The effect of resource aggregation at different scales: Optimal foraging behavior of Cotesia rubecula

Resources can be aggregated both within and between patches. In this article, we examine how aggregation at these different scales influences the behavior and performance of foragers. We developed an optimal foraging model of the foraging behavior of the parasitoid wasp Cotesia rubecula parasitizing the larvae of the cabbage butterfly Pieris rapae. The optimal behavior was found using stochastic dynamic programming. The most interesting and novel result is that the effect of resource aggregation within and between patches depends on the degree of aggregation both within and between patches as well as on the local host density in the occupied patch, but lifetime reproductive success depends only on aggregation within patches. Our findings have profound implications for the way in which we measure heterogeneity at different scales and model the response of organisms to spatial heterogeneity.

Dynamic load balancing for the distributed mining of molecular structures

In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable for large-scale, multi-domain, heterogeneous environments, such as computational grids.

Decentralized load balancing for highly irregular search problems

In this paper, we present a distributed computing framework for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available. The framework is based on a peer-to-peer computing environment and dynamic load balancing. The system allows for dynamic resource aggregation, does not depend on any specific meta-computing middleware and is suitable for large-scale, multi-domain, heterogeneous environments, such as computational Grids. Dynamic load balancing policies based on global statistics are known to provide optimal load balancing performance, while randomized techniques provide high scalability. The proposed method combines both advantages and adopts distributed job-pools and a randomized polling technique. The framework has been successfully adopted in a parallel search algorithm for subgraph mining and evaluated on a molecular compounds dataset. The parallel application has shown good calability and close-to linear speedup in a distributed network of workstations.

Efficient mining of discriminative molecular fragments

Frequent pattern discovery in structured data is receiving an increasing attention in many application areas of sciences. However, the computational complexity and the large amount of data to be explored often make the sequential algorithms unsuitable. In this context high performance distributed computing becomes a very interesting and promising approach. In this paper we present a parallel formulation of the frequent subgraph mining problem to discover interesting patterns in molecular compounds. The application is characterized by a highly irregular tree-structured computation. No estimation is available for task workloads, which show a power-law distribution in a wide range. The proposed approach allows dynamic resource aggregation and provides fault and latency tolerance. These features make the distributed application suitable for multi-domain heterogeneous environments, such as computational Grids. The distributed application has been evaluated on the well known National Cancer Institute’s HIV-screening dataset.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

Differential species-specific ectoparasitic mite intensities in two intimately coexisting sibling bat species: resource-mediated host attractiveness or parasite specialization?

1. The mechanisms underlying host choice strategies by parasites remain poorly understood. We address two main questions: (i) do parasites prefer vulnerable or well-fed hosts, and (ii) to what extent is a parasite species specialized towards a given host species? 2. To answer these questions, we investigated, both in the field and in the lab, a host-parasite system comprising one ectoparasitic mite (Spinturnix myoti) and its major hosts, two sibling species of bats (Myotis myotis and M blythii), which coexist intimately in colonial nursery roosts. We exploited the close physical associations between host species in colonial roosts as well as naturally occurring annual variation in food abundance to investigate the relationships between parasite intensities and (i) host species and (ii) individual nutritional status. 3. Although horizontal transmission of parasites was facilitated by the intimate aggregation of bats within their colonial clusters, we found significant interspecific differences in degree of infestation throughout the 6 years of the study, with M. myotis always more heavily parasitized than M. blythii. This pattern was replicated in a laboratory experiment in which any species-specific resistance induced by exploitation of different trophic niches in nature was removed. 4. Within both host species, S. myoti showed a clear preference for individuals with higher nutritional status. In years with high resource abundance, both bat hosts harboured more parasites than in low-resource years, although the relative difference in parasite burden across species was maintained. This pattern of host choice was also replicated in the laboratory. When offered a choice, parasites always colonized better-fed individuals. 5. These results show first that host specialization in our study system occurred. Second, immediate parasite choice clearly operated towards the selection of hosts in good nutritional state.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

