WorldWideScience

Sample records for model rem predictions

  1. Dream to predict? REM dreaming as prospective coding

    Directory of Open Access Journals (Sweden)

    Sue eLlewellyn

    2016-01-01

    Full Text Available The dream as prediction seems inherently improbable. The bizarre occurrences in dreams never characterize everyday life. Dreams do not come true! But assuming that bizarreness negates expectations may rest on a misunderstanding of how the predictive brain works. In evolutionary terms, the ability to rapidly predict what sensory input implies- through expectations derived from discerning patterns in associated past experiences- would have enhanced fitness and survival. For example, food and water are essential for survival, associating past experiences (to identify location patterns predicts where they can be found. Similarly, prediction may enable predator identification from what would have been only a fleeting and ambiguous stimulus- without prior expectations. To confront the many challenges associated with natural settings, visual perception is vital for humans (and most mammals and often responses must be rapid. Predictive coding during wake may, therefore, be based on unconscious imagery so that visual perception is maintained and appropriate motor actions triggered quickly. Speed may also dictate the form of the imagery. Bizarreness, during REM dreaming, may result from a prospective code fusing phenomena with the same meaning- within a particular context. For example, if the context is possible predation, from the perspective of the prey two different predators can both mean the same (i.e. immediate danger and require the same response (e.g. flight. Prospective coding may also prune redundancy from memories, to focus the image on the contextually-relevant elements only, thus, rendering the non-relevant phenomena indeterminate- another aspect of bizarreness. In sum, this paper offers an evolutionary take on REM dreaming as a form of prospective coding which identifies a probabilistic pattern in past events. This pattern is portrayed in an unconscious, associative, sensorimotor image which may support cognition in wake through being

  2. Coupled flip-flop model for REM sleep regulation in the rat.

    Directory of Open Access Journals (Sweden)

    Justin R Dunmyre

    Full Text Available Recent experimental studies investigating the neuronal regulation of rapid eye movement (REM sleep have identified mutually inhibitory synaptic projections among REM sleep-promoting (REM-on and REM sleep-inhibiting (REM-off neuronal populations that act to maintain the REM sleep state and control its onset and offset. The control mechanism of mutually inhibitory synaptic interactions mirrors the proposed flip-flop switch for sleep-wake regulation consisting of mutually inhibitory synaptic projections between wake- and sleep-promoting neuronal populations. While a number of synaptic projections have been identified between these REM-on/REM-off populations and wake/sleep-promoting populations, the specific interactions that govern behavioral state transitions have not been completely determined. Using a minimal mathematical model, we investigated behavioral state transition dynamics dictated by a system of coupled flip-flops, one to control transitions between wake and sleep states, and another to control transitions into and out of REM sleep. The model describes the neurotransmitter-mediated inhibitory interactions between a wake- and sleep-promoting population, and between a REM-on and REM-off population. We proposed interactions between the wake/sleep and REM-on/REM-off flip-flops to replicate the behavioral state statistics and probabilities of behavioral state transitions measured from experimental recordings of rat sleep under ad libitum conditions and after 24 h of REM sleep deprivation. Reliable transitions from REM sleep to wake, as dictated by the data, indicated the necessity of an excitatory projection from the REM-on population to the wake-promoting population. To replicate the increase in REM-wake-REM transitions observed after 24 h REM sleep deprivation required that this excitatory projection promote transient activation of the wake-promoting population. Obtaining the reliable wake-nonREM sleep transitions observed in the data

  3. Coupled flip-flop model for REM sleep regulation in the rat.

    Science.gov (United States)

    Dunmyre, Justin R; Mashour, George A; Booth, Victoria

    2014-01-01

    Recent experimental studies investigating the neuronal regulation of rapid eye movement (REM) sleep have identified mutually inhibitory synaptic projections among REM sleep-promoting (REM-on) and REM sleep-inhibiting (REM-off) neuronal populations that act to maintain the REM sleep state and control its onset and offset. The control mechanism of mutually inhibitory synaptic interactions mirrors the proposed flip-flop switch for sleep-wake regulation consisting of mutually inhibitory synaptic projections between wake- and sleep-promoting neuronal populations. While a number of synaptic projections have been identified between these REM-on/REM-off populations and wake/sleep-promoting populations, the specific interactions that govern behavioral state transitions have not been completely determined. Using a minimal mathematical model, we investigated behavioral state transition dynamics dictated by a system of coupled flip-flops, one to control transitions between wake and sleep states, and another to control transitions into and out of REM sleep. The model describes the neurotransmitter-mediated inhibitory interactions between a wake- and sleep-promoting population, and between a REM-on and REM-off population. We proposed interactions between the wake/sleep and REM-on/REM-off flip-flops to replicate the behavioral state statistics and probabilities of behavioral state transitions measured from experimental recordings of rat sleep under ad libitum conditions and after 24 h of REM sleep deprivation. Reliable transitions from REM sleep to wake, as dictated by the data, indicated the necessity of an excitatory projection from the REM-on population to the wake-promoting population. To replicate the increase in REM-wake-REM transitions observed after 24 h REM sleep deprivation required that this excitatory projection promote transient activation of the wake-promoting population. Obtaining the reliable wake-nonREM sleep transitions observed in the data required that

  4. The predictive value of Muller maneuver in REM-dependent obstructive sleep apnea.

    Science.gov (United States)

    Ozcan, Kursat Murat; Ozcan, Muge; Ozdogan, Fatih; Hizli, Omer; Dere, Huseyin; Unal, Adnan

    2013-09-01

    To our knowledge, no studies up to date have investigated the correlation of rapid eye movement (REM) dependent obstructive sleep apnea syndrome (OSAS) and Muller maneuver. The aim of this study is to investigate whether REM-dependent OSAS is predicted by the findings of the Muller maneuver. The study was conducted on 149 patients with witnessed apnea and daytime sleepiness. Muller maneuver was performed to all patients and the obstruction site was determined using a five-point scale. Then, polysomnography of the patient was obtained and the apnea-hypopnea indexes were determined in total sleep time, REM-dependent sleep and non-REM-dependent sleep. The correlations between the Muller maneuver findings and polysomnographic data were analyzed. The ages of the patients included in the study ranged between 25 and 73 years with a mean age of 49.3 ± 10.1 years. Their mean body mass index was 30.8 ± 5.1 kg/m(2) (range 21.9-55.4 kg/m(2)). The patients' mean apnea-hypopnea indexes in total sleep time was 28.1 and ranged between 5.4 and 124.3. REM-dependent OSAS was determined in 49 patients. When the data were analyzed, it was determined that there were no statistically significant correlations between tongue base or lateral pharyngeal band obstruction at the level of hypopharynx and the REM-dependent OSAS. At the level of the soft palate, the obstruction caused by the lateral pharyngeal bands or soft palate and REM dependency did not show any statistically significant correlation (p > 0.05). In conclusion, Muller maneuver does not provide useful data to predict REM dependency of OSAS.

  5. General description of KAERI LBLOCA realistic evaluation model (REM) for ECCS evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sang Yong; Lee, Young Jin; Chung, Bub Dong; Lee, Won Jae [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1994-06-01

    A realistic evaluation model (REM) for LBLOCA licensing calculation is developed for application to pressurezed ligh water reactors. The developmental aim of the KAERI-REM is to provide a systematic methodology that is simple in structure and to used and built upon sound logical reasoning, for improving the code capability to realistically describe the LBLOCA phenomena and for evaluating the associated uncertainties. The method strives to be faithful to the intention of being best-estimate, that is, the method aims to evaluate the best-estimate values and the associated uncertainties while complying to the requirements in the ECCS regulations. As a demonstration, KAERI-REM was applied to quantify the safety margin for LBLOCA for Kori 3 and 4 and appended to this report. (Author) 11 refs., 2 figs., 6 tabs.

  6. Using the relational event model (REM) to investigate the temporal dynamics of animal social networks.

    Science.gov (United States)

    Tranmer, Mark; Marcum, Christopher Steven; Morton, F Blake; Croft, Darren P; de Kort, Selvino R

    2015-03-01

    Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula, in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

  7. REM sleep dysregulation in depression: state of the art.

    Science.gov (United States)

    Palagini, Laura; Baglioni, Chiara; Ciapparelli, Antonio; Gemignani, Angelo; Riemann, Dieter

    2013-10-01

    Disturbances of sleep are typical for most depressed patients and belong to the core symptoms of the disorder. Since the 1960s polysomnographic sleep research has demonstrated that besides disturbances of sleep continuity, depression is associated with altered sleep architecture, i.e., a decrease in slow wave sleep (SWS) production and disturbed rapid eye movement (REM) sleep regulation. Shortened REM latency (i.e., the interval between sleep onset and the occurrence of the first REM period), increased REM sleep duration and increased REM density (i.e., the frequency of rapid eye movements per REM period) have been considered as biological markers of depression which might predict relapse and recurrence. High risk studies including healthy relatives of patients with depression demonstrate that REM sleep alterations may precede the clinical expression of depression and may thus be useful in identifying subjects at high risk for the illness. Several models have been developed to explain REM sleep abnormalities in depression, like the cholinergic-aminergic imbalance model or chronobiologically inspired theories, which are reviewed in this overview. Moreover, REM sleep alterations have been recently considered not only as biological "scars" but as true endophenotypes of depression. This review discusses the genetic, neurochemical and neurobiological factors that have been implicated to play a role in the complex relationships between REM sleep and depression. We hypothesize on the one hand that REM sleep dysregulation in depression may be linked to a genetic predisposition/vulnerability to develop the illness; on the other hand it is conceivable that REM sleep disinhibition in itself is a part of a maladaptive stress reaction with increased allostatic load. We also discuss whether the REM sleep changes in depression may contribute themselves to the development of central symptoms of depression such as cognitive distortions including negative self-esteem and the

  8. Endogenous cholinergic input to the pontine REM sleep generator is not required for REM sleep to occur.

    Science.gov (United States)

    Grace, Kevin P; Vanstone, Lindsay E; Horner, Richard L

    2014-10-22

    Initial theories of rapid eye movement (REM) sleep generation posited that induction of the state required activation of the pontine subceruleus (SubC) by cholinergic inputs. Although the capacity of cholinergic neurotransmission to contribute to REM sleep generation has been established, the role of cholinergic inputs in the generation of REM sleep is ultimately undetermined as the critical test of this hypothesis (local blockade of SubC acetylcholine receptors) has not been rigorously performed. We used bilateral microdialysis in freely behaving rats (n = 32), instrumented for electroencephalographic and electromyographic recording, to locally manipulate neurotransmission in the SubC with select drugs. As predicted, combined microperfusion of D-AP5 (glutamate receptor antagonist) and muscimol (GABAA receptor agonist) in the SubC virtually eliminated REM sleep. However, REM sleep was not reduced by scopolamine microperfusion in this same region, at a concentration capable of blocking the effects of cholinergic receptor stimulation. This result suggests that transmission of REM sleep drive to the SubC is acetylcholine-independent. Although SubC cholinergic inputs are not majorly involved in REM sleep generation, they may perform a minor function in the reinforcement of transitions into REM sleep, as evidenced by increases in non-REM-to-REM sleep transition duration and failure rate during cholinergic receptor blockade. Cholinergic receptor antagonism also attenuated the normal increase in hippocampal θ oscillations that characterize REM sleep. Using computational modeling, we show that our in vivo results are consistent with a mutually excitatory interaction between the SubC and cholinergic neurons where, importantly, cholinergic neuron activation is gated by SubC activity.

  9. Commentary on the mutual interaction model of McCarley and Massaquoi for REM-NREM cycle

    NARCIS (Netherlands)

    Daan, Serge; Beersma, Domien G.M.

    1986-01-01

    McCarley and Massaquoi successfully simulated human REM-NREM cycle characteristics by extending the McCarley-Hobson model with two sets of assumptions, one creating limit cycle behavior, the other introducing two sources of circadian variation. We argue that the limit cycle assumptions, due to freed

  10. Effects of thermoregulation on human sleep patterns: A mathematical model of sleep-wake cycles with REM-NREM subcircuit

    OpenAIRE

    Bañuelos, Selenne; Best, Janet; Huguet Casades, Gemma; Prieto-Langarica, Alicia; Pyzza, Pamela; Schmidt, Markus; Wilson, Shelby

    2015-01-01

    In this paper we construct a mathematical model of human sleep/wake regulation with thermoregulation and temperature e ects. Simulations of this model show features previously presented in experimental data such as elongation of duration and number of REM bouts across the night as well as the appearance of awakenings due to deviations in body temperature from thermoneutrality. This model helps to demonstrate the importance of temperature in the sleep cycle. Further modi cations of the model t...

  11. REM sleep deprivation generates cognitive and neurochemical disruptions in the intranigral rotenone model of Parkinson's disease.

    Science.gov (United States)

    Dos Santos, Ana Carolina D; Castro, Marcela Alexandra V; Jose, Elis Angela K; Delattre, Ana Márcia; Dombrowski, Patrícia A; Da Cunha, Claudio; Ferraz, Anete C; Lima, Marcelo M S

    2013-11-01

    The recently described intranigral rotenone model of Parkinson's disease (PD) in rodents provides an interesting model for studying mechanisms of toxin-induced dopaminergic neuronal injury. The relevance of this model remains unexplored with regard to sleep disorders that occur in PD. On this basis, the construction of a PD model depicting several behavioral and neurochemical alterations related to sleep would be helpful in understanding the association between PD and sleep regulation. We performed bilateral intranigral injections of rotenone (12 μg) on day 0 and the open-field test initially on day 20 after rotenone. Acquisition phase of the object-recognition test, executed also during day 20, was followed by an exact period of 24 hr of rapid eye movement (REM) sleep deprivation (REMSD; day 21). In the subsequent day (22), the rats were re-exposed to the open-field test and to the object-recognition test (choice phase). After the last session of behavioral tests, the rat brains were immediately dissected, and their striata were collected for neurochemical purposes. We observed that a brief exposure to REMSD was able to impair drastically the object-recognition test, similarly to a nigrostriatal lesion promoted by intranigral rotenone. However, the combination of REMSD and rotenone surprisingly did not inflict memory impairment, concomitant with a moderate compensatory mechanism mediated by striatal dopamine release. In addition, we demonstrated the existence of changes in serotonin and noradrenaline neurotransmissions within the striatum mostly as a function of REMSD and REMSD plus rotenone, respectively.

  12. REM sleep rescues learning from interference.

    Science.gov (United States)

    McDevitt, Elizabeth A; Duggan, Katherine A; Mednick, Sara C

    2015-07-01

    Classical human memory studies investigating the acquisition of temporally-linked events have found that the memories for two events will interfere with each other and cause forgetting (i.e., interference; Wixted, 2004). Importantly, sleep helps consolidate memories and protect them from subsequent interference (Ellenbogen, Hulbert, Stickgold, Dinges, & Thompson-Schill, 2006). We asked whether sleep can also repair memories that have already been damaged by interference. Using a perceptual learning paradigm, we induced interference either before or after a consolidation period. We varied brain states during consolidation by comparing active wake, quiet wake, and naps with either non-rapid eye movement sleep (NREM), or both NREM and REM sleep. When interference occurred after consolidation, sleep and wake both produced learning. However, interference prior to consolidation impaired memory, with retroactive interference showing more disruption than proactive interference. Sleep rescued learning damaged by interference. Critically, only naps that contained REM sleep were able to rescue learning that was highly disrupted by retroactive interference. Furthermore, the magnitude of rescued learning was correlated with the amount of REM sleep. We demonstrate the first evidence of a process by which the brain can rescue and consolidate memories damaged by interference, and that this process requires REM sleep. We explain these results within a theoretical model that considers how interference during encoding interacts with consolidation processes to predict which memories are retained or lost.

  13. Symposium: Normal and abnormal REM sleep regulation: REM sleep in depression-an overview.

    Science.gov (United States)

    Berger; Riemann

    1993-12-01

    Abnormalities of REM sleep, i.e. shortening of REM latency, lengthening of the duration of the first REM period and heightening of REM density, which are frequently observed in patients with a major depressive disorder (MDD), have attracted considerable interest. Initial hopes that these aberrant patterns of sleep constitute specific markers for the primary/endogenous sub-type of depression have not been fulfilled. The specificity of REM sleep disinhibition for depression in comparison with other psychopathological groups is challenged as well. Demographic variables like age and sex exert strong influences on sleep physiology and must be controlled when searching for specific markers of depressed sleep. It is still an open question whether abnormalities of sleep are state- or trait-markers of depression. Beyond baseline studies, the cholinergic REM induction test (CRIT) indicated a heightened responsitivity of the REM sleep system to cholinergic challenge in depression compared with healthy controls and other psychopathological groups, with the exception of schizophrenia. A special role for REM sleep in depression is supported by the well-known REM sleep suppressing effect of most antidepressants. The antidepressant effect of selective REM deprivation by awakenings stresses the importance of mechanisms involved in REM sleep regulation for the understanding of the pathophysiology of depressive disorders. The positive effect of total sleep deprivation on depressive mood which can be reversed by daytime naps, furthermore emphasizes relationships between sleep and depression. Experimental evidence as described above instigated several theories like the REM deprivation hypothesis, the 2-process model and the reciprocal interaction model of nonREM-REM sleep regulation to explain the deviant sleep pattern of depression. The different models will be discussed with reference to empirical data gathered in the field.

  14. Water cycle at Gale crater through MSL/REMS observations

    Science.gov (United States)

    Harri, Ari-Matti; Genzer, Maria; Kemppinen, Osku; Gomez-Elvira, Javier; Savijärvi, Hannu; McConnochie, Tim; De la Torre, Manuel; Haberle, Robert; Polkko, Jouni; Paton, Mark; Richardson, Mark I.; Newman, Claire E.; Siili, Tero; Makinen, Terhi

    2016-10-01

    The Mars Science laboratory (MSL) has been successfully operating at the Gale crater since early August 2012 and has provided a wealth of extremely valuable data. That includes atmospheric observations by the REMS instrument performing atmospheric pressure, temperature of the air, ground temperature, wind speed and direction, relative humidity (REMS-H), and UV measurements.The REMS-H relative humidity device is based on polymeric capacitive humidity sensors developed by Vaisala Inc. and it makes use of three (3) humidity sensor heads. The humidity device is mounted on the REMS boom providing ventilation with the ambient atmosphere through a filter protecting the device from airborne dust.The REMS-H humidity instrument has created an unprecedented data record of more than two full Martian. REMS-H measured the relative humidity and temperature at 1.6 m height for a period of 5 minutes every hour as part of the MSL/REMS instrument package. We focus on describing the annual in situ water cycle with the new REMS-H instrument calibration for the period of two Martian years. The results will be constrained through comparison with independent indirect observations and through modeling efforts.We inferred the hourly atmospheric VMR from the REMS-H observations and compared these VMR measurements with predictions of VMR from our 1D column Martian atmospheric model and regolith to investigate the local water cycle, exchange processes and the local climate in Gale Crater. The strong diurnal variation suggests there are surface-atmosphere exchange processes at Gale Crater during all seasons, which depletes moisture to the ground in the evening and nighttime and release the moisture back to the atmosphere during the daytime. On the other hand, these processes do not result in significant water deposition on the ground, because frost has not been detected in Gale Crater by any of the MSL observations. Hence, our modelling results presumably indicate that adsorption processes take

  15. Is the nonREM-REM sleep cycle reset by forced awakenings from REM sleep?

    NARCIS (Netherlands)

    Grozinger, M; Beersma, DGM; Fell, J; Roschke, J

    2002-01-01

    In selective REM sleep deprivation (SRSD), the occurrence of stage REM is repeatedly interrupted by short awakenings. Typically, the interventions aggregate in clusters resembling the REM episodes in undisturbed sleep. This salient phenomenon can easily be explained if the nonREM-REM sleep process i

  16. Study of a modified REMS score for prediction of the risk o f death for patients with ST segment elevation myocardial infarction%改良 REMS 评分对 ST 段抬高性心肌梗死患者近期死亡风险的预测价值

    Institute of Scientific and Technical Information of China (English)

    吉春玲; 周厚荣; 杨秀林; 瞿详; 任亦频; 金睿; 张谦

    2015-01-01

    STEMI预后的预测性更优越,改良评分越高,病情越重,病死率越高。%Objective To establish a modified REMS evaluation system and assess the new scoring system by using a retrospective data, comparing the predictive value of the modified REMS score, GRCAE and REMS scoring system in patients with ST segment elevation myocardial infarction ( STEMI) with recent mortality risk.Methods A retrospective review of patients of 394 cases with STEMI were collected from April 2013 to December 2014 in the Department of Emergency and Department of Cardiology of CCU in our hospital, to screening out independent risk factors for increasing 30 day mortality rate with STEMI by univariate and multivariate logistic regression analysis and establish a modified REMS scoring system, the lowest sore value were recorded for a modified REMS evaluation system, GRACE risk scores and REMS risk scores for each patient within 2 hour.Death cases during 30 days after onset were evaluated.To comparing the predictive value of the three scoring system to the sererity with STEMI and the incidence of 30 days by ROC curve.Results A total of 49 patients died from cardiovascular disease within 30 days ( the mortality rate of 12.4%) .Two hundred and seventy-two cases underwent reperfusion therapy in all STEMI cases,including 31 cases of emergency thrombolic therapy (7.8%) and 57cases with emergency PCI treatment (14.5%).Multiple regression analysis showed that age, systolic blood pressure, killip classification ,ST elevation, arrhythmia and cTnI concentration were independent predictors of death in patients with STEMI .Modified REMS risk scores, GRACE risk scores and REMS risk scores were higher in non survivors in comparison with survivors [Modified REMS (points):16.71 ±2.14 vs 12.95 ±3.26; GRACE (points): 196.29 ±36.79 vs 163.23 ±33.14; REMS ( points): 7.57 ±2.71 vs 5.21 ±2.65].Area under the curve for the modified REMS, GRACE and REMS scores to patients with STEMI died from heart

  17. Sleep-stage sequencing of sleep-onset REM periods in MSLT predicts treatment response in patients with narcolepsy.

    Science.gov (United States)

    Drakatos, Panagis; Patel, Kishankumar; Thakrar, Chiraag; Williams, Adrian J; Kent, Brian D; Leschziner, Guy D

    2016-04-01

    Current treatment recommendations for narcolepsy suggest that modafinil should be used as a first-line treatment ahead of conventional stimulants or sodium oxybate. In this study, performed in a tertiary sleep disorders centre, treatment responses were examined following these recommendations, and the ability of sleep-stage sequencing of sleep-onset rapid eye movement periods in the multiple sleep latency test to predict treatment response. Over a 3.5-year period, 255 patients were retrospectively identified in the authors' database as patients diagnosed with narcolepsy, type 1 (with cataplexy) or type 2 (without) using clinical and polysomnographic criteria. Eligible patients were examined in detail, sleep study data were abstracted and sleep-stage sequencing of sleep-onset rapid eye movement periods were analysed. Response to treatment was graded utilizing an internally developed scale. Seventy-five patients were included (39% males). Forty (53%) were diagnosed with type 1 narcolepsy with a mean follow-up of 2.37 ± 1.35 years. Ninety-seven percent of the patients were initially started on modafinil, and overall 59% reported complete response on the last follow-up. Twenty-nine patients (39%) had the sequence of sleep stage 1 or wake to rapid eye movement in all of their sleep-onset rapid eye movement periods, with most of these diagnosed as narcolepsy type 1 (72%). The presence of this specific sleep-stage sequence in all sleep-onset rapid eye movement periods was associated with worse treatment response (P = 0.0023). Sleep-stage sequence analysis of sleep-onset rapid eye movement periods in the multiple sleep latency test may aid the prediction of treatment response in narcoleptics and provide a useful prognostic tool in clinical practice, above and beyond their classification as narcolepsy type 1 or 2.

  18. Winds measured by the Rover Environmental Monitoring Station (REMS) during the Mars Science Laboratory (MSL) rover's Bagnold Dunes Campaign and comparison with numerical modeling using MarsWRF

    Science.gov (United States)

    Newman, Claire E.; Gómez-Elvira, Javier; Marin, Mercedes; Navarro, Sara; Torres, Josefina; Richardson, Mark I.; Battalio, J. Michael; Guzewich, Scott D.; Sullivan, Robert; de la Torre, Manuel; Vasavada, Ashwin R.; Bridges, Nathan T.

    2017-07-01

    A high density of REMS wind measurements were collected in three science investigations during MSL's Bagnold Dunes Campaign, which took place over ∼80 sols around southern winter solstice (Ls∼90°) and constituted the first in situ analysis of the environmental conditions, morphology, structure, and composition of an active dune field on Mars. The Wind Characterization Investigation was designed to fully characterize the near-surface wind field just outside the dunes and confirmed the primarily upslope/downslope flow expected from theory and modeling of the circulation on the slopes of Aeolis Mons in this season. The basic pattern of winds is 'upslope' (from the northwest, heading up Aeolis Mons) during the daytime (∼09:00-17:00 or 18:00) and 'downslope' (from the southeast, heading down Aeolis Mons) at night (∼20:00 to some time before 08:00). Between these times the wind rotates largely clockwise, giving generally westerly winds mid-morning and easterly winds in the early evening. The timings of these direction changes are relatively consistent from sol to sol; however, the wind direction and speed at any given time shows considerable intersol variability. This pattern and timing is similar to predictions from the MarsWRF numerical model, run at a resolution of ∼490 m in this region, although the model predicts the upslope winds to have a stronger component from the E than the W, misses a wind speed peak at ∼09:00, and under-predicts the strength of daytime wind speeds by ∼2-4 m/s. The Namib Dune Lee Investigation reveals 'blocking' of northerly winds by the dune, leaving primarily a westerly component to the daytime winds, and also shows a broadening of the 1 Hz wind speed distribution likely associated with lee turbulence. The Namib Dune Side Investigation measured primarily daytime winds at the side of the same dune, in support of aeolian change detection experiments designed to put limits on the saltation threshold, and also appears to show the

  19. REM sleep Behaviour Disorder.

    Science.gov (United States)

    Ferini-Strambi, Luigi; Rinaldi, Fabrizio; Giora, Enrico; Marelli, Sara; Galbiati, Andrea

    2016-01-01

    Rapid Eye Movement (REM) sleep Behaviour Disorder (RBD) is a REM sleep parasomnia characterized by loss of the muscle atonia that typically occurs during REM sleep, therefore allowing patients to act out their dreams. RBD manifests itself clinically as a violent behaviour occurring during the night, and is detected at the polysomnography by phasic and/or tonic muscle activity on the electromyography channel. In absence of neurological signs or central nervous system lesions, RBD is defined as idiopathic. Nevertheless, in a large number of cases the development of neurodegenerative diseases in RBD patients has been described, with the duration of the follow-up representing a fundamental aspect. A growing number of clinical, neurophysiologic and neuropsychological studies aimed to detect early markers of neurodegenerative dysfunction in RBD patients. Anyway, the evidence of impaired cortical activity, subtle neurocognitive dysfunction, olfactory and autonomic impairment and neuroimaging brain changes in RBD patients is challenging the concept of an idiopathic form of RBD, supporting the idea of RBD as an early manifestation of a more complex neurodegenerative process.

  20. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  1. Towards a better reliability of risk assessment: development of a qualitative & quantitative risk evaluation model (Q2REM) for different trades of construction works in Hong Kong.

    Science.gov (United States)

    Fung, Ivan W H; Lo, Tommy Y; Tung, Karen C F

    2012-09-01

    Since the safety professionals are the key decision makers dealing with project safety and risk assessment in the construction industry, their perceptions of safety risk would directly affect the reliability of risk assessment. The safety professionals generally tend to heavily rely on their own past experiences to make subjective decisions on risk assessment without systematic decision making. Indeed, understanding of the underlying principles of risk assessment is significant. In this study, the qualitative analysis on the safety professionals' beliefs of risk assessment and their perceptions towards risk assessment, including their recognitions of possible accident causes, the degree of differentiations on their perceptions of risk levels of different trades of works, recognitions of the occurrence of different types of accidents, and their inter-relationships with safety performance in terms of accident rates will be explored in the Stage 1. At the second stage, the deficiencies of the current general practice for risk assessment can be sorted out firstly. Based on the findings from Stage 1 and the historical accident data from 15 large-scaled construction projects in 3-year average, a risk evaluation model prioritizing the risk levels of different trades of works and which cause different types of site accident due to various accident causes will be developed quantitatively. With the suggested systematic accident recording techniques, this model can be implemented in the construction industry at both project level and organizational level. The model (Q(2)REM) not only act as a useful supplementary guideline of risk assessment for the construction safety professionals, but also assists them to pinpoint the potential risks on site for the construction workers under respective trades of works through safety trainings and education. It, in turn, arouses their awareness on safety risk. As the Q(2)REM can clearly show the potential accident causes leading to

  2. The role of REM sleep theta activity in emotional memory.

    Science.gov (United States)

    Hutchison, Isabel C; Rathore, Shailendra

    2015-01-01

    While non-REM (NREM) sleep has been strongly implicated in the reactivation and consolidation of memory traces, the role of rapid-eye movement (REM) sleep remains unclear. A growing body of research on humans and animals provide behavioral evidence for a role of REM sleep in the strengthening and modulation of emotional memories. Theta activity-which describes low frequency oscillations in the local field potential within the hippocampus, amygdala and neocortex-is a prominent feature of both wake and REM sleep in humans and rodents. Theta coherence between the hippocampus and amygdala drives large-scale pontine-geniculo-occipital (PGO) waves, the density of which predicts increases in plasticity-related gene expression. This could potentially facilitate the processing of emotional memory traces within the hippocampus during REM sleep. Further, the timing of hippocampal activity in relation to theta phase is vital in determining subsequent potentiation of neuronal activity. This could allow the emotionally modulated strengthening of novel and gradual weakening of consolidated hippocampal memory traces during REM sleep. Hippocampal theta activity is also correlated with REM sleep levels of achetylcholine - which is thought to reduce hippocampal inputs in the neocortex. The additional low levels of noradrenaline during REM sleep, which facilitate feedback within the neocortex, could allow the integration of novel memory traces previously consolidated during NREM sleep. We therefore propose that REM sleep mediates the prioritized processing of emotional memories within the hippocampus, the integration of previously consolidated memory traces within the neocortex, as well as the disengagement of consolidated neocortical memory traces from the hippocampus.

  3. Predictive models in urology.

    Science.gov (United States)

    Cestari, Andrea

    2013-01-01

    Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology.

  4. Effects of psychot herapy on REM latency and REM time.

    Science.gov (United States)

    Karle, W; Hopper, M; Switzer, A; Corriere, R; Woldenberg, L

    1980-08-01

    This study investigated the effect of a functional psychotherapy on the sleep EEG patterns of 6 patients. Contrary to original expectations no significant group differences in REM time and REM latency were found between two nights following therapy sessions and two normal nights. However, across the 4 nights the patients exhibited an average REM latency of 71 min. which was significantly shorter than that recorded in an independent study with the same design and a similar subject population. Clausen, Sersen, and Lidsky (1974) reported an average REM latency of 107.3 min. for 10 normal subjects also recorded across four nights. This result is compared with those in several other studies and discussed in relation to possible changes in dream patterns.

  5. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... paper, we will present an introduction to the theory and application of MPC with Matlab codes written to ... model predictive control, linear systems, discrete-time systems, ... and then compute very rapidly for this open-loop con-.

  6. The role of REM theta activity in emotional memory

    Directory of Open Access Journals (Sweden)

    Isabel Camilla Hutchison

    2015-10-01

    Full Text Available While NREM sleep has been strongly implicated in the reactivation and consolidation of memory traces, the role of REM sleep remains unclear. A growing body of research on humans and animals provide behavioral evidence for a role of REM sleep in the strengthening and modulation of emotional memories. Theta activity – which describes low frequency oscillations in the local field potential within the hippocampus, amygdala and neocortex – is a prominent feature of both wake and REM sleep in humans and rodents. Theta coherence between the hippocampus and amygdala drives large-scale PGO waves, the density of which predicts increases in plasticity-related gene expression. This could potentially facilitate the processing of emotional memory traces within the hippocampus during REM sleep. Further, the timing of hippocampal activity in relation to theta phase is vital in determining subsequent potentiation of neuronal activity. This could allow the emotionally modulated strengthening of novel and the gradual weakening of consolidated hippocampal memory traces observed in both wake and REM sleep. Hippocampal theta activity is also correlated with REM sleep acetylcholine levels – which are thought to reduce hippocampal afferent inputs in the neocortex. The additional low levels of noradrenaline during REM sleep, which facilitate recurrent activation within the neocortex, could allow the integration of novel memory traces previously consolidated during NREM sleep. We therefore propose that REM sleep mediates the prioritized processing of emotional memories within the hippocampus, the integration of previously consolidated memory traces within the neocortex, as well as the disengagement of consolidated neocortical memory traces from the hippocampus.

  7. Comparing neural correlates of REM sleep in posttraumatic stress disorder and depression: a neuroimaging study.

    Science.gov (United States)

    Ebdlahad, Sommer; Nofzinger, Eric A; James, Jeffrey A; Buysse, Daniel J; Price, Julie C; Germain, Anne

    2013-12-30

    Rapid eye movement (REM) sleep disturbances predict poor clinical outcomes in posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). In MDD, REM sleep is characterized by activation of limbic and paralimbic brain regions compared to wakefulness. The neural correlates of PTSD during REM sleep remain scarcely explored, and comparisons of PTSD and MDD have not been conducted. The present study sought to compare brain activity patterns during wakefulness and REM sleep in 13 adults with PTSD and 12 adults with MDD using [¹⁸F]-fluoro-2-deoxy-D-glucose positron emission tomography (PET). PTSD was associated with greater increase in relative regional cerebral metabolic rate of glucose (rCMRglc) in limbic and paralimbic structures in REM sleep compared to wakefulness. Post-hoc comparisons indicated that MDD was associated with greater limbic and paralimbic rCMRglc during wakefulness but not REM sleep compared to PTSD. Our findings suggest that PTSD is associated with increased REM sleep limbic and paralimbic metabolism, whereas MDD is associated with wake and REM hypermetabolism in these areas. These observations suggest that PTSD and MDD disrupt REM sleep through different neurobiological processes. Optimal sleep treatments between the two disorders may differ: REM-specific therapy may be more effective in PTSD.

  8. Nominal model predictive control

    OpenAIRE

    Grüne, Lars

    2013-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  9. Nominal Model Predictive Control

    OpenAIRE

    Grüne, Lars

    2014-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  10. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  11. Semi-Empirical Study of the Indirect Exchange Interaction in the Rem - Al System

    Science.gov (United States)

    Shakarov, Kh. O.

    2016-05-01

    The Ruderman-Kittel-Kasuya-Yosida exchange interaction (RKKY) is semi-empirically studied for the first time in compounds of binary REM - Al systems (REM - rare-earth metals: Gd, Dy, Ho, Er) using experimental values of paramagnetic Curie point (θp) of these compounds. Prediction of the RKKY theory was confirmed, i.e. there is a direct proportional dependence of θp value on de Gennes factor for equiatomic compounds of heavy REM with aluminum, just as in the case of pure REM. Values of the indirect exchange interaction parameter were semi-empirically estimated for the studied compounds. In general, it was established that RKKY-type exchange interaction is typical for REM compounds with aluminum, just as for pure REM.

  12. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  13. The 'scanning hypothesis' of rapid eye movements during REM sleep: a review of the evidence.

    Science.gov (United States)

    Arnulf, I

    2011-12-01

    Rapid eye movements (REMs) and visual dreams are salient features of REM sleep. However, it is unclear whether the eyes scan dream images. Several lines of evidence oppose the scanning hypothesis: REMs persist in animals and humans without sight (pontine cats, foetus, neonates, born-blinds), some binocular REMs are not conjugated (no focus point), REMs occur in parallel (not in series) with the stimulation of the visual cortex by ponto-geniculo-occipital spikes, and visual dreams can be obtained in non REM sleep. Studies that retrospectively compared the direction of REMs to dream recall recorded after having awakened the sleeper yielded inconsistent results, with a concordance varying from 9 to 80%. However, this method was subject to methodological flaws, including the bias of retrospection and neck atonia that does not allow the determination of the exact direction of gaze. Using the model of RBD (in which patients are able to enact their dreams due to the absence of muscle atonia) in 56 patients, we directly determined if the eyes moved in the same directions as the head and limbs. When REMs accompanied goal-oriented motor behaviour during RBD (e.g., framing something, greeting with the hand, climbing a ladder), 90% were directed towards the action of the patient (same plane and direction). REMs were however absent in 38% of goal-oriented behaviours. This directional coherence between limbs, head and eye movements during RBD suggests that, when present, REMs imitate the scanning of the dream scene. Because REMs index and complexity were similar in patients with RBD and controls, this concordance can be extended to normal REM sleep. These results are consistent with the model of a brainstem generator activating simultaneously images, sounds, limbs movements and REMs in a coordinated parallel manner, as in a virtual reality.

  14. REM sleep instability--a new pathway for insomnia?

    Science.gov (United States)

    Riemann, D; Spiegelhalder, K; Nissen, C; Hirscher, V; Baglioni, C; Feige, B

    2012-07-01

    Chronic insomnia afflicts approximately 10% of the adult population and is associated with daytime impairments and an elevated risk for developing somatic and mental disorders. Current pathophysiological models propose a persistent hyperarousal on the cognitive, emotional and physiological levels. However, the marked discrepancy between minor objective alterations in standard parameters of sleep continuity and the profound subjective impairment in patients with insomnia is unresolved. We propose that "instability" of REM sleep contributes to the experience of disrupted and non-restorative sleep and to the explanation of this discrepancy. This concept is based on evidence showing increased micro- and macro-arousals during REM sleep in insomnia patients. As REM sleep represents the most highly aroused brain state during sleep it seems particularly prone to fragmentation in individuals with persistent hyperarousal. The continuity hypothesis of dream production suggests that pre-sleep concerns of patients with insomnia, i. e., worries about poor sleep and its consequences, dominate their dream content. Enhanced arousal during REM sleep may render these wake-like cognitions more accessible to conscious perception, memory storage and morning recall, resulting in the experience of disrupted and non-restorative sleep. Furthermore, chronic fragmentation of REM sleep might lead to dysfunction in a ventral emotional neural network, including limbic and paralimbic areas that are specifically activated during REM sleep. This dysfunction, along with attenuated functioning in a dorsal executive neural network, including frontal and prefrontal areas, might contribute to emotional and cognitive alterations and an elevated risk of developing depression.

  15. The value of REM sleep parameters in differentiating Alzheimer's disease from old-age depression and normal aging.

    Science.gov (United States)

    Dykierek, P; Stadtmüller, G; Schramm, P; Bahro, M; van Calker, D; Braus, D F; Steigleider, P; Löw, H; Hohagen, F; Gattaz, W F; Berger, M; Riemann, D

    1998-01-01

    Pseudodementia as a common trait in elderly depressives presents a major problem in gerontopsychiatry, especially for the differential diagnosis between Old-Age Depression (OAD) and Dementia of the Alzheimer Type (DAT). The present polysomnographic study examined parameters of sleep continuity, sleep architecture, and REM sleep to differentiate DAT from OAD. The investigation was based on the theoretical framework of the cholinergic-aminergic imbalance model of depression, the cholinergic deficit hypothesis of Alzheimer's disease and the reciprocal interaction model of Non-REM/REM sleep regulation, according to which REM sleep parameters should have high discriminative value to differentiate OAD and DAT. We investigated 35 DAT patients, 39 OAD patients and 42 healthy controls for two consecutive nights in the sleep laboratory. The DAT patients were in relatively early/mild stages of the disease, the severity of depression in the OAD group was moderate to severe. Depressed patients showed characteristic 'depression-like' EEG sleep alterations, i.e. a lower sleep efficiency, a higher amount of nocturnal awakenings and decreased sleep stage 2. Sleep continuity and architecture in DAT was less disturbed. Nearly all REM sleep measures differentiated significantly between the diagnostic groups. OAD patients showed a shortened REM latency, increased REM density and a high rate of Sleep Onset REM periods (SOREM), whereas in DAT REM density was decreased in comparison to control subjects. REM latency in DAT was not prolonged as expected. To assess the discriminative power of REM sleep variables a series of discriminant analyses were conducted. Overall, 86% of patients were correctly classified, using REM density and REM latency measures. Our findings suggest that REM density as an indicator of phasic activity appears to be more sensitive as a biological marker for the differential diagnosis of OAD and DAT than REM latency. The results support the role of central cholinergic

  16. The cholinergic REM induction test with RS 86 after scopolamine pretreatment in healthy subjects.

    Science.gov (United States)

    Riemann, D; Hohagen, F; Fleckenstein, P; Schredl, M; Berger, M

    1991-09-01

    A shortened latency of rapid eye movement (REM) sleep is one of the most stable biological abnormalities described in depressive patients. According to the reciprocal interaction model of non-REM and REM sleep regulation, REM sleep disinhibition at the beginning of the night in depression is a consequence of heightened central nervous system cholinergic transmitter activity in relation to aminergic transmitter activity. A recent study has indicated that muscarinic supersensitivity, rather than quantitatively enhanced cholinergic activity, may be the primary cause of REM sleep abnormalities in depression. The present study tested this hypothesis by treating healthy volunteers for 3 days with a cholinergic antagonist (scopolamine) in the morning, in an effort to induce muscarinic receptor supersensitivity. On the last day of scopolamine administration, RS 86, an orally active cholinergic agonist, was administered before bedtime to test whether this procedure would induce sleep onset REM periods. Whereas scopolamine treatment tended to advance REM sleep and to heighten REM density in healthy controls in comparison to NaCl administration, the additional cholinergic stimulation did not provoke further REM sleep disinhibition. This result underlines the need to take a hypofunction of aminergic transmitter systems into account in attempts to explain the pronounced advance of REM sleep typically seen in depressives.

  17. REM sleep modulation by perifornical orexinergic inputs to the pedunculo-pontine tegmental neurons in rats.

    Science.gov (United States)

    Khanday, M A; Mallick, B N

    2015-11-12

    Rapid eye movement sleep (REMS) is regulated by the interaction of the REM-ON and REM-OFF neurons located in the pedunculo-pontine-tegmentum (PPT) and the locus coeruleus (LC), respectively. Many other brain areas, particularly those controlling non-REMS (NREMS) and waking, modulate REMS by modulating these REMS-related neurons. Perifornical (PeF) orexin (Ox)-ergic neurons are reported to increase waking and reduce NREMS as well as REMS; dysfunction of the PeF neurons are related to REMS loss-associated disorders. Hence, we were interested in understanding the neural mechanism of PeF-induced REMS modulation. As a first step we have recently reported that PeF Ox-ergic neurons modulate REMS by influencing the LC neurons (site for REM-OFF neurons). Thereafter, in this in vivo study we have explored the role of PeF inputs on the PPT neurons (site for REM-ON neurons) for the regulation of REMS. Chronic male rats were surgically prepared with implanted bilateral cannulae in PeF and PPT and electrodes for recording sleep-waking patterns. After post-surgical recovery sleep-waking-REMS were recorded when bilateral PeF neurons were stimulated by glutamate and simultaneously bilateral PPT neurons were infused with either saline or orexin receptor1 (OX1R) antagonist. It was observed that PeF stimulation increased waking and decreased NREMS as well as REMS, which were prevented by OX1R antagonist into the PPT. We conclude that the PeF stimulation-induced reduction in REMS was likely to be due to inhibition of REM-ON neurons in the PPT. As waking and NREMS are inversely related, subject to confirmation, the reduction in NREMS could be due to increased waking or vice versa. Based on our findings from this and earlier studies we have proposed a model showing connections between PeF- and PPT-neurons for REMS regulation.

  18. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...

  19. Melanoma risk prediction models

    Directory of Open Access Journals (Sweden)

    Nikolić Jelena

    2014-01-01

    Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were

  20. Retention over a Period of REM or non-REM Sleep.

    Science.gov (United States)

    Tilley, Andrew J.

    1981-01-01

    Subjects, awaked, presented with a word list, and tested with arousal measures, were reawaked during REM or non-REM sleep and retested. Recall was facilitated by REM sleep. It was hypothesized that the high arousal level associated with REM sleep incidentally maintained the memory trace in a more retrievable form. (Author/SJL)

  1. REM sleep homeostasis in the absence of REM sleep: Effects of antidepressants.

    Science.gov (United States)

    McCarthy, Andrew; Wafford, Keith; Shanks, Elaine; Ligocki, Marcin; Edgar, Dale M; Dijk, Derk-Jan

    2016-09-01

    Most antidepressants suppress rapid eye movement (REM) sleep, which is thought to be important to brain function, yet the resulting REM sleep restriction is well tolerated. This study investigated the impact of antidepressants with different mechanisms of action, such as selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCA), on the regulation of REM sleep in rats. REM sleep was first demonstrated to be homeostatically regulated using 5, 8 and 10 h of REM-sleep specific restriction through EEG-triggered arousals, with an average of 91 ± 10% of lost REM sleep recovered following a 26-29 -hour recovery period. Acute treatment with the antidepressants paroxetine, citalopram and imipramine inhibited REM sleep by 84 ± 8, 84 ± 8 and 69 ± 9% respectively relative to vehicle control. The pharmacologically-induced REM sleep deficits by paroxetine and citalopram were not fully recovered, whereas, after imipramine the REM sleep deficit was fully compensated. Given the marked difference between REM sleep recovery following the administration of paroxetine, citalopram, imipramine and REM sleep restriction, the homeostatic response was further examined by pairing REM sleep specific restriction with the three antidepressants. Surprisingly, the physiologically-induced REM sleep deficits incurred prior to suppression of REM sleep by all antidepressants was consistently recovered. The data indicate that REM sleep homeostasis remains operative following subsequent treatment with antidepressants and is unaffected by additional pharmacological inhibition of REM sleep.

  2. Is the nonREM–REM sleep cycle reset by forced awakenings from REM sleep?

    NARCIS (Netherlands)

    Grözinger, Michael; Beersma, Domien G.M.; Fell, Jürgen; Röschke, Joachim

    2002-01-01

    In selective REM sleep deprivation (SRSD), the occurrence of stage REM is repeatedly interrupted by short awakenings. Typically, the interventions aggregate in clusters resembling the REM episodes in undisturbed sleep. This salient phenomenon can easily be explained if the nonREM–REM sleep process i

  3. The Reciprocal Internal/External Frame of Reference Model Using Grades and Test Scores

    Science.gov (United States)

    Möller, Jens; Zimmermann, Friederike; Köller, Olaf

    2014-01-01

    Background: The reciprocal I/E model (RI/EM) combines the internal/external frame of reference model (I/EM) with the reciprocal effects model (REM). The RI/EM extends the I/EM longitudinally and the REM across domains. The model predicts that, within domains, mathematics and verbal achievement (VACH) and academic self-concept have positive effects…

  4. Manipulating REM sleep in older adults by selective REM sleep deprivation and physiological as well as pharmacological REM sleep augmentation methods.

