2,042 research outputs found
Locally adaptive factor processes for multivariate time series
In modeling multivariate time series, it is important to allow time-varying
smoothness in the mean and covariance process. In particular, there may be
certain time intervals exhibiting rapid changes and others in which changes are
slow. If such time-varying smoothness is not accounted for, one can obtain
misleading inferences and predictions, with over-smoothing across erratic time
intervals and under-smoothing across times exhibiting slow variation. This can
lead to mis-calibration of predictive intervals, which can be substantially too
narrow or wide depending on the time. We propose a locally adaptive factor
process for characterizing multivariate mean-covariance changes in continuous
time, allowing locally varying smoothness in both the mean and covariance
matrix. This process is constructed utilizing latent dictionary functions
evolving in time through nested Gaussian processes and linearly related to the
observed data with a sparse mapping. Using a differential equation
representation, we bypass usual computational bottlenecks in obtaining MCMC and
online algorithms for approximate Bayesian inference. The performance is
assessed in simulations and illustrated in a financial application
Hemisphere Mixing: a Fully Data-Driven Model of QCD Multijet Backgrounds for LHC Searches
A novel method is proposed here to precisely model the multi-dimensional
features of QCD multi-jet events in hadron collisions. The method relies on the
schematization of high-pT QCD processes as 2->2 reactions made complex by
sub-leading effects. The construction of libraries of hemispheres from
experimental data and the definition of a suitable nearest-neighbor-based
association map allow for the generation of artificial events that reproduce
with surprising accuracy the kinematics of the QCD component of original data,
while remaining insensitive to small signal contaminations. The method is
succinctly described and its performance is tested in the case of the search
for the hh->bbbb process at the LHC.Comment: 4 pages plus header, 1 figure, proceedings of EPS 2017 Venic
Relationship Between Nasal Cycle, Nasal Symptoms and Nasal Cytology
Background: The nasal cycle is the spontaneous congestion and decongestion of nasal mucosa that happens during the day. Classically, 4 types of nasal cycle patterns have been described: (1) classic, (2) parallel, (3) irregular, and (4) acyclic. Hypothalamus has been considered as the central regulator even if several external factors may influence its activity. Objective: The aim of the study was to evaluate the presence of a correlation between nasal cycle pattern, nasal cytology and nasal symptoms. Methods: Thirty healthy volunteers have been enrolled in the study. All subjects completed a Sino-Nasal Outcome Test-22 questionnaire and a Visual Analog Scale (VAS) for nasal obstruction. The nasal cycle was studied by means of peak nasal inspiratory flow. Nasal cytology has been used to evaluate the presence of local nasal inflammation. Results: Nineteen subjects showed a parallel nasal cycle pattern, while 11 showed a regular one. A parallel pattern was present in 60% of asymptomatic subjects and in 67% of the symptomatic one (P = 1). VAS for nasal obstruction did not show a significant difference between the 2 patterns of the nasal cycle (P =.398). Seventeen subjects had a normal rhinocytogram, while 13 volunteers showed a neutrophilic rhinitis; 53.8% of the subjects with a neutrophilic rhinitis showed a parallel pattern, while the remaining 46.2% had a regular one. In the case of a normal cytology, 70.6% of the volunteers had a parallel pattern and 29.4% had a regular one. Differences between the 2 groups were not statistically significant (P =.575). Conclusion: Rhinitis with neutrophils seems to not influence the nasal cycle pattern. Based on the present results, the pattern of nasal cycle does not influence subjective nasal obstruction sensation
Fast Bayesian Functional Data Analysis: Application to basal body temperature data.
In many clinical settings, it is of interest to monitor a bio-marker over time for a patient in order to estimate that patient's trajectory and to identify or predict clinically important features. For example, these features may correspond to a low or high point in the trajectory or to a sudden change. There is a need for fast algorithms for estimating functional trajectories while borrowing information from other patients about the shape and location of features in the function. Borrowing of information is crucial when observations are sparse and the interest is in prediction. In this paper, we presents an application of a fast approximate Bayes functional data analysis relying on spareness-favoring hierarchical priors for P-spline basis coefficients. The proposed method is used to rapidly estimate individual-specific functions. We present an application to basal body temperature (bbt) data
A flexible two-piece normal dynamic linear model
We construct a flexible dynamic linear model for the analysis and prediction of multivariate time series, assuming a two-piece normal initial distribution for the state vector. We derive a novel Kalman filter for this model, obtaining a two components mixture as predictive and filtering distributions. In order to estimate the covariance of the error sequences, we develop a Gibbs-sampling algorithm to perform Bayesian inference. The proposed approach is validated and compared with a Gaussian dynamic linear model in simulations and on a real data set
A retrospective study on long-term efficacy of intranasal lysine-aspirin in controlling NSAID-exacerbated respiratory disease
Purpose:
Aspirin treatment after desensitization (ATAD) represents an effective therapeutic option suitable for NSAID-exacerbated respiratory disease (N-ERD) patients with recalcitrant disease. Intranasal administration of lysine-aspirin (LAS) has been suggested as a safer and faster route than oral ATAD but evidence for its use is less strong. We investigated nasal LAS therapy long-term efficacy based on objective outcomes, smell function, polyp recurrence and need for surgery or rescue therapy. Clinical biomarkers predicting response to intranasal LAS, long-term side effects and consequences of discontinuing treatment have been evaluated.
