Inventory model for seasonal demand with option to change the market

In real life, when bulk purchase becomes convenient or even mandatory, it is a common practice for distributors to explore an alternative market in order to maximize the revenue earned. In this paper, we consider an inventory model for a product having seasonal demand with two potential markets, say, primary and alternate. The distributor has a single opportunity of procurement prior to multiple demand seasons in the primary and the alternate market. Both the markets have similar demand patterns, with time lag between their demand seasons. The demand is a price and time dependent function with increasing, constant and declining phases within each demand season. The scale parameter of demand rate depends upon the market. In each market, successive seasons are separated by random time. In one replenishment cycle, the distributor has a single option to exit the primary market by transferring the inventory, with or without change in selling price. This option can be exercised at the end of any complete season at the primary market. Our investigations indicate that it will be beneficial for the distributor to shift to the alternate market even at a slightly lower selling price if demand rate in the alternate market is higher. Optimal number of seasons at the primary market before change of price or market is obtained. Optimal policy is obtained for jointly determining the order quantity and price. Concavity of the profit function is discussed. Solution procedure, numerical examples and sensitivity analysis are presented.     

A general framework for efficient geographic routing in wireless networks

We propose a new link metric called normalized advance (NADV) for geographic routing in multihop wireless networks. NADV selects neighbors with the optimal trade-off between proximity and link cost. Coupled with the local next hop decision in geographic routing, NADV enables an adaptive and efficient cost-aware routing strategy. Depending on the objective or message priority, applications can use the NADV framework to minimize various types of link cost.We present efficient methods for link cost estimation and perform detailed experiments in simulated environments. Our results show that NADV outperforms current schemes in many aspects: for example, in high noise environments with frequent packet losses, the use of NADV leads to 81% higher delivery ratio. When compared to centralized routing under certain settings, geographic routing using NADV finds paths whose cost is close to the optimum. We also conducted experiments in Emulab testbed and the results demonstrate that our proposed approach performs well in practice.     

Differential regulation of redox proteins and chaperones in HbEβ-thalassemia erythrocyte proteome

Purpose: In (hemoglobin, Hb) HbEβ‐thalassemia, HbE (β‐26 Glu→Lys) interacts with β‐thalassemia to produce clinical manifestation of varying severity. This is the first proteomic effort to study changes in protein levels of erythrocytes isolated from HbEβ‐thalassemic patients compared to normal. Experimental design: We have used 2‐DE and MALDI‐MS/MS‐based techniques to investigate the differential proteome profiling of membrane and Hb‐depleted fraction of cytosolic proteins of erythrocytes isolated from the peripheral blood samples of HbEβ‐thalassemia patients and normal volunteers. Results: Our study showed that redox regulators such as peroxiredoxin 2, Cu‐Zn superoxide dismutase and thioredoxin and chaperones such as α‐hemoglobin stabilizing protein and HSP‐70 were upregulated in HbEβ‐thalassemia. We have also observed larger amounts of membrane associated globin chains and indications of disruption of spectrin‐based junctional complex in the membrane skeleton of HbEβ‐thalassemic erythrocytes upon detection of low molecular weight fragments of β‐spectrin and decrease in β‐actin and dematin content. Conclusion and clinical relevance: We have observed interesting changes in the proteomic levels of redox regulators and chaperons in the thalassemic hemolysates and have observed strong correlation or association of the extent of such proteomic changes with HbE levels. This could be important in understanding the role of HbE in disease progression and pathophysiology.     

Effect of numerical integration on meshless methods

In this paper, we present the effect of numerical integration on meshless methods with shape functions that reproduce polynomials of degree k1. The meshless method was used on a second order Neumann problem and we derived an estimate for the energy norm of the error between the exact solution and the approximate solution from the meshless method under the presence of numerical integration. This estimate was obtained under the assumption that the numerical integration scheme satisfied a form of Green’s formula. We also indicated how to obtain numerical integration schemes satisfying this property.     

Semantics-driven annotation of patient-specific 3D data: a step to assist diagnosis and treatment of rheumatoid arthritis

In the digital era, patient-specific 3D models (3D-PSMs) are becoming increasingly relevant in computer-assisted diagnosis, surgery training on digital models, or implant design. While advanced imaging and reconstruction techniques can create accurate and detailed 3D models of patients’ anatomy, software tools that are able to fully exploit the potential of 3D-PSMs are still far from being satisfactory. In particular, there is still a lack of integrated approaches for extracting, coding, sharing and retrieving medically relevant information from 3D-PSMs and use it concretely as a support to diagnosis and treatment. In this article, we propose the SemAnatomy3D framework, which demonstrates how the ontology-driven annotation of 3D-PSMs and of their anatomically relevant features (parts of relevance) can assist clinicians to document more effectively pathologies and their evolution. We exemplify the idea in the context of the diagnosis of rheumatoid arthritis of the hand district, and show how feature extraction tools and semantic 3D annotation can provide a rich characterization of anatomical landmarks (e.g., articular facets, prominent features, ligament attachments) and pathological markers (erosions, bone loss). The core contributions are an ontology-driven part-based annotation method for the 3D-PSMs and a novel automatic localization of erosion and quantification of the OMERACT RAMRIS erosion score. Finally, our results have been compared against a medical ground truth.     

Experimental realization of quantum cheque using a five-qubit quantum computer

Quantum cheques could be a forgery-free way to make transaction in a quantum networked banking system with perfect security against any no-signalling adversary. Here, we demonstrate the implementation of quantum cheque, proposed by Moulick and Panigrahi (Quantum Inf Process 15:2475–2486, 2016), using the five-qubit IBM quantum computer. Appropriate single qubit, CNOT and Fredkin gates are used in an optimized configuration. The accuracy of implementation is checked and verified through quantum state tomography by comparing results from the theoretical and experimental density matrices.     

Kinetics of alpha precipitation in Ti-6 wt % Cr and Ti-11 wt % Mo

The morphology and kinetics of the precipitation of the alpha phase produced by two different heat treatment routes, namely, (a) direct isothermal decomposition and (b)-quenching and subsequent ageing, were studied. In isothermally decomposed samples the (supersaturated) + transformation was seen to occur mainly through the discontinuous growth of the transformed zone consisting of groups of parallel side plates from the grain boundary regions towards the interior of the grain. Unlike for the case of a regular discontinuous precipitation, here the transformed regions are not separated from the untransformed by an incoherent interface and the growing-plates do obey a fixed orientation relationship with the grain from which they are evolved. The theory of cellular reaction has been applied to explain the growth rate of the duplex ( + ) region. The overall reaction kinetics were analysed on the basis of the Johnson-Mehl formulation and were found to be consistent with that of a discontinuous precipitation reaction, where grain boundary nucleation sites were saturated at an early stage of the transformation. The structure of the-quenched samples showed a uniform distribution of athermal omega particles which acted as precursors to the-precipitates. As a consequence, the reaction rate was greatly enhanced and-precipitation in the quenched and aged samples was seen to occur continuously in the entire body of the grain.     

Energy storage behaviour of some binary alkali borate glasses by thermoluminescence studies

Thermoluminescence behaviour of a series of binary alkali borate glasses has been investigated to study their energy storage mechanism. Sodium borate glasses of varying composition have been prepared and their glow curves recorded after exposing them to X-rays (CuK radiation, 30 kV, 10 mA) of different dosages at room temperature. The effect of the nature and concentration of alkali oxide and the dose of irradiation on the nature of thermoluminescent glow curves were also studied. Borate glasses containing different concentrations of Na₂O exhibit significantly different glow curves. These glow curves have been analysed and the nature of traps responsible for TL emission are tentatively identified. The broad and complex nature of the glow pattern is attributed to distribution of trap depths in these materials. The viability of borate glasses in the construction of TL dosimeters are discussed.     

Analyzing collective behavior from blogs using swarm intelligence

With the rapid growth of the availability and popularity of interpersonal and behavior-rich resources such as blogs and other social media avenues, emerging opportunities and challenges arise as people now can, and do, actively use computational intelligence to seek out and understand the opinions of others. The study of collective behavior of individuals has implications to business intelligence, predictive analytics, customer relationship management, and examining online collective action as manifested by various flash mobs, the Arab Spring (2011) and other such events. In this article, we introduce a nature-inspired theory to model collective behavior from the observed data on blogs using swarm intelligence, where the goal is to accurately model and predict the future behavior of a large population after observing their interactions during a training phase. Specifically, an ant colony optimization model is trained with behavioral trend from the blog data and is tested over real-world blogs. Promising results were obtained in trend prediction using ant colony based pheromone classier and CHI statistical measure. We provide empirical guidelines for selecting suitable parameters for the model, conclude with interesting observations, and envision future research directions.