Thermodynamic properties of liquid metals

Technique for determining heats of fusion and heat capacities of liquid metals at high temperatur

Thermodynamic property determination in low gravity

Techniques for determining heat capacities and other properties of molten metals were investigated and critically evaluated. Precisely determining heat capacities calorimetrically in space poses several problems. The weight of a drop calorimeter block along with the necessity of obtaining a large number of data points tend to make traditional approaches appear infeasible. However, for many substances exhibiting sufficiently high thermal conductivities and with known emissivities, it appears possible to investigate their properties by observing the rate of cooling of a levitated sphere which is initially at a uniform temperature above the melting point. A special advantage of the levitation method is that considerable supercooling is expected, making the study of the heat capacities of molten metals both above and below their melting points possible

Matrix isolation as a tool for studying interstellar chemical reactions

Since the identification of the OH radical as an interstellar species, over 50 molecular species were identified as interstellar denizens. While identification of new species appears straightforward, an explanation for their mechanisms of formation is not. Most astronomers concede that large bodies like interstellar dust grains are necessary for adsorption of molecules and their energies of reactions, but many of the mechanistic steps are unknown and speculative. It is proposed that data from matrix isolation experiments involving the reactions of refractory materials (especially C, Si, and Fe atoms and clusters) with small molecules (mainly H2, H2O, CO, CO2) are particularly applicable to explaining mechanistic details of likely interstellar chemical reactions. In many cases, matrix isolation techniques are the sole method of studying such reactions; also in many cases, complexations and bond rearrangements yield molecules never before observed. The study of these reactions thus provides a logical basis for the mechanisms of interstellar reactions. A list of reactions is presented that would simulate interstellar chemical reactions. These reactions were studied using FTIR-matrix isolation techniques

Efficiency of TTAC's ORTEC IDM

ORNL's Technical Testing and Analysis Center (TTAC) acquired a High Purity Germanium Detector (HPGe) from ORTEC - a variant called an Interchangeable Detection Module (IDM). This detector has excellent energy resolution as well as high intrinsic efficiency. The purpose of this report is to detail the determination of the efficiency curve of the IDM, so future measurements can quantify the (otherwise unknown) activity of sources. Without such a curve, the activity cannot be directly reported by use of the IDM alone - a separate device such as an ion chamber would be required. This builds upon the capability of TTAC. The method for determining the energy-dependent intrinsic efficiency is laid-out in this report. It's noteworthy that this basic technique can be applied to any spectroscopic radiation detector, independent of the specific type (e.g. NaI, CzT, ClYC)

Materials science experiments in space

The criteria for the selection of the experimental areas and individual experiments were that the experiment or area must make a meaningful contribution to the field of material science and that the space environment was either an absolute requirement for the successful execution of the experiment or that the experiment can be more economically or more conveniently performed in space. A number of experimental areas and individual experiments were recommended for further consideration as space experiments. Areas not considered to be fruitful and others needing additional analysis in order to determine their suitability for conduct in space are also listed. Recommendations were made concerning the manner in which these materials science experiments are carried out and the related studies that should be pursued

Sublimation Pressures of Refractory Fluorides

Vapor species identification, absolute vapor pressures and heats of sublimation of refractory metal fluoride

Validation of a 22-Gene Genomic Classifier in Patients With Recurrent Prostate Cancer An Ancillary Study of the NRG/RTOG 9601 Randomized Clinical Trial

IMPORTANCE: Decipher (Decipher Biosciences Inc) is a genomic classifier (GC) developed to estimate the risk of distant metastasis (DM) after radical prostatectomy (RP) in patients with prostate cancer. OBJECTIVE: To validate the GC in the context of a randomized phase 3 trial. DESIGN, SETTING, AND PARTICIPANTS: This ancillary study used RP specimens from the phase 3 placebo-controlled NRG/RTOG 9601 randomized clinical trial conducted from March 1998 to March 2003. The specimens were centrally reviewed, and RNA was extracted from the highest-grade tumor available in 2019 with a median follow-up of 13 years. Clinical-grade whole transcriptomes from samples passing quality control were assigned GC scores (scale, 0-1). A National Clinical Trials Network–approved prespecified statistical plan included the primary objective of validating the independent prognostic ability of GC for DM, with secondary end points of prostate cancer–specific mortality (PCSM) and overall survival (OS). Data were analyzed from September 2019 to December 2019. INTERVENTIONS: Salvage radiotherapy (sRT) with or without 2 years of bicalutamide. MAIN OUTCOMES AND MEASURES: The preplanned primary end point of this study was the independent association of the GC with the development of DM. RESULTS: In this ancillary study of specimens from a phase 3 randomized clinical trial, GC scores were generated from 486 of 760 randomized patients with a median follow-up of 13 years; samples from a total of 352 men (median [interquartile range] age, 64.5 (60-70) years; 314 White [89.2%] participants) passed microarray quality control and comprised the final cohort for analysis. On multivariable analysis, the GC (continuous variable, per 0.1 unit) was independently associated with DM (hazard ratio [HR], 1.17; 95% CI, 1.05-1.32; P = .006), PCSM (HR, 1.39; 95% CI, 1.20-1.63; P < .001), and OS (HR, 1.17; 95% CI, 1.06-1.29; P = .002) after adjusting for age, race/ethnicity, Gleason score, T stage, margin status, entry prostate-specific antigen, and treatment arm. Although the original planned analysis was not powered to detect a treatment effect interaction by GC score, the estimated absolute effect of bicalutamide on 12-year OS was less when comparing patients with lower vs higher GC scores (2.4% vs 8.9%), which was further demonstrated in men receiving early sRT at a prostate-specific antigen level lower than 0.7 ng/mL (−7.8% vs 4.6%). CONCLUSIONS AND RELEVANCE: This ancillary validation study of the Decipher GC in a randomized trial cohort demonstrated association of the GC with DM, PCSM, and OS independent of standard clinicopathologic variables. These results suggest that not all men with biochemically recurrent prostate cancer after surgery benefit equally from the addition of hormone therapy to sRT. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT0000287

Accurate peak list extraction from proteomic mass spectra for identification and profiling studies

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry is an essential technique in proteomics both to identify the proteins of a biological sample and to compare proteomic profiles of different samples. In both cases, the main phase of the data analysis is the procedure to extract the significant features from a mass spectrum. Its final output is the so-called peak list which contains the mass, the charge and the intensity of every detected biomolecule. The main steps of the peak list extraction procedure are usually preprocessing, peak detection, peak selection, charge determination and monoisotoping operation.</p> <p>Results</p> <p>This paper describes an original algorithm for peak list extraction from low and high resolution mass spectra. It has been developed principally to improve the precision of peak extraction in comparison to other reference algorithms. It contains many innovative features among which a sophisticated method for managing the overlapping isotopic distributions.</p> <p>Conclusions</p> <p>The performances of the basic version of the algorithm and of its optional functionalities have been evaluated in this paper on both SELDI-TOF, MALDI-TOF and ESI-FTICR ECD mass spectra. Executable files of MassSpec, a MATLAB implementation of the peak list extraction procedure for Windows and Linux systems, can be downloaded free of charge for nonprofit institutions from the following web site: <url>http://aimed11.unipv.it/MassSpec</url></p

Signal Processing for NDE

Nowadays, testing and evaluating of industrial equipment using nondestructive tests, is a fundamental step in the manufacturing process. The complexity and high costs of manufacturing industrial components, require examinations in some way about the quality and reliability of the specimens. However, it should be noted, that in order to accurately perform the nondestructive test, in addition to theoretical knowledge, it is also essential to have the experience and carefulness, which requires special courses and experience with theoretical education. Therefore, in the traditional methods, which are based on manual testing techniques and the test results depend on the operator, there is the possibility of an invalid inference from the test data. In other words, the accuracy of conclusion from the obtained data is dependent on the skill and experience of the operator. Thus, using the signal processing techniques for nondestructive evaluation (NDE), it is possible to optimize the methods of nondestructive inspection, and in other words, to improve the overall system performance, in terms of reliability and system implementation costs. In recent years, intelligent signal processing techniques have had a significant impact on the progress of nondestructive assessment. In other words, by automating the processing of nondestructive data and signals, and using the artificial intelligence methods, it is possible to optimize nondestructive inspection methods. Hence, improve overall system performance in terms of reliability and Implementation costs of the system. This chapter reviews the issues of intelligent processing of nondestructive testing (NDT) signals