Aranha Junior, Ayrton Alves; Arend, Lavinia Nery; Ribeiro, Vanessa; Zavascki, Alexandre Prehn; Tuon, Felipe Francisco
2015-01-01
This study evaluated the efficacy of tigecycline (TIG), polymyxin B (PMB), and meropenem (MER) in 80 rats challenged with Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae infection. A time-kill assay was performed with the same strain. Triple therapy and PMB+TIG were synergistic, promoted 100% survival, and produced negative peritoneal cultures, while MER+TIG showed lower survival and higher culture positivity than other regimens (P = 0.018) and was antagonistic. In vivo and in vitro studies showed that combined regimens, except MER+TIG, were more effective than monotherapies for this KPC-producing strain. PMID:25896686
Study on Calculation Model of Time Producing Runoff in Winter Wheat Farmland%麦田降雨产流时间计算模型研究
Institute of Scientific and Technical Information of China (English)
刘战东; 高阳; 巩文军; 段爱旺
2012-01-01
In order to study the effects of several influence factors on time producing runoff and the corresponding quantitative relationships, the influence of rainfall intensity, canopy cover and initial soil moisture profile on the time producing runoff in the winter wheat farmland was studied by simulated rainfall. The results indicated that in the same initial soil moisture profile conditions, the rainfall intensity and time producing runoff was a significant power function (P〈0.01). Correlation function between Leaf area index (LAI) and time producing runoff was linear, and reached a significant level, but plant height associated poorly with time producing runoff. The soil moisture at 0~20 cm, 0~40 cm showed more obvious positive linear correlation with time producing runoff (P〈0.01), the effect of initial soil moisture below 40 cm on the time producing runoff was relatively smaller. Considering all factors, through multiple regression analysis, calculation power of function model for time producing runoff in the winter wheat farmland was established. Upon examination, the model had good simulation results.%为探讨多种因素对麦田降雨产流时间的影响及其相应的定量关系，通过模拟降雨试验，研究了麦田降雨强度、冠层覆盖及初始土壤剖面含水量对降雨产流时间的影响。结果表明，在相同初始土壤剖面含水状态条件下，降雨强度与产流时间呈显著幂函数关系（P〈0.01）；产流时间与叶面积指数呈极显著线性正相关（P〈0.01），与株高相关性较差； 0~20、0~40 cm土层初始土壤剖面含水量与产流时间具有较明显的线性正相关关系（P〈0.01），40 cm以下土层土壤含水量对产流时间影响相对较小。通过多元回归分析建立的产流时间幂函数计算模型具有较好的模拟效果。
Monetary Shocks in Models with Inattentive Producers.
Alvarez, Fernando E; Lippi, Francesco; Paciello, Luigi
2016-04-01
We study models where prices respond slowly to shocks because firms are rationally inattentive. Producers must pay a cost to observe the determinants of the current profit maximizing price, and hence observe them infrequently. To generate large real effects of monetary shocks in such a model the time between observations must be long and/or highly volatile. Previous work on rational inattentiveness has allowed for observation intervals that are either constant-but-long (e.g. Caballero, 1989 or Reis, 2006) or volatile-but-short (e.g. Reis's, 2006 example where observation costs are negligible), but not both. In these models, the real effects of monetary policy are small for realistic values of the duration between observations. We show that non-negligible observation costs produce both of these effects: intervals between observations are infrequent and volatile. This generates large real effects of monetary policy for realistic values of the average time between observations.
Regular transport dynamics produce chaotic travel times.
Villalobos, Jorge; Muñoz, Víctor; Rogan, José; Zarama, Roberto; Johnson, Neil F; Toledo, Benjamín; Valdivia, Juan Alejandro
2014-06-01
In the hope of making passenger travel times shorter and more reliable, many cities are introducing dedicated bus lanes (e.g., Bogota, London, Miami). Here we show that chaotic travel times are actually a natural consequence of individual bus function, and hence of public transport systems more generally, i.e., chaotic dynamics emerge even when the route is empty and straight, stops and lights are equidistant and regular, and loading times are negligible. More generally, our findings provide a novel example of chaotic dynamics emerging from a single object following Newton's laws of motion in a regularized one-dimensional system.
Continuous Time Model Estimation
Carl Chiarella; Shenhuai Gao
2004-01-01
This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the trend model by simulation, and how to calculate standard errors from estimation of the noise model. It also discusses the numerical difficulties involved in discrete time models that bring about the unit ...
Gap timing and the spectral timing model.
Hopson, J W
1999-04-01
A hypothesized mechanism underlying gap timing was implemented in the Spectral Timing Model [Grossberg, S., Schmajuk, N., 1989. Neural dynamics of adaptive timing and temporal discrimination during associative learning. Neural Netw. 2, 79-102] , a neural network timing model. The activation of the network nodes was made to decay in the absence of the timed signal, causing the model to shift its peak response time in a fashion similar to that shown in animal subjects. The model was then able to accurately simulate a parametric study of gap timing [Cabeza de Vaca, S., Brown, B., Hemmes, N., 1994. Internal clock and memory processes in aminal timing. J. Exp. Psychol.: Anim. Behav. Process. 20 (2), 184-198]. The addition of a memory decay process appears to produce the correct pattern of results in both Scalar Expectancy Theory models and in the Spectral Timing Model, and the fact that the same process should be effective in two such disparate models argues strongly that process reflects a true aspect of animal cognition.
Directory of Open Access Journals (Sweden)
Oleg Svatos
2013-01-01
Full Text Available In this paper we analyze complexity of time limits we can find especially in regulated processes of public administration. First we review the most popular process modeling languages. There is defined an example scenario based on the current Czech legislature which is then captured in discussed process modeling languages. Analysis shows that the contemporary process modeling languages support capturing of the time limit only partially. This causes troubles to analysts and unnecessary complexity of the models. Upon unsatisfying results of the contemporary process modeling languages we analyze the complexity of the time limits in greater detail and outline lifecycles of a time limit using the multiple dynamic generalizations pattern. As an alternative to the popular process modeling languages there is presented PSD process modeling language, which supports the defined lifecycles of a time limit natively and therefore allows keeping the models simple and easy to understand.
Producing complex spoken numerals for time and space
Meeuwissen, M.H.W.
2004-01-01
This thesis addressed the spoken production of complex numerals for time and space. The production of complex numerical expressions like those involved in telling time (e.g., 'quarter to four') or producing house numbers (e.g., 'two hundred forty-five') has been almost completely ignored. Yet, adult
Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)
2004-01-01
textabstractThis book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book
How to produce flat slabs: insights from numeric modeling
Constantin Manea, Vlad; Perez-Gussinye, Marta; Manea, Marina
2010-05-01
Flat slab subduction occurs at ~10% of the active convergent margins and it is assumed that subduction of oceanic aseismic ridges or seamount chains is the main mechanism to produce very low angle subduction slabs. However, recent numeric and analog modeling showed that ridges alone of moderate dimensions subducted perpendicular to the trench are not sufficient to produce flat-slab geometries. Therefore an alternative mechanism able to produce flat-slabs is required. In this paper we present dynamic numeric modeling results of subduction in the vicinity of thick continental lithosphere, as a craton for example. We tailored our modeling setup for the Chilean margins at ~31° and our models are integrated back in time 30 Myr. Modeling results show that a craton thickness of 200 km or more when approaching the trench is capable of blocking the asthenospheric flow in the mantle wedge and increasing considerably the suction force. We were able to produce a flat slab that fits well the flat slab geometry in Chile (based on seismicity) and stress distribution. We conclude that thick cratons located in the vicinity of subduction zones, are capable to produce very low angle slabs, and probable a combination of buoyant ridge subduction with a neighbor thick craton represent a better mechanism to produce flat slabs.
Data Producers Courting Data Reusers: Two Cases from Modeling Communities
Directory of Open Access Journals (Sweden)
Jillian Wallis
2014-07-01
Full Text Available Data sharing is a difficult process for both the data producer and the data reuser. Both parties are faced with more disincentives than incentives. Data producers need to sink time and resources into adding metadata for data to be findable and usable, and there is no promise of receiving credit for this effort. Making data available also leaves data producers vulnerable to being scooped or data misuse. Data reusers also need to sink time and resources into evaluating data and trying to understand them, making collecting their own data a more attractive option. In spite of these difficulties, some data producers are looking for new ways to make data sharing and reuse a more viable option. This paper presents two cases from the surface and climate modeling communities, where researchers who produce data are reaching out to other researchers who would be interested in reusing the data. These cases are evaluated as a strategy to identify ways to overcome the challenges typically experienced by both data producers and data reusers. By working together with reusers, data producers are able to mitigate the disincentives and create incentives for sharing data. By working with data producers, data reusers are able to circumvent the hurdles that make data reuse so challenging.
The relativity of time perception produced by facial emotion stimuli.
Lee, Kwang-Hyuk; Seelam, Kalyan; O'Brien, Tom
2011-12-01
We systematically examined the impact of emotional stimuli on time perception in a temporal reproduction paradigm where participants reproduced the duration of a facial emotion stimulus using an oval-shape stimulus or vice versa. Experiment 1 asked participants to reproduce the duration of an angry face (or the oval) presented for 2,000 ms. Experiment 2 included a range of emotional expressions (happy, sad, angry, and neutral faces as well as the oval stimulus) presented for different durations (500, 1,500, and 2,000 ms). We found that participants over-reproduced the durations of happy and sad faces using the oval stimulus. By contrast, there was a trend of under-reproduction when the duration of the oval stimulus was reproduced using the angry face. We suggest that increased attention to a facial emotion produces the relativity of time perception.
Zheng, F.
2011-01-01
Urban travel times are intrinsically uncertain due to a lot of stochastic characteristics of traffic, especially at signalized intersections. A single travel time does not have much meaning and is not informative to drivers or traffic managers. The range of travel times is large such that certain tr
Zheng, F.
2011-01-01
Urban travel times are intrinsically uncertain due to a lot of stochastic characteristics of traffic, especially at signalized intersections. A single travel time does not have much meaning and is not informative to drivers or traffic managers. The range of travel times is large such that certain
Zheng, F.
2011-01-01
Urban travel times are intrinsically uncertain due to a lot of stochastic characteristics of traffic, especially at signalized intersections. A single travel time does not have much meaning and is not informative to drivers or traffic managers. The range of travel times is large such that certain tr
Introduction to Time Series Modeling
Kitagawa, Genshiro
2010-01-01
In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f
Time-Correlated Particles Produced by Cosmic Rays
Energy Technology Data Exchange (ETDEWEB)
Chapline, George F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Glenn, Andrew M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nakae, Les F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pawelczak, Iwona [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Snyderman, Neal J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sheets, Steven A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wurtz, Ron E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-05-06
This report describes the NA-22 supported cosmic ray experimental and analysis activities carried out at LLNL since the last report, dated October 1, 2013. In particular we report on an analysis of the origin of the plastic scintillator signals resembling the signals produced by minimum ionizing particles (MIPs). Our most notable result is that when measured in coincidence with a liquid scintillator neutron signal the MIP-like signals in the plastic scintillators are mainly due to high energy tertiary neutrons.
Electric Potential in a Dielectric Sphere Head Produced by a Time-Harmonic Equivalent Current Dipole
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A time-harmonic equivalent current dipole model is proposed to simulate EEG source which deals with the problem concerning the capacitance effect. The expressions of potentials in both homogeneous infinite dielectric medium and dielectric sphere on the electroquasistatic condition are presented. The potential in a 3-layer inhomogeneous spherical head is computed by using this model. The influences on potential produced by time-harmonic character and permittivity are discussed. The results show that potentials in dielectric sphere are affected by frequency and permittivity.
