PROSTATIC INTRAEPITHELIAL NEOPLASIA (PIN) - PERFORMANCE OF BAYESIAN BELIEF NETWORK FOR DIAGNOSIS AND GRADING

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

Interventions to improve the appropriate use of polypharmacy for older people

Background
Inappropriate polypharmacy is a particular concern in older people and is associated with negative health outcomes. Choosing the best interventions to improve appropriate polypharmacy is a priority, hence interest in appropriate polypharmacy, where many medicines may be used to achieve better clinical outcomes for patients, is growing.

Objectives
This review sought to determine which interventions, alone or in combination, are effective in improving the appropriate use of polypharmacy and reducing medication-related problems in older people.

Search methods
In November 2013, for this first update, a range of literature databases including MEDLINE and EMBASE were searched, and handsearching of reference lists was performed. Search terms included 'polypharmacy', 'medication appropriateness' and 'inappropriate prescribing'.

Selection criteria
A range of study designs were eligible. Eligible studies described interventions affecting prescribing aimed at improving appropriate polypharmacy in people 65 years of age and older in which a validated measure of appropriateness was used (e.g. Beers criteria, Medication Appropriateness Index (MAI)).

Data collection and analysis
Two review authors independently reviewed abstracts of eligible studies, extracted data and assessed risk of bias of included studies. Study-specific estimates were pooled, and a random-effects model was used to yield summary estimates of effect and 95% confidence intervals (CIs). The GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach was used to assess the overall quality of evidence for each pooled outcome.

Main results
Two studies were added to this review to bring the total number of included studies to 12. One intervention consisted of computerised decision support; 11 complex, multi-faceted pharmaceutical approaches to interventions were provided in a variety of settings. Interventions were delivered by healthcare professionals, such as prescribers and pharmacists. Appropriateness of prescribing was measured using validated tools, including the MAI score post intervention (eight studies), Beers criteria (four studies), STOPP criteria (two studies) and START criteria (one study). Interventions included in this review resulted in a reduction in inappropriate medication usage. Based on the GRADE approach, the overall quality of evidence for all pooled outcomes ranged from very low to low. A greater reduction in MAI scores between baseline and follow-up was seen in the intervention group when compared with the control group (four studies; mean difference -6.78, 95% CI -12.34 to -1.22). Postintervention pooled data showed a lower summated MAI score (five studies; mean difference -3.88, 95% CI -5.40 to -2.35) and fewer Beers drugs per participant (two studies; mean difference -0.1, 95% CI -0.28 to 0.09) in the intervention group compared with the control group. Evidence of the effects of interventions on hospital admissions (five studies) and of medication-related problems (six studies) was conflicting.

Authors' conclusions
It is unclear whether interventions to improve appropriate polypharmacy, such as pharmaceutical care, resulted in clinically significant improvement; however, they appear beneficial in terms of reducing inappropriate prescribing.

Soil Moisture Deficit as a predictor of the trend in soil water status of grass fields

Nutrient loss from agricultural land following organic fertilizer spreading can lead to eutrophication and poor water quality. The risk of pollution is partly related to the soil water status during and after spreading. In response to these issues, a decision support system (DSS) for nutrient management has been developed to predict when soil and weather conditions are suitable for slurry spreading. At the core of the DSS, the Hybrid Soil Moisture Deficit (HSMD) model estimates soil water status relative to field capacity (FC) for three soil classes (well, moderately and poorly drained) and has potential to predict the occurrence of a transport vector when the soil is wetter than FC. Three years of field observation of volumetric water content was used to validate HSMD model predictions of water status and to ensure correct use and interpretation of the drainage classes. Point HSMD model predictions were validated with respect to the temporal and spatial variations in volumetric water content and soil strength properties. It was found that the HSMD model predictions were well related to topsoil water content through time, but a new class intermediate between poor and moderate, perhaps ‘imperfectly drained’, was needed. With correct allocations of a field into a drainage class, the HSMD model predictions reflect field scale trends in water status and therefore the model is suitable for use at the core of a DSS.

