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Firms can derive insights not only from their own failures but also from the innovation failures of counterparts in the same industry. This study investigates how 109 Chinese A‐share listed high‐tech firms (2013–2022) learn from counterparts' innovation failures to improve their success rate of innovation and emphasizes the crucial role of venture capital (VC) syndication networks in facilitating knowledge transfer. Central VCs within the network notably enhance vicarious learning from others' failures. Further empirical analysis shows a significant increase in the success rate of exploitative innovations, while the impact on exploratory innovations is minimal. [ABSTRACT FROM AUTHOR]

China has abundant shale gas resources with good exploration value and development potential, making it a recent hotspot for exploration and development. It is widely agreed that large-scale hydraulic fracturing is essential for reservoir enhancement in shale formations. However, the evolution of fractures during hydraulic fracturing is highly complex, necessitating research on the influence of various factors on the vertical propagation of hydraulic fractures. Based on geological and engineering parameters from the Luzhou block in southern Sichuan, this study employed the finite element method (FEM) and the cohesive element method to establish a coupled fluid-solid model for the vertical propagation of hydraulic fractures. Numerical simulations were conducted to investigate the interaction between hydraulic fractures and natural weak planes, clarifying the mechanisms involved. This study elucidates how different rock and natural weak plane properties affect the vertical propagation of hydraulic fractures and draws diagrams illustrating these interactions. The research indicated three fracture distribution patterns after the intersection of hydraulic fractures with natural weak planes: passive fractures, 'I'-shaped fractures, and crossing fractures. The main fractures in these patterns exhibit initial damage and damage evolution characterized by tensile failure. Specifically, in passive fractures, the initial damage and damage evolution of natural weak planes manifest as shear failure. In 'I'-shaped fractures, the initial damage in natural weak planes is characterized by shear failure, with damage evolution showing tensile failure. Crossing fractures show minimal damage in the weak planes. Under conditions of high natural weak plane cohesive strength, high Young's modulus, low interlayer rock cohesive strength, high vertical stress difference, low interlayer stress difference, and high intersection angles, crossing fractures tend to form. Conversely, conditions of low natural weak plane cohesive strength, low Young's modulus, high interlayer rock cohesive strength, low vertical stress difference, high interlayer stress difference, and low intersection angles favor the formation of 'I'-shaped fractures. Passive fractures form under conditions of low natural weak plane cohesive strength and high vertical stress difference. This study found that Poisson's ratio has a minimal effect on the vertical expansion of hydraulic fractures under the studied conditions, with natural weak plane strength being the primary control factor for fracture patterns. These findings enhance the theoretical foundation for the vertical propagation of hydraulic fractures in deep shale formations, facilitating the development and implementation of strategies for enhancing production in shale reservoirs with natural weak planes and better optimizing production in different types of shale reservoirs. [ABSTRACT FROM AUTHOR]

It has become a consensus that large-scale hydraulic fracturing is adopted to achieve the stimulation of unconventional oil and gas reservoir. The complex fracture network formed by fracturing is closely related to the effect of reservoir stimulation, which has extremely complicated evolution process. Therefore, it is necessary to study the evolution law of fracture network in large-scale hydraulic fracturing of unconventional reservoirs. In this article, the geological engineering parameters of horizontal well H in shale gas reservoir in southern Sichuan are taken as an example, a three-dimensional fracture network expansion model is established based on the boundary element method and finite volume method, and the simulation of the complex fracture network in a whole well section is carried out to analyze the evolution law of reservoir fracture network under different geological and engineering parameters. The results show that the horizontal stress field distribution has a significant effect on fracture geometric form. Hydraulic fractures in reservoirs with larger horizontal stress difference have stronger directivity, while the horizontal wellbore tends to obtain better reservoir stimulation results when it is parallel to the minimum horizontal principal stress setting. The conjugated natural fracture developed in the reservoir inhibits the hydraulic expansion fractures in both directions. Although it increases the complexity of the fractures, it is not necessarily conducive to improving the reservoir stimulation effectiveness. The lower the strength of natural fracture is, the more complex the fracture geometric form becomes, and the smaller the stimulated reservoir volume is. Correspondingly, the higher the strength of natural fracture is, the simpler the fracture geometric form becomes, and the larger the stimulated reservoir volume is. Suitable fracturing construction displacement can not only contribute to form a more complex fracture distribution, but also help to obtain a larger stimulated reservoir volume. The optimal construction displacement ranges from 10 to 14 m3/min. Low viscosity fracturing fluids are suitable for the formation of long-narrow fractures and able to connect with the remote reservoir and form complex fracture networks. Lower viscosity fluids can be used to achieve better reservoir stimulation effectiveness when sand-carrying capacity is met. [ABSTRACT FROM AUTHOR]

