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The stock turnover values are sensitive to external factors, and remain great challenges in its prediction. The consideration is that search engine data can reflect market environment, policies and attentions on stocks. Therefore, a dual sides autoregression (DSAR) method is proposed to benefit from both observed turnover values and exogenous data. The proposed DSAR consists of linear representation stage and combination stage. In linear representation stage, the short-term patterns of turnover values and query data are represented, respectively. In combination stage, the outputs from previous stages are combined. Intensive experiments on two groups of data collections show the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

District heat load forecasting is a challenging task that involves predicting future heat demand based on historical data and various influencing factors. Accurate forecasting is essential for optimizing energy production and distribution in district heating systems. However, most existing forecasting models lack transparency and interpretability and fail to capture the spatial–temporal dependencies in the data. Moreover, they often require a large amount of annotated data for training, which can be costly and time-consuming to obtain. In this paper, we present a novel approach to district heat load forecasting, which involves predicting future heat demand based on historical data and various influencing factors. The proposed approach is based on an Active Graph Recurrent Network (Ac-GRN), which leverages the strengths of active deep learning and graph neural networks to capture the complex spatial–temporal dependencies in the data. The approach also provides explainability for its predictions by using correlation-based attribution methods. The active deep learning component can effectively select the most informative and representative samples from a large pool of data, reducing the frequency and cost of data collection and human effort. The graph neural network component can model both linear and nonlinear relationships among heat meters using bidirectional recurrent connections, enhancing the accuracy and robustness of the predictions. We conduct extensive experiments and compare our approach with eleven state-of-the-art models on a real-world dataset of district heating consumption data from Danish residential buildings. Our results show that our approach outperforms other models in terms of accuracy, robustness, reliability, and computational efficiency for multi-horizon multi-step district heat load forecasting. Our approach also provides meaningful explanations for its predictions by highlighting the most influential factors and heat meters for each prediction. This paper makes a novel contribution to district heat load forecasting with explainability. • Novel approach for district heat load forecasting with active deep learning and graph neural networks. • Explainable predictions using gradient-based attribution methods. • Outperforms state-of-the-art models in accuracy and robustness. • Evaluates on real-world district heating data and conducts ablation studies. [ABSTRACT FROM AUTHOR]

The phase diagrams for carbamazepine (CBZ) and nicotinamide (NCT) in ethanol and ethanol/ethyl acetate mixture were constructed at 298.15 K and 313.15 K under atmospheric pressure using the static method. The solubility of the 1:1 cocrystal is correlated as a function of the cocrystal former (nicotinamide) concentration by a mathematical model based on solubility product theory and the complexation process. The phase diagram of a CBZ–NCT cocrystal in pure ethanol at 298.15 K is asymmetric, which leads to an excess of coformer being needed to isolate the cocrystal. In terms of this issue, it was found that the solvent mixture can have a significant effect on the symmetry of phase diagrams. Employing solvent mixtures could make the phase diagrams of the CBZ–NCT cocrystal more symmetric and enlarge the safe operation region for the cocrystal. Additionally, in the cocrystal formation process, the nucleation of cocrystal and carbamazepine in a slurry crystallization, is a competitive relationship. For avoiding single component crystallization, the supersaturation ratio of cocrystal to drug should be increased to inhibit carbamazepine nucleation. These findings are all beneficial to the development of the cocrystallization process of the CBZ–NCT cocrystal. [ABSTRACT FROM AUTHOR]

Underground hydrocarbon reservoir rocks comprise numerous multiscale irregular pores that significantly affect the mechanical and fluid transport properties of the rock. It is considerably challenging for in situ geological monitoring and laboratory tests to accurately characterize the changes in the interior structure and the corresponding mechanical properties of the rock mass during dynamic excavation processes. The 3-D numerical reconstruction models that are based on the statistical information extracted from X-ray computed tomography (XCT) images provide a feasible method to obtain and characterize the interior pore structures and their effects on the physical responses of reservoir rocks. However, obtaining sufficient high-resolution 2-D XCT images is economically expensive by the traditional fan beam CT scan system. Reconstructing 3-D porous structures by computational methods using statistical information extracted from XCT images usually has low efficiency. Therefore, in this paper, we introduce a novel method to numerically reconstruct natural sandstone rock using a small number of 2-D XCT images. The Bayesian information criterion was used to determine the minimum number of 2-D XCT images required to ensure the expected reconstruction accuracy. A multithread parallel reconstruction scheme was employed to improve the efficiency. The accuracy of the proposed method was verified by comparing the statistical correlation functions, geometrical and topological characteristics, and mechanical properties of pore structures between the reconstructed model and a sandstone prototype. This paper provides a method to achieve fast, economic, and accurate 3-D reconstruction of porous rock. [ABSTRACT FROM AUTHOR]

