[Assessment of compliance for oral medicines with MMSE, Mini-Mental State Examination, in hospitalized elderly patients].

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Miura, Masatomo; Kakei, Masafumi; Iwasawa, Saaya; Morii, Tsukasa; Miura, Takeshi; Sasaki, Hiroshi; Satoh, Takehiro; Fujita, Hiroki; Narita, Takuma; Shirakawa, Hideko; Yamada, Yuichiro; Suzuki, Toshio

2007-10-01

The minimental state examination (MMSE) is a widely used, standardized method to assess cognitive function including movement-related disorders with high reliability. We studied the relationship between MMSE scores and the ability to take oral medications correctly (ingestion compliance) in 70 elderly inpatients (mean age 71.3+/-7.0 years). Patients with abnormal glucose tolerance as determined by an HbA(1c) level of 5.8% or greater including diabetes showed a trend of lower MMSE scores compared with patients with normal glucose tolerance, and the scores were negatively correlated with HbA1c, age, and systolic blood pressure (P<0.05). Self-management in taking oral medications was very difficult in 4 patients whose MMSE scores were 21 points or less. Thus ingestion supervisions by nurses were required in these patients. Furthermore, 9 of 12 noncompliant patients had MMSE scores ranging from 22 to 26 points. We instructed these patients to take medications in a one-dose package as a useful tool to improve compliance. The MMSE score was 27 or higher in 44 of 54 compliant patients, and 10 patients had scores ranging from 21 to 26. The sensitivity and specificity for noncompliance at an MMSE score cut-off point of 26 were 75.0% and 81.5%, respectively. In conclusion, it is necessary to coordinate ingestion methods matched to each patient according to their abilities to comply with medication schedules. They should be preevaluated with the MMSE to improve ingestion compliance. The MMSE is a recommended test in hospitalized elderly patients for the assessment of the ability to take medications safely.

A comparison of the performance of the 3-D super-ensemble and an ensemble Kalman filter for short-range regional ocean prediction

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Baptiste Mourre

2014-01-01

Full Text Available This study compares the ability of two approaches integrating models and data to forecast the Ligurian Sea regional oceanographic conditions in the short-term range (0–72 hours when constrained by a common observation dataset. The post-processing 3-D super-ensemble (3DSE algorithm, which uses observations to optimally combine multi-model forecasts into a single prediction of the oceanic variable, is first considered. The 3DSE predictive skills are compared to those of the Regional Ocean Modeling System model in which observations are assimilated through a more conventional ensemble Kalman filter (EnKF approach. Assimilated measurements include sea surface temperature maps, and temperature and salinity subsurface observations from a fleet of five underwater gliders. Retrospective analyses are carried out to produce daily predictions during the 11-d period of the REP10 sea trial experiment. The forecast skill evaluation based on a distributed multi-sensor validation dataset indicates an overall superior performance of the EnKF, both at the surface and at depth. While the 3DSE and EnKF perform comparably well in the area spanned by the incorporated measurements, the 3DSE accuracy is found to rapidly decrease outside this area. In particular, the univariate formulation of the method combined with the absence of regular surface salinity measurements produces large errors in the 3DSE salinity forecast. On the contrary, the EnKF leads to more homogeneous forecast errors over the modelling domain for both temperature and salinity. The EnKF is found to consistently improve the predictions with respect to the control solution without assimilation and to be positively skilled when compared to the climatological estimate. For typical regional oceanographic applications with scarce subsurface observations, the lack of physical spatial and multivariate error covariances applicable to the individual model weights in the 3DSE formulation constitutes a major

Super-stable Poissonian structures

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Eliazar, Iddo

2012-01-01

In this paper we characterize classes of Poisson processes whose statistical structures are super-stable. We consider a flow generated by a one-dimensional ordinary differential equation, and an ensemble of particles ‘surfing’ the flow. The particles start from random initial positions, and are propagated along the flow by stochastic ‘wave processes’ with general statistics and general cross correlations. Setting the initial positions to be Poisson processes, we characterize the classes of Poisson processes that render the particles’ positions—at all times, and invariantly with respect to the wave processes—statistically identical to their initial positions. These Poisson processes are termed ‘super-stable’ and facilitate the generalization of the notion of stationary distributions far beyond the realm of Markov dynamics. (paper)

Super-stable Poissonian structures

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Eliazar, Iddo

2012-10-01

In this paper we characterize classes of Poisson processes whose statistical structures are super-stable. We consider a flow generated by a one-dimensional ordinary differential equation, and an ensemble of particles ‘surfing’ the flow. The particles start from random initial positions, and are propagated along the flow by stochastic ‘wave processes’ with general statistics and general cross correlations. Setting the initial positions to be Poisson processes, we characterize the classes of Poisson processes that render the particles’ positions—at all times, and invariantly with respect to the wave processes—statistically identical to their initial positions. These Poisson processes are termed ‘super-stable’ and facilitate the generalization of the notion of stationary distributions far beyond the realm of Markov dynamics.

Stacked generalization: an introduction to super learning.

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Naimi, Ashley I; Balzer, Laura B

2018-04-10

Stacked generalization is an ensemble method that allows researchers to combine several different prediction algorithms into one. Since its introduction in the early 1990s, the method has evolved several times into a host of methods among which is the "Super Learner". Super Learner uses V-fold cross-validation to build the optimal weighted combination of predictions from a library of candidate algorithms. Optimality is defined by a user-specified objective function, such as minimizing mean squared error or maximizing the area under the receiver operating characteristic curve. Although relatively simple in nature, use of Super Learner by epidemiologists has been hampered by limitations in understanding conceptual and technical details. We work step-by-step through two examples to illustrate concepts and address common concerns.

Use of days of the week in a modified mini-mental state exam (M-MMSE) for detecting geriatric cognitive impairment.

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Hamrick, Irene; Hafiz, Razia; Cummings, Doyle M

2013-01-01

The purpose of this study was to compare a modified version of the Mini-Mental State Examination (MMSE) with the standard MMSE and the Mini-Cog in patients ≥65 years old, stratified by education and literacy level. This cross-sectional exploratory study enrolled a convenience sample of 219 patients with a complaint of memory loss or a diagnosis of dementia from a geriatric outpatient clinic, nursing home, senior center, and university hospital. The MMSE was administered, and in addition to spelling and serial 7s backward, patients were asked to recite the days of the week backward with the intent to reduce educational bias. Scores on the modified MMSE were compared with scores of the MMSE and the Mini-Cog. Of the 219 patients, 157 were identified with cognitive impairment by the Mini-Cog. Using a cutoff of ≤23, the MMSE identified 118 patients and the modified MMSE identified 91 patients with cognitive impairment, and with a cutoff of ≤27 the MMSE identified 168 and the modified MMSE 149 patients. All cognitively intact subjects correctly recited the days of the week backward. Specificity of the modified MMSE was higher than the MMSE for most groups. The highest sensitivity and specificity (94% and 88%, respectively) as well as positive and negative predictive values (96% and 81%, respectively) were in patients with low levels of education for the modified MMSE using a cut off of ≤27. Using the days of the week in the MMSE among illiterate and semiliterate participants and with education less than high school, and using a cutoff of 27 of 30, correlates better with Mini-Cog for dementia screening, with fewer false positives.

Using the Folstein Mini Mental State Exam (MMSE) to explore methodological issues in cognitive aging research.

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Monroe, Todd; Carter, Michael

2012-09-01

Cognitive scales are used frequently in geriatric research and practice. These instruments are constructed with underlying assumptions that are a part of their validation process. A common measurement scale used in older adults is the Folstein Mini Mental State Exam (MMSE). The MMSE was designed to screen for cognitive impairment and is used often in geriatric research. This paper has three aims. Aim one was to explore four potential threats to validity in the use of the MMSE: (1) administering the exam without meeting the underlying assumptions, (2) not reporting that the underlying assumptions were assessed prior to test administration, (3) use of variable and inconsistent cut-off scores for the determination of presence of cognitive impairment, and (4) failure to adjust the scores based on the demographic characteristics of the tested subject. Aim two was to conduct a literature search to determine if the assumptions of (1) education level assessment, (2) sensory assessment, and (3) language fluency were being met and clearly reported in published research using the MMSE. Aim three was to provide recommendations to minimalize threats to validity in research studies that use cognitive scales, such as the MMSE. We found inconsistencies in published work in reporting whether or not subjects meet the assumptions that underlie a reliable and valid MMSE score. These inconsistencies can pose threats to the reliability of exam results. Fourteen of the 50 studies reviewed reported inclusion of all three of these assumptions. Inconsistencies in reporting the inclusion of the underlying assumptions for a reliable score could mean that subjects were not appropriate to be tested by use of the MMSE or that an appropriate test administration of the MMSE was not clearly reported. Thus, the research literature could have threats to both validity and reliability based on misuse of or improper reported use of the MMSE. Six recommendations are provided to minimalize these threats

A Note on Functional Averages over Gaussian Ensembles

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Gabriel H. Tucci

2013-01-01

Full Text Available We find a new formula for matrix averages over the Gaussian ensemble. Let H be an n×n Gaussian random matrix with complex, independent, and identically distributed entries of zero mean and unit variance. Given an n×n positive definite matrix A and a continuous function f:ℝ+→ℝ such that ∫0∞‍e-αt|f(t|2dt0, we find a new formula for the expectation [Tr(f(HAH*]. Taking f(x=log(1+x gives another formula for the capacity of the MIMO communication channel, and taking f(x=(1+x-1 gives the MMSE achieved by a linear receiver.

On Channel Estimation for OFDM/TDM Using MMSE-FDE in a Fast Fading Channel

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Gacanin Haris

2009-01-01

Full Text Available Abstract MMSE-FDE can improve the transmission performance of OFDM combined with time division multiplexing (OFDM/TDM, but knowledge of the channel state information and the noise variance is required to compute the MMSE weight. In this paper, a performance evaluation of OFDM/TDM using MMSE-FDE with pilot-assisted channel estimation over a fast fading channel is presented. To improve the tracking ability against fast fading a robust pilot-assisted channel estimation is presented that uses time-domain filtering on a slot-by-slot basis and frequency-domain interpolation. We derive the mean square error (MSE of the channel estimator and then discuss a tradeoff between improving the tracking ability against fading and the noise reduction. The achievable bit error rate (BER performance is evaluated by computer simulation and compared with conventional OFDM. It is shown that the OFDM/TDM using MMSE-FDE achieves a lower BER and a better tracking ability against fast fading in comparison with conventional OFDM.

Delayed Recall and Working Memory MMSE Domains Predict Delirium following Cardiac Surgery.

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Price, Catherine C; Garvan, Cynthia; Hizel, Loren P; Lopez, Marcos G; Billings, Frederic T

2017-01-01

Reduced preoperative cognition is a risk factor for postoperative delirium. The significance for type of preoperative cognitive deficit, however, has yet to be explored and could provide important insights into mechanisms and prediction of delirium. Our goal was to determine if certain cognitive domains from the general cognitive screener, the Mini-Mental State Exam (MMSE), predict delirium after cardiac surgery. Patients completed a preoperative MMSE prior to undergoing elective cardiac surgery. Following surgery, delirium was assessed throughout ICU stay using the Confusion Assessment Method for ICU delirium and the Richmond Agitation and Sedation Scale. Cardiac surgery patients who developed delirium (n = 137) had lower total MMSE scores than patients who did not develop delirium (n = 457). In particular, orientation to place, working memory, delayed recall, and language domain scores were lower. Of these, only the working memory and delayed recall domains predicted delirium in a regression model adjusting for history of chronic obstructive pulmonary disease, age, sex, and duration of cardiopulmonary bypass. For each word not recalled on the three-word delayed recall assessment, the odds of delirium increased by 50%. For each item missed on the working memory index, the odds of delirium increased by 36%. Of the patients who developed delirium, 47% had a primary impairment in memory, 21% in working memory, and 33% in both domains. The area under the receiver operating characteristics curve using only the working memory and delayed recall domains was 0.75, compared to 0.76 for total MMSE score. Delirium risk is greater for individuals with reduced MMSE scores on the delayed recall and working memory domains. Research should address why patients with memory and executive vulnerabilities are more prone to postoperative delirium than those with other cognitive limitations.

Is the Mini-Mental State Examination (MMSE useful for eligibility screening of research participants with substance use disorder?

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Aldebarán Toledo-Fernández

2016-06-01

Full Text Available Introduction: the MMSE is used for eligibility screening of potential research participants diagnosed with substance use disorder (SUD, as abilities needed to provide a valid informed consent or accurate information could be impaired in these clinical populations. Knowledge about the capacity of the MMSE to detect impairment in these abilities or at least to assess impact of SUD on its total score, however, is rather diffuse. This has important ethical and methodological implications. Objective: to analyze effects of SUD only, main substances of abuse, age of onset of substance use, recent substance use, and psychiatric comorbidity upon MMSE outcome. The overall purpose of the study was to assess the utility of the MMSE for eligibility screening of potential research participants with SUD. Method: individuals were recruited from residential facilities for substance use treatment. A demographic questionnaire, MMSE and Mini International Neuropsychiatric Interview were used. Results: A total of 601 participants were gathered for main analysis. Controlling for education, no differences in MMSE score were detected within main substances of abuse (F=1.25[4,529], p=.28, nor between SUD only versus SUD with psychiatric comorbidity (F=.58[1,597], p=.44. Effects of age of onset and recent use of specific substances upon MMSE score were also absent. Discussion and conclusions: If there is some cognitive impairment in this clinical population, it may not be pertinently assessed by the MMSE, thus casting doubt on its pertinence for eligibility screening.

MMSE Estimator for Children’s Speech with Car and Weather Noise

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Sayuthi, V.

2018-04-01

Previous research mentioned that most people need and use vehicles for various purposes, in this recent time and future, as a means of traveling. Many ways can be done in a vehicle, such as for enjoying entertainment, and doing work, so vehicles not just only as a means of traveling. In this study, we will examine the children’s speech from a girl in the vehicle that affected by noise disturbances from the sound source of car noise and the weather sound noise around it, in this case, the rainy weather noise. Vehicle sounds may be from car engine or car air conditioner. The minimum mean square error (MMSE) estimator is used as an attempt to obtain or detect the children’s clear speech by representing simulation research as random process signal that factored by the autocorrelation of both the child’s voice and the disturbance noise signal. This MMSE estimator can be considered as wiener filter as the clear sound are reconstructed again. We expected that the results of this study can help as the basis for development of entertainment or communication technology for passengers of vehicles in the future, particularly using MMSE estimators.

How to calculate an MMSE score from a MODA score (and vice versa) in patients with Alzheimer's disease.

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Cazzaniga, R; Francescani, A; Saetti, C; Spinnler, H

2003-11-01

The aim of the present study was to provide a statistically sound way of reciprocally converting scores of the mini-mental state examination (MMSE) and the Milan overall dementia assessment (MODA). A consecutive series of 182 patients with "probable" Alzheimer's disease patients was examined with both tests. MODA and MMSE scores proved to be highly correlated. A formula for converting MODA and MMSE scores was generated.

The usefulness of the Korean version of modified Mini-Mental State Examination (K-mMMSE for dementia screening in community dwelling elderly people

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Cho Ki-Hyun

2004-07-01

Full Text Available Abstract Background We assessed whether the Korean version of modified Mini-Mental State Examination (K-mMMSE has improved performance as a screening test for cognitive impairment or dementia in a general population compared with the Korean Mini-Mental State Examination (K-MMSE. Methods Screening interviews were conducted with people aged 65 and over in Noam-dong, Namwon-city, Jeonbuk province. There were 522 community participants, of whom 235 underwent clinical and neuropsychological examination for diagnosis of dementia and Cognitive Impairment No Dementia (CIND. Sensitivity, specificity and areas under the receiver operating characteristic (ROC curves for the K-mMMSE and the K-MMSE were the main outcome measures. Results Cronbach's alpha for the K-mMMSE was 0.91, compared with 0.84 for the K-MMSE. The areas under the ROC curves in identifying all levels of CIND or dementia were 0.91 for the K-mMMSE and 0.89 for the K-MMSE (P r = 0.89. Conclusion Our findings indicate that the K-mMMSE is more reliable and valid than the K-MMSE as a cognitive screen in a population based study of dementia. Considering the test characteristics, the K-MMSE and modified version are expected to be optimally used in clinical and epidemiologic fields.

Three sides of the same coin: measuring global cognitive impairment with the MMSE, ADAS-cog and CAMCOG.

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Wouters, Hans; van Gool, Willem A; Schmand, Ben; Zwinderman, Aeilko H; Lindeboom, Robert

2010-08-01

The total scores of the ADAS-cog, MMSE and CAMCOG, comprising various cognitive tasks, are widely used to measure a dimension of global cognitive impairment. It is unknown, however, whether this dimension is common to these instruments. This hampers comparisons when either of these instruments is used. The extent to which these instruments share a common dimension of global cognitive impairment and how their scores relate was examined. Rasch analysis of CAMCOG and MMSE data of participants from a population based study and two memory clinics pooled with ADAS-cog and MMSE data of participants from three RCTs (overall N = 1566) to estimate a common dimension of global cognitive impairment and to examine the goodness of fit of the individual items to this dimension. Using the estimated common dimension of global cognitive impairment, the total scores of the instruments could be related, e.g. a mean level of global cognitive impairment corresponded to a predicted score of 11.4 (ADAS-cog), 72.6 (CAMCOG) and 22.2 (MMSE). When revised according to The Rasch validity analyses, every individual item could be fitted to the dimension. The MMSE, ADAS-cog and CAMCOG reflect a valid common dimension of global cognitive impairment, which enables comparisons of RCTs that use the ADAS-cog and observational studies that use the CAMCOG and MMSE.

Olfactory Function, Eating Ability, and Visceral Obesity Associated with MMSE Three Years after Parkinson's Disease Diagnosis.

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Vikdahl, M; Domellöf, M E; Forsgren, L; Håglin, L

2015-11-01

This study examines whether risk factors for poor nutrition are associated with global cognitive function three years after confirmed Parkinson's disease (PD) diagnosis. The follow-up investigations for this prospective community-based study were conducted three years after PD diagnosis. The study participants lived in Västerbotten County, a region in northern Sweden with 142,000 inhabitants. This study population consisted of 118 PD outpatients from the study of Newly Diagnosed PD in Umeå (NYPUM). Global cognition was assessed with the Mini Mental State Examination (MMSE) at baseline and at follow-up. Anthropometry, nutrition (Mini Nutritional Assessment, MNA, 3-day food registration, 3-FDR), olfactory function (Brief Smell Identification Test, B-SIT), and swallowing, cutting food, and salivation (single questions from the Unified Parkinson's Disease Rating Scale, UPDRS) were used as markers for nutritional status. The MMSE score decreased over three years (-1.06±3.38, p=0.001). Olfactory function at baseline was associated to MMSE at three years (B=0.365, p=0.004). Changes in waist/hip ratio (B=113.29, p=0.017), swallowing (B=1.18, P=0.033), and cutting food (B=-1.80, p=0.000) were associated with MMSE at follow-up. This study indicates that olfactory function, cutting food, swallowing, and visceral obesity are associated with MMSE three years after PD diagnosis.

Relationship between brain perfusion SPECT and MMSE score in dementia of Alzheimer's type: a statistical parametric mapping analysis

International Nuclear Information System (INIS)

Kang, Hye Jin; Kang, Eun Joo; Lee, Jae Sung

2002-01-01

The aim of this study was to identify the brain areas in which reductions of regional cerebral blood flow (rCBF) were correlated with decline of general mental function, measured by Mini-Mental State Examination (MMSE). Tc-99m HMPAO brain SPECT was performed in 9 probable AD patients at the initial and follow-up periods of 1.8 years (average) after the first study. MMSE scores were also measured in both occasions. The mean MMSE score of the initial study 16.4 (range: 5-24) and the mean MMSE score of the follow-up was 8.1 (range: 0-17). Each SPECT image was normalized to the cerebellar activity and a correlation analysis was performed between the level of rCBF in AD patients and the MMSE scores by voxel-based analysis using SPM99 software. Significant correlation was found between the blood-flow decrease in left inferior prefrontal region(BA 47) and left middle temporal region (BA 21) and the MMSE score changes. Additional areas such as anterior and posterior cingulate cortices, precuneus, and bilateral superior and middle prefrontal regions showed and similar trends. A relationship was found between reduction of regional cerebral blood flow in left prefrontal and temporal areas and decline of cognitive function in Alzheimer's diseases (AD) patients. This voxel-based analysis is useful in evaluating the progress of cognitive function in Alzheimer's disease

The Montreal Cognitive Assessment (MoCA) is superior to the Mini Mental State Examination (MMSE) in detection of Korsakoff's syndrome.

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Oudman, Erik; Postma, Albert; Van der Stigchel, Stefan; Appelhof, Britt; Wijnia, Jan W; Nijboer, Tanja C W

2014-01-01

The Montreal Cognitive Assessment (MoCA) and Mini Mental State Examination (MMSE) are brief screening instruments for cognitive disorders. Although these instruments have frequently been used in the detection of dementia, there is currently little knowledge on the validity to detect Korsakoff's syndrome (KS) with both screening instruments. KS is a chronic neuropsychiatric disorder associated with profound declarative amnesia after thiamine deficiency. A representative sample of 30 patients with KS and 30 age-, education-, gender- and premorbid-IQ-matched controls was administered the MoCA and MMSE. The area under the receiver operating characteristic curve (AUC) was calculated in addition to the sensitivity, specificity, positive predictive value, and negative predictive value for various cut-off points on the MoCA and MMSE. Compared with the MMSE, the MoCA demonstrated consistently superior psychometric properties and discriminant validity--AUC: MoCA (1.00 SE .003) and MMSE (0.92 SE .033). When applying a cut-off value as suggested in the manuals of both instruments, the MMSE (< 24) misdiagnosed 46.7% of the patients, while the MoCA (< 26) diagnosed all patients correctly. As a screening instrument with the most optimal cut-offs, the MoCA (optimal cutoff point 22/23, 98.3% correctly diagnosed) was superior to the MMSE (optimal cutoff point 26/27, 83.3% correctly diagnosed). We conclude that both tests have adequate psychometric properties as a screening instrument for the detection of KS, but the MoCA is superior to the MMSE for this specific patient population.

ASEP of MIMO System with MMSE-OSIC Detection over Weibull-Gamma Fading Channel Subject to AWGGN

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Keerti Tiwari

2016-01-01

Full Text Available Ordered successive interference cancellation (OSIC is adopted with minimum mean square error (MMSE detection to enhance the multiple-input multiple-output (MIMO system performance. The optimum detection technique improves the error rate performance but increases system complexity. Therefore, MMSE-OSIC detection is used which reduces error rate compared to traditional MMSE with low complexity. The system performance is analyzed in composite fading environment that includes multipath and shadowing effects known as Weibull-Gamma (WG fading. Along with the composite fading, a generalized noise that is additive white generalized Gaussian noise (AWGGN is considered to show the impact of wireless scenario. This noise model includes various forms of noise as special cases such as impulsive, Gamma, Laplacian, Gaussian, and uniform. Consequently, generalized Q-function is used to model noise. The average symbol error probability (ASEP of MIMO system is computed for 16-quadrature amplitude modulation (16-QAM using MMSE-OSIC detection in WG fading perturbed by AWGGN. Analytical expressions are given in terms of Fox-H function (FHF. These expressions demonstrate the best fit to simulation results.

The stability of AQT processing speed, ADAS-Cog and MMSE during acetylcholinesterase inhibitor treatment in Alzheimer's disease.

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Wiig, E H; Annas, P; Basun, H; Andreasen, N; Lannfelt, L; Zetterberg, H; Blennow, K; Minthon, L

2010-03-01

To explore the longitudinal stability of measures of cognition during treatment with acetylcholinesterase inhibitors (AchEI) in patients with Alzheimer's disease (AD). Cognitive status was measured in a cohort of 60 patients at 6 months after initiation of treatment with AchEI (baseline) and after an additional 6 months of treatment (endpoint). A Quick Test of Cognitive Speed (AQT), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and MMSE were administered concurrently. Correlations (rho) between age and AQT processing speed were non-significant, but were significant for ADAS-Cog and Mini Mental State Examination (MMSE). AQT and ADAS-Cog means did not differ significantly between baseline and endpoint. There was a small, significant reduction in MMSE point scores. Measures of stability (Spearman's rho) were moderate-to-high for all tests. Means for subgroups did not differ as a function of medication type. AQT processing speed, ADAS-Cog, and MMSE measures proved stable during the second 6 months of treatment with AChEI.

[Validity and Reliability Studies of Modified Mini Mental State Examination (MMSE-E) For Turkish Illiterate Patients With Diagnosis of Alzheimer Disease].

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Babacan-Yıldız, Gülsen; Ur-Özçelik, Emel; Kolukısa, Mehmet; Işık, Ahmet Turan; Gürsoy, Esra; Kocaman, Gülşen; Çelebi, Arif

2016-01-01

To investigate the validity and reliability of modified Mini Mental State Examination (MMSE-E) for illiterate patients in a Turkish population with Alzheimer's disease (AD). A total of 107 illiterate patients with Alzheimer's Disease (women: 65, men: 42) and 68 illiterate healthy volunteer subjects (women: 36, men: 32) were included in the study. MMSE-I and Geriatrics Depression Scale were performed on all subjects, Alzheimer patients were also administered Basic Activities of Daily Living (B- ADL). Clinical Dementia Rating (CDR) was used to determine the severity of disease, while a receiver operating characteristic (ROC) analysis was performed to analyze the cut-off scores of MMSE-I, and the positive/negative predictive values that were calculated for the optimal cut-off scores. Internal consistency was measured using Cronbach's coefficient . Additionally, correlations between total MMSE-I score and the CDR, B-ADL, and GDS scores were examined. The MMSE-I scores significantly and inversely correlated with CDR (-0.82, p=0.000) and B-ADL scores (-0.051, p=0.000). The optimal cut-off points of MMSE-I were 23/24, which yielded a sensitivity of 99.0% - %100.0, a specificity of 98.5% - 97.0%, and an AUC of 1.0/1.0, respectively. Reliability of the MMSE-I was high α = 0.70). The total MMSE-I score was able to differentiate the AD group from the control group.

Preservation of quantum states via a super-Zeno effect on ensemble quantum computers

International Nuclear Information System (INIS)

Ting-Ting, Ren; Jun, Luo; Xian-Ping, Sun; Ming-Sheng, Zhan

2009-01-01

Following a recent proposal by Dhar et al (2006 Phys. Rev. Lett. 96 100405), we demonstrate experimentally the preservation of quantum states in a two-qubit system based on a super-Zeno effect using liquid-state nuclear magnetic resonance techniques. Using inverting radiofrequency pulses and delicately selecting time intervals between two pulses, we suppress the effect of decoherence of quantum states. We observe that preservation of the quantum state |11) with the super-Zeno effect is three times more efficient than the ordinary one with the standard Zeno effect. (general)

Assessing uncertainties in flood forecasts for decision making: prototype of an operational flood management system integrating ensemble predictions

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J. Dietrich

2009-08-01

Full Text Available Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydro-meteorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average super-ensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.

Correlation between the Montreal Cognitive Assessment-Indonesian Version (Moca-INA) and the Mini-Mental State Examination (MMSE) in Elderly.

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Rambe, Aldy Safruddin; Fitri, Fasihah Irfani

2017-12-15

As the rapid growth of the elderly population and the increased prevalence of Alezheimer's Disease and related disorders, there is an increasing need for effective cognitive screening. The Mini Mental State Examination (MMSE) is the most frequently used screening test of cognitive impairment because of its convenience. The Montreal Cognitive Assessment-Indonesian Version (MoCA-INA) has been validated and recently been used as a cognitive screening tool. The aim of this study was to compare the MMSE and MoCA-INA scores and to determine the correlation between the MMSE and MoCA-INA scores in elderly. This was a cross-sectional study including 83 elderly subjects from November 2016 until June 2017. We performed MMSE and MoCA-INA for assessment of cognitive function and the time between each test was at least 30 minutes. The study included 83 subjects which were consisted of 46 (55.4%) males and 37 (44.6%) females. The mean age was 69.19 ± 4.23 ranging from 65 to 79 years old. The average MMSE scores was 24.96 ± 3.38 (range 14 to 30). The average MoCA-INA scores was 21.06 ± 4.56 (range 5 to 30). The Pearson correlation coefficient between the scores was 0.71 (p<0.005). There were no significant differences of both scores based on history of hypertension, diabetes mellitus and previous stroke, but there was a significant difference in MMSE scores based on level of education. The MoCA-INA score showed a good correlation with the MMSE score. Both tests showed comparable results but MoCA-INA showed lower average with wider range of scores.

Mini-mental Parkinson (MMP) as a dementia screening test: comparison with the Mini-Mental State Examination (MMSE).

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Larner, Andrew J

2012-07-01

As populations age, screening instruments for cognitive impairment and dementia will become of increasing importance in clinical practice. Mini-Mental Parkinson (MMP), a derivative of the Mini-Mental State Examination (MMSE), was originally described as a cognitive screening instrument for use in Parkinson's disease. Its item content addresses some of the acknowledged shortcomings of the MMSE. Pragmatic use of MMP in general cognitive clinics has not previously been examined. To compare the performance of two scales, Mini-Mental Parkinson (MMP) and the Mini-Mental State Examination (MMSE), as cognitive screening instruments for dementia in a memory clinic population. MMP was administered prospectively to 201 consecutive new patient referrals independent of other tests used to establish dementia diagnosis according to standard diagnostic criteria (DSM-IV). Diagnostic utility of MMP for dementia was measured and compared with MMSE. MMP proved easy to use and acceptable to patients. Optimal test accuracy (0.86) was at MMP cutoff of ≤ 17/32, with sensitivity 0.51, specificity 0.97, positive predictive value 0.83, negative predictive value 0.87, and area under Receiver Operating Characteristic curve 0.89. Using a higher cutoff (≤ 29/32), MMP sensitivity was 1.00 with specificity 0.70. MMP scores correlated with MMSE (r = 0.93) and diagnostic agreement was high (κ = 0.85). MMP is a useful screening instrument in the memory clinic setting, with patients who fall below the designated cutoff requiring further investigation to ascertain a cause for their cognitive impairment.

Coding Across Multicodes and Time in CDMA Systems Employing MMSE Multiuser Detector

Directory of Open Access Journals (Sweden)

Park Jeongsoon

2004-01-01

Full Text Available When combining a multicode CDMA system with convolutional coding, two methods have been considered in the literature. In one method, coding is across time in each multicode channel while in the other the coding is across both multicodes and time. In this paper, a performance/complexity analysis of decoding metrics and trellis structures for the two schemes is carried out. It is shown that the latter scheme can exploit the multicode diversity inherent in convolutionally coded direct sequence code division multiple access (DS-CDMA systems which employ minimum mean squared error (MMSE multiuser detectors. In particular, when the MMSE detector provides sufficiently different signal-to-interference ratios (SIRs for the multicode channels, coding across multicodes and time can obtain significant performance gain over coding across time, with nearly the same decoding complexity.

A Practical, Hardware Friendly MMSE Detector for MIMO-OFDM-Based Systems

Directory of Open Access Journals (Sweden)

Babak Daneshrad

2008-04-01

Full Text Available Design and implementation of a highly optimized MIMO (multiple-input multiple-output detector requires cooptimization of the algorithm with the underlying hardware architecture. Special attention must be paid to application requirements such as throughput, latency, and resource constraints. In this work, we focus on a highly optimized matrix inversion free 4×4 MMSE (minimum mean square error MIMO detector implementation. The work has resulted in a real-time field-programmable gate array-based implementation (FPGA- on a Xilinx Virtex-2 6000 using only 9003 logic slices, 66 multipliers, and 24 Block RAMs (less than 33% of the overall resources of this part. The design delivers over 420 Mbps sustained throughput with a small 2.77-microsecond latency. The designed 4×4 linear MMSE MIMO detector is capable of complying with the proposed IEEE 802.11n standard.

Predictors of performance on the MMSE and the DRS-2 among American Indian elders.

Science.gov (United States)

Jervis, Lori L; Fickenscher, Alexandra; Beals, Janette; Cullum, C Munro; Novins, Douglas K; Manson, Spero M; Arciniegas, David B

2010-01-01

Little is known about factors that predict older American Indians' performance on cognitive tests. This study examined 137 American Indian elders' performance on the MMSE and the Dementia Rating Scale-Second Edition (DRS-2). Multivariate regression identified younger age, more education, not receiving Supplemental Security Income, and frequent receipt of needed health care as predictors of better performance on the MMSE. Better performance on the DRS-2 was predicted by more education, boarding school attendance, not receiving Supplemental Security Income, and frequent receipt of needed health care. This study points to the importance of economic and educational factors on cognitive test performance among American Indian elders.

Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) performance in progressive supranuclear palsy and multiple system atrophy.

Science.gov (United States)

Fiorenzato, Eleonora; Weis, Luca; Falup-Pecurariu, Cristian; Diaconu, Stefania; Siri, Chiara; Reali, Elisa; Pezzoli, Gianni; Bisiacchi, Patrizia; Antonini, Angelo; Biundo, Roberta

2016-12-01

To determine if Montreal Cognitive Assessment (MoCA) is more sensitive than the commonly used Mini-Mental State Examination (MMSE) in detecting cognitive abnormalities in patients with probable progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) compared with Parkinson's disease (PD). In this multicenter observational study, MMSE and MoCA were administered in a random order to 130 patients: 35 MSA, 30 PSP and 65 age, and education and gender matched-PD. We assessed between-group differences for MMSE, MoCA, and their subitems. Receiver-operating characteristic (ROC) curves were calculated. The mean MMSE was higher than the mean MoCA score in each MSA (27.7 ± 2.4 vs. 22.9 ± 3.0, p < 0.0001), PSP (26.0 ± 2.9 vs. 18.2 ± 3.9, p < 0.0001), and PD (27.3 ± 2.0 vs. 22.3 ± 3.5, p < 0.0001). MoCA total score as well as its letter fluency subitem differentiated PSP from MSA and PD with high specificity and moderate sensitivity. More specifically, a cut-off score of 7 F-words or less per minute would support a diagnosis of PSP (PSP vs. PD: 86 % specificity, 70 % sensitivity; PSP vs. MSA: 71 % specificity, 70 % sensitivity). By contrast, MMSE presented an overall ceiling effect for most subitems, except for the pentagon scores, where PSP did less well than MSA or PD patients. These preliminary results suggest that PSP and MSA, similar to PD patients, may present normal MMSE and reduced MoCA performance. Overall, MoCA is more sensitive than MMSE in detecting cognitive impairment in atypical parkinsonism and together with verbal fluency would be a useful test to support PSP diagnosis.

Adaptive DSP Algorithms for UMTS: Blind Adaptive MMSE and PIC Multiuser Detection

NARCIS (Netherlands)

Potman, J.

2003-01-01

A study of the application of blind adaptive Minimum Mean Square Error (MMSE) and Parallel Interference Cancellation (PIC) multiuser detection techniques to Wideband Code Division Multiple Access (WCDMA), the physical layer of Universal Mobile Telecommunication System (UMTS), has been performed as

On the impact of receiver imperfections on the MMSE-IRC receiver performance in 5G networks

DEFF Research Database (Denmark)

Tavares, Fernando Menezes Leitão; Berardinelli, Gilberto; Mahmood, Nurul Huda

2014-01-01

The usage of Minimum Mean Square Error - Interference Rejection Combining (MMSE-IRC) receivers is expected to be a significant performance booster in the ultra-dense deployment of small cells envisioned by an upcoming 5th generation (5G) Radio Access Technology (RAT). However, hardware limitation...... simulation results confirm that a realistic MMSE-IRC receiver can achieve throughput gains close to ideal, provided a reasonably high resolution Analog-to-Digital Converter (ADC) as well as a supportive radio frame format design are used....

Handling missing Mini-Mental State Examination (MMSE) values: Results from a cross-sectional long-term-care study.

Science.gov (United States)

Godin, Judith; Keefe, Janice; Andrew, Melissa K

2017-04-01

Missing values are commonly encountered on the Mini Mental State Examination (MMSE), particularly when administered to frail older people. This presents challenges for MMSE scoring in research settings. We sought to describe missingness in MMSEs administered in long-term-care facilities (LTCF) and to compare and contrast approaches to dealing with missing items. As part of the Care and Construction project in Nova Scotia, Canada, LTCF residents completed an MMSE. Different methods of dealing with missing values (e.g., use of raw scores, raw scores/number of items attempted, scale-level multiple imputation [MI], and blended approaches) are compared to item-level MI. The MMSE was administered to 320 residents living in 23 LTCF. The sample was predominately female (73%), and 38% of participants were aged >85 years. At least one item was missing from 122 (38.2%) of the MMSEs. Data were not Missing Completely at Random (MCAR), χ 2 (1110) = 1,351, p < 0.001. Using raw scores for those missing <6 items in combination with scale-level MI resulted in the regression coefficients and standard errors closest to item-level MI. Patterns of missing items often suggest systematic problems, such as trouble with manual dexterity, literacy, or visual impairment. While these observations may be relatively easy to take into account in clinical settings, non-random missingness presents challenges for research and must be considered in statistical analyses. We present suggestions for dealing with missing MMSE data based on the extent of missingness and the goal of analyses. Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

MMSE-NP-RISIC-Based Channel Equalization for MIMO-SC-FDE Troposcatter Communication Systems

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Zedong Xie

2016-01-01

Full Text Available The impact of intersymbol interference (ISI on single-carrier frequency-domain equalization with multiple input multiple output (MIMO-SC-FDE troposcatter communication systems is severe. Most of the channel equalization methods fail to solve it completely. In this paper, given the disadvantages of the noise-predictive (NP MMSE-based and the residual intersymbol interference cancellation (RISIC equalization in the single input single output (SISO system, we focus on the combination of both equalization schemes mentioned above. After extending both of them into MIMO system for the first time, we introduce a novel MMSE-NP-RISIC equalization method for MIMO-SC-FDE troposcatter communication systems. Analysis and simulation results validate the performance of the proposed method in time-varying frequency-selective troposcatter channel at an acceptable computational complexity cost.

Anisotropic kinetic energy release and gyroscopic behavior of CO2 super rotors from an optical centrifuge

Science.gov (United States)

Murray, Matthew J.; Ogden, Hannah M.; Mullin, Amy S.

2017-10-01

An optical centrifuge is used to generate an ensemble of CO2 super rotors with oriented angular momentum. The collision dynamics and energy transfer behavior of the super rotor molecules are investigated using high-resolution transient IR absorption spectroscopy. New multipass IR detection provides improved sensitivity to perform polarization-dependent transient studies for rotational states with 76 ≤ J ≤ 100. Polarization-dependent measurements show that the collision-induced kinetic energy release is spatially anisotropic and results from both near-resonant energy transfer between super rotor molecules and non-resonant energy transfer between super rotors and thermal molecules. J-dependent studies show that the extent and duration of the orientational anisotropy increase with rotational angular momentum. The super rotors exhibit behavior akin to molecular gyroscopes, wherein molecules with larger amounts of angular momentum are less likely to change their angular momentum orientation through collisions.

Super differential forms on super Riemann surfaces

International Nuclear Information System (INIS)

Konisi, Gaku; Takahasi, Wataru; Saito, Takesi.

1994-01-01

Line integral on the super Riemann surface is discussed. A 'super differential operator' which possesses both properties of differential and of differential operator is proposed. With this 'super differential operator' a new theory of differential form on the super Riemann surface is constructed. We call 'the new differentials on the super Riemann surface' 'the super differentials'. As the applications of our theory, the existency theorems of singular 'super differentials' such as 'super abelian differentials of the 3rd kind' and of a super projective connection are examined. (author)

Performance of Mini-Mental State Examination (MMSE) in long-stay patients with schizophrenia or schizoaffective disorders in a psychiatric institute.

Science.gov (United States)

Ong, Hui Lin; Subramaniam, Mythily; Abdin, Edimansyah; Wang, Peizhi; Vaingankar, Janhavi Ajit; Lee, Siau Pheng; Shafie, Saleha; Seow, Esmond; Chong, Siow Ann

2016-07-30

Studies have found that age and education were associated with cognition in older adults. However, little is known how clinical factors (e.g. age of illness onset, length of hospital stay, type of antipsychotic medications, and duration of illness) are associated with cognitive functioning in patients with schizophrenia. This study aimed to examine the influence of socio-demographic and clinical factors on cognitive domains measured using Mini-Mental State Examination (MMSE) among patients with schizophrenia or schizoaffective disorders residing in a psychiatric institute in Singapore. A single-phase interview was conducted at the Institute of Mental Health (IMH) in patients diagnosed with schizophrenia or schizoaffective disorders (n=110). MMSE was administered to all participants. Data on socio-demographic characteristics, smoking, alcohol consumption, and medical history were collected. Age, gender, and level of education were significantly associated with MMSE scores. After adjusting for all socio-demographic correlates, longer length of hospital stay remained significant in predicting lower MMSE scores. Length of hospital stay was independently associated with cognitive functioning. Early interventions for cognition such as physical and mental exercises should be implemented for better prognosis. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

[Mini Mental State Examination (MMSE): determination of cutoff scores according to age and educational level].

Science.gov (United States)

Solias, A; Skapinakis, P; Degleris, N; Pantoleon, M; Katirtzoglou, E; Politis, A

2014-01-01

For the last 38 years, Mini Mental State Examination (MMSE) has been widely used as a dementia screening measure in everyday clinical practice as well as in both cohort and cross-sectional studies. Its validity and reliability for the Greek population has explicitly been documented. However, the effect of age and education on the subject's performance makes it necessary to reckon them in the estimation of the "cutoff score". The purpose of this study is to estimate the prevalence of dementia in Greek population and determine the "cutoff score" by age and education-corrected norms. Cross sectional study of 630 patients older than 55 years, who live independently in Ilion and Helioupolis Municipalities was conducted, 27.3% of the subjects tested in the study were diagnosed with memory disorder according to their MMSE scores and the validation for the Greek population. The effect of age and education to the subjects' performance was statistically significant (p=.000). The use of standard "cutoff score" was not proved to be useful for the personalized interpretation of the results, as documented by the fact that older individuals with lower education had a poorer performance relatively to younger, highly educated subjects. Comparatively to the group age of 55-60 years, the odds ratio after the age of 75 years varies from 2.58 to 4.91. Regarding the variable factor of education, the odds ratio for the first degree education graduates decreases from 1.43 to 3.19 for the third degree education graduates in comparison with the group of illiterates. In conclusion, the use of the "cutoff score" algorithm and the simultaneous estimation of age and education effect on MMSE score may prove useful for the proper evaluation of MMSE performance. According to the age and education of examine candidates in the community and the primary care, we propose the use of the 25th percentile as a more useful cutoff score in order to decrease the false positive results.

Converting MMSE to MoCA and MoCA 5-minute protocol in an educationally heterogeneous sample with stroke or transient ischemic attack.

Science.gov (United States)

Wong, Adrian; Black, Sandra E; Yiu, Stanley Y P; Au, Lisa W C; Lau, Alexander Y L; Soo, Yannie O Y; Chan, Anne Y Y; Leung, Thomas W H; Wong, Lawrence K S; Kwok, Timothy C Y; Cheung, Theodore C K; Leung, Kam-Tat; Lam, Bonnie Y K; Kwan, Joseph S K; Mok, Vincent C T

2018-05-01

The Montreal Cognitive Assessment (MoCA) is psychometrically superior over the Mini-mental State Examination (MMSE) for cognitive screening in stroke or transient ischemic attack (TIA). It is free for clinical and research use. The objective of this study is to convert scores from the MMSE to MoCA and MoCA-5-minute protocol (MoCA-5 min) and to examine the ability of the converted scores in detecting cognitive impairment after stroke or TIA. A total of 904 patients were randomly divided into training (n = 623) and validation (n = 281) samples matched for demography and cognition. MMSE scores were converted to MoCA and MoCA-5 min using (1) equipercentile method with log-linear smoothing and (2) Poisson regression adjusting for age and education. Receiver operating characteristics curve analysis was used to examine the ability of the converted scores in differentiating patients with cognitive impairment. The mean education was 5.8 (SD = 4.6; ranged 0-20) years. The entire spectrum of MMSE scores was converted to MoCA and MoCA-5 min using equipercentile method. Relationship between MMSE and MoCA scores was confounded by age and education, and a conversion equation with adjustment for age and education was derived. In the validation sample, the converted scores differentiated cognitively impaired patients with area under receiver operating characteristics curve 0.826 to 0.859. We provided 2 methods to convert scores from the MMSE to MoCA and MoCA-5 min based on a large sample of patients with stroke or TIA having a wide range of education and cognitive levels. The converted scores differentiated patients with cognitive impairment after stroke or TIA with high accuracy. Copyright © 2018 John Wiley & Sons, Ltd.

The Ensembl REST API: Ensembl Data for Any Language.

Science.gov (United States)

Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

2015-01-01

We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.

Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF): A data assimilation scheme for memory intensive, high performance computing

Science.gov (United States)

Hut, Rolf; Amisigo, Barnabas A.; Steele-Dunne, Susan; van de Giesen, Nick

2015-12-01

Reduction of Used Memory Ensemble Kalman Filtering (RumEnKF) is introduced as a variant on the Ensemble Kalman Filter (EnKF). RumEnKF differs from EnKF in that it does not store the entire ensemble, but rather only saves the first two moments of the ensemble distribution. In this way, the number of ensemble members that can be calculated is less dependent on available memory, and mainly on available computing power (CPU). RumEnKF is developed to make optimal use of current generation super computer architecture, where the number of available floating point operations (flops) increases more rapidly than the available memory and where inter-node communication can quickly become a bottleneck. RumEnKF reduces the used memory compared to the EnKF when the number of ensemble members is greater than half the number of state variables. In this paper, three simple models are used (auto-regressive, low dimensional Lorenz and high dimensional Lorenz) to show that RumEnKF performs similarly to the EnKF. Furthermore, it is also shown that increasing the ensemble size has a similar impact on the estimation error from the three algorithms.

