The development of highly efficient, low-cost and stable electrocatalysts for overall water splitting is highly desirable for the storage of intermittent solar energy and wind energy sources. Herein, ...we show for the first time that nickel can be extracted from NiFe-layered double hydroxide (NiFe-LDH) to generate an Ni2P@FePOx heterostructure. The Ni2P@FePOx heterostructure was converted to an Ni2P@NiFe hydroxide heterostructure (P-NiFe) during water splitting, which displays high electrocatalytic performance for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in 1.0 M KOH solution, with an overpotential of 75 mV at 10 mA cm−2 for HER, and overpotentials of 205, 230 and 430 mV at 10, 100 and 1000 mA cm−2 for OER, respectively. Moreover, it could afford a stable current density of 10 mA cm−2 for overall water splitting at 1.51 V in 1.0 M KOH with long-term durability (100 h). This cell voltage is among the best reported values for bifunctional electrocatalysts. The results of theoretical calculations demonstrate that P-NiFe displays optimized adsorption energies for both HER and OER intermediates at the nickel active sites, thus dramatically enhancing its electrocatalytic activity.
•Combined with the error reconstruction rate, an adaptive VMD technology is developed and used for data preprocessing.•Two mainstream deep learning methods (LSTM, DBN) are used as sub-series ...predictors, and the classic PSO algorithm is utilized to determine the number of neurons in the DBN network.•A novel hybrid prediction model based on the PSO-DBN nonlinear combination mechanism is proposed.
Wind power forecasting plays a vital role in enhancing the efficiency of power grid operation and increasing the competitiveness of power market. In this paper, a novel hybrid forecasting model is developed by using the decomposition strategy, nonlinear weighted combination, and two deep learning models to overcome the drawbacks of the linear weighted combination and further enhance wind power forecasting accuracy and stability. Firstly, the variational mode decomposition (VMD) technique is employed to decompose the original wind power series to extract local features. Then, the long short-term memory neural networks (LSTM) and deep belief networks based on particle swarm optimization (PSO-DBN) are utilized to construct sub-series prediction models. Finally, the multiple sub-series forecasting models are integrated by a nonlinear weighted combination method based on PSO-DBN to construct a hybrid model for short-term wind power forecasting. To verify the performance of the developed forecasting model, wind speed data of 10 min from a wind farm in Shaanxi Dingbian, China are selected as case studies. The results show that the proposed method in this paper is more effective than other existing methods.
Chloride-induced corrosion of reinforcement has endangered the safety of reinforced concrete (RC) structures. It is, therefore, necessary to strengthen the corroded RC members to ensure structural ...safety. This study aims to investigate the effectiveness of alkali-activated slag (AAS) ferrocement jackets in strengthening corroded RC columns. AAS ferrocement specimens with various layers of stainless steel wire mesh (SSWM) were subjected to direct tensile tests. Square RC columns suffered artificially accelerated corrosion and were subsequently strengthened by AAS ferrocement jackets. Axial compressive tests were conducted on the column specimens. Experimental results have shown that corroded specimens suffer severe losses in loading capacity up to 46% as compared with the control one. Volume fraction of transverse SSWM (ρv) plays primary role in loading capacity and ductility of ferrocement and its confinement on column specimens. Ferrocement with ρv of 0.266% can rehabilitate loading capacity of specimens with corrosion degrees of 8.9% and 18.3% by 37% and 46%, respectively. Corroded specimen strengthened by ferrocement with ρv of 0.532% achieves approximately two times the ductility than the one without strengthening. Ferrocement jackets provide better and uniform confinement to core concrete than new stirrups. Analytical models are proposed to predict tensile strength of AAS ferrocement and loading capacity of specimens strengthened by ferrocement jackets. The prediction is in good agreement with experimental results.
MicroRNAs (miRNAs) and Twist1-induced epithelial-mesenchymal transition (EMT) in cancer cell dissemination are well established, but the involvement of long noncoding RNAs (lncRNAs) in ...Twist1-mediated signaling remains largely unknown.
RT-qPCR and western blotting were conducted to detect the expression levels of lncRNA JPX and Twist1 in lung cancer cell lines and tissues. The impact of JPX on Twist1 expression, cell growth, invasion, apoptosis, and in vivo tumor growth were investigated in lung cancer cells by western blotting, rescue experiments, colony formation assay, flow cytometry, and xenograft animal experiment.
