Characterizing Wood Components as Network Polymers by Dynamic Mechanical Analysis

The characterization of structure-property relationships in wood components, such as lignin, is a critical aspect of utilization. This point has been emphasized recently with concerns directed toward the application of natural products as wood bonding agents. Dynamic mechanical analysis is a valuable technique for the study of these relations because of its sensitivity to variations in polymer structure

Indentation and self-healing mechanisms of a self-assembled monolayer:a combined experimental and modeling study

A combination of in situ vibrational sum-frequency generation (SFG) spectroscopy and molecular-dynamics (MD) simulations has allowed us to study the effects of indentation of self-assembled octadecylphosphonic acid (ODPA) monolayers on α-Al2O3(0001). Stress-induced changes in the vibrational signatures of C–H stretching vibrations in SFG spectra and the results of MD simulations provide clear evidence for an increase in gauche-defect density in the monolayer as a response to indentation. A stress-dependent analysis indicates that the defect density reaches saturation at approximately 155 MPa. After stress is released, the MD simulations show an almost instantaneous healing of pressure-induced defects in good agreement with experimental results. The lateral extent of the contact areas was studied with colocalized SFG spectroscopy and compared to theoretical predictions for pressure gradients from Hertzian contact theory. SFG experiments reveal a gradual increase in gauche-defect density with pressure before saturation close to the contact center. Furthermore, our MD simulations show a spatial anisotropy of pressure-induced effects within ODPA domains: molecules tilted in the direction of the pressure gradient increase in tilt angle while those on the opposite side form gauche-defects

Results of Aortocoronary Bypass Surgery for Angina Pectoris

To determine the relative risks and benefits of coronary bypass surgery for angina pectoris, we examined the results in our first consecutive 360 patients operated upon between May 1970 and December 1975. The age range was 27 to 75 years; there were 309 males and 51 females. The patients were classified clinically as having stable angina in 119 cases (33%), unstable angina in 205 cases (57%) and preinfarction angina in 36 cases (10%). Unstable angina was defined as a definite recent increase in severity or frequency of chest pain, angina at rest or nocturnal angina. Preinfarction angina was defined as a syndrome of prolonged angina, poorly controlled by nitrites, occurring at rest with typical ECG changes of ischemia. Such patients underwent observation in the Coronary Intensive Care Unit followed by emergency arteriography and surgery, usually within 24 hours

Value-Compressed Sparse Column (VCSC): Sparse Matrix Storage for Redundant Data

Compressed Sparse Column (CSC) and Coordinate (COO) are popular compression formats for sparse matrices. However, both CSC and COO are general purpose and cannot take advantage of any of the properties of the data other than sparsity, such as data redundancy. Highly redundant sparse data is common in many machine learning applications, such as genomics, and is often too large for in-core computation using conventional sparse storage formats. In this paper, we present two extensions to CSC: (1) Value-Compressed Sparse Column (VCSC) and (2) Index- and Value-Compressed Sparse Column (IVCSC). VCSC takes advantage of high redundancy within a column to further compress data up to 3-fold over COO and 2.25-fold over CSC, without significant negative impact to performance characteristics. IVCSC extends VCSC by compressing index arrays through delta encoding and byte-packing, achieving a 10-fold decrease in memory usage over COO and 7.5-fold decrease over CSC. Our benchmarks on simulated and real data show that VCSC and IVCSC can be read in compressed form with little added computational cost. These two novel compression formats offer a broadly useful solution to encoding and reading redundant sparse data