90 research outputs found

    Detecting long-range dependence in non-stationary time series

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    An important problem in time series analysis is the discrimination between non-stationarity and longrange dependence. Most of the literature considers the problem of testing specific parametric hypotheses of non-stationarity (such as a change in the mean) against long-range dependent stationary alternatives. In this paper we suggest a simple approach, which can be used to test the null-hypothesis of a general non-stationary short-memory against the alternative of a non-stationary long-memory process. The test procedure works in the spectral domain and uses a sequence of approximating tvFARIMA models to estimate the time varying long-range dependence parameter. We prove uniform consistency of this estimate and asymptotic normality of an averaged version. These results yield a simple test (based on the quantiles of the standard normal distribution), and it is demonstrated in a simulation study that - despite of its semi-parametric nature - the new test outperforms the currently available methods, which are constructed to discriminate between specific parametric hypotheses of non-stationarity short- and stationarity long-range dependence.Comment: Keywords and phrases: spectral density, long-memory, non-stationary processes, goodness-of-fit tests, empirical spectral measure, integrated periodogram, locally stationary process, approximating model

    Goodness-of-fit tests in long-range dependent processes under fixed alternatives

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    In a recent paper Fay and Philippe (2002) proposed a goodness-of-fit test for long-range dependent processes which uses the logarithmic contrast as information measure. These authors established asymptotic normality under the null hypothesis and local alternatives. In the present note we extend these results and show that the corresponding test statistic is also normally distributed under fixed alternatives. AMS Subject Classi cation: 60F05, 62F0

    Measuring stationarity in long-memory processes

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    In this paper we consider the problem of measuring stationarity in locally stationary longmemory processes. We introduce an L2-distance between the spectral density of the locally stationary process and its best approximation under the assumption of stationarity. The distance is estimated by a numerical approximation of the integrated spectral periodogram and asymptotic normality of the resulting estimate is established. The results can be used to construct a simple test for the hypothesis of stationarity in locally stationary long-range dependent processes. We also propose a bootstrap procedure to improve the approximation of the nominal level and prove its consistency. Throughout the paper, we will work with Riemann sums of a squared periodogram instead of integrals (as it is usually done in the literature) and as a byproduct of independent interest it is demonstrated that the two approaches behave differently in the limit

    Detecting long-range dependence in non-stationary time series

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    An important problem in time series analysis is the discrimination between non-stationarity and longrange dependence. Most of the literature considers the problem of testing specificc parametric hypotheses of non-stationarity (such as a change in the mean) against long-range dependent stationary alternatives. In this paper we suggest a simple nonparametric approach, which can be used to test the null-hypothesis of a general non-stationary short-memory against the alternative of a non-stationary long-memory process. This test is working in the spectral domain and uses a sieve of approximating tvFARIMA models to estimate the time varying long-range dependence parameter nonparametrically. We prove uniform consistency of this estimate and asymptotic normality of an averaged version. These results yield a simple test (based on the quantiles of the standard normal distribution), and it is demonstrated in a simulation study that - despite of its nonparametric nature - the new test outperforms the currently available methods, which are constructed to discriminate between speci fic parametric hypotheses of non-stationarity short- and stationarity long-range dependence

    Chemical and biological profiles of essential oil from different parts of Myrtus communis L. subsp. communis from Turkey

