The application of nanotechnology in the food industry enables prioritization of consumers’ needs. Nanotechnology has the ability to provide new forms of control on food structure; therefore, this technology has higher industrial value. This paper briefly introduces the main concepts of nanotechnology and its correlation with size reduction performance. This paper also introduces the main nanobjects and their potential applications in food, and summarizes various studies and their applications in food industry.

There are numerous studies reported on the usage of the sapindus emarginatus (SE) fruit in cancer and other treatments in the past few years. In this study, crude SE fruit extract was prepared and it was further used to synthesis gold nanoparticles (Au Nps). The synthesized Au Nps were left embedded in the SE fruit extract. The Au Nps embedded in the SE fruit extract (SE-Au Nps) were characterized using UV-Visiable Spectroscopy, Centrifugal Particle Size analyzer (CPS), Scanning Electron Microscope (SEM) and Fourier Transform Infrared Spectroscopy (FTIR). MTT assay was carried out for both SE fruit extract and SE-Au Nps on MCF7 breast cancer cell line and thus compared. The UV-Visible Absorbance for the SE-Au Nps was obtained at 543 nm. The centrifugal particle size analysis of the Au Nps embedded in SE fruit extract showed the size of the nanoparticles to be widely varying with higher fraction of particles between the size ranges of 15 to 20 nm. The morphology of the Au Nps embedded in SE fruit extract was observed using SEM. The presence of Au Nps in SE fruit extract was confirmed using FTIR. The results of the MTT assay on MCF7 breast cancer cell line proved that the % cell viability was less for SE-Au Nps than that of the SE fruit extract alone. Thus, the antiproliferative activity of the SE fruit extract was significantly enhanced by embedding it with Au Nps and it can be effectively used in therapeutic applications after further studies.

Our intention in assembling this special issue of the Journal of Infrastructure, Policy and Development is to offer a state-of-the-art tour through the political economy issues associated with the provision of public infrastructure, and with the use of Public-Private Partnerships (PPPs) in particular. Anyone who is familiar with PPPs cannot fail to be impressed by the diversity of positions and claims regarding their properties. Some scholars maintain that PPPs are an efficient tool to enhance productivity due to their ability to manage demand-side risk. In contrast, other scholars see in PPPs a scheme whereby the public assumes the risk while the private partner takes the profit.

The reduction of biodiversity and the decline in wildlife populations are urgent environmental issues with devasting consequences for ecosystems and human health. As a result, the protection of wildlife and biodiversity has emerged as one of humanity’s greatest goals, not only for protecting and maintaining human health but also for environmental, economic, and social well-being. In recent years, people have become increasingly aware of the importance and effectiveness of wildlife conservation efforts alongside environmental protection measures, sustainable agricultural practices and non-harmful production procedures and services. This study describes the development and implementation of a labeling scheme for wildlife and biodiversity protection for products or services. The label is designed to encourage the adoption of sustainable and environmentally friendly production methods and services that will contribute to biodiversity conservation and the harmonic coexistence of human-wildlife. Moreover, using a case study approach, the research presents an innovative information system designed to streamline the label-awarding process, ensuring transparency and efficiency. The established system evaluates the sustainability practices and measures implemented by businesses, with a focus on honey production in this case. Additionally, the study explores the broader social implications of the label, particularly its potential to engage consumers and promote awareness of biodiversity conservation.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.

This problem is a solar hut photovoltaic cell in the attached and overhead two installation methods, the type of photovoltaic cells and array mode and inverter type optimization design issues. In question 1, since the photovoltaic cells are attached to the roof and exterior surfaces, the direction and angle of the battery are uniquely determined by the direction and angle of the attached surface. The problem is translated to optimize the installation of a certain type on a single surface area (array) of photovoltaic cells, so that the total amount of solar photovoltaic power generation as much as possible, and the unit power generation costs as small as possible, which is a multi-objective optimization problem. The problem can be discussed in the ideal environment in a single surface area of the battery installation optimization program, and then the actual environment of the multi-surface optimization. In the solution to Problem 1, the unit on the south of the roof of the battery at the moment to accept the solar energy formula is generated. The definition of and is the moment of direct radiation intensity, for the moment the sun and the south of the roof of the plane where the angle, for the level of horizontal radiation intensity, for the south of the roof and the horizontal angle, the planefor the plane, the center of the heart, the vertical upward direction is the axis of the positive coordinate system, obtained with the sun height angle , the sun azimuth , red angle, angle and the sun when the relationship is generated. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of electricity generation is 77126 degrees, the economic benefits of 16,488 yuan, the recovery period of 21.3 years. In question 2, because the photovoltaic cells in the roof and the external wall surface can be installed overhead, the panel orientation and tilt will affect the efficiency of photovoltaic cells. Therefore, in the optimization scheme of Problem 1, the orientation and inclination of the panel on each surface are further adjusted to calculate the optimum orientation and inclination of the panel on each surface. The problem can be in the ideal weather environment to establish the sun running and the battery board efficiency model, and then the measured environment test. The optimal orientation of the panel is southward, and the optimal angle with the ground plane is 39.89 degrees. The conclusion is only installed in the small roof surface type of battery C11, and the rest of the surface is not installed. 35 years of generating capacity of 82165.2 degrees, the economic benefits of 18,998 yuan, the recovery period of 13 years. In question 3, by the optimization of the above two issues, in the building to meet the requirements of the hut under the design of the various aspects of the cabin and battery installation, and further optimize the total power generation of the hut, economic benefits. The whole model solver is run in MATLAB7.0.