High-Pressure Micellar Solutions of Polystyrene-block-polybutadiene and Polystyrene-block-polyisoprene in Propane Exhibit Cloud-Pressure Reduction and Distinct Micellization End Points

Micellar solutions of polystyrene-block-polybutadiene and polystyrene-block-polyisoprene in propane are found to exhibit significantly lower cloud pressures than the corresponding hypothetical nonmicellar solutions. Such a cloud-pressure reduction indicates the extent to which micelle formation enhances the apparent diblock solubility in near-critical and hence compressible propane. Concentration-dependent pressure-temperature points beyond which no micelles can be formed, referred to as the micellization end points, are found to depend on the block type, size, and ratio. The cloud-pressure reduction and the micellization end point measured for styrene-diene diblocks in propane should be characteristic of all amphiphilic diblock copolymer solutions that form micelles in compressible solvents.

Sofya: Supporting Rapid Development of Dynamic Program Analyses for Java

Dynamic analysis is an increasingly important means of supporting software validation and maintenance. To date, developers of dynamic analyses have used low-level instrumentation and debug interfaces to realize their analyses. Many dynamic analyses, however, share multiple common high-level requirements, e.g., capture of program data state as well as events, and efficient and accurate event capture in the presence of threading. We present SOFYA – an infra-structure designed to provide high-level, efficient, concurrency-aware support for building analyses that reason about rich observations of program data and events. It provides a layered, modular architecture, which has been successfully used to rapidly develop and evaluate a variety of demanding dynamic program analyses. In this paper, we describe the SOFYA framework, the challenges it addresses, and survey several such analyses.

JVM-based Techniques for Improving Java Observability

Observability measures the support of computer systems to accurately capture, analyze, and present (collectively observe) the internal information about the systems. Observability frameworks play important roles for program understanding, troubleshooting, performance diagnosis, and optimizations. However, traditional solutions are either expensive or coarse-grained, consequently compromising their utility in accommodating today’s increasingly complex software systems. New solutions are emerging for VM-based languages due to the full control language VMs have over program executions. Existing such solutions, nonetheless, still lack flexibility, have high overhead, or provide limited context information for developing powerful dynamic analyses. In this thesis, we present a VM-based infrastructure, called marker tracing framework (MTF), to address the deficiencies in the existing solutions for providing better observability for VM-based languages. MTF serves as a solid foundation for implementing fine-grained low-overhead program instrumentation. Specifically, MTF allows analysis clients to: 1) define custom events with rich semantics ; 2) specify precisely the program locations where the events should trigger; and 3) adaptively enable/disable the instrumentation at runtime. In addition, MTF-based analysis clients are more powerful by having access to all information available to the VM. To demonstrate the utility and effectiveness of MTF, we present two analysis clients: 1) dynamic typestate analysis with adaptive online program analysis (AOPA); and 2) selective probabilistic calling context analysis (SPCC). In addition, we evaluate the runtime performance of MTF and the typestate client with the DaCapo benchmarks. The results show that: 1) MTF has acceptable runtime overhead when tracing moderate numbers of marker events; and 2) AOPA is highly effective in reducing the event frequency for the dynamic typestate analysis; and 3) language VMs can be exploited to offer greater observability.

Process for producing biodiesel fuel with reduced viscosity and a cloud point below thirty-two (32) degrees fahrenheit

Triglycerides are reacted in a liquid phase reaction with methanol and a homogeneous basic catalyst. The reaction yields a spatially separated two phase result with an upper located non-polar phase consisting principally of non-polar methyl esters and a lower located phase consisting principally of glycerol and residual methyl esters. The glycerol phase is passed through a strong cationic ion exchanger to remove anions, resulting in a neutral product which is flashed to remove methanol and which is reacted with isobutylene in the presence of a strong acid catalyst to produce glycerol ethers. The glycerol ethers are then added back to the upper located methyl ethyl ester phase to provide an improved biodiesel fuel.