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Although electrocatalytic water splitting is a very promising and sustainable method for generating hydrogen as a clean energy source, the design and synthesis of stable and efficient noble metal-free catalysts faces some serious challenges. In this work, an electrocatalyst with heterostructure of MoS 2 and orthogonal phase of CoSe 2 (MoS 2 @o-CoSe 2) is derived from Co-based metal organic framework (Co-MOF). The complex shows excellent hydrogen evolution reaction (HER) activity and long-term stability in alkaline medium attributed to its porous structure, ultrathin nanosheet morphology, synergistic effect of each component owing to the tightly bonded interface and optimal electronic structure after phase transition. MoS 2 @o-CoSe 2 exhibits low overpotential of 34 mV at a current density of 10 mA cm−2 and a Tafel slope of 41 mV dec−1. These results are superior to most recently reported Mo-based and Co-based electrocatalysts. Importantly, the performance of MoS 2 @o-CoSe 2 at high current densities is even better than that of commercial Pt/C electrode. Our results emphasize the importance of phase engineering and show that the combination of MOF with transition metal disulfides is an effective way to develop highly active and sustainable efficient electrocatalysts for water hydrolysis. • MOF-derived MoS 2 @o-CoSe 2 shows excellent HER performance. • Low overpotential, high exchange current densities and fast kinetics are achieved. • Performance of MoS 2 @o-CoSe 2 at high current densities is even better than Pt/C. • The phase transition is essential to promote the HER performance. [ABSTRACT FROM AUTHOR]

Microbial application is an efficient, economical, and ecofriendly method for remediating black-odorous rivers. In this study, the field treatment effect and microbial community changes were monitored during remediation by the acclimated complex microorganisms of a typical black-odorous stream. After the treatment, the total phosphorus and ammonia contents decreased by 74.0% and 76.3% and the concentrations of dissolved oxygen increased from 1.65 to 4.90 mg/L, indicating the effectiveness of the acclimated composite microorganisms. The proportion of Bacteroidetes decreased significantly by 48.1% and that of Firmicutes increased by 2.23% on average, and the microbial diversity index first increased and then tended to be uniform. Redundancy analysis demonstrated that the pH, dissolved oxygen, and oxidation-reduction potential together determined the composition of the microbial communities (p < 0.05). These findings showed that the acclimated composite microorganisms can effectively remediate the black odor. [Display omitted] [ABSTRACT FROM AUTHOR]

The main challenge in addressing constrained multi-objective optimization problems (CMOPs) lies in achieving a balance among convergence, diversity, and feasibility. To address this issue, this paper proposes a constrained multi-objective evolutionary algorithm with Pareto estimation via neural network named CMOEA-PeNN. In order to exploit and explore the decision space, the proposed algorithm employs a dual-population mechanism, which is trained with a self-organizing map (SOM). Firstly, the population distribution structure in decision space is mapped to objective space while preserving neighborhood information, and then the neuron weight is utilized to estimate the Pareto front (PF). Secondly, a novel approach is devised to preserve the feasibility of the population and enhance the estimation of the Pareto front by SOM. The achievement scalarizing function (ASF) is employed to choose promising solutions. This strategy could guide the population toward the optimal solution while exploring the small feasible regions. Finally, the performance of CMOEA-PeNN is compared with five state-of-the-art constrained multi-objective evolutionary algorithms (CMOEAs) on three widely used benchmark problems and a real-world problem. The experimental results show that CMOEA-PeNN could archive competitive performance in solving CMOPs. [ABSTRACT FROM AUTHOR]

Electrochemical activation is an effective method for synthesizing economically feasible heterogeneous hydrogen evolution reaction (HER) electrocatalysts. Herein, we first synthesized MoO2-Co2Mo3O8 precatalyst, which was electrochemically activated to produce K2Mo3O10 within the original phase to form the heterogeneous structure. The electrochemically activated samples demonstrate exceptional HER activity in alkaline medium, which exhibit a low overpotential of 31 mV at current density of 10 mA cm−2 (135 mV at 100 mA cm−2), as well as a small Tafel slope of 34 mV dec−1. This is due to the creation of multiphase heterostructures that prompt interfacial interactions and accelerate charge transfer. Simultaneously, the creation of additional active sites increases their intrinsic activities. The combined effects collectively enhance the HER performance. The application of this method in the preparation of HER catalysts is still relatively unexplored, thus rendering our work a pioneering contribution to the field. [ABSTRACT FROM AUTHOR]

