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The combined effects of several complex phenomena cause the deterioration of elements in steel hydraulic structures (SHSs) within the US lock system: corrosion, cracking and fatigue, impact and overloads. Predicting the future condition state of these structures by the use of current condition state inspection data can be achieved through the probabilistic chain deterioration model. The purpose of this study is to derive the transition probability matrix using final elements modeling of a miter gate.

If predicted accurately, this information would yield benefits in determining the need for rehabilitation or replacement of SHS. However, because of the complexity and difficulties on obtaining sufficient inspection data, there is a lack of available condition states needed to formulate proper transition probability matrices for each deterioration case.

This study focuses on using a three-dimensional explicit finite element analysis (FEM) of a miter gate that has been fully validated with experimental data to derive the transition probability matrix when the loss of flexural capacity in a corroded member is simulated.

New methodology using computational mechanics to derive the transition probability matrices of navigation steel structures has been presented.

The difficulty of deriving the transition probability matrix to perform a Markovian analysis increases when limited amount of inspection data is available. The used state of practice FEM to derive the transition probability matrix is not just necessary but also essential when the need for proper maintenance is required but limited amount of the condition of the structural system is unknown.

Since the core issue of Chinese economics is to elucidate the logical relationship between socialism and the market economy, it necessitates a robust foundation for microeconomic analysis to uncover the behavioral patterns and characteristics of microeconomic agents in a socialist market economy and identify the conditions and methods for the functioning of market mechanisms.

The core issue of microeconomics with Chinese characteristics is to identify the economic logic of how market mechanisms play a decisive role in resource allocation under the basic socialist economic system based on China's reform.

The core issue in building the foundation of microeconomic analysis of Chinese economics is addressing the compatibility issue between SOEs and a market economy.

In the author’s view, this can be achieved under the logic of classified reform so as to build the microeconomic foundation for the effective functioning of a socialist market economy.

Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces budgetary limitations. Managing a network of transportation infrastructure assets, especially when the number is large, is a multifaceted challenge. This paper aims to develop a life-cycle cost analysis (LCCA) based transportation infrastructure asset management analytical framework to study the impacts of a few key parameters/factors on deterioration and life-cycle cost. Using the bridge as an example infrastructure type, the framework incorporates an optimization model for optimizing maintenance, repair, rehabilitation (MR&R) and replacement decisions in a finite planning horizon.

The analytical framework is further developed through a series of model variations, scenario and sensitivity analysis, simulation processes and numerical experiments to show the impacts of various parameters/factors and draw managerial insights. One notable analysis is to explicitly model the epistemic uncertainties of infrastructure deterioration models, which have been overlooked in previous research. The proposed methodology can be adapted to different types of assets for solving general asset management and capital planning problems.

The experiments and case studies revealed several findings. First, the authors showed the importance of the deterioration model parameter (i.e. Markov transition probability). Inaccurate information of p will lead to suboptimal solutions and results in excessive total cost. Second, both agency cost and user cost of a single facility will have significant impacts on the system cost and correlation between them also influences the system cost. Third, the optimal budget can be found and the system cost is tolerant to budge variations within a certain range. Four, the model minimizes the total cost by optimizing the allocation of funds to bridges weighing the trade-off between user and agency costs.

On the path forward to develop the next generation of bridge management systems methodologies, the authors make an exploration of incorporating the epistemic uncertainties of the stochastic deterioration models into bridge MR&R capital planning and decision-making. The authors propose an optimization approach that does not only incorporate the inherent stochasticity of bridge deterioration but also considers the epistemic uncertainties and variances of the model parameters of Markovian transition probabilities due to data errors or modeling processes.

Switching power converters for photovoltaic (PV) applications with high gain are rapidly expanding. To obtain better voltage gain, low switch stress, low ripple and cost-effective converters, researchers are developing several topologies.

It was decided to use the particle swarm optimization approach for this system in order to compute the precise PI controller gain parameters under steady state and dynamic changing circumstances. A high-gain q- ZS boost converter is used as an intermittent converter between a PV and brushless direct current (BLDC) motor to attain maximum power point tracking, which also reduces the torque ripples. A MATLAB/Simulink environment has been used to build and test the positive output quadratic boost high gain converters (PQBHGC)-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. The simulation results show that the PQBHGC-3 topology is effective in comparison with other HG cell DC–DC converters in terms of efficiency, reduced ripples, etc. which is most suitable for PV-driven BLDC applications.

The simulation results have showed that the PQBHGC-3 gives better performance with minimum voltage ripple of 2V and current ripple of 0.4A which eventually reduces the ripples in the torque in a BLDC motor. Also, the efficiency for the suggested PQBHGC-3 for PV-based BLDC applications is the best with 99%.