Is mini-mental score examination (MMSE scoring a new predictor of uncontrolled hypertension?

Directory of Open Access Journals (Sweden)

Khaled Sayed

2014-03-01

Conclusion: We conclude that MMSE is a simple test to run in clinic and can give an idea about the degree of structural damage caused to the brain; and hence predict whether or not the patient’s BP is well controlled. This would not replace the 24-hour ABPM but may help guide the clinicians to request this 24-hour monitoring.

The Agreement between the MMSE and IQCODE Tests in a Community-Based Sample of Subjects Aged 70 Years or Older Receiving In-Home Nursing: An Explorative Study

Directory of Open Access Journals (Sweden)

Øyvind Kirkevold

2015-02-01

Full Text Available Aim: It was the aim of this study to compare the Mini-Mental State Examination (MMSE with the Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE and to explore the characteristics of subjects with possible dementia with only one of the two tools. Methods: We used a random sample of patients aged 70+ receiving social service or in-home nursing. The patients were tested with the MMSE, and the next of kin was interviewed using the following: the IQCODE, the Cornell Scale for Depression in Dementia (CSDD, the Neuropsychiatric Inventory (NPI, instrumental activities of daily living (IADL, personal ADL (PADL and the General Medical Health Rating (GMHR. Results: Subjects with dementia defined only according to the MMSE showed a pattern of scores on IADL, PADL, CSDD, NPI-10 and GMHR similar to the no-dementia group according to both the MMSE and the IQCODE. Those with dementia defined only according to the IQCODE showed a pattern of scores similar to the possible dementia group according to both the MMSE and the IQCODE.

Ensemble Methods

Science.gov (United States)

Re, Matteo; Valentini, Giorgio

2012-03-01

Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been

Importance of rotational adiabaticity in collisions of CO2 super rotors with Ar and He

Science.gov (United States)

Murray, Matthew J.; Ogden, Hannah M.; Mullin, Amy S.

2018-02-01

The collision dynamics of optically centrifuged CO2 with Ar and He are reported here. The optical centrifuge produces an ensemble of CO2 molecules in high rotational states (with J ˜ 220) with oriented angular momentum. Polarization-dependent high-resolution transient IR absorption spectroscopy was used to measure the relaxation dynamics in the presence of Ar or He by probing the CO2 J = 76 and 100 states with Er o t=2306 and 3979 cm-1, respectively. The data show that He relaxes the CO2 super rotors more quickly than Ar. Doppler-broadened line profiles show that He collisions induce substantially larger rotation-to-translation energy transfer. CO2 super rotors have greater orientational anisotropy with He collisions and the anisotropy from the He collisions persists longer than with Ar. Super rotor relaxation dynamics are discussed in terms of mass effects related to classical gyroscope physics and collisional rotational adiabaticity.

Super-quantum curves from super-eigenvalue models

Energy Technology Data Exchange (ETDEWEB)

Ciosmak, Paweł [Faculty of Mathematics, Informatics and Mechanics, University of Warsaw,ul. Banacha 2, 02-097 Warsaw (Poland); Hadasz, Leszek [M. Smoluchowski Institute of Physics, Jagiellonian University,ul. Łojasiewicza 11, 30-348 Kraków (Poland); Manabe, Masahide [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Sułkowski, Piotr [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E. California Blvd, Pasadena, CA 91125 (United States)

2016-10-10

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Super-quantum curves from super-eigenvalue models

International Nuclear Information System (INIS)

Ciosmak, Paweł; Hadasz, Leszek; Manabe, Masahide; Sułkowski, Piotr

2016-01-01

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Super-quantum curves from super-eigenvalue models

Science.gov (United States)

Ciosmak, Paweł; Hadasz, Leszek; Manabe, Masahide; Sułkowski, Piotr

2016-10-01

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/ β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Comparison between mini mental state examination (MMSE) and Montreal cognitive assessment Indonesian version (MoCA-Ina) as an early detection of cognitive impairments in post-stroke patients

Science.gov (United States)

Lestari, S.; Mistivani, I.; Rumende, C. M.; Kusumaningsih, W.

2017-08-01

Mild cognitive impairment (MCI) is defined as cognitive impairment that may never develop into dementia. Cognitive impairment is one long-term complication of a stroke. The Mini Mental State Examination (MMSE), which is commonly used as a screening tool for cognitive impairment, has a low sensitivity to detect cognitive impairment, especially MCI. Alternatively, the Montreal Cognitive Assessment Indonesian version (MoCA-Ina) has been reported to have a higher sensitivity than the MMSE. The aim of this study was to compare the proportion of MCI identified between the MMSE and MoCA-Ina in stroke patients. This was a cross-sectional study of stroke outpatients who attended the Polyclinic Neuromuscular Division, Rehabilitation Department, and Polyclinic Stroke, Neurology Department Cipto Mangunkusumo General Hospital, Jakarta. The proportion of MCI identified using the MMSE was 31.03% compared to 72.41% when using the MoCA-Ina. This difference was statistically significant (Fisher’s exact test, p = 0.033). The proportion of MCI in stroke patients was higher when using the MoCA-Ina compared to the MMSE. The MoCA-Ina should be used as an alternative in the early detection of MCI in stroke patients, especially those undergoing rehabilitation.

Coagulation calculations of icy planet formation around 0.1-0.5 M {sub ☉} stars: Super-Earths from large planetesimals

Energy Technology Data Exchange (ETDEWEB)

Kenyon, Scott J. [Smithsonian Astrophysical Observatory, 60 Garden Street, Cambridge, MA 02138 (United States); Bromley, Benjamin C., E-mail: skenyon@cfa.harvard.edu, E-mail: bromley@physics.utah.edu [Department of Physics, University of Utah, 201 JFB, Salt Lake City, UT 84112 (United States)

2014-01-01

We investigate formation mechanisms for icy super-Earth-mass planets orbiting at 2-20 AU around 0.1-0.5 M {sub ☉} stars. A large ensemble of coagulation calculations demonstrates a new formation channel: disks composed of large planetesimals with radii of 30-300 km form super-Earths on timescales of ∼1 Gyr. In other gas-poor disks, a collisional cascade grinds planetesimals to dust before the largest planets reach super-Earth masses. Once icy Earth-mass planets form, they migrate through the leftover swarm of planetesimals at rates of 0.01-1 AU Myr{sup –1}. On timescales of 10 Myr to 1 Gyr, many of these planets migrate through the disk of leftover planetesimals from semimajor axes of 5-10 AU to 1-2 AU. A few percent of super-Earths might migrate to semimajor axes of 0.1-0.2 AU. When the disk has an initial mass comparable with the minimum-mass solar nebula, scaled to the mass of the central star, the predicted frequency of super-Earths matches the observed frequency.

Screening an elderly hearing impaired population for mild cognitive impairment using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA).

Science.gov (United States)

Lim, Magdalene Yeok Leng; Loo, Jenny Hooi Yin

2018-07-01

To determine if there is an association between hearing loss and poorer cognitive scores on Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) and to determine if poor hearing acuity affects scoring on the cognitive screening tests of MMSE and MoCA. One hundred fourteen elderly patients (Singapore residents) aged between 55 and 86 years were sampled. Participants completed a brief history questionnaire, pure tone audiometry, and 2 cognitive screening tests-the MMSE and MoCA. Average hearing thresholds of the better ear in the frequencies of 0.5, 1, 2, and 4 kHz were used for data analysis. Hearing loss was significantly associated with poorer cognitive scores in Poisson regression models adjusted for age. Mini-Mental State Examination scores were shown to decrease by 2.8% (P = .029), and MoCA scores by 3.5% (P = .013) for every 10 dB of hearing loss. Analysis of hearing-sensitive components of "Registration" and "Recall" in MMSE and MoCA using chi-square tests showed significantly poorer performance in the hearing loss group as compared to the normal hearing group. Phonetic analysis of target words with high error rates shows that the poor performance was likely contributed by decreased hearing acuity, on top of a possible true deficit in cognition in the hearing impaired. Hearing loss is associated with poorer cognitive scores on MMSE and MoCA, and cognitive scoring is likely confounded by poor hearing ability. This highlights an important, often overlooked aspect of sensory impairment during cognitive screening. Provisions should be made when testing for cognition in the hearing-impaired population to avoid over-referral and subsequent misdiagnoses of cognitive impairment. Copyright © 2018 John Wiley & Sons, Ltd.

Reliability and validity of revised Turkish version of Mini Mental State Examination (rMMSE-T) in community-dwelling educated and uneducated elderly.

Science.gov (United States)

Keskinoglu, Pembe; Ucku, Reyhan; Yener, Görsev; Yaka, Erdem; Kurt, Pinar; Tunca, Zeliha

2009-11-01

To evaluate the reliability and validity of the revised Turkish version of Mini Mental State Examination (rMMSE-T) in educated and uneducated community-dwelling elderly, to re-organize the present Turkish version of MMSE and to determine cut-off point of the revised test. This cross-sectional and analytical study involved totally 490 elderly subjects selected by cluster sampling method. Receiver operating characteristic (ROC) analysis, kappa analysis and Cronbach's alpha coefficients were used for statistical analysis. Areas under ROC curve in educated and uneducated elderly were found as 0.953 and 0.907. Cut-off point of 22/23 of rMMSE-T in educated elderly had the highest sensitivity (90.9), specificity (97.0) and positive likelihood ratio (30.3), whereas cut-off point of 18/19 of the test in uneducated elderly had the highest sensitivity (82.7), specificity (92.3) and positive likelihood ratio (10.7). The Cronbach's alpha values of the rMMSE-T for educated and uneducated elderly were higher than 0.7 (sign of good internal consistency of the test). A significant correlations between intrarater and interrater test-retest in educated elderly subjects were observed (0.966 (p = 0.000); 0.855 (p = 0.000), respectively), and also in uneducated elderly (0.988 (p = 0.000); 0.934 (p = 0.000), respectively). Kappa value of the test in educated and uneducated elderly showed a perfect agreement interraters (1.000) and a substantial agreement in intraraters (1.000, 0.784; 0.826, 0.656, respectively). rMMSE-T had a high reliability and validity. It will be more appropriate to use the revised test and the new cut-off point for the diagnosis and screening of dementia among community-dwelling Turkish elderly population. Copyright 2009 John Wiley & Sons, Ltd.

Low Complexity Submatrix Divided MMSE Sparse-SQRD Detection for MIMO-OFDM with ESPAR Antenna Receiver

Directory of Open Access Journals (Sweden)

Diego Javier Reinoso Chisaguano

2013-01-01

Full Text Available Multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM with an electronically steerable passive array radiator (ESPAR antenna receiver can improve the bit error rate performance and obtains additional diversity gain without increasing the number of Radio Frequency (RF front-end circuits. However, due to the large size of the channel matrix, the computational cost required for the detection process using Vertical-Bell Laboratories Layered Space-Time (V-BLAST detection is too high to be implemented. Using the minimum mean square error sparse-sorted QR decomposition (MMSE sparse-SQRD algorithm for the detection process the average computational cost can be considerably reduced but is still higher compared with a conventional MIMOOFDM system without ESPAR antenna receiver. In this paper, we propose to use a low complexity submatrix divided MMSE sparse-SQRD algorithm for the detection process of MIMOOFDM with ESPAR antenna receiver. The computational cost analysis and simulation results show that on average the proposed scheme can further reduce the computational cost and achieve a complexity comparable to the conventional MIMO-OFDM detection schemes.

Throughput of Type II HARQ-OFDM/TDM Using MMSE-FDE in a Multipath Channel

Directory of Open Access Journals (Sweden)

Haris Gacanin

2009-01-01

Full Text Available In type II hybrid ARQ (HARQ schemes, the uncoded information bits are transmitted first, while the error correction parity bits are sent upon request. Consequently, frequency diversity cannot be exploited during the first transmission. In this paper, we present the use of OFDM/TDM with MMSE-FDE and type II HARQ to increase throughput of OFDM due to frequency diversity gain.

Super jackstraws and super waterwheels

International Nuclear Information System (INIS)

Cho, Jin-Ho

2007-01-01

We construct various new BPS states of D-branes preserving 8 supersymmetries. These include super Jackstraws (a bunch of scattered D- or (p, q)-strings preserving supersymmetries), and super waterwheels (a number of D2-branes intersecting at generic angles on parallel lines while preserving supersymmetries). Super D-Jackstraws are scattered in various dimensions but are dynamical with all their intersections following a common null direction. Meanwhile, super (p, q)-Jackstraws form a planar static configuration. We show that the SO(2) subgroup of SL(2, R), the group of classical S-duality transformations in IIB theory, can be used to generate this latter configuration of variously charged (p, q)-strings intersecting at various angles. The waterwheel configuration of D2-branes preserves 8 supersymmetries as long as the 'critical' Born-Infeld electric fields are along the common direction

Nonlinear Super Integrable Couplings of Super Classical-Boussinesq Hierarchy

Directory of Open Access Journals (Sweden)

Xiuzhi Xing

2014-01-01

Full Text Available Nonlinear integrable couplings of super classical-Boussinesq hierarchy based upon an enlarged matrix Lie super algebra were constructed. Then, its super Hamiltonian structures were established by using super trace identity. As its reduction, nonlinear integrable couplings of the classical integrable hierarchy were obtained.

On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

KAUST Repository

Luo, Xiaodong; Hoteit, Ibrahim; Moroz, Irene M.

2010-01-01

However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

The super-classical-Boussinesq hierarchy and its super-Hamiltonian structure

International Nuclear Information System (INIS)

Si-Xing, Tao; Tie-Cheng, Xia

2010-01-01

Based on the constructed Lie superalgebra, the super-classical-Boussinesq hierarchy is obtained. Then, its super-Hamiltonian structure is obtained by making use of super-trace identity. Furthermore, the super-classical-Boussinesq hierarchy is also integrable in the sense of Liouville. (general)

Mini-Mental State Examination (MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in community and primary care populations

OpenAIRE

Creavin, Sam T; Wisniewski, Susanna; Noel-Storr, Anna H; Trevelyan, Clare M; Hampton, Thomas; Rayment, Dane; Thom, Victoria M; Nash, Kirsty J E; Elhamoui, Hosam; Milligan, Rowena; Patel, Anish S; Tsivos, Demitra V; Wing, Tracey; Phillips, Emma; Kellman, Sophie M

2016-01-01

BACKGROUND: The Mini Mental State Examination (MMSE) is a cognitive test that is commonly used as part of the evaluation for possible dementia.OBJECTIVES: To determine the diagnostic accuracy of the Mini-Mental State Examination (MMSE) at various cut points for dementia in people aged 65 years and over in community and primary care settings who had not undergone prior testing for dementia.SEARCH METHODS: We searched the specialised register of the Cochrane Dementia and Cognitive Improvement G...

Robust isotropic super-resolution by maximizing a Laplace posterior for MRI volumes

Science.gov (United States)

Han, Xian-Hua; Iwamoto, Yutaro; Shiino, Akihiko; Chen, Yen-Wei

2014-03-01

Magnetic resonance imaging can only acquire volume data with finite resolution due to various factors. In particular, the resolution in one direction (such as the slice direction) is much lower than others (such as the in-plane direction), yielding un-realistic visualizations. This study explores to reconstruct MRI isotropic resolution volumes from three orthogonal scans. This proposed super- resolution reconstruction is formulated as a maximum a posterior (MAP) problem, which relies on the generation model of the acquired scans from the unknown high-resolution volumes. Generally, the deviation ensemble of the reconstructed high-resolution (HR) volume from the available LR ones in the MAP is represented as a Gaussian distribution, which usually results in some noise and artifacts in the reconstructed HR volume. Therefore, this paper investigates a robust super-resolution by formulating the deviation set as a Laplace distribution, which assumes sparsity in the deviation ensemble based on the possible insight of the appeared large values only around some unexpected regions. In addition, in order to achieve reliable HR MRI volume, we integrates the priors such as bilateral total variation (BTV) and non-local mean (NLM) into the proposed MAP framework for suppressing artifacts and enriching visual detail. We validate the proposed robust SR strategy using MRI mouse data with high-definition resolution in two direction and low-resolution in one direction, which are imaged in three orthogonal scans: axial, coronal and sagittal planes. Experiments verifies that the proposed strategy can achieve much better HR MRI volumes than the conventional MAP method even with very high-magnification factor: 10.

On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

KAUST Repository

Luo, Xiaodong

2010-09-19

The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

Science.gov (United States)

Chen, Lei; Kamel, Mohamed S.

2016-01-01

In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

Iterative MMSE Detection for MIMO/BLAST DS-CDMA Systems in Frequency Selective Fading Channels - Achieving High Performance in Fully Loaded Systems

Science.gov (United States)

Silva, João Carlos; Souto, Nuno; Cercas, Francisco; Dinis, Rui

A MMSE (Minimum Mean Square Error) DS-CDMA (Direct Sequence-Code Division Multiple Access) receiver coupled with a low-complexity iterative interference suppression algorithm was devised for a MIMO/BLAST (Multiple Input, Multiple Output / Bell Laboratories Layered Space Time) system in order to improve system performance, considering frequency selective fading channels. The scheme is compared against the simple MMSE receiver, for both QPSK and 16QAM modulations, under SISO (Single Input, Single Output) and MIMO systems, the latter with 2Tx by 2Rx and 4Tx by 4Rx (MIMO order 2 and 4 respectively) antennas. To assess its performance in an existing system, the uncoded UMTS HSDPA (High Speed Downlink Packet Access) standard was considered.

A super soliton connection

International Nuclear Information System (INIS)

Gurses, M.; Oguz, O.

1985-07-01

Integrable super non-linear classical partial differential equations are considered. A super s1(2,R) algebra valued connection 1-form is constructed. It is shown that curvature 2-form of this super connection vanishes by virtue of the integrable super equations of motion. A super extension of the AKNS scheme is presented and a class of super extension of the Lax hierarchy and super non-linear Schroedinger equation are found. O(N) extension and the Baecklund transformations of the above super equations are also considered. (author)

Ensembl 2004.

Science.gov (United States)

Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

2004-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

Directory of Open Access Journals (Sweden)

Jan D. Keller

2008-12-01

Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

Is the Montreal Cognitive Assessment (MoCA) test better suited than the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) detection among people aged over 60? Meta-analysis.

Science.gov (United States)

Ciesielska, Natalia; Sokołowski, Remigiusz; Mazur, Ewelina; Podhorecka, Marta; Polak-Szabela, Anna; Kędziora-Kornatowska, Kornelia

2016-10-31

Screening tests play a crucial role in dementia diagnostics, thus they should be very sensitive for mild cognitive impairment (MCI) assessment. Nowadays, the MiniMental State Examination (MMSE) is the most commonly used scale in cognitive function evaluation, albeit it is claimed to be imprecise for MCI detection. The Montreal Cognitive Assessment (MoCA), was created as an alternative method for MMSE. Aim. MoCA vs. MMSE credibility assessment in detecting MCI, while taking into consideration the sensitivity and specificity by cut-off points. A systematic literature search was carried out by the authors using EBSCO host Web, Wiley Online Library, Springer Link, Science Direct and Medline databases. The following medical subject headings were used in the search: mild cognitive impairment, mini-mental state examination, Montreal cognitive assessment, diagnostics value. Papers which met inclusion and exclusion criteria were chosen to be included in this review. At the end, for the evaluation of MoCA 20, and MMSE 13 studies were qualified. Research credibility was established by computing weighted arithmetic mean, where weight is defined as population for which the result of sensitivity and specificity for the cut-off point was achieved. The cut-offs are shown as ROC curve and accuracy of diagnosis for MoCA and MMSE was calculated as the area under the curve (AUC). ROC curve analysis for MoCA demonstrated that MCI best detection can be achieved with a cut-off point of 24/25 (n = 9350, the sensitivity of 80.48% and specificity of 81.19%). AUC was 0.846 (95% CI 0.823-0.868). For MMSE, it turned out that more important cut-off was of 27/28 (n = 882, 66.34% sensitivity and specificity of 72.94%). AUC was 0.736 (95% CI 0.718-0.767). MoCA test better meets the criteria for screening tests for the detection of MCI among patients over 60 years of age than MMSE.

Performance Comparison between CDTD and STTD for DS-CDMA/MMSE-FDE with Frequency-Domain ICI Cancellation

Science.gov (United States)

Takeda, Kazuaki; Kojima, Yohei; Adachi, Fumiyuki

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can provide a better bit error rate (BER) performance than rake combining. However, the residual inter-chip interference (ICI) is produced after MMSE-FDE and this degrades the BER performance. Recently, we showed that frequency-domain ICI cancellation can bring the BER performance close to the theoretical lower bound. To further improve the BER performance, transmit antenna diversity technique is effective. Cyclic delay transmit diversity (CDTD) can increase the number of equivalent paths and hence achieve a large frequency diversity gain. Space-time transmit diversity (STTD) can obtain antenna diversity gain due to the space-time coding and achieve a better BER performance than CDTD. Objective of this paper is to show that the BER performance degradation of CDTD is mainly due to the residual ICI and that the introduction of ICI cancellation gives almost the same BER performance as STTD. This study provides a very important result that CDTD has a great advantage of providing a higher throughput than STTD. This is confirmed by computer simulation. The computer simulation results show that CDTD can achieve higher throughput than STTD when ICI cancellation is introduced.

Super-Calogero-Moser-Sutherland systems and free super-oscillators: a mapping

International Nuclear Information System (INIS)

Ghosh, Pijush K.

2001-01-01

We show that the supersymmetric rational Calogero-Moser-Sutherland (CMS) model of A N+1 -type is equivalent to a set of free super-oscillators, through a similarity transformation. We prescribe methods to construct the complete eigenspectrum and the associated eigenfunctions, both in supersymmetry-preserving as well as supersymmetry-breaking phases, from the free super-oscillator basis. Further we show that a wide class of super-Hamiltonians realizing dynamical OSp(2 vertical bar 2) supersymmetry, which also includes all types of rational super-CMS as a small subset, are equivalent to free super-oscillators. We study BC N+1 -type super-CMS model in some detail to understand the subtleties involved in this method

Super Riemann surfaces

International Nuclear Information System (INIS)

Rogers, Alice

1990-01-01

A super Riemann surface is a particular kind of (1,1)-dimensional complex analytic supermanifold. From the point of view of super-manifold theory, super Riemann surfaces are interesting because they furnish the simplest examples of what have become known as non-split supermanifolds, that is, supermanifolds where the odd and even parts are genuinely intertwined, as opposed to split supermanifolds which are essentially the exterior bundles of a vector bundle over a conventional manifold. However undoubtedly the main motivation for the study of super Riemann surfaces has been their relevance to the Polyakov quantisation of the spinning string. Some of the papers on super Riemann surfaces are reviewed. Although recent work has shown all super Riemann surfaces are algebraic, some areas of difficulty remain. (author)

BREEDING SUPER-EARTHS AND BIRTHING SUPER-PUFFS IN TRANSITIONAL DISKS

Energy Technology Data Exchange (ETDEWEB)

Lee, Eve J.; Chiang, Eugene, E-mail: evelee@berkeley.edu, E-mail: echiang@astro.berkeley.edu [Department of Astronomy, University of California Berkeley, Berkeley, CA 94720-3411 (United States)

2016-02-01

The riddle posed by super-Earths (1–4R{sub ⊕}, 2–20M{sub ⊕}) is that they are not Jupiters: their core masses are large enough to trigger runaway gas accretion, yet somehow super-Earths accreted atmospheres that weigh only a few percent of their total mass. We show that this puzzle is solved if super-Earths formed late, as the last vestiges of their parent gas disks were about to clear. This scenario would seem to present fine-tuning problems, but we show that there are none. Ambient gas densities can span many (in one case up to 9) orders of magnitude, and super-Earths can still robustly emerge after ∼0.1–1 Myr with percent-by-weight atmospheres. Super-Earth cores are naturally bred in gas-poor environments where gas dynamical friction has weakened sufficiently to allow constituent protocores to gravitationally stir one another and merge. So little gas is present at the time of core assembly that cores hardly migrate by disk torques: formation of super-Earths can be in situ. The basic picture—that close-in super-Earths form in a gas-poor (but not gas-empty) inner disk, fed continuously by gas that bleeds inward from a more massive outer disk—recalls the largely evacuated but still accreting inner cavities of transitional protoplanetary disks. We also address the inverse problem presented by super-puffs: an uncommon class of short-period planets seemingly too voluminous for their small masses (4–10R{sub ⊕}, 2–6M{sub ⊕}). Super-puffs most easily acquire their thick atmospheres as dust-free, rapidly cooling worlds outside ∼1 AU where nebular gas is colder, less dense, and therefore less opaque. Unlike super-Earths, which can form in situ, super-puffs probably migrated in to their current orbits; they are expected to form the outer links of mean-motion resonant chains, and to exhibit greater water content. We close by confronting observations and itemizing remaining questions.

BREEDING SUPER-EARTHS AND BIRTHING SUPER-PUFFS IN TRANSITIONAL DISKS

International Nuclear Information System (INIS)

Lee, Eve J.; Chiang, Eugene

2016-01-01

The riddle posed by super-Earths (1–4R ⊕ , 2–20M ⊕ ) is that they are not Jupiters: their core masses are large enough to trigger runaway gas accretion, yet somehow super-Earths accreted atmospheres that weigh only a few percent of their total mass. We show that this puzzle is solved if super-Earths formed late, as the last vestiges of their parent gas disks were about to clear. This scenario would seem to present fine-tuning problems, but we show that there are none. Ambient gas densities can span many (in one case up to 9) orders of magnitude, and super-Earths can still robustly emerge after ∼0.1–1 Myr with percent-by-weight atmospheres. Super-Earth cores are naturally bred in gas-poor environments where gas dynamical friction has weakened sufficiently to allow constituent protocores to gravitationally stir one another and merge. So little gas is present at the time of core assembly that cores hardly migrate by disk torques: formation of super-Earths can be in situ. The basic picture—that close-in super-Earths form in a gas-poor (but not gas-empty) inner disk, fed continuously by gas that bleeds inward from a more massive outer disk—recalls the largely evacuated but still accreting inner cavities of transitional protoplanetary disks. We also address the inverse problem presented by super-puffs: an uncommon class of short-period planets seemingly too voluminous for their small masses (4–10R ⊕ , 2–6M ⊕ ). Super-puffs most easily acquire their thick atmospheres as dust-free, rapidly cooling worlds outside ∼1 AU where nebular gas is colder, less dense, and therefore less opaque. Unlike super-Earths, which can form in situ, super-puffs probably migrated in to their current orbits; they are expected to form the outer links of mean-motion resonant chains, and to exhibit greater water content. We close by confronting observations and itemizing remaining questions

The Super Patalan Numbers

OpenAIRE

Richardson, Thomas M.

2014-01-01

We introduce the super Patalan numbers, a generalization of the super Catalan numbers in the sense of Gessel, and prove a number of properties analagous to those of the super Catalan numbers. The super Patalan numbers generalize the super Catalan numbers similarly to how the Patalan numbers generalize the Catalan numbers.

Grassmann, super-Kac-Moody and super-derivation algebras

International Nuclear Information System (INIS)

Frappat, L.; Ragoucy, E.; Sorba, P.

1989-05-01

We study the cyclic cocycles of degree one on the Grassmann algebra and on the super-circle with N supersymmetries (i.e. the tensor product of the algebra of functions on the circle times a Grassmann algebra with N generators). They are related to central extensions of graded loop algebras (i.e. super-Kac-Moody algebras). The corresponding algebras of super-derivations have to be compatible with the cocycle characterizing the extension; we give a general method for determining these algebras and examine in particular the cases N = 1,2,3. We also discuss their relations with the Ademollo et al. algebras, and examine the possibility of defining new kinds of super-conformal algebras, which, for N > 1, generalize the N = 1 Ramond-Neveu-Schwarz algebra

Theory of nonlinear optical response of ensembles of double quantum dots

Science.gov (United States)

Sitek, Anna; Machnikowski, Paweł

2009-09-01

We study theoretically the time-resolved four-wave mixing (FWM) response of an ensemble of pairs of quantum dots undergoing radiative recombination. At short (picosecond) delay times, the response signal shows beats that may be dominated by the subensemble of resonant pairs, which gives access to the information on the interdot coupling. At longer delay times, the decay of the FWM signal is governed by two rates which result from the collective interaction between the two dots and the radiation modes. The two rates correspond to the subradiant and super-radiant components in the radiative decay. Coupling between the dots enhances the collective effects and makes them observable even when the average energy mismatch between the dots is relatively large.

[Discriminatory validity and association of the mini-mental test (MMSE) and the memory alteration test (M@T) with a neuropsychological battery in patients with amnestic mild cognitive impairment and Alzheimer's disease].

Science.gov (United States)

Rami, L; Bosch, B; Valls-Pedret, C; Caprile, C; Sánchez-Valle Díaz, R; Molinuevo, J L

To establish the discriminatory validity of the mini-mental test (MMSE) and the memory alteration test (M@T) for the diagnosis of amnestic mild cognitive impairment (aMCI) and probable Alzheimer's disease (AD), and also to study the association between the results obtained in screening tests, a neuropsychological battery and a functional questionnaire in healthy persons and in patients with aMCI and AD. We evaluated 27 normal controls, 27 patients with aMCI and 35 patients with AD using the MMSE and a memory screening test, the M@T, a neuropsychological battery and a questionnaire on functional activities of daily living. Pearson correlation coefficients were used to evaluate the relations between the scores on the M@T and the MMSE and the neuropsychological tests. The area below the curve, the sensitivity and the specificity were calculated for the screening tests. In patients with aMCI, the scores on the M@T and the MMSE were strongly associated with the performance in the episodic memory tests in frontal tests and with the scores on the functional questionnaire, but not with tests that evaluated praxias and perceptive functions. In patients with AD, the scores on the M@T and the MMSE were associated with results in semantic memory, language, executive functions and praxias, but not with perceptive tests and functional questionnaires. In patients with aMCI and AD, the association between MMSE and M@T only correlate with some cognitive functions, without there being any association with other cognitive functions. Therefore, screening tests cannot be used as the only instrument for evaluating the cognitive status in patients with suspected dementia.

Entropy of network ensembles

Science.gov (United States)

Bianconi, Ginestra

2009-03-01

In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

Ensembl variation resources

Directory of Open Access Journals (Sweden)

Marin-Garcia Pablo

2010-05-01

Full Text Available Abstract Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.

NYYD Ensemble

Index Scriptorium Estoniae

2002-01-01

NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx

The Montreal Cognitive Assessment (MoCA) is superior to the Mini Mental State Examination (MMSE) in detection of korsakoffs syndrome

NARCIS (Netherlands)

Oudman, Erik; Postma, Albert; Van Der Stigchel, Stefan; Appelhof, Britt; Wijnia, Jan W.; Nijboer, Tanja C W

2014-01-01

The Montreal Cognitive Assessment (MoCA) and Mini Mental State Examination (MMSE) are brief screening instruments for cognitive disorders. Although these instruments have frequently been used in the detection of dementia, there is currently little knowledge on the validity to detect Korsakoffs

Research and development of super light water reactors and super fast reactors in Japan

International Nuclear Information System (INIS)

Oka, Y.; Morooka, S.; Yamakawa, M.; Ishiwatari, Y.; Ikejiri, S.; Katsumura, Y.; Muroya, Y.; Terai, T.; Sasaki, K.; Mori, H.; Hamamoto, Y.; Okumura, K.; Kugo, T.; Nakatsuka, T.; Ezato, K.; Akasaka, N.; Hotta, A.

2011-01-01

Super Light Water Reactors (Super LWR) and Super Fast Reactors (Super FR) are the supercritical- pressure light water cooled reactors (SCWR) that are developed by the research group of University of Tokyo since 1989 and now jointly under development with the researchers of Waseda University, University of Tokyo and other organizations in Japan. The principle of the reactor concept development, the results of the past Super LWR and Super FR R&D as well as the R&D program of the Super FR second phase project are described. (author)

The super W∞ symmetry of the Manin-Radul super KP hierarchy

International Nuclear Information System (INIS)

Das, A.; Sin, S.J.

1991-11-01

We show that the Manin-Radul super KP hierarchy is invariant under super W ∞ transformations. These transformations are characterized by time dependent flows which commute with the usual flows generated by the conserved quantities of the super KP hierarchy. (author). 16 refs

'Lazy' quantum ensembles

International Nuclear Information System (INIS)

Parfionov, George; Zapatrin, Roman

2006-01-01

We compare different strategies aimed to prepare an ensemble with a given density matrix ρ. Preparing the ensemble of eigenstates of ρ with appropriate probabilities can be treated as 'generous' strategy: it provides maximal accessible information about the state. Another extremity is the so-called 'Scrooge' ensemble, which is mostly stingy in sharing the information. We introduce 'lazy' ensembles which require minimal effort to prepare the density matrix by selecting pure states with respect to completely random choice. We consider two parties, Alice and Bob, playing a kind of game. Bob wishes to guess which pure state is prepared by Alice. His null hypothesis, based on the lack of any information about Alice's intention, is that Alice prepares any pure state with equal probability. Then, the average quantum state measured by Bob turns out to be ρ, and he has to make a new hypothesis about Alice's intention solely based on the information that the observed density matrix is ρ. The arising 'lazy' ensemble is shown to be the alternative hypothesis which minimizes type I error

Reduced-Rank Chip-Level MMSE Equalization for the 3G CDMA Forward Link with Code-Multiplexed Pilot

Directory of Open Access Journals (Sweden)

Goldstein J Scott

2002-01-01

Full Text Available This paper deals with synchronous direct-sequence code-division multiple access (CDMA transmission using orthogonal channel codes in frequency selective multipath, motivated by the forward link in 3G CDMA systems. The chip-level minimum mean square error (MMSE estimate of the (multiuser synchronous sum signal transmitted by the base, followed by a correlate and sum, has been shown to perform very well in saturated systems compared to a Rake receiver. In this paper, we present the reduced-rank, chip-level MMSE estimation based on the multistage nested Wiener filter (MSNWF. We show that, for the case of a known channel, only a small number of stages of the MSNWF is needed to achieve near full-rank MSE performance over a practical single-to-noise ratio (SNR range. This holds true even for an edge-of-cell scenario, where two base stations are contributing near equal-power signals, as well as for the single base station case. We then utilize the code-multiplexed pilot channel to train the MSNWF coefficients and show that adaptive MSNWF operating in a very low rank subspace performs slightly better than full-rank recursive least square (RLS and significantly better than least mean square (LMS. An important advantage of the MSNWF is that it can be implemented in a lattice structure, which involves significantly less computation than RLS. We also present structured MMSE equalizers that exploit the estimate of the multipath arrival times and the underlying channel structure to project the data vector onto a much lower dimensional subspace. Specifically, due to the sparseness of high-speed CDMA multipath channels, the channel vector lies in the subspace spanned by a small number of columns of the pulse shaping filter convolution matrix. We demonstrate that the performance of these structured low-rank equalizers is much superior to unstructured equalizers in terms of convergence speed and error rates.

Cerebral blood flow study with 3D-SSP and neuropsychological evaluation by mini-mental state examination (MMSE) before and after clipping of unruptured cerebral aneurysm

International Nuclear Information System (INIS)

Takada, Hidekazu; Sasaki, Takehiko; Osato, Toshiaki

2006-01-01

We evaluate the influence of surgery for unruptured aneurysms on cerebral blood flow and neuropsychological estimate. We evaluated the cases of 28 consecutive patients with unruptured cerebral aneurysm treated with direct surgery accompanied by craniotomy. Before and after surgery, MRI, 123 I-IMP-SPECT with 3D-SSP analysis and MMSE were performed. There was not a significant decrease in MMSE. In 123 I-IMP-SPECT, it was recognized that the cerebral blood flow was decreased at the frontal operculum of operative site. These results indicate that careful neuropsychological evaluation is essential to make a favorable treatment plan for unruptured aneulysms. (author)

Imprinting and recalling cortical ensembles.

Science.gov (United States)

Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S; Yuste, Rafael

2016-08-12

Neuronal ensembles are coactive groups of neurons that may represent building blocks of cortical circuits. These ensembles could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations from ensembles in the visual cortex of awake mice builds neuronal ensembles that recur spontaneously after being imprinted and do not disrupt preexisting ones. Moreover, imprinted ensembles can be recalled by single- cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. Copyright © 2016, American Association for the Advancement of Science.

World Music Ensemble: Kulintang

Science.gov (United States)

Beegle, Amy C.

2012-01-01

As instrumental world music ensembles such as steel pan, mariachi, gamelan and West African drums are becoming more the norm than the exception in North American school music programs, there are other world music ensembles just starting to gain popularity in particular parts of the United States. The kulintang ensemble, a drum and gong ensemble…

Reduction of 4-dim self dual super Yang-Mills onto super Riemann surfaces

International Nuclear Information System (INIS)

Mendoza, A.; Restuccia, A.; Martin, I.

1990-05-01

Recently self dual super Yang-Mills over a super Riemann surface was obtained as the zero set of a moment map on the space of superconnections to the dual of the super Lie algebra of gauge transformations. We present a new formulation of 4-dim Euclidean self dual super Yang-Mills in terms of constraints on the supercurvature. By dimensional reduction we obtain the same set of superconformal field equations which define self dual connections on a super Riemann surface. (author). 10 refs

On the Effect of Sphere-Overlap on Super Coarse-Grained Models of Protein Assemblies

Science.gov (United States)

Degiacomi, Matteo T.

2018-05-01

Ion mobility mass spectrometry (IM/MS) can provide structural information on intact protein complexes. Such data, including connectivity and collision cross sections (CCS) of assemblies' subunits, can in turn be used as a guide to produce representative super coarse-grained models. These models are constituted by ensembles of overlapping spheres, each representing a protein subunit. A model is considered plausible if the CCS and sphere-overlap levels of its subunits fall within predetermined confidence intervals. While the first is determined by experimental error, the latter is based on a statistical analysis on a range of protein dimers. Here, we first propose a new expression to describe the overlap between two spheres. Then we analyze the effect of specific overlap cutoff choices on the precision and accuracy of super coarse-grained models. Finally, we propose a method to determine overlap cutoff levels on a per-case scenario, based on collected CCS data, and show that it can be applied to the characterization of the assembly topology of symmetrical homo-multimers. [Figure not available: see fulltext.

Calculus super review

CERN Document Server

2012-01-01

Get all you need to know with Super Reviews! Each Super Review is packed with in-depth, student-friendly topic reviews that fully explain everything about the subject. The Calculus I Super Review includes a review of functions, limits, basic derivatives, the definite integral, combinations, and permutations. Take the Super Review quizzes to see how much you've learned - and where you need more study. Makes an excellent study aid and textbook companion. Great for self-study!DETAILS- From cover to cover, each in-depth topic review is easy-to-follow and easy-to-grasp - Perfect when preparing for

Estimasi Kanal Akustik Bawah Air Untuk Perairan Dangkal Menggunakan Metode Least Square (LS dan Minimum Mean Square Error (MMSE

Directory of Open Access Journals (Sweden)

Mardawia M Panrereng

2015-06-01

Full Text Available Dalam beberapa tahun terakhir, sistem komunikasi akustik bawah air banyak dikembangkan oleh beberapa peneliti. Besarnya tantangan yang dihadapi membuat para peneliti semakin tertarik untuk mengembangkan penelitian dibidang ini. Kanal bawah air merupakan media komunikasi yang sulit karena adanya attenuasi, absorption, dan multipath yang disebabkan oleh gerakan gelombang air setiap saat. Untuk perairan dangkal, multipath disebabkan adanya pantulan dari permukaan dan dasar laut. Kebutuhan pengiriman data cepat dengan bandwidth terbatas menjadikan Ortogonal Frequency Division Multiplexing (OFDM sebagai solusi untuk komunikasi transmisi tinggi dengan modulasi menggunakan Binary Phase-Shift Keying (BPSK. Estimasi kanal bertujuan untuk mengetahui karakteristik respon impuls kanal propagasi dengan mengirimkan pilot simbol. Pada estimasi kanal menggunakan metode Least Square (LS nilai Mean Square Error (MSE yang diperoleh cenderung lebih besar dari metode estimasi kanal menggunakan metode Minimum Mean Square (MMSE. Hasil kinerja estimasi kanal berdasarkan perhitungan Bit Error Rate (BER untuk estimasi kanal menggunakan metode LS dan metode MMSE tidak menunjukkan perbedaan yang signifikan yaitu berselisih satu SNR untuk setiap metode estimasi kanal yang digunakan.

Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

KAUST Repository

Toye, Habib

2017-05-26

We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

Supermanifolds and super Riemann surfaces

International Nuclear Information System (INIS)

Rabin, J.M.

1986-09-01

The theory of super Riemann surfaces is rigorously developed using Rogers' theory of supermanifolds. The global structures of super Teichmueller space and super moduli space are determined. The super modular group is shown to be precisely the ordinary modular group. Super moduli space is shown to be the gauge-fixing slice for the fermionic string path integral

Mini-Mental State Examination (MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in community and primary care populations.

Science.gov (United States)

Creavin, Sam T; Wisniewski, Susanna; Noel-Storr, Anna H; Trevelyan, Clare M; Hampton, Thomas; Rayment, Dane; Thom, Victoria M; Nash, Kirsty J E; Elhamoui, Hosam; Milligan, Rowena; Patel, Anish S; Tsivos, Demitra V; Wing, Tracey; Phillips, Emma; Kellman, Sophie M; Shackleton, Hannah L; Singleton, Georgina F; Neale, Bethany E; Watton, Martha E; Cullum, Sarah

2016-01-13

The Mini Mental State Examination (MMSE) is a cognitive test that is commonly used as part of the evaluation for possible dementia. To determine the diagnostic accuracy of the Mini-Mental State Examination (MMSE) at various cut points for dementia in people aged 65 years and over in community and primary care settings who had not undergone prior testing for dementia. We searched the specialised register of the Cochrane Dementia and Cognitive Improvement Group, MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), LILACS (BIREME), ALOIS, BIOSIS previews (Thomson Reuters Web of Science), and Web of Science Core Collection, including the Science Citation Index and the Conference Proceedings Citation Index (Thomson Reuters Web of Science). We also searched specialised sources of diagnostic test accuracy studies and reviews: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). We attempted to locate possibly relevant but unpublished data by contacting researchers in this field. We first performed the searches in November 2012 and then fully updated them in May 2014. We did not apply any language or date restrictions to the electronic searches, and we did not use any methodological filters as a method to restrict the search overall. We included studies that compared the 11-item (maximum score 30) MMSE test (at any cut point) in people who had not undergone prior testing versus a commonly accepted clinical reference standard for all-cause dementia and subtypes (Alzheimer disease dementia, Lewy body dementia, vascular dementia, frontotemporal dementia). Clinical diagnosis included all-cause (unspecified) dementia, as defined by any version of the Diagnostic and Statistical Manual of Mental Disorders (DSM); International Classification of

Deterministic phase measurements exhibiting super-sensitivity and super-resolution

DEFF Research Database (Denmark)

Schäfermeier, Clemens; Ježek, Miroslav; Madsen, Lars S.

2018-01-01

Phase super-sensitivity is obtained when the sensitivity in a phase measurement goes beyond the quantum shot noise limit, whereas super-resolution is obtained when the interference fringes in an interferometer are narrower than half the input wavelength. Here we show experimentally that these two...

Localization of atomic ensembles via superfluorescence

International Nuclear Information System (INIS)

Macovei, Mihai; Evers, Joerg; Keitel, Christoph H.; Zubairy, M. Suhail

2007-01-01

The subwavelength localization of an ensemble of atoms concentrated to a small volume in space is investigated. The localization relies on the interaction of the ensemble with a standing wave laser field. The light scattered in the interaction of the standing wave field and the atom ensemble depends on the position of the ensemble relative to the standing wave nodes. This relation can be described by a fluorescence intensity profile, which depends on the standing wave field parameters and the ensemble properties and which is modified due to collective effects in the ensemble of nearby particles. We demonstrate that the intensity profile can be tailored to suit different localization setups. Finally, we apply these results to two localization schemes. First, we show how to localize an ensemble fixed at a certain position in the standing wave field. Second, we discuss localization of an ensemble passing through the standing wave field

Ensembl 2017

OpenAIRE

Aken, Bronwen L.; Achuthan, Premanand; Akanni, Wasiu; Amode, M. Ridwan; Bernsdorff, Friederike; Bhai, Jyothish; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Gil, Laurent; Gir?n, Carlos Garc?a; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.

2016-01-01

Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access ...

Ensemble Sampling

OpenAIRE

Lu, Xiuyuan; Van Roy, Benjamin

2017-01-01

Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applica...

EnsembleGASVR: A novel ensemble method for classifying missense single nucleotide polymorphisms

KAUST Repository

Rapakoulia, Trisevgeni; Theofilatos, Konstantinos A.; Kleftogiannis, Dimitrios A.; Likothanasis, Spiridon D.; Tsakalidis, Athanasios K.; Mavroudi, Seferina P.

2014-01-01

do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel

EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data

Energy Technology Data Exchange (ETDEWEB)

Shu, Qingya; Guo, Hanqi; Che, Limei; Yuan, Xiaoru; Liu, Junfeng; Liang, Jie

2016-04-19

We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based on ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.

Impacts of calibration strategies and ensemble methods on ensemble flood forecasting over Lanjiang basin, Southeast China

Science.gov (United States)

Liu, Li; Xu, Yue-Ping

2017-04-01

Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.

The canonical ensemble redefined - 1: Formalism

International Nuclear Information System (INIS)

Venkataraman, R.