Coordination in coteaching: Producing alignment in real time
Roth, Wolff-Michael; Tobin, Kenneth; Carambo, Cristobal; Dalland, Chris
2005-07-01
In coteaching, two or more teachers take collective responsibility for enacting a curriculum together with their students. Past research provided some indication that in the course of coteaching, not only the teaching practices of the partners become increasingly alike but also do unconsciously produced ways of moving about the classroom, hand gestures, and body movements. In this study, we investigate the possible sources of occurrence for the coordination of social and physical practices and provide exemplary episodes at a fine-grained level from one coteaching pair. Drawing on key concepts from cultural sociology, we show how participants continuously create material and social resources that allow for new forms of agency in subsequent moments. Such resources include physical, temporal, and social spaces and meaning-making entities (language, inscriptions). We show how in productive coteaching, participants deploy and take advantage of these resources in synchronized and coordinated ways. The synchronization operates both at the temporal level, where coteachers work in concert like experienced jazz musicians in a jam session, and at a substantive level, where the practices of one look like those of the other. As coteachers generally are not aware that they adopt the ways of their partners as we articulate them here, there are considerable consequences, for better or worse, that arise from teaching with another person.
Distinct timing mechanisms produce discrete and continuous movements.
Directory of Open Access Journals (Sweden)
Raoul Huys
2008-04-01
Full Text Available The differentiation of discrete and continuous movement is one of the pillars of motor behavior classification. Discrete movements have a definite beginning and end, whereas continuous movements do not have such discriminable end points. In the past decade there has been vigorous debate whether this classification implies different control processes. This debate up until the present has been empirically based. Here, we present an unambiguous non-empirical classification based on theorems in dynamical system theory that sets discrete and continuous movements apart. Through computational simulations of representative modes of each class and topological analysis of the flow in state space, we show that distinct control mechanisms underwrite discrete and fast rhythmic movements. In particular, we demonstrate that discrete movements require a time keeper while fast rhythmic movements do not. We validate our computational findings experimentally using a behavioral paradigm in which human participants performed finger flexion-extension movements at various movement paces and under different instructions. Our results demonstrate that the human motor system employs different timing control mechanisms (presumably via differential recruitment of neural subsystems to accomplish varying behavioral functions such as speed constraints.
Models for dependent time series
Tunnicliffe Wilson, Granville; Haywood, John
2015-01-01
Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater
Multi-model Cross Pollination in Time
Du, Hailiang
2016-01-01
Predictive skill of complex models is often not uniform in model-state space; in weather forecasting models, for example, the skill of the model can be greater in populated regions of interest than in "remote" regions of the globe. Given a collection of models, a multi-model forecast system using the cross pollination in time approach can be generalised to take advantage of instances where some models produce systematically more accurate forecast of some components of the model-state. This generalisation is stated and then successfully demonstrated in a moderate ~40 dimensional nonlinear dynamical system suggested by Lorenz. In this demonstration four imperfect models, each with similar global forecast skill, are used. Future applications in weather forecasting and in economic forecasting are discussed. The demonstration establishes that cross pollinating forecast trajectories to enrich the collection of simulations upon which the forecast is built can yield a new forecast system with significantly more skill...
Video Editing and Medication to Produce a Therapeutic Self Model
Dowrick, Peter W.; Raeburn, John M.
1977-01-01
Self-modeling requires the production of a videotape in which the subject is seen to perform in a model way. A 4-year-old "hyperactive" boy, initially under psychotropic medication, was unable to role play suitable behaviors. Video editing was used to produce a videotape that when watched by the subject, had therapeutic effects as compared with an…
Producing a Set of Models for the Iron Homeostasis Network
Directory of Open Access Journals (Sweden)
Nicolas Mobilia
2013-08-01
Full Text Available This paper presents a method for modeling biological systems which combines formal techniques on intervals, numerical simulations and satisfaction of Signal Temporal Logic (STL formulas. The main modeling challenge addressed by this approach is the large uncertainty in the values of the parameters due to the experimental difficulties of getting accurate biological data. This method considers intervals for each parameter and a formal description of the expected behavior of the model. In a first step, it produces reduced intervals of possible parameter values. Then by performing a systematic search in these intervals, it defines sets of parameter values used in the next step. This procedure aims at finding a sub-space where the model robustly behaves as expected. We apply this method to the modeling of the cellular iron homeostasis network in erythroid progenitors. The produced model describes explicitly the regulation mechanism which acts at the translational level.
Modelling of interference pattern produced by Michelson interferometer
Glebov, Victor; Lashmanov, Oleg
2016-04-01
Using of Michelson interferometer is shown in the field of measurement of periodical displacements of the con-trolled object. The foundations of optical interferometry are presented. The features of Michelson interferometer are described. The mathematical model of interference pattern produced by Michelson interferometer is created. It takes in consideration such parameters as the angles at which the mirrors are located and the lengths of two optical paths.
Timing analysis by model checking
Naydich, Dimitri; Guaspari, David
2000-01-01
The safety of modern avionics relies on high integrity software that can be verified to meet hard real-time requirements. The limits of verification technology therefore determine acceptable engineering practice. To simplify verification problems, safety-critical systems are commonly implemented under the severe constraints of a cyclic executive, which make design an expensive trial-and-error process highly intolerant of change. Important advances in analysis techniques, such as rate monotonic analysis (RMA), have provided a theoretical and practical basis for easing these onerous restrictions. But RMA and its kindred have two limitations: they apply only to verifying the requirement of schedulability (that tasks meet their deadlines) and they cannot be applied to many common programming paradigms. We address both these limitations by applying model checking, a technique with successful industrial applications in hardware design. Model checking algorithms analyze finite state machines, either by explicit state enumeration or by symbolic manipulation. Since quantitative timing properties involve a potentially unbounded state variable (a clock), our first problem is to construct a finite approximation that is conservative for the properties being analyzed-if the approximation satisfies the properties of interest, so does the infinite model. To reduce the potential for state space explosion we must further optimize this finite model. Experiments with some simple optimizations have yielded a hundred-fold efficiency improvement over published techniques.
Model emulates human smooth pursuit system producing zero-latency target tracking.
Bahill, A T; McDonald, J D
1983-01-01
Humans can overcome the 150 ms time delay of the smooth pursuit eye movement system and track smoothly moving visual targets with zero-latency. Our target-selective adaptive control model can also overcome an inherent time delay and produce zero-latency tracking. No other model or man-made system can do this. Our model is physically realizable and physiologically realistic. The technique used in our model should be useful for analyzing other time-delay systems, such as man-machine systems and robots.
Modelling of Attentional Dwell Time
DEFF Research Database (Denmark)
Petersen, Anders; Kyllingsbæk, Søren; Bundesen, Claus
2009-01-01
into the temporal domain. In the neural interpretation of TVA (NTVA; Bundesen, Habekost and Kyllingsbæk, 2005), processing resources are implemented as allocation of cortical cells to objects in the visual field. A feedback mechanism is then used to keep encoded objects in VSTM alive. The proposed model...... of attentional dwell time extends these mechanisms by proposing that the processing resources (cells) already engaged in a feedback loop (i.e. allocated to an object) are locked in VSTM and therefore cannot be allocated to other objects in the visual field before the encoded object has been released...
Transducer model produces facilitation from opposite-sign flanks
Solomon, J. A.; Watson, A. B.; Morgan, M. J.
1999-01-01
Small spots, lines and Gabor patterns can be easier to detect when they are superimposed upon similar spots, lines and Gabor patterns. Traditionally, such facilitation has been understood to be a consequence of nonlinear contrast transduction. Facilitation has also been reported to arise from non-overlapping patterns with opposite sign. We point out that this result does not preclude the traditional explanation for superimposed targets. Moreover, we find that facilitation from opposite-sign flanks is weaker than facilitation from same-sign flanks. Simulations with a transducer model produce opposite-sign facilitation.
Modeling terrestrial gamma ray flashes produced by relativistic feedback discharges
Liu, Ningyu; Dwyer, Joseph R.
2013-05-01
This paper reports a modeling study of terrestrial gamma ray flashes (TGFs) produced by relativistic feedback discharges. Terrestrial gamma ray flashes are intense energetic radiation originating from the Earth's atmosphere that has been observed by spacecraft. They are produced by bremsstrahlung interactions of energetic electrons, known as runaway electrons, with air atoms. An efficient physical mechanism for producing large fluxes of the runaway electrons to make the TGFs is the relativistic feedback discharge, where seed runaway electrons are generated by positrons and X-rays, products of the discharge itself. Once the relativistic feedback discharge becomes self-sustaining, an exponentially increasing number of relativistic electron avalanches propagate through the same high-field region inside the thundercloud until the electric field is partially discharged by the ionization created by the discharge. The modeling results indicate that the durations of the TGF pulses produced by the relativistic feedback discharge vary from tens of microseconds to several milliseconds, encompassing all durations of the TGFs observed so far. In addition, when a sufficiently large potential difference is available in thunderclouds, a self-propagating discharge known as the relativistic feedback streamer can be formed, which propagates like a conventional positive streamer. For the relativistic feedback streamer, the positive feedback mechanism of runaway electron production by the positrons and X-rays plays a similar role as the photoionization for the conventional positive streamer. The simulation results of the relativistic feedback streamer show that a sequence of TGF pulses with varying durations can be produced by the streamer. The relativistic streamer may initially propagate with a pulsed manner and turn into a continuous propagation mode at a later stage. Milliseconds long TGF pulses can be produced by the feedback streamer during its continuous propagation. However
Models of travel time and reliability for freight transport
Energy Technology Data Exchange (ETDEWEB)
Terziev, M.N.; Roberts, P.O.
1976-12-01
The model produces a probability distribution of the trip time associated with the shipment of freight between a given origin and destination by a given mode and route. Using distributions of the type produced by the model, it is possible to determine two important measures of the quality of service offered by the carrier. These measures are the main travel time and the reliability of delivery. The reliability measure describes the spread of the travel-time distribution. The model described herein was developed originally as part of the railroad rationalization study conducted at MIT and sponsored by the Federal Railroad Administration. This work built upon earlier research in railroad reliability models. Because of the predominantly rail background of this model, the initial discussion focuses on the problem of modeling rail-trip-time reliability. Then, it is shown that the model can also be used to study truck and barge operations.
Search for the Standard Model Higgs Boson Produced in Association with Top Quarks
Energy Technology Data Exchange (ETDEWEB)
Wilson, Jonathan Samuel [Ohio State U.
2011-01-01
We have performed a search for the Standard Model Higgs boson produced in association with top quarks in the lepton plus jets channel. We impose no constraints on the decay of the Higgs boson. We employ ensembles of neural networks to discriminate events containing a Higgs boson from the dominant tt¯background, and set upper bounds on the Higgs production cross section. At a Higgs boson mass mH = 120 GeV/c2 , we expect to exclude a cross section 12.7 times the Standard Model prediction, and we observe an exclusion 27.4 times the Standard Model prediction with 95 % confidence.