Urban green space has a critical impact on the urban ecological environment, residents' health, and urban sustainability. Quantifying residential exposure to green space and proposing targeted enhancement strategies in urban areas is helpful to rationally plan urban green space construction, reduce the inequality in residential exposure to green space, and promote environmental equity. However, the long-time evolution analysis of residential exposure to green space at different scales and the influence of green space quality on residential exposure to green space are rarely reported. Here we produced a long-time series dataset of urban green space from 1990 to 2020 based on the 30 m Landsat data and used the Normalized Difference Vegetation Index (NDVI) as a representation of the green space quality to comprehensively analyze residential exposure to green space at the city and block scales within the 5th ring of Beijing, China. We found that the urban green space in Beijing is mainly distributed in urban areas between the 4th and 5th rings (i.e., 153.4 km2 in 2020), and there is little green space within the 2nd ring area (i.e., 12.6 km2 in 2020). There is clear spatial inequality in residential exposure to green space, and about 2.88 million (i.e., ~27%) residents have experienced different degrees of decline in residential exposure to green space from 2015 to 2020. However, the degree of inequality in residential exposure to green space has gradually weakened from a high level (Palma ratio = 2.84) in 1990 to a relatively low level (Palma ratio = 0.81) in 2020. In addition, the spatial-temporal analysis method of residential exposure to green space based on green space quality has certain advantages that can help explore the degraded and lost areas of green space. [ABSTRACT FROM AUTHOR]

Tip growth is an extreme form of polarized cell expansion that occurs in all eukaryotic kingdoms to generate highly elongated tubular cells with specialized functions, including fungal hyphae, animal neurons, plant pollen tubes, and root hairs (RHs). RHs are tubular structures that protrude from the root epidermis to facilitate water and nutrient uptake, microbial interactions, and plant anchorage. RH tip growth requires polarized vesicle targeting and active exocytosis at apical growth sites. However, how apical exocytosis is spatially and temporally controlled during tip growth remains elusive. Here, we report that the Qa-Soluble N -ethylmaleimide-sensitive factor attachment protein receptor (SNARE) SYP121 acts as an effector of Rho of Plants 2 (ROP2), mediating the regulation of RH tip growth. We show that active ROP2 promotes SYP121 targeting to the apical plasma membrane. Moreover, ROP2 directly interacts with SYP121 and promotes the interaction between SYP121 and the R-SNARE VAMP722 to form a SNARE complex, probably by facilitating the release of the Sec1/Munc18 protein SEC11, which suppresses the function of SYP121. Thus, the ROP2-SYP121 pathway facilitates exocytic trafficking during RH tip growth. Our study uncovers a direct link between an ROP GTPase and vesicular trafficking and a new mechanism for the control of apical exocytosis, whereby ROP GTPase signaling spatially regulates SNARE complex assembly and the polar distribution of a Q-SNARE. Root hair tip growth requires polarized vesicle targeting and active exocytosis at apical growth site, but how it is spatially and temporally controlled remains elusive. This study demonstrates that ROP2 directly regulates the polar localization of SYP121 and its interaction with VAMP722 for SNARE complex assembly, establishing a tight link between ROP signaling and apical exocytosis during root hair tip growth. [ABSTRACT FROM AUTHOR]

