A development and integration framework for optimisation-based enterprise solutions

The operations research literature includes some papers describing collaborative work between researchers and industry. However, not much literature exists that outlines methodologies to guide the development of a decision support module and its integration into an existing information management system. Here we describe a framework to aid the collaborative development of an optimisation solution by researchers and information system developers. The proposed framework also helps in the effective integration of the information management system and the decision support module. The framework is divided into three main components: a data model, a data extractor and validator, and a solution visualisation and auxiliary platform. We also describe our experience and positive results from applying the proposed development and integration framework to a project involving the development on an optimisation-based solution for workforce scheduling and optimisation problems. We hope that this contribution would be particularly useful for less experienced researchers and practitioners who embark on a collaborative development of a decision support module based on optimisation techniques

A development and integration framework for optimisation-based enterprise solutions

The operations research literature includes some papers describing collaborative work between researchers and industry. However, not much literature exists that outlines methodologies to guide the development of a decision support module and its integration into an existing information management system. Here we describe a framework to aid the collaborative development of an optimisation solution by researchers and information system developers. The proposed framework also helps in the effective integration of the information management system and the decision support module. The framework is divided into three main components: a data model, a data extractor and validator, and a solution visualisation and auxiliary platform. We also describe our experience and positive results from applying the proposed development and integration framework to a project involving the development on an optimisation-based solution for workforce scheduling and optimisation problems. We hope that this contribution would be particularly useful for less experienced researchers and practitioners who embark on a collaborative development of a decision support module based on optimisation techniques

The role of the disorder range and electronic energy in the graphene nanoribbons perfect transmission

Numerical calculations based on the recursive Green's functions method in the tight-binding approximation are performed to calculate the dimensionless conductance $g$ in disordered graphene nanoribbons with Gaussian scatterers. The influence of the transition from short- to long-ranged disorder on $g$ is studied as well as its effects on the formation of a perfectly conducting channel. We also investigate the dependence of electronic energy on the perfectly conducting channel. We propose and calculate a backscattering estimative in order to establish the connection between the perfectly conducting channel (with $g=1$) and the amount of intervalley scattering.Comment: 7 pages, 9 figures. To be published on Phys. Rev.

A Hidden Complication of Pigtail Catheter Insertion

Pigtail catheters have emerged as an effective and less morbid alternative to traditional chest tubes for evacuation of pleural air. Rare complications in the literature have been reported. We report a case of a 92-year-old male who presented with dyspnea and shock, noted to have a pneumothorax requiring tube thoracostomy. Computed tomography demonstrated pigtail within the lung parenchyma. We discuss the implications of this occurrence

Analysis of objectives relationships in multiobjective problems using trade-off region maps

Understanding the relationships between objectives in many-objective optimisation problems is desirable in order to develop more effective algorithms. We propose a techniquefor the analysis and visualisation of complex relationships between many (three or more) objectives. This technique looks at conflicting, harmonious and independent objectives relationships from different perspectives. To do that, it uses correlation, trade-off regions maps and scatter-plots in a four step approach. We apply the proposed technique to a set of instances of the well-known multiobjective multidimensional knapsack problem. The experimental results show that with the proposed technique we can identify local and complex relationships between objectives, trade-offs not derived from pairwise relationships, gaps in the fitness landscape, and regions of interest. Such information can be used to tailor the development of algorithms

Using goal programming on estimated Pareto fronts to solve multiobjective problems

Modern multiobjective algorithms can be computationally inefficient in producing good approximation sets for highly constrained many-objective problems. Such problems are common in real-world applications where decision-makers need to assess multiple conflicting objectives. Also, different instances of real-world problems often share similar fitness landscapes because key parts of the data are the same across these instances. We we propose a novel methodology that consists of solving one instance of a given problem scenario using computationally expensive multiobjective algorithms to obtain a good approximation set and then using Goal Programming with efficient single-objective algorithms to solve other instances of the same problem scenario. We propose three goal-based objective functions and show that on a real-world home healthcare planning problem the methodology can produce improved results in a shorter computation time

Food Insecurity and the Behavioral and Intellectual Development of Children: A Review of the Evidence

