Platinum nanocrystals on carbon black were synthesized by an electrochemical square‐wave potential method (HIF‐Pt/C, see picture). The nanocrystals have high‐index facets and a high density of atomic ...steps. Thanks to this high density, the catalysts exhibit at least twice the activity and selectivity of commercial Pt/C catalysts for ethanol electrooxidation into CO2.
In this paper, we present how the Friedrichs–Lee model could be extended to the relativistic scenario and be combined with the relativistic quark pair creation model in a consistent way. This scheme ...could be applied to study the “unquenched” effect of the meson spectra. As an example, if the lowest
J
PC
=
0
+
+
(
u
u
¯
+
d
d
¯
)
/
2
bound state in the potential model is coupled to the
π
π
continuum, two resonance poles could be found from the scattering amplitude for the continuum states. One of them could correspond to the
f
0
(
500
)
/
σ
and the other probably
f
0
(
1370
)
. This scheme might shed more light on why extra states could appear in the hadron spectrum other than the prediction of the quark potential model.
It is important to predict the hidden behavior of a complex system. In the existing models for predicting the hidden behavior, the hidden belief rule base (HBRB) is an effective model which can use ...qualitative knowledge and quantitative data. However, the frame of discernment (FoD) of HBRB which is composed of some states or propositions and the universal set including all states or propositions is not complete. The global ignorance and local ignorance cannot be considered at the same time, which may lead to the inaccurate forecasting results. To solve the problems, a new HBRB model named as PHBRB in which the hidden behavior is described on the FoD of the power set is proposed in this correspondence paper. Furthermore, by using the evidential reasoning rule as the inference tool of PHBRB, a new projection covariance matrix adaption evolution strategy is developed to optimize the parameters of PHBRB so that more accurate prediction results can be obtained. A case study of network security situation prediction is conducted to demonstrate the effectiveness of the newly proposed method.
Flexible covalent organic frameworks (COFs) are intriguing for their dynamic properties distinctive from rigid counterparts but still suffer from limited accessibility. Especially, controlling ...flexibility of COFs is challenging and the impact of different flexibility on properties of COFs has rarely been unveiled. This article reports stepwise adjustment on flexibility of two-dimensional COFs, which is realized by the designed synthesis of rigid COF (R-COF), semi-flexible COF (SF-COF), and flexible COF (F-COF) through polymerization, linker exchange, and linkage conversion with a newly developed method for reduction of hydrazone, respectively. Significant difference in breathing behavior and self-adaptive capability of the three COFs are uncovered through vapor response and iodine capture experiments. Gas sorption experiments indicate that the porosity of F-COF could switch from "close" state in nitrogen to "open" state in carbon dioxide, which are not observed for R-COF and SF-COF. This study not only develops a strategy to adjust the flexibility of COFs by tuning their linkers and linkages, but also provides a deep insight into the impact of different flexibility on properties of COFs, which lays a foundation for the development of this new class of dynamic porous materials.
We propose a probabilistic methodology to estimate a demand curve for operating reserves, where the curve represents the amount that a system operator is willing to pay for these services. The demand ...curve is quantified by the cost of unserved energy and the expected loss of load, accounting for uncertainty from generator contingencies, load forecasting errors, and wind power forecasting errors. The methodology addresses two key challenges in electricity market design: integrating wind power more efficiently and improving scarcity pricing. In a case study, we apply the proposed operating reserve strategies in a two-settlement electricity market with centralized unit commitment and economic dispatch and co-optimization of energy and reserves. We compare the proposed probabilistic approach to traditional operating reserve rules. We use the Illinois power system to illustrate the efficiency of the proposed reserve market modeling approach when it is combined with probabilistic wind power forecasting.
Chiral trisubstituted vicinal diols are a type of important organic compounds, serving as both common structure units in bioactive natural products and chiral auxiliaries in asymmetric synthesis. ...Herein, by using siloxypropadienes as the precursors of allyl copper(I) species, a copper(I)‐catalyzed diastereoselective and enantioselective reductive allylation of ketones was achieved, providing both syn‐diols and anti‐diols in good to excellent enantioselectivity. DFT calculations show that cis‐γ‐siloxy‐allyl copper species are generated favorably with either 1‐TBSO‐propadiene or 1‐TIPSO‐propadiene. Moreover, the steric difference of TBS group and TIPS group distinguishes the face selectivity of acetophenone, leading to syn‐selectivity for 1‐TBSO‐propadiene and anti‐selectivity for 1‐TIPSO‐propadiene. Easy transformations of the products were performed, demonstrating the synthetic utility of the present method. Moreover, one chiral diol prepared in the above transformations was used as a suitable organocatalyst for the catalytic asymmetric reductive self‐coupling of aldimines generated in situ with B2(neo)2.
An asymmetric synthesis of trisubstituted vicinal diols is accomplished by copper(I)‐catalyzed diastereoselective and enantioselective reductive allylation of ketones with siloxypropadienes. The generation of both syn‐diols and anti‐diols is rationalized by DFT calculations, which show that cis‐γ‐siloxy‐allyl copper species are generated favorably in the reduction of either 1‐TBSO‐propadiene or 1‐TIPSO‐propadiene by copper hydride species.
