scholarly journals RECCAP uncertainty

2012 ◽  
Vol 9 (2) ◽  
pp. 1829-1868 ◽  
Author(s):  
I. G. Enting ◽  
P. J. Rayner ◽  
P. Ciais
Keyword(s):  
Standard Deviation ◽  
Probability Distributions ◽  
Location Parameter ◽  
Carbon Budgets ◽  
Space And Time ◽  
Estimation Procedures ◽  
Full Form ◽  
The Mean ◽  
Almost All ◽  
The Impact

Abstract. Characterisation of regional carbon budgets and processes (the overall task addressed in this series of articles) is inherently a statistical task. In full form this means that almost all quantities used or produced are realizations or instances of probability distributions. We usually compress the description of these distributions by using some kind of location parameter (e.g. the mean) and some measure of spread or uncertainty (e.g. the standard deviation). Characterising and calculating these uncertainties, and their structure in space and time, is as important as the location parameter but uncertainties are both harder to calculate and harder to interpret. In this paper we describe the various classes of uncertainty that arise in a process like RECCAP and describe how they interact in formal estimation procedures. We also point out the impact these uncertainties will have on the various RECCAP synthesis activities.

scholarly journals Carbon Cycle Uncertainty in REgional Carbon Cycle Assessment and Processes (RECCAP)

2012 ◽  
Vol 9 (8) ◽  
pp. 2889-2904 ◽  
Author(s):  
I. G. Enting ◽  
P. J. Rayner ◽  
P. Ciais
Keyword(s):  
Standard Deviation ◽  
Carbon Cycle ◽  
Probability Distributions ◽  
Location Parameter ◽  
Carbon Budgets ◽  
Space And Time ◽  
Full Form ◽  
The Mean ◽  
Almost All ◽  
The Impact

Abstract. Characterisation of estimates of regional carbon budgets and processes is inherently a statistical task. In full form this means that almost all quantities used or produced are realizations or instances of probability distributions. We usually compress the description of these distributions by using some kind of location parameter (e.g. the mean) and some measure of spread or uncertainty (e.g. the standard deviation). Characterising and calculating these uncertainties, and their structure in space and time, is as important as the location parameter, but uncertainties are both hard to calculate and hard to interpret. In this paper we describe the various classes of uncertainty that arise in a process like RECCAP and describe how they interact in formal estimation procedures. We also point out the impact these uncertainties will have on the various RECCAP synthesis activities.

Asteroid and Comet Impact Speeds upon Mars: Significance for Panspermia and the Supply of Organics

1997 ◽  
Vol 161 ◽  
pp. 197-201 ◽  
Author(s):  
Duncan Steel
Keyword(s):  
Probability Distributions ◽  
Regions Of Interest ◽  
Significant Fraction ◽  
Organic Chemicals ◽  
Impact Speed ◽  
The Mean ◽  
The Impact

AbstractWhilst lithopanspermia depends upon massive impacts occurring at a speed above some limit, the intact delivery of organic chemicals or other volatiles to a planet requires the impact speed to be below some other limit such that a significant fraction of that material escapes destruction. Thus the two opposite ends of the impact speed distributions are the regions of interest in the bioastronomical context, whereas much modelling work on impacts delivers, or makes use of, only the mean speed. Here the probability distributions of impact speeds upon Mars are calculated for (i) the orbital distribution of known asteroids; and (ii) the expected distribution of near-parabolic cometary orbits. It is found that cometary impacts are far more likely to eject rocks from Mars (over 99 percent of the cometary impacts are at speeds above 20 km/sec, but at most 5 percent of the asteroidal impacts); paradoxically, the objects impacting at speeds low enough to make organic/volatile survival possible (the asteroids) are those which are depleted in such species.