Price-Maker Wind Power Producer Participating in a Joint Day-Ahead and Real-Time Market
DEFF Research Database (Denmark)
Delikaraoglou, Stefanos; Papakonstantinou, Athanasios; Ordoudis, Christos;
2015-01-01
-stage stochastic problem, co-optimizing day-ahead and real-time dispatch. In this framework, we introduce a bilevel model to derive the optimal bid of a strategic wind power producer acting as price-maker both in day-ahead and real-time stages. The proposed model is a Mathematical Program with Equilibrium...... Constraints (MPEC) that is reformulated as a single-level Mixed-Integer Linear Program (MILP), which can be readily solved. Our analysis shows that adopting strategic behaviour may improve producer’s expected profit as the share of wind power increases. However, this incentive diminishes in power systems...
Modeling nitrogen plasmas produced by intense electron beams
Energy Technology Data Exchange (ETDEWEB)
Angus, J. R.; Swanekamp, S. B.; Schumer, J. W.; Hinshelwood, D. D. [Plasma Physics Division, Naval Research Laboratory, Washington, DC 20375 (United States); Mosher, D.; Ottinger, P. F. [Independent contractors for NRL through Engility, Inc., Alexandria, Virginia 22314 (United States)
2016-05-15
A new gas–chemistry model is presented to treat the breakdown of a nitrogen gas with pressures on the order of 1 Torr from intense electron beams with current densities on the order of 10 kA/cm{sup 2} and pulse durations on the order of 100 ns. For these parameter regimes, the gas transitions from a weakly ionized molecular state to a strongly ionized atomic state on the time scale of the beam pulse. The model is coupled to a 0D–circuit model using the rigid–beam approximation that can be driven by specifying the time and spatial profiles of the beam pulse. Simulation results are in good agreement with experimental measurements of the line–integrated electron density from experiments done using the Gamble II generator at the Naval Research Laboratory. It is found that the species are mostly in the ground and metastable states during the atomic phase, but that ionization proceeds predominantly through thermal ionization of optically allowed states with excitation energies close to the ionization limit.
Modeling ventilation time in forage tower silos.
Bahloul, A; Chavez, M; Reggio, M; Roberge, B; Goyer, N
2012-10-01
The fermentation process in forage tower silos produces a significant amount of gases, which can easily reach dangerous concentrations and constitute a hazard for silo operators. To maintain a non-toxic environment, silo ventilation is applied. Literature reviews show that the fermentation gases reach high concentrations in the headspace of a silo and flow down the silo from the chute door to the feed room. In this article, a detailed parametric analysis of forced ventilation scenarios built via numerical simulation was performed. The methodology is based on the solution of the Navier-Stokes equations, coupled with transport equations for the gas concentrations. Validation was achieved by comparing the numerical results with experimental data obtained from a scale model silo using the tracer gas testing method for O2 and CO2 concentrations. Good agreement was found between the experimental and numerical results. The set of numerical simulations made it possible to establish a simple analytical model to predict the minimum time required to ventilate a silo to make it safe to enter. This ventilation time takes into account the headspace above the forage, the airflow rate, and the initial concentrations of O2 and CO2. The final analytical model was validated with available results from the literature.
Anderson, D. M.; Snowden, D. P.; Bochenek, R.; Bickel, A.
2015-12-01
In the U.S. coastal waters, a network of eleven regional coastal ocean observing systems support real-time coastal and ocean observing. The platforms supported and variables acquired are diverse, ranging from current sensing high frequency (HF) radar to autonomous gliders. The system incorporates data produced by other networks and experimental systems, further increasing the breadth of the collection. Strategies promoted by the U.S. Integrated Ocean Observing System (IOOS) ensure these data are not lost at sea. Every data set deserves a description. ISO and FGDC compliant metadata enables catalog interoperability and record-sharing. Extensive use of netCDF with the Climate and Forecast convention (identifying both metadata and a structured format) is shown to be a powerful strategy to promote discovery, interoperability, and re-use of the data. To integrate specialized data which are often obscure, quality control protocols are being developed to homogenize the QC and make these data more integrate-able. Data Assembly Centers have been established to integrate some specialized streams including gliders, animal telemetry, and HF radar. Subsets of data that are ingested into the National Data Buoy Center are also routed to the Global Telecommunications System (GTS) of the World Meteorological Organization to assure wide international distribution. From the GTS, data are assimilated into now-cast and forecast models, fed to other observing systems, and used to support observation-based decision making such as forecasts, warnings, and alerts. For a few years apps were a popular way to deliver these real-time data streams to phones and tablets. Responsive and adaptive web sites are an emerging flexible strategy to provide access to the regional coastal ocean observations.
EXAMINING THE MOVEMENTS OF MOBILE NODES IN THE REAL WORLD TO PRODUCE ACCURATE MOBILITY MODELS
Directory of Open Access Journals (Sweden)
TANWEER ALAM
2010-09-01
Full Text Available All communication occurs through a wireless median in an ad hoc network. Ad hoc networks are dynamically created and maintained by the individual nodes comprising the network. Random Waypoint Mobility Model is a model that includes pause times between changes in destination and speed. To produce a real-world environment within which an ad hoc network can be formed among a set of nodes, there is a need for the development of realistic, generic and comprehensive mobility models. In this paper, we examine the movements of entities in the real world and present the production of mobility model in an ad hoc network.
The use of synthetic input sequences in time series modeling
Energy Technology Data Exchange (ETDEWEB)
Oliveira, Dair Jose de [Programa de Pos-Graduacao em Engenharia Eletrica, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, 31.270-901 Belo Horizonte, MG (Brazil); Letellier, Christophe [CORIA/CNRS UMR 6614, Universite et INSA de Rouen, Av. de l' Universite, BP 12, F-76801 Saint-Etienne du Rouvray cedex (France); Gomes, Murilo E.D. [Programa de Pos-Graduacao em Engenharia Eletrica, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, 31.270-901 Belo Horizonte, MG (Brazil); Aguirre, Luis A. [Programa de Pos-Graduacao em Engenharia Eletrica, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, 31.270-901 Belo Horizonte, MG (Brazil)], E-mail: aguirre@cpdee.ufmg.br
2008-08-04
In many situations time series models obtained from noise-like data settle to trivial solutions under iteration. This Letter proposes a way of producing a synthetic (dummy) input, that is included to prevent the model from settling down to a trivial solution, while maintaining features of the original signal. Simulated benchmark models and a real time series of RR intervals from an ECG are used to illustrate the procedure.
The use of synthetic input sequences in time series modeling
de Oliveira, Dair José; Letellier, Christophe; Gomes, Murilo E. D.; Aguirre, Luis A.
2008-08-01
In many situations time series models obtained from noise-like data settle to trivial solutions under iteration. This Letter proposes a way of producing a synthetic (dummy) input, that is included to prevent the model from settling down to a trivial solution, while maintaining features of the original signal. Simulated benchmark models and a real time series of RR intervals from an ECG are used to illustrate the procedure.
Energy spectra and fluence of the neutrons produced in deformed space-time conditions
Cardone, F.; Rosada, A.
2016-10-01
In this work, spectra of energy and fluence of neutrons produced in the conditions of deformed space-time (DST), due to the violation of the local Lorentz invariance (LLI) in the nuclear interactions are shown for the first time. DST-neutrons are produced by a mechanical process in which AISI 304 steel bars undergo a sonication using ultrasounds with 20 kHz and 330 W. The energy spectrum of the DST-neutrons has been investigated both at low (less than 0.4 MeV) and at high (up to 4 MeV) energy. We could conclude that the DST-neutrons have different spectra for different energy intervals. It is therefore possible to hypothesize that the DST-neutrons production presents peculiar features not only with respect to the time (asynchrony) and space (asymmetry) but also in the neutron energy spectra.
Mathematical Models of Waiting Time.
Gordon, Sheldon P.; Gordon, Florence S.
1990-01-01
Considered are several mathematical models that can be used to study different waiting situations. Problems involving waiting at a red light, bank, restaurant, and supermarket are discussed. A computer program which may be used with these problems is provided. (CW)
Ruin Probability in Linear Time Series Model
Institute of Scientific and Technical Information of China (English)
ZHANG Lihong
2005-01-01
This paper analyzes a continuous time risk model with a linear model used to model the claim process. The time is discretized stochastically using the times when claims occur, using Doob's stopping time theorem and martingale inequalities to obtain expressions for the ruin probability as well as both exponential and non-exponential upper bounds for the ruin probability for an infinite time horizon. Numerical results are included to illustrate the accuracy of the non-exponential bound.
Dynamic models in space and time
Elhorst, J.P.
2001-01-01
This paper presents a first-order autoregressive distributed lag model in both space and time. It is shown that this model encompasses a wide series of simpler models frequently used in the analysis of space-time data as well as models that better fit the data and have never been used before. A fram
Is the jet-drive flute model able to produce modulated sounds like Flautas de Chinos ?
Terrien, Soizic; De La Cuadra, Patricio; Fabre, Benoît
2014-01-01
Flautas de chinos - prehispanic chilean flutes played during ritual celebrations in central Chile - are known to produce very particular beating sounds, the so-called sonido rajado. Some previous works have focused on the spectral analysis of these sounds, and on the input impedance of the complex resonator. However, the beating sounds origin remains to be investigated. Throughout this paper, a comparison is provided between the characteristics of both the sound produced by flautas de chinos and a synthesis sound obtained through time-domain simulation of the jet-drive model for flute-like instruments. Jet-drive model appears to be able to produce quasiperiodic sounds similar to sonido rajado. Finally, the analysis of the system dynamics through numerical continuation methods allows to explore the production mechanism of these quasiperiodic regimes.
Time lags in biological models
MacDonald, Norman
1978-01-01
In many biological models it is necessary to allow the rates of change of the variables to depend on the past history, rather than only the current values, of the variables. The models may require discrete lags, with the use of delay-differential equations, or distributed lags, with the use of integro-differential equations. In these lecture notes I discuss the reasons for including lags, especially distributed lags, in biological models. These reasons may be inherent in the system studied, or may be the result of simplifying assumptions made in the model used. I examine some of the techniques available for studying the solution of the equations. A large proportion of the material presented relates to a special method that can be applied to a particular class of distributed lags. This method uses an extended set of ordinary differential equations. I examine the local stability of equilibrium points, and the existence and frequency of periodic solutions. I discuss the qualitative effects of lags, and how these...
RTMOD: Real-Time MODel evaluation
Energy Technology Data Exchange (ETDEWEB)
Graziani, G; Galmarini, S. [Joint Research centre, Ispra (Italy); Mikkelsen, T. [Risoe National Lab., Wind Energy and Atmospheric Physics Dept. (Denmark)
2000-01-01
The 1998 - 1999 RTMOD project is a system based on an automated statistical evaluation for the inter-comparison of real-time forecasts produced by long-range atmospheric dispersion models for national nuclear emergency predictions of cross-boundary consequences. The background of RTMOD was the 1994 ETEX project that involved about 50 models run in several Institutes around the world to simulate two real tracer releases involving a large part of the European territory. In the preliminary phase of ETEX, three dry runs (i.e. simulations in real-time of fictitious releases) were carried out. At that time, the World Wide Web was not available to all the exercise participants, and plume predictions were therefore submitted to JRC-Ispra by fax and regular mail for subsequent processing. The rapid development of the World Wide Web in the second half of the nineties, together with the experience gained during the ETEX exercises suggested the development of this project. RTMOD featured a web-based user-friendly interface for data submission and an interactive program module for displaying, intercomparison and analysis of the forecasts. RTMOD has focussed on model intercomparison of concentration predictions at the nodes of a regular grid with 0.5 degrees of resolution both in latitude and in longitude, the domain grid extending from 5W to 40E and 40N to 65N. Hypothetical releases were notified around the world to the 28 model forecasters via the web on a one-day warning in advance. They then accessed the RTMOD web page for detailed information on the actual release, and as soon as possible they then uploaded their predictions to the RTMOD server and could soon after start their inter-comparison analysis with other modelers. When additional forecast data arrived, already existing statistical results would be recalculated to include the influence by all available predictions. The new web-based RTMOD concept has proven useful as a practical decision-making tool for realtime
Connectionist and diffusion models of reaction time.