    Science.gov (United States)

    Hornung, Orla P; Regen, Francesca; Schredl, Michael; Heuser, Isabella; Danker-Hopfe, Heidi

    2006-02-01

    Experimental approaches to manipulate REM sleep within the cognitive neuroscience of sleep are usually based on sleep deprivation paradigms and focus on younger adults. In the present study, a traditional selective REM sleep deprivation paradigm as well as two alternative manipulation paradigms targeting REM sleep augmentation were investigated in healthy older adults. The study sample consisted of 107 participants, male and female, between the ages of 60 and 82 years, who had been randomly assigned to five experimental groups. During the study night, a first group was deprived of REM sleep by selective REM sleep awakenings, while a second group was woken during stage 2 NREM sleep in matched frequency. Physiological REM sleep augmentation was realized by REM sleep rebound after selective REM sleep deprivation, pharmacological REM sleep augmentation by administering an acetylcholinesterase inhibitor in a double-blind, placebo-controlled design. Deprivation and augmentation paradigms manipulated REM sleep significantly, the former affecting more global measures such as REM sleep minutes and percentage, the latter more organizational aspects such as stage shifts to REM sleep, REM latency, REM density (only pharmacological augmentation) and phasic REM sleep duration. According to our findings, selective REM sleep deprivation seems to be an efficient method of REM sleep manipulation in healthy older adults. While physiological rebound-based and pharmacological cholinergic REM sleep augmentation methods both failed to affect global measures of REM sleep, their efficiency in manipulating organizational aspects of REM sleep extends the traditional scope of REM sleep manipulation methods within the cognitive neuroscience of sleep.

  5. Compilation of an emissions data base for Europe, base year 1995, and development of large scale emissions reduction scenarios for the chemical transport model REM/CALGRID. Final report; Modellierung und Puefung von Strategien zur Verminderung der Belastung durch Ozon. Erstellung einer europaweiten Emissionsdatenbasis mit Bezugsjahr 1995 und die Erarbeitung von Emissionsszenarien fuer die grossraeumigen Ausbreitungsrechnungen mit REM/CALGRID. Schlussbericht

    Energy Technology Data Exchange (ETDEWEB)

    Stern, R.

    2003-02-01

    The report describes the emissions data base created by TNO, Netherlands, which is used for the chemical transport model REM/CALGRID. Base year is 1995. The data base covers Europe with grids of 0.5 x 0.25 lat long and contains the anthropogenic emissions of SO{sub 2}, NO{sub x}, NMVOC, CO, CH{sub 4}, NH{sub 3}, PM{sub 10}, PM{sub 2.5}. The data base uses CORINAIR and CEPMEIP information and the SNAP source group classifiction of CORINAIR. For emissions scenario calculations, 3 scenarios were developed based on information provided by IIASA: situation 2005, CLE-scenario 2010 and MFR-scenario 2010. The CLE-scenario is based on the current legislation and the national emissions ceilings, NEC. The MFR-scenario describes the maximum feasible reduction measures. (orig.)

  6. REM sleep behavior disorder: from dreams to neurodegeneration.

    Science.gov (United States)

    Postuma, Ronald B; Gagnon, Jean-Francois; Montplaisir, Jacques Y

    2012-06-01

    REM sleep behavior disorder is a unique parasomnia characterized by dream enactment behavior during REM sleep. Unless triggered by pharmacologic agents such as antidepressants, it is generally related to damage of pontomedullary brainstem structures. Idiopathic REM sleep behavior disorder (RBD) is a well-established risk factor for neurodegenerative disease. Prospective studies have estimated that at least 40-65% of patients with idiopathic RBD will eventually develop a defined neurodegenerative phenotype, almost always a 'synucleinopathy' (Parkinson's disease, Lewy Body dementia or multiple system atrophy). In most cases, patients appear to develop a syndrome with overlapping features of both Parkinson's disease and Lewy body dementia. The interval between RBD onset and disease onset averages 10-15 years, suggesting a promisingly large window for intervention into preclinical disease stages. The ability of RBD to predict disease has major implications for design and development of neuroprotective therapy, and testing of other predictive markers of synuclein-mediated neurodegeneration. Recent studies in idiopathic RBD patients have demonstrated that olfaction, color vision, severity of REM atonia loss, transcranial ultrasound of the substantia nigra, and dopaminergic neuroimaging can predict development of neurodegenerative disease.

  7. Selective REM sleep deprivation in narcolepsy.

    Science.gov (United States)

    Vu, Manh Hoang; Hurni, Christoph; Mathis, Johannes; Roth, Corinne; Bassetti, Claudio L

    2011-03-01

    Narcolepsy is characterized by excessive daytime sleepiness and rapid eye movement (REM) sleep abnormalities, including cataplexy. The aim of this study was to assess REM sleep pressure and homeostasis in narcolepsy. Six patients with narcolepsy and six healthy controls underwent a REM sleep deprivation protocol, including one habituation, one baseline, two deprivation nights (D1, D2) and one recovery night. Multiple sleep latency tests (MSLTs) were performed during the day after baseline and after D2. During D1 and D2 REM sleep was prevented by awakening the subjects at the first polysomnographic signs of REM sleep for 2 min. Mean sleep latency and number of sleep-onset REM periods (SOREMs) were determined on all MSLT. More interventions were required to prevent REM sleep in narcoleptics compared with control subjects during D1 (57 ± 16 versus 24 ± 10) and D2 (87 ± 22 versus 35 ± 8, P = 0.004). Interventions increased from D1 to D2 by 46% in controls and by 53% in narcoleptics (P REM sleep deprivation was successful in both controls (mean reduction of REM to 6% of baseline) and narcoleptics (11%). Both groups had a reduction of total sleep time during the deprivation nights (P = 0.03). Neither group had REM sleep rebound in the recovery night. Narcoleptics had, however, an increase in the number of SOREMs on MSLT (P = 0.005). There was no increase in the number of cataplexies after selective REM sleep deprivation. We conclude that: (i) REM sleep pressure is higher in narcoleptics; (ii) REM sleep homeostasis is similar in narcoleptics and controls; (iii) in narcoleptics selective REM sleep deprivation may have an effect on sleep propensity but not on cataplexy.

  8. Cutamesine Overcomes REM Sleep Deprivation-Induced Memory Loss : Relationship to Sigma-1 Receptor Occupancy

    NARCIS (Netherlands)

    Kuzhuppilly Ramakrishnan, Nisha; Schepers, Marianne; Luurtsema, Gert; Nyakas, Csaba J.; Elsinga, Philip H.; Ishiwata, Kiichi; Dierckx, Rudi A. J. O.; van Waarde, Aren

    2015-01-01

    Rapid eye movement (REM) sleep deprivation (SD) decreases cerebral sigma-1 receptor expression and causes cognitive deficits. Sigma-1 agonists are cognitive enhancers. Here, we investigate the effect of cutamesine treatment in the REM SD model. Sigma-1 receptor occupancy (RO) in the rat brain by cut

  9. Cutamesine Overcomes REM Sleep Deprivation-Induced Memory Loss : Relationship to Sigma-1 Receptor Occupancy

    NARCIS (Netherlands)

    Kuzhuppilly Ramakrishnan, Nisha; Schepers, Marianne; Luurtsema, Gert; Nyakas, Csaba J.; Elsinga, Philip H.; Ishiwata, Kiichi; Dierckx, Rudi A. J. O.; van Waarde, Aren

    Rapid eye movement (REM) sleep deprivation (SD) decreases cerebral sigma-1 receptor expression and causes cognitive deficits. Sigma-1 agonists are cognitive enhancers. Here, we investigate the effect of cutamesine treatment in the REM SD model. Sigma-1 receptor occupancy (RO) in the rat brain by

  10. Why Does REM Sleep Occur? A Wake-up Hypothesis

    Directory of Open Access Journals (Sweden)

    Dr. W. R. eKlemm

    2011-09-01

    Full Text Available Brain activity differs in the various sleep stages and in conscious wakefulness. Awakening from sleep requires restoration of the complex nerve impulse patterns in neuronal network assemblies necessary to re-create and sustain conscious wakefulness. Herein I propose that the brain uses REM to help wake itself up after it has had a sufficient amount of sleep. Evidence suggesting this hypothesis includes the facts that, 1 when first going to sleep, the brain plunges into Stage N3 (formerly called Stage IV, a deep abyss of sleep, and, as the night progresses, the sleep is punctuated by episodes of REM that become longer and more frequent toward morning, 2 conscious-like dreams are a reliable component of the REM state in which the dreamer is an active mental observer or agent in the dream, 3 the last awakening during a night’s sleep usually occurs in a REM episode during or at the end of a dream, 4 both REM and awake consciousness seem to arise out of a similar brainstem ascending arousal system 5 N3 is a functionally perturbed state that eventually must be corrected so that embodied brain can direct adaptive behavior, and 6 corticofugal projections to brainstem arousal areas provide a way to trigger increased cortical activity in REM to progressively raise the sleeping brain to the threshold required for wakefulness. This paper shows how the hypothesis conforms to common experience and has substantial predictive and explanatory power regarding the phenomenology of sleep in terms of ontogeny, aging, phylogeny, abnormal/disease states, cognition, and behavioral physiology. That broad range of consistency is not matched by competing theories, which are summarized herein. Specific ways to test this wake-up hypothesis are suggested. Such research could lead to a better understanding of awake consciousness.

  11. Predictive Models for Music

    OpenAIRE

    Paiement, Jean-François; Grandvalet, Yves; Bengio, Samy

    2008-01-01

    Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce generative models for melodies. We decompose melodic modeling into two subtasks. We first propose a rhythm model based on the distributions of distances between subsequences. Then, we define a generative model for melodies given chords and rhythms based on modeling sequences of Narmour featur...

  12. Zephyr - the prediction models

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg

    2001-01-01

    This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Dani...

  13. Olfactory impairment in the rotenone model of Parkinson's disease is associated with bulbar dopaminergic D2 activity after REM sleep deprivation

    Directory of Open Access Journals (Sweden)

    Laís Soares Rodrigues

    2014-12-01

    Full Text Available Olfactory and rapid eye movement (REM sleep deficits are commonly found in untreated subjects with a recent diagnosis of Parkinson's disease (PD. Besides different studies reported declines in olfactory performances during a short period of sleep deprivation. Mechanisms underlying these clinical manifestations are poorly understood although the impairment in the dopamine (DA neurotransmission in the olfactory bulb and in the nigrostriatal pathway may have important roles in olfactory as well as in REM sleep disturbances. Therefore, we have led to the hypothesis that a modulation of the dopaminergic D2 receptors in the olfactory bulb could provide a more comprehensive understanding of the olfactory deficits in PD and after a short period of REM sleep deprivation (REMSD. We decided to investigate the olfactory, neurochemical and histological alterations generated by the administration of piribedil (a selective D2 agonist or raclopride (a selective D2 antagonist, within the glomerular layer of the olfactory bulb, in rats submitted to intranigral rotenone and REMSD. Our findings provided a remarkable evidence of the occurrence of a negative correlation (r = - 0.52, P = 0.04 between the number of periglomerular TH-ir neurons and the bulbar levels of DA in the rotenone, but not sham groups. A significant positive correlation (r = 0.34, P = 0.03 was observed between nigral DA and olfactory discrimination index (DI, for the sham groups, indicating that increased DA levels in the substantia nigra pars compacta (SNpc are associated to enhanced olfactory discrimination performance. Also, increased levels in bulbar and striatal DA induced by piribedil in the rotenone control and rotenone REMSD groups were consistent with reduced amounts of DI. The present evidence reinforce that DA produced by periglomerular neurons, and particularly the bulbar dopaminergic D2 receptors, are essential participants in the olfactory discrimination processes, as well as SNpc

  14. Olfactory impairment in the rotenone model of Parkinson's disease is associated with bulbar dopaminergic D2 activity after REM sleep deprivation.

    Science.gov (United States)

    Rodrigues, Lais S; Targa, Adriano D S; Noseda, Ana Carolina D; Aurich, Mariana F; Da Cunha, Cláudio; Lima, Marcelo M S

    2014-01-01

    Olfactory and rapid eye movement (REM) sleep deficits are commonly found in untreated subjects with a recent diagnosis of Parkinson's disease (PD). Additionally, different studies report declines in olfactory performance during a short period of sleep deprivation. Mechanisms underlying these clinical manifestations are poorly understood, and impairment of dopamine (DA) neurotransmission in the olfactory bulb and the nigrostriatal pathway may have important roles in olfaction and REM sleep disturbances. Therefore, we hypothesized that modulation of the dopaminergic D2 receptors in the olfactory bulb could provide a more comprehensive understanding of the olfactory deficits in PD and REM sleep deprivation (REMSD). We decided to investigate the olfactory, neurochemical, and histological alterations generated through the administration of piribedil (a selective D2 agonist) or raclopride (a selective D2 antagonist) within the glomerular layer of the olfactory bulb, in rats subjected to intranigral rotenone and REMSD. Our findings provide evidence of the occurrence of a negative correlation (r = -0.52, P = 0.04) between the number of periglomerular TH-ir neurons and the bulbar levels of DA in the rotenone, but not sham, groups. A significant positive correlation (r = 0.34, P = 0.03) was observed between nigrostriatal DA levels and olfactory discrimination index (DI) for the sham groups, indicating that increased DA levels in the substantia nigra pars compacta (SNpc) are associated with enhanced olfactory discrimination performance. Also, increased levels in bulbar and striatal DA were induced by piribedil in the rotenone control and rotenone REMSD groups, consistent with reductions in the DI. The present evidence reinforce the idea that DA produced by periglomerular neurons, particularly the bulbar dopaminergic D2 receptors, is an essential participant in olfactory discrimination processes, as the SNpc, and the striatum.

  15. Olfactory impairment in the rotenone model of Parkinson’s disease is associated with bulbar dopaminergic D2 activity after REM sleep deprivation

    Science.gov (United States)

    Rodrigues, Lais S.; Targa, Adriano D. S.; Noseda, Ana Carolina D.; Aurich, Mariana F.; Da Cunha, Cláudio; Lima, Marcelo M. S.

    2014-01-01

    Olfactory and rapid eye movement (REM) sleep deficits are commonly found in untreated subjects with a recent diagnosis of Parkinson’s disease (PD). Additionally, different studies report declines in olfactory performance during a short period of sleep deprivation. Mechanisms underlying these clinical manifestations are poorly understood, and impairment of dopamine (DA) neurotransmission in the olfactory bulb and the nigrostriatal pathway may have important roles in olfaction and REM sleep disturbances. Therefore, we hypothesized that modulation of the dopaminergic D2 receptors in the olfactory bulb could provide a more comprehensive understanding of the olfactory deficits in PD and REM sleep deprivation (REMSD). We decided to investigate the olfactory, neurochemical, and histological alterations generated through the administration of piribedil (a selective D2 agonist) or raclopride (a selective D2 antagonist) within the glomerular layer of the olfactory bulb, in rats subjected to intranigral rotenone and REMSD. Our findings provide evidence of the occurrence of a negative correlation (r = −0.52, P = 0.04) between the number of periglomerular TH-ir neurons and the bulbar levels of DA in the rotenone, but not sham, groups. A significant positive correlation (r = 0.34, P = 0.03) was observed between nigrostriatal DA levels and olfactory discrimination index (DI) for the sham groups, indicating that increased DA levels in the substantia nigra pars compacta (SNpc) are associated with enhanced olfactory discrimination performance. Also, increased levels in bulbar and striatal DA were induced by piribedil in the rotenone control and rotenone REMSD groups, consistent with reductions in the DI. The present evidence reinforce the idea that DA produced by periglomerular neurons, particularly the bulbar dopaminergic D2 receptors, is an essential participant in olfactory discrimination processes, as the SNpc, and the striatum. PMID:25520618

  16. REM Sleep Phase Preference in the Crepuscular Octodon degus Assessed by Selective REM Sleep Deprivation

    Science.gov (United States)

    Ocampo-Garcés, Adrián; Hernández, Felipe; Palacios, Adrian G.

    2013-01-01

    Study Objectives: To determine rapid eye movement (REM) sleep phase preference in a crepuscular mammal (Octodon degus) by challenging the specific REM sleep homeostatic response during the diurnal and nocturnal anticrepuscular rest phases. Design: We have investigated REM sleep rebound, recovery, and documented REM sleep propensity measures during and after diurnal and nocturnal selective REM sleep deprivations. Subjects: Nine male wild-captured O. degus prepared for polysomnographic recordings Interventions: Animals were recorded during four consecutive baseline and two separate diurnal or nocturnal deprivation days, under a 12:12 light-dark schedule. Three-h selective REM sleep deprivations were performed, starting at midday (zeitgeber time 6) or midnight (zeitgeber time 18). Measurements and Results: Diurnal and nocturnal REM sleep deprivations provoked equivalent amounts of REM sleep debt, but a consistent REM sleep rebound was found only after nocturnal deprivation. The nocturnal rebound was characterized by a complete recovery of REM sleep associated with an augment in REM/total sleep time ratio and enhancement in REM sleep episode consolidation. Conclusions: Our results support the notion that the circadian system actively promotes REM sleep. We propose that the sleep-wake cycle of O. degus is modulated by a chorus of circadian oscillators with a bimodal crepuscular modulation of arousal and a unimodal promotion of nocturnal REM sleep. Citation: Ocampo-Garcés A; Hernández F; Palacios AG. REM sleep phase preference in the crepuscular Octodon degus assessed by selective REM sleep deprivation. SLEEP 2013;36(8):1247-1256. PMID:23904685

  17. In vitro model for the study of the role of the mesopontine region in rapid eye movement (REM sleep and wakefulness.

    Directory of Open Access Journals (Sweden)

    Esteban Pino

    2017-06-01

    Full Text Available O estudo de estratégias neurais para a organização do comportamento em vertebrados constitui um desafio maior para a neurociencia. O avanço do conhecimento nessa área depende criticamente da utilização de modelos experimentais adequados que suportem múltiplos níveis de análise (por exemplo: comportamental, circuital, celular,  sináptico e molecular e abordagens por múltiplas técnicas. Decidiu-se analisar in vitro uma rede neural da união mesopontina do tronco encefálico criticamente envolvida no controle do sono de movimentos oculares rápidos (S-REM. Apesar da riqueza de provas que sustentam o papel desta rede em relação ao S-REM, os mecanismos celulares e sinápticos subjacentes a este controle são pouco conhecidos e permanecem sob intensa investigação. Para avançar no conhecimento desses mecanismos, caracterizou-se morfológica e funcionalmente uma fatia de tronco encefálico de rato, na qual as estruturas críticas para o controle do S-REM, i.e.: núcleos tegmentais laterodorsal e pedunculopontino, e sua projeção para o núcleo reticular pontis oralis (PnO estão presentes e operantes. A inclusão do núcleo motor do trigêmeo na fatia permitiu detectar mudanças da excitabilidade das motoneuronas provocadas por manipulações farmacológicas do PnO, representativas das alterações do tônus muscular associados com operações semelhantes quando realizados in vivo. A utlização deste modelo in vitro de S-REM permitirá contribuir para a elucidação de estratégias neurais que operam em níveis intermedios de organização do SN de mamíferos para a geração e regulação de um estado comportamental.

  18. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used...... to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...

  19. Modelling, controlling, predicting blackouts

    CERN Document Server

    Wang, Chengwei; Baptista, Murilo S

    2016-01-01

    The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids, and another one for smart grids. The control strategie...

  20. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  1. Antidepressant suppression of non-REM sleep spindles and REM sleep impairs hippocampus-dependent learning while augmenting striatum-dependent learning.

    Science.gov (United States)

    Watts, Alain; Gritton, Howard J; Sweigart, Jamie; Poe, Gina R

    2012-09-26

    Rapid eye movement (REM) sleep enhances hippocampus-dependent associative memory, but REM deprivation has little impact on striatum-dependent procedural learning. Antidepressant medications are known to inhibit REM sleep, but it is not well understood if antidepressant treatments impact learning and memory. We explored antidepressant REM suppression effects on learning by training animals daily on a spatial task under familiar and novel conditions, followed by training on a procedural memory task. Daily treatment with the antidepressant and norepinephrine reuptake inhibitor desipramine (DMI) strongly suppressed REM sleep in rats for several hours, as has been described in humans. We also found that DMI treatment reduced the spindle-rich transition-to-REM sleep state (TR), which has not been previously reported. DMI REM suppression gradually weakened performance on a once familiar hippocampus-dependent maze (reconsolidation error). DMI also impaired learning of the novel maze (consolidation error). Unexpectedly, learning of novel reward positions and memory of familiar positions were equally and oppositely correlated with amounts of TR sleep. Conversely, DMI treatment enhanced performance on a separate striatum-dependent, procedural T-maze task that was positively correlated with the amounts of slow-wave sleep (SWS). Our results suggest that learning strategy switches in patients taking REM sleep-suppressing antidepressants might serve to offset sleep-dependent hippocampal impairments to partially preserve performance. State-performance correlations support a model wherein reconsolidation of hippocampus-dependent familiar memories occurs during REM sleep, novel information is incorporated and consolidated during TR, and dorsal striatum-dependent procedural learning is augmented during SWS.

  2. Overnight improvements in two REM sleep-sensitive tasks are associated with both REM and NREM sleep changes, sleep spindle features, and awakenings for dream recall.

    Science.gov (United States)

    Nielsen, T; O'Reilly, C; Carr, M; Dumel, G; Godin, I; Solomonova, E; Lara-Carrasco, J; Blanchette-Carrière, C; Paquette, T

    2015-07-01

    Memory consolidation is associated with sleep physiology but the contribution of specific sleep stages remains controversial. To clarify the contribution of REM sleep, participants were administered two REM sleep-sensitive tasks to determine if associated changes occurred only in REM sleep. Twenty-two participants (7 men) were administered the Corsi Block Tapping and Tower of Hanoi tasks prior to and again after a night of sleep. Task improvers and non-improvers were compared for sleep structure, sleep spindles, and dream recall. Control participants (N = 15) completed the tasks twice during the day without intervening sleep. Overnight Corsi Block improvement was associated with more REM sleep whereas Tower of Hanoi improvement was associated with more N2 sleep. Corsi Block improvement correlated positively with %REM sleep and Tower of Hanoi improvement with %N2 sleep. Post-hoc analyses suggest Tower of Hanoi effects-but not Corsi Block effects-are due to trait differences. Sleep spindle density was associated with Tower of Hanoi improvement whereas spindle amplitude correlated with Corsi Block improvement. Number of REM awakenings for dream reporting (but not dream recall per se) was associated with Corsi Block, but not Tower of Hanoi, improvement but was confounded with REM sleep time. This non-replication of one of 2 REM-sensitive task effects challenges both 'dual-process' and 'sequential' or 'sleep organization' models of sleep-dependent learning and points rather to capacity limitations on REM sleep. Experimental awakenings for sampling dream mentation may not perturb sleep-dependent learning effects; they may even enhance them.

  3. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy production......The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...... and HIRLAM predictions. The statistical models belong to the class of conditional parametric models. The models are estimated using local polynomial regression, but the estimation method is here extended to be adaptive in order to allow for slow changes in the system e.g. caused by the annual variations...

  4. Cells of a common developmental origin regulate REM/non-REM sleep and wakefulness in mice.

    Science.gov (United States)

    Hayashi, Yu; Kashiwagi, Mitsuaki; Yasuda, Kosuke; Ando, Reiko; Kanuka, Mika; Sakai, Kazuya; Itohara, Shigeyoshi

    2015-11-20

    Mammalian sleep comprises rapid eye movement (REM) sleep and non-REM (NREM) sleep. To functionally isolate from the complex mixture of neurons populating the brainstem pons those involved in switching between REM and NREM sleep, we chemogenetically manipulated neurons of a specific embryonic cell lineage in mice. We identified excitatory glutamatergic neurons that inhibit REM sleep and promote NREM sleep. These neurons shared a common developmental origin with neurons promoting wakefulness; both derived from a pool of proneural hindbrain cells expressing Atoh1 at embryonic day 10.5. We also identified inhibitory γ-aminobutyric acid-releasing neurons that act downstream to inhibit REM sleep. Artificial reduction or prolongation of REM sleep in turn affected slow-wave activity during subsequent NREM sleep, implicating REM sleep in the regulation of NREM sleep.

  5. Short REM latency in impotence without depression.

    Science.gov (United States)

    Schmidt, H S; Nofzinger, E A

    1988-05-01

    In a retrospective study, the presence of depression was studied in a group of 14 impotent patients who were selected on the basis of the similarity between their electroencephalographic (EEG) sleep patterns and those of patients with endogenous depression. Specifically, the value of rapid eye movement (REM) latency plus age less than 100 was used as a selection criterion. Sleep continuity disturbances, increased REM time, and increased REM% were noted in the short REM latency impotent group. On the basis of MMPI and psychiatric history and interview, only one of these impotent patients showed major depression. The authors conclude that impotent patients with a short REM latency are not, as a group, depressed and that the incidence of depression in impotent men should be determined irrespective of EEG sleep findings.

  6. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...

  7. Kef el-Kérem

    OpenAIRE

    Roubet, C.

    2012-01-01

    À 35 km au sud-est de Tiaret, près de l’axe routier Tiaret-Aflou, au delà de l’agglomération de Nador (Trézel), se dressent les derniers chaînons telliens de l’Oranie orientale. Orientés SE/NW, les Djebels ben Nsoui (1 474 m) et Nador/Belvédère (1453 m) surplombent une zone de daïa et de grands chotts, formant les Hauts-Plateaux oranais. Au nord-ouest du Djebel Nador s’élève le relief tabulaire du Kef el-Kérem et jaillit la résurgence de l’Oued Sousselem (Cadenat, 1966, Carte n° 247 de Trézel...

  8. Predictive models of forest dynamics.

    Science.gov (United States)

    Purves, Drew; Pacala, Stephen

    2008-06-13

    Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

  9. Thermophysical properties along Curiosity's traverse in Gale crater, Mars, derived from the REMS ground temperature sensor

    Science.gov (United States)

    Vasavada, Ashwin R.; Piqueux, Sylvain; Lewis, Kevin W.; Lemmon, Mark T.; Smith, Michael D.

    2017-03-01

    The REMS instrument onboard the Mars Science Laboratory rover, Curiosity, has measured ground temperature nearly continuously at hourly intervals for two Mars years. Coverage of the entire diurnal cycle at 1 Hz is available every few martian days. We compare these measurements with predictions of surface-atmosphere thermal models to derive the apparent thermal inertia and thermally derived albedo along the rover's traverse after accounting for the radiative effects of atmospheric water ice during fall and winter, as is necessary to match the measured seasonal trend. The REMS measurements can distinguish between active sand, other loose materials, mudstone, and sandstone based on their thermophysical properties. However, the apparent thermal inertias of bedrock-dominated surfaces (∼350-550 J m-2 K-1 s-½) are lower than expected. We use rover imagery and the detailed shape of the diurnal ground temperature curve to explore whether lateral or vertical heterogeneity in the surface materials within the sensor footprint might explain the low inertias. We find that the bedrock component of the surface can have a thermal inertia as high as 650-1700 J m-2 K-1 s-½ for mudstone sites and ∼700 J m-2 K-1 s-½ for sandstone sites in models runs that include lateral and vertical mixing. Although the results of our forward modeling approach may be non-unique, they demonstrate the potential to extract information about lateral and vertical variations in thermophysical properties from temporally resolved measurements of ground temperature.

  10. Automatic REM sleep detection associated with idiopathic rem sleep Behavior Disorder

    DEFF Research Database (Denmark)

    Kempfner, J; Sørensen, Gertrud Laura; Sorensen, H B D

    2011-01-01

    Rapid eye movement sleep Behavior Disorder (RBD) is a strong early marker of later development of Parkinsonism. Currently there are no objective methods to identify and discriminate abnormal from normal motor activity during REM sleep. Therefore, a REM sleep detection without the use of chin...... electromyography (EMG) is useful. This is addressed by analyzing the classification performance when implementing two automatic REM sleep detectors. The first detector uses the electroencephalography (EEG), electrooculography (EOG) and EMG to detect REM sleep, while the second detector only uses the EEG and EOG....

  11. Arousal state feedback as a potential physiological generator of the ultradian REM/NREM sleep cycle.

    Science.gov (United States)

    Phillips, A J K; Robinson, P A; Klerman, E B

    2013-02-21

    Human sleep episodes are characterized by an approximately 90-min ultradian oscillation between rapid eye movement (REM) and non-REM (NREM) sleep stages. The source of this oscillation is not known. Pacemaker mechanisms for this rhythm have been proposed, such as a reciprocal interaction network, but these fail to account for documented homeostatic regulation of both sleep stages. Here, two candidate mechanisms are investigated using a simple model that has stable states corresponding to Wake, REM sleep, and NREM sleep. Unlike other models of the ultradian rhythm, this model of sleep dynamics does not include an ultradian pacemaker, nor does it invoke a hypothetical homeostatic process that exists purely to drive ultradian rhythms. Instead, only two inputs are included: the homeostatic drive for Sleep and the circadian drive for Wake. These two inputs have been the basis for the most influential Sleep/Wake models, but have not previously been identified as possible ultradian rhythm generators. Using the model, realistic ultradian rhythms are generated by arousal state feedback to either the homeostatic or circadian drive. For the proposed 'homeostatic mechanism', homeostatic pressure increases in Wake and REM sleep, and decreases in NREM sleep. For the proposed 'circadian mechanism', the circadian drive is up-regulated in Wake and REM sleep, and is down-regulated in NREM sleep. The two mechanisms are complementary in the features they capture. The homeostatic mechanism reproduces experimentally observed rebounds in NREM sleep duration and intensity following total sleep deprivation, and rebounds in both NREM sleep intensity and REM sleep duration following selective REM sleep deprivation. The circadian mechanism does not reproduce sleep state rebounds, but more accurately reproduces the temporal patterns observed in a normal night of sleep. These findings have important implications in terms of sleep physiology and they provide a parsimonious explanation for the

  12. Family history of idiopathic REM behavior disorder

    DEFF Research Database (Denmark)

    Dauvilliers, Yves; Postuma, Ronald B; Ferini-Strambi, Luigi;

    2013-01-01

    To compare the frequency of proxy-reported REM sleep behavior disorder (RBD) among relatives of patients with polysomnogram-diagnosed idiopathic RBD (iRBD) in comparison to controls using a large multicenter clinic-based cohort.......To compare the frequency of proxy-reported REM sleep behavior disorder (RBD) among relatives of patients with polysomnogram-diagnosed idiopathic RBD (iRBD) in comparison to controls using a large multicenter clinic-based cohort....

  13. REMS Wind Sensor Preliminary Results

    Science.gov (United States)

    De La Torre Juarez, M.; Gomez-Elvira, J.; Navarro, S.; Marin, M.; Torres, J.; Rafkin, S. C.; Newman, C. E.; Pla-García, J.

    2015-12-01

    The REMS instrument is part of the Mars Science Laboratory payload. It is a sensor suite distributed over several parts of the rover. The wind sensor, which is composed of two booms equipped with a set of hot plate anemometers, is installed on the Rover Sensing Mast (RSM). During landing most of the hot plates of one boom were damaged, most likely by the pebbles lifted by the Sky Crane thruster. The loss of one wind boom necessitated a full review of the data processing strategy. Different algorithms have been tested on the readings of the first Mars year, and these results are now archived in the Planetary Data System (PDS), The presentation will include a description of the data processing methods and of the resulting products, including the typical evolution of wind speed and direction session-by-session, hour-by-hour and other kinds of statistics . A review of the wind readings over the first Mars year will also be presented.

  14. Schema-conformant memories are preferentially consolidated during REM sleep.

    Science.gov (United States)

    Durrant, Simon J; Cairney, Scott A; McDermott, Cathal; Lewis, Penelope A

    2015-07-01

    Memory consolidation is most commonly described by the standard model, which proposes an initial binding role for the hippocampus which diminishes over time as intracortical connections are strengthened. Recent evidence suggests that slow wave sleep (SWS) plays an essential role in this process. Existing animal and human studies have suggested that memories which fit tightly into an existing knowledge framework or schema might use an alternative consolidation route in which the medial prefrontal cortex takes on the binding role. In this study we sought to investigate the role of sleep in this process using a novel melodic memory task. Participants were asked to remember 32 melodies, half of which conformed to a tonal schema present in all enculturated listeners, and half of which did not fit with this schema. After a 24-h consolidation interval, participants were asked to remember a further 32 melodies, before being given a recognition test in which melodies from both sessions were presented alongside some previously unheard foils. Participants remembered schema-conformant melodies better than non-conformant ones. This was much more strongly the case for consolidated melodies, suggesting that consolidation over a 24-h period preferentially consolidated schema-conformant items. Overnight sleep was monitored between the sessions, and the extent of the consolidation benefit for schema-conformant items was associated with both the amount of REM sleep obtained and EEG theta power in frontal and central regions during REM sleep. Overall our data suggest that REM sleep plays a crucial role in the rapid consolidation of schema-conformant items. This finding is consistent with previous results from animal studies and the SLIMM model of Van Kesteren, Ruiter, Fernández, and Henson (2012), and suggest that REM sleep, rather than SWS, may be involved in an alternative pathway of consolidation for schema-conformant memories.

  15. Design and analysis of a model predictive controller for active queue management.

    Science.gov (United States)

    Wang, Ping; Chen, Hong; Yang, Xiaoping; Ma, Yan

    2012-01-01

    Model predictive (MP) control as a novel active queue management (AQM) algorithm in dynamic computer networks is proposed. According to the predicted future queue length in the data buffer, early packets at the router are dropped reasonably by the MPAQM controller so that the queue length reaches the desired value with minimal tracking error. The drop probability is obtained by optimizing the network performance. Further, randomized algorithms are applied to analyze the robustness of MPAQM successfully, and also to provide the stability domain of systems with uncertain network parameters. The performances of MPAQM are evaluated through a series of simulations in NS2. The simulation results show that the MPAQM algorithm outperforms RED, PI, and REM algorithms in terms of stability, disturbance rejection, and robustness.

  16. REM sleep deprivation during 5 hours leads to an immediate REM sleep rebound and to suppression of non-REM sleep intensity

    NARCIS (Netherlands)

    Beersma, D.G.M.; Dijk, D.J.; Blok, Guus; Everhardus, I.

    Nine healthy male subjects were deprived of REM sleep during the first 5 h after sleep onset. Afterwards recovery sleep was undisturbed. During the deprivation period the non-REM EEG power spectrum was reduced when compared to baseline for the frequencies up to 7 Hz, despite the fact that non-REM

  17. REM sleep deprivation during 5 hours leads to an immediate REM sleep rebound and to suppression of non-REM sleep intensity

    NARCIS (Netherlands)

    Beersma, D.G.M.; Dijk, D.J.; Blok, Guus; Everhardus, I.

    1990-01-01

    Nine healthy male subjects were deprived of REM sleep during the first 5 h after sleep onset. Afterwards recovery sleep was undisturbed. During the deprivation period the non-REM EEG power spectrum was reduced when compared to baseline for the frequencies up to 7 Hz, despite the fact that non-REM sl

  18. Oximetry Signal Processing Identifies REM Sleep-Related Vulnerability Trait in Asthmatic Children

    Science.gov (United States)

    Perez, Geovanny F.; Gutierrez, Maria J.; Huseni, Shehlanoor; Pancham, Khrisna; Rodriguez-Martinez, Carlos E.; Nino, Cesar L.; Nino, Gustavo

    2013-01-01

    Rationale. The sleep-related factors that modulate the nocturnal worsening of asthma in children are poorly understood. This study addressed the hypothesis that asthmatic children have a REM sleep-related vulnerability trait that is independent of OSA. Methods. We conducted a retrospective cross-sectional analysis of pulse-oximetry signals obtained during REM and NREM sleep in control and asthmatic children (n = 134). Asthma classification was based on preestablished clinical criteria. Multivariate linear regression model was built to control for potential confounders (significance level P ≤ 0.05). Results. Our data demonstrated that (1) baseline nocturnal respiratory parameters were not significantly different in asthmatic versus control children, (2) the maximal % of SaO2 desaturation during REM, but not during NREM, was significantly higher in asthmatic children, and (3) multivariate analysis revealed that the association between asthma and REM-related maximal % SaO2 desaturation was independent of demographic variables. Conclusion. These results demonstrate that children with asthma have a REM-related vulnerability trait that impacts oxygenation independently of OSA. Further research is needed to delineate the REM sleep neurobiological mechanisms that modulate the phenotypical expression of nocturnal asthma in children. PMID:24288619

  19. Oximetry Signal Processing Identifies REM Sleep-Related Vulnerability Trait in Asthmatic Children

    Directory of Open Access Journals (Sweden)

    Geovanny F. Perez

    2013-01-01

    Full Text Available Rationale. The sleep-related factors that modulate the nocturnal worsening of asthma in children are poorly understood. This study addressed the hypothesis that asthmatic children have a REM sleep-related vulnerability trait that is independent of OSA. Methods. We conducted a retrospective cross-sectional analysis of pulse-oximetry signals obtained during REM and NREM sleep in control and asthmatic children (n=134. Asthma classification was based on preestablished clinical criteria. Multivariate linear regression model was built to control for potential confounders (significance level P≤0.05. Results. Our data demonstrated that (1 baseline nocturnal respiratory parameters were not significantly different in asthmatic versus control children, (2 the maximal % of SaO2 desaturation during REM, but not during NREM, was significantly higher in asthmatic children, and (3 multivariate analysis revealed that the association between asthma and REM-related maximal % SaO2 desaturation was independent of demographic variables. Conclusion. These results demonstrate that children with asthma have a REM-related vulnerability trait that impacts oxygenation independently of OSA. Further research is needed to delineate the REM sleep neurobiological mechanisms that modulate the phenotypical expression of nocturnal asthma in children.

  20. Sleep alterations following exposure to stress predict fear-associated memory impairments in a rodent model of PTSD.

    Science.gov (United States)

    Vanderheyden, William M; George, Sophie A; Urpa, Lea; Kehoe, Michaela; Liberzon, Israel; Poe, Gina R

    2015-08-01

    Sleep abnormalities, such as insomnia, nightmares, hyper-arousal, and difficulty initiating or maintaining sleep, are diagnostic criteria of posttraumatic stress disorder (PTSD). The vivid dream state, rapid eye movement (REM) sleep, has been implicated in processing emotional memories. We have hypothesized that REM sleep is maladaptive in those suffering from PTSD. However, the precise neurobiological mechanisms regulating sleep disturbances following trauma exposure are poorly understood. Using single prolonged stress (SPS), a well-validated rodent model of PTSD, we measured sleep alterations in response to stressor exposure and over a subsequent 7-day isolation period during which the PTSD-like phenotype develops. SPS resulted in acute increases in REM sleep and transition to REM sleep, and decreased waking in addition to alterations in sleep architecture. The severity of the PTSD-like phenotype was later assessed by measuring freezing levels on a fear-associated memory test. Interestingly, the change in REM sleep following SPS was significantly correlated with freezing behavior during extinction recall assessed more than a week later. Reductions in theta (4-10 Hz) and sigma (10-15 Hz) band power during transition to REM sleep also correlated with impaired fear-associated memory processing. These data reveal that changes in REM sleep, transition to REM sleep, waking, and theta and sigma power may serve as sleep biomarkers to identify individuals with increased susceptibility to PTSD following trauma exposure.

  1. PREDICT : model for prediction of survival in localized prostate cancer

    NARCIS (Netherlands)

    Kerkmeijer, Linda G W; Monninkhof, Evelyn M.; van Oort, Inge M.; van der Poel, Henk G.; de Meerleer, Gert; van Vulpen, Marco

    2016-01-01

    Purpose: Current models for prediction of prostate cancer-specific survival do not incorporate all present-day interventions. In the present study, a pre-treatment prediction model for patients with localized prostate cancer was developed.Methods: From 1989 to 2008, 3383 patients were treated with I

  2. Mechanisms of REM sleep in health and disease.

    Science.gov (United States)

    Fraigne, Jimmy J; Grace, Kevin P; Horner, Richard L; Peever, John

    2014-11-01

    Our understanding of rapid eye movement (REM) sleep and how it is generated remains a topic of debate. Understanding REM sleep mechanisms is important because several sleep disorders result from disturbances in the neural circuits that control REM sleep and its characteristics. This review highlights recent work concerning how the central nervous system regulates REM sleep, and how the make up and breakdown of these REM sleep-generating circuits contribute to narcolepsy, REM sleep behaviour disorder and sleep apnea. A complex interaction between brainstem REM sleep core circuits and forebrain and hypothalamic structures is necessary to generate REM sleep. Cholinergic activation and GABAergic inhibition trigger the activation of subcoeruleus neurons, which form the core of the REM sleep circuit. Untimely activation of REM sleep circuits leads to cataplexy - involuntary muscle weakness or paralysis - a major symptom of narcolepsy. Degeneration of the REM circuit is associated with excessive muscle activation in REM sleep behaviour disorder. Inappropriate arousal from sleep during obstructive sleep apnea repeatedly disturbs the activity of sleep circuits, particularly the REM sleep circuit.

  3. Removal of ocular artifacts from the REM sleep EEG

    NARCIS (Netherlands)

    D. Waterman; J.C. Woestenburg; M. Elton; W. Hofman; A. Kok

    1992-01-01

    The present report concerns the first study in which electrooculographic (EOG) contamination of electroencephalographic (EEG) recordings in rapid eye movement (REM) sleep is systematically investigated. Contamination of REM sleep EEG recordings in six subjects was evaluated in the frequency domain.

  4. Predictive Modeling of Cardiac Ischemia

    Science.gov (United States)

    Anderson, Gary T.

    1996-01-01

    The goal of the Contextual Alarms Management System (CALMS) project is to develop sophisticated models to predict the onset of clinical cardiac ischemia before it occurs. The system will continuously monitor cardiac patients and set off an alarm when they appear about to suffer an ischemic episode. The models take as inputs information from patient history and combine it with continuously updated information extracted from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural network and rough set methodologies are then used to forecast the onset of clinical ischemia before it transpires, thus allowing early intervention aimed at preventing morbid complications from occurring. The models will differ from previous attempts by including combinations of continuous and discrete inputs. A commercial medical instrumentation and software company has invested funds in the project with a goal of commercialization of the technology. The end product will be a system that analyzes physiologic parameters and produces an alarm when myocardial ischemia is present. If proven feasible, a CALMS-based system will be added to existing heart monitoring hardware.

  5. A Time-Dependent Oceanic Aerosol Profile Model.

    Science.gov (United States)

    1982-02-10

    t iCk t ,% il 01t 11Uc’. .l2 inm[proirnt ent in thi-, model can he ohtained bk simph\\ upgrading the .,irli(Ui ..uhr(iutntcN u,,cd tl ItiL " model Th...PRINT Ni 17 P(20)=4 18 RETURN 20 REM SAVE WORLD ROUTINE 21 P(20)=5 22 RETURN 10000 GO TO 30090 20000 REM -------------------- OVL -- AREA 20010 REM 30000...RETURN 20000 REM 20010 REM --- 20020 REM @AEROSOL/PROGRAM/TASK1 20030 REM STUART GATHMAN NRL CODE 4327 20040 REM - 20050 REM 20060 UNIT 1 20070 DIM A

  6. Numerical weather prediction model tuning via ensemble prediction system

    Science.gov (United States)

    Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

    2011-12-01

    This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

  7. RemBench: A Digital Workbench for Rembrandt Research

    NARCIS (Netherlands)

    Verberne, Suzan; Van Leeuwen, Rudie; Gerritsen, G.H.; Boves, Lou

    2016-01-01

    In this paper, we present RemBench, a search engine for research into the life and works of Rembrandt van Rijn. RemBench combines the data from four different databases behind one interface using federated search technology. Metadata filtering is enabled through faceted search. RemBench enables art

  8. Automatic REM Sleep Detection Associated with Idiopathic REM Sleep Behavior Disorder

    DEFF Research Database (Denmark)

    Kempfner, Jacob; Sørensen, Gertrud Laura; Sørensen, Helge Bjarup Dissing

    2011-01-01

    Rapid eye movement sleep Behavior Disorder (RBD) is a strong early marker of later development of Parkinsonism. Currently there are no objective methods to identify and discriminate abnormal from normal motor activity during REM sleep. Therefore, a REM sleep detection without the use of chin...... electromyography (EMG) is useful. This is addressed by analyzing the classification performance when implementing two automatic REM sleep detectors. The first detector uses the electroencephalography (EEG), electrooculography (EOG) and EMG to detect REM sleep, while the second detector only uses the EEG and EOG....... Method: Ten normal controls and ten age matched patients diagnosed with RBD were enrolled. All subjects underwent one polysomnographic (PSG) recording, which was manual scored according to the new sleep-scoring standard from the American Academy of Sleep Medicine. Based on the manual scoring...

  9. CAN NON-REM SLEEP BE DEPRESSOGENIC

    NARCIS (Netherlands)

    BEERSMA, DGM; VANDENHOOFDAKKER, RH

    Sleep and mood are clearly interrelated in major depression, as shown by the antidepressive effects of various experiments, such as total sleep deprivation, partial sleep deprivation, REM sleep deprivation, and temporal shifts of the sleep period. The prevailing hypotheses explaining these effects

  10. Can non-REM sleep be depressogenic?

    NARCIS (Netherlands)

    Beersma, Domien G.M.; Hoofdakker, Rutger H. van den

    1992-01-01

    Sleep and mood are clearly interrelated in major depression, as shown by the antidepressive effects of various experiments, such as total sleep deprivation, partial sleep deprivation, REM sleep deprivation, and temporal shifts of the sleep period. The prevailing hypotheses explaining these effects

  11. Can non-REM sleep be depressogenic?

    NARCIS (Netherlands)

    Beersma, Domien G.M.; Hoofdakker, Rutger H. van den

    1992-01-01

    Sleep and mood are clearly interrelated in major depression, as shown by the antidepressive effects of various experiments, such as total sleep deprivation, partial sleep deprivation, REM sleep deprivation, and temporal shifts of the sleep period. The prevailing hypotheses explaining these effects c

  12. CAN NON-REM SLEEP BE DEPRESSOGENIC

    NARCIS (Netherlands)

    BEERSMA, DGM; VANDENHOOFDAKKER, RH

    1992-01-01

    Sleep and mood are clearly interrelated in major depression, as shown by the antidepressive effects of various experiments, such as total sleep deprivation, partial sleep deprivation, REM sleep deprivation, and temporal shifts of the sleep period. The prevailing hypotheses explaining these effects c

  13. Loss of REM sleep features across nighttime in REM sleep behavior disorder

    OpenAIRE

    Arnaldi, Dario; Latimier, Alice; Leu-Semenescu, Smaranda; VIDAILHET, Marie; Arnulf, Isabelle

    2016-01-01

    International audience; ObjectivesMelatonin is a chronobiotic treatment which also alleviates rapid eye movement (REM) sleep behavior disorder (RBD). Because the mechanisms of this benefit are unclear, we evaluated the clock-dependent REM sleep characteristics in patients with RBD, whether idiopathic (iRBD) or associated with Parkinson's Disease (PD), and we compared findings with PD patients without RBD and with healthy subjects.MethodsAn overnight videopolysomnography was performed in ten i...

