Two-temperature coronal flow above a thin disk

We extended the disk corona model (Meyer & Meyer-Hofmeister 1994; Meyer, Liu, & Meyer-Hofmeister 2000a) to the inner region of galactic nuclei by including different temperatures in ions and electrons as well as Compton cooling. We found that the mass evaporation rate and hence the fraction of accretion energy released in the corona depend strongly on the rate of incoming mass flow from outer edge of the disk, a larger rate leading to more Compton cooling, less efficient evaporation and a weaker corona. We also found a strong dependence on the viscosity, higher viscosity leading to an enhanced mass flow in the corona and therefore more evaporation of gas from the disk below. If we take accretion rates in units of the Eddington rate our results become independent on the mass of the central black hole. The model predicts weaker contributions to the hard X-rays for objects with higher accretion rate like narrow-line Seyfert 1 galaxies (NLS1s), in agreement with observations. For luminous active galactic nuclei (AGN) strong Compton cooling in the innermost corona is so efficient that a large amount of additional heating is required to maintain the corona above the thin disk.Comment: 17 pages, 6 figures. ApJ accepte

In The Land Of Wedding Bells

https://digitalcommons.library.umaine.edu/mmb-vp/1873/thumbnail.jp

In The Land Of Wedding Bells

https://digitalcommons.library.umaine.edu/mmb-vp/1874/thumbnail.jp

In The Land Of Wedding Bells

https://digitalcommons.library.umaine.edu/mmb-vp/1872/thumbnail.jp

Dynamic Classification of Moisture Stress Using Canopy and Leaf Temperature Responses to a Step Changes of Incident Radiation

Environmental conditions affect plant productivity and understanding how plants respond to drought stress can be measured in different ways. This study focused on measuring leaf response time to induced water stress. Leaf response time to a step increase and step decrease in radiation was computed for four species of well-watered and water-stressed plants in a controlled environment. The canopy temperature was measured with an infrared thermometer and a thermal imaging camera. Thermal images were analyzed to determine the average temperature of a selected single, unobstructed leaf at the top of the canopy. Both the canopy response time and the single leaf response time were computed for this study. The response times to a step change of radiation for well-watered plants were generally longer than the response times of water stressed plants. These results show that response time may be used as an indicator of plant water stress

Dynamic Classification of Moisture Stress Using Canopy and Leaf Temperature Responses to a Step Changes of Incident Radiation

Environmental conditions affect plant productivity and understanding how plants respond to drought stress can be measured in different ways. This study focused on measuring leaf response time to induced water stress. Leaf response time to a step increase and step decrease in radiation was computed for four species of well-watered and water-stressed plants in a controlled environment. The canopy temperature was measured with an infrared thermometer and a thermal imaging camera. Thermal images were analyzed to determine the average temperature of a selected single, unobstructed leaf at the top of the canopy. Both the canopy response time and the single leaf response time were computed for this study. The response times to a step change of radiation for well-watered plants were generally longer than the response times of water stressed plants. These results show that response time may be used as an indicator of plant water stress

Airflow Characteristics of Commonly Used Temperature Radiation Shields*

The air temperature radiation shield is a key component in air temperature measurement in weather station networks; however, it is widely recognized that significant errors in the measured air temperature exist due to insufficient airflow past the air temperature sensor housed inside the shield. During the last several decades, the U.S. National Weather Service has employed a number of different shields in air temperature measurements. This paper focuses on the airflow characteristics inside air temperature shields including the Maximum–Minimum Temperature System (MMTS), the Gill shields, and the Cotton Region Shelter (CRS). Average airspeed profiles and airflow efficiency inside the shields are investigated in this study under both windtable and field conditions using an omnidirectional hot-wire sensor. Results from the windtable measurements indicate that the average airspeeds inside the shields oscillated along the center line of the Gill and MMTS shields as the ‘‘windtable air’’ speed was changed from 1.03 to 2.62 m s1; the MMTS airflow efficiency demonstrated a nearly constant value, but the Gill’s airflow efficiency increased. A linear transfer equation between the airspeed measured at the normal operating position for the temperature sensor inside the shield and the ambient wind speed was found under field conditions for all three nonaspirated air temperature radiation shields (CRS, Gill, and MMTS). Results indicate that the naturally ventilated temperature radiation shields are unable to provide sufficient ventilation when the ambient wind speed is less than 5 m s 1 at the radiation shield height

Management and Modeling of Winter-time Basil Cultivars Grown with a Cap MAT System

Basil (Ocimum basilicum) is a high value crop, currently grown in the field and greenhouses in Nebraska. Winter-time, greenhouse studies were conducted during 2015 and 2016, focusing on cultivars of basil grown on a Cap MAT II® system with various levels of fertilizer application. The goal was to select high value cultivars that could be grown in Nebraska greenhouses. The studies used water content, electrical conductivity, photosynthetically active radiation (PAR), and relative humidity, air and soil media temperature sensors. Greenhouse systems can be very complex, even though controlled by mechanical heating and cooling. Uncertain or ambiguous environmental and plant growth factors can occur, where growers need to plan, adapt, and react appropriately. Plant harvest weights and electronic sensor data was recorded over time and used for training and internally validating fuzzy logic inference and classification models. Studies showed that GENFIS2 ‘subtractive clustering’ of data, prior to ANFIS training, resulted in good correlations for predicted growth (R2 \u3e 0.85), with small numbers of effective rules and membership functions. Cross-validation and internal validation studies also showed good correlations (R2 \u3e 0.85). Decisions on basil cultivar selection and forecasting as to how quickly a basil crop will reach marketable size will help growers to know when to harvest, for optimal yield and predictable quantity of essential oils. If one can predict reliably how much essential oil will be produced, then the methods and resultant products can be proposed for USP or FDA approval. Currently, most plant medicinal and herbal oils and other supplements vary too widely in composition for approval. The use of fuzzy set theory could be a useful mathematical tool for plant and horticultural production studies

Management and Modeling of Winter-time Basil Cultivars Grown with a Cap MAT System

Basil (Ocimum basilicum) is a high value crop, currently grown in the field and greenhouses in Nebraska. Winter-time, greenhouse studies were conducted during 2015 and 2016, focusing on cultivars of basil grown on a Cap MAT II® system with various levels of fertilizer application. The goal was to select high value cultivars that could be grown in Nebraska greenhouses. The studies used water content, electrical conductivity, photosynthetically active radiation (PAR), and relative humidity, air and soil media temperature sensors. Greenhouse systems can be very complex, even though controlled by mechanical heating and cooling. Uncertain or ambiguous environmental and plant growth factors can occur, where growers need to plan, adapt, and react appropriately. Plant harvest weights and electronic sensor data was recorded over time and used for training and internally validating fuzzy logic inference and classification models. Studies showed that GENFIS2 ‘subtractive clustering’ of data, prior to ANFIS training, resulted in good correlations for predicted growth (R2 \u3e 0.85), with small numbers of effective rules and membership functions. Cross-validation and internal validation studies also showed good correlations (R2 \u3e 0.85). Decisions on basil cultivar selection and forecasting as to how quickly a basil crop will reach marketable size will help growers to know when to harvest, for optimal yield and predictable quantity of essential oils. If one can predict reliably how much essential oil will be produced, then the methods and resultant products can be proposed for USP or FDA approval. Currently, most plant medicinal and herbal oils and other supplements vary too widely in composition for approval. The use of fuzzy set theory could be a useful mathematical tool for plant and horticultural production studies