Moment-Based Multi-Resolution HWENO Scheme for Hyperbolic Conservation Laws

In this paper, a high-order moment-based multi-resolution Hermite weighted essentially non-oscillatory (HWENO) scheme is designed for hyperbolic conservation laws. The main idea of this scheme is derived from our previous work [J. Comput. Phys., 446 (2021) 110653], in which the integral averages of the function and its first order derivative are used to reconstruct both the function and its first order derivative values at the boundaries. However, in this paper, only the function values at the Gauss-Lobatto points in the one or two dimensional case need to be reconstructed by using the information of the zeroth and first order moments. In addition, an extra modification procedure is used to modify those first order moments in the troubled-cells, which leads to an improvement of stability and an enhancement of resolution near discontinuities. To obtain the same order of accuracy, the size of the stencil required by this moment-based multi-resolution HWENO scheme is still the same as the general HWENO scheme and is more compact than the general WENO scheme. Moreover, the linear weights are not unique and are independent of the node position, and the CFL number can still be 0.6 whether for the one or two dimensional case, which has to be 0.2 in the two dimensional case for other HWENO schemes. Extensive numerical examples are given to demonstrate the stability and resolution of such moment-based multi-resolution HWENO scheme.     

Appropriateness of End-of-Life Care in People Dying With Dementia: Applying Quality Indicators on Linked Administrative Databases

ObjectivesDementia is a progressive incurable life-limiting illness. Previous research suggests end-of-life care for people with dementia should have a symptomatic focus with an effort to avoid burdensome interventions that would not improve quality of life. This study aims to assess the appropriateness of end-of-life care in people who died with dementia in Belgium and to establish relative performance standards by measuring validated population-level quality indicators.DesignWe conducted a retrospective observational study.Setting and ParticipantsWe included all persons deceased with dementia in 2015 in Belgium. Data from 8 administratively collected population-level databases was linked.MeasuresWe used a validated set of 28 quality indicators for end-of-life dementia care. We compared quality indicator scores across 14 healthcare regions to establish relative benchmarks.ResultsIn Belgium in 2015, 10,629 people died with dementia. For indicators of appropriate end-of-life care, people who died with dementia had on average 1.83 contacts with their family physician in the last week before death, whereas 68.4% died at home or in their nursing home of residence. For indicators of inappropriate end-of-life care, 32.4% were admitted to the hospital and 36.3% underwent diagnostic testing in the last 30 days before death, whereas 25.1% died in the hospital. In the last 30 days, emergency department admission varied between 19% and 31%, dispensing of gastric protectors between 18% and 42%, and antihypertensives between 40% and 53% between healthcare regions, with at least 25% of health regions below 46%.Conclusions and ImplicationsOur study found indications of appropriate as well as inappropriate end-of-life care in people with dementia, including high rates of family physician contact, as well as high percentages of diagnostic testing, and emergency department and hospital admissions. We also found high risk-adjusted variation for multiple quality indicators, indicating opportunity for quality improvement in end-of-life dementia care.     

Radiomics for classification of bone mineral loss: A machine learning study

PurposeThe purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches.Materials and methodsA total of 147 patients were included in this retrospective single-center study. There were 12 men and 135 women with a mean age of 56.88 ± 10.6 (SD) years (range: 28–87 years). For each patient, seven regions including four lumbar and three femoral including trochanteric, intertrochanteric and neck were segmented on bone mineral densitometry images and 54 texture features were extracted from the regions. The performance of four feature selection methods, including classifier attribute evaluation (CLAE), one rule attribute evaluation (ORAE), gain ratio attribute evaluation (GRAE) and principal components analysis (PRCA) along with four classification methods, including random forest (RF), random committee (RC), K-nearest neighbor (KN) and logit-boost (LB) were evaluated. Four classification categories, including osteopenia vs. normal, osteoporosis vs. normal, osteopenia vs. osteoporosis and osteoporosis + osteopenia vs. osteoporosis were examined for the defined seven regions. The classification model performances were evaluated using the area under the receiver operator characteristic curve (AUC).ResultsThe AUC values ranged from 0.50 to 0.78. The combination of methods RF + CLAE, RF + ORAE and RC + ORAE yielded highest performance (AUC = 0.78) in discriminating between osteoporosis and normal state in the trochanteric region. The combinations of RF + PRCA and LB + PRCA had the highest performance (AUC = 0.76) in discriminating between osteoporosis and normal state in the neck region.ConclusionThe machine learning radiomic approach can be considered as a new method for bone mineral deficiency disease classification using bone mineral densitometry image features.     