Factors associated with mobility apprehension in persons with lower limb amputation

2020 ◽  
Vol 44 (4) ◽  
pp. 208-214
Author(s):  
Shannon L Mathis
Keyword(s):  
Standard Deviation ◽  
Lower Limb ◽  
Avoidance Behavior ◽  
Pain Catastrophizing ◽  
Lower Limb Amputation ◽  
Limb Amputation ◽  
Walking Ability ◽  
Factors Associated ◽  
The Mean ◽  
The Impact

Background: Factors that are related to mobility apprehension were measured in a sample of persons with lower-limb amputation. Objectives: The purpose was to determine whether intensity, interference, or catastrophizing are associated with mobility apprehension. Study design: Cross-sectional study. Methods: Persons with amputation of a lower limb who were attending a national limb loss conference were recruited to complete a survey. Subjects were administered the Tampa Scale for Kinesiophobia to measure mobility apprehension. The Brief Pain Inventory was administered to quantify the affect of pain on general activity, walking ability, and enjoyment of life. The Pain Catastrophizing Scale was administered to assess the tendency to ruminate and magnify pain sensations. A multivariable linear regression was performed to determine factors associated with mobility apprehension. Results: Fifty-three people with lower-limb amputation participated in the study. The mean (standard deviation) score for mobility apprehension was 34.2 (6.0). Mean (standard deviation) pain intensity and interference scores were 1.6 (1.7) and 2.5 (2.6), respectively. The mean (standard deviation) pain catastrophizing score was 9.1 (10). Pain catastrophizing was the only variable associated with higher mobility apprehension ( β = 0.31, p < 0.001, R2 = 0.32). Results suggest that for every one-point increase in the pain catastrophizing score, mobility apprehension will increase by 0.3 of a point. Conclusion: These preliminary results suggest that pain catastrophizing was related to mobility apprehension in this cohort of persons with lower-limb amputation. This relationship indicates that the exploration of avoidance behaviors, such as pain catastrophizing, may be useful when developing a program for physical rehabilitation. Clinical relevance Pain catastrophizing, an avoidance behavior, may be associated with higher levels of mobility apprehension in persons with major lower-limb amputation. Understanding the impact of fear-avoidance behavior will allow clinicians to identify individuals at risk for poor outcomes following amputation surgery and to develop psychological strategies to complement treatment.

scholarly journals Validation of SCIAMACHY HDO/H<sub>2</sub>O measurements using the TCCON and NDACC-MUSICA networks

2015 ◽  
Vol 8 (4) ◽  
pp. 1799-1818 ◽  
Author(s):  
R. A. Scheepmaker ◽  
C. Frankenberg ◽  
N. M. Deutscher ◽  
M. Schneider ◽  
S. Barthlott ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Hydrological Cycle ◽  
Source Region ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
The Tibetan Plateau ◽  
Wet Season ◽  
Data Set ◽  
The Mean ◽  
The Impact

Abstract. Measurements of the atmospheric HDO/H2O ratio help us to better understand the hydrological cycle and improve models to correctly simulate tropospheric humidity and therefore climate change. We present an updated version of the column-averaged HDO/H2O ratio data set from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The data set is extended with 2 additional years, now covering 2003–2007, and is validated against co-located ground-based total column δD measurements from Fourier transform spectrometers (FTS) of the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC, produced within the framework of the MUSICA project). Even though the time overlap among the available data is not yet ideal, we determined a mean negative bias in SCIAMACHY δD of −35 ± 30‰ compared to TCCON and −69 ± 15‰ compared to MUSICA (the uncertainty indicating the station-to-station standard deviation). The bias shows a latitudinal dependency, being largest (∼ −60 to −80‰) at the highest latitudes and smallest (∼ −20 to −30‰) at the lowest latitudes. We have tested the impact of an offset correction to the SCIAMACHY HDO and H2O columns. This correction leads to a humidity- and latitude-dependent shift in δD and an improvement of the bias by 27‰, although it does not lead to an improved correlation with the FTS measurements nor to a strong reduction of the latitudinal dependency of the bias. The correction might be an improvement for dry, high-altitude areas, such as the Tibetan Plateau and the Andes region. For these areas, however, validation is currently impossible due to a lack of ground stations. The mean standard deviation of single-sounding SCIAMACHY–FTS differences is ∼ 115‰, which is reduced by a factor ∼ 2 when we consider monthly means. When we relax the strict matching of individual measurements and focus on the mean seasonalities using all available FTS data, we find that the correlation coefficients between SCIAMACHY and the FTS networks improve from 0.2 to 0.7–0.8. Certain ground stations show a clear asymmetry in δD during the transition from the dry to the wet season and back, which is also detected by SCIAMACHY. This asymmetry points to a transition in the source region temperature or location of the water vapour and shows the added information that HDO/H2O measurements provide when used in combination with variations in humidity.

scholarly journals Significant Effect of Project Based Learning Video on Students’ Listening Skill in Pandemic Situation

2021 ◽  
Vol 5 (2) ◽  
pp. 425
Author(s):  
Ni Wayan Febiyanti ◽  
Putu Kerti Nitiasih ◽  
Luh Gd Rahayu Budiarta ◽  
Ni Luh Putu Era Adnyayanti
Keyword(s):  
Standard Deviation ◽  
Quantitative Research ◽  
Listening Comprehension ◽  
Mean Value ◽  
Project Based Learning ◽  
School Students ◽  
Innovative Teaching ◽  
Listening Skill ◽  
The Mean ◽  
The Impact

Listening is one of the most important language skills to be learned by students. However, it is very difficult for teachers to teach these skills in learning during the Covid-19 pandemic. Teachers need innovative teaching techniques, one of which is using video media. This study aims to investigate the impact of using project-based learning videos on students' listening comprehension skills. The population in this study involved 4th grade elementary school students. The sample in this study used 40 grade 4 students from one intact class that were selected with a specific purpose. This research includes quantitative research with one group pretest-posttest design. The data collection instrument in this study used a listening comprehension test and a listening comprehension assessment rubric. The data collected were analyzed using descriptive and inferential statistical analysis. From the results of the study, it was found that the mean value of the group at the posttest was 86.85 which was greater than the mean value at the pretest, which was 75.75. The standard deviation on the pretest also shows a value of 5,678 and the standard deviation on the posttest is 3,180. From the results of statistical inferential analysis shows that the value of Sig. (2-tailed) is .000. and lower than Sig. levels (.05). Therefore, it can be concluded that there is a significant impact on the use of project-based learning videos on students' listening comprehension during the covid-19 pandemic.

scholarly journals Analysis of a Discrete-Time Queueing Model with Disasters

Mathematics ◽  
2021 ◽  
Vol 9 (24) ◽  
pp. 3283
Author(s):  
Mustafa Demircioglu ◽  
Herwig Bruneel ◽  
Sabine Wittevrongel
Keyword(s):  
Discrete Time ◽  
Queueing System ◽  
Time Slot ◽  
Probability Distributions ◽  
Single Server ◽  
Bernoulli Process ◽  
Tail Probabilities ◽  
Mean Values ◽  
The Mean ◽  
The Impact

Queueing models with disasters can be used to evaluate the impact of a breakdown or a system reset in a service facility. In this paper, we consider a discrete-time single-server queueing system with general independent arrivals and general independent service times and we study the effect of the occurrence of disasters on the queueing behavior. Disasters occur independently from time slot to time slot according to a Bernoulli process and result in the simultaneous removal of all customers from the queueing system. General probability distributions are allowed for both the number of customer arrivals during a slot and the length of the service time of a customer (expressed in slots). Using a two-dimensional Markovian state description of the system, we obtain expressions for the probability, generating functions, the mean values, variances and tail probabilities of both the system content and the sojourn time of an arbitrary customer under a first-come-first-served policy. The customer loss probability due to a disaster occurrence is derived as well. Some numerical illustrations are given.

scholarly journals Comparative statistical analysis of simulated ice management effectiveness

2019 ◽  
Vol 2 (1) ◽  
pp. 79-91
Author(s):  
Amy Price ◽  
Maria Yulmetova ◽  
Sarah Khalil
Keyword(s):  
Confidence Intervals ◽  
Probability Distributions ◽  
Management Effectiveness ◽  
Distribution Fitting ◽  
Management Performance ◽  
Distance Ratio ◽  
The Mean ◽  
Comparative Statistical Analysis ◽  
Level Of Experience ◽  
The Impact

