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Ferredoxin (Fd) is a small metalloprotein holding one or two Fe-S clusters in its inner shell. Like many other metalloproteins, Fd is redox active and involved in electron transfer during cellular metabolism. The electrons from reduced Fd are mostly used to regenerate NADPH under physiological conditions. Increasing number of attempts have been reported, however, where Fd delivers electrons to enable biosynthesis of valuable compounds. Various compounds ranging from H2 to vitamin D3 have been synthesized successfully using electrons mediated by Fd molecules. In this review, we provide an overview of the engineering studies utilizing Fd for biosynthesis of targeted molecules. The emphasis is on the role and activity of Fd as well as the methods used to improve the rate of electron transfer. Both microbial and electrochemical biosynthesis technologies are described and compared with respect to productivity and the compound being produced. In addition to the ferredoxins from the microbial organisms, artificially designed de novo types are described, highlighting the potential of the emerging computational methods used in metabolic and protein engineering. We believe that the recent advances in utilization of Fd for biosynthesis can result in breakthrough innovation across the biotechnology industry. [ABSTRACT FROM AUTHOR]

H 2 is an important commodity chemical that can also be used as an alternative fuel. The way how H 2 is currently produced and distributed, however, is not compatible with this usage. This is primarily due to the high costs associated with storing and delivering H 2 from the centralized production facilities to the end-use sites like H 2 stations that will be distributed throughout a region. Here, we propose a methodology for configuring the distributed H 2 production system that minimizes the overall cost in delivering H 2 to demand sites while meeting the safety requirements. The methodology also takes into account changes in costs with respect to production volume by applying the concept of economy of scale. The proposed methodology is applied to a hypothetical case involving H 2 supply to three stations. The results demonstrate significant reduction in the overall cost when adopting the optimal solution found by our methodology compared to the traditional, centralized production system. Insights on the cost structures associated with producing and delivering H 2 are provided, as well as specific improvements required to make H 2 affordable at the level defined by the international society. • A new methodology for configuring sizes and layout of distributed H 2 production system. • Comparative analysis between the centralized and distributed H 2 production system. • Costs of various H 2 production technologies and sensitivity analyses of key parameters. [ABSTRACT FROM AUTHOR]

Cell-free systems utilize a subset of cellular components without intact cell wall and/or membranes. The system was first invented for use in fermentation. Subsequent improvements enabled its application in protein synthesis, which is still the most common use of the system. Lately, attempts have been reported where metabolic engineering concepts and techniques were applied to cell-free systems and/or vice-versa. These attempts and advances led to exciting discoveries about biochemical reactions, as well as properties and/or structures of cellular components that make up complex biological systems. This review will first provide a basic overview and brief history of the cell-free system. Then, explanation on recent advances in the field will be provided, followed by notes on the innovative applications. Future outlook of the field will also be covered with the emphasis on how the emerging data science methods can be applied to improve the system and its applicability. [ABSTRACT FROM AUTHOR]

Biological H 2 production is one of the alternative technologies for producing H 2 in a renewable and sustainable fashion. The technology often relies on the [FeFe] hydrogenase enzyme for catalyzing the H 2 production reaction from protons and electrons as it is highly efficient. The high O 2 sensitivity of the enzyme have been one of the key obstacles for implementing the technology, but recent findings showed the feasibility of improving O 2 tolerance via protein engineering. In this study, we investigated the changes in the O 2 tolerance and aerobic H 2 production activity of an [FeFe] hydrogenase by replacing methionines on the surface with leucines. None of the mutations were detrimental to protein folding, and a few were able to exert either positive or negative influence on the O 2 tolerance of the enzyme. We combined the mutation exhibiting the highest improvement in O 2 tolerance with the rest of the Met – Leu replacements; however, the results indicated non-synergistic impact on the tolerance. Combinations with the other types of mutations that have been reported previously also failed to further improve the O 2 tolerance of the hydrogenase. These results provide new insights on how mutagenesis affects the enzyme's functional properties, as well as the molecular mechanism(s) behind the tolerance. • A novel mutation that enhances the O 2 tolerance of the [FeFe] hydrogenase. • Analysis of the combinatorial mutagenesis' influence on the key functional properties. • Protein engineering work employing both in silico and experimental methods. [ABSTRACT FROM AUTHOR]

