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BackgroundCorn stover (CS) is evaluated as the most favorable candidate feedstock for butanol production via microbial acetone–butanol–ethanol (ABE) fermentation by Clostridium acetobutylicum. By independent acid pretreatment and enzymatic hydrolysis, fermentable sugars (mainly glucose and xylose) were released, of which glucose was naturally utilized as the most preferred carbon source by C. acetobutylicum. However, the ABE fermentation using corn stover hydrolysate (CSH) without detoxification is typically limited to poor sugars utilization, butanol production and productivity. In the presence of pretreatment-derived inhibitors, the intracellular ATP and NADH, as important factors involved in cell growth, solventogenesis initiation and stress response, are exceedingly challenged owing to disrupted glucose phosphotransferase system (PTS). Therefore, there is a necessity to develop effective engineering approaches to overcome these limitations for high-efficient butanol production from CSH without detoxification.ResultsPTS-engineered C. acetobutylicum strains were constructed via overexpression and knockout of gene glcG encoding glucose-specific PTS IICBA, which pleiotropically regulated glucose utilization, cell growth, solventogenesis and inhibitors tolerance. The PTSGlcG-overexpressing strain exhibited high fermentation efficiency, wherein butanol production and productivity was 11.1 g/L and 0.31 g/L/h, compared to those of 11.0 g/L and 0.15 g/L/h with the PTSGlcG-deficient strain. During CSH culture without detoxification, the PTSGlcG-overexpressing strain exhibited desirable inhibitors tolerance and solventogenesis with butanol production of 10.0 g/L, increased by 300% and 400% compared to those of 2.5 and 2.0 g/L with the control and PTSGlcG-deficient strains, respectively. As a result of extra glucose and 10 g/L CaCO3 addition into CSH, butanol production and productivity were further maximized to 12.5 g/L and 0.39 g/L/h. These validated improvements on the PTSGlcG-overexpressing strain were ascribed to not only efficient glucose transport but also its cascading effects on intracellular ATP and NADH generation, solventogenesis initiation and inhibitors tolerance at the exponential growth phase.ConclusionThe PTSGluG regulation could be an effective engineering approach for high-efficient ABE fermentation from lignocellulosic hydrolysates without detoxification or wastewater generation, providing fundamental information for economically sustainable butanol production with high productivity.

Large-scale datasets inevitably contain noisy labels, which induces weak performance of deep neural networks (DNNs). Many existing methods focus on loss and regularization tricks, as well as characterizing and modelling differences between noisy and clean samples. However, taking advantage of information from different extents of distortion in latent feature space, is less explored and remains challenging. To solve this problem, we analyze characteristic distortion extents of different high-dimensional features, achieving the conclusion that features vary in their degree of deformation in their correlations with respect to categorical variables. Aforementioned disturbances on features not only reduce sensitivity and contribution of latent features to classification, but also bring obstacles into generating decision boundaries. To mitigate these issues, we propose class sensitivity feature extractor (CSFE) and T-type generative classifier (TGC). Based on the weighted Mahalanobis distance between conditional and unconditional cumulative distribution function after variance-stabilizing transformation, CSFE realizes high quality feature extraction through evaluating class-wise discrimination ability and sensitivity to classification. TGC introduces student-t estimator to clustering analysis in latent space, which is more robust in generating decision boundaries while maintaining equivalent efficiency. To alleviate the cost of retraining a whole DNN, we propose an ensemble model to simultaneously generate robust decision boundaries and train the DNN with the improved CSFE named SoftCSFE. Extensive experiments on three datasets, which are the RML2016.10a dataset, UCR Time Series Classification Archive dataset and a real-world dataset Clothing1M, show advantages of our methods.

The Weather Research and Forecasting (WRF) model is a mesoscale numerical weather prediction system, which is widely used in major high-performance server platforms. This study focuses on the performance evaluation and optimization of WRF on Huawei’s self-developed kunpeng 920 processor platform, aiming to improve the operational efficiency of WRF. The results of the study show that the scalability of WRF on kunpeng 920 processor is well performed; the performance of WRF on kunpeng 920 processor is improved by 32.6% after invoking the Fast Math Library and Domain Decomposition Core Tile Division optimization. In terms of IO, the main optimizations are parallel IO and asynchronous IO. Eventually, the single output time of WRF is reduced from 37.28 s in serial IO mode to 0.14 s in asynchronous IO mode, and the overall running time is reduced from 1078.80 s to 807.94 s.

