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The selective electrooxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid (FDCA) is of great significance in replacing terephthalic acid for the production of high-performance polymeric materials. This necessitates the development of advanced electrocatalysts. Ni-based nanomaterials, known for their unique electronic structure and high intrinsic activity, show great promise for the selective electrooxidation of HMF to FDCA. To provide guidance for the further development of advanced HMF electrocatalysts, we present a comprehensive review of recent progress in this field, focusing on HMFOR mechanisms, effective engineering strategies (e.g., morphology design, defect engineering, interface engineering, and strain engineering) for improving electrocatalytic performance, and representative Ni-based catalysts used for HMFOR. Finally, we offer a conclusion and highlight the challenging issues that need to be addressed, providing researchers with direction for future endeavors. • A review on the oxidation of HMF into FDCA catalyzed by Ni-based materials is summarized. • The mechanisms of HMF electrooxidation are described thoroughly. • Strategies for optimizing the catalytic performance of Ni-based materials for HMFOR are mentioned. • Recent progresses, challenges, and perspectives are highlighted. [ABSTRACT FROM AUTHOR]

This study uses the Hicks-Moorsteen index method to examine the impact mechanism of the digital economy on the total factor productivity and its decomposition efficiencies of the high-tech industry in China. The results show that the total factor productivity of the high-tech industry in the research and development phase is significantly and positively influenced by the primary phase of digital economy development. Digital economy development has a positive impact on technical change, according to the specific path analysis, which has an inverted U-shaped nonlinear characteristic. With a U-shaped nonlinear characteristic, it has a significant and persistent negative impact on efficiency changes, where the positive impact of technological spillovers on the digital economy outweighs the negative impact of technological shocks. The threshold effect test shows that the best condition for promoting total factor productivity and its decomposition efficiency in the R&D stage of high-tech industry was achieved when the digital economy composite index was between 2.611 and 2.747. • We study the effect-mechanism of digital economy on total factor productivity. • Total factor productivity is impacted positively by digital economy. • Digital economy has a positive impact on technical change. • Digital economy has a negative influence on efficiency change. • We provide the best condition for promoting total factor productivity. [ABSTRACT FROM AUTHOR]

Geochemical compositions of the Lower Cambrian Niutitang Formation shales in the southeastern Yangtze Platform margin were investigated for provenance, tectonic setting, and depositional environment. The shale samples are characterized by higher abundances of large ion lithophile elements (Cs, Ba, and Pb), lower abundances of high field strength elements (Cr, Sc, and Co) and transition elements (Th, Zr, Hf, Nb, and Ta) relative to average shale. North American shale composition (NASC) -normalized rare earth element (REE) patterns are observed, with negative Ce anomalies, negative Eu anomalies, and positive Y anomalies. The chemical index of alteration (CIA) varies from 68.67–74.93. Alkali and alkaline element contents and CIA values suggest that the source rocks have undergone moderate weathering. The index of compositional variability (ICV), Zr/Sc and Th/Sc ratios vary from 0.53 to 1.07, 5.31 to 8.18 and 0.52–1.02, respectively. ICV values and relationships between Zr/Sc and Th/Sc ratios indicate negligible sedimentary recycling. The Al 2 O 3 /TiO 2 (14–26) and TiO 2 /Zr (56–77) ratios imply that the source rocks of the investigated shales had intermediate igneous compositions. However, Cr/V ratios and a La/Th–Hf discrimination diagram suggest that the intermediate compositional signal of the source rocks was derived from a mixture of 75% mafic and 25% felsic igneous rocks rather than intermediate igneous rocks. The major source was the Jiangnan continental island arc with bimodal igneous rocks, lying to the south of the study area, together with a contribution from granites and gneisses uplifted and eroded in the Yangtze Block. Discrimination of tectonic setting using major and trace elements indicates that the source rocks originated in a transitional setting from active continental to passive margin, consistent with the failed intracontinental rift model for the evolution of the South China plate. The Niutitang Formation shales were deposited in a rift basin setting under conditions of anoxic bottom water in a redox-stratified water column, with organic-rich shales prospective for shale-gas production being found in deep-water downslope and basin environments rather than the shallow-water shelf. [ABSTRACT FROM AUTHOR]