Towards utilizing Model-Driven Engineering of Composite Applications for business performance analysis

Composite Applications on top of SAPs implementation of SOA (Enterprise SOA) enable the extension of already existing business logic. In this paper we show, based on a case study, how Model-Driven Engineering concepts are applied in the development of such Composite Applications. Our Case Study extends a back-end business process which is required for the specific needs of a demo company selling wine. We use this to describe how the business centric models specifying the modified business behaviour of our case study can be utilized for business performance analysis where most of the actions are performed by humans. In particular, we apply a refined version of Model-Driven Performance Engineering that we proposed in our previous work and motivate which business domain specifics have to be taken into account for business performance analysis. We additionally motivate the need for performance related decision support for domain experts, who generally lack performance related skills. Such a support should offer visual guidance about what should be changed in the design and resource mapping to get improved results with respect to modification constraints and performance objectives, or objectives for time.

Étude des impacts écologiques du dynamisme spatio-temporel des habitats naturels sur la faune menacée du Complexe Zones Humides Mahavavy-Kinkony, Madagascar.

This study of the Mahavavy-Kinkony Wetland Complex (MKWC) assesses the impacts of habitat change on the resident globally threatened fauna. Located in Boeny Region, northwest Madagascar, the Complex encompasses a range of habitats including freshwater lakes, rivers, marshes, mangrove forests, and deciduous forest. Spatial modelling and analysis tools were used to (i) identify the important habitats for selected, threatened fauna, (ii) assess their change from 1950 to 2005, (iii) detect the causes of change, (iv) simulate changes to 2050 and (v) evaluate the impacts of change. The approach for prioritising potential habitats for threatened species used ecological science techniques assisted by the decision support software Marxan. Nineteen species were analysed: nine birds, three primates, three fish, three bats and one reptile. Based on knowledge of local land use, supervised classification of Landsat images from 2005 was used to classify the land use of the Complex. Simulations of land use change to 2050 were carried out based on the Land Change Modeler module in Idrisi Andes with the neural network algorithm. Changes in land use at site level have occurred over time but they are not significant. However, reductions in the extent of reed marshes at Lake Kinkony and forests at Tsiombikibo and Marofandroboka directly threaten the species that depend on these habitats. Long term change monitoring is recommended for the Mahavavy Delta, in order to evaluate the predictions through time. The future change of Andohaomby forest is of great concern and conservation actions are recommended as a high priority. Abnormal physicochemical properties were detected in lake Kinkony due to erosion of the four watersheds to the south, therefore an anti-erosion management plan is required for these watersheds. Among the species of global conservation concern, Sakalava rail (Amaurornis olivieri), Crowned sifaka (Propithecus coronatus) and dambabe (Paretroplus dambabe) are estimated the most affected, but at the site level Decken’s sifaka (Propithecus deckeni), kotsovato (Paretroplus kieneri) and Madagascan big-headed turtle (Erymnochelys madagascariensis) are also threatened. Local enforcement of national legislation on hunting means that MKWC is among the sites where the flying fox (Pteropus rufus) and Madagascan rousette (Rousettus madagascariensis) are well protected. Ecological restoration, ecological research and actions to reduce anthropogenic pressures are recommended.

An Intelligent Threat Prevention Framework with Heterogeneous Information

Three issues usually are associated with threat prevention intelligent surveillance systems. First, the fusion and interpretation of large scale incomplete heterogeneous information; second, the demand of effectively predicting suspects’ intention and ranking the potential threats posed by each suspect; third, strategies of allocating limited security resources (e.g., the dispatch of security team) to prevent a suspect’s further actions towards critical assets. However, in the literature, these three issues are seldomly considered together in a sensor network based intelligent surveillance framework. To address
this problem, in this paper, we propose a multi-level decision support framework for in-time reaction in intelligent surveillance. More specifically, based on a multi-criteria event modeling framework, we design a method to predict the most plausible intention of a suspect. Following this, a decision support model is proposed to rank each suspect based on their threat severity and to determine resource allocation strategies. Finally, formal properties are discussed to justify our framework.