  14. Motor-behavioral episodes in REM sleep behavior disorder and phasic events during REM sleep.

    Science.gov (United States)

    Manni, Raffaele; Terzaghi, Michele; Glorioso, Margaret

    2009-02-01

    To investigate if sudden-onset motor-behavioral episodes in REM sleep behavior disorder (RBD) are associated with phasic events of REM sleep, and to explore the potential meaning of such an association. Observational review analysis. Tertiary sleep center. Twelve individuals (11 males; mean age 67.6 +/- 7.4 years) affected by idiopathic RBD, displaying a total of 978 motor-behavioral episodes during nocturnal in-laboratory video-PSG. N/A. The motor activity displayed was primitive in 69.1% and purposeful/semi-purposeful in 30.9% of the motor-behavioral episodes recorded. Sleeptalking was significantly more associated with purposeful/semi-purposeful motor activity than crying and/or incomprehensible muttering (71.0% versus 21.4%, P<0.005). In 58.2% of the motor-behavioral episodes, phasic EEG-EOG events (rapid eye movements [REMs], alpha bursts, or sawtooth waves [STWs]) occurred simultaneously. Each variable (REMs, STWs, alpha bursts) was associated more with purposefullsemi-purposeful than with primitive movements (P<0.05). Motor-behavioral episodes in RBD were significantly more likely to occur in association with phasic than with tonic periods of REM sleep. The presence of REMs, alpha bursts and STWs was found to be more frequent in more complex episodes. We hypothesize that motor-behavioral episodes in RBD are likely to occur when the brain, during REM sleep, is in a state of increased instability (presence of alpha bursts) and experiencing stronger stimulation of visual areas (REMs).

  15. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...

  16. Parkinsonian tremor loses its alternating aspect during non-REM sleep and is inhibited by REM sleep.

    Science.gov (United States)

    Askenasy, J J; Yahr, M D

    1990-01-01

    Non-REM sleep transforms the waking alternating Parkinsonian tremor into subclinical repetitive muscle contractions whose amplitude and duration decrease as non-REM sleep progresses from stages I to IV. During REM sleep Parkinsonian tremor disappears while the isolated muscle events increase significantly. PMID:2246656

  17. Parkinsonian tremor loses its alternating aspect during non-REM sleep and is inhibited by REM sleep.

    OpenAIRE

    Askenasy, J. J.; Yahr, M D

    1990-01-01

    Non-REM sleep transforms the waking alternating Parkinsonian tremor into subclinical repetitive muscle contractions whose amplitude and duration decrease as non-REM sleep progresses from stages I to IV. During REM sleep Parkinsonian tremor disappears while the isolated muscle events increase significantly.

  18. Posttraining Increases in REM Sleep Intensity Implicate REM Sleep in Memory Processing and Provide a Biological Marker of Learning Potential

    Science.gov (United States)

    Nader, Rebecca S.; Smith, Carlyle T.; Nixon, Margaret R.

    2004-01-01

    Posttraining rapid eye movement (REM) sleep has been reported to be important for efficient memory consolidation. The present results demonstrate increases in the intensity of REM sleep during the night of sleep following cognitive procedural/implicit task acquisition. These REM increases manifest as increases in total number of rapid eye…

  19. Sleep in depression: the influence of age, gender and diagnostic subtype on baseline sleep and the cholinergic REM induction test with RS 86.

    Science.gov (United States)

    Riemann, D; Hohagen, F; Bahro, M; Berger, M

    1994-01-01

    One hundred and eight healthy controls and 178 patients with a major depressive disorder according to DSM-III were investigated in the sleep laboratory after a 7-day drug wash-out period. Subsamples of 36 healthy controls and 56 patients additionally took part in the cholinergic rapid eye movement (REM) sleep induction test with RS 86. Data analysis revealed that age exerted powerful influences on sleep in control subjects and depressed patients. Sleep efficiency and amount of slow wave sleep (SWS) decreased with age, whereas the number of awakenings, early morning awakening, and amounts of wake time and stage 1 increased with age. REM latency was negatively correlated with age only in the group of patients with a major depression. Statistical analysis revealed group differences for almost all parameters of sleep continuity with disturbed indices in the depressed group. Differences in SWS were not detected. REM latency and REM density were altered in depression compared to healthy subjects. Sex differences existed for the amounts of stage 1 and SWS. The cholinergic REM induction test resulted in a significantly more pronounced induction of REM sleep in depressed patients compared with healthy controls, provoking sleep onset REM periods as well in those depressed patients showing baseline REM latencies in the normal range. Depressed patients with or without melancholia (according to DSM-III) did not differ from each other, either concerning baseline sleep or with respect to the results of the cholinergic REM induction test. The results stress the importance of age when comparing sleep patterns of healthy controls with those of depressed patients. Furthermore they underline the usefulness of the cholinergic REM induction test for differentiating depressed patients from healthy controls and support the reciprocal interaction model of nonREM-REM regulation and the cholinergic-aminergic imbalance hypothesis of affective disorders.

  20. Predictive Model Assessment for Count Data

    Science.gov (United States)

    2007-09-05

    critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts...the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. We consider a recent suggestion by Baker and...Figure 5. Boxplots for various scores for patent data count regressions. 11 Table 1 Four predictive models for larynx cancer counts in Germany, 1998–2002

  1. EEG sleep in depression and in remission and the REM sleep response to the cholinergic agonist RS 86.

    Science.gov (United States)

    Riemann, D; Berger, M

    1989-06-01

    A comparison of the sleep EEG patterns of patients with a major depressive disorder intraindividually between remitted and depressed state revealed an improvement of parameters of sleep continuity and a tendency for normalization of rapid eye movement (REM) latency and REM density in the former. Additional application of the cholinergic agonist RS 86 prior to sleep did not reveal a heightened sensitivity of the REM sleep system in the remitted sample. Whereas a group of presently ill depressives displayed a drastic reduction of REM latency, results of the remitted patients were comparable to healthy controls. Furthermore, RS 86 significantly reduced slow-wave sleep in all groups investigated and had a differential impact on the density of the first REM period and early morning awakening in actively ill patients as compared to remitted patients. The results do not favor the hypothesis of a trait specificity of REM sleep abnormalities for depressive disorders. Furthermore they support the model of a cholinergic supersensitivity, as measured by REM induction after RS 86, as a state but not a trait marker of affective illness. Generalization of the present study may, however, be limited by the fact that the remitted patients were free of symptomatology and psychoactive medication for a long period (mean 3 years), therefore constituting an untypical group of formerly depressed patients with a seemingly low risk of relapse.

  2. Endothelial function and sleep: associations of flow-mediated dilation with perceived sleep quality and rapid eye movement (REM) sleep.

    Science.gov (United States)

    Cooper, Denise C; Ziegler, Michael G; Milic, Milos S; Ancoli-Israel, Sonia; Mills, Paul J; Loredo, José S; Von Känel, Roland; Dimsdale, Joel E

    2014-02-01

    Endothelial function typically precedes clinical manifestations of cardiovascular disease and provides a potential mechanism for the associations observed between cardiovascular disease and sleep quality. This study examined how subjective and objective indicators of sleep quality relate to endothelial function, as measured by brachial artery flow-mediated dilation (FMD). In a clinical research centre, 100 non-shift working adults (mean age: 36 years) completed FMD testing and the Pittsburgh Sleep Quality Index, along with a polysomnography assessment to obtain the following measures: slow wave sleep, percentage rapid eye movement (REM) sleep, REM sleep latency, total arousal index, total sleep time, wake after sleep onset, sleep efficiency and apnea-hypopnea index. Bivariate correlations and follow-up multiple regressions examined how FMD related to subjective (i.e., Pittsburgh Sleep Quality Index scores) and objective (i.e., polysomnography-derived) indicators of sleep quality. After FMD showed bivariate correlations with Pittsburgh Sleep Quality Index scores, percentage REM sleep and REM latency, further examination with separate regression models indicated that these associations remained significant after adjustments for sex, age, race, hypertension, body mass index, apnea-hypopnea index, smoking and income (Ps Quality Index increased (indicating decreased subjective sleep quality) and percentage REM sleep decreased, while REM sleep latency increased (Ps quality and adverse changes in REM sleep were associated with diminished vasodilation, which could link sleep disturbances to cardiovascular disease.

  3. Control of REM sleep by ventral medulla GABAergic neurons.

    Science.gov (United States)

    Weber, Franz; Chung, Shinjae; Beier, Kevin T; Xu, Min; Luo, Liqun; Dan, Yang

    2015-10-15

    Rapid eye movement (REM) sleep is a distinct brain state characterized by activated electroencephalogram and complete skeletal muscle paralysis, and is associated with vivid dreams. Transection studies by Jouvet first demonstrated that the brainstem is both necessary and sufficient for REM sleep generation, and the neural circuits in the pons have since been studied extensively. The medulla also contains neurons that are active during REM sleep, but whether they play a causal role in REM sleep generation remains unclear. Here we show that a GABAergic (γ-aminobutyric-acid-releasing) pathway originating from the ventral medulla powerfully promotes REM sleep in mice. Optogenetic activation of ventral medulla GABAergic neurons rapidly and reliably initiated REM sleep episodes and prolonged their durations, whereas inactivating these neurons had the opposite effects. Optrode recordings from channelrhodopsin-2-tagged ventral medulla GABAergic neurons showed that they were most active during REM sleep (REMmax), and during wakefulness they were preferentially active during eating and grooming. Furthermore, dual retrograde tracing showed that the rostral projections to the pons and midbrain and caudal projections to the spinal cord originate from separate ventral medulla neuron populations. Activating the rostral GABAergic projections was sufficient for both the induction and maintenance of REM sleep, which are probably mediated in part by inhibition of REM-suppressing GABAergic neurons in the ventrolateral periaqueductal grey. These results identify a key component of the pontomedullary network controlling REM sleep. The capability to induce REM sleep on command may offer a powerful tool for investigating its functions.

  4. Dicholine succinate, the neuronal insulin sensitizer, normalizes behavior, REM sleep, hippocampal pGSK3 beta and mRNAs of NMDA receptor subunits in mouse models of depression

    Directory of Open Access Journals (Sweden)

    Brandon H. Cline

    2015-02-01

    Full Text Available Central insulin receptor-mediated signalling is attracting the growing attention of researchers because of rapidly accumulating evidence implicating it in the mechanisms of plasticity, stress response and neuropsychiatric disorders including depression. Dicholine succinate (DS, a mitochondrial complex II substrate, was shown to enhance insulin-receptor mediated signaling in neurons and is regarded as a sensitizer of the neuronal insulin receptor. Compounds enhancing neuronal insulin receptor-mediated transmission exert an antidepressant-like effect in several pre-clinical paradigms of depression; similarly, such properties for DS were found with a stress-induced anhedonia model. Here, we additionally studied the effects of DS on several variables which were ameliorated by other insulin receptor sensitizers in mice. Pre-treatment with DS of chronically stressed C57BL6 mice rescued normal contextual fear conditioning, hippocampal gene expression of NMDA receptor subunit NR2A, the NR2A/NR2B ratio and increased REM sleep rebound after acute predation. In 18-month-old C57BL6 mice, a model of elderly depression, DS restored normal sucrose preference and activated the expression of neural plasticity factors in the hippocampus as shown by Illumina microarray. Finally, young naïve DS-treated C57BL6 mice had reduced depressive- and anxiety-like behaviours and, similarly to imipramine-treated mice, preserved hippocampal levels of the phosphorylated (inactive form of GSK3 beta that was lowered by forced swimming in pharmacologically naïve animals. Thus, DS can ameliorate behavioural and molecular outcomes under a variety of stress- and depression-related conditions. This further highlights neuronal insulin signalling as a new factor of pathogenesis and a potential pharmacotherapy of affective pathologies.

  5. Nonlinear chaotic model for predicting storm surges

    Directory of Open Access Journals (Sweden)

    M. Siek

    2010-09-01

    Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

  6. Nonlinear chaotic model for predicting storm surges

    NARCIS (Netherlands)

    Siek, M.; Solomatine, D.P.

    This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables.

  7. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain,...

  8. What links schizophrenia and dreaming? Common phenomenological and neurobiological features of schizophrenia and REM sleep

    Directory of Open Access Journals (Sweden)

    Skrzypińska, Dagna

    2013-06-01

    Full Text Available Aim. The aim of this theoretical study is to present common phenomenological and neurobiological features of schizophrenia and REM sleep.Results. A review of professional literature was conducted in order to synthesize current findings about associations between schizophrenia and REM sleep. Many researches reveal that both states share some common phenomenological and neurobiological features. Autism, lack of insight and a loss of autonomy in relation to mental content are just some of the characteristics that occur on a phenomenological level in both dreams during REM sleep (lucid dreaming excluded and schizophrenia. Data from experimental conditions revealed that the waking mentation of patients suffering from schizophrenia has a similar degree of formal cognitive bizarreness as dream narratives obtained from both non-clinical and clinical populations. On the other hand, some common neurobiological features of the REM sleep stage and schizophrenia are: lack of central inhibitory processes, intracerebral disconnections, dysfunction of the dorsolateral prefrontal cortex or nucleus accumbens and disturbed responsiveness. Moreover, there is similaractivation of dopamine, acetylcholine, noradrenaline, serotonin and glutamate in both states.Conclusions. Common phenomenological and neurobiological characteristics of these two states suggest that data about REM sleep could help introduce a useful experimental model of schizophrenia.

  9. How to Establish Clinical Prediction Models

    Directory of Open Access Journals (Sweden)

    Yong-ho Lee

    2016-03-01

    Full Text Available A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.

  10. Particle Reduction Strategies - PAREST. Influence of the boundary conditions from the global chemistry transport model TM5 on the regional aerosol chemistry transport model REM CALGRID; Strategien zur Verminderung der Feinstaubbelastung - PAREST. Einfluss der Randbedingungen aus dem globalen Chemie-Transport-Modell TM5 auf das regionale Aerosol-Chemie-Transport-Modell REM-CALGRID. Teilbericht

    Energy Technology Data Exchange (ETDEWEB)

    Kerschbaumer, Andreas; Hannig, Katrin [Freie Univ. Berlin (Germany). Inst. fuer Meteorologie, Troposphaerische Umweltforschung

    2013-06-15

    In this report the coupling of a global model is presented with a continental model. It examines how far the forecasts of regional air quality in Europe are affected by the choice of boundary conditions. The focus of this report is to analyze the influence of different boundary conditions on the calculated soil concentrations of ozone and PM10. A model evaluation, however, was not the aim of this study. [German] In diesem Bericht wird die Koppelung eines Globalmodells mit einem kontinentalen Modell vorgestellt. Es wird untersucht, wie weit die Prognosen der regionalen Luftqualitaet in Europa von der Wahl der Randbedingungen beeinflusst werden. Der Schwerpunkt des vorliegenden Berichts liegt in der Analyse des Einflusses der verschiedenen Randbedingungen auf die berechneten Bodenkonzentrationen von Ozon und PM10. Eine Modellevaluierung hingegen war nicht Ziel dieser Studie.

  11. Language learning efficiency, dreams and REM sleep.

    Science.gov (United States)

    De Koninck, J; Christ, G; Hébert, G; Rinfret, N

    1990-06-01

    As a follow-up from a previous study, four subjects taking a 6-week French language immersion program maintained a dream diary starting 2 weeks before until 2 weeks after the course. They also slept in the laboratory during four series of nights: one before the course, two during the course and one after the course. Confirming previous observations, it was observed that those subjects who made significant progress in French learning, experienced French incorporations into dreams earlier and had more verbal communication in their dreams during the language training than those who made little progress. Combining these results with those of the earlier study revealed significant positive correlations between language learning efficiency and both increases in REM sleep percentages, and verbal communication in dreams, as well as a negative correlation with latency to the first French incorporation in dreams. These results support the notion that REM sleep and dreaming are related to waking cognitive processes.

  12. Evidence that adrenergic ventrolateral medullary cells are activated whereas precerebellar lateral reticular nucleus neurons are suppressed during REM sleep.

    Directory of Open Access Journals (Sweden)

    Georg M Stettner

    Full Text Available Rapid eye movement sleep (REMS is generated in the brainstem by a distributed network of neurochemically distinct neurons. In the pons, the main subtypes are cholinergic and glutamatergic REMS-on cells and aminergic REMS-off cells. Pontine REMS-on cells send axons to the ventrolateral medulla (VLM, but little is known about REMS-related activity of VLM cells. In urethane-anesthetized rats, dorsomedial pontine injections of carbachol trigger REMS-like episodes that include cortical and hippocampal activation and suppression of motoneuronal activity; the episodes last 4-8 min and can be elicited repeatedly. We used this model to determine whether VLM catecholaminergic cells are silenced during REMS, as is typical of most aminergic neurons studied to date, and to investigate other REMS-related cells in this region. In 18 anesthetized, paralyzed and artificially ventilated rats, we obtained extracellular recordings from VLM cells when REMS-like episodes were elicited by pontine carbachol injections (10 mM, 10 nl. One major group were the cells that were activated during the episodes (n = 10. Their baseline firing rate of 3.7±2.1 (SD Hz increased to 9.7±2.1 Hz. Most were found in the adrenergic C1 region and at sites located less than 50 µm from dopamine β-hydroxylase-positive (DBH(+ neurons. Another major group were the silenced or suppressed cells (n = 35. Most were localized in the lateral reticular nucleus (LRN and distantly from any DBH(+ cells. Their baseline firing rates were 6.8±4.4 Hz and 15.8±7.1 Hz, respectively, with the activity of the latter reduced to 7.4±3.8 Hz. We conclude that, in contrast to the pontine noradrenergic cells that are silenced during REMS, medullary adrenergic C1 neurons, many of which drive the sympathetic output, are activated. Our data also show that afferent input transmitted to the cerebellum through the LRN is attenuated during REMS. This may distort the spatial representation of body position

  13. The influence of gravity on REM sleep

    OpenAIRE

    Gonfalone, Alain; Jha,Sushil

    2015-01-01

    Alain A Gonfalone,1 Sushil K Jha2 1European Space Agency, Paris, France; 2School of Life Sciences, Jawaharlal Nehru University, New Delhi, India Abstract: It is suggested that environmental variables, and gravity in particular, are the main determinants of sleep duration. Assuming that the rapid eye movement (REM) sleep state depends on the influence of gravity allows a better understanding of sleep across the animal world. This paper is based on numerous results already published on sleep b...

  14. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    is a realization of a continuous-discrete multivariate stochastic transfer function model. The proposed prediction error-methods are demonstrated for a SISO system parameterized by the transfer functions with time delays of a continuous-discrete-time linear stochastic system. The simulations for this case suggest......Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which...... computational resources. The identification method is suitable for predictive control....

  15. Isobaric Molecular Dynamics Version of the Generalized Replica Exchange Method (gREM): Liquid-Vapor Equilibrium.

    Science.gov (United States)

    Małolepsza, Edyta; Secor, Maxim; Keyes, Tom

    2015-10-22

    A prescription for sampling isobaric generalized ensembles with molecular dynamics is presented and applied to the generalized replica exchange method (gREM), which was designed to simulate first-order phase transitions. The properties of the isobaric gREM ensemble are discussed, and a study is presented for the liquid-vapor equilibrium of the guest molecules given for gas hydrate formation with the mW water model. Phase diagrams, critical parameters, and a law of corresponding states are obtained.

  16. Human REM sleep: influence on feeding behaviour, with clinical implications.

    Science.gov (United States)

    Horne, James A

    2015-08-01

    Rapid eye movement (REM) sleep shares many underlying mechanisms with wakefulness, to a much greater extent than does non-REM, especially those relating to feeding behaviours, appetite, curiosity, exploratory (locomotor) activities, as well as aspects of emotions, particularly 'fear extinction'. REM is most evident in infancy, thereafter declining in what seems to be a dispensable manner that largely reciprocates increasing wakefulness. However, human adults retain more REM than do other mammals, where for us it is most abundant during our usual final REM period (fREMP) of the night, nearing wakefulness. The case is made that our REM is unusual, and that (i) fREMP retains this 'dispensability', acting as a proxy for wakefulness, able to be forfeited (without REM rebound) and substituted by physical activity (locomotion) when pressures of wakefulness increase; (ii) REM's atonia (inhibited motor output) may be a proxy for this locomotion; (iii) our nocturnal sleep typically develops into a physiological fast, especially during fREMP, which is also an appetite suppressant; (iv) REM may have 'anti-obesity' properties, and that the loss of fREMP may well enhance appetite and contribute to weight gain ('overeating') in habitually short sleepers; (v) as we also select foods for their hedonic (emotional) values, REM may be integral to developing food preferences and dislikes; and (vii) REM seems to have wider influences in regulating energy balance in terms of exercise 'substitution' and energy (body heat) retention. Avenues for further research are proposed, linking REM with feeding behaviours, including eating disorders, and effects of REM-suppressant medications.

  17. REM sleep enhancement of probabilistic classification learning is sensitive to subsequent interference.

    Science.gov (United States)

    Barsky, Murray M; Tucker, Matthew A; Stickgold, Robert

    2015-07-01

    During wakefulness the brain creates meaningful relationships between disparate stimuli in ways that escape conscious awareness. Processes active during sleep can strengthen these relationships, leading to more adaptive use of those stimuli when encountered during subsequent wake. Performance on the Weather Prediction Task (WPT), a well-studied measure of implicit probabilistic learning, has been shown to improve significantly following a night of sleep, with stronger initial learning predicting more nocturnal REM sleep. We investigated this relationship further, studying the effect on WPT performance of a daytime nap containing REM sleep. We also added an interference condition after the nap/wake period as an additional probe of memory strength. Our results show that a nap significantly boosts WPT performance, and that this improvement is correlated with the amount of REM sleep obtained during the nap. When interference training is introduced following the nap, however, this REM-sleep benefit vanishes. In contrast, following an equal period of wake, performance is both unchanged from training and unaffected by interference training. Thus, while the true probabilistic relationships between WPT stimuli are strengthened by sleep, these changes are selectively susceptible to the destructive effects of retroactive interference, at least in the short term.

  18. Case studies in archaeological predictive modelling

    NARCIS (Netherlands)

    Verhagen, Jacobus Wilhelmus Hermanus Philippus

    2007-01-01

    In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing p

  19. Childhood asthma prediction models: a systematic review.

    Science.gov (United States)

    Smit, Henriette A; Pinart, Mariona; Antó, Josep M; Keil, Thomas; Bousquet, Jean; Carlsen, Kai H; Moons, Karel G M; Hooft, Lotty; Carlsen, Karin C Lødrup

    2015-12-01

    Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.

  20. Breathing during REM and non-REM sleep: correlated versus uncorrelated behaviour

    Science.gov (United States)

    Kantelhardt, Jan W.; Penzel, Thomas; Rostig, Sven; Becker, Heinrich F.; Havlin, Shlomo; Bunde, Armin

    2003-03-01

    Healthy sleep can be characterized by several stages: deep sleep, light sleep, and REM sleep. Here we show that these sleep stages lead to different autonomic regulation of breathing. Using the detrended fluctuation analysis up to the fourth order we find that breath-to-breath intervals and breath volumes separated by several breaths are long-range correlated during the REM stages and during wake states. In contrast, in the non-REM stages (deep sleep and light sleep), long-range correlations are absent. This behaviour is very similar to the correlation behaviour of the heart rate during the night and may be related to the phase synchronization between heartbeat and breathing found recently. We speculate that the differences are caused by different cortically influenced control of the autonomic nervous system.

  1. The Neuronal Transition Probability (NTP) Model for the Dynamic Progression of Non-REM Sleep EEG: The Role of the Suprachiasmatic Nucleus

    CERN Document Server

    Merica, H

    2011-01-01

    Little attention has gone into linking to its neuronal substrates the dynamic structure of non-rapid-eye-movement (NREM) sleep, defined as the pattern of time-course power in all frequency bands across an entire episode. Using the spectral power time-courses in the sleep electroencephalogram (EEG), we showed in the typical first episode, several moves towards-and-away from deep sleep, each having an identical pattern linking the major frequency bands beta, sigma and delta. The neuronal transition probability model (NTP) - in fitting the data well - successfully explained the pattern as resulting from stochastic transitions of the firing-rates of the thalamically-projecting brainstem-activating neurons, alternating between two steady dynamic-states (towards-and-away from deep sleep) each initiated by a so-far unidentified flip-flop. The aims here are to identify this flip-flop and to demonstrate that the model fits well all NREM episodes, not just the first. Using published data on suprachiasmatic nucleus (SCN...

  2. Association between the activation of MCH and orexin immunorective neurons and REM sleep architecture during REM rebound after a three day long REM deprivation.

    Science.gov (United States)

    Kitka, Tamas; Adori, Csaba; Katai, Zita; Vas, Szilvia; Molnar, Eszter; Papp, Rege S; Toth, Zsuzsanna E; Bagdy, Gyorgy

    2011-10-01

    Rapid eye movement (REM) sleep rebound following REM deprivation using the platform-on-water method is characterized by increased time spent in REM sleep and activation of melanin-concentrating hormone (MCH) expressing neurons. Orexinergic neurons discharge reciprocally to MCH-ergic neurons across the sleep-wake cycle. However, the relation between REM architecture and the aforementioned neuropeptides remained unclear. MCH-ergic neurons can be divided into two subpopulations regarding their cocaine- and amphetamine-regulated transcript (CART) immunoreactivity, and among them the activation of CART-immunoreactive subpopulation is higher during the REM rebound. However, the possible role of stress in this association has not been elucidated. Our aims were to analyze the relationship between the architecture of REM rebound and the activation of hypothalamic MCH-ergic and orexinergic neurons. We also intended to separate the effect of stress and REM deprivation on the subsequent activation of subpopulations of MCH-ergic neurons. In order to detect neuronal activity, we performed MCH/cFos and orexin/cFos double immunohistochemistry on home cage, sleep deprived and sleep-rebound rats using the platform-on-water method with small and large (stress control) platforms. Furthermore, REM architecture was analyzed and a triple MCH/CART/cFos immunohistochemistry was also performed on the rebound groups in the same animals. We found that the activity of MCH- and orexin-immunoreactive neurons during REM rebound was positively and negatively correlated with the number of REM bouts, respectively. A negative reciprocal correlation was also found between the activation of MCH- and orexin-immunoreactive neurons during REM rebound. Furthermore, difference between the activation of CART-immunoreactive (CART-IR) and non-CART-immunoreactive MCH-ergic neuron subpopulations was found only after selective REM deprivation, it was absent in the large platform (stress control) rebound group

  3. z-ph-REM: A photometric redshift code for the REM telescope

    CERN Document Server

    Fernández-Soto, A

    2003-01-01

    The REM telescope is being deployed these very days at the La Silla Observatory in Chile, and will be fully operational by the beginning of 2004. It is a very fast-slewing robotized telescope, endowed with optical and near-infrared capabilities, designed with the primary objective of performing rapid follow-up of GRB events. One of the key issues will be the prompt recognition of potentially interesting bursts (those happening at high redshift or peculiarly reddened). Here I present a sketch of z-ph-REM, the photometric redshift code designed for this mission.

  4. Polysomnographic Features of Sleep Disturbances and REM Sleep Behavior Disorder in the Unilateral 6-OHDA Lesioned Hemiparkinsonian Rat

    Directory of Open Access Journals (Sweden)

    Quynh Vo

    2014-01-01

    Full Text Available Sleep pattern disruption, specifically REM sleep behavior disorder (RBD, is a major nonmotor cause of disability in PD. Understanding the pathophysiology of these sleep pattern disturbances is critical to find effective treatments. 24-hour polysomnography (PSG, the gold standard for sleep studies, has never been used to test sleep dysfunction in the standard 6-OHDA lesioned hemiparkinsonian (HP rat PD model. In this study, we recorded 24-hour PSG from normal and HP rats. Recordings were scored into wake, rapid eye movement (REM, and non-REM (NREM. We then examined EEG to identify REM periods and EMG to check muscle activity during REM. Normal rats showed higher wakefulness (70–80% during the dark phase and lower wakefulness (20% during the light phase. HP rats showed 30–50% sleep in both phases, less modulation and synchronization to the light schedule (P<0.0001, and more long run lengths of wakefulness (P<0.05. HP rats also had more REM epochs with muscle activity than control rats (P<0.05. Our findings that the sleep architecture in the HP rat resembles that of PD patients demonstrate the value of this model in studying the pathophysiological basis of PD sleep disturbances and preclinical therapeutics for PD related sleep disorders including RBD.

  5. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  6. Comparisons Between Model Predictions and Spectral Measurements of Charged and Neutral Particles on the Martian Surface

    Science.gov (United States)

    Kim, Myung-Hee Y.; Cucinotta, Francis A.; Zeitlin, Cary; Hassler, Donald M.; Ehresmann, Bent; Rafkin, Scot C. R.; Wimmer-Schweingruber, Robert F.; Boettcher, Stephan; Boehm, Eckart; Guo, Jingnan; hide

    2014-01-01

    Detailed measurements of the energetic particle radiation environment on the surface of Mars have been made by the Radiation Assessment Detector (RAD) on the Curiosity rover since August 2012. RAD is a particle detector that measures the energy spectrum of charged particles (10 to approx. 200 MeV/u) and high energy neutrons (approx 8 to 200 MeV). The data obtained on the surface of Mars for 300 sols are compared to the simulation results using the Badhwar-O'Neill galactic cosmic ray (GCR) environment model and the high-charge and energy transport (HZETRN) code. For the nuclear interactions of primary GCR through Mars atmosphere and Curiosity rover, the quantum multiple scattering theory of nuclear fragmentation (QMSFRG) is used. For describing the daily column depth of atmosphere, daily atmospheric pressure measurements at Gale Crater by the MSL Rover Environmental Monitoring Station (REMS) are implemented into transport calculations. Particle flux at RAD after traversing varying depths of atmosphere depends on the slant angles, and the model accounts for shielding of the RAD "E" dosimetry detector by the rest of the instrument. Detailed comparisons between model predictions and spectral data of various particle types provide the validation of radiation transport models, and suggest that future radiation environments on Mars can be predicted accurately. These contributions lend support to the understanding of radiation health risks to astronauts for the planning of various mission scenarios

  7. [Development of a computer program to simulate the predictions of the replaced elements model of Pavlovian conditioning].

    Science.gov (United States)

    Vogel, Edgar H; Díaz, Claudia A; Ramírez, Jorge A; Jarur, Mary C; Pérez-Acosta, Andrés M; Wagner, Allan R

    2007-08-01

    Despite of the apparent simplicity of Pavlovian conditioning, research on its mechanisms has caused considerable debate, such as the dispute about whether the associated stimuli are coded in an "elementistic"(a compound stimuli is equivalent to the sum of its components) or a "configural" (a compound stimuli is a unique exemplar) fashion. This controversy is evident in the abundant research on the contrasting predictions of elementistic and the configural models. Recently, some mixed solutions have been proposed, which, although they have the advantages of both approaches, are difficult to evaluate due to their complexity. This paper presents a computer program to conduct simulations of a mixed model ( replaced elements model or REM). Instructions and examples are provided to use the simulator for research and educational purposes.

  8. Selective REM Sleep Deprivation Improves Expectation-Related Placebo Analgesia.

    Science.gov (United States)

    Chouchou, Florian; Chauny, Jean-Marc; Rainville, Pierre; Lavigne, Gilles J

    2015-01-01

    The placebo effect is a neurobiological and psychophysiological process known to influence perceived pain relief. Optimization of placebo analgesia may contribute to the clinical efficacy and effectiveness of medication for acute and chronic pain management. We know that the placebo effect operates through two main mechanisms, expectations and learning, which is also influenced by sleep. Moreover, a recent study suggested that rapid eye movement (REM) sleep is associated with modulation of expectation-mediated placebo analgesia. We examined placebo analgesia following pharmacological REM sleep deprivation and we tested the hypothesis that relief expectations and placebo analgesia would be improved by experimental REM sleep deprivation in healthy volunteers. Following an adaptive night in a sleep laboratory, 26 healthy volunteers underwent classical experimental placebo analgesic conditioning in the evening combined with pharmacological REM sleep deprivation (clonidine: 13 volunteers or inert control pill: 13 volunteers). Medication was administered in a double-blind manner at bedtime, and placebo analgesia was tested in the morning. Results revealed that 1) placebo analgesia improved with REM sleep deprivation; 2) pain relief expectations did not differ between REM sleep deprivation and control groups; and 3) REM sleep moderated the relationship between pain relief expectations and placebo analgesia. These results support the putative role of REM sleep in modulating placebo analgesia. The mechanisms involved in these improvements in placebo analgesia and pain relief following selective REM sleep deprivation should be further investigated.

  9. Selective REM Sleep Deprivation Improves Expectation-Related Placebo Analgesia.

    Directory of Open Access Journals (Sweden)

    Florian Chouchou

    Full Text Available The placebo effect is a neurobiological and psychophysiological process known to influence perceived pain relief. Optimization of placebo analgesia may contribute to the clinical efficacy and effectiveness of medication for acute and chronic pain management. We know that the placebo effect operates through two main mechanisms, expectations and learning, which is also influenced by sleep. Moreover, a recent study suggested that rapid eye movement (REM sleep is associated with modulation of expectation-mediated placebo analgesia. We examined placebo analgesia following pharmacological REM sleep deprivation and we tested the hypothesis that relief expectations and placebo analgesia would be improved by experimental REM sleep deprivation in healthy volunteers. Following an adaptive night in a sleep laboratory, 26 healthy volunteers underwent classical experimental placebo analgesic conditioning in the evening combined with pharmacological REM sleep deprivation (clonidine: 13 volunteers or inert control pill: 13 volunteers. Medication was administered in a double-blind manner at bedtime, and placebo analgesia was tested in the morning. Results revealed that 1 placebo analgesia improved with REM sleep deprivation; 2 pain relief expectations did not differ between REM sleep deprivation and control groups; and 3 REM sleep moderated the relationship between pain relief expectations and placebo analgesia. These results support the putative role of REM sleep in modulating placebo analgesia. The mechanisms involved in these improvements in placebo analgesia and pain relief following selective REM sleep deprivation should be further investigated.

  10. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...

  11. Massive Predictive Modeling using Oracle R Enterprise

    CERN Document Server

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  12. Autonomic symptoms in idiopathic REM behavior disorder

    DEFF Research Database (Denmark)

    Ferini-Strambi, Luigi; Oertel, Wolfgang; Dauvilliers, Yves

    2014-01-01

    , and sexual dysfunction. Our results show that compared to control subjects with a similar overall age and sex distribution, patients with iRBD experience significantly more problems with gastrointestinal, urinary, and cardiovascular functioning. The most prominent differences in severity of autonomic......Patients with idiopathic REM sleep behavior disorder (iRBD) are at very high risk of developing neurodegenerative synucleinopathies, which are disorders with prominent autonomic dysfunction. Several studies have documented autonomic dysfunction in iRBD, but large-scale assessment of autonomic...

  13. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  20. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  1. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  2. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  3. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Posterior Predictive Model Checking in Bayesian Networks

    Science.gov (United States)

    Crawford, Aaron

    2014-01-01

    This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…

  6. A Course in... Model Predictive Control.

    Science.gov (United States)

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  7. Equivalency and unbiasedness of grey prediction models

    Institute of Scientific and Technical Information of China (English)

    Bo Zeng; Chuan Li; Guo Chen; Xianjun Long

    2015-01-01

    In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction mo-dels, the equivalence and unbiasedness of grey prediction mo-dels are analyzed and verified. The results show that al the grey prediction models that are strictly derived from x(0)(k) +az(1)(k) = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homoge-neous exponential sequence can be accomplished. However, the models derived from dx(1)/dt+ax(1) =b are only close to those derived from x(0)(k)+az(1)(k)=b provided that|a|has to satisfy|a| < 0.1; neither could the unbiased simulation for the homoge-neous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.

  8. Predictability of extreme values in geophysical models

    Directory of Open Access Journals (Sweden)

    A. E. Sterk

    2012-09-01

    Full Text Available Extreme value theory in deterministic systems is concerned with unlikely large (or small values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical models. We study whether finite-time Lyapunov exponents are larger or smaller for initial conditions leading to extremes. General statements on whether extreme values are better or less predictable are not possible: the predictability of extreme values depends on the observable, the attractor of the system, and the prediction lead time.

  9. Hybrid modeling and prediction of dynamical systems

    Science.gov (United States)

    Lloyd, Alun L.; Flores, Kevin B.

    2017-01-01

    Scientific analysis often relies on the ability to make accurate predictions of a system’s dynamics. Mechanistic models, parameterized by a number of unknown parameters, are often used for this purpose. Accurate estimation of the model state and parameters prior to prediction is necessary, but may be complicated by issues such as noisy data and uncertainty in parameters and initial conditions. At the other end of the spectrum exist nonparametric methods, which rely solely on data to build their predictions. While these nonparametric methods do not require a model of the system, their performance is strongly influenced by the amount and noisiness of the data. In this article, we consider a hybrid approach to modeling and prediction which merges recent advancements in nonparametric analysis with standard parametric methods. The general idea is to replace a subset of a mechanistic model’s equations with their corresponding nonparametric representations, resulting in a hybrid modeling and prediction scheme. Overall, we find that this hybrid approach allows for more robust parameter estimation and improved short-term prediction in situations where there is a large uncertainty in model parameters. We demonstrate these advantages in the classical Lorenz-63 chaotic system and in networks of Hindmarsh-Rose neurons before application to experimentally collected structured population data. PMID:28692642

  10. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.

  11. Property predictions using microstructural modeling

    Energy Technology Data Exchange (ETDEWEB)

    Wang, K.G. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)]. E-mail: wangk2@rpi.edu; Guo, Z. [Sente Software Ltd., Surrey Technology Centre, 40 Occam Road, Guildford GU2 7YG (United Kingdom); Sha, W. [Metals Research Group, School of Civil Engineering, Architecture and Planning, The Queen' s University of Belfast, Belfast BT7 1NN (United Kingdom); Glicksman, M.E. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States); Rajan, K. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)

    2005-07-15

    Precipitation hardening in an Fe-12Ni-6Mn maraging steel during overaging is quantified. First, applying our recent kinetic model of coarsening [Phys. Rev. E, 69 (2004) 061507], and incorporating the Ashby-Orowan relationship, we link quantifiable aspects of the microstructures of these steels to their mechanical properties, including especially the hardness. Specifically, hardness measurements allow calculation of the precipitate size as a function of time and temperature through the Ashby-Orowan relationship. Second, calculated precipitate sizes and thermodynamic data determined with Thermo-Calc[copyright] are used with our recent kinetic coarsening model to extract diffusion coefficients during overaging from hardness measurements. Finally, employing more accurate diffusion parameters, we determined the hardness of these alloys independently from theory, and found agreement with experimental hardness data. Diffusion coefficients determined during overaging of these steels are notably higher than those found during the aging - an observation suggesting that precipitate growth during aging and precipitate coarsening during overaging are not controlled by the same diffusion mechanism.

  12. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  13. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp

    2016-01-01

    Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... that describes the variation between subjects. The ODE setup implies that the variation for a single subject is described by a single parameter (or vector), namely the variance (covariance) of the residuals. Furthermore the prediction of the states is given as the solution to the ODEs and hence assumed...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...

  14. Precision Plate Plan View Pattern Predictive Model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yang; YANG Quan; HE An-rui; WANG Xiao-chen; ZHANG Yun

    2011-01-01

    According to the rolling features of plate mill, a 3D elastic-plastic FEM (finite element model) based on full restart method of ANSYS/LS-DYNA was established to study the inhomogeneous plastic deformation of multipass plate rolling. By analyzing the simulation results, the difference of head and tail ends predictive models was found and modified. According to the numerical simulation results of 120 different kinds of conditions, precision plate plan view pattern predictive model was established. Based on these models, the sizing MAS (mizushima automatic plan view pattern control system) method was designed and used on a 2 800 mm plate mill. Comparing the rolled plates with and without PVPP (plan view pattern predictive) model, the reduced width deviation indicates that the olate !olan view Dattern predictive model is preeise.

  15. The Swift Mission and the Robotic Telescope REM

    Science.gov (United States)

    Chincarini, Guido

    2003-12-01

    The Swift satellite and the REM telescope projects are devoted to the study of Gamma-Ray bursts. Both missions are mainly designed to investigate on the prompt GRB emission. In the following, we give a brief outline of GRB science and describe the main technical capabilities of Swift and REM.

  16. REM sleep at its core—Circuits, neurotransmitters and pathophysiology

    Directory of Open Access Journals (Sweden)

    John ePeever

    2015-05-01

    Full Text Available REM sleep is generated and maintained by the interaction of a variety of neurotransmitter systems in the brainstem, forebrain and hypothalamus. Within these circuits lies a core region that is active during REM sleep, known as the subcoeruleus nucleus (SubC or sublaterodorsal nucleus. It is hypothesized that glutamatergic SubC neurons regulate REM sleep and its defining features such as muscle paralysis and cortical activation. REM sleep paralysis is initiated when glutamatergic SubC activate neurons in the ventral medial medulla (VMM, which causes release of GABA and glycine onto skeletal motoneurons. REM sleep timing is controlled by activity of GABAergic neurons in the ventrolateral periaqueductal gray (vlPAG and dorsal paragigantocellular reticular nucleus (DPGi as well as melanin-concentrating hormone (MCH neurons in the hypothalamus and cholinergic cells in the laterodorsal (LDT and pedunculo-pontine tegmentum (PPT in the brainstem. Determining how these circuits interact with the SubC is important because breakdown in their communication is hypothesized to underlie cataplexy/narcolepsy and REM sleep behaviour disorder (RBD. This review synthesizes our current understanding of mechanisms generating healthy REM sleep and how dysfunction of these circuits contributes to common REM sleep disorders such as cataplexy/narcolepsy and RBD.

  17. REM Sleep at its Core – Circuits, Neurotransmitters, and Pathophysiology

    Science.gov (United States)

    Fraigne, Jimmy J.; Torontali, Zoltan A.; Snow, Matthew B.; Peever, John H.

    2015-01-01

    Rapid eye movement (REM) sleep is generated and maintained by the interaction of a variety of neurotransmitter systems in the brainstem, forebrain, and hypothalamus. Within these circuits lies a core region that is active during REM sleep, known as the subcoeruleus nucleus (SubC) or sublaterodorsal nucleus. It is hypothesized that glutamatergic SubC neurons regulate REM sleep and its defining features such as muscle paralysis and cortical activation. REM sleep paralysis is initiated when glutamatergic SubC cells activate neurons in the ventral medial medulla, which causes release of GABA and glycine onto skeletal motoneurons. REM sleep timing is controlled by activity of GABAergic neurons in the ventrolateral periaqueductal gray and dorsal paragigantocellular reticular nucleus as well as melanin-concentrating hormone neurons in the hypothalamus and cholinergic cells in the laterodorsal and pedunculo-pontine tegmentum in the brainstem. Determining how these circuits interact with the SubC is important because breakdown in their communication is hypothesized to underlie narcolepsy/cataplexy and REM sleep behavior disorder (RBD). This review synthesizes our current understanding of mechanisms generating healthy REM sleep and how dysfunction of these circuits contributes to common REM sleep disorders such as cataplexy/narcolepsy and RBD. PMID:26074874

  18. Automatic detection of REM sleep in subjects without atonia

    DEFF Research Database (Denmark)

    Kempfner, Jacob; Jennum, Poul; Nikolic, Miki

    2012-01-01

    Idiopathic Rapid-Rye-Movement (REM) sleep Behavior Disorder (iRBD) is a strong early marker of Parkinson's Disease and is characterized by REM sleep without atonia (RSWA) and increased phasic muscle activity. Current proposed methods for detecting RSWA assume the presence of a manually scored hyp...

  19. NBC Hazard Prediction Model Capability Analysis

    Science.gov (United States)

    1999-09-01

    Puff( SCIPUFF ) Model Verification and Evaluation Study, Air Resources Laboratory, NOAA, May 1998. Based on the NOAA review, the VLSTRACK developers...TO SUBSTANTIAL DIFFERENCES IN PREDICTIONS HPAC uses a transport and dispersion (T&D) model called SCIPUFF and an associated mean wind field model... SCIPUFF is a model for atmospheric dispersion that uses the Gaussian puff method - an arbitrary time-dependent concentration field is represented

  20. Medical image of the week: alpha intrusion into REM sleep

    Directory of Open Access Journals (Sweden)

    Shetty S

    2015-12-01

    Full Text Available A 45-year-old woman with a past medical history of hypertension and chronic headaches was referred to the sleep laboratory for high clinical suspicion for sleep apnea based on a history of snoring, witnessed apnea and excessive daytime sleepiness. An overnight sleep study was performed. Images during N3 Sleep and REM sleep are shown (Figures 1 and 2. Alpha intrusion in delta sleep is seen in patients with fibromyalgia, depression, chronic fatigue syndrome, anxiety disorder, and primary sleep disorders like psychophysiological insomnia, obstructive sleep apnea, circadian disorders and narcolepsy (1. Bursts of alpha waves during REM sleep may be more common during phasic REM than tonic REM. The REM alpha bursts (alpha activity lasting at least 3 seconds without an increase in EMG amplitude may represent microarousals (2. Hypersynchronous theta activity should be differentiated from the spike and waveform activity seen in seizures.

