scholarly journals Measurement of theνeand total8B solar neutrino fluxes with the Sudbury Neutrino Observatory phase-III data set

2013 ◽  
Vol 87 (1) ◽  
Author(s):  
B. Aharmim ◽  
S. N. Ahmed ◽  
J. F. Amsbaugh ◽  
J. M. Anaya ◽  
A. E. Anthony ◽  
...  
Keyword(s):  
Solar Neutrino ◽  
Phase Iii ◽  
Sudbury Neutrino Observatory ◽  
Data Set ◽  
Neutrino Fluxes

scholarly journals Determination of theνeand totalB8solar neutrino fluxes using the Sudbury Neutrino Observatory Phase I data set

2007 ◽  
Vol 75 (4) ◽  
Author(s):  
B. Aharmim ◽  
Q. R. Ahmad ◽  
S. N. Ahmed ◽  
R. C. Allen ◽  
T. C. Andersen ◽  
...  
Keyword(s):  
Phase I ◽  
Sudbury Neutrino Observatory ◽  
Data Set ◽  
Neutrino Fluxes

NONLINEARITY AND CHAOS IN 8B SOLAR NEUTRINO FLUX SIGNALS FROM SUDBURY NEUTRINO OBSERVATORY

Fractals ◽  
2012 ◽  
Vol 20 (01) ◽  
pp. 17-32 ◽  
Author(s):  
MOFAZZAL H. KHONDEKAR ◽  
DIPENDRA N. GHOSH ◽  
KOUSHIK GHOSH ◽  
ANUP KUMAR BHATTACHARYA
Keyword(s):  
Solar Neutrino ◽  
Neutrino Flux ◽  
Recurrence Plot ◽  
Sudbury Neutrino Observatory ◽  
Largest Lyapunov Exponent ◽  
Process Dynamics ◽  
Quantification Analysis ◽  
Long Term Forecasting ◽  
Short Term Forecasting ◽  
Neutrino Fluxes

The Sudbury neutrino observatory (SNO) detects 8 B solar neutrino fluxes from both the D2O and Salt detector. In the present analysis we have taken into consideration the flux data from 2nd November, 1999 to 27th May, 2001 from the D2O detector and that from 26th July, 2001 to 28th August, 2003 from the Salt detector. We have applied Delay Vector Variance analysis, 0-1 test, correlation dimension analysis, largest Lyapunov exponent method, recurrence plot and recurrence quantification analysis to explore the complexity and chaosity in these two time series. Present study reveals deterministic chaotic behaviour of these two signals which in turn suggests that long-term forecasting is not possible for these two signals but short-term forecasting can be made provided the model for the process dynamics is known to us.

scholarly journals Characterisation of MS phenotypes across the age span using a novel data set integrating 34 clinical trials (NO.MS cohort): Age is a key contributor to presentation

2021 ◽  
pp. 135245852098863
Author(s):  
Frank Dahlke ◽  
Douglas L Arnold ◽  
Piet Aarden ◽  
Habib Ganjgahi ◽  
Dieter A Häring ◽  
...  
Keyword(s):  
Disease Activity ◽  
Brain Volume ◽  
Young Patients ◽  
Clinical Trial Data ◽  
Study Data ◽  
Phase Iii ◽  
Brain Images ◽  
Data Set ◽  
Brain Volume Loss ◽  
Phase Iii Study

Background: The Oxford Big Data Institute, multiple sclerosis (MS) physicians and Novartis aim to address unresolved questions in MS with a novel comprehensive clinical trial data set. Objective: The objective of this study is to describe the Novartis–Oxford MS (NO.MS) data set and to explore the relationships between age, disease activity and disease worsening across MS phenotypes. Methods: We report key characteristics of NO.MS. We modelled MS lesion formation, relapse frequency, brain volume change and disability worsening cross-sectionally, as a function of patients’ baseline age, using phase III study data (≈8000 patients). Results: NO.MS contains data of ≈35,000 patients (>200,000 brain images from ≈10,000 patients), with >10 years follow-up. (1) Focal disease activity is highest in paediatric patients and decreases with age, (2) brain volume loss is similar across age and phenotypes and (3) the youngest patients have the lowest likelihood (<25%) of disability worsening over 2 years while risk is higher (25%–75%) in older, disabled or progressive MS patients. Young patients benefit most from treatment. Conclusion: NO.MS will illuminate questions related to MS characterisation, progression and prognosis. Age modulates relapse frequency and, thus, the phenotypic presentation of MS. Disease worsening across all phenotypes is mediated by age and appears to some extent be independent from new focal inflammatory activity.