British Society of Gastroenterology guidelines on the diagnosis and management of Barrett's oesophagus

These guidelines provide a practical and evidence-based resource for the management of patients with Barrett's oesophagus and related early neoplasia. The Appraisal of Guidelines for Research and Evaluation (AGREE II) instrument was followed to provide a methodological strategy for the guideline development. A systematic review of the literature was performed for English language articles published up until December 2012 in order to address controversial issues in Barrett's oesophagus including definition, screening and diagnosis, surveillance, pathological grading for dysplasia, management of dysplasia, and early cancer including training requirements. The rigour and quality of the studies was evaluated using the SIGN checklist system. Recommendations on each topic were scored by each author using a five-tier system (A+, strong agreement, to D+, strongly disagree). Statements that failed to reach substantial agreement among authors, defined as >80% agreement (A or A+), were revisited and modified until substantial agreement (>80%) was reached. In formulating these guidelines, we took into consideration benefits and risks for the population and national health system, as well as patient perspectives. For the first time, we have suggested stratification of patients according to their estimated cancer risk based on clinical and histopathological criteria. In order to improve communication between clinicians, we recommend the use of minimum datasets for reporting endoscopic and pathological findings. We advocate endoscopic therapy for high-grade dysplasia and early cancer, which should be performed in high-volume centres. We hope that these guidelines will standardise and improve management for patients with Barrett's oesophagus and related neoplasia.

Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.

Robust implantable antenna for in-body communications

A compact implantable printed meandered folded dipole antenna with a volume of 101.8 mm3 and robust performance is presented for operation in the 2.4 GHz medical ISM bands. The implant antenna is shown to maintain its return loss performance in the 2360???2400 MHz, 2400???2483.5 MHz and 2483.5???2500 MHz frequency bands, simulated in eleven different body tissue types with a broad range of electrical properties. Bandwidth and resonant frequency changes are reported for the same antenna implanted in high water content tissues such as muscle and skin as well as low water content tissues such as subcutaneous fat and bone. The antenna was also shown to maintain its return loss performance as it was moved towards a tissue boundary within a simulated phantom testbed.

Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Conhecimento comum e perceção do risco na gestão territorial costeira

As zonas costeiras, pelas suas características naturais, disponibilizam à sociedade múltiplas oportunidades e serviços, o que favorece uma ocupação desmedida deste território e a ocorrência de transformações relevantes provocadas pela intervenção humana. A simultaneidade da influência das atividades e intervenções humanas e da ocorrência das funções naturais deste território, revestidas de um forte caráter dinâmico, encontra-se na base do desenvolvimento quer de conflitos do tipo socioambiental, quer de situações de risco costeiro. A contribuir para esta situação, surge também a problemática das alterações climáticas, com impactos em domínios diversos, como por exemplo biodiversidade, pesca ou turismo, com um registo de aumento e intensidade de acidentes naturais associados a fenómenos meteorológicos. Apesar da existência de um conjunto de instrumentos de preservação dos recursos naturais e de ordenamento e gestão territorial, a degradação do sistema natural costeiro é muito visível, com impactos negativos de complexa recuperação. Refira-se, também, o caráter de exceção dos planos de ordenamento da orla costeira, em particular em frentes urbanas consolidadas ou em consolidação, permitindo o contínuo aumento da urbanização na orla costeira. A atuação das entidades responsáveis pela gestão do território costeiro tem sido desenvolvida com um baixo nível de envolvimento da população e maioritariamente no sentido de dar resposta às situações de perigo que vão surgindo, com a implementação de estruturas de defesa costeira, suportadas pelo erário público, cujos impactos se traduzem num agravamento do estado da zona costeira portuguesa, em geral. A região de Aveiro é um exemplo da problemática exposta, onde se registam frequentemente episódios de perigo costeiro, considerando-se urgente a tomada de medidas que contribuam para a sustentabilidade deste território, associada a uma visão de longo prazo, e que deverão passar pela integração do risco na gestão territorial costeira. Esta investigação, com a qual se pretende aumentar o conhecimento científico, desenvolver uma abordagem integrada de diversos domínios disciplinares, demonstrar a relevância da valorização do conhecimento comum e da perceção social na gestão do território, bem como desenvolver uma ferramenta de suporte à gestão territorial da zona costeira, tem como propósito contribuir para a preservação do sistema natural costeiro e para o aumento dos níveis de segurança humana face ao risco costeiro. Nesse sentido, desenvolveu-se um estudo de perceção social em aglomerados urbanos costeiros da região de Aveiro, para avaliação da perceção do risco costeiro e da gestão do território e recolha de conhecimento comum sobre a dinâmica costeira. Concebeu-se, também, um sistema de informação geográfica que permite às entidades de gestão do território costeiro uma atuação facilitada, articulada e de caráter preventivo, suportada na integração de conhecimentos científico, técnico e comum, de perceções e aspirações, de limites, propostas e condicionantes de planos de ordenamento e gestão do território existentes, entre outra informação, e com potencialidade para evoluir simultaneamente para um sistema de aviso de acidentes. Como resultados do estudo empírico destacam-se a forte ligação da população ao mar, de caráter afetivo ou pela pretensão de utilização da praia, a desvalorização do risco costeiro, apesar do reconhecimento do recuo da linha de costa, a valorização das estruturas de defesa costeira, a escassa disponibilização de informação à população acerca do risco costeiro a que está exposta, e a importância atribuída à participação da população no processo de gestão territorial costeira. O sistema de informação geográfica foi validado para o caso da Praia de Esmoriz, permitindo identificar, por exemplo, para cada proprietário de habitação localizada em área de risco, a disponibilidade para participar no processo de gestão territorial costeira ou a abertura para aderir a um processo de relocalização da habitação. Face à pertinência do tema e à expectativa do mesmo ser considerado uma prioridade da política da atualidade, considera-se a necessidade de desenvolvimentos futuros de aprofundamento de conhecimentos em paralelo com uma aproximação ao sistema institucional de gestão territorial costeira, no sentido da minimização dos conflitos entre dinâmica costeira e uso do território e da prevenção do risco costeiro, particularmente risco de inundação e de erosão.

The assessment of the practicability of the SOCOPSE project

Dissertação de Mestrado, Gestão da Água e da Costa, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2010

Tourism planning informatization

The Tourism activity, due to its own characteristics, causes high environmental impact and its development should be influenced by the environmental characteristics of each region. The Information Systems, mainly those which represent the geographical information, will permit the development of a design, allowing the Decision-Maker the consult, the management and the presentation of decision schemes based on the defined measures of the Tourism Planning of a region. As the information associated with this design should be real and update, the Internet should be used as a means of access to the information of the region. The design presents the schemes associated to each decision, offering competitive advantages to the Decision-Makers involved in the decision process, since it is possible to evaluate, foresee and control the future environmental impacts of Tourism.

GIS on tourism planning: preventing the impacts caused by the developing tourism activity in a specific site

The environment is one of the greatest concerns of humankind. Nowadays, the activities which improve or destroy it must be assessed and controlled by efficient means which should permit the control of environmental impact caused by the development of these activities. This document presents an information system implementation, as a Decision Support system, allowing the Decision Maker to evaluate, foresee and control the future environmental impact of Tourism through consultation, the management and the presentation of decision schemes based on defined measures of a regional tourism planning.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.