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    The present study reports chemical composition, antidiabetic, anti-inflammatory and antioxidant potential of essential oils from leaves and twigs of Myrtus communis L. subsp. communis from Turkey. Essential oils were obtained separately from leaves and twigs of Myrtus communis subsp. communis (MC) by hydrodistillation using a Clevenger-type apparatus. Chemical compositions were determined using GC/MS. Antidiabetic, anti-inflammatory and antioxidant activities of essential oils were tested by őĪ-amylase inhibitory, 5-lipoxygenase inhibitory and DPPH/ABTS radical scavenging methods, respectively. The major compounds of essential oil of Myrtus communis subsp. communis leaves (MCLEO) were őĪ-pinene (35.6%), 1,8-cineole (28.3%), linalool (10.5%), and limonene (8.2%), while the major constituents of essential oil of Myrtus communis subsp. communis twigs (MCTEO) were őĪ-pinene (30.7%), 1,8-cineole (23.5%), p-cymene (13.3%) and limonene (11.9%). MCLEO and MCTEO showed good and moderate radical scavenging activity with IC50¬† values of 124.40 ¬Ķg/mL and 390.10 ¬Ķg/mL for ABTS radical, respectively. MCLEO and MCTEO exhibited significant radical scavenging activity with IC50 values of 34.13 ¬Ķg/mL and 28.15 ¬Ķg/mL for DPPH radical, respectively. Also, MCLEO and MCTEO displayed strong and good antidiabetic activity with IC50 values of 29.94 ¬Ķg/mL and 159.80 ¬Ķg/mL against őĪ-amylase enzyme, respectively. Finally, MCLEO and MCTEO showed good anti-inflammatory activity with IC50 values 86.10 ¬Ķg/ mL and 96.55 ¬Ķg/mL against 5-lipoxygenase enzyme, respectively. From the present study it can be concluded that essential oils, especially MCLEO, possess good antidiabetic, anti- inflammatory and antioxidant activities. Also, this is the first study on chemical composition of MCTEO from Turkey, as well as on őĪ-amylase inhibitory and 5-lipoxygenase inhibitory activities of MCLEO and MCTEO

    Volume CXIV, Number 4, November 7, 1996

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    Objective: Turner syndrome (TS) is a chromosomal disorder caused by complete or partial X chromosome monosomy that manifests various clinical features depending on the karyotype and on the genetic background of affected girls. This study aimed to systematically investigate the key clinical features of TS in relationship to karyotype in a large pediatric Turkish patient population.Methods: Our retrospective study included 842 karyotype-proven TS patients aged 0-18 years who were evaluated in 35 different centers in Turkey in the years 2013-2014.Results: The most common karyotype was 45,X (50.7%), followed by 45,X/46,XX (10.8%), 46,X,i(Xq) (10.1%) and 45,X/46,X,i(Xq) (9.5%). Mean age at diagnosis was 10.2¬Ī4.4 years. The most common presenting complaints were short stature and delayed puberty. Among patients diagnosed before age one year, the ratio of karyotype 45,X was significantly higher than that of other karyotype groups. Cardiac defects (bicuspid aortic valve, coarctation of the aorta and aortic stenosis) were the most common congenital anomalies, occurring in 25% of the TS cases. This was followed by urinary system anomalies (horseshoe kidney, double collector duct system and renal rotation) detected in 16.3%. Hashimoto's thyroiditis was found in 11.1% of patients, gastrointestinal abnormalities in 8.9%, ear nose and throat problems in 22.6%, dermatologic problems in 21.8% and osteoporosis in 15.3%. Learning difficulties and/or psychosocial problems were encountered in 39.1%. Insulin resistance and impaired fasting glucose were detected in 3.4% and 2.2%, respectively. Dyslipidemia prevalence was 11.4%.Conclusion: This comprehensive study systematically evaluated the largest group of karyotype-proven TS girls to date. The karyotype distribution, congenital anomaly and comorbidity profile closely parallel that from other countries and support the need for close medical surveillance of these complex patients throughout their lifespa

    Mobile banking in the government-to-person payment sector for financial inclusion in Pakistan

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    Whilst there have been growing interest and efforts by governments in developing countries to disburse digital government-to-person (G2P) payments to promote financial inclusion, the role of mobile banking in the receipt of social cash remains under-researched. Through an interpretive case study of the Benazir Income Support Programme (BISP) in Pakistan, this paper applies Orlikowski’s Duality of Technology that critically examines mobile banking usage by women beneficiaries and technology's effects on the institutional properties of their households. Qualitative data were collected through semi-structured interviews from participants located in Pakistan. The findings highlighted that mobile banking enabled women to receive the full amount of grants, securely and conveniently, from agents. However, mobile banking imposed human, socio-economic and technological constraints which restricted women's access to and usage of financial services that limited financial inclusion. Women were socially and politically empowered, thereby, social inclusion was transformative. This paper theoretically contributes to the Duality of Technology framework that was deterministic for women beneficiaries. The study accentuates the redesign of mobile banking to match women's capabilities, and imparting financial and digital training to them. Also, the provision of a range of financial resources to beneficiaries may steer micro-entrepreneurial activities to advance the inclusion agenda in Pakistan

    Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

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    Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low‚Äďmiddle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthes