The performance of carbon-based materials as negative electrodes for supercapacitors can be effectively enhanced through the method like increasing the surface area and active sites as well as ...heteroatoms doping, while the limited capacitance caused by the surface adsorption mechanism restricts the further improvement of capacitance. Herein, we design hollow and porous FeP spheres (H-FeP) in-situ encapsulated into 3D honeycomb-like porous graphitic N, P-codoping carbon (PGNPC) by a unique post-annealing strategy. The post-annealing process acts as an efficient modification strategy in two aspects: the formation of a porous graphitic carbon framework during the catalytic reaction between iron oxide with carbon and the morphology changing from solid to hollow by introducing the Kirkendall diffusion process. With the synergetic effect of introducing hollow FeP into carbon, the N, P-codoping and 3D porous graphitic carbon framework ensure the as-prepared materials with enhanced performance for negative electrodes. Thus, H-FeP@PGNPC materials display outstanding specific capacitance (696 F g−1), high rate capacity and cycling stability. Using multi-shelled Mn3O4 encapsulated in rGO as the positive electrode, the assembled asymmetric supercapacitor exhibits high specific capacitance and energy density with negligible capacity loss (retain 90% after 5000 cycles).
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•Novel in-situ encapsulated hollow FeP into N,P-codoped porous graphenic framework obtained through a high-yield process.•The catalytic reaction caused by the post-annealing process provides extra pseudocapacitive contributions.•The porosity and hollow structure of FeP manipulated by Kirkendall effect.•Porous graphenic framework simultaneously acts as the buffer layer and expressway for electrons transport.
Purpose
When blended, animal and plant proteins can complement each other in terms of amino acid composition and release time. In this study, we investigated whether the blended protein diet has a ...better feeding effect than the single protein diet, and to reveal the differences in growth and intestinal microbiota composition caused by the blended protein diet.
Methods
Forty Sprague Dawley (SD) rats received diets with different protein sources, including casein (C), whey protein (WP), black soybean protein (BSP), and black soybean-whey blended protein (BS-WP), for eight weeks. To investigate the effects of blended protein supplement on gut microbiota and metabolites, we performed a high throughput 16S rDNA sequencing and fecal metabolomics profiling. In addition, we determined growth and serum biochemical indices, and conducted intestinal morphology analyses.
Results
Compared to those in the BSP and WP groups, the daily body weight gain and feed conversion efficiency increased in the BS-WP group. Serum biochemical indices indicated that the protein utilization efficiency of the WP and BS-WP groups was relatively high, and the BS-WP blended protein diet improved the protein adoption rate. The BS-WP blended protein diet also improved intestinal tissue morphology and promoted intestinal villi development compared to the single protein diets. Furthermore, dietary protein altered the composition of gut microbiota, the gut microbial diversity of rats fed with the BS-WP diet was significantly (
P
< 0.05) higher than that of the other groups. The difference in dietary protein corresponded with an alteration of fecal amino acids and their metabolites, and tryptophan and tyrosine metabolism were the key mechanisms leading to the changes in fecal microbial composition.
Conclusion
Dietary protein sources played an important role in the growth and development of rats by influencing intestinal metabolism and microbial composition. The BS-WP blended protein diet was more conducive to nutrient absorption than the single protein diet. Furthermore, blended protein increased the diversity of intestinal microbes and aided the establishment of intestinal barrier function.
Most parents consider private supplementary tutoring (PT) as an effective means of improving academic achievement. However, previous studies on this method have produced either partial or ...inconclusive results on its effectiveness. Thus, in the present study we conducted a comprehensive analysis of the learning of middle school students in China, with specific focus on the final year of middle school. The analysis was based on a specially designed longitudinal survey of private supplementary tutoring in mathematics. An analysis using hierarchical linear regression showed that regular private tutoring, throughout the school years, could have a minor effect on students’ mathematical achievements by the final year of middle school. These results suggest that parents should make careful choices for their children’s private tutoring, and the government must issue comprehensive, professional guidelines to regulate the private tutoring industry. Moreover, other countries could find major take-aways from the Chinese experience of private tutoring for enhancing students’ mathematical performances.
Unmanned aerial vehicles (UAVs) are widely used in power transmission line inspection nowadays and they need to navigate automatically by recognizing the category and accurate position of ...transmission pylon equipment in line inspection. Semantic segmentation is an effective method for recognizing transmission pylon equipment. In this paper, a semantic segmentation algorithm that fuses infrared and natural light images is proposed. A cross-modal attention interaction activation mechanism is adopted to fully exploit the complementation between natural light and infrared images. Firstly, a global information block with a feature pyramid structure is used to deeply mine and fuse multi-scale global contextual information of fused features, and then the block is used to conduct feature aggregation in the decoding processing, and enough aggregation with multi-scale features of infrared and natural light images is used to enhance the expression ability of the model and improve the accuracy of semantic segmentation of transmission pylon equipment in complex scenes. Our method guides the process of low-level up-sampling and restoration by denser global and high-level features. Experimental results on a dataset of transmission pylon equipment collected by us show that the proposed method achieved better semantic segmentation results than the state-of-the-art methods.
