A Research Agenda for Helminth Diseases of Humans: Basic Research and Enabling Technologies to Support Control and Elimination of Helminthiases

Successful and sustainable intervention against human helminthiases depends on optimal utilisation of available control measures and development of new tools and strategies, as well as an understanding of the evolutionary implications of prolonged intervention on parasite populations and those of their hosts and vectors. This will depend largely on updated knowledge of relevant and fundamental parasite biology. There is a need, therefore, to exploit and apply new knowledge and techniques in order to make significant and novel gains in combating helminthiases and supporting the sustainability of current and successful mass drug administration (MDA) programmes. Among the fields of basic research that are likely to yield improved control tools, the Disease Reference Group on Helminth Infections (DRG4) has identified four broad areas that stand out as central to the development of the next generation of helminth control measures: 1) parasite genetics, genomics, and functional genomics; 2) parasite immunology; 3) (vertebrate) host–parasite interactions and immunopathology; and 4) (invertebrate) host–parasite interactions and transmission biology. The DRG4 was established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR). The Group was given the mandate to undertake a comprehensive review of recent advances in helminthiases research in order to identify notable gaps and highlight priority areas. This paper summarises recent advances and discusses challenges in the investigation of the fundamental biology of those helminth parasites under the DRG4 Group's remit according to the identified priorities, and presents a research and development agenda for basic parasite research and enabling technologies that will help support control and elimination efforts against human helminthiases

A Hybrid Multicriteria 0/1 Programming Methodology for Prioritizing the Measures of River Basin Management Plans

The Programmes of Measures (PoMs) are included in the River Basin Management Plans (RBMPs). They comprise the outputs on the analysis of pressures, impacts and status of the water bodies, by designating those actions that need to be employed for the amelioration of the water quality status. In this research a methodology based on the coupling of hybrid multicriteria methods, namely outranking, in which 6 criteria and 37 alternatives are integrated, with a 0/1 linear programming in which the cost of the measures is induced as a constraint, is proposed for the prioritization of the supplementary PoMs that are included in the RBMP of Central Macedonia, Greece. The results of the research demonstrated the usefulness of the methodology when financial constraints do not permit the implementation of the whole set of measures

Hybrid Fuzzy—Probabilistic Analysis and Classification of the Hydrological Drought

The consideration of a theoretical probability distribution regarding the annual cumulative discharge will provide a significant opportunity to characterize the intensity of the hydrological drought. However, the matching between the observed probabilities and the adopted theoretical probability distribution can not be identical. Hence, in this work this matching is achieved by using a fuzzy regression based methodology and the attributes of the log-normal distribution. Finally, an ascending procedure to classify the intensity of hydrological drought is proposed and it is applied in case of the Evros River

Applying a Flexible Fuzzy Adaptive Regression to Runoff Estimation

A smart, flexible, fuzzy-based regression is proposed in order to describe non-constant behavior of runoff as a function of precipitation. Hence, for high precipitation, beyond a fuzzy threshold, a conventional linear (precise) relation between precipitation and runoff is established, while for low precipitation, a curve with different behavior is activated. Between these curves and for a runoff range, each curve holds to some degree. Hence, a simplified Sugeno architecture scheme is established on few logical rules. Alternatively, the model can be enhanced by using a combination between the fuzzy linear regression of Tanaka and the aforementioned simplified Sugeno architecture. The training process is achieved based on the Particle Swarm Optimization (PSO) method

A Hybrid Multicriteria 0/1 Programming Methodology for Prioritizing the Measures of River Basin Management Plans

The Programmes of Measures (PoMs) are included in the River Basin Management Plans (RBMPs). They comprise the outputs on the analysis of pressures, impacts and status of the water bodies, by designating those actions that need to be employed for the amelioration of the water quality status. In this research a methodology based on the coupling of hybrid multicriteria methods, namely outranking, in which 6 criteria and 37 alternatives are integrated, with a 0/1 linear programming in which the cost of the measures is induced as a constraint, is proposed for the prioritization of the supplementary PoMs that are included in the RBMP of Central Macedonia, Greece. The results of the research demonstrated the usefulness of the methodology when financial constraints do not permit the implementation of the whole set of measures

