Interview with Tim Norris at the Mt. Vernon Farmer\u27s Exchange

Tim Norris, a worker at the Mount Vernon Farmer\u27s exchange, discusses how the Farmer\u27s exchange works, including the crops that come into the exchange and when they come in. He also discusses how the exchange works, and what sort of machinery they use. Tim goes into detail of how exactly the exchange works, so that others can understand the process.https://digital.kenyon.edu/ffp_interviews/1018/thumbnail.jp

Leveraging Infrastructure as an Economic Development Tool

Most communities don’t realize the value of their existing infrastructure (roads, utilities, etc.) in terms of economic development. Understanding your infrastructure is key to pursuing and competing for economic development projects in your community. This presentation discusses the role of infrastructure in economic development and how to position your community for future success

Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision.

Deep feedforward neural network models of vision dominate in both computational neuroscience and engineering. The primate visual system, by contrast, contains abundant recurrent connections. Recurrent signal flow enables recycling of limited computational resources over time, and so might boost the performance of a physically finite brain or model. Here we show: (1) Recurrent convolutional neural network models outperform feedforward convolutional models matched in their number of parameters in large-scale visual recognition tasks on natural images. (2) Setting a confidence threshold, at which recurrent computations terminate and a decision is made, enables flexible trading of speed for accuracy. At a given confidence threshold, the model expends more time and energy on images that are harder to recognise, without requiring additional parameters for deeper computations. (3) The recurrent model's reaction time for an image predicts the human reaction time for the same image better than several parameter-matched and state-of-the-art feedforward models. (4) Across confidence thresholds, the recurrent model emulates the behaviour of feedforward control models in that it achieves the same accuracy at approximately the same computational cost (mean number of floating-point operations). However, the recurrent model can be run longer (higher confidence threshold) and then outperforms parameter-matched feedforward comparison models. These results suggest that recurrent connectivity, a hallmark of biological visual systems, may be essential for understanding the accuracy, flexibility, and dynamics of human visual recognition

Ecohydrology of a Floodplain Forest: Relationships Between Evapotranspiration, Vegetation, and Topography at Congaree National Park, South Carolina

Congaree National Park supports high biodiversity and provides ecosystem services for the surrounding area in the floodplain wetland system, especially in the bottomland hardwood forests which contain some of the last remaining old-growth stands in the eastern U.S. Maintaining the hydraulic functions of this ecosystem is essential not only for the conservation of biodiversity, but also for the ecosystem services it provides, such as nitrification, denitrification, decomposition, removal of organic carbon, and phosphorous uptake and sorption. Because management practices of the park depend on understanding the area‟s hydrology, past research has been performed to analyze the flooding of Congaree River. However, not much has been done to better understand groundwater movement through the floodplain sediments in the Congaree River Valley. The goal of this project is to quantify interactions between the shallow unconfined aquifer and local vegetation surrounding eight piezometers in the Congaree Observation Well Network at Congaree National Park through calculating and comparing evapotranspiration rates, specific yield, vegetation diversity and basal area, and microtopography. Data on groundwater response to storm events, diurnal signals caused by evaporation and transpiration in the forest, vegetation community structure, and local topography were compared to better understand the role of these factors on vegetation water demand in this wetland-dominated system

Contributions of wood smoke and vehicle emissions to ambient concentrations of volatile organic compounds and particulate matter during the Yakima wintertime nitrate study

A multiple linear regression (MLR) chemical mass balance model was applied to data collected during an air quality field experiment in Yakima, WA, during January 2013 to determine the relative contribution of residential wood combustion (RWC) and vehicle emissions to ambient pollutant levels. Acetonitrile was used as a chemical tracer for wood burning and nitrogen oxides (NOx) as a chemical tracer for mobile sources. RWC was found to be a substantial source of gas phase air toxics in wintertime. The MLR model found RWC primarily responsible for emissions of formaldehyde (73%), acetaldehyde (69%), and black carbon (55%) and mobile sources primarily responsible for emissions of carbon monoxide (CO; 83%), toluene (81%), C2-alkylbenzenes (81%), and benzene (64%). When compared with the Environmental Protection Agency’s 2011 winter emission inventory, the MLR results suggest that the contribution of RWC to CO emissions was underestimated in the inventory by a factor of 2. Emission ratios to NOx from the MLR model agreed to within 25% with wintertime emission ratios predicted from the Motor Vehicle Emissions Simulator (MOVES) 2010b emission model for Yakima County for all pollutants modeled except for CO, C2-alkylbenzenes, and black carbon. The MLR model results suggest that MOVES was overpredicting mobile source emissions of CO relative to NOx by a factor of 1.33 and black carbon relative to NOx by about a factor of 3

Recurrence is required to capture the representational dynamics of the human visual system.

The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object processing is commonly viewed and studied as a feedforward process. Here, we measure and model the rapid representational dynamics across multiple stages of the human ventral stream using time-resolved brain imaging and deep learning. We observe substantial representational transformations during the first 300 ms of processing within and across ventral-stream regions. Categorical divisions emerge in sequence, cascading forward and in reverse across regions, and Granger causality analysis suggests bidirectional information flow between regions. Finally, recurrent deep neural network models clearly outperform parameter-matched feedforward models in terms of their ability to capture the multiregion cortical dynamics. Targeted virtual cooling experiments on the recurrent deep network models further substantiate the importance of their lateral and top-down connections. These results establish that recurrent models are required to understand information processing in the human ventral stream

Hyperamylasemia post living donor nephrectomy does not relate to pain

Introduction The aetiology of pain after laparoscopic donor nephrectomy remains unclear. Given the proximity of the left kidney to the tail of the pancreas, we aimed to assess whether mobilisation and retrieval of the left kidney might inflame the pancreas, leading to pain and hyperamylasaemia in the post-operative period. Patient and methods In the present study, 16 consecutive live kidney donors were analysed in the same three months period. Amylase levels were measured on days 1 and 2. For each 24-hour period postoperatively analgesia consumption was recorded, as well as pain scores at rest on a visual analogue scale (VAS). Results Three out of 16 donors presented hyperamylasemia. A multiple regression analysis found levobupivacaine dose, propofol dose, transversus abdominis plane block and day 1 amylase did not significantly predict pain scores. Interestingly, body mass index significantly correlated with increased pain scores (p = 0.041). Also, increasing CO2 insufflation pressure and use of local anaesthetic infusion catheters predicted a decreased deep pain score (p = 0.036 and p = 0.037). Conclusion There was no correlation of amylase levels and pain scores. Pancreatitis is a rare complication of nephrectomy and no overt cases were seen in the case of donor nephrectomy

Individual differences among deep neural network models.

Deep neural networks (DNNs) excel at visual recognition tasks and are increasingly used as a modeling framework for neural computations in the primate brain. Just like individual brains, each DNN has a unique connectivity and representational profile. Here, we investigate individual differences among DNN instances that arise from varying only the random initialization of the network weights. Using tools typically employed in systems neuroscience, we show that this minimal change in initial conditions prior to training leads to substantial differences in intermediate and higher-level network representations despite similar network-level classification performance. We locate the origins of the effects in an under-constrained alignment of category exemplars, rather than misaligned category centroids. These results call into question the common practice of using single networks to derive insights into neural information processing and rather suggest that computational neuroscientists working with DNNs may need to base their inferences on groups of multiple network instances

Morphological and genomic shifts in mole-rat 'queens' increase fecundity but reduce skeletal integrity.

In some mammals and many social insects, highly cooperative societies are characterized by reproductive division of labor, in which breeders and nonbreeders become behaviorally and morphologically distinct. While differences in behavior and growth between breeders and nonbreeders have been extensively described, little is known of their molecular underpinnings. Here, we investigate the consequences of breeding for skeletal morphology and gene regulation in highly cooperative Damaraland mole-rats. By experimentally assigning breeding 'queen' status versus nonbreeder status to age-matched littermates, we confirm that queens experience vertebral growth that likely confers advantages to fecundity. However, they also upregulate bone resorption pathways and show reductions in femoral mass, which predicts increased vulnerability to fracture. Together, our results show that, as in eusocial insects, reproductive division of labor in mole-rats leads to gene regulatory rewiring and extensive morphological plasticity. However, in mole-rats, concentrated reproduction is also accompanied by costs to bone strength