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Previous studies have demonstrated that high physiological levels of reactive oxygen species induce pupal diapause and extend lifespan in the moth Helicoverpa armigera. This has been shown to occur via protein arginine methyltransferase 1 (PRMT1) blockade of Akt-mediated phosphorylation of the transcription factor FoxO, after which activated FoxO promotes the initiation of diapause. However, it is unclear how PRMT1 is activated upstream of FoxO activity. Here, we show that high reactive oxygen species levels in the brains of H. armigera diapause-destined pupae activate the expression of c-Jun N-terminal kinase, which subsequently activates the transcription factor cAMP-response element binding protein. We show that cAMP-response element binding protein then directly binds to the PRMT1 promoter and upregulates its expression to prevent Akt-mediated FoxO phosphorylation and downstream FoxO nuclear localization. This novel finding that c-Jun N-terminal kinase promotes FoxO nuclear localization in a PRMT1-dependent manner to regulate pupal diapause reveals a complex regulatory mechanism in extending the healthspan of H. armigera. [ABSTRACT FROM AUTHOR]

Hydrogen storage performance for metal hydride (MH) reactor is restricted by the poor thermal conductivity of MH. In this study, the gradient porosity metal foam was added into MH reactor for enhancing heat transportation (GMF reactor), and its hydrogen absorption performance was investigated numerically in detail. Then, thermal resistance analysis was conducted to analyze the heat transportation in GMF reactor, and Genetic Algorithm was applied for optimizing metal foam distribution under different conditions. It was indicated that the hydrogenation performance for optimized two-layer GMF reactor was increased by 11.5% compared with uniform metal foam reactor (UMF reactor). The optimization results indicated that the optimal volumetric fractions of metal foam (VFMF) are about 0.08 for both optimized GMF reactor and UMF reactor with the trade-off of hydrogen storage capacity and hydrogen absorption rate. Then, a new indicator of comprehensive hydrogen storage performance (CHSP) for MH reactor was proposed, which includes the influence of hydrogen storage rate, hydrogen storage capacity, volumetric storage density and gravimetric storage density. Besides, the hydrogenation performance for optimized GMF reactor was improved with metal foam layer increasing, and the optimal porosity distribution was gradually approaching a specific power exponent trend. It was showed that the hydrogenation performance for power-exponent GMF reactor was increased by 2.8% and 18.2% compared with that of optimized four-layer GMF reactor and UMF reactor, respectively. • Gradient porosity metal foam (GMF) was added into MH bed to improve heat transfer. • Genetic algorithm was used to optimize the distribution of metal foam. • Performance of two-layer GMF reactor increases by 11.5% compared with UMF reactor. • The optimal volumetric fraction of metal foam (VFMF) for reactors equal about 0.08. • A new indicator of comprehensive hydrogen storage performance (CHSP) was proposed. [ABSTRACT FROM AUTHOR]

Postoperative adjuvant chemotherapy followed surgery is the standard management for localized advanced colorectal carcinoma (CRC). Mucinous adenocarcinoma (MAC) is a peculiar histological subtype of CRC, but the prognosis of MAC patients is controversial. The objective of this study is to assess the implication of MAC in survival of patients treated with surgery and firs-line adjuvant chemotherapy. Studies describing outcomes for advanced MAC and non-specific adenocarcinoma (AC) of CRC patients treated with first-line postoperative adjuvant chemotherapy followed surgery were searched in PubMed, Embase, Medline, EBSCO, Wiley, and Cochrane Library (January 1963–August 2021). Hazard ratios (HRs) of overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS) for MAC to AC were extracted. Random-effects model was used for calculating the pooled HRs and 95% confidence interval (CI). This meta-analysis is comprised of 8 studies involving a total of 124,303 CRC patients treated with first-line adjuvant chemotherapy followed surgery. The pooled HR for MAC was 1.23 (95% CI, 1.07–1.41, p < 0.01, I2 = 80%), and the DFS (HR, 2.95, 95% CI, 1.22–7.14) of MAC patients were significantly poorer than AC patients. Similar results were also observed in stage III and FOLFOX regimen subgroups. MAC was a risk factor for prognosis of localized advanced CRC patients treated with postoperative first-line adjuvant chemotherapy. Thus, the role of first-line adjuvant chemotherapy regimens should be further studied in these MAC patients. [ABSTRACT FROM AUTHOR]

