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Due to the poor underground environment, which makes the images of underground video in coal mines seriously degraded. However, the existing semantic segmentation model based on deep learning has the problem of fuzzy edge segmentation after image sharpness. A new method is proposed, which uses the fusion edge optimization module to process the boundary information and uses the gated convolution layer to connect the traditional feature extraction module to process the information in parallel. In order to supervise the learning of contour information, the binary cross entropy loss function was used to improve the learning effect, and the segmentation effect was optimized together with the loss function of conventional branches. The experimental results show that compared with other methods, the method based on the fusion edge optimization module improves the overall semantic segmentation accuracy and edge segmentation accuracy when the semantic segmentation task of the clarified coal mine image is performed.

Lithium–sulfur (Li–S) batteries have received continuous attention due to their high theoretical specific capacity. However, the shuttle effect of lithium polysulfides (LiPSs) severely limits its development. Modification of commercial polypropylene (PP) separators is regarded as an effective strategy to suppress the shuttle effect. In this paper, NiFe-PBA-derived carbon-based porous bimetallic phosphide (NFP) was inserted into the carbon nanotube (CNT) networks, and these composites were utilized to modify the PP separator. CNT networks provide abundant pathways of electron transport to improve the conductivity of S cathode and Li2S. Ni2P and Fe2P in NFP exhibit robust chemisorption and catalytic effects on LiPSs. Moreover, porous structures and networks were beneficial for Li+ immigration. The synergistic effects of NFP and CNT networks enable the modified separator to obtain a high electrical conductivity, superior adsorption capability, and enhanced catalytic performance. Assembled Li–S batteries show a high initial discharge specific capacity of 1244 mAh g–1 at 0.2 C. Notably, the highest discharge-specific capacity reached up to 938.9 mAh g–1 at 1 C, and the average capacity decay rate per cycle after 300 cycles was a mere 0.067%. This study paves the way for a robust research pathway in harnessing transition metal phosphides and carbon materials for modified separators, offering an effective strategy to realize high-performance Li–S batteries. [ABSTRACT FROM AUTHOR]

Am J Physiol Renal Physiol 298: F209-F215, 2010. First published October 14, 2009; doi: 10.1152/ajprenal.00451.2009.--Episodes of acute renal failure (ARF) are not always fully reversible and may lead to chronic disease, due in part to an inadequate regenerative response. The Notch signaling pathway is involved in determining cell fate during development, and tissue maintenance and repair in adult organs. The purpose of this study was to examine the role of the Notch pathway in renal regeneration following ARF. Kidney injury, induced by ischemia-reperfusion, resulted in early activation of the Notch pathway, as evidenced by increased expression of Notch1 and Notch2 intracellular domain (cleaved Notch). The effect of exogenous administration of the Notch ligand Delta-like-4 (DLL4) on recovery from ARF was then studied. Rats were pretreated by intraperitoneal injection of DLL4 or vehicle control. Two days following the last DLL4 dose, ARF was induced by bilateral renal artery clamping for 45 min followed by reperfusion. The severity of renal injury was similar in DLL4 and control rats. Renal recovery was facilitated by DLL4 treatment, as evidenced by faster return of serum creatinine to baseline by 48 h in DLL4-treated rats as against 5 days in vehicle-treated control rats. Cell proliferation was higher in the DLL4-treated group. In conclusion, activation of the Notch pathway occurs following ARF. Pretreatment with the Notch ligand DLL4 enhanced recovery from ARF and represents a potential novel therapeutic option for regenerating the injured kidney. Delta-like-4; acute kidney injury; cellular proliferation; ischemia-reperfusion

A competitive electrochemiluminescence immunoassay was established based on the isoluminol-H2O2 (ABEI-H2O2) system catalyzed by cobalt hydroxide (Co(OH)2) to detect florfenicol residues in food. First , ultra-thin two-dimensional Co(OH)2 nanosheets were used as the catalyst of ABEI-H2O2 system, and excellent catalytic effects were acquired by catalytic decomposition of hydrogen peroxide with cobalt ions. Then, bimetal PdAg (Pd/Ag) alloy nanoparticles were used as a bridge to connect ABEI and antibody due to their good biocompatibility; Pd/Ag alloy nanoparticles also had a catalytic effect to further amplify the ECL signal in the system due to the synergistic catalytic effect of the bimetal. A competitive immunoassay strategy was used to detect florfenicol, where the florfenicol in the sample will compete with the antibody for the limited binding sites on the coating antigen. The ECL immunosensor for florfenicol detection shows high sensitivity, with a linear range from 10−4 to 102 ng mL−1, and a detection limit of 3.1 × 10−5 ng mL−1, where the scan potential was varied from 0 to 0.6 V vs Ag/AgCl. This work was the first to use Co(OH)2 nanosheets and bimetal PdAg catalytic signal amplification methods to design the sensor, which provides a novel, convenient and reliable strategy for ultra-sensitive detection of florfenicol, and other biological small molecules. A novel ECL immunosensor based on ABEI-H2O22 [ABSTRACT FROM AUTHOR]