Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

World University root node

Biological Sciences and Engineering

European Journal of Immunology

Intravenous immunoglobulin protects from experimental allergic bronchopulmonary aspergillosis via a sialylation-dependent mechanism

Mitochondria, the powerhouse of the cell, known for producing energy through oxidative phosphorylation and the Krebs cycle, continue gaining notoriety for roles beyond bioenergetics. Recently in Nature, Weinberg et al. (2019) reported that mitochondrial complex III is indispensable for suppressive function of regulatory T cells, thus highlighting the importance of mitochondria in immune tolerance. © 2019 Elsevier Inc. Mitochondria, the powerhouse of the cell, known for producing energy through oxidative phosphorylation and the Krebs cycle, continue gaining notoriety for roles beyond bioenergetics. Recently in Nature, Weinberg et al. reported that mitochondrial complex III is indispensable for suppressive function of regulatory T cells, thus highlighting the importance of mitochondria in immune tolerance. © 2019 Elsevier Inc.

Fulltext

Cell Metabolism

Regulatory T Cells under the Mercy of Mitochondria

Autoimmunity Reviews

Does intravenous immunoglobulin therapy in Guillain-Barré syndrome patients interfere with serological Zika detection?

Interaction between innate immune cells and parasite plays a key role in the immunopathogenesis of lymphatic filariasis. Despite being professional antigen presenting cells critical for the pathogen recognition, processing and presenting the antigens for mounting T cell responses, the dendritic cell response and its role in initiating CD4+ T cell response to filaria, in particular Wuchereria bancrofti, the most prevalent microfilaria is still not clear. Herein, we demonstrate that a 70 kDa phosphorylcholine-binding W. bancrofti sheath antigen induces human dendritic cell maturation and secretion of several pro-inflammatory cytokines. Further, microfilarial sheath antigen-stimulated dendritic cells drive predominantly Th1 and regulatory T cell responses while Th17 and Th2 responses are marginal. Mechanistically, sheath antigen-induced dendritic cell maturation, and Th1 and regulatory T cell responses are mediated via toll-like receptor 4 signaling. Our data suggest that W. bancrofti sheath antigen exploits dendritic cells to mediate distinct CD4+ T cell responses and immunopathogenesis of lymphatic filariasis. © 2019, The Author(s).

Communications Biology

Wuchereria bancrofti filaria activates human dendritic cells and polarizes T helper 1 and regulatory T cells via toll-like receptor 4

The influence of geomembrane in maintaining the sealing efficiency of a landfill cover system at the onset of flexural distress was studied by conducting a series of centrifuge tests performed at 40 gravities. The tests were performed using a 4.5 m radius beam centrifuge having a capacity of 2,500 g-kN available at IIT Bombay on model composite barriers of 0.6 m thickness. The thickness and tensile stiffness of the geomembrane were varied. All the models were instrumented with pore pressure transducers (PPTs), linear variable differential transformers (LVDTs), a digital camera and a charge-coupled device (CCD) video camera to study the performance of the barriers during centrifuge tests. The sealing efficiency of the composite barriers was found to be maintained even after the formation of full-depth cracks within 0.6 m thick clay barriers subjected to a maximum distortion level of 0.125. This observed behaviour is attributed to the downward thrust exerted by the deformed geomembrane at the zone of maximum curvature which hinders the infiltration of water through the cracks. The downward thrust exerted by the geomembrane on the clay barrier was found to be more for barriers provided with stiffer and thicker geomembrane. © Springer Nature Singapore Pte Ltd 2019.

Department of Civil Engineering

Lecture Notes in Civil Engineering

Influence of geomembrane stiffness on the integrity of landfill covers: Centrifuge modelling

We present an experimental study of the superconducting properties of NiBi 3 as a function of pressure by means of resistivity and magnetization measurements and combine our results with density functional theory calculations of the band structure under pressure. We find a moderate suppression of the critical temperature from K to K by pressures up to 2 GPa. By taking into account the change of the band structure as a function of pressure, we argue that the decrease in is consistent with conventional, electron-phonon-mediated BCS-type superconductivity. © 2018 IOP Publishing Ltd.

Department of Physics

Journal of Physics Condensed Matter

Effect of pressure on the physical properties of the superconductor NiBi 3

To study the analog of Suita'fs conjecture for domains ⊂Cn, n ≥ 2, Blocki introduced the invariant Fκ D (z) = KD(z)λIκ D(z), where KD (z) is the Bergman kernel of D along the diagonal and λIκ D(z) is the Lebesgue measure of the Kobayashi indicatrix at the point z. In this note, we study the behaviour of Fκ D (z) (and other similar invariants using different metrics) on strongly pseudconvex domains and also compute its limiting behaviour explicitly at certain points of decoupled egg domains in C2. © 2019 American Mathematical Society.

Department of Mathematics

Proceedings of the American Mathematical Society

Remarks on the higher dimensional suita conjecture

Transfer learning across heterogeneous feature spaces can, in general, be a very difficult problem in practice due to the heterogeneity of features and lack of correspondence between data points of different domains. In this paper, we present a novel supervised domain adaptation algorithm (SHDA-RF) that transfers knowledge from a data-rich source domain to a target domain with only few training instances. The proposed method makes use of random forests to identify pivot features that bridge the two domains. The key idea of the proposed feature transfer approach is that every path in a decision tree leading to a partition of the data is associated with a certain label distribution and the label distributions that appear both in the source and target random forest models can be used as pivots for bridging the two domains. This information is used to generate a sparse feature transformation matrix, which maps patterns from the source feature space to the target feature space. The target model is then retrained along with the projected source data. We conduct extensive experiments on diverse datasets of varying dimensions and sparsity to verify the superiority of the proposed approach over other baseline and state of the art transfer approaches.

Department of Data Science

Artificial Intelligence

Supervised heterogeneous feature transfer via random forests

Department of Mechanical Engineering

Preprints of the National Meeting of Japan Welding Society

Modeling of residual stresses in stationary shoulder friction stir welding

Time series are ubiquitous in real world problems and computing distance between two time series is often required in several learning tasks. Computing similarity between time series by ignoring variations in speed or warping is often encountered and dynamic time warping (DTW) is the state of the art. However DTW is not applicable in algorithms which require kernel or vectors. In this paper, we propose a mechanism named WaRTEm to generate vector embeddings of time series such that distance measures in the embedding space exhibit resilience to warping. Therefore, WaRTEm is more widely applicable than DTW. WaRTEm is based on a twin auto-encoder architecture and a training strategy involving warping operators for generating warping resilient embeddings for time series datasets. We evaluate the performance of WaRTEm and observed more than 20% improvement over DTW in multiple real-world datasets.