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Gaseous flames and pulverized coal flames are considered to examine relationships between lab-scale flames, semi-industrial scale and industrial-scale flames. The experimental data spans the thermal input range from the lowest scale of 30 kW to the largest of 12 MW with several intermediate scales. The primary questions are whether effects observed in lab-scale flames are scalable to industrial applications and whether mathematical models developed on the basis of lab-scale data are directly applicable to industrial flames. It has been observed that disparity between the in-flame temperatures measured in lab-scale and in large-scale flames can be as large as 100–200 K due to different measurement techniques used. In lab-scale experiments one observes a strong interaction between turbulence and chemistry and the measured data is sensitive to small alterations to burner inputs and/or boundary conditions. The sensitivity almost disappears at large-scales since the convective mixings is the dominant (the slowest) mechanism. In other words, different effects are seen at small- and large-scales and different mechanisms are controlling. Although the paper is concerned with single flames, in our opinion, the conclusions are also relevant to gas turbines. Until genuine efforts are taken to develop a good understanding of combustion system scaling, the worlds of combustion science and combustion engineering will remain parted. • Turbulence- chemistry interaction determines structure of lab-scale flames whilst convective mixing is the controlling mechanism in industrial flames. • CFD-based models developed and validated using lab-scale data have to be substantially modified and tuned to provide accurate predictions of industrial flames. • Until genuine efforts are taken to developed a good understanding of combustion system scaling, the worlds of combustion science and engineering will remain parted. [ABSTRACT FROM AUTHOR]

A reverse supply chain, as a post-consumption activity, aims at extracting value from products at end of their life cycle (Mafakher and Nasiri, Journal of Cleaner Production 59:185-196, 2013). As well, company's awareness is attracting increasing attention toward sustainable business practices. Open-innovation is a typical example of coordinative activity that a manufacturer should share a profits generated through reverse supply chain with retailer. The aim of this paper provide insights toward open innovation practice in sharing profits between two strategic partners, manufacturer and retailer to maximize an individual profits as well as total profits concurrently in reverse supply chain. For analyzing effects of open innovation strategies, we modeled reverse supply chain environments using system dynamics approach and compared the gap of profits between non-coordinative (decentralized) and coordinative activity. Three cooperative contracts in terms of how to share the cost and profit between two parties are proposed in this paper. Each contract was analyzed according to the following three contract processes. The first stage is that manufacturer proposes contracts to retailer. The second is that retailer evaluates proposed contracts and choices the best contract which can lead to maximize its expected profit. Finally retailer and manufacturer adjust parameters of the best contract for achieving mutual goal of supply chain. Through the experimental results, we discuss best coordinative strategy between manufacturer and retailer in order to maximize a profit in reverse SC. [ABSTRACT FROM AUTHOR]

Given the economic squeeze world over, search for what we call frugal grassroots innovations in Honey Bee Network, has become even more urgent and relevant in the recent years. And, to shape this search, models and concepts like open innovation, reverse innovation (GE, Market-Relevant Design: Making ECGs Available Across India, 2009); (Govindarajan, Reverse Innovation: a Playbook, 2012); (Govindarajan and Ramamurti. Global Strategy Journal, 1: 191-205, 2011); (Govindarajan and Euchner, Res. Technol. Manage , 55: 13-17, 2012, Govindrajan and Trimble, 40(5), 5-11, 2012), embedded innovation (Simanis and Hart, Innovation from the Inside Out, MIT Sloan Management Review, 2009), extremely affordable, low-cost, frugal innovation (Honey Bee Network, 1989-2016, Gupta, 2000); (Gupta AK, How Local Knowledge can Boost Scientific Studies, 2007); (Gupta AK, Indian Hidden hotebd of invention, 2009a; Gupta AK, , 2009b) etc., have emerged over time. We wish to trace the evolution of the Open Innovation Theory (Urban and Von Hippel, Manag. Sci. 34(5), 569-582, 1988) in the context of the Honey Bee Network working on such ideas for over 26 years. The idea is to study the different strands of relationships between knowledge providers and seekers which make the system truly reciprocal, responsible and responsive. When systems become open, search cost for inclusive innovation will automatically come down and the knowledge system will also become more symmetrical and inclusive. Inclusive innovation for social development implies that new solutions should help in dealing with one or more of the five factors of exclusion: spatial, seasonal, sectoral, skill and social. These should also be accessible, affordable, available and adaptable to varying and differentiated user endowments and needs, besides being circular. One has to understand the interaction between natural, social, ethical and intellectual capital, situated in the institutional context of innovations: at, from, for and with grassroots level communities for defining inclusivity in the innovation ecosystem. A company or a community, when in need of an innovative solution to a local problem, may seek it from outside, develop it inside, or co-create/contract it out. The nature of reciprocity between knowledge and innovation exchange partners may have different types of asymmetries (Bansemir and Neyer 2009). Different ethical principle enunciated in the Honey Bee Network may or may not be followed. The discourse on open innovation has been biased in the favour of corporates seeking ideas form outside rather than sharing their own innovation/knowledge as a public good or commons, or even at low cost with less-advantaged industry actors. In this paper, we reflect on such biases that companies and scholars have developed and propose a framework to temper it. The need for such a correction becomes even more important when various kind of climatic, institutional and market risks are making socio-economic systems more fragile and vulnerable to various uncertainties and fluctuations. Coping with risks is significantly related to malleability of innovations. The process of evolving and nurturing innovations may have a bearing on their eventual adaptability to user. We argue that when both technology platform and application domains are known well, the incubation model works. Generally, through this process, incremental innovation grows better. But, when both are unknown or are ambiguous, sanctuary model works better. In incubators, the chaos is outside and the order is inside. In sanctuary, it is the opposite. It is not very surprising that sanctuary nurtures innovation which is more suited to fluctuating climate and market-uncertain environments. Innovations don't have relevance only at artefactual level. One can learn at metaphorical, heuristic and gestalt levels too. Building bridges between formal and informal knowledge systems poses a unique challenge in designing reciprocal and responsible open innovation platforms? This paper pleads for more reciprocal, respectful and responsible exchanges of knowledge between formal and informal sector adding value to the contributions of grassroots green innovators. [ABSTRACT FROM AUTHOR]