1984-12-01

For studying the thermodynamic properties of systems we propose an ensemble that lies in between the familiar canonical and microcanonical ensembles. We point out the transition from the canonical to microcanonical ensemble and prove from a comparative study that all these ensembles do not yield the same results even in the thermodynamic limit. An investigation of the coupling between two or more systems with these ensembles suggests that the state of thermodynamical equilibrium is a special case of statistical equilibrium. (author)

Theory of super LIE groups

International Nuclear Information System (INIS)

Prakash, M.

1985-01-01

The theory of supergravity has attracted increasing attention in the recent years as a unified theory of elementary particle interactions. The superspace formulation of the theory is highly suggestive of an underlying geometrical structure of superspace. It also incorporates the beautifully geometrical general theory of relativity. It leads us to believe that a better understanding of its geometry would result in a better understanding of the theory itself, and furthermore, that the geometry of superspace would also have physical consequences. As a first step towards that goal, we develop here a theory of super Lie groups. These are groups that have the same relation to a super Lie algebra as Lie groups have to a Lie algebra. More precisely, a super Lie group is a super-manifold and a group such that the group operations are super-analytic. The super Lie algebra of a super Lie group is related to the local properties of the group near the identity. This work develops the algebraic and super-analytical tools necessary for our theory, including proofs of a set of existence and uniqueness theorems for a class of super-differential equations

Algebra & trigonometry super review

CERN Document Server

2012-01-01

Get all you need to know with Super Reviews! Each Super Review is packed with in-depth, student-friendly topic reviews that fully explain everything about the subject. The Algebra and Trigonometry Super Review includes sets and set operations, number systems and fundamental algebraic laws and operations, exponents and radicals, polynomials and rational expressions, equations, linear equations and systems of linear equations, inequalities, relations and functions, quadratic equations, equations of higher order, ratios, proportions, and variations. Take the Super Review quizzes to see how much y

Melting in super-earths.

Science.gov (United States)

Stixrude, Lars

2014-04-28

We examine the possible extent of melting in rock-iron super-earths, focusing on those in the habitable zone. We consider the energetics of accretion and core formation, the timescale of cooling and its dependence on viscosity and partial melting, thermal regulation via the temperature dependence of viscosity, and the melting curves of rock and iron components at the ultra-high pressures characteristic of super-earths. We find that the efficiency of kinetic energy deposition during accretion increases with planetary mass; considering the likely role of giant impacts and core formation, we find that super-earths probably complete their accretionary phase in an entirely molten state. Considerations of thermal regulation lead us to propose model temperature profiles of super-earths that are controlled by silicate melting. We estimate melting curves of iron and rock components up to the extreme pressures characteristic of super-earth interiors based on existing experimental and ab initio results and scaling laws. We construct super-earth thermal models by solving the equations of mass conservation and hydrostatic equilibrium, together with equations of state of rock and iron components. We set the potential temperature at the core-mantle boundary and at the surface to the local silicate melting temperature. We find that ancient (∼4 Gyr) super-earths may be partially molten at the top and bottom of their mantles, and that mantle convection is sufficiently vigorous to sustain dynamo action over the whole range of super-earth masses.

Ensemble methods for handwritten digit recognition

DEFF Research Database (Denmark)

Hansen, Lars Kai; Liisberg, Christian; Salamon, P.

1992-01-01

Neural network ensembles are applied to handwritten digit recognition. The individual networks of the ensemble are combinations of sparse look-up tables (LUTs) with random receptive fields. It is shown that the consensus of a group of networks outperforms the best individual of the ensemble....... It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...... by optimizing the receptive fields. It is concluded that it is possible to improve performance significantly by introducing moderate-size ensembles; in particular, a 20-25% improvement has been found. The ensemble random LUTs, when trained on a medium-size database, reach a performance (without rejects) of 94...

Eigenfunction statistics of Wishart Brownian ensembles

International Nuclear Information System (INIS)

Shukla, Pragya

2017-01-01

We theoretically analyze the eigenfunction fluctuation measures for a Hermitian ensemble which appears as an intermediate state of the perturbation of a stationary ensemble by another stationary ensemble of Wishart (Laguerre) type. Similar to the perturbation by a Gaussian stationary ensemble, the measures undergo a diffusive dynamics in terms of the perturbation parameter but the energy-dependence of the fluctuations is different in the two cases. This may have important consequences for the eigenfunction dynamics as well as phase transition studies in many areas of complexity where Brownian ensembles appear. (paper)

SuperB Progress Report: Detector

Energy Technology Data Exchange (ETDEWEB)

Grauges, E.; /Barcelona U., ECM; Donvito, G.; Spinoso, V.; /INFN, Bari /Bari U.; Manghisoni, M.; Re, V.; Traversi, G.; /INFN, Pavia /Bergamo U., Ingengneria Dept.; Eigen, G.; Fehlker, D.; Helleve, L.; /Bergen U.; Carbone, A.; Di Sipio, R.; Gabrielli, A.; Galli, D.; Giorgi, F.; Marconi, U.; Perazzini, S.; Sbarra, C.; Vagnoni, V.; Valentinetti, S.; Villa, M.; Zoccoli, A.; /INFN, Bologna /Bologna U. /Caltech /Carleton U. /Cincinnati U. /INFN, CNAF /INFN, Ferrara /Ferrara U. /UC, Irvine /Taras Shevchenko U. /Orsay, LAL /LBL, Berkeley /UC, Berkeley /Frascati /INFN, Legnaro /Orsay, IPN /Maryland U. /McGill U. /INFN, Milan /Milan U. /INFN, Naples /Naples U. /Novosibirsk, IYF /INFN, Padua /Padua U. /INFN, Pavia /Pavia U. /INFN, Perugia /Perugia U. /INFN, Perugia /Caltech /INFN, Pisa /Pisa U. /Pisa, Scuola Normale Superiore /PNL, Richland /Queen Mary, U. of London /Rutherford /INFN, Rome /Rome U. /INFN, Rome2 /Rome U.,Tor Vergata /INFN, Rome3 /Rome III U. /SLAC /Tel Aviv U. /INFN, Turin /Turin U. /INFN, Padua /Trento U. /INFN, Trieste /Trieste U. /TRIUMF /British Columbia U. /Montreal U. /Victoria U.

2012-02-14

This report describes the present status of the detector design for SuperB. It is one of four separate progress reports that, taken collectively, describe progress made on the SuperB Project since the publication of the SuperB Conceptual Design Report in 2007 and the Proceedings of SuperB Workshop VI in Valencia in 2008.

SuperB Progress Report: Detector

International Nuclear Information System (INIS)

Grauges, E.; Donvito, G.; Spinoso, V.; Manghisoni, M.; Re, V.; Traversi, G.; Eigen, G.; Fehlker, D.; Helleve, L.; Cheng, C.; Chivukula, A.; Doll, D.; Echenard, B.; Hitlin, D.; Ongmongkolkul, P.; Porter, F.; Rakitin, A.; Thomas, M.; Zhu, R.; Tatishvili, G.; Andreassen, R.; Fabby, C.; Meadows, B.; Simpson, A.; Sokoloff, M.; Tomko, K.; Fella, A.; Andreotti, M.; Baldini, W.; Calabrese, R.; Carassiti, V.; Cibinetto, G.; Cotta Ramusino, A.; Gianoli, A.; Luppi, E.; Munerato, M.; Santoro, V.; Tomassetti, L.; Stoker, D.; Bezshyyko, O.; Dolinska, G.; Arnaud, N.; Beigbeder, C.; Bogard, F.; Breton, D.; Burmistrov, L.; Charlet, D.; Maalmi, J.; Perez Perez, L.; Puill, V.; Stocchi, A.; Tocut, V.; Wallon, S.; Wormser, G.; Brown, D.

2012-01-01

This report describes the present status of the detector design for SuperB. It is one of four separate progress reports that, taken collectively, describe progress made on the SuperB Project since the publication of the SuperB Conceptual Design Report in 2007 and the Proceedings of SuperB Workshop VI in Valencia in 2008.

SuperB Progress Reports Accelerator

CERN Document Server

Biagini, Maria Enrica; Boscolo, M; Buonomo, B; Demma, T; Drago, A; Esposito, M; Guiducci, S; Mazzitelli, G; Pellegrino, L; Preger, M A; Raimondi, P; Ricci, R; Rotundo, U; Sanelli, C; Serio, M; Stella, A; Tomassini, S; Zobov, M; Bertsche, K; Brachman, A; Cai, Y; Chao, A; Chesnut, R; Donald, M.H; Field, C; Fisher, A; Kharakh, D; Krasnykh, A; Moffeit, K; Nosochkov, Y; Pivi, M; Seeman, J; Sullivan, M.K; Weathersby, S; Weidemann, A; Weisend, J; Wienands, U; Wittmer, W; Woods, M; Yocky, G; Bogomiagkov, A; Koop, I; Levichev, E; Nikitin, S; Okunev, I; Piminov, P; Sinyatkin, S; Shatilov, D; Vobly, P; Bosi, F; Liuzzo, S; Paoloni, E; Bonis, J; Chehab, R; Le Meur, G; Lepercq, P; Letellier-Cohen, F; Mercier, B; Poirier, F; Prevost, C; Rimbault, C; Touze, F; Variola, A; Bolzon, B; Brunetti, L; Jeremie, A; Baylac, M; Bourrion, O; De Conto, J M; Gomez, Y; Meot, F; Monseu, N; Tourres, D; Vescovi, C; Chanci, A; Napoly, O; Barber, D P; Bettoni, S; Quatraro, D

2010-01-01

This report details the present status of the Accelerator design for the SuperB Project. It is one of four separate progress reports that, taken collectively, describe progress made on the SuperB Project since the publication of the SuperB Conceptual Design Report in 2007 and the Proceedings of SuperB Workshop VI in Valencia in 2008.

Measuring social interaction in music ensembles.

Science.gov (United States)

Volpe, Gualtiero; D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano

2016-05-05

Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances. © 2016 The Author(s).

Deformations of super Riemann surfaces

International Nuclear Information System (INIS)

Ninnemann, H.

1992-01-01

Two different approaches to (Konstant-Leites-) super Riemann surfaces are investigated. In the local approach, i.e. glueing open superdomains by superconformal transition functions, deformations of the superconformal structure are discussed. On the other hand, the representation of compact super Riemann surfaces of genus greater than one as a fundamental domain in the Poincare upper half-plane provides a simple description of super Laplace operators acting on automorphic p-forms. Considering purely odd deformations of super Riemann surfaces, the number of linear independent holomorphic sections of arbitrary holomorphic line bundles will be shown to be independent of the odd moduli, leading to a simple proof of the Riemann-Roch theorem for compact super Riemann surfaces. As a further consequence, the explicit connections between determinants of super Laplacians and Selberg's super zeta functions can be determined, allowing to calculate at least the 2-loop contribution to the fermionic string partition function. (orig.)

Deformations of super Riemann surfaces

Energy Technology Data Exchange (ETDEWEB)

Ninnemann, H [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

1992-11-01

Two different approaches to (Konstant-Leites-) super Riemann surfaces are investigated. In the local approach, i.e. glueing open superdomains by superconformal transition functions, deformations of the superconformal structure are discussed. On the other hand, the representation of compact super Riemann surfaces of genus greater than one as a fundamental domain in the Poincare upper half-plane provides a simple description of super Laplace operators acting on automorphic p-forms. Considering purely odd deformations of super Riemann surfaces, the number of linear independent holomorphic sections of arbitrary holomorphic line bundles will be shown to be independent of the odd moduli, leading to a simple proof of the Riemann-Roch theorem for compact super Riemann surfaces. As a further consequence, the explicit connections between determinants of super Laplacians and Selberg's super zeta functions can be determined, allowing to calculate at least the 2-loop contribution to the fermionic string partition function. (orig.).

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

Science.gov (United States)

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Joys of Community Ensemble Playing: The Case of the Happy Roll Elastic Ensemble in Taiwan

Science.gov (United States)

Hsieh, Yuan-Mei; Kao, Kai-Chi

2012-01-01

The Happy Roll Elastic Ensemble (HREE) is a community music ensemble supported by Tainan Culture Centre in Taiwan. With enjoyment and friendship as its primary goals, it aims to facilitate the joys of ensemble playing and the spirit of social networking. This article highlights the key aspects of HREE's development in its first two years…

Ensemble Data Mining Methods

Science.gov (United States)

Oza, Nikunj C.

2004-01-01

Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

Science.gov (United States)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

Super periodic potential

Science.gov (United States)

Hasan, Mohammd; Mandal, Bhabani Prasad

2018-04-01

In this paper we introduce the concept of super periodic potential (SPP) of arbitrary order n, n ∈I+, in one dimension. General theory of wave propagation through SPP of order n is presented and the reflection and transmission coefficients are derived in their closed analytical form by transfer matrix formulation. We present scattering features of super periodic rectangular potential and super periodic delta potential as special cases of SPP. It is found that the symmetric self-similarity is the special case of super periodicity. Thus by identifying a symmetric fractal potential as special cases of SPP, one can obtain the tunnelling amplitude for a particle from such fractal potential. By using the formalism of SPP we obtain the close form expression of tunnelling amplitude of a particle for general Cantor and Smith-Volterra-Cantor potentials.

Ensembl 2002: accommodating comparative genomics.

Science.gov (United States)

Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

2003-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

The classicality and quantumness of a quantum ensemble

International Nuclear Information System (INIS)

Zhu Xuanmin; Pang Shengshi; Wu Shengjun; Liu Quanhui

2011-01-01

In this Letter, we investigate the classicality and quantumness of a quantum ensemble. We define a quantity called ensemble classicality based on classical cloning strategy (ECCC) to characterize how classical a quantum ensemble is. An ensemble of commuting states has a unit ECCC, while a general ensemble can have a ECCC less than 1. We also study how quantum an ensemble is by defining a related quantity called quantumness. We find that the classicality of an ensemble is closely related to how perfectly the ensemble can be cloned, and that the quantumness of the ensemble used in a quantum key distribution (QKD) protocol is exactly the attainable lower bound of the error rate in the sifted key. - Highlights: → A quantity is defined to characterize how classical a quantum ensemble is. → The classicality of an ensemble is closely related to the cloning performance. → Another quantity is also defined to investigate how quantum an ensemble is. → This quantity gives the lower bound of the error rate in a QKD protocol.

Frames in super Hilbert modules

Directory of Open Access Journals (Sweden)

Mehdi Rashidi-Kouchi

2018-01-01

Full Text Available In this paper, we define super Hilbert module and investigate frames in this space. Super Hilbert modules are  generalization of super Hilbert spaces in Hilbert C*-module setting. Also, we define frames in a super Hilbert module and characterize them by using of the concept of g-frames in a Hilbert C*-module. Finally, disjoint frames in Hilbert C*-modules are introduced and investigated.

The semantic similarity ensemble

Directory of Open Access Journals (Sweden)

Andrea Ballatore

2013-12-01

Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

Quantum ensembles of quantum classifiers.

Science.gov (United States)

Schuld, Maria; Petruccione, Francesco

2018-02-09

Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

Musical ensembles in Ancient Mesapotamia

NARCIS (Netherlands)

Krispijn, T.J.H.; Dumbrill, R.; Finkel, I.

2010-01-01

Identification of musical instruments from ancient Mesopotamia by comparing musical ensembles attested in Sumerian and Akkadian texts with depicted ensembles. Lexicographical contributions to the Sumerian and Akkadian lexicon.

PSO-Ensemble Demo Application

DEFF Research Database (Denmark)

2004-01-01

Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output...

Multilevel ensemble Kalman filter

KAUST Repository

Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

2016-01-01

This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

Multilevel ensemble Kalman filter

KAUST Repository

Chernov, Alexey

2016-01-06

This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

(Super Variable Costing-Throughput Costing)

OpenAIRE

Çakıcı, Cemal

2006-01-01

(Super Variable Costing-Throughput Costing) The aim of this study is to explain the super-variable costing method which is a new subject in cost and management accounting and to show it’s working practicly.Shortly, super-variable costing can be defined as a costing method which is use only direct material costs in calculate of product costs and treats all costs except these (direct labor and overhead) as periad costs or operating costs.By using super-variable costing method, product costs ar...

Multi-Model Ensemble Wake Vortex Prediction

Science.gov (United States)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

Institute of Scientific and Technical Information of China (English)

Zhaoxia PU; Joshua HACKER

2009-01-01

This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

Monthly ENSO Forecast Skill and Lagged Ensemble Size

Science.gov (United States)

Trenary, L.; DelSole, T.; Tippett, M. K.; Pegion, K.

2018-04-01

The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real-time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real-time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8-10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities.

Electrically tuned super-capacitors

OpenAIRE

Chowdhury, Tazima S.; Grebel, Haim

2015-01-01

Fast charging and discharging of large amounts of electrical energy make super-capacitors ideal for short-term energy storage [1-5]. In its simplest form, the super-capacitor is an electrolytic capacitor made of an anode and a cathode immersed in an electrolyte. As for an ordinary capacitor, minimizing the charge separation distance and increasing the electrode area increase capacitance. In super-capacitors, charge separation is of nano-meter scale at each of the electrode interface (the Helm...

Example-Based Super-Resolution Fluorescence Microscopy.

Science.gov (United States)

Jia, Shu; Han, Boran; Kutz, J Nathan

2018-04-23

Capturing biological dynamics with high spatiotemporal resolution demands the advancement in imaging technologies. Super-resolution fluorescence microscopy offers spatial resolution surpassing the diffraction limit to resolve near-molecular-level details. While various strategies have been reported to improve the temporal resolution of super-resolution imaging, all super-resolution techniques are still fundamentally limited by the trade-off associated with the longer image acquisition time that is needed to achieve higher spatial information. Here, we demonstrated an example-based, computational method that aims to obtain super-resolution images using conventional imaging without increasing the imaging time. With a low-resolution image input, the method provides an estimate of its super-resolution image based on an example database that contains super- and low-resolution image pairs of biological structures of interest. The computational imaging of cellular microtubules agrees approximately with the experimental super-resolution STORM results. This new approach may offer potential improvements in temporal resolution for experimental super-resolution fluorescence microscopy and provide a new path for large-data aided biomedical imaging.

Handbook of Super 8 Production.

Science.gov (United States)

Telzer, Ronnie, Ed.

This handbook is designed for anyone interested in producing super 8 films at any level of complexity and cost. Separate chapters present detailed discussions of the following topics: super 8 production systems and super 8 shooting and editing systems; budgeting; cinematography and sound recording; preparing to edit; editing; mixing sound tracks;…

The super-resolution debate

Science.gov (United States)

Won, Rachel

2018-05-01

In the quest for nanoscopy with super-resolution, consensus from the imaging community is that super-resolution is not always needed and that scientists should choose an imaging technique based on their specific application.

SuperMAG: Present and Future Capabilities

Science.gov (United States)

Hsieh, S. W.; Gjerloev, J. W.; Barnes, R. J.

2009-12-01

SuperMAG is a global collaboration that provides ground magnetic field perturbations from a long list of stations in the same coordinate system, identical time resolution and with a common baseline removal approach. This unique high quality dataset provides a continuous and nearly global monitoring of the ground magnetic field perturbation. Currently, only archived data are available on the website and hence it targets basic research without any operational capabilities. The existing SuperMAG software can be easily adapted to ingest real-time or near real-time data and provide a now-casting capability. The SuperDARN program has a long history of providing near real-time maps of the northern hemisphere electrostatic potential and as both SuperMAG and SuperDARN share common software it is relatively easy to adapt these maps for global magnetic perturbations. Magnetometer measurements would be assimilated by the SuperMAG server using a variety of techniques, either by downloading data at regular intervals from remote servers or by real-time streaming connections. The existing SuperMAG analysis software would then process these measurements to provide the final calibrated data set using the SuperMAG coordinate system. The existing plotting software would then be used to produce regularly updated global plots. The talk will focus on current SuperMAG capabilities illustrating the potential for now-casting and eventually forecasting.

A Theoretical Analysis of Why Hybrid Ensembles Work

Directory of Open Access Journals (Sweden)

Kuo-Wei Hsu

2017-01-01

Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

Super-quasi-conformal transformation and Schiffer variation on super-Riemann surface

International Nuclear Information System (INIS)

Takahasi, Wataru

1990-01-01

A set of equations which characterizes the super-Teichmueller deformations is proposed. It is a supersymmetric extension of the Beltrami equation. Relations between the set of equations and the Schiffer variations with the KN bases are discussed. This application of the KN bases shows the powerfulness of the KN theory in the study of super-Riemann surfaces. (author)

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

Science.gov (United States)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

An "Ensemble Approach" to Modernizing Extreme Precipitation Estimation for Dam Safety Decision-Making

Science.gov (United States)

Cifelli, R.; Mahoney, K. M.; Webb, R. S.; McCormick, B.

2017-12-01

To ensure structural and operational safety of dams and other water management infrastructure, water resources managers and engineers require information about the potential for heavy precipitation. The methods and data used to estimate extreme rainfall amounts for managing risk are based on 40-year-old science and in need of improvement. The need to evaluate new approaches based on the best science available has led the states of Colorado and New Mexico to engage a body of scientists and engineers in an innovative "ensemble approach" to updating extreme precipitation estimates. NOAA is at the forefront of one of three technical approaches that make up the "ensemble study"; the three approaches are conducted concurrently and in collaboration with each other. One approach is the conventional deterministic, "storm-based" method, another is a risk-based regional precipitation frequency estimation tool, and the third is an experimental approach utilizing NOAA's state-of-the-art High Resolution Rapid Refresh (HRRR) physically-based dynamical weather prediction model. The goal of the overall project is to use the individual strengths of these different methods to define an updated and broadly acceptable state of the practice for evaluation and design of dam spillways. This talk will highlight the NOAA research and NOAA's role in the overarching goal to better understand and characterizing extreme precipitation estimation uncertainty. The research led by NOAA explores a novel high-resolution dataset and post-processing techniques using a super-ensemble of hourly forecasts from the HRRR model. We also investigate how this rich dataset may be combined with statistical methods to optimally cast the data in probabilistic frameworks. NOAA expertise in the physical processes that drive extreme precipitation is also employed to develop careful testing and improved understanding of the limitations of older estimation methods and assumptions. The process of decision making in the

Super families

International Nuclear Information System (INIS)

Amato, N.; Maldonado, R.H.C.

1989-01-01

The study on phenomena in the super high energy region, Σ E j > 1000 TeV revealed events that present a big dark spot in central region with high concentration of energy and particles, called halo. Six super families with halo were analysed by Brazil-Japan Cooperation of Cosmic Rays. For each family the lateral distribution of energy density was constructed and R c Σ E (R c ) was estimated. For studying primary composition, the energy correlation with particles released separately in hadrons and gamma rays was analysed. (M.C.K.)

New concept of statistical ensembles

International Nuclear Information System (INIS)

Gorenstein, M.I.

2009-01-01

An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution is introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.

A class of energy-based ensembles in Tsallis statistics

International Nuclear Information System (INIS)

Chandrashekar, R; Naina Mohammed, S S

2011-01-01

A comprehensive investigation is carried out on the class of energy-based ensembles. The eight ensembles are divided into two main classes. In the isothermal class of ensembles the individual members are at the same temperature. A unified framework is evolved to describe the four isothermal ensembles using the currently accepted third constraint formalism. The isothermal–isobaric, grand canonical and generalized ensembles are illustrated through a study of the classical nonrelativistic and extreme relativistic ideal gas models. An exact calculation is possible only in the case of the isothermal–isobaric ensemble. The study of the ideal gas models in the grand canonical and the generalized ensembles has been carried out using a perturbative procedure with the nonextensivity parameter (1 − q) as the expansion parameter. Though all the thermodynamic quantities have been computed up to a particular order in (1 − q) the procedure can be extended up to any arbitrary order in the expansion parameter. In the adiabatic class of ensembles the individual members of the ensemble have the same value of the heat function and a unified formulation to described all four ensembles is given. The nonrelativistic and the extreme relativistic ideal gases are studied in the isoenthalpic–isobaric ensemble, the adiabatic ensemble with number fluctuations and the adiabatic ensemble with number and particle fluctuations

The Ensembl genome database project.

Science.gov (United States)

Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

2002-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

Advanced Atmospheric Ensemble Modeling Techniques

Energy Technology Data Exchange (ETDEWEB)

Buckley, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Chiswell, S. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Kurzeja, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Maze, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Viner, B. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Werth, D. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2017-09-29

Ensemble modeling (EM), the creation of multiple atmospheric simulations for a given time period, has become an essential tool for characterizing uncertainties in model predictions. We explore two novel ensemble modeling techniques: (1) perturbation of model parameters (Adaptive Programming, AP), and (2) data assimilation (Ensemble Kalman Filter, EnKF). The current research is an extension to work from last year and examines transport on a small spatial scale (<100 km) in complex terrain, for more rigorous testing of the ensemble technique. Two different release cases were studied, a coastal release (SF6) and an inland release (Freon) which consisted of two release times. Observations of tracer concentration and meteorology are used to judge the ensemble results. In addition, adaptive grid techniques have been developed to reduce required computing resources for transport calculations. Using a 20- member ensemble, the standard approach generated downwind transport that was quantitatively good for both releases; however, the EnKF method produced additional improvement for the coastal release where the spatial and temporal differences due to interior valley heating lead to the inland movement of the plume. The AP technique showed improvements for both release cases, with more improvement shown in the inland release. This research demonstrated that transport accuracy can be improved when models are adapted to a particular location/time or when important local data is assimilated into the simulation and enhances SRNL’s capability in atmospheric transport modeling in support of its current customer base and local site missions, as well as our ability to attract new customers within the intelligence community.

Layered Ensemble Architecture for Time Series Forecasting.

Science.gov (United States)

Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

2016-01-01

Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

Rotationally invariant family of Levy-like random matrix ensembles

International Nuclear Information System (INIS)

Choi, Jinmyung; Muttalib, K A

2009-01-01

We introduce a family of rotationally invariant random matrix ensembles characterized by a parameter λ. While λ = 1 corresponds to well-known critical ensembles, we show that λ ≠ 1 describes 'Levy-like' ensembles, characterized by power-law eigenvalue densities. For λ > 1 the density is bounded, as in Gaussian ensembles, but λ < 1 describes ensembles characterized by densities with long tails. In particular, the model allows us to evaluate, in terms of a novel family of orthogonal polynomials, the eigenvalue correlations for Levy-like ensembles. These correlations differ qualitatively from those in either the Gaussian or the critical ensembles. (fast track communication)

SuperAGILE Services at ASDC

International Nuclear Information System (INIS)

Preger, B.; Verrecchia, F.; Pittori, C.; Antonelli, L. A.; Giommi, P.; Lazzarotto, F.; Evangelista, Y.

2008-01-01

The Italian Space Agency Science Data Center (ASDC) is a facility with several responsibilities including support to all the ASI scientific missions as for management and archival of the data, acting as the interface between ASI and the scientific community and providing on-line access to the data hosted. In this poster we describe the services that ASDC provides for SuperAGILE, in particular the ASDC public web pages devoted to the dissemination of SuperAGILE scientific results. SuperAGILE is the X-Ray imager onboard the AGILE mission, and provides the scientific community with orbit-by-orbit information on the observed sources. Crucial source information including position and flux in chosen energy bands will be reported in the SuperAGILE public web page at ASDC. Given their particular interest, another web page will be dedicated entirely to GRBs and other transients, where new event alerts will be notified and where users will find all the available informations on the GRBs detected by SuperAGILE

The Super-Kamiokande detector

International Nuclear Information System (INIS)

Fukuda, S.; Fukuda, Y.; Hayakawa, T.; Ichihara, E.; Ishitsuka, M.; Itow, Y.; Kajita, T.; Kameda, J.; Kaneyuki, K.; Kasuga, S.; Kobayashi, K.; Kobayashi, Y.; Koshio, Y.; Miura, M.; Moriyama, S.; Nakahata, M.; Nakayama, S.; Namba, T.; Obayashi, Y.; Okada, A.; Oketa, M.; Okumura, K.; Oyabu, T.; Sakurai, N.; Shiozawa, M.; Suzuki, Y.; Takeuchi, Y.; Toshito, T.; Totsuka, Y.; Yamada, S.; Desai, S.; Earl, M.; Hong, J.T.; Kearns, E.; Masuzawa, M.; Messier, M.D.; Stone, J.L.; Sulak, L.R.; Walter, C.W.; Wang, W.; Scholberg, K.; Barszczak, T.; Casper, D.; Liu, D.W.; Gajewski, W.; Halverson, P.G.; Hsu, J.; Kropp, W.R.; Mine, S.; Price, L.R.; Reines, F.; Smy, M.; Sobel, H.W.; Vagins, M.R.; Ganezer, K.S.; Keig, W.E.; Ellsworth, R.W.; Tasaka, S.; Flanagan, J.W.; Kibayashi, A.; Learned, J.G.; Matsuno, S.; Stenger, V.J.; Hayato, Y.; Ishii, T.; Ichikawa, A.; Kanzaki, J.; Kobayashi, T.; Maruyama, T.; Nakamura, K.; Oyama, Y.; Sakai, A.; Sakuda, M.; Sasaki, O.; Echigo, S.; Iwashita, T.; Kohama, M.; Suzuki, A.T.; Hasegawa, M.; Inagaki, T.; Kato, I.; Maesaka, H.; Nakaya, T.; Nishikawa, K.; Yamamoto, S.; Haines, T.J.; Kim, B.K.; Sanford, R.; Svoboda, R.; Blaufuss, E.; Chen, M.L.; Conner, Z.; Goodman, J.A.; Guillian, E.; Sullivan, G.W.; Turcan, D.; Habig, A.; Ackerman, M.; Goebel, F.; Hill, J.; Jung, C.K.; Kato, T.; Kerr, D.; Malek, M.; Martens, K.; Mauger, C.; McGrew, C.; Sharkey, E.; Viren, B.; Yanagisawa, C.; Doki, W.; Inaba, S.; Ito, K.; Kirisawa, M.; Kitaguchi, M.; Mitsuda, C.; Miyano, K.; Saji, C.; Takahata, M.; Takahashi, M.; Higuchi, K.; Kajiyama, Y.; Kusano, A.; Nagashima, Y.; Nitta, K.; Takita, M.; Yamaguchi, T.; Yoshida, M.; Kim, H.I.; Kim, S.B.; Yoo, J.; Okazawa, H.; Etoh, M.; Fujita, K.; Gando, Y.; Hasegawa, A.; Hasegawa, T.; Hatakeyama, S.; Inoue, K.; Ishihara, K.; Iwamoto, T.; Koga, M.; Nishiyama, I.; Ogawa, H.; Shirai, J.; Suzuki, A.; Takayama, T.; Tsushima, F.; Koshiba, M.; Ichikawa, Y.; Hashimoto, T.; Hatakeyama, Y.; Koike, M.; Horiuchi, T.; Nemoto, M.; Nishijima, K.; Takeda, H.; Fujiyasu, H.; Futagami, T.; Ishino, H.; Kanaya, Y.; Morii, M.; Nishihama, H.; Nishimura, H.; Suzuki, T.; Watanabe, Y.; Kielczewska, D.; Golebiewska, U.; Berns, H.G.; Boyd, S.B.; Doyle, R.A.; George, J.S.; Stachyra, A.L.; Wai, L.L.; Wilkes, R.J.; Young, K.K.; Kobayashi, H.

2003-01-01

Super-Kamiokande is the world's largest water Cherenkov detector, with net mass 50,000 tons. During the period April, 1996 to July, 2001, Super-Kamiokande I collected 1678 live-days of data, observing neutrinos from the Sun, Earth's atmosphere, and the K2K long-baseline neutrino beam with high efficiency. These data provided crucial information for our current understanding of neutrino oscillations, as well as setting stringent limits on nucleon decay. In this paper, we describe the detector in detail, including its site, configuration, data acquisition equipment, online and offline software, and calibration systems which were used during Super-Kamiokande I

Generation of live offspring from vitrified embryos with synthetic polymers SuperCool X-1000 and SuperCool Z-1000.

Science.gov (United States)

Marco-Jimenez, F; Jimenez-Trigos, E; Lavara, R; Vicente, J S

2014-01-01

Ice growth and recrystallisation are considered important factors in determining vitrification outcomes. Synthetic polymers inhibit ice formation during cooling or warming of the vitrification process. The aim of this study was to assess the effect of adding commercially available synthetic polymers SuperCool X-1000 and SuperCool Z-1000 to vitrification media on in vivo development competence of rabbit embryos. Four hundred and thirty morphologically normal embryos recovered at 72 h of gestation were used. The vitrification media contained 20% dimethyl sulphoxide and 20% ethylene glycol, either alone or in combination with 1% of SuperCool X-1000 and 1% SuperCool. Our results show that embryos can be successfully vitrified using SuperCool X-1000 and SuperCool Z-1000 and when embryos are transferred, live offspring can be successfully produced. In conclusion, our results demonstrated that we succeeded for the first time in obtaining live offspring after vitrification of embryos using SuperCool X-1000 and SuperCool Z-1000 polymers.

Further results on super graceful labeling of graphs

Directory of Open Access Journals (Sweden)

Gee-Choon Lau

2016-08-01

Full Text Available Let G=(V(G,E(G be a simple, finite and undirected graph of order p and size q. A bijection f:V(G∪E(G→{k,k+1,k+2,…,k+p+q−1} such that f(uv=|f(u−f(v| for every edge uv∈E(G is said to be a k-super graceful labeling of G. We say G is k-super graceful if it admits a k-super graceful labeling. For k=1, the function f is called a super graceful labeling and a graph is super graceful if it admits a super graceful labeling. In this paper, we study the super gracefulness of complete graph, the disjoint union of certain star graphs, the complete tripartite graphs K(1,1,n, and certain families of trees. We also present four methods of constructing new super graceful graphs. In particular, all trees of order at most 7 are super graceful. We conjecture that all trees are super graceful.

Diversity in random subspacing ensembles

NARCIS (Netherlands)

Tsymbal, A.; Pechenizkiy, M.; Cunningham, P.; Kambayashi, Y.; Mohania, M.K.; Wöß, W.

2004-01-01

Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. It was shown experimentally and theoretically that in order for an ensemble to be effective, it should consist of classifiers having diversity in their predictions. A number of ways are

Squeezing of Collective Excitations in Spin Ensembles

DEFF Research Database (Denmark)

Kraglund Andersen, Christian; Mølmer, Klaus

2012-01-01

We analyse the possibility to create two-mode spin squeezed states of two separate spin ensembles by inverting the spins in one ensemble and allowing spin exchange between the ensembles via a near resonant cavity field. We investigate the dynamics of the system using a combination of numerical an...

Urban runoff forecasting with ensemble weather predictions

DEFF Research Database (Denmark)

Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice.......This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice....

Multilevel ensemble Kalman filtering

KAUST Repository

Hoel, Haakon

2016-01-08

The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

Multilevel ensemble Kalman filtering

KAUST Repository

Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

2016-01-01

The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

Super cool X-1000 and Super cool Z-1000, two ice blockers, and their effect on vitrification/warming of mouse embryos.

Science.gov (United States)

Badrzadeh, H; Najmabadi, S; Paymani, R; Macaso, T; Azadbadi, Z; Ahmady, A

2010-07-01

To evaluate the survival and blastocyst formation rates of mouse embryos after vitrification/thaw process with different ice blocker media. We used X-1000 and Z-1000 separately and mixed using V-Kim, a closed vitrification system. Mouse embryos were vitrified using ethylene glycol based medium supplemented with Super cool X-1000 and/or Super cool Z-1000. Survival rates for the control, Super cool X-1000, Super cool Z-1000, and Super cool X-1000/Z-1000 groups were 74%, 72%, 68%, and 85% respectively, with no significant difference among experimental and control groups; however, a significantly higher survival rate was noticed in the Super cool X-1000/Z-1000 group when compared with the Super cool Z-1000 group. Blastocyst formation rates for the control, Super cool X-1000, Super cool Z-1000, and Super cool X-1000/Z-1000 groups were 71%, 66%, 65%, and 72% respectively. There was no significant difference in this rate among control and experimental groups. In a closed vitrification system, addition of ice blocker Super cool X-1000 to the vitrification solution containing Super cool Z-1000 may improve the embryo survival rate. We recommend combined ice blocker usage to optimize the vitrification outcome. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Superstring field theories on super-flag manifolds: superdiff S1/S1 and superdiff S1/super S1

International Nuclear Information System (INIS)

Zhao Zhiyong; Wu, Ke; Saito, Takesi

1987-01-01

We generalize the geometric approach of Bowick and Rajeev [BR] to superstring field theories. The anomaly is identified with nonvanishing of the Ricci curvature of the super-flag manifold. We explicitly calculate the curvatures of superdiff S 1 /S 1 and superdiff S 1 /superS 1 using super-Toeplitz operator techniques. No regularization is needed in this formalism. The critical dimension D=10 is rediscovered as a result of vanishing curvature of the product bundle over the super-flag manifold. (orig.)

SuperB Progress Report for Physics

Energy Technology Data Exchange (ETDEWEB)

O' Leary, B.; /Aachen, Tech. Hochsch.; Matias, J.; Ramon, M.; /Barcelona, IFAE; Pous, E.; /Barcelona U.; De Fazio, F.; Palano, A.; /INFN, Bari; Eigen, G.; /Bergen U.; Asgeirsson, D.; /British Columbia U.; Cheng, C.H.; Chivukula, A.; Echenard, B.; Hitlin, D.G.; Porter, F.; Rakitin, A.; /Caltech; Heinemeyer, S.; /Cantabria Inst. of Phys.; McElrath, B.; /CERN; Andreassen, R.; Meadows, B.; Sokoloff, M.; /Cincinnati U.; Blanke, M.; /Cornell U., Phys. Dept.; Lesiak, T.; /Cracow, INP /DESY /Zurich, ETH /INFN, Ferrara /Frascati /INFN, Genoa /Glasgow U. /Indiana U. /Mainz U., Inst. Phys. /Karlsruhe, Inst. Technol. /KEK, Tsukuba /LBL, Berkeley /UC, Berkeley /Lisbon, IST /Ljubljana U. /Madrid, Autonoma U. /Maryland U. /MIT /INFN, Milan /McGill U. /Munich, Tech. U. /Notre Dame U. /PNL, Richland /INFN, Padua /Paris U., VI-VII /Orsay, LAL /Orsay, LPT /INFN, Pavia /INFN, Perugia /INFN, Pisa /Queen Mary, U. of London /Regensburg U. /Republica U., Montevideo /Frascati /INFN, Rome /INFN, Rome /INFN, Rome /Rutherford /Sassari U. /Siegen U. /SLAC /Southern Methodist U. /Tel Aviv U. /Tohoku U. /INFN, Turin /INFN, Trieste /Uppsala U. /Valencia U., IFIC /Victoria U. /Wayne State U. /Wisconsin U., Madison

2012-02-14

SuperB is a high luminosity e{sup +}e{sup -} collider that will be able to indirectly probe new physics at energy scales far beyond the reach of any man made accelerator planned or in existence. Just as detailed understanding of the Standard Model of particle physics was developed from stringent constraints imposed by flavour changing processes between quarks, the detailed structure of any new physics is severely constrained by flavour processes. In order to elucidate this structure it is necessary to perform a number of complementary studies of a set of golden channels. With these measurements in hand, the pattern of deviations from the Standard Model behavior can be used as a test of the structure of new physics. If new physics is found at the LHC, then the many golden measurements from SuperB will help decode the subtle nature of the new physics. However if no new particles are found at the LHC, SuperB will be able to search for new physics at energy scales up to 10-100 TeV. In either scenario, flavour physics measurements that can be made at SuperB play a pivotal role in understanding the nature of physics beyond the Standard Model. Examples for using the interplay between measurements to discriminate New Physics models are discussed in this document. SuperB is a Super Flavour Factory, in addition to studying large samples of B{sub u,d,s}, D and {tau} decays, SuperB has a broad physics programme that includes spectroscopy both in terms of the Standard Model and exotica, and precision measurements of sin{sup 2} {theta}{sub W}. In addition to performing CP violation measurements at the {Upsilon}(4S) and {phi}(3770), SuperB will test CPT in these systems, and lepton universality in a number of different processes. The multitude of rare decay measurements possible at SuperB can be used to constrain scenarios of physics beyond the Standard Model. In terms of other precision tests of the Standard Model, this experiment will be able to perform precision over

SuperB Progress Report for Physics

International Nuclear Information System (INIS)

O'Leary, B.; Matias, J.; Ramon, M.

2012-01-01

SuperB is a high luminosity e + e - collider that will be able to indirectly probe new physics at energy scales far beyond the reach of any man made accelerator planned or in existence. Just as detailed understanding of the Standard Model of particle physics was developed from stringent constraints imposed by flavour changing processes between quarks, the detailed structure of any new physics is severely constrained by flavour processes. In order to elucidate this structure it is necessary to perform a number of complementary studies of a set of golden channels. With these measurements in hand, the pattern of deviations from the Standard Model behavior can be used as a test of the structure of new physics. If new physics is found at the LHC, then the many golden measurements from SuperB will help decode the subtle nature of the new physics. However if no new particles are found at the LHC, SuperB will be able to search for new physics at energy scales up to 10-100 TeV. In either scenario, flavour physics measurements that can be made at SuperB play a pivotal role in understanding the nature of physics beyond the Standard Model. Examples for using the interplay between measurements to discriminate New Physics models are discussed in this document. SuperB is a Super Flavour Factory, in addition to studying large samples of B u,d,s , D and τ decays, SuperB has a broad physics programme that includes spectroscopy both in terms of the Standard Model and exotica, and precision measurements of sin 2 θ W . In addition to performing CP violation measurements at the Υ(4S) and φ(3770), SuperB will test CPT in these systems, and lepton universality in a number of different processes. The multitude of rare decay measurements possible at SuperB can be used to constrain scenarios of physics beyond the Standard Model. In terms of other precision tests of the Standard Model, this experiment will be able to perform precision over-constraints of the unitarity triangle through

Bayesian ensemble refinement by replica simulations and reweighting

Science.gov (United States)

Hummer, Gerhard; Köfinger, Jürgen

2015-12-01

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Protein folding simulations by generalized-ensemble algorithms.

Science.gov (United States)

Yoda, Takao; Sugita, Yuji; Okamoto, Yuko

2014-01-01

In the protein folding problem, conventional simulations in physical statistical mechanical ensembles, such as the canonical ensemble with fixed temperature, face a great difficulty. This is because there exist a huge number of local-minimum-energy states in the system and the conventional simulations tend to get trapped in these states, giving wrong results. Generalized-ensemble algorithms are based on artificial unphysical ensembles and overcome the above difficulty by performing random walks in potential energy, volume, and other physical quantities or their corresponding conjugate parameters such as temperature, pressure, etc. The advantage of generalized-ensemble simulations lies in the fact that they not only avoid getting trapped in states of energy local minima but also allows the calculations of physical quantities as functions of temperature or other parameters from a single simulation run. In this article we review the generalized-ensemble algorithms. Four examples, multicanonical algorithm, replica-exchange method, replica-exchange multicanonical algorithm, and multicanonical replica-exchange method, are described in detail. Examples of their applications to the protein folding problem are presented.

Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China

Science.gov (United States)

Liu, Li; Gao, Chao; Xuan, Weidong; Xu, Yue-Ping

2017-11-01

Ensemble flood forecasts by hydrological models using numerical weather prediction products as forcing data are becoming more commonly used in operational flood forecasting applications. In this study, a hydrological ensemble flood forecasting system comprised of an automatically calibrated Variable Infiltration Capacity model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated. The hydrological model is optimized by the parallel programmed ε-NSGA II multi-objective algorithm. According to the solutions by ε-NSGA II, two differently parameterized models are determined to simulate daily flows and peak flows at each of the three hydrological stations. Then a simple yet effective modular approach is proposed to combine these daily and peak flows at the same station into one composite series. Five ensemble methods and various evaluation metrics are adopted. The results show that ε-NSGA II can provide an objective determination on parameter estimation, and the parallel program permits a more efficient simulation. It is also demonstrated that the forecasts from ECMWF have more favorable skill scores than other Ensemble Prediction Systems. The multimodel ensembles have advantages over all the single model ensembles and the multimodel methods weighted on members and skill scores outperform other methods. Furthermore, the overall performance at three stations can be satisfactory up to ten days, however the hydrological errors can degrade the skill score by approximately 2 days, and the influence persists until a lead time of 10 days with a weakening trend. With respect to peak flows selected by the Peaks Over Threshold approach, the ensemble means from single models or multimodels are generally underestimated, indicating that the ensemble mean can bring overall improvement in forecasting of flows. For

Architectural Engineering to Super-Light Structures

DEFF Research Database (Denmark)

Castberg, Niels Andreas

The increasing global urbanisation creates a great demand for new buildings. In the aim to honour this, a new structural system, offering flexibility and variation at no extra cost appears beneficial. Super-Light Structures constitute such a system. This PhD thesis examines Super-Light Structures...... with architectural engineering as a starting point. The thesis is based on a two stringed hypothesis: Architectural engineering gives rise to better architecture and Super-Light Structures support and enables a static, challenging architecture. The aim of the thesis is to clarify architectural engineering's impact...... on the work process between architects and engineers in the design development. Using architectural engineering, Super-Light Structures are examined in an architectural context, and it is explained how digital tools can support architectural engineering and design of Super-Light Structures. The experiences...

Ensemble method for dengue prediction.

Science.gov (United States)

Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

2018-01-01

In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

Ensemble method for dengue prediction.