Hydrogen gas sensing is critical for energy storage, industrial safety, and environmental monitoring. However, traditional sensors still face challenges in selectivity, sensitivity, and stability. This work introduces an innovative N-polar GaN/AlGaN high-electron-mobility transistor (HEMT) with a 10 nm Pd catalytic layer as a hydrogen sensor. The device achieves ppm-level H2 detection with rapid recovery and reusability, which is comparable to or even exceeds the performance of conventional Ga-polar HEMTs. The N-polar structure enhances sensitivity through its unique polarization-induced 2DEG and intrinsic back barrier, while the Pd layer catalyzes H2 dissociation, forming a dipole layer that can modulate the Schottky barrier height. Experimental results demonstrate superior performance at both room temperature and elevated temperatures. Specifically, at 200 °C, the sensor exhibits a response of 102% toward 200 ppm H2, with response/recovery times of 150 s/17 s. This represents a 96% enhancement in sensitivity and a reduction of 180 s/14 s in response/recovery times compared to room-temperature conditions (23 °C). These findings highlight the potential of N-polar HEMTs for high-performance hydrogen sensing applications.

Large yellow croaker (Larimichthys crocea) is an economically important marine fish species of China. Due to overfishing and marine pollution, the wild stocks of this croaker have collapsed in the past decades. Meanwhile, the cultured croaker is facing the difficulties of reduced genetic diversity and low growth rate. To explore the molecular markers related to the growth traits of croaker and providing the related SNPs for the marker-assisted selection, we used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic bases of growth traits in a cultured population and identify the SNPs that associated with important growth traits by GWAS. A total of 220 individuals were genotyped by ddRAD sequencing. After quality control, 27,227 SNPs were identified in 220 samples and used for GWAS analysis. We identified 13 genome-wide significant associated SNPs of growth traits on 8 chromosomes, and the beta P of these SNPs ranged from 0.01 to 0.86. Through the definition of candidate regions and gene annotation, candidate genes related to growth were identified, including important regulators such as fgf18, fgf1, nr3c1, cyp8b1, fabp2, cyp2r1, ppara, and ccm2l. We also identified SNPs and candidate genes that significantly associated with body shape, including bmp7, col1a1, col11a2, and col18a1, which are also economically important traits for large yellow croaker aquaculture. The results provided insights into the genetic basis of growth and body shape in large yellow croaker population and would provide reliable genetic markers for molecular marker-assisted selection in the future. Meanwhile, the result established a basis for our subsequent fine mapping and related gene study.

Unconventional superconductivity typically emerges out of a strongly correlated normal state, manifesting as a highly renormalised Fermi liquid or a strange metal with T -linear resistivity. In Ruddlesden-Popper bilayer nickelates, superconductivity with a critical temperature T c exceeding 80 and 40 K has been respectively realised in pressurised bulk crystals and epitaxially strained thin films. These advancements call for the characterisation of fundamental normal-state and superconducting parameters in these new materials platforms of high- T c superconductivity. Here we report detailed magnetotransport experiments on superconducting La 2 PrNi 2 O 7 (LPNO) thin films under pulsed magnetic fields up to 64 T and access the normal-state behaviour over a wide temperature range between 1.5 and 300 K. We find that the normal state of thin-film LPNO exhibits the hallmarks of Fermi-liquid transport, including T 2 temperature dependence of resistivity and Hall angle, and H 2 magnetoresistance obeying Kohler scaling. Using the empirical Kadowaki-Woods ratio, we estimate a quasiparticle effective mass m * / m e  ≃ 10, thereby revealing the highly renormalised Fermi liquid state therein. Our results demonstrate that thin-film LPNO follows the same T c / T F scaling observed across a myriad of strongly correlated superconductors and establish key normal-state characteristics of strained bilayer superconducting nickelates. The authors report magneto-transport experiments on La 2 PrNi 2 O 7 thin films under pulsed magnetic fields up to 64 T to suppress the superconductivity. They find that the normal state is a highly renormalised Fermi liquid.

