scholarly journals CLOUD ANALYTICS FOR SHORT-TERM LTE METRIC PREDICTION - CAPACITY, CLOUD FRAMEWORK AND PERFORMANCE

2016 ◽  
Vol 4 (4) ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 99
Author(s):  
Catherine Johnson ◽  
Tim Snelling ◽  
James Huntington ◽  
Jules Taylor-Pickard ◽  
Helen Warren ◽  
...  

2017 ◽  
Author(s):  
Aymen A. Elfiky ◽  
Maximilian J. Pany ◽  
Ravi B. Parikh ◽  
Ziad Obermeyer

ABSTRACTBackgroundCancer patients who die soon after starting chemotherapy incur costs of treatment without benefits. Accurately predicting mortality risk from chemotherapy is important, but few patient data-driven tools exist. We sought to create and validate a machine learning model predicting mortality for patients starting new chemotherapy.MethodsWe obtained electronic health records for patients treated at a large cancer center (26,946 patients; 51,774 new regimens) over 2004-14, linked to Social Security data for date of death. The model was derived using 2004-11 data, and performance measured on non-overlapping 2012-14 data.Findings30-day mortality from chemotherapy start was 2.1%. Common cancers included breast (21.1%), colorectal (19.3%), and lung (18.0%). Model predictions were accurate for all patients (AUC 0.94). Predictions for patients starting palliative chemotherapy (46.6% of regimens), for whom prognosis is particularly important, remained highly accurate (AUC 0.92). To illustrate model discrimination, we ranked patients initiating palliative chemotherapy by model-predicted mortality risk, and calculated observed mortality by risk decile. 30-day mortality in the highest-risk decile was 22.6%; in the lowest-risk decile, no patients died. Predictions remained accurate across all primary cancers, stages, and chemotherapies—even for clinical trial regimens that first appeared in years after the model was trained (AUC 0.94). The model also performed well for prediction of 180-day mortality (AUC 0.87; mortality 74.8% in the highest risk decile vs. 0.2% in the lowest). Predictions were more accurate than data from randomized trials of individual chemotherapies, or SEER estimates.InterpretationA machine learning algorithm accurately predicted short-term mortality in patients starting chemotherapy using EHR data. Further research is necessary to determine generalizability and the feasibility of applying this algorithm in clinical settings.


2021 ◽  
Vol 5 (1) ◽  
pp. 123-142
Author(s):  
Kim Foong Jee ◽  
Jia En Joanne Ngui ◽  
Pei Pei Jessica Poh ◽  
Wai Loon Chan ◽  
Yet Siang Wong

This paper examines the relationship between capital structure and performance of firms. The study is confined to plantation sector companies in Malaysia and is based on a sample of 39 firms which listed in Bursa Malaysia for the period from 2009 to 2019. This study uses two performance measures which are ROA and ROE as the dependent variable. Besides, the capital structure measures are the short-term debt, long-term debt, total debt and firm growth, which as the independent variables. Size will be the control variable in this study. Moreover, a fixed-effect panel regression analysis has been used to analyse the impact of capital structure on firm performance. The results indicate that firm performance, which is in term of ROA, have an insignificant relationship with short-term debt (STD) and long-term debt (LTD). For the total debt (TD) and growth, there is a significant relationship with ROA. However, for the performance measured by ROE, it has an insignificant relationship with short-term debt (STD), long-term debt (LTD) and total debt (TD). Furthermore, there is a significant relationship between the growth and the performance firms from plantation sector in Malaysia.


2017 ◽  
Vol 12 (7) ◽  
pp. 886-892 ◽  
Author(s):  
Christos K. Argus ◽  
James R. Broatch ◽  
Aaron C. Petersen ◽  
Remco Polman ◽  
David J. Bishop ◽  
...  

Context:An athlete’s ability to recover quickly is important when there is limited time between training and competition. As such, recovery strategies are commonly used to expedite the recovery process.Purpose:To determine the effectiveness of both cold-water immersion (CWI) and contrast water therapy (CWT) compared with control on short-term recovery (<4 h) after a single full-body resistance-training session.Methods:Thirteen men (age 26 ± 5 y, weight 79 ± 7 kg, height 177 ± 5 cm) were assessed for perceptual (fatigue and soreness) and performance measures (maximal voluntary isometric contraction [MVC] of the knee extensors, weighted and unweighted countermovement jumps) before and immediately after the training session. Subjects then completed 1 of three 14-min recovery strategies (CWI, CWT, or passive sitting [CON]), with the perceptual and performance measures reassessed immediately, 2 h, and 4 h postrecovery.Results:Peak torque during MVC and jump performance were significantly decreased (P < .05) after the resistance-training session and remained depressed for at least 4 h postrecovery in all conditions. Neither CWI nor CWT had any effect on perceptual or performance measures over the 4-h recovery period.Conclusions:CWI and CWT did not improve short-term (<4-h) recovery after a conventional resistance-training session.


