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

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

Ground Waves Generated by Pile Driving, and Structural Interaction

Pre-formed steel or concrete pile elements are installed by high energy impact or vibro-driver, which causes outgoing ground waves. In severe cases, adjacent buildings are at risk of damage. Assessment of risk is conventionally by reference to threshold limits of vibration. The global approach considers neither the interactive effects between ground and structure, nor frequency and duration. Here, firstly, the dynamics of a pile head impact and of the transmission of a portion of the energy into the ground were modelled by a combination of finite elements (FE), springs and dashpots. The boundary disturbances were then applied to a second model of the soil as an elastic half space. This outer model was constructed of axisymmetric finite and infinite elements for calibration against on-site measurements. The infinite elements (IE) represented a wider zone, and avoided spurious wave reflections at boundaries. Next, the verified ground disturbances adjacent to the pile were used as input to a three-dimensional FE/IE wedge-shaped model of a ‘slice’ of the axisymmetric system. Various structural forms, of steel frame structures and of brick walls, were added, giving a dynamic soil-structure analysis. Results show the responses of flexible and stiff structures to outgoing waves caused by impact pile driving and vibro-driving

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

Comparison of the RNA-amplification based methods RT–PCR and NASBA for the detection of circulating tumour cells

Increasingly, reverse transcriptase polymerase chain reaction (RT–PCR) is used to detect clinically significant tumour cells in blood or bone marrow. This may result in a redefinition of disease-free and clinical relapse. However, its clinical utility may be limited by lack of automation or reproducibility. Recent studies have suggested nucleic acid sequence-based amplification of target RNA may be more robust. In this study, nucleic acid sequence-based amplification was established to detect melanoma, colorectal and prostate cancer cells. Nucleic acid sequence-based amplification and RT–PCR both successfully amplified target RNA in peripheral blood samples from patients with melanoma and colorectal cancer, but only RT–PCR detected PSA in blood samples from patients with prostate cancer. There was relatively good agreement between sample replicates analyzed by RT–PCR (Kappa values of one for tyrosinase, 0.67 for CK-20 and one for PSA), but less agreement when analyzed by nucleic acid sequence-based amplification. This may limit the routine use of NASBA for the detection of clinically significant disease. In summary, RT–PCR appears at present to be the most reliable and reproducible method for the detection of low-level disease in cancer patients, although prospective studies are warranted to assess the clinical utility of different molecular diagnostic methods

Psychosocial difficulties, deprivation and cancer: three questionnaire studies involving 609 cancer patients

The aim of the study is to investigate associations between deprivation and self-reported social difficulties and psychological distress in cancer patients. A total of 304 men and 305 women (age range 18–88 years) with a range of cancer diagnoses and living in a socially diverse region (Carstairs and Morris index) completed the Hospital Anxiety and Depression Scale and the Social Difficulties Inventory. Univariate analyses of variance revealed statistically significant differences in reported social difficulties between groups (F (67, 576)=2.4, P<0.0001) with stage of disease (F (5, 576)=7.6, P<0.0001), age (F (2, 576)=4.8, P=0.009) and to a lesser extent deprivation (F (1, 576)=4.0, P=0.048) making significant contributions. Significantly more social difficulties were reported by less affluent patients with locally recurrent disease or ‘survivors'. No other interactions were found. Significant differences in levels of reported psychological distress were found between groups (F (67, 575)=1.723, P=0.001) for stage of disease, sex and deprivation but no interactions observed. In conclusion, deprivation is associated with reported psychological distress and, to a lesser extent, social difficulties. Patients at particular risk cannot be identified with confidence by socio-demographic and clinical means supporting the recommendation from National Institute for Clinical Excellence for provision of psychosocial assessment for individual cancer patients

Stress corrosion cracking of titanium alloys Fourth quarterly progress report, 1 Jan. - 31 Mar. 1965

Stress corrosion rupturing of titanium alloy - fracture mechanic

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