Abstract Photosynthetic H 2 production has been a compelling but elusive objective. Here we describe how coordinated bioreactor, metabolic pathway, and protein engineering now suggest feasibility for the sustainable, solar-powered production of a storable fuel to complement our expanding photovoltaic and wind based capacities. The need to contain and harvest the gaseous products provides decisive solar bioreactor design advantages by limiting O 2 exposure to prolific, but O 2 -sensitive H 2 producing enzymes—[FeFe] hydrogenases. CO 2 supply and cell growth can also be limited so that most of the photosynthetic reduction capacity is directed toward H 2 production. Yet, natural [FeFe] hydrogenases are still too O 2 sensitive for technology implementation. We report the discovery of new variants and a new O 2 tolerance mechanism that significantly reduce the sensitivity to O 2 exposure without lowering H 2 production rates or losing electrons to O 2 reduction. Testing the improved hydrogenases with a biologically derived, light-dependent electron source provides evidence that this game changing technology has the potential for sustainable large-scale fuel production. Highlights • A single Cys replacement improved O 2 tolerance with only a minor activity loss. • Saturation mutagenesis found synergistic, non-Cys mutations for improving O 2 tolerance. • Higher O 2 tolerance enabled more than 300% improvement in light-driven H 2 production. [ABSTRACT FROM AUTHOR]

Hydrogenases, ferredoxins, and ferredoxin-NADP+ reductases (FNR) are redox proteins that mediate electron metabolism in vivo, and are also potential components for biological H2 production technologies. A high-throughput H2 production assay device (H2PAD) is presented that enables simultaneous evaluation of 96 individual H2 production reactions to identify components that improve performance. Using a CCD camera and image analysis software, H2PAD senses the chemo-optical response of Pd/WO3 thin films to the H2 produced. H2PAD-enabled discovery of hydrogenase and FNR mutants that enhance biological H2 production is reported. From a library of 10 080 randomly mutated Clostridium pasteurianum [FeFe] hydrogenases, we found a mutant with nearly 3-fold higher H2 production specific activity. From a library of 400 semi-randomly mutated Oryza sativa FNR, the top hit enabled a 60 % increase in NADPH-driven H2 production rates. H2PAD can also facilitate elucidation of fundamental biochemical mechanisms within these systems. [ABSTRACT FROM AUTHOR]

Hydrogenases, ferredoxins, and ferredoxin-NADP+ reductases (FNR) are redox proteins that mediate electron metabolism in vivo, and are also potential components for biological H2 production technologies. A high-throughput H2 production assay device (H2PAD) is presented that enables simultaneous evaluation of 96 individual H2 production reactions to identify components that improve performance. Using a CCD camera and image analysis software, H2PAD senses the chemo-optical response of Pd/WO3 thin films to the H2 produced. H2PAD-enabled discovery of hydrogenase and FNR mutants that enhance biological H2 production is reported. From a library of 10 080 randomly mutated Clostridium pasteurianum [FeFe] hydrogenases, we found a mutant with nearly 3-fold higher H2 production specific activity. From a library of 400 semi-randomly mutated Oryza sativa FNR, the top hit enabled a 60 % increase in NADPH-driven H2 production rates. H2PAD can also facilitate elucidation of fundamental biochemical mechanisms within these systems. [ABSTRACT FROM AUTHOR]

In a real stereo vision system, the acquired stereo images suffer from varying radiometric changes due to illumination and camera parameter changes. Therefore, we propose an effective matching scheme created by building a content adaptive descriptor. Specifically, the descriptor reflects image contents and its element are adaptively weighted and applied to estimate the correct corresponding pixels based on the entropy energy function even under radiometric changes. For the performance evaluation, the proposed scheme is compared with the state-of-art algorithm using Middlebury and KITTI Vision stereo datasets that have radiometric changes. Specifically, 24 of 71 indoor image pairs in the Middlebury and 3 of 7 outdoor pairs are selected, respectively. Experimental result shows that the proposed method reports 6.23% bad pixel matching on average, but it outperforms state-of-the-art algorithms by reducing around 2% bad pixel matching error, which achieves about 16.5% performance improvement. [ABSTRACT FROM AUTHOR]

Improving a functional property of an enzyme via mutagenesis is still a challenging problem due to vast search space and difficulty of predicting the effects of mutation(s). Machine learning has proven to be proficient in solving similar problems with unprecedented speed owing to the latest advances in computing power and analytical algorithms. In this study, we investigate the performance of machine learning methods in predicting the H2 production activity and O2 tolerance of the hydrogenase variants. Experimentally measured activities and tolerance of 377 variants having single or double amino acid replacements are used to train and test seven types of machine learning models. Binary representation of amino acid sequence as well as the series of vectors quantifying physicochemical properties of amino acids, namely VHSE, are employed as features representing each variant. The results show that the VHSE enable higher performance, especially with respect to correlation coefficient and coefficient of determination in addition to the root mean square error. Next, the analysis of model performance with respect to changes in the data size and heterogeneity is conducted to provide insights on designing effective mutagenesis library for applying machine learning. The best performance was obtained when support vector machine or ridge regression was trained using a large, homogeneous data. In this manner, our study reveals the factors affecting the performance of machine learning in identifying the enzyme variants with enhanced function. [ABSTRACT FROM AUTHOR]

Abstract: We perform the first long-term (>1 year) continuous adjoint simulations with a global atmospheric chemistry–transport model focusing on population exposure to fine particulate matter (PM2.5) and associated risk of early death. Sensitivities relevant to intercontinental and high-altitude PM pollution are calculated with particular application to aircraft emissions. Specifically, the sensitivities of premature mortality risk in different regions to NO x , SO x , CO, VOC and primary PM2.5 emissions as a function of location are computed. We apply the resultant sensitivity matrices to aircraft emissions, finding that NO x emissions are responsible for 93% of population exposure to aircraft-attributable PM2.5. Aircraft NO x accounts for all of aircraft-attributable nitrate exposure (as expected) and 53% of aircraft-attributable sulfate exposure due to the strong “oxidative coupling” between aircraft NO x emissions and non-aviation SO2 emissions in terms of sulfate formation. Of the health risk-weighted human PM2.5 exposure attributable to aviation, 73% occurs in Asia, followed by 18% in Europe. 95% of the air quality impacts of aircraft emissions in the US are incurred outside the US. We also assess the impact of uncertainty or changes in (non-aviation) ammonia emissions on aviation-attributable PM2.5 exposure by calculating second-order sensitivities. We note the potential application of the sensitivity matrices as a rapid policy analysis tool in aviation environmental policy contexts. [Copyright &y& Elsevier]

PDF/A is a version of Portable Document Format designed for archiving and preservation. Due to its popularity, many electronic documents exist in PDF format, and the ability to convert an existing PDF into a conforming PDF/A file is as important, if not more, as being able to produce documents in PDF/A format. The Florida Digital Archive conducted a study to select a PDF to PDF/A conversion application as part of its format normalization strategy in the summer of 2012. This article documents the evaluation process and presents the results in such a way that they provide insight into challenges and potential drawbacks during similar evaluation or implementation. [ABSTRACT FROM AUTHOR]

Abstract: During the last few decades, energy planning has focused on meeting domestic demand at lower total costs. However, global warming and the shared recognition of it have transformed the problem of energy planning into a more complex task with a greater number of issues to be considered. Since the key issue is to reduce greenhouse effects, governments around the world have begun to make investments in renewable energy systems (e.g., hydro, wind, solar, and/or biomass power). The relatively high costs of renewable energy systems and the uncertain outlook of their rate of diffusion in the market make it difficult to heavily rely on them. The uncertain variations in production cost over time are especially challenging. To handle uncertainties, the concept of the learning rate was adopted in this study so as to compute the costs of energy systems in the future and Monte Carlo simulation was performed. The aim of this study was to optimize plans of conventional and prospective renewable energy systems with respect to production cost. The production cost included capital, fixed, variable, and external costs. For the case study, the energy situation in South Korea was used. The results of the case study where the proposed methodology was applied could provide useful insights economically and strategies of sustainable energy management for ambiguous environments. [Copyright &y& Elsevier]

Abstract: This paper studies economics of renewable energy systems with consideration of future prospects on costs and uncertain external conditions that may affect competitiveness in the power plant market. The concept of learning curve is adopted to compute estimates on the costs of installing and operating renewable energy systems in the future; fuel costs and carbon price are modeled as scenario-dependent variables to analyze their impact on total costs under different scenarios. The proposed approach allows evaluation and comparison of total costs necessary in implementing renewable energy plans under varying technological, and/or economical conditions that face uncertainty at present. Moreover, analyzing the evaluation results further with techniques like sensitivity analysis can identify factors central to reducing the total costs. As an illustrative case-study, the Korean government’s renewable energy plan has been evaluated accordingly, under three different scenarios defined by International Energy Agency (IEA). The evaluation results indicate minor changes in total costs of achieving the plan among three scenarios, mainly due to counterbalancing between the price of fossil fuels and carbon price. Further analyses revealed factors central to lowering the total costs necessary in implementing the plan—hybridization between renewable energy systems, reduction of biomass production costs via technological innovation, increasing learning rates by focusing on R&D and international cooperation. [Copyright &y& Elsevier]

Abstract: In this paper, a new approach has been proposed that allows a robust optimization of sustainable energy planning over a period of years. It is based on the modified energy flow optimization model (EFOM) and minimizes total costs in planning capacities of power plants and CCS to be added, stripped or retrofitted. In the process, it reduces risks due to a high volatility in fuel prices; it also provides robustness against infeasibility with respect to meeting the required emission level by adopting a penalty constant that corresponds to the price level of emission allowances. In this manner, the proposed methodology enables decision makers to determine the optimal capacities of power plants and/or CCS, as well as volumes of emissions trading in the future that will meet the required emission level and satisfy energy demand from various user-sections with minimum costs and maximum robustness. They can also gain valuable insights on the effects that the price of emission allowances has on the competitiveness of RES and CCS technologies; it may be used in, for example, setting appropriate subsidies and tax policies for promoting greater use of these technologies. The proposed methodology is applied to a case based on directions and volumes of energy flows in South Korea during the year 2008. [Copyright &y& Elsevier]

Abstract: The modification of the electrical characteristics of field-effect transistors (FETs) with channels composed of n- or p-type silicon nanowires (SiNWs) by oxygen plasma treatment is investigated in this study. The SiNWs obtained from silicon bulk wafers are <111> surface-oriented and their doping concentrations are ∼1021 and ∼1017 cm−3 for the n- and p-type SiNWs, respectively. After the back-gate SiNWFETs were subjected to oxygen plasma treatment, the magnitude of the drain current of the n-type SiNWs was decreased, whereas that of the p-type SiNWs was increased, while the gate-dependent characteristics of both of types of SiNWs were improved. The changes in the electrical characteristics are due to the adsorption of oxygen ions on the surface of the SiNWs. To verify the effect of the oxygen ions, the SiNWFETs were kept in a vacuum for 24h whereupon their electrical characteristics tended to revert to their inherent state. [Copyright &y& Elsevier]

We report a precision medicine platform that evaluates the probability of chemotherapy drug efficacy for canine lymphoma by combining ex vivo chemosensitivity and immunophenotyping assays with computational modelling. We isolated live cancer cells from fresh fine needle aspirates of affected lymph nodes and collected post‐treatment clinical responses in 261 canine lymphoma patients scheduled to receive at least 1 of 5 common chemotherapy agents (doxorubicin, vincristine, cyclophosphamide, lomustine and rabacfosadine). We used flow cytometry analysis for immunophenotyping and ex vivo chemosensitivity testing. For each drug, 70% of treated patients were randomly selected to train a random forest model to predict the probability of positive Veterinary Cooperative Oncology Group (VCOG) clinical response based on input variables including antigen expression profiles and treatment sensitivity readouts for each patient's cancer cells. The remaining 30% of patients were used to test model performance. Most models showed a test set ROC‐AUC > 0.65, and all models had overall ROC‐AUC > 0.95. Predicted response scores significantly distinguished (P <.001) positive responses from negative responses in B‐cell and T‐cell disease and newly diagnosed and relapsed patients. Patient groups with predicted response scores >50% showed a statistically significant reduction (log‐rank P <.05) in time to complete response when compared to the groups with scores <50%. The computational models developed in this study enabled the conversion of ex vivo cell‐based chemosensitivity assay results into a predicted probability of in vivo therapeutic efficacy, which may help improve treatment outcomes of individual canine lymphoma patients by providing predictive estimates of positive treatment response. [ABSTRACT FROM AUTHOR]

In jurisdictions including the US and the EU ground transportation and marine fuels have recently been required to contain lower concentrations of sulfur, which has resulted in reduced atmospheric SOx emissions. In contrast, the maximum sulfur content of aviation fuel has remained unchanged at 3000 ppm (although sulfur levels average 600 ppm in practice). We assess the costs and benefits of a potential ultra-low sulfur (15 ppm) jet fuel standard ("ULSJ"). We estimate that global implementation of ULSJ will cost US$1-4bn per year and prevent 900-4000 air quality-related premature mortalities per year. Radiative forcing associated with reduction in atmospheric sulfate, nitrate, and ammonium loading is estimated at +3.4 mW/m2 (equivalent to about 1/10th of the warming due to CO2 emissions from aviation) and ULSJ increases life cycle CO2 emissions by approximately 2%. The public health benefits are dominated by the reduction in cruise SOx emissions, so a key uncertainty is the atmospheric modeling of vertical transport of pollution from cruise altitudes to the ground. Comparisons of modeled and measured vertical profiles of CO, PAN, O3, and 7Be indicate that this uncertainty is low relative to uncertainties regarding the value of statistical life and the toxicity of fine particulate matter. [ABSTRACT FROM AUTHOR]