Stimuli-responsive, smart, or intelligent polymers are materials that significantly change their physical or chemical properties when there is a small change in the surrounding environment due to either internal or external stimuli. In the last two decades or so, there has been tremendous growth in the strategies to develop various types of stimuli-responsive polymer (SRP) materials/systems that are suitable for various fields, including biomedical, material science, nanotechnology, biotechnology, surface and colloid sciences, biochemistry, and the environmental field. The wide acceptability of SRPs is due to their availability in different architectural forms such as scaffolds, aggregates, hydrogels, pickering emulsions, core-shell particles, nanogels, micelles, membranes, capsules, and layer-by-layer films. The present review focuses on different types of SRPs, such as physical, chemical, and biological, and various important applications, including controlled drug delivery (CDD), stabilization of colloidal dispersion, diagnostics (sensors and imaging), tissue engineering, regenerative medicines, and actuators. The applications of SRPs have immense potential in various fields, and the author hopes these polymers will add a new field of applications through new concepts.

In order to promote the application of noise map in high-speed railway noise management, the high-speed railway noise map drawing technology based on the combination of noise prediction model and geographic information system (GIS) is studied. Firstly, according to the distribution characteristics of noise sources and line structure characteristics of high-speed railway, the prediction model of multi equivalent sound sources and the calculation method of sound barrier insertion loss of high-speed railway are optimized; secondly, a three-dimensional geographic information model of a high-speed railway is built in GIS software, and the railway noise prediction technology based on the model is developed again; then, the noise of discrete nodes is calculated, and the continuous noise distribution map is drawn by spatial interpolation. The research results show that the comparison error between the noise map of a high-speed railway drawn by this technology and the measured results is less than 1 dB (A), which verifies the accuracy and practicality of the high-speed railway noise map, and can be used as a reference for the railway noise management department to formulate noise control countermeasures.

Financial shocks have an incredible socioeconomic effect on both developed and developing countries. Various recent studies demonstrated that bad public governance impacted public health across all nations. In fact, this study aims to use panel data for 21 countries from the Middle East and North Africa (MENA) region over the period 2000–2020 to scrutinize the effect of both governance and financial crises on public health. We use the generalized method of moments (GMM) approach to carry out the empirical analysis. The objective of using this method is to deal with the issue of endogeneity between exogen variables. Results outline that there is a significant positive association between public governance indicators and public health. Moreover, we found a strong negative association between financial shocks and public health. Thus, the direct negative impact of financial crisis on public health could be mitigated by the indirect positive impacts via institutions and good public governance. This study gives insights to policymakers to take appropriate measures to decrease the severity of the financial shocks and improve healthcare services.

Introduction: Growth, yield and quality of okra (Abelmoschus esculentus (L.) Moench) are related to fertilizer application, being nitrogen (N) the most outstanding, due to its direct relationship with photosynthesis and vegetative growth of the plant. Objective: The objective was to evaluate the agronomic and productivity characteristics of okra as a function of N dose. Materials and methods: The study was conducted at the experimental area of Campus Gurupi, the Universidad Federal de Tocantins (UFT), Brazil, in two planting periods (autumn/winter and spring/summer). The experimental design used was randomized block design (RBD) with six treatments (50, 100, 150, 150, 200 and 250 kg N ha^-1) and four replications. Urea was used as a source of N. The characteristics evaluated were: productivity, average fruit mass, height and plant chlorophyll index. Results: Productivity and plant height were superior in the fall/winter crop. Mean fruit mass and chlorophyll index were not influenced by planting time. For productivity, a linear response was obtained with increasing dose up to the limit of the N dose used (250 kg ha^-1), with a mean value higher than 14 t of fruit. Mean mass and plant height responded linearly to increasing N dose. Nitrogen affected the chlorophyll index, with maximum values of 45.96 and 47.19, observed in the two evaluation periods. Conclusion: Planting time and N content in the soil interacted with plant height, being favorable in the period without precipitation. N influenced all the characteristics, demonstrating the importance of nitrogen fertilization in the development of okra plants.

Nowadays, more and more cars have begun to enter into innumerable families; the family car has become a necessity for Chinese households who have certain purchasing power. However, the ups and downs of oil prices have brought some impact on people's automobile consumption activities. Therefore, after collecting the information of the oil price and family car consumer, carried on through in-depth analysis of the relevant data with reasonable relationship, and then developed a suitable for China's national conditions and finished oil pricing model, thereby the National Development and Reform Commission have proposed the suggestion for China's refined oil pricing mechanisms and promoting the healthy development of new energy vehicles with specific measures. For question 1, through the problem analysis and information access, combined with the past and current situation of the domestic refined oil prices, we analyze the following seven factors: international crude oil prices, China's annual crude oil imports, China's annual crude oil exports, crude oil output in China, China's annual GDP per capita, China's annual consumption of crude oil, the total annual energy consumption in China, all have influence on China's refined oil prices. By monadic linear regression analysis, annual average prices of domestic refined oil products have a certain correlation with the various influencing factors, and then by multiple linear regression way eventually concluded the final relationship between oil prices and the influence factors, which compared with the current price, and make reasonable evaluation model. Through the establishment of various influencing factors and function of time, and using the evaluation model for refined oil product price to make reasonable forecast. According to this model, in order to predict refined oil product price as $122.15 per barrel in 2016. For question two, we basically sums up three key factor which influence the quantity of family vehicle: China's oil product prices, the annual GDP per capita, total road mileage. Through Excel to make the relationship curves of different quantity of family cars against influencing factors, and use Grey Forecasting method to forecast the quantity of family cars. And carries on the residual error test, it is used to conclude that the rationality of the model is highly. The number of private cars of the city of xi 'an is predicts that to 8.302 million vehicles by 2020. For question three, we discussed the relationship between international crude oil prices and domestic exports of crude oil export with domestic refined oil prices, through its multiple linear regressions to get the final pricing model. For question four, according to three previous established models, we proposed China's refined oil pricing mechanism proposal to the national development and Reform Commission: perfect price controls, deeper product market, and integration of resources consideration and environmental protection class tax types, adjust the consumption tax collection and Administration links, and improve the production cost accounting.

The use of plant viruses as bioherbicides represents a fascinating and promising frontier in modern agriculture and weed management. This review article delves into the multifaceted world of harnessing plant viruses for herbicidal purposes, shedding light on their potential as eco-friendly, sustainable alternatives to traditional chemical herbicides. We begin by exploring the diverse mechanisms through which plant viruses can target and control weeds, from altering gene expression to disrupting essential physiological processes. The article highlights the advantages of utilizing plant viruses, such as their specificity for weed species, minimal impact on non-target plants, and a reduced environmental footprint. Furthermore, we investigate the remarkable versatility of plant viruses, showcasing their adaptability to various weed species and agricultural environments. The review delves into the latest advancements in genetic modification techniques, which enable the engineering of plant viruses for enhanced herbicidal properties and safety. In addition to their efficacy, we discuss the economic and ecological advantages of using plant viruses as bioherbicides, emphasizing their potential to reduce chemical herbicide usage and decrease the development of herbicide-resistant weeds. We also address the regulatory and safety considerations associated with the application of plant viruses in agriculture. Ultimately, this review article underscores the immense potential of plant viruses as bioherbicides and calls for further research, development, and responsible deployment to harness these microscopic agents in the ongoing quest for sustainable and environmentally friendly weed management strategies.