Phosphorus Immobilization in Poultry Litter and Litter-amended soils with Aluminum, Calcium and Iron amendments

Arkansas produces approximately one billion broilers each year. Phosphorous (P) runoff from fields receiving poultry litter is believed to be one of the primary factors affecting water quality in Northwest Arkansas. Poultry litter contains approximately 20 g P kg-1, of which about 2 g P kg-1 is water soluble. Soils that have received repeated heavy applications of litter may have water soluble P contents of as high as 10 mg P Kg-1 soil. The objective of this study was to determine if soluble P levels could be reduced in poultry litter and litter-amended soils with Al,Ca, and/or Fe amendments. Poultry litter was amended with alum, sodium aluminate, quick lime, slaked lime, calcitic limestone, dolomitic limestone, gypsum, ferrous chloride, ferric chloride, ferrous sulfate and ferric sulfate, and incubated in the dark at 25°C for one week. Three soils which had been excessively fertilized with poultry litter were amended with alum, ferrous sulfate, calcitic limestone, gypsum and slaked lime and incubated for 4 weeks at 25 °C. In the litter studies, the Ca treatments were tested with and without CaF2 additions in an attempt to precipitate fluorapatite. At the end of the incubation period, the litter and soils were extracted with deionized water and soluble reactive P (SRP) was determined. SRP levels in the poultry litter were reduced from over 2,000 mg P kg-1 litter to less than 1 mg P kg-1 litter with the addition of alum, quick lime, slaked lime, ferrous chloride, ferric chloride, ferrous sulfate and ferric sulfate under favorable pH conditions. S.RP levels in the soils were reduced from approximately 5 mg P Kg-1 soil to less than 0.05 mg P Kg-1 soil with the addition of alum and ferrous sulfate under favorable pH conditions. Gypsum and sodium aluminate reduced SRP levels in litter by 50 to 60 percent while calcitic and dolomitic limestone were even less effective. In soils, the Ca amendments were less effective than the Al and Fe amendments, although slaked lime was effective at high pH. The results of these studies suggest that treating litter and excessively fertilized soils with some of these compounds, particularly alum, could significantly reduce the amount of SRP in runoff from littered pastures. Therefore, chemical additions to reduce SRP in litter and soil may be a best management practice in situations where eutrophication of adjacent water bodies due to P runoff has been identified. Preliminary calculations indicate that this .p ractice may be economically feasible. However, more research is needed to determine any beneficial and/or detrimental aspects of this practice

Hysteresis and competition between disorder and crystallization in sheared and vibrated granular flow

Experiments on spherical particles in a 3D Couette cell vibrated from below and sheared from above show a hysteretic freezing/melting transition. Under sufficient vibration a crystallized state is observed, which can be melted by sufficient shear. The critical line for this transition coincides with equal kinetic energies for vibration and shear. The force distribution is double-peaked in the crystalline state and single-peaked with an approximately exponential tail in the disordered state. A linear relation between pressure and volume ($dP/dV > 0$) exists for a continuum of partially and/or intermittently melted states over a range of parameters

Hysterectomy, endometrial ablation, and levonorgestrel releasing intrauterine system (Mirena) for treatment of heavy menstrual bleeding : cost effectiveness analysis

Peer reviewedPublisher PD

Stoichiometry control of sputtered CuCl thin films: Influence on ultraviolet emission properties

We demonstrate that the chemical composition of the sputtered CuCl thin films could be finely controlled by adjusting the bias to the substrate. The films deposited without any intentional bias were Cl rich (CuCl1+x), a bias of −22 V yielded stoichiometric CuCl, and a further increase in the negative bias resulted in Cl deficient films (CuCl1−x). The crystalline and optical properties were found to be associated with the chemical composition. Cl rich films showed a deep level green emission at around 515 nm in addition to ultraviolet (UV) excitonic emission. The stoichiometric films have higher optical quality, exhibiting a sharp UV emission at around 385 nm at room temperature, compared to nonstoichiometric samples. Visible luminescence related to deep level defects was not observed in the stoichiometric films. Changes in energy of the flux from the target and the subsequent ion bombardment on the substrate surface are correlated with the variations in chemical composition and their impact on the film microstructure and UV emission

Crossover Behavior in Burst Avalanches of Fiber Bundles: Signature of Imminent Failure

Bundles of many fibers, with statistically distributed thresholds for breakdown of individual fibers and where the load carried by a bursting fiber is equally distributed among the surviving members, are considered. During the breakdown process, avalanches consisting of simultaneous rupture of several fibers occur, with a distribution D(Delta) of the magnitude Delta of such avalanches. We show that there is, for certain threshold distributions, a crossover behavior of D(Delta) between two power laws D(Delta) proportional to Delta^(-xi), with xi=3/2 or xi=5/2. The latter is known to be the generic behavior, and we give the condition for which the D(Delta) proportional to Delta^(-3/2) behavior is seen. This crossover is a signal of imminent catastrophic failure in the fiber bundle. We find the same crossover behavior in the fuse model.Comment: 4 pages, 4 figure

