An engineering approach to modelling, decision support and control for sustainable systems

Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems.     

The Framework for 21st Century Learning: A first-rate foundation for music education assessment and teacher evaluation

Federal laws and funding initiatives, such as the No Child Left Behind Act and the Race to the Top campaign, have created an increasing incentive for schools nationwide to document student progress, standardize assessment practices, and evaluate teachers according to student success. In response, the Common Core State Standards, a popular yet controversial policy, has emerged. Implemented at the state level, these standards focus heavily on the areas of English language arts and mathematics, subjects not traditionally incorporated to a great extent in music classrooms. In order for music to maintain a role as an essential subject in the school curriculum, it is imperative that music educators be able to associate themselves with a complementary initiative that allows them to demonstrate how students are meeting benchmarks required at the state and national levels without sacrificing the integrity of music instruction itself. Of the existing models available, the Framework for 21st Century Learning provides the most appropriate structure for determining music teacher effectiveness and for organizing learning objectives that can be assessed to show student growth in music education classrooms.     

Decision science for effective management of populations subject to stochasticity and imperfect knowledge

Many species are threatened by human activity through processes such as habitat modification, water management, hunting, and introduction of invasive species. These anthropogenic threats must be mitigated as efficiently as possible because both time and money available for mitigation are limited. For example, it is essential to address the type and degree of uncertainties present to derive effective management strategies for managed populations. Decision science provides the tools required to produce effective management strategies that can maximize or minimize the desired objective(s) based on imperfect knowledge, taking into account stochasticity. Of particular importance are questions such as how much of available budgets should be invested in reducing uncertainty and which uncertainties should be reduced. In such instances, decision science can help select efficient environmental management actions that may be subject to stochasticity and imperfect knowledge. Here, we review the use of decision science in environmental management to demonstrate the utility of the decision science framework. Our points are illustrated using examples from the literature. We conclude that collaboration between theoreticians and practitioners is crucial to maximize the benefits of decision science’s rational approach to dealing with uncertainty.     

Sweet Science for ALL! Supporting Inquiry-Based Learning Through M&Ms Investigation for English Language Learners

This article describes a series of inquiry-based lessons that provide English language learners (ELLs) with opportunities to experience science and engineering practices with conceptual understanding as well as to develop their language proficiency in elementary classrooms. The four-lesson sequence models how various types of instructional strategies for ELLs can be embedded through science lessons with thoughtful consideration of ELLs’ diverse cultural backgrounds. The cross-curricular science lessons provide ELLs with opportunities to apply and enhance their mathematics, reading, writing, and communicating skills while investigating the properties of M&Ms.     

Natural decision theory: A general formalism for the analysis of evolved characteristics

Classical Decision Theory, a mature and highly developed theory of rational choice, can be applied within evolutionary biology to the question of what traits an organism ought “rationally” to adopt, given that it wants to maximize its fitness. In this way the powerful formalism of decision theory can be brought to bear on the problem of how to predict which characters will be favored by natural selection, or to explain why certain characters have been so favored.Under some circumstances the classical theory of decision can be applied as it stands to an evolutionary problem simply by substituting an appropriate measure of biological fitness for the decision-theoretic concept of “utility”. Under other circumstances, however, it is necessary to extend the classical rules of decision in certain new directions. The result is a family of decision calculi of which the classical is only one. The name “Natural Decision Theory” is proposed for this extended class of biologically relevant decision methods.The decision tree method of diagramming an evolutionary decision situation is illustrated for the classical and three non-classical decision criteria, and is suggested as a potential means of gaining new insights into evolutionary forces.     

Design of forest management planning DSS for wildfire risk reduction

Forest management planning is generally a complicated task. The amount of data, information and knowledge involved in the management process is often overwhelming. Decision support systems can help forest managers make well documented decisions concerning forest management planning. These systems include a wide variety of components, depending on the management goals of the forested land. Although an increased growth of decision support systems in specific domains of forest management planning exists, there is no special design model for the deployment of forest management planning. To this direction, this paper has the following objectives: Firstly, to propose a conceptual design model for developing goal-driven forest management planning decision support systems. Secondly, to apply the design model for a particular case of these systems, the wildfire risk reduction decision support systems. Thirdly, to present the deployment of a wildfire risk reduction decision support system as well as its results for a specific forest area.     