Methods:
A retrospective analysis of a database of 60 N-ERD patients seen between 2012 and 2020 was performed in March 2021. They were followed up at 3-months, 1-, 2- and 3-years with upper and lower airway functions assessed at each follow-up.
Results:
Higher nasal airflow and smell scores were found at each follow-up in patients taking LAS (p < 0.001 and p = 0.048 respectively). No influence of LAS on pulmonary function measurements was observed. Patient on intranasal LAS showed a lower rate of revision sinus surgery when compared to those who discontinued the treatment (p < 0.001). None of the variables studied was found to influence LAS treatment response.
Conclusion:
Our study demonstrates the clinical effectiveness of long-term intranasal LAS in the management of N-ERD in terms of improved nasal airflow and olfaction and a reduced need for revision sinus surgery. Intranasal LAS is safe, being associated with a lower rate of side effects when compared to oral ATAD. However, discontinuation of the treatment at any stage is associated with a loss of clinical benefit
Hematologic and biochemical reference intervals in Shetland Sheepdogs
Background: Several breeds have physiological peculiarities that induce variations in reference intervals (RIs) compared with the general canine population. Shetland sheepdogs (SSs) are reported to be more predisposed to different diseases (eg, hyperlipidemia, gallbladder mucocele, and hypothyroidism). Consequently, a breed-specific approach is more often required. Objectives: The aim of this study was to determine whether the RIs of the general canine population could be applied to that of SSs, and to generate breed-specific RIs, where appropriate. Methods: Sixty\ua0clinically healthy and fasted SSs (36% of the population registered at the Italian Breed association) were examined. Routine hematology and biochemistry analyses were performed. The transference method was used to compare the results of SSs with the RIs of the general canine population. When these RIs were not validated, new RIs were generated according to the guidelines of the American Society of Veterinary Clinical Pathology. Differences associated with sex, age, coat color, and whether used as a pet, a herding dog, or an agility dog were also investigated. Results: The transference method validated for 30/38 SS RIs. For 6 of the remaining 8 variables, the difference with the claimed RIs could depend on preanalytical or analytical artifacts, whereas for glucose and total cholesterol, these differences could depend on breed peculiarities. However, in all SSs, the concentration of cholesterol was <12.95\ua0mmol/L. Relevant differences associated with sex, age, coat color, and use were not found. Conclusions: This study suggests that breed-specific RIs should be used for glucose and cholesterol in SSs
Near-infrared adaptive optics imaging of high redshift quasars
The properties of high redshift quasar host galaxies are studied, in order to
investigate the connection between galaxy evolution, nuclear activity, and the
formation of supermassive black holes. We combine new near-infrared
observations of three high redshift quasars (2 < z < 3), obtained at the ESO
Very Large Telescope equipped with adaptive optics, with selected data from the
literature. For the three new objects we were able to detect and characterize
the properties of the host galaxy, found to be consistent with those of massive
elliptical galaxies of M(R) ~ -24.7 for the one radio loud quasar, and M(R) ~
-23.8 for the two radio quiet quasars. When combined with existing data at
lower redshift, these new observations depict a scenario where the host
galaxies of radio loud quasars are seen to follow the expected trend of
luminous (~5L*) elliptical galaxies undergoing passive evolution. This trend is
remarkably similar to that followed by radio galaxies at z > 1.5. Radio quiet
quasars hosts also follow a similar trend but at a lower average luminosity
(~0.5 mag dimmer). The data indicate that quasar host galaxies are already
fully formed at epochs as early as ~2 Gyr after the Big Bang and then passively
fade in luminosity to the present epoch.Comment: Accepted for publication in ApJ, 24 pages, 10 figure
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