Penalty-free feasibility boundary convergent multi-objective evolutionary algorithm for the optimization of water distribution systems

This paper presents a new penalty-free multi-objective evolutionary approach (PFMOEA) for the optimization of water distribution systems (WDSs). The proposed approach utilizes pressure dependent analysis (PDA) to develop a multi-objective evolutionary search. PDA is able to simulate both normal and pressure deficient networks and provides the means to accurately and rapidly identify the feasible region of the solution space, effectively locating global or near global optimal solutions along its active constraint boundary. The significant advantage of this method over previous methods is that it eliminates the need for ad-hoc penalty functions, additional “boundary search” parameters, or special constraint handling procedures. Conceptually, the approach is downright straightforward and probably the simplest hitherto. The PFMOEA has been applied to several WDS benchmarks and its performance examined. It is demonstrated that the approach is highly robust and efficient in locating optimal solutions. Superior results in terms of the initial network construction cost and number of hydraulic simulations required were obtained. The improvements are demonstrated through comparisons with previously published solutions from the literature

Exploration of the rotational power consumption of a rigid flapping wing

Accepted versio

Informational entropy : a failure tolerance and reliability surrogate for water distribution networks

Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies

Major agricultural changes required to mitigate phosphorus losses under climate change

Phosphorus losses from land to water will be impacted by climate change and land management for food production, with detrimental impacts on aquatic ecosystems. Here we use a unique combination of methods to evaluate the impact of projected climate change on future phosphorus transfers, and to assess what scale of agricultural change would be needed to mitigate these transfers. We combine novel high-frequency phosphorus flux data from three representative catchments across the UK, a new high-spatial resolution climate model, uncertainty estimates from an ensemble of future climate simulations, two phosphorus transfer models of contrasting complexity and a simplified representation of the potential intensification of agriculture based on expert elicitation from land managers. We show that the effect of climate change on average winter phosphorus loads (predicted increase up to 30% by 2050s) will be limited only by large-scale agricultural changes (e.g., 20–80% reduction in phosphorus inputs)

Moving carbon between spheres, the potential oxalate-carbonate pathway of Brosimum alicastrum Sw.; Moraceae.

Aims The Oxalate-Carbonate Pathway (OCP) is a biogeochemical process that transfers atmospheric CO2 into the geologic reservoir as CaCO3; however, until now all investigations on this process have focused on species with limited food benefits. This study evaluates a potential OCP associated with Brosimum alicastrum, a Neotropical species with agroforestry potential (ca. 70–200 kg-nuts yr−1), in the calcareous soils of Haiti and Mexico. Methods / results Enzymatic analysis demonstrated significant concentrations of calcium oxalate (5.97 % D.W.) were associated with B. alicastrum tissue in all sample sites. The presence of oxalotrophism was also confirmed with microbiological analyses in both countries. High concentrations of total calcium (>7 g kg−1) and lithogenic carbonate obscured the localised alkalinisation and identification of secondary carbonate associated with the OCP at most sample sites, except Ma Rouge, Haiti. Soils adjacent to subjects in Ma Rouge demonstrated an increase in pH (0.63) and CaCO3 concentration (5.9 %) that, when coupled with root-like secondary carbonate deposits in Mexico, implies that the OCP does also occur in calcareous soils. Conclusions Therefore this study confirms that the OCP also occurs in calcareous soils, adjacent to B. alicastrum, and could play a fundamental and un-accounted role in the global calcium-carbon coupled cycle

Challenge clusters facing LCA in environmental decision-making—what we can learn from biofuels

Purpose Bioenergy is increasingly used to help meet greenhouse gas (GHG) and renewable energy targets. However, bioenergy’s sustainability has been questioned, resulting in increasing use of life cycle assessment (LCA). Bioenergy systems are global and complex, and market forces can result in significant changes, relevant to LCA and policy. The goal of this paper is to illustrate the complexities associated with LCA, with particular focus on bioenergy and associated policy development, so that its use can more effectively inform policymakers. Methods The review is based on the results from a series of workshops focused on bioenergy life cycle assessment. Expert submissions were compiled and categorized within the first two workshops. Over 100 issues emerged. Accounting for redundancies and close similarities in the list, this reduced to around 60 challenges, many of which are deeply interrelated. Some of these issues were then explored further at a policyfacing workshop in London, UK. The authors applied a rigorous approach to categorize the challenges identified to be at the intersection of biofuels/bioenergy LCA and policy. Results and discussion The credibility of LCA is core to its use in policy. Even LCAs that comply with ISO standards and policy and regulatory instruments leave a great deal of scope for interpretation and flexibility. Within the bioenergy sector, this has led to frustration and at times a lack of obvious direction. This paper identifies the main challenge clusters: overarching issues, application and practice and value and ethical judgments. Many of these are reflective of the transition from application of LCA to assess individual products or systems to the wider approach that is becoming more common. Uncertainty in impact assessment strongly influences planning and compliance due to challenges in assigning accountability, and communicating the inherent complexity and uncertainty within bioenergy is becoming of greater importance. Conclusions The emergence of LCA in bioenergy governance is particularly significant because other sectors are likely to transition to similar governance models. LCA is being stretched to accommodate complex and broad policy-relevant questions, seeking to incorporate externalities that have major implications for long-term sustainability. As policy increasingly relies on LCA, the strains placed on the methodology are becoming both clearer and impedimentary. The implications for energy policy, and in particular bioenergy, are large