Background: Given that an alarming 1 in 5 children in the USA are at risk of hunger (1 in 3 among black and Latino children), and that 3.9 million households with children are food insecure, it is crucial to understand how household food insecurity (HFI) affects the present and future well-being of our children. Purpose: The objectives of this review article are to: (i) examine the association between HFI and child intellectual, behavioral and psycho-emotional development, controlling for socio-economic indicators; (ii) review the hypothesis that HFI is indeed a mediator of the relationship between poverty and poor child development outcomes; (iii) examine if the potential impact of HFI on caregivers’ mental health well-being mediates the relationship between HFI and child development outcomes. Methods: Pubmed search using the key words “food insecurity children.” For articles to be included they had to: (i) be based on studies measuring HFI using an experience-based scale, (ii) be peer reviewed, and (iii) include child intellectual, behavioral and/or socio-emotional development outcomes. Studies were also selected based on backward and forward Pubmed searches, and from the authors’ files. After reviewing the abstracts based on inclusion criteria a total of 26 studies were selected. Results: HFI represents not only a biological but also a psycho-emotional and developmental challenge to children exposed to it. Children exposed to HFI are more likely to internalize or externalize problems, as compared to children not exposed to HFI. This in turn is likely to translate into poor academic/cognitive performance and intellectual achievement later on in life. A pathway through which HFI may affect child development is possibly mediated by caregivers’ mental health status, especially parental stress and depression. Thus, HFI is likely to foster dysfunctional family environments. Conclusion: Findings indicate that food insecure households may require continued food assistance and psycho-emotional support until they transition to a “stable” food secure situation. This approach will require a much better integration of social policies and access to programs offering food assistance and mental health services to those in need. Findings also fully justify increased access of vulnerable children to programs that promote early in life improved nutrition as well as early psycho-social and cognitive stimulation opportunities

Towards an efficient API for optimisation problems data

The literature presents many application programming interfaces (APIs) and frameworks that provide state of the art algorithms and techniques for solving optimisation problems. The same cannot be said about APIs and frameworks focused on the problem data itself because with the peculiarities and details of each variant of a problem, it is virtually impossible to provide general tools that are broad enough to be useful on a large scale. However, there are benefits of employing problem-centred APIs in a R&D environment: improving the understanding of the problem, providing fairness on the results comparison, providing efficient data structures for different solving techniques, etc. Therefore, in this work we propose a novel design methodology for an API focused on an optimisation problem. Our methodology relies on a data parser to handle the problem specification files and on a set of efficient data structures to handle the information on memory, in an intuitive fashion for researchers and efficient for the solving algorithms. Also, we present the concepts of a solution dispenser that can manage solutions objects in memory better than built-in garbage collectors. Finally, we describe the positive results of employing a tailored API to a project involving the development of optimisation solutions for workforce scheduling and routing problems

An evolutionary algorithm for graph planarisation by vertex deletion

A non-planar graph can only be planarised if it is structurally modified. This work presents a new heuristic algorithm that uses vertices deletion to modify a non-planar graph in order to obtain a planar subgraph. The proposed algorithm aims to delete a minimum number of vertices to achieve its goal. The vertex deletion number of a graph G = (V,E) is the smallest integer k ? 0 such that there is an induced planar subgraph of G obtained by the removal of k vertices of G. Considering that the corresponding decision problem is NPcomplete and an approximation algorithm for graph planarisation by vertices deletion does not exist, this work proposes an evolutionary algorithm that uses a constructive heuristic algorithm to planarise a graph. This constructive heuristic has time complexity of O(n+m), where m = |V| and n = |E|, and it is based on the PQ-trees data structure and on the vertex deletion operation. The algorithm performance is verified by means of case studies

Bovine Papillomavirus Clastogenic Effect Analyzed in Comet Assay

Bovine papillomavirus (BPV) is an oncogenic virus related to serious livestock diseases. Oncoproteins encoded by BPV are involved in several steps of cellular transformation and have been reported as presenting clastogenic effects in peripheral lymphocytes and primary culture cells. the aim of this study was to evaluate the clastogenic potential of BPV types 1, 2, and 4 by comet assay. Peripheral blood was collected from 37 bovines, 32 infected with different levels of papillomatosis (12 animals have no affection) and five calves, virus free (negative control). the viral identification showed presence of more than one virus type in 59.375% of the infected animals. Comet assay was performed according to alkaline technique. the Kruskal-Wallis test showed statistical difference between the negative control group and infected animals (P = 0.0015). the Dunn post hoc test showed difference comparing the infected animals with calves. Mann-Whitney U test verified no difference between animals infected with only one viral type and animals presenting more than one viral type. the comet assay is considered an efficient tool for assessment of damage in the host chromatin due to viral action, specifically highlighting viral activity in blood cells.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundacao do Desenvolvimento Administrativo (PAP-FUNDAP)Inst Butantan, Genet Lab, BR-05503900 São Paulo, BrazilUniv São Paulo, Inst Ciencias Biomed, Programa Posgrad Interunidades Biotecnol, BR-05508900 São Paulo, BrazilUniversidade Federal de São Paulo, Programa Posgrad Biol Estrutural & Func, BR-04023900 São Paulo, BrazilUniv Fed Integracao Latinoamer UNILA, Dept Biol, BR-85867970 Foz Do Iguacu, PR, BrazilUniversidade Federal de São Paulo, Programa Posgrad Biol Estrutural & Func, BR-04023900 São Paulo, BrazilCNPq: 402539/2011-7Web of Scienc