Reduction of waste biosolids by RAS-ozonation: Model validation and sensitivity analysis for biosolids reduction and nitrification

Biosolids reduction model by return activated sludge ozonation was validated by simulating nitrification data compiled from our pilot-scale and the literature studies. Then, a global sensitivity analysis (GSA) was performed to identify influential and non-influential parameters for biosolids reduction efficiency, change in specific nitrification activity (SNA), and alteration to expected nitrification stability. In general, the model outputs were sensitive to operational and ozone reaction parameters, but not to biochemical parameters. For operational parameters, mainly temperature and initial solids retention time (SRT) influenced all model outputs. For biosolids reduction, increase in the degradability of the influent COD decreased the reduction efficiency. For SNA, the changes were highly dependent on the influent TKN/COD ratio. Our findings also imply that the stability of the nitrification process in ozonated systems should be enhanced at constant MLVSS for warm temperatures, but could be reduced at temperatures below 12 °C and aerated SRTs below 10 days.     

Event-triggered variable horizon Supervisory Predictive control of hybrid power plants

The supervision of a hybrid power plant, including solar panels, a gas microturbine and a storage unit operating under varying solar power profiles is considered. The Economic Supervisory Predictive controller assigns the power references to the controlled subsystems of the hybrid cell using a financial criterion. A prediction of the renewable sources power is embedded into the supervisor. Results deteriorate when the solar power is unsteady, owing to the inaccuracy of the predictions for a long-range horizon of 10 s. The receding horizon is switched between an upper and a lower value according to the amplitude of the solar power trend. Theoretical results show the relevance of horizon switching, according to a tradeoff between performance and prediction accuracy. Experimental results, obtained in a Hardware In the Loop (HIL) framework, show the relevance of the variable horizon approach. Power amplifiers allow us to simulate virtual components, such as a gas microturbine, and to blend their powers with that of real devices (storage unit, real solar panels). In this case, fuel savings, reaching 15%, obtained under unsteady operating conditions lead to a better overall performance of the hybrid cell. The overall savings obtained in the experiments amount to 12%.     

Science fiction reduces the eeriness of android robots: A field experiment

As suggested by the uncanny valley hypothesis, robots that resemble humans likely elicit feelings of eeriness. Based on the psychological model of meaning maintenance, we expected that the uncanny valley experience could be mitigated through a fictional story, due to the meaning-generating function of narratives. A field experiment was conducted, in which 75 participants interacted with the humanlike robot Telenoid. Prior to the interaction, they either read a short story, a non-narrative leaflet about the robot, or they received no preliminary information. Eeriness ratings were significantly lower in the science fiction condition than in both other conditions. This effect was mediated by higher perceived human-likeness of the robot. Our findings suggest that science fiction may provide meaning for otherwise unsettling future technologies.     

Prediction of sediment,particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model

A Generalised Additive Modelling (GAM) approach is applied to prediction of both particulate and dissolved nutrient concentrations in a wet-tropical river (the Fitzroy River, Queensland, Australia). In addition to covariant terms considered in previous work (i.e. flow, discounted flow and a rising-falling limb term), we considered several new potential covariates: meteorological and hydrological variables that are routinely monitored, available in near-real time, and were considered to have potential predictive power. Of the additional terms considered, only flows from three tributaries of the Fitzroy River (namely, the Nogoa, Comet and Isaac Rivers) were found to significantly improve the model. Inclusion of one or more of these additional flow terms greatly improved results for dissolved nitrogen and dissolved phosphorus concentrations, which were not otherwise amenable to prediction. In particular, the Nogoa sub-catchment, dominated by pasture for cattle, was found to be important in determining dissolved inorganic nitrogen and phosphorus concentrations reaching the river mouth. This insight may direct further research, including future refinement of processed-based catchment models. The GAMs described here are used to provide near real-time river boundary conditions for a complex coupled hydrodynamic and biogeochemical model of the Great Barrier Reef Lagoon, and can be coupled with a forecasting hydrological model to allow integrated forecasting simulations of the catchment to coast system.     

Landau-Zener模型中纠缠演化及转移的研究

研究了受外场驱动的两个二能级系统分别与两个单模量子化光场相互作用模型中纠缠演化及转移问题。该工作主要是对外场驱动的Landau-Zener模型进行了研究，采用旋转波近似的方法，通过数值计算详细分析了二能级系统初始状态、能级间的耦合常数以及驱动外场的参数对子系统间纠缠和转移特性的影响。结果表明，适当调节模型中的参数，可以使系统初始纠缠完全转移为光腔场间的纠缠，实现二能级系统与光场间的最大纠缠转移。     

Value chain analysis of bio-coal business in Finland: Perspectives from multiple value chain members

The purpose of this study is to provide a comprehensive outline of the Value Chain (VC)¹ of bio-coal in Finland, define the proper business models of bio-coal business, and investigate the interrelationships between VC activities. The major findings are: 1) the study found significant interrelationships between support and primary activities in the bio-coal VC which suggest that we should not emphasis only the core value/primary activities of the bio-coal business, but pay more attentions to the “side values”/support activities; 2) The study identified political and environmental factors as the effective drivers, while technology and cost-profit uncertainty as major restrictions for the Finnish bio-coal business. The authors would like to suggest that instead of purely “environmental concerns”, the term “sustainability credentials” should be emphasized, which means value creating and adding items should not limit to monetary values, but consider social and environmental value propositions. 3) The study identified “low competition” in the current bio-coal business in Finland, which implies opportunities of market entrance for Finnish and international companies; 4) The study identified that the current Finnish bio-coal model is the decentralized model at the local level. However, the future Finnish bio-coal model will be a large scaled model, with a focus on export sales.     

Sustainability of ride-hailing services in China’s mobility market: A simulation model of socio-technical system transition

As a symbol of sharing economy, ride-hailing services have spread to Asia, where various forms of services have been established according to the existing socio-technical regimes, including legal, policy, and environmental concerns. China, in particular, has accepted ride-hailing services by revising existing institutions. This study analyzes China’s acceptance of ride-hailing services in the socio-technical system context set up for legacy services. Simulation modeling, combined with transition theory and an agent-based model, is used to analyze the data. This study calculates consumer disutility based on mobility market share, reflecting consumer preference, and predicts the sustainability of ride-hailing services. The simulation results conclude that legalization and socio-technical context are of importance for sustainable mobility.     

Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

An unsupervised approach to generating generic summaries of documents

We present an optimization-based unsupervised approach to automatic document summarization. In the proposed approach, text summarization is modeled as a Boolean programming problem. This model generally attempts to optimize three properties, namely, (1) relevance: summary should contain informative textual units that are relevant to the user; (2) redundancy: summaries should not contain multiple textual units that convey the same information; and (3) length: summary is bounded in length. The approach proposed in this paper is applicable to both tasks: single- and multi-document summarization. In both tasks, documents are split into sentences in preprocessing. We select some salient sentences from document(s) to generate a summary. Finally, the summary is generated by threading all the selected sentences in the order that they appear in the original document(s). We implemented our model on multi-document summarization task. When comparing our methods to several existing summarization methods on an open DUC2005 and DUC2007 data sets, we found that our method improves the summarization results significantly. This is because, first, when extracting summary sentences, this method not only focuses on the relevance scores of sentences to the whole sentence collection, but also the topic representative of sentences. Second, when generating a summary, this method also deals with the problem of repetition of information. The methods were evaluated using ROUGE-1, ROUGE-2 and ROUGE-SU4 metrics. In this paper, we also demonstrate that the summarization result depends on the similarity measure. Results of the experiment showed that combination of symmetric and asymmetric similarity measures yields better result than their use separately.     

An analytical model for optimizing the performance of graphene based silicon Schottky barrier solar cells

In this paper, a model taking into account the effects of carrier loss mechanisms has been developed. The model simulates the photovoltaic properties of the graphene/n-type silicon Schottky barrier solar cells (G/n-Si_SBSC), and it can reproduce the experimentally determined parameters of the G/n-Si_SBSC. To overcome the low efficiencies of G/n-Si_SBSC, their performances have been optimized by modifying the work function of graphene and Si properties, accounted for variation of its thickness and doping level. The obtained results show that the work function of graphene has the major impact on the device performance. Also, the temperature dependence of the G/n-Si_SBSC performance is investigated.