Some insights on the recent spate of accidents in Indian Railways

Indian Railways (IR), the largest rail passenger carrier in the world, has experienced 11 major accidents due to derailment or collision between trains in the year 2010, leading to several human casualties and large-scale disruptions in traffic. Alarmingly, 8 of these 11 accidents have occurred within a specific geographical region known as the Indo-Gangetic plain. In order to identify the general causes of such frequent accidents, and the specific factors leading to repeated accidents in a particular region, we systematically collect and analyze data of IR traffic over the last two decades. We find that there has been an unbalanced growth in IR traffic in the Indo-Gangetic plain over the last two decades, and consequently most of the high-traffic rail-routes presently lie in this region. However, construction of new tracks and train-routes has been nominal compared to the increase in traffic, leading to frequent congestion and over-utilization of existing tracks. Modeling the traffic-flow using computer simulations, we also show that if all trains were to travel in accordance with the IR schedule, the present infrastructure would be insufficient to handle the resultant traffic-flow in some of the high-traffic routes. Hence this study reflects some of the inherent problems in the scheduling of trains and evolution of IR, and also identifies several regions where traffic is likely to exceed safe limits.     

Realisation of a Lorentz algebra in Lorentz violating theory

A Lorentz non-invariant higher derivative effective action in flat spacetime, characterised by a constant vector, can be made invariant under infinitesimal Lorentz transformations by restricting the allowed field configurations. These restricted fields are defined as functions of the background vector in such a way that background dependence of the dynamics of the physical system is no longer manifest. We show here that they also provide a field basis for the realisation of a Lorentz algebra and allow the construction of a Poincaré invariant symplectic two-form on the covariant phase space of the theory.     

A hybrid model based on dynamic programming,neural networks,and surrogate value for inventory optimisation applications

This paper proposes a new approach to minimise inventory levels and their associated costs within large geographically dispersed organisations. For such organisations, attaining a high degree of agility is becoming increasingly important. Linear regression-based tools have traditionally been employed to assist human experts in inventory optimisation; endeavours; recently, Neural Network (NN) techniques have been proposed for this domain. The objective of this paper is to create a hybrid framework that can be utilised for analysis, modelling and forecasting purposes. This framework combines two existing approaches and introduces a new associated cost parameter that serves as a surrogate for customer satisfaction. The use of this hybrid framework is described using a running example related to a large geographically dispersed organisation.     

Pd-Catalyzed Regioselective Domino C−C Bond Formation to Access N-Fused Benzimidazo-Indolo-Isoquinoline Heterocycles

Regioselective synthesis of N-fused benzimidazo-indolo-isoquinoline heterocycles via Pd-catalyzed domino coupling reaction of 1-(1-methyl-1H-indol-2-yl)-1H-benzimidazoles and aryl halides was developed. This one pot methodology proceeded via a five-member carbopalladacycle intermediate and provided direct and facile route to access structurally complex polyheterocycles in moderate to good yields. These unique hybrid molecules resembled structural similarity with naturally isolated alkaloids. Notably, the present domino process occurred through activation of three C−H bonds and the simultaneous formation of two new C−C bonds in one-shot. These molecules exhibited strong solid and solution phase fluorescence and their emission spectra in both the medium are reported here.     

Antioxidant Polymers with Enhanced Neuroprotection Against Insulin Fibrillation

Lipoic acid (LA) and dihydrolipoic acid (DHLA) are well established antioxidants to scavenge reactive oxygen species (ROS). However, they are carboxylates with ≈4.7 pKa making them negatively charged at physiological pH (7.4) reducing their passive diffusion through cell membranes. LA is known to be capable of reducing protein fibrillation. Incorporation of LA and especially DHLA in polymer side chains are scarce. Herein, the first examples of the anti-amyloidogenic effect of LA and DHLA incorporated into the side-chain of a block copolymer with a water-soluble poly(polyethylene glycol methyl ether methacrylate) (PPEGMA) segment are presented. The resultant polymers show improved ROS scavenging activity and improved ability to reduce insulin fibrillation compared to free LA and DHLA. Furthermore, the resultant polymers are also capable of disintegrating preformed insulin firbrils. Interestingly, polymers with dihydro-lipoate moieties showed 93% free radical scavenging activity with 91% anti-fibrillating efficacies for insulin protein confirmed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay and Thioflavin T (ThT) dye binding study, respectively. Further, the antioxidant polymers increase the cell viability against fibrillar insulin aggregates that may be involved in the etiology of several diseases. Overall, this work reveals that antioxidant polymer-based therapeutic agents can serve as a powerful modulation strategy for developing novel drugs in future against amyloid-related disorders.