[Objective] To understand the relationship between species diversity and tree growth in natural secondary forests in Northeast China, to determine the reasonable size of species diversity, and to carry out appropriate nurturing harvesting and artificial replanting, so as to provide a scientific and theoretical basis for secondary forest management and management. [Methods] A total of 123 sample plots were set up in the Xiaoxinganling (XXAL), Zhangguangcailing (ZGCL), Laojialing (LYL), Changbai Mountain (CBS), Hadaling (HDL) and Longgang Mountain (LGS) areas in Northeast China, they were used to investigate the species composition, importance value, diversity and tree growth in each area. [Results] A total of 48 species belonging to 17 families and 31 genera were investigated in all the sample plots, among which the sample plots in Longgang Mountain contained the largest number of families, genera and species, followed by Hada Ling, Changbai Mountain, Laoyaling, Zhangguangcai Mountain and Xiaoxinganling. The α-diversity index of species in the sample sites was the largest in Changbai Mountain and the smallest in Xiaoxinganling, and the difference between them was significant (P < 0.05), while the richness index was the largest in Longgang Mountain and the smallest in Xiaoxinganling. The difference between them was significant (P < 0.05), while the greater the difference in latitude between the regions, the more obvious the difference in β-diversity index of species in the sample sites, and the fewer species shared between the two regions. The higher the rate of community succession, the higher the average diameter at breast height and the average tree height in each region were CBS > LYL > LGS > ZGCL > HDL > XXAL. The largest breast tree species in each region was Mongolian oak in Changbai Mountain with a diameter at breast height of 64.8 cm, and the smallest breast tree species in each region was Tyrannus sylvestris in Longgang Mountain with a diameter at breast height of 4.0 cm. The highest tree species in each region was Liriodendron sylvestris in Longgang Mountain with a height of 28.9 m, and the smallest species is yellow pineapple with a height of 1.3 m in Longgang Mountain. [Conclusion] Within a certain range, species diversity has a facilitating effect on the average diameter at breast height and average tree height of species within a stand. Therefore, during the management of secondary forests, appropriate nurturing harvesting and artificial replanting should be adopted to ensure reasonable species diversity in the stands and provide optimal space for the growth of natural secondary forests.

Nanoparticle drug delivery systems are engineered technologies that use nanoparticles for the targeted delivery and controlled release of therapeutic agents. Cisplatin-loaded nanoparticle formulations were optimized utilizing response surface methods and the central composite rotating design model. This study employed a central composite rotatable design with a three-factored factorial design with three tiers. Three independent variables namely drug polymer ratio, aqueous organic phase ration, and stabilizer concentration were used to examine the particle size, entrapment efficiency, and drug loading of cisplatin PLGA nanoparticles as responses. The results revealed that this response surface approach might be able to be used to find the best formulation for the cisplatin PLGA nanoparticles. A polymer ratio of 1:8.27, organic phase ratio of 1:6, and stabilizer concentration of 0.15 were found to be optimum for cisplatin PLGA nanoparticles. Nanoparticles made under the optimal conditions found yielded a 112 nm particle size and a 95.4 percent entrapment efficiency, as well as a drug loading of 9 percent. The cisplatin PLGA nanoparticles tailored for scanning electon microscopy displayed a spherical form. A series of in vitro tests showed that the nanoparticle delivered cisplatin progressively over time. According to this work, the Response Surface Methodology (RSM) employing the central composite rotatable design may be successfully used to simulate cisplatin-PLGA nanoparticles.

The purpose of this work is to present the model of a Parabolic Trough Solar Collector (PTC) using the Finite Element Method to predict the thermal behavior of the working fluid along the collector receiver tube. The thermal efficiency is estimated based on the governing equations involved in the heat transfer processes. To validate the model results, a thermal simulation of the fluid was performed using Solidworks software. The maximum error obtained from the comparison of the modeling with the simulation was 7.6% at a flow rate of 1 L/min. According to the results obtained from the statistical errors, the method can effectively predict the fluid temperature at high flow rates. The developed model can be useful as a design tool, in the optimization of the time spent in the simulations generated by the software and in the minimization of the manufacturing costs related to Parabolic Trough Solar Collectors.

This study aimed to analyze government policies in education during the Covid-19 pandemic and how teachers exercised discretion in dealing with limitations in policy implementation. This research work used the desk review method to obtain data on government policies in the field of education during the Covid-19 pandemic. In addition, interviews were conducted to determine the discretion taken in implementing the learning-from-home policy. There were three learning models during the pandemic: face-to-face learning in turns (shifts), online learning, and home visits. Online learning policies did not work well at the pandemic’s beginning due to limited infrastructure and human resources. To overcome various limitations, the government provided internet quota assistance and curriculum adjustments and improved online learning infrastructure. The discretion taken by the teachers in implementing the learning-from-home policy was very dependent on the student’s condition and the availability of the internet network. The practical implication of this research is that street-level bureaucrats need to pay attention to discretionary standards when deciding to provide satisfaction to the people they serve.

Developing countries have witnessed a rise in infrastructure spending over the past decades; however, infrastructure spending in most developed countries, particularly the US, continues to decline. As a result, in 2021, the US Congress passed a Bipartisan Infrastructure Bill, which invests $1 trillion in the country’s infrastructure every year. Using the principal component analysis and VAR estimation, we analyzed the impact of infrastructure (transportation and water, railway networks, aviation, energy, and fixed telephone lines) on economic growth in the US. Our findings show that infrastructure spending positively and significantly impacted economic growth. Additionally, the impulse response analysis shows that shocks to infrastructure spending had positive and persistent effects on economic growth. Our results suggest that infrastructure investment spurs economic growth. Based on our findings, sustained public spending on transport and water, railway networks, aviation, energy, and fixed telephone lines infrastructure by the US government will positively impact economic growth in the country. The study also suggests that policies that promote infrastructure spending, such as the Bipartisan Infrastructure Law (Infrastructure Investment and Jobs Act) passed by the US Congress, should be enhanced to boost economic growth in the US.