132 research outputs found
The Levy sections theorem: an application to econophysics
We employ the Levy sections theorem in the analysis of selected dollar exchange rate time series. The theorem is an extension of the classical central limit theorem and offers an alternative to the most usual analysis of the sum variable. We find that the presence of fat tails can be related to the local volatility pattern of the series.
El papel de la movilidad geográfica en la expansión de Aedes albopictus y en la transmisión de enfermedades infecciosas
Ponencia sobre el papel de la movilidad geográfica en la expansión de Aedes albopictus y en la transmisión de enfermedades infecciosas. Se estudia la dispersión de Aedes albopictus basados en el análisis de datos de la invasión en la provincia de Girona durante 2009-2011; y la dispersión epidémica en redes desarrollando un marco teórico para la modelización de la propagación de enfermedades infecciosas.N
The Levy sections theorem: an application to econophysics
We employ the Levy sections theorem in the analysis of selected dollar exchange
rate time series. The theorem is an extension of the classical central limit theorem
and offers an alternative to the most usual analysis of the sum variable. We find
that the presence of fat tails can be related to the local volatility pattern of the
series
ACED: Accelerated Computational Electrochemical systems Discovery
Large-scale electrification is vital to addressing the climate crisis, but
many engineering challenges remain to fully electrifying both the chemical
industry and transportation. In both of these areas, new electrochemical
materials and systems will be critical, but developing these systems currently
relies heavily on computationally expensive first-principles simulations as
well as human-time-intensive experimental trial and error. We propose to
develop an automated workflow that accelerates these computational steps by
introducing both automated error handling in generating the first-principles
training data as well as physics-informed machine learning surrogates to
further reduce computational cost. It will also have the capacity to include
automated experiments "in the loop" in order to dramatically accelerate the
overall materials discovery pipeline.Comment: 4 pages, 1 figure, accepted to NeurIPS Climate Change and AI Workshop
2020, updating acknowledgements and citation
Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors
Brain tumors are the most common solid tumors and the leading cause of
cancer-related death among children. Tumor segmentation is essential in
surgical and treatment planning, and response assessment and monitoring.
However, manual segmentation is time-consuming and has high inter-operator
variability, underscoring the need for more efficient methods. We compared two
deep learning-based 3D segmentation models, DeepMedic and nnU-Net, after
training with pediatric-specific multi-institutional brain tumor data using
based on multi-parametric MRI scans.Multi-parametric preoperative MRI scans of
339 pediatric patients (n=293 internal and n=46 external cohorts) with a
variety of tumor subtypes, were preprocessed and manually segmented into four
tumor subregions, i.e., enhancing tumor (ET), non-enhancing tumor (NET), cystic
components (CC), and peritumoral edema (ED). After training, performance of the
two models on internal and external test sets was evaluated using Dice scores,
sensitivity, and Hausdorff distance with reference to ground truth manual
segmentations. Dice score for nnU-Net internal test sets was (mean +/- SD
(median)) 0.9+/-0.07 (0.94) for WT, 0.77+/-0.29 for ET, 0.66+/-0.32 for NET,
0.71+/-0.33 for CC, and 0.71+/-0.40 for ED, respectively. For DeepMedic the
Dice scores were 0.82+/-0.16 for WT, 0.66+/-0.32 for ET, 0.48+/-0.27, for NET,
0.48+/-0.36 for CC, and 0.19+/-0.33 for ED, respectively. Dice scores were
significantly higher for nnU-Net (p<=0.01). External validation of the trained
nnU-Net model on the multi-institutional BraTS-PEDs 2023 dataset revealed high
generalization capability in segmentation of whole tumor and tumor core with
Dice scores of 0.87+/-0.13 (0.91) and 0.83+/-0.18 (0.89), respectively.
Pediatric-specific data trained nnU-Net model is superior to DeepMedic for
whole tumor and subregion segmentation of pediatric brain tumors
Clinical chronobiology: a timely consideration in critical care medicine
A fundamental aspect of human physiology is its cyclical nature over a 24-h period, a feature conserved across most life on Earth. Organisms compartmentalise processes with respect to time in order to promote survival, in a manner that mirrors the rotation of the planet and accompanying diurnal cycles of light and darkness. The influence of circadian rhythms can no longer be overlooked in clinical settings; this review provides intensivists with an up-to-date understanding of the burgeoning field of chronobiology, and suggests ways to incorporate these concepts into daily practice to improve patient outcomes. We outline the function of molecular clocks in remote tissues, which adjust cellular and global physiological function according to the time of day, and the potential clinical advantages to keeping in time with them. We highlight the consequences of "chronopathology", when this harmony is lost, and the risk factors for this condition in critically ill patients. We introduce the concept of "chronofitness" as a new target in the treatment of critical illness: preserving the internal synchronisation of clocks in different tissues, as well as external synchronisation with the environment. We describe methods for monitoring circadian rhythms in a clinical setting, and how this technology may be used for identifying optimal time windows for interventions, or to alert the physician to a critical deterioration of circadian rhythmicity. We suggest a chronobiological approach to critical illness, involving multicomponent strategies to promote chronofitness (chronobundles), and further investment in the development of personalised, time-based treatment for critically ill patients
Robust estimation of bacterial cell count from optical density
Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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