Statistical power and analytical quantification

It is suggested that power analysis should be formally incorporated into quantification experiment reports in order to substantiate the conclusions derived from experimental data more effectively. The article addressed the issues of power analysis calculation, sample size estimation and appropriate data reporting in quantitative analytical comparisons. Illustrative examples from the literature are used to show how the described power analysis theory could be applied in practice.     

Optimizing substitution matrices by separating score distributions

MOTIVATION: Homology search is one of the most fundamental tools in Bioinformatics. Typical alignment algorithms use substitution matrices and gap costs. Thus, the improvement of substitution matrices increases accuracy of homology searches. Generally, substitution matrices are derived from aligned sequences whose relationships are known, and gap costs are determined by trial and error. To discriminate relationships more clearly, we are encouraged to optimize the substitution matrices from statistical viewpoints using both positive and negative examples utilizing Bayesian decision theory. RESULTS: Using Cluster of Orthologous Group (COG) database, we optimized substitution matrices. The classification accuracy of the obtained matrix is better than that of conventional substitution matrices to COG database. It also achieves good performance in classifying with other databases.     

What can genome-scale metabolic network reconstructions do for prokaryotic systematics?

It has recently been proposed that in addition to Nomenclature, Classification and Identification, Comprehending Microbial Diversity may be considered as the fourth tenet of microbial systematics [Staley JT (2010) The Bulletin of BISMiS, 1(1): 1–5]. As this fourth goal implies a fundamental understanding of microbial speciation, this perspective article argues that translation of bacterial genome sequences into metabolic features may contribute to the development of modern polyphasic taxonomic approaches. Genome-scale metabolic network reconstructions (GSMRs), which are the result of computationally predicted and experimentally confirmed stoichiometric matrices incorporating all enzyme and metabolite components encoded by a genome sequence, provide a platform that can illustrate bacterial speciation. As the topology and the composition of GSMRs are expected to be the result of adaptive evolution, the features of these networks may provide the prokaryotic taxonomist with novel tools for reaching the fourth tenet of microbial systematics. Through selected examples from the Actinobacteria, which have been inferred from GSMRs and experimentally confirmed after phenotypic characterisation, it will be shown that this level of information can be incorporated into modern polyphasic taxonomic approaches. In conclusion, three specific examples are illustrated to show how GSMRs will revolutionize prokaryotic systematics, as has previously occurred in many other fields of microbiology.     

Requirements for alpha(5)beta(1) integrin-mediated retraction of fibronectin-fibrin matrices.

Retraction of the blood clot by nucleated cells contributes both to hemostasis and to tissue remodeling. Although plasma fibronectin (FN) is a key component of the clot, its role in clot retraction is unclear. In this report, we demonstrate that the incorporation of FN into fibrin matrices significantly improves clot retraction by nucleated cells expressing the integrin alpha(5)beta(1). Further, we show that FN-fibrin clots support increased cell spreading when compared with fibrin matrices. To determine the structural requirements for FN in this process, recombinant FN monomers deficient in ligand binding or fibrin cross-linking were incorporated into fibrin clots. We show that recombinant FN monomers support clot retraction by Chinese hamster ovary cells expressing the integrin alpha(5)beta(1). This process depends on both the Arg-Gly-Asp (RGD) and the synergy cell-binding sites and on covalent FN-fibrin binding, demonstrating that cross-linking within the clot is important for cell-FN interactions. These data show that alpha(5)beta(1) can bind to FN within a clot to promote clot retraction and support cell shape change. This provides strong evidence that alpha(5)beta(1)-FN interactions may contribute to the cellular events required for wound contraction.     

Consistent Implementation of Decisions in the Brain

Despite the complexity and variability of decision processes, motor responses are generally stereotypical and independent of decision difficulty. How is this consistency achieved? Through an engineering analogy we consider how and why a system should be designed to realise not only flexible decision-making, but also consistent decision implementation. We specifically consider neurobiologically-plausible accumulator models of decision-making, in which decisions are made when a decision threshold is reached. To trade-off between the speed and accuracy of the decision in these models, one can either adjust the thresholds themselves or, equivalently, fix the thresholds and adjust baseline activation. Here we review how this equivalence can be implemented in such models. We then argue that manipulating baseline activation is preferable as it realises consistent decision implementation by ensuring consistency of motor inputs, summarise empirical evidence in support of this hypothesis, and suggest that it could be a general principle of decision making and implementation. Our goal is therefore to review how neurobiologically-plausible models of decision-making can manipulate speed-accuracy trade-offs using different mechanisms, to consider which of these mechanisms has more desirable decision-implementation properties, and then review the relevant neuroscientific data on which mechanism brains actually use.     

