Acquisitions Driven by Stock Overvaluation

Overvaluation might drive a firm to use its stock to acquire another firm whose stock is not as overpriced. Though hypothetically desirable, these acquisitions create little, if any, value for acquirer shareholders. Two factors impede value creation for acquirer stockholders from these transactions (despite large differences in relative overvaluation at announcement): acquirers paying large premiums to targets, and investors’ correction of acquirer overvaluation during the bid period. Furthermore, acquirer CEOs obtain a large amount of new stock and option grants after acquisitions and realize a net gain in wealth, further suggesting that equity overvaluation increases agency costs and the resulting actions benefit managers more than shareholders (Jensen (2005))

Spin-3/2 baryons from an anisotropic lattice QCD action

The mass spectrum of baryons in the spin-3/2 sector is computed in quenched lattice QCD using a tadpole-improved anisotropic action. Both isospin 1/2 and 3/2 (the traditional decuplet) are considered, as well as members that contain strange quarks. States with positive and negative parities are isolated by parity projection, while states with spin-3/2 and spin-1/2 are separated by spin projection. The extent to which spin projection is needed is examined. The issue of optimal interpolating field is also investigated. The results are discussed in relation to previous calculations and experiment.Comment: modified version to appear in Phys Rev

Käivitus mahepiimakarjakasvatuse rahvusvaheline koostööprojekt

2018. aasta kevadel käivitus ERA-Net CORE Organic Cofund projekt „Uuenduslikud, jätkusuutlikud ja karjatamisel põhinevad piimatootmissüsteemid, mis integreerivad lehmade ja noorloomade koos pidamise (GrazyDaisy)“. Projekti üldine eesmärk on parandada karjamaade kasutamist ning uurida, millised on olnud mahetootjate senised kogemused piimalehmade ja vasikate koos kasvatamisel. Lisaks selgitatakse välja, millised on peamised terviseprobleemid, kuidas loomi ravitakse ja mil moel oleks võimalik ravimite kasutust vähendada. Projektiga kutsutakse liituma mahepiima tootmisega tegelevaid talusid. Kavas on hinnata karjamaade kasutamist, karjatamise korraldust, loomade söötmist jm tegevusi. Praegu püütakse välja selgitada, millised on tootjate huvid ja ideed uuringute läbiviimisel. Projekt kestab 2020. aasta lõpuni ja sellega on seotud 15 partnerit 8 riigist. Projekti toetab Maaeluministeerium

Bayesian Wavelet Estimation of Long Memory Parameter

A Bayesian wavelet estimation method for estimating parameters of a stationary I(d) process is represented as an useful alternative to the existing frequentist wavelet estimation methods. The effectiveness of the proposed method is demonstrated through Monte Carlo simulations. The sampling from the posterior distribution is through the Markov Chain Monte Carlo (MCMC) easily implemented in the WinBUGS software package

The feasibility of utilizing remotely sensed data to assess and monitor oceanic gamefish

There are no author-identified significant results in this report

Application of Deep Learning to Brain Connectivity Classification in Large MRI Datasets

The use of machine learning for whole-brain classification of magnetic resonance imaging (MRI) data is of clear interest, both for understanding phenotypic differences in brain structure and function and for diagnostic applications. Developments of deep learning models in the past decade have revolutionized photographic image and speech recognition, bringing promise to do the same to other fields of science. However, there are many practical and theoretical challenges in the translation of such methods to the unique context of MRIs of the brain. This thesis presents a theoretical underpinning for whole-brain classification of extremely large datasets of multi-site MRIs, including machine learning model architecture, dataset curation methods, machine learning visualization methods, encoding of MRI data, and feature extraction. To replicate large sample sizes typically applied to deep learning models, a dataset of over 50,000 functional and structural MRIs was amassed from nine different databases, and the undertaken analyses were conducted on three covariates commonly found across these collections: sex, resting state/task, and autism spectrum disorder. I find that deep learning is not only a method that has promise for clinical application in the future, but also a powerful statistical tool for analyzing complex, nonlinear relationships in brain data where conventional statistics may fail. However, results are also dependent on factors such as dataset imbalances, confounding factors such as motion and head size, selected methods of encoding MRI data, variability of machine learning models and selected methods of visualizing the machine learning results. In this thesis, I present the following methodological innovations: (1) a method of balancing datasets as a means of regressing out measurable confounding factors; (2) a means of removing spatial biases from deep learning visualization methods; (3) methods of encoding functional and structural datasets as connectivity matrices; (4) the use of ensemble models and convolutional neural network architectures to improve classification accuracy and consistency; (5) adaptation of deep learning visualization methods to study brain connections utilized in the classification process. Additionally, I discuss interpretations, limitations, and future directions of this research.Gates Cambridge Scholarshi

