51 research outputs found

    Does Index Futures Trading Reduce Volatility in the Chinese Stock Market? A Panel Data Evaluation Approach

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    This paper investigates the effect of introducing index futures trading on the spot price volatility in the Chinese stock market. We employ a recently developed panel data policy evaluation approach (Hsiao et al. 2011) to construct counterfactuals of the spot market volatility, based mainly on cross-sectional correlations between the Chinese and international stock markets. This new method does not need to specify a particular regression or a time series model for the volatility process around the introduction date of index futures trading, and thus avoids the potential omitted variable bias caused by uncontrolled market factors in the existing literature. Our results provide empirical evidence that the introduction of index futures trading significantly reduces the volatility of the Chinese stock market, which is robust to different model selection criteria and various prediction approaches.

    Shadow Hunter: Low-Illumination Object-Detection Algorithm

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    Recently, object detection, which is focused on images with normal illumination levels, has achieved great success. However, the accuracy of object detection is reduced in suboptimal environments due to the images plagued by noise and low contrast. For boosting the performance of object-detection tasks under low-illumination conditions, we propose three modules for improvement: (1) the low-level feature attention (LFA) module learns to focus on the regional feature information of the object in the low-illumination environment, highlighting important features and filtering noisy information; (2) the feature fusion neck (FFN) obtains enriched feature information by fusing the feature information of the feature map after backbone; (3) the context-spatial decoupling head (CSDH) enables the classification head to focus on contextual semantic information so that the localization head obtains richer spatial details. Extensive experiments show that our algorithm realizing end-to-end detection shows good performance in low-illumination images

    Measuring follow-up completeness

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    Completeness of follow-up is often used as a measure of the quality of follow-up, but the method used to compute it is often not declared. An ideal measure should be based on follow-up years instead of patients. Clark, Altman, and De Stavola proposed such a measure, called "C", which is the percentage of the maximum possible follow-up years, as of a given date, that has actually been accounted for or observed. However, such a measure will underestimate the true completeness, because the denominator ( maximum possible follow-up years) does not account for unobserved patient deaths occurring before that date, and therefore, it is realistically unachievable. We propose a modification, C*, of Clark's C, which accounts for the effect of unobserved patient deaths in attenuating the maximum potential follow-up, and thus gives a higher percentage for achieved follow-up completeness. We validated this theoretical improvement by comparing the values of C and C* computed for our long-term coronary artery bypass graft patients to the true completeness, which was obtained by using the National Death Index to complete our missing follow-up data. Using Clark's C, the follow-up completeness was 80.4% and using our C* it is 84.5%, whereas the true follow- up completeness based on National Death Index information was 85.0%

    Bayesian stopping guidelines for heart valve premarket approval studies

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    ObjectivesThe Data Monitoring Committee (DMC) for the premarket approval (PMA) study of a new heart valve prosthesis convenes periodically to review the accumulating results of the study, and determines, among other things, whether there is enough concern with safety to stop the study. Their deliberations are largely subjective, based on their combined experience and expertise, but an objective aid to evaluating complication rates, usually called a stopping rule, is desirable.MethodsThe US Food and Drug Administration has designated objective performance criteria (OPC) for 7 heart valve complications. At the end of the PMA study, when approximately 800 patient-years have been accumulated, the complication rates must compare favorably with the OPC. Given the results to date at an interim review of the data, we use a Bayesian approach to compute the probability of passing the OPC test by the end of study.ResultsWe provide a method that the DMC can use to predict the probability of passing the OPC test for each complication, and a graphical aid for each number of events, observed at 100 patient-year intervals.ConclusionsAlthough the DMC ultimately uses combined experience and expertise to make the decision to stop a PMA valve study, we have provided an objective assessment of the probability of the valve ultimately passing the OPC test to aid in making that decision

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    Significance of computed tomography combined with postural stimulation test in predicting laterality of primary aldosteronism

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    Abstract Backgrounds Adrenal venous sampling (AVS) represents the gold standard for classifying primary aldosteronism (PA). However, AVS is a technically demanding, expensive and invasive procedure. Computed tomography (CT) scans is recommended as the initial study of classification diagnosis by the current guidelines. In addition, postural stimulation test (PST) has been used to provide additional subtype diagnostic information. Objective This work aimed to evaluate the diagnostic utility of the adrenal CT combined with PST in the classification diagnosis of PA. Methods We analyzed PA patients who underwent AVS from November 2017 to February 2022 at a single center. Subtype classification of PA was determined by AVS. We analyzed the concordance rate between AVS outcomes, adrenal CT, and PST, and explored the value of adrenal CT combined with PST for predicting laterality of PA. Results Total 531 PA patients were included in the present study. The concordance rate between AVS and the adrenal CT was 51.0%(271/531). Receiver operating characteristic (ROC) curve of PST showed that the area under curve (AUC) was 0.604 [95% confidence interval (CI): 0.556, 0.652], the optimal cut-off value was 30%. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+LR), and negative likelihood ratio (−LR) of PST for diagnosis bilateral PA on AVS was 72.8, 46.2%, 0.48, 0.71, 1.35, and 0.59, respectively. The prevalence of unilateral PA on AVS in patients with unilateral lesion on CT and negative PST, unilateral lesion on CT and positive PST, bilateral normal or lesions on CT and negative PST, and bilateral normal or lesions on CT and positive PST was 82.4% (108/131), 59.9% (91/152), 50.7% (37/73), and 44.6% (78/175), respectively. The sensitivity, specificity, PPV, NPV, +LR, and -LR of adrenal CT combined with PST for the diagnosis of unilateral PA were 34.4, 89.4%, 0.82, 0.49, 3.25, and 0.73, respectively. Conclusions The combination of CT findings and PST can improve the accuracy of predicting laterality of PA

    Weaving our energyscapes: Using hydrogen to store renewable energy in a network composed of existing threads

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    This project aims to address the challenges posed by the transition to renewable energy sources. This will cause an unstable and unreliable energy flow, which does not correspond with the current energy use patterns of society. Different elements of the current energy network are analysed. They have a big role in the transition towards a completely renewable energy system. The proposed solution involves the utilisation of hydrogen as a means to store and transport renewable energy. In order to achieve this, consumption and production patterns in North-western Europe are analysed in relation to existing energy infrastructure that is suitable for carrying hydrogen. With a combination of different data sources and a created algorithm a model is created that is able to generate clusters. These clusters resulted in a continental framework containing 3 typologies of energy landscapes. A centralized, decentralized and a resilient zone; inbetween. These landscapes are characterised by their population, proximity and current land use against societal challenges such as justice, resilience, polarisation, and reliability. Self-made algorithms are used to transcribe the landscapes into a collection of physical energy elements that will be needed in areas. These measurements are visualized to propose what the future “energyscapes” could look like. The project suggests implementations on different scales for the new paradigm in the energy transition where hydrogen contributes to a just and reliable energy system.AR2U086 R&D Studio – Spatial Strategies for the Global MetropolisAR2U088 R&D Methodology for UrbanismArchitecture, Urbanism and Building Sciences | Urbanis

    Mechanical heart valves: are two leaflets better than one?

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    We sought to compare the long-term clinical outcomes of patients who underwent isolated aortic valve replacement with single-disc and bileaflet mechanical heart valves
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