  1. REM: A Collaborative Framework for Building Indigenous Cultural Competence.

    Science.gov (United States)

    Power, Tamara; Virdun, Claudia; Sherwood, Juanita; Parker, Nicola; Van Balen, Jane; Gray, Joanne; Jackson, Debra

    2016-09-01

    The well-documented health disparities between the Australian Indigenous and non-Indigenous population mandates a comprehensive response from health professionals. This article outlines the approach taken by one faculty of health in a large urban Australian university to enhance cultural competence in students from a variety of fields. Here we outline a collaborative and deeply respectful process of Indigenous and non-Indigenous university staff collectively developing a model that has framed the embedding of a common faculty Indigenous graduate attribute across the curriculum. Through collaborative committee processes, the development of the principles of "Respect; Engagement and sharing; Moving forward" (REM) has provided both a framework and way of "being and doing" our work. By drawing together the recurring principles and qualities that characterize Indigenous cultural competence the result will be students and staff learning and bringing into their lives and practice, important Indigenous cultural understanding.

  2. REM Sleep Behaviour Disorder in Older Individuals: Epidemiology, Pathophysiology, and Management

    Science.gov (United States)

    Trotti, Lynn Marie

    2010-01-01

    Rapid eye movement (REM) sleep behavior disorder (RBD) is a sleep disorder that predominantly affects older adults, in which patients appear to be enacting their dreams while in REM sleep. The behaviors are typically violent, in association with violent dream content, so serious harm can be done to the patient or the bed-partner. The estimated prevalence in adults is 0.4–0.5%, but the frequency is much higher in certain neurodegenerative diseases, especially Parkinson's disease, Dementia with Lewy bodies, and multiple systems atrophy. RBD can occur in the absence of diagnosed neurologic diseases (the “idiopathic” form), although patients with this form of RBD may have subtle neurologic abnormalities and often ultimately develop a neurodegenerative disorder. Animal models and cases of RBD developing after brainstem lesions (pontine tegmentum, medulla) have led to the understanding that RBD is caused by a lack of normal REM muscle atonia and a lack of normal suppression of locomotor generators during REM. Clonazepam is used as first-line therapy for RBD and melatonin for second-line therapy, although evidence for both of these interventions comes from uncontrolled case series. Because the risk of injury to the patient or the bed-partner is high, interventions to improve the safety of the sleep environment are also often necessary. This review describes the epidemiology, pathophysiology, and treatment of RBD. PMID:20524706

  3. Corporate prediction models, ratios or regression analysis?

    NARCIS (Netherlands)

    Bijnen, E.J.; Wijn, M.F.C.M.

    1994-01-01

    The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in

  4. Modelling Chemical Reasoning to Predict Reactions

    CERN Document Server

    Segler, Marwin H S

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180,000 randomly selected binary reactions. We show that our data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-) discovering novel transformations (even including transition-metal catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph, and because each single reaction prediction is typically ac...

  5. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  6. Genetic models of homosexuality: generating testable predictions

    OpenAIRE

    Gavrilets, Sergey; Rice, William R.

    2006-01-01

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality inclu...

  7. Wind farm production prediction - The Zephyr model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)

    2002-06-01

    This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)

  8. The Antarctic permafrost as a testbed for REMS (Rover Environmental Monitoring Station-Mars Science Laboratory)

    Science.gov (United States)

    Esteban, B.; Ramos, M.; Sebastián, E.; Armiens, C.; Gómez-Elvira, J.; Cabos, W.; de Pablo, M. A.

    2009-04-01

    two soil temperature plates based on Pt100 sensors are in close contact with the surface in the angle of view of the GT-REMS thermopiles. In this work, we present a preliminary analysis of the data obtained in the Antarctic field campaign 2008-2009. For the analysis we developed a theoretical model which is briefly outlined here. We also present the results of simulations carried out with the model and their validation against the antarctic data. Complementary to the Antarctic experiments, we carried out an experience with all the instruments during the last summer in the CAB-Spain which are also used in the analysis. Finally, we compare the results of the last polar and CAB experiments in order to check the improvements introduced in GT-REMS.

  9. Predictive model for segmented poly(urea

    Directory of Open Access Journals (Sweden)

    Frankl P.

    2012-08-01

    Full Text Available Segmented poly(urea has been shown to be of significant benefit in protecting vehicles from blast and impact and there have been several experimental studies to determine the mechanisms by which this protective function might occur. One suggested route is by mechanical activation of the glass transition. In order to enable design of protective structures using this material a constitutive model and equation of state are needed for numerical simulation hydrocodes. Determination of such a predictive model may also help elucidate the beneficial mechanisms that occur in polyurea during high rate loading. The tool deployed to do this has been Group Interaction Modelling (GIM – a mean field technique that has been shown to predict the mechanical and physical properties of polymers from their structure alone. The structure of polyurea has been used to characterise the parameters in the GIM scheme without recourse to experimental data and the equation of state and constitutive model predicts response over a wide range of temperatures and strain rates. The shock Hugoniot has been predicted and validated against existing data. Mechanical response in tensile tests has also been predicted and validated.

  10. PREDICTIVE CAPACITY OF ARCH FAMILY MODELS

    Directory of Open Access Journals (Sweden)

    Raphael Silveira Amaro

    2016-03-01

    Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.

  11. Predictive QSAR modeling of phosphodiesterase 4 inhibitors.

    Science.gov (United States)

    Kovalishyn, Vasyl; Tanchuk, Vsevolod; Charochkina, Larisa; Semenuta, Ivan; Prokopenko, Volodymyr

    2012-02-01

    A series of diverse organic compounds, phosphodiesterase type 4 (PDE-4) inhibitors, have been modeled using a QSAR-based approach. 48 QSAR models were compared by following the same procedure with different combinations of descriptors and machine learning methods. QSAR methodologies used random forests and associative neural networks. The predictive ability of the models was tested through leave-one-out cross-validation, giving a Q² = 0.66-0.78 for regression models and total accuracies Ac=0.85-0.91 for classification models. Predictions for the external evaluation sets obtained accuracies in the range of 0.82-0.88 (for active/inactive classifications) and Q² = 0.62-0.76 for regressions. The method showed itself to be a potential tool for estimation of IC₅₀ of new drug-like candidates at early stages of drug development. Copyright © 2011 Elsevier Inc. All rights reserved.

  12. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-02-01

    Full Text Available Orientation: The article discussed the importance of rigour in credit risk assessment.Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan.Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities.Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems.Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk.Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product.Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  13. Calibrated predictions for multivariate competing risks models.

    Science.gov (United States)

    Gorfine, Malka; Hsu, Li; Zucker, David M; Parmigiani, Giovanni

    2014-04-01

    Prediction models for time-to-event data play a prominent role in assessing the individual risk of a disease, such as cancer. Accurate disease prediction models provide an efficient tool for identifying individuals at high risk, and provide the groundwork for estimating the population burden and cost of disease and for developing patient care guidelines. We focus on risk prediction of a disease in which family history is an important risk factor that reflects inherited genetic susceptibility, shared environment, and common behavior patterns. In this work family history is accommodated using frailty models, with the main novel feature being allowing for competing risks, such as other diseases or mortality. We show through a simulation study that naively treating competing risks as independent right censoring events results in non-calibrated predictions, with the expected number of events overestimated. Discrimination performance is not affected by ignoring competing risks. Our proposed prediction methodologies correctly account for competing events, are very well calibrated, and easy to implement.

  14. Form Follows Function: A Model for Clinical Supervision of Genetic Counseling Students.

    Science.gov (United States)

    Wherley, Colleen; Veach, Patricia McCarthy; Martyr, Meredith A; LeRoy, Bonnie S

    2015-10-01

    Supervision plays a vital role in genetic counselor training, yet models describing genetic counseling supervision processes and outcomes are lacking. This paper describes a proposed supervision model intended to provide a framework to promote comprehensive and consistent clinical supervision training for genetic counseling students. Based on the principle "form follows function," the model reflects and reinforces McCarthy Veach et al.'s empirically derived model of genetic counseling practice - the "Reciprocal Engagement Model" (REM). The REM consists of mutually interactive educational, relational, and psychosocial components. The Reciprocal Engagement Model of Supervision (REM-S) has similar components and corresponding tenets, goals, and outcomes. The 5 REM-S tenets are: Learning and applying genetic information are key; Relationship is integral to genetic counseling supervision; Student autonomy must be supported; Students are capable; and Student emotions matter. The REM-S outcomes are: Student understands and applies information to independently provide effective services, develop professionally, and engage in self-reflective practice. The 16 REM-S goals are informed by the REM of genetic counseling practice and supported by prior literature. A review of models in medicine and psychology confirms the REM-S contains supervision elements common in healthcare fields, while remaining unique to genetic counseling. The REM-S shows promise for enhancing genetic counselor supervision training and practice and for promoting research on clinical supervision. The REM-S is presented in detail along with specific examples and training and research suggestions.

  15. Modelling language evolution: Examples and predictions.

    Science.gov (United States)

    Gong, Tao; Shuai, Lan; Zhang, Menghan

    2014-06-01

    We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

  16. Modelling language evolution: Examples and predictions

    Science.gov (United States)

    Gong, Tao; Shuai, Lan; Zhang, Menghan

    2014-06-01

    We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

  17. Global Solar Dynamo Models: Simulations and Predictions

    Indian Academy of Sciences (India)

    Mausumi Dikpati; Peter A. Gilman

    2008-03-01

    Flux-transport type solar dynamos have achieved considerable success in correctly simulating many solar cycle features, and are now being used for prediction of solar cycle timing and amplitude.We first define flux-transport dynamos and demonstrate how they work. The essential added ingredient in this class of models is meridional circulation, which governs the dynamo period and also plays a crucial role in determining the Sun’s memory about its past magnetic fields.We show that flux-transport dynamo models can explain many key features of solar cycles. Then we show that a predictive tool can be built from this class of dynamo that can be used to predict mean solar cycle features by assimilating magnetic field data from previous cycles.

  18. Model Predictive Control of Sewer Networks

    Science.gov (United States)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik; Poulsen, Niels K.; Falk, Anne K. V.

    2017-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and controlled have thus become essential factors for effcient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control.

  19. DKIST Polarization Modeling and Performance Predictions

    Science.gov (United States)

    Harrington, David

    2016-05-01

    Calibrating the Mueller matrices of large aperture telescopes and associated coude instrumentation requires astronomical sources and several modeling assumptions to predict the behavior of the system polarization with field of view, altitude, azimuth and wavelength. The Daniel K Inouye Solar Telescope (DKIST) polarimetric instrumentation requires very high accuracy calibration of a complex coude path with an off-axis f/2 primary mirror, time dependent optical configurations and substantial field of view. Polarization predictions across a diversity of optical configurations, tracking scenarios, slit geometries and vendor coating formulations are critical to both construction and contined operations efforts. Recent daytime sky based polarization calibrations of the 4m AEOS telescope and HiVIS spectropolarimeter on Haleakala have provided system Mueller matrices over full telescope articulation for a 15-reflection coude system. AEOS and HiVIS are a DKIST analog with a many-fold coude optical feed and similar mirror coatings creating 100% polarization cross-talk with altitude, azimuth and wavelength. Polarization modeling predictions using Zemax have successfully matched the altitude-azimuth-wavelength dependence on HiVIS with the few percent amplitude limitations of several instrument artifacts. Polarization predictions for coude beam paths depend greatly on modeling the angle-of-incidence dependences in powered optics and the mirror coating formulations. A 6 month HiVIS daytime sky calibration plan has been analyzed for accuracy under a wide range of sky conditions and data analysis algorithms. Predictions of polarimetric performance for the DKIST first-light instrumentation suite have been created under a range of configurations. These new modeling tools and polarization predictions have substantial impact for the design, fabrication and calibration process in the presence of manufacturing issues, science use-case requirements and ultimate system calibration

  20. Modelling Chemical Reasoning to Predict Reactions

    OpenAIRE

    Segler, Marwin H. S.; Waller, Mark P.

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outpe...

  1. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert; Knox, James

    2016-01-01

    Fully predictive models of the Four Bed Molecular Sieve of the Carbon Dioxide Removal Assembly on the International Space Station are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.

  2. Raman Model Predicting Hardness of Covalent Crystals

    OpenAIRE

    Zhou, Xiang-Feng; Qian, Quang-Rui; Sun, Jian; Tian, Yongjun; Wang, Hui-Tian

    2009-01-01

    Based on the fact that both hardness and vibrational Raman spectrum depend on the intrinsic property of chemical bonds, we propose a new theoretical model for predicting hardness of a covalent crystal. The quantitative relationship between hardness and vibrational Raman frequencies deduced from the typical zincblende covalent crystals is validated to be also applicable for the complex multicomponent crystals. This model enables us to nondestructively and indirectly characterize the hardness o...

  3. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts

  4. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  5. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ

  6. Prediction modelling for population conviction data

    NARCIS (Netherlands)

    Tollenaar, N.

    2017-01-01

    In this thesis, the possibilities of using prediction models for judicial penal case data are investigated. The development and refinement of a risk taxation scale based on these data is discussed. When false positives are weighted equally severe as false negatives, 70% can be classified correctly.

  7. A Predictive Model for MSSW Student Success

    Science.gov (United States)

    Napier, Angela Michele

    2011-01-01

    This study tested a hypothetical model for predicting both graduate GPA and graduation of University of Louisville Kent School of Social Work Master of Science in Social Work (MSSW) students entering the program during the 2001-2005 school years. The preexisting characteristics of demographics, academic preparedness and culture shock along with…

  8. Predictability of extreme values in geophysical models

    NARCIS (Netherlands)

    Sterk, A.E.; Holland, M.P.; Rabassa, P.; Broer, H.W.; Vitolo, R.

    2012-01-01

    Extreme value theory in deterministic systems is concerned with unlikely large (or small) values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical model

  9. A revised prediction model for natural conception

    NARCIS (Netherlands)

    Bensdorp, A.J.; Steeg, J.W. van der; Steures, P.; Habbema, J.D.; Hompes, P.G.; Bossuyt, P.M.; Veen, F. van der; Mol, B.W.; Eijkemans, M.J.; Kremer, J.A.M.; et al.,

    2017-01-01

    One of the aims in reproductive medicine is to differentiate between couples that have favourable chances of conceiving naturally and those that do not. Since the development of the prediction model of Hunault, characteristics of the subfertile population have changed. The objective of this analysis

  10. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  11. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ

  12. Leptogenesis in minimal predictive seesaw models

    CERN Document Server

    Björkeroth, Fredrik; Varzielas, Ivo de Medeiros; King, Stephen F

    2015-01-01

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to $(\

  13. Specialized Language Models using Dialogue Predictions

    CERN Document Server

    Popovici, C; Popovici, Cosmin; Baggia, Paolo

    1996-01-01

    This paper analyses language modeling in spoken dialogue systems for accessing a database. The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. For this reason several models have been created, each one for a specific system question, such as the request or the confirmation of a parameter. The use of dialogue-dependent language models increases the performance both at the recognition and at the understanding level, especially on answers to system requests. Moreover other methods to increase performance, like automatic clustering of vocabulary words or the use of better acoustic models during recognition, does not affect the improvements given by dialogue-dependent language models. The system used in our experiments is Dialogos, the Italian spoken dialogue system used for accessing railway timetable information over the telephone. The experiments were carried out on a large corpus of dialogues coll...

  14. Caries risk assessment models in caries prediction

    Directory of Open Access Journals (Sweden)

    Amila Zukanović

    2013-11-01

    Full Text Available Objective. The aim of this research was to assess the efficiency of different multifactor models in caries prediction. Material and methods. Data from the questionnaire and objective examination of 109 examinees was entered into the Cariogram, Previser and Caries-Risk Assessment Tool (CAT multifactor risk assessment models. Caries risk was assessed with the help of all three models for each patient, classifying them as low, medium or high-risk patients. The development of new caries lesions over a period of three years [Decay Missing Filled Tooth (DMFT increment = difference between Decay Missing Filled Tooth Surface (DMFTS index at baseline and follow up], provided for examination of the predictive capacity concerning different multifactor models. Results. The data gathered showed that different multifactor risk assessment models give significantly different results (Friedman test: Chi square = 100.073, p=0.000. Cariogram is the model which identified the majority of examinees as medium risk patients (70%. The other two models were more radical in risk assessment, giving more unfavorable risk –profiles for patients. In only 12% of the patients did the three multifactor models assess the risk in the same way. Previser and CAT gave the same results in 63% of cases – the Wilcoxon test showed that there is no statistically significant difference in caries risk assessment between these two models (Z = -1.805, p=0.071. Conclusions. Evaluation of three different multifactor caries risk assessment models (Cariogram, PreViser and CAT showed that only the Cariogram can successfully predict new caries development in 12-year-old Bosnian children.

  15. Disease prediction models and operational readiness.

    Directory of Open Access Journals (Sweden)

    Courtney D Corley

    Full Text Available The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011. We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4, spatial (26, ecological niche (28, diagnostic or clinical (6, spread or response (9, and reviews (3. The model parameters (e.g., etiology, climatic, spatial, cultural and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological were recorded and reviewed. A component of this review is the identification of verification and validation (V&V methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology

  16. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...

  17. ENSO Prediction using Vector Autoregressive Models

    Science.gov (United States)

    Chapman, D. R.; Cane, M. A.; Henderson, N.; Lee, D.; Chen, C.

    2013-12-01

    A recent comparison (Barnston et al, 2012 BAMS) shows the ENSO forecasting skill of dynamical models now exceeds that of statistical models, but the best statistical models are comparable to all but the very best dynamical models. In this comparison the leading statistical model is the one based on the Empirical Model Reduction (EMR) method. Here we report on experiments with multilevel Vector Autoregressive models using only sea surface temperatures (SSTs) as predictors. VAR(L) models generalizes Linear Inverse Models (LIM), which are a VAR(1) method, as well as multilevel univariate autoregressive models. Optimal forecast skill is achieved using 12 to 14 months of prior state information (i.e 12-14 levels), which allows SSTs alone to capture the effects of other variables such as heat content as well as seasonality. The use of multiple levels allows the model advancing one month at a time to perform at least as well for a 6 month forecast as a model constructed to explicitly forecast 6 months ahead. We infer that the multilevel model has fully captured the linear dynamics (cf. Penland and Magorian, 1993 J. Climate). Finally, while VAR(L) is equivalent to L-level EMR, we show in a 150 year cross validated assessment that we can increase forecast skill by improving on the EMR initialization procedure. The greatest benefit of this change is in allowing the prediction to make effective use of information over many more months.

  18. Electrostatic ion thrusters - towards predictive modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)

    2014-02-15

    The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  19. Gas explosion prediction using CFD models

    Energy Technology Data Exchange (ETDEWEB)

    Niemann-Delius, C.; Okafor, E. [RWTH Aachen Univ. (Germany); Buhrow, C. [TU Bergakademie Freiberg Univ. (Germany)

    2006-07-15

    A number of CFD models are currently available to model gaseous explosions in complex geometries. Some of these tools allow the representation of complex environments within hydrocarbon production plants. In certain explosion scenarios, a correction is usually made for the presence of buildings and other complexities by using crude approximations to obtain realistic estimates of explosion behaviour as can be found when predicting the strength of blast waves resulting from initial explosions. With the advance of computational technology, and greater availability of computing power, computational fluid dynamics (CFD) tools are becoming increasingly available for solving such a wide range of explosion problems. A CFD-based explosion code - FLACS can, for instance, be confidently used to understand the impact of blast overpressures in a plant environment consisting of obstacles such as buildings, structures, and pipes. With its porosity concept representing geometry details smaller than the grid, FLACS can represent geometry well, even when using coarse grid resolutions. The performance of FLACS has been evaluated using a wide range of field data. In the present paper, the concept of computational fluid dynamics (CFD) and its application to gas explosion prediction is presented. Furthermore, the predictive capabilities of CFD-based gaseous explosion simulators are demonstrated using FLACS. Details about the FLACS-code, some extensions made to FLACS, model validation exercises, application, and some results from blast load prediction within an industrial facility are presented. (orig.)

  20. Genetic models of homosexuality: generating testable predictions.

    Science.gov (United States)

    Gavrilets, Sergey; Rice, William R

    2006-12-22

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism.

  1. Characterizing Attention with Predictive Network Models.

    Science.gov (United States)

    Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M

    2017-04-01

    Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. A Study On Distributed Model Predictive Consensus

    CERN Document Server

    Keviczky, Tamas

    2008-01-01

    We investigate convergence properties of a proposed distributed model predictive control (DMPC) scheme, where agents negotiate to compute an optimal consensus point using an incremental subgradient method based on primal decomposition as described in Johansson et al. [2006, 2007]. The objective of the distributed control strategy is to agree upon and achieve an optimal common output value for a group of agents in the presence of constraints on the agent dynamics using local predictive controllers. Stability analysis using a receding horizon implementation of the distributed optimal consensus scheme is performed. Conditions are given under which convergence can be obtained even if the negotiations do not reach full consensus.

  3. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    R. G. SILVA

    1999-03-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  4. Slow waves, sharp waves, ripples, and REM in sleeping dragons.

    Science.gov (United States)

    Shein-Idelson, Mark; Ondracek, Janie M; Liaw, Hua-Peng; Reiter, Sam; Laurent, Gilles

    2016-04-29

    Sleep has been described in animals ranging from worms to humans. Yet the electrophysiological characteristics of brain sleep, such as slow-wave (SW) and rapid eye movement (REM) activities, are thought to be restricted to mammals and birds. Recording from the brain of a lizard, the Australian dragon Pogona vitticeps, we identified SW and REM sleep patterns, thus pushing back the probable evolution of these dynamics at least to the emergence of amniotes. The SW and REM sleep patterns that we observed in lizards oscillated continuously for 6 to 10 hours with a period of ~80 seconds. The networks controlling SW-REM antagonism in amniotes may thus originate from a common, ancient oscillator circuit. Lizard SW dynamics closely resemble those observed in rodent hippocampal CA1, yet they originate from a brain area, the dorsal ventricular ridge, that has no obvious hodological similarity with the mammalian hippocampus.

  5. Performance model to predict overall defect density

    Directory of Open Access Journals (Sweden)

    J Venkatesh

    2012-08-01

    Full Text Available Management by metrics is the expectation from the IT service providers to stay as a differentiator. Given a project, the associated parameters and dynamics, the behaviour and outcome need to be predicted. There is lot of focus on the end state and in minimizing defect leakage as much as possible. In most of the cases, the actions taken are re-active. It is too late in the life cycle. Root cause analysis and corrective actions can be implemented only to the benefit of the next project. The focus has to shift left, towards the execution phase than waiting for lessons to be learnt post the implementation. How do we pro-actively predict defect metrics and have a preventive action plan in place. This paper illustrates the process performance model to predict overall defect density based on data from projects in an organization.

  6. Neuro-fuzzy modeling in bankruptcy prediction

    Directory of Open Access Journals (Sweden)

    Vlachos D.

    2003-01-01

    Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

  7. Pressure prediction model for compression garment design.

    Science.gov (United States)

    Leung, W Y; Yuen, D W; Ng, Sun Pui; Shi, S Q

    2010-01-01

    Based on the application of Laplace's law to compression garments, an equation for predicting garment pressure, incorporating the body circumference, the cross-sectional area of fabric, applied strain (as a function of reduction factor), and its corresponding Young's modulus, is developed. Design procedures are presented to predict garment pressure using the aforementioned parameters for clinical applications. Compression garments have been widely used in treating burning scars. Fabricating a compression garment with a required pressure is important in the healing process. A systematic and scientific design method can enable the occupational therapist and compression garments' manufacturer to custom-make a compression garment with a specific pressure. The objectives of this study are 1) to develop a pressure prediction model incorporating different design factors to estimate the pressure exerted by the compression garments before fabrication; and 2) to propose more design procedures in clinical applications. Three kinds of fabrics cut at different bias angles were tested under uniaxial tension, as were samples made in a double-layered structure. Sets of nonlinear force-extension data were obtained for calculating the predicted pressure. Using the value at 0° bias angle as reference, the Young's modulus can vary by as much as 29% for fabric type P11117, 43% for fabric type PN2170, and even 360% for fabric type AP85120 at a reduction factor of 20%. When comparing the predicted pressure calculated from the single-layered and double-layered fabrics, the double-layered construction provides a larger range of target pressure at a particular strain. The anisotropic and nonlinear behaviors of the fabrics have thus been determined. Compression garments can be methodically designed by the proposed analytical pressure prediction model.

  8. Enhanced emotional reactivity after selective REM sleep deprivation in humans: an fMRI study

    OpenAIRE

    Rosales-Lagarde, Alejandra; Jorge L Armony; del Río-Portilla, Yolanda; Trejo-Martínez, David; Conde, Ruben; Corsi-Cabrera, Maria

    2012-01-01

    Converging evidence from animal and human studies suggest that rapid eye movement (REM) sleep modulates emotional processing. The aim of the present study was to explore the effects of selective REM sleep deprivation (REM-D) on emotional responses to threatening visual stimuli and their brain correlates using functional magnetic resonance imaging (fMRI). Twenty healthy subjects were randomly assigned to two groups: selective REM-D, by awakening them at each REM sleep onset, or non-rapid eye m...

  9. Enhanced emotional reactivity after selective REM sleep deprivation in humans: an fMRI study

    OpenAIRE

    Alejandra eRosales-Lagarde; Jorge L Armony; Yolanda edel Río-Portilla; David eTrejo-Martínez; Ruben eConde; Maria eCorsi-Cabrera

    2012-01-01

    Converging evidence from animal and human studies suggest that REM sleep modulates emotional processing. The aim of the present study was to explore the effects of selective REM sleep deprivation on emotional responses to threatening visual stimuli and their brain correlates using functional magnetic resonance imaging (fMRI). Twenty healthy subjects were randomly assigned to two groups: selective REM sleep deprivation (REM-D), by awakening them at each REM sleep onset, or NREM sleep interrupt...

  10. Statistical assessment of predictive modeling uncertainty

    Science.gov (United States)

    Barzaghi, Riccardo; Marotta, Anna Maria

    2017-04-01

    When the results of geophysical models are compared with data, the uncertainties of the model are typically disregarded. We propose a method for defining the uncertainty of a geophysical model based on a numerical procedure that estimates the empirical auto and cross-covariances of model-estimated quantities. These empirical values are then fitted by proper covariance functions and used to compute the covariance matrix associated with the model predictions. The method is tested using a geophysical finite element model in the Mediterranean region. Using a novel χ2 analysis in which both data and model uncertainties are taken into account, the model's estimated tectonic strain pattern due to the Africa-Eurasia convergence in the area that extends from the Calabrian Arc to the Alpine domain is compared with that estimated from GPS velocities while taking into account the model uncertainty through its covariance structure and the covariance of the GPS estimates. The results indicate that including the estimated model covariance in the testing procedure leads to lower observed χ2 values that have better statistical significance and might help a sharper identification of the best-fitting geophysical models.

  11. Seasonal Predictability in a Model Atmosphere.

    Science.gov (United States)

    Lin, Hai

    2001-07-01

    The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.

  12. Vocabulary learning benefits from REM after slow-wave sleep.

    Science.gov (United States)

    Batterink, Laura J; Westerberg, Carmen E; Paller, Ken A

    2017-10-01

    Memory reactivation during slow-wave sleep (SWS) influences the consolidation of recently acquired knowledge. This reactivation occurs spontaneously during sleep but can also be triggered by presenting learning-related cues, a technique known as targeted memory reactivation (TMR). Here we examined whether TMR can improve vocabulary learning. Participants learned the meanings of 60 novel words. Auditory cues for half the words were subsequently presented during SWS in an afternoon nap. Memory performance for cued versus uncued words did not differ at the group level but was systematically influenced by REM sleep duration. Participants who obtained relatively greater amounts of REM showed a significant benefit for cued relative to uncued words, whereas participants who obtained little or no REM demonstrated a significant effect in the opposite direction. We propose that REM after SWS may be critical for the consolidation of highly integrative memories, such as new vocabulary. Reactivation during SWS may allow newly encoded memories to be associated with other information, but this association can include disruptive linkages with pre-existing memories. Subsequent REM sleep may then be particularly beneficial for integrating new memories into appropriate pre-existing memory networks. These findings support the general proposition that memory storage benefits optimally from a cyclic succession of SWS and REM. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Forebrain activation in REM sleep: an FDG PET study.

    Science.gov (United States)

    Nofzinger, E A; Mintun, M A; Wiseman, M; Kupfer, D J; Moore, R Y

    1997-10-03

    Rapid eye movement (REM) sleep is a behavioral state characterized by cerebral cortical activation with dreaming as an associated behavior. The brainstem mechanisms involved in the generation of REM sleep are well-known, but the forebrain mechanisms that might distinguish it from waking are not well understood. We report here a positron emission tomography (PET) study of regional cerebral glucose utilization in the human forebrain during REM sleep in comparison to waking in six healthy adult females using the 18F-deoxyglucose method. In REM sleep, there is relative activation, shown by increased glucose utilization, in phylogenetically old limbic and paralimbic regions which include the lateral hypothalamic area, amygdaloid complex, septal-ventral striatal areas, and infralimbic, prelimbic, orbitofrontal, cingulate, entorhinal and insular cortices. The largest area of activation is a bilateral, confluent paramedian zone which extends from the septal area into ventral striatum, infralimbic, prelimbic, orbitofrontal and anterior cingulate cortex. There are only small and scattered areas of apparent deactivation. These data suggest that an important function of REM sleep is the integration of neocortical function with basal forebrain-hypothalamic motivational and reward mechanisms. This is in accordance with views that alterations in REM sleep in psychiatric disorders, such as depression, may reflect dysregulation in limbic and paralimbic structures.

  14. Medical image of the week: REM without atonia

    Directory of Open Access Journals (Sweden)

    Bartell J

    2015-03-01

    Full Text Available No abstract available. Article truncated after 150 words. A 78 year-old man with a past medical history of Parkinson’s disease (PD presented to the sleep medicine clinic for evaluation of obstructive sleep apnea (OSA. An overnight polysomnogram (PSG study was consistent with sleep apnea and revealed frequent leg and arm movements and sleep-talking during rapid eye movement (REM sleep. REM sleep behavior disorder (RBD is a parasomnia characterized by repeated episodes of abnormal behavior occurring during REM sleep (1,2. On PSG, REM sleep without atonia is seen while features of “normal REM” such as number of REM periods and REM cycling remain intact (2. RBD emerges most often in the context of alpha-synucleinopathies, and occurs in up to 60% of PD patients (3. The presence of RBD may be an important preclinical symptom prior to the onset of PD. Cases of PD with RBD are associated with a unique phenotype with an older age of onset, longer disease ...

  15. A dual-detector extended range rem-counter

    CERN Document Server

    Ferrarini, M; Silari, M; Agosteo, S

    2010-01-01

    The design and characterization of a dual-detector spherical rem counter is discussed in this paper. The rem counter is based on a polythene sphere with lead and cadmium insets, designed to host at its centre either an active (He-3 SP9 proportional counter) or a passive (CR39 + B-10 radiator) thermal neutron detector. Its sensitivity ranges from thermal energies up to 1 GeV. A Monte Carlo characterization of this dual-detector rem counter has shown no significant change in the shape of the response curve obtained with the two detectors. The rem counter has been calibrated with a Pu-Be source. An intercomparison in a high-energy neutron field has been carried out at the CERF facility at CERN among the rem counter in the two configurations, two commercial units and the original version of the active LINUS in use at CERN. Both the active and passive versions of the rem counter agree, within the statistical uncertainties, with the CERN LINUS and with the facility reference values. Both versions of the instrument ...

  16. Effects of REM sleep deprivation on sensorimotor gating and startle habituation in rats: role of social isolation in early development.

    Science.gov (United States)

    Chang, Hsin-An; Liu, Yia-Ping; Tung, Che-Se; Chang, Chuan-Chia; Tzeng, Nian-Sheng; Huang, San-Yuan

    2014-07-11

    The present study examined the role of rapid eye movement (REM) sleep on sensorimotor gating function in a developmentally rodent model of schizophrenic-spectrum disorders. Startle magnitude, prepulse inhibition (PPI) and startle habituation in an acoustic startle test were measured after 72-h of REM sleep deprivation (REMSD) in 14-week-old rats that were reared in one of the following conditions: control social interaction, 2-week isolation, and continuous isolation, since weaning. The results showed that REMSD significantly inhibited rats' PPI in socially controlled rats, and rats in two isolation groups appeared less sensitive to REMSD. After REMSD, startle habituation was significantly reduced in continuous-isolated rats but not in 2-week-isolated rats. These data indicate that REM sleep is essential for PPI; REMSD inhibits startle habituation in rats with continuous social isolation. In addition, social interaction, in early life or for the whole life, functions differently to the sensorimotor gating.

  17. A kinetic model for predicting biodegradation.

    Science.gov (United States)

    Dimitrov, S; Pavlov, T; Nedelcheva, D; Reuschenbach, P; Silvani, M; Bias, R; Comber, M; Low, L; Lee, C; Parkerton, T; Mekenyan, O

    2007-01-01

    Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a '10 day window' criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the '10-day window' criterion.

  18. The Swift Mission and the REM Telescope

    Science.gov (United States)

    Gehrels, N.; Chincarini, G.; Giommi, P.; Mason, K. O.; Nousek, J. A.; Wells, A. A.; White, N. E.; Barthelemy, S. D.; Burrow, D. N.; Hurley, K. C.

    2003-01-01

    Following a description of the science drive which originated the Swift Mission, this is US NASA MIDEX Mission with the collaboration of Italy and the UK, we will describe the status of the hardware and the observing strategy. The telemetry is carried out via the TDRSS satellite for those communications that need immediate response. The data transfer and the scheduled uploading of routine commands will be done through the ASI Malindi station in Kenia. Both in the US and in Europe a large effort will be done to follow the bursts with the maximum of efficiency and as soon as possible after the alert. We will describe how the ESO VLT telescopes are able to respond to the alert. To address the problematic of the dark bursts and to immediately follow up all of the bursts also in the Near Infrared we designed and built a 60 cm NIR Robotic telescope, REM, to be located on the ESO ground at Cerro La Silla. The instrumentation includes also a low dispersion spectrograph with the capability of multi wavelength optical photometry.

  19. REM meter for pulsed sources of neutrons

    Energy Technology Data Exchange (ETDEWEB)

    Thorngate, J.E.; Hunt, G.F.; Rueppel, D.W.

    1980-08-13

    A rem meter was constructed specifically for measuring neutrons produced by fusion experiments for which the source pulses last 10 ms or longer. The detector is a /sup 6/Li glass scintillator, 25.4 mm in diameter and 3.2 mm thick, surrounded by 11.5 cm of polyethylene. This detector has a sensitivity of 8.5 x 10/sup 4/ counts/mrem. The signals from this fast scintillator are shaped using a shorted delay line to produce pulses that are only 10 ns long so that dose equivalent rates up to 12 mrem/s can be measured with less than a 1% counting loss. The associated electronic circuits store detector counts only when the count rate exceeds a preset level. When the count rate returns to background, a conversion from counts to dose equivalent is made and the results are displayed. As a means of recording the number of source pulses that have occurred, a second display shows how many times the preset count rate has been exceeded. Accumulation of detector counts and readouts can also be controlled manually. The unit will display the integrated dose equilavent up to 200 mrem in 0.01 mrem steps. A pulse-height discriminator rejects gamma-ray interactions below 1 MeV, and the detector size limits the response above that energy. The instrument can be operated from an ac line or will run on rechargeable batteries for up to 12 hours.

  20. The Swift Mission and the REM Telescope

    Science.gov (United States)

    Gehrels, N.; Chincarini, G.; Giommi, P.; Mason, K. O.; Nousek, J. A.; Wells, A. A.; White, N. E.; Barthelemy, S. D.; Burrow, D. N.; Hurley, K. C.

    2003-01-01

    Following a description of the science drive which originated the Swift Mission, this is US NASA MIDEX Mission with the collaboration of Italy and the UK, we will describe the status of the hardware and the observing strategy. The telemetry is carried out via the TDRSS satellite for those communications that need immediate response. The data transfer and the scheduled uploading of routine commands will be done through the ASI Malindi station in Kenia. Both in the US and in Europe a large effort will be done to follow the bursts with the maximum of efficiency and as soon as possible after the alert. We will describe how the ESO VLT telescopes are able to respond to the alert. To address the problematic of the dark bursts and to immediately follow up all of the bursts also in the Near Infrared we designed and built a 60 cm NIR Robotic telescope, REM, to be located on the ESO ground at Cerro La Silla. The instrumentation includes also a low dispersion spectrograph with the capability of multi wavelength optical photometry.

  1. Disease Prediction Models and Operational Readiness

    Energy Technology Data Exchange (ETDEWEB)

    Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.

    2014-03-19

    INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the

  2. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  3. Predictive Modeling in Actinide Chemistry and Catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-16

    These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.

  4. Probabilistic prediction models for aggregate quarry siting

    Science.gov (United States)

    Robinson, G.R.; Larkins, P.M.

    2007-01-01

    Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.

  5. Predicting Footbridge Response using Stochastic Load Models

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2013-01-01

    Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing s...... as it pinpoints which decisions to be concerned about when the goal is to predict footbridge response. The studies involve estimating footbridge responses using Monte-Carlo simulations and focus is on estimating vertical structural response to single person loading....

  6. Nonconvex Model Predictive Control for Commercial Refrigeration

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F.S.; Jørgensen, John Bagterp

    2013-01-01

    is to minimize the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost...... the iterations, which is more than fast enough to run in real-time. We demonstrate our method on a realistic model, with a full year simulation and 15 minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost...

  7. Genetic inactivation of glutamate neurons in the rat sublaterodorsal tegmental nucleus recapitulates REM sleep behaviour disorder.

    Science.gov (United States)

    Valencia Garcia, Sara; Libourel, Paul-Antoine; Lazarus, Michael; Grassi, Daniela; Luppi, Pierre-Hervé; Fort, Patrice

    2017-02-01

    -enacting behaviours. These animals display symptoms and behaviours during paradoxical sleep that closely mimic human REM sleep behaviour disorder. Altogether, our data demonstrate that glutamate sublaterodorsal tegmental nucleus neurons generate muscle atonia during paradoxical sleep likely through descending projections to glycine/GABA premotor neurons in the ventral medulla. Although playing a role in paradoxical sleep regulation, they are, however, not necessary for inducing the state itself. The present work further validates a potent new preclinical REM sleep behaviour disorder model that opens avenues for studying and treating this disabling sleep disorder, and advances potential regions implicated in prodromal stages of synucleinopathies such as Parkinson's disease. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Predictive In Vivo Models for Oncology.

    Science.gov (United States)

    Behrens, Diana; Rolff, Jana; Hoffmann, Jens

    2016-01-01

    Experimental oncology research and preclinical drug development both substantially require specific, clinically relevant in vitro and in vivo tumor models. The increasing knowledge about the heterogeneity of cancer requested a substantial restructuring of the test systems for the different stages of development. To be able to cope with the complexity of the disease, larger panels of patient-derived tumor models have to be implemented and extensively characterized. Together with individual genetically engineered tumor models and supported by core functions for expression profiling and data analysis, an integrated discovery process has been generated for predictive and personalized drug development.Improved “humanized” mouse models should help to overcome current limitations given by xenogeneic barrier between humans and mice. Establishment of a functional human immune system and a corresponding human microenvironment in laboratory animals will strongly support further research.Drug discovery, systems biology, and translational research are moving closer together to address all the new hallmarks of cancer, increase the success rate of drug development, and increase the predictive value of preclinical models.

  9. Constructing predictive models of human running.

    Science.gov (United States)

    Maus, Horst-Moritz; Revzen, Shai; Guckenheimer, John; Ludwig, Christian; Reger, Johann; Seyfarth, Andre

    2015-02-06

    Running is an essential mode of human locomotion, during which ballistic aerial phases alternate with phases when a single foot contacts the ground. The spring-loaded inverted pendulum (SLIP) provides a starting point for modelling running, and generates ground reaction forces that resemble those of the centre of mass (CoM) of a human runner. Here, we show that while SLIP reproduces within-step kinematics of the CoM in three dimensions, it fails to reproduce stability and predict future motions. We construct SLIP control models using data-driven Floquet analysis, and show how these models may be used to obtain predictive models of human running with six additional states comprising the position and velocity of the swing-leg ankle. Our methods are general, and may be applied to any rhythmic physical system. We provide an approach for identifying an event-driven linear controller that approximates an observed stabilization strategy, and for producing a reduced-state model which closely recovers the observed dynamics. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  10. Statistical Seasonal Sea Surface based Prediction Model

    Science.gov (United States)

    Suarez, Roberto; Rodriguez-Fonseca, Belen; Diouf, Ibrahima

    2014-05-01

    The interannual variability of the sea surface temperature (SST) plays a key role in the strongly seasonal rainfall regime on the West African region. The predictability of the seasonal cycle of rainfall is a field widely discussed by the scientific community, with results that fail to be satisfactory due to the difficulty of dynamical models to reproduce the behavior of the Inter Tropical Convergence Zone (ITCZ). To tackle this problem, a statistical model based on oceanic predictors has been developed at the Universidad Complutense of Madrid (UCM) with the aim to complement and enhance the predictability of the West African Monsoon (WAM) as an alternative to the coupled models. The model, called S4CAST (SST-based Statistical Seasonal Forecast) is based on discriminant analysis techniques, specifically the Maximum Covariance Analysis (MCA) and Canonical Correlation Analysis (CCA). Beyond the application of the model to the prediciton of rainfall in West Africa, its use extends to a range of different oceanic, atmospheric and helth related parameters influenced by the temperature of the sea surface as a defining factor of variability.

  11. Predictive modeling by the cerebellum improves proprioception.

    Science.gov (United States)

    Bhanpuri, Nasir H; Okamura, Allison M; Bastian, Amy J

    2013-09-04

    Because sensation is delayed, real-time movement control requires not just sensing, but also predicting limb position, a function hypothesized for the cerebellum. Such cerebellar predictions could contribute to perception of limb position (i.e., proprioception), particularly when a person actively moves the limb. Here we show that human cerebellar patients have proprioceptive deficits compared with controls during active movement, but not when the arm is moved passively. Furthermore, when healthy subjects move in a force field with unpredictable dynamics, they have active proprioceptive deficits similar to cerebellar patients. Therefore, muscle activity alone is likely insufficient to enhance proprioception and predictability (i.e., an internal model of the body and environment) is important for active movement to benefit proprioception. We conclude that cerebellar patients have an active proprioceptive deficit consistent with disrupted movement prediction rather than an inability to generally enhance peripheral proprioceptive signals during action and suggest that active proprioceptive deficits should be considered a fundamental cerebellar impairment of clinical importance.

  12. A prediction model for Clostridium difficile recurrence

    Directory of Open Access Journals (Sweden)

    Francis D. LaBarbera

    2015-02-01

    Full Text Available Background: Clostridium difficile infection (CDI is a growing problem in the community and hospital setting. Its incidence has been on the rise over the past two decades, and it is quickly becoming a major concern for the health care system. High rate of recurrence is one of the major hurdles in the successful treatment of C. difficile infection. There have been few studies that have looked at patterns of recurrence. The studies currently available have shown a number of risk factors associated with C. difficile recurrence (CDR; however, there is little consensus on the impact of most of the identified risk factors. Methods: Our study was a retrospective chart review of 198 patients diagnosed with CDI via Polymerase Chain Reaction (PCR from February 2009 to Jun 2013. In our study, we decided to use a machine learning algorithm called the Random Forest (RF to analyze all of the factors proposed to be associated with CDR. This model is capable of making predictions based on a large number of variables, and has outperformed numerous other models and statistical methods. Results: We came up with a model that was able to accurately predict the CDR with a sensitivity of 83.3%, specificity of 63.1%, and area under curve of 82.6%. Like other similar studies that have used the RF model, we also had very impressive results. Conclusions: We hope that in the future, machine learning algorithms, such as the RF, will see a wider application.

  13. Gamma-Ray Pulsars Models and Predictions

    CERN Document Server

    Harding, A K

    2001-01-01

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...

  14. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  15. Ground Motion Prediction Models for Caucasus Region

    Science.gov (United States)

    Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

    2016-04-01

    Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

  16. Modeling and Prediction of Krueger Device Noise

    Science.gov (United States)

    Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

    2016-01-01

    This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.

  17. A generative model for predicting terrorist incidents

    Science.gov (United States)

    Verma, Dinesh C.; Verma, Archit; Felmlee, Diane; Pearson, Gavin; Whitaker, Roger

    2017-05-01

    A major concern in coalition peace-support operations is the incidence of terrorist activity. In this paper, we propose a generative model for the occurrence of the terrorist incidents, and illustrate that an increase in diversity, as measured by the number of different social groups to which that an individual belongs, is inversely correlated with the likelihood of a terrorist incident in the society. A generative model is one that can predict the likelihood of events in new contexts, as opposed to statistical models which are used to predict the future incidents based on the history of the incidents in an existing context. Generative models can be useful in planning for persistent Information Surveillance and Reconnaissance (ISR) since they allow an estimation of regions in the theater of operation where terrorist incidents may arise, and thus can be used to better allocate the assignment and deployment of ISR assets. In this paper, we present a taxonomy of terrorist incidents, identify factors related to occurrence of terrorist incidents, and provide a mathematical analysis calculating the likelihood of occurrence of terrorist incidents in three common real-life scenarios arising in peace-keeping operations

  18. Optimal feedback scheduling of model predictive controllers

    Institute of Scientific and Technical Information of China (English)

    Pingfang ZHOU; Jianying XIE; Xiaolong DENG

    2006-01-01

    Model predictive control (MPC) could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling (FS-CBS) of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server (CBS), whose reserved processor time is adjusted dynamically. The constraints in the FSCBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness.

  19. Objective calibration of numerical weather prediction models

    Science.gov (United States)

    Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

    2017-07-01

    Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

  20. Prediction models from CAD models of 3D objects

    Science.gov (United States)

    Camps, Octavia I.

    1992-11-01

    In this paper we present a probabilistic prediction based approach for CAD-based object recognition. Given a CAD model of an object, the PREMIO system combines techniques of analytic graphics and physical models of lights and sensors to predict how features of the object will appear in images. In nearly 4,000 experiments on analytically-generated and real images, we show that in a semi-controlled environment, predicting the detectability of features of the image can successfully guide a search procedure to make informed choices of model and image features in its search for correspondences that can be used to hypothesize the pose of the object. Furthermore, we provide a rigorous experimental protocol that can be used to determine the optimal number of correspondences to seek so that the probability of failing to find a pose and of finding an inaccurate pose are minimized.