Directory of Open Access Journals (Sweden)

Anna L Buczak

Full Text Available In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico during four dengue seasons: 1 peak height (i.e., maximum weekly number of cases during a transmission season; 2 peak week (i.e., week in which the maximum weekly number of cases occurred; and 3 total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date.Our approach used ensemble models created by combining three disparate types of component models: 1 two-dimensional Method of Analogues models incorporating both dengue and climate data; 2 additive seasonal Holt-Winters models with and without wavelet smoothing; and 3 simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations.Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week.The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

Contact planarization of ensemble nanowires

Science.gov (United States)

Chia, A. C. E.; LaPierre, R. R.

2011-06-01

The viability of four organic polymers (S1808, SC200, SU8 and Cyclotene) as filling materials to achieve planarization of ensemble nanowire arrays is reported. Analysis of the porosity, surface roughness and thermal stability of each filling material was performed. Sonication was used as an effective method to remove the tops of the nanowires (NWs) to achieve complete planarization. Ensemble nanowire devices were fully fabricated and I-V measurements confirmed that Cyclotene effectively planarizes the NWs while still serving the role as an insulating layer between the top and bottom contacts. These processes and analysis can be easily implemented into future characterization and fabrication of ensemble NWs for optoelectronic device applications.

Ensemble forecasting of species distributions.

Science.gov (United States)

Araújo, Miguel B; New, Mark

2007-01-01

Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

Detecting Water on Super-Earths Using JAVST

Science.gov (United States)

Deming, D.

2010-01-01

Nearby lower train sequence stars host a class of planets known as Super-Earths, that have no analog in our own solar system. Super-Earths are rocky and/or icy planets with masses up to about 10 Earth masses, They are expected to host atmospheres generated by a number of processes including accretion of chondritic material. Water vapor should be a common constituent of super-Earth atmospheres, and may be detectable in transiting super-Earths using transmission spectroscopy during primar y eclipse, and emission spectroscopy at secondary eclipse. I will discuss the prospects for super-Earth atmospheric measurements using JWST.

Supergrassmannians, super τ-functions and strings

International Nuclear Information System (INIS)

Dolgikh, S.N.; Schwarz, A.S.

1989-03-01

Recently, infinite-dimensional grassmannians and their supergeneralizations were used to study conformal two-dimensional fields and strings. In particular, the super Mumford form (holomorphic square root from the superstring measure on moduli space) was expressed through super analog of Sato τ-function. In this paper we present results of supergrassmannians and super τ-functions. 8 refs

Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation

NARCIS (Netherlands)

Boonstra, S.; van der Blom, K.; Hofmeyer, H.; Emmerich, M.T.M.; van Schijndel, A.W.M.; de Wilde, P.

2018-01-01

Multi-disciplinary optimisation of building spatial designs is characterised by large solution spaces. Here two approaches are introduced, one being super-structured and the other super-structure free. Both are different in nature and perform differently for large solution spaces and each requires

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

Science.gov (United States)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

Conductor gestures influence evaluations of ensemble performance.

Science.gov (United States)

Morrison, Steven J; Price, Harry E; Smedley, Eric M; Meals, Cory D

2014-01-01

Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor's gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the ensemble's articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble's performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

Super Virasoro algebra and solvable supersymmetric quantum field theories

International Nuclear Information System (INIS)

Yamanaka, Itaru; Sasaki, Ryu.

1987-09-01

Interesting and deep relationships between super Virasoro algebras and super soliton systems (super KdV, super mKdV and super sine-Gordon equations) are investigated at both classical and quantum levels. An infinite set of conserved quantities responsible for solvability is characterized by super Virasoro algebras only. Several members of the infinite set of conserved quantities are derived explicitly. (author)

Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

Energy Technology Data Exchange (ETDEWEB)

Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

2016-10-01

The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

Modality-Driven Classification and Visualization of Ensemble Variance

Energy Technology Data Exchange (ETDEWEB)

Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

2016-10-01

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

Bioactive focus in conformational ensembles: a pluralistic approach

Science.gov (United States)

Habgood, Matthew

2017-12-01

Computational generation of conformational ensembles is key to contemporary drug design. Selecting the members of the ensemble that will approximate the conformation most likely to bind to a desired target (the bioactive conformation) is difficult, given that the potential energy usually used to generate and rank the ensemble is a notoriously poor discriminator between bioactive and non-bioactive conformations. In this study an approach to generating a focused ensemble is proposed in which each conformation is assigned multiple rankings based not just on potential energy but also on solvation energy, hydrophobic or hydrophilic interaction energy, radius of gyration, and on a statistical potential derived from Cambridge Structural Database data. The best ranked structures derived from each system are then assembled into a new ensemble that is shown to be better focused on bioactive conformations. This pluralistic approach is tested on ensembles generated by the Molecular Operating Environment's Low Mode Molecular Dynamics module, and by the Cambridge Crystallographic Data Centre's conformation generator software.

Demonstrating the value of larger ensembles in forecasting physical systems

Directory of Open Access Journals (Sweden)

Reason L. Machete

2016-12-01

Full Text Available Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying variations in the sensitivity of the model all the way to providing actionable probability forecasts of the future. Whatever the goal is, success depends on the properties of the ensemble, and there is a longstanding discussion in meteorology as to the size of initial condition ensemble most appropriate for Numerical Weather Prediction. In terms of resource allocation: how is one to divide finite computing resources between model complexity, ensemble size, data assimilation and other components of the forecast system. One wishes to avoid undersampling information available from the model's dynamics, yet one also wishes to use the highest fidelity model available. Arguably, a higher fidelity model can better exploit a larger ensemble; nevertheless it is often suggested that a relatively small ensemble, say ~16 members, is sufficient and that larger ensembles are not an effective investment of resources. This claim is shown to be dubious when the goal is probabilistic forecasting, even in settings where the forecast model is informative but imperfect. Probability forecasts for a ‘simple’ physical system are evaluated at different lead times; ensembles of up to 256 members are considered. The pure density estimation context (where ensemble members are drawn from the same underlying distribution as the target differs from the forecasting context, where one is given a high fidelity (but imperfect model. In the forecasting context, the information provided by additional members depends also on the fidelity of the model, the ensemble formation scheme (data assimilation, the ensemble interpretation and the nature of the observational noise. The effect of increasing the ensemble size is quantified by

Ensemble Weight Enumerators for Protograph LDPC Codes

Science.gov (United States)

Divsalar, Dariush

2006-01-01

Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length ensemble weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining ensemble average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular ensembles, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on ensemble weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.

Ensemble atmospheric dispersion calculations for decision support systems

International Nuclear Information System (INIS)

Borysiewicz, M.; Potempski, S.; Galkowski, A.; Zelazny, R.

2003-01-01

This document describes two approaches to long-range atmospheric dispersion of pollutants based on the ensemble concept. In the first part of the report some experiences related to the exercises undertaken under the ENSEMBLE project of the European Union are presented. The second part is devoted to the implementation of mesoscale numerical prediction models RAMS and atmospheric dispersion model HYPACT on Beowulf cluster and theirs usage for ensemble forecasting and long range atmospheric ensemble dispersion calculations based on available meteorological data from NCEO, NOAA (USA). (author)

Is Quantum Gravity a Super-Quantum Theory?

OpenAIRE

Chang, Lay Nam; Lewis, Zachary; Minic, Djordje; Takeuchi, Tatsu

2013-01-01

We argue that quantum gravity should be a super-quantum theory, that is, a theory whose non-local correlations are stronger than those of canonical quantum theory. As a super-quantum theory, quantum gravity should display distinct experimentally observable super-correlations of entangled stringy states.

Learning from errors in super-resolution.

Science.gov (United States)

Tang, Yi; Yuan, Yuan

2014-11-01

A novel framework of learning-based super-resolution is proposed by employing the process of learning from the estimation errors. The estimation errors generated by different learning-based super-resolution algorithms are statistically shown to be sparse and uncertain. The sparsity of the estimation errors means most of estimation errors are small enough. The uncertainty of the estimation errors means the location of the pixel with larger estimation error is random. Noticing the prior information about the estimation errors, a nonlinear boosting process of learning from these estimation errors is introduced into the general framework of the learning-based super-resolution. Within the novel framework of super-resolution, a low-rank decomposition technique is used to share the information of different super-resolution estimations and to remove the sparse estimation errors from different learning algorithms or training samples. The experimental results show the effectiveness and the efficiency of the proposed framework in enhancing the performance of different learning-based algorithms.

Ensemble-Based Data Assimilation in Reservoir Characterization: A Review

Directory of Open Access Journals (Sweden)

Seungpil Jung

2018-02-01

Full Text Available This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF and ensemble smoother (ES as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization.

Superparticle on the 'super' Poincare upper half plane

Energy Technology Data Exchange (ETDEWEB)

Uehara, S; Yasui, Yukinora

1988-03-17

A non-relativistic superparticle moving freely on the 'super' Poincare upper half plane is investigated. The lagrangian is invariant under the super Moebius transformations SPL (2, R), so that it can be projected into the lagrangian on the super Riemann surface. The quantum hamiltonian becomes the 'super' Laplace-Beltrami operator in the curved superspace.

Super boson-fermion correspondence

International Nuclear Information System (INIS)

Kac, V.G.; Leur van de, J.W.

1987-01-01

Since the pioneering work of Skyrme, the boson-fermion correspondence has been playing an increasingly important role in 2-dimensional quantum field theory. More recently, it has become an important ingredient in the work of the Kyoto school on the KP hierarchy of soliton equations. In the present paper we establish a super boson-fermion correspondence, having in mind its applications to super KP hierarchies

Various multistage ensembles for prediction of heating energy consumption

Directory of Open Access Journals (Sweden)

Radisa Jovanovic

2015-04-01

Full Text Available Feedforward neural network models are created for prediction of daily heating energy consumption of a NTNU university campus Gloshaugen using actual measured data for training and testing. Improvement of prediction accuracy is proposed by using neural network ensemble. Previously trained feed-forward neural networks are first separated into clusters, using k-means algorithm, and then the best network of each cluster is chosen as member of an ensemble. Two conventional averaging methods for obtaining ensemble output are applied; simple and weighted. In order to achieve better prediction results, multistage ensemble is investigated. As second level, adaptive neuro-fuzzy inference system with various clustering and membership functions are used to aggregate the selected ensemble members. Feedforward neural network in second stage is also analyzed. It is shown that using ensemble of neural networks can predict heating energy consumption with better accuracy than the best trained single neural network, while the best results are achieved with multistage ensemble.

The Solution Construction of Heterotic Super-Liouville Model

Science.gov (United States)

Yang, Zhan-Ying; Zhen, Yi

2001-12-01

We investigate the heterotic super-Liouville model on the base of the basic Lie super-algebra Osp(1|2).Using the super extension of Leznov-Saveliev analysis and Drinfeld-Sokolov linear system, we construct the explicit solution of the heterotic super-Liouville system in component form. We also show that the solutions are local and periodic by calculating the exchange relation of the solution. Finally starting from the action of heterotic super-Liouville model, we obtain the conserved current and conserved charge which possessed the BRST properties.

Super-radiance in Nuclear Physics

International Nuclear Information System (INIS)

Auerbach, N

2015-01-01

The theory of the super-radiant mechanism as applied to various phenomena in nuclear physics is presented. The connection between super-radiance and the notion of doorway is presented. The statistics of resonance widths in a many-body Fermi system with open channels is discussed. Depending on the strength of the coupling to the continuum such systems show deviations from the standard Porter-Thomas distribution. The deviations result from the process of increasing interaction of the intrinsic states via the common decay channels. In the limit of very strong coupling this leads to super-radiance. (paper)

Ensemble Machine Learning Methods and Applications

CERN Document Server

Ma, Yunqian

2012-01-01

It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

Super-hydrophobic surfaces of SiO₂-coated SiC nanowires: fabrication, mechanism and ultraviolet-durable super-hydrophobicity.

Science.gov (United States)

Zhao, Jian; Li, Zhenjiang; Zhang, Meng; Meng, Alan

2015-04-15

The interest in highly water-repellent surfaces of SiO2-coated SiC nanowires has grown in recent years due to the desire for self-cleaning and anticorrosive surfaces. It is imperative that a simple chemical treatment with fluoroalkylsilane (FAS, CF3(CF2)7CH2CH2Si(OC2H5)3) in ethanol solution at room temperature resulted in super-hydrophobic surfaces of SiO2-coated SiC nanowires. The static water contact angle of SiO2-coated SiC nanowires surfaces was changed from 0° to 153° and the morphology, microstructure and crystal phase of the products were almost no transformation before and after super-hydrophobic treatment. Moreover, a mechanism was expounded reasonably, which could elucidate the reasons for their super-hydrophobic behavior. It is important that the super-hydrophobic surfaces of SiO2-coated SiC nanowires possessed ultraviolet-durable (UV-durable) super-hydrophobicity. Copyright © 2014 Elsevier Inc. All rights reserved.

Deriving Global Convection Maps From SuperDARN Measurements

Science.gov (United States)

Gjerloev, J. W.; Waters, C. L.; Barnes, R. J.

2018-04-01

A new statistical modeling technique for determining the global ionospheric convection is described. The principal component regression (PCR)-based technique is based on Super Dual Auroral Radar Network (SuperDARN) observations and is an advanced version of the PCR technique that Waters et al. (https//:doi.org.10.1002/2015JA021596) used for the SuperMAG data. While SuperMAG ground magnetic field perturbations are vector measurements, SuperDARN provides line-of-sight measurements of the ionospheric convection flow. Each line-of-sight flow has a known azimuth (or direction), which must be converted into the actual vector flow. However, the component perpendicular to the azimuth direction is unknown. Our method uses historical data from the SuperDARN database and PCR to determine a fill-in model convection distribution for any given universal time. The fill-in data process is driven by a list of state descriptors (magnetic indices and the solar zenith angle). The final solution is then derived from a spherical cap harmonic fit to the SuperDARN measurements and the fill-in model. When compared with the standard SuperDARN fill-in model, we find that our fill-in model provides improved solutions, and the final solutions are in better agreement with the SuperDARN measurements. Our solutions are far less dynamic than the standard SuperDARN solutions, which we interpret as being due to a lack of magnetosphere-ionosphere inertia and communication delays in the standard SuperDARN technique while it is inherently included in our approach. Rather, we argue that the magnetosphere-ionosphere system has inertia that prevents the global convection from changing abruptly in response to an interplanetary magnetic field change.

Popular Music and the Instrumental Ensemble.

Science.gov (United States)

Boespflug, George

1999-01-01

Discusses popular music, the role of the musical performer as a creator, and the styles of jazz and popular music. Describes the pop ensemble at the college level, focusing on improvisation, rehearsals, recording, and performance. Argues that pop ensembles be used in junior and senior high school. (CMK)

Ensemble Kalman methods for inverse problems

International Nuclear Information System (INIS)

Iglesias, Marco A; Law, Kody J H; Stuart, Andrew M

2013-01-01

The ensemble Kalman filter (EnKF) was introduced by Evensen in 1994 (Evensen 1994 J. Geophys. Res. 99 10143–62) as a novel method for data assimilation: state estimation for noisily observed time-dependent problems. Since that time it has had enormous impact in many application domains because of its robustness and ease of implementation, and numerical evidence of its accuracy. In this paper we propose the application of an iterative ensemble Kalman method for the solution of a wide class of inverse problems. In this context we show that the estimate of the unknown function that we obtain with the ensemble Kalman method lies in a subspace A spanned by the initial ensemble. Hence the resulting error may be bounded above by the error found from the best approximation in this subspace. We provide numerical experiments which compare the error incurred by the ensemble Kalman method for inverse problems with the error of the best approximation in A, and with variants on traditional least-squares approaches, restricted to the subspace A. In so doing we demonstrate that the ensemble Kalman method for inverse problems provides a derivative-free optimization method with comparable accuracy to that achieved by traditional least-squares approaches. Furthermore, we also demonstrate that the accuracy is of the same order of magnitude as that achieved by the best approximation. Three examples are used to demonstrate these assertions: inversion of a compact linear operator; inversion of piezometric head to determine hydraulic conductivity in a Darcy model of groundwater flow; and inversion of Eulerian velocity measurements at positive times to determine the initial condition in an incompressible fluid. (paper)

Super-Hamiltonian Structures and Conservation Laws of a New Six-Component Super-Ablowitz-Kaup-Newell-Segur Hierarchy

Directory of Open Access Journals (Sweden)

Fucai You

2014-01-01

Full Text Available A six-component super-Ablowitz-Kaup-Newell-Segur (-AKNS hierarchy is proposed by the zero curvature equation associated with Lie superalgebras. Supertrace identity is used to furnish the super-Hamiltonian structures for the resulting nonlinear superintegrable hierarchy. Furthermore, we derive the infinite conservation laws of the first two nonlinear super-AKNS equations in the hierarchy by utilizing spectral parameter expansions. PACS: 02.30.Ik; 02.30.Jr; 02.20.Sv.

Genetic Algorithm Optimized Neural Networks Ensemble as ...

African Journals Online (AJOL)

Marquardt algorithm by varying conditions such as inputs, hidden neurons, initialization, training sets and random Gaussian noise injection to ... Several such ensembles formed the population which was evolved to generate the fittest ensemble.

Global Ensemble Forecast System (GEFS) [1 Deg.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

Bidirectional Modulation of Intrinsic Excitability in Rat Prelimbic Cortex Neuronal Ensembles and Non-Ensembles after Operant Learning.

Science.gov (United States)

Whitaker, Leslie R; Warren, Brandon L; Venniro, Marco; Harte, Tyler C; McPherson, Kylie B; Beidel, Jennifer; Bossert, Jennifer M; Shaham, Yavin; Bonci, Antonello; Hope, Bruce T

2017-09-06

Learned associations between environmental stimuli and rewards drive goal-directed learning and motivated behavior. These memories are thought to be encoded by alterations within specific patterns of sparsely distributed neurons called neuronal ensembles that are activated selectively by reward-predictive stimuli. Here, we use the Fos promoter to identify strongly activated neuronal ensembles in rat prelimbic cortex (PLC) and assess altered intrinsic excitability after 10 d of operant food self-administration training (1 h/d). First, we used the Daun02 inactivation procedure in male FosLacZ-transgenic rats to ablate selectively Fos-expressing PLC neurons that were active during operant food self-administration. Selective ablation of these neurons decreased food seeking. We then used male FosGFP-transgenic rats to assess selective alterations of intrinsic excitability in Fos-expressing neuronal ensembles (FosGFP + ) that were activated during food self-administration and compared these with alterations in less activated non-ensemble neurons (FosGFP - ). Using whole-cell recordings of layer V pyramidal neurons in an ex vivo brain slice preparation, we found that operant self-administration increased excitability of FosGFP + neurons and decreased excitability of FosGFP - neurons. Increased excitability of FosGFP + neurons was driven by increased steady-state input resistance. Decreased excitability of FosGFP - neurons was driven by increased contribution of small-conductance calcium-activated potassium (SK) channels. Injections of the specific SK channel antagonist apamin into PLC increased Fos expression but had no effect on food seeking. Overall, operant learning increased intrinsic excitability of PLC Fos-expressing neuronal ensembles that play a role in food seeking but decreased intrinsic excitability of Fos - non-ensembles. SIGNIFICANCE STATEMENT Prefrontal cortex activity plays a critical role in operant learning, but the underlying cellular mechanisms are

A novel super-resolution camera model

Science.gov (United States)

Shao, Xiaopeng; Wang, Yi; Xu, Jie; Wang, Lin; Liu, Fei; Luo, Qiuhua; Chen, Xiaodong; Bi, Xiangli

2015-05-01

Aiming to realize super resolution(SR) to single image and video reconstruction, a super resolution camera model is proposed for the problem that the resolution of the images obtained by traditional cameras behave comparatively low. To achieve this function we put a certain driving device such as piezoelectric ceramics in the camera. By controlling the driving device, a set of continuous low resolution(LR) images can be obtained and stored instantaneity, which reflect the randomness of the displacements and the real-time performance of the storage very well. The low resolution image sequences have different redundant information and some particular priori information, thus it is possible to restore super resolution image factually and effectively. The sample method is used to derive the reconstruction principle of super resolution, which analyzes the possible improvement degree of the resolution in theory. The super resolution algorithm based on learning is used to reconstruct single image and the variational Bayesian algorithm is simulated to reconstruct the low resolution images with random displacements, which models the unknown high resolution image, motion parameters and unknown model parameters in one hierarchical Bayesian framework. Utilizing sub-pixel registration method, a super resolution image of the scene can be reconstructed. The results of 16 images reconstruction show that this camera model can increase the image resolution to 2 times, obtaining images with higher resolution in currently available hardware levels.

Quantization of super Teichmueller spaces

International Nuclear Information System (INIS)

Aghaei, Nezhla

2016-08-01

The quantization of the Teichmueller spaces of Riemann surfaces has found important applications to conformal field theory and N=2 supersymmetric gauge theories. We construct a quantization of the Teichmueller spaces of super Riemann surfaces, using coordinates associated to the ideal triangulations of super Riemann surfaces. A new feature is the non-trivial dependence on the choice of a spin structure which can be encoded combinatorially in a certain refinement of the ideal triangulation. We construct a projective unitary representation of the groupoid of changes of refined ideal triangulations. Therefore, we demonstrate that the dependence of the resulting quantum theory on the choice of a triangulation is inessential. In the quantum Teichmueller theory, it was observed that the key object defining the Teichmueller theory has a close relation to the representation theory of the Borel half of U q (sl(2)). In our research we observed that the role of U q (sl(2)) is taken by quantum superalgebra U q (osp(1 vertical stroke 2)). A Borel half of U q (osp(1 vertical stroke 2)) is the super quantum plane. The canonical element of the Heisenberg double of the quantum super plane is evaluated in certain infinite dimensional representations on L 2 (R) x C 1 vertical stroke 1 and compared to the flip operator from the Teichmueller theory of super Riemann surfaces.

Derivation of Mayer Series from Canonical Ensemble

International Nuclear Information System (INIS)

Wang Xian-Zhi

2016-01-01

Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula. (paper)

Derivation of Mayer Series from Canonical Ensemble

Science.gov (United States)

Wang, Xian-Zhi

2016-02-01

Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.

SuperSegger

DEFF Research Database (Denmark)

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B

2016-01-01

-colonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter, and neighboring cells......Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well......-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment micro...

Super-Lagrangians

International Nuclear Information System (INIS)

Beyl, L.M.

1979-01-01

It is shown that the Einstein, Weyl, supergravity and superconformal theories are special cases of gauge transformations in SU(4vertical-barN). This group is shown to contain SU(2,2) x SU(N) x U(1) for its commuting or Bose part, and to contain 8N supersymmetry generators for its anticommuting or Fermi part. Using the electromagnetic Lagrangian as a model, a super-Lagrangian is constructed for vector potentials. Invariance is automatic in free space, but, in the presence of matter, restrictions on the supersymmetry transformations are necessary. The Weyl action and the Einstein cosmological field equations are obtained in the appropriate limits. Finally, a super-Lagrangian is constructed from nongeometric principles which includes the Dirac Lagrangian and except for a sum over symmetry indices resembles the electron-electromagnetic Lagrangian

SuperB A High-Luminosity Asymmetric $e^+ e^-$ Super Flavour Factory : Conceptual Design Report

CERN Document Server

Bona, M.; Grauges Pous, E.; Colangelo, P.; De Fazio, F.; Palano, A.; Manghisoni, M.; Re, V.; Traversi, G.; Eigen, G.; Venturini, M.; Soni, N.; Bruschi, M.; De Castro, S.; Faccioli, P.; Gabrieli, A.; Giacobbe, B.; Semprini Cesare, N.; Spighi, R.; Villa, M.; Zoccoli, A.; Hearty, C.; McKenna, J.; Soni, A.; Khan, A.; Barniakov, A.Y.; Barniakov, M.Y.; Blinov, V.E.; Druzhinin, V.P.; Golubev, V.B.; Kononov, S.A.; Koop, I.A.; Kravchenko, E.A.; Levichev, E.B.; Nikitin, S.A.; Onuchin, A.P.; Piminov, P.A.; Serednyakov, S.I.; Shatilov, D.N.; Skovpen, Y.I.; Solodov, E.A.; Cheng, C.H.; Echenard, B.; Fang, F.; Hitlin, D.J.; Porter, F.C.; Asner, D.M.; Pham, T.N.; Fleischer, R.; Giudice, G.F.; Hurth, T.; Mangano, M.; Mancinelli, G.; Meadows, B.T.; Schwartz, A.J.; Sokoloff, M.D.; Soffer, A.; Beard, C.D.; Haas, T.; Mankel, R.; Hiller, G.; Ball, P.; Pappagallo, M.; Pennington, M.R.; Gradl, W.; Playfer, S.; Abada, A.; Becirevic, D.; Descotes-Genon, S.; Pene, O.; Andreotti, D.; Andreotti, M.; Bettoni, D.; Bozzi, C.; Calabresi, R.; Cecchi, A.; Cibinetto, G.; Franchini, P.; Luppi, E.; Negrini, M.; Petrella, A.; Piemontese, L.; Prencipe, E.; Santoro, V.; Stancari, G.; Anulli, F.; Baldini-Ferroli, R.; Biagini, M.E.; Boscolo, M.; Calcaterra, A.; Drago, A.; Finocchiaro, G.; Guiducci, S.; Isidori, G.; Pacetti, S.; Patteri, P.; Peruzzi, I.M.; Piccolo, M.; Preger, M.A.; Raimondi, P.; Rama, M.; Vaccarezza, C.; Zallo, A.; Zobov, M.; De Sangro, R.; Buzzo, A.; Lo Vetere, M.; Macri, M.; Monge, M.R.; Passaggio, S.; Patrignani, C.; Robutti, E.; Tosi, S.; Matias, J.; Panduro Vazquez, W.; Borzumati, F.; Eyges, V.; Prell, S.A.; Pedlar, T.K.; Korpar, S.; Pestonik, R.; Staric, M.; Neubert, M.; Denig, A.G.; Nierste, U.; Agoh, T.; Ohmi, K.; Ohnishi, Y.; Fry, J.R.; Touramanis, C.; Wolski, A.; Golob, B.; Krizan, P.; Flaecher, H.; Bevan, A.J.; Di Lodovico, F.; George, K.A.; Barlow, R.; Lafferty, G.; Jawahery, A.; Roberts, D.A.; Simi, G.; Patel, P.M.; Robertson, S.H.; Lazzaro, A.; Palombo, F.; Kaidalov, A.; Buras, A.J.; Tarantino, C.; Buchalla, G.; Sanda, A.I.; D'Ambrosio, G.; Ricciardi, G.; Bigi, I.; Jessop, C.P.; Losecco, J.M.; Honscheid, K.; Arnaud, N.; Chehab, R.; Fedala, Y.; Polci, F.; Roudeau, P.; Sordini, V.; Soskov, V.; Stocchi, A.; Variola, A.; Vivoli, A.; Wormser, G.; Zomer, F.; Bertolin, A.; Brugnera, R.; Gagliardi, N.; Gaz, A.; Margoni, M.; Morandin, M.; Posocco, M.; Rotondo, M.; Simonetto, F.; Stroili, R.; Bonneaud, G.R.; Lombardo, V.; Calderini, G.; Ratti, L.; Speziali, V.; Biasini, M.; Covarelli, R.; Manoni, E.; Servoli, L.; Angelini, C.; Batignani, G.; Bettarini, S.; Bosi, F.; Carpinelli, M.; Cenci, R.; Cervelli, A.; Dell'Orso, M.; Forti, F.; Giannetti, P.; Giorgi, M.; Lusiani, A.; Marchiori, G.; Massa, M.; Mazur, M.A.; Morsani, F.; Neri, N.; Paoloni, E.; Raffaelli, F.; Rizzo, G.; Walsh, J.; Braun, V.; Lenz, A.; Adams, G.S.; Danko, I.Z.; Baracchini, E.; Bellini, F.; Cavoto, G.; D'Orazio, A.; Del Re, D.; Di Marco, E.; Faccini, R.; Ferrarotto, F.; Gaspero, Mario; Jackson, P.; Martinelli, G.; Mazzoni, M.A.; Morganti, Silvio; Piredda, G.; Renga, F.; Silvestrini, L.; Voena, C.; Catani, L.; Di Ciaccio, A.; Messi, R.; Santovetti, E.; Satta, A.; Ciuchini, M.; Lubicz, V.; Wilson, F.F.; Godang, R.; Chen, X.; Liu, H.; Park, W.; Purohit, M.; Trivedi, A.; White, R.M.; Wilson, J.R.; Allen, M.T.; Aston, D.; Bartoldus, R.; Brodsky, S.J.; Cai, Y.; Coleman, J.; Convery, M.R.; DeBarger, S.; Dingfelder, J.C.; Dubois-Felsmann, G.P.; Ecklund, S.; Fisher, A.S.; Haller, G.; Heifets, S.A.; Kaminski, J.; Kelsey, M.H.; Kocian, M.L.; Leith, D.W.G.S.; Li, N.; Luitz, S.; Luth, V.; MacFarlane, D.; Messner, R.; Muller, D.R.; Nosochkov, Y.; Novokhatski, A.; Pivi, M.; Ratcliff, B.N.; Roodman, A.; Schwiening, J.; Seeman, J.; Snyder, A.; Sullivan, M.; Va'Vra, J.; Wienands, U.; Wisniewski, W.; Stoeck, H.; Cheng, H.Y.; Li, H.N.; Keum, Y.Y.; Gronau, M.; Grossman, Y.; Bianchi, F.; Gamba, D.; Gambino, P.; Marchetto, F.; Menichetti, Ezio A.; Mussa, R.; Pelliccioni, M.; Dalla Betta, G.F.; Bomben, M.; Bosisio, L.; Cartaro, C.; Lanceri, L.; Vitale, L.; Azzolini, V.; Bernabeu, J.; Lopez-March, N.; Martinez-Vidal, F.; Milanes, D.A.; Oyanguren, A.; Paradisi, P.; Pich, A.; Sanchis-Lozano, M.A.; Kowalewski, Robert V.; Roney, J.M.; Back, J.J.; Gershon, T.J.; Harrison, P.F.; Latham, T.E.; Mohanty, G.B.; Petrov, A.A.; Pierini, M.; INFN

2007-01-01

The physics objectives of SuperB, an asymmetric electron-positron collider with a luminosity above 10^36/cm^2/s are described, together with the conceptual design of a novel low emittance design that achieves this performance with wallplug power comparable to that of the current B Factories, and an upgraded detector capable of doing the physics in the SuperB environment.

Ensemble inequivalence: Landau theory and the ABC model

International Nuclear Information System (INIS)

Cohen, O; Mukamel, D

2012-01-01

It is well known that systems with long-range interactions may exhibit different phase diagrams when studied within two different ensembles. In many of the previously studied examples of ensemble inequivalence, the phase diagrams differ only when the transition in one of the ensembles is first order. By contrast, in a recent study of a generalized ABC model, the canonical and grand-canonical ensembles of the model were shown to differ even when they both exhibit a continuous transition. Here we show that the order of the transition where ensemble inequivalence may occur is related to the symmetry properties of the order parameter associated with the transition. This is done by analyzing the Landau expansion of a generic model with long-range interactions. The conclusions drawn from the generic analysis are demonstrated for the ABC model by explicit calculation of its Landau expansion. (paper)

Regionalization of post-processed ensemble runoff forecasts

Directory of Open Access Journals (Sweden)

J. O. Skøien

2016-05-01

Full Text Available For many years, meteorological models have been run with perturbated initial conditions or parameters to produce ensemble forecasts that are used as a proxy of the uncertainty of the forecasts. However, the ensembles are usually both biased (the mean is systematically too high or too low, compared with the observed weather, and has dispersion errors (the ensemble variance indicates a too low or too high confidence in the forecast, compared with the observed weather. The ensembles are therefore commonly post-processed to correct for these shortcomings. Here we look at one of these techniques, referred to as Ensemble Model Output Statistics (EMOS (Gneiting et al., 2005. Originally, the post-processing parameters were identified as a fixed set of parameters for a region. The application of our work is the European Flood Awareness System (http://www.efas.eu, where a distributed model is run with meteorological ensembles as input. We are therefore dealing with a considerably larger data set than previous analyses. We also want to regionalize the parameters themselves for other locations than the calibration gauges. The post-processing parameters are therefore estimated for each calibration station, but with a spatial penalty for deviations from neighbouring stations, depending on the expected semivariance between the calibration catchment and these stations. The estimated post-processed parameters can then be used for regionalization of the postprocessing parameters also for uncalibrated locations using top-kriging in the rtop-package (Skøien et al., 2006, 2014. We will show results from cross-validation of the methodology and although our interest is mainly in identifying exceedance probabilities for certain return levels, we will also show how the rtop package can be used for creating a set of post-processed ensembles through simulations.

Pauci ex tanto numero: reducing redundancy in multi-model ensembles

Science.gov (United States)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-02-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date no attempts in this direction are documented within the air quality (AQ) community, although the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared biases among models will determine a biased ensemble, making therefore essential the errors of the ensemble members to be independent so that bias can cancel out. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated) we discourage selecting the members of the ensemble simply on the basis of scores, that is, independence and skills need to be considered disjointly.

A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

KAUST Repository

Altaf, Muhammad

2014-08-01

This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

KAUST Repository

Altaf, Muhammad; Butler, T.; Mayo, T.; Luo, X.; Dawson, C.; Heemink, A. W.; Hoteit, Ibrahim

2014-01-01

This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL

Energy Technology Data Exchange (ETDEWEB)

Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.

2011-05-10

The High-Resolution Mid-Atlantic Forecasting Ensemble (HME) is a federated effort to improve operational forecasts related to precipitation, convection and boundary layer evolution, and fire weather utilizing data and computing resources from a diverse group of cooperating institutions in order to create a mesoscale ensemble from independent members. Collaborating organizations involved in the project include universities, National Weather Service offices, and national laboratories, including the Savannah River National Laboratory (SRNL). The ensemble system is produced from an overlapping numerical weather prediction model domain and parameter subsets provided by each contributing member. The coordination, synthesis, and dissemination of the ensemble information are performed by the Renaissance Computing Institute (RENCI) at the University of North Carolina-Chapel Hill. This paper discusses background related to the HME effort, SRNL participation, and example results available from the RENCI website.

The Hydrologic Ensemble Prediction Experiment (HEPEX)

Science.gov (United States)

Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.

2012-12-01

The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological ensemble prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

Pauci ex tanto numero: reduce redundancy in multi-model ensembles

Science.gov (United States)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-08-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date, no attempts in this direction have been documented within the air quality (AQ) community despite the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared, dependant biases among models do not cancel out but will instead determine a biased ensemble. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated), we discourage selecting the members of the ensemble simply on the basis of scores; that is, independence and skills need to be considered disjointly.

Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

DEFF Research Database (Denmark)

Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh

2015-01-01

Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

Super capacitor modeling with artificial neural network (ANN)

Energy Technology Data Exchange (ETDEWEB)

Marie-Francoise, J.N.; Gualous, H.; Berthon, A. [Universite de Franche-Comte, Lab. en Electronique, Electrotechnique et Systemes (L2ES), UTBM, INRETS (LRE T31) 90 - Belfort (France)

2004-07-01

This paper presents super-capacitors modeling using Artificial Neural Network (ANN). The principle consists on a black box nonlinear multiple inputs single output (MISO) model. The system inputs are temperature and current, the output is the super-capacitor voltage. The learning and the validation of the ANN model from experimental charge and discharge of super-capacitor establish the relationship between inputs and output. The learning and the validation of the ANN model use experimental results of 2700 F, 3700 F and a super-capacitor pack. Once the network is trained, the ANN model can predict the super-capacitor behaviour with temperature variations. The update parameters of the ANN model are performed thanks to Levenberg-Marquardt method in order to minimize the error between the output of the system and the predicted output. The obtained results with the ANN model of super-capacitor and experimental ones are in good agreement. (authors)

sl(1|2) Super-Toda Fields

Science.gov (United States)

Yang, Zhan-Ying; Xue, Pan-Pan; Zhao, Liu; Shi, Kang-Jie

2008-11-01

Explicit exact solution of supersymmetric Toda fields associated with the Lie superalgebra sl(2|1) is constructed. The approach used is a super extension of Leznov Saveliev algebraic analysis, which is based on a pair of chiral and antichiral Drienfeld Sokolov systems. Though such approach is well understood for Toda field theories associated with ordinary Lie algebras, its super analogue was only successful in the super Liouville case with the underlying Lie superalgebra osp(1|2). The problem lies in that a key step in the construction makes use of the tensor product decomposition of the highest weight representations of the underlying Lie superalgebra, which is not clear until recently. So our construction made in this paper presents a first explicit example of Leznov Saveliev analysis for super Toda systems associated with underlying Lie superalgebras of the rank higher than 1.

sl(1|2) Super-Toda Fields

International Nuclear Information System (INIS)

Yang Zhanying; Xue Panpan; Zhao Liu; Shi Kangjie

2008-01-01

Explicit exact solution of supersymmetric Toda fields associated with the Lie superalgebra sl(2|1) is constructed. The approach used is a super extension of Leznov-Saveliev algebraic analysis, which is based on a pair of chiral and antichiral Drienfeld-Sokolov systems. Though such approach is well understood for Toda field theories associated with ordinary Lie algebras, its super analogue was only successful in the super Liouville case with the underlying Lie superalgebra osp(1|2). The problem lies in that a key step in the construction makes use of the tensor product decomposition of the highest weight representations of the underlying Lie superalgebra, which is not clear until recently. So our construction made in this paper presents a first explicit example of Leznov-Saveliev analysis for super Toda systems associated with underlying Lie superalgebras of the rank higher than 1

Decadal climate predictions improved by ocean ensemble dispersion filtering

Science.gov (United States)

Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

2017-06-01

Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.Plain Language SummaryDecadal predictions aim to predict the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. The ocean memory due to its heat capacity holds big potential skill. In recent years, more precise initialization techniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions. Ensembles are another important aspect. Applying slightly perturbed predictions to trigger the famous butterfly effect results in an ensemble. Instead of evaluating one prediction, but the whole ensemble with its

Ensemble-based Probabilistic Forecasting at Horns Rev

DEFF Research Database (Denmark)

Pinson, Pierre; Madsen, Henrik

2009-01-01

forecasting methodology. In a first stage, ensemble forecasts of meteorological variables are converted to power through a suitable power curve model. This modelemploys local polynomial regression, and is adoptively estimated with an orthogonal fitting method. The obtained ensemble forecasts of wind power...

DroidEnsemble: Detecting Android Malicious Applications with Ensemble of String and Structural Static Features

KAUST Repository

Wang, Wei

2018-05-11

Android platform has dominated the Operating System of mobile devices. However, the dramatic increase of Android malicious applications (malapps) has caused serious software failures to Android system and posed a great threat to users. The effective detection of Android malapps has thus become an emerging yet crucial issue. Characterizing the behaviors of Android applications (apps) is essential to detecting malapps. Most existing work on detecting Android malapps was mainly based on string static features such as permissions and API usage extracted from apps. There also exists work on the detection of Android malapps with structural features, such as Control Flow Graph (CFG) and Data Flow Graph (DFG). As Android malapps have become increasingly polymorphic and sophisticated, using only one type of static features may result in false negatives. In this work, we propose DroidEnsemble that takes advantages of both string features and structural features to systematically and comprehensively characterize the static behaviors of Android apps and thus build a more accurate detection model for the detection of Android malapps. We extract each app’s string features, including permissions, hardware features, filter intents, restricted API calls, used permissions, code patterns, as well as structural features like function call graph. We then use three machine learning algorithms, namely, Support Vector Machine (SVM), k-Nearest Neighbor (kNN) and Random Forest (RF), to evaluate the performance of these two types of features and of their ensemble. In the experiments, We evaluate our methods and models with 1386 benign apps and 1296 malapps. Extensive experimental results demonstrate the effectiveness of DroidEnsemble. It achieves the detection accuracy as 95.8% with only string features and as 90.68% with only structural features. DroidEnsemble reaches the detection accuracy as 98.4% with the ensemble of both types of features, reducing 9 false positives and 12 false

A superparticle on the 'super' Poincare upper half plane

International Nuclear Information System (INIS)

Uehara, S.; Yasui, Yukinora

1988-01-01

A non-relativistic superparticle moving freely on the 'super' Poincare upper half plane is investigated. The lagrangian is invariant under the super Moebius transformations SPL (2, R), so that it can be projected into the lagrangian on the super Riemann surface. The quantum hamiltonian becomes the 'super' Laplace-Beltrami operator in the curved superspace. (orig.)

Raspberry Pi super cluster

CERN Document Server

Dennis, Andrew K

2013-01-01

This book follows a step-by-step, tutorial-based approach which will teach you how to develop your own super cluster using Raspberry Pi computers quickly and efficiently.Raspberry Pi Super Cluster is an introductory guide for those interested in experimenting with parallel computing at home. Aimed at Raspberry Pi enthusiasts, this book is a primer for getting your first cluster up and running.Basic knowledge of C or Java would be helpful but no prior knowledge of parallel computing is necessary.

Crossover ensembles of random matrices and skew-orthogonal polynomials

International Nuclear Information System (INIS)

Kumar, Santosh; Pandey, Akhilesh

2011-01-01

Highlights: → We study crossover ensembles of Jacobi family of random matrices. → We consider correlations for orthogonal-unitary and symplectic-unitary crossovers. → We use the method of skew-orthogonal polynomials and quaternion determinants. → We prove universality of spectral correlations in crossover ensembles. → We discuss applications to quantum conductance and communication theory problems. - Abstract: In a recent paper (S. Kumar, A. Pandey, Phys. Rev. E, 79, 2009, p. 026211) we considered Jacobi family (including Laguerre and Gaussian cases) of random matrix ensembles and reported exact solutions of crossover problems involving time-reversal symmetry breaking. In the present paper we give details of the work. We start with Dyson's Brownian motion description of random matrix ensembles and obtain universal hierarchic relations among the unfolded correlation functions. For arbitrary dimensions we derive the joint probability density (jpd) of eigenvalues for all transitions leading to unitary ensembles as equilibrium ensembles. We focus on the orthogonal-unitary and symplectic-unitary crossovers and give generic expressions for jpd of eigenvalues, two-point kernels and n-level correlation functions. This involves generalization of the theory of skew-orthogonal polynomials to crossover ensembles. We also consider crossovers in the circular ensembles to show the generality of our method. In the large dimensionality limit, correlations in spectra with arbitrary initial density are shown to be universal when expressed in terms of a rescaled symmetry breaking parameter. Applications of our crossover results to communication theory and quantum conductance problems are also briefly discussed.

Representing Color Ensembles.

Science.gov (United States)

Chetverikov, Andrey; Campana, Gianluca; Kristjánsson, Árni

2017-10-01

Colors are rarely uniform, yet little is known about how people represent color distributions. We introduce a new method for studying color ensembles based on intertrial learning in visual search. Participants looked for an oddly colored diamond among diamonds with colors taken from either uniform or Gaussian color distributions. On test trials, the targets had various distances in feature space from the mean of the preceding distractor color distribution. Targets on test trials therefore served as probes into probabilistic representations of distractor colors. Test-trial response times revealed a striking similarity between the physical distribution of colors and their internal representations. The results demonstrate that the visual system represents color ensembles in a more detailed way than previously thought, coding not only mean and variance but, most surprisingly, the actual shape (uniform or Gaussian) of the distribution of colors in the environment.

Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

KAUST Repository

Liu, Bo

2015-11-11

We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

Design ensemble machine learning model for breast cancer diagnosis.

Science.gov (United States)

Hsieh, Sheau-Ling; Hsieh, Sung-Huai; Cheng, Po-Hsun; Chen, Chi-Huang; Hsu, Kai-Ping; Lee, I-Shun; Wang, Zhenyu; Lai, Feipei

2012-10-01

In this paper, we classify the breast cancer of medical diagnostic data. Information gain has been adapted for feature selections. Neural fuzzy (NF), k-nearest neighbor (KNN), quadratic classifier (QC), each single model scheme as well as their associated, ensemble ones have been developed for classifications. In addition, a combined ensemble model with these three schemes has been constructed for further validations. The experimental results indicate that the ensemble learning performs better than individual single ones. Moreover, the combined ensemble model illustrates the highest accuracy of classifications for the breast cancer among all models.

BEWARE OF...SUPER GLUES!!

CERN Multimedia

2006-01-01

What happened? A number of accidents have occurred with the use of 'Super Glues'. Some individuals have suffered injuries - severe irritation, or skin bonded together - through getting glue on their face and in their eyes. What are the hazards associated with glues? 'Super Glues' (i.e. cyanoacrylates): Are harmful if swallowed and are chemical irritants to the eyes, respiratory system and skin. Present the risk of polymerization (hardening) leading to skin damage. Be careful ! 'Super Glues' can bond to skin and eyes in seconds. Note: Other glues, resins and hardeners are also chemicals and as such can cause serious damage to the skin, eyes, respiratory or digestive tract. (For example: some components can be toxic, harmful, corrosive, sensitizing agents, etc.). How to prevent accidents in the future? Read the Material Safety Data Sheet (MSDS) for all of the glues you work with. Check the label on the container to find out which of the materials you work with are hazardous. Wear the right Per...