2020 ◽  
Vol 12 (16) ◽  
pp. 2545 ◽  
Author(s):  
Andrea Monti-Guarnieri ◽  
Marco Manzoni ◽  
Davide Giudici ◽  
Andrea Recchia ◽  
Stefano Tebaldini

The paper addresses the temporal stability of distributed targets, particularly referring to vegetation, to evaluate the degradation affecting synthetic aperture radar (SAR) imaging and repeat-pass interferometry, and provide efficient SAR simulation schemes for generating big dataset from wide areas. The models that are mostly adopted in literature are critically reviewed, and aim to study decorrelation in a range of time (from hours to days), of interest for long-term SAR, such as ground-based or geosynchronous, or repeat-pass SAR interferometry. It is shown that none of them explicitly account for a decorrelation occurring in the short-term. An explanation is provided, and a novel temporal decorrelation model is proposed to account for that fast decorrelation. A formal method is developed to evaluate the performance of SAR focusing, and interferometry on a homogenous, stationary scene, in terms of Signal-to-Clutter Ratio (SCR), and interferometric coherence. Finally, an efficient implementation of an SAR simulator capable of handling the realistic case of heterogeneous decorrelation over a wide area is discussed. Examples are given by assuming two geostationary SAR missions in C and X band.


Author(s):  
Vernon Webb ◽  
Michael Hickner ◽  
Donald Baird ◽  
Scott Case ◽  
John Lesko

The electrical and mechanical properties of new lightweight graphite polymeric separator plates aged in a PEM fuel cell were investigated to assess their resistance to short-term durability. While the changes in electrical properties of great interest to the operation of the fuel cell, mechanical and dimensional stability over the life of the cell are critical. Thus, new polymeric based separator plates developed at Virginia Tech were aged under standard operating conditions in a PEM fuel cell over 300 hours at low pressure and 85°C. A comparison of conductivity, stiffness and strength of aged plates was made to as manufactured and unaged plates. Over the aging period, electrical conductivity did not decline even as the fuel cell performance showed some changes as evidenced by polarization curves. However, the mechanical strength of the monopolar plates was observed to declined less than 10% after 300 hours of fuel cell operation, due to the lack of stability of the polyester resin used to facilitate the rapid manufacturing of these new plates. These property changes were found to be independent of aging on the reduction and oxidation sides. Further work continues on plates formed through both fiber wet lay technology and those produced by compression molding of unique graphite filled epoxy systems, and to improve the electrochemical performance of cells fabricated using the resulting plates to levels comparable to those observed when using existing plate materials.


2010 ◽  
Vol 108 (4) ◽  
pp. 898-905 ◽  
Author(s):  
Martin Thomassen ◽  
Peter M. Christensen ◽  
Thomas P. Gunnarsson ◽  
Lars Nybo ◽  
Jens Bangsbo

The present study examined muscle adaptations and alterations in performance of highly trained soccer players with intensified training or training cessation. Eighteen elite soccer players were, for a 2-wk period, assigned to either a group that performed high-intensity training with a reduction in the amount of training (HI, n = 7), or an inactivity group without training (IN, n = 11). HI improved ( P < 0.05) performance of the 4th, 6th, and 10th sprint in a repeated 20-m sprint test, and IN reduced ( P < 0.05) performance in the 5th to the 10th sprints after the 2-wk intervention period. In addition, the Yo-Yo intermittent recovery level 2 test performance of IN was lowered from 845 ± 48 to 654 ± 30 m. In HI, the protein expression of the Na+-K+ pump α2-isoform was 15% higher ( P < 0.05) after the intervention period, whereas no changes were observed in α1- and β1-isoform expression. In IN, Na+-K+ pump expression was not changed. In HI, the FXYD1ser68-to-FXYD1 ratio was 27% higher ( P < 0.01) after the intervention period, and, in IN, the AB_FXYD1ser68 signal was 18% lower ( P < 0.05) after inactivity. The change in FXYD1ser68-to-FXYD1 ratio was correlated ( r2 = 0.35; P < 0.05) with change in performance in repeated sprint test. The present data suggest that short-term intensified training, even for trained soccer players, can increase muscle Na+-K+ pump α2-isoform expression, and that cessation of training for 2 wk does not affect the expression of Na+-K+ pump isoforms. Resting phosphorylation status of the Na+-K+ pump is changed by training and inactivity and may play a role in performance during repeated, intense exercise.


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