A Linear Stochastic Programming Model for Optimal Leveraged Portfolio Selection

The literature of portfolio optimization is extensive and covers several important aspects of the asset allocation problem. However, previous works consider simplified linear borrowing cost functions that leads to suboptimal allocations. This paper aims at efficiently solving the leveraged portfolio selection problem with a thorough borrowing cost representation comprising a number lenders with different rates and credit limits. We propose a two-stage stochastic programming model for asset and debt allocation considering a CVaR-based risk constraint and a convex piecewise-linear borrowing cost function. We compare our model to its counterpart with the fixed borrowing rate approximation used in literature. Numerical results show our model significantly improves performance in terms of risk-return trade-off.     

Statistical analysis of achievable resolution limit in the near field source localization context

In this fast communication, we derive the statistical resolution limit (SRL), characterizing the minimal parameter separation, to resolve two closely spaced known near-field sources impinging on a linear array. Toward this goal, we conduct on the first-order Taylor expansion of the observation model a Generalized Likelihood Ratio Test (GLRT) based on a Constrained Maximum Likelihood Estimator (CMLE) of the SRL. More precisely, the minimum separation between two near-field sources, that is detectable for a given probability of false alarm and a given probability of detection, is derived herein. Finally, numerical simulations are done to quantify the impact of the array geometry of the signal sources power distribution and of the array aperture on the statistical resolution limit.     

Thermally induced microstructure and morphology transformations in molybdenum disulfide–octadecyltrimethylammonim layered nanocomposite

Microstructure of layered nanocomposite compound consisting of molybdenum disulfide single layers and the layers of octadecyltrimethylammonium molecules as well as the structure of destruction products of this hybrid compound were studied by high resolution transmission electron microscopy (HRTEM) and powder X-ray diffraction (XRD) techniques. Changes in composition, ordering and morphology of the host and guest layers of the compound occurring due to release of organic guest from the interlayer space of MoS₂ on heating or on action of electronic beam have been revealed. Removal of the guest was found to initiate formation in the initial layered structure of the packets consisting of a few MoS₂ layers which come close together within the distances of ca. 1–1.5 nm and 0.6–0.7 nm after heating at 250 °C and 400 °C, respectively. Leaving the guest also causes deformations of MoS₂ layers resulting in their non-flat geometry. At 400 °C, strong bending of a part of the sulfide layers with the radius as small as 3–4 nm was observed.     

Virtual RF system platform dedicated to heterogeneous complex SoC design

In this paper, we propose to develop a hierarchical library associated with various simulators that can be used in a single platform, called TrustMe-ViP, which enables a unique simulation framework and full model interoperability. Such platform is dedicated to complex SoC design, such as trusted personal devices where cost and time-to-market are very important constraints. To validate this methodology, we present the estimation of BER and power consumption for a Bluetooth transceiver.     

Managing the complex data center environment: an Integrated Energy-aware Framework

The problem of Information Technology energy consumption has gained much attention due to the always increasing use of IT both for business and for personal reasons. In particular, data centers are now playing a much more important role in the modern society, where the information is available all the time and everywhere. In this context, the aim of this paper is to study energy efficiency issues within data centers from the Information System perspective. The proposed approach integrates the application and infrastructure capabilities, in which the enactment of adaptation mechanisms is aligned with the business process. Based on both energy and quality dimensions of service-based applications, a model-based approach supports the formulation of new constrained optimization problem that takes into consideration over-constrained solutions where the goal is to obtain the better trade-off between energy and quality requirements. These ideas are combined within a framework where time-based analysis allow the identification of potential system threats and drive the selection of adaptation actions improving overall energy and quality requirements, represented by indicators satisfaction. In addition, the framework includes an evolution mechanism that is able to evaluate past decisions feedback in order to adjust the model according to the current underlying environment. Finally, the benefits of the approach are analyzed in an experimental setting.     

Nuclear DNA barcodes for cod identification in mildly-treated and processed food products

Gadoids are a group of fish with historical importance in the fishing industry. The high demand for cod is one of the reasons why cod products are often mislabelled, and numerous observations have been made on the replacement of Atlantic cod (Gadus morhua) by cheaper species or its illegal capture in contravention of fish quotas. Fish species identification is traditionally based on morphological features, but this may be difficult in case of heat-treated or processed products, or where the species look similar, as in the Gadoid group. DNA-based approaches (using either nuclear or mitochondrial DNA) are most commonly used in this case, due to their high specificity and to the high resilience of the target molecules to food processing techniques. In this article, we identified, using an automated screening approach, novel barcode regions and their associated primers in the nuclear genome, to be used for the efficient identification of Gadoids. The barcode regions were tested on official and commercial samples, raw or mildly treated products, like frozen, or salted, as well as pre-cooked complex mixtures and processed samples, using next-generation sequencing (NGS) technique. The method proposed could complement existing fish identification strategies in establishing an efficient framework to detect and prevent frauds along the food chain.     

Evaluation of the effect of heat input in superduplex stainless steel deposition by the plasma powder process*

Plasma powder surfacing is one of the latest processes for application of coatings, with control of dilution as its main feature. Surfacing with superduplex stainless steels is an interesting option for the construction and repair of equipment for applications in a highly corrosive environment, allowing the desired characteristics to be achieved: corrosion resistance and good mechanical properties. The aim of this work is to assess the ferrite content in the weld metal and the mechanical characteristics via microhardness profiles in surfacing of C-Mn steel pipes with deposition of UNS S32760 by plasma powder surfacing. Welding operations were carried out on pipes with deposition of SDSS, employing three welding heat input levels, varying the welding speed or the welding current. Then the geometry was analysed, the ferrite content in the weld metal was quantified and the microhardness profile was recorded. Variation in welding heat input caused changes in weld bead geometry, with variation in the welding current producing the most significant changes. Increase in heat input caused decrease in ferrite content of the weld metal. Regarding microhardness, only the condition with a higher level of welding current gave sufficiently high levels of microhardness in the weld metal.     

Mixture and non-mixture cure fraction models based on the generalized modified Weibull distribution with an application to gastric cancer data

The cure fraction models are usually used to model lifetime time data with long-term survivors. In the present article, we introduce a Bayesian analysis of the four-parameter generalized modified Weibull (GMW) distribution in presence of cure fraction, censored data and covariates. In order to include the proportion of “cured” patients, mixture and non-mixture formulation models are considered. To demonstrate the ability of using this model in the analysis of real data, we consider an application to data from patients with gastric adenocarcinoma. Inferences are obtained by using MCMC (Markov Chain Monte Carlo) methods.