Ratcliff, R; Van Zandt, T; McKoon, G
1999-04-01
Two connectionist frameworks, GRAIN (J. L. McClelland, 1993) and brain-state-in-a-box (J. A. Anderson, 1991), and R. Ratcliff's (1978) diffusion model were evaluated using data from a signal detection task. Dependent variables included response probabilities, reaction times for correct and error responses, and shapes of reaction-time distributions. The diffusion model accounted for all aspects of the data, including error reaction times that had previously been a problem for all response-time models. The connectionist models accounted for many aspects of the data adequately, but each failed to a greater or lesser degree in important ways except for one model that was similar to the diffusion model. The findings advance the development of the diffusion model and show that the long tradition of reaction-time research and theory is a fertile domain for development and testing of connectionist assumptions about how decisions are generated over time.
Time-Weighted Balanced Stochastic Model Reduction
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Shaker, Hamid Reza
2011-01-01
A new relative error model reduction technique for linear time invariant (LTI) systems is proposed in this paper. Both continuous and discrete time systems can be reduced within this framework. The proposed model reduction method is mainly based upon time-weighted balanced truncation and a recent...
Model checking timed automata : techniques and applications
Hendriks, Martijn.
2006-01-01
Model checking is a technique to automatically analyse systems that have been modeled in a formal language. The timed automaton framework is such a formal language. It is suitable to model many realistic problems in which time plays a central role. Examples are distributed algorithms, protocols, emb
Lag space estimation in time series modelling
DEFF Research Database (Denmark)
Goutte, Cyril
1997-01-01
The purpose of this article is to investigate some techniques for finding the relevant lag-space, i.e. input information, for time series modelling. This is an important aspect of time series modelling, as it conditions the design of the model through the regressor vector a.k.a. the input layer...
Nonlinear time series modelling: an introduction
Simon M. Potter
1999-01-01
Recent developments in nonlinear time series modelling are reviewed. Three main types of nonlinear models are discussed: Markov Switching, Threshold Autoregression and Smooth Transition Autoregression. Classical and Bayesian estimation techniques are described for each model. Parametric tests for nonlinearity are reviewed with examples from the three types of models. Finally, forecasting and impulse response analysis is developed.
Larger Neural Responses Produce BOLD Signals That Begin Earlier in Time
Directory of Open Access Journals (Sweden)
Serena eThompson
2014-06-01
Full Text Available Functional MRI analyses commonly rely on the assumption that the temporal dynamics of hemodynamic response functions (HRFs are independent of the amplitude of the neural signals that give rise to them. The validity of this assumption is particularly important for techniques that use fMRI to resolve sub-second timing distinctions between responses, in order to make inferences about the ordering of neural processes. Whether or not the detailed shape of the HRF is independent of neural response amplitude remains an open question, however. We performed experiments in which we measured responses in primary visual cortex (V1 to large, contrast-reversing checkerboards at a range of contrast levels, which should produce varying amounts of neural activity. Ten subjects (ages 22-52 were studied in each of two experiments using 3 Tesla scanners. We used rapid, 250 msec, temporal sampling (repetition time, or TR and both short and long inter-stimulus interval (ISI stimulus presentations. We tested for a systematic relationship between the onset of the HRF and its amplitude across conditions, and found a strong negative correlation between the two measures when stimuli were separated in time (long- and medium-ISI experiments, but not the short-ISI experiment. Thus, stimuli that produce larger neural responses, as indexed by HRF amplitude, also produced HRFs with shorter onsets. The relationship between amplitude and latency was strongest in voxels with lowest mean-normalized variance (i.e., parenchymal voxels. The onset differences observed in the longer-ISI experiments are likely attributable to mechanisms of neurovascular coupling, since they are substantially larger than reported differences in the onset of action potentials in V1 as a function of response amplitude.
A Simple Fuzzy Time Series Forecasting Model
DEFF Research Database (Denmark)
Ortiz-Arroyo, Daniel
2016-01-01
In this paper we describe a new ﬁrst order fuzzy time series forecasting model. We show that our automatic fuzzy partitioning method provides an accurate approximation to the time series that when combined with rule forecasting and an OWA operator improves forecasting accuracy. Our model does...... not attempt to provide the best results in comparison with other forecasting methods but to show how to improve ﬁrst order models using simple techniques. However, we show that our ﬁrst order model is still capable of outperforming some more complex higher order fuzzy time series models....
Time series modeling, computation, and inference
Prado, Raquel
2010-01-01
The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit
Marang, Leonie; van Loosdrecht, Mark C M; Kleerebezem, Robbert
2015-12-01
Although the enrichment of specialized microbial cultures for the production of polyhydroxyalkanoates (PHA) is generally performed in sequencing batch reactors (SBRs), the required feast-famine conditions can also be established using two or more continuous stirred-tank reactors (CSTRs) in series with partial biomass recirculation. The use of CSTRs offers several advantages, but will result in distributed residence times and a less strict separation between feast and famine conditions. The aim of this study was to investigate the impact of the reactor configuration, and various process and biomass-specific parameters, on the enrichment of PHA-producing bacteria. A set of mathematical models was developed to predict the growth of Plasticicumulans acidivorans-as a model PHA producer-in competition with a non-storing heterotroph. A macroscopic model considering lumped biomass and an agent-based model considering individual cells were created to study the effect of residence time distribution and the resulting distributed bacterial states. The simulations showed that in the 2-stage CSTR system the selective pressure for PHA-producing bacteria is significantly lower than in the SBR, and strongly affected by the chosen feast-famine ratio. This is the result of substrate competition based on both the maximum specific substrate uptake rate and substrate affinity. Although the macroscopic model overestimates the selective pressure in the 2-stage CSTR system, it provides a quick and fairly good impression of the reactor performance and the impact of process and biomass-specific parameters.
Delivery Time Reliability Model of Logistics Network
Liusan Wu; Qingmei Tan; Yuehui Zhang
2013-01-01
Natural disasters like earthquake and flood will surely destroy the existing traffic network, usually accompanied by delivery delay or even network collapse. A logistics-network-related delivery time reliability model defined by a shortest-time entropy is proposed as a means to estimate the actual delivery time reliability. The less the entropy is, the stronger the delivery time reliability remains, and vice versa. The shortest delivery time is computed separately based on two different assum...
Continuous-Time Modeling with Spatial Dependence
Oud, J.H.L.; Folmer, H.; Patuelli, R.; Nijkamp, P.
2012-01-01
(Spatial) panel data are routinely modeled in discrete time (DT). However, compelling arguments exist for continuous-time (CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete
Continuous-Time Modeling with Spatial Dependence
Oud, J.; Folmer, H.; Patuelli, R.; Nijkamp, P.
(Spatial) panel data are routinely modeled in discrete time (DT). However, compelling arguments exist for continuous-time (CT) modeling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an incomplete
Bayesian inference for pulsar timing models
Vigeland, Sarah J
2013-01-01
The extremely regular, periodic radio emission from millisecond pulsars make them useful tools for studying neutron star astrophysics, general relativity, and low-frequency gravitational waves. These studies require that the observed pulse time of arrivals are fit to complicated timing models that describe numerous effects such as the astrometry of the source, the evolution of the pulsar's spin, the presence of a binary companion, and the propagation of the pulses through the interstellar medium. In this paper, we discuss the benefits of using Bayesian inference to obtain these timing solutions. These include the validation of linearized least-squares model fits when they are correct, and the proper characterization of parameter uncertainties when they are not; the incorporation of prior parameter information and of models of correlated noise; and the Bayesian comparison of alternative timing models. We describe our computational setup, which combines the timing models of tempo2 with the nested-sampling integ...
Mixed continuous/discrete time modelling with exact time adjustments
Rovers, K.C.; Kuper, Jan; van de Burgwal, M.D.; Kokkeler, Andre B.J.; Smit, Gerardus Johannes Maria
2011-01-01
Many systems interact with their physical environment. Design of such systems need a modelling and simulation tool which can deal with both the continuous and discrete aspects. However, most current tools are not adequately able to do so, as they implement both continuous and discrete time signals
Review of current GPS methodologies for producing accurate time series and their error sources
He, Xiaoxing; Montillet, Jean-Philippe; Fernandes, Rui; Bos, Machiel; Yu, Kegen; Hua, Xianghong; Jiang, Weiping
2017-05-01
The Global Positioning System (GPS) is an important tool to observe and model geodynamic processes such as plate tectonics and post-glacial rebound. In the last three decades, GPS has seen tremendous advances in the precision of the measurements, which allow researchers to study geophysical signals through a careful analysis of daily time series of GPS receiver coordinates. However, the GPS observations contain errors and the time series can be described as the sum of a real signal and noise. The signal itself can again be divided into station displacements due to geophysical causes and to disturbing factors. Examples of the latter are errors in the realization and stability of the reference frame and corrections due to ionospheric and tropospheric delays and GPS satellite orbit errors. There is an increasing demand on detecting millimeter to sub-millimeter level ground displacement signals in order to further understand regional scale geodetic phenomena hence requiring further improvements in the sensitivity of the GPS solutions. This paper provides a review spanning over 25 years of advances in processing strategies, error mitigation methods and noise modeling for the processing and analysis of GPS daily position time series. The processing of the observations is described step-by-step and mainly with three different strategies in order to explain the weaknesses and strengths of the existing methodologies. In particular, we focus on the choice of the stochastic model in the GPS time series, which directly affects the estimation of the functional model including, for example, tectonic rates, seasonal signals and co-seismic offsets. Moreover, the geodetic community continues to develop computational methods to fully automatize all phases from analysis of GPS time series. This idea is greatly motivated by the large number of GPS receivers installed around the world for diverse applications ranging from surveying small deformations of civil engineering structures (e
A hypocentral version of the space-time ETAS model
Guo, Yicun; Zhuang, Jiancang; Zhou, Shiyong
2015-10-01
The space-time Epidemic-Type Aftershock Sequence (ETAS) model is extended by incorporating the depth component of earthquake hypocentres. The depths of the direct offspring produced by an earthquake are assumed to be independent of the epicentre locations and to follow a beta distribution, whose shape parameter is determined by the depth of the parent event. This new model is verified by applying it to the Southern California earthquake catalogue. The results show that the new model fits data better than the original epicentre ETAS model and that it provides the potential for modelling and forecasting seismicity with higher resolutions.
Discounting Models for Outcomes over Continuous Time
DEFF Research Database (Denmark)
Harvey, Charles M.; Østerdal, Lars Peter
Events that occur over a period of time can be described either as sequences of outcomes at discrete times or as functions of outcomes in an interval of time. This paper presents discounting models for events of the latter type. Conditions on preferences are shown to be satisfied if and only if t...