This paper presents a constant voltage operation of a Six-Phase Self-Excited Induction Generator (SPSEIG) driven by a fixed speed wind turbine using an Ant colony optimisation (ACO) technique to predict the behaviour of a the machine. In this paper, an attempt has been made to estimate the excitation capacitance requirements of a SPSEIG for maintaining rated terminal voltage and frequency. The range of capacitance variation required for maintaining constant terminal voltage while supplying a load of variable magnitude is evaluated. Analytical approaches, suitable for all the configurations of shunt capacitances such as variable excitation capacitance connected across (i) single three-phase winding set only and (ii) both the three-phase winding sets of an SPSEIG for operation as a simple shunt on no load and pure resistive load, are presented. The mathematical model developed is based on loop impedance method using graph theory. It is shown that the proposed technique is very effective and useful for making the SPSEIG feasible for remote areas with wind potential. The proposed approach is tested and compared with Genetic Algorithm (GA) and Fmincon technique. [ABSTRACT FROM AUTHOR]

Pigs exposed to stressors might change their daily typical feeding intake pattern. The objective of this study was to develop a method for the early identification of deviations from an individual pig's typical feeding patterns. In addition, a general approach was proposed to model feed intake and real-time individual nutrient requirements for pigs with atypical feeding patterns. First, a dynamic linear model (DLM) was proposed to model the typical daily feed intake (DFI) and daily gain (DG) patterns of pigs. Individual DFI and DG dynamics are described by a univariate DLM in conjunction with Kalman filtering. A standardized tabular cumulative sum (CUMSUM) control chart was applied to the forecast errors generated by DLM to activate an alarm when a pig showed deviations from its typical feeding patterns. The relative feed intake (RFI) during a challenge period was calculated. For that, the forecasted individual pig DFI is expressed as its highest DFI relative to the intake during pre-challenge period. Finally, the DLM and RFI approaches were integrated into the actual precision-feeding model (original model) to estimate real-time individual nutrient requirements for pigs with atypical feeding patterns. This general approach was evaluated with data from two studies (130 pigs, at 35.25 ± 3.9 kg of initial BW) that investigated during 84 days the effect of precision-feeding systems for growing-finishing pigs. The proposed general approach to estimating real-time individual nutrient requirements (updated model) was evaluated by comparing its estimates with those generated by the original model. For 11 individuals out of 130, the DLM did not fit the observed data well in a specific period, resulting in an increase in the sum of standardized forecast errors and in the number of time steps that the model needed to adapt to the new patterns. This poor fit can be identified by the increase in the CUMSUM with a consequent alarm generated. The results of this study show that the updated model made it possible to reduce intra-individual variation for the estimated lysine requirements in comparison with the original model, especially for individuals with atypical feeding patterns. In conclusion, the DLM in conjunction with CUMSUM could be used as a tool for the online monitoring of DFI for growing-finishing pigs. Moreover, the proposed general approach allows the estimation of real-time amino acid requirements and accounts for the reduced feed intake and growth potential of pigs with atypical feeding patterns. [ABSTRACT FROM AUTHOR]

Background: The traditional economic models are increasingly perceived as weak in explaining the bubbles and crashes in financial markets and the associated crisis. Thus, especially after the global financial crisis in 2008, agent-based model (ABM) is getting an attention as an alternative approach for a better understanding of complex dynamics of financial market. Methods: This paper develops an ABM to replicate financial instability, such as bubbles and crashes in asset markets, by introducing a simple idea of 'heterogeneous expectation' and 'herding behavior' by which agents in different groups have different expectations about a 'tipping point' where they expect the price to stop rising anymore but to begins to fall. Results: It is shown that, when the agents have different expectations on the tipping point, the collapse of the price does not emerge automatically, and price fluctuations are often small and even some (seemingly) flat intervals appear. We also verify the impact of the herding behavior by dividing agents into several groups of varying sizes but with the same expectations. By changing the size of groups, we establish that the more agents share the same expectations about the tipping point, the higher volatility of the asset price emerges. Conclusions: We confirm that bubble and burst of prices are more like to emerge when heterogeneous expectations about prices are combined with herding behavior among agents, so that agents in the same group share the similar expectations about the price changes. [ABSTRACT FROM AUTHOR]

