Potassium Relationships of Three Ohio Soils

Author Institution: The Ohio State University Agricultural Technical Institute; Department of Agronomy, The Ohio State UniversityThree Ohio soils, Hoytville clay, Brookston silty clay loam, and Wooster silt loam located at various branches of the Ohio Agricultural Research and Development Center, were studied. Bulk samples from each horizon were tested for exchangeable basic cations, pH, sulfuric acid extractable potassium (K+), and particle-size distribution. The surface horizons of each soil were characterized by measurement of cation exchange capacity, quantity-intensity adsorption isotherms for K+ and x-ray diffraction of the clay ( times greater than that for Wooster. Hoytville clay was predominantly illitic while the Brookston and Wooster clays were of a more mixed mineralogical nature. The potassium content and crystallinity of the illite in the Hoytville clay is lower than those of the Brookston and Wooster clays

Multicolor Polarimetry of Selected Be Stars: 1995-98

A new polarimeter called AnyPol has been used at Limber Observatory for four years to annually monitor the broadband linear polarization of a sample of bright northern Be stars. This is the fourth report on a program started in 1985 at McDonald Observatory and the first one to come entirely from the new installation. Although no variability was detected at the 3-sigma level during the current reporting period, analysis of the full 13-year data set is beginning to reveal hints of long-term variability that may provide clues for understanding the Be phenomenon.Comment: 25 pages including 17 tables; 17 figures; aaspp4 style; accepted by PAS

Isometric hip and knee torque measurements as an outcome measure in robot assisted gait training

Strength changes in lower limb muscles following robot assisted gait training (RAGT) in subjects with incomplete spinal cord injury (ISCI) has not been quantified using objective outcome measures. To record changes in the force generating capacity of lower limb muscles (recorded as peak voluntary isometric torque at the knee and hip), before, during and after RAGT in both acute and subacute/chronic ISCI subjects using a repeated measures study design. Eighteen subjects with ISCI participated in this study (Age range: 26–63 years mean age = 49.3 ± 11 years). Each subject participated in the study for a total period of eight weeks, including 6 weeks of RAGT using the Lokomat system (Hocoma AG, Switzerland). Peak torques were recorded in hip flexors, extensors, knee flexors and extensors using torque sensors that are incorporated within the Lokomat. All the tested lower limb muscle groups showed statistically significant (p < 0.001) increases in peak torques in the acute subjects. Comparison between the change in peak torque generated by a muscle and its motor score over time showed a non-linear relationship. The peak torque recorded during isometric contractions provided an objective outcome measure to record changes in muscle strength following RAGT

Defining clinical subtypes of adult asthma using electronic health records : analysis of a large UK primary care database with external validation

Acknowledgments EMFH was supported by a Medical Research Council PhD Studentship (eHERC/Farr). This work is carried out with the support of the Asthma UK Centre for Applied Research [AUKAC-2012-01] and Health Data Research UK which receives its funding from HDR UK Ltd (HDR-5012) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and the Wellcome Trust. The funders had no role in the study and the decision to submit this work to be considered for publication. This Project is based in part/wholly on Data from the Optimum Patient Care Research Database (opcrd.co.uk) obtained under licence from Optimum Patient Care Limited and its execution is approved by recognised experts affiliated to the Respiratory Effectiveness Group. However, the interpretation and conclusion contained in this report are those of the author/s alone. This study makes use of anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. We would like to acknowledge all the data providers who make anonymised data available for research. SAIL is not responsible for the interpretation of these data.Peer reviewedPublisher PD

Logistic model tree extraction from artificial neural networks

Artificial neural networks (ANNs) are a powerful and widely used pattern recognition technique. However, they remain “black boxes” giving no explanation for the decisions they make. This paper presents a new algorithm for extracting a logistic model tree (LMT) from a neural network, which gives a symbolic representation of the knowledge hidden within the ANN. Landwehr’s LMTs are based on standard decision trees, but the terminal nodes are replaced with logistic regression functions. This paper reports the results of an empirical evaluation that compares the new decision tree extraction algorithm with Quinlan’s C4.5 and ExTree. The evaluation used 12 standard benchmark datasets from the University of California, Irvine machine-learning repository. The results of this evaluation demonstrate that the new algorithm produces decision trees that have higher accuracy and higher fidelity than decision trees created by both C4.5 and ExTree

Decision tree extraction from trained neural networks

Artificial Neural Networks (ANNs) have proved both a popular and powerful technique for pattern recognition tasks in a number of problem domains. However, the adoption of ANNs in many areas has been impeded, due to their inability to explain how they came to their conclusion, or show in a readily comprehendible form the knowledge they have obtained. This paper presents an algorithm that addresses these problems. The algorithm achieves this by extracting a Decision Tree, a graphical and easily understood symbolic representation of a decision process, from a trained ANN. The algorithm does not make assumptions about the ANN’s architecture or training algorithm; therefore, it can be applied to any type of ANN. The algorithm is empirically compared with Quinlan’s C4.5 (a common Decision Tree induction algorithm) using standard benchmark datasets. For most of the datasets used in the evaluation, the new algorithm is shown to extract Decision Trees that have a higher predictive accuracy than those induced using C4.5 directly

Two-Dimensional Electronic Structure of the GaAs(110)-Bi System

The occupied electronic structure of the GaAs(110)-Bi(1×1) monolayer system has been studied using angle-resolved photoelectron spectroscopy with a synchrotron-radiation source. The overlayer system possesses at least three detectable surface states (S’, S’’ and S’’’) with two-dimensional character. Both the state with the lowest (S’) and the state with the highest (S’’’) binding energy are clearly visible over a large portion of the (1×1) surface Brillouin zone. The intermediate state (S’’) was observed along Γ¯ X¯ ’ and also in the neighborhood of X¯. The intensity of all three states exhibits a predominantly pz-like dependence on the polarization of the synchrotron light. However, S’’’ possesses a greater component of pxy-like character than either S’ or S’’. At the zone center, S’ is situated 0.5 eV above the valence-band maximum, and it disperses downwards by ≊1.0 eV to X¯, and by ≊0.8 eV to X¯ ’. At M¯ it has its binding-energy maximum, 1.3 eV below the energetic position at Γ¯. The two-dimensional electronic structure of this system is compared with that of the closely related GaAs(110)-Sb(1×1) monolayer system and with the results of first-principles calculations