Miracle-dz/UniFAR-FTUs huggingface dataset:
Marginal consistent dependence modelling using weak subordination for Brownian motions

We present an approach for modelling dependencies in exponential Lévy market models with arbitrary margins originated from time changed Brownian motions. Using weak subordination of Buchmann et al. [Bernoulli, 2017], we face a new layer of dependencies, superior to traditional approaches based on pathwise subordination, since weakly subordinated processes are not required to have independent components considering multivariate stochastic time changes. We apply a subordinator being able to incorporate any joint or idiosyncratic information arrivals. We emphasize multivariate variance gamma and normal inverse Gaussian processes and state explicit formulae for the Lévy characteristics. Using maximum likelihood, we estimate multivariate variance gamma models on various market data and show that these models are highly preferable to traditional approaches. Consistent values of basket-options under given marginal pricing models are achieved using the Esscher transform, generating a non-flat implied correlation surface.
Estimation and inference for precision matrices of non-stationary time series

In this paper, we consider the estimation and inference of precision matrices of a rich class of locally stationary and nonlinear time series assuming that only one realization of the time series is observed. Using a Cholesky decomposition technique, we show that the precision matrices can be directly estimated via a series of least squares linear regressions with smoothly time-varying coefficients. The method of sieves is utilized for the estimation and is shown to be efficient and optimally adaptive in terms of estimation accuracy and computational complexity. We establish an asymptotic theory for a class of ${\cal L}^2$ tests based on the nonparametric sieve estimators. The latter are used for testing whether the precision matrices are diagonal or banded. A high dimensional Gaussian approximation result is established for a wide class of quadratic form of non-stationary and nonlinear processes, which is of interest by itself.
Global Brain Perfusion and the Risk of Transient Ischemic Attack and Ischemic Stroke: The Rotterdam Study

Background The role of subtle disturbances of brain perfusion in the risk of transient ischemic attack (TIA) or ischemic stroke remains unknown. We examined the association between global brain perfusion and risk of TIA and ischemic stroke in the general population. Methods and Results Between 2005 and 2015, 5289 stroke‐free participants (mean age, 64.3 years; 55.6% women) from the Rotterdam Study underwent phase‐contrast brain magnetic resonance imaging at baseline to assess global brain perfusion. These participants were followed for incident TIA or ischemic stroke until January 1, 2016. We investigated associations between global brain perfusion (mL of blood flow/100 mL of brain/min) and risk of TIA and ischemic stroke using Cox regression models with adjustment for age, sex, and cardiovascular risk factors. Additionally, we investigated whether associations were modified by retinal vessel calibers, small and large vessel disease, blood pressure, and heart rate. During a median follow‐up of 7.2 years (36 103 person‐years), 137 participants suffered a TIA and another 108 an ischemic stroke. We found that lower global brain perfusion was associated with a higher risk of TIA, but not with the risk of ischemic stroke (adjusted hazard ratio, 95% CI, per standard deviation decrease of global brain perfusion: 1.29, 1.07–1.55 for TIA and adjusted hazard ratio of 1.06, 0.87–1.30 for ischemic stroke). Across strata of wider arteriolar retinal calibers, lower brain perfusion was more prominently associated with TIA, but not with ischemic stroke. Conclusions In a community‐dwelling population, impaired global brain perfusion increased the risk of TIA, but not of ischemic stroke.
Applying user preferences to optimize the contribution of HIV self‐testing to reaching the “first 90” target of UNAIDS Fast‐track strategy: results from discrete choice experiments in Zimbabwe

New HIV testing strategies are needed to reach the United Nations’ 90‐90‐90 target. HIV self‐testing (HIVST) can increase uptake, but users’ perspectives on optimal models of distribution and post‐test services are uncertain. We used discrete choice experiments (DCEs) to explore the impact of service characteristics on uptake along the testing cascade.
What Lies Beyond the Superordinate Trait Perfectionism Factors? The Perfectionistic Self-Presentation and Perfectionism Cognitions Inventory Versus the Big Three Perfectionism Scale in Predicting Depression and Social Anxiety

