Influence of β‐nucleation on polymorphism and properties in random copolymers and terpolymers of propylene

The competition between α, β, and γ polymorphs has been studied in several random copolymers and terpolymers of propylene, by performing X‐ray diffraction and differential scanning calorimetry experiments. Formation of β‐crystals, achieved by the addition of a β‐nucleating agent, was found to be highly dependent on comonomer type and crystallization conditions. Additionally, the mechanical properties have been evaluated from stress‐strain, microhardness and dynamic‐mechanical thermal analyses. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

A deep learning approach for the forensic evaluation of sexual assault

Despite the existence of patterns able to discriminate between consensual and non-consensual intercourse, the relevance of genital lesions in the corroboration of a legal rape complaint is currently under debate in many countries. The testimony of the physicians when assessing these lesions has been questioned in court due to several factors (e.g., a lack of comprehensive knowledge of lesions, wide spectrum of background area, among others). Therefore, it is relevant to provide automated tools to support the decision process in an objective manner. In this work, we evaluate the performance of state-of-the-art deep learning architectures for the forensic assessment of sexual assault. We propose a deep architecture and learning strategy to tackle the class imbalance on deep learning using ranking. The proposed methodologies achieved the best results when compared with handcrafted feature engineering and with other deep architectures.     

An approach to calibrate incentives for continuity of supply in the Spanish electricity distribution system

This paper proposes an approach to calibrate incentives for continuity of supply in electricity distribution in Spain. This approach consists on the estimation of the impact of continuity of supply improvements on distribution network costs. For this purpose, distribution costs resulting from different continuity of supply requirements are computed by a reference network model (RNM). The results obtained from the RNM are used to estimate a cost-function that considers continuity of supply a cost driver for distribution costs. This methodology is applied to three Spanish areas of service (an urban one, a semi-urban one and a rural one) in such a way that differences in distribution costs caused by the characteristics of the area type can be taken into account. The analysis indicated that distribution costs are more sensitive to continuity of supply improvements in rural areas of service. It also demonstrated that the incentive for reducing number of service interruptions should be higher than the incentive for reducing duration of service interruptions. Finally, the current Spanish incentive scheme for continuity of supply was analyzed under the perspective of the proposed approach.     

A methodology for screening of microalgae as a decision making tool for energy and green chemical process applications

The increasing interest for biotechnological use of microalgae demands a methodology for selection of species suitable to support the development of technologies based on the use of such non-conventional renewable raw material, i.e., green industrial applications. The vast and expanding collection of experimental data on both cell growth and biomass composition available in the literature can be used to reduce the cost of the experimental investigations required to support process engineering and optimization. Selecting the appropriate organism requires extracting useful information from such data, a cumbersome task since various multidisciplinary factors must be considered. This paper presents a computer-aided methodology for selecting appropriate algal species given an energy or green chemical process application employing microalgae as a renewable raw material. The approach is “system oriented”, based on biomass composition and chemical processing of the biomass downstream of the CO₂ biofixation and harvesting operations. Quantitative performance results are supported by professional process simulation. Besides comparison of a set of species performances, the proposed methodology also allows the discrimination among distinct algal compositions resulting from different growth conditions for a given species. Furthermore, three categories of screening metrics are proposed to be maximized by the decision making procedure in order to elicit the relevant information. To demonstrate the potential of the proposed methodology, a databank of both biochemical and elemental compositions of microalgal biomass was used in three green applications: Assessment of biomass heating value; production of syngas by gasification of the biomass; and production of Bio-H₂. Within the accuracy of the databank employed to illustrate the procedure, the methodology selected Botryococcus braunii and Isochrysis galbana as potential promising candidates, for the three examined applications.     

Prediction of the diffusion coefficients in multicomponent liquid refrigerant solutions

Immersion chilling and freezing (ICF) consist of soaking foods in a low freezing point liquid medium maintained at a low temperature that are considered secondary refrigerants. Data related to transport properties for the refrigerating media used in ICF processes are scarce, particularly for ternary and higher order systems. The objective of this work was to develop a model for the prediction of diffusion coefficients for systems of interest for ICF processes. The generalized Maxwell-Stefan equations were used in the model development. Data obtained from literature corresponding to Fick diffusion coefficients of the binary systems NaCl-H₂O and KCl-H₂O, and the ternary system NaCl-KCl-H₂O, were compared with predicted values. Results were satisfactory, errors of the main diffusion coefficients less than 13.5% being obtained. These results may be extended to the typical range of conditions of ICF, where no data are available in literature to date.     

Strawberries from integrated pest management and organic farming: Phenolic composition and antioxidant properties

Consumer awareness, pesticide and fertilizer contaminations and environmental concerns have resulted in significant demand for organically grown farm produce. Consumption of berries has become popular among health-conscious consumers due to the high levels of valuable antioxidants, such as anthocyanins and other phenolic compounds. The present study evaluated the influence that organic farming (OF) and integrated pest management (IPM) practise exert on the total phenolic content in 22 strawberry samples from four varieties. Postharvest performance of OF and IPM strawberries grown in the same area in the centre of Portugal and harvested at the same maturity stage were compared. Chemical profiles (phenolic compounds) were determined with the aid of HPLC-DAD/MS. Total phenolic content was higher for OF strawberry extracts. This study showed that the main differences in bioactive phytochemicals between organically and IPM grown strawberries concerned their anthocyanin levels. Organically grown strawberries were significantly higher in antioxidant activity than were the IPM strawberries, as measured by DPPH and FRAP assays.     

Distributed Approach to Control and Manage Context-based Multi-virtual Networks

Using the flexibility of Wireless Mesh Networks (WMNs) and network virtualization, we define a novel architecture that provides personalized access for users by splitting a WMN into several adaptable Virtual Networks (VNs). Each VN is configured to meet specific levels of user context demands (context can span from security, mobility or service requirements). Users are grouped according to similarity of their context, and associated to VNs matching their context. To break the traditional centralized solutions for WMN and virtualization control, this paper defines an overall framework to distribute the control responsibilities along the architectural entities, which can then cooperate to autonomously discover, select, create, extend or remove VNs on-demand according to user and WMN dynamics. We also propose an analytical model to evaluate several performance aspects of the distributed VN control when compared to centralized or decentralized solutions, validating the model against a simulation study.     

QoS-aware optimization of sensor network queries

The resource-constrained nature of mote-level wireless sensor networks (WSNs) poses challenges for the design of a general-purpose sensor network query processors (SNQPs). Existing SNQPs tend to generate query execution plans (QEPs) that are selected on the basis of a fixed, implicit expectation, for example, that energy consumption should be kept as small as possible. However, in WSN applications, the same query may be subject to several, possibly conflicting, quality-of-service (QoS) expectations concomitantly (for example maximizing data acquisition rates subject to keeping energy consumption low). It is also not uncommon for the QoS expectations to change over the lifetime of a deployment (for example from low to high data acquisition rates). This paper describes optimization algorithms that respond to stated QoS expectations (about acquisition rate, delivery time, energy consumption and lifetime) when making routing, placement, and timing decisions for in-WSN query processing. The paper shows experimentally that QoS-awareness offers significant benefits in responding to, and reconciling, diverse QoS expectations, thereby enabling QoS-aware SNQPs to generate efficient QEPs for a broader range WSN applications than has hitherto been possible.