Summary
Sorghum germplasm resources were abundant, and their comprehensive utilisation was also more in‐depth. Starch had attracted much attention as the main component in grain, but starch ...retrogradation limited its better development and utilisation. Therefore, the property changes of sorghum starch retrogradation were studied. The differences in the properties of the four kinds of sorghum starches during retrogradation were mainly due to composition and structure among the varieties. With the increase in retrogradation days, the order of L1 starch was better at 0.994, the retrogradation rate of L13 starch increased by 36.23%, and the recrystallisation degree of H5 starch was 0.064 worse than that of native starch. However, the physicochemical properties of H1 retrograded starch were different from those of the other three. It was shown that the solubility increased to 47.67%, the transparency was 43.36%, and the water‐holding capacity was 91.35%. Retrogradation made that the surface of sorghum starch gel fragments had an orderly scale‐like structure, which did not cause the generation of new groups, reduced the crystalline strength and the energy required for gelatinisation. The crystallisation rate was positively correlated with syneresis, swelling and orderliness, as well as T0, Tp, Tc and ΔH, and negatively correlated with water‐holding capacity.
In this work, we used scanning electron microscopy, fourier transform infrared and differential scanning calorimetry to analyze the retrogradation differences of four kinds of sorghum starch after gelatinization and storage for 28 days.
In this paper, a new similarity model is proposed, which based on rough set to evaluate the similarity degree of the two concepts of concept lattice. The proposed method combines featural and ...structural information into decision and has a higher correlation with human judgement, which can be viewed as the development of Tversky’s similarity model. Compared with other similarity models this approach is convenient to measure the similarity of the concepts of the large contexts, by which we can avoid constructing Hasse diagram and looking through all concepts of the context.
Differential gene expression analysis has the potential to discover candidate biomarkers, therapeutic targets, and gene signatures, which are critical for the prevention and treatment of diseases. ...Survival analyses have been used for differentially expressed genes (DEGs) identification for high-throughput gene datasets, in which genomic features (genes) are associated with survival outcomes, usually survival time of individuals. However, unbalanced samples in rare diseases generally have a high cost on data collection if using a large sample and a low power if using a small sample. How to save money when using an unaffordable sample is a practical question. The case-cohort (CCH) study design can blend the economy of case-control studies with the advantages of cohort studies. But it has not been seen in the medical research literature where high-throughput genomic data were involved. This dissertation developed statistical methods for analyzing the high-throughput gene expression data under the CCH design.It is straightforward to use the hypothesis testing methods such as the Likelihood Ratio test, Wald test, and score test based on the Cox Proportional Hazard (PH) model to identify DEGs associated with survival outcomes given a full cohort (random sample). But in a typical genomic study, thousands of hypothesis tests must be performed simultaneously, and a score test is usually preferred. It does not need to fit the Cox PH model iteratively; hence, it can save computing time and avoid potential convergence issues. Combining the advantage of the CCH study design and score test, we developed a score test under the CCH design to identify DEGs associated with survival outcomes. We provided asymptotic distribution theory and inferential procedures for the test. We also verified the validity of the inferential procedure in finite samples through simulation studies.Another popular approach to DEG identification is the permutation-based score test. It is a non-parametric method, and when it is used for survival outcome related DEG analysis, the strong PH and probability distribution assumptions do not need to be a concern. One advantage of this method is that it estimates the false discovery rate (FDR) directly from the permutation procedure, which takes into account the correlation among the genomic features (genes). However, it cannot be directly applied to the data from a CCH study design because a CCH sample is not a random sample. We developed a procedure to reconstruct a full cohort from a CCH sample and then perform the permutation-based score test on the reconstructed full cohort to identify the DEGs associated with survival outcomes. To illustrate the performance of our proposed method, we evaluated our testing procedures and compared our methods with other existing approaches in terms of the FDR and the power through the simulation study and the application to the real datasets from two cancer-related genomic studies.
Wastewater from olaquindox-producing factories contains high levels of salts and organics. In this study, we investigated the multiple freeze-thaw technology to recover olaquindox from wastewater and ...decrease its chemical oxygen demand (COD) and salinity. Results suggested that under lower ice formation rate, the removal efficiencies of COD, electric conductivity, ammonia nitrogen and total nitrogen could reach 99.4%, 98.2%, 98.7% and 98.5% respectively. Higher ice formation rate, however, promoted wastewater concentration and volume reduction. A liter of wastewater concentrate can recover 11.5 g solid through a simple crystallization step at 4 °C for 12 h. This substance contained mostly olaquindox based on Raman infrared spectroscopy, scanning electron microscopy, and energy dispersive spectrometry. An industrial-scale wastewater treatment process, which the theoretical cost is one seventh that of conventional technologies, was then proposed to recover olaquindox and treat wastewater.
•Olaquindox crystals of 11.5 g/L was recovered from wastewater concentrate.•Low ice formation rate promotes the formation of cleaner ice.•High ice formation rate increases the concentration ratio.•Cost of the treatment strategy is one seventh that of conventional technologies.
