Miracle-dz/UniFAR-FTUs huggingface dataset:
Formalism and Sample Applications : The Gaussian Case

The article reviews the statistical theory of signal detection in application to analysis of deterministic gravitational-wave signals in the noise of a detector. Statistical foundations for the theory of signal detection and parameter estimation are presented. Several tools needed for both theoretical evaluation of the optimal data analysis methods and for their practical implementation are introduced. They include optimal signal-to-noise ratio, Fisher matrix, false alarm and detection probabilities, F-statistic, template placement, and fitting factor. These tools apply to the case of signals buried in a stationary and Gaussian noise. Algorithms to efficiently implement the optimal data analysis techniques are discussed. Formulas are given for a general gravitational-wave signal that includes as special cases most of the deterministic signals of interest. This review is licensed under a Creative Commons Attribution-Non-Commercial-NoDerivs 2.0 Germany License. http://creativecommons.org/licenses/by-nc-nd/2.0/de/ Imprint / Terms of Use Living Reviews in Relativity are published by the Max Planck Institute for Gravitational Physics (Albert Einstein Institute), Am Mühlenberg 1, 14476 Potsdam, Germany. ISSN 1433-8351 This review is licensed under a Creative Commons Attribution-Non-Commercial-NoDerivs 2.0 Germany License: http://creativecommons.org/licenses/by-nc-nd/2.0/de/ Because a Living Reviews article can evolve over time, we recommend to cite the article as follows: Piotr Jaranowski and Andrzej Królak, “Gravitational-Wave Data Analysis. Formalism and Sample Applications: The Gaussian Case”, Living Rev. Relativity, 8, (2005), 3. [Online Article]: cited [<date>], http://www.livingreviews. org/lrr-2005-3 The date given as <date> then uniquely identifies the version of the article you are referring to.
Lithobates catesbeianus System : Freshwater _ terrestrial Kingdom Phylum Class Order Family Animalia Chordata Amphibia Anura Ranidae

The American bullfrog (Lithobates catesbeianus (=Rana catesbeiana)) is native to North America. It has been introduced all over the world to over 40 countries and four continents. Many introductions have been intentional with the purpose of establishing new food sources for human consumption. Other populations have been established from unintentional escapes from bullfrog farms. Consequences of the introduction of non-native amphibians to native herpetofauna can be severe. The American bullfrog has been held responsible for outbreaks of the chytrid fungus found to be responsible for declining amphibian populations in Central America and elsewhere. They are also important predators and competitors of endangered native amphibians and fish. The control of this invasive in Europe partly relies upon increasing awareness, monitoring and education about the dangers of releasing pets into the wild. Strict laws are also in place to prevent further introductions. Eradication is achieved largely by physical means including shooting, spears/gigs, bow and arrow, nets and traps.
Statistica Sinica Preprint

: We consider simultaneous inference of the time-varying correlation, as a function of time, between two nonstationary time series, when their trend functions are unknown. Unlike the stationary setting, where the effect of precentering using the sample mean is trivially negligible, in the nonstationary setting, it is difficult to quantify the effect of precentering using nonparametric trend function estimators. This is mainly because the trend estimators are time-varying across different time points, which makes it difficult to quantify their cumulative interaction with the error process in a time series setting. We propose using a centering scheme that, instead of aligning with the time point at which the data are observed, aligns with the time point at which the local correlation estimation is performed. We show that the proposed centering scheme leads to simultaneous confidence bands with a solid theoretical guarantee for the time-varying correlation between two nonstationary time series when their trend functions are
Banks ’ NonInterest Income and Systemic Risk

Which bank activities contribute more to systemic risk? This paper documents that banks with higher non-interest income to interest income ratio have a higher contribution to systemic risk. This suggests that noncore banking activities (outside the roam of traditional deposit taking and lending) are associated with a larger contribution to systemic risk. After decomposing total noninterest income into two components, trading income and investment banking and venture income, we find that both components are roughly equally related to systemic risk. We also find that banks with higher trading income one-year prior to a recession earned lower returns during the recession period. No such significant effect was found for investment banking and venture capital income. a Princeton University, NBER, CEPR, CESifo, and b Rutgers Business School, respectively. We thank Linda Allen, Turan Bali, Ivan Brick, Steve Brown, Robert Engle, Kose John, Lasse Pedersen, Thomas Philippon, Matt Richardson, Anthony Saunders, and seminar participants at Baruch, Fordham, NYU and Rutgers for helpful comments and discussions. All errors remain our responsibility.
On the effects of buoyancy on higher order moments in lazy plumes

