Association of Female Menopause With Atrioventricular Mechanics and Outcomes

BACKGROUND: Despite known sex differences in cardiac structure and function, little is known about how menopause and estrogen associate with atrioventricular mechanics and outcomes. OBJECTIVE: To study how, sex differences, loss of estrogen in menopause and duration of menopause, relate to atrioventricular mechanics and outcomes. METHODS: Among 4051 asymptomatic adults (49.8 ± 10.8 years, 35%women), left ventricular (LV) and left atrial (LA) mechanics were assessed using speckle-tracking. RESULTS: Post-menopausal (vs. pre-menopausal) women had similar LV ejection fraction but reduced GLS, reduced PALS, increased LA stiffness, higher LV sphericity and LV torsion (all p < 0.001). Multivariable analysis showed menopause to be associated with greater LV sphericity (0.02, 95%CI 0.01, 0.03), higher indexed LV mass (LVMi), lower mitral e’, lower LV GLS (0.37, 95%CI 0.04–0.70), higher LV torsion, larger LA volume, worse PALS (∼2.4-fold) and greater LA stiffness (0.028, 95%CI 0.01–0.05). Increasing years of menopause was associated with further reduction in GLS, markedly worse LA mechanics despite greater LV sphericity and higher torsion. Lower estradiol levels correlated with more impaired LV diastolic function, impaired LV GLS, greater LA stiffness, and increased LV sphericity and LV torsion (all p < 0.05). Approximately 5.5% (37/669) of post-menopausal women incident HF over 2.9 years of follow-up. Greater LV sphericity [adjusted hazard ratio (aHR) 1.04, 95%CI 1.00–1.07], impaired GLS (aHR 0.87, 95%CI 0.78–0.97), reduced peak left atrial longitudinal strain (PALS, aHR 0.94, 95%CI 0.90–0.99) and higher LA stiffness (aHR 10.5, 95%CI 1.69–64.6) were independently associated with the primary outcome of HF hospitalizations in post-menopause. Both PALS < 23% (aHR:1.32, 95%CI 1.01–3.49) and GLS < 16% (aHR:5.80, 95%CI 1.79–18.8) remained prognostic for the incidence of HF in post-menopausal women in dichotomous analyses, even after adjusting for confounders. Results were consistent with composite outcomes of HF hospitalizations and 1-year all-cause mortality as well. CONCLUSION: Menopause was associated with greater LV/LA remodeling and reduced LV longitudinal and LA function in women. The cardiac functional deficit with menopause and lower estradiol levels, along with their independent prognostic value post-menopause, may elucidate sex differences in heart failure further

Data layout transformation through in-place transposition

Matrix transposition is an important algorithmic building block for many numeric algorithms like multidimensional FFT. It has also been used to convert the storage layout of arrays. Intuitively, in-place transposition should be a good fit for GPU architectures due to limited available on-board memory capacity and high throughput. However, direct application of in-place transposition algorithms from CPU lacks the amount of parallelism and locality required by GPU to achieve good performance. In this thesis we present the first known in-place matrix transposition approach for the GPUs. Our implementation is based on a staged transposition algorithm where each stage is performed using an elementary tiled-wise transposition. With both low-level optimizations to the elementary tiled-wise transpositions as well as high-level improvements to existing staged transposition algorithm, our design is able to reach more than 20 GB/s sustained throughput on modern GPUs, and a 3X speedup. Furthermore, for many-core architectures like the GPUs, efficient off-chip memory access is crucial to high performance; the applications are often limited by off-chip memory bandwidth. Transforming data layout is an effective way to reshape the access patterns to improve off-chip memory access behavior, but several challenges had limited the use of automated data layout transformation systems on GPUs, namely how to efficiently handle arrays of aggregates, and transparently marshal data between layouts required by different performance sensitive kernels and legacy host code. While GPUs have higher memory bandwidth and are natural candidates for marshaling data between layouts, the relatively constrained GPU memory capacity, compared to that of the CPU, implies that not only the temporal cost of marshaling but also the spatial overhead must be considered for any practical layout transformation systems. As an application of the in-place transposition methodology, a novel approach to laying out arrays of aggregate types across GPU and CPU architectures is proposed to further improve memory parallelism and kernel performance beyond what is achieved by human programmers using discrete arrays today. Second, the system, DL, has a run-time library implemented in OpenCL that transparently and efficiently converts, or marshals, data to accommodate application components that have different data layout requirements. We present insights that lead to the design of this highly efficient run-time marshaling library. Third, we show experimental results that the new layout approach leads to substantial performance improvement at the applications level even when all marshaling cost is taken into account