AbstractIce management is critical for safe and efficient operations in ice-covered waters; thus, it is important to understand the impact of the operator’s experience in effective ice management performance. This study evaluated the confidence intervals of the mean and probability distributions of two different sample groups, novice cadets and experienced seafarers, to evaluate if there was a difference in effective ice management depending on the operator’s level of experience. The ice management effectiveness, in this study, is represented by the “clearing-to-distance ratio” that is the ratio between the area of cleared ice (km2) and the distance travelled by an ice management vessel (km) to maintain that cleared area. The data analysed in this study was obtained from a recent study conducted by Memorial University’s “Safety at Sea” research group. With the distribution fitting analysis providing inconclusive results regarding the normality of the data, the confidence intervals of the dataset means were obtained using both parametric approaches, such as t-test, Cox’s method, and Johnson t-approach, and non-parametric methods, namely Jackknife and Bootstrap methods, to examine if the assumption of normality was valid. The comparison of the obtained confidence interval results demonstrates that the mean efficiency of the cadets is more consistent, while it is more varied among seafarers. The noticeable difference in ice management performance between the cadet and seafarer sample groups is revealed, thus, proving that crew experience positively influences ice management effectiveness.

Higher Order Perturbation Analysis of Stochastic Thermal Systems With Correlated Uncertain Properties

2000 ◽  
Vol 123 (2) ◽  
pp. 390-398 ◽  
Author(s):  
A. F. Emery
Keyword(s):  
Standard Deviation ◽  
Boundary Conditions ◽  
Perturbation Analysis ◽  
Perturbation Methods ◽  
Higher Order ◽  
Order Perturbation ◽  
Thermal Systems ◽  
The Mean ◽  
Almost All ◽  
Correlated Parameters

How the behavior of thermal systems depends on uncertainties in properties and boundary conditions is an important aspect of simulation. This dependence is usually judged by the statistics of the response, i.e., the mean response and its standard deviation which are often determined by perturbation methods, ranging from 1st to 3rd order. The aim of this paper is to be a tutorial for those interested in estimating uncertainties by summarizing the author’s experience in using higher order perturbation analysis for thermal problems, detailing the underlying assumptions, and presenting several examples. Problems involving correlated parameters, which occur in almost all thermal experiments, are also treated. It is shown that the scale of correlation has a strong effect upon the statistics of the response and that such correlation should not be ignored. It is recommended that the 1st order estimates of the standard deviation and 2nd order estimates of the mean response be used when characterizing thermal systems with random variables, regardless of the degree of correlation.

scholarly journals Changes in Pediatric Fracture Cases during the Coronavirus Disease 2019 Pandemic: Data from a National Referral Orthopedic Hospital in Indonesia

2021 ◽  
Vol 9 (E) ◽  
pp. 754-758
Author(s):  
Pamudji Utomo ◽  
Muhammad Yogatama Wirawan ◽  
Hendra Cahya Kumara ◽  
Mochamadsyah Beizar Yudistira
Keyword(s):  
Standard Deviation ◽  
Population Group ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Service Support ◽  
Pediatric Fracture ◽  
Orthopedic Hospital ◽  
The Mean ◽  
The Impact

AIM: This study aims to compare the impact of coronavirus disease 2019 (COVID-19) on pediatric fracture services in a national referral orthopedic hospital in Indonesia to understand the service provisions that may be required during the pandemic. METHODS: The study compared the population group during 1 year of the COVID-19 pandemic in Indonesia to the same period 1 year before. This cross-sectional study was performed in Prof. Dr. R Soeharso Orthopedic Hospital, Surakarta, Indonesia, from March 2019 to February 2021. The subjects were pediatric fracture patients aged 0–18 years. Patients recorded on other orthopedic service support installations such as radiology, laboratory, or physiotherapy and diagnosed with any other orthopedic sub-specialty were excluded. RESULTS: A total of 1787 patients were recorded in this study, with the mean of pediatric fracture patients during the pre-COVID-19 period was 90.75 (standard deviation [SD]: 28.5) and during the COVID-19 period was 58.16 (SD: 19.17) monthly. In the 1st year of the pandemic, there was a significant reduction in clinical visits compared to the same period in 2019 (p < 0.005). CONCLUSION: There were significant differences in pediatric fracture cases clinic visits and patients’ length of stay in the COVID-19 period than before the COVID-19 occurred.

scholarly journals Patient-Reported Outcome Measures Identify Impairment Better Than Clinician Documentation during Pediatric Cancer Treatment

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3291-3291 ◽  
Author(s):  
Sarah K. Dobrozsi ◽  
Julie A. Panepinto
Keyword(s):  
Depressive Symptoms ◽  
Standard Deviation ◽  
Cancer Treatment ◽  
Patient Reported Outcome Measures ◽  
Patient Reported Outcome ◽  
Impaired Function ◽  
Patient Reported ◽  
The Mean ◽  
The Impact ◽  
Clinic Visits

Introduction: Children receiving treatment for cancer commonly experience symptoms during their course that impact patient function. Understanding limitations to patient function caused by symptoms is critical to supporting children through their illness; however assessment of function is not standardized which can result in the under recognition of symptoms. Patient-reported outcome measures (PROs) can systematically measure and quantify the impact of symptoms on patient function. PROs have the potential to improve clinician recognition of symptoms and provide additional objective information about the impact of symptoms on patient function. However, to date there are minimal data using PROs in a clinical setting to detect symptoms and function in children receiving treatment for cancer. The objective of this study was to determine if symptoms causing significant impact on patient function as detected by PROs are recognized by standard clinician interview. We hypothesize that PROs identify symptoms causing significant burden to patients with greater sensitivity than clinician documentation. Methods: We conducted a prospective study of children age 8-21 years old that began treatment for cancer within the previous 4 weeks. Patients completed self-reported PROMIS questionnaires measuring impaired mobility, pain, fatigue, anxiety, and depressive symptoms monthly at outpatient clinic visits during the first 6 months of cancer treatment. PROMIS is a validated PRO that provides separate scores for each symptom measured with a mean score of 50 and standard deviation of 10. Patients with scores more than 1 standard deviation from the mean (T score ≥ 10 points from mean of 50) have significantly impaired function. Clinician documentation of symptoms at clinic visits were abstracted from the medical record in dichotomous fashion (present/absent) using pre-defined key words to define each symptom. The proportion of clinic visits with impaired function detected by PROMIS was compared to proportion of clinic visits with symptom documented by clinician using chi square tests. Results: Forty children participated in the study. The mean age of study participants was 11.7 years (SD 4.7). Fifty-eight percent of the patients were male and 60% of patients had leukemia or lymphoma. Paired PRO data/clinician documentation was available for 150 visits. The mean number of clinic visits per study patient was 3.75 (range 2-5). Patients demonstrated impaired function on PROMIS related to any symptom measured at 24% of clinic visits. For all clinic visits at which PROMIS detected impaired function, the symptom was documented by the clinician only 20% of the time (p<0.0001). Mobility: When impaired function was detected by PROMIS, concerns related to mobility were documented by the clinician only 20% of the time (p<0.0001) (figure 1). Pain: When impaired function due to pain was detected by PROMIS, pain was documented by the clinician 38% of the time (p<0.0001) (figure 1). Fatigue: When impaired function due to fatigue was detected by PROMIS, fatigue was documented by the clinician only 20% of the time (p<0.0001) (figure 1). Anxiety: When impaired function due to anxiety was detected by PROMIS, anxiety was documented by the clinician at 0% of the visits (p<0.0001) (figure 1). Depressive symptoms: When impaired function due to depressive symptoms were detected by PROMIS, depressive symptoms were documented by the clinician only 7% of the time (p<0.0001) (figure 1). Conclusion: Symptoms causing significant impact on patient function as detected by PROs are poorly detected and documented by standard clinician interview. These data demonstrate the natural limitations of clinician interview to illicit the true impact of symptoms on patients' lives and the likelihood that clinicians are unaware of the impact of disease and treatment on individuals and their function. The discrepancies in detection of this burden by current practice highlight opportunities to use PRO data to supplement clinical practice. Disclosures Panepinto: HRSA, NIH: Research Funding; NKT Therapeutics, Inc: Consultancy.

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