Recently, the bilayer nickelate La 3 Ni 2 O 7 has been discovered as a new superconductor with transition temperature T c near 80 K under high pressure 1 , 2 – 3 . Despite extensive theoretical and experimental work to understand the nature of its superconductivity 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 – 29 , the requirement of extreme pressure restricts the use of many experimental probes and limits its application potential. Here we present signatures of superconductivity in La 3 Ni 2 O 7 thin films at ambient pressure, facilitated by the application of epitaxial compressive strain. The onset T c varies roughly from 26 to 42 K, with higher T c values correlating with smaller in-plane lattice constants. We observed the co-existence of other Ruddlesden–Popper phases within the films and dependence of transport behaviour with ozone annealing, suggesting that the observed low zero resistance T c of around 2 K can be attributed to stacking defects, grain boundaries and oxygen stoichiometry. This finding initiates numerous opportunities to stabilize and study superconductivity in bilayer nickelates at ambient pressure, and to facilitate the broad understanding of the ever-growing number of high temperature and unconventional superconductors in the transition metal oxides. Signatures of superconductivity in La 3 Ni 2 O 7 thin films are demonstrated, facilitated by the application of epitaxial compressive strain, suggesting that the observed low zero resistance T c of around 2 K can be attributed to several factors.

ObjectivesPatients with gallbladder carcinoma (GBC) lack effective treatment methods largely due to the inadequacy of both molecular characterisation and potential therapeutic targets. We previously uncovered a spectrum of genomic alterations and identified recurrent mutations in the ErbB pathway in GBC. Here, we aimed to study recurrent mutations of genes and pathways in a larger cohort of patients with GBC and investigate the potential mechanisms and clinical significance of these mutations.DesignWe performed whole-exome sequencing (WES) in 157 patients with GBC. Functional experiments were applied in GBC cell lines to explore the oncogenic roles of ERBB2/ERBB3 hotspot mutations, their correlation with PD-L1 expression and the underlying mechanisms. ERBB inhibitors and a PD-L1 blocker were used to evaluate the anticancer activities in co-culture systems in vitro and in vivo.ResultsWES identified ERBB2 and ERBB3 mutations at a frequency of 7%–8% in the expanded cohort, and patients with ERBB2/ERBB3 mutations exhibited poorer prognoses. A set of in vitro and in vivo experiments revealed increased proliferation/migration on ERBB2/ERBB3 mutation. Ectopic expression of ERBB2/ERBB3 mutants upregulated PD-L1 expression in GBC cells, effectively suppressed normal T-cell-mediated cytotoxicity in vitro through activation of the PI3K/Akt signalling pathway and contributed to the growth and progression of GBC in vivo. Treatment with an ERBB2/ERBB3 inhibitor or a PD-L1 monoclonal antibody reversed these immunosuppressive effects, and combined therapy revealed promising therapeutic activities.Conclusions ERBB2/ERBB3 mutations may serve as useful biomarkers in identifying patients who are sensitive to ERBB2/ERBB3 inhibitors and PD-L1 monoclonal antibody treatment.Trial registration number NCT02442414;Pre-results.

The NVH (noise, vibration, harshness) performance of a motor is one of the main problems affecting the comfort, safety, and reliability of electric vehicles. Electromagnetic force is the main cause of motor noise. Most of the existing research focuses on the overall noise level, and does not consider the impact of specific orders of electromagnetic force on noise, which results in a lack of applicability of noise reduction techniques. In this paper, a rotor with an auxiliary slot was used to weaken the electromagnetic force. A multi-objective optimization algorithm combining finite-element simulation with a response surface method was proposed. To determine the relationship between specific orders of electromagnetic force and the auxiliary slot parameters, simulation experiments were carried out with a large range and a large step size in finite-element analysis software. Then, the parameter range with a low value of electromagnetic force was selected. In this new range, the response surface method was used to establish the parameter and electromagnetic force expressions. Then, the linear weighting method in the multi-objective optimization algorithm was selected to determine the objective function of the multi-order electromagnetic force optimization. The weight of each order of electromagnetic force was set according to its contribution to the noise. Finally, the effectiveness of the proposed method was verified by simulations. Simulation results show that this method can quickly and effectively determine the optimal size of the auxiliary slot. In addition, the maximum value of the noise was reduced from 107.6 to 103.2 dB.