  1. Model predictive control of MSMPR crystallizers

    Science.gov (United States)

    Moldoványi, Nóra; Lakatos, Béla G.; Szeifert, Ferenc

    2005-02-01

    A multi-input-multi-output (MIMO) control problem of isothermal continuous crystallizers is addressed in order to create an adequate model-based control system. The moment equation model of mixed suspension, mixed product removal (MSMPR) crystallizers that forms a dynamical system is used, the state of which is represented by the vector of six variables: the first four leading moments of the crystal size, solute concentration and solvent concentration. Hence, the time evolution of the system occurs in a bounded region of the six-dimensional phase space. The controlled variables are the mean size of the grain; the crystal size-distribution and the manipulated variables are the input concentration of the solute and the flow rate. The controllability and observability as well as the coupling between the inputs and the outputs was analyzed by simulation using the linearized model. It is shown that the crystallizer is a nonlinear MIMO system with strong coupling between the state variables. Considering the possibilities of the model reduction, a third-order model was found quite adequate for the model estimation in model predictive control (MPC). The mean crystal size and the variance of the size distribution can be nearly separately controlled by the residence time and the inlet solute concentration, respectively. By seeding, the controllability of the crystallizer increases significantly, and the overshoots and the oscillations become smaller. The results of the controlling study have shown that the linear MPC is an adaptable and feasible controller of continuous crystallizers.

  2. An Anisotropic Hardening Model for Springback Prediction

    Science.gov (United States)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  3. Optogenetic activation of cholinergic neurons in the PPT or LDT induces REM sleep.

    Science.gov (United States)

    Van Dort, Christa J; Zachs, Daniel P; Kenny, Jonathan D; Zheng, Shu; Goldblum, Rebecca R; Gelwan, Noah A; Ramos, Daniel M; Nolan, Michael A; Wang, Karen; Weng, Feng-Ju; Lin, Yingxi; Wilson, Matthew A; Brown, Emery N

    2015-01-13

    Rapid eye movement (REM) sleep is an important component of the natural sleep/wake cycle, yet the mechanisms that regulate REM sleep remain incompletely understood. Cholinergic neurons in the mesopontine tegmentum have been implicated in REM sleep regulation, but lesions of this area have had varying effects on REM sleep. Therefore, this study aimed to clarify the role of cholinergic neurons in the pedunculopontine tegmentum (PPT) and laterodorsal tegmentum (LDT) in REM sleep generation. Selective optogenetic activation of cholinergic neurons in the PPT or LDT during non-REM (NREM) sleep increased the number of REM sleep episodes and did not change REM sleep episode duration. Activation of cholinergic neurons in the PPT or LDT during NREM sleep was sufficient to induce REM sleep.

  4. Predictive modelling of ferroelectric tunnel junctions

    Science.gov (United States)

    Velev, Julian P.; Burton, John D.; Zhuravlev, Mikhail Ye; Tsymbal, Evgeny Y.

    2016-05-01

    Ferroelectric tunnel junctions combine the phenomena of quantum-mechanical tunnelling and switchable spontaneous polarisation of a nanometre-thick ferroelectric film into novel device functionality. Switching the ferroelectric barrier polarisation direction produces a sizable change in resistance of the junction—a phenomenon known as the tunnelling electroresistance effect. From a fundamental perspective, ferroelectric tunnel junctions and their version with ferromagnetic electrodes, i.e., multiferroic tunnel junctions, are testbeds for studying the underlying mechanisms of tunnelling electroresistance as well as the interplay between electric and magnetic degrees of freedom and their effect on transport. From a practical perspective, ferroelectric tunnel junctions hold promise for disruptive device applications. In a very short time, they have traversed the path from basic model predictions to prototypes for novel non-volatile ferroelectric random access memories with non-destructive readout. This remarkable progress is to a large extent driven by a productive cycle of predictive modelling and innovative experimental effort. In this review article, we outline the development of the ferroelectric tunnel junction concept and the role of theoretical modelling in guiding experimental work. We discuss a wide range of physical phenomena that control the functional properties of ferroelectric tunnel junctions and summarise the state-of-the-art achievements in the field.

  5. Simple predictions from multifield inflationary models.

    Science.gov (United States)

    Easther, Richard; Frazer, Jonathan; Peiris, Hiranya V; Price, Layne C

    2014-04-25

    We explore whether multifield inflationary models make unambiguous predictions for fundamental cosmological observables. Focusing on N-quadratic inflation, we numerically evaluate the full perturbation equations for models with 2, 3, and O(100) fields, using several distinct methods for specifying the initial values of the background fields. All scenarios are highly predictive, with the probability distribution functions of the cosmological observables becoming more sharply peaked as N increases. For N=100 fields, 95% of our Monte Carlo samples fall in the ranges ns∈(0.9455,0.9534), α∈(-9.741,-7.047)×10-4, r∈(0.1445,0.1449), and riso∈(0.02137,3.510)×10-3 for the spectral index, running, tensor-to-scalar ratio, and isocurvature-to-adiabatic ratio, respectively. The expected amplitude of isocurvature perturbations grows with N, raising the possibility that many-field models may be sensitive to postinflationary physics and suggesting new avenues for testing these scenarios.

  6. Predictions of models for environmental radiological assessment

    Energy Technology Data Exchange (ETDEWEB)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa, E-mail: suelip@ird.gov.br, E-mail: dejanira@irg.gov.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Servico de Avaliacao de Impacto Ambiental, Rio de Janeiro, RJ (Brazil); Mahler, Claudio Fernando [Coppe. Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia, Universidade Federal do Rio de Janeiro (UFRJ) - Programa de Engenharia Civil, RJ (Brazil)

    2011-07-01

    In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for {sup 137}Cs and {sup 60}Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)

  7. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...

  8. A Modified Model Predictive Control Scheme

    Institute of Scientific and Technical Information of China (English)

    Xiao-Bing Hu; Wen-Hua Chen

    2005-01-01

    In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.

  9. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... facilitates plug-and-play addition of subsystems without redesign of any controllers. The method is supported by a number of simulations featuring a three-level smart-grid power control system for a small isolated power grid....

  10. Explicit model predictive control accuracy analysis

    OpenAIRE

    Knyazev, Andrew; Zhu, Peizhen; Di Cairano, Stefano

    2015-01-01

    Model Predictive Control (MPC) can efficiently control constrained systems in real-time applications. MPC feedback law for a linear system with linear inequality constraints can be explicitly computed off-line, which results in an off-line partition of the state space into non-overlapped convex regions, with affine control laws associated to each region of the partition. An actual implementation of this explicit MPC in low cost micro-controllers requires the data to be "quantized", i.e. repre...

  11. Critical conceptualism in environmental modeling and prediction.

    Science.gov (United States)

    Christakos, G

    2003-10-15

    Many important problems in environmental science and engineering are of a conceptual nature. Research and development, however, often becomes so preoccupied with technical issues, which are themselves fascinating, that it neglects essential methodological elements of conceptual reasoning and theoretical inquiry. This work suggests that valuable insight into environmental modeling can be gained by means of critical conceptualism which focuses on the software of human reason and, in practical terms, leads to a powerful methodological framework of space-time modeling and prediction. A knowledge synthesis system develops the rational means for the epistemic integration of various physical knowledge bases relevant to the natural system of interest in order to obtain a realistic representation of the system, provide a rigorous assessment of the uncertainty sources, generate meaningful predictions of environmental processes in space-time, and produce science-based decisions. No restriction is imposed on the shape of the distribution model or the form of the predictor (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated). The scientific reasoning structure underlying knowledge synthesis involves teleologic criteria and stochastic logic principles which have important advantages over the reasoning method of conventional space-time techniques. Insight is gained in terms of real world applications, including the following: the study of global ozone patterns in the atmosphere using data sets generated by instruments on board the Nimbus 7 satellite and secondary information in terms of total ozone-tropopause pressure models; the mapping of arsenic concentrations in the Bangladesh drinking water by assimilating hard and soft data from an extensive network of monitoring wells; and the dynamic imaging of probability distributions of pollutants across the Kalamazoo river.

  12. Detection of Northern Hemisphere Transient Baroclinic Eddies in REMS Pressure Data at Gale Crater Mars

    Science.gov (United States)

    Haberle, Robert; Kahre, Melinda A.; De la Torre, Manuel; Kass, David M.; Mars Science Laboratory Science Team

    2016-10-01

    Wintertime transient baroclinic eddies in the northern midlatitudes of Mars were identified in Viking Lander 2 (VL2, 48.3N, 134.0E) surface pressure data back in the early 1980s. Here we report the results of an analysis of REMS surface pressure data acquired by the Curiosity Rover in Gale Crater (4.5S, 137.4E) that suggests the meridional scale of these eddies is so large that the disturbances in the surface pressure fields they create extend across the equator and into the southern hemisphere. A power spectrum analysis of the seasonally detrended REMS pressure data from Ls=240-280 shows dominant periods of ~ 6 sols and ~2.2 sols (though with greatly reduced power) which are close the dominant periods of the transient eddies observed by VL2 at this season. Analysis of the surface pressure fields from the Ames Mars GCM for the same season also shows dominant periods at the grid points closest to VL2 and Gale Crater similar to those observed. In the model, the disturbances responsible for these oscillations are eastward traveling baroclinic eddies whose amplitudes are greatest at northern mid latitudes at this season, but whose meridional extent does indeed extend into the low latitudes of the southern hemisphere. REMS appears to be seeing the signature of these eddies, not only for this season but for the early fall and late winter seasons as well. While orbital images of the so called "flushing storms", which more closely correspond to the shorter period waves, show dust-lifting frontal systems that cross the equator, REMS data - even though acquired at a longitude of comparatively weak storm activity - provide the first in-situ evidence that northern hemisphere transient eddies can be detected at the surface in low latitudes of the southern hemisphere.

  13. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  14. 快速眼动睡眠剥夺对抑郁模型大鼠纹状体5-HTDA及腺苷的影响%Effects of REM sleep deprivation on 5-HT,DA and adenosine in striatum of depression-model rats

    Institute of Scientific and Technical Information of China (English)

    冯飞; 许崇涛; 徐国建; 吴东辉

    2014-01-01

    目的:通过对抑郁模型大鼠的快速眼动睡眠剥夺,观察大鼠强迫游泳不动时间及大鼠纹状体5-羟色胺、多巴胺和腺苷水平的变化,了解睡眠剥夺快速改善抑郁情绪的可能机制。方法将30只成年健康雄性大鼠分为正常对照组(A组)、抑郁模型组(B组)、抑郁模型+睡眠剥夺组(C组),在建立慢性轻度不可预见性应激的抑郁模型后,采用小平台水环境法对大鼠进行72 h快速眼动睡眠剥夺,以强迫游泳实验检测大鼠的不动时间,采用高效液相色谱-荧光检测法测定3组大鼠纹状体5-羟色胺、多巴胺水平,采用高效液相色谱-紫外检测法测定3组大鼠纹状体腺苷水平。结果21 d慢性轻度不可预见性应激后,大鼠的强迫游泳不动时间显著延长( P<0.05),快眼动睡眠剥夺后大鼠强迫游泳不动时间显著缩短(P<0.01)。A组、C组大鼠纹状体5-羟色胺及腺苷水平均显著高于B组( P<0.05或0.01),C组大鼠纹状体多巴胺水平显著高于A组、B组(P<0.01)。结论快速眼动睡眠剥夺可以逆转大鼠的抑郁样行为,并提高大鼠纹状体5-羟色胺、多巴胺水平,腺苷可能参与了睡眠剥夺的抗抑郁过程。%Objective To observe rats’ motionless time during forced swimming and changes of 5-HT ,DA and adenosine in striatum via depriving REM sleep of depression-model rats and to find out possible mecha-nism of REM sleep deprivation improving emotional emotion .Methods Thirty healthy male adult rats were divided into normal control group (group A) ,depression-model (group B) and depression-model with sleep deprivation (group C) ,72-hour REM sleep deprivations were carried out using “flower pot” tech-nique after establishing chronic mild unpredictable stress depression-model ,motionless times detected u-sing forced swimming ,striatum 5-HT and DA levels measured with high efficiency liquid

  15. REM SLEEP REBOUND AS AN ADAPTIVE RESPONSE TO STRESSFUL SITUATIONS

    Directory of Open Access Journals (Sweden)

    Deborah eSuchecki

    2012-04-01

    Full Text Available Stress and sleep are related to each other in a bidirectional way. If on one hand poor or inadequate sleep exacerbates emotional, behavioral and stress-related responses, on the other hand acute stress induces sleep rebound, most likely as a form to cope with the adverse stimuli. Chronic stress, conversely, has been claimed to be one of the triggering factors of emotional-related sleep disorders, such as insomnia, depressive- and anxiety-disorders. These outcomes are dependent on individual psychobiological characteristics, which confer more complexity to the stress-sleep relationship. Its neurobiology has only recently begun to be explored, through animal models, which are also valuable for the development of potential therapeutic agents and preventive actions. This review seeks to present data on the effects of stress on sleep and the different approaches used to study this relationship as well as possible neurobiological underpinnings and mechanisms involved. The results of numerous studies in humans and animals indicate that increased sleep, especially the REM phase, following a stressful situation is an important adaptive behavior for recovery. However, this endogenous advantage appears to be impaired in human beings and rodent strains that exhibit high levels of anxiety and anxiety-like behavior.

  16. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euro per km per year [1]. Aiming to reduce such maintenance expenditure, this paper...... presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time...... recovery on the track quality after tamping operation and (5) Tamping machine operation factors. A Danish railway track between Odense and Fredericia with 57.2 km of length is applied for a time period of two to four years in the proposed maintenance model. The total cost can be reduced with up to 50...

  17. A predictive fitness model for influenza

    Science.gov (United States)

    Łuksza, Marta; Lässig, Michael

    2014-03-01

    The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.

  18. Predictive Model of Radiative Neutrino Masses

    CERN Document Server

    Babu, K S

    2013-01-01

    We present a simple and predictive model of radiative neutrino masses. It is a special case of the Zee model which introduces two Higgs doublets and a charged singlet. We impose a family-dependent Z_4 symmetry acting on the leptons, which reduces the number of parameters describing neutrino oscillations to four. A variety of predictions follow: The hierarchy of neutrino masses must be inverted; the lightest neutrino mass is extremely small and calculable; one of the neutrino mixing angles is determined in terms of the other two; the phase parameters take CP-conserving values with \\delta_{CP} = \\pi; and the effective mass in neutrinoless double beta decay lies in a narrow range, m_{\\beta \\beta} = (17.6 - 18.5) meV. The ratio of vacuum expectation values of the two Higgs doublets, tan\\beta, is determined to be either 1.9 or 0.19 from neutrino oscillation data. Flavor-conserving and flavor-changing couplings of the Higgs doublets are also determined from neutrino data. The non-standard neutral Higgs bosons, if t...

  19. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...

  20. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  1. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model......A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...

  2. Two criteria for evaluating risk prediction models.

    Science.gov (United States)

    Pfeiffer, R M; Gail, M H

    2011-09-01

    We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow-up, PNF (p), namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q% of the population at highest risk. PNF (p) assess the feasibility of covering 100p% of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.

  3. Methods for Handling Missing Variables in Risk Prediction Models

    NARCIS (Netherlands)

    Held, Ulrike; Kessels, Alfons; Aymerich, Judith Garcia; Basagana, Xavier; ter Riet, Gerben; Moons, Karel G. M.; Puhan, Milo A.

    2016-01-01

    Prediction models should be externally validated before being used in clinical practice. Many published prediction models have never been validated. Uncollected predictor variables in otherwise suitable validation cohorts are the main factor precluding external validation.We used individual patient

  4. Role of corticosterone on sleep homeostasis induced by REM sleep deprivation in rats.

    Science.gov (United States)

    Machado, Ricardo Borges; Tufik, Sergio; Suchecki, Deborah

    2013-01-01

    Sleep is regulated by humoral and homeostatic processes. If on one hand chronic elevation of stress hormones impair sleep, on the other hand, rapid eye movement (REM) sleep deprivation induces elevation of glucocorticoids and time of REM sleep during the recovery period. In the present study we sought to examine whether manipulations of corticosterone levels during REM sleep deprivation would alter the subsequent sleep rebound. Adult male Wistar rats were fit with electrodes for sleep monitoring and submitted to four days of REM sleep deprivation under repeated corticosterone or metyrapone (an inhibitor of corticosterone synthesis) administration. Sleep parameters were continuously recorded throughout the sleep deprivation period and during 3 days of sleep recovery. Plasma levels of adrenocorticotropic hormone and corticosterone were also evaluated. Metyrapone treatment prevented the elevation of corticosterone plasma levels induced by REM sleep deprivation, whereas corticosterone administration to REM sleep-deprived rats resulted in lower corticosterone levels than in non-sleep deprived rats. Nonetheless, both corticosterone and metyrapone administration led to several alterations on sleep homeostasis, including reductions in the amount of non-REM and REM sleep during the recovery period, although corticosterone increased delta activity (1.0-4.0 Hz) during REM sleep deprivation. Metyrapone treatment of REM sleep-deprived rats reduced the number of REM sleep episodes. In conclusion, reduction of corticosterone levels during REM sleep deprivation resulted in impairment of sleep rebound, suggesting that physiological elevation of corticosterone levels resulting from REM sleep deprivation is necessary for plentiful recovery of sleep after this stressful event.

  5. A Temporally Controlled Inhibitory Drive Coordinates Twitch Movements during REM Sleep.

    Science.gov (United States)

    Brooks, Patricia L; Peever, John

    2016-05-01

    During REM sleep, skeletal muscles are paralyzed in one moment but twitch and jerk in the next. REM sleep twitches are traditionally considered random motor events that result from momentary lapses in REM sleep paralysis [1-3]. However, recent evidence indicates that twitches are not byproducts of REM sleep, but are in fact self-generated events that could function to promote motor learning and development [4-6]. If REM twitches are indeed purposefully generated, then they should be controlled by a coordinated and definable mechanism. Here, we used behavioral, electrophysiological, pharmacological, and neuroanatomical methods to demonstrate that an inhibitory drive onto skeletal motoneurons produces a temporally coordinated pattern of muscle twitches during REM sleep. First, we show that muscle twitches in adult rats are not uniformly distributed during REM sleep, but instead follow a well-defined temporal trajectory. They are largely absent during REM initiation but increase steadily thereafter, peaking toward REM termination. Next, we identify the transmitter mechanism that controls the temporal nature of twitch activity. Specifically, we show that a GABA and glycine drive onto motoneurons prevents twitch activity during REM initiation, but progressive weakening of this drive functions to promote twitch activity during REM termination. These results demonstrate that REM twitches are not random byproducts of REM sleep, but are instead rather coherently generated events controlled by a temporally variable inhibitory drive.

  6. Risk evaluation and mitigation strategies (REMS): educating the prescriber.

    Science.gov (United States)

    Nicholson, Susan C; Peterson, Janet; Yektashenas, Behin

    2012-02-01

    The US FDA Amendments Act of 2007 was signed into law on 27 September 2007. A provision of this law granted the FDA new powers to enhance drug safety by requiring the pharmaceutical industry to develop Risk Evaluation and Mitigation Strategies (REMS). REMS are deemed necessary when a question exists as to whether the benefits of a drug outweigh its risks. REMS constitute a safety plan with several potential components, including a medication guide, a communication plan, elements to ensure safe use and an implementation system to help guide the prescribers, pharmacists and patients. This applies to existing drugs on the market, new drug applications (NDAs), abbreviated NDAs (generics) and biologics licence applications. REMS represent an 'upgrade' from previously required risk minimization action plans, based on the strengthening of FDA powers of authority and enforceability to incur monetary penalties against individuals representing the pharmaceutical industry who fail to comply. For illustrative purposes, we chose the drug romiplostim (Nplate®) to present an REMS, as all components were utilized to help assuage risks associated with the drug. Romiplostim is an FDA-approved drug used to treat thrombocytopenia in patients with chronic immune (idiopathic) thrombocytopenic purpura that has a significant adverse safety profile based on the risk of changes in bone marrow reticulin formation and bone marrow fibroses, and other associated risks. This review of current REMS policy is intended to provide the prescriber with a better understanding of current modalities in FDA-mandated drug safety programmes, which will impact day-to-day healthcare provider practices.

  7. Estimating the magnitude of prediction uncertainties for the APLE model

    Science.gov (United States)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analysis for the Annual P ...

  8. Prediction of Catastrophes: an experimental model

    CERN Document Server

    Peters, Randall D; Pomeau, Yves

    2012-01-01

    Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could be. Described in this article is a "laboratory" setup that yields data of a type that is amenable to theoretical methods of prediction. Observations are made of a critical slowing down in the noisy signal of a solder wire creeping under constant stress. This effect is shown to be a fair signal of the forthcoming catastrophe in both of two dynamical models. The first is an "abstract" model in which a time dependent quantity drifts slowly but makes quick jumps from time to time. The second is a realistic physical model for the collective motion of dislocations (the Ananthakrishna set of equations for creep). Hope thus exists that similar changes in the response to ...

  9. Predictive modeling of low solubility semiconductor alloys

    Science.gov (United States)

    Rodriguez, Garrett V.; Millunchick, Joanna M.

    2016-09-01

    GaAsBi is of great interest for applications in high efficiency optoelectronic devices due to its highly tunable bandgap. However, the experimental growth of high Bi content films has proven difficult. Here, we model GaAsBi film growth using a kinetic Monte Carlo simulation that explicitly takes cation and anion reactions into account. The unique behavior of Bi droplets is explored, and a sharp decrease in Bi content upon Bi droplet formation is demonstrated. The high mobility of simulated Bi droplets on GaAsBi surfaces is shown to produce phase separated Ga-Bi droplets as well as depressions on the film surface. A phase diagram for a range of growth rates that predicts both Bi content and droplet formation is presented to guide the experimental growth of high Bi content GaAsBi films.

  10. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  11. Leptogenesis in minimal predictive seesaw models

    Science.gov (United States)

    Björkeroth, Fredrik; de Anda, Francisco J.; de Medeiros Varzielas, Ivo; King, Stephen F.

    2015-10-01

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to ( ν e , ν μ , ν τ ) proportional to (0, 1, 1) and (1, n, n - 2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A 4 vacuum alignment provides the required Yukawa structures with n = 3, while a {{Z}}_9 symmetry fixes the relatives phase to be a ninth root of unity.

  12. Increased Motor Activity During REM Sleep Is Linked with Dopamine Function in Idiopathic REM Sleep Behavior Disorder and Parkinson Disease

    DEFF Research Database (Denmark)

    Zoetmulder, Marielle; Nikolic, Miki; Biernat, Heidi B

    2016-01-01

    STUDY OBJECTIVES: Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by impaired motor inhibition during REM sleep, and dream-enacting behavior. RBD is especially associated with α-synucleinopathies, such as Parkinson disease (PD). Follow-up studies have shown...... that patients with idiopathic RBD (iRBD) have an increased risk of developing an α-synucleinopathy in later life. Although abundant studies have shown that degeneration of the nigrostriatal dopaminergic system is associated with daytime motor function in Parkinson disease, only few studies have investigated......-FP-CIT uptake in the putamen. In PD patients, EMG-activity was correlated to anti-Parkinson medication. CONCLUSIONS: Our results support the hypothesis that increased EMG-activity during REM sleep is at least partly linked to the nigrostriatal dopamine system in iRBD, and with dopamine function in PD....

  13. Increased Motor Activity During REM Sleep Is Linked with Dopamine Function in Idiopathic REM Sleep Behaviour Disorder and Parkinson Disease

    DEFF Research Database (Denmark)

    Zoetmulder, Marielle; Nikolic, Miki; Biernat, Heidi

    2016-01-01

    STUDY OBJECTIVES: Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by impaired motor inhibition during REM sleep, and dream-enacting behavior. RBD is especially associated with α-synucleinopathies, such as Parkinson disease (PD). Follow-up studies have shown...... that patients with idiopathic RBD (iRBD) have an increased risk of developing an α-synucleinopathy in later life. Although abundant studies have shown that degeneration of the nigrostriatal dopaminergic system is associated with daytime motor function in Parkinson disease, only few studies have investigated...... in the putamen. In PD patients, EMG-activity was correlated to anti-Parkinson medication. CONCLUSIONS: Our results support the hypothesis that increased EMG-activity during REM sleep is at least partly linked to the nigrostriatal dopamine system in iRBD, and with dopamine function in PD....

  14. Detection and removal of ocular artifacts from EEG signals for an automated REM sleep analysis.

    Science.gov (United States)

    Betta, Monica; Gemignani, Angelo; Landi, Alberto; Laurino, Marco; Piaggi, Paolo; Menicucci, Danilo

    2013-01-01

    Rapid eye movements (REMs) are a prominent feature of REM sleep, and their distribution and time density over the night represent important physiological and clinical parameters. At the same time, REMs produce substantial distortions on the electroencephalographic (EEG) signals, which strongly affect the significance of normal REM sleep quantitative study. In this work a new procedure for a complete and automated analysis of REM sleep is proposed, which includes both a REMs detection algorithm and an ocular artifact removal system. The two steps, based respectively on Wavelet Transform and adaptive filtering, are fully integrated and their performance is evaluated using REM simulated signals. Thanks to the integration with the detection algorithm, the proposed artifact removal system shows an enhanced accuracy in the recovering of the true EEG signal, compared to a system based on the adaptive filtering only. Finally the artifact removal system is applied to physiological data and an estimation of the actual distortion induced by REMs on EEG signals is supplied.

  15. The Neurobiological Mechanisms and Treatments of REM Sleep Disturbances in Depression.

    Science.gov (United States)

    Wang, Yi-Qun; Li, Rui; Zhang, Meng-Qi; Zhang, Ze; Qu, Wei-Min; Huang, Zhi-Li

    2015-01-01

    Most depressed patients suffer from sleep abnormalities, which are one of the critical symptoms of depression. They are robust risk factors for the initiation and development of depression. Studies about sleep electroencephalograms have shown characteristic changes in depression such as reductions in non-rapid eye movement sleep production, disruptions of sleep continuity and disinhibition of rapid eye movement (REM) sleep. REM sleep alterations include a decrease in REM sleep latency, an increase in REM sleep duration and REM sleep density with respect to depressive episodes. Emotional brain processing dependent on the normal sleep-wake regulation seems to be failed in depression, which also promotes the development of clinical depression. Also, REM sleep alterations have been considered as biomarkers of depression. The disturbances of norepinephrine and serotonin systems may contribute to REM sleep abnormalities in depression. Lastly, this review also discusses the effects of different antidepressants on REM sleep disturbances in depression.

  16. Comparing model predictions for ecosystem-based management

    DEFF Research Database (Denmark)

    Jacobsen, Nis Sand; Essington, Timothy E.; Andersen, Ken Haste

    2016-01-01

    Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (Ew......E)) and a size-structured fish community model. The models were compared with respect to predicted ecological consequences of fishing to identify commonalities and differences in model predictions for the California Current fish community. We compared the models regarding direct and indirect responses to fishing...... on one or more species. The size-based model predicted a higher fishing mortality needed to reach maximum sustainable yield than EwE for most species. The size-based model also predicted stronger top-down effects of predator removals than EwE. In contrast, EwE predicted stronger bottom-up effects...

  17. The hypocretins (orexins mediate the “phasic” components of REM sleep: A new hypothesis

    Directory of Open Access Journals (Sweden)

    Pablo Torterolo

    2014-03-01

    The hypocretinergic neurons are active during wakefulness in conjunction with the presence of motor activity that occurs during survival-related behaviors. These neurons decrease their firing rate during non-REM sleep; however there is still controversy upon the activity and role of these neurons during REM sleep. Hence, in the present report we conducted a critical review of the literature of the hypocretinergic system during REM sleep, and hypothesize a possible role of this system in the generation of REM sleep.

  18. Remaining Useful Lifetime (RUL - Probabilistic Predictive Model

    Directory of Open Access Journals (Sweden)

    Ephraim Suhir

    2011-01-01

    Full Text Available Reliability evaluations and assurances cannot be delayed until the device (system is fabricated and put into operation. Reliability of an electronic product should be conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications, by electrical, optical and mechanical measurements and testing; checked (screened during manufacturing (fabrication; and, if necessary and appropriate, maintained in the field during the product’s operation Simple and physically meaningful probabilistic predictive model is suggested for the evaluation of the remaining useful lifetime (RUL of an electronic device (system after an appreciable deviation from its normal operation conditions has been detected, and the increase in the failure rate and the change in the configuration of the wear-out portion of the bathtub has been assessed. The general concepts are illustrated by numerical examples. The model can be employed, along with other PHM forecasting and interfering tools and means, to evaluate and to maintain the high level of the reliability (probability of non-failure of a device (system at the operation stage of its lifetime.

  19. A Predictive Model of Geosynchronous Magnetopause Crossings

    CERN Document Server

    Dmitriev, A; Chao, J -K

    2013-01-01

    We have developed a model predicting whether or not the magnetopause crosses geosynchronous orbit at given location for given solar wind pressure Psw, Bz component of interplanetary magnetic field (IMF) and geomagnetic conditions characterized by 1-min SYM-H index. The model is based on more than 300 geosynchronous magnetopause crossings (GMCs) and about 6000 minutes when geosynchronous satellites of GOES and LANL series are located in the magnetosheath (so-called MSh intervals) in 1994 to 2001. Minimizing of the Psw required for GMCs and MSh intervals at various locations, Bz and SYM-H allows describing both an effect of magnetopause dawn-dusk asymmetry and saturation of Bz influence for very large southward IMF. The asymmetry is strong for large negative Bz and almost disappears when Bz is positive. We found that the larger amplitude of negative SYM-H the lower solar wind pressure is required for GMCs. We attribute this effect to a depletion of the dayside magnetic field by a storm-time intensification of t...

  20. Predictive modeling for EBPC in EBDW

    Science.gov (United States)

    Zimmermann, Rainer; Schulz, Martin; Hoppe, Wolfgang; Stock, Hans-Jürgen; Demmerle, Wolfgang; Zepka, Alex; Isoyan, Artak; Bomholt, Lars; Manakli, Serdar; Pain, Laurent

    2009-10-01

    We demonstrate a flow for e-beam proximity correction (EBPC) to e-beam direct write (EBDW) wafer manufacturing processes, demonstrating a solution that covers all steps from the generation of a test pattern for (experimental or virtual) measurement data creation, over e-beam model fitting, proximity effect correction (PEC), and verification of the results. We base our approach on a predictive, physical e-beam simulation tool, with the possibility to complement this with experimental data, and the goal of preparing the EBPC methods for the advent of high-volume EBDW tools. As an example, we apply and compare dose correction and geometric correction for low and high electron energies on 1D and 2D test patterns. In particular, we show some results of model-based geometric correction as it is typical for the optical case, but enhanced for the particularities of e-beam technology. The results are used to discuss PEC strategies, with respect to short and long range effects.

  1. The utility of respiratory inductance plethysmography in REM sleep scoring during multiple sleep latency testing.

    Science.gov (United States)

    Drakatos, Panagis; Higgins, Sean; Duncan, Iain; Bridle, Kate; Briscoe, Sam; Leschziner, Guy D; Kent, Brian D; Williams, Adrian J

    2016-08-01

    Rapid eye movement sleep (REM) presents with a characteristic erratic breathing pattern. We investigated the feasibility of using respiration, derived from respiratory inductance plethysmography (RIP), in conjunction with chin electromyography, electrocardiography and pulse oximetry to facilitate the identification of REM sleep (RespREM) during nocturnal polysomnography (NPSG) and Multiple Sleep Latency Testing (MSLT). The Cohen's weighted kappa for the presence of REM and its duration in 20 consecutive NPSGs, using RespREM and compared to the current guidelines, ranged between 0.74-0.93 and 0.68-0.73 respectively for 5 scorers. The respective intraclass correlation coefficients were above 0.89. In 97.7% of the Sleep-Onset-REM-Periods (SOREMPs) during 41 consecutive MSLTs with preserved RIP, the RespREM was present and in 46.6% it coincided with the REM onset, while in the majority of the remainder RespREM preceded conventional REM onset. The erratic breathing pattern during REM, derived from RIP, is present and easily recognisable during SOREMPs in the MSLTs and may serve as a useful adjunctive measurement in identifying REM sleep.

  2. Model for predicting mountain wave field uncertainties

    Science.gov (United States)

    Damiens, Florentin; Lott, François; Millet, Christophe; Plougonven, Riwal

    2017-04-01

    Studying the propagation of acoustic waves throughout troposphere requires knowledge of wind speed and temperature gradients from the ground up to about 10-20 km. Typical planetary boundary layers flows are known to present vertical low level shears that can interact with mountain waves, thereby triggering small-scale disturbances. Resolving these fluctuations for long-range propagation problems is, however, not feasible because of computer memory/time restrictions and thus, they need to be parameterized. When the disturbances are small enough, these fluctuations can be described by linear equations. Previous works by co-authors have shown that the critical layer dynamics that occur near the ground produces large horizontal flows and buoyancy disturbances that result in intense downslope winds and gravity wave breaking. While these phenomena manifest almost systematically for high Richardson numbers and when the boundary layer depth is relatively small compare to the mountain height, the process by which static stability affects downslope winds remains unclear. In the present work, new linear mountain gravity wave solutions are tested against numerical predictions obtained with the Weather Research and Forecasting (WRF) model. For Richardson numbers typically larger than unity, the mesoscale model is used to quantify the effect of neglected nonlinear terms on downslope winds and mountain wave patterns. At these regimes, the large downslope winds transport warm air, a so called "Foehn" effect than can impact sound propagation properties. The sensitivity of small-scale disturbances to Richardson number is quantified using two-dimensional spectral analysis. It is shown through a pilot study of subgrid scale fluctuations of boundary layer flows over realistic mountains that the cross-spectrum of mountain wave field is made up of the same components found in WRF simulations. The impact of each individual component on acoustic wave propagation is discussed in terms of

  3. Characteristic comparison of triglyceride-rich remnant lipoprotein measurement between a new homogenous assay (RemL-C and a conventional immunoseparation method (RLP-C

    Directory of Open Access Journals (Sweden)

    Saikawa Shinichi

    2008-05-01

    Full Text Available Abstract Background Increased serum remnant lipoproteins are supposed to predict cardiovascular disease in addition to increased LDL. A new homogenous assay for remnant lipoprotein-cholesterol (RemL-C has been developed as an alternative to remnant-like particle-cholesterol (RLP-C, an immunoseparation assay, widely used for the measurement of remnant lipoprotein cholesterol. Methods We evaluated the correlations and data validation between the 2 assays in 83 subjects (49 men and 34 women without diabetes, hypertension and medications for hyperlipidemia, diabetes, and hypertension, and investigated the characteristics of remnant lipoproteins obtained by the two methods (RLP-C and RemL-C and their relationships with IDL-cholesterol determined by our developed HPLC method. Results A positive correlation was significantly found between the two methods (r = 0.853, 95%CI 0.781–0.903, p RLP-C level. RemL-C (r = 0.339, 95%CI 0.152–0.903; p = 0.0005 significantly correlated with IDL-cholesterol, but not RLP-C (r = 0.17, 95%CI -0.047–0.372; p = 0.1237 in all the samples (n = 83. Conclusion These results suggest that there is generally a significant correlation between RemL-C and RLP-C. However, RemL-C assay is likely to reflect IDL more closely than RLP-C.

  4. Video analysis of motor events in REM sleep behavior disorder.

    Science.gov (United States)

    Frauscher, Birgit; Gschliesser, Viola; Brandauer, Elisabeth; Ulmer, Hanno; Peralta, Cecilia M; Müller, Jörg; Poewe, Werner; Högl, Birgit

    2007-07-30

    In REM sleep behavior disorder (RBD), several studies focused on electromyographic characterization of motor activity, whereas video analysis has remained more general. The aim of this study was to undertake a detailed and systematic video analysis. Nine polysomnographic records from 5 Parkinson patients with RBD were analyzed and compared with sex- and age-matched controls. Each motor event in the video during REM sleep was classified according to duration, type of movement, and topographical distribution. In RBD, a mean of 54 +/- 23.2 events/10 minutes of REM sleep (total 1392) were identified and visually analyzed. Seventy-five percent of all motor events lasted <2 seconds. Of these events, 1,155 (83.0%) were classified as elementary, 188 (13.5%) as complex behaviors, 50 (3.6%) as violent, and 146 (10.5%) as vocalizations. In the control group, 3.6 +/- 2.3 events/10 minutes (total 264) of predominantly elementary simple character (n = 240, 90.9%) were identified. Number and types of motor events differed significantly between patients and controls (P < 0.05). This study shows a very high number and great variety of motor events during REM sleep in symptomatic RBD. However, most motor events are minor, and violent episodes represent only a small fraction.

  5. Environmental risk factors for REM sleep behavior disorder

    DEFF Research Database (Denmark)

    Postuma, R B; Montplaisir, J Y; Pelletier, A

    2012-01-01

    Idiopathic REM sleep behavior disorder is a parasomnia characterized by dream enactment and is commonly a prediagnostic sign of parkinsonism and dementia. Since risk factors have not been defined, we initiated a multicenter case-control study to assess environmental and lifestyle risk factors...

  6. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  7. RFI modeling and prediction approach for SATOP applications: RFI prediction models

    Science.gov (United States)

    Nguyen, Tien M.; Tran, Hien T.; Wang, Zhonghai; Coons, Amanda; Nguyen, Charles C.; Lane, Steven A.; Pham, Khanh D.; Chen, Genshe; Wang, Gang

    2016-05-01

    This paper describes a technical approach for the development of RFI prediction models using carrier synchronization loop when calculating Bit or Carrier SNR degradation due to interferences for (i) detecting narrow-band and wideband RFI signals, and (ii) estimating and predicting the behavior of the RFI signals. The paper presents analytical and simulation models and provides both analytical and simulation results on the performance of USB (Unified S-Band) waveforms in the presence of narrow-band and wideband RFI signals. The models presented in this paper will allow the future USB command systems to detect the RFI presence, estimate the RFI characteristics and predict the RFI behavior in real-time for accurate assessment of the impacts of RFI on the command Bit Error Rate (BER) performance. The command BER degradation model presented in this paper also allows the ground system operator to estimate the optimum transmitted SNR to maintain a required command BER level in the presence of both friendly and un-friendly RFI sources.

  8. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to unders

  9. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  10. Predictability of the Indian Ocean Dipole in the coupled models

    Science.gov (United States)

    Liu, Huafeng; Tang, Youmin; Chen, Dake; Lian, Tao

    2017-03-01

    In this study, the Indian Ocean Dipole (IOD) predictability, measured by the Indian Dipole Mode Index (DMI), is comprehensively examined at the seasonal time scale, including its actual prediction skill and potential predictability, using the ENSEMBLES multiple model ensembles and the recently developed information-based theoretical framework of predictability. It was found that all model predictions have useful skill, which is normally defined by the anomaly correlation coefficient larger than 0.5, only at around 2-3 month leads. This is mainly because there are more false alarms in predictions as leading time increases. The DMI predictability has significant seasonal variation, and the predictions whose target seasons are boreal summer (JJA) and autumn (SON) are more reliable than that for other seasons. All of models fail to predict the IOD onset before May and suffer from the winter (DJF) predictability barrier. The potential predictability study indicates that, with the model development and initialization improvement, the prediction of IOD onset is likely to be improved but the winter barrier cannot be overcome. The IOD predictability also has decadal variation, with a high skill during the 1960s and the early 1990s, and a low skill during the early 1970s and early 1980s, which is very consistent with the potential predictability. The main factors controlling the IOD predictability, including its seasonal and decadal variations, are also analyzed in this study.

  11. Time trends and periodic cycles in REM sleep eye movements.

    Science.gov (United States)

    Krynicki, V

    1975-11-01

    Eye movements during REM sleep episodes were tabulated in 16 young adults. REM episodes were then broken down into four ranges according to length in min: (1) 11.0-21.3; (2) 21.7-29.7; (3) 30.0-42.3; (4) 42.7 or longer. These data were then analyzed for linear and quadratic trends. Eight episodes had a significant linear trend, 10 had a significant quadratic trend, 7 had both linear and quadratic trends, while 12 had no trend. The residuals from the best-fitting polynomial curve were then subject to a spectral analysis. In addition, 2 long periods of pre-sleep wakefulness (approximately 2 h each) were also analyzed. In general, the spectral analysis revealed the dominant presence of a slow cycle (period of 10 min to about 30 min) the exact period of which varied according to the length of the REM episode. A binomial probability test indicated that the presence of slow cycles was significant in REM episodes except for those in the 21-30 min range. For the episodes of wakefulness, a dominant slow cycle was found in both cases. The results give the impression of similarity in the periodic organization of eye movements during REM sleep and waking. The data also indicated that an ultradian (70-150 min) cycle was present in eye movements during sleep and waking. Further, the finding of a decrease in eye movements before sleep onset, coupled with previous reports of an increase in eye movement after sleep onset, indicate the presence of a circadian cycle.

  12. Optical and near-infrared photometric monitoring of the transient X-ray binary A0538-66 with REM

    Science.gov (United States)

    Ducci, L.; Covino, S.; Doroshenko, V.; Mereghetti, S.; Santangelo, A.; Sasaki, M.

    2016-11-01

    The transient Be/X-ray binary A0538-66 shows peculiar X-ray and optical variability. Despite numerous studies, the intrinsic properties underlying its anomalous behaviour remain poorly understood. Since September 2014 we have conducted the first quasi-simultaneous, optical and near-infrared photometric monitoring of A0538-66 in seven filters with the Rapid Eye Mount (REM) telescope to understand the properties of this binary system. We found that the REM light curves show fast flares lasting one or two days that repeat almost regularly every 16.6 d, which is the orbital period of the neutron star. If the optical flares are powered by X-ray outbursts through photon reprocessing, the REM light curves indicate that A0538-66 is still active in X-rays; bright X-ray flares (Lx ≳ 1037 erg s-1) could be observable during the periastron passages. The REM light curves show a long-term variability that is especially pronounced in the g-band and decreases with increasing wavelength until it no longer appears in the near-infrared light curves. In addition, A0538-66 is fainter with respect to previous optical observations, and this is likely because of the higher absorption of the stellar radiation of a denser circumstellar disc. On the basis of the current models, we interpret these observational results with a circumstellar disc around the Be star observed nearly edge-on during a partial depletion phase. The REM light curves also show short-term variability on timescales of 1 day, which is possibly indicative of perturbations in the density distribution of the circumstellar disc caused by the tidal interaction with the neutron star.

  13. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  14. Leptogenesis in minimal predictive seesaw models

    Energy Technology Data Exchange (ETDEWEB)

    Björkeroth, Fredrik [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom); Anda, Francisco J. de [Departamento de Física, CUCEI, Universidad de Guadalajara,Guadalajara (Mexico); Varzielas, Ivo de Medeiros; King, Stephen F. [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom)

    2015-10-15

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the “atmospheric” and “solar” neutrino masses with Yukawa couplings to (ν{sub e},ν{sub μ},ν{sub τ}) proportional to (0,1,1) and (1,n,n−2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A{sub 4} vacuum alignment provides the required Yukawa structures with n=3, while a ℤ{sub 9} symmetry fixes the relatives phase to be a ninth root of unity.

  15. QSPR Models for Octane Number Prediction

    Directory of Open Access Journals (Sweden)

    Jabir H. Al-Fahemi

    2014-01-01

    Full Text Available Quantitative structure-property relationship (QSPR is performed as a means to predict octane number of hydrocarbons via correlating properties to parameters calculated from molecular structure; such parameters are molecular mass M, hydration energy EH, boiling point BP, octanol/water distribution coefficient logP, molar refractivity MR, critical pressure CP, critical volume CV, and critical temperature CT. Principal component analysis (PCA and multiple linear regression technique (MLR were performed to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The results of PCA explain the interrelationships between octane number and different variables. Correlation coefficients were calculated using M.S. Excel to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The data set was split into training of 40 hydrocarbons and validation set of 25 hydrocarbons. The linear relationship between the selected descriptors and the octane number has coefficient of determination (R2=0.932, statistical significance (F=53.21, and standard errors (s =7.7. The obtained QSPR model was applied on the validation set of octane number for hydrocarbons giving RCV2=0.942 and s=6.328.

  16. Increases in cAMP, MAPK activity, and CREB phosphorylation during REM sleep: implications for REM sleep and memory consolidation.

    Science.gov (United States)

    Luo, Jie; Phan, Trongha X; Yang, Yimei; Garelick, Michael G; Storm, Daniel R

    2013-04-10

    The cyclic adenosine monophosphate (cAMP), mitogen-activated protein kinase (MAPK), and cAMP response element-binding protein (CREB) transcriptional pathway is required for consolidation of hippocampus-dependent memory. In mice, this pathway undergoes a circadian oscillation required for memory persistence that reaches a peak during the daytime. Because mice exhibit polyphasic sleep patterns during the day, this suggested the interesting possibility that cAMP, MAPK activity, and CREB phosphorylation may be elevated during sleep. Here, we report that cAMP, phospho-p44/42 MAPK, and phospho-CREB are higher in rapid eye movement (REM) sleep compared with awake mice but are not elevated in non-REM sleep. This peak of activity during REM sleep does not occur in mice lacking calmodulin-stimulated adenylyl cyclases, a mouse strain that learns but cannot consolidate hippocampus-dependent memory. We conclude that a preferential increase in cAMP, MAPK activity, and CREB phosphorylation during REM sleep may contribute to hippocampus-dependent memory consolidation.

  17. Predictability in models of the atmospheric circulation.

    NARCIS (Netherlands)

    Houtekamer, P.L.

    1992-01-01

    It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error are. The

  18. Levels of Interference in Long and Short-Term Memory Differentially Modulate Non-REM and REM Sleep.

    Science.gov (United States)

    Fraize, Nicolas; Carponcy, Julien; Joseph, Mickaël Antoine; Comte, Jean-Christophe; Luppi, Pierre-Hervé; Libourel, Paul-Antoine; Salin, Paul-Antoine; Malleret, Gaël; Parmentier, Régis

    2016-12-01

    It is commonly accepted that sleep is beneficial to memory processes, but it is still unclear if this benefit originates from improved memory consolidation or enhanced information processing. It has thus been proposed that sleep may also promote forgetting of undesirable and non-essential memories, a process required for optimization of cognitive resources. We tested the hypothesis that non-rapid eye movement sleep (NREMS) promotes forgetting of irrelevant information, more specifically when processing information in working memory (WM), while REM sleep (REMS) facilitates the consolidation of important information. We recorded sleep patterns of rats trained in a radial maze in three different tasks engaging either the long-term or short-term storage of information, as well as a gradual level of interference. We observed a transient increase in REMS amount on the day the animal learned the rule of a long-term/reference memory task (RM), and, in contrast, a positive correlation between the performance of rats trained in a WM task involving an important processing of interference and the amount of NREMS or slow wave activity. Various oscillatory events were also differentially modulated by the type of training involved. Notably, NREMS spindles and REMS rapid theta increase with RM training, while sharp-wave ripples increase with all types of training. These results suggest that REMS, but also rapid oscillations occurring during NREMS would be specifically implicated in the long-term memory in RM, whereas NREMS and slow oscillations could be involved in the forgetting of irrelevant information required for WM.

  19. Evaluating the evidence surrounding pontine cholinergic involvement in REM sleep generation

    Directory of Open Access Journals (Sweden)

    Kevin P Grace

    2015-09-01

    Full Text Available Rapid eye movement (REM sleep - characterized by vivid dreaming, motor paralysis, and heightened neural activity - is one of the fundamental states of the mammalian central nervous system. Initial theories of rapid eye movement (REM sleep generation posited that induction of the state required activation of the ‘pontine REM sleep generator’ by cholinergic inputs. Here we review and evaluate the evidence surrounding cholinergic involvement in REM sleep generation. We submit that: (i the capacity of pontine cholinergic neurotransmission to generate REM sleep has been firmly established by gain-of-function experiments, (ii the function of endogenous cholinergic input to REM sleep generating sites cannot be determined by gain-of-function experiments; rather, loss-of-function studies are required, (iii loss-of-function studies show that endogenous cholinergic input to the PFT is not required for REM sleep generation, and (iv Cholinergic input to the pontine REM sleep generating sites serve an accessory role in REM sleep generation: reinforcing non-REM-to-REM sleep transitions making them quicker and less likely to fail.

  20. Evaluating the Evidence Surrounding Pontine Cholinergic Involvement in REM Sleep Generation.

    Science.gov (United States)

    Grace, Kevin P; Horner, Richard L

    2015-01-01

    Rapid eye movement (REM) sleep - characterized by vivid dreaming, motor paralysis, and heightened neural activity - is one of the fundamental states of the mammalian central nervous system. Initial theories of REM sleep generation posited that induction of the state required activation of the "pontine REM sleep generator" by cholinergic inputs. Here, we review and evaluate the evidence surrounding cholinergic involvement in REM sleep generation. We submit that: (i) the capacity of pontine cholinergic neurotransmission to generate REM sleep has been firmly established by gain-of-function experiments, (ii) the function of endogenous cholinergic input to REM sleep generating sites cannot be determined by gain-of-function experiments; rather, loss-of-function studies are required, (iii) loss-of-function studies show that endogenous cholinergic input to the PTF is not required for REM sleep generation, and (iv) cholinergic input to the pontine REM sleep generating sites serve an accessory role in REM sleep generation: reinforcing non-REM-to-REM sleep transitions making them quicker and less likely to fail.

  1. Allostasis: a model of predictive regulation.

    Science.gov (United States)

    Sterling, Peter

    2012-04-12

    The premise of the standard regulatory model, "homeostasis", is flawed: the goal of regulation is not to preserve constancy of the internal milieu. Rather, it is to continually adjust the milieu to promote survival and reproduction. Regulatory mechanisms need to be efficient, but homeostasis (error-correction by feedback) is inherently inefficient. Thus, although feedbacks are certainly ubiquitous, they could not possibly serve as the primary regulatory mechanism. A newer model, "allostasis", proposes that efficient regulation requires anticipating needs and preparing to satisfy them before they arise. The advantages: (i) errors are reduced in magnitude and frequency; (ii) response capacities of different components are matched -- to prevent bottlenecks and reduce safety factors; (iii) resources are shared between systems to minimize reserve capacities; (iv) errors are remembered and used to reduce future errors. This regulatory strategy requires a dedicated organ, the brain. The brain tracks multitudinous variables and integrates their values with prior knowledge to predict needs and set priorities. The brain coordinates effectors to mobilize resources from modest bodily stores and enforces a system of flexible trade-offs: from each organ according to its ability, to each organ according to its need. The brain also helps regulate the internal milieu by governing anticipatory behavior. Thus, an animal conserves energy by moving to a warmer place - before it cools, and it conserves salt and water by moving to a cooler one before it sweats. The behavioral strategy requires continuously updating a set of specific "shopping lists" that document the growing need for each key component (warmth, food, salt, water). These appetites funnel into a common pathway that employs a "stick" to drive the organism toward filling the need, plus a "carrot" to relax the organism when the need is satisfied. The stick corresponds broadly to the sense of anxiety, and the carrot broadly to

  2. Required Collaborative Work in Online Courses: A Predictive Modeling Approach

    Science.gov (United States)

    Smith, Marlene A.; Kellogg, Deborah L.

    2015-01-01

    This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…

  3. A prediction model for assessing residential radon concentration in Switzerland

    NARCIS (Netherlands)

    Hauri, D.D.; Huss, A.; Zimmermann, F.; Kuehni, C.E.; Roosli, M.

    2012-01-01

    Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the

  4. Distributional Analysis for Model Predictive Deferrable Load Control

    OpenAIRE

    Chen, Niangjun; Gan, Lingwen; Low, Steven H.; Wierman, Adam

    2014-01-01

    Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In ...

  5. Prediction for Major Adverse Outcomes in Cardiac Surgery: Comparison of Three Prediction Models

    Directory of Open Access Journals (Sweden)

    Cheng-Hung Hsieh

    2007-09-01

    Conclusion: The Parsonnet score performed as well as the logistic regression models in predicting major adverse outcomes. The Parsonnet score appears to be a very suitable model for clinicians to use in risk stratification of cardiac surgery.

  6. REM sleep diversity following the pedunculopontine tegmental nucleus lesion in rat.

    Science.gov (United States)

    Petrovic, Jelena; Lazic, Katarina; Kalauzi, Aleksandar; Saponjic, Jasna

    2014-09-01

    The aim of this study was to demonstrate that two REM clusters, which emerge following bilateral pedunculopontine tegmental nucleus (PPT) lesions in rats, are two functionally distinct REM states. We performed the experiments in Wistar rats, chronically instrumented for sleep recording. Bilateral PPT lesions were produced by the microinfusion of 100 nl of 0.1M ibotenic acid (IBO). Following a recovery period of 2 weeks, we recorded their sleep for 6h. Bilateral PPT lesions were identified by NADPH - diaphorase histochemistry. We applied Fourier analysis to the signals acquired throughout the 6h recordings, and each 10s epoch was differentiated as a Wake, NREM or REM state. We analyzed the topography of the sleep/wake states architecture and their transition structure, their all state-related EEG microstructures, and the sensorimotor (SMCx) and motor (MCx) cortex REM related cortico-muscular coherences (CMCs). Bilateral PPT lesion in rats increased the likelihood of the emergence of two distinct REM sleep states, specifically expressed within the MCx: REM1 and REM2. Bilateral PPT lesion did not change the sleep/wake states architecture of the SMCx, but pathologically increased the duration of REM1 within the MCx, alongside increasing Wake/REM1/Wake and NREM/REM2/NREM transitions within both cortices. In addition, the augmented total REM SMCx EEG beta amplitude and REM1 MCx EEG theta amplitude was the underlying EEG microstructure pathology. PPT lesion induced REM1 and REM2 are differential states with regard to total EMG power, topographically distinct EEG microstructures, and locomotor drives to nuchal musculature.

  7. On hydrological model complexity, its geometrical interpretations and prediction uncertainty

    NARCIS (Netherlands)

    Arkesteijn, E.C.M.M.; Pande, S.

    2013-01-01

    Knowledge of hydrological model complexity can aid selection of an optimal prediction model out of a set of available models. Optimal model selection is formalized as selection of the least complex model out of a subset of models that have lower empirical risk. This may be considered equivalent to

  8. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara

    2017-01-01

    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...

  9. Predictive modeling of dental pain using neural network.

    Science.gov (United States)

    Kim, Eun Yeob; Lim, Kun Ok; Rhee, Hyun Sill

    2009-01-01

    The mouth is a part of the body for ingesting food that is the most basic foundation and important part. The dental pain predicted by the neural network model. As a result of making a predictive modeling, the fitness of the predictive modeling of dental pain factors was 80.0%. As for the people who are likely to experience dental pain predicted by the neural network model, preventive measures including proper eating habits, education on oral hygiene, and stress release must precede any dental treatment.

  10. Unilateral hemidiaphragm weakness is associated with positional hypoxemia in REM sleep.

    Science.gov (United States)

    Baltzan, Marcel A; Scott, Adrienne S; Wolkove, Norman

    2012-02-15

    Patients with unilateral diaphragmatic paralysis (UDP) have been reported to have varied respiratory symptoms and often reduced lung function. We sought to describe the polysomnographic respiratory characteristics in patients with UDP without obstructive sleep apnea. We prospectively collected 5 cases with clinical investigation regarding symptoms, lung function, and nocturnal polysomnography. The respiratory sleep characteristics were analyzed with standardized scoring of respiratory events in 30-sec epochs and comparison according to sleep-wake stages and body position with respect to oximetry. The cases were compared to 5 controls matched for age, gender, and body mass index. Three of 5 patients had significant awake lung restriction with a mean (range) forced vital capacity of 1.89 (1.48-2.24) liters, 72% (45% to 102%) predicted. All had REM sleep with few apneas and episodes of prolonged hypopneas characterized by important desaturation noted on oximetry. These desaturations were greatest during REM sleep when the patients slept supine with a mean (SD) saturation of 90.8% (4.5%) and minimum of 64% or on the side unaffected by UDP with a mean saturation of 87.8% (5.3%) and minimum of 67% (p sleep stages had few, if any significant desaturations and these events rarely occurred when the patient slept in the supine position. Saturation was lower in all sleep-wake stages and sleep positions compared to controls (p sleep with frequent desaturations.

  11. Prediction of peptide bonding affinity: kernel methods for nonlinear modeling

    CERN Document Server

    Bergeron, Charles; Sundling, C Matthew; Krein, Michael; Katt, Bill; Sukumar, Nagamani; Breneman, Curt M; Bennett, Kristin P

    2011-01-01

    This paper presents regression models obtained from a process of blind prediction of peptide binding affinity from provided descriptors for several distinct datasets as part of the 2006 Comparative Evaluation of Prediction Algorithms (COEPRA) contest. This paper finds that kernel partial least squares, a nonlinear partial least squares (PLS) algorithm, outperforms PLS, and that the incorporation of transferable atom equivalent features improves predictive capability.

  12. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  13. The Racial and Ethnic Microaggressions Scale (REMS): construction, reliability, and validity.

    Science.gov (United States)

    Nadal, Kevin L

    2011-10-01

    Racial microaggressions are subtle statements and behaviors that unconsciously communicate denigrating messages to people of color. In recent years, a theoretical taxonomy and subsequent qualitative studies have introduced the types of microaggressions that people of color experience. In the present study, college- and Internet-based samples of African Americans, Latina/os, Asian Americans, and multiracial participants (N = 661) were used to develop and validate the Racial and Ethnic Microaggression Scale (REMS). In Study 1, an exploratory principal-components analyses (n = 443) yielded a 6-factor model: (a) Assumptions of Inferiority, (b) Second-Class Citizen and Assumptions of Criminality, (c) Microinvalidations, (d) Exoticization/Assumptions of Similarity, (e) Environmental Microaggressions, and (f) Workplace and School Microaggressions, with a Cronbach's alpha of .912 for the overall model and subscales ranging from .783 to .873. In Study 2, a confirmatory factor analysis (n = 218) supported the 6-factor model with a Cronbach's alpha of .892. Further analyses indicate that the REMS is a valid measure of racial microaggressions, as evidenced by high correlations with existing measures of racism and participants' feedback. Future research directions and implications for practice are discussed.

  14. REM behaviour disorder detection associated with neurodegenerative diseases

    DEFF Research Database (Denmark)

    Kempfner, Jacob; Sorensen, Gertrud; Zoetmulder, Marielle

    2010-01-01

    Abnormal skeleton muscle activity during REM sleep is characterized as REM Behaviour Disorder (RBD), and may be an early marker for different neurodegenerative diseases. Early detection of RBD is therefore highly important, and in this ongoing study a semi-automatic method for RBD detection...... is proposed by analyzing the motor activity during sleep. Method: A total number of twelve patients have been involved in this study, six normal controls and six patients diagnosed with Parkinsons Disease (PD) with RBD. All subjects underwent at least one ambulant polysomnographic (PSG) recording. The sleep...... recordings were scored, according to the new sleep-scoring standard from the American Academy of Sleep Medicine, by two independent sleep specialists. A follow-up analysis of the scoring consensus between the two specialists has been conducted. Based on the agreement of the two manual scorings...

  15. REM Behaviour Disorder Detection Associated with Neurodegerative Diseases

    DEFF Research Database (Denmark)

    Kempfner, Jacob; Sørensen, Gertrud Laura; Zoetmulder, Marielle

    2010-01-01

    Abnormal skeleton muscle activity during REM sleep is characterized as REM Behaviour Disorder (RBD), and may be an early marker for different neurodegenerative diseases. Early detection of RBD is therefore highly important, and in this ongoing study a semi-automatic method for RBD detection...... is proposed by analyzing the motor activity during sleep. Method: A total number of twelve patients have been involved in this study, six normal controls and six patients diagnosed with Parkinsons Disease (PD) with RBD. All subjects underwent at least one ambulant polysomnographic (PSG) recording. The sleep...... recordings were scored, according to the new sleep-scoring standard from the American Academy of Sleep Medicine, by two independent sleep specialists. A follow-up analysis of the scoring consensus between the two specialists has been conducted. Based on the agreement of the two manual scorings...

  16. Prediction using patient comparison vs. modeling: a case study for mortality prediction.

    Science.gov (United States)

    Hoogendoorn, Mark; El Hassouni, Ali; Mok, Kwongyen; Ghassemi, Marzyeh; Szolovits, Peter

    2016-08-01

    Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients. We analyze and compare both approaches on the MIMIC-II ICU dataset to predict patient mortality and find that the patient similarity approach does not scale well and results in a less accurate model (AUC of 0.68) compared to the modeling approach (0.84). We also show that mortality can be predicted within a median of 72 hours.

  17. Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.;

    2016-01-01

    The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization...... problem. Moreover, to reduce the computation time and improve the controller's performance, a fuzzy predictive filter is introduced. With the purpose of testing the developed EMPC, a simulation controlling the temperature levels of an intelligent office building (PowerFlexHouse), with and without fuzzy...

  18. On the 90th Birthday of Rem Viktorovich Khokhlov

    Science.gov (United States)

    Makarov, V. A.

    2016-08-01

    July 15th 2016 marked the 90th birthday of Rem Viktorovich Khokhlov, a prominent Russian physicist, talented organiser of national and world science and higher education, rector of Lomonosov Moscow State University, vice-president of the USSR Academy of Sciences, founder and head of the Department of Wave Processes. He tragically died on 8 August 1977 trying to conquer the highest peak of the Pamir Mountains.

  19. Medical image of the week: alpha intrusion into REM sleep

    OpenAIRE

    Shetty S; Le T

    2015-01-01

    A 45-year-old woman with a past medical history of hypertension and chronic headaches was referred to the sleep laboratory for high clinical suspicion for sleep apnea based on a history of snoring, witnessed apnea and excessive daytime sleepiness. An overnight sleep study was performed. Images during N3 Sleep and REM sleep are shown (Figures 1 and 2). Alpha intrusion in delta sleep is seen in patients with fibromyalgia, depression, chronic fatigue syndrome, anxiety disorder, and primary sleep...

  20. Predictive modeling and reducing cyclic variability in autoignition engines

    Energy Technology Data Exchange (ETDEWEB)

    Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

    2016-08-30

    Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

  1. El trastorno de conducta del sueño rem

    Directory of Open Access Journals (Sweden)

    Alex Iranzo De Riquer, Dr.

    2013-05-01

    Full Text Available El trastorno de conducta durante el sueño REM (TCSR se caracteriza por conductas motoras vigorosas, pesadillas y ausencia de atonía muscular durante el sueño REM. Se debe a la disfunción directa o indirecta de las estructuras del tronco cerebral que regulan el sueño REM, especialmente el núcleo subceruleus. El TCSR puede ser idiopático o asociado a enfermedades neurológicas como la enfermedad de Parkinson (EP, la demencia con cuerpos de Lewy (DCL, la atrofia multisistémica (AMS y la narcolepsia. Los pacientes con la forma idiopática, especialmente los que tienen alterados el SPECT del transportador de la dopamina, la sonografía de la sustancia negra, los test de olfato y de la visión de colores, tienen un elevado riesgo de desarrollar la E P, DCL y AMS. El TCSR no debe considerarse como un simple trastorno del sueño, sino como una manifestación de una enfermedad neurológica. El clonazepam (0.25-4 mg y la melatonina (3-12 mg a la hora de acostarse mejoran los síntomas del TCSR pero no evitan, en la forma idiopática, la conversión a una enfermedad neurodegenerativa.

  2. Rare Case of Rapidly Worsening REM Sleep Induced Bradycardia

    Directory of Open Access Journals (Sweden)

    Ayyappa S. Duba

    2015-01-01

    Full Text Available Sinoatrial arrest also known as sinus pause occurs when sinoatrial node of the heart transiently ceases to generate the electrical impulse necessary for the myocardium to contract. It may last from 2.0 seconds to several minutes. Etiologies of sinoatrial arrest can be complex and heterogeneous. During rapid eye movement (REM sleep, sinus arrests unrelated to apnea or hypopnea are very rare and only a few cases have been reported. Here we report a case of 36-year-old male with no significant past medical history who presented to our hospital after a syncopal episode at night. Physical examination showed no cardiac or neurological abnormalities and initial EKG and neuroimaging were normal. Overnight telemonitor recorded several episodes of bradyarrhythmia with sinus arrest that progressively lengthened over time. Sleep study was done which confirmed that sinus arrests occurred more during REM sleep and are unrelated to apnea or hypopnea. Electrophysiology studies showed sinus nodal dysfunction with no junctional escape, subsequently a dual chamber pacemaker placed for rapidly worsening case of REM sleep induced bradycardia.

  3. Intelligent predictive model of ventilating capacity of imperial smelt furnace

    Institute of Scientific and Technical Information of China (English)

    唐朝晖; 胡燕瑜; 桂卫华; 吴敏

    2003-01-01

    In order to know the ventilating capacity of imperial smelt furnace (ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks(ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.

  4. A Prediction Model of the Capillary Pressure J-Function

    Science.gov (United States)

    Xu, W. S.; Luo, P. Y.; Sun, L.; Lin, N.

    2016-01-01

    The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative. PMID:27603701

  5. Adaptation of Predictive Models to PDA Hand-Held Devices

    Directory of Open Access Journals (Sweden)

    Lin, Edward J

    2008-01-01

    Full Text Available Prediction models using multiple logistic regression are appearing with increasing frequency in the medical literature. Problems associated with these models include the complexity of computations when applied in their pure form, and lack of availability at the bedside. Personal digital assistant (PDA hand-held devices equipped with spreadsheet software offer the clinician a readily available and easily applied means of applying predictive models at the bedside. The purposes of this article are to briefly review regression as a means of creating predictive models and to describe a method of choosing and adapting logistic regression models to emergency department (ED clinical practice.

  6. A model to predict the power output from wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

  7. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  8. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of new technologies

  9. Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

    Science.gov (United States)

    Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

    2016-01-01

    Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

  10. The Reciprocal Effects Model Revisited: Extending Its Reach to Gifted Students Attending Academically Selective Schools

    Science.gov (United States)

    Seaton, Marjorie; Marsh, Herbert W.; Parker, Philip D.; Craven, Rhonda G.; Yeung, Alexander S.

    2015-01-01

    The reciprocal effects model (REM) predicts a reciprocal relation between academic self-concept and academic achievement, whereby prior academic self-concept is associated with future gains in achievement, and prior achievement is related to subsequent academic self-concept. Although research in this area has been extensive, there has been a…

  11. Identification of the transmitter and receptor mechanisms responsible for REM sleep paralysis.

    Science.gov (United States)

    Brooks, Patricia L; Peever, John H

    2012-07-18

    During REM sleep the CNS is intensely active, but the skeletal motor system is paradoxically forced into a state of muscle paralysis. The mechanisms that trigger REM sleep paralysis are a matter of intense debate. Two competing theories argue that it is caused by either active inhibition or reduced excitation of somatic motoneuron activity. Here, we identify the transmitter and receptor mechanisms that function to silence skeletal muscles during REM sleep. We used behavioral, electrophysiological, receptor pharmacology and neuroanatomical approaches to determine how trigeminal motoneurons and masseter muscles are switched off during REM sleep in rats. We show that a powerful GABA and glycine drive triggers REM paralysis by switching off motoneuron activity. This drive inhibits motoneurons by targeting both metabotropic GABA(B) and ionotropic GABA(A)/glycine receptors. REM paralysis is only reversed when motoneurons are cut off from GABA(B), GABA(A) and glycine receptor-mediated inhibition. Neither metabotropic nor ionotropic receptor mechanisms alone are sufficient for generating REM paralysis. These results demonstrate that multiple receptor mechanisms trigger REM sleep paralysis. Breakdown in normal REM inhibition may underlie common sleep motor pathologies such as REM sleep behavior disorder.

  12. Post-learning REM sleep deprivation impairs long-term memory: reversal by acute nicotine treatment.

    Science.gov (United States)

    Aleisa, A M; Alzoubi, K H; Alkadhi, K A

    2011-07-15

    Rapid eye movement sleep deprivation (REM-SD) is associated with spatial learning and memory impairment. During REM-SD, an increase in nicotine consumption among habitual smokers and initiation of tobacco use by non-smokers have been reported. We have shown recently that nicotine treatment prevented learning and memory impairments associated with REM-SD. We now report the interactive effects of post-learning REM-SD and/or nicotine. The animals were first trained on the radial arm water maze (RAWM) task, then they were REM-sleep deprived using the modified multiple platform paradigm for 24h. During REM-SD period, the rats were injected with saline or nicotine (1mg/kg s.c. every 12h: a total of 3 injections). The animals were tested for long-term memory in the RAWM at the end of the REM-SD period. The 24h post-learning REM-SD significantly impaired long-term memory. However, nicotine treatment reversed the post-learning REM-SD-induced impairment of long-term memory. On the other hand, post-learning treatment of normal rats with nicotine for 24h enhanced long-term memory. These results indicate that post-learning acute nicotine treatment prevented the deleterious effect of REM-SD on cognitive abilities.

  13. Predicting Career Advancement with Structural Equation Modelling

    Science.gov (United States)

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  14. Predicting Career Advancement with Structural Equation Modelling

    Science.gov (United States)

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  15. Modeling and prediction of surgical procedure times

    NARCIS (Netherlands)

    P.S. Stepaniak (Pieter); C. Heij (Christiaan); G. de Vries (Guus)

    2009-01-01

    textabstractAccurate prediction of medical operation times is of crucial importance for cost efficient operation room planning in hospitals. This paper investigates the possible dependence of procedure times on surgeon factors like age, experience, gender, and team composition. The effect of these f

  16. Prediction Model of Sewing Technical Condition by Grey Neural Network

    Institute of Scientific and Technical Information of China (English)

    DONG Ying; FANG Fang; ZHANG Wei-yuan

    2007-01-01

    The grey system theory and the artificial neural network technology were applied to predict the sewing technical condition. The representative parameters, such as needle, stitch, were selected. Prediction model was established based on the different fabrics' mechanical properties that measured by KES instrument. Grey relevant degree analysis was applied to choose the input parameters of the neural network. The result showed that prediction model has good precision. The average relative error was 4.08% for needle and 4.25% for stitch.

  17. Active diagnosis of hybrid systems - A model predictive approach

    OpenAIRE

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeate...

  18. Evaluation of Fast-Time Wake Vortex Prediction Models

    Science.gov (United States)

    Proctor, Fred H.; Hamilton, David W.

    2009-01-01

    Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.

  19. Role of corticosterone on sleep homeostasis induced by REM sleep deprivation in rats.

    Directory of Open Access Journals (Sweden)

    Ricardo Borges Machado

    Full Text Available Sleep is regulated by humoral and homeostatic processes. If on one hand chronic elevation of stress hormones impair sleep, on the other hand, rapid eye movement (REM sleep deprivation induces elevation of glucocorticoids and time of REM sleep during the recovery period. In the present study we sought to examine whether manipulations of corticosterone levels during REM sleep deprivation would alter the subsequent sleep rebound. Adult male Wistar rats were fit with electrodes for sleep monitoring and submitted to four days of REM sleep deprivation under repeated corticosterone or metyrapone (an inhibitor of corticosterone synthesis administration. Sleep parameters were continuously recorded throughout the sleep deprivation period and during 3 days of sleep recovery. Plasma levels of adrenocorticotropic hormone and corticosterone were also evaluated. Metyrapone treatment prevented the elevation of corticosterone plasma levels induced by REM sleep deprivation, whereas corticosterone administration to REM sleep-deprived rats resulted in lower corticosterone levels than in non-sleep deprived rats. Nonetheless, both corticosterone and metyrapone administration led to several alterations on sleep homeostasis, including reductions in the amount of non-REM and REM sleep during the recovery period, although corticosterone increased delta activity (1.0-4.0 Hz during REM sleep deprivation. Metyrapone treatment of REM sleep-deprived rats reduced the number of REM sleep episodes. In conclusion, reduction of corticosterone levels during REM sleep deprivation resulted in impairment of sleep rebound, suggesting that physiological elevation of corticosterone levels resulting from REM sleep deprivation is necessary for plentiful recovery of sleep after this stressful event.

  20. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “any fall” and “recurrent falls.” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  1. Testing and analysis of internal hardwood log defect prediction models

    Science.gov (United States)

    R. Edward. Thomas

    2011-01-01

    The severity and location of internal defects determine the quality and value of lumber sawn from hardwood logs. Models have been developed to predict the size and position of internal defects based on external defect indicator measurements. These models were shown to predict approximately 80% of all internal knots based on external knot indicators. However, the size...

  2. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  3. Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode

  4. Refining the committee approach and uncertainty prediction in hydrological modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode

  5. Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode

  6. Refining the committee approach and uncertainty prediction in hydrological modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of mode

  7. The 'affect tagging and consolidation' (ATaC) model of depression vulnerability.

    Science.gov (United States)

    Harrington, Marcus O; Pennington, Kyla; Durrant, Simon J

    2017-02-15

    Since the 1960's polysomnographic sleep research has demonstrated that depressive episodes are associated with REM sleep alterations. Some of these alterations, such as increased REM sleep density, have also been observed in first-degree relatives of patients and remitted patients, suggesting that they may be vulnerability markers of major depressive disorder (MDD), rather than mere epiphenomena of the disorder. Neuroimaging studies have revealed that depression is also associated with heightened amygdala reactivity to negative emotional stimuli, which may also be a vulnerability marker for MDD. Several models have been developed to explain the respective roles of REM sleep alterations and negatively-biased amygdala activity in the pathology of MDD, however the possible interaction between these two potential risk-factors remains uncharted. This paper reviews the roles of the amygdala and REM sleep in the encoding and consolidation of negative emotional memories, respectively. We present our 'affect tagging and consolidation' (ATaC) model, which argues that increased REM sleep density and negatively-biased amygdala activity are two separate, genetically influenced risk-factors for depression which interact to promote the development of negative memory bias - a well-known cognitive vulnerability marker for depression. Predictions of the ATaC model may motivate research aimed at improving our understanding of sleep dependent memory consolidation in depression aetiology.

  8. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  9. Aerosol optical depth as observed by the Mars Science Laboratory REMS UV photodiodes

    Science.gov (United States)

    Smith, Michael D.; Zorzano, María-Paz; Lemmon, Mark; Martín-Torres, Javier; Mendaza de Cal, Teresa

    2016-12-01

    Systematic observations taken by the REMS UV photodiodes on a daily basis throughout the landed Mars Science Laboratory mission provide a highly useful tool for characterizing aerosols above Gale Crater. Radiative transfer modeling is used to model the approximately 1.75 Mars Years of observations taken to date taking into account multiple scattering from aerosols and the extended field of view of the REMS UV photodiodes. The retrievals show in detail the annual cycle of aerosol optical depth, which is punctuated with numerous short timescale events of increased optical depth. Dust deposition onto the photodiodes is accounted for by comparison with aerosol optical depth derived from direct imaging of the Sun by Mastcam. The effect of dust on the photodiodes is noticeable, but does not dominate the signal. Cleaning of dust from the photodiodes was observed in the season around Ls=270°, but not during other seasons. Systematic deviations in the residuals from the retrieval fit are indicative of changes in aerosol effective particle size, with larger particles present during periods of increased optical depth. This seasonal dependence of aerosol particle size is expected as dust activity injects larger particles into the air, while larger aerosols settle out of the atmosphere more quickly leading to a smaller average particle size over time.

  10. Aerosol Optical Depth as Observed by the Mars Science Laboratory REMS UV Photodiodes

    Science.gov (United States)

    Smith, M. D.; Zorzano, M.-P.; Lemmon, M.; Martin-Torres, J.; Mendaza de Cal, T.

    2017-01-01

    Systematic observations taken by the REMS UV photodiodes on a daily basis throughout the landed Mars Science Laboratory mission provide a highly useful tool for characterizing aerosols above Gale Crater. Radiative transfer modeling is used to model the approximately two Mars Years of observations taken to date taking into account multiple scattering from aerosols and the extended field of view of the REMS UV photodiodes. The retrievals show in detail the annual cycle of aerosol optical depth, which is punctuated with numerous short timescale events of increased optical depth. Dust deposition onto the photodiodes is accounted for by comparison with aerosol optical depth derived from direct imaging of the Sun by Mastcam. The effect of dust on the photodiodes is noticeable, but does not dominate the signal. Cleaning of dust from the photodiodes was observed in the season around Ls=270deg, but not during other seasons. Systematic deviations in the residuals from the retrieval fit are indicative of changes in aerosol effective particle size, with larger particles present during periods of increased optical depth. This seasonal dependence of aerosol particle size is expected as dust activity injects larger particles into the air, while larger aerosols settle out of the atmosphere more quickly leading to a smaller average particle size over time. A full description of these observations, the retrieval algorithm, and the results can be found in Smith et al. (2016).

  11. Impact of modellers' decisions on hydrological a priori predictions

    Science.gov (United States)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2014-06-01

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

  12. Econometric models for predicting confusion crop ratios

    Science.gov (United States)

    Umberger, D. E.; Proctor, M. H.; Clark, J. E.; Eisgruber, L. M.; Braschler, C. B. (Principal Investigator)

    1979-01-01

    Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.

  13. PEEX Modelling Platform for Seamless Environmental Prediction

    Science.gov (United States)

    Baklanov, Alexander; Mahura, Alexander; Arnold, Stephen; Makkonen, Risto; Petäjä, Tuukka; Kerminen, Veli-Matti; Lappalainen, Hanna K.; Ezau, Igor; Nuterman, Roman; Zhang, Wen; Penenko, Alexey; Gordov, Evgeny; Zilitinkevich, Sergej; Kulmala, Markku

    2017-04-01

    The Pan-Eurasian EXperiment (PEEX) is a multidisciplinary, multi-scale research programme stared in 2012 and aimed at resolving the major uncertainties in Earth System Science and global sustainability issues concerning the Arctic and boreal Northern Eurasian regions and in China. Such challenges include climate change, air quality, biodiversity loss, chemicalization, food supply, and the use of natural resources by mining, industry, energy production and transport. The research infrastructure introduces the current state of the art modeling platform and observation systems in the Pan-Eurasian region and presents the future baselines for the coherent and coordinated research infrastructures in the PEEX domain. The PEEX modeling Platform is characterized by a complex seamless integrated Earth System Modeling (ESM) approach, in combination with specific models of different processes and elements of the system, acting on different temporal and spatial scales. The ensemble approach is taken to the integration of modeling results from different models, participants and countries. PEEX utilizes the full potential of a hierarchy of models: scenario analysis, inverse modeling, and modeling based on measurement needs and processes. The models are validated and constrained by available in-situ and remote sensing data of various spatial and temporal scales using data assimilation and top-down modeling. The analyses of the anticipated large volumes of data produced by available models and sensors will be supported by a dedicated virtual research environment developed for these purposes.

  14. Models Predicting Success of Infertility Treatment: A Systematic Review

    Science.gov (United States)

    Zarinara, Alireza; Zeraati, Hojjat; Kamali, Koorosh; Mohammad, Kazem; Shahnazari, Parisa; Akhondi, Mohammad Mehdi

    2016-01-01

    Background: Infertile couples are faced with problems that affect their marital life. Infertility treatment is expensive and time consuming and occasionally isn’t simply possible. Prediction models for infertility treatment have been proposed and prediction of treatment success is a new field in infertility treatment. Because prediction of treatment success is a new need for infertile couples, this paper reviewed previous studies for catching a general concept in applicability of the models. Methods: This study was conducted as a systematic review at Avicenna Research Institute in 2015. Six data bases were searched based on WHO definitions and MESH key words. Papers about prediction models in infertility were evaluated. Results: Eighty one papers were eligible for the study. Papers covered years after 1986 and studies were designed retrospectively and prospectively. IVF prediction models have more shares in papers. Most common predictors were age, duration of infertility, ovarian and tubal problems. Conclusion: Prediction model can be clinically applied if the model can be statistically evaluated and has a good validation for treatment success. To achieve better results, the physician and the couples’ needs estimation for treatment success rate were based on history, the examination and clinical tests. Models must be checked for theoretical approach and appropriate validation. The privileges for applying the prediction models are the decrease in the cost and time, avoiding painful treatment of patients, assessment of treatment approach for physicians and decision making for health managers. The selection of the approach for designing and using these models is inevitable. PMID:27141461

  15. MULTI MODEL DATA MINING APPROACH FOR HEART FAILURE PREDICTION

    Directory of Open Access Journals (Sweden)

    Priyanka H U

    2016-09-01

    Full Text Available Developing predictive modelling solutions for risk estimation is extremely challenging in health-care informatics. Risk estimation involves integration of heterogeneous clinical sources having different representation from different health-care provider making the task increasingly complex. Such sources are typically voluminous, diverse, and significantly change over the time. Therefore, distributed and parallel computing tools collectively termed big data tools are in need which can synthesize and assist the physician to make right clinical decisions. In this work we propose multi-model predictive architecture, a novel approach for combining the predictive ability of multiple models for better prediction accuracy. We demonstrate the effectiveness and efficiency of the proposed work on data from Framingham Heart study. Results show that the proposed multi-model predictive architecture is able to provide better accuracy than best model approach. By modelling the error of predictive models we are able to choose sub set of models which yields accurate results. More information was modelled into system by multi-level mining which has resulted in enhanced predictive accuracy.

  16. The regional prediction model of PM10 concentrations for Turkey

    Science.gov (United States)

    Güler, Nevin; Güneri İşçi, Öznur

    2016-11-01

    This study is aimed to predict a regional model for weekly PM10 concentrations measured air pollution monitoring stations in Turkey. There are seven geographical regions in Turkey and numerous monitoring stations at each region. Predicting a model conventionally for each monitoring station requires a lot of labor and time and it may lead to degradation in quality of prediction when the number of measurements obtained from any õmonitoring station is small. Besides, prediction models obtained by this way only reflect the air pollutant behavior of a small area. This study uses Fuzzy C-Auto Regressive Model (FCARM) in order to find a prediction model to be reflected the regional behavior of weekly PM10 concentrations. The superiority of FCARM is to have the ability of considering simultaneously PM10 concentrations measured monitoring stations in the specified region. Besides, it also works even if the number of measurements obtained from the monitoring stations is different or small. In order to evaluate the performance of FCARM, FCARM is executed for all regions in Turkey and prediction results are compared to statistical Autoregressive (AR) Models predicted for each station separately. According to Mean Absolute Percentage Error (MAPE) criteria, it is observed that FCARM provides the better predictions with a less number of models.

  17. Gaussian mixture models as flux prediction method for central receivers

    Science.gov (United States)

    Grobler, Annemarie; Gauché, Paul; Smit, Willie

    2016-05-01

    Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.

  18. Nonlinear model predictive control of a packed distillation column

    Energy Technology Data Exchange (ETDEWEB)

    Patwardhan, A.A.; Edgar, T.F. (Univ. of Texas, Austin, TX (United States). Dept. of Chemical Engineering)

    1993-10-01

    A rigorous dynamic model based on fundamental chemical engineering principles was formulated for a packed distillation column separating a mixture of cyclohexane and n-heptane. This model was simplified to a form suitable for use in on-line model predictive control calculations. A packed distillation column was operated at several operating conditions to estimate two unknown model parameters in the rigorous and simplified models. The actual column response to step changes in the feed rate, distillate rate, and reboiler duty agreed well with dynamic model predictions. One unusual characteristic observed was that the packed column exhibited gain-sign changes, which are very difficult to treat using conventional linear feedback control. Nonlinear model predictive control was used to control the distillation column at an operating condition where the process gain changed sign. An on-line, nonlinear model-based scheme was used to estimate unknown/time-varying model parameters.

  19. Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant

    Institute of Scientific and Technical Information of China (English)

    CHEN Yue-hua; CAO Guang-yi; ZHU Xin-jian

    2007-01-01

    This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely.

  20. A burnout prediction model based around char morphology

    Energy Technology Data Exchange (ETDEWEB)

    T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre

    2005-07-01

    Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.

  1. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel;

    2006-01-01

    Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions...... day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results Our analyses show significant differences between predictions from different models......, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence-only approaches) and assumptions made by each...

  2. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan;

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re......-search of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset....... The conferred results show that the prediction errors can be decreased, while the computation time is reduced....

  3. Impaired extinction of fear conditioning after REM deprivation is magnified by rearing in an enriched environment.

    Science.gov (United States)

    Hunter, Amy Silvestri

    2015-07-01

    Evidence from both human and animal studies indicates that rapid eye movement sleep (REM) is essential for the acquisition and retention of information, particularly of an emotional nature. Learning and memory can also be impacted by manipulation of housing condition such as exposure to an enriched environment (EE). This study investigated the effects of REM deprivation and EE, both separately and combined, on the extinction of conditioned fear in rats. Consistent with prior studies, conditioning was enhanced in EE-reared rats and extinction was impaired in REM deprived rats. In addition, rats exposed to both REM deprivation and EE showed the greatest impairment in extinction, with effects persisting through the first two days of extinction training. This study is the first to explore the combination of REM deprivation and EE and suggests that manipulations that alter sleep, particularly REM, can have persisting deleterious effects on emotional memory processing.

  4. Improving Environmental Model Calibration and Prediction

    Science.gov (United States)

    2011-01-18

    groundwater model calibration. Adv. Water Resour., 29(4):605–623, 2006. [9] B.E. Skahill, J.S. Baggett, S. Frankenstein , and C.W. Downer. More efficient...of Hydrology, Environmental Modelling & Software, or Water Resources Research). Skahill, B., Baggett, J., Frankenstein , S., and Downer, C.W. (2009

  5. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    load shifting capabilities of the units that adapts to the given price predictions. We furthermore evaluated control performance in terms of economic savings for different control strategies and forecasts. Chapter 5 describes and compares the proposed large-scale Aggregator control strategies....... Aggregators are assumed to play an important role in the future Smart Grid and coordinate a large portfolio of units. The developed economic MPC controllers interfaces each unit directly to an Aggregator. We developed several MPC-based aggregation strategies that coordinates the global behavior of a portfolio...

  6. Combining logistic regression and neural networks to create predictive models.

    OpenAIRE

    Spackman, K. A.

    1992-01-01

    Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building wit...

  7. Assessment of performance of survival prediction models for cancer prognosis

    Directory of Open Access Journals (Sweden)

    Chen Hung-Chia

    2012-07-01

    Full Text Available Abstract Background Cancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient’s class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments. Methods We compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models. Results A public breast cancer dataset was used to compare several performance metrics using five prediction models. 1 For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2 The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3 Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results. Conclusions 1 Different performance metrics for evaluation of a survival prediction model may give different conclusions in

  8. Increased Motor Activity During REM Sleep Is Linked with Dopamine Function in Idiopathic REM Sleep Behavior Disorder and Parkinson Disease

    Science.gov (United States)

    Zoetmulder, Marielle; Nikolic, Miki; Biernat, Heidi; Korbo, Lise; Friberg, Lars; Jennum, Poul

    2016-01-01

    Study Objectives: Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by impaired motor inhibition during REM sleep, and dream-enacting behavior. RBD is especially associated with α-synucleinopathies, such as Parkinson disease (PD). Follow-up studies have shown that patients with idiopathic RBD (iRBD) have an increased risk of developing an α-synucleinopathy in later life. Although abundant studies have shown that degeneration of the nigrostriatal dopaminergic system is associated with daytime motor function in Parkinson disease, only few studies have investigated the relation between this system and electromyographic (EMG) activity during sleep. The objective of this study was to investigate the relationship between the nigrostriatal dopamine system and muscle activity during sleep in iRBD and PD. Methods: 10 iRBD patients, 10 PD patients with PD, 10 PD patients without RBD, and 10 healthy controls were included and assessed with (123)I-N-omega-fluoropropyl-2-beta-carboxymethoxy-3beta-(4-iodophenyl) nortropane ((123)I-FP-CIT) Single-photon emission computed tomography (SPECT) scanning (123I-FP-CIT SPECT), neurological examination, and polysomnography. Results: iRBD patients and PD patients with RBD had increased EMG-activity compared to healthy controls. 123I-FP-CIT uptake in the putamen-region was highest in controls, followed by iRBD patients, and lowest in PD patients. In iRBD patients, EMG-activity in the mentalis muscle was correlated to 123I-FP-CIT uptake in the putamen. In PD patients, EMG-activity was correlated to anti-Parkinson medication. Conclusions: Our results support the hypothesis that increased EMG-activity during REM sleep is at least partly linked to the nigrostriatal dopamine system in iRBD, and with dopamine function in PD. Citation: Zoetmulder M, Nikolic M, Biernat H, Korbo L, Friberg L, Jennum P. Increased motor activity during rem sleep is linked with dopamine function in idiopathic REM sleep behavior

  9. A thermodynamic model to predict wax formation in petroleum fluids

    Energy Technology Data Exchange (ETDEWEB)

    Coutinho, J.A.P. [Universidade de Aveiro (Portugal). Dept. de Quimica. Centro de Investigacao em Quimica]. E-mail: jcoutinho@dq.ua.pt; Pauly, J.; Daridon, J.L. [Universite de Pau et des Pays de l' Adour, Pau (France). Lab. des Fluides Complexes

    2001-12-01

    Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G{sup E} model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data. (author)

  10. A THERMODYNAMIC MODEL TO PREDICT WAX FORMATION IN PETROLEUM FLUIDS

    Directory of Open Access Journals (Sweden)

    J.A.P. Coutinho

    2001-12-01

    Full Text Available Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G E model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data.

  11. A systematic review of predictive modeling for bronchiolitis.

    Science.gov (United States)

    Luo, Gang; Nkoy, Flory L; Gesteland, Per H; Glasgow, Tiffany S; Stone, Bryan L

    2014-10-01

    Bronchiolitis is the most common cause of illness leading to hospitalization in young children. At present, many bronchiolitis management decisions are made subjectively, leading to significant practice variation among hospitals and physicians caring for children with bronchiolitis. To standardize care for bronchiolitis, researchers have proposed various models to predict the disease course to help determine a proper management plan. This paper reviews the existing state of the art of predictive modeling for bronchiolitis. Predictive modeling for respiratory syncytial virus (RSV) infection is covered whenever appropriate, as RSV accounts for about 70% of bronchiolitis cases. A systematic review was conducted through a PubMed search up to April 25, 2014. The literature on predictive modeling for bronchiolitis was retrieved using a comprehensive search query, which was developed through an iterative process. Search results were limited to human subjects, the English language, and children (birth to 18 years). The literature search returned 2312 references in total. After manual review, 168 of these references were determined to be relevant and are discussed in this paper. We identify several limitations and open problems in predictive modeling for bronchiolitis, and provide some preliminary thoughts on how to address them, with the hope to stimulate future research in this domain. Many problems remain open in predictive modeling for bronchiolitis. Future studies will need to address them to achieve optimal predictive models. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Climate predictability and prediction skill on seasonal time scales over South America from CHFP models

    Science.gov (United States)

    Osman, Marisol; Vera, C. S.

    2016-11-01

    This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to

  13. Predicting and Modelling of Survival Data when Cox's Regression Model does not hold

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...

  14. Pengembangan Ketahanan Keausan Pada Bahan Kampas Rem Sepeda Motor Dari Komposit Bonggol Jagung

    Directory of Open Access Journals (Sweden)

    Pramuko Ilmu Purboputro

    2016-08-01

    bahan kampas rem mempunyai nilai keausan yang paling rendah yaitu sebesar 0.00041mm2/kg , yang sedikit lebih besar dari produk di pasaran dengan keausan sebesar 0.00014 mm2/kg. Untuk Pengujian Keausan Ogoshi Kondisi basah dengan air, diperoleh bahwa, bahan kampas rem paling rendah keausannya yaitu sebesar 0,0062 mm2/kg, namun masih lebih tinggi sedikit dari bahan kampas rem pasaran (eksipart yaitu sebesar 0,0032 mm2/kg

  15. REMS: the environmental sensor suite for the Mars Science Laboratory rover

    OpenAIRE

    2012-01-01

    The Rover Environmental Monitoring Station (REMS) will investigate environ- mental factors directly tied to current habitability at the Martian surface during the Mars Sci- ence Laboratory (MSL) mission. Three major habitability factors are addressed by REMS: the thermal environment, ultraviolet irradiation, and water cycling. The thermal environment is determined by a mixture of processes, chief amongst these being the meteorological. Ac- cordingly, the REMS sensors have been ...

  16. Frequency of REM sleep behavior disorders in patients with Parkinson’s disease

    OpenAIRE

    Janković Marko; Svetel Marina; Kostić Vladimir

    2015-01-01

    Background/Aim. Sleep is prompted by natural cycles of activity in the brain and consists of two basic states: rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep. REM sleep behavior disorder (RBD) is characterized by violent motor and vocal behavior during REM sleep which represents dream enactment. The normal loss of muscle tone, with the exception of respiratory, sphincter, extra ocular and middle ear muscles, is absent in patients wit...