Recovery of the SuperTIGER Instrument and Preparations for the Flight of SuperTIGER-2

Science.gov (United States)

Walsh, N. E.; Supertiger Collaboration

2016-03-01

On December 8, 2012, the SuperTIGER (Trans-Iron Galactic Element Recorder) instrument began its long-duration balloon flight from Williams Field, Antarctica. Flying for a record-breaking 55 days at a mean altitude of 125,000 feet, the instrument successfully measured the relative elemental abundances of Galactic cosmic ray nuclei having charge (Z) greater than Z=10, showing very well resolved individual element peaks up to Z=40. The instrument measures particle charge and energy through the combined use of two Cherenkov detectors and three scintillation detectors, and determines particle trajectory with a scintillating fiber hodoscope. After cutdown and two years on the ice, SuperTIGER was successfully recovered in January, 2015. Its detectors and hodoscopes are being tested and refurbished, and are expected to be used again for a second flight, SuperTIGER-2. The second flight is aimed at improving SuperTIGER's already excellent charge resolution as well as at accumulating more data to be combined with that of SuperTIGER for improved statistics. In November 2015, a test of the scintillator saturation effect was performed at CERN using a beam of interacted Pb nuclei to help create more accurate charge reconstruction models that will help resolve elements in the range Z=41 to Z=60. This research was supported by NASA under Grants NNX09AC17G, NNX14AB25G, the Peggy and Steve Fossett Foundation and the McDonnell Center for the Space Sciences at Washington University.

Extension of the GHJW theorem for operator ensembles

International Nuclear Information System (INIS)

Choi, Jeong Woon; Hong, Dowon; Chang, Ku-Young; Chi, Dong Pyo; Lee, Soojoon

2011-01-01

The Gisin-Hughston-Jozsa-Wootters theorem plays an important role in analyzing various theories about quantum information, quantum communication, and quantum cryptography. It means that any purifications on the extended system which yield indistinguishable state ensembles on their subsystem should have a specific local unitary relation. In this Letter, we show that the local relation is also established even when the indistinguishability of state ensembles is extended to that of operator ensembles.

Skill prediction of local weather forecasts based on the ECMWF ensemble

Directory of Open Access Journals (Sweden)

C. Ziehmann

2001-01-01

Full Text Available Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF temperature and wind speed ensemble forecasts at 30 German stations. The results indicate that the population of the ensemble mode provides useful information for the uncertainty in temperature forecasts. The ensemble entropy is a similar good measure. This is not true for the spread if it is simply calculated as the variance of the ensemble members with respect to the ensemble mean. The number of clusters in the C regions is almost unrelated to the local skill. For wind forecasts, the results are less promising.

Ensemble methods for seasonal limited area forecasts

DEFF Research Database (Denmark)

Arritt, Raymond W.; Anderson, Christopher J.; Takle, Eugene S.

2004-01-01

The ensemble prediction methods used for seasonal limited area forecasts were examined by comparing methods for generating ensemble simulations of seasonal precipitation. The summer 1993 model over the north-central US was used as a test case. The four methods examined included the lagged-average...

Creating ensembles of decision trees through sampling

Science.gov (United States)

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

An Efficient Ensemble Learning Method for Gene Microarray Classification

Directory of Open Access Journals (Sweden)

Alireza Osareh

2013-01-01

Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

SuperHILAC

International Nuclear Information System (INIS)

Nemetz, R.; Selph, F.; Barnes, A.C.

1976-01-01

A brief discussion is given of improvements, operations, and research programs at the SuperHILAC. Improvements were made in beam injection, ion sources, and computer control systems. The research efficiency ranged between 70 and 90 percent during most of the year

Sub-Ensemble Coastal Flood Forecasting: A Case Study of Hurricane Sandy

Directory of Open Access Journals (Sweden)

Justin A. Schulte

2017-12-01

Full Text Available In this paper, it is proposed that coastal flood ensemble forecasts be partitioned into sub-ensemble forecasts using cluster analysis in order to produce representative statistics and to measure forecast uncertainty arising from the presence of clusters. After clustering the ensemble members, the ability to predict the cluster into which the observation will fall can be measured using a cluster skill score. Additional sub-ensemble and composite skill scores are proposed for assessing the forecast skill of a clustered ensemble forecast. A recently proposed method for statistically increasing the number of ensemble members is used to improve sub-ensemble probabilistic estimates. Through the application of the proposed methodology to Sandy coastal flood reforecasts, it is demonstrated that statistics computed using only ensemble members belonging to a specific cluster are more representative than those computed using all ensemble members simultaneously. A cluster skill-cluster uncertainty index relationship is identified, which is the cluster analog of the documented spread-skill relationship. Two sub-ensemble skill scores are shown to be positively correlated with cluster forecast skill, suggesting that skillfully forecasting the cluster into which the observation will fall is important to overall forecast skill. The identified relationships also suggest that the number of ensemble members within in each cluster can be used as guidance for assessing the potential for forecast error. The inevitable existence of ensemble member clusters in tidally dominated total water level prediction systems suggests that clustering is a necessary post-processing step for producing representative and skillful total water level forecasts.

Ensemble Bayesian forecasting system Part I: Theory and algorithms

Science.gov (United States)

Herr, Henry D.; Krzysztofowicz, Roman

2015-05-01

The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of

Supersymmetry applied to the spectrum edge of random matrix ensembles

International Nuclear Information System (INIS)

Andreev, A.V.; Simons, B.D.; Taniguchi, N.

1994-01-01

A new matrix ensemble has recently been proposed to describe the transport properties in mesoscopic quantum wires. Both analytical and numerical studies have shown that the ensemble of Laguerre or of chiral random matrices provides a good description of scattering properties in this class of systems. Until now only conventional methods of random matrix theory have been used to study statistical properties within this ensemble. We demonstrate that the supersymmetry method, already employed in the study Dyson ensembles, can be extended to treat this class of random matrix ensembles. In developing this approach we investigate both new, as well as verify known statistical measures. Although we focus on ensembles in which T-invariance is violated our approach lays the foundation for future studies of T-invariant systems. ((orig.))

Two-reduction of the super-KP hierarchy

International Nuclear Information System (INIS)

McArthur, I.N.

1994-01-01

Recursion relations are established for the residues of fractional powers of a two-reduced super-KP operator making use of the Baker-Akhiezer function. These show the integrability of the two-reduced even (or bosonic) flows of the super-KP hierarchy. Similar recursion relations are also proven for the residues of operators associated with the odd (or fermionic) flows of the Mulase-Rabin super-KP hierarchy. Due to the presence of a spectral parameter and itts fermionic partner in the Baker-Akhiezer function, these recursion relations should be relevant to any attempt to prove or disprove a recent proposal that the integrable hierarchy underlying two-dimensional quantum supergravity is the Mulase-Rabin super-KP hierarchy. (orig.)

Super-resolution imaging applied to moving object tracking

Science.gov (United States)

Swalaganata, Galandaru; Ratna Sulistyaningrum, Dwi; Setiyono, Budi

2017-10-01

Moving object tracking in a video is a method used to detect and analyze changes that occur in an object that being observed. Visual quality and the precision of the tracked target are highly wished in modern tracking system. The fact that the tracked object does not always seem clear causes the tracking result less precise. The reasons are low quality video, system noise, small object, and other factors. In order to improve the precision of the tracked object especially for small object, we propose a two step solution that integrates a super-resolution technique into tracking approach. First step is super-resolution imaging applied into frame sequences. This step was done by cropping the frame in several frame or all of frame. Second step is tracking the result of super-resolution images. Super-resolution image is a technique to obtain high-resolution images from low-resolution images. In this research single frame super-resolution technique is proposed for tracking approach. Single frame super-resolution was a kind of super-resolution that it has the advantage of fast computation time. The method used for tracking is Camshift. The advantages of Camshift was simple calculation based on HSV color that use its histogram for some condition and color of the object varies. The computational complexity and large memory requirements required for the implementation of super-resolution and tracking were reduced and the precision of the tracked target was good. Experiment showed that integrate a super-resolution imaging into tracking technique can track the object precisely with various background, shape changes of the object, and in a good light conditions.

Modeling task-specific neuronal ensembles improves decoding of grasp

Science.gov (United States)

Smith, Ryan J.; Soares, Alcimar B.; Rouse, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

2018-06-01

Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more

Improving Climate Projections Using "Intelligent" Ensembles

Science.gov (United States)

Baker, Noel C.; Taylor, Patrick C.

2015-01-01

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and

Mapping ionospheric backscatter measured by the SuperDARN HF radars – Part 2: Assessing SuperDARN virtual height models

Directory of Open Access Journals (Sweden)

T. K. Yeoman

2008-05-01

Full Text Available The Super Dual Auroral Radar Network (SuperDARN network of HF coherent backscatter radars form a unique global diagnostic of large-scale ionospheric and magnetospheric dynamics in the Northern and Southern Hemispheres. Currently the ground projections of the HF radar returns are routinely determined by a simple rangefinding algorithm, which takes no account of the prevailing, or indeed the average, HF propagation conditions. This is in spite of the fact that both direct E- and F-region backscatter and 1½-hop E- and F-region backscatter are commonly used in geophysical interpretation of the data. In a companion paper, Chisham et al. (2008 have suggested a new virtual height model for SuperDARN, based on average measured propagation paths. Over shorter propagation paths the existing rangefinding algorithm is adequate, but mapping errors become significant for longer paths where the roundness of the Earth becomes important, and a correct assumption of virtual height becomes more difficult. The SuperDARN radar at Hankasalmi has a propagation path to high power HF ionospheric modification facilities at both Tromsø on a ½-hop path and SPEAR on a 1½-hop path. The SuperDARN radar at Þykkvibǽr has propagation paths to both facilities over 1½-hop paths. These paths provide an opportunity to quantitatively test the available SuperDARN virtual height models. It is also possible to use HF radar backscatter which has been artificially induced by the ionospheric heaters as an accurate calibration point for the Hankasalmi elevation angle of arrival data, providing a range correction algorithm for the SuperDARN radars which directly uses elevation angle. These developments enable the accurate mappings of the SuperDARN electric field measurements which are required for the growing number of multi-instrument studies of the Earth's ionosphere and magnetosphere.

Super-leadership and work enjoyment: direct and moderated influences.

Science.gov (United States)

Müller, Günter F; Georgianna, Sibylle; Schermelleh-Engel, Karin; Roth, Anne C; Schreiber, Walter A; Sauerland, Martin; Muessigmann, Michael J; Jilg, Franziska

2013-12-01

Super-leadership is part of an approach called 'empowering leadership.' Within this approach, super-leadership is assumed to enable subordinates to lead themselves. The current study examined correlates of super-leadership. A questionnaire measuring two dimensions of super-leadership was used to analyze relationships between super-leadership and subordinates' work enjoyment, i.e., job satisfaction, subjective well-being, and emotional organizational commitment. In addition, moderating effects of the organizational context, i.e., organizational decentralization, on the relationships between super-leadership and work enjoyment were explored. 198 German employees from different occupations participated in the study. Latent moderator structural equation analysis revealed that the two factors of super-leadership, "coaching and communicative support" and "facilitation of personal autonomy and responsibility," had direct positive effects on subordinates' work enjoyment. Organizational decentralization moderated the effect of "coaching and communicative support" on work enjoyment but not the relations involving "facilitation of personal autonomy and responsibility." Conclusions for further research and practical applications were discussed.

Optimal super dense coding over memory channels

OpenAIRE

Shadman, Zahra; Kampermann, Hermann; Macchiavello, Chiara; Bruß, Dagmar

2011-01-01

We study the super dense coding capacity in the presence of quantum channels with correlated noise. We investigate both the cases of unitary and non-unitary encoding. Pauli channels for arbitrary dimensions are treated explicitly. The super dense coding capacity for some special channels and resource states is derived for unitary encoding. We also provide an example of a memory channel where non-unitary encoding leads to an improvement in the super dense coding capacity.

Generation of scenarios from calibrated ensemble forecasts with a dual ensemble copula coupling approach

DEFF Research Database (Denmark)

Ben Bouallègue, Zied; Heppelmann, Tobias; Theis, Susanne E.

2016-01-01

the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error. The new...... approach, called d-ECC, is applied to wind forecasts from the high resolution ensemble system COSMO-DE-EPS run operationally at the German weather service. Scenarios generated by ECC and d-ECC are compared and assessed in the form of time series by means of multivariate verification tools and in a product...

Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles

Science.gov (United States)

Treue, Stefan

2018-01-01

Abstract Single neurons in the primate lateral prefrontal cortex (LPFC) encode information about the allocation of visual attention and the features of visual stimuli. However, how this compares to the performance of neuronal ensembles at encoding the same information is poorly understood. Here, we recorded the responses of neuronal ensembles in the LPFC of two macaque monkeys while they performed a task that required attending to one of two moving random dot patterns positioned in different hemifields and ignoring the other pattern. We found single units selective for the location of the attended stimulus as well as for its motion direction. To determine the coding of both variables in the population of recorded units, we used a linear classifier and progressively built neuronal ensembles by iteratively adding units according to their individual performance (best single units), or by iteratively adding units based on their contribution to the ensemble performance (best ensemble). For both methods, ensembles of relatively small sizes (n decoding performance relative to individual single units. However, the decoder reached similar performance using fewer neurons with the best ensemble building method compared with the best single units method. Our results indicate that neuronal ensembles within the LPFC encode more information about the attended spatial and nonspatial features of visual stimuli than individual neurons. They further suggest that efficient coding of attention can be achieved by relatively small neuronal ensembles characterized by a certain relationship between signal and noise correlation structures. PMID:29568798

Super-insulation

International Nuclear Information System (INIS)

Gerold, J.

1985-01-01

The invention concerns super-insulation, which also acts as spacing between two pressurized surfaces, where the crossing bars in at least two layers are provided, with interposed foil. The super-insulation is designed so that it can take compression forces and limits thermal radiation and thermal conduction sufficiently, where the total density of heat flow is usually limited to a few watts per m 2 . The solution to the problem is characterized by the fact that the bars per layer are parallel and from layer to layer they are at an angle to each other and the crossover positions of the bars of different layers are at fixed places and so form contact columns. The basic idea is that bars crossing over each other to support compression forces are used so that contact columns are formed, which are compressed to a certain extent by the load. (orig./PW) [de

The Qualitative Scoring MMSE Pentagon Test (QSPT: A New Method for Differentiating Dementia with Lewy Body from Alzheimer’s Disease

Directory of Open Access Journals (Sweden)

Paolo Caffarra

2013-01-01

Full Text Available The differential diagnosis across different variants of degenerative diseases is sometimes controversial. This study aimed to validate a qualitative scoring method for the pentagons copy test (QSPT of Mini-Mental State Examination (MMSE based on the assessment of different parameters of the pentagons drawing, such as number of angles, distance/intersection, closure/opening, rotation, closing-in, and to verify its efficacy to differentiate dementia with Lewy Body (DLB from Alzheimer's disease (AD. We established the reliability of the qualitative scoring method through the inter-raters and intra-subjects analysis. QSPT was then applied to forty-six AD and forty-six DLB patients, using two phases statistical approach, standard and artificial neural network respectively. DLB patients had significant lower total score in the copy of pentagons and number of angles, distance/intersection, closure/opening, rotation compared to AD. However the logistic regression did not allow to establish any suitable modeling, whereas using Auto-Contractive Map (Auto-CM the DLB was more strongly associated with low scores in some qualitative parameters of pentagon copying, i.e. number of angles and opening/closure and, for the remaining subitems of the MMSE, in naming, repetition and written comprehension, and for demographic variables of gender (male and education (6–13 years. Twist system modeling showed that the QSPT had a good sensitivity (70.29% and specificity (78.67% (ROC-AUC 0.74. The proposed qualitative method of assessment of pentagons copying used in combination with non-linear analysis, showed to be consistent and effective in the differential diagnosis between Lewy Body and Alzheimer’s dementia.

Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

Directory of Open Access Journals (Sweden)

Jinyin Ye

2016-01-01

Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

Three-model ensemble wind prediction in southern Italy

Science.gov (United States)

Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo

2016-03-01

Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

Characterising Super-Earths

Directory of Open Access Journals (Sweden)

Valencia D.

2011-02-01

Full Text Available The era of Super-Earths has formally begun with the detection of transiting low-mass exoplanets CoRoT-7b and GJ 1214b. In the path of characterising super-Earths, the first step is to infer their composition. While the discovery data for CoRoT-7b, in combination with the high atmospheric mass loss rate inferred from the high insolation, suggested that it was a rocky planet, the new proposed mass values have widened the possibilities. The combined mass range 1−10 M⊕ allows for a volatile-rich (and requires it if the mass is less than 4 M⊕ , an Earth-like or a super-Mercury-like composition. In contrast, the radius of GJ 1214b is too large to admit a solid composition, thus it necessarily to have a substantial gas layer. Some evidence suggests that within this gas layer H/He is a small but non-negligible component. These two planets are the first of many transiting low-mass exoplanets expected to be detected and they exemplify the limitations faced when inferring composition, which come from the degenerate character of the problem and the large error bars in the data.

Global Ensemble Forecast System (GEFS) [2.5 Deg.

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

On-line Learning of Unlearnable True Teacher through Mobile Ensemble Teachers

Science.gov (United States)

Hirama, Takeshi; Hukushima, Koji

2008-09-01

The on-line learning of a hierarchical learning model is studied by a method based on statistical mechanics. In our model, a student of a simple perceptron learns from not a true teacher directly, but ensemble teachers who learn from a true teacher with a perceptron learning rule. Since the true teacher and ensemble teachers are expressed as nonmonotonic and simple perceptrons, respectively, the ensemble teachers go around the unlearnable true teacher with the distance between them fixed in an asymptotic steady state. The generalization performance of the student is shown to exceed that of the ensemble teachers in a transient state, as was shown in similar ensemble-teachers models. Furthermore, it is found that moving the ensemble teachers even in the steady state, in contrast to the fixed ensemble teachers, is efficient for the performance of the student.

An ensemble classifier to predict track geometry degradation

International Nuclear Information System (INIS)

Cárdenas-Gallo, Iván; Sarmiento, Carlos A.; Morales, Gilberto A.; Bolivar, Manuel A.; Akhavan-Tabatabaei, Raha

2017-01-01

Railway operations are inherently complex and source of several problems. In particular, track geometry defects are one of the leading causes of train accidents in the United States. This paper presents a solution approach which entails the construction of an ensemble classifier to forecast the degradation of track geometry. Our classifier is constructed by solving the problem from three different perspectives: deterioration, regression and classification. We considered a different model from each perspective and our results show that using an ensemble method improves the predictive performance. - Highlights: • We present an ensemble classifier to forecast the degradation of track geometry. • Our classifier considers three perspectives: deterioration, regression and classification. • We construct and test three models and our results show that using an ensemble method improves the predictive performance.

Neural Network Ensembles

DEFF Research Database (Denmark)

Hansen, Lars Kai; Salamon, Peter

1990-01-01

We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

Charm Physics at SuperB

International Nuclear Information System (INIS)

Meadows, Brian; Bevan, Adrian

2010-01-01

The study of Charm Decays at SuperB provide unique opportunities to understand the Standard Model and constrain new physics, both at the Y(4S), and at charm threshold. We discuss the physics potential of such measurements from the proposed SuperB experiment with 75 ab -1 of data at the Y(4S) and a subsequent run dedicated to exploiting quantum correlations at the charm threshold. (author)

NETL Super Computer

Data.gov (United States)

Federal Laboratory Consortium — The NETL Super Computer was designed for performing engineering calculations that apply to fossil energy research. It is one of the world’s larger supercomputers,...

Development of a regional ensemble prediction method for probabilistic weather prediction

International Nuclear Information System (INIS)

Nohara, Daisuke; Tamura, Hidetoshi; Hirakuchi, Hiromaru

2015-01-01

A regional ensemble prediction method has been developed to provide probabilistic weather prediction using a numerical weather prediction model. To obtain consistent perturbations with the synoptic weather pattern, both of initial and lateral boundary perturbations were given by differences between control and ensemble member of the Japan Meteorological Agency (JMA)'s operational one-week ensemble forecast. The method provides a multiple ensemble member with a horizontal resolution of 15 km for 48-hour based on a downscaling of the JMA's operational global forecast accompanied with the perturbations. The ensemble prediction was examined in the case of heavy snow fall event in Kanto area on January 14, 2013. The results showed that the predictions represent different features of high-resolution spatiotemporal distribution of precipitation affected by intensity and location of extra-tropical cyclone in each ensemble member. Although the ensemble prediction has model bias of mean values and variances in some variables such as wind speed and solar radiation, the ensemble prediction has a potential to append a probabilistic information to a deterministic prediction. (author)

The Use of Artificial-Intelligence-Based Ensembles for Intrusion Detection: A Review

Directory of Open Access Journals (Sweden)

Gulshan Kumar

2012-01-01

Full Text Available In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI- based techniques play prominent role in development of ensemble for intrusion detection (ID and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1 architecture & approach followed; (2 different methods utilized in different phases of ensemble learning; (3 other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs.

Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.

Science.gov (United States)

Kelly, David; Majda, Andrew J; Tong, Xin T

2015-08-25

The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.

Microsphere-based super-resolution scanning optical microscope.

Science.gov (United States)

Huszka, Gergely; Yang, Hui; Gijs, Martin A M

2017-06-26

High-refractive index dielectric microspheres positioned within the field of view of a microscope objective in a dielectric medium can focus the light into a so-called photonic nanojet. A sample placed in such nanojet can be imaged by the objective with super-resolution, i.e. with a resolution beyond the classical diffraction limit. However, when imaging nanostructures on a substrate, the propagation distance of a light wave in the dielectric medium in between the substrate and the microsphere must be small enough to reveal the sample's nanometric features. Therefore, only the central part of an image obtained through a microsphere shows super-resolution details, which are typically ∼100 nm using white light (peak at λ = 600 nm). We have performed finite element simulations of the role of this critical distance in the super-resolution effect. Super-resolution imaging of a sample placed beneath the microsphere is only possible within a very restricted central area of ∼10 μm 2 , where the separation distance between the substrate and the microsphere surface is very small (∼1 μm). To generate super-resolution images over larger areas of the sample, we have fixed a microsphere on a frame attached to the microscope objective, which is automatically scanned over the sample in a step-by-step fashion. This generates a set of image tiles, which are subsequently stitched into a single super-resolution image (with resolution of λ/4-λ/5) of a sample area of up to ∼10 4 μm 2 . Scanning a standard optical microscope objective with microsphere therefore enables super-resolution microscopy over the complete field-of-view of the objective.

The SuperB Project: Status and the Physics Reach

International Nuclear Information System (INIS)

Neri, Nicola

2012-01-01

The SuperB experiment is a next generation Super Flavour Factory expected to accumulate 75 ab −1 of data at the Υ(4S) in five years of nominal running, and will be built at the recently established Cabibbo Laboratory on the outskirts of Rome. In addition to running data at the Υ(4S), SuperB will be able to accumulate data from the ψ(3770) up to the Υ(6S). A polarized electron beam enables unique physics opportunities at SuperB. The large samples of B, D and τ decays that will be recorded at SuperB can be used to provide both stringent constraints on new physics scenarios, and over-constraints on the Standard Model. We present the status of the project as well as the physics potential of SuperB.

Super-resolution

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2014-01-01

Super-resolution, the process of obtaining one or more high-resolution images from one or more low-resolution observations, has been a very attractive research topic over the last two decades. It has found practical applications in many real world problems in different fields, from satellite...

Quark ensembles with infinite correlation length

OpenAIRE

Molodtsov, S. V.; Zinovjev, G. M.

2014-01-01

By studying quark ensembles with infinite correlation length we formulate the quantum field theory model that, as we show, is exactly integrable and develops an instability of its standard vacuum ensemble (the Dirac sea). We argue such an instability is rooted in high ground state degeneracy (for 'realistic' space-time dimensions) featuring a fairly specific form of energy distribution, and with the cutoff parameter going to infinity this inherent energy distribution becomes infinitely narrow...

A multi-model ensemble approach to seabed mapping

Science.gov (United States)

Diesing, Markus; Stephens, David

2015-06-01

Seabed habitat mapping based on swath acoustic data and ground-truth samples is an emergent and active marine science discipline. Significant progress could be achieved by transferring techniques and approaches that have been successfully developed and employed in such fields as terrestrial land cover mapping. One such promising approach is the multiple classifier system, which aims at improving classification performance by combining the outputs of several classifiers. Here we present results of a multi-model ensemble applied to multibeam acoustic data covering more than 5000 km2 of seabed in the North Sea with the aim to derive accurate spatial predictions of seabed substrate. A suite of six machine learning classifiers (k-Nearest Neighbour, Support Vector Machine, Classification Tree, Random Forest, Neural Network and Naïve Bayes) was trained with ground-truth sample data classified into seabed substrate classes and their prediction accuracy was assessed with an independent set of samples. The three and five best performing models were combined to classifier ensembles. Both ensembles led to increased prediction accuracy as compared to the best performing single classifier. The improvements were however not statistically significant at the 5% level. Although the three-model ensemble did not perform significantly better than its individual component models, we noticed that the five-model ensemble did perform significantly better than three of the five component models. A classifier ensemble might therefore be an effective strategy to improve classification performance. Another advantage is the fact that the agreement in predicted substrate class between the individual models of the ensemble could be used as a measure of confidence. We propose a simple and spatially explicit measure of confidence that is based on model agreement and prediction accuracy.

Critical Listening in the Ensemble Rehearsal: A Community of Learners

Science.gov (United States)

Bell, Cindy L.

2018-01-01

This article explores a strategy for engaging ensemble members in critical listening analysis of performances and presents opportunities for improving ensemble sound through rigorous dialogue, reflection, and attentive rehearsing. Critical listening asks ensemble members to draw on individual playing experience and knowledge to describe what they…

SVM and SVM Ensembles in Breast Cancer Prediction.

Science.gov (United States)

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

SVM and SVM Ensembles in Breast Cancer Prediction.

Directory of Open Access Journals (Sweden)

Min-Wei Huang

Full Text Available Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

Ensemble Data Mining Methods

Data.gov (United States)

National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...

FPGA-based quench detection system for super-FRS super-ferric dipole prototype

International Nuclear Information System (INIS)

Yang Tongjun; Wu Wei; Yao Qinggao; Yuan Ping; He Yuan; Han Shaofei; Ma Lizhen

2011-01-01

The quench detection system for Super-FRS super-ferric dipole prototype magnet of FAIR has been designed and built. The balance bridge was used to detect quench signal. In order to avoid blind zone of quench detection, two independent bridges were used. NI PXI-7830R FPGA was used to implement filter to quench signal and algorithm of quench decision and to produce quench trigger signal. Pre-sample technique was used in quench data acquisition. The data before and after quench could be recorded for analysis later. The test result indicated that the quench of the dipole's superconducting coil could be reliably detected by the quench detection module. (authors)

Ensemble Network Architecture for Deep Reinforcement Learning

Directory of Open Access Journals (Sweden)

Xi-liang Chen

2018-01-01

Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.

Shallow cumuli ensemble statistics for development of a stochastic parameterization

Science.gov (United States)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a

Selecting a climate model subset to optimise key ensemble properties

Directory of Open Access Journals (Sweden)

N. Herger

2018-02-01

Full Text Available End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

Selecting a climate model subset to optimise key ensemble properties

Science.gov (United States)

Herger, Nadja; Abramowitz, Gab; Knutti, Reto; Angélil, Oliver; Lehmann, Karsten; Sanderson, Benjamin M.

2018-02-01

End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

On evaluation of ensemble precipitation forecasts with observation-based ensembles

Directory of Open Access Journals (Sweden)

S. Jaun

2007-04-01

Full Text Available Spatial interpolation of precipitation data is uncertain. How important is this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation forecasts? These questions are discussed by experimental evaluation of the COSMO consortium's limited-area ensemble prediction system COSMO-LEPS. The applied performance measure is the often used Brier skill score (BSS. The observational references in the evaluation are (a analyzed rain gauge data by ordinary Kriging and (b ensembles of interpolated rain gauge data by stochastic simulation. This permits the consideration of either a deterministic reference (the event is observed or not with 100% certainty or a probabilistic reference that makes allowance for uncertainties in spatial averaging. The evaluation experiments show that the evaluation uncertainties are substantial even for the large area (41 300 km2 of Switzerland with a mean rain gauge distance as good as 7 km: the one- to three-day precipitation forecasts have skill decreasing with forecast lead time but the one- and two-day forecast performances differ not significantly.

Polarized ensembles of random pure states

Science.gov (United States)

Deelan Cunden, Fabio; Facchi, Paolo; Florio, Giuseppe

2013-08-01

A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise.

Oblique reconstructions in tomosynthesis. II. Super-resolution

International Nuclear Information System (INIS)

Acciavatti, Raymond J.; Maidment, Andrew D. A.

2013-01-01

Purpose: In tomosynthesis, super-resolution has been demonstrated using reconstruction planes parallel to the detector. Super-resolution allows for subpixel resolution relative to the detector. The purpose of this work is to develop an analytical model that generalizes super-resolution to oblique reconstruction planes.Methods: In a digital tomosynthesis system, a sinusoidal test object is modeled along oblique angles (i.e., “pitches”) relative to the plane of the detector in a 3D divergent-beam acquisition geometry. To investigate the potential for super-resolution, the input frequency is specified to be greater than the alias frequency of the detector. Reconstructions are evaluated in an oblique plane along the extent of the object using simple backprojection (SBP) and filtered backprojection (FBP). By comparing the amplitude of the reconstruction against the attenuation coefficient of the object at various frequencies, the modulation transfer function (MTF) is calculated to determine whether modulation is within detectable limits for super-resolution. For experimental validation of super-resolution, a goniometry stand was used to orient a bar pattern phantom along various pitches relative to the breast support in a commercial digital breast tomosynthesis system.Results: Using theoretical modeling, it is shown that a single projection image cannot resolve a sine input whose frequency exceeds the detector alias frequency. The high frequency input is correctly visualized in SBP or FBP reconstruction using a slice along the pitch of the object. The Fourier transform of this reconstructed slice is maximized at the input frequency as proof that the object is resolved. Consistent with the theoretical results, experimental images of a bar pattern phantom showed super-resolution in oblique reconstructions. At various pitches, the highest frequency with detectable modulation was determined by visual inspection of the bar patterns. The dependency of the highest

Oblique reconstructions in tomosynthesis. II. Super-resolution

Science.gov (United States)

Acciavatti, Raymond J.; Maidment, Andrew D. A.

2013-01-01

Purpose: In tomosynthesis, super-resolution has been demonstrated using reconstruction planes parallel to the detector. Super-resolution allows for subpixel resolution relative to the detector. The purpose of this work is to develop an analytical model that generalizes super-resolution to oblique reconstruction planes. Methods: In a digital tomosynthesis system, a sinusoidal test object is modeled along oblique angles (i.e., “pitches”) relative to the plane of the detector in a 3D divergent-beam acquisition geometry. To investigate the potential for super-resolution, the input frequency is specified to be greater than the alias frequency of the detector. Reconstructions are evaluated in an oblique plane along the extent of the object using simple backprojection (SBP) and filtered backprojection (FBP). By comparing the amplitude of the reconstruction against the attenuation coefficient of the object at various frequencies, the modulation transfer function (MTF) is calculated to determine whether modulation is within detectable limits for super-resolution. For experimental validation of super-resolution, a goniometry stand was used to orient a bar pattern phantom along various pitches relative to the breast support in a commercial digital breast tomosynthesis system. Results: Using theoretical modeling, it is shown that a single projection image cannot resolve a sine input whose frequency exceeds the detector alias frequency. The high frequency input is correctly visualized in SBP or FBP reconstruction using a slice along the pitch of the object. The Fourier transform of this reconstructed slice is maximized at the input frequency as proof that the object is resolved. Consistent with the theoretical results, experimental images of a bar pattern phantom showed super-resolution in oblique reconstructions. At various pitches, the highest frequency with detectable modulation was determined by visual inspection of the bar patterns. The dependency of the highest

An automated approach to network features of protein structure ensembles

Science.gov (United States)

Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi

2013-01-01

Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html. PMID:23934896

Super-cool Dark Matter arXiv

CERN Document Server

Hambye, Thomas; Teresi, Daniele

In dimension-less theories of dynamical generation of the weak scale, the Universe can undergo a period of low-scale inflation during which all particles are massless and super-cool. This leads to a new mechanism of generation of the cosmological Dark Matter (DM) relic density: super-cooling can easily suppress the amount of DM to the desired level. This is achieved for TeV-scale DM, if super-cooling ends when quark condensates form at the QCD phase transition. Along this scenario, the baryon asymmetry can be generated either at the phase transition or through leptogenesis. We show that the above mechanism takes place in old and new dimension-less models.

A note on the super AKNS equations

International Nuclear Information System (INIS)

Li Yishen; Zhang Lining.

1986-10-01

We find some relationships between the usual AKNS scheme with the super one, when its elements take value from the Grassmann algebra on a two-dimensional vector space. The solutions of these super AKNS equations are discussed. (author)

N=2 super - W3(2) algebra in superfields

International Nuclear Information System (INIS)

Krivonos, S.; Sorin, A.

1995-05-01

It is presented a manifestly N=2 supersymmetric formulation of N=2 super-W 3 (2) algebra (its classical version) in terms of the spin 1 unconstrained generating a N=2 superconformal subalgebra and the spins 1/2, 2 fermionic constrained supercurrents. It is considered a superfield reduction of N=2 super-W 3 (2) to N=2 super-W 3 and construct a family of evolution equations for which N=2 super-W 3 (2) provides the second Hamiltonian structure

Exact solution of super Liouville model

International Nuclear Information System (INIS)

Yang Zhanying; Zhao Liu; Zhen Yi

2000-01-01

Using Leznov-Saveliev algebraic analysis and Drinfeld-Sokolov construction, the authors obtained the explicit solutions to the super Liouville system in super covariant form and component form. The explicit solution in component form reduces naturally into the Egnchi-Hanson instanton solution of the usual Liouville equation if all the Grassmann odd components are set equal to zero

Developing an Ensemble Prediction System based on COSMO-DE

Science.gov (United States)

Theis, S.; Gebhardt, C.; Buchhold, M.; Ben Bouallègue, Z.; Ohl, R.; Paulat, M.; Peralta, C.

2010-09-01

The numerical weather prediction model COSMO-DE is a configuration of the COSMO model with a horizontal grid size of 2.8 km. It has been running operationally at DWD since 2007, it covers the area of Germany and produces forecasts with a lead time of 0-21 hours. The model COSMO-DE is convection-permitting, which means that it does without a parametrisation of deep convection and simulates deep convection explicitly. One aim is an improved forecast of convective heavy rain events. Convection-permitting models are in operational use at several weather services, but currently not in ensemble mode. It is expected that an ensemble system could reveal the advantages of a convection-permitting model even better. The probabilistic approach is necessary, because the explicit simulation of convective processes for more than a few hours cannot be viewed as a deterministic forecast anymore. This is due to the chaotic behaviour and short life cycle of the processes which are simulated explicitly now. In the framework of the project COSMO-DE-EPS, DWD is developing and implementing an ensemble prediction system (EPS) for the model COSMO-DE. The project COSMO-DE-EPS comprises the generation of ensemble members, as well as the verification and visualization of the ensemble forecasts and also statistical postprocessing. A pre-operational mode of the EPS with 20 ensemble members is foreseen to start in 2010. Operational use is envisaged to start in 2012, after an upgrade to 40 members and inclusion of statistical postprocessing. The presentation introduces the project COSMO-DE-EPS and describes the design of the ensemble as it is planned for the pre-operational mode. In particular, the currently implemented method for the generation of ensemble members will be explained and discussed. The method includes variations of initial conditions, lateral boundary conditions, and model physics. At present, pragmatic methods are applied which resemble the basic ideas of a multi-model approach

Siting the superconducting super collider

International Nuclear Information System (INIS)

Price, R.; Rooney, R.C.

1988-01-01

At the request of the Department of Energy, the National Academy of Sciences and the National Academy of Engineering established the Super Collider Site Evaluation Committee to evaluate the suitability of proposed sites for the Superconducting Super Collider. Thirty-six proposals were examined by the committee. Using the set of criteria announced by DOE in its Invitation for Site Proposals, the committee identified eight sites that merited inclusion on a ''best qualified list.'' The list represents the best collective judgment of 21 individuals, carefully chosen for their expertise and impartiality, after a detailed assessment of the proposals using 19 technical subcriteria and DOE's life cycle cost estimates. The sites, in alphabetical order, are: Arizona/Maricopa; Colorado; Illinois; Michigan/Stockbridge; New York/Rochester; North Carolina; Tennessee; and Texas/Dallas-Fort Worth. The evaluation of these sites and the Superconducting Super Collider are discussed in this book

The Hydrologic Ensemble Prediction Experiment (HEPEX)

Science.gov (United States)

Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena

2015-04-01

The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (www.hepex.org), HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

Ensemble-based forecasting at Horns Rev: Ensemble conversion and kernel dressing

DEFF Research Database (Denmark)

Pinson, Pierre; Madsen, Henrik

. The obtained ensemble forecasts of wind power are then converted into predictive distributions with an original adaptive kernel dressing method. The shape of the kernels is driven by a mean-variance model, the parameters of which are recursively estimated in order to maximize the overall skill of obtained...

Lattice gauge theory in the microcanonical ensemble

International Nuclear Information System (INIS)

Callaway, D.J.E.; Rahman, A.

1983-01-01

The microcanonical-ensemble formulation of lattice gauge theory proposed recently is examined in detail. Expectation values in this new ensemble are determined by solving a large set of coupled ordinary differential equations, after the fashion of a molecular dynamics simulation. Following a brief review of the microcanonical ensemble, calculations are performed for the gauge groups U(1), SU(2), and SU(3). The results are compared and contrasted with standard methods of computation. Several advantages of the new formalism are noted. For example, no random numbers are required to update the system. Also, this update is performed in a simultaneous fashion. Thus the microcanonical method presumably adapts well to parallel processing techniques, especially when the p action is highly nonlocal (such as when fermions are included)

Exploring and Listening to Chinese Classical Ensembles in General Music

Science.gov (United States)

Zhang, Wenzhuo

2017-01-01

Music diversity is valued in theory, but the extent to which it is efficiently presented in music class remains limited. Within this article, I aim to bridge this gap by introducing four genres of Chinese classical ensembles--Qin and Xiao duets, Jiang Nan bamboo and silk ensembles, Cantonese ensembles, and contemporary Chinese orchestras--into the…

Polarized ensembles of random pure states

International Nuclear Information System (INIS)

Cunden, Fabio Deelan; Facchi, Paolo; Florio, Giuseppe

2013-01-01

A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise. (paper)

Probabilistic Determination of Native State Ensembles of Proteins

DEFF Research Database (Denmark)

Olsson, Simon; Vögeli, Beat Rolf; Cavalli, Andrea

2014-01-01

ensembles of proteins by the combination of physical force fields and experimental data through modern statistical methodology. As an example, we use NMR residual dipolar couplings to determine a native state ensemble of the extensively studied third immunoglobulin binding domain of protein G (GB3...

Ensembles of a small number of conformations with relative populations

Energy Technology Data Exchange (ETDEWEB)

Vammi, Vijay, E-mail: vsvammi@iastate.edu; Song, Guang, E-mail: gsong@iastate.edu [Iowa State University, Bioinformatics and Computational Biology Program, Department of Computer Science (United States)

2015-12-15

In our previous work, we proposed a new way to represent protein native states, using ensembles of a small number of conformations with relative Populations, or ESP in short. Using Ubiquitin as an example, we showed that using a small number of conformations could greatly reduce the potential of overfitting and assigning relative populations to protein ensembles could significantly improve their quality. To demonstrate that ESP indeed is an excellent alternative to represent protein native states, in this work we compare the quality of two ESP ensembles of Ubiquitin with several well-known regular ensembles or average structure representations. Extensive amount of significant experimental data are employed to achieve a thorough assessment. Our results demonstrate that ESP ensembles, though much smaller in size comparing to regular ensembles, perform equally or even better sometimes in all four different types of experimental data used in the assessment, namely, the residual dipolar couplings, residual chemical shift anisotropy, hydrogen exchange rates, and solution scattering profiles. This work further underlines the significance of having relative populations in describing the native states.

On the proper use of Ensembles for Predictive Uncertainty assessment

Science.gov (United States)

Todini, Ezio; Coccia, Gabriele; Ortiz, Enrique

2015-04-01

Probabilistic forecasting has become popular in the last decades. Hydrological probabilistic forecasts have been based either on uncertainty processors (Krzysztofowic, 1999; Todini, 2004; Todini, 2008) or on ensembles, following meteorological traditional approaches and the establishment of the HEPEX program (http://hepex.irstea.fr. Unfortunately, the direct use of ensembles as a measure of the predictive density is an incorrect practice, because the ensemble measures the spread of the forecast instead of, following the definition of predictive uncertainty, the conditional probability of the future outcome conditional on the forecast. Only few correct approaches are reported in the literature, which correctly use the ensemble to estimate an expected conditional predictive density (Reggiani et al., 2009), similarly to what is done when several predictive models are available as in the BMA (Raftery et al., 2005) or MCP(Todini, 2008; Coccia and Todini, 2011) approaches. A major problem, limiting the correct use of ensembles, is in fact the difficulty of defining the time dependence of the ensemble members, due to the lack of a consistent ranking: in other words, when dealing with multiple models, the ith model remains the ith model regardless to the time of forecast, while this does not happen when dealing with ensemble members, since there is no definition for the ith member of an ensemble. Nonetheless, the MCP approach (Todini, 2008; Coccia and Todini, 2011), essentially based on a multiple regression in the Normal space, can be easily extended to use ensembles to represent the local (in time) smaller or larger conditional predictive uncertainty, as a function of the ensemble spread. This is done by modifying the classical linear regression equations, impliying perfectly observed predictors, to alternative regression equations similar to the Kalman filter ones, allowing for uncertain predictors. In this way, each prediction in time accounts for both the predictive

Ensemble Kalman filtering with one-step-ahead smoothing

KAUST Repository

Raboudi, Naila F.

2018-01-11

The ensemble Kalman filter (EnKF) is widely used for sequential data assimilation. It operates as a succession of forecast and analysis steps. In realistic large-scale applications, EnKFs are implemented with small ensembles and poorly known model error statistics. This limits their representativeness of the background error covariances and, thus, their performance. This work explores the efficiency of the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem to enhance the data assimilation performance of EnKFs. Filtering with OSA smoothing introduces an updated step with future observations, conditioning the ensemble sampling with more information. This should provide an improved background ensemble in the analysis step, which may help to mitigate the suboptimal character of EnKF-based methods. Here, the authors demonstrate the efficiency of a stochastic EnKF with OSA smoothing for state estimation. They then introduce a deterministic-like EnKF-OSA based on the singular evolutive interpolated ensemble Kalman (SEIK) filter. The authors show that the proposed SEIK-OSA outperforms both SEIK, as it efficiently exploits the data twice, and the stochastic EnKF-OSA, as it avoids observational error undersampling. They present extensive assimilation results from numerical experiments conducted with the Lorenz-96 model to demonstrate SEIK-OSA’s capabilities.

Universal critical wrapping probabilities in the canonical ensemble

Directory of Open Access Journals (Sweden)

Hao Hu

2015-09-01

Full Text Available Universal dimensionless quantities, such as Binder ratios and wrapping probabilities, play an important role in the study of critical phenomena. We study the finite-size scaling behavior of the wrapping probability for the Potts model in the random-cluster representation, under the constraint that the total number of occupied bonds is fixed, so that the canonical ensemble applies. We derive that, in the limit L→∞, the critical values of the wrapping probability are different from those of the unconstrained model, i.e. the model in the grand-canonical ensemble, but still universal, for systems with 2yt−d>0 where yt=1/ν is the thermal renormalization exponent and d is the spatial dimension. Similar modifications apply to other dimensionless quantities, such as Binder ratios. For systems with 2yt−d≤0, these quantities share same critical universal values in the two ensembles. It is also derived that new finite-size corrections are induced. These findings apply more generally to systems in the canonical ensemble, e.g. the dilute Potts model with a fixed total number of vacancies. Finally, we formulate an efficient cluster-type algorithm for the canonical ensemble, and confirm these predictions by extensive simulations.

A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting

International Nuclear Information System (INIS)

Tang, Ling; Yu, Lean; Wang, Shuai; Li, Jianping; Wang, Shouyang

2012-01-01

Highlights: ► A hybrid ensemble learning paradigm integrating EEMD and LSSVR is proposed. ► The hybrid ensemble method is useful to predict time series with high volatility. ► The ensemble method can be used for both one-step and multi-step ahead forecasting. - Abstract: In this paper, a novel hybrid ensemble learning paradigm integrating ensemble empirical mode decomposition (EEMD) and least squares support vector regression (LSSVR) is proposed for nuclear energy consumption forecasting, based on the principle of “decomposition and ensemble”. This hybrid ensemble learning paradigm is formulated specifically to address difficulties in modeling nuclear energy consumption, which has inherently high volatility, complexity and irregularity. In the proposed hybrid ensemble learning paradigm, EEMD, as a competitive decomposition method, is first applied to decompose original data of nuclear energy consumption (i.e. a difficult task) into a number of independent intrinsic mode functions (IMFs) of original data (i.e. some relatively easy subtasks). Then LSSVR, as a powerful forecasting tool, is implemented to predict all extracted IMFs independently. Finally, these predicted IMFs are aggregated into an ensemble result as final prediction, using another LSSVR. For illustration and verification purposes, the proposed learning paradigm is used to predict nuclear energy consumption in China. Empirical results demonstrate that the novel hybrid ensemble learning paradigm can outperform some other popular forecasting models in both level prediction and directional forecasting, indicating that it is a promising tool to predict complex time series with high volatility and irregularity.

The elastic buckling of super-graphene and super-square carbon nanotube networks

International Nuclear Information System (INIS)

Li Ying; Qiu Xinming; Yin Yajun; Yang Fan; Fan Qinshan

2010-01-01

The super-graphene (SG) and super-square (SS) carbon nanotube network are built by the straight single-walled carbon nanotubes and corresponding junctions. The elastic buckling behaviors of these carbon nanotube networks under different boundary conditions are explored through the molecular structural mechanics method. The following results are obtained: (a) The critical buckling forces of the SG and SS networks decrease as the side lengths or aspect ratios of the networks increase. The continuum plate theory could give good predictions to the buckling of the SS network but not the SG network with non-uniform buckling modes. (b) The carbon nanotube networks are more stable structures than the graphene structures with less carbon atoms.

Constructing Better Classifier Ensemble Based on Weighted Accuracy and Diversity Measure

Directory of Open Access Journals (Sweden)

Xiaodong Zeng

2014-01-01

Full Text Available A weighted accuracy and diversity (WAD method is presented, a novel measure used to evaluate the quality of the classifier ensemble, assisting in the ensemble selection task. The proposed measure is motivated by a commonly accepted hypothesis; that is, a robust classifier ensemble should not only be accurate but also different from every other member. In fact, accuracy and diversity are mutual restraint factors; that is, an ensemble with high accuracy may have low diversity, and an overly diverse ensemble may negatively affect accuracy. This study proposes a method to find the balance between accuracy and diversity that enhances the predictive ability of an ensemble for unknown data. The quality assessment for an ensemble is performed such that the final score is achieved by computing the harmonic mean of accuracy and diversity, where two weight parameters are used to balance them. The measure is compared to two representative measures, Kappa-Error and GenDiv, and two threshold measures that consider only accuracy or diversity, with two heuristic search algorithms, genetic algorithm, and forward hill-climbing algorithm, in ensemble selection tasks performed on 15 UCI benchmark datasets. The empirical results demonstrate that the WAD measure is superior to others in most cases.

One-dimensional super Calabi-Yau manifolds and their mirrors

Energy Technology Data Exchange (ETDEWEB)

Noja, S. [Dipartimento di Matematica, Università degli Studi di Milano,Via Saldini 50, I-20133 Milano (Italy); Cacciatori, S.L. [Dipartimento di Scienza e Alta Tecnologia, Università dell’Insubria, Via Valleggio 11, I-22100 Como (Italy); INFN, Sezione di Milano,Via Celoria 16, I-20133 Milano (Italy); Piazza, F. Dalla [Dipartimento di Scienza e Alta Tecnologia, Università dell’Insubria, Via Valleggio 11, I-22100 Como (Italy); Marrani, A. [Centro Studi e Ricerche ‘Enrico Fermi’,Via Panisperna 89A, I-00184 Roma (Italy); Dipartimento di Fisica e Astronomia ‘Galileo Galilei’, Università di Padova,and INFN, Sezione di Padova,Via Marzolo 8, I-35131 Padova (Italy); Re, R. [Dipartimento di Matematica e Informatica, Università degli Studi di Catania,Viale Andrea Doria 6, 95125 Catania (Italy)

2017-04-18

We apply a definition of generalised super Calabi-Yau variety (SCY) to supermanifolds of complex dimension one. One of our results is that there are two SCY’s having reduced manifold equal to ℙ{sup 1}, namely the projective super space ℙ{sup 1|2} and the weighted projective super space Wℙ{sub (2)}{sup 1|1}. Then we compute the corresponding sheaf cohomology of superforms, showing that the cohomology with picture number one is infinite dimensional, while the de Rham cohomology, which is what matters from a physical point of view, remains finite dimensional. Moreover, we provide the complete real and holomorphic de Rham cohomology for generic projective super spaces ℙ{sup n|m}. We also determine the automorphism groups: these always match the dimension of the projective super group with the only exception of ℙ{sup 1|2}, whose automorphism group turns out to be larger than the projective super group. By considering the cohomology of the super tangent sheaf, we compute the deformations of ℙ{sup 1|m}, discovering that the presence of a fermionic structure allows for deformations even if the reduced manifold is rigid. Finally, we show that ℙ{sup 1|2} is self-mirror, whereas Wℙ{sub (2)}{sup 1|1} has a zero dimensional mirror. Also, the mirror map for ℙ{sup 1|2} naturally endows it with a structure of N=2 super Riemann surface.

Visualization and classification of physiological failure modes in ensemble hemorrhage simulation

Science.gov (United States)

Zhang, Song; Pruett, William Andrew; Hester, Robert

2015-01-01

In an emergency situation such as hemorrhage, doctors need to predict which patients need immediate treatment and care. This task is difficult because of the diverse response to hemorrhage in human population. Ensemble physiological simulations provide a means to sample a diverse range of subjects and may have a better chance of containing the correct solution. However, to reveal the patterns and trends from the ensemble simulation is a challenging task. We have developed a visualization framework for ensemble physiological simulations. The visualization helps users identify trends among ensemble members, classify ensemble member into subpopulations for analysis, and provide prediction to future events by matching a new patient's data to existing ensembles. We demonstrated the effectiveness of the visualization on simulated physiological data. The lessons learned here can be applied to clinically-collected physiological data in the future.

75 FR 77670 - SuperMedia, LLC, Formerly Known as Idearc Media, LLC, a Subsidiary of SuperMedia Information...

Science.gov (United States)

2010-12-13

... Known as Idearc Media, LLC, a Subsidiary of SuperMedia Information Services, LLC Publishing Group, Troy... Subsidiary of SuperMedia Information Services, LLC, Troy, New York, to apply for Trade Adjustment Assistance..., Publishing Group, Troy, New York, who became totally or partially separated from employment on or after...

Relation between native ensembles and experimental structures of proteins

DEFF Research Database (Denmark)

Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.

2006-01-01

Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest...... heterogeneity of the native state in solution. We find that different NMR measurements probing structure and dynamics of given proteins in solution, including order parameters, scalar couplings, and residual dipolar couplings, are remarkably well reproduced by their respective high-sequence similarity Protein...

Analysing 'super-participation' in online third spaces

NARCIS (Netherlands)

Graham, Todd; Wright, Scott; Cantijoch, Marta; Gibson, Rachel; Ward, Stephen

2014-01-01

This chapter focuses on our attempts to overcome the methodological challenges of 'super-participation' in online discussion forums, focusing on the participatory patterns and discursive activity of what we call 'super-participants'. Our principal contribution in this area (Graham and Wright 2013)

On the structure and phase transitions of power-law Poissonian ensembles

Science.gov (United States)

Eliazar, Iddo; Oshanin, Gleb

2012-10-01

Power-law Poissonian ensembles are Poisson processes that are defined on the positive half-line, and that are governed by power-law intensities. Power-law Poissonian ensembles are stochastic objects of fundamental significance; they uniquely display an array of fractal features and they uniquely generate a span of important applications. In this paper we apply three different methods—oligarchic analysis, Lorenzian analysis and heterogeneity analysis—to explore power-law Poissonian ensembles. The amalgamation of these analyses, combined with the topology of power-law Poissonian ensembles, establishes a detailed and multi-faceted picture of the statistical structure and the statistical phase transitions of these elemental ensembles.

Quantisation of super Teichmueller theory

International Nuclear Information System (INIS)

Aghaei, Nezhla; Hamburg Univ.; Pawelkiewicz, Michal; Techner, Joerg

2015-12-01

We construct a quantisation of the Teichmueller spaces of super Riemann surfaces using coordinates associated to ideal triangulations of super Riemann surfaces. A new feature is the non-trivial dependence on the choice of a spin structure which can be encoded combinatorially in a certain refinement of the ideal triangulation. By constructing a projective unitary representation of the groupoid of changes of refined ideal triangulations we demonstrate that the dependence of the resulting quantum theory on the choice of a triangulation is inessential.

Dissipation induced asymmetric steering of distant atomic ensembles

Science.gov (United States)

Cheng, Guangling; Tan, Huatang; Chen, Aixi

2018-04-01

The asymmetric steering effects of separated atomic ensembles denoted by the effective bosonic modes have been explored by the means of quantum reservoir engineering in the setting of the cascaded cavities, in each of which an atomic ensemble is involved. It is shown that the steady-state asymmetric steering of the mesoscopic objects is unconditionally achieved via the dissipation of the cavities, by which the nonlocal interaction occurs between two atomic ensembles, and the direction of steering could be easily controlled through variation of certain tunable system parameters. One advantage of the present scheme is that it could be rather robust against parameter fluctuations, and does not require the accurate control of evolution time and the original state of the system. Furthermore, the double-channel Raman transitions between the long-lived atomic ground states are used and the atomic ensembles act as the quantum network nodes, which makes our scheme insensitive to the collective spontaneous emission of atoms.

Skill forecasting from different wind power ensemble prediction methods

International Nuclear Information System (INIS)

Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

2007-01-01

This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

Using ensemble forecasting for wind power

Energy Technology Data Exchange (ETDEWEB)

Giebel, G.; Landberg, L.; Badger, J. [Risoe National Lab., Roskilde (Denmark); Sattler, K.

2003-07-01

Short-term prediction of wind power has a long tradition in Denmark. It is an essential tool for the operators to keep the grid from becoming unstable in a region like Jutland, where more than 27% of the electricity consumption comes from wind power. This means that the minimum load is already lower than the maximum production from wind energy alone. Danish utilities have therefore used short-term prediction of wind energy since the mid-90ies. However, the accuracy is still far from being sufficient in the eyes of the utilities (used to have load forecasts accurate to within 5% on a one-week horizon). The Ensemble project tries to alleviate the dependency of the forecast quality on one model by using multiple models, and also will investigate the possibilities of using the model spread of multiple models or of dedicated ensemble runs for a prediction of the uncertainty of the forecast. Usually, short-term forecasting works (especially for the horizon beyond 6 hours) by gathering input from a Numerical Weather Prediction (NWP) model. This input data is used together with online data in statistical models (this is the case eg in Zephyr/WPPT) to yield the output of the wind farms or of a whole region for the next 48 hours (only limited by the NWP model horizon). For the accuracy of the final production forecast, the accuracy of the NWP prediction is paramount. While many efforts are underway to increase the accuracy of the NWP forecasts themselves (which ultimately are limited by the amount of computing power available, the lack of a tight observational network on the Atlantic and limited physics modelling), another approach is to use ensembles of different models or different model runs. This can be either an ensemble of different models output for the same area, using different data assimilation schemes and different model physics, or a dedicated ensemble run by a large institution, where the same model is run with slight variations in initial conditions and

Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

Science.gov (United States)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

Exploring diversity in ensemble classification: Applications in large area land cover mapping

Science.gov (United States)

Mellor, Andrew; Boukir, Samia

2017-07-01

Ensemble classifiers, such as random forests, are now commonly applied in the field of remote sensing, and have been shown to perform better than single classifier systems, resulting in reduced generalisation error. Diversity across the members of ensemble classifiers is known to have a strong influence on classification performance - whereby classifier errors are uncorrelated and more uniformly distributed across ensemble members. The relationship between ensemble diversity and classification performance has not yet been fully explored in the fields of information science and machine learning and has never been examined in the field of remote sensing. This study is a novel exploration of ensemble diversity and its link to classification performance, applied to a multi-class canopy cover classification problem using random forests and multisource remote sensing and ancillary GIS data, across seven million hectares of diverse dry-sclerophyll dominated public forests in Victoria Australia. A particular emphasis is placed on analysing the relationship between ensemble diversity and ensemble margin - two key concepts in ensemble learning. The main novelty of our work is on boosting diversity by emphasizing the contribution of lower margin instances used in the learning process. Exploring the influence of tree pruning on diversity is also a new empirical analysis that contributes to a better understanding of ensemble performance. Results reveal insights into the trade-off between ensemble classification accuracy and diversity, and through the ensemble margin, demonstrate how inducing diversity by targeting lower margin training samples is a means of achieving better classifier performance for more difficult or rarer classes and reducing information redundancy in classification problems. Our findings inform strategies for collecting training data and designing and parameterising ensemble classifiers, such as random forests. This is particularly important in large area

Reliability of multi-model and structurally different single-model ensembles

Energy Technology Data Exchange (ETDEWEB)

Yokohata, Tokuta [National Institute for Environmental Studies, Center for Global Environmental Research, Tsukuba, Ibaraki (Japan); Annan, James D.; Hargreaves, Julia C. [Japan Agency for Marine-Earth Science and Technology, Research Institute for Global Change, Yokohama, Kanagawa (Japan); Collins, Matthew [University of Exeter, College of Engineering, Mathematics and Physical Sciences, Exeter (United Kingdom); Jackson, Charles S.; Tobis, Michael [The University of Texas at Austin, Institute of Geophysics, 10100 Burnet Rd., ROC-196, Mail Code R2200, Austin, TX (United States); Webb, Mark J. [Met Office Hadley Centre, Exeter (United Kingdom)

2012-08-15

The performance of several state-of-the-art climate model ensembles, including two multi-model ensembles (MMEs) and four structurally different (perturbed parameter) single model ensembles (SMEs), are investigated for the first time using the rank histogram approach. In this method, the reliability of a model ensemble is evaluated from the point of view of whether the observations can be regarded as being sampled from the ensemble. Our analysis reveals that, in the MMEs, the climate variables we investigated are broadly reliable on the global scale, with a tendency towards overdispersion. On the other hand, in the SMEs, the reliability differs depending on the ensemble and variable field considered. In general, the mean state and historical trend of surface air temperature, and mean state of precipitation are reliable in the SMEs. However, variables such as sea level pressure or top-of-atmosphere clear-sky shortwave radiation do not cover a sufficiently wide range in some. It is not possible to assess whether this is a fundamental feature of SMEs generated with particular model, or a consequence of the algorithm used to select and perturb the values of the parameters. As under-dispersion is a potentially more serious issue when using ensembles to make projections, we recommend the application of rank histograms to assess reliability when designing and running perturbed physics SMEs. (orig.)

On the forecast skill of a convection-permitting ensemble

Science.gov (United States)

Schellander-Gorgas, Theresa; Wang, Yong; Meier, Florian; Weidle, Florian; Wittmann, Christoph; Kann, Alexander

2017-01-01

The 2.5 km convection-permitting (CP) ensemble AROME-EPS (Applications of Research to Operations at Mesoscale - Ensemble Prediction System) is evaluated by comparison with the regional 11 km ensemble ALADIN-LAEF (Aire Limitée Adaption dynamique Développement InterNational - Limited Area Ensemble Forecasting) to show whether a benefit is provided by a CP EPS. The evaluation focuses on the abilities of the ensembles to quantitatively predict precipitation during a 3-month convective summer period over areas consisting of mountains and lowlands. The statistical verification uses surface observations and 1 km × 1 km precipitation analyses, and the verification scores involve state-of-the-art statistical measures for deterministic and probabilistic forecasts as well as novel spatial verification methods. The results show that the convection-permitting ensemble with higher-resolution AROME-EPS outperforms its mesoscale counterpart ALADIN-LAEF for precipitation forecasts. The positive impact is larger for the mountainous areas than for the lowlands. In particular, the diurnal precipitation cycle is improved in AROME-EPS, which leads to a significant improvement of scores at the concerned times of day (up to approximately one-third of the scored verification measure). Moreover, there are advantages for higher precipitation thresholds at small spatial scales, which are due to the improved simulation of the spatial structure of precipitation.

Super-entropic black holes and the Kerr-CFT correspondence

Energy Technology Data Exchange (ETDEWEB)

Sinamuli, Musema [Department of Physics and Astronomy, University of Waterloo,200 University Ave., Waterloo, Ontario N2L 3G1 (Canada); Perimeter Institute for Theoretical Physics,31 Caroline St., Waterloo, Ontario, N2L 2Y5 (Canada); Mann, Robert B. [Department of Physics and Astronomy, University of Waterloo,200 University Ave., Waterloo, Ontario N2L 3G1 (Canada)

2016-08-24

We demonstrate that Kerr-CFT duality can be extended to super-entropic black holes, which have non-compact horizons with finite area. We demonstrate that this duality is robust insofar as the ultra-spinning limit of a Kerr-AdS black hole (which yields the super-entropic class) commutes with the near-horizon limit (which yields the Kerr-CFT duality). Consequently the Bekenstein-Hawking and the CFT entropies are equivalent. We show that the duality holds for both singly-spinning super-entropic black holes in 4 dimensions and for doubly-spinning super-entropic black holes of gauged supergravity in 5 dimensions. In both cases we obtain not only the expected left/right temperatures, but also temperatures associated with electric charge and with a new thermodynamic parameter specific to super-entropic black holes.

Super-entropic black holes and the Kerr-CFT correspondence

International Nuclear Information System (INIS)

Sinamuli, Musema; Mann, Robert B.

2016-01-01

We demonstrate that Kerr-CFT duality can be extended to super-entropic black holes, which have non-compact horizons with finite area. We demonstrate that this duality is robust insofar as the ultra-spinning limit of a Kerr-AdS black hole (which yields the super-entropic class) commutes with the near-horizon limit (which yields the Kerr-CFT duality). Consequently the Bekenstein-Hawking and the CFT entropies are equivalent. We show that the duality holds for both singly-spinning super-entropic black holes in 4 dimensions and for doubly-spinning super-entropic black holes of gauged supergravity in 5 dimensions. In both cases we obtain not only the expected left/right temperatures, but also temperatures associated with electric charge and with a new thermodynamic parameter specific to super-entropic black holes.

Ensemble computing for the petroleum industry

International Nuclear Information System (INIS)

Annaratone, M.; Dossa, D.

1995-01-01

Computer downsizing is one of the most often used buzzwords in today's competitive business, and the petroleum industry is at the forefront of this revolution. Ensemble computing provides the key for computer downsizing with its first incarnation, i.e., workstation farms. This paper concerns the importance of increasing the productivity cycle and not just the execution time of a job. The authors introduce the concept of ensemble computing and workstation farms. The they discuss how different computing paradigms can be addressed by workstation farms

Ocean Predictability and Uncertainty Forecasts Using Local Ensemble Transfer Kalman Filter (LETKF)

Science.gov (United States)

Wei, M.; Hogan, P. J.; Rowley, C. D.; Smedstad, O. M.; Wallcraft, A. J.; Penny, S. G.

2017-12-01

Ocean predictability and uncertainty are studied with an ensemble system that has been developed based on the US Navy's operational HYCOM using the Local Ensemble Transfer Kalman Filter (LETKF) technology. One of the advantages of this method is that the best possible initial analysis states for the HYCOM forecasts are provided by the LETKF which assimilates operational observations using ensemble method. The background covariance during this assimilation process is implicitly supplied with the ensemble avoiding the difficult task of developing tangent linear and adjoint models out of HYCOM with the complicated hybrid isopycnal vertical coordinate for 4D-VAR. The flow-dependent background covariance from the ensemble will be an indispensable part in the next generation hybrid 4D-Var/ensemble data assimilation system. The predictability and uncertainty for the ocean forecasts are studied initially for the Gulf of Mexico. The results are compared with another ensemble system using Ensemble Transfer (ET) method which has been used in the Navy's operational center. The advantages and disadvantages are discussed.

REAL - Ensemble radar precipitation estimation for hydrology in a mountainous region

OpenAIRE

Germann, Urs; Berenguer Ferrer, Marc; Sempere Torres, Daniel; Zappa, Massimiliano

2009-01-01

An elegant solution to characterise the residual errors in radar precipitation estimates is to generate an ensemble of precipitation fields. The paper proposes a radar ensemble generator designed for usage in the Alps using LU decomposition (REAL), and presents first results from a real-time implementation coupling the radar ensemble with a semi-distributed rainfall–runoff model for flash flood modelling in a steep Alpine catchment. Each member of the radar ensemble is a possible realisati...

Non-Boltzmann Ensembles and Monte Carlo Simulations

International Nuclear Information System (INIS)

Murthy, K. P. N.

2016-01-01

Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc . This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g ( E , M ), as a function of both energy E , and order parameter M . This is carried out in two stages. We estimate g ( E ) in the first stage

Noodles: a tool for visualization of numerical weather model ensemble uncertainty.

Science.gov (United States)

Sanyal, Jibonananda; Zhang, Song; Dyer, Jamie; Mercer, Andrew; Amburn, Philip; Moorhead, Robert J

2010-01-01

Numerical weather prediction ensembles are routinely used for operational weather forecasting. The members of these ensembles are individual simulations with either slightly perturbed initial conditions or different model parameterizations, or occasionally both. Multi-member ensemble output is usually large, multivariate, and challenging to interpret interactively. Forecast meteorologists are interested in understanding the uncertainties associated with numerical weather prediction; specifically variability between the ensemble members. Currently, visualization of ensemble members is mostly accomplished through spaghetti plots of a single mid-troposphere pressure surface height contour. In order to explore new uncertainty visualization methods, the Weather Research and Forecasting (WRF) model was used to create a 48-hour, 18 member parameterization ensemble of the 13 March 1993 "Superstorm". A tool was designed to interactively explore the ensemble uncertainty of three important weather variables: water-vapor mixing ratio, perturbation potential temperature, and perturbation pressure. Uncertainty was quantified using individual ensemble member standard deviation, inter-quartile range, and the width of the 95% confidence interval. Bootstrapping was employed to overcome the dependence on normality in the uncertainty metrics. A coordinated view of ribbon and glyph-based uncertainty visualization, spaghetti plots, iso-pressure colormaps, and data transect plots was provided to two meteorologists for expert evaluation. They found it useful in assessing uncertainty in the data, especially in finding outliers in the ensemble run and therefore avoiding the WRF parameterizations that lead to these outliers. Additionally, the meteorologists could identify spatial regions where the uncertainty was significantly high, allowing for identification of poorly simulated storm environments and physical interpretation of these model issues.

Introduction of a super speed network in JNC

International Nuclear Information System (INIS)

Nosaki, Nobuhisa; Aoki, Kazuhisa; Narita, Nobuiku

2002-01-01

The construction of a super speed and broadband network with high cost performance is now possible through the resent remarkable development of information-communication technologies. Under such circumstances, the modification of LAN and WAN to the super speed network was required in accordance with the recent network demand in JNC. The trend of the information-communication technologies and the needs of information-communication infrastructure were reviewed as the first step. A modification of WAN to the super speed network with high cost performance was established in fiscal year 2000. This paper introduces the work procedures and the modification of the WAN in order to acquire a reduction in the running cost and the super speed network in the fiscal year. (author)

Super-Laplacians and their symmetries

Energy Technology Data Exchange (ETDEWEB)

Howe, P.S. [Department of Mathematics, King’s College London,The Strand, London, WC2R 2LS (United Kingdom); Lindström, University [Department of Physics and Astronomy, Theoretical Physics, Uppsala University,Uppsala, SE-751 20 (Sweden); Theoretical Physics, Imperial College London,Prince Consort Road, London, SW7 2AZ (United Kingdom)

2017-05-22

A super-Laplacian is a set of differential operators in superspace whose highest-dimensional component is given by the spacetime Laplacian. Symmetries of super-Laplacians are given by linear differential operators of arbitrary finite degree and are determined by superconformal Killing tensors. We investigate these in flat superspaces. The differential operators determining the symmetries give rise to algebras which can be identified in many cases with the tensor algebras of the relevant superconformal Lie algebras modulo certain ideals. They have applications to Higher Spin theories.

Super-preshowers (DPG-Fruehjahrstagung 2016)

Energy Technology Data Exchange (ETDEWEB)

Kaeaepae, Alex [Bergische Universitaet Wuppertal, Gaussstr. 20, 42119 Wuppertal (Germany); Collaboration: Pierre-Auger-Collaboration

2016-07-01

Based on the current data from the Pierre Auger Observatory, no evidence of cosmic ray photon primaries has been found. However, photon primaries could induce so-called ''super-preshowers'', which have not been considered sofar, but are a promising candidate for explaining the ''composition puzzle'' at ultra-high energies. In this presentation, possible super-preshower processes are examined, and their effects on important Auger parameters, such as the energy deposit and muon production, are studied via simulations.

Super-Laplacians and their symmetries

International Nuclear Information System (INIS)

Howe, P.S.; Lindström, University

2017-01-01

A super-Laplacian is a set of differential operators in superspace whose highest-dimensional component is given by the spacetime Laplacian. Symmetries of super-Laplacians are given by linear differential operators of arbitrary finite degree and are determined by superconformal Killing tensors. We investigate these in flat superspaces. The differential operators determining the symmetries give rise to algebras which can be identified in many cases with the tensor algebras of the relevant superconformal Lie algebras modulo certain ideals. They have applications to Higher Spin theories.

Ensemble Deep Learning for Biomedical Time Series Classification

Directory of Open Access Journals (Sweden)

Lin-peng Jin

2016-01-01

Full Text Available Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.

Device and Method for Gathering Ensemble Data Sets

Science.gov (United States)

Racette, Paul E. (Inventor)

2014-01-01

An ensemble detector uses calibrated noise references to produce ensemble sets of data from which properties of non-stationary processes may be extracted. The ensemble detector comprising: a receiver; a switching device coupled to the receiver, the switching device configured to selectively connect each of a plurality of reference noise signals to the receiver; and a gain modulation circuit coupled to the receiver and configured to vary a gain of the receiver based on a forcing signal; whereby the switching device selectively connects each of the plurality of reference noise signals to the receiver to produce an output signal derived from the plurality of reference noise signals and the forcing signal.

Combining 2-m temperature nowcasting and short range ensemble forecasting

Directory of Open Access Journals (Sweden)

A. Kann

2011-12-01

Full Text Available During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG since 2006 (Haiden et al., 2011, provides short range deterministic forecasts at high temporal (15 min–60 min and spatial (1 km resolution. An INCA Ensemble (INCA-EPS of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting which is running operationally at ZAMG (Wang et al., 2011. The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion for Gaussian distributed continuous

Migration-driven diversity of super-Earth compositions

Science.gov (United States)

Raymond, Sean N.; Boulet, Thibault; Izidoro, Andre; Esteves, Leandro; Bitsch, Bertram

2018-06-01

A leading model for the origin of super-Earths proposes that planetary embryos migrate inward and pile up on close-in orbits. As large embryos are thought to preferentially form beyond the snow line, this naively predicts that most super-Earths should be very water-rich. Here we show that the shortest-period planets formed in the migration model are often purely rocky. The inward migration of icy embryos through the terrestrial zone accelerates the growth of rocky planets via resonant shepherding. We illustrate this process with a simulation that provided a match to the Kepler-36 system of two planets on close orbits with very different densities. In the simulation, two super-Earths formed in a Kepler-36-like configuration; the inner planet was pure rock while the outer one was ice-rich. We conclude from a suite of simulations that the feeding zones of close-in super-Earths are likely to be broad and disconnected from their final orbital radii.

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

JEnsembl: a version-aware Java API to Ensembl data systems.

Science.gov (United States)

Paterson, Trevor; Law, Andy

2012-11-01

The Ensembl Project provides release-specific Perl APIs for efficient high-level programmatic access to data stored in various Ensembl database schema. Although Perl scripts are perfectly suited for processing large volumes of text-based data, Perl is not ideal for developing large-scale software applications nor embedding in graphical interfaces. The provision of a novel Java API would facilitate type-safe, modular, object-orientated development of new Bioinformatics tools with which to access, analyse and visualize Ensembl data. The JEnsembl API implementation provides basic data retrieval and manipulation functionality from the Core, Compara and Variation databases for all species in Ensembl and EnsemblGenomes and is a platform for the development of a richer API to Ensembl datasources. The JEnsembl architecture uses a text-based configuration module to provide evolving, versioned mappings from database schema to code objects. A single installation of the JEnsembl API can therefore simultaneously and transparently connect to current and previous database instances (such as those in the public archive) thus facilitating better analysis repeatability and allowing 'through time' comparative analyses to be performed. Project development, released code libraries, Maven repository and documentation are hosted at SourceForge (http://jensembl.sourceforge.net).

Dispersion of aerosol particles in the free atmosphere using ensemble forecasts

Directory of Open Access Journals (Sweden)

T. Haszpra

2013-10-01

Full Text Available The dispersion of aerosol particle pollutants is studied using 50 members of an ensemble forecast in the example of a hypothetical free atmospheric emission above Fukushima over a period of 2.5 days. Considerable differences are found among the dispersion predictions of the different ensemble members, as well as between the ensemble mean and the deterministic result at the end of the observation period. The variance is found to decrease with the particle size. The geographical area where a threshold concentration is exceeded in at least one ensemble member expands to a 5–10 times larger region than the area from the deterministic forecast, both for air column "concentration" and in the "deposition" field. We demonstrate that the root-mean-square distance of any particle from its own clones in the ensemble members can reach values on the order of one thousand kilometers. Even the centers of mass of the particle cloud of the ensemble members deviate considerably from that obtained by the deterministic forecast. All these indicate that an investigation of the dispersion of aerosol particles in the spirit of ensemble forecast contains useful hints for the improvement of risk assessment.

Orbital magnetism in ensembles of ballistic billiards

International Nuclear Information System (INIS)

Ullmo, D.; Richter, K.; Jalabert, R.A.

1993-01-01

The magnetic response of ensembles of small two-dimensional structures at finite temperatures is calculated. Using semiclassical methods and numerical calculation it is demonstrated that only short classical trajectories are relevant. The magnetic susceptibility is enhanced in regular systems, where these trajectories appear in families. For ensembles of squares large paramagnetic susceptibility is obtained, in good agreement with recent measurements in the ballistic regime. (authors). 20 refs., 2 figs

Pinching parameters for open (super) strings

Science.gov (United States)

Playle, Sam; Sciuto, Stefano

2018-02-01

We present an approach to the parametrization of (super) Schottky space obtained by sewing together three-punctured discs with strips. Different cubic ribbon graphs classify distinct sets of pinching parameters; we show how they are mapped onto each other. The parametrization is particularly well-suited to describing the region within (super) moduli space where open bosonic or Neveu-Schwarz string propagators become very long and thin, which dominates the IR behaviour of string theories. We show how worldsheet objects such as the Green's function converge to graph theoretic objects such as the Symanzik polynomials in the α ' → 0 limit, allowing us to see how string theory reproduces the sum over Feynman graphs. The (super) string measure takes on a simple and elegant form when expressed in terms of these parameters.

CLOUDS IN SUPER-EARTH ATMOSPHERES: CHEMICAL EQUILIBRIUM CALCULATIONS

Energy Technology Data Exchange (ETDEWEB)

Mbarek, Rostom; Kempton, Eliza M.-R., E-mail: mbarekro@grinnell.edu, E-mail: kemptone@grinnell.edu [Department of Physics, Grinnell College, Grinnell, IA 50112 (United States)

2016-08-20

Recent studies have unequivocally proven the existence of clouds in super-Earth atmospheres. Here we provide a theoretical context for the formation of super-Earth clouds by determining which condensates are likely to form under the assumption of chemical equilibrium. We study super-Earth atmospheres of diverse bulk composition, which are assumed to form by outgassing from a solid core of chondritic material, following Schaefer and Fegley. The super-Earth atmospheres that we study arise from planetary cores made up of individual types of chondritic meteorites. They range from highly reducing to oxidizing and have carbon to oxygen (C:O) ratios that are both sub-solar and super-solar, thereby spanning a range of atmospheric composition that is appropriate for low-mass exoplanets. Given the atomic makeup of these atmospheres, we minimize the global Gibbs free energy of formation for over 550 gases and condensates to obtain the molecular composition of the atmospheres over a temperature range of 350–3000 K. Clouds should form along the temperature–pressure boundaries where the condensed species appear in our calculation. We find that the composition of condensate clouds depends strongly on both the H:O and C:O ratios. For the super-Earth archetype GJ 1214b, KCl and ZnS are the primary cloud-forming condensates at solar composition, in agreement with previous work. However, for oxidizing atmospheres, K{sub 2}SO{sub 4} and ZnO condensates are favored instead, and for carbon-rich atmospheres with super-solar C:O ratios, graphite clouds appear. For even hotter planets, clouds form from a wide variety of rock-forming and metallic species.

Ensemble dispersion forecasting - Part 2. Application and evaluation

DEFF Research Database (Denmark)

Galmarini, S.; Bianconi, R.; Addis, R.

2004-01-01

of the dispersion of ETEX release 1 and the model ensemble is compared with the monitoring data. The scope of the comparison is to estimate to what extent the ensemble analysis is an improvement with respect to the single model results and represents a superior analysis of the process evolution. (C) 2004 Elsevier...

On some classes of super quasi-Einstein manifolds

International Nuclear Information System (INIS)

Ozguer, Cihan

2009-01-01

Quasi-Einstein and generalized quasi-Einstein manifolds are the generalizations of Einstein manifolds. In this study, we consider a super quasi-Einstein manifold, which is another generalization of an Einstein manifold. We find the curvature characterizations of a Ricci-pseudosymmetric and a quasi-conformally flat super quasi-Einstein manifolds. We also consider the condition C ∼ .S=0 on a super quasi-Einstein manifold, where C ∼ and S denote the quasi-conformal curvature tensor and Ricci tensor of the manifold, respectively.

SuperB Bunch-By-Bunch Feedback R&D

Energy Technology Data Exchange (ETDEWEB)

Drago, A.; Beretta, M.; /Frascati; Bertsche, K.; Novokhatski, A.; /SLAC; Migliorati, M.; /Rome U.

2011-08-12

The SuperB project has the goal to build in Italy, in the Frascati or Tor Vergata area, an asymmetric e{sup +}/e{sup -} Super Flavor Factory to achieve a peak luminosity > 10**36 cm{sup -2} s{sup -1}. The SuperB design is based on collisions with extremely low vertical emittance beams and high beam currents. A source of emittance growth comes from the bunch by bunch feedback systems producing high power correction signals to damp the beams. To limit any undesirable effect, a large R&D program is in progress, partially funded by the INFN Fifth National Scientific Committee through the SFEED (SuperB Feedback) project approved within the 2010 budget. The SuperB project [1] has the goal to build in Italy, in the Frascati or Tor Vergata area, an asymmetric e{sup +}/e{sup -} Super Flavor Factory to achieve a peak luminosity > 10**36 cm{sup -2} s{sup -1}. In the last and current years, the machine layout has been deeply modified, in particular the main rings are now shorter and an option with high currents has been foreseen. In the fig.1 the new SuperB layout is shown. From bunch-by-bunch feedback point of view, the simultaneous presence in the machine parameters, of very low emittance, of the order of 5-10 pm in the vertical plane, and very high currents, at level of 4 Ampere for the Low Energy Ring, asks for designing very carefully the bunch-by-bunch feedback systems. The parameter list is presented in Fig. 2. The bunch-by-bunch feedback design must take care of the risky and exciting challenges proposed in the SuperB specifications, but it should consider also some other important aspects: flexibility in terms of being able to cope to unexpected beam behaviours [2], [3] legacy of previous version experience [4], [5] and internal powerful diagnostics [6] as in the systems previously used in PEP-II and DAFNE [7].

A variational ensemble scheme for noisy image data assimilation

Science.gov (United States)

Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne

2014-05-01

Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow

Ensemble atmospheric dispersion modeling for emergency response consequence assessments

International Nuclear Information System (INIS)

Addis, R.P.; Buckley, R.L.

2003-01-01

Full text: Prognostic atmospheric dispersion models are used to generate consequence assessments, which assist decision-makers in the event of a release from a nuclear facility. Differences in the forecast wind fields generated by various meteorological agencies, differences in the transport and diffusion models themselves, as well as differences in the way these models treat the release source term, all may result in differences in the simulated plumes. This talk will address the U.S. participation in the European ENSEMBLE project, and present a perspective an how ensemble techniques may be used to enable atmospheric modelers to provide decision-makers with a more realistic understanding of how both the atmosphere and the models behave. Meteorological forecasts generated by numerical models from national and multinational meteorological agencies provide individual realizations of three-dimensional, time dependent atmospheric wind fields. These wind fields may be used to drive atmospheric dispersion (transport and diffusion) models, or they may be used to initiate other, finer resolution meteorological models, which in turn drive dispersion models. Many modeling agencies now utilize ensemble-modeling techniques to determine how sensitive the prognostic fields are to minor perturbations in the model parameters. However, the European Union programs RTMOD and ENSEMBLE are the first projects to utilize a WEB based ensemble approach to interpret the output from atmospheric dispersion models. The ensembles produced are different from those generated by meteorological forecasting centers in that they are ensembles of dispersion model outputs from many different atmospheric transport and diffusion models utilizing prognostic atmospheric fields from several different forecast centers. As such, they enable a decision-maker to consider the uncertainty in the plume transport and growth as a result of the differences in the forecast wind fields as well as the differences in the

Benchmarking Commercial Conformer Ensemble Generators.

Science.gov (United States)

Friedrich, Nils-Ole; de Bruyn Kops, Christina; Flachsenberg, Florian; Sommer, Kai; Rarey, Matthias; Kirchmair, Johannes

2017-11-27

We assess and compare the performance of eight commercial conformer ensemble generators (ConfGen, ConfGenX, cxcalc, iCon, MOE LowModeMD, MOE Stochastic, MOE Conformation Import, and OMEGA) and one leading free algorithm, the distance geometry algorithm implemented in RDKit. The comparative study is based on a new version of the Platinum Diverse Dataset, a high-quality benchmarking dataset of 2859 protein-bound ligand conformations extracted from the PDB. Differences in the performance of commercial algorithms are much smaller than those observed for free algorithms in our previous study (J. Chem. Inf. 2017, 57, 529-539). For commercial algorithms, the median minimum root-mean-square deviations measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers are between 0.46 and 0.61 Å. Commercial conformer ensemble generators are characterized by their high robustness, with at least 99% of all input molecules successfully processed and few or even no substantial geometrical errors detectable in their output conformations. The RDKit distance geometry algorithm (with minimization enabled) appears to be a good free alternative since its performance is comparable to that of the midranked commercial algorithms. Based on a statistical analysis, we elaborate on which algorithms to use and how to parametrize them for best performance in different application scenarios.

Mass Conservation and Positivity Preservation with Ensemble-type Kalman Filter Algorithms

Science.gov (United States)

Janjic, Tijana; McLaughlin, Dennis B.; Cohn, Stephen E.; Verlaan, Martin

2013-01-01

Maintaining conservative physical laws numerically has long been recognized as being important in the development of numerical weather prediction (NWP) models. In the broader context of data assimilation, concerted efforts to maintain conservation laws numerically and to understand the significance of doing so have begun only recently. In order to enforce physically based conservation laws of total mass and positivity in the ensemble Kalman filter, we incorporate constraints to ensure that the filter ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. We show that the analysis steps of ensemble transform Kalman filter (ETKF) algorithm and ensemble Kalman filter algorithm (EnKF) can conserve the mass integral, but do not preserve positivity. Further, if localization is applied or if negative values are simply set to zero, then the total mass is not conserved either. In order to ensure mass conservation, a projection matrix that corrects for localization effects is constructed. In order to maintain both mass conservation and positivity preservation through the analysis step, we construct a data assimilation algorithms based on quadratic programming and ensemble Kalman filtering. Mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate constraints. Some simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. The results show clear improvements in both analyses and forecasts, particularly in the presence of localized features. Behavior of the algorithm is also tested in presence of model error.

Ensembl Genomes 2016: more genomes, more complexity.

Science.gov (United States)

Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

2016-01-04

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Conductor gestures influence evaluations of ensemble performance

Directory of Open Access Journals (Sweden)

Steven eMorrison

2014-07-01

Full Text Available Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor’s gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance, articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and nonmajors (N = 285 viewed sixteen 30-second performances and evaluated the quality of the ensemble’s articulation, dynamics, technique and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble’s performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

Identifying Galactic Cosmic Ray Origins With Super-TIGER

Science.gov (United States)

deNolfo, Georgia; Binns, W. R.; Israel, M. H.; Christian, E. R.; Mitchell, J. W.; Hams, T.; Link, J. T.; Sasaki, M.; Labrador, A. W.; Mewaldt, R. A.;

Curve Boxplot: Generalization of Boxplot for Ensembles of Curves.

Science.gov (United States)

Mirzargar, Mahsa; Whitaker, Ross T; Kirby, Robert M

2014-12-01

In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics.

Conservation of Mass and Preservation of Positivity with Ensemble-Type Kalman Filter Algorithms

Science.gov (United States)

Janjic, Tijana; Mclaughlin, Dennis; Cohn, Stephen E.; Verlaan, Martin

2014-01-01

This paper considers the incorporation of constraints to enforce physically based conservation laws in the ensemble Kalman filter. In particular, constraints are used to ensure that the ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. In certain situations filtering algorithms such as the ensemble Kalman filter (EnKF) and ensemble transform Kalman filter (ETKF) yield updated ensembles that conserve mass but are negative, even though the actual states must be nonnegative. In such situations if negative values are set to zero, or a log transform is introduced, the total mass will not be conserved. In this study, mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate non-negativity constraints. Simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. In two examples, an update that includes a non-negativity constraint is able to properly describe the transport of a sharp feature (e.g., a triangle or cone). A number of implementation questions still need to be addressed, particularly the need to develop a computationally efficient quadratic programming update for large ensemble.

Momentum distribution functions in ensembles: the inequivalence of microcannonical and canonical ensembles in a finite ultracold system.

Science.gov (United States)

Wang, Pei; Xianlong, Gao; Li, Haibin

2013-08-01

It is demonstrated in many thermodynamic textbooks that the equivalence of the different ensembles is achieved in the thermodynamic limit. In this present work we discuss the inequivalence of microcanonical and canonical ensembles in a finite ultracold system at low energies. We calculate the microcanonical momentum distribution function (MDF) in a system of identical fermions (bosons). We find that the microcanonical MDF deviates from the canonical one, which is the Fermi-Dirac (Bose-Einstein) function, in a finite system at low energies where the single-particle density of states and its inverse are finite.

An educational model for ensemble streamflow simulation and uncertainty analysis

Directory of Open Access Journals (Sweden)

A. AghaKouchak

2013-02-01

Full Text Available This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.

A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

Science.gov (United States)

Hart, Emma; Sim, Kevin

2016-01-01

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

Does the combination of the MMSE and clock drawing test (mini-clock) improve the detection of mild Alzheimer's disease and mild cognitive impairment?

Science.gov (United States)

Cacho, Jesús; Benito-León, Julián; García-García, Ricardo; Fernández-Calvo, Bernardino; Vicente-Villardón, José Luis; Mitchell, Alex J

2010-01-01

There is currently a need to develop tools to identify patients with mild AD and mild cognitive impairment (MCI). We determined the validity and reliability of a brief, easily administered cognitive screening battery consisting of fusion of two well-known brief tests (Mini-Mental Status Examination [MMSE] and Clock Drawing Test [CDT]) (Mini-clock) to differentiate between patients with mild AD, MCI, and healthy control subjects. 66 consecutive patients with mild AD, 21 with MCI, and 66 healthy controls seen in a memory clinic setting were compared. Receiver operating characteristic (ROC) curve analysis was used to calculate the cut-off value permitting discrimination between mild AD, MCI, and healthy control subjects. Interrater and test-retest reliability were also assessed. Mean cognitive scores for patients with AD, MCI, and control subjects on all two individual tests were significantly different (for each, p Mini-clock was higher than that obtained with MMSE or CDT in differentiating mild AD from controls (0.973 vs. 0.952 and 0.881, respectively) and MCI from controls (0.855 vs. 0.821 and 0.779, respectively). Test-retest reliability for the Mini-clock was 0.99, meanwhile interrater reliability was 0.87. The mean time to complete the test for all subjects was 8 min and 50 s. The Mini-clock is highly sensitive and specific in the detection of mild AD and reasonably accurate when attempting to separate MCI from health controls. It has a high interrater and test-retest reliability, can be quickly administered, and does not require major training.

Inhomogeneous ensembles of radical pairs in chemical compasses

Science.gov (United States)

Procopio, Maria; Ritz, Thorsten

2016-11-01

The biophysical basis for the ability of animals to detect the geomagnetic field and to use it for finding directions remains a mystery of sensory biology. One much debated hypothesis suggests that an ensemble of specialized light-induced radical pair reactions can provide the primary signal for a magnetic compass sensor. The question arises what features of such a radical pair ensemble could be optimized by evolution so as to improve the detection of the direction of weak magnetic fields. Here, we focus on the overlooked aspect of the noise arising from inhomogeneity of copies of biomolecules in a realistic biological environment. Such inhomogeneity leads to variations of the radical pair parameters, thereby deteriorating the signal arising from an ensemble and providing a source of noise. We investigate the effect of variations in hyperfine interactions between different copies of simple radical pairs on the directional response of a compass system. We find that the choice of radical pair parameters greatly influences how strongly the directional response of an ensemble is affected by inhomogeneity.

Enhancing COSMO-DE ensemble forecasts by inexpensive techniques

Directory of Open Access Journals (Sweden)

Zied Ben Bouallègue

2013-02-01

Full Text Available COSMO-DE-EPS, a convection-permitting ensemble prediction system based on the high-resolution numerical weather prediction model COSMO-DE, is pre-operational since December 2010, providing probabilistic forecasts which cover Germany. This ensemble system comprises 20 members based on variations of the lateral boundary conditions, the physics parameterizations and the initial conditions. In order to increase the sample size in a computationally inexpensive way, COSMO-DE-EPS is combined with alternative ensemble techniques: the neighborhood method and the time-lagged approach. Their impact on the quality of the resulting probabilistic forecasts is assessed. Objective verification is performed over a six months period, scores based on the Brier score and its decomposition are shown for June 2011. The combination of the ensemble system with the alternative approaches improves probabilistic forecasts of precipitation in particular for high precipitation thresholds. Moreover, combining COSMO-DE-EPS with only the time-lagged approach improves the skill of area probabilities for precipitation and does not deteriorate the skill of 2 m-temperature and wind gusts forecasts.