Towards a Computational Model of a Methane Producing Archaeum
Directory of Open Access Journals (Sweden)
Joseph R. Peterson
2014-01-01
Full Text Available Progress towards a complete model of the methanogenic archaeum Methanosarcina acetivorans is reported. We characterized size distribution of the cells using differential interference contrast microscopy, finding them to be ellipsoidal with mean length and width of 2.9 μm and 2.3 μm, respectively, when grown on methanol and 30% smaller when grown on acetate. We used the single molecule pull down (SiMPull technique to measure average copy number of the Mcr complex and ribosomes. A kinetic model for the methanogenesis pathways based on biochemical studies and recent metabolic reconstructions for several related methanogens is presented. In this model, 26 reactions in the methanogenesis pathways are coupled to a cell mass production reaction that updates enzyme concentrations. RNA expression data (RNA-seq measured for cell cultures grown on acetate and methanol is used to estimate relative protein production per mole of ATP consumed. The model captures the experimentally observed methane production rates for cells growing on methanol and is most sensitive to the number of methyl-coenzyme-M reductase (Mcr and methyl-tetrahydromethanopterin:coenzyme-M methyltransferase (Mtr proteins. A draft transcriptional regulation network based on known interactions is proposed which we intend to integrate with the kinetic model to allow dynamic regulation.
Selective Maintenance Model Considering Time Uncertainty
Le Chen; Zhengping Shu; Yuan Li; Xuezhi Lv
2012-01-01
This study proposes a selective maintenance model for weapon system during mission interval. First, it gives relevant definitions and operational process of material support system. Then, it introduces current research on selective maintenance modeling. Finally, it establishes numerical model for selecting corrective and preventive maintenance tasks, considering time uncertainty brought by unpredictability of maintenance procedure, indetermination of downtime for spares and difference of skil...
The Whole Shebang: How Science Produced the Big Bang Model.
Ferris, Timothy
2002-01-01
Offers an account of the accumulation of evidence that has led scientists to have confidence in the big bang theory of the creation of the universe. Discusses the early work of Ptolemy, Copernicus, Kepler, Galileo, and Newton, noting the rise of astrophysics, and highlighting the birth of the big bang model (the cosmic microwave background theory…
Survey of time preference, delay discounting models
Directory of Open Access Journals (Sweden)
John R. Doyle
2013-03-01
Full Text Available The paper surveys over twenty models of delay discounting (also known as temporal discounting, time preference, time discounting, that psychologists and economists have put forward to explain the way people actually trade off time and money. Using little more than the basic algebra of powers and logarithms, I show how the models are derived, what assumptions they are based upon, and how different models relate to each other. Rather than concentrate only on discount functions themselves, I show how discount functions may be manipulated to isolate rate parameters for each model. This approach, consistently applied, helps focus attention on the three main components in any discounting model: subjectively perceived money; subjectively perceived time; and how these elements are combined. We group models by the number of parameters that have to be estimated, which means our exposition follows a trajectory of increasing complexity to the models. However, as the story unfolds it becomes clear that most models fall into a smaller number of families. We also show how new models may be constructed by combining elements of different models. The surveyed models are: Exponential; Hyperbolic; Arithmetic; Hyperboloid (Green and Myerson, Rachlin; Loewenstein and Prelec Generalized Hyperboloid; quasi-Hyperbolic (also known as beta-delta discounting; Benhabib et al's fixed cost; Benhabib et al's Exponential / Hyperbolic / quasi-Hyperbolic; Read's discounting fractions; Roelofsma's exponential time; Scholten and Read's discounting-by-intervals (DBI; Ebert and Prelec's constant sensitivity (CS; Bleichrodt et al.'s constant absolute decreasing impatience (CADI; Bleichrodt et al.'s constant relative decreasing impatience (CRDI; Green, Myerson, and Macaux's hyperboloid over intervals models; Killeen's additive utility; size-sensitive additive utility; Yi, Landes, and Bickel's memory trace models; McClure et al.'s two exponentials; and Scholten and Read's trade
Reduction of time for producing and acclimatizing two bamboo species in a greenhouse
Directory of Open Access Journals (Sweden)
Giovanni Aquino Gasparetto
2013-03-01
Full Text Available China has been investing in bamboo cultivation in Brazilian lands. However, there’s a significant deficit of seedling production for civil construction and the charcoal and cellulose sectors, something which compromises a part of the forestry sector. In order to contribute so that the bamboo production chain solves this problem, this study aimed to check whether the application of indole acetic acid (IAA could promote plant growth in a shorter cultivation time. In the study, Bambusa vulgaris and B. vulgaris var. vitatta stakes underwent two treatments (0.25% and 5.0% of IAA and they were grown on washed sand in a greenhouse. Number of leaves, stem growth, rooting, and chlorophyll content were investigated. There was no difference with regard to stem growth, root length, and number of leaves for both species in the two treatments (0.25% and 5% IAA. The chlorophyll content variation between the two species may constitute a quality parameter of forest seedling when compared to other bamboo species. After 43 days, the seedlings are ready for planting in areas of full sun. For the species studied here, the average time to the seedling sale is from 4 to 6 months, with no addition of auxin. Using this simple and low cost technique, several nurserymen will produce bamboo seedlings with reduced time, costs, and manpower.
Real-time Social Internet Data to Guide Forecasting Models
Energy Technology Data Exchange (ETDEWEB)
Del Valle, Sara Y. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-09-20
Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematical approaches and heterogeneous data streams.
Directory of Open Access Journals (Sweden)
Elizabeth A Osterndorff-Kahanek
Full Text Available Repeated ethanol exposure and withdrawal in mice increases voluntary drinking and represents an animal model of physical dependence. We examined time- and brain region-dependent changes in gene coexpression networks in amygdala (AMY, nucleus accumbens (NAC, prefrontal cortex (PFC, and liver after four weekly cycles of chronic intermittent ethanol (CIE vapor exposure in C57BL/6J mice. Microarrays were used to compare gene expression profiles at 0-, 8-, and 120-hours following the last ethanol exposure. Each brain region exhibited a large number of differentially expressed genes (2,000-3,000 at the 0- and 8-hour time points, but fewer changes were detected at the 120-hour time point (400-600. Within each region, there was little gene overlap across time (~20%. All brain regions were significantly enriched with differentially expressed immune-related genes at the 8-hour time point. Weighted gene correlation network analysis identified modules that were highly enriched with differentially expressed genes at the 0- and 8-hour time points with virtually no enrichment at 120 hours. Modules enriched for both ethanol-responsive and cell-specific genes were identified in each brain region. These results indicate that chronic alcohol exposure causes global 'rewiring' of coexpression systems involving glial and immune signaling as well as neuronal genes.
Model Epidemi Sirs Dengan Time Delay
Sinuhaji, Ferdinand
2016-01-01
The epidemic is an outbreak of an infectious disease situation in the population at a place that exceeds the normal approximation in a short period. When the disease is always contained in any place as well as with the causes, it is called endemic. This study discusses decrease SIRS epidemic models with time delay through a mathematical model based on the model of SIRS epidemic (Susceptible, Infective, Recovered, Susceptible). SIRS models used in this study with the assumption ...
In Vitro-Produced Pancreas Organogenesis Models In Three Dimensions
DEFF Research Database (Denmark)
Greggio, Chiara; De Franceschi, Filippo; Grapin-Botton, Anne
2015-01-01
of miniature organs in a dish and are emerging for the pancreas, starting from embryonic progenitors and adult cells. This review focusses on the currently available systems and how these allow new types of questions to be addressed. We discuss the expected advancements including their potential to study human...... pancreas development and function as well as to develop diabetes models and therapeutic cells. Stem Cells 2014....
Energy Technology Data Exchange (ETDEWEB)
Moura, Fabricio A.M.; Camacho, Jose R. [Universidade Federal de Uberlandia, School of Electrical Engineering, Rural Electricity and Alternative Sources Lab, PO Box 593, 38400.902 Uberlandia, MG (Brazil); Chaves, Marcelo L.R.; Guimaraes, Geraldo C. [Universidade Federal de Uberlandia, School of Electrical Engineering, Power Systems Dynamics Group, PO Box: 593, 38400.902 Uberlandia, MG (Brazil)
2010-02-15
The main task in this paper is to present a performance analysis of a distribution network in the presence of an independent power producer (IP) synchronous generator with its speed governor and voltage regulator modeled using TACS -Transient Analysis of Control Systems, for distributed generation studies. Regulators were implemented through their transfer functions in the S domain. However, since ATP-EMTP (Electromagnetic Transient Program) works in the time domain, a discretization is necessary to return the TACS output to time domain. It must be highlighted that this generator is driven by a steam turbine, and the whole system with regulators and the equivalent of the power authority system at the common coupling point (CCP) are modeled in the ''ATP-EMTP -Alternative Transients Program''. (author)
Real-time measurement of materials properties at high temperatures by laser produced plasmas
Kim, Yong W.
1990-01-01
Determination of elemental composition and thermophysical properties of materials at high temperatures, as visualized in the context of containerless materials processing in a microgravity environment, presents a variety of unusual requirements owing to the thermal hazards and interferences from electromagnetic control fields. In addition, such information is intended for process control applications and thus the measurements must be real time in nature. A new technique is described which was developed for real time, in-situ determination of the elemental composition of molten metallic alloys such as specialty steel. The technique is based on time-resolved spectroscopy of a laser produced plasma (LPP) plume resulting from the interaction of a giant laser pulse with a material target. The sensitivity and precision were demonstrated to be comparable to, or better than, the conventional methods of analysis which are applicable only to post-mortem specimens sampled from a molten metal pool. The LPP technique can be applied widely to other materials composition analysis applications. The LPP technique is extremely information rich and therefore provides opportunities for extracting other physical properties in addition to the materials composition. The case in point is that it is possible to determine thermophysical properties of the target materials at high temperatures by monitoring generation and transport of acoustic pulses as well as a number of other fluid-dynamic processes triggered by the LPP event. By manipulation of the scaling properties of the laser-matter interaction, many different kinds of flow events, ranging from shock waves to surface waves to flow induced instabilities, can be generated in a controllable manner. Time-resolved detection of these events can lead to such thermophysical quantities as volume and shear viscosities, thermal conductivity, specific heat, mass density, and others.
Delivery Time Reliability Model of Logistics Network
Directory of Open Access Journals (Sweden)
Liusan Wu
2013-01-01
Full Text Available Natural disasters like earthquake and flood will surely destroy the existing traffic network, usually accompanied by delivery delay or even network collapse. A logistics-network-related delivery time reliability model defined by a shortest-time entropy is proposed as a means to estimate the actual delivery time reliability. The less the entropy is, the stronger the delivery time reliability remains, and vice versa. The shortest delivery time is computed separately based on two different assumptions. If a path is concerned without capacity restriction, the shortest delivery time is positively related to the length of the shortest path, and if a path is concerned with capacity restriction, a minimax programming model is built to figure up the shortest delivery time. Finally, an example is utilized to confirm the validity and practicality of the proposed approach.
Building Chaotic Model From Incomplete Time Series
Siek, Michael; Solomatine, Dimitri
2010-05-01
This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual
Biomechanical model produced from light-activated dental composite resins: a holographic analysis
Pantelić, Dejan; Vasiljević, Darko; Blažić, Larisa; Savić-Šević, Svetlana; Murić, Branka; Nikolić, Marko
2013-11-01
Light-activated dental composites, commonly applied in dentistry, can be used as excellent material for producing biomechanical models. They can be cast in almost any shape in an appropriate silicone mold and quickly solidified by irradiation with light in the blue part of the spectrum. In that way, it is possible to obtain any number of nearly identical casts. The models can be used to study the behavior of arbitrary structure under mechanical loads. To test the technique, a simple mechanical model of the tooth with a mesio-occluso-distal cavity was manufactured. Composite resin restoration was placed inside the cavity and light cured. Real-time holographic interferometry was used to analyze the contraction of the composite resin and its effect on the surrounding material. The results obtained in the holographic experiment were in good agreement with those obtained using the finite element method.
