A Statistical Study of a Heech-maple Association at Turkey Run State Park

In 1928 Braun-Blanquet and Pavillard (1) published the Vocabulaire de Sociologie Végétale, in which an attempt was made to define and standardize the various current concepts relating to descriptive phytosociology. Since the continental concepts vary somewhat from those of American workers, the terminology differs slightly. The terms relating to the organization of any plant community are, according to them, arranged in a sociological Reléve or floristic enumeration in which each species of plant is given with the coefficient or number corresponding to the class to which it belongs in the analytical or synthetic concepts

Chlorophyll therapy and its relation to pathogenic bacteria

Although the green parts of plants have been used in the treatment of various diseases for many centuries, it was not until the scientific investigations of Willstaetter and Stoll in 1913 that actual proof of the worth of such remedies began to be found. The close similarity of the chemical character of the chlorophylls found in the chloroplasts of green plants to that of the hemoglobin in human blood led to the theory that the chlorophylls might be the factors in green plants which give them therapeutic value, so a great deal of scientific investigation has been undertaken in laboratories, hospitals and in the private practices of many physicians to determine the efficacy of chlorophyll therapy

Book Reviews 22-24

Various book reviews by various contributor

Learning-based Robust Model Predictive Control for Sector-bounded Lur'e Systems

For dynamical systems with uncertainty, robust controllers can be designed by assuming that the uncertainty is bounded. The less we know about the uncertainty in the system, the more conservative the bound must be, which in turn may lead to reduced control performance. If measurements of the uncertain term are available, this data may be used to reduce the uncertainty in order to make bounds as tight as possible. In this paper, we consider a linear system with a sector-bounded uncertainty. We develop a model predictive control algorithm to control the system, and use a weighted Bayesian linear regression model to learn the least conservative sector condition using measurements collected in closed-loop. The resulting robust model predictive control algorithm therefore reduces the conservativeness of the controller, and provides probabilistic guarantees of asymptotic stability and constraint satisfaction. The efficacy of the proposed method is shown in simulation.publishedVersio

A Levenberg-Marquardt Algorithm for Sparse Identification of Dynamical Systems

Low complexity of a system model is essential for its use in real-time applications. However, sparse identification methods commonly have stringent requirements that exclude them from being applied in an industrial setting. In this article, we introduce a flexible method for the sparse identification of dynamical systems described by ordinary differential equations. Our method relieves many of the requirements imposed by other methods that relate to the structure of the model and the dataset, such as fixed sampling rates, full state measurements, and linearity of the model. The Levenberg-Marquardt algorithm is used to solve the identification problem. We show that the Levenberg-Marquardt algorithm can be written in a form that enables parallel computing, which greatly diminishes the time required to solve the identification problem. An efficient backward elimination strategy is presented to construct a lean system model.publishedVersio

Role of Brachytherapy in the Postoperative Management of Endometrial Cancer: Decision-Making Analysis among Experienced European Radiation Oncologists.

BACKGROUND There are various society-specific guidelines addressing adjuvant brachytherapy (BT) after surgery for endometrial cancer (EC). However, these recommendations are not uniform. Against this background, clinicians need to make decisions despite gaps between best scientific evidence and clinical practice. We explored factors influencing decision-making for adjuvant BT in clinical routine among experienced European radiation oncologists in the field of gynaecological radiotherapy (RT). We also investigated the dose and technique of BT. METHODS Nineteen European experts for gynaecological BT selected by the Groupe Européen de Curiethérapie and the European Society for Radiotherapy & Oncology provided their decision criteria and technique for postoperative RT in EC. The decision criteria were captured and converted into decision trees, and consensus and dissent were evaluated based on the objective consensus methodology. RESULTS The decision criteria used by the experts were tumour extension, grading, nodal status, lymphovascular invasion, and cervical stroma/vaginal invasion (yes/no). No expert recommended adjuvant BT for pT1a G1-2 EC without substantial LVSI. Eighty-four percent of experts recommended BT for pT1a G3 EC without substantial LVSI. Up to 74% of experts used adjuvant BT for pT1b LVSI-negative and pT2 G1-2 LVSI-negative disease. For 74-84% of experts, EBRT + BT was the treatment of choice for nodal-positive pT2 disease and for pT3 EC with cervical/vaginal invasion. For all other tumour stages, there was no clear consensus for adjuvant treatment. Four experts already used molecular markers for decision-making. Sixty-five percent of experts recommended fractionation regimens of 3 × 7 Gy or 4 × 5 Gy for BT as monotherapy and 2 × 5 Gy for combination with EBRT. The most commonly used applicator for BT was a vaginal cylinder; 82% recommended image-guided BT. CONCLUSIONS There was a clear trend towards adjuvant BT for stage IA G3, stage IB, and stage II G1-2 LVSI-negative EC. Likewise, there was a non-uniform pattern for BT dose prescription but a clear trend towards 3D image-based BT. Finally, molecular characteristics were already used in daily decision-making by some experts under the pretext that upcoming trials will bring more clarity to this topic

Study of vector mesons in dimuon production in a large kinematic region in p-W and S-W interactions at 200 GeV/c/nucleon

Results are presented on $\rho+\omega$, $\phi$ and $J/\Psi$ production in p--W and $^{32}$S--W interactions at 200~GeV/c/nucleon measured via the dimuon decay in a large kinematic region. The data are normalized to the charged particle multiplicity in the same rapidity interval. They have been %CORR 1 obtained collected using the HELIOS/3 muon spectrometer at the CERN SPS. %CORR 2 and The ratio $\phi/{(\rho+\omega)}$ increases between proton and sulphur projectiles, and is further enhanced going from peripheral to central nucleus-nucleus interactions. This results from an increase in the number of produced $\phi$'s per charged particle. The increase in the ratio $\phi/{(\rho+\omega)}$ is not clearly dependent on p$_T$, but appears larger at higher rapidities, due to kinematic effects %CORR 3 and in conjunction with varying acceptance. $J/\Psi$ production, likewise normalized to charged multiplicity, is significantly lower in S--W compared to p--W interactions

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes