Coping Skills for Students with ADHD

Students diagnosed with Attention Deficit/Hyperactivity Disorder (ADHD) are often seen as problem students with little hope for academic success. It is common for these students to be medicated with a daily dosage of stimulants to help them function more appropriately in the classroom. This meta-synthesis identifies multiple ways to work with students with ADHD; effective interventions can help students with ADHD cope with their disorder and become more successful students

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Evaluation of integrated threshing and drying design concepts for paddy rice using analytical hierarchy process

Threshing and drying are two major postharvest activities that contribute significantly to postharvest losses for small and medium-scale rice farmers, leading to food insecurity and hunger in Sub-Saharan Africa. Developing an appropriate system for threshing and drying needs urgent attention. The objective of the study involved the use of Analytical Hierarchy Process (AHP) for evaluation and selection of the best option among four design concepts for development and fabrication. The four design concepts shortlisted were: (1) batch flow biomass-powered manual threshing and drying system, (2) recirculating diesel-powered mobile threshing and drying system, (3) mechanized threshing with solar drying batch system, and (4) tractor-powered recirculating continues flow integrated system. For the MCAHP analysis, 17 attributes were proposed and divided into five main criteria. The evaluation of the main criteria showed that cost had the highest score, followed by performance, safety, ease of installation and operation, and manufacturability, with a global score of 0.560, 0.202, 0.108, 0.083 and 0.048, respectively. It was observed that design concept two received the highest weighted score of 0.35 and was selected as the design concept to proceed with. The consistency ratios of the main criteria and  attributes were all less than 0.1, which is the allowable limit of inconsistency. In conclusion, concept 2 was selected as the best design for developing an integrated threshing and drying system for paddy rice and is recommended for development, fabrication, evaluation and optimisation. Int. J. Agril. Res. Innov. Tech. 14(1): 30-44, June 202

Predicting functional properties of milk powder based on manufacturing data in an industrial-scale powder plant

The fundamental science relating key physical and functional properties of milk powder to plant operating conditions is complex and largely unknown. Consequently this paper takes a data-driven approach to relate the routinely measured plant conditions to one vital function property known as sediment in an industrial-scale powder plant. Data from four consecutive production seasons was examined, and linear regression models based on a chosen set of processing variables were used to predict the sediment values. The average prediction error was well within the range of the uncertainty of the laboratory test. The models could be used to predict the effect of each individual plant variable on the sediment values which could be beneficial in quality optimisation. In addition the choice of the training data set used to compute regression coefficients was studied and the resultant regression models were compared to alternative PLS models built on the same data

TWO ESSAYS ON WHOLE FARM MODELING AND CROP MARKETING IN WESTERN KENTUCKY

This thesis is composed of two essays that investigate whole farm planning and crop marketing in western Kentucky. In the first essay, contracting decisions between food corn producers and a mill are analyzed to observe factors affecting the bushel amount farmers contract. Unbalanced panel data containing seven years’ worth of pricing and contract information are used with a fixed-effects model to generate parameter estimates and quantify their effect on bushels contracted. It was found that contract attributes, market condition, and relationship-specific assets had a significant effect on producers’ food corn contracting decisions. The second essay utilizes mixed-integer programming to optimize resource allocation and marketing strategy for a hypothetical farm. Post-optimal analysis is performed to determine non-binding capacities for drying and storage equipment. The model is re-run with these non-binding capacities to observe changes in net returns as well as planting, harvesting, and marketing strategies. New equipment and associated costs are identified, and the change in net returns from the base case is used as net cash flow in a net present value investment analysis. Results of the investment analysis indicate increasing drying and storage capacity is a wise investment given the scenario modeled

Effect of curing conditions and harvesting stage of maturity on Ethiopian onion bulb drying properties

The study was conducted to investigate the impact of curing conditions and harvesting stageson the drying quality of onion bulbs. The onion bulbs (Bombay Red cultivar) were harvested at three harvesting stages (early, optimum, and late maturity) and cured at three different temperatures (30, 40 and 50 oC) and relative humidity (30, 50 and 70%). The results revealed that curing temperature, RH, and maturity stage had significant effects on all measuredattributesexcept total soluble solids

The Translation of Spanish Agri-food Texts into English and Italian Using Machine Translation Engines: A Contrastive Study

La industria agroalimentaria es uno de los sectores económicos más importantes en España. El trabajo de los traductores en este sector permite la creación de nuevos negocios en otros países y, por lo tanto, contribuye al crecimiento económico. Entre los más importantes, el sector cárnico es líder en facturación y empleo directo. Por otra parte, la mayoría son pequeñas y medianas empresas y tienen la necesidad de adaptar información sobre sus productos para atraer a nuevos consumidores. Sin embargo, hay algunos ámbitos en los que aún no se ha investigado con profundidad, como los embutidos. El objetivo de este estudio es analizar el resultado de la traducción automática de un texto agroalimentario, del español al inglés y al italiano y utilizando diferentes motores de traducción automática, con la finalidad de identificar los errores principales, valorar qué motor de TA produce mejores resultados y enfatizar la importancia de formar a los traductores en este ámbito.Grado en Traducción e Interpretació