Diffusion of biologically relevant molecules through gel-like tissue scaffolds

Encapsulation of living cells into gel-like matrices that are capable of maintaining their viability over an extended time period is starting to play a major role in medicine in applications such as, cell-based sensors, cellular therapy, and tissue engineering. The permeability of nutrients and waste products through these matrices is critical to their performance. In this article, we report a methodology for selecting scaffolds with different permeabilities and surface area/volume ratios that can be used to house a 3D cell aggregate. Such a system can be modeled if the consumption or production rates for metabolites and waste products, respectively and the diffusion coefficients of these solutes in culture medium and the encapsulating gel matrix are known. A transient finite volume mass diffusion model, based on Fick's law, is derived where the consumption of a solute by the cells is modeled through a source term. The results show that the "performance" of cell-doped gel is critically dependent on the rate at which cells consume key molecules e.g., glucose. Pragmatically, the model also provides insight as to how many cells a given gel geometry and structure can support. The approach used applies to any porous structure where mass transport occurs through diffusion.     

The contributions of Indigenous Peoples and local communities to ecological restoration

Indigenous Peoples and local communities (IPLC) are affected by global environmental change because they directly rely on their immediate environment for meeting basic livelihood needs. Therefore, safeguarding and restoring ecosystem resilience is critical to support their well‐being. Based on examples from the literature, we illustrate how IPLC participate in restoration activities maintaining traditional practices, restoring land degraded by outsiders, and joining outside groups seeking to restore ecosystems. Our review also provides examples of how Indigenous and Local Knowledge can be incorporated in the planning, execution, and monitoring of restoration activities. However, not all restoration initiatives engaging IPLC are beneficial or successful, and the factors that lead to success are not fully known. While local involvement in restoration projects is often mentioned as an element of success, this is primarily associated to projects that actively involve IPLC in codesigning restoration activities affecting their territories, ensure both short‐term direct benefits to IPLC and long‐term support of the maintenance of restored areas, and recognize IPLC local traditions and customary institutions. Based on these examples, we argue that IPLC should be a more important focus in any post‐2020 CBD agenda on restoration.     

A decision-analytic framework for impact assessment part I: LCA and decision analysis

Life-cycle assessments (LCAs) are conducted to satisfy the aspiration of decision makers to consider the environment in their decision making. This paper reviews decision analysis and discusses how it can be used to structure the assessment and to integrate characterization and valuation. The decision analytic concepts of objectives (goals) and attributes (indicators of the degree to which an objective is achieved) are used to describe steps of the assessment of the entire impact chain. Decision analysis distinguishes among different types of objectives and attributes; it describes how these relate to each other. Impact indicators such as the Human Toxicity Potential are constructed attributes. A means-ends objectives network can show how the different constructed attributes relate to the objective of protecting the environment. As LCA takes disparate environmental impacts into account, it needs to assess their relative importance. Trade-off methods in decision analysis are grouped into utility theory and multicriteria decision aids; they have different advantages and disadvantages, but are all more sophisticated than simple weighting. The performance of the different trade-off methods has not yet been tested in an LCA context. In the second part of the paper, we present criteria for the development of characterization methods.     

神经外科临床决策支持系统设计研究

临床决策支持系统(Clinical decision support system,CDSS)是利用决策支持系统相关理论和技术,为临床医师在诊疗过程中提供诊疗决策的支持系统。本文根据临床神经外科疾病特点,提出基于KD、DB、和MD的框架系统结构,并构建临床疾病知识库、病人信息数据库和决策模型库,为下一步实现NCDSS功能提供理论基础和方法指导。     

Considerations Regarding the Use of Reference Area and Baseline Information in Ecological Risk Assessments

There has been debate in the recent literature as to whether a reference assessment should be included in ecological risk assessments (ERAs) of contaminated sites, and if so, how such an evaluation can be incorporated in a way that aids in decision making. It is our view that an assessment of reference conditions can be useful in the ERA process, for both prospective and retrospective ERAs, given adequate resources and acknowledgement and understanding of the limitations and uncertainties associated with this information. Suggestions and considerations for incorporating reference area information into an ecological risk assessment are discussed.     

