Search

Morphological anisotropic engineering is powerful to synthesize metal–organic frameworks (MOFs) with versatile physicochemical properties for diverse applications ranging from gas storage/separation to electrocatalysis and batteries, etc. Herein, we developed a carbon substrate guided strategy to manipulate the facet‐dependent coordination for morphology engineering of Fe‐THBQ (tetrahydroxy‐1,4‐benzoquinone) frameworks, which is built with cubic Fe octamer bridged by two parallel THBQ ligands along three orthogonal axes, extending to a three‐dimensional (3D) framework with pcu‐e network topology. The electronegative O‐containing functional groups on carbon surfaces compete with THBQ linkers to selectively interact with the unsaturated coordinated Fe cations on the {111} facets and inhibit crystal growth along the <111> direction. The morphology of Fe‐THBQ evolves from thermodynamically favored truncated cube to cuboctahedron depending on the content of O‐containing functional groups on the carbon substrate. The Fe‐THBQ with varied morphologies exhibits facet‐dependent performances for electrochemical lithium storage. This work will shed light on the morphology modulation of MOFs for promising applications. [ABSTRACT FROM AUTHOR]

Sodium‐ion batteries (SIBs) are recognized as promising energy storage devices. However, they suffer from rapid capacity decay at ultra‐low temperatures due to high Na+ desolvation energy barrier and unstable solid electrolyte interphase (SEI). Herein, a weakly solvating electrolyte (WSE) with decreased ion‐dipole interactions is designed for stable sodium storage in hard carbon (HC) anode at ultra‐low temperatures. 2‐methyltetrahydrofuran with low solvating power is incorporated into tetrahydrofuran to regulate the interactions between Na+ and solvents. The reduced Na+‐dipole interactions facilitate more anionic coordination in the first solvation sheath, which consistently maintains anion‐enhanced solvation structures from room to low temperatures to promote inorganic‐rich SEI formation. These enable WSE with a low freezing point of −83.3 °C and faster Na+ desolvation kinetics. The HC anode thus affords reversible capacities of 243.2 and 205.4 mAh g−1 at 50 mA g−1 at −40 and −60 °C, respectively, and the full cell of HC||Na3V2(PO4)3 yields an extended lifespan over 250 cycles with high capacity retention of ~100 % at −40 °C. This work sheds new lights on the ion‐dipole regulation for ultra‐low temperature SIBs. [ABSTRACT FROM AUTHOR]

Sodium‐ion batteries (SIBs) are recognized as promising energy storage devices. However, they suffer from rapid capacity decay at ultra‐low temperatures due to high Na+ desolvation energy barrier and unstable solid electrolyte interphase (SEI). Herein, a weakly solvating electrolyte (WSE) with decreased ion‐dipole interactions is designed for stable sodium storage in hard carbon (HC) anode at ultra‐low temperatures. 2‐methyltetrahydrofuran with low solvating power is incorporated into tetrahydrofuran to regulate the interactions between Na+ and solvents. The reduced Na+‐dipole interactions facilitate more anionic coordination in the first solvation sheath, which consistently maintains anion‐enhanced solvation structures from room to low temperatures to promote inorganic‐rich SEI formation. These enable WSE with a low freezing point of −83.3 °C and faster Na+ desolvation kinetics. The HC anode thus affords reversible capacities of 243.2 and 205.4 mAh g−1 at 50 mA g−1 at −40 and −60 °C, respectively, and the full cell of HC||Na3V2(PO4)3 yields an extended lifespan over 250 cycles with high capacity retention of ~100 % at −40 °C. This work sheds new lights on the ion‐dipole regulation for ultra‐low temperature SIBs. [ABSTRACT FROM AUTHOR]

Selective oxidation reactions of sulfides have been attracting chemists from different fields due to the wide applications of the products. In this work, two hybrid compounds of Evans–Showell type polyoxometalate, [Co(bpy)3]2[Co2Mo10O38H4]·6H2O (1) and [Cu3(bpy)3(H2O)6][Co2Mo10O38H4]·5H2O (2) (bpy = 2,2′-bipyridine), were designed to catalyze the oxidation of various sulfides. Their corresponding structures were determined by Fourier-Transform Infrared-Spectroscopy (FT-IR), X-ray diffraction (single-crystal and powder), and elemental mapping analysis, exhibiting three-dimensional supramolecular structures formed through extensive hydrogen bonding interactions. Compound 1, in the model reaction of selective oxidation of methyl phenyl sulfide (MPS) to methyl phenyl sulfoxide (MPSO), achieved complete conversion within 35 min and exhibited a dramatically higher turnover frequency (TOF) compared to those of the other various precursors. Compound 2 also exhibited excellent catalytic properties within 60 min, despite the significant difference in the three-dimensional stacking pattern from that of 1. Besides, more generally, both compounds showed satisfactory catalytic performance for different sulfide substrates. Finally, their excellent structural stability and recyclability under working conditions were confirmed using different tests. [ABSTRACT FROM AUTHOR]