scholarly journals Training and deploying a deep learning model for endoscopic severity grading in ulcerative colitis using multicenter clinical trial data

2021 ◽  
Vol 14 ◽  
pp. 263177452199062
Author(s):  
Benjamin Gutierrez Becker ◽  
Filippo Arcadu ◽  
Andreas Thalhammer ◽  
Citlalli Gamez Serna ◽  
Owen Feehan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Ulcerative Colitis ◽  
Clinical Trials ◽  
Deep Learning ◽  
Mayo Clinic ◽  
Automated System ◽  
Phase Iii ◽  
Plain Language ◽  
Data Set ◽  
Endoscopic Videos

Introduction: The Mayo Clinic Endoscopic Subscore is a commonly used grading system to assess the severity of ulcerative colitis. Correctly grading colonoscopies using the Mayo Clinic Endoscopic Subscore is a challenging task, with suboptimal rates of interrater and intrarater variability observed even among experienced and sufficiently trained experts. In recent years, several machine learning algorithms have been proposed in an effort to improve the standardization and reproducibility of Mayo Clinic Endoscopic Subscore grading. Methods: Here we propose an end-to-end fully automated system based on deep learning to predict a binary version of the Mayo Clinic Endoscopic Subscore directly from raw colonoscopy videos. Differently from previous studies, the proposed method mimics the assessment done in practice by a gastroenterologist, that is, traversing the whole colonoscopy video, identifying visually informative regions and computing an overall Mayo Clinic Endoscopic Subscore. The proposed deep learning–based system has been trained and deployed on raw colonoscopies using Mayo Clinic Endoscopic Subscore ground truth provided only at the colon section level, without manually selecting frames driving the severity scoring of ulcerative colitis. Results and Conclusion: Our evaluation on 1672 endoscopic videos obtained from a multisite data set obtained from the etrolizumab Phase II Eucalyptus and Phase III Hickory and Laurel clinical trials, show that our proposed methodology can grade endoscopic videos with a high degree of accuracy and robustness (Area Under the Receiver Operating Characteristic Curve = 0.84 for Mayo Clinic Endoscopic Subscore ⩾ 1, 0.85 for Mayo Clinic Endoscopic Subscore ⩾ 2 and 0.85 for Mayo Clinic Endoscopic Subscore ⩾ 3) and reduced amounts of manual annotation. Plain language summary Patient, caregiver and provider thoughts on educational materials about prescribing and medication safety Artificial intelligence can be used to automatically assess full endoscopic videos and estimate the severity of ulcerative colitis. In this work, we present an artificial intelligence algorithm for the automatic grading of ulcerative colitis in full endoscopic videos. Our artificial intelligence models were trained and evaluated on a large and diverse set of colonoscopy videos obtained from concluded clinical trials. We demonstrate not only that artificial intelligence is able to accurately grade full endoscopic videos, but also that using diverse data sets obtained from multiple sites is critical to train robust AI models that could potentially be deployed on real-world data.

Understanding the Importance of Capturing Climate and Occupancy Trends During Concept-Stage Sustainable Building Design

2018 ◽  
Author(s):  
Sean Lin ◽  
Bahaa Albarhami ◽  
Salvador Mayoral ◽  
Joseph Piacenza
Keyword(s):  
Energy Consumption ◽  
Simulation Models ◽  
Building Design ◽  
Building Energy ◽  
Simulation Software ◽  
Phase Iii ◽  
Data Set ◽  
Climate Zones ◽  
Leed Certification ◽  
Actual Energy Consumption

This paper presents a comparison of concept stage computational model predictions to capture how building energy consumption is affected by different climate zones. The California State University, Fullerton (CSUF) Student Housing Phase III, which received a Platinum Leadership in Energy and Environmental Design (LEED) certification for the Building Design and Construction category, and its performance in a LEED California Nonresidential Title 24 (NRT24) and ASHRAE 90.1 climate zones is used as a case study to illustrate the method. Through LEED approved simulation software, the standard compliant energy simulation models are compared to the occupancy scheduled models along with the actual energy consumption in different climate zones. The results provide insight to how variables within student dormitory life affect total building energy usage. Total amount of energy consumed per area is one new factor providing understanding into occupancy trends. This new data set reveals more understanding regarding how and where the energy is consumed to maintain a comfortable learning environment.

scholarly journals Volcanology and new geophysics: reality and prospects for example Yellowstone volcano