Realization of Deutsch-like algorithm using ensemble computing

International Nuclear Information System (INIS)

Wei Daxiu; Luo Jun; Sun Xianping; Zeng Xizhi

2003-01-01

The Deutsch-like algorithm [Phys. Rev. A. 63 (2001) 034101] distinguishes between even and odd query functions using fewer function calls than its possible classical counterpart in a two-qubit system. But the similar method cannot be applied to a multi-qubit system. We propose a new approach for solving Deutsch-like problem using ensemble computing. The proposed algorithm needs an ancillary qubit and can be easily extended to multi-qubit system with one query. Our ensemble algorithm beginning with a easily-prepared initial state has three main steps. The classifications of the functions can be obtained directly from the spectra of the ancilla qubit. We also demonstrate the new algorithm in a four-qubit molecular system using nuclear magnetic resonance (NMR). One hydrogen and three carbons are selected as the four qubits, and one of carbons is ancilla qubit. We choice two unitary transformations, corresponding to two functions (one odd function and one even function), to validate the ensemble algorithm. The results show that our experiment is successfully and our ensemble algorithm for solving the Deutsch-like problem is virtual

Spectral statistics in semiclassical random-matrix ensembles

International Nuclear Information System (INIS)

Feingold, M.; Leitner, D.M.; Wilkinson, M.

1991-01-01

A novel random-matrix ensemble is introduced which mimics the global structure inherent in the Hamiltonian matrices of autonomous, ergodic systems. Changes in its parameters induce a transition between a Poisson and a Wigner distribution for the level spacings, P(s). The intermediate distributions are uniquely determined by a single scaling variable. Semiclassical constraints force the ensemble to be in a regime with Wigner P(s) for systems with more than two freedoms

Multivariate localization methods for ensemble Kalman filtering

OpenAIRE

S. Roh; M. Jun; I. Szunyogh; M. G. Genton

2015-01-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of ...

Decimated Input Ensembles for Improved Generalization

Science.gov (United States)

Tumer, Kagan; Oza, Nikunj C.; Norvig, Peter (Technical Monitor)

1999-01-01

Recently, many researchers have demonstrated that using classifier ensembles (e.g., averaging the outputs of multiple classifiers before reaching a classification decision) leads to improved performance for many difficult generalization problems. However, in many domains there are serious impediments to such "turnkey" classification accuracy improvements. Most notable among these is the deleterious effect of highly correlated classifiers on the ensemble performance. One particular solution to this problem is generating "new" training sets by sampling the original one. However, with finite number of patterns, this causes a reduction in the training patterns each classifier sees, often resulting in considerably worsened generalization performance (particularly for high dimensional data domains) for each individual classifier. Generally, this drop in the accuracy of the individual classifier performance more than offsets any potential gains due to combining, unless diversity among classifiers is actively promoted. In this work, we introduce a method that: (1) reduces the correlation among the classifiers; (2) reduces the dimensionality of the data, thus lessening the impact of the 'curse of dimensionality'; and (3) improves the classification performance of the ensemble.

Tailored Random Graph Ensembles

International Nuclear Information System (INIS)

Roberts, E S; Annibale, A; Coolen, A C C

2013-01-01

Tailored graph ensembles are a developing bridge between biological networks and statistical mechanics. The aim is to use this concept to generate a suite of rigorous tools that can be used to quantify and compare the topology of cellular signalling networks, such as protein-protein interaction networks and gene regulation networks. We calculate exact and explicit formulae for the leading orders in the system size of the Shannon entropies of random graph ensembles constrained with degree distribution and degree-degree correlation. We also construct an ergodic detailed balance Markov chain with non-trivial acceptance probabilities which converges to a strictly uniform measure and is based on edge swaps that conserve all degrees. The acceptance probabilities can be generalized to define Markov chains that target any alternative desired measure on the space of directed or undirected graphs, in order to generate graphs with more sophisticated topological features.

Deviations from Wick's theorem in the canonical ensemble

Science.gov (United States)

Schönhammer, K.

2017-07-01

Wick's theorem for the expectation values of products of field operators for a system of noninteracting fermions or bosons plays an important role in the perturbative approach to the quantum many-body problem. A finite-temperature version holds in the framework of the grand canonical ensemble, but not for the canonical ensemble appropriate for systems with fixed particle number such as ultracold quantum gases in optical lattices. Here we present formulas for expectation values of products of field operators in the canonical ensemble using a method in the spirit of Gaudin's proof of Wick's theorem for the grand canonical case. The deviations from Wick's theorem are examined quantitatively for two simple models of noninteracting fermions.

Site-Mutation of Hydrophobic Core Residues Synchronically Poise Super Interleukin 2 for Signaling: Identifying Distant Structural Effects through Affordable Computations

Directory of Open Access Journals (Sweden)

Longcan Mei

2018-03-01

Full Text Available A superkine variant of interleukin-2 with six site mutations away from the binding interface developed from the yeast display technique has been previously characterized as undergoing a distal structure alteration which is responsible for its super-potency and provides an elegant case study with which to get insight about how to utilize allosteric effect to achieve desirable protein functions. By examining the dynamic network and the allosteric pathways related to those mutated residues using various computational approaches, we found that nanosecond time scale all-atom molecular dynamics simulations can identify the dynamic network as efficient as an ensemble algorithm. The differentiated pathways for the six core residues form a dynamic network that outlines the area of structure alteration. The results offer potentials of using affordable computing power to predict allosteric structure of mutants in knowledge-based mutagenesis.

Preferences of and Attitudes toward Treble Choral Ensembles

Science.gov (United States)

Wilson, Jill M.

2012-01-01

In choral ensembles, a pursuit where females far outnumber males, concern exists that females are being devalued. Attitudes of female choral singers may be negatively affected by the gender imbalance that exists in mixed choirs and by the placement of the mixed choir as the most select ensemble in a program. The purpose of this research was to…

SuperB Progress Reports - Physics

CERN Document Server

O'Leary, B.; Ramon, M.; Pous, E.; De Fazio, F.; Palano, A.; Eigen, G.; Asgeirsson, D.; Cheng, C.H.; Chivukula, A.; Echenard, B.; Hitlin, D.G.; Porter, F.; Rakitin, A.; Heinemeyer, S.; McElrath, B.; Andreassen, R.; Meadows, B.; Sokoloff, M.; Blanke, M.; Lesiak, T.; Shindou, T.; Ronga, F.; Baldini, W.; Bettoni, D.; Calabrese, R.; Cibinetto, G.; Luppi, E.; Rama, M.; Bossi, F.; Guido, E.; Patrignani, C.; Tosi, S.; Davies, C.; Lunghi, E.; Haisch, U.; Hurth, T.; Westhoff, S.; Crivellin, A.; Hofer, L.; Goto, T.; Brown, David Nathan; Branco, G.C.; Zupan, J.; Herrero, M.; Rodriguez-Sanchez, A.; Simi, G.; Tackmann, F.J.; Biassoni, P.; Lazzaro, A.; Lombardo, V.; Palombo, F.; Stracka, S.; Lindemann, D.M.; Robertson, S.H.; Duling, B.; Gemmler, K.; Gorbahn, M.; Jager, S.; Paradisi, P.; Straub, D.M.; Bigi, I.; Asner, D.M.; Fast, J.E.; Kouzes, R.T.; Morandin, M.; Rotondo, M.; Ben-Haim, E.; Arnaud, N.; Burmistrov, L.; Kou, E.; Perez, A.; Stocchi, A.; Viaud, B.; Domingo, F.; Piccinini, F.; Manoni, E.; Batignani, G.; Cervelli, A.; Forti, F.; Giorgi, M.; Lusiani, A.; Oberhof, B.; Paoloni, E.; Neri, N.; Walsh, J.; Bevan, A.; Bona, M.; Walker, C.; Weiland, C.; Lenz, A.; Gonzalez-Sprinberg, G.; Faccini, R.; Renga, F.; Polosa, A.; Silvestrini, L.; Virto, J.; Ciuchini, M.; Lubicz, V.; Tarantino, C.; Wilson, F.F.; Carpinelli, M.; Huber, T.; Mannel, T.; Graham, M.; Ratcliff, B.N.; Santoro, V.; Sekula, S.; Shougaev, K.; Soffer, A.; Shimizu, Y.; Gambino, P.; Mussa, R.; Nardecchia, M.; Stal, O.; Bernabeu, J.; Botella, F.; Jung, M.; Lopez March, N.; Martinez Vidal, F.; Oyanguren, A.; Pich, A.; Lozano, M.A.Sanchis; Vidal, J.; Vives, O.; Banerjee, S.; Roney, J.M.; Petrov, A.A.; Flood, K.

2010-01-01

SuperB is a high luminosity e+e- collider that will be able to indirectly probe new physics at energy scales far beyond the reach of any man made accelerator planned or in existence. Just as detailed understanding of the Standard Model of particle physics was developed from stringent constraints imposed by flavour changing processes between quarks, the detailed structure of any new physics is severely constrained by flavour processes. In order to elucidate this structure it is necessary to perform a number of complementary studies of a set of golden channels. With these measurements in hand, the pattern of deviations from the Standard Model behavior can be used as a test of the structure of new physics. If new physics is found at the LHC, then the many golden measurements from SuperB will help decode the subtle nature of the new physics. However if no new particles are found at the LHC, SuperB will be able to search for new physics at energy scales up to 10-100 TeV. In either scenario, flavour physics measure...

SuperB Technical Design Report

CERN Document Server

Baszczyk, M.; Kolodziej, J.; Kucewicz, W.; Sapor, M.; Jeremie, A.; Grauges Pous, E.; Bruno, G.E.; De Robertis, G.; Diacono, D.; Donvito, G.; Fusco, P.; Gargano, F.; Giordano, F.; Loddo, F.; Loparco, F.; Maggi, G.P.; Manzari, V.; Mazziotta, M.N.; Nappi, E.; Palano, A.; Santeramo, B.; Sgura, I.; Silvestris, L.; Spinoso, V.; Eigen, G.; Zalieckas, J.; Zhuo, Z.; Jenkovszky, L.; Balbi, G.; Boldini, M.; Bonacorsi, D.; Cafaro, V.; D'Antone, I.; Dallavalle, G.M.; Di Sipio, R.; Fabbri, F.; Fabbri, L.; Gabrielli, A.; Galli, D.; Giacomelli, P.; Giordano, V.; Giorgi, F.M.; Grandi, C.; Lax, I.; Lo Meo, S.; Marconi, U.; Montanari, A.; Pellegrini, G.; Piccinini, M.; Rovelli, T.; Semprini Cesari, N.; Torromeo, G.; Tosi, N.; Travaglini, R.; Vagnoni, V.M.; Valentinetti, S.; Villa, M.; Zoccoli, A.; Caron, J. -F.; Hearty, C.; Lu, P. F. -T.; Mattison, T.S.; McKenna, J.A.; So, R. Y.; Barnyakov, M. Yu.; Blinov, V.E.; Botov, A.A.; Druzhinin, V.P.; Golubev, V.B.; Kononov, S.A.; Kravchenko, E.A.; Levichev, E.B.; Onuchin, A.P.; Serednyakov, S.I.; Shtol, D.A.; Skovpen, Y.I.; Solodov, E.P.; Cardini, A.; Carpinelli, M.; Chao, D. S. -T.; Cheng, C.H.; Doll, D.A.; Echenard, B.; Flood, K.; Hanson, J.; Hitlin, D.G.; Ongmongkolkul, P.; Porter, F.C.; Zhu, R.Y.; Randazzo, N.; De La Cruz Burelo, E.; Zheng, Y.; Campos, P.; De Silva, M.; Kathirgamaraju, A.; Meadows, B.; Pushpawela, B.; Shi, Y.; Sokoloff, M.; Lopez Castro, G.; Ciaschini, V.; Franchini, P.; Giacomini, F.; Paolini, A.; Calderon Polania, G. A.; Laczek, S.; Romanowicz, P.; Szybinski, B.; Czuchry, M.; Flis, L.; Harezlak, D.; Kocot, J.; Radecki, M.; Sterzel, M.; Szepieniec, T.; Szymocha, T.; Wójcik, P.; Andreotti, M.; Baldini, W.; Calabrese, R.; Carassiti, V.; Cibinetto, G.; Cotta Ramusino, A.; Evangelisti, F.; Gianoli, A.; Luppi, E.; Malaguti, R.; Manzali, M.; Melchiorri, M.; Munerato, M.; Padoan, C.; Santoro, V.; Tomassetti, L.; Beretta, M.M.; Biagini, M.; Boscolo, M.; Capitolo, E.; de Sangro, R.; Esposito, M.; Felici, G.; Finocchiaro, G.; Gatta, M.; Gatti, C.; Guiducci, S.; Lauciani, S.; Patteri, P.; Peruzzi, I.; Piccolo, M.; Raimondi, P.; Rama, M.; Sanelli, C.; Tomassini, S.; Fabbricatore, P.; Delepine, D.; Reyes Santos, M. A.; Chrzaszcz, M.; Grzymkowski, R.; Knap, P.; Kotula, J.; Lesiak, T.; Ludwin, J.; Michalowski, J.; Pawlik, B.; Rachwal, B.; Stodulski, M.; Wiechczynski, J.; Witek, M.; Zawiejski, L.; Zdybal, M.; Aushev, V.Y.; Ustynov, A.; Arnaud, N.; Bambade, P.; Beigbeder, C.; Bogard, F.; Borsato, M.; Breton, D.; Brossard, J.; Burmistrov, L.; Charlet, D.; Chaumat, V.; Dadoun, O.; El Berni, M.; Maalmi, J.; Puill, V.; Rimbault, C.; Stocchi, A.; Tocut, V.; Variola, A.; Wallon, S.; Wormser, G.; Grancagnolo, F.; Ben-Haim, E.; Sitt, S.; Baylac, M.; Bourrion, O.; Deconto, J. -M.; Gomez Martinez, Y.; Monseu, N.; Muraz, J. -F.; Real, J. -S.; Vescovi, C.; Cenci, R.; Jawahery, A.; Roberts, D.; Twedt, E.W.; Cheaib, R.; Lindemann, D.; Nderitu, S.; Patel, P.; Robertson, S.H.; Swersky, D.; Warburton, A.; Cuautle Flores, E.; Toledo Sanchez, G.; Biassoni, P.; Bombelli, L.; Citterio, M.; Coelli, S.; Fiorini, C.; Liberali, V.; Monti, M.; Nasri, B.; Neri, N.; Palombo, F.; Sabatini, F.; Stabile, A.; Berra, A.; Giachero, A.; Gotti, C.; Lietti, D.; Maino, M.; Pessina, G.; Prest, M.; Martin, J. -P.; Simard, M.; Starinski, N.; Taras, P.; Drutskoy, A.; Makarychev, S.; Nefediev, A.V.; Aloisio, A.; Cavaliere, S.; De Nardo, G.; Della Pietra, M.; Doria, A.; Giordano, R.; Ordine, A.; Pardi, S.; Russo, G.; Sciacca, C.; Bigi, I.I.; Jessop, C.P.; Wang, W.; Bellato, M.; Benettoni, M.; Corvo, M.; Crescente, A.; Dal Corso, F.; Dosselli, U.; Fanin, C.; Gianelle, A.; Longo, S.; Michelotto, M.; Montecassiano, F.; Morandin, M.; Pengo, R.; Posocco, M.; Rotondo, M.; Simi, G.; Stroili, R.; Gaioni, L.; Manazza, A.; Manghisoni, M.; Ratti, L.; Re, V.; Traversi, G.; Zucca, S.; Bizzaglia, S.; Bizzarri, M.; Cecchi, C.; Germani, S.; Lebeau, M.; Lubrano, P.; Manoni, E.; Papi, A.; Rossi, A.; Scolieri, G.; Batignani, G.; Bettarini, S.; Casarosa, G.; Cervelli, A.; Fella, A.; Forti, F.; Giorgi, M.; Lilli, L.; Lusiani, A.; Oberhof, B.; Paladino, A.; Pantaleo, F.; Paoloni, E.; Perez Perez, A. L.; Rizzo, G.; Walsh, J.; Fernández Téllez, A.; Beck, G.; Berman, M.; Bevan, A.; Gannaway, F.; Inguglia, G.; Martin, A.J.; Morris, J.; Bocci, V.; Capodiferro, M.; Chiodi, G.; Dafinei, I.; Drenska, N.V.; Faccini, R.; Ferroni, F.; Gargiulo, C.; Gauzzi, P.; Luci, C.; Lunadei, R.; Martellotti, G.; Pellegrino, F.; Pettinacci, V.; Pinci, D.; Recchia, L.; Ruggeri, D.; Zullo, A.; Camarri, P.; Cardarelli, R.; De Santis, C.; Di Ciaccio, A.; Di Felice, V.; Di Palma, F.; Di Simone, A.; Marcelli, L.; Messi, R.; Moricciani, D.; Sparvoli, R.; Tammaro, S.; Branchini, P.; Budano, A.; Bussino, S.; Ciuchini, M.; Nguyen, F.; Passeri, A.; Ruggieri, F.; Spiriti, E.

2013-01-01

In this Technical Design Report (TDR) we describe the SuperB detector that was to be installed on the SuperB e+e- high luminosity collider. The SuperB asymmetric collider, which was to be constructed on the Tor Vergata campus near the INFN Frascati National Laboratory, was designed to operate both at the Upsilon(4S) center-of-mass energy with a luminosity of 10^{36} cm^{-2}s^{-1} and at the tau/charm production threshold with a luminosity of 10^{35} cm^{-2}s^{-1}. This high luminosity, producing a data sample about a factor 100 larger than present B Factories, would allow investigation of new physics effects in rare decays, CP Violation and Lepton Flavour Violation. This document details the detector design presented in the Conceptual Design Report (CDR) in 2007. The R&D and engineering studies performed to arrive at the full detector design are described, and an updated cost estimate is presented. A combination of a more realistic cost estimates and the unavailability of funds due of the global economic ...

Pioneering SUPER - Small Unit Passively-safe Enclosed Reactor - 15559

International Nuclear Information System (INIS)

Bhownik, P.K.; Gairola, A.; Shamim, J.A.; Suh, K.Y.; Suh, K.S.

2015-01-01

This paper presents the basic features of the Small Unit Passively-safe Enclosed Reactor abbreviated as SUPER, a new reactor system that has been designed and proposed at the Seoul National University's Department of Energy Systems Engineering. SUPER is a small modular reactor system or SMR that is cooled by sub-cooled as well as supercritical water. As a new member of SMRs, SUPER is a small-scale nuclear plant that is designed to be factory-manufactured and shipped as modules to be assembled at a site. The concept offers promising answers to many questions about nuclear power including proliferation resistance, waste management, safety, and startup costs. SUPER is a customized paradigm of a supercritical water reactor or SCWR, a type sharing commonalities with the current fleet of light water reactors, or LWRs. SUPER has evolved from the System-integrated Modular Advance Reactor, or SMART, being developed at the Korea Atomic Energy Research Institute, or KAERI. SUPER enhanced the safety features for robustness, design/equipment simplification for natural convection, multi-purpose application for co-generation flexibilities, suitable for isolated or small electrical grids, just-in-time capacity addition, short construction time, and last, but not least, lower capital cost per unit. The primary objectives of SUPER is to develop the conceptual design for a safe and economic small, natural circulation SCWR, to address the economic and safety attributes of the concept, and to demonstrate its technical feasibilities. (authors)

Super-resolution fluorescence microscopy by stepwise optical saturation

Science.gov (United States)

Zhang, Yide; Nallathamby, Prakash D.; Vigil, Genevieve D.; Khan, Aamir A.; Mason, Devon E.; Boerckel, Joel D.; Roeder, Ryan K.; Howard, Scott S.

2018-01-01

Super-resolution fluorescence microscopy is an important tool in biomedical research for its ability to discern features smaller than the diffraction limit. However, due to its difficult implementation and high cost, the super-resolution microscopy is not feasible in many applications. In this paper, we propose and demonstrate a saturation-based super-resolution fluorescence microscopy technique that can be easily implemented and requires neither additional hardware nor complex post-processing. The method is based on the principle of stepwise optical saturation (SOS), where M steps of raw fluorescence images are linearly combined to generate an image with a M-fold increase in resolution compared with conventional diffraction-limited images. For example, linearly combining (scaling and subtracting) two images obtained at regular powers extends the resolution by a factor of 1.4 beyond the diffraction limit. The resolution improvement in SOS microscopy is theoretically infinite but practically is limited by the signal-to-noise ratio. We perform simulations and experimentally demonstrate super-resolution microscopy with both one-photon (confocal) and multiphoton excitation fluorescence. We show that with the multiphoton modality, the SOS microscopy can provide super-resolution imaging deep in scattering samples. PMID:29675306

Focusing super resolution on the cytoskeleton [version 1; referees: 3 approved

Directory of Open Access Journals (Sweden)

Eric A. Shelden

2016-05-01

Full Text Available Super resolution imaging is becoming an increasingly important tool in the arsenal of methods available to cell biologists. In recognition of its potential, the Nobel Prize for chemistry was awarded to three investigators involved in the development of super resolution imaging methods in 2014. The availability of commercial instruments for super resolution imaging has further spurred the development of new methods and reagents designed to take advantage of super resolution techniques. Super resolution offers the advantages traditionally associated with light microscopy, including the use of gentle fixation and specimen preparation methods, the ability to visualize multiple elements within a single specimen, and the potential to visualize dynamic changes in living specimens over time. However, imaging of living cells over time is difficult and super resolution imaging is computationally demanding. In this review, we discuss the advantages/disadvantages of different super resolution systems for imaging fixed live specimens, with particular regard to cytoskeleton structures.

Ensemble prediction of floods – catchment non-linearity and forecast probabilities

Directory of Open Access Journals (Sweden)

C. Reszler

2007-07-01

Full Text Available Quantifying the uncertainty of flood forecasts by ensemble methods is becoming increasingly important for operational purposes. The aim of this paper is to examine how the ensemble distribution of precipitation forecasts propagates in the catchment system, and to interpret the flood forecast probabilities relative to the forecast errors. We use the 622 km2 Kamp catchment in Austria as an example where a comprehensive data set, including a 500 yr and a 1000 yr flood, is available. A spatially-distributed continuous rainfall-runoff model is used along with ensemble and deterministic precipitation forecasts that combine rain gauge data, radar data and the forecast fields of the ALADIN and ECMWF numerical weather prediction models. The analyses indicate that, for long lead times, the variability of the precipitation ensemble is amplified as it propagates through the catchment system as a result of non-linear catchment response. In contrast, for lead times shorter than the catchment lag time (e.g. 12 h and less, the variability of the precipitation ensemble is decreased as the forecasts are mainly controlled by observed upstream runoff and observed precipitation. Assuming that all ensemble members are equally likely, the statistical analyses for five flood events at the Kamp showed that the ensemble spread of the flood forecasts is always narrower than the distribution of the forecast errors. This is because the ensemble forecasts focus on the uncertainty in forecast precipitation as the dominant source of uncertainty, and other sources of uncertainty are not accounted for. However, a number of analyses, including Relative Operating Characteristic diagrams, indicate that the ensemble spread is a useful indicator to assess potential forecast errors for lead times larger than 12 h.

The structure of the super-W∞(λ) algebra

International Nuclear Information System (INIS)

Bergshoeff, E.; Wit, B. de; Vasiliev, M.

1991-01-01

We give a comprehensive treatment of the super-W ∞ (λ) algebra, an extension of the super-Virasoro algebra that contains generators of spin S ≥ 1/2. The parameter λ defines the embedding of the Virasoro subalgebra. We describe how to obtain the super-W ∞ (λ) algebra from the associative algebra of superspace differential operators. We discuss the structure of this associative algebra and its relation with the so-called wedge algebra, in which the generators for given spin are restricted to finite-dimensional representations of sl(2). From the super-W ∞ (λ) algebra one can obtain a variety of W ∞ algebras by consistent truncations for specific values of λ. Without truncation the algebras are formally isomorphic for different values of λ. We present a realization in terms of the currents of a supersymmetric bc system. (orig.)

Rainfall downscaling of weekly ensemble forecasts using self-organising maps

Directory of Open Access Journals (Sweden)

Masamichi Ohba

2016-03-01

Full Text Available This study presents an application of self-organising maps (SOMs to downscaling medium-range ensemble forecasts and probabilistic prediction of local precipitation in Japan. SOM was applied to analyse and connect the relationship between atmospheric patterns over Japan and local high-resolution precipitation data. Multiple SOM was simultaneously employed on four variables derived from the JRA-55 reanalysis over the area of study (south-western Japan, and a two-dimensional lattice of weather patterns (WPs was obtained. Weekly ensemble forecasts can be downscaled to local precipitation using the obtained multiple SOM. The downscaled precipitation is derived by the five SOM lattices based on the WPs of the global model ensemble forecasts for a particular day in 2009–2011. Because this method effectively handles the stochastic uncertainties from the large number of ensemble members, a probabilistic local precipitation is easily and quickly obtained from the ensemble forecasts. This downscaling of ensemble forecasts provides results better than those from a 20-km global spectral model (i.e. capturing the relatively detailed precipitation distribution over the region. To capture the effect of the detailed pattern differences in each SOM node, a statistical model is additionally concreted for each SOM node. The predictability skill of the ensemble forecasts is significantly improved under the neural network-statistics hybrid-downscaling technique, which then brings a much better skill score than the traditional method. It is expected that the results of this study will provide better guidance to the user community and contribute to the future development of dam-management models.

Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

Science.gov (United States)

Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

2017-06-01

Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

Cluster ensembles, quantization and the dilogarithm

DEFF Research Database (Denmark)

Fock, Vladimir; Goncharov, Alexander B.

2009-01-01

A cluster ensemble is a pair of positive spaces (i.e. varieties equipped with positive atlases), coming with an action of a symmetry group . The space is closely related to the spectrum of a cluster algebra [ 12 ]. The two spaces are related by a morphism . The space is equipped with a closed -form......, possibly degenerate, and the space has a Poisson structure. The map is compatible with these structures. The dilogarithm together with its motivic and quantum avatars plays a central role in the cluster ensemble structure. We define a non-commutative -deformation of the -space. When is a root of unity...

Nonequilibrium statistical mechanics ensemble method

CERN Document Server

Eu, Byung Chan

1998-01-01

In this monograph, nonequilibrium statistical mechanics is developed by means of ensemble methods on the basis of the Boltzmann equation, the generic Boltzmann equations for classical and quantum dilute gases, and a generalised Boltzmann equation for dense simple fluids The theories are developed in forms parallel with the equilibrium Gibbs ensemble theory in a way fully consistent with the laws of thermodynamics The generalised hydrodynamics equations are the integral part of the theory and describe the evolution of macroscopic processes in accordance with the laws of thermodynamics of systems far removed from equilibrium Audience This book will be of interest to researchers in the fields of statistical mechanics, condensed matter physics, gas dynamics, fluid dynamics, rheology, irreversible thermodynamics and nonequilibrium phenomena

Superfield realizations of N=2 super-W3

International Nuclear Information System (INIS)

Ivanov, E.; Krivonos, S.

1992-04-01

We present a manifestly N=2 supersymmetric formulation of N=2 super-W 3 algebra (its classical version) in terms of the spin 1 and spin 2 supercurrents. Two closely related types of the Feigin-Fuchs representation for these supercurrents are found: via two chiral spin 1/2 superfields generating N=2 extended U(1) Kac-Moody algebras and via two free chiral spin 0 superfields. We also construct a one-parameter family of N=2 super Boussinesq equations for which N=2 super-W 3 provides the second Hamiltonian structure. (author). 17 refs

Nonlinear super-resolution nano-optics and applications

CERN Document Server

Wei, Jingsong

2015-01-01

This book covers many advances in the subjects of nano-optics and nano photonics. The author describes the principle and technical schematics of common methods for breaking through the optical diffraction limit and focuses on realizing optical super-resolution with nonlinear effects of thin film materials. The applications of nonlinear optical super-resolution effects in nano-data storage, nanolithography, and nano-imaging are also presented. This book is useful to graduate students majoring in optics and nano science and also serves as a reference book for academic researchers, engineers, technical professionals in the fields of super-resolution optics and laser techniques, nano-optics and nano photonics, nano-data storage, nano imaging, micro/nanofabrication and nanolithography and nonlinear optics.

Quantum canonical ensemble: A projection operator approach

Science.gov (United States)

Magnus, Wim; Lemmens, Lucien; Brosens, Fons

2017-09-01

Knowing the exact number of particles N, and taking this knowledge into account, the quantum canonical ensemble imposes a constraint on the occupation number operators. The constraint particularly hampers the systematic calculation of the partition function and any relevant thermodynamic expectation value for arbitrary but fixed N. On the other hand, fixing only the average number of particles, one may remove the above constraint and simply factorize the traces in Fock space into traces over single-particle states. As is well known, that would be the strategy of the grand-canonical ensemble which, however, comes with an additional Lagrange multiplier to impose the average number of particles. The appearance of this multiplier can be avoided by invoking a projection operator that enables a constraint-free computation of the partition function and its derived quantities in the canonical ensemble, at the price of an angular or contour integration. Introduced in the recent past to handle various issues related to particle-number projected statistics, the projection operator approach proves beneficial to a wide variety of problems in condensed matter physics for which the canonical ensemble offers a natural and appropriate environment. In this light, we present a systematic treatment of the canonical ensemble that embeds the projection operator into the formalism of second quantization while explicitly fixing N, the very number of particles rather than the average. Being applicable to both bosonic and fermionic systems in arbitrary dimensions, transparent integral representations are provided for the partition function ZN and the Helmholtz free energy FN as well as for two- and four-point correlation functions. The chemical potential is not a Lagrange multiplier regulating the average particle number but can be extracted from FN+1 -FN, as illustrated for a two-dimensional fermion gas.

Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

KAUST Repository

Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim

2017-01-01

We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation

An iterative ensemble Kalman filter for reservoir engineering applications

NARCIS (Netherlands)

Krymskaya, M.V.; Hanea, R.G.; Verlaan, M.

2009-01-01

The study has been focused on examining the usage and the applicability of ensemble Kalman filtering techniques to the history matching procedures. The ensemble Kalman filter (EnKF) is often applied nowadays to solving such a problem. Meanwhile, traditional EnKF requires assumption of the

Improving the ensemble-optimization method through covariance-matrix adaptation

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Hof, P.M.J. van den; Jansen, J.D.

2015-01-01

Ensemble optimization (referred to throughout the remainder of the paper as EnOpt) is a rapidly emerging method for reservoirmodel-based production optimization. EnOpt uses an ensemble of controls to approximate the gradient of the objective function with respect to the controls. Current

Parallel quantum computing in a single ensemble quantum computer

International Nuclear Information System (INIS)

Long Guilu; Xiao, L.

2004-01-01

We propose a parallel quantum computing mode for ensemble quantum computer. In this mode, some qubits are in pure states while other qubits are in mixed states. It enables a single ensemble quantum computer to perform 'single-instruction-multidata' type of parallel computation. Parallel quantum computing can provide additional speedup in Grover's algorithm and Shor's algorithm. In addition, it also makes a fuller use of qubit resources in an ensemble quantum computer. As a result, some qubits discarded in the preparation of an effective pure state in the Schulman-Varizani and the Cleve-DiVincenzo algorithms can be reutilized

Fluctuation, stationarity, and ergodic properties of random-matrix ensembles

International Nuclear Information System (INIS)

Pandey, A.

1979-01-01

The properties of random-matrix ensembles and the application of such ensembles to energy-level fluctuations and strength fluctuations are discussed. The two-point correlation function for complex spectra described by the three standard Gaussian ensembles is calculated, and its essential simplicity, displayed by an elementary procedure that derives from the dominance of binary correlations. The resultant function is exact for the unitary case and a very good approximation to the orthogonal and symplectic cases. The same procedure yields the spectrum for a Gaussian orthogonal ensemble (GOE) deformed by a pairing interaction. Several extensions are given and relationships to other problems of current interest are discussed. The standard fluctuation measures are rederived for the GOE, and their extensions to the unitary and symplectic cases are given. The measures are shown to derive, for the most part, from the two-point function, and new relationships between them are established, answering some long-standing questions. Some comparisons with experimental values are also made. All the cluster functions, and therefore the fluctuation measures, are shown to be stationary and strongly ergodic, thus justifying the use of random matrices for individual spectra. Strength fluctuations in the orthogonal ensemble are also considered. The Porter-Thomas distribution in its various forms is rederived and its ergodicity is established

Convergence of the Square Root Ensemble Kalman Filter in the Large Ensemble Limit

Czech Academy of Sciences Publication Activity Database

Kwiatkowski, E.; Mandel, Jan

2015-01-01

Roč. 3, č. 1 (2015), s. 1-17 ISSN 2166-2525 R&D Projects: GA ČR GA13-34856S Institutional support: RVO:67985807 Keywords : data assimilation * Lp laws of large numbers * Hilbert space * ensemble Kalman filter Subject RIV: IN - Informatics, Computer Science

Spatio-temporal behaviour of medium-range ensemble forecasts

Science.gov (United States)

Kipling, Zak; Primo, Cristina; Charlton-Perez, Andrew

2010-05-01

Using the recently-developed mean-variance of logarithms (MVL) diagram, together with the TIGGE archive of medium-range ensemble forecasts from nine different centres, we present an analysis of the spatio-temporal dynamics of their perturbations, and show how the differences between models and perturbation techniques can explain the shape of their characteristic MVL curves. We also consider the use of the MVL diagram to compare the growth of perturbations within the ensemble with the growth of the forecast error, showing that there is a much closer correspondence for some models than others. We conclude by looking at how the MVL technique might assist in selecting models for inclusion in a multi-model ensemble, and suggest an experiment to test its potential in this context.

Microcanonical ensemble and algebra of conserved generators for generalized quantum dynamics

International Nuclear Information System (INIS)

Adler, S.L.; Horwitz, L.P.

1996-01-01

It has recently been shown, by application of statistical mechanical methods to determine the canonical ensemble governing the equilibrium distribution of operator initial values, that complex quantum field theory can emerge as a statistical approximation to an underlying generalized quantum dynamics. This result was obtained by an argument based on a Ward identity analogous to the equipartition theorem of classical statistical mechanics. We construct here a microcanonical ensemble which forms the basis of this canonical ensemble. This construction enables us to define the microcanonical entropy and free energy of the field configuration of the equilibrium distribution and to study the stability of the canonical ensemble. We also study the algebraic structure of the conserved generators from which the microcanonical and canonical ensembles are constructed, and the flows they induce on the phase space. copyright 1996 American Institute of Physics

Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

Science.gov (United States)

Ye, Qiang

2010-01-01

Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

From heavy nuclei to super-heavy nuclei; Des noyaux lourds aux super-lourds

Energy Technology Data Exchange (ETDEWEB)

Theisen, Ch

2003-01-01

The existence of super-heavy nuclei has been predicted nearly fifty years ago. Due to the strong coulomb repulsion, the stabilisation of these nuclei is possible only through shell effects. The reasons for this fragile stability, as well as the theoretical predictions concerning the position of the island of stability are presented in the first part of this lecture. In the second part, experiments and experimental techniques which have been used to synthesize or search for super-heavy elements are described. Spectroscopic studies performed in very heavy elements are presented in the following section. We close this lecture with techniques that are currently being developed in order to reach the superheavy island and to study the structure of very-heavy nuclei. (author)

Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

KAUST Repository

Luo, Xiaodong

2011-12-01

A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used in the Kalman filter. By design, the H∞ filter is more robust than the Kalman filter, in the sense that the estimation error in the H∞ filter in general has a finite growth rate with respect to the uncertainties in assimilation, except for a special case that corresponds to the Kalman filter. The original form of the H∞ filter contains global constraints in time, which may be inconvenient for sequential data assimilation problems. Therefore a variant is introduced that solves some time-local constraints instead, and hence it is called the time-local H∞ filter (TLHF). By analogy to the ensemble Kalman filter (EnKF), the concept of ensemble time-local H∞ filter (EnTLHF) is also proposed. The general form of the EnTLHF is outlined, and some of its special cases are discussed. In particular, it is shown that an EnKF with certain covariance inflation is essentially an EnTLHF. In this sense, the EnTLHF provides a general framework for conducting covariance inflation in the EnKF-based methods. Some numerical examples are used to assess the relative robustness of the TLHF–EnTLHF in comparison with the corresponding KF–EnKF method.

Ensemble system for Part-of-Speech tagging

OpenAIRE

Dell'Orletta, Felice

2009-01-01

The paper contains a description of the Felice-POS-Tagger and of its performance in Evalita 2009. Felice-POS-Tagger is an ensemble system that combines six different POS taggers. When evaluated on the official test set, the ensemble system outperforms each of the single tagger components and achieves the highest accuracy score in Evalita 2009 POS Closed Task. It is shown rst that the errors made from the dierent taggers are complementary, and then how to use this complementary behavior to the...

Learning to Run with Actor-Critic Ensemble

OpenAIRE

Huang, Zhewei; Zhou, Shuchang; Zhuang, BoEr; Zhou, Xinyu

2017-01-01

We introduce an Actor-Critic Ensemble(ACE) method for improving the performance of Deep Deterministic Policy Gradient(DDPG) algorithm. At inference time, our method uses a critic ensemble to select the best action from proposals of multiple actors running in parallel. By having a larger candidate set, our method can avoid actions that have fatal consequences, while staying deterministic. Using ACE, we have won the 2nd place in NIPS'17 Learning to Run competition, under the name of "Megvii-hzw...

Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

KAUST Repository

Luo, Xiaodong; Hoteit, Ibrahim

2011-01-01

A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used

The Formation of Super-Earths by Tidally Forced Turbulence

Science.gov (United States)

Yu, Cong

2017-12-01

The Kepler observations indicate that many exoplanets are super-Earths, which brings about a puzzle for the core-accretion scenario. Since observed super-Earths are in the range of critical mass, they accrete gas efficiently and become gas giants. Theoretically, super-Earths are predicted to be rare in the core-accretion framework. To resolve this contradiction, we propose that the tidally forced turbulent diffusion may affect the heat transport inside the planet. Thermal feedback induced by turbulent diffusion is investigated. We find that the tidally forced turbulence generates pseudo-adiabatic regions within radiative zones, which pushes the radiative-convective boundaries inward. This decreases the cooling luminosity and enhances the Kelvin-Helmholtz (KH) timescale. For a given lifetime of protoplanetary disks (PPDs), there exists a critical threshold for the turbulent diffusivity, ν critical. If ν turb > ν critical, the KH timescale is longer than the disk lifetime and the planet becomes a super-Earth, rather than a gas giant. We find that even a small value of turbulent diffusion has influential effects on the evolution of super-Earths. The ν critical increases with the core mass. We further ascertain that, within the minimum-mass extrasolar nebula, ν critical increases with the semimajor axis. This may explain the feature that super-Earths are common in inner PPD regions, while gas giants are common in outer PPD regions. The predicted envelope mass fraction is not fully consistent with observations. We discuss physical processes, such as late core assembly and mass-loss mechanisms, that may be operating during super-Earth formation.

Time-dependent generalized Gibbs ensembles in open quantum systems

Science.gov (United States)

Lange, Florian; Lenarčič, Zala; Rosch, Achim

2018-04-01

Generalized Gibbs ensembles have been used as powerful tools to describe the steady state of integrable many-particle quantum systems after a sudden change of the Hamiltonian. Here, we demonstrate numerically that they can be used for a much broader class of problems. We consider integrable systems in the presence of weak perturbations which break both integrability and drive the system to a state far from equilibrium. Under these conditions, we show that the steady state and the time evolution on long timescales can be accurately described by a (truncated) generalized Gibbs ensemble with time-dependent Lagrange parameters, determined from simple rate equations. We compare the numerically exact time evolutions of density matrices for small systems with a theory based on block-diagonal density matrices (diagonal ensemble) and a time-dependent generalized Gibbs ensemble containing only a small number of approximately conserved quantities, using the one-dimensional Heisenberg model with perturbations described by Lindblad operators as an example.

Precision bounds for gradient magnetometry with atomic ensembles

Science.gov (United States)

Apellaniz, Iagoba; Urizar-Lanz, Iñigo; Zimborás, Zoltán; Hyllus, Philipp; Tóth, Géza

2018-05-01

We study gradient magnetometry with an ensemble of atoms with arbitrary spin. We calculate precision bounds for estimating the gradient of the magnetic field based on the quantum Fisher information. For quantum states that are invariant under homogeneous magnetic fields, we need to measure a single observable to estimate the gradient. On the other hand, for states that are sensitive to homogeneous fields, a simultaneous measurement is needed, as the homogeneous field must also be estimated. We prove that for the cases studied in this paper, such a measurement is feasible. We present a method to calculate precision bounds for gradient estimation with a chain of atoms or with two spatially separated atomic ensembles. We also consider a single atomic ensemble with an arbitrary density profile, where the atoms cannot be addressed individually, and which is a very relevant case for experiments. Our model can take into account even correlations between particle positions. While in most of the discussion we consider an ensemble of localized particles that are classical with respect to their spatial degree of freedom, we also discuss the case of gradient metrology with a single Bose-Einstein condensate.

Terrestrial planet formation in the presence of migrating super-Earths

International Nuclear Information System (INIS)

Izidoro, André; Morbidelli, Alessandro; Raymond, Sean N.

2014-01-01

Super-Earths with orbital periods less than 100 days are extremely abundant around Sun-like stars. It is unlikely that these planets formed at their current locations. Rather, they likely formed at large distances from the star and subsequently migrated inward. Here we use N-body simulations to study the effect of super-Earths on the accretion of rocky planets. In our simulations, one or more super-Earths migrate inward through a disk of planetary embryos and planetesimals embedded in a gaseous disk. We tested a wide range of migration speeds and configurations. Fast-migrating super-Earths (τ mig ∼ 0.01-0.1 Myr) only have a modest effect on the protoplanetary embryos and planetesimals. Sufficient material survives to form rocky, Earth-like planets on orbits exterior to the super-Earths'. In contrast, slowly migrating super-Earths shepherd rocky material interior to their orbits and strongly deplete the terrestrial planet-forming zone. In this situation any Earth-sized planets in the habitable zone are extremely volatile-rich and are therefore probably not Earth-like.

Autonomous Operation of Super-Regenerative Receiver in BAN

NARCIS (Netherlands)

Kalyanasundaram, P.; Huang, L.; Dolmans, G.; Imamura, K.

2012-01-01

Super-regenerative receiver is one of the potential candidates to achieve ultra low power wireless communication in body area network (BAN). The main limitations of the super-regenerative receiver include the difficulty in choosing a good quench waveform to optimize its sensitivity and selectivity,

Embedded random matrix ensembles in quantum physics

CERN Document Server

Kota, V K B

2014-01-01

Although used with increasing frequency in many branches of physics, random matrix ensembles are not always sufficiently specific to account for important features of the physical system at hand. One refinement which retains the basic stochastic approach but allows for such features consists in the use of embedded ensembles.  The present text is an exhaustive introduction to and survey of this important field. Starting with an easy-to-read introduction to general random matrix theory, the text then develops the necessary concepts from the beginning, accompanying the reader to the frontiers of present-day research. With some notable exceptions, to date these ensembles have primarily been applied in nuclear spectroscopy. A characteristic example is the use of a random two-body interaction in the framework of the nuclear shell model. Yet, topics in atomic physics, mesoscopic physics, quantum information science and statistical mechanics of isolated finite quantum systems can also be addressed using these ensemb...

Understanding ensemble protein folding at atomic detail

International Nuclear Information System (INIS)

Wallin, Stefan; Shakhnovich, Eugene I

2008-01-01

Although far from routine, simulating the folding of specific short protein chains on the computer, at a detailed atomic level, is starting to become a reality. This remarkable progress, which has been made over the last decade or so, allows a fundamental aspect of the protein folding process to be addressed, namely its statistical nature. In order to make quantitative comparisons with experimental kinetic data a complete ensemble view of folding must be achieved, with key observables averaged over the large number of microscopically different folding trajectories available to a protein chain. Here we review recent advances in atomic-level protein folding simulations and the new insight provided by them into the protein folding process. An important element in understanding ensemble folding kinetics are methods for analyzing many separate folding trajectories, and we discuss techniques developed to condense the large amount of information contained in an ensemble of trajectories into a manageable picture of the folding process. (topical review)

Ensemble-free configurational temperature for spin systems

Science.gov (United States)

Palma, G.; Gutiérrez, G.; Davis, S.

2016-12-01

An estimator for the dynamical temperature in an arbitrary ensemble is derived in the framework of the conjugate variables theorem. We prove directly that its average indeed gives the inverse temperature and that it is independent of the ensemble. We test this estimator numerically by a simulation of the two-dimensional X Y model in the canonical ensemble. As this model is critical in the whole region of temperatures below the Berezinski-Kosterlitz-Thouless critical temperature TBKT, we use a generalization of Wolff's unicluster algorithm. The numerical results allow us to confirm the robustness of the analytical expression for the microscopic estimator of the temperature. This microscopic estimator has also the advantage that it gives a direct measure of the thermalization process and can be used to compute absolute errors associated with statistical fluctuations. In consequence, this estimator allows for a direct, absolute, and stringent test of the ergodicity of the underlying Markov process, which encodes the algorithm used in a numerical simulation.

Super-resolution Microscopy in Plant Cell Imaging.

Science.gov (United States)

Komis, George; Šamajová, Olga; Ovečka, Miroslav; Šamaj, Jozef

2015-12-01

Although the development of super-resolution microscopy methods dates back to 1994, relevant applications in plant cell imaging only started to emerge in 2010. Since then, the principal super-resolution methods, including structured-illumination microscopy (SIM), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), and stimulated emission depletion microscopy (STED), have been implemented in plant cell research. However, progress has been limited due to the challenging properties of plant material. Here we summarize the basic principles of existing super-resolution methods and provide examples of applications in plant science. The limitations imposed by the nature of plant material are reviewed and the potential for future applications in plant cell imaging is highlighted. Copyright © 2015 Elsevier Ltd. All rights reserved.