This study is the first of its kind comparing the different topologies of PQBHGC-1, PQBHGC-8, PQBHGC-4 and PQBHGC-3 topologies to analyse their effectiveness in PV-driven BLDC motor applications. This study suggests that the PQBHGC-3 topology is most suitable in PV-driven BLDC applications.

This paper aims to develop and argue for a new research path to advance theory on incumbent firm adaptation to discontinuous technological change. Integrating variance and process epistemologies, implications of distinguishing a firm's capacity to adapt from their adaptive choices are highlighted.

The concepts and argument presented are based on an extensive review and synthesis of the literature on the phenomenon.

Distinguishing resource-based capacity variables and behavioral-based choice variables can fuel progress in the literature on incumbent adaptation to technological changes. More attention is needed on the direct, proximate determinants of what occurs in the process of adaptation, e.g. the intermediate choices to adapt, the timing of adaptive actions and the selection of a means for adapting. Work must then associate specific choices with performance outcomes to complete both sides of the mediated cause-effect model connecting characteristics of the decision issue to performance.

Most studies toward understanding how incumbent firms adapt to discontinuous technological innovation have used variance analyses to identify firm and technology characteristics that explain adaptation outcomes. Focusing on characteristics and content, however, does not adequately explain why or how firms adapt. Scholars thus continue to lament the lack of clear, practical theory. I contend one heretofore unaddressed reason for this dissatisfaction is that too much of the research base neglects the importance of understanding choices and the factors affecting them.

The main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.

Modeling is the most relevant tool for understanding the functioning of some complex processes such as biological wastewater treatment. A steady state model equation of activated sludge model 1 (ASM1) was developed, especially for autotrophic biomass (XBA) and for oxygen uptake rate (OUR). Furthermore, a respirometric measurement, under steady state and endogenous conditions, was used as a new tool for quantifying the viable biomass concentration in the bioreactor.

The developed steady state equations simplified the sensitivity analysis and allowed the autotrophic biomass (XBA) quantification. Indeed, the XBA concentration was approximately 212 mg COD/L and 454 mgCOD/L for SRT, equal to 20 and 40 d, respectively. Under the steady state condition, monitoring of endogenous OUR permitted biomass quantification in the bioreactor. Comparing XBA obtained by the steady state equation and respirometric tool indicated a percentage deviation of about 3 to 13%. Modeling bioreactor using GPS-X showed an excellent agreement between simulation and experimental measurements concerning the XBA evolution.

These results confirmed the importance of respirometric measurements as a simple and available tool for quantifying biomass.

This paper aims to demonstrate methods that sustainability-conscious brands can use to include their primary producers in the measurement and reporting of the environment and sustainability performance of their supply chains. It explores three questions: How can farm businesses provide information required in sustainability reporting? What are the challenges and opportunities experienced in preparing and presenting the information? What future research and policy instruments might be needed to resolve these issues.

This study identifies and describes methods to provide the farm-level information needed for environmental performance and sustainability reporting frameworks. It demonstrates them by compiling natural capital accounts and environmental performance information for two wool producers in the grassy woodland biome of Eastern Australia; the contrasting history and management of these producers would be expected to result in different environmental performances.

The authors demonstrated an approach to NC accounting that is suitable for including primary producers in environmental performance reporting of supply chains and that can communicate whether individual producers are sustaining, improving or degrading their NC. Measurements suitable for informing farm management and for the estimation of supply chain performance can simultaneously produce information useful for aggregation to regional and national assessments.

The methods used should assist sustainability-conscious supply chains to more accurately assess the environmental performance of their primary producers and to use these assessments in selective sourcing strategies to improve supply chain performance. Empirical measures of environmental performance and natural capital have the potential to enable evaluation of the effectiveness of sustainability accounting frameworks in inducing businesses to reduce their environmental impacts and improve the condition of the natural capital they depend on.

Two significant social implications exist for the inclusion of primary producers in the sustainability and environmental performance reporting of supply chains. Firstly, it presently takes considerable time and expense for producers to prepare this information. Governments and members of the supply chain should acknowledge the value of this information to their organisations and consider sharing some of the cost of its preparation with primary producers. Secondly, the “additionality” requirement commonly present in existing frameworks may perversely exclude already high-performing producers from being recognised. The methods proposed in this paper provide a way to resolve this.

To the best of the authors’ knowledge, this research is the first to describe detailed methods of collecting data for natural capital accounting and environmental performance reporting for individual farms and the first to compile the information and present it in a manner coherent with the Kering EP&L and the UN SEEA EA. The authors believe that this will make a significant contribution to the development of fair and standardised ways of measuring individual farm performance and the performance of food, beverage and apparel supply chains.