ABSTRACT Jets and plumes are shear flows created by momentum and buoyant sources. They can be classified as either pure jets, forced plumes, pure plumes, or lazy plumes. Lazy plumes are characterised as having a high source buoyancy flux relative to the momentum flux. We use direct numerical simulations to simulate lazy plumes to ascertain the effects of increasing plume ‘laziness’ on the higher order moments, such as Reynolds stresses, third order moments and turbulent kinetic energy budgets. The mildly lazy plumes behaved like most plumes in terms of higher order statistics: a self-similar collapse some distance downstream and peak values comparable to previous experiments and simulations. The highly lazy plumes did not show a self-similar collapse and, in most cases, had higher peak values in all moments. The highly lazy plumes had higher levels of turbulence intensities due to the high buoyancy flux, leading to significant buoyancy-induced turbulence production downstream.
Effect of sensor number and location on accelerometry-based vertical ground reaction force estimation during walking

Knee osteoarthritis is a major cause of global disability and is a major cost for the healthcare system. Lower extremity loading is a determinant of knee osteoarthritis onset and progression; however, technology that assists rehabilitative clinicians in optimizing key metrics of lower extremity loading is significantly limited. The peak vertical component of the ground reaction force (vGRF) in the first 50% of stance is highly associated with biological and patient-reported outcomes linked to knee osteoarthritis symptoms. Monitoring and maintaining typical vGRF profiles may support healthy gait biomechanics and joint tissue loading to prevent the onset and progression of knee osteoarthritis. Yet, the optimal number of sensors and sensor placements for predicting accurate vGRF from accelerometry remains unknown. Our goals were to: 1) determine how many sensors and what sensor locations yielded the most accurate vGRF loading peak estimates during walking; and 2) characterize how prescribing different loading conditions affected vGRF loading peak estimates. We asked 20 young adult participants to wear 5 accelerometers on their waist, shanks, and feet and walk on a force-instrumented treadmill during control and targeted biofeedback conditions prompting 5% underloading and overloading vGRFs. We trained and tested machine learning models to estimate vGRF from the various sensor accelerometer inputs and identified which combinations were most accurate. We found that a neural network using one accelerometer at the waist yielded the most accurate loading peak vGRF estimates during walking, with errors around 4.3% body weight. The waist-only configuration was able to distinguish between control and overloading conditions prescribed using biofeedback, matching measured vGRF outcomes. Including foot or shank acceleration signals in the model reduced accuracy, particularly for the overloading condition. Our results suggest that a system designed to monitor changes in walking vGRF or to deploy targeted biofeedback may only need a single accelerometer located at the waist.
Identification of anatomical and angio-architectural features of at-risk cranial dural arteriovenous fistulas using machine learning approaches

Background. Cranial arteriovenous fistulas are rare complex vascular malformations that have a bleeding risk with potential lethal consequences. Despite this, knowledge of the vascular architectural features associated with the rupture risk are not always clearly defined. Methods. We retrospectively analyzed cranial arteriovenous fistulas in terms of their anatomical and angio-architectural features as evaluated on conventional subtraction angiography: Location of the fistula, fistula architecture, venous ectasia or pouches, presence of cortical draining veins, presence of pial feeders, outflow stenosis, presence of a major sinus thrombosis, flow-associated arterial aneurysms as well as presenting symptoms. Patterns in the data were identified after multiple components analysis followed by automatic k-means clustering and their predictive power was confirmed using a shallow feedforward neural network. Results. New relevant features predictive of hemorrhage, identified by using a shallow feed-forward neural network, were outflow stenosis, in addition to venous cortical drainage and venous ectasia. The neural network achieved relatively high performance metric, with area under the receiver operating characteristic curve (ROC AUC)) of 0.88 and accuracy of 0.8. We confirmed the relevance of these findings by performing a multiple correspondence analysis followed by k-means clustering in the angiographic feature vector space, additionally identifying architecture of the fistula as relevant factor. There was good agreement between the ground truth (hemorrhage) and the cluster labels (adjusted Rand score 0.273, purity index 0.82). Conclusion. Machine learning approach confirmed the importance of previously described features (cortical drainage and venous ectasia) but also uncovered novel relevant characters (outflow stenosis and fistula architecture) for the hemorrhage risk.
Physical activity, sedentary behaviour and sleep in COPD guidelines: A systematic review

