A performance evaluation framework of public health distribution network for essential medicines: lessons from the select Indian states

The present work has been carried out to develop a performance evaluation framework of distribution network design in public health with specific reference to essential medicines based on six different types of public health distribution networks (PHDNs) prevalent across six Indian states. We evaluated the performance of PHDNs on the criteria of cost and service and also on the sub-criteria of cost and service by following the analytic hierarchy process. We utilized the pairwise comparison method in determining the relative importance of criteria and sub-criteria by seeking responses from several experts and subsequently evaluated the PHDNs on all sub-criteria in a 7-point Likert scale by seeking views from the same experts. Finally, we developed the “cost–service matrix,” in which cost and service have been depicted in the horizontal and vertical axes, respectively. We demonstrated the performance of six PHDNs in this matrix in terms of cost and service by plotting scores obtained by them on cost and service, respectively. The findings of the study provide rich insights to the policy planners of public health.     

Challenges in Liquid‐Phase Exfoliation,Processing, and Assembly of Pristine Graphene

Recent developments in the exfoliation, dispersion, and processing of pristine graphene (i.e., non‐oxidized graphene) are described. General metrics are outlined that can be used to assess the quality and processability of various “graphene” products, as well as metrics that determine the potential for industrial scale‐up. The pristine graphene production process is categorized from a chemical engineering point of view with three key steps: i) pretreatment, ii) exfoliation, and iii) separation. How pristine graphene colloidal stability is distinct from the exfoliation step and is dependent upon graphene interactions with solvents and dispersants are extensively reviewed. Finally, the challenges and opportunities of using pristine graphene as nanofillers in polymer composites, as well as as building blocks for macrostructure assemblies are summarized in the context of large‐scale production.     

The role of protein kinase in C ischemic/reperfused preconditioned isolated rat hearts

Protein kinase C (PKC) has been implicated in the preconditioning-induced cardiac protection in ischemic/reperfused myocardium. We studied the effect of PKC inhibition with calphostin C (25, 50, 100, 200, 400, and 800 nM), a potent and specific inhibitor of PKC, in isolated working nonpreconditioned and preconditioned ischemic/reperfused hearts. In the nonpreconditioned groups, all hearts underwent 30 min of normothermic global ischemia followed by 30 min of reperfusion. In the preconditioned groups, hearts were subjected to four cycles of ischemic preconditioning by using 5 min of ischemia followed by 10 min reperfusion, before the induction of 30 min ischemia and reperfusion. At low concentrations of calphostin C (25, 50, and 100 nM), the PKC inhibitor had no effect on the incidence or arrhythmias or postischemic cardiac function in the nonpreconditioned ischemic/reperfused groups. With 200 and 400 nM of calphostin C, a significant increase in postischemic function and a reduction in the incidence of arrhythmias were observed in the nonpreconditioned ischemic/reperfused groups. Increasing the concentration of calphostin C to 800 NM, the recovery of postischemic cardiac function was similar to that of the drug-free control group. In preconditioned hearts, lower concentrations (< 100 nM) of calphostin C did not change the response of the myocardium to ischemia and reperfusion in comparison to the preconditioned drug-free myocardium. Two hundred and 400 nM of the PKC inhibitor further reduced the incidence of ventricular fibrillation (VF) from the preconditioned drug-free value of 50% to 0 (p < 0.05) and 0 (p < 0.05), respectively, indicating that the combination of the two, preconditioning and calphostin C, affords significant additional protection. Increasing the concentration of calphostin C to 800 nM blocked the cardioprotective effect of preconditioning (100% incidence of VF). The recovery of cardiac function was similarly improved at calphostin C doses of 200 and 400 nM and was reduced at 800 nM (p < 0.05). With 200 and 400 nM of calphostin C, both cytosolic and particulate PKC activity were reduced by approximately 40 and 60%, respectively, in both preconditioned and preconditioned/ischemic/reperfused hearts. The highest concentration of calphostin C (800 nM) resulted in almost a complete inhibition of cytosolic (100%) and particulate (85%) PKC activity correlated with the abolition of preconditioning-induced cardiac protection. In conclusion, calphostin C protects the ischemic myocardium obtained from intact animals, provides significant additional protection to preconditioning at moderate doses, and blocks the protective effect of preconditioning at high concentrations. The dual effects of calphostin C appear to be strictly dose and "enzyme inhibition" related.     

Affine-based registration of CT and MR modality images of human brain using multiresolution approaches: comparative study on genetic algorithm and particle swarm optimization

We present a non-linear 2-D/2-D affine registration technique for MR and CT modality images of section of human brain. Automatic registration is achieved by maximization of a similarity metric, which is the correlation function of two images. The proposed method has been implemented by choosing a realistic, practical transformation and optimization techniques. Correlation-based similarity metric should be maximal when two images are perfectly aligned. Since similarity metric is a non-convex function and contains many local optima, choice of search strategy for optimization is important in registration problem. Many optimization schemes are existing, most of which are local and require a starting point. In present study we have implemented genetic algorithm and particle swarm optimization technique to overcome this problem. A comparative study shows the superiority and robustness of swarm methodology over genetic approach.     

