Efficient Green Quasi-Two-Dimensional Perovskite Light-Emitting Diodes Based on Mix-Interlayer

Recently, quasi-two-dimensional (Q-2D) perovskites have received much attention due to their excellent photophysical properties. Phase compositions in Q-2D perovskites have obvious effect on the device performance. Here, efficient green perovskite light-emitting diodes (PeLEDs) were fabricated by employing o-fluorophenylethylammonium bromide (o-F-PEABr) and 2-aminoethanol hydrobromide (EOABr) as the mix-interlayer ligands. Phase compositions are rationally optimized through composition and interlayer engineering. Meanwhile, non-radiative recombination is greatly suppressed by the introduction of mix-interlayer ligands. Thus, green PeLEDs with a peak photoluminescence quantum yield (PLQY) of 81.4%, a narrow full width at half maximum (FWHM) of 19 nm, a maximum current efficiency (CE) of 27.7 cd/A, and a maximum external quantum efficiency (EQE) of 10.4% were realized. The results are expected to offer a feasible method to realize high-efficiency PeLEDs.

SYNTHESIS OF ACTIVATED CARBON AND CMC BEADS FROM CORN HUSK FOR EFFLUENT TREATMENT

Adsorption of dyes from the effluent is a well-known and feasible method been used in the industry. In the present work we are using corn husk agricultural waste as a sustainable raw material for synthesizing activated carbon using biopolymer carboxyl methyl cellulose for formation of beads. The beads formed are been used for removal of reactive ultra-orange RGB , acid telon yellow FG 01, basic coracryl red C2B. The surface area of beads is 39.87m2 /g. The maximum adsorption of reactive orange RGB , acid telon yellow and basic coracryl red is 68.25mg/g, 72.54mg/g and 30.21mg/g for 50ml of dye solution. The stock solution 0.4g/l of dye solution was prepared for each dye respectively. The beads formed shows a variable pH from 2 to 12 which is favourable for textile effluent. This is a green approach to use the agricultural waste for waste water treatment.

Study on the Release of Muscle Passive Force by Ultrasonic Mechanical Effect and its Related Mechanism

Background: Excessive muscle force impedes physical movement and relaxing passive muscle force substantially improves movement impairment. Ultrasound is an energy carrier with the characteristics of repetitive mechanical stimulation, which may be a feasible method to relieve muscle tension.Methods: We performed stress relaxation experiments on soleus muscle and combine the obtained results with the standard linear solid model to extract information of viscoelastic effect of ultrasound on muscle, and calculated muscle fibril content by histological analysis.Results: Ultrasound can accelerate muscle stress relaxation; the viscosity and elasticity coefficient of the ultrasound group was higher than that of the control group, and there was no significant difference between the three ultrasound intensities; H&E staining showed that muscle fibrillar content decreased and the matrix substance increased.Conclusion: We considered that ultrasound can change the microstructure of muscle, and the matrix substance plays a significant role in the relaxation process. In this paper, the relationship between muscle viscoelasticity and passive muscle force is obtained. The results provide an important theoretical basis and a feasible method for monitoring muscle functional characteristics by measuring muscle viscoelasticity.

Research on Recognition of Faces with Masks Based on Improved Neural Network

Background. At present, the new crown virus is spreading around the world, causing all people in the world to wear masks to prevent the spread of the virus. Problem. People with masks have found a lot of trouble for face recognition. Finding a feasible method to recognize faces wearing masks is a problem that needs to be solved urgently. Method. This paper proposes a mask recognition algorithm based on improved YOLO-V4 neural network and the integrated SE-Net and DenseNet network and introduces deformable convolution. Conclusion. Compared with other target detection networks, the improved YOLO-V4 neural network used in this paper improves the accuracy of face recognition and detection with masks to a certain extent.

Licorice Germplasm Resources Identification Using DNA Barcodes Inner-Variants

Based on the gradual transformation from wild growth to artificial cultivation, the accurate authentication of licorice seeds contributes to the first committed step of its quality control and is pivotal to ensure the clinical efficacy of licorice. However, it is still challenging to obtain genetically stable licorice germplasm resources due to the multi-source, multi-heterozygous, polyploid, and hybrid characteristics of licorice seeds. Here, a new method for determining the heterozygosity of licorice seed mixture, based on the various sites, and finding the composition characteristics of licorice seed is preliminarily designed and proposed. Namely, high-throughput full-length multiple DNA barcodes(HFMD), based on ITS multi-copy variation exist, the full-length amplicons of ITS2, psbA-trnH and ITS are directly sequenced by rDNA through the next-generation sequence(NGS) and single-molecule real-time (SMRT) technologies. By comparing the three sequencing methods, our results proved that SMRT sequencing successfully identified the complete gradients of complex mixed samples with the best performance. Meanwhile, HFMD is a brilliant and feasible method for evaluating the heterozygosity of licorice seeds. It shows a perfect interpretation of DNA barcoding and can be applied in multi-base multi-heterozygous and polyploid species.

Human Fecal Contamination Corresponds to Changes in the Freshwater Bacterial Communities of a Large River Basin

Surface waters in highly developed mixed-use watersheds are frequently impacted by a wide variety of pollutants, leading to a range of impairments that must be monitored and remediated. With advancing technologies, microbial community sequencing may soon become a feasible method for routine evaluation of the ecological quality and human health risk of a water body.

Isolation and identification of exosomes from feline plasma, urine and adipose-derived mesenchymal stem cells

Background Exosomes, internal proteins, lipids, and nucleic acids coated by phospholipid bilayer membranes, are one type of small extracellular vesicles, which can mediate cell-cell communication. In recent years, exosomes have gained considerable scientific interest due to their widely applied prospect in the diagnosis and therapeutics of human and animal diseases. In this study, we describe for the first time a feasible method designed to isolate and characterize exosomes from feline plasma, urine and adipose-derived mesenchymal stem cells. Results Exosomes from feline plasma, urine and adipose-derived mesenchymal stem cells were successfully isolated by differential centrifugation. Quantification and sizing of exosomes were assessed by transmission electron microscopy, flow nano analysis and western blotting. Detected particles showed the normal size (30–100 nm) and morphology described for exosomes, as well as presence of the transmembrane protein (TSG101, CD9, CD63, and CD81) known as exosomal marker. Conclusions The results suggest that differential centrifugation is a feasible method for isolation of exosomes from different types of feline samples. Moreover, these exosomes can be used to further diagnosis and therapeutics in veterinary pre-clinical and clinical studies.