2 weeks after which the same parameters were repeated. The in-vivo results were analysed by one way ANOVA followed by Tukey’s multiple comparison test.Results: The DC group demonstrated a increase in the fasting blood glucose compared to NC, HFD control while a significant decrease in the fasting blood glucose was observed with SC, Test groups (p<0.05) as compared to the DC group. TC showed a significant improvement in dyslipidemia compared to their baseline values (p<0.05). There was significant change in the serum MDA level and SOD activity.Conclusions: Resveratrol improves oxidative stress in diabetic rats

Effect of resveratrol on diabetic neuropathy in wistar albino rats

Background: Type 2 diabetes mellitus (DM) is a common chronic disease with increasing prevalence worldwide. Prolonged uncontrolled hyperglycemia, dyslipidemia are major risk factor for its complication like neuropathy. Since there is no definite treatment for diabetic neuropathy, this study aims to evaluate the effect of resveratrol on diabetic neuropathy in high fat diet with low dose streptozotocin induced type-2 DM model in wistar albino rats.Methods: First type 2 diabetic rat model was established. Wistar albino rats, fed with high-fat diet (HFD) rendered diabetic with streptozotocin, were divided into 6 groups, disease control (DC) treated with vehicle, standard control (SC) which received metformin, test groups treated with 5, 10, and 20 mg/kg b.w. of resveratrol and combination of half dose of metformin and resveratrol (10 mg/kg) (TC). A group of six normal animals served as normal control (NC), another six as HFD control. Fasting plasma glucose, lipid profile were measured one week after induction of diabetes. The animals were then treated orally for 2 weeks after which the same parameters were repeated. Behavioral biomarkers for neuropathy are measured in 4 weeks and 6 weeks of treatment. The in-vivo results were analyzed by one way ANOVA followed by Tukey’s multiple comparison test for biochemical parameters and Kruskal Wallis test followed by Dun’s multiple comparison test for behavioral biomarkers.Results: Increase in fasting plasma glucose (FPG), deranged lipid profile, increased neuropathy in DC compared to NC, HFD control while a significant decrease in FBG, improved pain behavior with SC, test groups (p&lt;0.05) as compared to the DC group.Conclusions: Resveratrol prevents diabetic neuropathy