It is vital to assess the lives of newly developed products by using failure data from various testing environments. In the current methods, two steps are generally included. The first step is ...transforming the failure data under one testing environment into the actual working environment, and the second step is integrating all failure data under the actual working environment into a unified result. However, most available methods cannot use information that includes part failure data and part expert knowledge simultaneously. To resolve the above issue, based on the belief rule base (BRB) and the evidential reasoning (ER) approach, a new BRB-ER-based model is proposed, where the BRB is used to transform the failure data from one testing environment into the actual working environment. The ER approach, which is adopted to aggregate the failure data from different testing environments, is used to assess the life of a product. To conclude, the BRB-ER-based model is applied to represent and integrate asynchronous multisource information. In the proposed model, the initial BRB system is constructed based on experts' knowledge, which results in uncertainty because of the ambiguous nature of human judgment and calls for training the parameters in the BRB-ER-based model. Therefore, an optimal algorithm that employs the differential evolutionary algorithm is proposed. The proposed model and the optimal algorithm operate in an integrated manner to improve the assessment precision by using both failure data and expert knowledge effectively. A case study in three scenarios and use of the conventional approach is examined to demonstrate the capability and potential applications of the new BRB-ER-based model.
The bag-of-words model is one of the most popular representation methods for object categorization. The key idea is to quantize each extracted key point into one of visual words, and then represent ...each image by a histogram of the visual words. For this purpose, a clustering algorithm (e.g., K-means), is generally used for generating the visual words. Although a number of studies have shown encouraging results of the bag-of-words representation for object categorization, theoretical studies on properties of the bag-of-words model is almost untouched, possibly due to the difficulty introduced by using a heuristic clustering process. In this paper, we present a statistical framework which generalizes the bag-of-words representation. In this framework, the visual words are generated by a statistical process rather than using a clustering algorithm, while the empirical performance is competitive to clustering-based method. A theoretical analysis based on statistical consistency is presented for the proposed framework. Moreover, based on the framework we developed two algorithms which do not rely on clustering, while achieving competitive performance in object categorization when compared to clustering-based bag-of-words representations.
Edge computing (EC) has quickly ascended to be the de-facto standard for hosting emerging low-latency applications, as exemplified by intelligent video surveillance, Internet of Vehicles, and ...augmented reality. For EC, service function chaining is envisioned as a promising approach to configure various services in an agile, flexible, and cost-efficient manner. When running on top of geographically dispersed edge clouds, fully unleashing the benefits of service function chaining is, however, by no means trivial. In this paper, we propose an online orchestration framework for cross-edge service function chaining, which aims to maximize the holistic cost efficiency, via jointly optimizing the resource provisioning and traffic routing on-the-fly. This long-term cost minimization problem is difficult since it is NP-hard and involves future uncertain information. To simultaneously address these dual challenges, we carefully combine an online optimization technique with an approximate optimization method in a joint optimization framework, through: 1) decomposing the long-term problem into a series of one-shot fractional problem with a regularization technique and 2) rounding the fractional solution to a near-optimal integral solution with a randomized dependent scheme that preserves the solution feasibility. The resulting online algorithm achieves an outstanding performance guarantee, as verified by both rigorous theoretical analysis and extensive trace-driven simulations.
Polyinosinic:polycytidylic acid (poly(I:C)) is a ligand of toll-like receptor (TLR) 3 that has been used as an immunostimulant in humans and mice against viral diseases based on its ability to ...enhance innate and adapt immunity. Antiviral effect of poly(I:C) has also been observed in teleost, however, the underling mechanism is not clear. In this study, we investigated the potential and signaling mechanism of poly(I:C) as an antiviral agent in a model of Japanese flounder (Paralichthys olivaceus) infected with megalocytivirus. We found that poly(I:C) exhibited strong antiviral activity and enhanced activation of head kidney macrophages and peripheral blood leukocytes. In vivo studies showed that (i) TLR3 as well as MDA5 knockdown reduced poly(I:C)-mediated immune response and antiviral activity to significant extents; (ii) when Myd88 was overexpressed in flounder, poly(I:C)-mediated antiviral activity was significantly decreased; (iii) when Myd88 was inactivated, the antiviral effect of poly(I:C) was significantly increased. Cellular study showed that (i) the NF-κB activity induced by poly(I:C) was upregulated in Myd88-overexpressing cells and unaffected in Myd88-inactivated cells; (ii) Myd88 overexpression inhibited and upregulated the expression of poly(I:C)-induced antiviral genes and inflammatory genes respectively; (iii) Myd88 inactivation enhanced the expression of the antiviral genes induced by poly(I:C). Taken together, these results indicate that poly(I:C) is an immunostimulant with antiviral potential, and that the immune response of poly(I:C) requires TLR3 and MDA5 and is negatively regulated by Myd88 in a manner not involving NK-κB. These results provide insights to the working mechanism of poly(I:C), TLR3, and Myd88 in fish.
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