Data-driven fuzzy analysis in quantitative mineral resource assessment

The integration of geo-information from multiple sources and of diverse nature in developing mineral favourability indexes (MFIs) is a well-known problem in mineral exploration and mineral resource assessment. Fuzzy set theory provides a convenient framework to combine and analyse qualitative and quantitative data independently of their source or characteristics. A novel, data-driven formulation for calculating MFIs based on fuzzy analysis is developed in this paper. Different geo-variables are considered fuzzy sets and their appropriate membership functions are defined and modelled. A new weighted average-type aggregation operator is then introduced to generate a new fuzzy set representing mineral favourability. The membership grades of the new fuzzy set are considered as the MFI. The weights for the aggregation operation combine the individual membership functions of the geo-variables, and are derived using information from training areas and L, regression. The technique is demonstrated in a case study of skarn tin deposits and is used to integrate geological, geochemical and magnetic data. The study area covers a total of 22.5 km(2) and is divided into 349 cells, which include nine control cells. Nine geo-variables are considered in this study. Depending on the nature of the various geo-variables, four different types of membership functions are used to model the fuzzy membership of the geo-variables involved. (C) 2002 Elsevier Science Ltd. All rights reserved.

An Integrated Framework To Improve The Concept Of Resource Specialisation.

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.

Infertility Care And The Introduction Of New Reproductive Technologies In Poor Resource Settings.

The overall prevalence of infertility was estimated to be 3.5-16.7% in developing countries and 6.9-9.3% in developed countries. Furthermore, according to reports from some regions of sub-Saharan Africa, the prevalence rate is 30-40%. The consequences of infertility and how it affects the lives of women in poor-resource settings, particularly in developing countries, has become an important issue to be discussed in reproductive health. In some societies, the inability to fulfill the desire to have children makes life difficult for the infertile couple. In many regions, infertility is considered a tragedy that affects not only the infertile couple or woman, but the entire family. This is a position paper which encompasses a review of the needs of low-income infertile couples, mainly those living in developing countries, regarding access to infertility care, including ART and initiatives to provide ART at low or affordable cost. Information was gathered from the databases MEDLINE, CENTRAL, POPLINE, EMBASE, LILACS, and ICTRP with the key words: infertility, low income, assisted reproductive technologies, affordable cost, low cost. There are few initiatives geared toward implementing ART procedures at low cost or at least at affordable cost in low-income populations. Nevertheless, from recent studies, possibilities have emerged for new low-cost initiatives that can help millions of couples to achieve the desire of having a biological child. It is necessary for healthcare professionals and policymakers to take into account these new initiatives in order to implement ART in resource-constrained settings.

Fluorescence, Aggregation Properties And Ft-ir Microspectroscopy Of Elastin And Collagen Fibers.

Histological and histochemical observations support the hypothesis that collagen fibers can link to elastic fibers. However, the resulting organization of elastin and collagen type complexes and differences between these materials in terms of macromolecular orientation and frequencies of their chemical vibrational groups have not yet been solved. This study aimed to investigate the macromolecular organization of pure elastin, collagen type I and elastin-collagen complexes using polarized light DIC-microscopy. Additionally, differences and similarities between pure elastin and collagen bundles (CB) were investigated by Fourier transform-infrared (FT-IR) microspectroscopy. Although elastin exhibited a faint birefringence, the elastin-collagen complex aggregates formed in solution exhibited a deep birefringence and formation of an ordered-supramolecular complex typical of collagen chiral structure. The FT-IR study revealed elastin and CB peptide NH groups involved in different types of H-bonding. More energy is absorbed in the vibrational transitions corresponding to CH, CH2 and CH3 groups (probably associated with the hydrophobicity demonstrated by 8-anilino-1-naphtalene sulfonic acid sodium salt [ANS] fluorescence), and to νCN, δNH and ωCH2 groups of elastin compared to CB. It is assumed that the α-helix contribution to the pure elastin amide I profile is 46.8%, whereas that of the B-sheet is 20% and that unordered structures contribute to the remaining percentage. An FT-IR profile library reveals that the elastin signature within the 1360-1189cm(-1) spectral range resembles that of Conex-Toray aramid fibers.