Oxidative damage, chronic hyperglycemia, and the formation of advanced glycation end products (AGEs) are important risk factors associated closely with diabetes and its complications. In the present study, the antidiabetic potential of navel orange peel was explored for the first time by evaluating the antioxidant, α-glucosidase inhibition, and antiglycation activities of its extracts and individual flavonoids. In total, seventeen flavonoids were identified from the peel extract, of which 5-hydroxy-6,7,3′,4′-tetramethoxyflavone, didymin and sinensetin were the most potent antioxidant, α-glucosidase inhibitor, and glycation inhibitor, respectively. In addition, the structure-activity relationship (SAR) studies of these flavonoids were performed in detail. Moreover, the most potent antidiabetic extract of navel orange peel was quantitatively analyzed by HPLC. The present results support the potent application of orange peel as a nutraceutical resource for diabetes management, and might be beneficial to the orange juice industry by providing useful information on the valorization of orange peel. [Display omitted] • Navel orange peel exhibited antidiabetic potential. • Seventeen flavonoids were isolated from the navel orange peel. • Antioxidant, α-glucosidase inhibition, and antiglycation activities were evaluated. • Structure-activity relationship studies were performed in detail. • The most potent antidiabetic extract was quantitatively analyzed by HPLC. [ABSTRACT FROM AUTHOR]

Rare earth (RE) elements with unique 4f orbitals have emerged as crucial components in advancing nanomaterials for improved electrocatalytic water splitting because of the overlap of the wavefunctions between d and f orbitals can lead to the formation of a charge-transfer highway, thereby decreasing the energy barrier and balancing the adsorption of intermediates during electrocatalytic reactions. This review summarizes recent developments in utilizing RE elements to enhance the performance of nanomaterials in water splitting applications. The unique electronic structure and catalytic properties of RE elements offer a promising avenue for optimizing electrocatalysts and improving overall efficiency in water electrolysis. Various RE element modulated catalysts used for driving water splitting are systematically discussed. Furthermore, the electronic interaction between RE elements and other elements in nanomaterials are explored, highlighting the potential for further enhancing electrocatalytic performance. This review emphasizes the significant role of RE elements in advancing nanomaterials for efficient electrocatalytic water splitting and sets the stage for future research directions in this area. • The rare earth elements can modify the electronic structure of catalysts. • The modifications imparted by rare earth elements on the properties of nanocatalysts are discussed. • Various rare earth modulated nanocatalysts for water splitting are highlighted. • The challenges and future outlook of this field are summarized. [ABSTRACT FROM AUTHOR]

• Duality in standard data envelopment analysis migrates to additive network model. • Parametric linear models are solved by an improved golden section method. • Frontier projection and divisional efficiency are derived in envelopment network model. In the previous literature, it is demonstrated that the dual equivalence of multiplier and envelopment models that exists in standard data envelopment analysis (DEA) is not necessarily true for network DEA to derive frontier projection and divisional efficiency. Multiplier network model is often used for computing the divisional efficiency while envelopment network model is often used for identifying the frontier projection for inefficient decision making units (DMUs). In this paper, we show that the duality of standard DEA can be extended to two-stage additive network DEA. We propose an improved golden section method to solve parametric linear multiplier network model. Based on the primal-dual correspondence of parametric linear programming, we subsequently develop envelopment network model in parametric linear form to determine frontier projection and to find divisional efficiency as well. [ABSTRACT FROM AUTHOR]

Fetal heart rate (FHR) monitoring is the most widely used tool in clinics to assess fetal health. However, FHR with low-quality signals may somehow exaggerate the risk of the fetus suffering from acidemia, thus contributing to an increase in cesarean section rates. If there is an algorithm capable to identify and reject low-quality signals and then calculate heart rate parameters only on high-quality signals, inappropriate obstetric interventions may be greatly reduced. Currently, only the Signal Quality Index (SQI) is available for adults. When we applied SQI to fetal data, its performance drops dramatically. To fill the gap in the fetal signal quality index, we developed an easy-to-use Fetal heart rate Signal Quality Index (FSQI) in this paper. Firstly, we used a human-in-the-loop strategy to reduce the amount of data annotation effort. Secondly, we developed the FSQI algorithm oriented towards the fetus to identify low-quality signal segments. Further, we proposed a post-processing technique based on fine-grained recognition to identify low-quality signal segments more accurately. Finally, we applied the FSQI algorithm in combination with the existing FHR deceleration event detection algorithm to test the effectiveness of the algorithm. The results showed that the FSQI algorithm we developed achieved an overall accuracy of 99.8842% in signal quality classification, while also eliminating 94.92% of the incorrectly detected deceleration events of current state-of-the-art methods. • The first paper focused on Fetal Heart Rate (FHR) signal quality. • Human-in-the-loop strategy to reduce the data annotation workload. • Our developed FHR Signal Quality Index (FSQI) achieves 99.8842% overall accuracy. [ABSTRACT FROM AUTHOR]