Li‐O2 batteries have garnered much attention due to their high theoretical energy density. However, the irreversible lithium plating/stripping on the anode limits their performance, which has been paid little attention. Herein, a solvation‐regulated strategy for stable lithium anodes in tetraethylene glycol dimethyl ether (G4) based electrolyte is attempted in Li‐O2 batteries. Trifluoroacetate anions (TFA−) with strong Li+ affinity are incorporated into the lithium bis(fluorosulfonyl)imide (LiTFSI)/G4 electrolyte to attenuate the Li+‐G4 interaction and form anion‐dominant solvates. The bisalt electrolyte with 0.5 M LiTFA and 0.5 M LiTFSI mitigates G4 decomposition and induces an inorganic‐rich solid electrolyte interphase (SEI). This contributes to decreased desolvation energy barrier from 58.20 to 46.31 kJ mol−1, compared with 1.0 M LiTFSI/G4, for facile interfacial Li+ diffusion and high efficiency. It yields extended lifespan of 120 cycles in Li‐O2 battery with a limited Li anode (7 mAh cm−2). This work gains comprehensive insights into rational electrolyte design for Li‐O2 batteries. [ABSTRACT FROM AUTHOR]

Li‐O2 batteries have garnered much attention due to their high theoretical energy density. However, the irreversible lithium plating/stripping on the anode limits their performance, which has been paid little attention. Herein, a solvation‐regulated strategy for stable lithium anodes in tetraethylene glycol dimethyl ether (G4) based electrolyte is attempted in Li‐O2 batteries. Trifluoroacetate anions (TFA−) with strong Li+ affinity are incorporated into the lithium bis(fluorosulfonyl)imide (LiTFSI)/G4 electrolyte to attenuate the Li+‐G4 interaction and form anion‐dominant solvates. The bisalt electrolyte with 0.5 M LiTFA and 0.5 M LiTFSI mitigates G4 decomposition and induces an inorganic‐rich solid electrolyte interphase (SEI). This contributes to decreased desolvation energy barrier from 58.20 to 46.31 kJ mol−1, compared with 1.0 M LiTFSI/G4, for facile interfacial Li+ diffusion and high efficiency. It yields extended lifespan of 120 cycles in Li‐O2 battery with a limited Li anode (7 mAh cm−2). This work gains comprehensive insights into rational electrolyte design for Li‐O2 batteries. [ABSTRACT FROM AUTHOR]

This paper introduces a novel feature selection method, called Feature Selection based on Importance Measures (FS-IM), to enhance the forecasting of crude oil returns. FS-IM innovatively combines active learning with the application of Gaussian noise to input features and selects the most relevant features using an optimal threshold value. The paper applies a ridge regression (RR) model based on FS-IM (FS-RR) to identify the factors that have important information for crude oil return forecasting. The paper compares FS-IM with other dimension reduction methods such as Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA), and Independent Component Analysis (ICA). The results show that FS-IM can significantly improve model accuracy, demonstrating its effectiveness in finding key features. Moreover, FS-IM is more stable and consistent than other dimension reduction methods in enhancing the prediction accuracy in different scenarios, indicating its superior capability in capturing complex relationships between input and output variables. Furthermore, this study compares FS-RR model with other 13 prediction models by conducting experiments using a series of evaluation metrics, different statistical tests, and different step-ahead predictions and training sets. The results confirm that the RR model based on FS-IM can consistently outperform other model in terms of predictive performance and economic value, proving its effectiveness and robustness. This study contributes to the literature on crude oil price forecasting by addressing the challenges of high-dimensional and complex data, and by providing a robust, practical tool for professionals in energy economics and finance. • A new feature selection method for crude oil forecasting using importance scores and Gaussian noise is proposed. • The method selects the most relevant features based on the prediction errors of a base forecasting model. • The method enhances the accuracy and value of ridge regression model compared to other methods. • The method handles high-dimensional and complex data without losing information or interpretability. [ABSTRACT FROM AUTHOR]

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]

Infectious diarrhea has high morbidity and mortality around the world. For this reason, diarrhea prediction has emerged as an important problem to prevent and control outbreaks. Numerous studies have built disease prediction models using large-scale data. However, these methods perform poorly on diarrhea data. To address this issue, this paper proposes a parsimonious model (PM), which takes historical outpatient visit counts, meteorological factors (MFs) and Baidu search indices (BSIs) as inputs to perform prediction. An experimental evaluation was done to compare the short-term prediction performance of ten algorithms for four groups of inputs, using data collected in Xiamen, China. Results show that the proposed method is effective in improving the prediction accuracy. [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]

The sodium extraction/insertion in layered transition‐metal oxide (TMO) cathode materials are typically accompanied by slab sliding and lattice changes, leading to microstructure destruction and capacity decay. Herein, negative lattice expansion is observed in an O3 type Ni‐based layered cathode of Na0.9Ni0.32Zn0.08Fe0.1Mn0.3Ti0.2O2 upon Na+ extraction. It is attributed to the weak Zn2+−O2− orbital hybridization and increased electron density of the surrounding oxygen for reinforced interlayer O−O repulsive force. This enables gliding of TMO slabs for the intergrowth phase transition of P3→OP2 to alleviate lattice strain with moderate lattice shrinkage, which exhibits general interslab spacings and volume changes as low as 2.4 % and 1.9 %, respectively. The strong Ti−O bonds accommodate the internal distortion of TMO6 octahedra due to the flexibility of TiO6 octahedra during cycling. These endow a high specific capacity of 144.9 mAh g−1 and excellent cycling performance of pouch‐type sodium‐ion batteries with 93 % capacity retention after 3600 cycles. [ABSTRACT FROM AUTHOR]

The sodium extraction/insertion in layered transition‐metal oxide (TMO) cathode materials are typically accompanied by slab sliding and lattice changes, leading to microstructure destruction and capacity decay. Herein, negative lattice expansion is observed in an O3 type Ni‐based layered cathode of Na0.9Ni0.32Zn0.08Fe0.1Mn0.3Ti0.2O2 upon Na+ extraction. It is attributed to the weak Zn2+−O2− orbital hybridization and increased electron density of the surrounding oxygen for reinforced interlayer O−O repulsive force. This enables gliding of TMO slabs for the intergrowth phase transition of P3→OP2 to alleviate lattice strain with moderate lattice shrinkage, which exhibits general interslab spacings and volume changes as low as 2.4 % and 1.9 %, respectively. The strong Ti−O bonds accommodate the internal distortion of TMO6 octahedra due to the flexibility of TiO6 octahedra during cycling. These endow a high specific capacity of 144.9 mAh g−1 and excellent cycling performance of pouch‐type sodium‐ion batteries with 93 % capacity retention after 3600 cycles. [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]

Aprotic Li‐O2 battery has attracted considerable interest for high theoretical energy density, however the disproportionation of the intermediate of superoxide (O2−) during discharge and charge leads to slow reaction kinetics and large voltage hysteresis. Herein, the chemically stable ruthenium tris(bipyridine) (RB) cations are employed as a soluble catalyst to alternate the pathway of O2− disproportionation and its kinetics in both the discharge and charge processes. RB captures O2− dimer and promotes their intramolecular charge transfer, and it decreases the energy barrier of the disproportionation reaction from 7.70 to 0.70 kcal mol−1. This facilitates the discharge and charge processes and simultaneously mitigates O2− and singlet oxygen related side reactions. These endow the Li‐O2 battery with reduced discharge/charge voltage gap of 0.72 V and prolonged lifespan for over 230 cycles when coupled with RuO2 catalyst. This work highlights the vital role of superoxide disproportionation for Li‐O2 battery. [ABSTRACT FROM AUTHOR]

Aprotic Li‐O2 battery has attracted considerable interest for high theoretical energy density, however the disproportionation of the intermediate of superoxide (O2−) during discharge and charge leads to slow reaction kinetics and large voltage hysteresis. Herein, the chemically stable ruthenium tris(bipyridine) (RB) cations are employed as a soluble catalyst to alternate the pathway of O2− disproportionation and its kinetics in both the discharge and charge processes. RB captures O2− dimer and promotes their intramolecular charge transfer, and it decreases the energy barrier of the disproportionation reaction from 7.70 to 0.70 kcal mol−1. This facilitates the discharge and charge processes and simultaneously mitigates O2− and singlet oxygen related side reactions. These endow the Li‐O2 battery with reduced discharge/charge voltage gap of 0.72 V and prolonged lifespan for over 230 cycles when coupled with RuO2 catalyst. This work highlights the vital role of superoxide disproportionation for Li‐O2 battery. [ABSTRACT FROM AUTHOR]