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods

Challenges Using Extrapolated Family-level Macroinvertebrate Metrics in Moderately Disturbed Tropical Streams: a Case-study From Belize

Family-level biotic metrics were originally designed to rapidly assess gross organic pollution effects, but came to be regarded as general measures of stream degradation. Improvements in water quality in developed countries have reignited debate about the limitations of family-level taxonomy to detect subtle change, and is resulting in a shift back towards generic and species-level analysis to assess smaller effects. Although the scale of pollution characterizing past condition of streams in developed countries persists in many developing regions, some areas are still considered to be only moderately disturbed. We sampled streams in Belize to investigate the ability of family-level macroinvertebrate metrics to detect change in stream catchments where less than 30% of forest had been cleared. Where disturbance did not co-vary with natural gradients of change, and in areas characterized by low intensity activities, none of the metrics tested detected significant change, despite evidence of environmental impacts. We highlight the need for further research to clarify the response of metrics to disturbance over a broader study area that allows replication for confounding sources of natural variation. We also recommend research to develop more detailed understanding of the taxonomy and ecology of Neotropical macroinvertebrates to improve the robustness of metric use

Heparan sulfate proteoglycans: structure, protein interactions and cell signaling

Heparan sulfate proteoglycans are ubiquitously found at the cell surface and extracellular matrix in all the animal species. This review will focus on the structural characteristics of the heparan sulfate proteoglycans related to protein interactions leading to cell signaling. The heparan sulfate chains due to their vast structural diversity are able to bind and interact with a wide variety of proteins, such as growth factors, chemokines, morphogens, extracellular matrix components, enzymes, among others. There is a specificity directing the interactions of heparan sulfates and target proteins, regarding both the fine structure of the polysaccharide chain as well precise protein motifs. Heparan sulfates play a role in cellular signaling either as receptor or co-receptor for different ligands, and the activation of downstream pathways is related to phosphorylation of different cytosolic proteins either directly or involving cytoskeleton interactions leading to gene regulation. The role of the heparan sulfate proteoglycans in cellular signaling and endocytic uptake pathways is also discussed.Proteoglicanos de heparam sulfato são encontrados tanto superfície celular quanto na matriz extracelular em todas as espécies animais. Esta revisão tem enfoque nas características estruturais dos proteoglicanos de heparam sulfato e nas interações destes proteoglicanos com proteínas que levam à sinalização celular. As cadeias de heparam sulfato, devido a sua variedade estrutural, são capazes de se ligar e interagir com ampla gama de proteínas, como fatores de crescimento, quimiocinas, morfógenos, componentes da matriz extracelular, enzimas, entreoutros. Existe uma especificidade estrutural que direciona as interações dos heparam sulfatos e proteínas alvo. Esta especificidade está relacionada com a estrutura da cadeia do polissacarídeo e os motivos conservados da cadeia polipeptídica das proteínas envolvidas nesta interação. Os heparam sulfatos possuem papel na sinalização celular como receptores ou coreceptores para diferentes ligantes. Esta ligação dispara vias de sinalização celular levam à fosforilação de diversas proteínas citosólicas ou com ou sem interações diretas com o citoesqueleto, culminando na regulação gênica. O papel dos proteoglicanos de heparam sulfato na sinalização celular e vias de captação endocítica também são discutidas nesta revisão.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Federal de São Paulo (UNIFESP) Departamento de BioquímicaUniversidade Federal de São Paulo (UNIFESP) Departamento de OftalmologiaUNIFESP, Depto. de BioquímicaUNIFESP, Depto. de OftalmologiaSciEL

Single-cell analysis tools for drug discovery and development

The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed