339,113 research outputs found

    A two-stage heuristic approach for fleet management optimization under time-varying demand

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    202105 bchyNot applicableRGCOthersRGC: General Research Funds 15280116,General Research Funds 15224818Others: P0001008Early release36 month

    Biotin synthesis in α-proteobacteria

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    Pimelic acid, a seven carbon α, ω-dicarboxylic acid (heptanedioic acid), has long been known to provide most biotin carbon atoms including all those of the valeryl side chain. Nevertheless, the first pathways of pimelate moiety synthesis have only recently been elucidated. Two mechanistically distinct pathways, those of Escherichia coli and Bacillus subtilis, are known. Both use fatty acid synthesis plus dedicated biotin synthetic enzymes to assemble the pimelate moiety. In contrast, the α-proteobacteria, which include important plant and mammalian pathogens plus plant symbionts, lack the E. coli and B. subtilis pimelate synthesis genes and instead encode a putative 3-ketoacyl-ACP synthase enzyme called BioZ in their biotin gene clusters. We report a novel pathway in which BioZ proteins catalyze a 3-ketoacyl-ACP synthase III-like reaction to produce pimeloyl-ACP. In this reaction five of the seven pimelate carbon atoms are derived from glutaryl-CoA, an intermediate in lysine degradation, rather than the fatty acid synthesis route used by E. coli and B. subtilis. The synthesis of glutaryl-CoA was long been thought to be a ligation of CoA to glutarate activated by ATP However such enzyme has never been identified. It was later thought to be a promiscuous conversion of oxo-adipate to glutaryl-CoA by ketoglutaryl-CoA dehydrogenase. The first publication clearly demonstrated a conversion of glutarate to glutaryl-CoA was characterized by the protein encoded by human C7orf10. The putative transferases having about 40% sequence similarity from α-proteobacteria strains and E. coli were purified and shown to catalyze transfer of CoA from succinyl-CoA to glutarate. They also have promiscuity to CoA donor and receptor with different chain length. Finally, disruption of the caiB gene resulted in biotin auxotrophy in Agrobacterium tumefaciens C58 and limited biotin synthesis in E. coli ΔbioC ΔbioH double deletion strains supplemented with bioZ. Structure and substrate specificity of BioZ has also been studied during this thesis work. The BioZ proteins, like the 3-ketoacyl-ACP synthase III fatty acid synthesis proteins (FabHs) use a Cys-His-Asn triad to catalyze the Claisen-like condensation reaction. Mutation of the catalytic cysteine assigned by sequence alignment to alanine resulted in an inactive enzyme and biotin auxotrophy in A. tumefaciens. The positively charged guanidino group of an arginine 147 residues in BioZ is pointing towards the negatively charged carboxyl group of glutaryl-CoA in the crystal structure of this mutant protein, and thus seems likely to function to stabilize the negative charge within the tunnel. However, mutation of the analogous threonine to arginine in E. coli FabH didn’t complement the pimeloyl-ACP auxotroph E. coli MG1655 ΔbioC ΔbioH double deletion strain for growth. Arginine 147 is likely not sufficient to determine substrate specificity in BioZ.LimitedAuthor requested closed access (OA after 2yrs) in Vireo ETD syste

    High pressure-temperature phase relations of basaltic crust up to mid-mantle conditions

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    A substantial amount of subducted basaltic crusts may exist in the lower mantle. It features distinct chemical composition from the peridotitic mantle and plays important roles in the chemical and dynamic evolution of Earth's interior. However, the chemical composition of mineral phases present in basaltic crust in the lower mantle is still poorly constrained. Here, we determined phase relations of normal mid-ocean ridge basalt (MORB) up to 52 GPa at 2000 K by multi-anvil press. Throughout our experiments, the mineral assemblages consist of five phases including bridgmanite, stishovite, calcium perovskite (davemaoite), calcium ferrite and new hexagonal aluminous phases. The density of MORB calculated from our phase assemblages and previously published thermoelastic data is 2-3% higher than that of the average mantle, which is consistent with literature. The new hexagonal aluminous phase is a host of potassium but only occupies 1-2 vol.% due to limited abundance of potassium in normal MORB. This indicates that the new hexagonal aluminous phase doesn't affect the elastic properties of basalt. Electron energy-loss spectra of recovered basaltic Al-rich bridgmanite show significant enrichment of ferrous iron (75-85%) compared with peridotitic Al-poor bridgmanite (∼30%), which is against previous studies showing that ferric iron ratio in bridgmanite increases with Al content. Ferric iron exhibits strong partitioning into the new hexagonal aluminous phase (41-64%), whereas bridgmanite (14-28%) and calcium ferrite phase (5-27%) remain Fe2+^{2+}-enriched. The oxygen vacancy component of MgAlO2.5 in bridgmanite is ∼11% up to 40 GPa, which is much higher than that in peridotitic bridgmanite (2-3%), possibly producing a viscosity contrast in the mid-mantle that would explain slab stagnation and plume thinning between 660 km and 1000 km depth. The presence of ferrous iron-rich bridgmanite in the deep lower mantle may contribute to seismic features of large low-shear-velocity provinces

    Imbalanced learning using actuarial modified loss function in tree-based models

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    The point mass at zero and the heavy tail of insurance loss distribution poses the challenge to apply traditional methods directly to claim loss modeling. Via an illustrative simple dataset, this thesis first pinpoints the pitfall in the traditional tree-based algorithm’s splitting function. This thesis then modifies the function to remedy the imbalance issue presented in the insurance loss modeling. We propose two novel actuarial modified loss functions, namely, weighted sum of squared error and Canberra loss functions. This modification imposes a significant penalty on grouping nonzero observations with zero ones at the splitting procedure. We examine and compare the predictive performance of such actuarial modified tree-based models in relation to the traditional models in a synthetic dataset. Our studies show that, such modification results in improved prediction and completely different tree structures.LimitedAuthor requested closed access (OA after 2yrs) in Vireo ETD syste

    Recent advances and future challenges in printed batteries

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    The continuous advances in smart and multifunctional materials and the corresponding growth of the Internet of Things require novel battery concepts with improved integration in different substrates and devices, leading to more efficient energy storage devices with higher power and energy density. These new batteries can be obtained through printing technologies, as they present interesting characteristics such as being thin, flexible, low cost and eco-friendlier, for an increasing number of applications such as smart cards, radio-frequency identification, portable medical diagnostic systems and sensors, among others. Further, printing technologies allow simple and low-cost up-scaling and, therefore, rapid technology transfer. The present review summarizes the recent advances in 2D and 3D printed batteries. 2D and 3D printing technologies are summarized and the state of the art on printed batteries is presented, divided by lithium batteries, Zn/MnO2 batteries, and other battery types. In recent years, printed batteries are being intensively developed by 3D printing technologies, where further developments in ink properties, compatibility with the manufacturing process and integration with devices are still required. In this context, the future challenges in the area of printed batteries are also presented and discussed.The authors thank the FCT (Fundação para a Ciência e Tecnologia) for financial support under the framework of Strategic Funding grants UID/FIS/04650/2019, UID/EEA/04436/2019 and UID/QUI/0686/2019; and project PTDC/FISMAC/28157/2017. The authors also thank the FCT for financial support under grants SFRH/BPD/112547/2015 (C.M.C.) and Investigator FCT Contract CEECIND/00833/ 2017 (R.G.) as well POCH and European Union. Financial support from the Basque Government Industry and Education Departments under the ELKARTEK, HAZITEK and PIBA (PIBA-2018-06) programs, respectively, is also acknowledge

    Microbial protein production by autotrophic nitrogen-fixing hydrogen-oxidizing bacteria

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    Interactive visualization framework for space plasma data sets

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    The capability of visualizing numerical data sets to graphs is imperative to our understanding of space physics. However, traditional visualization tools used in the space science community are either proprietary, lack portability or require paid license subscriptions. Therefore we are attempting to resolve these shortcomings by developing cross-platform, free-to-use, easily set up interactive visualization tools that is accessible to any web browsers. This project will showcase five different applications based on a Python framework called Dash developed by plotly. These applications are proved to be capable of visualizing 3D space physics data sets including satellite measurements, ground measurements, or numerical model simulation results. The first two applications use the Cluster II satellite measurement data set provided by ESA, courtesy of Dr.~Elena Kornberg from the Max Plank Institute. The third and the fourth applications use the simulated magnetic field data generated by the Tsyganenko magnetic field model. The fifth application visualizes ion density from an empirical model based on geo-tail data while the final application can plot calculation results from the Polar Wind Outflow Model. By demonstrating the advantages of our visualization tool, we hope to show the significance of a generalized framework, which could benefit the entire space science community. Due to the time constraint of this project, we did not explore all the options provided by Dash. However, we firmly believe this tool has great potential and will be more powerful with additional features such as parallel computing, cloud computing, and the ability to record animations.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste

    New insights in the performance and reuse of rGO/TiO2 composites for the photocatalytic hydrogen production

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    The viability of the photocatalytic hydrogen production is closely related to the performance and long term stability of the photocatalyst. In this work rGO/TiO2 composites have been synthetized with graphene oxide (GO) ratios from 1% to 10% and experimentally assessed towards hydrogen generation from methanol solutions. The performance of the composite with 2% of rGO (2 GT) has been compared to bare TiO2 working with 20% volume methanol solution. The hydrogen production initial rate showed similar values with both photocatalysts decreasing after about 24 h. Further analysis of the photocatalytic process at longer times showed the negative influence of hydrogen accumulation in the reaction system. Thus, an experimental procedure with argon purge was developed and the behavior of TiO2 and 2 GT photocatalysts was compared. It is concluded that TiO2 keeps its activity after 8 operation cycles while 2 GT performance reduces progressively. This can be attributed to the further reduction of GO and the increase of defects in its structure.Financial support from projects CTM2015-69845-R (MINECO/FEDER, UE) and RTI2018-099407-B-I00 (MCIU/AEI/FEDER, UE) is gratefully acknowledged. Juan Corredor is grateful to a FPI contract grant (BES-2016-079201)

    Loss minimization yields multicalibration for large neural networks

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    Multicalibration is a notion of fairness that aims to provide accurate predictions across a large set of groups. Multicalibration is known to be a different goal than loss minimization, even for simple predictors such as linear functions. In this note, we show that for (almost all) large neural network sizes, optimally minimizing squared error leads to multicalibration. Our results are about representational aspects of neural networks, and not about algorithmic or sample complexity considerations. Previous such results were known only for predictors that were nearly Bayes-optimal and were therefore representation independent. We emphasize that our results do not apply to specific algorithms for optimizing neural networks, such as SGD, and they should not be interpreted as "fairness comes for free from optimizing neural networks"

    Decentralized projected Riemannian gradient method for smooth optimization on compact submanifolds

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    We consider the problem of decentralized nonconvex optimization over a compact submanifold, where each local agent's objective function defined by the local dataset is smooth. Leveraging the powerful tool of proximal smoothness, we establish local linear convergence of the projected gradient descent method with unit step size for solving the consensus problem over the compact manifold. This serves as the basis for analyzing decentralized algorithms on manifolds. Then, we propose two decentralized methods, namely the decentralized projected Riemannian gradient descent (DPRGD) and the decentralized projected Riemannian gradient tracking (DPRGT) methods. We establish their convergence rates of O(1/K)\mathcal{O}(1/\sqrt{K}) and O(1/K)\mathcal{O}(1/K), respectively, to reach a stationary point. To the best of our knowledge, DPRGT is the first decentralized algorithm to achieve exact convergence for solving decentralized optimization over a compact manifold. The key ingredients in the proof are the Lipschitz-type inequalities of the projection operator on the compact manifold and smooth functions on the manifold, which could be of independent interest. Finally, we demonstrate the effectiveness of our proposed methods compared to state-of-the-art ones through numerical experiments on eigenvalue problems and low-rank matrix completion.Comment: 32 page
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