Geomaterials inherently contain many discontinuous, multi-scale, geometrically irregular pores, forming a complex porous structure that governs their mechanical and transport properties. The development of an efficient reconstruction method for representing porous structures can significantly contribute toward providing a better understanding of the governing effects of porous structures on the properties of porous materials. In order to improve the efficiency of reconstructing large-scale porous structures, a multi-thread parallel scheme was incorporated into the simulated annealing reconstruction method. In the method, four correlation functions, which include the two-point probability function, the linear-path functions for the pore phase and the solid phase, and the fractal system function for the solid phase, were employed for better reproduction of the complex well-connected porous structures. In addition, a random sphere packing method and a self-developed pre-conditioning method were incorporated to cast the initial reconstructed model and select independent interchanging pairs for parallel multi-thread calculation, respectively. The accuracy of the proposed algorithm was evaluated by examining the similarity between the reconstructed structure and a prototype in terms of their geometrical, topological, and mechanical properties. Comparisons of the reconstruction efficiency of porous models with various scales indicated that the parallel multi-thread scheme significantly shortened the execution time for reconstruction of a large-scale well-connected porous model compared to a sequential single-thread procedure. [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]

Rechargeable lithium‐oxygen batteries (LOBs) are considered to be the next‐generation energy technology owing to their high theoretical energy density. However, the sluggish cathode kinetics and degradation of Li anodes result in large voltage hysteresis and low coulombic efficiency. Various materials have been applied to promote the electrochemical performance of LOBs. Metal‐organic frameworks (MOFs) possessing porous structures, open active sites and adjustable pore sizes have been attempted as promising materials for catalysts and separators of LOBs. This concept presents an overview of different MOF‐based catalysts for LOBs, including traditional, conductive, semi‐conductive and soluble MOFs, as well as our recently proposed photo‐involved LOBs. Recent advances in MOF‐based separators to restrain the shuttling of redox mediators between cathodes and anodes and suppress the formation of lithium dendrites are also discussed. Finally, perspectives on the development of MOF‐based LOBs for future research are presented. [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]

• Developing a mathematical model to investigate the influence of solution volume on stochastic distribution of induction time. • Calculating transition volume of HMBTAD-acetonitrile system, at which the induction time becomes reproducible. • Measuring the induction time of HMBTAD in acetonitrile in different solution volumes to validate the mathematical model. Influence of solution volume on the inherent stochastic distribution of induction time during nucleation process was investigated by developing a mathematical model based on Single Nucleus Mechanism and the Poisson's distribution. The results show that the distribution of induction time turns narrower with the increase of solution volume, indicating that the stochastic nature of nucleation become weaker. Based on the mathematical model, the stochastic distribution of crystal nucleation at different solution volume can be determined. The induction time of HMBTAD in acetonitrile were measured at different volumes to validate the mathematical model. Transition volume at which the induction time becomes reproducible was also calculated from the mathematical model. The theoretically calculated value of transition volume is consistent with experimental result obtained from induction time measurement, which also verify the correctness of mathematical model. [ABSTRACT FROM AUTHOR]

Heat load prediction is essential for energy efficiency and carbon reduction in district heating systems. However, heat load is influenced by many factors, such as building characteristics, consumption behavior, and climate, making its prediction challenging. Traditional methods based on physical models are complex and insufficiently accurate, whereas most data-driven statistical methods ignore customer energy consumption behaviors and their correlation, and do not account for the temporal inertia of consumption. This paper proposes a graph ambient intelligence (GAIN) method for heat load prediction, which classifies customers based on their load profiles and uses collaborative attention on temporal graphs to capture their associations and the weather impact on heat loads. GAIN also incorporates recursive and autoregressive methods to model the temporal inertia of consumption. The proposed method is evaluated on four metrics and compared with fifteen baseline methods. The results show that GAIN achieves the lowest daily forecasting errors in terms of RMSE, MAE, and CV-RMSE, with values of 6.972, 4.442, and 0.191, respectively. Besides, the proposed method achieves a maximum reduction of 25%, 29%, and 25% in RMSE, MAE, and CV-RMSE, respectively, compared to other methods when taking meteorological factors into account. • Introduced GAIN model using graph neural networks for heat load forecasting. • Novel approach captures both local and global patterns in time series data. • Experiments show better accuracy and efficiency than conventional methods. • Promotes energy efficiency and carbon reduction in district heating systems. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is an irreversible neurodegenerative disease that has serious impacts on patients' lives. To provide timely accurate treatment and delay the deterioration of the disease, the accurate early diagnosis and clinical score prediction of PD are extremely important. Differing from previous studies on PD, we propose a network combining feature selection method with feature learning to obtain the most discriminative feature representation for longitudinal early diagnosis and clinical score prediction. Specifically, we first preprocess the multi-modal neuroimaging data at multiple time points to extract original longitudinal multi-modal features. Then, the feature selection method is performed to preliminary reduce the feature dimensions. Finally, the stacked sparse nonnegative autoencoder (SSNAE) is employed to obtain more discriminative longitudinal multi-modal features to improve the accuracy of early diagnosis and clinical score prediction at multiple time points. To verify our proposed network, diverse and extensive experiments are performed on the Parkinson's Progression Markers Initiative dataset, which aims to identify biological markers of PD risk, onset and progression. The results demonstrate that our proposed method is more efficient and achieves promising performance on both longitudinal early diagnosis and clinical scores prediction compared to state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Layered transition‐metal oxides are promising cathode candidates for sodium‐ion batteries. However, the inferior interphase formation and particulate fracture during sodiation/desodiation result in structure degradation and poor stability. Herein, the interface chemistry of P2‐Na0.640Ni0.343Mn0.657O2 in an electrolyte of 1.0 mol/L NaPF6 in diglyme is unveiled to enable highly reversible Na extraction and intercalation. The uniform and robust cathode‐electrolyte interphase layer is in situ formed with decomposition of diglyme molecules and anions in initial cycles. The NaF‐ and CO‐rich CEI film exhibits high mechanical strength and ionic conductivity, which suppresses the reconstruction of its electrode interphase from P2 phase to spinel‐like structure and reinforces its structure integrity without cracks. This favours facile Na+ transport and stable bulk redox reactions. It is demonstrated to show long cycling stability with capacity retention of 94.4% for 180 cycles and superior rate capability. This investigation highlights the cathode interphase chemistry in sodium‐ion batteries. [ABSTRACT FROM AUTHOR]

The uncertain infection transmission causes challenges in accurate disease prediction. Numerous methods have been proposed to capture the temporal pictures from past observations within equal time intervals, which are called single-grained time series. However, these methods are not suitable for capturing uncertain temporal dynamics from infectious disease time series, since the infectious diseases may propagate in the incubation period. To address this issue, this paper proposes a Dual-Grained Directional Representation (DGDR) to generate predictions, via consolidating the representations of an equal-grained time series and several fine-grained time series. Firstly, the proposed DGDR learns a transformed segmentation into three kinds of representations. And then those representations from both equal-grained data and fine-grained data are temporally consolidated to connect with outputs. Extensive experiments on two real infectious disease datasets are done to validate the proposed DGDR. Compared with the other twelve methods, MAE value is decreased by 31.5%, RMSE value is decreased by 29.9%, and R 2 value is improved by 87.6%. [ABSTRACT FROM AUTHOR]

Hard carbon (HC) is a promising anode material for sodium‐ion batteries, yet still suffers from low initial Coulombic efficiency (ICE) and unstable solid electrolyte interphase (SEI). Herein, sodium diphenyl ketone (Na‐DK) is applied to realize dual‐function presodiation for HC anodes. It compensates the irreversible Na uptake at the oxygen‐containing functional groups and reacts with carbon defects of five/seven‐membered rings for quasi‐metallic sodium in HC. The as‐formed sodium induces robust NaF‐rich SEI on HC in 1.0 M NaPF6 in diglyme, favoring the interfacial reaction kinetics and stable Na+ insertion and extraction. This renders the presodiated HC (pHC) with high ICE of ≈100 % and capacity retention of 82.4 % after 6800 cycles. It is demonstrated to couple with Na3V2(PO4)3 cathodes in full cells to show high capacity retention of ≈100 % after 700 cycles. This work provides in‐depth understanding of chemical presodiation and a new strategy for highly stable sodium‐ion batteries. [ABSTRACT FROM AUTHOR]