We observed that lncRNA JPX was upregulated in lung cancer metastatic tissues and was closely correlated with tumor size and an advanced stage. Functionally, JPX promoted lung cancer cell proliferation in vitro and facilitated lung tumor growth in vivo. Additionally, JPX upregulated Twist1 by competitively sponging miR-33a-5p and subsequently induced EMT and lung cancer cell invasion. Interestingly, JPX and Twist1 were coordinately upregulated in lung cancer tissues and cells. Mechanically, the JPX/miR-33a-5p/Twist1 axis participated in EMT progression by activating Wnt/β-catenin signaling.
These findings suggest that lncRNA JPX, a mediator of Twist1 signaling, could predispose lung cancer cells to metastasis and may serve as a potential target for targeted therapy.
‘Benggang’ is a local term for a widespread type of severgully erosion with steep collapsing walls in granitic, low, hilly areas of southern China, and its development and expansion are closely ...related to the shear strength of the collapsing wall. Plant roots play an important role in improving soil shear strength. However, the shear strength of root‐soil complexes in different layers of collapsing walls remains obscure. We selected Dicranopteris linearis fern roots and adopted the direct shear method to evaluate the effect of root weight density (RWD) (0–1.25 g 100 cm−3) on the shear properties of the lateritic, sandy and detritus layers. The results showed that roots could enhance soil shear strength, and the maximum increase in the lateritic layer was 11.53%, higher than that in the sandy (5.84%) and detritus layers (3.17%). As the root content increased, the cohesion of the sandy and detritus layers increased and then decreased, and their maximum increase in cohesion and the fitting optimal RWD were lower than those of the lateritic layer. The internal friction angle was not affected by roots. When the root content was constant, the shear strength and cohesion of the lateritic layer were significantly higher than those of the sandy and detritus layers, while their internal friction angle was significantly lower than that of the latter two layers. The average increment of soil cohesion calculated by the Wu‐Waldron model (WWM) was 10.52 kPa, which was 0.30, 3.75 and 19.38 times the measured average values of the lateritic, sandy and detritus layers, respectively. The correction coefficient k′ was 0.02–1.18, and the k'¯$$ \overline{k\hbox{'}} $$ in the lateritic layer was the highest (0.82), followed by that in the sandy and detritus layers. By combining the modified WWM with Coulomb's formula, new shear strength equations for root‐soil complexes of D. linearis were established. The predicted shear strength compared well with the measured shear strength (R2 > 0.90, NSE >0.90). Overall, the roots only had a significant reinforcement effect on the lateritic layer, and they could still not change the mechanical properties of the collapsing wall, which were more stable in the upper layers and weaker in the bottom. Therefore, other measures should be taken in the bottom layers to improve the stability of Benggangs.
Highlights
Effect of D. linearis roots on the shear strength of collapsing walls in Benggang was studied.
Roots could improve collapsing‐wall soil shear strength, mainly reflected in the cohesion.
The roots enhancement effect in lateritic layer was better than that of sandy and detritus layers.
New shear strength equations of root‐soil complexes were established based on the Wu‐Waldron model.
Exosomes are microvesicles secreted by cells. They contain a variety of bioactive substances with important roles in intercellular communication. Circular RNA (circRNA), a type of nucleic acid ...molecule found in exosomes, forms a covalently bonded closed loop without 5' caps or 3' poly(A) tails. It is structurally stable, widely distributed, and tissue specific. CircRNAs mainly act as microRNA sponges and have important regulatory roles in gene expression; they are superior to other non-coding RNAs as molecular diagnostic markers and drug treatment targets. Exosomal-derived circRNAs in the body fluids of tumor patients can modulate tumor proliferation, invasion, metastasis, and drug resistance. They can be used as effective biomarkers for early non-invasive diagnosis and prognostic evaluation of tumors, and also represent ideal targets for early precision therapeutic intervention. This review provides a theoretical basis for exploring the applications of exosomal circRNAs in malignant tumor diagnosis and treatment. We describe the biological functions of exosomal circRNAs in the occurrence and development of malignant tumors, their potential utility in diagnosis and treatment, and possible mechanisms.
As social and environmental issues become increasingly serious, both fuel costs and environmental impacts should be considered in the cogeneration process. In recent years, combined heat and power ...economic emission dispatch (CHPEED) has become a crucial optimization problem in power system management. In this paper, a novel reinforcement-learning-based multi-objective differential evolution (RLMODE) algorithm is suggested to deal with the CHPEED problem considering large-scale systems. In RLMODE, a Q-learning-based technique is adopted to automatically adjust the control parameters of the multi-objective algorithm. Specifically, the Pareto domination relationship between the offspring solution and the parent solution is used to determine the action reward, and the most-suitable algorithm parameter values for the environment model are adjusted through the Q-learning process. The proposed RLMODE was applied to solve four CHPEED problems: 5, 7, 100, and 140 generating units. The simulation results showed that, compared with four well-established multi-objective algorithms, the RLMODE algorithm achieved the smallest cost and smallest emission values for all four CHPEED problems. In addition, the RLMODE algorithm acquired better Pareto-optimal frontiers in terms of convergence and diversity. The superiority of RLMODE was particularly significant for two large-scale CHPEED problems.