  17. Predictive error analysis for a water resource management model

    Science.gov (United States)

    Gallagher, Mark; Doherty, John

    2007-02-01

    SummaryIn calibrating a model, a set of parameters is assigned to the model which will be employed for the making of all future predictions. If these parameters are estimated through solution of an inverse problem, formulated to be properly posed through either pre-calibration or mathematical regularisation, then solution of this inverse problem will, of necessity, lead to a simplified parameter set that omits the details of reality, while still fitting historical data acceptably well. Furthermore, estimates of parameters so obtained will be contaminated by measurement noise. Both of these phenomena will lead to errors in predictions made by the model, with the potential for error increasing with the hydraulic property detail on which the prediction depends. Integrity of model usage demands that model predictions be accompanied by some estimate of the possible errors associated with them. The present paper applies theory developed in a previous work to the analysis of predictive error associated with a real world, water resource management model. The analysis offers many challenges, including the fact that the model is a complex one that was partly calibrated by hand. Nevertheless, it is typical of models which are commonly employed as the basis for the making of important decisions, and for which such an analysis must be made. The potential errors associated with point-based and averaged water level and creek inflow predictions are examined, together with the dependence of these errors on the amount of averaging involved. Error variances associated with predictions made by the existing model are compared with "optimized error variances" that could have been obtained had calibration been undertaken in such a way as to minimize predictive error variance. The contributions by different parameter types to the overall error variance of selected predictions are also examined.

  18. Models for short term malaria prediction in Sri Lanka

    Directory of Open Access Journals (Sweden)

    Galappaththy Gawrie NL

    2008-05-01

    Full Text Available Abstract Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed.

  19. Aggregate driver model to enable predictable behaviour

    Science.gov (United States)

    Chowdhury, A.; Chakravarty, T.; Banerjee, T.; Balamuralidhar, P.

    2015-09-01

    The categorization of driving styles, particularly in terms of aggressiveness and skill is an emerging area of interest under the broader theme of intelligent transportation. There are two possible discriminatory techniques that can be applied for such categorization; a microscale (event based) model and a macro-scale (aggregate) model. It is believed that an aggregate model will reveal many interesting aspects of human-machine interaction; for example, we may be able to understand the propensities of individuals to carry out a given task over longer periods of time. A useful driver model may include the adaptive capability of the human driver, aggregated as the individual propensity to control speed/acceleration. Towards that objective, we carried out experiments by deploying smartphone based application to be used for data collection by a group of drivers. Data is primarily being collected from GPS measurements including position & speed on a second-by-second basis, for a number of trips over a two months period. Analysing the data set, aggregate models for individual drivers were created and their natural aggressiveness were deduced. In this paper, we present the initial results for 12 drivers. It is shown that the higher order moments of the acceleration profile is an important parameter and identifier of journey quality. It is also observed that the Kurtosis of the acceleration profiles stores major information about the driving styles. Such an observation leads to two different ranking systems based on acceleration data. Such driving behaviour models can be integrated with vehicle and road model and used to generate behavioural model for real traffic scenario.

  20. Validating predictions from climate envelope models

    Science.gov (United States)

    Watling, J.; Bucklin, D.; Speroterra, C.; Brandt, L.; Cabal, C.; Romañach, Stephanie S.; Mazzotti, Frank J.

    2013-01-01

    Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

  1. Noncausal spatial prediction filtering based on an ARMA model

    Institute of Scientific and Technical Information of China (English)

    Liu Zhipeng; Chen Xiaohong; Li Jingye

    2009-01-01

    Conventional f-x prediction filtering methods are based on an autoregressive model. The error section is first computed as a source noise but is removed as additive noise to obtain the signal, which results in an assumption inconsistency before and after filtering. In this paper, an autoregressive, moving-average model is employed to avoid the model inconsistency. Based on the ARMA model, a noncasual prediction filter is computed and a self-deconvolved projection filter is used for estimating additive noise in order to suppress random noise. The 1-D ARMA model is also extended to the 2-D spatial domain, which is the basis for noncasual spatial prediction filtering for random noise attenuation on 3-D seismic data. Synthetic and field data processing indicate this method can suppress random noise more effectively and preserve the signal simultaneously and does much better than other conventional prediction filtering methods.

  2. Performance Predictable ServiceBSP Model for Grid Computing

    Institute of Scientific and Technical Information of China (English)

    TONG Weiqin; MIAO Weikai

    2007-01-01

    This paper proposes a performance prediction model for grid computing model ServiceBSP to support developing high quality applications in grid environment. In ServiceBSP model,the agents carrying computing tasks are dispatched to the local domain of the selected computation services. By using the IP (integer program) approach, the Service Selection Agent selects the computation services with global optimized QoS (quality of service) consideration. The performance of a ServiceBSP application can be predicted according to the performance prediction model based on the QoS of the selected services. The performance prediction model can help users to analyze their applications and improve them by optimized the factors which affects the performance. The experiment shows that the Service Selection Agent can provide ServiceBSP users with satisfied QoS of applications.

  3. Two Predictions of a Compound Cue Model of Priming

    OpenAIRE

    Walenski, Matthew

    2003-01-01

    This paper examines two predictions of the compound cue model of priming (Ratcliff and McKoon, 1988). While this model has been used to provide an account of a wide range of priming effects, it may not actually predict priming in these or other circumstances. In order to predict priming effects, the compound cue model relies on an assumption that all items have the same number of associates. This assumption may be true in only a restricted number of cases. This paper demonstrates that when th...

  4. Respiratory muscle activity during REM sleep in patients with diaphragm paralysis.

    Science.gov (United States)

    Bennett, J R; Dunroy, H M A; Corfield, D R; Hart, N; Simonds, A K; Polkey, M I; Morrell, M J

    2004-01-13

    The diaphragm is the main inspiratory muscle during REM sleep. It was hypothesized that patients with isolated bilateral diaphragm paralysis (BDP) might not be able to sustain REM sleep. Polysomnography with EMG recordings was undertaken from accessory respiratory muscles in patients with BDP and normal subjects. Patients with BDP had a normal quantity of REM sleep (mean +/- SD, 18.6 +/- 7.5% of total sleep time) achieved by inspiratory recruitment of extradiaphragmatic muscles in both tonic and phasic REM, suggesting brainstem reorganization.

  5. REM Sleep and Endothermy: Potential Sites and Mechanism of a Reciprocal Interference

    Directory of Open Access Journals (Sweden)

    Matteo Cerri

    2017-08-01

    Full Text Available Numerous data show a reciprocal interaction between REM sleep and thermoregulation. During REM sleep, the function of thermoregulation appears to be impaired; from the other hand, the tonic activation of thermogenesis, such as during cold exposure, suppresses REM sleep occurrence. Recently, both the central neural network controlling REM sleep and the central neural network controlling thermoregulation have been progressively unraveled. Thermoregulation was shown to be controlled by a central “core” circuit, responsible for the maintenance of body temperature, modulated by a set of accessory areas. REM sleep was suggested to be controlled by a group of hypothalamic neurons overlooking at the REM sleep generating circuits within the brainstem. The two networks overlap in a few areas, and in this review, we will suggest that in such overlap may reside the explanation of the reciprocal interaction between REM sleep and thermoregulation. Considering the peculiar modulation of thermoregulation by REM sleep the result of their coincidental evolution, REM sleep may therefore be seen as a period of transient heterothermy.

  6. Effects of selective REM sleep deprivation on prefrontal gamma activity and executive functions.

    Science.gov (United States)

    Corsi-Cabrera, M; Rosales-Lagarde, A; del Río-Portilla, Y; Sifuentes-Ortega, R; Alcántara-Quintero, B

    2015-05-01

    Given that the dorsolateral prefrontal cortex is involved in executive functions and is deactivated and decoupled from posterior associative regions during REM sleep, that Gamma temporal coupling involved in information processing is enhanced during REM sleep, and that adult humans spend about 90 min of every 24h in REM sleep, it might be expected that REM sleep deprivation would modify Gamma temporal coupling and have a deteriorating effect on executive functions. We analyzed EEG Gamma activity and temporal coupling during implementation of a rule-guided task before and after REM sleep deprivation and its effect on verbal fluency, flexible thinking and selective attention. After two nights in the laboratory for adaptation, on the third night subjects (n=18) were randomly assigned to either selective REM sleep deprivation effectuated by awakening them at each REM sleep onset or, the same number of NREM sleep awakenings as a control for unspecific effects of sleep interruptions. Implementation of abstract rules to guide behavior required greater activation and synchronization of Gamma activity in the frontopolar regions after REM sleep reduction from 20.6% at baseline to just 3.93% of total sleep time. However, contrary to our hypothesis, both groups showed an overall improvement in executive task performance and no effect on their capacity to sustain selective attention. These results suggest that after one night of selective REM sleep deprivation executive functions can be compensated by increasing frontal activation and they still require the participation of supervisory control by frontopolar regions.

  7. Enhanced emotional reactivity after selective REM sleep deprivation in humans: an fMRI study

    Directory of Open Access Journals (Sweden)

    Alejandra eRosales-Lagarde

    2012-06-01

    Full Text Available Converging evidence from animal and human studies suggest that REM sleep modulates emotional processing. The aim of the present study was to explore the effects of selective REM sleep deprivation on emotional responses to threatening visual stimuli and their brain correlates using functional magnetic resonance imaging (fMRI. Twenty healthy subjects were randomly assigned to two groups: selective REM sleep deprivation (REM-D, by awakening them at each REM sleep onset, or NREM sleep interruptions (NREM-I as control for potential non-specific effects of awakenings and lack of sleep. In a within-subject design, a visual emotional-reactivity task was performed in the scanner before and 24 hours after sleep manipulation. Behaviorally, emotional reactivity was enhanced relative to baseline in the REM deprived group only. In terms of fMRI signal, there was an overall decrease in activity in the NREM-I group the second time subjects performed the task, particularly in regions involved in emotional processing, such as occipital and temporal areas, as well as in the ventrolateral prefrontal cortex, involved in top-down emotion regulation. In contrast, activity in these areas remained the same level or even increased in the REM-D group, compared to their baseline level.Taken together, these results suggest that lack of REM sleep in humans is associated with enhanced emotional reactivity, both at behavioral and neural levels, and thus highlight the specific role of REM sleep in regulating the neural substrates for emotional responsiveness.

  8. Aerodynamic Noise Prediction Using stochastic Turbulence Modeling

    Directory of Open Access Journals (Sweden)

    Arash Ahmadzadegan

    2008-01-01

    Full Text Available Amongst many approaches to determine the sound propagated from turbulent flows, hybrid methods, in which the turbulent noise source field is computed or modeled separately from the far field calculation, are frequently used. For basic estimation of sound propagation, less computationally intensive methods can be developed using stochastic models of the turbulent fluctuations (turbulent noise source field. A simple and easy to use stochastic model for generating turbulent velocity fluctuations called continuous filter white noise (CFWN model was used. This method based on the use of classical Langevian-equation to model the details of fluctuating field superimposed on averaged computed quantities. The resulting sound field due to the generated unsteady flow field was evaluated using Lighthill's acoustic analogy. Volume integral method used for evaluating the acoustic analogy. This formulation presents an advantage, as it confers the possibility to determine separately the contribution of the different integral terms and also integration regions to the radiated acoustic pressure. Our results validated by comparing the directivity and the overall sound pressure level (OSPL magnitudes with the available experimental results. Numerical results showed reasonable agreement with the experiments, both in maximum directivity and magnitude of the OSPL. This method presents a very suitable tool for the noise calculation of different engineering problems in early stages of the design process where rough estimates using cheaper methods are needed for different geometries.

  9. A Predictive Model of High Shear Thrombus Growth.

    Science.gov (United States)

    Mehrabadi, Marmar; Casa, Lauren D C; Aidun, Cyrus K; Ku, David N

    2016-08-01

    The ability to predict the timescale of thrombotic occlusion in stenotic vessels may improve patient risk assessment for thrombotic events. In blood contacting devices, thrombosis predictions can lead to improved designs to minimize thrombotic risks. We have developed and validated a model of high shear thrombosis based on empirical correlations between thrombus growth and shear rate. A mathematical model was developed to predict the growth of thrombus based on the hemodynamic shear rate. The model predicts thrombus deposition based on initial geometric and fluid mechanic conditions, which are updated throughout the simulation to reflect the changing lumen dimensions. The model was validated by comparing predictions against actual thrombus growth in six separate in vitro experiments: stenotic glass capillary tubes (diameter = 345 µm) at three shear rates, the PFA-100(®) system, two microfluidic channel dimensions (heights = 300 and 82 µm), and a stenotic aortic graft (diameter = 5.5 mm). Comparison of the predicted occlusion times to experimental results shows excellent agreement. The model is also applied to a clinical angiography image to illustrate the time course of thrombosis in a stenotic carotid artery after plaque cap rupture. Our model can accurately predict thrombotic occlusion time over a wide range of hemodynamic conditions.

  10. The application of modeling and prediction with MRA wavelet network

    Institute of Scientific and Technical Information of China (English)

    LU Shu-ping; YANG Xue-jing; ZHAO Xi-ren

    2004-01-01

    As there are lots of non-linear systems in the real engineering, it is very important to do more researches on the modeling and prediction of non-linear systems. Based on the multi-resolution analysis (MRA) of wavelet theory, this paper combined the wavelet theory with neural network and established a MRA wavelet network with the scaling function and wavelet function as its neurons. From the analysis in the frequency domain, the results indicated that MRA wavelet network was better than other wavelet networks in the ability of approaching to the signals. An essential research was carried out on modeling and prediction with MRA wavelet network in the non-linear system. Using the lengthwise sway data received from the experiment of ship model, a model of offline prediction was established and was applied to the short-time prediction of ship motion. The simulation results indicated that the forecasting model improved the prediction precision effectively, lengthened the forecasting time and had a better prediction results than that of AR linear model.The research indicates that it is feasible to use the MRA wavelet network in the short -time prediction of ship motion.

  11. A COMPARISON BETWEEN THREE PREDICTIVE MODELS OF COMPUTATIONAL INTELLIGENCE

    Directory of Open Access Journals (Sweden)

    DUMITRU CIOBANU

    2013-12-01

    Full Text Available Time series prediction is an open problem and many researchers are trying to find new predictive methods and improvements for the existing ones. Lately methods based on neural networks are used extensively for time series prediction. Also, support vector machines have solved some of the problems faced by neural networks and they began to be widely used for time series prediction. The main drawback of those two methods is that they are global models and in the case of a chaotic time series it is unlikely to find such model. In this paper it is presented a comparison between three predictive from computational intelligence field one based on neural networks one based on support vector machine and another based on chaos theory. We show that the model based on chaos theory is an alternative to the other two methods.

  12. MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model

    Science.gov (United States)

    Wu, Jie; Ren, Hong-Li; Zuo, Jinqing; Zhao, Chongbo; Chen, Lijuan; Li, Qiaoping

    2016-09-01

    This study evaluates performance of Madden-Julian oscillation (MJO) prediction in the Beijing Climate Center Atmospheric General Circulation Model (BCC_AGCM2.2). By using the real-time multivariate MJO (RMM) indices, it is shown that the MJO prediction skill of BCC_AGCM2.2 extends to about 16-17 days before the bivariate anomaly correlation coefficient drops to 0.5 and the root-mean-square error increases to the level of the climatological prediction. The prediction skill showed a seasonal dependence, with the highest skill occurring in boreal autumn, and a phase dependence with higher skill for predictions initiated from phases 2-4. The results of the MJO predictability analysis showed that the upper bounds of the prediction skill can be extended to 26 days by using a single-member estimate, and to 42 days by using the ensemble-mean estimate, which also exhibited an initial amplitude and phase dependence. The observed relationship between the MJO and the North Atlantic Oscillation was accurately reproduced by BCC_AGCM2.2 for most initial phases of the MJO, accompanied with the Rossby wave trains in the Northern Hemisphere extratropics driven by MJO convection forcing. Overall, BCC_AGCM2.2 displayed a significant ability to predict the MJO and its teleconnections without interacting with the ocean, which provided a useful tool for fully extracting the predictability source of subseasonal prediction.

  13. Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

    Directory of Open Access Journals (Sweden)

    Saerom Park

    Full Text Available Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

  14. Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

    Science.gov (United States)

    Park, Saerom; Lee, Jaewook; Son, Youngdoo

    2016-01-01

    Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

  15. New Approaches for Channel Prediction Based on Sinusoidal Modeling

    Directory of Open Access Journals (Sweden)

    Ekman Torbjörn

    2007-01-01

    Full Text Available Long-range channel prediction is considered to be one of the most important enabling technologies to future wireless communication systems. The prediction of Rayleigh fading channels is studied in the frame of sinusoidal modeling in this paper. A stochastic sinusoidal model to represent a Rayleigh fading channel is proposed. Three different predictors based on the statistical sinusoidal model are proposed. These methods outperform the standard linear predictor (LP in Monte Carlo simulations, but underperform with real measurement data, probably due to nonstationary model parameters. To mitigate these modeling errors, a joint moving average and sinusoidal (JMAS prediction model and the associated joint least-squares (LS predictor are proposed. It combines the sinusoidal model with an LP to handle unmodeled dynamics in the signal. The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.

  16. Prediction model for spring dust weather frequency in North China

    Institute of Scientific and Technical Information of China (English)

    LANG XianMei

    2008-01-01

    It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, I.e. Model-Ⅰ and model-Ⅱ, are then set up respectively based on observed climate data and the 32-year (1970--2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-Ⅰ, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-Ⅱ, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-Ⅰ. The model-Ⅱ can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-Ⅰ's one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-Ⅱ, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.

  17. Prediction model for spring dust weather frequency in North China

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, i.e. model-I and model-II, are then set up respectively based on observed climate data and the 32-year (1970 -2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-I, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-II, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-I. The model-II can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-I’s one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-II, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.

  18. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik;

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored...... and controlled have thus become essential factors for efficient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona...

  19. A burnout prediction model based around char morphology

    Energy Technology Data Exchange (ETDEWEB)

    Tao Wu; Edward Lester; Michael Cloke [University of Nottingham, Nottingham (United Kingdom). School of Chemical, Environmental and Mining Engineering

    2006-05-15

    Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coal particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.

  20. An evaluation of mathematical models for predicting skin permeability.

    Science.gov (United States)

    Lian, Guoping; Chen, Longjian; Han, Lujia

    2008-01-01

    A number of mathematical models have been proposed for predicting skin permeability, mostly empirical and very few are deterministic. Early empirical models use simple lipophilicity parameters. The recent trend is to use more complicated molecular structure descriptors. There has been much debate on which models best predict skin permeability. This article evaluates various mathematical models using a comprehensive experimental dataset of skin permeability for 124 chemical compounds compiled from various sources. Of the seven models compared, the deterministic model of Mitragotri gives the best prediction. The simple quantitative structure permeability relationships (QSPR) model of Potts and Guy gives the second best prediction. The two models have many features in common. Both assume the lipid matrix as the pathway of transdermal permeation. Both use octanol-water partition coefficient and molecular size. Even the mathematical formulae are similar. All other empirical QSPR models that use more complicated molecular structure descriptors fail to provide satisfactory prediction. The molecular structure descriptors in the more complicated QSPR models are empirically related to skin permeation. The mechanism on how these descriptors affect transdermal permeation is not clear. Mathematically it is an ill-defined approach to use many colinearly related parameters rather than fewer independent parameters in multi-linear regression.

  1. The role of vestibular system and the cerebellum in adapting to gravitoinertial, spatial orientation and postural challenges of REM sleep.

    Science.gov (United States)

    Dharani, Nataraj E

    2005-01-01

    The underlying reasons for, and mechanisms of rapid eye movement (REM) sleep events remain a mystery. The mystery has arisen from interpreting REM sleep events as occurring in 'isolation' from the world at large, and phylogenetically ancient brain areas using 'primal' gravity-dependent coordinates, reflexes and stimuli parameters to relay and process information about self and environment. This paper views REM sleep as a phylogenetically older form of wakefulness, wherein the brain uses a gravitoinertial-centred reference frame and an internal self-object model to evaluate and integrate inputs from several sensory systems and to adapt to spatial-temporal disintegration and malignant cholinergic-induced vasodepressor/ventilatory threat. The integration of vestibular and non-vestibular sensory graviceptor signals enables estimation and control of centre of the body mass, position and spatial relationship of body parts, gaze, head and whole-body tilt, spatial orientation and autonomic functions relative to gravity. The vestibulocerebellum and vermis, via vestibular and fastigial nucleus, coordinate inputs and outputs from several sensory systems and modulate the amplitude and duration of 'fight-or-flight' vestibulo-orienting and autonomic 'burst' responses to overcome the ongoing challenges. Resolving multisystem conflicts during the unique stresses (gravitoinertial, hypoxic, thermal, immobilisation, etc.) of REM sleep enables learning, cross-modal plasticity, higher-order integration and multidimensional spatial updating of sensory-motor-cognitive components. This paper aims to generate discussion, reinterpretation and creative testing of this novel hypothesis, which, if experimentally confirmed, has major implications across medicine, bioscience and space physiology, from developmental, clinical, research and theoretical perspectives.

  2. Blockage of dopaminergic D(2) receptors produces decrease of REM but not of slow wave sleep in rats after REM sleep deprivation.

    Science.gov (United States)

    Lima, Marcelo M S; Andersen, Monica L; Reksidler, Angela B; Silva, Andressa; Zager, Adriano; Zanata, Sílvio M; Vital, Maria A B F; Tufik, Sergio

    2008-04-01

    Dopamine (DA) has, as of late, become singled out from the profusion of other neurotransmitters as what could be called a key substance, in the regulation of the sleep-wake states. We have hypothesized that dopaminergic D(2) receptor blockage induced by haloperidol could generate a reduction or even an ablation of rapid eye movement (REM) sleep. Otherwise, the use of the selective D(2) agonist, piribedil, could potentiate REM sleep. Electrophysiological findings demonstrate that D(2) blockage produced a dramatic reduction of REM sleep during the rebound (REB) period after 96 h of REM sleep deprivation (RSD). This reduction of REM sleep was accompanied by an increment in SWS, which is possibly accounted for the observed increase in the sleep efficiency. Conversely, our findings also demonstrate that the administration of piribedil did not generate additional increase of REM sleep. Additionally, D(2) receptors were found down-regulated, in the haloperidol group, after RSD, and subsequently up-regulated after REB group, contrasting to the D(1) down-regulation at the same period. In this sense, the current data indicate a participation of the D(2) receptor for REM sleep regulation and consequently in the REM sleep/SWS balance. Herein, we propose that the mechanism underlying the striatal D(2) up-regulation is due to an effect as consequence of RSD which originally produces selective D(2) supersensitivity, and after its period probably generates a surge in D(2) expression. In conclusion we report a particular action of the dopaminergic neurotransmission in REM sleep relying on D(2) activation.

  3. Bayesian Age-Period-Cohort Modeling and Prediction - BAMP

    Directory of Open Access Journals (Sweden)

    Volker J. Schmid

    2007-10-01

    Full Text Available The software package BAMP provides a method of analyzing incidence or mortality data on the Lexis diagram, using a Bayesian version of an age-period-cohort model. A hierarchical model is assumed with a binomial model in the first-stage. As smoothing priors for the age, period and cohort parameters random walks of first and second order, with and without an additional unstructured component are available. Unstructured heterogeneity can also be included in the model. In order to evaluate the model fit, posterior deviance, DIC and predictive deviances are computed. By projecting the random walk prior into the future, future death rates can be predicted.

  4. Declarative memory consolidation during the first night in a sleep lab: the role of REM sleep and cortisol.

    Science.gov (United States)

    Goerke, Monique; Cohrs, Stefan; Rodenbeck, Andrea; Grittner, Ulrike; Sommer, Werner; Kunz, Dieter

    2013-07-01

    While the consolidation of declarative memory is supported by slow wave sleep (SWS) in healthy subjects, it has been shown to be associated with rapid eye movement (REM) sleep in patients with insomnia. Sleep during a subject's first night in an unfamiliar environment is often disturbed, and this so-called first-night effect (FNE) has often been used as a model of transient insomnia. Additionally, sleeping for the first time in an unfamiliar environment can lead to increased cortisol secretion, and declarative memory consolidation likely depends on low cortisol levels, especially during the early part of the night. Accounting for intersubject variability in the FNE, we examined the relationship between sleep stages, cortisol secretion and declarative memory performance in 27 healthy young men. Declarative memory performance improved significantly after sleep. Whereas memory performance during the learning session and retrieval testing was strongly associated with cortisol secretion, the overnight gain was not. Post hoc analyses indicated that the overnight gain appears to be modulated by the extent of the FNE: a significant overnight improvement in memory performance was found only in subjects with a weak FNE (n=12). In these subjects, no association was found between any sleep stage and the improvement observed in their memory performance. In subjects with a strong FNE (n=12), however, the overnight change in memory performance was associated with the proportion of REM sleep and the total number of REMs. Disturbed sleep in an unfamiliar environment therefore appears to affect the memory consolidation process.

  5. Validation of a tuber blight (Phytophthora infestans) prediction model

    Science.gov (United States)

    Potato tuber blight caused by Phytophthora infestans accounts for significant losses in storage. There is limited published quantitative data on predicting tuber blight. We validated a tuber blight prediction model developed in New York with cultivars Allegany, NY 101, and Katahdin using independent...

  6. Prediction of bypass transition with differential Reynolds stress models

    NARCIS (Netherlands)

    Westin, K.J.A.; Henkes, R.A.W.M.

    1998-01-01

    Boundary layer transition induced by high levels of free stream turbulence (FSl), so called bypass transition, can not be predicted with conventional stability calculations (e.g. the en-method). The use of turbulence models for transition prediction has shown some success for this type of flows, and

  7. Prediction Models of Free-Field Vibrations from Railway Traffic

    DEFF Research Database (Denmark)

    Malmborg, Jens; Persson, Kent; Persson, Peter

    2017-01-01

    and railways close to where people work and live. Annoyance from traffic-induced vibrations and noise is expected to be a growing issue. To predict the level of vibration and noise in buildings caused by railway and road traffic, calculation models are needed. In the present paper, a simplified prediction...

  8. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...

  9. Space Weather: Measurements, Models and Predictions

    Science.gov (United States)

    2014-03-21

    and record high levels of cosmic ray flux. There were broad-ranging terrestrial responses to this inactivity of the Sun. BC was involved in the...techniques for converting from one coordinate system (e.g., the invariant coordinate system used for the model) to another (e.g., the latitude- radius

  10. Monotone models for prediction in data mining

    NARCIS (Netherlands)

    Velikova, M.V.

    2006-01-01

    This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledge into a data mining process. Monotonicity constraints are enforced at two stages¿data preparation and data modeling. The main contributions of the research are a novel procedure to test the degree of

  11. Predicting Magazine Audiences with a Loglinear Model.

    Science.gov (United States)

    1987-07-01

    important use of e.d. estimates is in media selection ( Aaker 1975; Lee 1962, 1963; Little and Lodish 1969). All advertising campaigns have a budget. It...N.Z. Listener 6061 39.0 4 0 22 References Aaker , D.A. (1975), "ADMOD:An Advertising Decision Model," Journal of Marketing Research, February, 37-45

  12. Scanpath Based N-Gram Models for Predicting Reading Behavior

    DEFF Research Database (Denmark)

    Mishra, Abhijit; Bhattacharyya, Pushpak; Carl, Michael

    2013-01-01

    Predicting reading behavior is a difficult task. Reading behavior depends on various linguistic factors (e.g. sentence length, structural complexity etc.) and other factors (e.g individual's reading style, age etc.). Ideally, a reading model should be similar to a language model where the model i...

  13. Better predictions when models are wrong or underspecified

    NARCIS (Netherlands)

    Ommen, Matthijs van

    2015-01-01

    Many statistical methods rely on models of reality in order to learn from data and to make predictions about future data. By necessity, these models usually do not match reality exactly, but are either wrong (none of the hypotheses in the model provides an accurate description of reality) or undersp

  14. REM - Rapid Eye Mount. A fast slewing robotized infrared telescope

    CERN Document Server

    Covino, S; Chincarini, G L; Rodono, M; Ghisellini, G; Antonelli, A; Conconi, P; Cutispoto, G; Molinari, E; Covino, Stefano; Zerbi, Filippo; Chincarini, Guido; Rodono', Marcello; Ghisellini, Gabriele; Antonelli, Angelo; Conconi, Paolo; Cutispoto, Giuseppe; Molinari, Emilio

    2001-01-01

    The main goal of the REM project is the observation of prompt afterglow of Gamma-Ray Burst (GRB) events. Such observations at Near InfraRed (NIR) wavelengths are even very promising, since they allow to monitor high-z Ly-$\\alpha$ absorbed bursts as well as events occurring in dusty star-forming regions. In addition to GRB science, a large amount of time ($\\sim 40%$) will be available for different scientific targets: among these the study of variability of stellar objects open exciting new perspectives.

  15. Lucid dreaming verified by volitional communication during REM sleep.

    Science.gov (United States)

    La Berge, S P; Nagel, L E; Dement, W C; Zarcone, V P

    1981-06-01

    The occurrence of lucid dreaming (dreaming while being conscious that one is dreaming) has been verified for 5 selected subjects who signaled that they knew they were dreaming while continuing to dream during unequivocal REM sleep. The signals consisted of particular dream actions having observable concomitants and were performed in accordance with pre-sleep agreement. The ability of proficient lucid dreamers to signal in this manner makes possible a new approach to dream research--such subjects, while lucid, could carry out diverse dream experiments marking the exact time of particular dream events, allowing derivation of of precise psychophysiological correlations and methodical testing of hypotheses.

  16. The Simultaneous Additive and Relative SysRem Algorithm

    Directory of Open Access Journals (Sweden)

    Ofir A.

    2011-02-01

    Full Text Available We present the SARS algorithm, which is a generalization of the popular SysRem detrending technique. This generalization allows including multiple external parameters in a simultaneous solution with the unknown effects. Using SARS allowed us to show that the magnitude-dependant systematic effect discovered by Mazeh et al. (2009 in the CoRoT data is probably caused by an additive –rather than relative– noise source. A post-processing scheme based on SARS performs well and indeed allows for the detection of new transit-like signals that were not previously detected.

  17. Hybrid Corporate Performance Prediction Model Considering Technical Capability

    Directory of Open Access Journals (Sweden)

    Joonhyuck Lee

    2016-07-01

    Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.

  18. A Multistep Chaotic Model for Municipal Solid Waste Generation Prediction.

    Science.gov (United States)

    Song, Jingwei; He, Jiaying

    2014-08-01

    In this study, a univariate local chaotic model is proposed to make one-step and multistep forecasts for daily municipal solid waste (MSW) generation in Seattle, Washington. For MSW generation prediction with long history data, this forecasting model was created based on a nonlinear dynamic method called phase-space reconstruction. Compared with other nonlinear predictive models, such as artificial neural network (ANN) and partial least square-support vector machine (PLS-SVM), and a commonly used linear seasonal autoregressive integrated moving average (sARIMA) model, this method has demonstrated better prediction accuracy from 1-step ahead prediction to 14-step ahead prediction assessed by both mean absolute percentage error (MAPE) and root mean square error (RMSE). Max error, MAPE, and RMSE show that chaotic models were more reliable than the other three models. As chaotic models do not involve random walk, their performance does not vary while ANN and PLS-SVM make different forecasts in each trial. Moreover, this chaotic model was less time consuming than ANN and PLS-SVM models.

  19. Using Pareto points for model identification in predictive toxicology.

    Science.gov (United States)

    Palczewska, Anna; Neagu, Daniel; Ridley, Mick

    2013-03-22

    : Predictive toxicology is concerned with the development of models that are able to predict the toxicity of chemicals. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in cosmetics, drug design or food protection to speed up the process of chemical compound discovery while reducing the need for lab tests. There is an extensive literature associated with the best practice of model generation and data integration but management and automated identification of relevant models from available collections of models is still an open problem. Currently, the decision on which model should be used for a new chemical compound is left to users. This paper intends to initiate the discussion on automated model identification. We present an algorithm, based on Pareto optimality, which mines model collections and identifies a model that offers a reliable prediction for a new chemical compound. The performance of this new approach is verified for two endpoints: IGC50 and LogP. The results show a great potential for automated model identification methods in predictive toxicology.

  20. On the Predictiveness of Single-Field Inflationary Models

    CERN Document Server

    Burgess, C.P.; Trott, Michael

    2014-01-01

    We re-examine the predictiveness of single-field inflationary models and discuss how an unknown UV completion can complicate determining inflationary model parameters from observations, even from precision measurements. Besides the usual naturalness issues associated with having a shallow inflationary potential, we describe another issue for inflation, namely, unknown UV physics modifies the running of Standard Model (SM) parameters and thereby introduces uncertainty into the potential inflationary predictions. We illustrate this point using the minimal Higgs Inflationary scenario, which is arguably the most predictive single-field model on the market, because its predictions for $A_s$, $r$ and $n_s$ are made using only one new free parameter beyond those measured in particle physics experiments, and run up to the inflationary regime. We find that this issue can already have observable effects. At the same time, this UV-parameter dependence in the Renormalization Group allows Higgs Inflation to occur (in prin...

  1. A Composite Model Predictive Control Strategy for Furnaces

    Institute of Scientific and Technical Information of China (English)

    Hao Zang; Hongguang Li; Jingwen Huang; Jia Wang

    2014-01-01

    Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimi-zation of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control (CMPC) strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The control ers connected with two kinds of communi-cation networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reason-able CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.

  2. Submission Form for Peer-Reviewed Cancer Risk Prediction Models

    Science.gov (United States)

    If you have information about a peer-reviewd cancer risk prediction model that you would like to be considered for inclusion on this list, submit as much information as possible through the form on this page.

  3. ACCIDENT PREDICTION MODELS FOR UNSIGNALISED URBAN JUNCTIONS IN GHANA

    Directory of Open Access Journals (Sweden)

    Mohammed SALIFU, MSc., PhD, MIHT, MGhIE

    2004-01-01

    The accident prediction models developed have a potentially wide area of application and their systematic use is likely to improve considerably the quality and delivery of the engineering aspects of accident mitigation and prevention in Ghana.

  4. Using a Prediction Model to Manage Cyber Security Threats

    National Research Council Canada - National Science Library

    Jaganathan, Venkatesh; Cherurveettil, Priyesh; Muthu Sivashanmugam, Premapriya

    2015-01-01

    .... The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security...

  5. Development of a multi-year climate prediction model | Alexander ...

    African Journals Online (AJOL)

    Development of a multi-year climate prediction model. ... The available water resources in Southern Africa are rapidly approaching the limits of economic exploitation. ... that could be attributed to climate change arising from human activities.

  6. Compensatory versus noncompensatory models for predicting consumer preferences

    Directory of Open Access Journals (Sweden)

    Anja Dieckmann

    2009-04-01

    Full Text Available Standard preference models in consumer research assume that people weigh and add all attributes of the available options to derive a decision, while there is growing evidence for the use of simplifying heuristics. Recently, a greedoid algorithm has been developed (Yee, Dahan, Hauser and Orlin, 2007; Kohli and Jedidi, 2007 to model lexicographic heuristics from preference data. We compare predictive accuracies of the greedoid approach and standard conjoint analysis in an online study with a rating and a ranking task. The lexicographic model derived from the greedoid algorithm was better at predicting ranking compared to rating data, but overall, it achieved lower predictive accuracy for hold-out data than the compensatory model estimated by conjoint analysis. However, a considerable minority of participants was better predicted by lexicographic strategies. We conclude that the new algorithm will not replace standard tools for analyzing preferences, but can boost the study of situational and individual differences in preferential choice processes.

  7. Haskell financial data modeling and predictive analytics

    CERN Document Server

    Ryzhov, Pavel

    2013-01-01

    This book is a hands-on guide that teaches readers how to use Haskell's tools and libraries to analyze data from real-world sources in an easy-to-understand manner.This book is great for developers who are new to financial data modeling using Haskell. A basic knowledge of functional programming is not required but will be useful. An interest in high frequency finance is essential.

  8. Mesoscale Wind Predictions for Wave Model Evaluation

    Science.gov (United States)

    2016-06-07

    N0001400WX20041(B) http://www.nrlmry.navy.mil LONG TERM GOALS The long-term goal is to demonstrate the significance and importance of high...ocean waves by an appropriate wave model. OBJECTIVES The main objectives of this project are to: 1. Build the infrastructure to generate the...temperature for all COAMPS grids at the resolution of each of these grids. These analyses are important for the proper 2 specification of the lower

  9. Modeling Seizure Self-Prediction: An E-Diary Study

    Science.gov (United States)

    Haut, Sheryl R.; Hall, Charles B.; Borkowski, Thomas; Tennen, Howard; Lipton, Richard B.

    2013-01-01

    Purpose A subset of patients with epilepsy successfully self-predicted seizures in a paper diary study. We conducted an e-diary study to ensure that prediction precedes seizures, and to characterize the prodromal features and time windows that underlie self-prediction. Methods Subjects 18 or older with LRE and ≥3 seizures/month maintained an e-diary, reporting AM/PM data daily, including mood, premonitory symptoms, and all seizures. Self-prediction was rated by, “How likely are you to experience a seizure [time frame]”? Five choices ranged from almost certain (>95% chance) to very unlikely. Relative odds of seizure (OR) within time frames was examined using Poisson models with log normal random effects to adjust for multiple observations. Key Findings Nineteen subjects reported 244 eligible seizures. OR for prediction choices within 6hrs was as high as 9.31 (1.92,45.23) for “almost certain”. Prediction was most robust within 6hrs of diary entry, and remained significant up to 12hrs. For 9 best predictors, average sensitivity was 50%. Older age contributed to successful self-prediction, and self-prediction appeared to be driven by mood and premonitory symptoms. In multivariate modeling of seizure occurrence, self-prediction (2.84; 1.68,4.81), favorable change in mood (0.82; 0.67,0.99) and number of premonitory symptoms (1,11; 1.00,1.24) were significant. Significance Some persons with epilepsy can self-predict seizures. In these individuals, the odds of a seizure following a positive prediction are high. Predictions were robust, not attributable to recall bias, and were related to self awareness of mood and premonitory features. The 6-hour prediction window is suitable for the development of pre-emptive therapy. PMID:24111898

  10. Personalized Predictive Modeling and Risk Factor Identification using Patient Similarity.

    Science.gov (United States)

    Ng, Kenney; Sun, Jimeng; Hu, Jianying; Wang, Fei

    2015-01-01

    Personalized predictive models are customized for an individual patient and trained using information from similar patients. Compared to global models trained on all patients, they have the potential to produce more accurate risk scores and capture more relevant risk factors for individual patients. This paper presents an approach for building personalized predictive models and generating personalized risk factor profiles. A locally supervised metric learning (LSML) similarity measure is trained for diabetes onset and used to find clinically similar patients. Personalized risk profiles are created by analyzing the parameters of the trained personalized logistic regression models. A 15,000 patient data set, derived from electronic health records, is used to evaluate the approach. The predictive results show that the personalized models can outperform the global model. Cluster analysis of the risk profiles show groups of patients with similar risk factors, differences in the top risk factors for different groups of patients and differences between the individual and global risk factors.

  11. Model predictive control of P-time event graphs

    Science.gov (United States)

    Hamri, H.; Kara, R.; Amari, S.

    2016-12-01

    This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.

  12. Prediction of cloud droplet number in a general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Ghan, S.J.; Leung, L.R. [Pacific Northwest National Lab., Richland, WA (United States)

    1996-04-01

    We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.

  13. Using connectome-based predictive modeling to predict individual behavior from brain connectivity.

    Science.gov (United States)

    Shen, Xilin; Finn, Emily S; Scheinost, Dustin; Rosenberg, Monica D; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

    2017-03-01

    Neuroimaging is a fast-developing research area in which anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale data sets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: (i) feature selection, (ii) feature summarization, (iii) model building, and (iv) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a considerable amount of the variance in these measures. It has been demonstrated that the CPM protocol performs as well as or better than many of the existing approaches in brain-behavior prediction. As CPM focuses on linear modeling and a purely data-driven approach, neuroscientists with limited or no experience in machine learning or optimization will find it easy to implement these protocols. Depending on the volume of data to be processed, the protocol can take 10-100 min for model building, 1-48 h for permutation testing, and 10-20 min for visualization of results.

  14. Mixed models for predictive modeling in actuarial science

    NARCIS (Netherlands)

    Antonio, K.; Zhang, Y.

    2012-01-01

    We start with a general discussion of mixed (also called multilevel) models and continue with illustrating specific (actuarial) applications of this type of models. Technical details on (linear, generalized, non-linear) mixed models follow: model assumptions, specifications, estimation techniques

  15. Webinar of paper 2013, Which method predicts recidivism best? A comparison of statistical, machine learning and data mining predictive models

    NARCIS (Netherlands)

    Tollenaar, N.; Van der Heijden, P.G.M.|info:eu-repo/dai/nl/073087998

    2013-01-01

    Using criminal population criminal conviction history information, prediction models are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining

  16. Webinar of paper 2013, Which method predicts recidivism best? A comparison of statistical, machine learning and data mining predictive models

    NARCIS (Netherlands)

    Tollenaar, N.; Van der Heijden, P.G.M.

    2013-01-01

    Using criminal population criminal conviction history information, prediction models are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining

  17. Catalytic cracking models developed for predictive control purposes

    Directory of Open Access Journals (Sweden)

    Dag Ljungqvist

    1993-04-01

    Full Text Available The paper deals with state-space modeling issues in the context of model-predictive control, with application to catalytic cracking. Emphasis is placed on model establishment, verification and online adjustment. Both the Fluid Catalytic Cracking (FCC and the Residual Catalytic Cracking (RCC units are discussed. Catalytic cracking units involve complex interactive processes which are difficult to operate and control in an economically optimal way. The strong nonlinearities of the FCC process mean that the control calculation should be based on a nonlinear model with the relevant constraints included. However, the model can be simple compared to the complexity of the catalytic cracking plant. Model validity is ensured by a robust online model adjustment strategy. Model-predictive control schemes based on linear convolution models have been successfully applied to the supervisory dynamic control of catalytic cracking units, and the control can be further improved by the SSPC scheme.

  18. Technical note: A linear model for predicting δ13 Cprotein.

    Science.gov (United States)

    Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M

    2015-08-01

    Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2)  = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ(13) Cprotein . This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. The model presented here appears to hold significant potential for the prediction of the carbon isotope signature of dietary protein using only such data as is routinely generated in the course of stable isotope analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.

  19. Traffic Prediction Scheme based on Chaotic Models in Wireless Networks

    Directory of Open Access Journals (Sweden)

    Xiangrong Feng

    2013-09-01

    Full Text Available Based on the local support vector algorithm of chaotic time series analysis, the Hannan-Quinn information criterion and SAX symbolization are introduced. Then a novel prediction algorithm is proposed, which is successfully applied to the prediction of wireless network traffic. For the correct prediction problems of short-term flow with smaller data set size, the weakness of the algorithms during model construction is analyzed by study and comparison to LDK prediction algorithm. It is verified the Hannan-Quinn information principle can be used to calculate the number of neighbor points to replace pervious empirical method, which uses the number of neighbor points to acquire more accurate prediction model. Finally, actual flow data is applied to confirm the accuracy rate of the proposed algorithm LSDHQ. It is testified by our experiments that it also has higher performance in adaptability than that of LSDHQ algorithm.

  20. Toward a predictive model for elastomer seals

    Science.gov (United States)

    Molinari, Nicola; Khawaja, Musab; Sutton, Adrian; Mostofi, Arash

    Nitrile butadiene rubber (NBR) and hydrogenated-NBR (HNBR) are widely used elastomers, especially as seals in oil and gas applications. During exposure to well-hole conditions, ingress of gases causes degradation of performance, including mechanical failure. We use computer simulations to investigate this problem at two different length and time-scales. First, we study the solubility of gases in the elastomer using a chemically-inspired description of HNBR based on the OPLS all-atom force-field. Starting with a model of NBR, C=C double bonds are saturated with either hydrogen or intramolecular cross-links, mimicking the hydrogenation of NBR to form HNBR. We validate against trends for the mass density and glass transition temperature for HNBR as a function of cross-link density, and for NBR as a function of the fraction of acrylonitrile in the copolymer. Second, we study mechanical behaviour using a coarse-grained model that overcomes some of the length and time-scale limitations of an all-atom approach. Nanoparticle fillers added to the elastomer matrix to enhance mechanical response are also included. Our initial focus is on understanding the mechanical properties at the elevated temperatures and pressures experienced in well-hole conditions.

  1. Using a Prediction Model to Manage Cyber Security Threats

    Directory of Open Access Journals (Sweden)

    Venkatesh Jaganathan

    2015-01-01

    Full Text Available Cyber-attacks are an important issue faced by all organizations. Securing information systems is critical. Organizations should be able to understand the ecosystem and predict attacks. Predicting attacks quantitatively should be part of risk management. The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security. This model also considers the environmental information required. It is generalized and can be customized to the needs of the individual organization.

  2. Using a Prediction Model to Manage Cyber Security Threats.

    Science.gov (United States)

    Jaganathan, Venkatesh; Cherurveettil, Priyesh; Muthu Sivashanmugam, Premapriya

    2015-01-01

    Cyber-attacks are an important issue faced by all organizations. Securing information systems is critical. Organizations should be able to understand the ecosystem and predict attacks. Predicting attacks quantitatively should be part of risk management. The cost impact due to worms, viruses, or other malicious software is significant. This paper proposes a mathematical model to predict the impact of an attack based on significant factors that influence cyber security. This model also considers the environmental information required. It is generalized and can be customized to the needs of the individual organization.

  3. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh;

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and faulty...... outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeated until the fault is detected by a passive diagnoser. It is demonstrated how the generated excitation signal...

  4. Aero-acoustic noise of wind turbines. Noise prediction models

    Energy Technology Data Exchange (ETDEWEB)

    Maribo Pedersen, B. [ed.

    1997-12-31

    Semi-empirical and CAA (Computational AeroAcoustics) noise prediction techniques are the subject of this expert meeting. The meeting presents and discusses models and methods. The meeting may provide answers to the following questions: What Noise sources are the most important? How are the sources best modeled? What needs to be done to do better predictions? Does it boil down to correct prediction of the unsteady aerodynamics around the rotor? Or is the difficult part to convert the aerodynamics into acoustics? (LN)

  5. Model Predictive Control of a Wave Energy Converter

    DEFF Research Database (Denmark)

    Andersen, Palle; Pedersen, Tom Søndergård; Nielsen, Kirsten Mølgaard;

    2015-01-01

    In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a model...... connecting undisturbed wave sequences to sequences of torque. Losses in the conversion from mechanical to electrical power are taken into account in two ways. Conventional reactive controllers are tuned for each sea state with the assumption that the converter has the same efficiency back and forth. MPC...