Hard carbon (HC) is a promising anode material for sodium‐ion batteries, yet still suffers from low initial Coulombic efficiency (ICE) and unstable solid electrolyte interphase (SEI). Herein, sodium diphenyl ketone (Na‐DK) is applied to realize dual‐function presodiation for HC anodes. It compensates the irreversible Na uptake at the oxygen‐containing functional groups and reacts with carbon defects of five/seven‐membered rings for quasi‐metallic sodium in HC. The as‐formed sodium induces robust NaF‐rich SEI on HC in 1.0 M NaPF6 in diglyme, favoring the interfacial reaction kinetics and stable Na+ insertion and extraction. This renders the presodiated HC (pHC) with high ICE of ≈100 % and capacity retention of 82.4 % after 6800 cycles. It is demonstrated to couple with Na3V2(PO4)3 cathodes in full cells to show high capacity retention of ≈100 % after 700 cycles. This work provides in‐depth understanding of chemical presodiation and a new strategy for highly stable sodium‐ion batteries. [ABSTRACT FROM AUTHOR]

To investigate interspecific cross-compatibility among Chimonanthus praecox (L.) Link, C. salicifolius S. Y. Hu, and C. nitens Oliver, pollen–pistil interaction by fluorescence microscopy and hybrid embryo development by whole mount clearing technique were observed. The results indicated that for all reciprocal crosses among the three species, pollen grains of the male parents could adhere to and germinate in the stigmas of female parents. For any cross combination, pollen tube growth could reach the embryo sac, and double fertilization could be completed. These findings indicated that no obvious barriers to interspecific hybridization existed at the stages of pollen germination and pollen tube elongation until double fertilization. Although certain proportion (29.6% at 9 d and 36.3% at 15 d after pollination) of abortions (e.g., non-fertilization and retarded or non-existent endosperm development) in normally pollinated embryos of C. praecox at different stages were also observed, a greatly increased proportion (66.1% at 8 d and 76.7% at 15 d after pollination in C. praecox × C. nitens , and 60.0% at 8 d and 75.0% at 15 d after pollination in C. praecox × C. salicifolius ) of hybrid embryos did not complete double fertilization or completed double fertilization but underwent abortion due to the retardation of endosperm development. Comparing to normally pollinated embryos of C. praecox , the retardation of endosperm development in hybridizations occurred earlier. Moreover, the occurrence of abortions among different cross combinations was basically consistent. Thus, the retardation of the endosperm development of hybrid embryos after double fertilization (after the globular embryo stage) is an important factor leading to the failure of distant hybridization between Chimonanthus species. [ABSTRACT FROM AUTHOR]

Selective oxidation of substituted phenols is an ideal method for preparing functionalized p-benzoquinones (p-BQs), which serve as versatile raw materials for the synthesis of a variety of biologically active compounds. Herein, two new polyoxometalate-based supramolecular porous frameworks, K3(H2O)4[Cu(tza)2(H2O)]2[Cu(Htza)2(H2O)2][BW12O40]·6H2O (1) and H3K3(H2O)3[Cu(Htza)2(H2O)]3[SiW12O44]·14H2O (2) (Htza = tetrazol-1-ylacetic acid), were synthesized and structurally characterized by elemental analysis, infrared spectroscopy, thermal analysis, UV-vis diffuse reflectance spectroscopy, and single-crystal X-ray and powder diffraction. The single-crystal X-ray diffraction analysis indicates that both compounds possess unique petal-like twelve-nucleated Cu-organic units composed of triangular and hexagonal metal–organic loops. In 1, the Cu-organic units are isolated and [BW12O40]5− polyoxoanions are sandwiched between staggered adjacent triangular channels in the structure. However in 2, the Cu-organic units extend into a two-dimensional layered structure, and the [SiW12O44]12− polyoxoanions occupy the larger hexagonal channels in the stacked structure. Both compounds as heterogeneous catalysts can catalyze the selective oxidation of substituted phenols to high value-added p-BQs under mild conditions (60 °C) with TBHP as the oxidant, particularly in the oxidation of 2,3,6-trimethylphenol to 2,3,5-trimethyl-p-benzoquinone (TMBQ, key intermediate in vitamin E production). Within 8–10 min, the yield of TMBQ is close to 100%, and oxidant utilization efficiency is up to 94.2% for 1 and 90.9% for 2. The turnover frequencies of 1 and 2 are as high as 5000 and 4000 h−1, respectively. No obvious decrease in the yield of TMBQ was observed after five cycles, which indicates the excellent sustainability of both compounds. Our study of the catalytic mechanism suggests that there is a two-site synergetic effect: (i) the copper ion acts as the catalytic site of the homolytic radical pathway; and (ii) the polyoxoanion acts as the active center of the heterolytic oxygen atom transfer pathway. [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]