Effects of Dark Brown Sugar Replacing Sucrose and Calcium Carbonate, Chitosan, and Chitooligosaccharide Addition on Acrylamide and 5-Hydroxymethylfurfural Mitigation in Brown Sugar Cookies

The objective of this study was to evaluate effects of dark brown sugar on acrylamide and 5-hydroxymethylfurfural (HMF) levels in brown sugar cookies. Dark brown sugar was used as a raw material instead of sucrose, and chitosan, chitooligosaccharides, or calcium carbonate were added to investigate their effect on acrylamide and HMF mitigation. The results demonstrated that the higher the content of acrylamide in the dark brown sugar, the higher the amount of acrylamide produced in baked brown sugar cookies. The addition of dark brown sugar significantly increased the diameter and decreased the thickness of cookies, which induced more acrylamide formation. Therefore, the sucrose control cookies were harder and thicker than dark brown sugar cookies. The addition of 1% chitosan, chitooligosaccharide, or calcium carbonate did not reduce the acrylamide formation of the brown sugar cookies. The content of acrylamide and HMF in the sucrose control group was lower than that in dark brown sugar groups, and chitooligosaccharide increased the level of HMF. This is due to the fact that the content of reducing sugar in dark brown sugar is higher than that in sucrose, and dark brown sugar contains acrylamide. There was no difference in the concentration of reducing sugar between test and control cookies (p &gt; 0.05). The L values of brown sugar were lower than those of sucrose cookies, especially for chitooligosaccharide addition (p &lt; 0.05). The addition of chitooligosaccharide generated more Maillard reaction products and caramelization. The reducing power of dark brown sugar cookies was higher than that of sucrose control cookies. The baking industry should choose sucrose or dark brown sugar containing a low acrylamide content as an ingredient to prevent the final products from containing high levels of acrylamide

Long-Term Flooding Maps Forecasting System Using Series Machine Learning and Numerical Weather Prediction System

Accurate real-time forecasts of inundation depth and area during typhoon flooding is crucial to disaster emergency response. The development of an inundation forecasting model has been recognized as essential to manage disaster risk. In the past, most researchers used multiple single-point forecasts to obtain surface flooding depth forecasts with spatial interpolation. In this study, a forecasting model (QPF-RIF) integrating a hydrodynamic model (SOBEK), support vector machine–multi-step forecast (SVM-MSF), and a self-organizing map (SOM) were proposed. The task of this model was divided into four parts: hydrodynamic simulation, point forecasting, inundation database clustering, and spatial expansion. First, the SOBEK model was used in simulating inundation hydrodynamics to construct the flooding maps database. Second, the SVM-MSF yields water level (inundation volume) forecasted with a 1 to 72 h lead time. Third, the SOM clustered the previous flooding maps database into several groups representing different flooding characteristics. Finally, a spatial expansion module produced inundation maps based on forecasting information from forecasting flood volume and flood causative factors. To demonstrate the effectiveness of the proposed forecasting model, we presented an application to the Yilan River basin in Taiwan. Our forecasting results indicated that the proposed model yields accurate flood inundation maps (less than 1 cm error) for a 1 h lead time. For long-term forecasting (46 h to 72 h ahead), the model controlled the error of the forecast results within 7 cm. In the testing events, the model forecasted an average of 83% of the flooding area in the long term. This flood inundation forecasting model is expected to be useful in providing early flood warning information for disaster emergency response