A markov chain monte carlo method for inverse stochastic modeling and uncertainty assessment

Unlike the traditional two-stage methods, a conditional and inverse-conditional simulation approach may directly generate independent, identically distributed realizations to honor both static data and state data in one step. The Markov chain Monte Carlo (McMC) method was proved a powerful tool to perform such type of stochastic simulation. One of the main advantages of the McMC over the traditional sensitivity-based optimization methods to inverse problems is its power, flexibility and well-posedness in incorporating observation data from different sources. In this work, an improved version of the McMC method is presented to perform the stochastic simulation of reservoirs and aquifers in the framework of multi-Gaussian geostatistics. First, a blocking scheme is proposed to overcome the limitations of the classic single-component Metropolis-Hastings-type McMC. One of the main characteristics of the blocking McMC (BMcMC) scheme is that, depending on the inconsistence between the prior model and the reality, it can preserve the prior spatial structure and statistics as users specified. At the same time, it improves the mixing of the Markov chain and hence enhances the computational efficiency of the McMC. Furthermore, the exploration ability and the mixing speed of McMC are efficiently improved by coupling the multiscale proposals, i.e., the coupled multiscale McMC method. In order to make the BMcMC method capable of dealing with the high-dimensional cases, a multi-scale scheme is introduced to accelerate the computation of the likelihood which greatly improves the computational efficiency of the McMC due to the fact that most of the computational efforts are spent on the forward simulations. To this end, a flexible-grid full-tensor finite-difference simulator, which is widely compatible with the outputs from various upscaling subroutines, is developed to solve the flow equations and a constant-displacement random-walk particle-tracking method, which enhances the comFu, J. (2008). A markov chain monte carlo method for inverse stochastic modeling and uncertainty assessment [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1969Palanci

Revisiting the Relationship between Poverty and Environmental Sustainability in Sub-Saharan African Countries using Dynamic Econometric Models

Sustainable development remains an important issue in the quest to achieve a safe and a better world. The expansion of the 8 millennium development goals into the 17 sustainable development goals is a testament of the conscious desire to improve the human environment to ensure better quality of life for its citizens. This study assembles a collection of four sophisticated econometric models to determine the impact of poverty and other variables on two indicators of environmental sustainability. Beside, economic development, the study confirmed the negative impact of poverty on both indicators of sustainable development. The results prove that poverty in sub-Saharan Africa is a threat to environmental quality and its consequential challenges. The call to promote environmentally responsible behaviours should not be focused on developed countries alone. Poverty is also associated with high levels of pollution and poor countries including countries in sub-Saharan Africa contributes must equally restrategise for effective environmental goals. The study further discloses that poverty is one of the strongest factors that affect environmental sustainability. This observation is not a contradiction to the well-established fact that prosperity or economic growth is a major precursor of unsustainable environment. On the contrary the evidence in this paper amplifies a consequence of a social crisis if they fester at both ends. In one breath, whereas economic growth or economic prosperity can compromise the quality of the environment. In conclusion, this result implies that African countries in their pursuit of economic growth, education and effective healthcare to ameliorate poverty must incorporate other aggressive strategies to hasten poverty reduction

How to model and implement connections between physical and virtual models for digital twin application

Digital twin (DT) is a virtual mirror (representation) of a physical world or a system along its lifecycle. As for a complex discrete manufacturing system (DMS), it is a digital model for emulating or reproducing the functions or actions of a real manufacturing system by giving the system simulation information or directly driven by a real system with proper connections between the DT model and the real-world system. It is a key building block for smart factory and manufacturing under the Industry 4.0 paradigm. The key research question is how to effectively create a DT model during the design stage of a complex manufacturing system and to make it usable throughout the system's lifecycle such as the production stage. Given that there are some existing discussions on DT framework development, this paper focuses on the modeling methods for rapidly creating a virtual model and the connection implementation mechanism between a physical world production system at a workshop level and its mirrored virtual model. To reach above goals, in this paper, the discrete event system (DES) modeling theory is applied to the three-dimension DT model. First, for formally representing a manufacturing system and creating its virtual model, seven basic elements: controller, executor, processor, buffer, flowing entity, virtual service node and logistics path of a DMS have been identified and the concept of the logistics path network and the service cell is introduced to uniformly describe a manufacturing system. Second, for implementing interconnection and interaction, a new interconnection and data interaction mechanism between the physical system and its virtual model for through-life applications has been designed. With them, each service cell consists of seven elements and encapsulates input/output information and control logic. All the discrete cells are constructed and mapped onto different production-process-oriented digital manufacturing modules by integrating logical, geometric and data models. As a result, the virtual-physical connection is realized to form a DT model. The proposed virtual modeling method and the associated connection mechanism have been applied to a real-world workshop DT to demonstrate its practicality and usefulness

Determination of vehicle requirements of AGV system based on discrete event simulation and response surface methodology

The determination of AGV vehicle requirements in a manufacturing system has a great impact on the system performance. This paper first defines the AGV vehicle requirement determination as a general optimization problem, and secondly develops a new AGV vehicle requirement determination method capable of effective solving the problem. This method features with the combination of discrete event simulation (DES), sensitivity analysis, fractional factorial design (FFD) and response surface methodology (RSM). Tests and comparisons with other simulation based methods have shown that the proposed method combining the simulation method with analytical method, can make full use of their respective advantages and overcome the defects of existing methods. It is more practical

Visualizing the transfer-messenger RNA as the ribosome resumes translation

Bacterial ribosomes that are stalled on mRNAs lacking a stop codon can be rescued by a process called ‘transtranslation' that involves the ribonucleoprotein complex tmRNA–SmpB. This cryo-EM study, and the copublished study by Weis et al, reveal how translation on tmRNA is resume

Recent Advances on the Halo- and Cyano-Trifluoromethylation of Alkenes and Alkynes

Incorporation of fluorine into organic molecules is a well-established strategy in the design of advanced materials, agrochemicals, and pharmaceuticals. Among numerous modern synthetic approaches, functionalization of unsaturated bonds with simultaneous addition of trifluoromethyl group along with other substituents is currently one of the most attractive methods undergoing wide-ranging development. In this review article, we discuss the most significant contributions made in this area during the last decade (2012−2021). The reactions reviewed in this work include chloro-, bromo-, iodo-, fluoro- and cyano-trifluoromethylation of alkenes and alkynes

Bayesian inference of population expansions in domestic bovines

The past population dynamics of four domestic and one wild species of bovine were estimated using Bayesian skyline plots, a coalescent Markov chain Monte Carlo method that does not require an assumed parametric model of demographic history. Four domestic species share a recent rapid population expansion not visible in the wild African buffalo (Syncerus caffer). The estimated timings of the expansions are consistent with the archaeological records of domestication

Climate change : strategies for mitigation and adaptation

The sustainability of life on Earth is under increasing threat due to humaninduced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and global stability. These trends call for the implementation of mitigation and adaptation strategies. Pollution and environmental degradation exacerbate existing problems and make people and nature more susceptible to the effects of climate change. In this review, we examine the current state of global climate change from different perspectives. We summarize evidence of climate change in Earth’s spheres, discuss emission pathways and drivers of climate change, and analyze the impact of climate change on environmental and human health. We also explore strategies for climate change mitigation and adaptation and highlight key challenges for reversing and adapting to global climate change