The volcanic rocks of the Es3 (third member of the Shahejie) formation in the eastern sag of the Liaohe Basin are composed of basalt and trachyte, and the reservoir characteristics indicate complex reservoir space and strong heterogeneity. The latter is closely related to oil and gas reserves, and is important for evaluating reservoirs and predicting their oil and gas production. Electrical imaging data are obtained during such analysis and are subsequently transformed into a porosity map to obtain the porosity spectra and bin distribution. The results can then be used to qualitatively study the heterogeneity of the reservoir. In the present study, however, quantitative analysis is applied to evaluate the reservoir diversity of these volcanic rocks by calculating four heterogeneity parameters: the sorting index and the porosity variation coefficient, porosity ratio, and the heterogeneity coefficient. Combining the porosity spectra and porosity bin features enables the reservoir heterogeneity to be divided into three categories. The first is weak heterogeneity, which has both a sorting index and variation coefficient of <0.15, a porosity ratio of <2, and a porosity heterogeneity coefficient of <1.5. The second is moderate heterogeneity, with both a sorting index and porosity variation coefficient of 0.15–0.25, a porosity ratio of 2–4, and a porosity heterogeneity coefficient of 1.5–2.0. The third is strong heterogeneity, with both a sorting index and porosity variation coefficient of >0.25, a porosity ratio of >4, and a porosity heterogeneity coefficient of >2.0. In these three cases, the porosity spectra are dominated by unimodal distributions, bimodal distributions with tails, or multimodal distributions with tails, respectively. The heterogeneity of the volcanic reservoir was controlled by the lithology. The trachyte, from which most oil and gas is presently produced, is characterized mainly by weak heterogeneity, and the basalt is characterized mostly by moderate or strong heterogeneity. Thus, exploration conducted in the basalt layer should consider reservoirs with moderate heterogeneity and large pore sizes. • Heterogeneity of volcanic reservoir is analyzed by the porosity spectrum and porosity bins distribution derived from electrical imaging log in detail. • Based on the four heterogeneity parameters the heterogeneity can be quantitatively divided into three categories. • It is predicted that the favorable lithologic belts are trachyte with weak heterogeneity and basalt with moderate heterogeneity and large pore sizes. [ABSTRACT FROM AUTHOR]

Banana is an important source of carotenoids, and the fruit accumulate carotenoids during the ripening process. However, the regulatory mechanisms underlying carotenoid production in banana fruit have not been well studied. Here, we report that MaERF124 is a negative transcriptional regulator of carotenogenesis genes in banana. The reduced accumulation of MaERF124 was accompanied with the increased contents of carotenoids during the ripening of the four banana varieties, suggesting a negative role of MaERF124 in carotenoid production. Further assays showed that MaERF124 acts as a transcriptional repressor and directly targets the promoters of carotenoid biosynthetic genes including MaDXR , MaGGPS , MaCRTISO and MaLCYB1.2. Moreover, ectopic expression of MaERF124 in tomato fruit repressed the transcript levels of carotenoid formation genes to inhibit carotenoid production. Taken together, these findings reveal that MaERF124 negatively modulates carotenoid formation via transcriptional repression of key genes involved in carotenoid synthesis, which provides a regulatory machinery for improving the contents of carotenoids in banana fruit. • Reduced expression of MaERF124 is inversely associated with carotenoid accumulation. • MaERF124 acts as a transcriptional repressor. • MaERF124 suppresses the transcription of carotenogenesis genes. • Overexpression of MaERF124 in tomato inhibits carotenoid production. [ABSTRACT FROM AUTHOR]

Fruit size is an important fruit quality trait that influences the production and commodity values of loquats (Eriobotrya japonica Lindl.). The Small Auxin Upregulated RNA (SAUR) gene family has proven to play a vital role in the fruit development of many plant species. However, it has not been comprehensively studied in a genome-wide manner in loquats, and its role in regulating fruit size remains unknown. In this study, we identified 95 EjSAUR genes in the loquat genome. Tandem duplication and segmental duplication contributed to the expansion of this gene family in loquats. Phylogenetic analysis grouped the SAURs from Arabidopsis, rice, and loquat into nine clusters. By analyzing the transcriptome profiles in different tissues and at different fruit developmental stages and comparing two sister lines with contrasting fruit sizes, as well as by functional predictions, a candidate gene (EjSAUR22) highly expressed in expanding fruits was selected for further functional investigation. A combination of Indoleacetic acid (IAA) treatment and virus-induced gene silencing revealed that EjSAUR22 was not only responsive to auxin, but also played a role in regulating cell size and fruit expansion. The findings from our study provide a solid foundation for understanding the molecular mechanisms controlling fruit size in loquats, and also provide potential targets for manipulation of fruit size to accelerate loquat breeding. [ABSTRACT FROM AUTHOR]

Accurate and timely traffic flow prediction is a critical part of the steps to alleviate traffic congestion. Fully considering the spatial–temporal dependencies of traffic flow is the key to accurately predicting traffic flow. Addressing the problem that traditional methods are difficult to capture the complex spatial–temporal dependence of urban traffic flow, and therefore cannot meet the accuracy requirements for medium and long-term prediction tasks, this paper uses Graph Convolution (GCN) and Long Short-Term Memory (LSTM) methods to capture time and space dependence through data analysis, and proposes a new type of deep learning model MCGC-LSTM. GCN is utilized to learn spatial dependence by analyzing the topological structure of an urban road traffic network, while LSTM is utilized to learn temporal dependence by analyzing the dynamic changes of traffic flow. The experimental results based on a real data set show that this method can achieve better prediction accuracy. [ABSTRACT FROM AUTHOR]