Abstract Extreme perfectionism has been linked with distress and dysfunction. This association is reflected by the recent development of the Big Three Perfectionism Scale (BTPS), which has superordinate trait-based scales that assess 3 broad elements—rigid, self-critical, and narcissistic perfectionism. We examined psychometric features of the BTPS as well as the links between the BTPS and indexes of distress. A sample of 602 undergraduates completed the BTPS, the Perfectionistic Self-Presentation Scale, the Perfectionism Cognitions Inventory, and measures of social anxiety and depression. Support was obtained for the psychometric qualities of the BTPS. All 3 superordinate trait factors were associated with social anxiety and depression. Analyses also established that rigid perfectionism, self-critical perfectionism, and narcissistic perfectionism are associated with perfectionistic cognitions and perfectionistic self-presentation. In addition, the results of a series of regression analyses established that perfectionistic self-presentation and perfectionistic cognitions accounted for significant unique variance in distress beyond the variance attributable to rigid, narcissistic, and self-critical perfectionism. Overall, our results suggest that the BTPS has significant promise as a predictor of various forms of dysfunction, but the cognitive and self-presentational aspects of the perfectionism construct are also uniquely relevant and not redundant with the BTPS superordinate trait factors
The association between metabolic syndrome severity and oxidative stress induced by maximal exercise testing – a cross-sectional study

Abstract Purpose: Oxidative stress (OS) has been implicated in the pathogenesis of metabolic syndrome (MetS). The acute change in OS biomarkers due to exercise, known as exercise-induced OS (EIOS), is postulated to be a more appropriate marker of OS compared to spot OS measures. These studies objectives were to investigate EIOS in participants with MetS and compare the associations between EIOS, spot OS measures and MetS severity. Methods: Sixty-three participants with MetS had MetS severity assessed using the MetS Z-score. Participants undertook a cardiorespiratory fitness test (O2peak) to volitional exhaustion (∼8–12 minutes). Plasma OS (total F2-isoprostanes (IsoP), protein carbonyls (PCs)) and antioxidant (glutathione peroxidase (GPx), total antioxidant status (TAS)) biomarkers were measured from samples obtained before and five minutes post-O2peak test. Wilcoxon’s signed-rank tests were used to determine changes in OS markers. Results: There were no significant (p > 0.05) changes in OS or antioxidant biomarkers from pre- to post-exercise (median (interquartile range): IsoP –15.5 (–71.8 to 47.8) pg/mL; PC –0.01 (–0.16 to 0.13) nmol/mg protein; GPx 0.76 (–4.94 to 9.82) U/L, TAS 0.03 (0.00–0.05) mmol/L). Conclusions: A O2peak test to exhaustion failed to induce OS in participants with MetS. There were no associations between MetS severity and spot OS or EIOS biomarkers.
Assessment of Food Safety Knowledge, Self-Reported Practices, and Microbiological Hand Hygiene Levels of Produce Handlers in Qatar.

HIGHLIGHTS Workers' hygiene is one of the most important risk factors in transferring pathogens to foods. Produce handlers lacked basic knowledge on personal hygiene and food safety. Produce handlers' hand hygiene levels were below set standards. This study is the first of its kind in the region; thus, it helps fill an existing knowledge gap.
Overlapping Surgery in Plastic Surgery: An Analysis of Patient Safety and Clinical Outcomes.

BACKGROUND Overlapping surgery is an important and controversial health care issue. To date, there is minimal evidence on the safety of overlapping surgery in plastic surgery. The purpose of this study was to evaluate and compare outcomes for patients undergoing overlapping surgery versus nonoverlapping surgery in plastic surgery. METHODS This is a retrospective cohort study of consecutive patients undergoing plastic surgery procedures at a tertiary academic center between January of 2016 and January of 2018. Demographic and procedural characteristics, clinical outcomes, and adverse events were analyzed for patients undergoing overlapping versus nonoverlapping surgery. An a priori power analysis was performed, and chi-square, Wilcoxon rank sum, and bivariate logistic regression tests were used for analyses. RESULTS Eight hundred sixty-six patients constituted the study population: 555 (64.1 percent) underwent nonoverlapping surgery and 311 (35.9 percent) underwent overlapping surgery. There was no significant difference (p > 0.050) in mean age, body mass index, tobacco use, American Society of Anesthesiologists rating, or Charlson Comorbidity Index score between cohorts. Comparison of nonoverlapping and overlapping cases revealed no differences in complications (12.1 percent versus 11.9 percent; p = 0.939), reoperations (6.1 percent versus 6.8 percent; p = 0.717), readmissions (3.6 percent versus 3.5 percent; p = 0.960), or emergency room visits (4.7 percent versus 4.8 percent; p = 0.927). Stratification by procedure demonstrated no difference (p > 0.050) in complications between cohorts. Median operative time was significantly longer for overlapping operations (105 minutes versus 83 minutes; p = 0.004). CONCLUSIONS This study supports the safety of overlapping surgery in plastic surgery. CLINICAL QUESTION/LEVEL OF EVIDENCE Therapeutic, III.
Assessment of MERRA-2 Surface PM2.5 over the Yangtze River Basin: Ground-based Verification, Spatiotemporal Distribution and Meteorological Dependence

A good understanding of how meteorological conditions exacerbate or mitigate air pollution is critical for developing robust emission reduction policies. Thus, based on a multiple linear regression (MLR) model in this study, the quantified impacts of six meteorological variables on PM2.5 (i.e., particle matter with diameter of 2.5 µm or less) and its major components were estimated over the Yangtze River Basin (YRB). The 38-year (1980–2017) daily PM2.5 and meteorological data were derived from the newly-released Modern-Era Retrospective Analysis and Research and Application, version 2 (MERRA-2) products. The MERRA-2 PM2.5 was underestimated compared with ground measurements, partly due to the bias in the MERRA-2 Aerosol Optical Depth (AOD) assimilation. An over-increasing trend in each PM2.5 component occurred for the whole study period; however, this has been curbed since 2007. The MLR model suggested that meteorological variability could explain up to 67% of the PM2.5 changes. PM2.5 was robustly anti-correlated with surface wind speed, precipitation and boundary layer height (BLH), but was positively correlated with temperature throughout the YRB. The relationship of relative humidity (RH) and total cloud cover with PM2.5 showed regional dependencies, with negative correlation in the Yangtze River Delta (YRD) and positive correlation in the other areas. In particular, PM2.5 was most sensitive to surface wind speed, and the sensitivity was approximately −2.42 µg m−3 m−1 s. This study highlighted the impact of meteorological conditions on PM2.5 growth, although it was much smaller than the anthropogenic emissions impact.
Association between PRDM16, MEF2D, TRPM8, LRP1 gene polymorphisms and migraine susceptibility in the She ethnic population in China.

BACKGROUND The prevalence of migraines in the She population, a minority in China, is significantly higher than that in Han Chinese and other Asian populations. Two single nucleotide polymorphisms (SNPs) have been found to be associated with migraine susceptibility in the She population. PURPOSE This study investigated four SNPs, identified in genome-wide association studies, within migraine-susceptible loci in Han Chinese for their association with migraine susceptibility in the She population. METHODS Two-hundred unrelated migraine patients and 200 healthy controls were recruited. The SNPs examined included rs2651899 (PRDM16 ), rs2274316 (MEF2D ), rs7577262 (TRPM8) and rs11172113 (LRP1). Genotyping of the SNPs was performed by allele-specific polymerase chain reaction and direct sequencing. RESULTS No significant differences between the participants with migraines and controls (participants without migraines) were demonstrated in genotypes, alleles and allele carriage frequencies for the four SNPs. A subgroup analysis found that migraine with aura had a lower frequency of C allele positivity in rs2651899 than in healthy controls (59.6% vs. 74.5%, respectively; P < 0.034). Univariate analyses indicated that no genotype of the four SNPs had a significant association with migraines. Males had a lower risk of migraines, and advanced age was a significant risk factor for migraines in females. CONCLUSION The SNPs in four migraine susceptible loci in Han Chinese were not risk factors for migraines in a relatively small sample of the She population.
Ultrasound in the Assessment of Parotid Duct Stenosis

Parotid duct stenosis may occur with or without accompanying ductal anomalies, with associated differences in their pathogenesis and management. By identifying the characteristics of a stenosis, ultrasound (US) can assist in tailored management of parotid duct stenosis. The objective of this study was therefore to describe the US characteristics of parotid duct stenoses and to evaluate criteria for whether and in what ways these can be distinguished from each other by using US.
A Clinical Overview of Off-label Use of Gabapentinoid Drugs.