In the decade, researchers have proposed many remarkable algorithms in structural design, training modes, etc., in the field of Generative AI. However, with the explosive growth of demand for data and annotation in generative models and the emphasis on data-centric algorithms, improving model performance by improving data-efficiency has become another way for the future development of generative models. In this paper, we propose a new strategy to improve the performance of the generative models inspired by active learning. Through the cognitive feature extractor of generative models (similar oracle in active learning) to complete the annotation of data informativeness. By guiding the generative models to focus on samples in low-feature density region, i.e., with high informativeness, the models can gradually achieve "full-cognition" of the data. We conduct extensive experiments to verify the effectiveness of our strategy and demonstrate its widespread application in generative models and downstream data-driven tasks. [ABSTRACT FROM AUTHOR]

Face swapping represents a formidable challenge—it involves a technique that can seamlessly transplant the identity traits from a source figure into the target figure while meticulously preserving the remaining attributes of the target's figure. In the paper, we present HQFace, our framework to achieve the high-quality face swapping. Our exploration revealed that within the latent codes of facial images, identity information are dispersed across a spectrum of feature dimensions to varying extents. Based on this discovery, we design an innovative adaptive 'exploration-fusion' mechanism that adaptive searches identity information across these dimensions, and deftly fuses together the threads of identity-specific and the remaining attributes of the target's figure. To enhance the verisimilitude of the facial details even further, we integrated a dual encoding and decoding tactic into the aforementioned fusion process. This novel strategy mitigates the potential hue distortions in facial complexions, which may arise from encoding drifts compared to latent spatial anchors. HQFace is put to the test through a comprehensive series of experiments, which stands as a testament to the framework's ability to deliver high-quality face swapping with strikingly true and devoid of artifacts. • We study identity information across diverse feature dimensions. • We create a adaptive exploration-fusion mech to operate feature. • We propose a dual en-decoding approach refines facial details. • HQFace can execute high-quality face swapping. [ABSTRACT FROM AUTHOR]

Adding the heat transfer enhancement components into the MH reactor can improve the hydrogen absorption/desorption rate, but the vital indicators as the gravimetric and volumetric hydrogen storage density decrease at the same time, which is hardly considered in the published researches. In this study, a comprehensive hydrogen storage performance (CHSP) indicator for the MH reactor has been proposed considering the above contradiction, which can be applied to evaluate the comprehensive performance of the MH reactor and compare the reactor performances with different heat transfer configurations. Then, with the constraint of the CHSP, the heat transfer structure of the classical finned-tube MH reactor is optimized using a novel sieving optimization strategy which combines the Taguchi design and the data-driven optimization (ANN model + GA) to increase the optimization efficiency and the reliability of optimization solutions. The optimized results indicate that the optimal structural parameters of the finned-tube MH reactor are the diameter of heat exchange tube d of 5.13 mm, the fin thickness h of 0.28 mm, the fin radius r of 21.73 mm and the fin number N of 11, and the optimal CHSP is 0.547 mg/s. • Considering tradeoff between reaction rate enhancement and hydrogen storage density decrease. • A comprehensive performance indicator CHSP for MH reactor is established. • Sieving optimization strategy is proposed to increase optimization efficiency. • Taguchi design is applied to decrease the required data size of ANN model. • The optimal CHSP of finned-tube MH reactor is 0.547 mg/s. [ABSTRACT FROM AUTHOR]