Estimation of Fuzzy Parameters in the Linear Muskingum Model with the Aid of Particle Swarm Optimization

The Muskingum method is one of the widely used methods for lumped flood routing in natural rivers. Calibration of its parameters remains an active challenge for the researchers. The task has been mostly addressed by using crisp numbers, but fuzzy seems a reasonable alternative to account for parameter uncertainty. In this work, a fuzzy Muskingum model is proposed where the assessment of the outflow as a fuzzy quantity is based on the crisp linear Muskingum method but with fuzzy parameters as inputs. This calculation can be achieved based on the extension principle of the fuzzy sets and logic. The critical point is the calibration of the proposed fuzzy extension of the Muskingum method. Due to complexity of the model, the particle swarm optimization (PSO) method is used to enable the use of a simulation process for each possible solution that composes the swarm. A weighted sum of several performance criteria is used as the fitness function of the PSO. The function accounts for the inclusive constraints (the property that the data must be included within the produced fuzzy band) and for the magnitude of the fuzzy band, since large uncertainty may render the model non-functional. Four case studies from the references are used to benchmark the proposed method, including smooth, double, and non-smooth data and a complex, real case study that shows the advantages of the approach. The use of fuzzy parameters is closer to the uncertain nature of the problem. The new methodology increases the reliability of the prediction. Furthermore, the produced fuzzy band can include, to a significant degree, the observed data and the output of the existent crisp methodologies even if they include more complex assumptions

Threat Prioritization and Causality Relations for Sustainable Water Management under the Circular Economy Principles: Case Study in Laspias River, Greece Using eDPSIR and DEMATEL

The Circular Economy set a frame to govern sustainable growth. Laspias river basin (Thrace) is characterized by various land and water uses and pressures posed directly and/or indirectly on the riverine system which acts as a burdened receptor. The aim is to prioritize threats in the basin and to further recognize the causality relationships in main elements affecting water management parameters that fall upon circular economy using enhanced DPSIR, Decision Making Trial and Evaluation Laboratory (DEMATEL) techniques. To assess the status quo, circular economy principles were adopted using a sustainable water management perspective embedded in DPSIR to link the causes and effects components. The key criteria based on the cause-factors were mined simplifying the multicriteria analysis of the effects. Findings highlight the multiplicity of pressures and origin of the impacts. This method proved as a valuable tool to track threats prior to stakeholder mapping for participatory management

Hybrid Fuzzy—Probabilistic Analysis and Classification of the Hydrological Drought

The consideration of a theoretical probability distribution regarding the annual cumulative discharge will provide a significant opportunity to characterize the intensity of the hydrological drought. However, the matching between the observed probabilities and the adopted theoretical probability distribution can not be identical. Hence, in this work this matching is achieved by using a fuzzy regression based methodology and the attributes of the log-normal distribution. Finally, an ascending procedure to classify the intensity of hydrological drought is proposed and it is applied in case of the Evros River

Relating Hydro-Meteorological Variables to Water Table in an Unconfined Aquifer via Fuzzy Linear Regression

This study aims to assess the short-term response of groundwater to the main hydro-meteorological variables of drought in a coastal unconfined aquifer. For this purpose, a multiple fuzzy linear regression-based methodology is implemented in order to relate rainfall, streamflow and the potential evapotranspiration to groundwater. Fuzzy regression analysis is recommended when there is a lack of data. The uncertainty of the system is incorporated into the regression coefficients which, in this study, are considered to be fuzzy symmetrical triangular numbers. Two objective functions are used producing a fuzzy band in which all the observed data must be included. The first objective function, based on Tanaka’s model, minimizes the total width of the produced fuzzy band. The second one includes the first while additionally minimizing the distance between the central value of the fuzzy output of the model and the observed value. Validity of the model is checked through suitability measures. The present methodology is applied at the east part of the Nestos River Delta in the Prefecture of Xanthi (Greece), where the observed values of the depth of groundwater level of four wells are examined