79 research outputs found

    Adaptive Feed Rate Policies for Spiral Drilling Using Markov Decision Process

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    In this study, the feed rate optimization model based on a Markov Decision Process (MDP) was introduced for spiral drilling process. Firstly, the experimental data on spiral drilling was taken from literature for different axial force parameters and with various feed rate decisions made, having the length of a hole being drilled as a reward. Proposed optimization model was computed using value iteration method. Secondly, the results of computations were displayed for optimal decision to be made on each state. Proposed decisions for an optimal feed rate could be utilized in order to improve the efficiency of spiral drilling process in terms of cost and time

    Graphic Processing Units (GPUs)-Based Haptic Simulator for Dental Implant Surgery

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    This paper presents a haptics-based training simulator for dental implant surgery. Most of the previously developed dental simulators are targeted for exploring and drilling purpose only. The penalty-based contact force models with spherical-shaped dental tools are often adopted for simplicity and computational efficiency. In contrast, our simulator is equipped with a more precise force model adapted from the Voxmap-PointShell (VPS) method to capture the essential features of the drilling procedure, with no limitations on drill shape. In addition, a real-time torque model is proposed to simulate the torque resistance in the implant insertion procedure, based on patient-specific tissue properties and implant geometry. To achieve better anatomical accuracy, our oral model is reconstructed from cone beam computed tomography (CBCT) images with a voxel-based method. To enhance the real-time response, the parallel computing power of GPUs is exploited through extra efforts in data structure design, algorithms parallelization, and graphic memory utilization. Results show that the developed system can produce appropriate force feedback at different tissue layers during pilot drilling and can create proper resistance torque responses during implant insertion

    Acute decompensated heart failure in a non cardiology tertiary referral centre, Sarawak General Hospital (SGH‑HF)

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    Abstract Background: Data on clinical characteristics of acute decompensated heart failure (ADHF) in Malaysia especially in East Malaysia is lacking. Methods: This is a prospective observational study in Sarawak General Hospital, Medical Department, from October 2017 to September 2018. Patients with primary admission diagnosis of ADHF were recruited and followed up for 90 days. Data on patient’s characteristics, precipitating factors, medications and short-term clinical outcomes were recorded. Results: Majority of the patients were classified in lower socioeconomic group and the mean age was 59 years old. Hypertension, diabetes mellitus and dyslipidaemia were the common underlying comorbidities. Heart failure with ischemic aetiology was the commonest ADHF admission precipitating factor. 48.6% of patients were having preserved ejection fraction HF and the median NT-ProBNP level was 4230 pg/mL. Prescription rate of the evidencebased heart failure medication was low. The in-patient mortality and the average length of hospital stay were 7.5% and 5 days respectively. 43% of patients required either ICU care or advanced cardiopulmonary support. The 30-day, 90-day mortality and readmission rate were 13.1%, 11.2%, 16.8% and 14% respectively. Conclusion: Comparing with the HF data from West and Asia Pacific, the short-term mortality and readmission rate were high among the ADHF patients in our study cohort. Maladaptation to evidence-based HF prescription and the higher prevalence of cardiovascular risk factors in younger patients were among the possible issues to be addressed to improve the HF outcome in regions with similar socioeconomic background. Keywords: Acute decompensated heart failure, Epidemiology, Sarawak, Southeast Asia, Malaysi

    Clinical Outcome Predictor using Killip Scoring in Acute Decompensated Heart Failure (ADHF): A Non-Cardiac Centre Pilot Experience