Background The gabapentinoid drugs gabapentin and pregabalin were originally developed as antiseizure drugs but now are prescribed mainly for treatment of pain. For gabapentin, the only pain-related indication approved by the US Food and Drug Administration (FDA) is postherpetic neuralgia. For pregabalin, FDA-approved indications related to pain are limited to postherpetic neuralgia, neuropathic pain associated with diabetic neuropathy or spinal cord injury, and fibromyalgia. Despite these limited indications, gabapentin and pregabalin are widely prescribed off-label for various other pain syndromes. Such use is growing, possibly because clinicians are searching increasingly for alternatives to opioids. Observations This report summarizes the limited published evidence to support off-label gabapentinoid uses, describes clinical cases in which off-label use is problematic, and notes how review articles and guidelines tend to overstate gabapentinoid effectiveness. Conclusions Clinicians who prescribe gabapentinoids off-label for pain should be aware of the limited evidence and should acknowledge to patients that potential benefits are uncertain for most off-label uses.
An update on biology, diagnosis and treatment of primary plasma cell leukemia

ABSTRACT Introduction: Primary plasma cell leukemia (PPCL) is one of the most aggressive hematological malignancies. The prognosis of PPCL patients remains poor, although some improvements have been made in recent years. Areas covered: In this review recent clinical and biological advances in PPCL are reported. Some recommendations for the practical management of these patients are provided, with a particular focus on the role of novel agents and transplant procedures. A brief description of the currently ongoing clinical trials with new drugs is also enclosed. Expert opinion: PPCL still represents a difficult challenge for all hematologists. Here the authors provide a personal view on how the current, generally unsatisfactory results in this neoplastic disorder could be improved. In particular, dedicated studies exploring alternative therapies are necessary and eagerly awaited. Such studies should possibly be based on new biological information that could be of help in identifying novel genetic biomarkers for risk stratification and new actionable molecular targets.
A Randomized Assessor-Blinded Wait-List-Controlled Trial to Assess the Effectiveness of Acupuncture in the Management of Chemotherapy-Induced Peripheral Neuropathy

Purpose: Chemotherapy-induced peripheral neuropathy is a complex side effect with few available treatment options. The aim of the study was to test the effectiveness of an 8-week course of acupuncture in the management of chemotherapy-induced peripheral neuropathy in cancer patients who were receiving or had received neurotoxic chemotherapy. Methods: Randomized assessor-blinded controlled trial with 2 arms; one arm received acupuncture twice weekly for 8 weeks, while the other arm was a wait-list control group receiving only standard care. Primary outcome was pain intensity and interference over the past week using the Brief Pain Inventory at the end of the intervention. Secondary outcomes included clinical assessment (CTCAE [Common Toxicity Criteria for Adverse Events] grading and Total Neuropathy Score–Clinical Version) and nerve conduction studies; and patient-reported outcome measures (Functional Assessment of Cancer Therapy–Gynecologic Oncology Group–Neurotoxicity Quality of Life scale and Symptom Distress Scale) assessed at baseline, end of treatment (8 weeks), week 14, and week 20 from the beginning of treatment. Results: Eighty-seven patients were randomized to the experimental arm (n = 44) and to the standard care wait-list control arm (n = 43). Significant changes at 8 weeks were detected in relation to primary outcome (pain), the clinical neurological assessment, quality of life domains, and symptom distress (all P < .05). Improvements in pain interference, neurotoxicity-related symptoms, and functional aspects of quality of life were sustained in the 14-week assessment (P < .05), as were physical and functional well-being at the 20-week assessment (P < .05). Conclusions: Acupuncture is an effective intervention for treating chemotherapy-induced peripheral neuropathy and improving patients’ quality of life and experience with neurotoxicity-related symptoms with longer term effects evident.
Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing

Ocean colour (OC) remote sensing is important for monitoring marine ecosystems. However, inverting the OC signal from the top-of-atmosphere (TOA) radiance measured by satellite sensors remains a challenge as the retrieval accuracy is highly dependent on the performance of the atmospheric correction as well as sensor calibration. In this study, the performances of four atmospheric correction (AC) algorithms, the Atmospheric and Radiometric Correction of Satellite Imagery (ARCSI), Atmospheric Correction for OLI ‘lite’ (ACOLITE), Landsat 8 Surface Reflectance (LSR) Climate Data Record (Landsat CDR), herein referred to as LaSRC (Landsat 8 Surface Reflectance Code), and the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), implemented for Landsat 8 Operational Land Imager (OLI) data, were evaluated. The OLI-derived remote sensing reflectance (Rrs) products (also known as Level-2 products) were tested against near-simultaneous in-situ data acquired from the OC component of the Aerosol Robotic Network (AERONET-OC). Analyses of the match-ups revealed that generic atmospheric correction methods (i.e., ARCSI and LaSRC), which perform reasonably well over land, provide inaccurate Level-2 products over coastal waters, in particular, in the blue bands. Between water-specific AC methods (i.e., SeaDAS and ACOLITE), SeaDAS was found to perform better over complex waters with root-mean-square error (RMSE) varying from 0.0013 to 0.0005 sr−1 for the 443 and 655 nm channels, respectively. An assessment of the effects of dominant environmental variables revealed AC retrieval errors were influenced by the solar zenith angle and wind speed for ACOLITE and SeaDAS in the 443 and 482 nm channels. Recognizing that the AERONET-OC sites are not representative of inland waters, extensive research and analyses are required to further evaluate the performance of various AC methods for high-resolution imagers like Landsat 8 and Sentinel-2 under a broad range of aquatic/atmospheric conditions.
Reheating and dark radiation after fibre inflation

We study perturbative reheating at the end of fibre inflation where the inflaton is a closed string modulus with a Starobinsky-like potential. We first derive the spectral index ns and the tensor-to-scalar ratio r as a function of the number of efoldings and the parameter R which controls slow-roll breaking corrections. We then compute the inflaton couplings and decay rates into ultra-light bulk axions and visible sector fields on D7-branes wrapping the inflaton divisor. This leads to a reheating temperature of order 1010 GeV which requires 52 efoldings. Ultra-light axions contribute to dark radiation even if Δ Neff is almost negligible in the generic case where the visible sector D7-stack supports a non-zero gauge flux. If the parameter R is chosen to be small enough, ns≃ 0.965 is then in perfect agreement with current observations while r turns out to be of order r≃ 0.007. If instead the flux on the inflaton divisor is turned off, Δ Neff≲ 0.6 which, when used as a prior for Planck data, requires ns≃ 0.99. After R is fixed to obtain such a value of ns, primordial gravity waves are larger since r≃ 0.01.
UAV-Based High Throughput Phenotyping in Citrus Utilizing Multispectral Imaging and Artificial Intelligence

Traditional plant breeding evaluation methods are time-consuming, labor-intensive, and costly. Accurate and rapid phenotypic trait data acquisition and analysis can improve genomic selection and accelerate cultivar development. In this work, a technique for data acquisition and image processing was developed utilizing small unmanned aerial vehicles (UAVs), multispectral imaging, and deep learning convolutional neural networks to evaluate phenotypic characteristics on citrus crops. This low-cost and automated high-throughput phenotyping technique utilizes artificial intelligence (AI) and machine learning (ML) to: (i) detect, count, and geolocate trees and tree gaps; (ii) categorize trees based on their canopy size; (iii) develop individual tree health indices; and (iv) evaluate citrus varieties and rootstocks. The proposed remote sensing technique was able to detect and count citrus trees in a grove of 4,931 trees, with precision and recall of 99.9% and 99.7%, respectively, estimate their canopy size with overall accuracy of 85.5%, and detect, count, and geolocate tree gaps with a precision and recall of 100% and 94.6%, respectively. This UAV-based technique provides a consistent, more direct, cost-effective, and rapid method to evaluate phenotypic characteristics of citrus varieties and rootstocks.