Comprehensive review of anti-tubercular treatment induced liver injury

The challenge in the management of tuberculosis is further compounded by the liver injury associated with anti-tubercular treatment (ATT) drugs. The problem of drug-induced liver injury (DILI) associated with ATT drugs is significant in the developing countries because of high disease burden, limited monitoring due to scarce resources and lack of awareness. There is heterogeneity in the pharmacokinetics and pharmacodynamics of the various first line ATT drugs. There are various genetic and environmental factors that affect DILI. Various guidelines have been proposed to treat and monitor DILI. This article reviews the problem, risk factors, mechanism, and management strategies of the DILI associated with ATT

Placement of the Internal Pulse Generator for Deep Brain Stimulation in the Upper Back to Prevent Fracture of the Extension Wire due to Generator Rotation: Case Report

Deep brain stimulation (DBS) is a common surgical procedure used for the treatment of Parkinson's disease (PD) and essential tremor. A potential complication of this procedure is hardware failure. The authors report a case of DBS hardware failure in which repeated fractures of the extension wire were caused by abnormal rotational movements of the IPG placed in the loose subclavicular tissue of an overweight female. Implantation of the IPG in the suprascapular area prevented further extension wire fractures. This strategy may be especially relevant in overweight females with loose subclavicular tissue

Actor-Critic based Improper Reinforcement Learning

We consider an improper reinforcement learning setting where a learner is given $M$ base controllers for an unknown Markov decision process, and wishes to combine them optimally to produce a potentially new controller that can outperform each of the base ones. This can be useful in tuning across controllers, learnt possibly in mismatched or simulated environments, to obtain a good controller for a given target environment with relatively few trials. Towards this, we propose two algorithms: (1) a Policy Gradient-based approach; and (2) an algorithm that can switch between a simple Actor-Critic (AC) based scheme and a Natural Actor-Critic (NAC) scheme depending on the available information. Both algorithms operate over a class of improper mixtures of the given controllers. For the first case, we derive convergence rate guarantees assuming access to a gradient oracle. For the AC-based approach we provide convergence rate guarantees to a stationary point in the basic AC case and to a global optimum in the NAC case. Numerical results on (i) the standard control theoretic benchmark of stabilizing an cartpole; and (ii) a constrained queueing task show that our improper policy optimization algorithm can stabilize the system even when the base policies at its disposal are unstable.Comment: arXiv admin note: substantial text overlap with arXiv:2102.0820

A Low-Delay MAC for IoT Applications: Decentralized Optimal Scheduling of Queues without Explicit State Information Sharing

We consider a system of several collocated nodes sharing a time slotted wireless channel, and seek a MAC (medium access control) that (i) provides low mean delay, (ii) has distributed control (i.e., there is no central scheduler), and (iii) does not require explicit exchange of state information or control signals. The design of such MAC protocols must keep in mind the need for contention access at light traffic, and scheduled access in heavy traffic, leading to the long-standing interest in hybrid, adaptive MACs. Working in the discrete time setting, for the distributed MAC design, we consider a practical information structure where each node has local information and some common information obtained from overhearing. In this setting, "ZMAC" is an existing protocol that is hybrid and adaptive. We approach the problem via two steps (1) We show that it is sufficient for the policy to be "greedy" and "exhaustive". Limiting the policy to this class reduces the problem to obtaining a queue switching policy at queue emptiness instants. (2) Formulating the delay optimal scheduling as a POMDP (partially observed Markov decision process), we show that the optimal switching rule is Stochastic Largest Queue (SLQ). Using this theory as the basis, we then develop a practical distributed scheduler, QZMAC, which is also tunable. We implement QZMAC on standard off-the-shelf TelosB motes and also use simulations to compare QZMAC with the full-knowledge centralized scheduler, and with ZMAC. We use our implementation to study the impact of false detection while overhearing the common information, and the efficiency of QZMAC. Our simulation results show that the mean delay with QZMAC is close that of the full-knowledge centralized scheduler.Comment: 28 pages, 19 figure

Snakes of Telangana: An annotated checklist with new locality records and notes on natural history

With every growing human population and the resultant shrinkage of natural habitats, snakes are frequently encountered in and around human settlements, leading to widespread human-wildlife conflict. Conservation efforts involve rescue & relocation of 'stray' snakes, to mitigate snakebites, human deaths & snake mortality. We utilized snake rescue data of Friends of Snakes Society, Hyderabad, Telangana, recorded between the years 1995 and 2020, to present an annotated snake checklist for Telangana, along with their distribution. Further, opportunistic encounters and temporary captive care of the rescued species yielded significant insights into habitat preferences, dietary choices, aposematic responses, breeding cycles, etc., of various species of this region