An Assessment Of the EU-Turkey Agreement

Since its origin the European Union has championed refugee law and has been a supporter of human rights throughout the world. However, the EU-Turkey Agreement addressing the European migration crisis has sparked a debate with respect to whether the European Union is upholding its commitment to human rights, or symbolically neglecting its responsibility through its 2016 Agreement with Turkey. The migration crisis has undoubtedly torn at the heart of the members of the European Union and has created hostile tensions among member states that question future freedom of movement between states and, on a larger spectrum, the future of the European Union itself. This paper addresses whether or not the EU-Turkey Agreement is an ethical agreement on behalf of the European Union and assesses whether the European Union should reevaluate the Agreement in order to uphold its commitment to human rights. It concludes, based on the Asylum Procedures Directive of the United Nations Refugee Agency, that Turkey cannot be considered a safe third country and the European Union should rethink its partnership in the migration crisis with Turkey

Hierarchical Estimation of Oceanic Surface Velocity Fields From Satellite Imagery.

Oceanic surface velocity fields are objectively estimated from time-sequential satellite images of sea-surface temperature from the Advanced Very High Resolution Radiometey on board the National Oceanic and Atmospheric Administration\u27s polar orbiters. The hierarchical technique uses the concept of image pyramids and multi-resolution grids for increased computational efficiency. Images are Gaussian filtered and sub-sampled from fine to coarse grid scales. The number of pyramid levels is selected such that the maximum expected velocity in the image results in a displacement of less than one pixel at the coarsest spatial scale. Maximum Cross-Correlation at the sub-pixel level with orthogonal polynomial approximation is used to compute a velocity field at each level of the pyramid which is then iterated assuming a locally linear velocity field. The first image at the next finer level of the pyramid is warped towards the second image by the calculated velocity field. At each succeeding finer grid scale, the velocity field is updated and the process repeated. The final result is an estimated velocity at each pixel at the finest resolution of the imagery. There are no free parameters as used in some gradient-based approaches and the only assumption is that the velocity field is locally linear. Test cases are shown using both simulated and real images with numerically simulated velocity fields which demonstrate the accuracy of the technique. Results are compared to gradient-based techniques using concepts of optical flow and projection onto convex sets and to the standard Maximum Cross-Correlation technique. The hierarchical computations for a real satellite image numerically advected by a rotational sheared flow recover the original field with a rms speed error of 12.6% and direction error of 4.9\sp\circ. Hierarchically-estimated velocity fields from real image pairs are compared to ground-truth estimates of the velocity from satellite-tracked drifters in the eastern Gulf of Mexico. Results indicate the technique underestimates daily mean buoy vector speeds, but with reasonably good direction. The problems of ground truth relations to hierarchically computed flows are discussed with regard to mismatches of time and space scales of measurement

Particle physics methodologies applied to time-of-flight positron emission tomography with silicon-photomultipliers and inorganic scintillators

Positron emission tomography, or PET, is a medical imaging technique which has been used in clinical environments for over two decades. With the advent of fast timing detectors and scintillating crystals, it is possible to envisage improvements to the technique with the inclusion of time-of-flight capabilities. In this context, silicon photomultipliers coupled to fast inorganic LYSO crystals are investigated as a possible technology choice. As part of the ENVISION collaboration a range of photon detectors were investigated experimentally, leading to the selection of specific devices for use in a first prototype detector, currently being commissioned at the Rutherford Appleton Laboratory. In order to characterise the design of the prototype a GEANT4 simulation has been developed describing coupled systems of silicon photomultipliers and LYSO scintillators. Very good agreement is seen between the timing response of the experimental and simulated systems. Results of the simulation for a range of detector array arrangements are presented and a number of optimisations proposed for the final prototype design. Without the results provided here a detector system including only 3x3x5 mm3 crystals would have been adopted. A 3x3x5 mm3 crystal geometry is shown to provide little-to-no timing advantage over an identical system with 3x3x10 mm3 crystals, where detection efficiency is improved by approximately a factor of three. Additionally an investigation is presented which explores the impact of using events where gamma-ray photons are scattered internally within the detector array. It is shown that including such events could increase the signal achievable with one-to-one coupled detector arrays systems for PET by approximately 60%, with only minor reductions in coincidence timing resolution