Live Demonstration: An IoT Wearable Device for Real-time Blood Glucose Prediction with Edge AI

Blood glucose (BG) prediction is crucial to the successful management of type 1 diabetes (T1D) by allowing for proactive medical interventions and treatment. We present an IoT-enabled wearable device for real-time BG prediction based on continuous glucose monitoring (CGM) and a novel attention-based recurrent neural network (RNN). The complete hardware contains a system on a chip (SoC) that enables BLE connectivity and executes the embedded RNN with edge inference. This device can provide 24-hour predictive glucose alerts, i.e., hypoglycemia, to improve BG control and prevent or mitigate potential complications. Meanwhile, it can be connected to desktop computers and smartphones for the visualization of BG trajectories, data storage, and model update

IoMT-Enabled Real-time Blood Glucose Prediction with Deep Learning and Edge Computing

Blood glucose (BG) prediction is essential to the success of glycemic control in type 1 diabetes (T1D) management. Empowered by the recent development of the Internet of Medical Things (IoMT), continuous glucose monitoring (CGM) and deep learning technologies have been demonstrated to achieve the state of the art in BG prediction. However, it is challenging to implement such algorithms in actual clinical settings to provide persistent decision support due to the high demand for computational resources, while smartphone-based implementations are limited by short battery life and require users to carry the device. In this work, we propose a new deep learning model using an attention-based evidential recurrent neural network and design an IoMT-enabled wearable device to implement the embedded model, which comprises a low-cost and low-power system on a chip to perform Bluetooth connectivity and edge computing for real-time BG prediction and predictive hypoglycemia detection. In addition, we developed a smartphone app to visualize BG trajectories and predictions, and desktop and cloud platforms to backup data and fine-tune models. The embedded model was evaluated on three clinical datasets including 47 T1D subjects. The proposed model achieved superior performance of root mean square error (RMSE), mean absolute error, and glucose-specific RMSE, and obtained the best accuracy for hypoglycemia detection when compared with a group of machine learning baseline methods. Moreover, we performed hardware-in-the-loop in silico trials with 10 virtual T1D adults to test the whole IoMT system with predictive low-glucose management, which significantly reduced hypoglycemia and improved BG control

Effect of discontinuity in threshold distribution on the critical behaviour of a random fiber bundle

The critical behaviour of a Random Fiber Bundle Model with mixed uniform distribution of threshold strengths and global load sharing rule is studied with a special emphasis on the nature of distribution of avalanches for different parameters of the distribution. The discontinuity in the threshold strength distribution of fibers non-trivially modifies the critical stress as well as puts a restriction on the allowed values of parameters for which the recursive dynamics approach holds good. The discontinuity leads to a non-universal behaviour in the avalanche size distribution for smaller values of avalanche size. We observe that apart from the mean field behaviour for larger avalanches, a new behaviour for smaller avalanche size is observed as a critical threshold distribution is approached. The phenomenological understanding of the above result is provided using the exact analytical result for the avalanche size distribution. Most interestingly,the prominence of non-universal behaviour in avalanche size distribution depends on the system parameters.Comment: 6 pages, 4 figures, text and figures modifie

Improvements to the Indiana Geological Survey’s Petroleum Database Management System

This poster was presented at the 2011 Annual Meeting of the American Association of Petroleum Geologists, Eastern Section, in Arlington, Virginia, in September 2011.The Indiana Geological Survey’s Petroleum Database Management System (PDMS) is a web application that provides online access to petroleum-related geological information. Since its debut in 2004, the application has been widely used by the petroleum industry, academia, government agencies, and the general public. On June 6, 2011, a significantly enhanced version of the PDMS went online. New features include a robust search menu that permits elaborate queries of more than 74,000 petroleum wells, rapid and convenient online viewing and downloading of PDF-file well reports and both PDF- and TIFF-file geophysical and other well logs, and streamlined menus for easily accessing extensive well data. An interactive, context-driven web help explains every concept or term used. The PDMS is organized in three main sections. The Well Tables Section includes such information as well location descriptions, completion zones, logs, operators, lease names, tests, reports, hydrocarbon shows, samples, cores, geologic formations and tops, and directional survey data. The Map Viewer Section contains many user-selectable layer options for showing well locations, petroleum fields, producing formations, aerial photographs, and topographic maps. Wells shown in the Map Viewer are hyperlinked to the Well Tables for easy access to the well data. The Fields and Production Section summarizes oil, natural gas, and gas storage field data, including historical oil production volumes in both tables and charts