DeepDualEnhancer: A Dual-Feature Input DNABert Based Deep Learning Method for Enhancer Recognition.

Enhancers are cis-regulatory DNA sequences that are widely distributed throughout the genome. They can precisely regulate the expression of target genes. Since the features of enhancer segments are difficult to detect, we propose DeepDualEnhancer, a DNABert-based method using a multi-scale convolutional neural network, BiLSTM, for enhancer identification.

CC4S: Encouraging Certainty and Consistency in Scribble-Supervised Semantic Segmentation.

Deep learning-based solutions have achieved impressive performance in semantic segmentation but often require large amounts of training data with fine-grained annotations. To alleviate such requisition, a variety of weakly supervised annotation strategies have been proposed, among which scribble supervision is emerging as a popular one due to its user-friendly annotation way. However, the sparsity and diversity of scribble annotations make it nontrivial to train a network to produce deterministic and consistent predictions directly.

Revealing the closed pore formation of waste wood-derived hard carbon for advanced sodium-ion battery.

Although the closed pore structure plays a key role in contributing low-voltage plateau capacity of hard carbon anode for sodium-ion batteries, the formation mechanism of closed pores is still under debate. Here, we employ waste wood-derived hard carbon as a template to systematically establish the formation mechanisms of closed pores and their effect on sodium storage performance. We find that the high crystallinity cellulose in nature wood decomposes to long-range carbon layers as the wall of closed pore, and the amorphous component can hinder the graphitization of carbon layer and induce the crispation of long-range carbon layers.

Improved Antibacterial Properties of Polylactic Acid-Based Nanofibers Loaded with ZnO-Ag Nanoparticles through Pore Engineering.

In the post-epidemic era, bio-based protective fiber materials with active protective functions are of utmost importance, not only to combat the spread of pathogens but also to reduce the environmental impact of petroleum-based protective materials. Here, efficient antibacterial polylactic acid-based (PLA-based) fibers are prepared by solution blow spinning and their pore structures are regulated by controlling the ratio of the solvent components in the spinning solutions. The porous PLA-based fibers exhibit antibacterial efficiencies of over 99% against and over 98% against , which are significantly higher than that of the nonporous PLA-based fibers.

Designing highly efficient 3D porous Ni-Fe sulfide nanosheets based catalyst for the overall water splitting through component regulation.

Constructing efficient and stable bifunctional catalysts is essential to improve the conversion efficiency of overall water splitting (OWS). In this work, 3D porous Ni-Fe sulfide nanosheets supported on nickel foam (Ni-Fe-S/NF) were synthesized by a facile hydrothermal method. The optimized NiS-FeS/NF-2 electrode realized ultra-high efficiency for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER).

Toward a High-Energy-Density Cathode with Enhanced Temperature Adaptability for Sodium-Ion Batteries: A Case Study of NaMnZr(PO) Microspheres with Embedded Dual-Carbon Networks.

Polyanionic cathode materials that have high energy density and good temperature adaptability are in high demand for practical applications in sodium-ion batteries (SIBs). In this study, a scalable spray-drying strategy has been proposed to construct interconnected conductive networks composed of amorphous carbon and reduced graphene oxide in NaMnZr(PO) microspheres (NMZP@C-rGO). The dual-carbon conductive networks provide fast electron migration pathways in the microspheres.

Ultrastrong low-carbon nanosteel produced by heterostructure and interstitial mediated warm rolling.

Ultrastrong materials can notably help with improving the energy efficiency of transportation vehicles by reducing their weight. Grain refinement by severe plastic deformation is, so far, the most effective approach to produce bulk strong nanostructured metals, but its scaling up for industrial production has been a challenge. Here, we report an ultrastrong (2.

Super Diffusion for Salient Object Detection.

One major branch of saliency object detection methods are diffusion-based which construct a graph model on a given image and diffuse seed saliency values to the whole graph by a diffusion matrix. While their performance is sensitive to specific feature spaces and scales used for the diffusion matrix definition, little work has been published to systematically promote the robustness and accuracy of salient object detection under the generic mechanism of diffusion. In this work, we firstly present a novel view of the working mechanism of the diffusion process based on mathematical analysis, which reveals that the diffusion process is actually computing the similarity of nodes with respect to the seeds based on diffusion maps.

Microstructure and Mechanical Properties of a Cold-Rolled Ultrafine-Grained Dual-Phase Steel.

A new processing route to produce Ultrafine-Grained Dual-Phase steel has been proposed, involving cold-rolling and subsequent intercritical annealing of a fibrous ferrite⁻martensite starting structure. Ultrafine-grained DP (UFG-DP) steel with an average ferrite grain size of about ~2.7 μm and an average martensite island size of ~2.