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    Background: Physicians in tertiary centers face a constant challenge in selecting patient with ADHF to be admitted from district healthcare centre, especially with limited resources. Appropriate risk stratification of patients with ADHF would improve the efficiency of our healthcare delivery system. Objective: We aim to find potential relationship between Killip clinical scoring with clinical outcome of ADHF, including in-patient mortality and requirement of advanced cardiorespiratory support. Methods: 35 consecutive cases with a discharge diagnosis of ADHF and admission creatinine clearance of more than 30 were randomly reviewed. Cases were analyzed retrospectively for their Killip score, in-patient mortality, requirement of advance cardiorespiratory care or ICU admission. Results: There were 21 male patients (60%) and 14 female patients. Mean age was 61±19 years old. Mean duration of ward-stay was 6±4 days. Comorbidities were 14 (40%) with history of coronary artery diseases and 17 (49%) with diabetes mellitus. 15 patients (43%) were on at least a single type of guideline directed medication for heart failure. The cohort was almost evenly distributed between those with a Killip score of 2 and above 2. A Killip score of 3 and above was found to have good positive predictive value (87%) for advanced cardio-respiratory care and negative predictive value of 78%. No in-patient death was observed for the group with Killip 2 while 5 deaths were recorded in the group scoring more than 2. A Killip score of 3 had excellent (100%) negative predictive value for in-patient mortality but poor positive predictive value (33%). Significant relationship (p<0.001) was observed for Killip scoring on both outcomes. Conclusion: Killip scoring may be useful for on-call physician to decide the need on tertiary care among patient with ADHF and mortality outcome. However, more prospective studies and patients should be recruited to validate the study

    Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).

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    PURPOSE: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. EXPERIMENTAL DESIGN: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. RESULTS: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. CONCLUSIONS: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.Core funding for this project was provided by the National Institutes of Health (R01-CA172404, PI: S.J. Ramus; and R01-CA168758, PIs: J.A. Doherty and M.A.Rossing), the Canadian Institutes for Health Research (Proof-of-Principle I program, PIs: D.G.Huntsman and M.S. Anglesio), the United States Department of Defense Ovarian Cancer Research Program (OC110433, PI: D.D. Bowtell). A. Talhouk is funded through a Michael Smith Foundation for Health Research Scholar Award. M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation. J. George was partially supported by the NIH/National Cancer Institute award number P30CA034196. C. Wang was a Career Enhancement Awardee of the Mayo Clinic SPORE in Ovarian Cancer (P50 CA136393). D.G. Huntsman receives support from the Dr. Chew Wei Memorial Professorship in Gynecologic Oncology, and the Canada Research Chairs program (Research Chair in Molecular and Genomic Pathology). M. Widschwendter receives funding from the European Union’s Horizon 2020 European Research Council Programme, H2020 BRCA-ERC under Grant Agreement No. 742432 as well as the charity, The Eve Appeal (https://eveappeal.org.uk/), and support of the National Institute for Health Research (NIHR) and the University College London Hospitals (UCLH) Biomedical Research Centre. G.E. Konecny is supported by the Miriam and Sheldon Adelson Medical Research Foundation. B.Y. Karlan is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124. H.R. Harris is 20 supported by the NIH/National Cancer Institute award number K22 CA193860. OVCARE (including the VAN study) receives support through the BC Cancer Foundation and The VGH+UBC Hospital Foundation (authors AT, BG, DGH, and MSA). The AOV study is supported by the Canadian Institutes of Health Research (MOP86727). The Gynaecological Oncology Biobank at Westmead, a member of the Australasian Biospecimen Network-Oncology group, was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16. The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID199600; ID400413 and ID400281). BriTROC-1 was funded by Ovarian Cancer Action (to IAM and JDB, grant number 006) and supported by Cancer Research UK (grant numbers A15973, A15601, A18072, A17197, A19274 and A19694) and the National Institute for Health Research Cambridge and Imperial Biomedical Research Centres. Samples from the Mayo Clinic were collected and provided with support of P50 CA136393 (E.L.G., G.L.K, S.H.K, M.E.S.)

    Laser-induced materials and processes for rapid prototyping

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    A case study of women auditors in Singapore.

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    102 p.The objectives of this project is to identify the factors contributing to job satisfaction of women auditors. In addition, it determines the impact of family commitments on their career. This study also attempts to study the problems encountered by women auditors in the areas of career advancement, working relationships and equality of treatment.ACCOUNTANC

    Guest editorial

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    Marketing of consumer loans

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    In Singapore today, everything from shampoo to designer wears come in an array of brands and packagings. Financial products are no exception.BUSINES
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