Nishant Shah described the many contradictions that qualitative research reveals, based on his work in rural India. In a region with the highest mobile phone penetration in India, children and young people use Chinese-based mobile phones, where they have learned enough of the characters to manage to communicate. Despite women’s access to technology being difficult and not always socially allowed, it was intriguing that women with limited access to mobile phones were often up to date on their favourite soap opera because they could access what Shah called ‘human internets’: their young children would borrow their father’s devices, and then stage afternoon performances to re-enact key moments for the village, to update themselves on the content of soap operas and other popular shows. Using these examples to demonstrate the richness of qualitative data collected by Shah and his colleagues, he focused on children and young people’s participation in the research process. Shah urged a shift in thinking from ‘children on the internet to children as internet’. He encouraged participants to re-think the image of the child internet user as ‘fragile’. for children to have access to laptops outside, but not in their homes. Here, traditional measures of household computer access would miss key contextual clues to the everyday life of the child. In developing studies of children, Shah recommended thinking of children as having agency, and empowering children and young people to help researchers develop a child’s eye view of the world – how do they think of themselves, and what interventions would they want to make? What is lacking for many is a structure of belonging (online) over and above access to technology.
Nishant Shah described the many contradictions that qualitative research reveals, based on his work in rural India. In a region with the highest mobile phone penetration in India, children and young people use Chinese-based mobile phones, where they have learned enough of the characters to manage to communicate. Despite women’s access to technology being difficult and not always socially allowed, it was intriguing that women with limited access to mobile phones were often up to date on their favourite soap opera because they could access what Shah called ‘human internets’: their young children would borrow their father’s devices, and then stage afternoon performances to re-enact key moments for the village, to update themselves on the content of soap operas and other popular shows. Using these examples to demonstrate the richness of qualitative data collected by Shah and his colleagues, he focused on children and young people’s participation in the research process. Shah urged a shift in thinking from ‘children on the internet to children as internet’. He encouraged participants to re-think the image of the child internet user as ‘fragile’. for children to have access to laptops outside, but not in their homes. Here, traditional measures of household computer access would miss key contextual clues to the everyday life of the child. In developing studies of children, Shah recommended thinking of children as having agency, and empowering children and young people to help researchers develop a child’s eye view of the world – how do they think of themselves, and what interventions would they want to make? What is lacking for many is a structure of belonging (online) over and above access to technology.
This report was prepared by the Northern Nevada Development Authority and the Business Resource
Innovation Center, the business branch of Carson City Library, for the Governor’s Office of Economic
Development. Support for this report was provided by the members of the Agriculture Committee of the
Northern Nevada Development Authority. Special thanks to Lynn Hettrick, Jim Barbee, Al DiStefano, Sarah
Adler, University of Nevada Cooperative Extension Program, Doug Taylor, and Ann Louhela for providing
valuable information and industry insight. Thanks to Eugenia Larmore of Ekay Economic Consultants for
her expertise, resources, and economic development and impact analysis report that added to the
foundation of this study. Thanks to the NNDA staff for their tireless efforts in getting this report ready for
publication.
Rice is one of the most important main food sources in Iran and the world. The correct identification of the type of pest in the early stages of preventive action has a significant role in reducing the damage to the crop. Traditional methods are not only time-consuming but also provide inaccurate results, As a result, precision agriculture and its associated technology systems have emerged. Precision agriculture utilizes information technology such as GPS, GIS, remote sensing, and machine learning to implement agricultural inter-farm technical measures to achieve better marginal benefits for the economy and environment. Machine learning is a division of artificial intelligence that can automatically progress based on experience gained. Deep learning is a subfield of machine learning that models the concepts of using deep neural networks with several high-level abstract layers. This capability has led to careful consideration in agricultural management. The diagnosis of disease and predicting the time of destruction, with a focus on artificial intelligence, has been the subject of much research in precision agriculture. This article presents, in the first step, a trained model of the Chilo suppressalis pest using data received from the smartphone, validated with the opinion of experts. In the second step, we introduce the developed system based on the smartphone. By using this system, farmers can share their pest images through the Internet and learn about the type of pest on their farm, and finally, take the necessary measures to combat it. This operation is done quickly and efficiently using the developed artificial intelligence. In the continuation of the article, the second part introduces the materials and methods, and the third part presents the results. The fourth section also discusses and concludes the research.
Modeling and Fabrication of a Robot for Sowing in a Seedling Tray (Case Study...J. Agricultural Machinery
Adopting new technologies for crop growth has the characteristics of improving disaster resistance and stress tolerance, ensuring stable yields, and improving product quality. Currently, the cultivation of seed trays relies on huge labor power, and further mechanization is needed to increase production. However, there are some problems in this operation, such as the difficulty of improving the speed of a single machine, seedling deficiency detection, automatic planting, and controlling the quality, which need to be solved urgently. To solve these problems, there are already some meaningful attempts. Si et al. (2012) applied a photoelectric sensor to a vegetable transplanter, which can measure the distance between seedlings and the movement speed of seedlings in a seedling guide tube, to prevent omission transplantation. Yang et al. (2018) designed a seedling separation device with reciprocating movement of the seedling cup for rice transplanting. Tests show that the structure of the mechanical parts of the seedling separation device meets the requirements of seed movement. The optimization of the control system can improve the positioning accuracy according to requirements and achieve the purpose of automatic seedling division. Chen et al. (2020) designed and tested of soft-pot-tray automatic embedding system for a light-economical pot seedling nursery machine. The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%. The successful tray embedding rate was 100% and the seed exposure rate was less than 1% with a linear velocity of the conveyor belt of 0.92 m s-1. The experiment findings agreed well with the analytical results.
Despite the sharp decline in Iran's water resources and growing population, the need to produce food and agricultural products is greater than ever. In the past, most seeds were planted directly into the soil, and many water resources, especially groundwater, were used for direct seed sowing and plant germination. One way to reduce the consumption of water, fertilizers, and pesticides is to plant seedlings instead of direct seed sowing. Therefore, the purpose of this study was dynamic modeling and fabrication of seed planting systems in seedling trays.
Environmental Impact Assessment of Electricity Generation in Wind Power Plant...J. Agricultural Machinery
Introduction
The world’s growing population has led to an inevitable increase in energy demand, and this, in addition to the depletion of non-renewable energy sources, can lead to several environmental issues. Wind power has proven to be a reliable and sustainable source of electricity, particularly in light of the pressing need to mitigate environmental impact and promote the use of renewable energy. The purpose of this research is to investigate and compare the environmental effects of electricity production from two wind power plants, Aqkand and Kahak, using wind turbines with a capacity of 2.5 megawatts for a period of three different lifetimes (20, 25, and 30 years).
Materials and Methods
The present study investigates the environmental effects of electricity generation during the life cycle of wind farms (Kahak and Aqkand) during the construction and operation of these power plants and the cumulative exergy demand index. The specifications of the wind turbines used in the current research are: turbine capacity of 2.5 MW, rotor diameter of 103 meters, rotor weight of 56 tonnes, three blades, each blade is 50.3 meters long and weighs 34.8 tonnes. The turbines are manufactured by Mapna and used in dry conditions. A functional unit of one kilowatt of electricity was selected and the data were analyzed in SIMAPRO software using IMPACT2002+ method with 15 midpoint indicators and four final indicators.
Results and Discussion
The results showed that the stage of raw materials and production has the highest impact on the creation of midpoint indicators, which is due to extraction, manufacturing, and production of parts such as steel casting using non-renewable energy and activities such as high-temperature welding. The total environmental index of Aqkand and Kahak wind power plants for 1 kWh of generated electricity was 5.84 and 4.45 μPt respectively, more than half of which belongs to the damage to human health category. The investigation of the ionizing radiation index showed that the use of diesel fuel in the installation phase resulted in the highest amount of emissions in both of the power plants, so the share of pollutant emissions in the raw materials and production phase is more than 40%, and in the installation phase due to diesel fuel consumption was more than 48%. The investigation of the eutrophication index showed that the raw materials and production stage accounted for more than 95% of the damage to the ecosystem quality category, and in the meantime, copper and electrical components had the highest amount of contribution to the raw materials and production stage. Additionally, diesel fuel accounted for the largest part of the result in the installation stage, and the transportation and maintenance stage included less than 1% of this result. The investigation of the renewable energy consumption index showed that the stage of raw materials and turbine production in the Aqkand power plant with a share of 68% and the Kahak power plant wi
This report was prepared by the Northern Nevada Development Authority and the Business Resource
Innovation Center, the business branch of Carson City Library, for the Governor’s Office of Economic
Development. Support for this report was provided by the members of the Agriculture Committee of the
Northern Nevada Development Authority. Special thanks to Lynn Hettrick, Jim Barbee, Al DiStefano, Sarah
Adler, University of Nevada Cooperative Extension Program, Doug Taylor, and Ann Louhela for providing
valuable information and industry insight. Thanks to Eugenia Larmore of Ekay Economic Consultants for
her expertise, resources, and economic development and impact analysis report that added to the
foundation of this study. Thanks to the NNDA staff for their tireless efforts in getting this report ready for
publication.
Rice is one of the most important main food sources in Iran and the world. The correct identification of the type of pest in the early stages of preventive action has a significant role in reducing the damage to the crop. Traditional methods are not only time-consuming but also provide inaccurate results, As a result, precision agriculture and its associated technology systems have emerged. Precision agriculture utilizes information technology such as GPS, GIS, remote sensing, and machine learning to implement agricultural inter-farm technical measures to achieve better marginal benefits for the economy and environment. Machine learning is a division of artificial intelligence that can automatically progress based on experience gained. Deep learning is a subfield of machine learning that models the concepts of using deep neural networks with several high-level abstract layers. This capability has led to careful consideration in agricultural management. The diagnosis of disease and predicting the time of destruction, with a focus on artificial intelligence, has been the subject of much research in precision agriculture. This article presents, in the first step, a trained model of the Chilo suppressalis pest using data received from the smartphone, validated with the opinion of experts. In the second step, we introduce the developed system based on the smartphone. By using this system, farmers can share their pest images through the Internet and learn about the type of pest on their farm, and finally, take the necessary measures to combat it. This operation is done quickly and efficiently using the developed artificial intelligence. In the continuation of the article, the second part introduces the materials and methods, and the third part presents the results. The fourth section also discusses and concludes the research.
Modeling and Fabrication of a Robot for Sowing in a Seedling Tray (Case Study...J. Agricultural Machinery
Adopting new technologies for crop growth has the characteristics of improving disaster resistance and stress tolerance, ensuring stable yields, and improving product quality. Currently, the cultivation of seed trays relies on huge labor power, and further mechanization is needed to increase production. However, there are some problems in this operation, such as the difficulty of improving the speed of a single machine, seedling deficiency detection, automatic planting, and controlling the quality, which need to be solved urgently. To solve these problems, there are already some meaningful attempts. Si et al. (2012) applied a photoelectric sensor to a vegetable transplanter, which can measure the distance between seedlings and the movement speed of seedlings in a seedling guide tube, to prevent omission transplantation. Yang et al. (2018) designed a seedling separation device with reciprocating movement of the seedling cup for rice transplanting. Tests show that the structure of the mechanical parts of the seedling separation device meets the requirements of seed movement. The optimization of the control system can improve the positioning accuracy according to requirements and achieve the purpose of automatic seedling division. Chen et al. (2020) designed and tested of soft-pot-tray automatic embedding system for a light-economical pot seedling nursery machine. The experimental results showed that the embedded-hard-tray automatic lowering mechanism was reliable and stable as the tray placement success rate was greater than 99%. The successful tray embedding rate was 100% and the seed exposure rate was less than 1% with a linear velocity of the conveyor belt of 0.92 m s-1. The experiment findings agreed well with the analytical results.