2019 ◽  
pp. 25-35
Author(s):  
O. B. Khavroshkin ◽  
S. A. Fedotov ◽  
V. V. Tsyplakov ◽  
A. N. Boiko
Keyword(s):  
Solar System ◽  
Detailed Analysis ◽  
Volcanic Activity ◽  
Solar Neutrino ◽  
Strong Influence ◽  
Open Systems ◽  
Neutrino Flux ◽  
Solar Neutrino Flux ◽  
New Geophysics ◽  
Neutrino Fluxes

The dynamic portrait of Yellowstone volcano activity in the form of detailed analysis of key parameters and in real time is presented. Some preliminary findings show that active volcanoes are energetically open systems with a strong influence of the external astrophysical component, primarily solar muon and neutrino fluxes. This should be taken into account when predicting their activity. The astrophysical component of activity may be one of the main mechanisms synchronizing the state of supervolcanoes. The astrophysical component of volcanic activity can exist in other volcanoes of the terrestrial planets of the Solar system, which also experience the synchronizing effects of the solar neutrino flux, that is, the planets of the Solar system can be found to have common rhythms of volcanic activity.

scholarly journals Solar Neutrinos Spectroscopy with Borexino Phase-II

2018 ◽  
Author(s):  
Lino Miramonti ◽  
M. Agostini ◽  
K. Altenmueller ◽  
S. Appel ◽  
V. Atroshchenko ◽  
...  
Keyword(s):  
Phase Ii ◽  
Solar Neutrino ◽  
Wide Band ◽  
Solar Neutrinos ◽  
Low Energy ◽  
Fusion Reactions ◽  
Oscillation Mechanism ◽  
Upper Limits ◽  
Flux Measurements ◽  
Neutrino Fluxes

Solar neutrinos have played a central role in the discovery of the neutrino oscillation mechanism. They still are proving to be a unique tool to help investigate the fusion reactions that power stars and further probe basic neutrino properties. The Borexino neutrino observatory has been operationally acquiring data at Laboratori Nazionali del Gran Sasso in Italy since 2007. Its main goal is the real-time study of low energy neutrinos (solar or originated elsewhere, such as geo-neutrinos). The latest analysis of experimental data, taken during the so-called Borexino Phase-II (2011-present), will be showcased in this talk - yielding new high-precision, simultaneous wide band flux measurements of the four main solar neutrino components belonging to the "pp" fusion chain (pp, pep, 7Be, 8B), as well as upper limits on the remaining two solar neutrino fluxes (CNO and hep).

Prostate-specific antigen as a measure of disease outcome in metastatic hormone-refractory prostate cancer.

1993 ◽  
Vol 11 (4) ◽  
pp. 607-615 ◽  
Author(s):  
W K Kelly ◽  
H I Scher ◽  
M Mazumdar ◽  
V Vlamis ◽  
M Schwartz ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Prostate Specific Antigen ◽  
Univariate Analysis ◽  
Prognostic Significance ◽  
Specific Antigen ◽  
Phase Iii ◽  
Cancer Center ◽  
Hormone Refractory Prostate Cancer ◽  
Data Set ◽  
Hormone Refractory

PURPOSE To evaluate the prognostic significance of pretreatment parameters and posttherapy declines in prostate-specific antigen (PSA) in relation to the survival of patients with hormone-refractory prostate cancer. PATIENTS AND METHODS One hundred ten assessable patients treated on seven sequential protocols at Memorial Sloan-Kettering Cancer Center (MSKCC) for hormone-refractory prostate cancer were evaluated for 29 different pretherapy and posttherapy parameters, including a posttherapy decline in PSA of 50% and 80% from baseline. RESULTS In the univariate analysis, initial Karnofsky performance status (KPS) > or = 80% was associated with a favorable outcome (P = .005), while age, extent of disease on bone scan, and individual sites of metastatic disease were not significant. No difference in survival was observed between patients with measurable or assessable (bone only) disease. Initial hemoglobin (HGB; P = .0012), alkaline phosphatase (ALK; P = .0015), and lactate dehydrogenase (LDH; P = .0002) levels were significant discriminators, while the initial PSA was not. Using a landmark analysis, a significantly longer median survival rate was observed for patients with a > or = 50% decline in PSA (median not reached) versus patients with a less than 50% decline in PSA (median, 8.6 months; P = .0001). Multivariate analysis using the Cox proportional hazards model showed that a > or = 50% decline in PSA (P = .0004) and the natural log of LDH (P = .0001) were the two most significant variables predicting survival. The model was confirmed on an independent data set from the Norwegian Radium Hospital (NRH) in Oslo, Norway. CONCLUSION The results suggest that posttherapy PSA declines can be used as a surrogate end point to evaluate new agents in hormone-refractory prostate cancer. The criteria for response need prospective validation in phase III trials.

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