Feature Matching in Time Series Modelling
Xia, Yingcun
2011-01-01
Using a time series model to mimic an observed time series has a long history. However, with regard to this objective, conventional estimation methods for discrete-time dynamical models are frequently found to be wanting. In the absence of a true model, we prefer an alternative approach to conventional model fitting that typically involves one-step-ahead prediction errors. Our primary aim is to match the joint probability distribution of the observable time series, including long-term features of the dynamics that underpin the data, such as cycles, long memory and others, rather than short-term prediction. For want of a better name, we call this specific aim {\\it feature matching}. The challenges of model mis-specification, measurement errors and the scarcity of data are forever present in real time series modelling. In this paper, by synthesizing earlier attempts into an extended-likelihood, we develop a systematic approach to empirical time series analysis to address these challenges and to aim at achieving...
Modeling noisy time series Physiological tremor
Timmer, J
1998-01-01
Empirical time series often contain observational noise. We investigate the effect of this noise on the estimated parameters of models fitted to the data. For data of physiological tremor, i.e. a small amplitude oscillation of the outstretched hand of healthy subjects, we compare the results for a linear model that explicitly includes additional observational noise to one that ignores this noise. We discuss problems and possible solutions for nonlinear deterministic as well as nonlinear stochastic processes. Especially we discuss the state space model applicable for modeling noisy stochastic systems and Bock's algorithm capable for modeling noisy deterministic systems.
Modeling discrete time-to-event data
Tutz, Gerhard
2016-01-01
This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are expla...
Estimating High-Dimensional Time Series Models
DEFF Research Database (Denmark)
Medeiros, Marcelo C.; Mendes, Eduardo F.
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly...
Forecasting with periodic autoregressive time series models
Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)
1999-01-01
textabstractThis paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption
Forecasting with periodic autoregressive time series models
Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)
1999-01-01
textabstractThis paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption
Flexible boosting of accelerated failure time models
Directory of Open Access Journals (Sweden)
Hothorn Torsten
2008-06-01
Full Text Available Abstract Background When boosting algorithms are used for building survival models from high-dimensional data, it is common to fit a Cox proportional hazards model or to use least squares techniques for fitting semiparametric accelerated failure time models. There are cases, however, where fitting a fully parametric accelerated failure time model is a good alternative to these methods, especially when the proportional hazards assumption is not justified. Boosting algorithms for the estimation of parametric accelerated failure time models have not been developed so far, since these models require the estimation of a model-specific scale parameter which traditional boosting algorithms are not able to deal with. Results We introduce a new boosting algorithm for censored time-to-event data which is suitable for fitting parametric accelerated failure time models. Estimation of the predictor function is carried out simultaneously with the estimation of the scale parameter, so that the negative log likelihood of the survival distribution can be used as a loss function for the boosting algorithm. The estimation of the scale parameter does not affect the favorable properties of boosting with respect to variable selection. Conclusion The analysis of a high-dimensional set of microarray data demonstrates that the new algorithm is able to outperform boosting with the Cox partial likelihood when the proportional hazards assumption is questionable. In low-dimensional settings, i.e., when classical likelihood estimation of a parametric accelerated failure time model is possible, simulations show that the new boosting algorithm closely approximates the estimates obtained from the maximum likelihood method.
Discrete-time modelling of musical instruments
Välimäki, Vesa; Pakarinen, Jyri; Erkut, Cumhur; Karjalainen, Matti
2006-01-01
This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect to time, because the aim is to run the simulation using a computer. The physics-based modelling methods can be classified as mass-spring, modal, wave digital, finite difference, digital waveguide and source-filter models. We present the basic theory and a discussion on possible extensions for each modelling technique. For some methods, a simple model example is chosen from the existing literature demonstrating a typical use of the method. For instance, in the case of the digital waveguide modelling technique a vibrating string model is discussed, and in the case of the wave digital filter technique we present a classical piano hammer model. We tackle some nonlinear and time-varying models and include new results on the digital waveguide modelling of a nonlinear string. Current trends and future directions in physical modelling of musical instruments are discussed.
Discrete-time modelling of musical instruments
Energy Technology Data Exchange (ETDEWEB)
Vaelimaeki, Vesa; Pakarinen, Jyri; Erkut, Cumhur; Karjalainen, Matti [Laboratory of Acoustics and Audio Signal Processing, Helsinki University of Technology, PO Box 3000, FI-02015 TKK, Espoo (Finland)
2006-01-01
This article describes physical modelling techniques that can be used for simulating musical instruments. The methods are closely related to digital signal processing. They discretize the system with respect to time, because the aim is to run the simulation using a computer. The physics-based modelling methods can be classified as mass-spring, modal, wave digital, finite difference, digital waveguide and source-filter models. We present the basic theory and a discussion on possible extensions for each modelling technique. For some methods, a simple model example is chosen from the existing literature demonstrating a typical use of the method. For instance, in the case of the digital waveguide modelling technique a vibrating string model is discussed, and in the case of the wave digital filter technique we present a classical piano hammer model. We tackle some nonlinear and time-varying models and include new results on the digital waveguide modelling of a nonlinear string. Current trends and future directions in physical modelling of musical instruments are discussed.
Alternative time representation in dopamine models.
Rivest, François; Kalaska, John F; Bengio, Yoshua
2010-02-01
Dopaminergic neuron activity has been modeled during learning and appetitive behavior, most commonly using the temporal-difference (TD) algorithm. However, a proper representation of elapsed time and of the exact task is usually required for the model to work. Most models use timing elements such as delay-line representations of time that are not biologically realistic for intervals in the range of seconds. The interval-timing literature provides several alternatives. One of them is that timing could emerge from general network dynamics, instead of coming from a dedicated circuit. Here, we present a general rate-based learning model based on long short-term memory (LSTM) networks that learns a time representation when needed. Using a naïve network learning its environment in conjunction with TD, we reproduce dopamine activity in appetitive trace conditioning with a constant CS-US interval, including probe trials with unexpected delays. The proposed model learns a representation of the environment dynamics in an adaptive biologically plausible framework, without recourse to delay lines or other special-purpose circuits. Instead, the model predicts that the task-dependent representation of time is learned by experience, is encoded in ramp-like changes in single-neuron activity distributed across small neural networks, and reflects a temporal integration mechanism resulting from the inherent dynamics of recurrent loops within the network. The model also reproduces the known finding that trace conditioning is more difficult than delay conditioning and that the learned representation of the task can be highly dependent on the types of trials experienced during training. Finally, it suggests that the phasic dopaminergic signal could facilitate learning in the cortex.
DEFF Research Database (Denmark)
Sørup, Hjalte Jomo Danielsen; Madsen, Henrik; Arnbjerg-Nielsen, Karsten
2011-01-01
A very fine temporal and volumetric resolution precipitation time series is modeled using Markov models. Both 1st and 2nd order Markov models as well as seasonal and diurnal models are investigated and evaluated using likelihood based techniques. The 2nd order Markov model is found to be insignif...
Directory of Open Access Journals (Sweden)
Francisco Estrada
Full Text Available In this paper evidence of anthropogenic influence over the warming of the 20th century is presented and the debate regarding the time-series properties of global temperatures is addressed in depth. The 20th century global temperature simulations produced for the Intergovernmental Panel on Climate Change's Fourth Assessment Report and a set of the radiative forcing series used to drive them are analyzed using modern econometric techniques. Results show that both temperatures and radiative forcing series share similar time-series properties and a common nonlinear secular movement. This long-term co-movement is characterized by the existence of time-ordered breaks in the slope of their trend functions. The evidence presented in this paper suggests that while natural forcing factors may help explain the warming of the first part of the century, anthropogenic forcing has been its main driver since the 1970's. In terms of Article 2 of the United Nations Framework Convention on Climate Change, significant anthropogenic interference with the climate system has already occurred and the current climate models are capable of accurately simulating the response of the climate system, even if it consists in a rapid or abrupt change, to changes in external forcing factors. This paper presents a new methodological approach for conducting time-series based attribution studies.
From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets
K. Boer-Sorban (Katalin); U. Kaymak (Uzay); J. Spiering (Jaap)
2006-01-01
textabstractMost agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modelling of financial markets. We study the behaviour of a learning market maker in a market with
From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets
K. Boer-Sorban (Katalin); U. Kaymak (Uzay); J. Spiering (Jaap)
2006-01-01
textabstractMost agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modelling of financial markets. We study the behaviour of a learning market maker in a market with
Time-varying modeling of cerebral hemodynamics.
Marmarelis, Vasilis Z; Shin, Dae C; Orme, Melissa; Rong Zhang
2014-03-01
The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, cerebral flow autoregulation (CFA) and CO2 vasomotor reactivity (CVR), have attracted much attention because they are implicated in many important clinical conditions and pathologies (orthostatic intolerance, syncope, hypertension, stroke, vascular dementia, mild cognitive impairment, Alzheimer's disease, and other neurodegenerative diseases with cerebrovascular components). Both CFA and CVR are dynamic physiological processes by which cerebral blood flow is regulated in response to fluctuations in cerebral perfusion pressure and blood CO2 tension. Several modeling studies to date have analyzed beat-to-beat hemodynamic data in order to advance our quantitative understanding of CFA-CVR dynamics. A confounding factor in these studies is the fact that the dynamics of the CFA-CVR processes appear to vary with time (i.e., changes in cerebrovascular characteristics) due to neural, endocrine, and metabolic effects. This paper seeks to address this issue by tracking the changes in linear time-invariant models obtained from short successive segments of data from ten healthy human subjects. The results suggest that systemic variations exist but have stationary statistics and, therefore, the use of time-invariant modeling yields "time-averaged models" of physiological and clinical utility.
Modeling of the time sharing for lecturers
Directory of Open Access Journals (Sweden)
E. Yu. Shakhova
2017-01-01
Full Text Available In the context of modernization of the Russian system of higher education, it is necessary to analyze the working time of the university lecturers, taking into account both basic job functions as the university lecturer, and others.The mathematical problem is presented for the optimal working time planning for the university lecturers. The review of the documents, native and foreign works on the study is made. Simulation conditions, based on analysis of the subject area, are defined. Models of optimal working time sharing of the university lecturers («the second half of the day» are developed and implemented in the system MathCAD. Optimal solutions have been obtained.Three problems have been solved:1 to find the optimal time sharing for «the second half of the day» in a certain position of the university lecturer;2 to find the optimal time sharing for «the second half of the day» for all positions of the university lecturers in view of the established model of the academic load differentiation;3 to find the volume value of the non-standardized part of time work in the department for the academic year, taking into account: the established model of an academic load differentiation, distribution of the Faculty number for the positions and the optimal time sharing «the second half of the day» for the university lecturers of the department.Examples are given of the analysis results. The practical application of the research: the developed models can be used when planning the working time of an individual professor in the preparation of the work plan of the university department for the academic year, as well as to conduct a comprehensive analysis of the administrative decisions in the development of local university regulations.
