Extremophiles in Sustainable Bioenergy Production as Microbial Fuel Cells

Microbial fuel cell (MFC) technology is considered one of the renewable sources of energy for the production of bioelectricity from waste. Due to the depletion of fossil fuels and environmental considerations, MFC haa garnered increasing importance as it is a sustainable and environmentally-friendly method of generation of bioenergy. In MFC, electroactive bacteria (EAB) and biofilms are harnessed to convert organic substances to electrical energy. Extremophiles survive in extreme environments, and they have demonstrated potential applications in microbial electrical systems (MES) and MFC technology. The key limitations of MFC are the low power output and engineering constraints of the fuel cell. Hence, it is imperative to understand the genetics, key metabolic pathways, and molecular mechanisms of the EAB for enhancing the power generation in MFC. This chapter gives a brief overview of the scope and applications of extremophiles in wastewater treatment, bioelectricity, and biohydrogen production using MFC, eventually enhancing the functional efficiency of MFC.

A FAST assembly simulation analysis method for hull blocks with engineering constraints

In order to effectively improve the assembly efficiency for hull blocks, an assembly simulation analysis method considering engineering constraints is proposed in this paper, and an integrated system of shipbuilding accuracy analysis and assembly analysis considering multi-constraints is developed. The method is divided into pre-matching model and fine matching model. In the pre-matching model, an Improved Coherent Point Drift (ICPD) algorithm is used to obtain more accurate initial matching values. The fine matching model firstly uses the Analytic Hierarchy Process (AHP) algorithm to automatically obtain the constrained weights, then the weights vector is used to add the assembly constraints for hull blocks such as straightness, hard point constraints etc. into the multi-objective optimization function. By solving the function, the optimum positioning location and the most reasonable adjustment scheme are obtained. This method shortens the occupancy time of the equipment used to build the hull, reduces the workload of the staff, and improves the efficiency and quality of shipbuilding. The integrated system adds engineering constraints analysis module and the function of automatically finding and eliminating error measurement points. Through the verification of the examples, the integrated system realizes the automation and intellectualization of the assembly for hull blocks.

Dragline Stripping Method Review to Maximize Productivity and Coal Recovery at Major Fault Zone - A Case Study

Strategic mine planning is substantial to ensure maximum coal recovery across severely faulted geological conditions with predicted below water table excavation. An optimum plan would improve multiple engineering constraints to deliver high recovery with safety and best possible efficiency of machineries deployed at the problematic area. One such case is of Southern pit at Sasan coal mine, India with fault throw varying from 3m to 40m through a series of parallel merging faults located closely within strike length of 800m. It has challenged the mine for better coal recovery, machine performance and scheduled pit progression over recent corner strips. This paper describes how the mine has overcome complexities of operating in the fault area with localised consistent water seepage. It discusses new pre-strip parameters adopted to enhance dragline productivity, preparation of stable dragline operating bench under given bottom wet overburden conditions, and coal extraction plan which has been incorporated together with dragline stripping plan to improve recovery at the area of study. Several aspects of process have been highlighted during implementation, such as requirement of early dewatering setup for dragline low-wall stability and coal roof cleaning.

Joint Extraction of Multiple Relations and Entities from Building Code Clauses

The extraction of regulatory information is a prerequisite for automated code compliance checking. Although a number of machine learning models have been explored for extracting computer-understandable engineering constraints from code clauses written in natural language, most are inadequate to address the complexity of the semantic relations between named entities. In particular, the existence of two or more overlapping relations involving the same entity greatly exacerbates the difficulty of information extraction. In this paper, a joint extraction model is proposed to extract the relations among entities in the form of triplets. In the proposed model, a hybrid deep learning algorithm combined with a decomposition strategy is applied. First, all candidate subject entities are identified, and then, the associated object entities and predicate relations are simultaneously detected. In this way, multiple relations, especially overlapping relations, can be extracted. Furthermore, nonrelated pairs are excluded through the judicious recognition of subject entities. Moreover, a collection of domain-specific entity and relation types is investigated for model implementation. The experimental results indicate that the proposed model is promising for extracting multiple relations and entities from building codes.

Re-Sounding Alarms: Designing Ergonomic Auditory Interfaces by Embracing Musical Insights

Auditory alarms are an important component of human–computer interfaces, used in mission-critical industries such as aviation, nuclear power plants, and hospital settings. Unfortunately, problems with recognition, detection, and annoyance continue to hamper their effectiveness. Historically, they appear designed more in response to engineering constraints than principles of hearing science. Here we argue that auditory perception in general and music perception in particular hold valuable lessons for alarm designers. We also discuss ongoing research suggesting that the temporal complexity of musical tones offers promising insight into new ways of addressing widely recognized shortcomings of current alarms.

A Point Set Analysis Method for Hull Blocks Based on CPD and Engineering Constraints

A point set analysis method considering the practical engineering constraints has been proposed in this article. First, the coherent point drift method was used to obtain the initial values of data analysis. Second, the error distribution in different directions was expressed by weight vectors. Last, the multiobjective optimization model was built and the engineering constrains were introduced into the multioptimization objective function to achieve the optimal data analysis results. The experimental results proved that the method could obtain the reasonable data analysis results, which met the engineering constraints. It provides the important basis for the subsequent assembly.

Multiple constraints and objectives should inform the negotiated filling of the Grand Ethiopian Renaissance Dam

<p>This study analyzes the implications of a variety of filling approaches of the Grand Ethiopian Renaissance Dam (GERD) for the outlet management and dam engineering. A daily water balance model of the GERD is developed and used to investigate the ability of the GERD outlets to enable six reservoir filling scenarios. Results show that the turbines’ outlets, the bottom outlets, and the spillways would sufficiently provide downstream releases during the steady-state operation of the GERD. The river diversion outlets of the GERD are necessary to enable agreements on reservoir filling and the Ethiopian turbine phasing-in plan. The use of the river diversion outlets requires compliance with dam engineering constraints such as steel lining, head limit, and maximum flow speed. We propose a multi-objective optimization framework for reservoir filling whereby dam engineering constraints are considered in the negotiations on the initial filling of multi-year storage reservoirs.</p>