Limitations on the extent of off-center displacements in TbMnO3 from EXAFS measurements

We present EXAFS data at the Mn K and Tb L3 edges that provide upper limits on the possible displacements of any atoms in TbMnO3. The displacements must be less than 0.005-0.01A for all atoms which eliminates the possibility of moderate distortions (0.02A) with a small c-axis component, but for which the displacements in the ab plane average to zero. Assuming the polarization arises from a displacement of the O2 atoms along the c-axis, the measured polarization then leads to an O2 displacement that is at least 6X10^{-4}A, well below our experimental limit. Thus a combination of the EXAFS and the measured electrical polarization indicate that the atomic displacements likely lie in the range 6X10^{-4} - 5X10^{-3}A.Comment: submitted to PRB; 11 pages (preprint form) 7 figure

Corporate Boards and Ownership Structure as Antecedents of Corporate Governance Disclosure in Saudi Arabian Publicly Listed Corporations

We investigate whether and to what extent publicly listed corporations voluntarily comply with and disclose recommended good corporate governance (CG) practices, and distinctively examine whether the observed cross-sectional differences in such CG disclosures can be explained by ownership and board mechanisms with specific focus on Saudi Arabia. Our results suggest that corporations with larger boards, a big-four auditor, higher government ownership, a CG committee and higher institutional ownership disclose considerably more than those that are not. By contrast, we find that an increase in block ownership significantly reduces CG disclosure. Our results are generally robust to a number of econometric models that control for different types of disclosure indices, firm-specific characteristics and firm-level fixed-effects. Our results have important implications for policy-makers, practitioners and regulatory authorities, especially those in developing countries across the globe

An Alternative Technique for Immediate Direct-to-Implant Breast Reconstruction-A Case Series

BACKGROUND: The practice of breast reconstruction continues to evolve with the introduction of new technologies. The authors describe a unique approach allowing immediate direct-to-implant reconstruction that can be performed on an outpatient basis. METHODS: After a nipple-sparing mastectomy, acellular dermal matrix (ADM)-covered implants are placed in a prepectoral position in an immediate reconstruction. Assessment of results was performed via a retrospective review of demographic and procedural data. RESULTS: Forty-five patients (79 breasts), mean age 46.8 years, were treated with direct-to-implant reconstruction using ADM-wrapped implants placed above the muscle with mean follow-up of 23.1 months (median 22 mo). Mean body mass index was 24.3, and 15 patients (33.3%) were current or former smokers. Twenty-seven patients (60%) had prior breast surgery with 22 (49%) exposed to chemotherapy and 34 (76%) radiation. Procedure time averaged 155 minutes and hospital length of stay averaged 0.6 days. Complications included flap necrosis in 22 cases (28%), seroma in 12 (15%), infection in 8 (10%), rippling in 28 (35%), and contracture in 8 (10%). In 14 breasts (18%), postoperative wound complications (flap necrosis or infection) led to implant loss. CONCLUSIONS: The availability of ADM and cohesive gel implants has allowed us to perform above-the-muscle implant breast reconstruction in reduced time and often on an outpatient basis. Complication rates were comparable to expected results of standard expander-to-implant, staged breast reconstruction. This technique is a viable option delivering clinically and aesthetically acceptable results in select patients

Utilization of Surplus Milk in the Small Dairy Plant: 4. Stirred Curd Types of Cheese

In this series of publications an effort is made to describe how a variety of products can be prepared in plants where surplus milk is a problem. Each type of product is described in detail, methods of manufacturing are outlined, and the equipment and supplies needed are listed. As far as possible similar equipment is used for several products. In this publication the preparation of a group of stirred curd types of cheese is presented

An evaluation: The potential of discarded tires as a source of fuel

The destructive distillation of rubber tire samples was studied by thermogravimetry, differential scanning calorimetry, combustion calorimetry, and mass spectroscopy. The decomposition reaction was found to be exothermic and produced a mass loss of 65 percent. The gas evolution curves that were obtained indicate that a variety of organic materials are evolved simultaneously during the decomposition of the rubber polymer

An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths

A chordless cycle (induced cycle) $C$ of a graph is a cycle without any chord, meaning that there is no edge outside the cycle connecting two vertices of the cycle. A chordless path is defined similarly. In this paper, we consider the problems of enumerating chordless cycles/paths of a given graph $G=(V,E),$ and propose algorithms taking $O(|E|)$ time for each chordless cycle/path. In the existing studies, the problems had not been deeply studied in the theoretical computer science area, and no output polynomial time algorithm has been proposed. Our experiments showed that the computation time of our algorithms is constant per chordless cycle/path for non-dense random graphs and real-world graphs. They also show that the number of chordless cycles is much smaller than the number of cycles. We applied the algorithm to prediction of NMR (Nuclear Magnetic Resonance) spectra, and increased the accuracy of the prediction

Evaluation of support vector machine based forecasting tool in electricity price forecasting for Australian national electricity market participants

In this paper we present an analysis of the results of a study into wholesale (spot) electricity price forecasting utilising Neural Networks (NNs) and Support Vector Machines (SVM). Frequent regulatory changes in electricity markets and the quickly evolving market participant pricing (bidding) strategies cause efficient retraining to be crucial in maintaining the accuracy of electricity price forecasting models. The efficiency of NN and SVM retraining for price forecasting was evaluated using Australian National Electricity Market (NEM), New South Wales regional data over the period from September 1998 to December 1998. The analysis of the results showed that SVMs with one unique solution, produce more consistent forecasting accuracies and so require less time to optimally train than NNs which can result in a solution at any of a large number of local minima. The SVM and NN forecasting accuracies were found to be very similar

Evaluation Of Support Vector Machine Based Forecasting Tool In Electricity Price Forecasting For Australian National Electricity Market Participants

In this paper, we present an analysis of the results of a study into wholesale (spot) electricity price forecasting utilising Neural Networks (NNs) and Support Vector Machines (SVM). Frequent regulatory changes in electricity markets and the quickly evolving market participant pricing (bidding) strategies cause efficient retraining to be crucial in maintaining the accuracy of electricity price forecasting models. The efficiency of NN and SVM retraining for price forecasting was evaluated using Australian National Electricity Market (NEM), New South Wales regional data over the period from September 1998 to December 1998. The analysis of the results showed that SVMs with one unique solution, produce more consistent forecasting accuracies and so require less time to optimally train than NNs, which can result in a solution at any of a large number of local minima. The SVM and NN forecasting accuracies were found to be very similar