The solubility of N,N′-Bis(2,2,6,6-tetramethyl-4-piperidinyl)-1,6-hexanediamine in seven pure solvents (acetonitrile, acetone, methyl acetate, ethyl acetate, propyl acetate, isopropyl acetate and isobutyl acetate) and two binary solvent mixtures (acetone + acetonitrile and methyl acetate + acetonitrile) were measured from 273.15 to 303.15 K at atmospheric pressure by a dynamic method. The solubility data in these pure solvents were correlated by the modified Apelblat model, the Wilson model and the NRTL model, and that in the binary solvents mixture were fitted to the CNIBS/R-K model and the NRTL model. Furthermore, the mixing thermodynamic properties in pure and binary solvent systems were calculated and are discussed, based on the NRTL model. Finally, the applicability of the model of Zhang et al. (Ind Eng Chem Res 51:6933-6938, 2012) in correlating solubility data versus dielectric constant was extended from organic solvent-water mixtures to pure organic solvents and nonaqueous organic solvent mixtures. It was found that the dissolution behavior of a compound in the binary solvent mixtures can be predicted to some extent from those in pure solvents. [ABSTRACT FROM AUTHOR]

From sustainable development and application standpoint, visible-light-driven oxidation of sulfides is emerging as sizzling focuses. In this work, a series of novel polyoxometalate-based photocatalysts, PW 12 -M@COFs 1 − 3 (M = Ag+ 1 , Cu2+ 2 , Ni2+ 3) were successfully synthesized via the electrostatic interactions between POM anion and cationic porous M@COFs, which were characterized by infrared (IR) spectroscopy, EDS analysis, solid diffuse reflective spectroscopy etc. These compounds exhibit strong visible light adsorption and can be used as excellent photocatalysts for the oxidation of sulfides to sulfoxides and the degradation of chemical warfare agent simulant, 2-chloroethyl ethyl sulfide (CEES). Especially, compound 1 with Ag+ has the best catalytic activity, achieving 98% of methyl phenyl sulfide conversion with 99% of selectivity in 3.5 h illuminated by a 10 W 425 nm light-emitting diode (LED). When extended to other sulfur-containing compounds, it also demonstrates satisfactory yield to sulfoxide and degrade CEES within 2 h. The mechanism reveals that both singlet oxygen and superoxide radicals act as the reactive oxygen species for the visible-light-driven oxidation of various sulfides, corresponding to the photoinduced electron-transfer and energy-transfer pathways. Moreover, these catalysts exhibited excellent catalytic and structural stability. [Display omitted] • Three novel photocatalysts were synthesized by incorporating POMs anions to cationic M@COFs. • The PW 12 -Ag@COF shows highest photocatalytic activity for the oxidation of sulfides. • POMs improve the separation efficiency of photogenerated carriers by Ag@COF to boost photocatalytic activity. • The photocatalytic mechanism reveals 1O 2 , O 2 •− and holes as the active species. [ABSTRACT FROM AUTHOR]

The solid-liquid equilibrium data of erythromycin ethylsuccinate in six pure organic solvents including tetrahydrofuran, acetone, acetonitrile, hexane, ethanol and 2-propanol were determined by using the gravimetric method over the temperature range from 288.15 K to 323.15 K. The experimental solubility data was correlated by modified Apelblat equation, van't Hoff, Wilson, and NRTL model, among which the modified Apelblat model was found to have the best agreement with the experimental results. The mixing Gibbs free energy, mixing enthalpy, and mixing entropy were calculated by Non-random two liquid (NRTL) model. The solubility behavior of EES at given temperature were illustrated by Hansen SPs values. [ABSTRACT FROM AUTHOR]

• The Cl- ions in the solution promote the passive dissolution reaction process. • The dissolved surface in the chloride-containing solution is significantly flatter. • The transpassive dissolution rate and current efficiency are enhanced by Cl- ions. The electrolyte solution significantly affects electrochemical machining. This study investigates the electrochemical dissolution behavior of a laser solid formed Hastelloy X nickel-based superalloy in 15 wt% NaNO 3 , 7.5 wt% NaNO 3 + 7.5 wt% NaCl, and 15 wt% NaCl solutions. The Cl- ions in the electrolyte solution accelerates the passive dissolution rate because the electrochemical reactions at the metal/film and film/solution interfaces are promoted. During the transpassive dissolution process, the Cl- ions in the electrolyte solution weaken the hindering effect of the transpassive film on the dissolution process, resulting in a faster transpassive dissolution rate and a higher current efficiency. Furthermore, the flatness of the dissolved surface in the chloride-containing solution is significantly higher than that in the chloride-free solution. Two models are proposed to illustrate the passive and transpassive dissolution behaviors. This study provides theoretical guidance for the selection of electrolyte solutions for the electrochemical machining of laser solid formed nickel-based superalloys. [ABSTRACT FROM AUTHOR]