Metallochlorophylls of magnesium, copper and zinc: evaluation of the influence of the first coordination sphere on their solvatochromism and aggregation properties

In this study the role of different metal centers (magnesium, zinc and copper) on the enhancement of the hydrophilic character of metallochlorophylls, was evaluated. The solvatochromism as well as the aggregation process for these compounds in water/ethanol mixtures at different volume ratios were evaluated using Fluorescence, and Resonant Light Scattering (RLS) measurements, aiming to characterize the behavior of these compounds. Independently on the studied metallochlorophyll, the presence of at least 60% of water results in a considerable increase in the fluorescence emission, probably a direct consequence of a lower aggregation of these compounds, which is confirmed by the results from RLS measurements. Additionally, the results suggest that magnesium and zinc chlorophyll should be promising phototherapeutic agents for Photodynamic Therapy.

State-of-the-Art and Future Directions for Green Human Resource Management: Introduction to the Special Issue

The topic of environmental sustainability is generating increased concern among business executives, governments, consumers, and management scholars. As these stakeholders struggle with the challenges and opportunities presented by an array of environmental issues, HRM scholars and practitioners alike have been relatively slow to engage in the ongoing discussions and debates. Through this special issue on Green FIRM, we seek to stimulate the field of HRM to expand its role in the pursuit of environmentally sustainable business. In this introduction to the special issue, we first provide an overview of the articles that appear in the special issue. Next we present a detailed discussion of research questions that arise from a consideration of several functional HRM practices, including performance management; training, development, and learning; compensation and rewards; and organizational culture. We conclude by describing opportunities for research at the intersection of strategic HRM and environmental management. If pursued with vigor, research addressing this extensive agenda could begin to establish a healthy field of Green FIRM scholarship.

Developmental Potential of Bovine Hand-Made Clone Embryos Reconstructed by Aggregation or Fusion with Distinct Cytoplasmic Volumes

Animal cloning has been associated with developmental abnormalities, with the level of heteroplasmy caused by the procedure being one of its potential limiting factors. The aim of this study was to determine the effect of the fusion of hemicytoplasts or aggregation of hemiembryos, varying the final cytoplasmic volume, on development and cell density of embryos produced by hand-made cloning (HMC), parthenogenesis or by in vitro fertilization (IVF). One or two enucleated hemicytoplasts were paired and fused with one skin somatic cell. Activated clone and zona-free parthenote embryos and hemiembryos were in vitro cultured in the well-of-the-well (WOW) system, being allocated to one of six experimental groups, on a per WOW basis: single clone or parthenote hemiembryos (1 x 50%); aggregation of two (2 x 50%), three (3 x 50%), or four (4 x 50%) clone or parthenote hemiembryos; single clone or parthenote embryos (1 x 100%); or aggregation of two clone or parthenote embryos (2 x 100%). Control zona-intact parthenote or IVF embryos were in vitro cultured in four-well dishes. Results indicated that the increase in the number of aggregated structures within each WOW was followed by a linear increase in cleavage, blastocyst rate, and cell density. The increase in cytoplasmic volume, either by fusion or by aggregation, had a positive effect on embryo development, supporting the establishment of pregnancies and the birth of a viable clone calf after transfer to recipients. However, embryo aggregation did not improve development on a hemicytoplast basis, except for the aggregation of two clone embryos.

Merging Resource Availability with Isotope Mixing Models: The Role of Neutral Interaction Assumptions

Background: Bayesian mixing models have allowed for the inclusion of uncertainty and prior information in the analysis of trophic interactions using stable isotopes. Formulating prior distributions is relatively straightforward when incorporating dietary data. However, the use of data that are related, but not directly proportional, to diet (such as prey availability data) is often problematic because such information is not necessarily predictive of diet, and the information required to build a reliable prior distribution for all prey species is often unavailable. Omitting prey availability data impacts the estimation of a predator's diet and introduces the strong assumption of consumer ultrageneralism (where all prey are consumed in equal proportions), particularly when multiple prey have similar isotope values. Methodology: We develop a procedure to incorporate prey availability data into Bayesian mixing models conditional on the similarity of isotope values between two prey. If a pair of prey have similar isotope values (resulting in highly uncertain mixing model results), our model increases the weight of availability data in estimating the contribution of prey to a predator's diet. We test the utility of this method in an intertidal community against independently measured feeding rates. Conclusions: Our results indicate that our weighting procedure increases the accuracy by which consumer diets can be inferred in situations where multiple prey have similar isotope values. This suggests that the exchange of formalism for predictive power is merited, particularly when the relationship between prey availability and a predator's diet cannot be assumed for all species in a system.