Hemophilia A(HA) is an X-linked recessive bleeding disorder caused by mutations in coagulation factor VIII. Nowadays, exogenous coagulation factor replacement therapy is the main treatment. With the ...continuous development of gene therapy, new research directions have been provided for the treatment of hemophilia A. CRISPR-Cas9 technology was applied to select suitable target sites, and mediate the targeted knock-in and efficient expression of exogenous B-domain-deleted FⅧ variant gene through corresponding vectors for the treatment of hemophilia A.CRISPR-Cas9 technology is an emerging gene editing tool with great efficiency, safety and effectiveness, and has been widely used in hemophilia gene therapy research. This paper reviews the vector selection, construction of therapeutic genes, gene editing technology and selection of expression target sites for hemophilia A gene therapy at this stage.
In recent years, convolutional neural network (CNN)-based spatiotemporal fusion (STF) models for remote sensing images have made significant progress. However, existing STF models may suffer from two ...main drawbacks. Firstly, multi-band prediction often generates a hybrid feature representation that includes information from all bands. This blending of features can lead to the loss or blurring of high-frequency details, making it challenging to reconstruct multi-spectral remote sensing images with significant spectral differences between bands. Another challenge in many STF models is the limited preservation of spectral information during 2D convolution operations. Combining all input channels’ convolution results into a single-channel output feature map can lead to the degradation of spectral dimension information. To address these issues and to strike a balance between avoiding hybrid features and fully utilizing spectral information, we propose a remote sensing image STF model that combines single-band and multi-band prediction (SMSTFM). The SMSTFM initially performs single-band prediction, generating separate predicted images for each band, which are then stacked together to form a preliminary fused image. Subsequently, the multi-band prediction module leverages the spectral dimension information of the input images to further enhance the preliminary predictions. We employ the modern ConvNeXt convolutional module as the primary feature extraction component. During the multi-band prediction phase, we enhance the spatial and channel information captures by replacing the 2D convolutions within ConvNeXt with 3D convolutions. In the experimental section, we evaluate our proposed algorithm on two public datasets with 16x resolution differences and one dataset with a 3x resolution difference. The results demonstrate that our SMSTFM achieves state-of-the-art performance on these datasets and is proven effective and reasonable through ablation studies.
Biodiversity plays a fundamental role in provisioning and regulating forest ecosystem functions and services. Above‐ground (plants) and below‐ground (soil microbes) biodiversity could have ...asynchronous change paces to human‐driven land‐use impacts. Yet, we know very little how they affect the provision of multiple forest functions related to carbon accumulation, water retention capacity and nutrient cycling simultaneously (i.e. ecosystem multifunctionality; EMF). We used a dataset of 22,000 temperate forest trees from 260 plots within 11 permanent forest sites in Northeastern China, which are recovering from three post‐logging disturbances. We assessed the direct and mediating effects of multiple attributes of plant biodiversity (taxonomic, phylogenetic, functional and stand structure) and soil biodiversity (bacteria and fungi) on EMF under the three disturbance levels. We found the highest EMF in highly disturbed rather than undisturbed mature forests. Plant taxonomic, phylogenetic, functional and stand structural diversity had both positive and negative effects on EMF, depending on how the EMF index was quantified, whereas soil microbial diversity exhibited a consistent positive impact. Biodiversity indices explained on average 45% (26%–58%) of the variation in EMF, whereas climate and disturbance together explained on average 7% (0.4%–15%). Our result highlighted that the tremendous effect of biodiversity on EMF, largely overpassing those of both climate and disturbance. While above‐ (β = 0.02–0.19) and below‐ground (β = 0.16–0.26) biodiversity had direct positive effects on EMF, their opposite mediating effects (β = −0.22 vs. β = 0.35 respectively) played as divergent pathways to human disturbance impacts on EMF. Our study sheds light on the need for integrative frameworks simultaneously considering above‐ and below‐ground attributes to grasp the global picture of biodiversity effects on ecosystem functioning and services. Suitable management interventions could maintain both plant and soil microbial biodiversity, and thus guarantee a long‐term functioning and provisioning of ecosystem services in an increasing disturbance frequency world.
Higher EMF was found in disturbed forests rather than relatively undisturbed mature forests. Above‐and below‐ground biodiversity had direct positive effects on EMF, their opposite mediating effects played as divergent pathways to human disturbance impacts on EMF.
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