Integrating Geographical Information Systems, Fuzzy Logic and Analytical Hierarchy Process in Modelling Optimum Sites for Locating Water Reservoirs. A Case Study of the Debub District in Eritrea

The aim of this study was to model water reservoir site selection for a real world application in the administrative district of Debub, Eritrea. This is a region were scarcity of water is a fundamental problem. Erratic rainfall, drought and unfavourable hydro-geological characteristics exacerbates the region’s water supply. Consequently, the population of Debub is facing severe water shortages and building reservoirs has been promoted as a possible solution to meet the future demand of water supply. This was the most powerful motivation to identify candidate sites for locating water reservoirs. A number of conflicting qualitative and quantitative criteria exist for evaluating alternative sites. Decisions regarding criteria are often accompanied by ambiguities and vagueness. This makes fuzzy logic a more natural approach to this kind of Multi-criteria Decision Analysis (MCDA) problems. This paper proposes a combined two-stage MCDA methodology. The first stage involved utilizing the most simplistic type of data aggregation techniques known as Boolean Intersection or logical AND to identify areas restricted by environmental and hydrological constraints and therefore excluded from further study. The second stage involved integrating fuzzy logic with the Analytic Hierarchy Process (AHP) to identify optimum and back-up candidate water reservoir sites in the area designated for further study

Mapping of quorum sensing interaction network of commensal and pathogenic staphylococci

Staphylococci utilize secreted autoinducing peptides (AIPs) to regulate group behavior through a process called quorum sensing (QS). For pathogenic staphylococci, such as Staphylococcus aureus, QS regulates the expression of major virulence factors, and QS inhibition has been proposed as an alternative to antibiotics for the treatment of infections with methicillin-resistant S. aureus (MRSA). Here, we surveyed the interaction map between QS systems of the pathogens S. aureus, Staphylococcus epidermidis, and Staphylococcus lugdunensis and all the currently known staphylococcal AIPs, covering 21 different species. We identified six of these ribosomally synthesized and post-translationally modified peptides (RiPPs) in this study and compiled the full collection of AIPs by chemical synthesis. The resulting mapping provided 280 QS interactions that were divided into human- and animal-associated staphylococci, showing substantial differences in inhibitory potencies between the groups. AIPs of the bovine-associated species Staphylococcus simulans displayed potential as QS inhibitors toward the investigated strains and were therefore chosen as a starting point for a structure-activity relationship study. This study provides insights into the requirements for QS interference, yielding the most potent inhibitors reported to date for S. epidermidis and S. lugdunensis. Furthermore, we tested an S. simulans AIP as an anti-virulence agent in an assay to assess the risk of acquired suppression of the inhibitory effect, and we established an assay set-up to successfully monitor agr deactivation of virulent MRSA by the QS inhibitor. Finally, a peptide was shown to attenuate skin infection caused by MRSA in a mouse model. Our results reveal a complex network of staphylococcal interactions and provide further impetus for the investigation of QS modulation in the targeting of antibiotic-resistant pathogens.IMPORTANCEBacteria from the Staphylococcus genus produce macrocyclic peptides, called autoinducing peptides (AIPs), used in inter-cell communication with their kin. Differences in AIP sequence and length produced by different staphylococcal species can result in communication interference, altering the physiology of co-inhabiting staphylococci in complex microbiotas. Opportunistic pathogens like Staphylococcus aureus regulate the expression of toxins using this peptide-mediated communication, and its inhibition has, therefore, been proposed as a strategy to target infections caused by methicillin-resistant S. aureus (MRSA). The systematic mapping of AIP activities, structure-activity relationship studies, and evaluation of resistance development provided in this paper, therefore, serve as a resource for the future discovery of inhibitory peptides for the investigation of bacterial communication

USO DE REDES NEURAIS ARTIFICIAIS NA PONDERAÇÃO INICIAL DA TÉCNICA AHP EM ANÁLISES DE VULNERABILIDADE DE BACIAS HIDROGRÁFICAS

Em muitos problemas decisórios, a informação fornecida pelos tomadores de decisão muitas vezes é imprecisa ou incerta devido ao limite de tempo, a falta de dados ou capacidades de avaliar as informações disponíveis. Como forma de superar essas dificuldades, algumas pesquisas têm apresentado a aplicação da técnica Analytical Hierarchic Ponderation (AHP). Esta técnica estrutura um problema de decisão complicada em uma hierarquia de subproblemas, faz comparações par a par das informações de entrada e, a partir do ranqueamento dos resultados, permite estimar pesos para cada variável apresentada. Entretanto, reconhece-se que o ponto mais fraco do método é a ponderação inicial das variáveis de entrada, visto que o conhecimento de especialistas pode ser subjetivo e a importância relativa entre os elementos de análise pode variar. O que não se discute na literatura é a importância desses pesos e a variação da ordem no cálculo dos pesos finais. Por isso, esta pesquisa avalia diferentes cenários no contexto de vulnerabilidade ambiental comparando as variações entre as ponderações iniciais da AHP em relação a ponderação realizada por um grupo de especialistas e em relação a ponderações iniciais obtidas a partir de redes neurais como forma de minimizar a subjetividade do processo de anális