A stochastic space-time model for intermittent precipitation occurrences
Sun, Ying
2016-01-28
Modeling a precipitation field is challenging due to its intermittent and highly scale-dependent nature. Motivated by the features of high-frequency precipitation data from a network of rain gauges, we propose a threshold space-time t random field (tRF) model for 15-minute precipitation occurrences. This model is constructed through a space-time Gaussian random field (GRF) with random scaling varying along time or space and time. It can be viewed as a generalization of the purely spatial tRF, and has a hierarchical representation that allows for Bayesian interpretation. Developing appropriate tools for evaluating precipitation models is a crucial part of the model-building process, and we focus on evaluating whether models can produce the observed conditional dry and rain probabilities given that some set of neighboring sites all have rain or all have no rain. These conditional probabilities show that the proposed space-time model has noticeable improvements in some characteristics of joint rainfall occurrences for the data we have considered.
Institute of Scientific and Technical Information of China (English)
Daming Li; Fanxiang Kong; Xiaoli Shi; Linlin Ye; Yang Yu; Zhen Yang
2012-01-01
Lake Taihu,a large,shallow hypertrophic freshwater lake in eastern China,has experienced lake-wide toxic cyanobacterial blooms annually during summer season in the past decades.Spatial changes in the abundance of hepatotoxin microcystin-producing and nonmicrocystin producing Microcystis populations were investigated in the lake in August of 2009 and 2010.To monitor the densities of the total Microcystis population and the potential microcystin-producing subpopulation,we used a quantitative real-time PCR assay targeting the phycocyanin intergenic spacer (PC-IGS) and the microcystin synthetase gene (mcyD),respectively.On the basis of quantification by real-time PCR analysis,the abundance of potential toxic Microcystis genotypes and the ratio of the mcyD subpopulation to the total Microcystis varied significantly,from 4.08×104 to 5.22×107 copies/mL,from 5.7% to 65.8%,respectively.Correlation analysis showed a strong positive relationship between chlorophyll-a,toxic Microcystis and total Microcystis; the abundance of toxic Microcystis correlated positively with total phosphorus and ortho-phosphate concentrations,but negatively with TN:TP ratio and nitrate concentrations.Meanwhile the proportion of potential toxic genotypes within Microcystis population showed positive correlation with total phosphorus and ortho-phosphate concentrations.Our data suggest that increased phosphorus loading may be a significant factor promoting the occurrence of toxic Microcystis bloom in Lake Taihu.
Forecasting with nonlinear time series models
DEFF Research Database (Denmark)
Kock, Anders Bredahl; Teräsvirta, Timo
and two versions of a simple artificial neural network model. Techniques for generating multi-period forecasts from nonlinear models recursively are considered, and the direct (non-recursive) method for this purpose is mentioned as well. Forecasting with com- plex dynamic systems, albeit less frequently...... applied to economic fore- casting problems, is briefly highlighted. A number of large published studies comparing macroeconomic forecasts obtained using different time series models are discussed, and the paper also contains a small simulation study comparing recursive and direct forecasts in a partic...
Formal Modeling and Analysis of Timed Systems
DEFF Research Database (Denmark)
Larsen, Kim Guldstrand; Niebert, Peter
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Formal Modeling and Analysis of Timed Systems, FORMATS 2003, held in Marseille, France in September 2003. The 19 revised full papers presented together with an invited paper and the abstracts...
Modeling biological rhythms in failure time data
Directory of Open Access Journals (Sweden)
Myles James D
2006-11-01
Full Text Available Abstract Background The human body exhibits a variety of biological rhythms. There are patterns that correspond, among others, to the daily wake/sleep cycle, a yearly seasonal cycle and, in women, the menstrual cycle. Sine/cosine functions are often used to model biological patterns for continuous data, but this model is not appropriate for analysis of biological rhythms in failure time data. Methods We adapt the cosinor method to the proportional hazards model and present a method to provide an estimate and confidence interval of the time when the minimum hazard is achieved. We then apply this model to data taken from a clinical trial of adjuvant of pre-menopausal breast cancer patients. Results The application of this technique to the breast cancer data revealed that the optimal day for pre-resection incisional or excisional biopsy of 28-day cycle (i. e. the day associated with the lowest recurrence rate is day 8 with 95% confidence interval of 4–12 days. We found that older age, fewer positive nodes, smaller tumor size, and experimental treatment were predictive of longer relapse-free survival. Conclusion In this paper we have described a method for modeling failure time data with an underlying biological rhythm. The advantage of adapting a cosinor model to proportional hazards model is its ability to model right censored data. We have presented a method to provide an estimate and confidence interval of the day in the menstrual cycle where the minimum hazard is achieved. This method is not limited to breast cancer data, and may be applied to any biological rhythms linked to right censored data.
Selection of Sinopec Lubricating Oil Producing Bases by Using the AHP Model
Institute of Scientific and Technical Information of China (English)
Song Yunchang; Song Zhaozheng; Zheng Chengguo; Jiang Qingzhe; Xu Chunming
2007-01-01
The factors affecting the development of Sinopec lubricating oil were analyzed in this paper,and an analytic hierarchy process (AHP) model for selecting lubricating-oil producing bases was developed. By using this model,nine lubricating oil producing companies under Sinopec were comprehensively evaluated. The evaluation result showed that the Maoming Lubricating Oil Company (Guangdong province),Jingmen Lubricating Oil Company (Hubei province) and Changcheng Lube Oil Company (Beijing) are top three choices,and should be developed preferentially for the development of Sinopec producing bases of lubricating oil in the future. The conclusions provide the theoretical basis for selecting lubricating oil producing bases for decision makers.
Functional copmponents produced by multi-jet modelling combined with electroforming and machining
Directory of Open Access Journals (Sweden)
Baier, Oliver
2014-08-01
Full Text Available In fuel cell technology, certain components are used that are responsible for guiding liquid media. When these components are produced by conventional manufacturing, there are often sealing issues, and trouble- and maintenance-free deployment cannot be ensured. Against this background, a new process combination has been developed in a joint project between the University of Duisburg-Essen, the Center for Fuel Cell Technology (ZBT, and the company Galvano-T electroplating forming GmbH. The approach is to combine multi-jet modelling (MJM, electroforming and milling in order to produce a defined external geometry. The wax models are generated on copper base plates and copper-coated to a desirable thickness. Following this, the undefined electroplated surfaces are machined to achieve the desired measurement, and the wax is melted out. This paper presents, first, how this process is technically feasible, then describes how the MJM on a 3-D Systems ThermoJet was adapted to stabilise the process.In the AiF-sponsored ZIM project, existing limits and possibilities are shown and different approaches of electroplating are investigated. This paper explores whether or not activation of the wax structure by a conductive initial layer is required. Using the described process chain, different parts were built: a heat exchanger, a vaporiser, and a reformer (in which pellets were integrated in an intermediate step. In addition, multiple-layer parts with different functions were built by repeating the process combination several times.
A Search for the Standard Model Higgs Boson Produced in Association with a $W$ Boson
Energy Technology Data Exchange (ETDEWEB)
Frank, Martin Johannes [Baylor Univ., Waco, TX (United States)
2011-05-01
We present a search for a standard model Higgs boson produced in association with a W boson using data collected with the CDF II detector from p$\\bar{p}$ collisions at √s = 1.96 TeV. The search is performed in the WH → ℓvb$\\bar{b}$ channel. The two quarks usually fragment into two jets, but sometimes a third jet can be produced via gluon radiation, so we have increased the standard two-jet sample by including events that contain three jets. We reconstruct the Higgs boson using two or three jets depending on the kinematics of the event. We find an improvement in our search sensitivity using the larger sample together with this multijet reconstruction technique. Our data show no evidence of a Higgs boson, so we set 95% confidence level upper limits on the WH production rate. We set limits between 3.36 and 28.7 times the standard model prediction for Higgs boson masses ranging from 100 to 150 GeV/c^{2}.
Time models and cognitive processes: a review
Directory of Open Access Journals (Sweden)
Michail eManiadakis
2014-02-01
Full Text Available The sense of time is an essential capacity of humans, with a major role in many of the cognitive processes expressed in our daily lifes. So far, in cognitive science and robotics research, mental capacities have been investigated in a theoretical and modelling framework that largely neglects the flow of time. Only recently there has been a small but constantly increasing interest in the temporal aspects of cognition, integrating time into a range of different models of perceptuo-motor capacities. The current paper aims to review existing works in the field and suggest directions for fruitful future work. This is particularly important for the newly developed field of artificial temporal cognition that is expected to significantly contribute in the development of sophisticated artificial agents seamlessly integrated into human societies.
Constitutive model with time-dependent deformations
DEFF Research Database (Denmark)
Krogsbøll, Anette
1998-01-01
are common in time as well as size. This problem is adressed by means of a new constitutive model for soils. It is able to describe the behavior of soils at different deformation rates. The model defines time-dependent and stress-related deformations separately. They are related to each other and they occur......In many geological and Engineering problems it is necessary to transform information from one scale to another. Data collected at laboratory scale are often used to evaluate field problems on a much larger scale. This is certainly true for geological problems where extreme scale differences...... simultanelously. The model is based on concepts from elasticity and viscoplasticity theories. In addition to Hooke's law for the elastic behavior, the framework for the viscoplastic behavior consists, in the general case (two-dimensional or three-dimensional), of a yield surface, an associated flow rule...
Bockmann, Michelle R.; Harris, Abbe V.; Bennett, Corinna N.; Ruba Odeh; Hughes, Toby E.; Townsend, Grant C
2011-01-01
Findings are presented from a prospective cohort study of timing of primary tooth emergence and timing of oral colonization of Streptococcus mutans (S. mutans) in Australian twins. The paper focuses on differences in colonization timing in genetically identical monozygotic (MZ) twins. Timing of tooth emergence was based on parental report. Colonization timing of S. mutans were established by plating samples of plaque and saliva on selective media at 3 monthly intervals and assessing colony mo...
High emergence of ESBL-producing E. coli cystitis: Time to get smarter in Cyprus
Directory of Open Access Journals (Sweden)
Leon eCantas
2016-01-01
Full Text Available Background: Widespread prevalence of extended-spectrum βeta-lactamase producing Escherichia coli (ESBL-producing E. coli limits the infection therapeutic options and is a growing global health problem. In this study our aim was to investigate the antimicrobial resistance profile of the E. coli in hospitalized and out- patients in Cyprus. Results: During the period 2010-2014, 389 strains of E. coli were isolated from urine samples of hospitalized and out-patients in Cyprus. ESBL-producing E. coli, was observed in 53% of hospitalized and 44% in out-patients, latest one being in 2014. All ESBL-producing E. coli remained susceptible to amikacin, carbapenems except ertapenem (in-patients= 6%, out-patients= 11%. Conclusions: High emerging ESBL-producing E. coli from urine samples in hospitalized and out-patients is an extremely worrisome sign of development of untreatable infections in the near future on the island. We therefore emphasize the immediate need for establishment of optimal therapy guidelines based on the country specific surveillance programs. The need for urgent prescription habit changes and ban of over-the-counter sale of antimicrobials at each segment of healthcare services is also discussed in this research.
High Emergence of ESBL-Producing E. coli Cystitis: Time to Get Smarter in Cyprus.
