Web-GIS models: accomplishing modularity with aspects

Spatial concerns of Web geographical information systems (Web-GIS) are inherently crosscutting and volatile: crosscutting because they affect multiple functionalities of Web-GIS systems, and volatile because their status may change often. If these concerns are not modularized properly, the quality of Web-GIS services, particularly with regard to adaptation and evolution, can be severely compromised. This paper uses aspect-orientation to model crosscutting and volatile spatial concerns. By modeling both types of concerns, crosscutting and volatile, as candidate aspects, one can use dynamic weaving to add or remove them from a system at runtime. The aspect-oriented approach proposed starts with the identification and specification of crosscutting concerns and follows by composing these using modeling aspects using a transformation approach, an aspect-oriented modeling technique. The conflicts that can emerge due to the composition order are also taken into consideration. Finally, this paper proposes a set of reusable GIS crosscutting concerns, documenting them in a concern catalogue.     

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.     

The ECHORD project proposals analysis – Research profiles,collaboration patterns and research topic trends

This paper investigates the research profiles, collaboration patterns and research topic trends which can be identified in the proposals submitted to the ECHORD (European Clearing House for Open Robotics Development) FP7 project. On a country level, clusters were identified and characterized by patterns of proposal production per inhabitant, score and international cooperation. Belgium and Sweden constitute a cluster characterized by high proposal production, with very high scores and extensive international collaboration. Belgium also excels from another cluster analysis, being as the only country where 100% of proposals involve industry–academia cooperation and obtain scores above 10. Other findings show that single partner proposals have significantly lower quality than multi-partner proposals but, on the other hand, the number of countries involved shows no influence on the quality of the proposals. Despite the high number of industrial participants present on the proposals, it is observed that they play secondary roles in the proposals, with a very low number projects leaded by companies. Also, it is observed that partnerships between research institutions (non-universities) are the most successful. Concerning topics of the proposals, the technology human–robot interface and the product vision robot for small-scale manufacturing are the most significant. Finally, the paper shows clusters of institutions extracted from the giant network of relations obtained from the ECHORD set of proposals.     

Decision Tree-Based Data Mining and Rule Induction for Identifying High Quality Groundwater Zones to Water Supply Management: a Novel Hybrid Use of Data Mining and GIS

Water Resources Management - Groundwater is an important source to supply drinking water demands in both arid and semi-arid regions. Nevertheless, locating high quality drinking water is a major...     

Microbiological,immunological, and histological changes in the gut of Salmonella Enteritidis-challenged rats fed goat cheese containing Lactobacillus rhamnosus EM1107

Cheeses are able to serve as suitable matrices for supplying probiotics to consumers, enabling appropriate conditions for bacteria to survive gastric transit and reach the gut, where they are assumed to promote beneficial processes. The present study aimed to evaluate the microbiological, immunological, and histological changes in the gut of Salmonella Enteritidis-challenged rats fed goat cheese supplemented with the probiotic strain Lactobacillus rhamnosus EM1107. Thirty male albino Wistar rats were randomly distributed into 5 experimental groups with 6 animals each: negative (NC) and positive (PtC) control groups, control goat cheese (CCh), goat cheese added with L. rhamnosus EM1107 (LrCh), and L. rhamnosus EM1107 only (EM1107). All animals, except NC group were challenged with Salmonella Enteritidis (10⁹ cfu in 1 mL of saline through oral gavage). Microbial composition was assessed with high-throughput 16S rRNA sequencing by means of Illumina MiSeq (Illumina, San Diego, CA). Nuclear factor kappa B (NF-κB) from the animal cecum tissue was determined by real-time PCR and interleukins (TNF-α, IL-1β, IL-10, and IFN-γ) by means of ELISA. Myeloperoxidase and malondialdehyde levels were determined biochemically. The administration of the L. rhamnosus EM1107 probiotic strain, either as a pure culture or added to a cheese matrix, was able to reduce Salmonella colonization in the intestinal lumen and lessen tissue damage compared with rats from PtC group. In addition, the use of cheese for the probiotic strain delivery (LrCh) was associated with a marked shift in the gut microbiota composition toward the increase of beneficial organisms such as Blautia and Lactobacillus and a reduction in NF-κB expression. These findings support our hypothesis that cheeses might be explored as functional matrices for the efficacious delivery of probiotic strains to consumers.     

Synthesis of Ion Imprinted Polymers by Copolymerization of Zn(II) and Al(III)8-hydroxy Quinolone Complexes with Divinylbenzene and Methacryclic Acid

In this research work, Zinc(II) and Aluminum(III)-IIP's were synthesized by optimizing the amount of methacrylic acid as monomer, divinylbenzene as cross-linker. The IIP's were functionalized with 8-hydroxy quinolone complexes of the two metal ions under thermal conditions by copolymerization with monomer and cross-linker. The IIP's and Non-IIP's were characterized using FT-IR, TGA, and SEM analysis. A quite remarkable difference in the size was observed of the polymers (Zn(II) 1.0 µm and Al(III) 0.1 µm). A stronger affinity was observed with IIP in comparison with Non-IIP at pH 3.1 and 4.5 for Zn(II) and Al(III) ions on their respective polymers.