Online probabilistic learning with an ensemble of forecasts

Science.gov (United States)

Thorey, Jean; Mallet, Vivien; Chaussin, Christophe

2016-04-01

Our objective is to produce a calibrated weighted ensemble to forecast a univariate time series. In addition to a meteorological ensemble of forecasts, we rely on observations or analyses of the target variable. The celebrated Continuous Ranked Probability Score (CRPS) is used to evaluate the probabilistic forecasts. However applying the CRPS on weighted empirical distribution functions (deriving from the weighted ensemble) may introduce a bias because of which minimizing the CRPS does not produce the optimal weights. Thus we propose an unbiased version of the CRPS which relies on clusters of members and is strictly proper. We adapt online learning methods for the minimization of the CRPS. These methods generate the weights associated to the members in the forecasted empirical distribution function. The weights are updated before each forecast step using only past observations and forecasts. Our learning algorithms provide the theoretical guarantee that, in the long run, the CRPS of the weighted forecasts is at least as good as the CRPS of any weighted ensemble with weights constant in time. In particular, the performance of our forecast is better than that of any subset ensemble with uniform weights. A noteworthy advantage of our algorithm is that it does not require any assumption on the distributions of the observations and forecasts, both for the application and for the theoretical guarantee to hold. As application example on meteorological forecasts for photovoltaic production integration, we show that our algorithm generates a calibrated probabilistic forecast, with significant performance improvements on probabilistic diagnostic tools (the CRPS, the reliability diagram and the rank histogram).

Extreme super-resolution using the spherical geodesic waveguide

Science.gov (United States)

Miñano, Juan Carlos; González, Juan Carlos; Benítez, Pablo; Grabovičkić, Dejan

2012-06-01

Leonhardt demonstrated (2009) that the 2D Maxwell Fish Eye lens (MFE) can focus perfectly 2D Helmholtz waves of arbitrary frequency, i.e., it can transport perfectly an outward (monopole) 2D Helmholtz wave field, generated by a point source, towards a "perfect point drain" located at the corresponding image point. Moreover, a prototype with λ/5 super-resolution (SR) property for one microwave frequency has been manufactured and tested (Ma et al, 2010). Although this prototype has been loaded with an impedance different from the "perfect point drain", it has shown super-resolution property. However, neither software simulations nor experimental measurements for a broad band of frequencies have yet been reported. Here we present steady state simulations for two cases, using perfect drain as suggested by Leonhardt and without perfect drain as in the prototype. All the simulations have been done using a device equivalent to the MFE, called the Spherical Geodesic Waveguide (SGW). The results show the super-resolution up to λ/3000, for the system loaded with the perfect drain, and up to λ /500 for a not perfect load. In both cases super-resolution only happens for discrete number of frequencies. Out of these frequencies, the SGW does not show super-resolution in the analysis carried out.

Improving the ensemble optimization method through covariance matrix adaptation (CMA-EnOpt)

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Hof, P.M.J. van den; Jansen, J.D.

2013-01-01

Ensemble Optimization (EnOpt) is a rapidly emerging method for reservoir model based production optimization. EnOpt uses an ensemble of controls to approximate the gradient of the objective function with respect to the controls. Current implementations of EnOpt use a Gaussian ensemble with a

Scalable quantum information processing with atomic ensembles and flying photons

International Nuclear Information System (INIS)

Mei Feng; Yu Yafei; Feng Mang; Zhang Zhiming

2009-01-01

We present a scheme for scalable quantum information processing with atomic ensembles and flying photons. Using the Rydberg blockade, we encode the qubits in the collective atomic states, which could be manipulated fast and easily due to the enhanced interaction in comparison to the single-atom case. We demonstrate that our proposed gating could be applied to generation of two-dimensional cluster states for measurement-based quantum computation. Moreover, the atomic ensembles also function as quantum repeaters useful for long-distance quantum state transfer. We show the possibility of our scheme to work in bad cavity or in weak coupling regime, which could much relax the experimental requirement. The efficient coherent operations on the ensemble qubits enable our scheme to be switchable between quantum computation and quantum communication using atomic ensembles.

Statistical Analysis of Protein Ensembles

Science.gov (United States)

Máté, Gabriell; Heermann, Dieter

2014-04-01

As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

Ensemble Forecasts with Useful Skill-Spread Relationships for African meningitis and Asia Streamflow Forecasting

Science.gov (United States)

Hopson, T. M.

2014-12-01

One potential benefit of an ensemble prediction system (EPS) is its capacity to forecast its own forecast error through the ensemble spread-error relationship. In practice, an EPS is often quite limited in its ability to represent the variable expectation of forecast error through the variable dispersion of the ensemble, and perhaps more fundamentally, in its ability to provide enough variability in the ensembles dispersion to make the skill-spread relationship even potentially useful (irrespective of whether the EPS is well-calibrated or not). In this paper we examine the ensemble skill-spread relationship of an ensemble constructed from the TIGGE (THORPEX Interactive Grand Global Ensemble) dataset of global forecasts and a combination of multi-model and post-processing approaches. Both of the multi-model and post-processing techniques are based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. The methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. A context for these concepts is provided by assessing the constructed ensemble in forecasting district-level humidity impacting the incidence of meningitis in the meningitis belt of Africa, and in forecasting flooding events in the Brahmaputra and Ganges basins of South Asia.

EUROv Super Beam Studies

International Nuclear Information System (INIS)

Dracos, Marcos

2011-01-01

Neutrino Super Beams use conventional techniques to significantly increase the neutrino beam intensity compared to the present neutrino facilities. An essential part of these facilities is an intense proton driver producing a beam power higher than a MW. The protons hit a target able to accept the high proton beam intensity. The produced charged particles are focused by a system of magnetic horns towards the experiment detectors. The main challenge of these projects is to deal with the high beam intensity for many years. New high power neutrino facilities could be build at CERN profiting from an eventual construction of a high power proton driver. The European FP7 Design Study EUROv, among other neutrino beams, studies this Super Beam possibility. This paper will give the latest developments in this direction.

Adiabatic passage and ensemble control of quantum systems

International Nuclear Information System (INIS)

Leghtas, Z; Sarlette, A; Rouchon, P

2011-01-01

This paper considers population transfer between eigenstates of a finite quantum ladder controlled by a classical electric field. Using an appropriate change of variables, we show that this setting can be set in the framework of adiabatic passage, which is known to facilitate ensemble control of quantum systems. Building on this insight, we present a mathematical proof of robustness for a control protocol-chirped pulse-practised by experimentalists to drive an ensemble of quantum systems from the ground state to the most excited state. We then propose new adiabatic control protocols using a single chirped and amplitude-shaped pulse, to robustly perform any permutation of eigenstate populations, on an ensemble of systems with unknown coupling strengths. These adiabatic control protocols are illustrated by simulations on a four-level ladder.

Steam generator development in France for the Super Phenix project; Generateurs de vapeur developpes en France pour Super Phenix

Energy Technology Data Exchange (ETDEWEB)

Robin, M G

1975-07-01

'Steam Generator Development for Super Phenix Project'. The development program of steam generators studied by Fives-Cail Babcock and Stein Industrie Companies, jointly with CEA end EDF, for the Super Phenix 1200 MWe Fast Breeder Power Plant, is presented. The main characteristics of both sodium heated steam generators are emphasized and experimental studies related to their key features are reported. (author)

Face Recognition by Metropolitan Police Super-Recognisers.

Science.gov (United States)

Robertson, David J; Noyes, Eilidh; Dowsett, Andrew J; Jenkins, Rob; Burton, A Mike

2016-01-01

Face recognition is used to prove identity across a wide variety of settings. Despite this, research consistently shows that people are typically rather poor at matching faces to photos. Some professional groups, such as police and passport officers, have been shown to perform just as poorly as the general public on standard tests of face recognition. However, face recognition skills are subject to wide individual variation, with some people showing exceptional ability-a group that has come to be known as 'super-recognisers'. The Metropolitan Police Force (London) recruits 'super-recognisers' from within its ranks, for deployment on various identification tasks. Here we test four working super-recognisers from within this police force, and ask whether they are really able to perform at levels above control groups. We consistently find that the police 'super-recognisers' perform at well above normal levels on tests of unfamiliar and familiar face matching, with degraded as well as high quality images. Recruiting employees with high levels of skill in these areas, and allocating them to relevant tasks, is an efficient way to overcome some of the known difficulties associated with unfamiliar face recognition.

Conductor and Ensemble Performance Expressivity and State Festival Ratings

Science.gov (United States)

Price, Harry E.; Chang, E. Christina

2005-01-01

This study is the second in a series examining the relationship between conducting and ensemble performance. The purpose was to further examine the associations among conductor, ensemble performance expressivity, and festival ratings. Participants were asked to rate the expressivity of video-only conducting and parallel audio-only excerpts from a…

Constructing Support Vector Machine Ensembles for Cancer Classification Based on Proteomic Profiling

Institute of Scientific and Technical Information of China (English)

Yong Mao; Xiao-Bo Zhou; Dao-Ying Pi; You-Xian Sun

2005-01-01

In this study, we present a constructive algorithm for training cooperative support vector machine ensembles (CSVMEs). CSVME combines ensemble architecture design with cooperative training for individual SVMs in ensembles. Unlike most previous studies on training ensembles, CSVME puts emphasis on both accuracy and collaboration among individual SVMs in an ensemble. A group of SVMs selected on the basis of recursive classifier elimination is used in CSVME, and the number of the individual SVMs selected to construct CSVME is determined by 10-fold cross-validation. This kind of SVME has been tested on two ovarian cancer datasets previously obtained by proteomic mass spectrometry. By combining several individual SVMs, the proposed method achieves better performance than the SVME of all base SVMs.

Hot super-Earths stripped by their host stars.

Science.gov (United States)

Lundkvist, M S; Kjeldsen, H; Albrecht, S; Davies, G R; Basu, S; Huber, D; Justesen, A B; Karoff, C; Silva Aguirre, V; Van Eylen, V; Vang, C; Arentoft, T; Barclay, T; Bedding, T R; Campante, T L; Chaplin, W J; Christensen-Dalsgaard, J; Elsworth, Y P; Gilliland, R L; Handberg, R; Hekker, S; Kawaler, S D; Lund, M N; Metcalfe, T S; Miglio, A; Rowe, J F; Stello, D; Tingley, B; White, T R

2016-04-11

Simulations predict that hot super-Earth sized exoplanets can have their envelopes stripped by photoevaporation, which would present itself as a lack of these exoplanets. However, this absence in the exoplanet population has escaped a firm detection. Here we demonstrate, using asteroseismology on a sample of exoplanets and exoplanet candidates observed during the Kepler mission that, while there is an abundance of super-Earth sized exoplanets with low incident fluxes, none are found with high incident fluxes. We do not find any exoplanets with radii between 2.2 and 3.8 Earth radii with incident flux above 650 times the incident flux on Earth. This gap in the population of exoplanets is explained by evaporation of volatile elements and thus supports the predictions. The confirmation of a hot-super-Earth desert caused by evaporation will add an important constraint on simulations of planetary systems, since they must be able to reproduce the dearth of close-in super-Earths.

Equivalence of Linear MMSE Detection in DS-CDMA and MC-CDMA Systems over Time and Frequency Selective Channels

Directory of Open Access Journals (Sweden)

Tamer A. Kadous

2003-01-01

Full Text Available The goal of this paper is to compare the performance of the linear minimum mean square error (MMSE detector for a class of code division multiple access (CDMA systems in time and frequency selective channels. Specifically, we consider direct sequence (DS-CDMA, multicarrier (MC-CDMA, and the MC-DS-CDMA systems. Two key tools are used in our development. First, a general time-frequency framework that includes the different CDMA systems as special cases. Second, the duality between time and frequency domains that is used to derive equivalences between the different CDMA systems operating over purely frequency selective and purely time selective channels. We then combine the insights obtained from these special cases to assess the performance of CDMA systems over time and frequency selective channels. We provide sufficient conditions for the codes employed by the CDMA systems for the equivalences to hold. Numerical results are presented to illustrate the results.

Sequential Ensembles Tolerant to Synthetic Aperture Radar (SAR Soil Moisture Retrieval Errors

Directory of Open Access Journals (Sweden)

Ju Hyoung Lee

2016-04-01

Full Text Available Due to complicated and undefined systematic errors in satellite observation, data assimilation integrating model states with satellite observations is more complicated than field measurements-based data assimilation at a local scale. In the case of Synthetic Aperture Radar (SAR soil moisture, the systematic errors arising from uncertainties in roughness conditions are significant and unavoidable, but current satellite bias correction methods do not resolve the problems very well. Thus, apart from the bias correction process of satellite observation, it is important to assess the inherent capability of satellite data assimilation in such sub-optimal but more realistic observational error conditions. To this end, time-evolving sequential ensembles of the Ensemble Kalman Filter (EnKF is compared with stationary ensemble of the Ensemble Optimal Interpolation (EnOI scheme that does not evolve the ensembles over time. As the sensitivity analysis demonstrated that the surface roughness is more sensitive to the SAR retrievals than measurement errors, it is a scope of this study to monitor how data assimilation alters the effects of roughness on SAR soil moisture retrievals. In results, two data assimilation schemes all provided intermediate values between SAR overestimation, and model underestimation. However, under the same SAR observational error conditions, the sequential ensembles approached a calibrated model showing the lowest Root Mean Square Error (RMSE, while the stationary ensemble converged towards the SAR observations exhibiting the highest RMSE. As compared to stationary ensembles, sequential ensembles have a better tolerance to SAR retrieval errors. Such inherent nature of EnKF suggests an operational merit as a satellite data assimilation system, due to the limitation of bias correction methods currently available.

Pulsating stars in SuperWASP

Directory of Open Access Journals (Sweden)

Holdsworth Daniel L.

2017-01-01

Full Text Available SuperWASP is one of the largest ground-based surveys for transiting exoplanets. To date, it has observed over 31 million stars. Such an extensive database of time resolved photometry holds the potential for extensive searches of stellar variability, and provide solid candidates for the upcoming TESS mission. Previous work by e.g. [15], [5], [12] has shown that the WASP archive provides a wealth of pulsationally variable stars. In this talk I will provide an overview of the SuperWASP project, present some of the published results from the survey, and some of the on-going work to identify key targets for the TESS mission.

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

Science.gov (United States)

Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

2018-01-01

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

Analyzing the impact of changing size and composition of a crop model ensemble

Science.gov (United States)

Rodríguez, Alfredo

2017-04-01

The use of an ensemble of crop growth simulation models is a practice recently adopted in order to quantify aspects of uncertainties in model simulations. Yet, while the climate modelling community has extensively investigated the properties of model ensembles and their implications, this has hardly been investigated for crop model ensembles (Wallach et al., 2016). In their ensemble of 27 wheat models, Martre et al. (2015) found that the accuracy of the multi-model ensemble-average only increases up to an ensemble size of ca. 10, but does not improve when including more models in the analysis. However, even when this number of members is reached, questions about the impact of the addition or removal of a member to/from the ensemble arise. When selecting ensemble members, identifying members with poor performance or giving implausible results can make a large difference on the outcome. The objective of this study is to set up a methodology that defines indicators to show the effects of changing the ensemble composition and size on simulation results, when a selection procedure of ensemble members is applied. Ensemble mean or median, and variance are measures used to depict ensemble results among other indicators. We are utilizing simulations from an ensemble of wheat models that have been used to construct impact response surfaces (Pirttioja et al., 2015) (IRSs). These show the response of an impact variable (e.g., crop yield) to systematic changes in two explanatory variables (e.g., precipitation and temperature). Using these, we compare different sub-ensembles in terms of the mean, median and spread, and also by comparing IRSs. The methodology developed here allows comparing an ensemble before and after applying any procedure that changes the ensemble composition and size by measuring the impact of this decision on the ensemble central tendency measures. The methodology could also be further developed to compare the effect of changing ensemble composition and size

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

Impact of ensemble learning in the assessment of skeletal maturity.

Science.gov (United States)

Cunha, Pedro; Moura, Daniel C; Guevara López, Miguel Angel; Guerra, Conceição; Pinto, Daniela; Ramos, Isabel

2014-09-01

The assessment of the bone age, or skeletal maturity, is an important task in pediatrics that measures the degree of maturation of children's bones. Nowadays, there is no standard clinical procedure for assessing bone age and the most widely used approaches are the Greulich and Pyle and the Tanner and Whitehouse methods. Computer methods have been proposed to automatize the process; however, there is a lack of exploration about how to combine the features of the different parts of the hand, and how to take advantage of ensemble techniques for this purpose. This paper presents a study where the use of ensemble techniques for improving bone age assessment is evaluated. A new computer method was developed that extracts descriptors for each joint of each finger, which are then combined using different ensemble schemes for obtaining a final bone age value. Three popular ensemble schemes are explored in this study: bagging, stacking and voting. Best results were achieved by bagging with a rule-based regression (M5P), scoring a mean absolute error of 10.16 months. Results show that ensemble techniques improve the prediction performance of most of the evaluated regression algorithms, always achieving best or comparable to best results. Therefore, the success of the ensemble methods allow us to conclude that their use may improve computer-based bone age assessment, offering a scalable option for utilizing multiple regions of interest and combining their output.

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

Directory of Open Access Journals (Sweden)

Joeri Ruyssinck

Full Text Available One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made

Isospin impurity and super-allowed {beta} transitions; Impurite d`isospin et transitions {beta} super-permises

Energy Technology Data Exchange (ETDEWEB)

Sagawa, H. [Center for Mathematical Science, University of Aizu, Aizu-Wakamatsu, Fukushima 965 (Japan); Van Giai Nguyen [Theoretical Physics Division, Inst. de Physique Nucleaire, Paris-11 Univ., 91 - Orsay (France); Suzuki, T. [Department of Physics, Nihon University, Tokyo 156 (Japan)

1999-10-01

We study the effect of isospin impurity on the super-allowed Fermi {beta} decay using microscopic HF and RPA (or TDA) model taking into account CSB and CIB interactions. It is found that the isospin impurity of N = Z nuclei gives enhancement of the sum rule of Fermi transition probabilities. On the other hand, the super-allowed transitions between odd-odd J = 0 nuclei and even-even J = 0 nuclei are quenched because on the cancellation of the isospin impurity effects of mother and daughter nuclei. An implication of the calculated Fermi transition rate on the unitarity of Cabbibo-Kobayashi-Maskawa mixing matrix is also discussed. (authors) 3 refs., 1 fig.

Ensemble of classifiers based network intrusion detection system performance bound

CSIR Research Space (South Africa)

Mkuzangwe, Nenekazi NP

2017-11-01

Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

A Ruby API to query the Ensembl database for genomic features.

Science.gov (United States)

Strozzi, Francesco; Aerts, Jan

2011-04-01

The Ensembl database makes genomic features available via its Genome Browser. It is also possible to access the underlying data through a Perl API for advanced querying. We have developed a full-featured Ruby API to the Ensembl databases, providing the same functionality as the Perl interface with additional features. A single Ruby API is used to access different releases of the Ensembl databases and is also able to query multi-species databases. Most functionality of the API is provided using the ActiveRecord pattern. The library depends on introspection to make it release independent. The API is available through the Rubygem system and can be installed with the command gem install ruby-ensembl-api.

An Adaptive Approach to Mitigate Background Covariance Limitations in the Ensemble Kalman Filter

KAUST Repository

Song, Hajoon

2010-07-01

A new approach is proposed to address the background covariance limitations arising from undersampled ensembles and unaccounted model errors in the ensemble Kalman filter (EnKF). The method enhances the representativeness of the EnKF ensemble by augmenting it with new members chosen adaptively to add missing information that prevents the EnKF from fully fitting the data to the ensemble. The vectors to be added are obtained by back projecting the residuals of the observation misfits from the EnKF analysis step onto the state space. The back projection is done using an optimal interpolation (OI) scheme based on an estimated covariance of the subspace missing from the ensemble. In the experiments reported here, the OI uses a preselected stationary background covariance matrix, as in the hybrid EnKF–three-dimensional variational data assimilation (3DVAR) approach, but the resulting correction is included as a new ensemble member instead of being added to all existing ensemble members. The adaptive approach is tested with the Lorenz-96 model. The hybrid EnKF–3DVAR is used as a benchmark to evaluate the performance of the adaptive approach. Assimilation experiments suggest that the new adaptive scheme significantly improves the EnKF behavior when it suffers from small size ensembles and neglected model errors. It was further found to be competitive with the hybrid EnKF–3DVAR approach, depending on ensemble size and data coverage.

A new six-component super soliton hierarchy and its self-consistent sources and conservation laws

International Nuclear Information System (INIS)

Wei Han-yu; Xia Tie-cheng

2016-01-01

A new six-component super soliton hierarchy is obtained based on matrix Lie super algebras. Super trace identity is used to furnish the super Hamiltonian structures for the resulting nonlinear super integrable hierarchy. After that, the self-consistent sources of the new six-component super soliton hierarchy are presented. Furthermore, we establish the infinitely many conservation laws for the integrable super soliton hierarchy. (paper)

Impressive Super Phenix

International Nuclear Information System (INIS)

Olds, F.C.

1979-01-01

The 1200-MWe fast breeder reactor, Super Phenix at Creys-Malville, is scheduled for commercial operation in 1983. This is the world's first near-commercial-sized fast breeder. As a near-commercial-sized unit, it represents essentially the technology and hardware of the first fully commercial follow-on units. In its size, its components, its design, the technology it represents, and its project schedule, it is impressive. As of May 1979, the Super Phenix nuclear steam boiler in the Creys-Malville plant bore an estimated cost of $700 million, without fuel. The total cost of the Creys-Malville plant now is estimated at about $1.4 billion. This is about twice the cost of a comparable standardized PWR being built in France today. However, it should be borne in mind that Creys-Malville carries the high cost of a first-of-the-line prototype, and that France's PWRs are standardized, second-generation units. Electricity from Creys-Malville is estimated to cost a little more than electricity would cost from a coal-fired plant complete with flue gas scrubbing

Super-Group Field Cosmology in Batalin-Vilkovisky Formulation

Science.gov (United States)

Upadhyay, Sudhaker

2016-09-01

In this paper we study the third quantized super-group field cosmology, a model in multiverse scenario, in Batalin-Vilkovisky (BV) formulation. Further, we propose the superfield/super-antifield dependent BRST symmetry transformations. Within this formulation we establish connection between the two different solutions of the quantum master equation within the BV formulation.

Nonlinear super-W algebras at fixed central charge

NARCIS (Netherlands)

Bergshoeff, E.

1991-01-01

We discuss how a class of nonlinear higher-spin superalgebras, containing a Virasoro subalgebra at fixed central charge, can be obtained from a realisation of the super-W∞(λ) algebra in terms of a supersymmetric BC system. We explicitly work out the example of the nonlinear super-W2 algebra.

Conservation laws and self-consistent sources for a super-CKdV equation hierarchy

International Nuclear Information System (INIS)

Li Li

2011-01-01

From the super-matrix Lie algebras, we consider a super-extension of the CKdV equation hierarchy in the present Letter, and propose the super-CKdV hierarchy with self-consistent sources. Furthermore, we establish the infinitely many conservation laws for the integrable super-CKdV hierarchy.

Conservation laws and self-consistent sources for a super-CKdV equation hierarchy

Energy Technology Data Exchange (ETDEWEB)

Li Li, E-mail: li07099@163.co [College of Maths and Systematic Science, Shenyang Normal University, Shenyang 110034 (China)

2011-03-14

From the super-matrix Lie algebras, we consider a super-extension of the CKdV equation hierarchy in the present Letter, and propose the super-CKdV hierarchy with self-consistent sources. Furthermore, we establish the infinitely many conservation laws for the integrable super-CKdV hierarchy.

Acoustic Design of Super-light Structures

DEFF Research Database (Denmark)

Christensen, Jacob Ellehauge; Hertz, Kristian Dahl; Brunskog, Jonas

in a controlled laboratory environment have been conducted with the element in order to evaluate its performance in airborne and impact sound insulation. These results have been employed in simulations of the flanking transmission to estimate the in-situ performance of the super-light slab element. The flanking...... aggregate (leca) along with a newly developed technology called pearl-chain reinforcement, which is a system for post-tensioning. Here, it is shown how to combine these technologies within a precast super-light slab element, while honoring the requirements of a holistic design. Acoustic experiments...

Covariant super reggeon calculus for superstrings

International Nuclear Information System (INIS)

Petersen, J.L.; Sidenius, J.R.; Tollsten, A.K.

1988-07-01

A previously developed formalism for the bosonic string is extended to the Neveu-Schwarz-Ramond string using 2-d superspace techniques throughout. 3-string vertices for NS- and R-strings are constructed, sewing rules developed, and the technique of quasi-superconformal modes is set up for constructing the measure on super moduli space. Symmetries, such as superconformal invariance and BRST-invariance, are guaranteed ab initio. Picture changing and bosonization are avoided. Examples are given. The formalism should allow a superstring loop calculus based on supermoduli. Results concerning the ensuing super-Schottky description are given. (orig.)

Adaptive calibration of (u,v)‐wind ensemble forecasts

DEFF Research Database (Denmark)

Pinson, Pierre

2012-01-01

of sufficient reliability. The original framework introduced here allows for an adaptive bivariate calibration of these ensemble forecasts. The originality of this methodology lies in the fact that calibrated ensembles still consist of a set of (space–time) trajectories, after translation and dilation...... of translation and dilation factors are discussed. Copyright © 2012 Royal Meteorological Society...

Modeling polydispersive ensembles of diamond nanoparticles

International Nuclear Information System (INIS)

Barnard, Amanda S

2013-01-01

While significant progress has been made toward production of monodispersed samples of a variety of nanoparticles, in cases such as diamond nanoparticles (nanodiamonds) a significant degree of polydispersivity persists, so scaling-up of laboratory applications to industrial levels has its challenges. In many cases, however, monodispersivity is not essential for reliable application, provided that the inevitable uncertainties are just as predictable as the functional properties. As computational methods of materials design are becoming more widespread, there is a growing need for robust methods for modeling ensembles of nanoparticles, that capture the structural complexity characteristic of real specimens. In this paper we present a simple statistical approach to modeling of ensembles of nanoparticles, and apply it to nanodiamond, based on sets of individual simulations that have been carefully selected to describe specific structural sources that are responsible for scattering of fundamental properties, and that are typically difficult to eliminate experimentally. For the purposes of demonstration we show how scattering in the Fermi energy and the electronic band gap are related to different structural variations (sources), and how these results can be combined strategically to yield statistically significant predictions of the properties of an entire ensemble of nanodiamonds, rather than merely one individual ‘model’ particle or a non-representative sub-set. (paper)

Performance Evaluations for Super-Resolution Mosaicing on UAS Surveillance Videos

Directory of Open Access Journals (Sweden)

Aldo Camargo

2013-05-01

Full Text Available Abstract Unmanned Aircraft Systems (UAS have been widely applied for reconnaissance and surveillance by exploiting information collected from the digital imaging payload. The super-resolution (SR mosaicing of low-resolution (LR UAS surveillance video frames has become a critical requirement for UAS video processing and is important for further effective image understanding. In this paper we develop a novel super-resolution framework, which does not require the construction of sparse matrices. The proposed method implements image operations in the spatial domain and applies an iterated back-projection to construct super-resolution mosaics from the overlapping UAS surveillance video frames. The Steepest Descent method, the Conjugate Gradient method and the Levenberg-Marquardt algorithm are used to numerically solve the nonlinear optimization problem for estimating a super-resolution mosaic. A quantitative performance comparison in terms of computation time and visual quality of the super-resolution mosaics through the three numerical techniques is presented.

Impedance measurement and modelling of super-capacitors for railway applications

Energy Technology Data Exchange (ETDEWEB)

Hammar, A.; Chabas, J. [Societe Nationale des Chemins de fer Francais (SNCF), Dir. de la Recherche, 75 - Paris (France); Coquery, G.; Lallemand, R. [Institut National de Recherche sur les Transports et leur Securite (INRETS), Lab. des Technologies Nouvelles, 94 - Arcueil (France); Rojat, G.; Venet, P. [Lyon-1 Univ. Claude Bernard, CEGELY, 69 - Villeurbanne (France)

2004-07-01

Railways and electrical traction systems require high power rates to achieve their operating performances. Systems of power supply based on super-capacitors should offer high power density along with good energy efficiency and expected operating safety. We investigate general behaviours of super-capacitors with two powerful methods of analysis. The first is constant charge/discharge current at high level value (500 A), the second is impedance spectroscopy which leads to the acquisition of a set of parameters that are considered sufficient to describe general properties of super-capacitor, in particular the state of health and the available energy in any operating conditions. An electrical circuit model is defined for super-capacitors based on activated carbon and organic electrolyte. It takes into account the dependence of super-capacitor to voltage and current. The mixture of data of the two methods permits to obtain a representative model for power applications. Matlab/Simulink simulations are shown to verify the validity of the model. (authors)

The 2015 super-resolution microscopy roadmap

International Nuclear Information System (INIS)

Hell, Stefan W; Sahl, Steffen J; Bates, Mark; Jakobs, Stefan; Zhuang, Xiaowei; Heintzmann, Rainer; Booth, Martin J; Bewersdorf, Joerg; Shtengel, Gleb; Hess, Harald; Tinnefeld, Philip; Honigmann, Alf; Testa, Ilaria; Cognet, Laurent; Lounis, Brahim; Ewers, Helge; Davis, Simon J; Eggeling, Christian; Klenerman, David; Willig, Katrin I

2015-01-01

Far-field optical microscopy using focused light is an important tool in a number of scientific disciplines including chemical, (bio)physical and biomedical research, particularly with respect to the study of living cells and organisms. Unfortunately, the applicability of the optical microscope is limited, since the diffraction of light imposes limitations on the spatial resolution of the image. Consequently the details of, for example, cellular protein distributions, can be visualized only to a certain extent. Fortunately, recent years have witnessed the development of ‘super-resolution’ far-field optical microscopy (nanoscopy) techniques such as stimulated emission depletion (STED), ground state depletion (GSD), reversible saturated optical (fluorescence) transitions (RESOLFT), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) or saturated structured illumination microscopy (SSIM), all in one way or another addressing the problem of the limited spatial resolution of far-field optical microscopy. While SIM achieves a two-fold improvement in spatial resolution compared to conventional optical microscopy, STED, RESOLFT, PALM/STORM, or SSIM have all gone beyond, pushing the limits of optical image resolution to the nanometer scale. Consequently, all super-resolution techniques open new avenues of biomedical research. Because the field is so young, the potential capabilities of different super-resolution microscopy approaches have yet to be fully explored, and uncertainties remain when considering the best choice of methodology. Thus, even for experts, the road to the future is sometimes shrouded in mist. The super-resolution optical microscopy roadmap of Journal of Physics D: Applied Physics addresses this need for clarity. It provides guidance to the outstanding questions through a collection of short review articles from experts in the field, giving a thorough

Multivariate localization methods for ensemble Kalman filtering

KAUST Repository

Roh, S.

2015-12-03

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Microcanonical ensemble extensive thermodynamics of Tsallis statistics

International Nuclear Information System (INIS)

Parvan, A.S.

2005-01-01

The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics.The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ = 1/q - 1 in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z bar = 1/(q - 1)N = const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

Multivariate localization methods for ensemble Kalman filtering

KAUST Repository

Roh, S.

2015-05-08

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Multivariate localization methods for ensemble Kalman filtering

KAUST Repository

Roh, S.; Jun, M.; Szunyogh, I.; Genton, Marc G.

2015-01-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Multivariate localization methods for ensemble Kalman filtering

Science.gov (United States)

Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

2015-12-01

In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

Microcanonical ensemble extensive thermodynamics of Tsallis statistics

International Nuclear Information System (INIS)

Parvan, A.S.

2006-01-01

The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics. The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ=1/(q-1) in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z-bar =1/(q-1)N=const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

N=2 super - W{sub 3}{sup (2)} algebra in superfields

Energy Technology Data Exchange (ETDEWEB)

Krivonos, S; Sorin, A [Joint Inst. for Nuclear Research, Dubna (Russian Federation). Lab. of Theoretical Physics; [Istituto Nazionale di Fisica Nucleare, Frascati (Italy); Ivanov, E [Joint Inst. for Nuclear Research, Dubna (Russian Federation). Lab. of Theoretical Physics

1995-05-01

It is presented a manifestly N=2 supersymmetric formulation of N=2 super-W{sub 3}{sup (2)} algebra (its classical version) in terms of the spin 1 unconstrained generating a N=2 superconformal subalgebra and the spins 1/2, 2 fermionic constrained supercurrents. It is considered a superfield reduction of N=2 super-W{sub 3}{sup (2)} to N=2 super-W{sub 3} and construct a family of evolution equations for which N=2 super-W{sub 3}{sup (2)} provides the second Hamiltonian structure.

Super Bowli teooria soovitab aktsiaid osta / Fredy-Edwin Esse

Index Scriptorium Estoniae

Esse, Fredy-Edwin

2011-01-01

Super Bowli teooria kohaselt tõuseb Dow Jones, kui võidab algupärase NFL-i meeskond. MarketWatchi peaökonomist Irwin Keller avaldab arvamust, miks tasuks investoritel Super Bowli tulemustele tähelepanu pöörata

Single-particle model of a strongly driven, dense, nanoscale quantum ensemble

Science.gov (United States)

DiLoreto, C. S.; Rangan, C.

2018-01-01

We study the effects of interatomic interactions on the quantum dynamics of a dense, nanoscale, atomic ensemble driven by a strong electromagnetic field. We use a self-consistent, mean-field technique based on the pseudospectral time-domain method and a full, three-directional basis to solve the coupled Maxwell-Liouville equations. We find that interatomic interactions generate a decoherence in the state of an ensemble on a much faster time scale than the excited-state lifetime of individual atoms. We present a single-particle model of the driven, dense ensemble by incorporating interactions into a dephasing rate. This single-particle model reproduces the essential physics of the full simulation and is an efficient way of rapidly estimating the collective dynamics of a dense ensemble.

Super-resolution Phase Tomography

KAUST Repository

Depeursinge, Christian; Cotte, Yann; Toy, Fatih; Jourdain, Pascal; Boss, Daiel; Marquet, Pierre; Magistretti, Pierre J.

2013-01-01

Digital Holographic Microscopy (DHM) yields reconstructed complex wavefields. It allows synthesizing the aperture of a virtual microscope up to 2π, offering super-resolution phase images. Live images of micro-organisms and neurons with resolution less than 100 nm are presented.

Super-resolution Phase Tomography

KAUST Repository

Depeursinge, Christian

2013-04-21

Digital Holographic Microscopy (DHM) yields reconstructed complex wavefields. It allows synthesizing the aperture of a virtual microscope up to 2π, offering super-resolution phase images. Live images of micro-organisms and neurons with resolution less than 100 nm are presented.

New idea on the classification of world super-large deposits

International Nuclear Information System (INIS)

Tong Hangshou

2012-01-01

According to the theory of 'multi factors and compound genesis', 'complexity of mineralization' and 'metallogenic series', this paper proposed a new classification idea on the world super-large deposits with the combination of new results on the study of global background for super-large deposits and the model of 'conjugation of multi-source and focus of multi-factors'. 15 super-large deposits with the reserve over 50000 t were studied as the ases, 6 types and 13 sub-types of economics-genesis have been divided for the super-large deposit. The classification is discoursed with symbols and worlds and brief introduction on typical deposit. (authors)

Research Advances in High-Yielding Cultivation and Physiology of Super Rice

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Jing FU

2012-09-01

Full Text Available In 1996, China launched a program to breed super rice or super hybrid rice by combining intersubspecific heterosis with ideal plant types. Today, approximately 80 super rice varieties have been released and some of them show high grain yields of 12–21 t/hm2 in field experiments. The main reasons for the high yields of super rice varieties, compared with those of conventional varieties, can be summarized as follows: more spikelets per panicle and larger sink size (number of spikelets per square meter; larger leaf area index, longer duration of green leaf, greater photosynthetic rate, higher lodging resistance, greater dry matter accumulation before the heading stage, greater remobilization of pre-stored carbohydrates from stems and leaves to grains during the grain-filling period; and larger root system and greater root activity. However, there are two main problems in super rice production: poor grain-filling of the later-flowering inferior spikelets (in contrast to earlier-flowering superior spikelets, and low and unstable seed-setting rate. Here, we review recent research advances in the crop physiology of super rice, focusing on biological features, formation of yield components, and population quality. Finally, we suggest further research on crop physiology of super rice.

Benefits of an ultra large and multiresolution ensemble for estimating available wind power

Science.gov (United States)

Berndt, Jonas; Hoppe, Charlotte; Elbern, Hendrik

2016-04-01

In this study we investigate the benefits of an ultra large ensemble with up to 1000 members including multiple nesting with a target horizontal resolution of 1 km. The ensemble shall be used as a basis to detect events of extreme errors in wind power forecasting. Forecast value is the wind vector at wind turbine hub height (~ 100 m) in the short range (1 to 24 hour). Current wind power forecast systems rest already on NWP ensemble models. However, only calibrated ensembles from meteorological institutions serve as input so far, with limited spatial resolution (˜10 - 80 km) and member number (˜ 50). Perturbations related to the specific merits of wind power production are yet missing. Thus, single extreme error events which are not detected by such ensemble power forecasts occur infrequently. The numerical forecast model used in this study is the Weather Research and Forecasting Model (WRF). Model uncertainties are represented by stochastic parametrization of sub-grid processes via stochastically perturbed parametrization tendencies and in conjunction via the complementary stochastic kinetic-energy backscatter scheme already provided by WRF. We perform continuous ensemble updates by comparing each ensemble member with available observations using a sequential importance resampling filter to improve the model accuracy while maintaining ensemble spread. Additionally, we use different ensemble systems from global models (ECMWF and GFS) as input and boundary conditions to capture different synoptic conditions. Critical weather situations which are connected to extreme error events are located and corresponding perturbation techniques are applied. The demanding computational effort is overcome by utilising the supercomputer JUQUEEN at the Forschungszentrum Juelich.

SINGLE FRAME SUPER RESOLUTION OF NONCOOPERATIVE IRIS IMAGES

Directory of Open Access Journals (Sweden)

Anand Deshpande

2016-11-01

Full Text Available Image super-resolution, a process to enhance image resolution, has important applications in biometrics, satellite imaging, high definition television, medical imaging, etc. The long range captured iris identification systems often suffer from low resolution and meager focus of the captured iris images. These degrade the iris recognition performance. This paper proposes enhanced iterated back projection (EIBP method to super resolute the long range captured iris polar images. The performance of proposed method is tested and analyzed on CASIA long range iris database by comparing peak signal to noise ratio (PSNR and structural similarity index (SSIM with state-of-the-art super resolution (SR algorithms. It is further analyzed by increasing the up-sampling factor. Performance analysis shows that the proposed method is superior to state-of-the-art algorithms, the peak signal-to-noise ratio improved about 0.1-1.5 dB. The results demonstrate that the proposed method is well suited to super resolve the iris polar images captured at a long distance

The Super-Seniors Study: Phenotypic characterization of a healthy 85+ population.

Science.gov (United States)

Halaschek-Wiener, Julius; Tindale, Lauren C; Collins, Jennifer A; Leach, Stephen; McManus, Bruce; Madden, Kenneth; Meneilly, Graydon; Le, Nhu D; Connors, Joseph M; Brooks-Wilson, Angela R

2018-01-01

To understand why some people live to advanced age in good health and others do not, it is important to study not only disease, but also long-term good health. The Super-Seniors Study aims to identify factors associated with healthy aging. 480 healthy oldest-old 'Super-Seniors' aged 85 to 105 years and never diagnosed with cancer, cardiovascular disease, diabetes, dementia, or major pulmonary disease, were compared to 545 mid-life controls aged 41-54, who represent a group that is unselected for survival from late-life diseases. Health and lifestyle information, personal and family medical history, and blood samples were collected from all participants. Super-Seniors also underwent four geriatric tests. Super-Seniors showed high cognitive (Mini-Mental State Exam mean = 28.3) and functional capacity (Instrumental Activities of Daily Living Scale mean = 21.4), as well as high physical function (Timed Up and Go mean = 12.3 seconds) and low levels of depression (Geriatric Depression Scale mean = 1.5). Super-Seniors were less likely to be current smokers than controls, but the frequency of drinking alcohol was the same in both groups. Super-Seniors were more likely to have 4 or more offspring; controls were more likely to have no children. Female Super-Seniors had a mean age of last fertility 1.9 years older than controls, and were 2.3 times more likely to have had a child at ≥ 40 years. The parents of Super-Seniors had mean ages of deaths of 79.3 years for mothers, and 74.5 years for fathers, each exceeding the life expectancy for their era by a decade. Super-Seniors are cognitively and physically high functioning individuals who have evaded major age-related chronic diseases into old age, representing the approximately top 1% for healthspan. The familiality of long lifespan of the parents of Super-Seniors supports the hypothesis that heritable factors contribute to this desirable phenotype.

SuperCDMS Underground Detector Fabrication Facility

Energy Technology Data Exchange (ETDEWEB)

Platt, M.; Mahapatra, R.; Bunker, Raymond A.; Orrell, John L.

2018-03-01

The SuperCDMS SNOLAB dark matter experiment processes Ge and Si crystals into fully tested phonon and ionization detectors at surface fabrication and test facilities. If not mitigated, it is anticipated that trace-level production of radioisotopes in the crystals due to exposure to cosmic rays at (or above) sea level will result in the dominant source of background events in future dark matter searches using the current SuperCDMS detector technology. Fabrication and testing of detectors in underground facilities shielded from cosmic radiation is one way to directly reduce production of trace levels of radioisotopes, thereby improving experimental sensitivity for the discovery of dark matter beyond the level of the current experiment. In this report, we investigate the cost and feasibility to establish a complete detector fabrication processing chain in an underground location to mitigate cosmogenic activation of the Ge and Si detector substrates. For a specific and concrete evaluation, we explore options for such a facility located at SNOLAB, an underground laboratory in Sudbury, Canada hosting the current and future experimental phases of SuperCDMS.

Can the confidence in long range atmospheric transport models be increased? The pan European experience of ensemble

International Nuclear Information System (INIS)

Galmarini, S.; Bianconi, R.; Mikkelsen, T.

2003-01-01

ensemble forecast represents a finite sampling of a probability distribution and it is demonstrated to have more value than any corresponding single deterministic forecast. The ENSEMBLE statistical tools and model results can be used according to in-house protocols and approaches to emergency response with no a priori treatment by the system. ENSEMBLE is also an important and valuable tool for countries that currently do not have an in-house forecasting capacity. External super-national organisations may also access the system to have a European overview an the evolution of the situation. The real time availability of all such information in a uniform framework implicitly reduces the possibility of conflicting decisions taken by different countries and reduces the risk of relying on a single model. (author)

Ensemble models of neutrophil trafficking in severe sepsis.

Directory of Open Access Journals (Sweden)

Sang Ok Song

Full Text Available A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about 18% of the treated population that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental

Multi-model ensembles for assessment of flood losses and associated uncertainty

Science.gov (United States)

Figueiredo, Rui; Schröter, Kai; Weiss-Motz, Alexander; Martina, Mario L. V.; Kreibich, Heidi

2018-05-01

Flood loss modelling is a crucial part of risk assessments. However, it is subject to large uncertainty that is often neglected. Most models available in the literature are deterministic, providing only single point estimates of flood loss, and large disparities tend to exist among them. Adopting any one such model in a risk assessment context is likely to lead to inaccurate loss estimates and sub-optimal decision-making. In this paper, we propose the use of multi-model ensembles to address these issues. This approach, which has been applied successfully in other scientific fields, is based on the combination of different model outputs with the aim of improving the skill and usefulness of predictions. We first propose a model rating framework to support ensemble construction, based on a probability tree of model properties, which establishes relative degrees of belief between candidate models. Using 20 flood loss models in two test cases, we then construct numerous multi-model ensembles, based both on the rating framework and on a stochastic method, differing in terms of participating members, ensemble size and model weights. We evaluate the performance of ensemble means, as well as their probabilistic skill and reliability. Our results demonstrate that well-designed multi-model ensembles represent a pragmatic approach to consistently obtain more accurate flood loss estimates and reliable probability distributions of model uncertainty.

The Super-Kamiokande experiment

International Nuclear Information System (INIS)

Nishijima, K.

2000-01-01

The Super-Kamiokande experiment is a multi purpose experiment using a large imaging water Cherenkov detector with 50,000 tons of pure water. The detector is located 1000 m underground in the Kamioka mine in Japan, and it can detect particle interactions whose visible energies are between 5 MeV and 100 GeV, so that we can study many physics subjects as follows. Solar neutrino problem is one of the most important unsolved problems in astrophysics. Kamiokande experiment confirmed the deficit of neutrino flux compared to the standard Solar model prediction, which was first reported by R. Davis's pioneering work. Currently it is widely believed that the deficit is due to the neutrino oscillation. The Super-Kamiokande is a unique detector to measure the distortion of the energy spectrum of neutrinos, variation of the neutrino flux between day and night, and the seasonal variation of the flux. Those are related to the neutrino oscillation and independent of the Solar model uncertainty. Atmospheric neutrino anomaly was first announced by Kamiokande experiment, and the Super-Kamiokande recently provided clear evidence for neutrino oscillation as the solution to the anomaly. Observed ratio of muons to electrons is significantly smaller than what is expected. Moreover, zenith-angle distribution of observed muon neutrinos shows the strong up-down asymmetry. The zenith angle distribution of upward-going muons provides another information and the result also supports the oscillation hypothesis. We investigate not only the Solar neutrino problem and atmospheric neutrino anomaly, but also other astrophysical neutrino phenomena such as neutrino bursts from supernova explosions, high energy neutrino emission from point sources, neutrino events in correlation with Solar flares, and gamma-ray bursts. Search for nucleon decay is also one of the primary objectives of our experiment. However no evidence for nucleon decay has been observed yet, and we only set a lower limit on the partial