The mathematical model for physical and chemical processes during wood chips gasification in a gasifier is presented in this paper to offer some reference data for the gasifier structure design and operation optimization. The RNG k – ε model is employed in the numerical simulation of turbulent combustion gas flow. Non-premixed combustion model is used to describe the species reaction and transportation. The movement and gasification of wood chip particle is described by Lagrange model. The Eulerian conservation equations of gas phase are solved using the control volume approach. The distributions of temperature and chemical species, residence time of wood particles are numerically obtained. The results indicate that this design will cause vortex structure at lower chamber for the interaction between the forwarding flow of air and the reverse flow of syngas. This vortex will make produced syngas to combust further; the productions are CO 2 and H 2 O substituting CO and H 2 , which will decrease the temperature inside the chamber and quality of syngas. In order to optimize operational case, five different equivalence ratios of airflow are computed and compared with experimental test. The predicted temperatures of outgoing gas agree well with the experimental results. Modeling results can provide some references for gasifier structure design and optimum operation case. [ABSTRACT FROM AUTHOR]

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed ‘omics’ technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A ‘system’ approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with ‘system approaches’ in animal sciences, providing exciting opportunities to predict and modulate animal traits. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of digital production and information technologies on the development of logistic systems of different kinds: megalogistic, macrologistic, and micrologistic. The notions of a logistic system and types of logistic systems imply that logistics is considered in its broad sense as a modern methodology for managing all types of flows that appear in the process of socioeconomic activities of society and business: material, information, energy, financial and labor flows. The methodology discussed in this paper gives the answer to the question of what impact digital production and information technologies have on the development of various types of logistic systems. The methodology includes building a mathematical model in which the endogenous variables of the model reflect the resulting variables of the logistic system, while the exogenous variables reflect digital production and information technologies. The mathematical model is a system of interdependent dynamic econometric equations. Each equation is an autoregressive distributed lags model. In the model, the current values of an endogenous variable depend on their previous values, as well as on the current and previous values of other endogenous and exogenous variables. The novelty of the research is in the developed methodology for a comprehensive assessment of the impact made by digitalization on a totality of the interrelated and interdependent resulting indicators of the logistic system. A comprehensive assessment of the impact made by digitalization on a totality of interrelated and interdependent indicators of the logistic system is understood as a change in the indicators of the logistic system due to the effect of digitalization. The proposed methodology for a comprehensive assessment was empirically tested for Salesforce company. [ABSTRACT FROM AUTHOR]

Based on geologic and development characteristics of tight gas reservoir, a tight gas reservoir/fractured horizontal wellbore coupling model at unsteady state is derived by Green functions and Newman product principle, and the analytical solutions of dimensionless velocity and dimensionless pressure are obtained as well. Practical calculation example shows that main seepage of a fractured horizontal well surrounds the artificial fractures. When more fractures are fractured, the shapes of isobars from inner to outer are: families of conjugate ellipses, bone-shaped curves and a family of ellipses. According to the seepage law, effective technological measures of drilling and producing are given in the paper. [ABSTRACT FROM AUTHOR]

Abstract: This paper introduces a methodology for incorporating metrics for electric-sector reliability into a global Integrated Assessment Model. Using load, resource availability, and system dispatch data with high temporal resolution, we designed a set of reduced-form constraints that guide investment and usage decisions among power plants in IIASA''s MESSAGE model. The analysis examines how such reliability metrics impact modeled system build-out, including in scenarios with greenhouse gas (GHG) limits. Scenarios show how carefully chosen model constraints can allow a flexible approach to treating integrations concerns of variable renewable technologies into the electric sector in a high-level energy model. [Copyright &y& Elsevier]

In this paper, factorial models of the dietary requirements for protein, nitrogen and individual indispensable amino acids are developed from published information on the relationship between age and protein deposition and between protein (amino acid) intake and nitrogen balance. The results are used to develop recommendations on the protein-energy ratio and the amino acid pattern of the diet. As part of the development of the models, factors affecting dietary protein digestibility, bioavailability and efficiency of utilization are discussed. Over the age range of 6-24 mo the models predict a fall in the weight-specific protein and amino acid requirement that results almost entirely from the changes in the growth rate of the children. It is also concluded that the requirement for the maintenance of body protein equilibrium (so-called maintenance) changes little with age. This contrasts markedly with the relationship between age and energy requirements. The amino acid modeling implies that the optimum pattern of individual essential amino acids also changes only marginally across the age range considered in the report. The calculations of the dietary requirement for whole protein imply that achieving a minimum protein-energy ratio of 6.3% is desirable. The amount of protein needed from complementary foods for breast-fed children is discussed. [ABSTRACT FROM AUTHOR]