Despite the sharp decline in Iran's water resources and growing population, the need to produce food and agricultural products is greater than ever. In the past, most seeds were planted directly into the soil, and many water resources, especially groundwater, were used for direct seed sowing and plant germination. One way to reduce the consumption of water, fertilizers, and pesticides is to plant seedlings instead of direct seed sowing. Therefore, the purpose of this study was dynamic modeling and fabrication of seed planting systems in seedling trays.
Environmental Impact Assessment of Electricity Generation in Wind Power Plant...J. Agricultural Machinery
Introduction
The world’s growing population has led to an inevitable increase in energy demand, and this, in addition to the depletion of non-renewable energy sources, can lead to several environmental issues. Wind power has proven to be a reliable and sustainable source of electricity, particularly in light of the pressing need to mitigate environmental impact and promote the use of renewable energy. The purpose of this research is to investigate and compare the environmental effects of electricity production from two wind power plants, Aqkand and Kahak, using wind turbines with a capacity of 2.5 megawatts for a period of three different lifetimes (20, 25, and 30 years).
Materials and Methods
The present study investigates the environmental effects of electricity generation during the life cycle of wind farms (Kahak and Aqkand) during the construction and operation of these power plants and the cumulative exergy demand index. The specifications of the wind turbines used in the current research are: turbine capacity of 2.5 MW, rotor diameter of 103 meters, rotor weight of 56 tonnes, three blades, each blade is 50.3 meters long and weighs 34.8 tonnes. The turbines are manufactured by Mapna and used in dry conditions. A functional unit of one kilowatt of electricity was selected and the data were analyzed in SIMAPRO software using IMPACT2002+ method with 15 midpoint indicators and four final indicators.
Results and Discussion
The results showed that the stage of raw materials and production has the highest impact on the creation of midpoint indicators, which is due to extraction, manufacturing, and production of parts such as steel casting using non-renewable energy and activities such as high-temperature welding. The total environmental index of Aqkand and Kahak wind power plants for 1 kWh of generated electricity was 5.84 and 4.45 μPt respectively, more than half of which belongs to the damage to human health category. The investigation of the ionizing radiation index showed that the use of diesel fuel in the installation phase resulted in the highest amount of emissions in both of the power plants, so the share of pollutant emissions in the raw materials and production phase is more than 40%, and in the installation phase due to diesel fuel consumption was more than 48%. The investigation of the eutrophication index showed that the raw materials and production stage accounted for more than 95% of the damage to the ecosystem quality category, and in the meantime, copper and electrical components had the highest amount of contribution to the raw materials and production stage. Additionally, diesel fuel accounted for the largest part of the result in the installation stage, and the transportation and maintenance stage included less than 1% of this result. The investigation of the renewable energy consumption index showed that the stage of raw materials and turbine production in the Aqkand power plant with a share of 68% and the Kahak power plant wi
Introduction
Gelatin is one of the most widely used colloidal proteins, which has unique hydrocolloidal property. Gelatin is derived from collagen by changing the thermal nature. This product is widely used in food, pharmaceutical, biomedical, cosmetic and photography industries. Global gelatin demand for food and non-food products is increasing. Two important properties of nanoparticles are: Increasing the surface-to-volume ratio of nanoparticles causes the atoms on the surface to have a much greater effect on their properties than the atoms within the particle volume. The effects of quantum size, which is the second feature. Methods for preparing nanoparticles from natural macromolecules: In general, two major methods for making protein nanoparticles have been reported Emulsion-solvent evaporation method and sedimentation or phase separation method in aqueous medium. Numerous methods have been reported for the preparation of nanoparticles from natural macromolecules. The first method is based on emulsification and the second method is based on phase separation in aqueous medium. In the first method, due to the instability of the emulsion, it is not possible to prepare nanoparticles smaller than 500 nm with a narrow particle size distribution. Therefore, coagulation method or anti-solvent method which is based on phase separation was proposed to prepare nanoparticles from natural macromolecules.