Objectives: Physical activity, sedentary and sleep behaviours have strong associations with health. This systematic review aimed to identify how clinical practice guidelines (CPGs) for the management of chronic obstructive pulmonary disease (COPD) report specific recommendations and strategies for these movement behaviours. Methods: A systematic search of databases (Medline, Scopus, CiNAHL, EMbase, Clinical Guideline), reference lists and websites identified current versions of CPGs published since 2005. Specific recommendations and strategies concerning physical activity, sedentary behaviour and sleep were extracted verbatim. The proportions of CPGs providing specific recommendations and strategies were reported. Results: From 2370 citations identified, 35 CPGs were eligible for inclusion. Of these, 21 (60%) provided specific recommendations for physical activity, while none provided specific recommendations for sedentary behaviour or sleep. The most commonly suggested strategies to improve movement behaviours were encouragement from a healthcare provider (physical activity n = 20; sedentary behaviour n = 2) and referral for a diagnostic sleep study (sleep n = 4). Conclusion: Since optimal physical activity, sedentary behaviour and sleep durations and patterns are likely to be associated with mitigating the effects of COPD, as well as with general health and well-being, there is a need for further COPD-specific research, consensus and incorporation of recommendations and strategies into CPGs.
CONVERGENCE OF STATIONARY RBF-SCHEMES FOR THE NUMERICAL SOLUTION OF EVOLUTION EQUATIONS

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. CONVERGENCE OF STATIONARY RBF-SCHEMES FOR THE NUMERICAL SOLUTION OF EVOLUTION EQUATIONS Brad Baxter, Raymond Brummelhuis
PENGARUH CITRA MEREK, HARGA DAN KUALITAS PRODUK TERHADAP MINAT PEMBELIAN ULANG KOSMETIK PT. PARAGON TECHNOLOGY AND INNOVATION

The Influence of brand image, price and product quality on PT. Paragon Technoogy and Innovation. This research was conducted on a business administration student at Mulawarman University who had purchased cosmetics.This study aims to examine the effect of brand image, price and product quality on cosmetic repurchase interests. Data distributing questionnaires to 116 respondents. The sampling technique used is non probability sampling (accidental sampling). The data obtained were analyzed using multiple linear regression techniques with the help of statistical software SPSS version 23. The brand image variable partially has no effect and is insignificant to the repurchase interest, Price partially has a negative and not significant effect on repurchase interest and the quality product variable partially has a significant effect on repurchase interest and is the most powerful or dominant variable.Suggestions to increase repurchase interest is to maintain product quality.Brand image, Price, Product Quality, Repurchase Interest
Consistent Inference for Predictive Regressions in Persistent VAR Economies

This paper studies the properties of standard predictive regressions in model economies, characterized through persistent vector autoregressive dynamics for the state variables and the associated series of interest. In particular, we consider a setting where all, or a subset, of the variables may be fractionally integrated, and note that this induces a spurious regression problem. We then propose a new inference and testing procedure - the local spectrum (LCM) approach - for the joint significance of the regressors, which is robust against the variables having different integration orders. The LCM procedure is based on (semi-)parametric fractional-filtering and band spectrum regression using a suitably selected set of frequency ordinates. We establish the asymptotic properties and explain how they differ from and extend existing procedures. Using these new inference and testing techniques, we explore the implications of assuming VAR dynamics in predictive regressions for the realized return variation. Standard least squares predictive regressions indicate that popular financial and macroeconomic variables carry valuable information about return volatility. In contrast, we find no significant evidence using our robust LCM procedure, indicating that prior conclusions may be premature. In fact, if anything, our results suggest the reverse causality, i.e., rising volatility predates adverse innovations to key macroeconomic variables. Simulations are employed to illustrate the relevance of the theoretical arguments for finite-sample inference.
But you have to remember P.J. Daniell of Sheffield

P. J. Daniell is a mysterious figure who appears at several turns in the history of mathematics in the 20th century, in the fields of integration, stochastic processes, statistics, control engineering and even in the history of English mathematical education. The main focus of this paper is on Daniell’s work in relation to the development of probability in the twentieth century. But as it seems that no survey of his work and life has been attempted for 60 years I try to consider all his contributions and place them in an appropriate historical context.
Dysosmia and dysgeusia as differential diagnostics for clinical triaging of COVID-19 cases

Smell and taste disorders are recognized as frequent, and often the only, signs occurring in the early phase of SARS-Cov-2 infection and in many cases perdure as post-viral symptoms. This evidence raised a general reconsideration of chemosensory deficits, further suggesting that their appearance can be considered as a discriminative and predictive tool to detect COVID-19 cases. In this study, encompassing the first and second pandemic wave, participants estimated their olfactory and gustatory sensitivity, plus they were administered the validated Brief Smell Identification Test (BSIT). We observed that smell and taste impairments were mainly experienced by COVID-19-positive subjects with comparable severity of respiratory symptoms as non-COVID-19 patients. In addition, we noticed that the diagnostic power of subjective olfactory assessments upon SARS-Cov-2 infection is comparable to quantitative evaluation, suggesting that self-reporting could be adopted as the first line of intervention, anticipating more exhaustive procedures aimed at containing COVID-19 diffusion and consequently preserving general health. Overall, results from this work share similarity with other studies, therefore further underlying that olfactory and gustatory disbalance can be distinctive hallmarks in COVID-19 continuum.
Why some countries but not others? Urbanisation, GDP and endemic disease predict global SARS-CoV-2 excess mortality patterns.

The global impact of the SARS-CoV-2 pandemic has been uneven, with some regions experiencing significant excess mortality while others have been relatively unaffected. Yet factors which predict this variation remain enigmatic, particularly at large spatial scales. We used spatially explicit Bayesian models that integrate socio-demographic and endemic disease data at the country level to provide robust global estimates of excess SARS-CoV-2 mortality (P scores) for the years 2020 and 2021. We find that gross domestic product (GDP), spatial patterns and urbanization are strong predictors of excess mortality, with countries characterized by low GDP but high urbanization experiencing the highest levels of excess mortality. Intriguingly, we also observed that the prevalence of malaria and human immunodeficiency virus (HIV) are associated with country-level SARS-CoV-2 excess mortality in Africa and the Western Pacific, whereby countries with low HIV prevalence but high malaria prevalence tend to have lower levels of excess mortality. While these associations are correlative in nature at the macro-scale, they emphasize that patterns of endemic disease and socio-demographic factors are needed to understand the global dynamics of SARS-CoV-2.
Longitudinal enlargement of choroid plexus is associated with inflammation and neurodegeneration in RRMS patients

Background: The Choroid Plexus (CP) plays a potential role in the initiation and propagation of neuroinflammatory processes in MS. However, the progressive change of the CP and its associations with biomarkers of acute and chronic inflammation, along with MS-related brain structure atrophy, have not been investigated. Objective: This study aims to explore the longitudinal dynamics of the CP in RRMS patients and assess its relationship with inflammation and with atrophy in various brain compartments. Methods: 57 RRMS patients were examined annually for a minimum of 60 months using following MRI protocols: pre- and post-contrast (gadolinium) Sagittal 3D T1, FLAIR CUBE, diffusion weighted MRI. CP was manually segmented at baseline and last follow-up and normalised by head size. Annually lesion segmentation was performed by iQ-MSTM software suite and brain was segmented using AssemblyNet. Results: Over the study period, the volume of CP increased by an average of 1.4% annually. The magnitude of CP enlargement significantly correlated with central brain atrophy, and to a lesser extent, total brain atrophy, white matter, and deep grey matter atrophy. Furthermore, progressive CP enlargement was significantly associated with the volume and severity of chronic lesion expansion (r=0.66, p<0.001), but not with the number or volume of new lesions. Conclusion: Our findings indicate that ongoing inflammatory activity in the CP is linked to low-grade demyelination at the rim of chronic lesions and associated neurodegeneration of periventricular white and grey matter.
Untreated clinical course of cerebral cavernous malformations: a prospective, population-based cohort study

Citation for published version: Al-Shahi Salman, R, Hall, JM, Horne, MA, Moultrie, F, Josephson, CB, Bhattacharya, JJ, Counsell, CE, Murray, GD, Papanastassiou, V, Ritchie, V, Roberts, RC, Sellar, RJ, Warlow, CP & Scottish Audit of Intracranial Vascular Malformations (SAIVMs) collaborators 2012, 'Untreated clinical course of cerebral cavernous malformations: a prospective, population-based cohort study', Lancet Neurology, vol. 11, no. 3, pp. 217-224. https://doi.org/10.1016/S1474-4422(12)70004-2
Leaf physiological and morphological constraints of water-use efficiency in C3 plants

Abstract The increasing evaporative demand due to climate change will significantly affect the balance of carbon assimilation and water losses of plants worldwide. The development of crop varieties with improved water-use efficiency (WUE) will be critical for adapting agricultural strategies under predicted future climates. This review aims to summarize the most important leaf morpho-physiological constraints of WUE in C3 plants and identify gaps in knowledge. From the carbon gain side of the WUE, the discussed parameters are mesophyll conductance, carboxylation efficiency and respiratory losses. The traits and parameters affecting the waterside of WUE balance discussed in this review are stomatal size and density, stomatal control and residual water losses (cuticular and bark conductance), nocturnal conductance and leaf hydraulic conductance. In addition, we discussed the impact of leaf anatomy and crown architecture on both the carbon gain and water loss components of WUE. There are multiple possible targets for future development in understanding sources of WUE variability in plants. We identified residual water losses and respiratory carbon losses as the greatest knowledge gaps of whole-plant WUE assessments. Moreover, the impact of trichomes, leaf hydraulic conductance and canopy structure on plants’ WUE is still not well understood. The development of a multi-trait approach is urgently needed for a better understanding of WUE dynamics and optimization.