¿Es el intervalo libre de docetaxel un factor predictivo para el cáncer de próstata resistente a la castración?

ObjectiveProstate cancer (PCa) is the second most common solid tumor in men and the fifth leading cause of cancer-related death. In advanced stage, palliative treatments are used instead of curative therapies. Therefore, finding predictive indicators seems crucial. Patients with castration-resistant prostate cancer (CRPC) that received Dx chemotherapy have been retrospectively reviewed. The aim of this study was to investigate whether docetaxel (Dx)-free interval could have a predictive value for PCa and influence other sequential therapies.Material and methodsThis clinical trial study was performed on 104 patients at Medeniyet University Oncology Clinic in 2018-2020. All CRPC patients had metastases, received Dx as first-line treatment and underwent androgen receptor axis targeted (ARAT) therapy after disease progression. We analyzed patients’ progression time after Dx therapy and the effects on sequential treatment.ResultsAfter Dx therapy, all patients received ARAT (abiraterone (ABI) n: 49 (47.1%) and enzalutamide (ENZ) n: 54 (51.9%)) as a second-line treatment, except for one patient who received cabazitaxel. There was a statistically significant relationship between the Dx-free interval and duration of response to ARAT (P<.001). The response time of ARAT treatment was <10.5 months in all patients whose Dx-free interval period was <9 months.ConclusionsOur findings support the theory that Dx-free interval can be a predictive factor for CRPC. CRPC disease can be classified as Dx-sensitive disease or Dx-resistance disease, based on the Dx-free interval. Decision on subsequent treatments could be made considering this information.     

Troubled-Cell Indicator Based on Mean Value Property for Hybrid WENO Schemes

In this paper, we introduce a new type of troubled-cell indicator to improve hybrid weighted essentially non-oscillatory (WENO) schemes for solving the hyperbolic conservation laws. The hybrid WENO schemes selectively adopt the high-order linear upwind scheme or the WENO scheme to avoid the local characteristic decompositions and calculations of the nonlinear weights in smooth regions. Therefore, they can reduce computational cost while maintaining non-oscillatory properties in non-smooth regions. Reliable troubled-cell indicators are essential for efficient hybrid WENO methods. Most of troubled-cell indicators require proper parameters to detect discontinuities precisely, but it is very difficult to determine the parameters automatically. We develop a new troubled-cell indicator derived from the mean value theorem that does not require any variable parameters. Additionally, we investigate the characteristics of indicator variable; one of the conserved properties or the entropy is considered as indicator variable. Detailed numerical tests for 1D and 2D Euler equations are conducted to demonstrate the performance of the proposed indicator. The results with the proposed troubled-cell indicator are in good agreement with pure WENO schemes. Also the new indicator has advantages in the computational cost compared with the other indicators.     

基于平均最邻近和缓冲区分析方法的预防接种门诊空间分布特征分析

目的从空间角度分析黔南州预防接种门诊分布特征情况,为卫生资源的优化配置提供依据。方法采用平均最邻近和缓存区分析研究区域内预防接种门诊的空间分布模式以及服务范围。结果研究区域内预防接种门诊空间分布格局呈随机分布,预防接种服务最大服务范围未覆盖所有区域,其中预防接种门诊服务覆盖面积占比,长顺县最高为99.95%,独山县最低为83.12%。结论平均最邻近和缓冲区分析方法能直观地展示预防接种门诊空间分布特征以及测量服务范围,为合理设置预防接种门诊的提供参考依据。