Simple approach for the plasma treatment of polymeric membranes and investigation of the aging effect

The modification of the surface characteristics after treatment with plasma in polymeric materials, such as the aging phenomenon, calls the attention of research in the area of nonthermal plasma technology. In this work, a direct treatment with dielectric-barrier discharge plasma was used on the surfaces of ultrafiltration membranes. The measurements of the contact angle with water, attenuated total reflectance accessory, zeta potential, atomic force microscopy and scanning electron microscopy-MEV were performed on the surfaces to verify changes after plasma treatment and to understand the occurrence and timing of the plasma aging effect. In the analysis of the membrane performance, hydraulic permeation and protein retention tests were performed. The results showed an improvement in wettability and hydrophilic properties in the post-treated membranes. The study of reversibility/aging of the post-plasma surface is important for research that deals with the modification of polymeric membranes. Changes in surface morphology, topography and wettability of the membranes were observed up to seven days after treatment, with a tendency to return to the initial characteristics of the membranes.     

Food-water security and virtual water trade in the Middle East and North Africa

The purpose of this study is to analyze the political economy of food-water security in the water-scarce Middle East and North Africa region. The study deploys the lens of virtual water trade to determine how the region's economies have met their rising food-water requirements over the past three decades. It is shown that the region's water and food security currently depend to a considerable extent on water from outside the region, ‘embedded’ in food imports and accessed through trade. The analysis includes blue (surface and groundwater) and green water resources.     

Titans’ revenge: Detecting Zeus via its own flaws

Malware is one of the main threats to the Internet security in general, and to commercial transactions in particular. However, given the high level of sophistication reached by malware (e.g. usage of encrypted payload and obfuscation techniques), malware detection tools and techniques still call for effective and efficient solutions. In this paper, we address a specific, dreadful, and widely diffused financial malware: Zeus.The contributions of this paper are manifold: first, we propose a technique to break the encrypted malware communications, extracting the keystream used to encrypt such communications; second, we provide a generalization of the proposed keystream extraction technique. Further, we propose Cronus, an IDS that specifically targets Zeus malware. The implementation of Cronus has been experimentally tested on a production network, and its high quality performance and effectiveness are discussed. Finally, we highlight some principles underlying malware—and Zeus in particular—that could pave the way for further investigation in this field.     

Coreference resolution: an empirical study based on SemEval-2010 shared Task 1

This paper presents an empirical evaluation of coreference resolution that covers several interrelated dimensions. The main goal is to complete the comparative analysis from the SemEval-2010 task on Coreference Resolution in Multiple Languages. To do so, the study restricts the number of languages and systems involved, but extends and deepens the analysis of the system outputs, including a more qualitative discussion. The paper compares three automatic coreference resolution systems for three languages (English, Catalan and Spanish) in four evaluation settings, and using four evaluation measures. Given that our main goal is not to provide a comparison between resolution algorithms, these are merely used as tools to shed light on the different conditions under which coreference resolution is evaluated. Although the dimensions are strongly interdependent, making it very difficult to extract general principles, the study reveals a series of interesting issues in relation to coreference resolution: the portability of systems across languages, the influence of the type and quality of input annotations, and the behavior of the scoring measures.     

Morphology and structure of the pollen cone and pollen grain of the Araucaria species from Argentina

The pollen cone and the pollen grain of the two Argentinean species of Araucaria are described with LM, SEM and TEM. Primordia of pollen cones are formed in April and May and reach maturity by mid-October in A. angustifolia (Bert.) O. Kuntze and by mid-November in A. araucana. (Mol.) K. Koch. Characters of the mature pollen cones and microsporophylls between both taxa are clearly differentiated. Pollen grains are spheroidal-subspheroidal, inaperturate, and asaccate with granulate exine and a subequatorial annular area that corresponds to the sexine thickness. Sculpturing consists of irregularly dispersed granules that are sometimes fused to each other (A. angustifolia) or forming microrugulae (A. araucana). Microgranules and microspinules are also present. The pollen wall ultrastructure is formed by a granular ectexine and lamellated endexine. Granular elements in A. angustifolia are more loosely disposed, form more interstices, and are gradually smaller towards the endexine than in A. araucana. To asses the probable relationships within the family, we compared the pollen grains of the two Araucaria species with those of other extant genera (Agathis, Wollemia) and also with fossil pollen (Araucariacites, Balmeiopsis, Cyclusphaera, Dilwynites) attributed to Araucariaceae.     

Multimedia ontology population through semantic analysis and hierarchical deep features extraction techniques

Knowledge and Information Systems - The rapid increase of available data in different complex contexts needs automatic tasks to manage and process contents. Semantic Web technologies represent the...     

Development of a water-in-oil-in-water multiple emulsion system integrating biomimetic aqueous-core lipid nanodroplets for protein entity stabilization. Part II: process and product characterization

The aqueous-core enclosed in lipid nanoballoons integrating multiple emulsions of the type water-in-oil-in-water mimic, at least in theory, the environment within viable cells, thus being suitable for housing hydrophilic protein entities such as bioactive proteins, peptides and bacteriophage particles. This study reports a complete physicochemical characterization of optimized biomimetic aqueous-core lipid nanoballoons housing hydrophilic (BSA) protein entities, evolved from a statistical 2³×3¹ factorial design study (three variables at two levels and one variable at three levels) that was the subject of the first paper of a series of three, aiming at complete stabilization of the three-dimensional structure of protein entities attempted via housing the said molecular entities within biomimetic aqueous-core lipid nanoballoons integrating a multiple (W/O/W) emulsion. The statistical factorial design followed led to the production of an optimum W/O/W multiple emulsion possessing quite homogeneous particles with an average hydrodynamic size of (186.2?±?2.6) nm and average Zeta potential of (?36.5?±?0.9) mV, and exhibiting a polydispersity index of 0.206?±?0.014. Additionally, the results obtained for the diffusion coefficient of the lipid nanoballoons integrating the optimized W/O/W multiple emulsion were comparable and of the same order of magnitude (10^?12 m² s^?1) as those published by other authors since, typically, diffusion coefficients for molecules range from 10^?10 to 10^?7 m² s^?1, but diffusion coefficients for nanoparticles are typically of the order of magnitude of 10^?12 m² s^?1.     

Design of a decision support system for machine tool selection based on machine characteristics and performance tests

Economic globalization, together with heightened market competition and increasingly short product life cycles are motivating companies to use advanced manufacturing technologies. Use of high speed machining is increasingly widespread; however, as the technology is relatively new, it lacks a deep-rooted knowledge base which would facilitate implementation. One of the most frequent problems facing companies wishing to adopt this technology is selecting the most appropriate machine tool for the product in question and own enterprise characteristics. This paper presents a decision support system for high speed milling machine tool selection based on machine characteristics and performance tests. Profile machining tests are designed and conducted in participating machining centers. The decision support system is based on product dimension accuracy, process parameters such as feed rate and interpolation scheme used by CNC and machine characteristics such as machine accuracy and cost. Experimental data for process error and cycle operation time are obtained from profile machining tests with different geometrical feature zones that are often used in manufacturing of discrete parts or die/moulds. All those input parameters have direct impact on productivity and manufacturing cost. Artificial neural network models are utilized for decision support system with reasonable prediction capability.