Testing the Effects of Classroom Supports on Children's Social and Behavioral Skills at Key Transition Points Using Latent Growth Modeling

Social and behavioral problems can interfere with a child's acquisition of age-appropriate skills, which may lead to antisocial behavior in adolescence and adulthood. Thus, determining how best to support positive skills during early childhood is critical. Using data from the first three phases of the NICHD Study of Early Child Care and Youth Development, I investigated whether participation in preschool, first, or third grade classrooms that were more emotionally supportive or academically focused resulted in better social skills and fewer problem behaviors at key transition points (i.e., preschool and third grade) than did participation in classrooms that were less supportive or less academically focused. Three findings are noteworthy. First, more emotionally supportive classrooms resulted in better social skills and fewer problem behaviors in preschool and third grade, even after correcting for observed family, child, and neighborhood selection factors; this effect did not exist for classrooms that were more academically focused. Second, immersion in classrooms that were more emotionally supportive at preschool, first, and third grade led to better social skills and fewer problem behaviors in preschool and third grade than did immersion in classrooms of average or below average emotional support across this period. Third, observed child factors, as opposed to family or neighborhood factors, seem to drive the pattern of findings. Effect sizes were small to modest. Implications for practice and future research are discussed.     

THE WINDOW OF OPPORTUNITY: DECISION THEORY AND THE TIMING OF PROGNOSTIC TESTS FOR NEWBORN INFANTS

In many forms of severe acute brain injury there is an early phase when prognosis is uncertain, followed later by physiological recovery and the possibility of more certain predictions of future impairment. There may be a window of opportunity for withdrawal of life support early, but if decisions are delayed there is the risk that the patient will survive with severe impairment. In this paper I focus on the example of neonatal encephalopathy and the question of the timing of prognostic tests and decisions to continue or to withdraw life‐sustaining treatment. Should testing be performed early or later; and how should parents decide what to do given the conflicting values at stake? I apply decision theory to the problem, using sensitivity analysis to assess how different features of the tests or different values would affect a decision to perform early or late prognostic testing. I draw some general conclusions from this model for decisions about the timing of testing in neonatal encephalopathy. Finally I consider possible solutions to the problem posed by the window of opportunity. Decision theory highlights the costs of uncertainty. This may prompt further research into improving prognostic tests. But it may also prompt us to reconsider our current attitudes towards the palliative care of newborn infants predicted to be severely impaired.     

Reaction times and intelligence: a comparison of Japanese and British children

Japanese and British 9-year-old children were compared on the standard progressive matrices and twelve reaction time parameters providing measures of simple and complex decision times, movement times and variabilities. The mean of the Japanese children on the progressive matrices exceeded that of the British children by 0.65 SD units and on the decision times component of reaction times by 0.50 SD units, suggesting that the high Japanese mean on psychometric intelligence is largely explicable in terms of the more efficient processing of information at the neurological level. Japanese children also showed faster movement times but, contrary to expectation, had greater variabilities than British children.     

Direct Look from a Predator Shortens the Risk-Assessment Time by Prey

Decision making process is an important component of information use by animals and has already been studied in natural situations. Decision making takes time, which is expressed as a cost in evolutionary explanations of decision making abilities of animals. However, the duration of information assessment and decision making process has not been measured in a natural situation. Here, we use responses of wild magpies (Pica pica) to predictably approaching humans to demonstrate that, regardless of whether the bird perceived high (decided to fly away) or low (resumed foraging) threat level, the bird assessed the situation faster when approaching humans looked directly at it than when the humans were not directly looking at it. This indicates that prey is able to extract more information about the predator’s intentions and to respond sooner when the predator is continuously (“intently”) looking at the prey. The results generally illustrate how an increase of information available to an individual leads to a shorter assessment and decision making process, confirming one of central tenets of psychology of information use in a wild bird species in its natural habitat.