Extracting valuable metals from waste lithium-ion batteries is beneficial to the long-term growth of social economy and environmental maintenance from lithium-ion batteries, yet it faces serious challenges. The study aims to propose a harmless and efficient electrolysis method for selectively preparing nickel products from lithium-ion batteries leachate by controlling the competitive reductive order for Ni2+ and H 2 O. Compared with current pyrometallurgy, hydrometallurgy, and bio-metallurgy methods, electrolysis method allows selective preparation of different nickel products. No additional chemicals are introduced, or no membrane limitation. Achieving zero pollution emissions while saving costs. The results of serial experiments show that the level of nickel reduction can be controlled to produce different types of nickel products. The current efficiency reached a maximum value of 84.7±4.5%. 125 A/m2, 0.05 M Ni2+, 1.5 h, 60 A/m2, 0.1 M Ni2+, 2 h, 125 A/m2, 0.25 M Ni2+, 2 h are the optimal conditions for forming Ni(OH) 2 , black powder Ni and silvery flake Ni, respectively. In electrolysis process, selective nickel products, H 2 and O 2 can be prepared. H 2 can be used as clean energy and increases economic benefits. This study provides a clean and high-efficiency method for selectively preparing nickel products from lithium-ion batteries leachate. [Display omitted] • A clean electrolysis was designed to simultaneous extraction and separation of nickel product. • Maximum current efficiency is 84.7±4.5% where products are Ni(OH) 2 and nickel plates. • Mechanism of simultaneous extraction and separation nickel product was offered. [ABSTRACT FROM AUTHOR]

Microbial electrosynthesis is a biocathode-driven device for chemicals production from carbon dioxide reduction and has been a promising carbon-consuming technology to alleviate the greenhouse effect and acquire the renewable energy. However, previous studies primarily focused on the effect of the operating parameters on the biocathode with an indirect electron transfer (IDET) pathway instead of a direct electron transfer (DET) pathway for CO 2 reduction. In this work, we aim to study the effect of the operating parameters, including temperature, inorganic carbon source, and initial pH value, on the biocathode with a DET pathway for CO 2 reduction to CH 4. The CH 4 -producing biocathodes showed the respective optimum performance at the condition of 35 °C temperature, 4 g L−1 bicarbonate concentration, and pH 7.5 catholyte. This work provides an important guidance for the operation and development of microbial electrosynthesis for CO 2 reduction to chemicals. • Effects of temperature, inorganic carbon source, and pH value were studied. • 35 °C, 4 g L−1 bicarbonate, and pH 7.5 were the optimum operating parameters. • The Faradaic efficiencies for CH 4 production at all conditions exceeded 90%. [ABSTRACT FROM AUTHOR]

A novel cylindrical metal hydride (MH) reactor with loop-type finned tube and jacket heat exchanger was proposed in this work. This MH reactor is expected to possess high performance due to the enhanced heat transfer, compact structure and good gas tightness. A three-dimensional multi-physical model for hydrogen absorption was presented to investigate the evolutions of temperature and concentration in the MH bed, as well as the mean reaction rate of hydrogen absorption process. The effects of different fin configurations on the performance of the proposed MH reactor were also examined. It was indicated that the evolution curve of the mean reaction rate for the whole hydrogen absorption process can be divided into two stages. The reaction rate in the first stage is mainly dependent on the initial conditions (i.e., temperature and gas pressure) of MH bed, whereas the second stage is mainly influenced by the heat dissipation from MH bed to cooling fluid. For the proposed MH reactor, the total charging time for reaching 90% hydrogen saturation can be decreased by 56.8% and 81.9% as compared with that for cylindrical MH reactor with finned double U-shape tube heat exchanger and cylindrical MH reactor with finned single-tube heat exchanger, respectively. Also, it was found that the interlaced layout design of inner and outer fins can improve the uniformity of the temperature distribution inside the MH bed as compared with the parallel layout configuration. Besides, it was showed that increasing the number of fins with keeping the total fin volume constant, the absorption performance of the reactor can be improved. • A novel MH reactor with loop-type finned tube and jacket heat exchanger was proposed. • Three-dimensional multi-physical model for hydrogen absorption was presented. • Evolution of mean reaction rate of hydrogen absorption was analyzed. • The proposed reactor exhibits well performance due to the enhanced heat transfer. • The effects of fin configurations on the reactor performance were examined. [ABSTRACT FROM AUTHOR]