Materials and Methods
Type B (cow) gelatin was purchased from processing company with Bloom 260-240 food and pharmaceutical Iran solvent gelatin solution of 25% aqueous acetate glutaraldehyde from Iran Neutron Company. Two-stage anti-solvent method was used to produce gelatin nanoparticles. Then, to form nanoparticles, acetone was added dropwise while stirring until the dissolved acetone begins to change color and eventually turns white, which indicates the formation of nanoparticles. Finally, glutaraldehyde solution was added for cross-linking and finally centrifuged.
Results and Discussion
The results showed that with increasing gelatin concentration, nanoparticle size and PDI increased significantly. According to the announced results, the solvent has a direct effect on the size. Therefore, the best mixing speed is determined to achieve the smallest particle size. Zeta potential is the best indicator for determining the electrical status of the particle surface and a factor for the stability of the potential of the colloidal system because it indicates the amount of charge accumulation in the immobile layer and the intensity of adsorption of opposite ions on the particle surface. If all the particles in the suspension are negatively or positively charged, the particles tend to repel each other and do not tend to accumulate. The tendency of co-particles to repel each other is directly related to the zeta potential. Fabricated gelatin nanoparticles have a stable structure, and are heat resistant. These nanoparticles are ready to be used to accept
Introduction
Intelligent food packaging as a new technology can maintain the quality and safety of food during its shelf life. This technology uses indicators and sensors that are used in packaging and detects physiological changes in food (due to microbial and chemical degradation). These indicators usually provide information that can be easily identified by the food distributor and the consumer. However, most of the markers currently used are non-renewable and non-degradable synthetic materials. Microalgae that live in both marine and freshwater are a versatile solution for building new biosensors to detect pollutants such as herbicides or heavy metals. These photosynthetic microorganisms are very sensitive to their environmental changes and allow the detection of pollutants. In the past few years, several studies have been conducted in relation to the development, evaluation and application of biosensors using natural compounds in smart food packaging, and some of them are reported and summarized in Table 2.
Materials and Methods
In these studies, examples are mainly focused on biosensors related to biopolymers, but some other synthetic polymers that are easily degraded have also been used as examples. In Table 2, it is also specified what the function and application of the sensor is and how it reacts to the loss of freshness of food. Most sensors are sensitive to the change in pH caused by the release of volatile nitrogen compounds, and this change is characterized by a colorimetric response. Sensors are usually placed in the space above the food container, avoiding direct contact with the food, but close enough to detect changes in the environment and respond to changes in food quality. When these biosensors are integrated with biopolymers, they are usually incorporated into the polymer structure, and the color change of the layers (film) indicates changes in food quality in the packed product. The collected information also clearly shows that extracts rich in chemical compounds of pigments that change color with pH and especially anthocyanins have been used in these biosensors. In addition, most studies of biosensors have been conducted on fish, meat, and seafood, which is probably because their quality degradation is an important economic loss and also because the pH of the surrounding environment is changed during the degradation process. , and this change is easily detected through pH-sensitive biosensors. Smart food packaging technology has made it possible to monitor food quality by incorporating markers, sensors and radio frequency identification (RFID) into packaging. The technology also allows producers and consumers to trace the history of a product through important points in the food supply chain.Interestingly, some compounds applied and tested in the sensor not only provide a pH-sensitive dye, but also have other bioactive properties, for example, antimicrobial properties, and its presence in the polymer matrix can also incr