Generative networks are effective tools for digital materials (DM) inverse design. However, the optimization performance of generative networks is restricted by the increasing discrepancy between the optimized input and the prescribed input domain as the design loop increases. Herein, a correction technique is incorporated into generative deep neural network (GDNN) and generative deep convolutional neural network (GDCNN). The correction is performed by pulling the machine learning (ML)‐optimized inputs back to the prescribed domain at certain interval during the optimization process instead of only postprocessing at the end. A DM system with two phases, i.e., the matrix phase and the pore phase, is used for the structural design. The datasets are produced using a numerical model and describe the relationship between the material structure and the elastic modulus and tensile strength. The results show that the optimization effectiveness of corrected GDNN/GDCNN significantly improves given the fact that more structures converge to the best structures and fewer nonrepetitive structures are left after optimization, which helps to search for the best structures and decreases the computational burden when verifying the ML‐recommended structures. The corrected GDNN and GDCNN also manage to find structures with higher tensile strength in the new inverse design. [ABSTRACT FROM AUTHOR]

It is difficult to identify optimal cut-off frequencies for filters used with the common spatial pattern (CSP) method in motor imagery (MI)-based brain-computer interfaces (BCIs). Most current studies choose filter cut-frequencies based on experience or intuition, resulting in sub-optimal use of MI-related spectral information in the electroencephalography (EEG). To improve information utilization, we propose a SincNet-based hybrid neural network (SHNN) for MI-based BCIs. First, raw EEG is segmented into different time windows and mapped into the CSP feature space. Then, SincNets are used as filter bank band-pass filters to automatically filter the data. Next, we used squeeze-and-excitation modules to learn a sparse representation of the filtered data. The resulting sparse data were fed into convolutional neural networks to learn deep feature representations. Finally, these deep features were fed into a gated recurrent unit module to seek sequential relations, and a fully connected layer was used for classification. We used the BCI competition IV datasets 2a and 2b to verify the effectiveness of our SHNN method. The mean classification accuracies (kappa values) of our SHNN method are 0.7426 (0.6648) on dataset 2a and 0.8349 (0.6697) on dataset 2b, respectively. The statistical test results demonstrate that our SHNN can significantly outperform other state-of-the-art methods on these datasets. [ABSTRACT FROM AUTHOR]

The black, small-bandgap semiconducting framework Eu-dfdmat features extensive Eu3+–sulfur bridges from the linear linker 2,5-difluoro-3,6-dimercaptoterephthalate (dfdmt). Each Eu center is chelated to four dfdmt linkers to form an anionic coordination sphere involving four carboxyl O and four mercapto S centers (EuO4S4), wherein the charge buildup can be alleviated by the electron-withdrawing fluoro groups. The extensive metal-linker bonding, together with a trace of Eu2+ species, appears to boost electronic interaction in the 2D net, generating a small band gap of 1.31 eV (946 nm), albeit a modest conductivity (e.g., 10−6 S m−1). The crystals also exhibit persistent EPR signals indicative of organic radicals (g = 2.002). The Eu-dfdmt solid are stable in air and can be exfoliated into ultrathin nanosheets (ca. 5 nm; 6–8 layers). [ABSTRACT FROM AUTHOR]

Visual models of fractured-vuggy reservoirs were designed and manufactured to conduct experiments of nitrogen assisted gravity drainage (NAGD). The impacts of flooding pattern, gas injection rate, well type, and displacement direction (vertical or horizontal) on development performances and remaining oil distribution were studied. The results show that during NAGD, the sweep scope is decided by the connections between producer and reservoir, and the local sweep efficiency is decided by fracture-vuggy configuration. The homogenous fractured reservoir has higher oil recovery, and the bigger the aperture of fracture is, the higher the recovery. The main regions of remaining oil due to poor connectivity and gas-oil gravity difference include blind fractures and vugs below the connected fractures, the bottom of vugs, and the narrow and low-angle fractures. The accumulation of remaining oil in the bottom of reservoir is easily formed and controlled by the connections between producers and reservoir. The higher the gas injection rate and the stronger the fracture heterogeneity, the earlier the gas channeling and the lower the oil recovery of the producer will be. Horizontal wells have the best development effect, so horizontal well can be applied in fractured-vuggy reservoirs without bottom water. Producers should be preferentially drilled at low structural position. Gas channeling firstly occurs in the producer at high structural position, and it should be shut in timely to improve the utilization of injected gas. [ABSTRACT FROM AUTHOR]

In this study, hypoxia inducible factor-1α (HIF-1α) and hypoxia inducible factor-1β (HIF-1β) from small abalone Haliotis diversicolor were cloned. The cDNA of H. diversicolor HIF-1α (HdHIF-1α) is 2833bp encoding a protein of 711aa and H. diversicolor HIF-1β (HdHIF-1β) is 1919bp encoding a protein of 590aa. Similar to other species' HIF-1, HdHIF-1 has one basic helix–loop–helix (bHLH) domain and two Per-Arnt-Sim (PAS) domains, and HdHIF-1α has a oxygen-dependent degradation domain (ODDD) with two proline hydroxylation motifs and a C-terminal transactivation domain (C-TAD) with an asparagine hydroxylation motif. Under normoxic conditions, HdHIF-1α and HdHIF-1β mRNAs were constitutively present in all examined tissues. Under hypoxia (2.0mg/L DO at 25°C) stress, HdHIF-1α expression was up-regulated in gills at 4h, 24h and 96h, and in hemocytes at 24h and 96h, while HdHIF-1β remained relatively constant. Under thermal stress (31°C), HdHIF-1α expression was significantly increased in gills at 4h, and hemocytes at 0h and 4h, while HdHIF-1β expression still remained relatively constant. These results suggested that HIF-1α may play an important role in adaption to poor environment in H. diversicolor. [ABSTRACT FROM AUTHOR]

• UHPFRC for primarily shear strengthening of RC structures is reviewed. • Focus is on interface behaviour between UHPFRC and concrete in bond and structural tests. • Actual interfacial strength between UHPFRC and concrete is rarely measured by available test methods. • Knowledge on behaviour of UHPFRC hybrid systems under combined mechanical and environmental loads and reliable modelling methods are lacking. Ultra-High Performance Fiber-Reinforced Concrete (UHPFRC) is, due to its superior mechanical properties and low permeability, a promising material for the restoration and improvement of the mechanical resistance and durability of existing Reinforced Concrete (RC) structures. This paper reviews the strengthening applications of UHPFRC in flexure, shear and punching shear, with a focus on shear performance of hybrid structures and the UHPFRC-concrete interface behavior which is governing the response of the hybrid beams. Holistic review approach is adopted considering not only structural behaviour of hybrid UHPFRC-concrete beams at the macro-scale, but also parameters governing the interface behaviour between concrete and UHPFRC at the meso- and micro-scale. Current analytical and numerical methods to predict the shear or punching shear capacity of RC structures strengthened with UHPFRC are reviewed and critically analyzed. Furthermore, the frequently overlooked role of interface, the effects of bonding technique, moisture exchange between the two materials, differential shrinkage and the role of coupled environmental and mechanical loads are discussed. It is observed that although extensive research work has been conducted to study the performance of hybrid UHPFRC-concrete structures, poor understanding of the behavior at the interface between concrete and UHPFRC, the role of thermal and hygral gradients and stress concentration for premature debonding, and the lack of reliable models and design codes impede the wide application of UHPFRC. [ABSTRACT FROM AUTHOR]

Vein-graft bypass is commonly performed to overcome atherosclerosis but is limited by high failure rates, principally due to neointimal wall thickening. Recent studies reveal that endothelial-mesenchymal transition (EndoMT) is critical for vein-graft neointima formation. BETs are a family of Bromo/ExtraTerminal domains-containing epigenetic reader proteins (BRD2, BRD3, BRD4). They bind acetylated histones through their unique tandem bromodomains (BD1, BD2), facilitating transcriptional complex formation and cell-state transitions. The role for BETs, including individual BRDs and their unique BDs, is not well understood in EndoMT and neointimal formation. Repression of BRD4 expression abrogated TGFβ1-induced EndoMT, with greater effects than BRD2 or BRD3 knockdown. An inhibitor selective for BD2 in all BETs, but not that for BD1, blocked EndoMT. Moreover, expression of a dominant-negative BRD4-specific BD2 fully abolished EndoMT. Concordantly, BRD4 knockdown repressed TGFβ1-stimulated increase of ZEB1 protein – a transcription factor integral in EndoMT. In vivo , lentiviral gene transfer of either BRD4 shRNA or dominant negative BRD4-specific BD2 mitigated neointimal development in rat jugular veins grafted to carotid arteries. Our data reveal the BD2 domain of BRD4 as a determinant driving EndoMT in vitro and neointimal formation in vivo. These findings provide new insight into BET biology, while offering prospects of specific BET domain targeting as an approach to limiting neointima and extending vein graft patency. • Vein-graft bypass is a common treatment for cardiovascular disease; it often fails due to stenosing neointima. • EndoMT (endothelial-mesenchymal transition) is an important contributor to vein-graft neointima formation • We identified BRD4 bromodomain-2 as an epigenetic determinant of EndoMT of cultured primary endothelial cells. • Our in vivo transgenic studies indicate that inhibiting BRD4 bromodomain-2 effectively mitigates neointima in vein grafts. [ABSTRACT FROM AUTHOR]

The performance of motor imagery electroencephalogram (MI-EEG) decoding systems is easily affected by noise. As a higher-order spectra (HOS), the bispectrum is capable of suppressing Gaussian noise and increasing the signal-to-noise ratio of signals. However, the sum of logarithmic amplitudes (SLA) and the first order spectral moment (FOSM) features extracted from the bispectrum only use the numerical values of the bispectrum, ignoring the related information between different frequency bins. In this study, we proposed a novel framework, termed a bispectrum-based hybrid neural network (BHNN), to make full use of bispectrum for improving the performance of the MI-based brain-computer interface (BCI). Specifically, the BHNN consisted of a convolutional neural network (CNN), gated recurrent units (GRU), and squeeze-and-excitation (SE) modules. The SE modules and CNNs are first used to learn the deep relation between frequency bins of the bispectrum estimated from different time window segmentations of the MI-EEG. Then, we used GRU to seek the overlooked sequential information of the bispectrum. To validate the effectiveness of the proposed BHNN, three public BCI competition datasets were used in this study. The results demonstrated that the BHNN can achieve promising performance in decoding MI-EEG. The statistical test results demonstrated that the proposed BHNN can significantly outperform other competing methods (p < =0.05). The proposed BHNN is a novel bispectrum-based neural network, which can enhance the decoding performance of MI-based BCIs. • This study proposes a novel neural network to make full use of bispectrum for improving the performance of the MI-BCI. • The combination use of the CNN and SE module can learn the deep relation between frequency bins of the bispectrum. • The GRU can take advantage of sequential information in different time windows. [ABSTRACT FROM AUTHOR]