Authentication protocol based on collective quantum steering

It is well known that certain quantum correlations like quantum steering exhibit a monogamous relationship. In this paper, we exploit the asymmetric nature of quantum steering and show that there exist states which exhibit a polygamous correlation, known as collective correlation [He and Reid, Phys. Rev. Lett. 111, 250403 (2013)], where the state of one party, Alice, can be steered only by the joint effort of the other two parties, Bob and Charlie. As an example, we explicitly single out a particular set of $3$ qubit states which exhibit this polygamous relationship, known as collective steerability. We provide a recipe to identify the complete set of such states. We also provide a possible application of such states to an information theoretic task, termed as quantum key authentication (QKA) protocol. QKA can also be used in conjunction with other well known cryptography protocols to improve their security and we provide one such example with quantum private comparison (QPC).Comment: 6 pages, 1 figure, comments appreciated :

Molecular Dynamics Simulation-Based Study on Enhancing Thermal Properties of Graphene-Reinforced Thermoplastic Polyurethane Nanocomposite for Heat Exchanger Materials

Molecular dynamics (MD) simulation-based development of heat resistance nanocomposite materials for nanoheat transfer devices (like nanoheat exchanger) and applications have been studied. In this study, MD software (Materials Studio) has been used to know the heat transport behaviors of the graphene-reinforced thermoplastic polyurethane (Gr/TPU) nanocomposite. The effect of graphene weight percentage (wt%) on thermal properties (e.g., glass transition temperature, coefficient of thermal expansion, heat capacity, thermal conductivity, and interface thermal conductance) of Gr/TPU nanocomposites has been studied. Condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field which is incorporated in both amorphous and forcite plus atomistic simulation modules within the software are used for this present study. Layer models have been developed to characterize thermal properties of the Gr/TPU nanocomposites. It is seen from the simulation results that glass transition temperature (Tg) of the Gr/TPU nanocomposites is higher than that of pure TPU. MD simulation results indicate that addition of graphene into TPU matrix enhances thermal conductivity. The present study provides effective guidance and understanding of the thermal mechanism of graphene/TPU nanocomposites for improving their thermal properties. Finally, the revealed enhanced thermal properties of nanocomposites, the interfacial interaction energy, and the free volume of polymer nanocomposites are examined and discussed

A study on antimicrobial agents utilization pattern using anatomical therapeutic chemical / daily defined dose system and adverse drug reaction pattern in the intensive care unit of a tertiary care teaching hospital in North Eastern state of India

Background: Successful use of antibiotics has brought a revolutionary change in the management of infectious diseases but has also resulted in its irrational use. Indiscriminate use of anti-microbial agents (AMAs) has been well-documented in the ICUs where polypharmacy is a common phenomenon, thus increasing the risk of Adverse Drug Reactions (ADRs). It is extremely imperative to evaluate the prescribing pattern of antimicrobials for enabling suitable modifications in prescribing patterns; to increase the therapeutic benefits and for optimizing the health care services.Methods: With the objective to assess the prescription patterns of AMAs and the rationality of their use this observational study was undertaken in the Intensive Care Unit of a Tertiary Care Hospital for two months.Results: Of the total 127 patients, 80 (62.99%) were male and 47 (37.01%) were female at an average age of 51.3±18.3 years. 102 (80.31%) patients received AMAs at average of 1.71±0.99 and 25 (19.69%) didn’t. Betalactam antibiotics were the most frequently (72.99 %) prescribed class. Meropenem was the most commonly prescribed (41 occasions) agent. The length of stay in ICU per patient was 4.42±3.49 days. 41.63% patients had more than two morbidities. No AMAs were prescribed in generic name. In 28 (27.45%) patients the AMAs prescribing were irrational.Conclusions: The high utilization rates of costly AMAs and irrational prescriptions are matters of great concern and need to be urgently addressed by use of guidelines, surveillance and antibiotic restriction policies and sensitization programs at all level of healthcare

Suspected Intestinal Tuberculosis Might Be Crohn's Disease

In this case report we provide evidence that supports a link between mycobacteria and Crohn's disease. The patient in question, KG, presented on three separate occasions over a ten years period with features suggestive of intestinal tuberculosis. He was treated successfully on each occasion with antimycobacterial drugs. When he presented a fourth time with the same symptoms, he was diagnosed with Crohn's disease based on findings from endoscopy, histology and CT. Subsequently he was treated with a course of steroids and made a full recovery. This case adds weight to the theory that mycobateria has an aetiological role in Crohn's disease

A Design of Digital Microfluidic Biochip along with Structural and Behavioural Features in Triangular Electrode Based Array

AbstractDigital microfluidic based biochip manoeuvres on the theory of microfluidic technology, having a broad variety of applications in chemistry, biology, environmental monitoring, military etc. Being concerned about the technological advancement in this domain, we have focused on equilateral triangular electrodes based DMFB systems. Accepting the associated design issues, here, we have addressed many facets of such electrodes regarding their structural and behavioural issues in comparison to the existing square electrodes. As the requisite voltage reduction is a key challenging design issues, to implement all the tasks using triangular electrodes that are possible in square electrode arrays as well, is a tedious job. Furthermore, to deal with this new design deploying triangular electrodes, we have analyzed all the necessary decisive factors including fluidic constraints to ensure safe droplet movements and other modular operations together with mixing and routing. Moreover, an algorithm has been developed to find a route for a given source and destination pair in this newly designed DMFB. Finally, we have included a comparative study between this new design and the existing one while encountering the above mentioned issues

On the Feasibility and Robustness of Pointwise Evaluation of Query Performance Prediction

Despite the retrieval effectiveness of queries being mutually independent of one another, the evaluation of query performance prediction (QPP) systems has been carried out by measuring rank correlation over an entire set of queries. Such a listwise approach has a number of disadvantages, notably that it does not support the common requirement of assessing QPP for individual queries. In this paper, we propose a pointwise QPP framework that allows us to evaluate the quality of a QPP system for individual queries by measuring the deviations between each prediction versus the corresponding true value, and then aggregating the results over a set of queries. Our experiments demonstrate that this new approach leads to smaller variances in QPP evaluations across a range of different target metrics and retrieval models

Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP

In information retrieval, query performance prediction aims to predict whether a search engine is likely to succeed in retrieving potentially relevant documents to a user’s query. This problem is usually cast into a regression problem where a machine should predict the effectiveness (in terms of an information retrieval measure) of the search engine on a given query. The solutions range from simple unsupervised approaches where a single source of information (e.g., the variance of the retrieval similarity scores in NQC), predicts the search engine effectiveness for a given query, to more involved ones that rely on supervised machine learning making use of several sources of information, e.g., the learning to rank (LETOR) features, word embedding similarities etc. In this paper, we investigate the combination of two different types of evidences into a single neural network model. While our first source of information corresponds to the semantic interaction between the terms in queries and their top-retrieved documents, our second source of information corresponds to that of LETOR features