Role of chloride in hot salt stress-corrosion cracking of titanium-aluminum alloys

Role of chloride in hot salt stress corrosion cracking of titanium-aluminum alloy

The Human Performance Laboratory

No abstract available

Stress corrosion cracking of titanium alloys progress report, apr. 1 - jun. 30, 1964

Hot salt stress corrosion cracking in titanium alloys - chloride corrosion role determination using chlorine isotopes and relation between crack morphology and alloy structur

Comparison of data on Mutation Frequencies of Mice Caused by Radiation - Low Dose Model -

We propose LD(Low Dose) model, the extension of LDM model which was proposed in the previous paper [Y. Manabe et al.: J. Phys. Soc. Jpn. 81 (2012) 104004] to estimate biological damage caused by irradiation. LD model takes account of all the considerable effects including cell death effect as well as proliferation, apoptosis, repair. As a typical example of estimation, we apply LD model to the experiment of mutation frequency on the responses induced by the exposure to low levels of ionizing radiation. The most famous and extensive experiments are those summarized by Russell and Kelly [Russell, W. L. & Kelly, E. M: Proc. Natl Acad. Sci. USA 79 (1982) 539-541], which are known as 'Mega-mouse project'. This provides us with important information of the frequencies of transmitted specific-locus mutations induced in mouse spermatogonia stem-cells. It is found that the numerical results of the mutation frequency of mice are in reasonable agreement with the experimental data: the LD model reproduces the total dose and dose rate dependence of data reasonably. In order to see such dose-rate dependence more explicitly, we introduce the dose-rate effectiveness factor (DREF). This represents a sort of preventable effects such as repair, apoptosis and death of broken cells, which are to be competitive with proliferation effect of broken cells induced by irradiation.Comment: subimitting to J. Phys. Soc. Jpn, 32 pages, 8 figure

Study protocol: The Adherence and Intensification of Medications (AIM) study - a cluster randomized controlled effectiveness study

Abstract Background Many patients with diabetes have poor blood pressure (BP) control. Pharmacological therapy is the cornerstone of effective BP treatment, yet there are high rates both of poor medication adherence and failure to intensify medications. Successful medication management requires an effective partnership between providers who initiate and increase doses of effective medications and patients who adhere to the regimen. Methods In this cluster-randomized controlled effectiveness study, primary care teams within sites were randomized to a program led by a clinical pharmacist trained in motivational interviewing-based behavioral counseling approaches and authorized to make BP medication changes or to usual care. This study involved the collection of data during a 14-month intervention period in three Department of Veterans Affairs facilities and two Kaiser Permanente Northern California facilities. The clinical pharmacist was supported by clinical information systems that enabled proactive identification of, and outreach to, eligible patients identified on the basis of poor BP control and either medication refill gaps or lack of recent medication intensification. The primary outcome is the relative change in systolic blood pressure (SBP) measurements over time. Secondary outcomes are changes in Hemoglobin A1c, low-density lipoprotein cholesterol (LDL), medication adherence determined from pharmacy refill data, and medication intensification rates. Discussion Integration of the three intervention elements - proactive identification, adherence counseling and medication intensification - is essential to achieve optimal levels of control for high-risk patients. Testing the effectiveness of this intervention at the team level allows us to study the program as it would typically be implemented within a clinic setting, including how it integrates with other elements of care. Trial Registration The ClinicalTrials.gov registration number is NCT00495794.http://deepblue.lib.umich.edu/bitstream/2027.42/78258/1/1745-6215-11-95.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78258/2/1745-6215-11-95.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78258/3/1745-6215-11-95-S1.DOCPeer Reviewe

Unsupervised machine learning of integrated health and social care data from the Macmillan Improving the Cancer Journey service in Glasgow

Background: Improving the Cancer Journey (ICJ) was launched in 2014 by Glasgow City Council and Macmillan Cancer Support. As part of routine service, data is collected on ICJ users including demographic and health information, results from holistic needs assessments and quality of life scores as measured by EQ-5D health status. There is also data on the number and type of referrals made and feedback from users on the overall service. By applying artificial intelligence and interactive visualization technologies to this data, we seek to improve service provision and optimize resource allocation.Method: An unsupervised machine-learning algorithm was deployed to cluster the data. The classical k-means algorithm was extended with the k-modes technique for categorical data, and the gap heuristic automatically identified the number of clusters. The resulting clusters are used to summarize complex data sets and produce three-dimensional visualizations of the data landscape. Furthermore, the traits of new ICJ clients are predicted by approximately matching their details to the nearest existing cluster center.Results: Cross-validation showed the model’s effectiveness over a wide range of traits. For example, the model can predict marital status, employment status and housing type with an accuracy between 2.4 to 4.8 times greater than random selection. One of the most interesting preliminary findings is that area deprivation (measured through Scottish Index of Multiple Deprivation-SIMD) is a better predictor of an ICJ client’s needs than primary diagnosis (cancer type).Conclusion: A key strength of this system is its ability to rapidly ingest new data on its own and derive new predictions from those data. This means the model can guide service provision by forecasting demand based on actual or hypothesized data. The aim is to provide intelligent person-centered recommendations. The machine-learning model described here is part of a prototype software tool currently under development for use by the cancer support community.Disclosure: Funded by Macmillan Cancer Support</p

Evolution of electronic and ionic structure of Mg-clusters with the growth cluster size

The optimized structure and electronic properties of neutral and singly charged magnesium clusters have been investigated using ab initio theoretical methods based on density-functional theory and systematic post-Hartree-Fock many-body perturbation theory accounting for all electrons in the system. We have systematically calculated the optimized geometries of neutral and singly charged magnesium clusters consisting of up to 21 atoms, electronic shell closures, binding energies per atom, ionization potentials and the gap between the highest occupied and the lowest unoccupied molecular orbitals. We have investigated the transition to the hcp structure and metallic evolution of the magnesium clusters, as well as the stability of linear chains and rings of magnesium atoms. The results obtained are compared with the available experimental data and the results of other theoretical works.Comment: 30 pages, 10 figures, 3 table

ChlVPP combination chemotherapy for Hodgkin's disease: long-term results.

Two hundred and eighty-four patients with advanced Hodgkin's disease (HD) (stage II with poor prognostic features and stage III/IV) have been treated with the ChlVPP combination chemotherapy regimen (chlorambucil, vinblastine, procarbazine and prednisolone) in a single-centre unselected series. Median follow up is 92 months. Fifty-five patients had previously received radiotherapy but none had received previous chemotherapy. Eighty-five per cent of previously untreated patients and 91% of previously irradiated patients entered complete remission (CR); 71% and 68% of these respectively remain in CR at 10 years and 65% and 64% of each group respectively are alive at 10 years. On univariate analysis, age, stage, site of visceral disease and lymphocyte count predicted survival and on multivariate analysis age, absence of symptoms, absence of lung, liver or bone marrow disease and achieving a CR remained important predictors of survival. Acute toxicity was mild. The 10 year actuarial risk of acute leukaemia was 2.7%. This study adds further support to the view that chlorambucil is as effective and less toxic than mustine in combination chemotherapy for HD. We suggest that MOPP chemotherapy is no longer routinely indicated for HD

SREBP1c-CRY1 signalling represses hepatic glucose production by promoting FOXO1 degradation during refeeding

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