Hadamard quantum broadcast channels

We consider three different communication tasks for quantum broadcast channels, and we determine the capacity region of a Hadamard broadcast channel for these various tasks. We define a Hadamard broadcast channel to be such that the channel from the sender to one of the receivers is entanglement-breaking and the channel from the sender to the other receiver is complementary to this one. As such, this channel is a quantum generalization of a degraded broadcast channel, which is well known in classical information theory. The first communication task we consider is classical communication to both receivers, the second is quantum communication to the stronger receiver and classical communication to other, and the third is entanglement-assisted classical communication to the stronger receiver and unassisted classical communication to the other. The structure of a Hadamard broadcast channel plays a critical role in our analysis: The channel to the weaker receiver can be simulated by performing a measurement channel on the stronger receiver’s system, followed by a preparation channel. As such, we can incorporate the classical output of the measurement channel as an auxiliary variable and solve all three of the above capacities for Hadamard broadcast channels, in this way avoiding known difficulties associated with quantum auxiliary variables.     

A synopsis on node compromise detection in wireless sensor networks using sequential analysis (Invited Review Article)

By exploiting the unattended nature of the wireless sensor networks, an attacker can physically capture and compromise sensor nodes and then launch a variety of attacks. He can additionally create many replicas of a few compromised nodes and spread these replicas over the network, thus launching further attacks with their help. In order to minimize the damage incurred by compromised and replicated nodes, it is very important to detect such malicious nodes as quickly as possible. In this review article, we synthesize our previous works on node compromise detection in sensor networks while providing the extended analysis in terms of performance comparison to the related work. More specifically, we use the methodology of the sequential analysis to detect static and mobile compromised nodes, as well as mobile replicated nodes in sensor networks. With the help of analytical and simulation results, we also demonstrate that our schemes provide robust and efficient node compromise detection capability.     

Automatic Clustering Using an Improved Differential Evolution Algorithm

Differential evolution (DE) has emerged as one of the fast, robust, and efficient global search heuristics of current interest. This paper describes an application of DE to the automatic clustering of large unlabeled data sets. In contrast to most of the existing clustering techniques, the proposed algorithm requires no prior knowledge of the data to be classified. Rather, it determines the optimal number of partitions of the data "on the run." Superiority of the new method is demonstrated by comparing it with two recently developed partitional clustering techniques and one popular hierarchical clustering algorithm. The partitional clustering algorithms are based on two powerful well-known optimization algorithms, namely the genetic algorithm and the particle swarm optimization. An interesting real-world application of the proposed method to automatic segmentation of images is also reported.     

A study of the oxidation kinetics of CuFeO2 in the Cu-Fe-O system

The oxidation kinetics of CuFeO₂ in the Cu-Fe-O system have been studied between 500 and 900° C in an atmosphere containing 1 vol% oxygen in a nitrogen stream using thermogravimetric analysis (TGA). It was found that addition of Fe₂O₃ to the CuFeO₂ caused a decrease in the oxidation rate while addition of CuO caused an increase. On increasing the concentration of Fe₂O₃ the activation energy was found to increase from ~ 18 kcal mol^–1 to ~ 45 kcal mol^–1 and the exponent n in Avrami's equationf=1-exp (–kt ⁿ) was also observed to increase, from 1.3 to 2.3. On adding CuO to the CuFeO₂ in the Cu-Fe-O system the activation energy decreased from ~ 18 kcal mol^–1 to ~ 8 kcal mol^–1. The variation in both values indicates changes in the oxidation mechanisms. The microstructural changes associated with oxidation have been studied using optical microscopy. A model has been proposed to explain the results.     

An inertia-adaptive particle swarm system with particle mobility factor for improved global optimization

Particle Swarm Optimization (PSO) has recently emerged as a nature-inspired algorithm for real parameter optimization. This article describes a method for improving the final accuracy and the convergence speed of PSO by firstly adding a new coefficient (called mobility factor) to the position updating equation and secondly modulating the inertia weight according to the distance between a particle and the globally best position found so far. The two-fold modification tries to balance between the explorative and exploitative tendencies of the swarm with an objective of achieving better search performance. We also mathematically analyze the effect of the modifications on the dynamics of the PSO algorithm. The new algorithm has been shown to be statistically significantly better than the basic PSO and four of its state-of-the-art variants on a twelve-function test-suite in terms of speed, accuracy, and robustness.