  6. Modelling and prediction of non-stationary optical turbulence behaviour

    Science.gov (United States)

    Doelman, Niek; Osborn, James

    2016-07-01

    There is a strong need to model the temporal fluctuations in turbulence parameters, for instance for scheduling, simulation and prediction purposes. This paper aims at modelling the dynamic behaviour of the turbulence coherence length r0, utilising measurement data from the Stereo-SCIDAR instrument installed at the Isaac Newton Telescope at La Palma. Based on an estimate of the power spectral density function, a low order stochastic model to capture the temporal variability of r0 is proposed. The impact of this type of stochastic model on the prediction of the coherence length behaviour is shown.

  7. Research on Drag Torque Prediction Model for the Wet Clutches

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Considering the surface tension effect and centrifugal effect, a mathematical model based on Reynolds equation for predicting the drag torque of disengage wet clutches is presented. The model indicates that the equivalent radius is a function of clutch speed and flow rate. The drag torque achieves its peak at a critical speed. Above this speed, drag torque drops due to the shrinking of the oil film. The model also points out that viscosity and flow rate effects on drag torque. Experimental results indicate that the model is reasonable and it performs well for predicting the drag torque peak.

  8. Model output statistics applied to wind power prediction

    Energy Technology Data Exchange (ETDEWEB)

    Joensen, A.; Giebel, G.; Landberg, L. [Risoe National Lab., Roskilde (Denmark); Madsen, H.; Nielsen, H.A. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

    1999-03-01

    Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

  9. Development and application of chronic disease risk prediction models.

    Science.gov (United States)

    Oh, Sun Min; Stefani, Katherine M; Kim, Hyeon Chang

    2014-07-01

    Currently, non-communicable chronic diseases are a major cause of morbidity and mortality worldwide, and a large proportion of chronic diseases are preventable through risk factor management. However, the prevention efficacy at the individual level is not yet satisfactory. Chronic disease prediction models have been developed to assist physicians and individuals in clinical decision-making. A chronic disease prediction model assesses multiple risk factors together and estimates an absolute disease risk for the individual. Accurate prediction of an individual's future risk for a certain disease enables the comparison of benefits and risks of treatment, the costs of alternative prevention strategies, and selection of the most efficient strategy for the individual. A large number of chronic disease prediction models, especially targeting cardiovascular diseases and cancers, have been suggested, and some of them have been adopted in the clinical practice guidelines and recommendations of many countries. Although few chronic disease prediction tools have been suggested in the Korean population, their clinical utility is not as high as expected. This article reviews methodologies that are commonly used for developing and evaluating a chronic disease prediction model and discusses the current status of chronic disease prediction in Korea.

  10. Evaluation of burst pressure prediction models for line pipes

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Xian-Kui, E-mail: zhux@battelle.org [Battelle Memorial Institute, 505 King Avenue, Columbus, OH 43201 (United States); Leis, Brian N. [Battelle Memorial Institute, 505 King Avenue, Columbus, OH 43201 (United States)

    2012-01-15

    Accurate prediction of burst pressure plays a central role in engineering design and integrity assessment of oil and gas pipelines. Theoretical and empirical solutions for such prediction are evaluated in this paper relative to a burst pressure database comprising more than 100 tests covering a variety of pipeline steel grades and pipe sizes. Solutions considered include three based on plasticity theory for the end-capped, thin-walled, defect-free line pipe subjected to internal pressure in terms of the Tresca, von Mises, and ZL (or Zhu-Leis) criteria, one based on a cylindrical instability stress (CIS) concept, and a large group of analytical and empirical models previously evaluated by Law and Bowie (International Journal of Pressure Vessels and Piping, 84, 2007: 487-492). It is found that these models can be categorized into either a Tresca-family or a von Mises-family of solutions, except for those due to Margetson and Zhu-Leis models. The viability of predictions is measured via statistical analyses in terms of a mean error and its standard deviation. Consistent with an independent parallel evaluation using another large database, the Zhu-Leis solution is found best for predicting burst pressure, including consideration of strain hardening effects, while the Tresca strength solutions including Barlow, Maximum shear stress, Turner, and the ASME boiler code provide reasonably good predictions for the class of line-pipe steels with intermediate strain hardening response. - Highlights: Black-Right-Pointing-Pointer This paper evaluates different burst pressure prediction models for line pipes. Black-Right-Pointing-Pointer The existing models are categorized into two major groups of Tresca and von Mises solutions. Black-Right-Pointing-Pointer Prediction quality of each model is assessed statistically using a large full-scale burst test database. Black-Right-Pointing-Pointer The Zhu-Leis solution is identified as the best predictive model.

  11. Outcome Prediction in Mathematical Models of Immune Response to Infection.

    Directory of Open Access Journals (Sweden)

    Manuel Mai

    Full Text Available Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of 'virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability v in the ODE models by randomly selecting the model parameters from distributions with coefficients of variation v that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near 100% accuracy for v = 0, and the accuracy decreases with increasing v for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for v > 0. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.

  12. Development of Interpretable Predictive Models for BPH and Prostate Cancer

    Science.gov (United States)

    Bermejo, Pablo; Vivo, Alicia; Tárraga, Pedro J; Rodríguez-Montes, JA

    2015-01-01

    BACKGROUND Traditional methods for deciding whether to recommend a patient for a prostate biopsy are based on cut-off levels of stand-alone markers such as prostate-specific antigen (PSA) or any of its derivatives. However, in the last decade we have seen the increasing use of predictive models that combine, in a non-linear manner, several predictives that are better able to predict prostate cancer (PC), but these fail to help the clinician to distinguish between PC and benign prostate hyperplasia (BPH) patients. We construct two new models that are capable of predicting both PC and BPH. METHODS An observational study was performed on 150 patients with PSA ≥3 ng/mL and age >50 years. We built a decision tree and a logistic regression model, validated with the leave-one-out methodology, in order to predict PC or BPH, or reject both. RESULTS Statistical dependence with PC and BPH was found for prostate volume (P-value < 0.001), PSA (P-value < 0.001), international prostate symptom score (IPSS; P-value < 0.001), digital rectal examination (DRE; P-value < 0.001), age (P-value < 0.002), antecedents (P-value < 0.006), and meat consumption (P-value < 0.08). The two predictive models that were constructed selected a subset of these, namely, volume, PSA, DRE, and IPSS, obtaining an area under the ROC curve (AUC) between 72% and 80% for both PC and BPH prediction. CONCLUSION PSA and volume together help to build predictive models that accurately distinguish among PC, BPH, and patients without any of these pathologies. Our decision tree and logistic regression models outperform the AUC obtained in the compared studies. Using these models as decision support, the number of unnecessary biopsies might be significantly reduced. PMID:25780348

  13. Model Predictive Control of Wind Turbines

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian

    the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving......Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines...... are controlled by pitching the blades and by controlling the electro-magnetic torque of the generator, thus slowing the rotation of the blades. Improved control of wind turbines, leading to reduced fatigue loads, can be exploited by using less materials in the construction of the wind turbine or by reducing...

  14. Numerical modeling capabilities to predict repository performance

    Energy Technology Data Exchange (ETDEWEB)

    1979-09-01

    This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used.

  15. Comparison of Linear Prediction Models for Audio Signals

    Directory of Open Access Journals (Sweden)

    2009-03-01

    Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.

  16. Comparison of Linear Prediction Models for Audio Signals

    Directory of Open Access Journals (Sweden)

    van Waterschoot Toon

    2008-01-01

    Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.

  17. Hidden Markov models for prediction of protein features

    DEFF Research Database (Denmark)

    Bystroff, Christopher; Krogh, Anders

    2008-01-01

    Hidden Markov Models (HMMs) are an extremely versatile statistical representation that can be used to model any set of one-dimensional discrete symbol data. HMMs can model protein sequences in many ways, depending on what features of the protein are represented by the Markov states. For protein...... structure prediction, states have been chosen to represent either homologous sequence positions, local or secondary structure types, or transmembrane locality. The resulting models can be used to predict common ancestry, secondary or local structure, or membrane topology by applying one of the two standard...... algorithms for comparing a sequence to a model. In this chapter, we review those algorithms and discuss how HMMs have been constructed and refined for the purpose of protein structure prediction....

  18. Modelling of physical properties - databases, uncertainties and predictive power

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    Physical and thermodynamic property in the form of raw data or estimated values for pure compounds and mixtures are important pre-requisites for performing tasks such as, process design, simulation and optimization; computer aided molecular/mixture (product) design; and, product-process analysis...... connectivity approach. The development of these models requires measured property data and based on them, the regression of model parameters is performed. Although this class of models is empirical by nature, they do allow extrapolation from the regressed model parameters to predict properties of chemicals...... not included in the measured data-set. Therefore, they are also considered as predictive models. The paper will highlight different issues/challenges related to the role of the databases and the mathematical and thermodynamic consistency of the measured/estimated data, the predictive nature of the developed...

  19. Modeling, Prediction, and Control of Heating Temperature for Tube Billet

    Directory of Open Access Journals (Sweden)

    Yachun Mao

    2015-01-01

    Full Text Available Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.

  20. Predicting artificailly drained areas by means of selective model ensemble

    DEFF Research Database (Denmark)

    Møller, Anders Bjørn; Beucher, Amélie; Iversen, Bo Vangsø

    . The approaches employed include decision trees, discriminant analysis, regression models, neural networks and support vector machines amongst others. Several models are trained with each method, using variously the original soil covariates and principal components of the covariates. With a large ensemble...... out since the mid-19th century, and it has been estimated that half of the cultivated area is artificially drained (Olesen, 2009). A number of machine learning approaches can be used to predict artificially drained areas in geographic space. However, instead of choosing the most accurate model....... The study aims firstly to train a large number of models to predict the extent of artificially drained areas using various machine learning approaches. Secondly, the study will develop a method for selecting the models, which give a good prediction of artificially drained areas, when used in conjunction...

  1. Experimental study on prediction model for maximum rebound ratio

    Institute of Scientific and Technical Information of China (English)

    LEI Wei-dong; TENG Jun; A.HEFNY; ZHAO Jian; GUAN Jiong

    2007-01-01

    The proposed prediction model for estimating the maximum rebound ratio was applied to a field explosion test, Mandai test in Singapore.The estimated possible maximum Deak particle velocities(PPVs)were compared with the field records.Three of the four available field-recorded PPVs lie exactly below the estimated possible maximum values as expected.while the fourth available field-recorded PPV lies close to and a bit higher than the estimated maximum possible PPV The comparison results show that the predicted PPVs from the proposed prediction model for the maximum rebound ratio match the field.recorded PPVs better than those from two empirical formulae.The very good agreement between the estimated and field-recorded values validates the proposed prediction model for estimating PPV in a rock mass with a set of ipints due to application of a two dimensional compressional wave at the boundary of a tunnel or a borehole.

  2. Groundwater Level Prediction using M5 Model Trees

    Science.gov (United States)

    Nalarajan, Nitha Ayinippully; Mohandas, C.

    2015-01-01

    Groundwater is an important resource, readily available and having high economic value and social benefit. Recently, it had been considered a dependable source of uncontaminated water. During the past two decades, increased rate of extraction and other greedy human actions have resulted in the groundwater crisis, both qualitatively and quantitatively. Under prevailing circumstances, the availability of predicted groundwater levels increase the importance of this valuable resource, as an aid in the planning of groundwater resources. For this purpose, data-driven prediction models are widely used in the present day world. M5 model tree (MT) is a popular soft computing method emerging as a promising method for numeric prediction, producing understandable models. The present study discusses the groundwater level predictions using MT employing only the historical groundwater levels from a groundwater monitoring well. The results showed that MT can be successively used for forecasting groundwater levels.

  3. A Fusion Model for CPU Load Prediction in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Dayu Xu

    2013-11-01

    Full Text Available Load prediction plays a key role in cost-optimal resource allocation and datacenter energy saving. In this paper, we use real-world traces from Cloud platform and propose a fusion model to forecast the future CPU loads. First, long CPU load time series data are divided into short sequences with same length from the historical data on the basis of cloud control cycle. Then we use kernel fuzzy c-means clustering algorithm to put the subsequences into different clusters. For each cluster, with current load sequence, a genetic algorithm optimized wavelet Elman neural network prediction model is exploited to predict the CPU load in next time interval. Finally, we obtain the optimal cloud computing CPU load prediction results from the cluster and its corresponding predictor with minimum forecasting error. Experimental results show that our algorithm performs better than other models reported in previous works.

  4. Modelling proteins' hidden conformations to predict antibiotic resistance

    Science.gov (United States)

    Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

    2016-10-01

    TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

  5. A Hybrid Neural Network Prediction Model of Air Ticket Sales

    Directory of Open Access Journals (Sweden)

    Han-Chen Huang

    2013-11-01

    Full Text Available Air ticket sales revenue is an important source of revenue for travel agencies, and if future air ticket sales revenue can be accurately forecast, travel agencies will be able to advance procurement to achieve a sufficient amount of cost-effective tickets. Therefore, this study applied the Artificial Neural Network (ANN and Genetic Algorithms (GA to establish a prediction model of travel agency air ticket sales revenue. By verifying the empirical data, this study proved that the established prediction model has accurate prediction power, and MAPE (mean absolute percentage error is only 9.11%. The established model can provide business operators with reliable and efficient prediction data as a reference for operational decisions.

  6. E-commerce business model mining and prediction

    Institute of Scientific and Technical Information of China (English)

    Zhou-zhou HE; Zhong-fei ZHANG; Chun-ming CHEN; Zheng-gang WANG

    2015-01-01

    We study the problem of business model mining and prediction in the e-commerce context. Unlike most existing approaches where this is typically formulated as a regression problem or a time-series prediction problem, we take a different formulation to this problem by noting that these existing approaches fail to consider the potential relationships both among the consumers (consumer infl uence) and among the shops (competitions or collaborations). Taking this observation into consideration, we propose a new method for e-commerce business model mining and prediction, called EBMM, which combines regression with community analysis. The challenge is that the links in the network are typically not directly observed, which is addressed by applying information diffusion theory through the consumer-shop network. Extensive evaluations using Alibaba Group e-commerce data demonstrate the promise and superiority of EBMM to the state-of-the-art methods in terms of business model mining and prediction.

  7. Model for Predicting Passage of Invasive Fish Species Through Culverts

    Science.gov (United States)

    Neary, V.

    2010-12-01

    Conservation efforts to promote or inhibit fish passage include the application of simple fish passage models to determine whether an open channel flow allows passage of a given fish species. Derivations of simple fish passage models for uniform and nonuniform flow conditions are presented. For uniform flow conditions, a model equation is developed that predicts the mean-current velocity threshold in a fishway, or velocity barrier, which causes exhaustion at a given maximum distance of ascent. The derivation of a simple expression for this exhaustion-threshold (ET) passage model is presented using kinematic principles coupled with fatigue curves for threatened and endangered fish species. Mean current velocities at or above the threshold predict failure to pass. Mean current velocities below the threshold predict successful passage. The model is therefore intuitive and easily applied to predict passage or exclusion. The ET model’s simplicity comes with limitations, however, including its application only to uniform flow, which is rarely found in the field. This limitation is addressed by deriving a model that accounts for nonuniform conditions, including backwater profiles and drawdown curves. Comparison of these models with experimental data from volitional swimming studies of fish indicates reasonable performance, but limitations are still present due to the difficulty in predicting fish behavior and passage strategies that can vary among individuals and different fish species.

  8. Some Remarks on CFD Drag Prediction of an Aircraft Model

    Science.gov (United States)

    Peng, S. H.; Eliasson, P.

    Observed in CFD drag predictions for the DLR-F6 aircraft model with various configurations, some issues are addressed. The emphasis is placed on the effect of turbulence modeling and grid resolution. With several different turbulence models, the predicted flow feature around the aircraft is highlighted. It is shown that the prediction of the separation bubble in the wing-body junction is closely related to the inherent modeling mechanism of turbulence production. For the configuration with an additional fairing, which has effectively removed the separation bubble, it is illustrated that the drag prediction may be altered even for attached turbulent boundary layer when different turbulence models are used. Grid sensitivity studies are performed with two groups of subsequently refined grids. It is observed that, in contrast to the lift, the drag prediction is rather sensitive to the grid refinement, as well as to the artificial diffusion added for solving the turbulence transport equation. It is demonstrated that an effective grid refinement should drive the predicted drag components monotonically and linearly converged to a finite value.

  9. Signature prediction for model-based automatic target recognition

    Science.gov (United States)

    Keydel, Eric R.; Lee, Shung W.

    1996-06-01

    The moving and stationary target recognition (MSTAR) model- based automatic target recognition (ATR) system utilizes a paradigm which matches features extracted form an unknown SAR target signature against predictions of those features generated from models of the sensing process and candidate target geometries. The candidate target geometry yielding the best match between predicted and extracted features defines the identify of the unknown target. MSTAR will extend the current model-based ATR state-of-the-art in a number of significant directions. These include: use of Bayesian techniques for evidence accrual, reasoning over target subparts, coarse-to-fine hypothesis search strategies, and explicit reasoning over target articulation, configuration, occlusion, and lay-over. These advances also imply significant technical challenges, particularly for the MSTAR feature prediction module (MPM). In addition to accurate electromagnetics, the MPM must provide traceback between input target geometry and output features, on-line target geometry manipulation, target subpart feature prediction, explicit models for local scene effects, and generation of sensitivity and uncertainty measures for the predicted features. This paper describes the MPM design which is being developed to satisfy these requirements. The overall module structure is presented, along with the specific deign elements focused on MSTAR requirements. Particular attention is paid to design elements that enable on-line prediction of features within the time constraints mandated by model-driven ATR. Finally, the current status, development schedule, and further extensions in the module design are described.

  10. Multi-model ensemble hydrologic prediction and uncertainties analysis

    Directory of Open Access Journals (Sweden)

    S. Jiang

    2014-09-01

    Full Text Available Modelling uncertainties (i.e. input errors, parameter uncertainties and model structural errors inevitably exist in hydrological prediction. A lot of recent attention has focused on these, of which input error modelling, parameter optimization and multi-model ensemble strategies are the three most popular methods to demonstrate the impacts of modelling uncertainties. In this paper the Xinanjiang model, the Hybrid rainfall–runoff model and the HYMOD model were applied to the Mishui Basin, south China, for daily streamflow ensemble simulation and uncertainty analysis. The three models were first calibrated by two parameter optimization algorithms, namely, the Shuffled Complex Evolution method (SCE-UA and the Shuffled Complex Evolution Metropolis method (SCEM-UA; next, the input uncertainty was accounted for by introducing a normally-distributed error multiplier; then, the simulation sets calculated from the three models were combined by Bayesian model averaging (BMA. The results show that both these parameter optimization algorithms generate good streamflow simulations; specifically the SCEM-UA can imply parameter uncertainty and give the posterior distribution of the parameters. Considering the precipitation input uncertainty, the streamflow simulation precision does not improve very much. While the BMA combination not only improves the streamflow prediction precision, it also gives quantitative uncertainty bounds for the simulation sets. The SCEM-UA calculated prediction interval is better than the SCE-UA calculated one. These results suggest that considering the model parameters' uncertainties and doing multi-model ensemble simulations are very practical for streamflow prediction and flood forecasting, from which more precision prediction and more reliable uncertainty bounds can be generated.

  11. Comorbidity and medication in REM sleep behavior disorder

    DEFF Research Database (Denmark)

    Frauscher, Birgit; Jennum, Poul; Ju, Yo-El S

    2014-01-01

    OBJECTIVE: This controlled study investigated associations between comorbidity and medication in patients with polysomnographically confirmed idiopathic REM sleep behavior disorder (iRBD), using a large multicenter clinic-based cohort. METHODS: Data of a self-administered questionnaire on comorbi......OBJECTIVE: This controlled study investigated associations between comorbidity and medication in patients with polysomnographically confirmed idiopathic REM sleep behavior disorder (iRBD), using a large multicenter clinic-based cohort. METHODS: Data of a self-administered questionnaire...... more lifetime antidepressant use than comorbid depression (antidepressant use: OR 1.9, 95% CI 1.1-3.3; depression: OR 1.6, 95% CI 1.0-2.5). Patients with iRBD reported more ischemic heart disease (OR 1.9, 95% CI 1.1-3.1). This association did not change substantially when adjusting for cardiovascular...... risk factors (OR 2.3, 95% CI 1.3-3.9). The use of inhaled glucocorticoids was higher in patients with iRBD compared to controls (OR 5.3, 95% CI 1.8-15.8), likely reflecting the higher smoking rate in iRBD (smoking: OR 15.3, 95% CI 2.0-118.8; nonsmoking: OR 2.4, 95% CI 0.4-13.2) and consequent pulmonary...

  12. Model predictive torque control with an extended prediction horizon for electrical drive systems

    Science.gov (United States)

    Wang, Fengxiang; Zhang, Zhenbin; Kennel, Ralph; Rodríguez, José

    2015-07-01

    This paper presents a model predictive torque control method for electrical drive systems. A two-step prediction horizon is achieved by considering the reduction of the torque ripples. The electromagnetic torque and the stator flux error between predicted values and the references, and an over-current protection are considered in the cost function design. The best voltage vector is selected by minimising the value of the cost function, which aims to achieve a low torque ripple in two intervals. The study is carried out experimentally. The results show that the proposed method achieves good performance in both steady and transient states.

  13. Embryo quality predictive models based on cumulus cells gene expression

    Directory of Open Access Journals (Sweden)

    Devjak R

    2016-06-01

    Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

  14. Validation of Biomarker-based risk prediction models

    OpenAIRE

    Taylor, Jeremy M.G.; Ankerst, Donna P.; Andridge, Rebecca R.

    2008-01-01

    The increasing availability and use of predictive models to facilitate informed decision making highlights the need for careful assessment of the validity of these models. In particular, models involving biomarkers require careful validation for two reasons: issues with overfitting when complex models involve a large number of biomarkers, and inter-laboratory variation in assays used to measure biomarkers. In this paper we distinguish between internal and external statistical validation. Inte...

  15. Prediction error, ketamine and psychosis: An updated model.

    Science.gov (United States)

    Corlett, Philip R; Honey, Garry D; Fletcher, Paul C

    2016-11-01

    In 2007, we proposed an explanation of delusion formation as aberrant prediction error-driven associative learning. Further, we argued that the NMDA receptor antagonist ketamine provided a good model for this process. Subsequently, we validated the model in patients with psychosis, relating aberrant prediction error signals to delusion severity. During the ensuing period, we have developed these ideas, drawing on the simple principle that brains build a model of the world and refine it by minimising prediction errors, as well as using it to guide perceptual inferences. While previously we focused on the prediction error signal per se, an updated view takes into account its precision, as well as the precision of prior expectations. With this expanded perspective, we see several possible routes to psychotic symptoms - which may explain the heterogeneity of psychotic illness, as well as the fact that other drugs, with different pharmacological actions, can produce psychotomimetic effects. In this article, we review the basic principles of this model and highlight specific ways in which prediction errors can be perturbed, in particular considering the reliability and uncertainty of predictions. The expanded model explains hallucinations as perturbations of the uncertainty mediated balance between expectation and prediction error. Here, expectations dominate and create perceptions by suppressing or ignoring actual inputs. Negative symptoms may arise due to poor reliability of predictions in service of action. By mapping from biology to belief and perception, the account proffers new explanations of psychosis. However, challenges remain. We attempt to address some of these concerns and suggest future directions, incorporating other symptoms into the model, building towards better understanding of psychosis. © The Author(s) 2016.

  16. Differential effects of a dual orexin receptor antagonist (SB-649868) and zolpidem on sleep initiation and consolidation, SWS, REM sleep, and EEG power spectra in a model of situational insomnia.

    Science.gov (United States)

    Bettica, Paolo; Squassante, Lisa; Groeger, John A; Gennery, Brian; Winsky-Sommerer, Raphaelle; Dijk, Derk-Jan

    2012-04-01

    Orexins have a role in sleep regulation, and orexin receptor antagonists are under development for the treatment of insomnia. We conducted a randomised, double-blind, placebo-controlled, four-period crossover study to investigate the effect of single doses of the dual orexin receptor antagonist SB-649868 (10 or 30 mg) and a positive control zolpidem (10 mg), an allosteric modulator of GABA(A) receptors. Objective and subjective sleep parameters and next-day performance were assessed in 51 healthy male volunteers in a traffic noise model of situational insomnia. Compared with placebo, SB-649868 10 and 30 mg increased total sleep time (TST) by 17 and 31 min (peffects on sleep structure and the EEG that are different from those of zolpidem.

  17. A Novel Technique to Calculate UV Opacity at Gale Crater from MSL/REMS Measurements

    Science.gov (United States)

    Vicente-Retortillo, Álvaro; Martínez, Germán M.; Renno, Nilton O.; Lemmon, Mark T.; Mason, Emily L.; de la Torre-Juárez, Manuel

    2016-04-01

    The Rover Environmental Monitoring Station (REMS) on board the Mars Science Laboratory (MSL) mission carries a UV sensor that for the first time is measuring the solar radiation at the surface of Mars in six bands between 200 and 380 nm [1]. Here we present a novel methodology to calculate the atmospheric opacity by using the UV photodiode output currents measured by this sensor (TELRDR products) and ancillary (ADR) data. We estimate the diffuse and total radiation signals by analyzing the events in which the direct solar beam was temporarily blocked by the masthead or by the mast of the rover. Then we use a radiative transfer model with updated radiative properties of the Martian aerosols ([2], [3]) based on the Monte-Carlo method to retrieve the UV opacity from those measurements. Therefore, this methodology is not sensitive to the degradation of the sensor due to the deposition of dust on it. In addition, by using TELRDR and ADR data, inconsistencies in the processed reduced data (ENVRDR and MODRDR products, in units of W/m2) found when the solar zenith angle relative to REMS rover frame is above 30° are avoided. In order to validate our technique, we compare the UV opacities with those derived from Mastcam observations at 880 nm. We find that both opacities show a good agreement and follow a similar seasonal trend, with the UV opacity showing values generally lower than at 880 nm. The difference between both opacities varies over the year, with the minimum difference occurring during the first half of the winter, when both opacities show their annual lowest values. The temporal variation of this difference may be used to analyze changes in the dust size distribution. [1] Gómez-Elvira, J., Armiens, C., Castañer, L., Domínguez, M., Genzer, M. et al. REMS: the environmental sensor suite for the Mars Science Laboratory rover. Space Sci. Rev., 170 (1-4), 583-640, 2012. [2] Vicente-Retortillo, A., Valero, F., Vázquez, L. and Martínez, G. M. A model to calculate

  18. Predicting Solar Cycle 25 using Surface Flux Transport Model

    Science.gov (United States)

    Imada, Shinsuke; Iijima, Haruhisa; Hotta, Hideyuki; Shiota, Daiko; Kusano, Kanya

    2017-08-01

    It is thought that the longer-term variations of the solar activity may affect the Earth’s climate. Therefore, predicting the next solar cycle is crucial for the forecast of the “solar-terrestrial environment”. To build prediction schemes for the next solar cycle is a key for the long-term space weather study. Recently, the relationship between polar magnetic field at the solar minimum and next solar activity is intensively discussed. Because we can determine the polar magnetic field at the solar minimum roughly 3 years before the next solar maximum, we may discuss the next solar cycle 3years before. Further, the longer term (~5 years) prediction might be achieved by estimating the polar magnetic field with the Surface Flux Transport (SFT) model. Now, we are developing a prediction scheme by SFT model as a part of the PSTEP (Project for Solar-Terrestrial Environment Prediction) and adapting to the Cycle 25 prediction. The predicted polar field strength of Cycle 24/25 minimum is several tens of percent smaller than Cycle 23/24 minimum. The result suggests that the amplitude of Cycle 25 is weaker than the current cycle. We also try to obtain the meridional flow, differential rotation, and turbulent diffusivity from recent modern observations (Hinode and Solar Dynamics Observatory). These parameters will be used in the SFT models to predict the polar magnetic fields strength at the solar minimum. In this presentation, we will explain the outline of our strategy to predict the next solar cycle and discuss the initial results for Cycle 25 prediction.

  19. Predicting soil acidification trends at Plynlimon using the SAFE model

    Directory of Open Access Journals (Sweden)

    B. Reynolds

    1997-01-01

    Full Text Available The SAFE model has been applied to an acid grassland site, located on base-poor stagnopodzol soils derived from Lower Palaeozoic greywackes. The model predicts that acidification of the soil has occurred in response to increased acid deposition following the industrial revolution. Limited recovery is predicted following the decline in sulphur deposition during the mid to late 1970s. Reducing excess sulphur and NOx deposition in 1998 to 40% and 70% of 1980 levels results in further recovery but soil chemical conditions (base saturation, soil water pH and ANC do not return to values predicted in pre-industrial times. The SAFE model predicts that critical loads (expressed in terms of the (Ca+Mg+K:Alcrit ratio for six vegetation species found in acid grassland communities are not exceeded despite the increase in deposited acidity following the industrial revolution. The relative growth response of selected vegetation species characteristic of acid grassland swards has been predicted using a damage function linking growth to soil solution base cation to aluminium ratio. The results show that very small growth reductions can be expected for 'acid tolerant' plants growing in acid upland soils. For more sensitive species such as Holcus lanatus, SAFE predicts that growth would have been reduced by about 20% between 1951 and 1983, when acid inputs were greatest. Recovery to c. 90% of normal growth (under laboratory conditions is predicted as acidic inputs decline.

  20. H-reflex suppression and autonomic activation during lucid REM sleep: a case study.

    Science.gov (United States)

    Brylowski, A; Levitan, L; LaBerge, S

    1989-08-01

    A single subject, a proficient lucid dreamer experienced with signaling the onset of lucidity (reflective consciousness of dreaming) by means of voluntary eye movements, spent 4 nonconsecutive nights in the sleep laboratory. The subject reported becoming lucid and signaling in 8 of the 18 rapid-eye movement (REM) periods recorded. Ten lucid dream reports were verified by polygraphic examination of signals, providing a total of 12.5 min of signal-verified lucid REM. H-Reflex amplitude was recorded every 5 s, along with continuous recording of electroencephalogram, electrooculogram, electromyogram, electrocardiogram, finger pulse, and respiration. Significant findings included greater mean H-reflex suppression during lucid REM sleep than during nonlucid REM and correlations of H-reflex suppression with increased eye movement density, heart rate, and respiration rate. These results support previous studies reporting that lucid REM is not, as might be supposed, a state closer to awakening than ordinary, or nonlucid, REM; rather, lucid dreaming occurs during unequivocal REM sleep and is characteristically associated with phasic REM activation.

  1. The supramammillary nucleus and the claustrum activate the cortex during REM sleep.

    Science.gov (United States)

    Renouard, Leslie; Billwiller, Francesca; Ogawa, Keiko; Clément, Olivier; Camargo, Nutabi; Abdelkarim, Mouaadh; Gay, Nadine; Scoté-Blachon, Céline; Touré, Rouguy; Libourel, Paul-Antoine; Ravassard, Pascal; Salvert, Denise; Peyron, Christelle; Claustrat, Bruno; Léger, Lucienne; Salin, Paul; Malleret, Gael; Fort, Patrice; Luppi, Pierre-Hervé

    2015-04-01

    Evidence in humans suggests that limbic cortices are more active during rapid eye movement (REM or paradoxical) sleep than during waking, a phenomenon fitting with the presence of vivid dreaming during this state. In that context, it seemed essential to determine which populations of cortical neurons are activated during REM sleep. Our aim in the present study is to fill this gap by combining gene expression analysis, functional neuroanatomy, and neurochemical lesions in rats. We find in rats that, during REM sleep hypersomnia compared to control and REM sleep deprivation, the dentate gyrus, claustrum, cortical amygdaloid nucleus, and medial entorhinal and retrosplenial cortices are the only cortical structures containing neurons with an increased expression of Bdnf, FOS, and ARC, known markers of activation and/or synaptic plasticity. Further, the dentate gyrus is the only cortical structure containing more FOS-labeled neurons during REM sleep hypersomnia than during waking. Combining FOS staining, retrograde labeling, and neurochemical lesion, we then provide evidence that FOS overexpression occurring in the cortex during REM sleep hypersomnia is due to projections from the supramammillary nucleus and the claustrum. Our results strongly suggest that only a subset of cortical and hippocampal neurons are activated and display plasticity during REM sleep by means of ascending projections from the claustrum and the supramammillary nucleus. Our results pave the way for future studies to identify the function of REM sleep with regard to dreaming and emotional memory processing.

  2. REM sleep deprivation inhibits LTP in vivo in area CA1 of rat hippocampus.

    Science.gov (United States)

    Kim, Eun Young; Mahmoud, Ghada S; Grover, Lawrence M

    2005-11-18

    Rapid eye movement (REM) sleep deprivation has previously been shown to interfere with normal learning and memory and to inhibit long-term potentiation (LTP) in vitro. Previous studies on REM sleep deprivation and LTP have relied on in vitro analysis in isolated brain slices taken from animals following several days of sleep deprivation. LTP in the hippocampus in situ may differ from LTP in vitro due to modulatory inputs from other brain regions, which are altered after REM sleep deprivation. Here, we examined LTP in unanesthetized, behaving animals on the first and second recovery days following REM sleep deprivation to determine if similar effects are seen in vivo as previously reported in vitro. We found that LTP was significantly impaired in REM sleep-deprived animals on the second recovery day but not the first recovery day. Our results extend previous findings by showing that REM sleep deprivation continues to affect hippocampal function for more than 24h following the end of deprivation. Our results also suggest the presence of a modulatory process not present in vitro. Our findings are not explained by stress during REM sleep deprivation because equivalent circulating corticosterone levels (an index of stress) were found during both REM sleep deprivation and control treatment.

  3. Physics-Informed Machine Learning for Predictive Turbulence Modeling: A Priori Assessment of Prediction Confidence

    CERN Document Server

    Wu, Jin-Long; Xiao, Heng; Ling, Julia

    2016-01-01

    Although Reynolds-Averaged Navier-Stokes (RANS) equations are still the dominant tool for engineering design and analysis applications involving turbulent flows, standard RANS models are known to be unreliable in many flows of engineering relevance, including flows with separation, strong pressure gradients or mean flow curvature. With increasing amounts of 3-dimensional experimental data and high fidelity simulation data from Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS), data-driven turbulence modeling has become a promising approach to increase the predictive capability of RANS simulations. Recently, a data-driven turbulence modeling approach via machine learning has been proposed to predict the Reynolds stress anisotropy of a given flow based on high fidelity data from closely related flows. In this work, the closeness of different flows is investigated to assess the prediction confidence a priori. Specifically, the Mahalanobis distance and the kernel density estimation (KDE) technique...

  4. Extended Range Hydrological Predictions: Uncertainty Associated with Model Parametrization

    Science.gov (United States)

    Joseph, J.; Ghosh, S.; Sahai, A. K.

    2016-12-01

    The better understanding of various atmospheric processes has led to improved predictions of meteorological conditions at various temporal scale, ranging from short term which cover a period up to 2 days to long term covering a period of more than 10 days. Accurate prediction of hydrological variables can be done using these predicted meteorological conditions, which would be helpful in proper management of water resources. Extended range hydrological simulation includes the prediction of hydrological variables for a period more than 10 days. The main sources of uncertainty in hydrological predictions include the uncertainty in the initial conditions, meteorological forcing and model parametrization. In the present study, the Extended Range Prediction developed for India for monsoon by Indian Institute of Tropical Meteorology (IITM), Pune is used as meteorological forcing for the Variable Infiltration Capacity (VIC) model. Sensitive hydrological parameters, as derived from literature, along with a few vegetation parameters are assumed to be uncertain and 1000 random values are generated given their prescribed ranges. Uncertainty bands are generated by performing Monte-Carlo Simulations (MCS) for the generated sets of parameters and observed meteorological forcings. The basins with minimum human intervention, within the Indian Peninsular region, are identified and validation of results are carried out using the observed gauge discharge. Further, the uncertainty bands are generated for the extended range hydrological predictions by performing MCS for the same set of parameters and extended range meteorological predictions. The results demonstrate the uncertainty associated with the model parametrisation for the extended range hydrological simulations. Keywords: Extended Range Prediction, Variable Infiltration Capacity model, Monte Carlo Simulation.

  5. Predictive modeling of coral disease distribution within a reef system.

    Directory of Open Access Journals (Sweden)

    Gareth J Williams

    Full Text Available Diseases often display complex and distinct associations with their environment due to differences in etiology, modes of transmission between hosts, and the shifting balance between pathogen virulence and host resistance. Statistical modeling has been underutilized in coral disease research to explore the spatial patterns that result from this triad of interactions. We tested the hypotheses that: 1 coral diseases show distinct associations with multiple environmental factors, 2 incorporating interactions (synergistic collinearities among environmental variables is important when predicting coral disease spatial patterns, and 3 modeling overall coral disease prevalence (the prevalence of multiple diseases as a single proportion value will increase predictive error relative to modeling the same diseases independently. Four coral diseases: Porites growth anomalies (PorGA, Porites tissue loss (PorTL, Porites trematodiasis (PorTrem, and Montipora white syndrome (MWS, and their interactions with 17 predictor variables were modeled using boosted regression trees (BRT within a reef system in Hawaii. Each disease showed distinct associations with the predictors. Environmental predictors showing the strongest overall associations with the coral diseases were both biotic and abiotic. PorGA was optimally predicted by a negative association with turbidity, PorTL and MWS by declines in butterflyfish and juvenile parrotfish abundance respectively, and PorTrem by a modal relationship with Porites host cover. Incorporating interactions among predictor variables contributed to the predictive power of our models, particularly for PorTrem. Combining diseases (using overall disease prevalence as the model response, led to an average six-fold increase in cross-validation predictive deviance over modeling the diseases individually. We therefore recommend coral diseases to be modeled separately, unless known to have etiologies that respond in a similar manner to

  6. A CHAID Based Performance Prediction Model in Educational Data Mining

    Directory of Open Access Journals (Sweden)

    R. Bhaskaran

    2010-01-01

    Full Text Available The performance in higher secondary school education in India is a turning point in the academic lives of all students. As this academic performance is influenced by many factors, it is essential to develop predictive data mining model for students' performance so as to identify the slow learners and study the influence of the dominant factors on their academic performance. In the present investigation, a survey cum experimental methodology was adopted to generate a database and it was constructed from a primary and a secondary source. While the primary data was collected from the regular students, the secondary data was gathered from the school and office of the Chief Educational Officer (CEO. A total of 1000 datasets of the year 2006 from five different schools in three different districts of Tamilnadu were collected. The raw data was preprocessed in terms of filling up missing values, transforming values in one form into another and relevant attribute/ variable selection. As a result, we had 772 student records, which were used for CHAID prediction model construction. A set of prediction rules were extracted from CHIAD prediction model and the efficiency of the generated CHIAD prediction model was found. The accuracy of the present model was compared with other model and it has been found to be satisfactory.

  7. Precise methods for conducted EMI modeling,analysis,and prediction

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Focusing on the state-of-the-art conducted EMI prediction, this paper presents a noise source lumped circuit modeling and identification method, an EMI modeling method based on multiple slope approximation of switching transitions, and dou-ble Fourier integral method modeling PWM conversion units to achieve an accurate modeling of EMI noise source. Meanwhile, a new sensitivity analysis method, a general coupling model for steel ground loops, and a partial element equivalent circuit method are proposed to identify and characterize conducted EMI coupling paths. The EMI noise and propagation modeling provide an accurate prediction of conducted EMI in the entire frequency range (0―10 MHz) with good practicability and generality. Finally a new measurement approach is presented to identify the surface current of large dimensional metal shell. The proposed analytical modeling methodology is verified by experimental results.

  8. Precise methods for conducted EMI modeling,analysis, and prediction

    Institute of Scientific and Technical Information of China (English)

    MA WeiMing; ZHAO ZhiHua; MENG Jin; PAN QiJun; ZHANG Lei

    2008-01-01

    Focusing on the state-of-the-art conducted EMI prediction, this paper presents a noise source lumped circuit modeling and identification method, an EMI modeling method based on multiple slope approximation of switching transitions, and dou-ble Fourier integral method modeling PWM conversion units to achieve an accurate modeling of EMI noise source. Meanwhile, a new sensitivity analysis method, a general coupling model for steel ground loops, and a partial element equivalent circuit method are proposed to identify and characterize conducted EMI coupling paths. The EMI noise and propagation modeling provide an accurate prediction of conducted EMI in the entire frequency range (0-10 MHz) with good practicability and generality. Finally a new measurement approach is presented to identify the surface current of large dimensional metal shell. The proposed analytical modeling methodology is verified by experimental results.

  9. Predictive Control, Competitive Model Business Planning, and Innovation ERP

    DEFF Research Database (Denmark)

    Nourani, Cyrus F.; Lauth, Codrina

    2015-01-01

    is not viewed as the sum of its component elements, but the product of their interactions. The paper starts with introducing a systems approach to business modeling. A competitive business modeling technique, based on the author's planning techniques is applied. Systemic decisions are based on common......New optimality principles are put forth based on competitive model business planning. A Generalized MinMax local optimum dynamic programming algorithm is presented and applied to business model computing where predictive techniques can determine local optima. Based on a systems model an enterprise...... Loops, are applied to complex management decisions. Predictive modeling specifics are briefed. A preliminary optimal game modeling technique is presented in brief with applications to innovation and R&D management. Conducting gap and risk analysis can assist with this process. Example application areas...

  10. Predicting nucleosome positioning using a duration Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Widom Jonathan

    2010-06-01

    Full Text Available Abstract Background The nucleosome is the fundamental packing unit of DNAs in eukaryotic cells. Its detailed positioning on the genome is closely related to chromosome functions. Increasing evidence has shown that genomic DNA sequence itself is highly predictive of nucleosome positioning genome-wide. Therefore a fast software tool for predicting nucleosome positioning can help understanding how a genome's nucleosome organization may facilitate genome function. Results We present a duration Hidden Markov model for nucleosome positioning prediction by explicitly modeling the linker DNA length. The nucleosome and linker models trained from yeast data are re-scaled when making predictions for other species to adjust for differences in base composition. A software tool named NuPoP is developed in three formats for free download. Conclusions Simulation studies show that modeling the linker length distribution and utilizing a base composition re-scaling method both improve the prediction of nucleosome positioning regarding sensitivity and false discovery rate. NuPoP provides a user-friendly software tool for predicting the nucleosome occupancy and the most probable nucleosome positioning map for genomic sequences of any size. When compared with two existing methods, NuPoP shows improved performance in sensitivity.

  11. Experience-based model predictive control using reinforcement learning

    NARCIS (Netherlands)

    Negenborn, R.R.; De Schutter, B.; Wiering, M.A.; Hellendoorn, J.

    2004-01-01

    Model predictive control (MPC) is becoming an increasingly popular method to select actions for controlling dynamic systems. TraditionallyMPC uses a model of the system to be controlled and a performance function to characterize the desired behavior of the system. The MPC agent finds actions over a

  12. Evaluation of preformance of Predictive Models for Deoxynivalenol in Wheat

    NARCIS (Netherlands)

    Fels, van der H.J.

    2014-01-01

    The aim of this study was to evaluate the performance of two predictive models for deoxynivalenol contamination of wheat at harvest in the Netherlands, including the use of weather forecast data and external model validation. Data were collected in a different year and from different wheat fields th

  13. Katz model prediction of Caenorhabditis elegans mutagenesis on STS-42

    Science.gov (United States)

    Cucinotta, Francis A.; Wilson, John W.; Katz, Robert; Badhwar, Gautam D.

    1992-01-01

    Response parameters that describe the production of recessive lethal mutations in C. elegans from ionizing radiation are obtained with the Katz track structure model. The authors used models of the space radiation environment and radiation transport to predict and discuss mutation rates for C. elegans on the IML-1 experiment aboard STS-42.

  14. A model to predict the sound reflection from forests

    NARCIS (Netherlands)

    Wunderli, J.M.; Salomons, E.M.

    2009-01-01

    A model is presented to predict the reflection of sound at forest edges. A single tree is modelled as a vertical cylinder. For the reflection at a cylinder an analytical solution is given based on the theory of scattering of spherical waves. The entire forest is represented by a line of cylinders

  15. Atmospheric modelling for seasonal prediction at the CSIR

    CSIR Research Space (South Africa)

    Landman, WA

    2014-10-01

    Full Text Available by observed monthly sea-surface temperature (SST) and sea-ice fields. The AGCM is the conformal-cubic atmospheric model (CCAM) administered by the Council for Scientific and Industrial Research. Since the model is forced with observed rather than predicted...

  16. A model to predict the sound reflection from forests

    NARCIS (Netherlands)

    Wunderli, J.M.; Salomons, E.M.

    2009-01-01

    A model is presented to predict the reflection of sound at forest edges. A single tree is modelled as a vertical cylinder. For the reflection at a cylinder an analytical solution is given based on the theory of scattering of spherical waves. The entire forest is represented by a line of cylinders pl

  17. Validation of a multi-objective, predictive urban traffic model

    NARCIS (Netherlands)

    Wilmink, I.R.; Haak, P. van den; Woldeab, Z.; Vreeswijk, J.

    2013-01-01

    This paper describes the results of the verification and validation of the ecoStrategic Model, which was developed, implemented and tested in the eCoMove project. The model uses real-time and historical traffic information to determine the current, predicted and desired state of traffic in a network

  18. Prediction of speech intelligibility based on an auditory preprocessing model

    DEFF Research Database (Denmark)

    Christiansen, Claus Forup Corlin; Pedersen, Michael Syskind; Dau, Torsten

    2010-01-01

    in noise experiment was used for training and an ideal binary mask experiment was used for evaluation. All three models were able to capture the trends in the speech in noise training data well, but the proposed model provides a better prediction of the binary mask test data, particularly when the binary...... masks degenerate to a noise vocoder....

  19. Evaluation of preformance of Predictive Models for Deoxynivalenol in Wheat

    NARCIS (Netherlands)

    Fels, van der H.J.

    2014-01-01

    The aim of this study was to evaluate the performance of two predictive models for deoxynivalenol contamination of wheat at harvest in the Netherlands, including the use of weather forecast data and external model validation. Data were collected in a different year and from different wheat fields

  20. A Climate System Model, Numerical Simulation and Climate Predictability

    Institute of Scientific and Technical Information of China (English)

    ZENG Qingcun; WANG Huijun; LIN Zhaohui; ZHOU Guangqing; YU Yongqiang

    2007-01-01

    @@ The implementation of the project has lasted for more than 20 years. As a result, the following key innovative achievements have been obtained, ranging from the basic theory of climate dynamics, numerical model development and its related computational theory to the dynamical climate prediction using the climate system models: