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Correlation clustering problem (CorCP) is a classical clustering problem, which clusters data based on the similarity of data set, and has many applications in interaction networks, cross-lingual link detection, and communication networks, etc. In this paper, we study a practical generalization of the CorCP, called the capacitated correlation clustering problem (the capacitated CorCP), by constructing a labeled complete graph. On this labeled complete graph, each vertex represents a piece of data. If two pieces of data are similar, then the edge between the corresponding vertices is marked by a positive label [Formula: see text]. Otherwise, this edge is marked by a negative label −. The objective of the capacitated CorCP is to group some similar data sets into one cluster as far as possible, while satisfying the cluster capacity constraint. To achieve this objective, we shall partition the vertex set of the labeled complete graph into several clusters, each cluster’s size subjecting to an upper bound, so as to minimize the number of disagreements. Here the number of disagreements is defined as the total number of the edges with positive labels between clusters and the edges with negative labels within clusters. Different with the previous algorithm in [18], which subjects to the constraint on the cluster size by a penalty measure, we design an algorithm for the capacitated CorCP to directly output a feasible solution by iteratively constructing clusters based on a preset threshold. Through carefully setting the threshold and sophisticatedly analyzing, our algorithm is proved to have an improved approximation ratio of 5.37. In addition, we also conduct a series of numerical experiments to demonstrate the effectiveness of our algorithm.

Rock cracking caused by thermal shocking occurs widely in geothermal exploitation processes, such as wellbore drilling, reservoir stimulation, and long-term geothermal extraction. In this study, the permeability, P-wave velocity, uniaxial compressive strength, and tensile strength of granite subjected to heating (100 ~ 300℃) and cooling in water with different temperatures (0 ~ 60℃) were experimentally investigated. Moreover, the evolution of temperature field, cooling rate, and temperature gradient inside the samples during rapid cooling were tested. The results show that a decrease in the temperature of the cooling water aggravates the deterioration of the physical and mechanical properties of the granite after rapid cooling; this deterioration is specifically manifested in the increase in permeability and the decrease in P-wave velocity and mechanical strength of the granite samples. The heat transfer mechanism of the high-temperature granite under rapid cooling is characterized by unsteady heat conduction. The evolution of the internal temperature, cooling rate, and temperature gradient of the granite samples with time can be divided into three stages: the first 200s is the rapid cooling stage; 200s ~ 400s is the slow cooling stage; 400s ~ 600s is the temperature basically constant stage. The evolution of the cooling rate and temperature gradient formed in the high-temperature granite specimens under rapid cooling is consistent, and they all show a trend of rapid increase first followed by a slow decrease. The maximum values of the cooling rate and temperature gradient always appear in the area near the outer surface, which is closest to the solid–liquid heat exchange interface. This study has potential guiding significance for the application of rapid cooling in the development of enhanced geothermal system.

In geothermal mining, the mechanical properties and micro‐structure of the rock under different temperature or cooling modes are highly relevant to the stability of the artificial reservoir. For reflect the actual working conditions, an experimental study is carried out on high‐temperature granite that has been cooled both naturally and rapidly with water. The following conclusions are reached. (a) The wave velocity, elastic modulus, and uniaxial compressive strength of the test specimen decrease with an increase in its heating temperature under both cooling modes. (b) The characteristics of the stress‐strain curve of granite are different after different temperatures and cooling modes. With natural cooling, the stress‐strain curve features double peaks in the range of 200‐300°C, whereas such phenomenon occurs at temperatures greater than 300°C with water cooling. (c) When the temperature is less than 300°C, no obvious change occurs in the crystal structure of the sample. When the temperature is more than 300°C, the original micro‐cracks gradually expand and eventually develop into larger cracks.

Due to the accumulation of solar observational data and the development of data-driven algorithms, deep learning methods are widely applied to build a solar flare forecasting model. Most of the works focus on how to design or select proper deep networks for the forecasting task. Nevertheless, the influence of image resolution on the learning based solar flare forecasting model has not been analyzed and discussed. In this Paper, we investigate the influence of the resolution of magnetograms on the accuracy of solar flare forecasting. We study the active regions by the Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI) magnetograms from 2010 to 2019. Then, we downsample them to get a database containing active regions with several resolutions. Afterwards, three deep neural networks (i) AlexNet, (ii) ResNet-18, and (iii) SqueezeNet are implemented to evaluate the performance of solar flare forecasting compared to different resolutions of magnetogram. In experiments, we first did comparative experiments on our own simulated HMI database with different resolutions. Then we conducted experiments on two selected actual overlapping databases, Hinode–HMI and Michelson Doppler Imager–HMI, to reconfirm our conclusions. The experiment results show that all the selected deep learning networks are insensitive to the resolution to a certain extent. We visualized the regions of interest of the network from an interpretable perspective and found that the deep learning network pays more attention to the global features extracted from active regions that are not sensitive to local information in magnetograms.

Developing metal-organic framework (MOF)-based fluorescent probes for efficient detection and discrimination of polluting ions in groundwater is vital for environmental protection and human health. In this paper, we prepared two luminescence-active transition MOFs, namely, Zn-MOF and Cd-MOF, and conducted sensing experiments. The results show that they both exhibit multiple-target detection for Fe

An integrated immobilization to encapsulate the Pd/C-coated magnetic nanoparticles within the chiral Ru/diamine-functionalized silica shell for the construction of a bifunctional magnetic catalyst is developed. This catalyst realizes a synergistic Suzuki cross-coupling/asymmetric transfer hydrogenation and a successive reduction/asymmetric transfer hydrogenation for the preparation of chiral aromatic alcohols.

An ab initio and direct dynamic study of the reactions of CH3O2 + CH3OH and CH3O2 + CH2OH has been carried out over the temperature range of 300–1500 K. All stationary points were calculated at the MP2/aug-cc-pVTZ level of theory for CH3O2 + CH3OH or at the M06-2X/MG3S level of theory for CH3O2 + CH2OH and identified for the local minimum. The energetic parameters were refined at the QCISD(T)/cc-pVTZ and CCSD(T)/aug-cc-pVTZ levels of theory. For the reaction of CH3OO + CH3OH, two hydrogen abstraction channels producing CH3OOH + CH2OH (R1) and CH3OOH + CH3O (R2) were confirmed. These two channels consist of the same reversible first step involving the formation of a prereactive complex in the entrance channel. The rate constants of these two channels have been calculated by canonical transition station theory (TST) and canonical variational transition station theory (VTST) with Eckart tunneling correction and compared with the available literature data. The positive temperature dependence of the rate const...

Immobilization of molecular catalysts in a superhydrophobic material can efficiently overcome the shortage of low catalytic efficiency in heterogeneous catalysis. In this study, by taking advantage of a superhydrophobic mesostructured silica as a support, we incorporated conveniently chiral diamine to the silicate network, thus constructing two hydrophobic rhodium/diamine- and ruthenium/diamine-functionalized heterogeneous catalysts. Analyses via solid-state carbon NMR spectroscopy disclosed the well-defined single-site active species in the silicate framework of these catalysts, while the water contact angle measurements reflected their high hydrophobicity. Characterizations via scanning and transmission electron microscopy revealed their monodispersed feature. As presented in the study, the hydrophobic rhodium/diamine-functionalized catalyst greatly promotes the enantioselective tandem reduction/lactonization of ethyl 2-acylarylcarboxylates to afford various chiral phthalides, whereas the hydrophobic ruthenium/diamine-functionalized catalyst boosts an efficient asymmetric transfer hydrogenation-dynamic kinetic resolution process for construction of 1,2-distereocentered diethyl α-benzoyl-β-hydroxyphosphonates. As envisaged, the as-made catalysts with high hydrophobicity and uniformly distributed single-site catalytically active nature make combinational contributions to their catalytic performances, affording chiral products in high yields with up to 99% enantioselectivity. Moreover, the catalysts can be also recovered easily and recycled repeatedly, making them attracting candidates in efficient organic transformations.

The effect of ethanol on the ethylene consumption in fuel-rich, premixed, laminar, burner-stabilized flames at atmospheric pressure was investigated. A pure ethylene flame and three ethylene/ethanol flames with different ethanol fractions were simulated at the same equivalence ratio. The results showed that the different reaction rates for ethylene consumption in the flames were related to the reaction kinetics in these flames with an insignificant thermal effect. Changes in key radical concentrations in the flames were observed depending upon the initial ethanol mole fraction in the fuel, and the reaction pathways responsible for the production and destruction of ethylene were identified. The chemical behaviors differed significantly at different flame heights above the burner. At the flame height with a temperature of 769 K, a decrease in the OH concentration was responsible for the reduction in the reaction rate for ethylene consumption with the addition of ethanol. At the flame height with a temperatu...

Manipulation of dual active centers via an integrated immobilization strategy can overcome the restriction of homogeneous catalysis in a sequential organic transformation. Herein, by utilizing hollow-shell-structured silica, hydrogen-bonding immobilization via a ship-in-a-bottle synthesis locks a Pd(carbene) center in a nanocage and covalent-bonding immobilization tethers chiral Ru(diamine) centers within the nanochannels, constructing a hetero-bifunctional catalyst. The benefit of this dual center manipulation enables a challenging Suzuki coupling-asymmetric transfer hydrogenation tandem reaction, and the advantage of this process provides various chiral biarylols with enhanced reactivity and enantioselectivity.

Development of a simple and easy handing process for preparation of multifunctional heterogenous catalysts and exploration of their applications in sequential organic transformation are of great significance in heterogeneous asymmetric catalysis. Herein, through the utilization of a BF4- anion–bonding strategy, we anchor conveniently both organic bases and chiral ruthenium complex into the nanopores of Me-FDU−12, fabricating a Lewis base/Ru bifunctional heterogeneous catalyst. As we envisaged, cyclic amine as a Lewis base promotes an intermolecular aza–Michael addition between enones and arylamines, affording γ-secondary amino ketones featuring with aryl motif, whereas ruthenium/diamine species as catalytic promoter boosts an asymmetric transfer hydrogenation of γ-secondary amino ketones to γ-secondary amino alcohols. As expected, both enhance synergistically the aza–Michael addition/asymmetric transfer hydrogenation one–pot enantioselective organic transformation, producing chiral γ-secondary amino alcohols with up to 98% enantioselectivity. Unique features, such as operationally simple one–step synthesis of heterogeneous catalyst, homo–like catalytic environment as well as green sustainable process make this heterogeneous catalyst an attracting in a practical preparation of optically pure pharmaceutical intermediates of antidepressants.