• Initial set cathode potentials determine the electron transfer behavior of biocathode. • Biocathodes developed at > –0.8 V mainly possessed a direct electron transfer manner. • Biocathodes developed at < –0.8 V mainly possessed an indirect electron transfer pathway. Microbial electrosynthesis is an innovative technology capable of producing biofuels (particularly CH 4) via CO 2 reduction. Electron-uptaking from biocathode by microorganisms is the key step in the process of microbial electrosynthesis. However, the lack of understanding of electron transfer behaviors and their affecting factors largely limit the development of microbial electrosynthesis. Herein, we investigated the effects of initial startup cathode potentials (–0.7, –0.8, –0.9, –1.0 and –1.1 V vs. Ag/AgCl) on the electron transfer behaviors of biocathodes. The cyclic voltammetry (CV) showed typical sigmoidal catalytic currents corresponding to the CO 2 reduction on the biocathodes started up at –0.7 and –0.8 V, but not on the other biocathodes. The CH 4 production rate, Faradaic efficiency, scanning electron microscopy (SEM), and microbial community were also investigated. All the results indicated that the startup cathode potentials determine the electron transfer behaviors of biocathode: the biocathodes started up at –0.7 and –0.8 V mainly possessed a direct electron transfer manner, while the biocathodes started up at –0.9, –1.0 and –1.1 V mainly possessed an indirect electron transfer pathway. This study provides a guidance for the development of CH 4 -producing biocathodes with a desired electron transfer behavior. [ABSTRACT FROM AUTHOR]

Now, deep learning technology has gradually matured and successfully applied in various fields, bringing great convenience to human life. However, people neglect the importance of early sample collection and data processing while continuously improving the quality of network models, which often leads to poor application effect of models in practical projects. At present, the Data-centric AI campaign has started in the field of deep learning, with the purpose of letting researchers pay attention to the quality of data. This paper proposes a sample selecting method based on feature density from the motion idea, which can be applied to practical application scenarios where there is a huge deviation in the distribution of train set and test set, the dataset redundancy is too high, and the dataset sampling is guided. This method uses ternary loss function to constrain and aggregate sample feature points, constructs feature density space through feature extractor, traverses feature points to calculate distance between samples, judges special category redundancy and deletes redundant samples, and finally retains samples as highly representative samples to optimize dataset distribution. In the experiment, the self-built dataset IP05 are used in this paper. Sufficient experimental results show that the samples selected by the feature density sample selecting method are indeed more representative. • We propose a sample screening method based on feature density which can reduce the redundancy of train set in smart agriculture. • Ternary loss is used in our proposed method to constrain or aggregate sample feature points, and constructs feature density space through feature extractor. • A feature density function is proposed to calculate the feature point density in the feature density space to assist reducing samples. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Hierarchical vertical graphene/nanorods structure displays excellent liquid repellence and anti-platelet adhesion properties. • The hierarchical structure can be integrated as H 2 O 2 electrochemical sensors. • The hierarchical structure-based sensor could resist the contamination of biocomponents in blood serum. Abstract Detection of H 2 O 2 in bio-fluids plays an important role in early-diagnosis of many diseases, and thus the development of electrochemical H 2 O 2 sensors has been explored. However, constructing robust sensors that could self-clean and avoid biofouling is still challenging, because the complex compositions of bio-fluids could easily absorb to or even passivate the sensor electrode. In this work, we reported the development of H 2 O 2 electrochemical sensor based on hierarchical vertical graphene/nanorods structure (vG/NRs) with self-cleaning and anti-biofouling properties. The hierarchical vG/NRs structure consisted of ZnO nanorods branched on vertical graphene nanowalls, which were fabricated through multiple steps of plasma enhanced chemical vapor deposition, atomic layer deposition and hydrothermal growth. The hierarchical vG/NRs after fluorination (vG/NRs-F) displayed excellent liquid repellence and anti-platelet adhesion properties. The vG/NRs-F was utilized as working electrodes and integrated as electrochemical sensors. H 2 O 2 molecules in solution could access to the vG/NRs surface, inducing electrochemical signals for detection with reasonable sensitivity and selectivity. Meanwhile, the vG/NRs-F electrode could resist the contamination of biocomponents in blood serum after sensing experiment, enabling stable sensing of H 2 O 2 without interfering by biofouling. Our work offers a promising strategy to design self-cleaning and anti-biofouling sensors with extended applicability for detection in complex biological fluids. [ABSTRACT FROM AUTHOR]