Nitroarenes as Antitubercular Agents: Stereoelectronic Modulation to Mitigate Mutagenicity

Nitroarenes are less preferred in drug discovery due to their potential to be mutagenic. However, several nitroarenes were shown to be promising antitubercular agents with specific modes of action, namely, nitroimidazoles and benzothiazinones. The nitro group in these compounds is activated through different mechanisms, both enzymatic and non‐enzymatic, in mycobacteria prior to binding to the target of interest. From a whole‐cell screening program, we identified a novel lead nitrobenzothiazole (BT) series that acts by inhibition of decaprenylphosphoryl‐β‐d ‐ribose 2′‐epimerase (DprE1) of Mycobacterium tuberculosis (Mtb). The lead was found to be mutagenic to start with. Our efforts to mitigate mutagenicity resulted in the identification of 6‐methyl‐7‐nitro‐5‐(trifluoromethyl)‐1,3‐benzothiazoles (cBTs), a novel class of antitubercular agents that are non‐mutagenic and exhibit an improved safety profile. The methyl group ortho to the nitro group decreases the electron affinity of the series, and is hence responsible for the non‐mutagenic nature of these compounds. Additionally, the co‐crystal structure of cBT in complex with Mtb DprE1 established the mode of binding. This investigation led to a new non‐mutagenic antitubercular agent and demonstrates that the mutagenic nature of nitroarenes can be solved by modulation of stereoelectronic properties.     

Effect of prior cold work on mechanical properties, electrical conductivity and microstructure of aged Cu-Ti alloys

The mechanical properties, electrical conductivity and microstructure of Cu-2.7wt%Ti and Cu-5.4wt%Ti alloys have been studied in different conditions employing hardness and resistivity measurements, tensile tests and optical, scanning and transmission electron microscopy. Ageing of undeformed as well as cold worked alloys raises their hardness, strength and electrical conductivity. The hardness increased from 120 VHN for solution treated Cu-2.7Ti to 455 VHN for ST + cold worked + peak aged Cu-5.4Ti alloy. While tensile stength increased from 430 to 1450 MPa, the ductility (elongation) decreased from 36 to 1.5%. A maximum conductivity of 25% International Annealed Copper Standard (IACS) for Cu-2.7Ti and 14.5% IACS for Cu-5.4Ti is obtained with the present treatments. Peak strength was obtained when the solution treated alloys are aged at 450°C for 16 hours due to precipitation of ordered, metastable and coherent , Cu₄Ti phase having body centred tetragonal (bct) structure. While mechanical properties of Cu-Ti alloys are comparable, electrical conductivity is less than that of commercial Cu-Be-Co alloys.     

Java based replicated server objects and their remote method invocations in a distributed environment

A distributed system is said to be fault‐tolerant if it is able to provide important services despite partial failures of the computers or software objects in the system. These systems are needed to support applications such as remote access and control, virtual mobile offices and wide area collaborative systems where there are chances of failures in the network and software objects. Fault‐tolerance is usually achieved by replicating the objects in the system. Traditional distributed applications constructed using Java RMI (remote method invocation) are not fault‐tolerant because of the lack of support of object replication. The objective of the present work is to design a remote method invocation that supports server object replication. To provide a fault‐tolerant service to the remote client objects, server objects are actively replicated. The problems associated with the method invocation in the context of active server object replication are presented and solutions are discussed and implemented. Copyright © 2001 John Wiley & Sons, Ltd.     

Implementation of a Gaussian process-based machine learning grasp predictor

With the goal of advancing the state of automatic robotic grasping, we present a novel approach that combines machine learning techniques and physical validation on a robotic platform to develop a comprehensive grasp predictor. After collecting a large grasp sample set (522 grasps), we first conduct a statistical analysis of the predictive ability of grasp quality metrics that are commonly used in the robotics literature. We then apply principal component analysis and Gaussian process (GP) algorithms on the grasp metrics that are discriminative to build a classifier, validate its performance, and compare the results to existing grasp planners. The key findings are as follows: (i) several of the existing grasp metrics are weak predictors of grasp quality when implemented on a robotic platform; (ii) the GP-based classifier significantly improves grasp prediction by combining multiple grasp metrics to increase true positive classification at low false positive rates; (iii) The GP classifier can be used generate new grasps to improve bad grasp samples by performing a local search to find neighboring grasps which have improved contact points and higher success rate.     

Java-MaC: A Run-Time Assurance Approach for Java Programs

We describe Java-MaC, a prototype implementation of the Monitoring and Checking (MaC) architecture for Java programs. The MaC architecture provides assurance that the target program is running correctly with respect to a formal requirements specification by monitoring and checking the execution of the target program at run-time. MaC bridges the gap between formal verification, which ensures the correctness of a design rather than an implementation, and testing, which does not provide formal guarantees about the correctness of the system.Use of formal requirement specifications in run-time monitoring and checking is the salient aspect of the MaC architecture. MaC is a lightweight formal method solution which works as a viable complement to the current heavyweight formal methods. In addition, analysis processes of the architecture including instrumentation of the target program, monitoring, and checking are performed fully automatically without human direction, which increases the accuracy of the analysis. Another important feature of the architecture is the clear separation between monitoring implementation-dependent low-level behaviors and checking high-level behaviors, which allows the reuse of a high-level requirement specification even when the target program implementation changes. Furthermore, this separation makes the architecture modular and allows the flexibility of incorporating third party tools into the architecture. The paper presents an overview of the MaC architecture and a prototype implementation Java-MaC.     

Comparison of Expedient and Optima Reinforcement Schemes for Learning Systems

Stochastic automata models have been successfully used in the past for modeling learning systems. An automaton model with a variable structure reacts to inputs from a random environment by changing the probabilities of its actions. These changes are carried out using a reinforcement scheme in such a manner that the automaton evolves to a final structure which is satisfactory in some sense. Several reinforcement schemes have been proposed in the literature for updating the structure of automata [1–4]. Most of these are expedient schemes which in the limit yield structures which are better than a device that chooses the actions with equal probabilities irrespective of the environment's response. A few schemes have also been suggested recently which in the limit lead to a continuous selection of a single optimal action as the output of the automaton, when it operates in a stationary environment and are called optimal schemes [5–7]. The question naturally arises as to which of the schemes are to be preferred in practical applications. In view of the anticipated extensive use of learning schemes in multilevel decision-making systems this question of optimality versus expediency takes on particular significance. Consequently, a comparison has to be made not merely of individual automata schemes but also of the effectiveness of such schemes in situations involving several automata (e.g. stochastic games, multilevel systems).     

Computing hierarchical curve-skeletons of 3D objects

A curve-skeleton of a 3D object is a stick-like figure or centerline representation of that object. It is used for diverse applications, including virtual colonoscopy and animation. In this paper, we introduce the concept of hierarchical curve-skeletons and describe a general and robust methodology that computes a family of increasingly detailed curve-skeletons. The algorithm is based upon computing a repulsive force field over a discretization of the 3D object and using topological characteristics of the resulting vector field, such as critical points and critical curves, to extract the curve-skeleton. We demonstrate this method on many different types of 3D objects (volumetric, polygonal and scattered point sets) and discuss various extensions of this approach.