The era of crowd network is coming and the research of its steady-state is of great importance. This paper aims to establish a crowd network simulation platform and maintaining the relative stability of multi-source dissemination systems.

With this simulation platform, this paper studies the characteristics of “emergence,” monitors the state of the system and according to the fixed point judges the system of steady-state conditions, then uses three control conditions and control methods to control the system status to acquire general rules for maintain the stability of multi-source information dissemination systems.

This paper establishes a novel steady-state maintenance simulation framework. It will be useful for achieving controllability to the evolution of information dissemination and simulating the effectiveness of control conditions for multi-source information dissemination systems.

This paper will help researchers to solve problems of public opinion control in multi-source information dissemination in crowd network.

The purpose of this study is to unravel the changing nature of climate change impact on the food and human security sector of the Nigerian State.

This study is an in-depth case study that involves the use of both quantitative and qualitative data. Statistical data on climate variability in Nigeria obtained from reliable databases were use in the making of analysis. Also, data derived from semi-structure interviews and special reports from International Non-governmental organizations on the subject matter were also used in the study. The findings of the study were based on an in-depth analysis of both primary and secondary sources of data. The secondary data were derived from existing published academic works. The primary data was developed using qualitative data that were collected from January to November, 2018 to 2019 in the different regions of Nigeria. For the South East, primary data was collected from Abakaliki, Ebonyi State. In the South-South, primary data was collected from Asaba, Delta State. In the South West, primary data was collected from Barutin, Kwara State. In the North East, primary data was collected from Maiduguri, while in North West, data was collected from Gusau, Zamfara State. In the North Central, data was collected from Markurdi, Benue State. During the data collection, 48 semi-structured Key Informant Interviews (KIIs) were carried out in the six selected research areas that represented their geo-political zones. Six Focus Group Discussions (FGDs) were carried out, one for each of these six selected cities. Each of the Focus Group Discussions comprised between five and seven respondents. The idea of KIIs and FGDs is to allow the respondents to freely express their ideas comprehensively. Again, in other to get varied forms of responses, the respondents are mainly farmers however, a number of NGOs, civil servants, fertilizer sellers, government officials, transporters and aged men and women/retirees. It should be noted that the respondents cut across male and female gender of all ages and ethnic configuration. The respondents were also randomly selected through social networking. To avoid having people of similar The KIIs were three academics; two community leaders; two small scale fish farmers; rice, cassava, fish, livestock and crop farmers. All KIIs ad TIs were transcribed and analysed using thematic content analysis.

The findings revealed that climate change has negatively affected food security in Nigeria. it has also led to continuous armed confrontations over natural resources thereby undermining human security in the country.

This study is 100% original and can be assessed through turn it in evaluation.

The purpose of this paper is to analyze numerically the blowup in finite time of the solutions to a one-dimensional, bidirectional, nonlinear wave model equation for the propagation of small-amplitude waves in shallow water, as a function of the relaxation time, linear and nonlinear drift, power of the nonlinear advection flux, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of three types of initial conditions.

An implicit, first-order accurate in time, finite difference method valid for semipositive relaxation times has been used to solve the equation in a truncated domain for three different initial conditions, a first-order time derivative initially equal to zero and several constant wave speeds.

The numerical experiments show a very rapid transient from the initial conditions to the formation of a leading propagating wave, whose duration depends strongly on the shape, amplitude and width of the initial data as well as on the coefficients of the bidirectional equation. The blowup times for the triangular conditions have been found to be larger than those for the Gaussian ones, and the latter are larger than those for rectangular conditions, thus indicating that the blowup time decreases as the smoothness of the initial conditions decreases. The blowup time has also been found to decrease as the relaxation time, degree of nonlinearity, linear drift coefficient and amplitude of the initial conditions are increased, and as the width of the initial condition is decreased, but it increases as the viscosity coefficient is increased. No blowup has been observed for relaxation times smaller than one-hundredth, viscosity coefficients larger than ten-thousandths, quadratic and cubic nonlinearities, and initial Gaussian, triangular and rectangular conditions of unity amplitude.

The blowup of a one-dimensional, bidirectional equation that is a model for the propagation of waves in shallow water, longitudinal displacement in homogeneous viscoelastic bars, nerve conduction, nonlinear acoustics and heat transfer in very small devices and/or at very high transfer rates has been determined numerically as a function of the linear and nonlinear drift coefficients, power of the nonlinear drift, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of the initial conditions for nonzero relaxation times.