Cantas, Leon; Suer, Kaya; Guler, Emrah; Imir, Turgut
2015-01-01
Widespread prevalence of extended-spectrum βeta-lactamase producing Escherichia coli (ESBL-producing E. coli) limits the infection therapeutic options and is a growing global health problem. In this study our aim was to investigate the antimicrobial resistance profile of the E. coli in hospitalized and out-patients in Cyprus. During the period 2010-2014, 389 strains of E. coli were isolated from urine samples of hospitalized and out-patients in Cyprus. ESBL-producing E. coli, was observed in 53% of hospitalized and 44% in out-patients, latest one being in 2014. All ESBL-producing E. coli remained susceptible to amikacin, carbapenems except ertapenem (in-patients = 6%, out-patients = 11%). High emerging ESBL-producing E. coli from urine samples in hospitalized and out-patients is an extremely worrisome sign of development of untreatable infections in the near future on the island. We therefore emphasize the immediate need for establishment of optimal therapy guidelines based on the country specific surveillance programs. The need for new treatment strategies, urgent prescription habit changes and ban of over-the-counter sale of antimicrobials at each segment of healthcare services is also discussed in this research.
Fisher Information Framework for Time Series Modeling
Venkatesan, R C
2016-01-01
A robust prediction model invoking the Takens embedding theorem, whose \\textit{working hypothesis} is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the \\textit{working hypothesis} satisfy a time independent Schr\\"{o}dinger-like equation in a vector setting. The inference of i) the probability density function of the coefficients of the \\textit{working hypothesis} and ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defi...
Confirmation and calibration of computer modeling of tsunamis produced by Augustine volcano, Alaska
Beget, James E.; Kowalik, Zygmunt
2006-01-01
Numerical modeling has been used to calculate the characteristics of a tsunami generated by a landslide into Cook Inlet from Augustine Volcano. The modeling predicts travel times of ca. 50-75 minutes to the nearest populated areas, and indicates that significant wave amplification occurs near Mt. Iliamna on the western side of Cook Inlet, and near the Nanwelak and the Homer-Anchor Point areas on the east side of Cook Inlet. Augustine volcano last produced a tsunami during an eruption in 1883, and field evidence of the extent and height of the 1883 tsunamis can be used to test and constrain the results of the computer modeling. Tsunami deposits on Augustine Island indicate waves near the landslide source were more than 19 m high, while 1883 tsunami deposits in distal sites record waves 6-8 m high. Paleotsunami deposits were found at sites along the coast near Mt. Iliamna, Nanwelak, and Homer, consistent with numerical modeling indicating significant tsunami wave amplification occurs in these areas.
Linear Parametric Model Checking of Timed Automata
DEFF Research Database (Denmark)
Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle
2001-01-01
of a subclass of parametric timed automata (L/U automata), for which the emptiness problem is decidable, contrary to the full class where it is know to be undecidable. Also we present a number of lemmas enabling the verication eort to be reduced for L/U automata in some cases. We illustrate our approach......We present an extension of the model checker Uppaal capable of synthesize linear parameter constraints for the correctness of parametric timed automata. The symbolic representation of the (parametric) state-space is shown to be correct. A second contribution of this paper is the identication...
Time series modeling for automatic target recognition
Sokolnikov, Andre
2012-05-01
Time series modeling is proposed for identification of targets whose images are not clearly seen. The model building takes into account air turbulence, precipitation, fog, smoke and other factors obscuring and distorting the image. The complex of library data (of images, etc.) serving as a basis for identification provides the deterministic part of the identification process, while the partial image features, distorted parts, irrelevant pieces and absence of particular features comprise the stochastic part of the target identification. The missing data approach is elaborated that helps the prediction process for the image creation or reconstruction. The results are provided.
The times they are a-changin': carbapenems for extended-spectrum-β-lactamase-producing bacteria.
Rodríguez-Baño, Jesús
2015-09-01
Several antimicrobial agents are being investigated as alternatives to carbapenems in the treatment of infections caused by ESBL-producing Enterobacteriaceae, which may be useful in avoiding overuse of carbapenems in the context of recent global spread of carbapenem-resistant Enterobacteriaceae. The most promising candidates for invasive infections so far are β-lactam/β-lactamase inhibitor combinations and cephamycins.
Shiga toxin (Stx) producing E. coli (STEC) are a major family of foodborne pathogens of immense public health, zoonotic and economic significance in the US and worldwide. To date, there are no published reports on use of recombinase polymerase amplification (RPA) for STEC detection. The primary goal...
Sáenz Segura, F.; Haese, D' M.F.C.; Schipper, R.A.
2010-01-01
We model the contractual arrangements between smallholder pepper (Piper nigrum L.) producers and a single processor in Costa Rica. Producers in the El Roble settlement sell their pepper to only one processing firm, which exerts its monopsonistic bargaining power by setting the purchase price of
Sáenz Segura, F.; Haese, D' M.F.C.; Schipper, R.A.
2010-01-01
We model the contractual arrangements between smallholder pepper (Piper nigrum L.) producers and a single processor in Costa Rica. Producers in the El Roble settlement sell their pepper to only one processing firm, which exerts its monopsonistic bargaining power by setting the purchase price of fres
Modelling of Patterns in Space and Time
Murray, James
1984-01-01
This volume contains a selection of papers presented at the work shop "Modelling of Patterns in Space and Time", organized by the 80nderforschungsbereich 123, "8tochastische Mathematische Modelle", in Heidelberg, July 4-8, 1983. The main aim of this workshop was to bring together physicists, chemists, biologists and mathematicians for an exchange of ideas and results in modelling patterns. Since the mathe matical problems arising depend only partially on the particular field of applications the interdisciplinary cooperation proved very useful. The workshop mainly treated phenomena showing spatial structures. The special areas covered were morphogenesis, growth in cell cultures, competition systems, structured populations, chemotaxis, chemical precipitation, space-time oscillations in chemical reactors, patterns in flames and fluids and mathematical methods. The discussions between experimentalists and theoreticians were especially interesting and effective. The editors hope that these proceedings reflect ...
Time Series Modelling using Proc Varmax
DEFF Research Database (Denmark)
Milhøj, Anders
2007-01-01
In this paper it will be demonstrated how various time series problems could be met using Proc Varmax. The procedure is rather new and hence new features like cointegration, testing for Granger causality are included, but it also means that more traditional ARIMA modelling as outlined by Box & Je...... & Jenkins is performed in a more modern way using the computer resources which are now available...
Time series modeling for syndromic surveillance
Directory of Open Access Journals (Sweden)
Mandl Kenneth D
2003-01-01
Full Text Available Abstract Background Emergency department (ED based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Methods Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Results Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Conclusions Time series methods applied to historical ED utilization data are an important tool
A generalized additive regression model for survival times
DEFF Research Database (Denmark)
Scheike, Thomas H.
2001-01-01
Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models......Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models...
A generalized additive regression model for survival times
DEFF Research Database (Denmark)
Scheike, Thomas H.
2001-01-01
Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models......Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models...
Greenhouse Modeling Using Continuous Timed Petri Nets
Directory of Open Access Journals (Sweden)
José Luis Tovany
2013-01-01
Full Text Available This paper presents a continuous timed Petri nets (ContPNs based greenhouse modeling methodology. The presented methodology is based on the definition of elementary ContPN modules which are designed to capture the components of a general energy and mass balance differential equation, like parts that are reducing or increasing variables, such as heat, CO2 concentration, and humidity. The semantics of ContPN is also extended in order to deal with variables depending on external greenhouse variables, such as solar radiation. Each external variable is represented by a place whose marking depends on an a priori known function, for instance, the solar radiation function of the greenhouse site, which can be obtained statistically. The modeling methodology is illustrated with a greenhouse modeling example.
Modeling utilization distributions in space and time.
Keating, Kim A; Cherry, Steve
2009-07-01
W. Van Winkle defined the utilization distribution (UD) as a probability density that gives an animal's relative frequency of occurrence in a two-dimensional (x, y) plane. We extend Van Winkle's work by redefining the UD as the relative frequency distribution of an animal's occurrence in all four dimensions of space and time. We then describe a product kernel model estimation method, devising a novel kernel from the wrapped Cauchy distribution to handle circularly distributed temporal covariates, such as day of year. Using Monte Carlo simulations of animal movements in space and time, we assess estimator performance. Although not unbiased, the product kernel method yields models highly correlated (Pearson's r = 0.975) with true probabilities of occurrence and successfully captures temporal variations in density of occurrence. In an empirical example, we estimate the expected UD in three dimensions (x, y, and t) for animals belonging to each of two distinct bighorn sheep (Ovis canadensis) social groups in Glacier National Park, Montana, USA. Results show the method can yield ecologically informative models that successfully depict temporal variations in density of occurrence for a seasonally migratory species. Some implications of this new approach to UD modeling are discussed.
Multi-model cross-pollination in time
Du, Hailiang; Smith, Leonard A.
2017-09-01
The predictive skill of complex models is rarely uniform in model-state space; in weather forecasting models, for example, the skill of the model can be greater in the regions of most interest to a particular operational agency than it is in ;remote; regions of the globe. Given a collection of models, a multi-model forecast system using the cross-pollination in time approach can be generalized to take advantage of instances where some models produce forecasts with more information regarding specific components of the model-state than other models, systematically. This generalization is stated and then successfully demonstrated in a moderate (∼ 40) dimensional nonlinear dynamical system, suggested by Lorenz, using four imperfect models with similar global forecast skill. Applications to weather forecasting and in economic forecasting are discussed. Given that the relative importance of different phenomena in shaping the weather changes in latitude, changes in attitude among forecast centers in terms of the resources assigned to each phenomena are to be expected. The demonstration establishes that cross-pollinating elements of forecast trajectories enriches the collection of simulations upon which the forecast is built, and given the same collection of models can yield a new forecast system with significantly more skill than the original forecast system.
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
Burn-up and Operation Time of Fuel Elements Produced in IPEN
Tondin, Julio Benedito Marin; Filho, Tufic Madi
2011-08-01
The aim of this paper is to present the developed work along the operational and reliability tests of fuel elements produced in the Institute of Energetic and Nuclear Research, IPEN-CNEN/SP, from the 1980's. The study analyzed the U-235 burn evolution and the element remain in the research reactor IEA-R1. The fuel elements are of the type MTR (Material Testing Reactor), the standard with 18 plates and a 12-plate control, with a nominal mean enrichment of 20%.
Energy Technology Data Exchange (ETDEWEB)
Ducomet, B
2000-07-01
We review some models of self-gravitating fluids, used to described in a unified frame work collective vibration modes of heavy nuclei, and large time evolution of radiation and reacting stars. (authors)
Funke, Bernd; López-Puertas, Manuel; Stiller, Gabriele P.; Versick, Stefan; von Clarmann, Thomas
2016-07-01
The MIPAS Fourier transform spectrometer on board Envisat has measured global distributions of the six principal reactive nitrogen (NOy) compounds (HNO3, NO2, NO, N2O5, ClONO2, and HNO4) during 2002-2012. These observations were used previously to detect regular polar winter descent of reactive nitrogen produced by energetic particle precipitation (EPP) down to the lower stratosphere, often called the EPP indirect effect. It has further been shown that the observed fraction of NOy produced by EPP (EPP-NOy) has a nearly linear relationship with the geomagnetic Ap index when taking into account the time lag introduced by transport. Here we exploit these results in a semi-empirical model for computation of EPP-modulated NOy densities and wintertime downward fluxes through stratospheric and mesospheric pressure levels. Since the Ap dependence of EPP-NOy is distorted during episodes of strong descent in Arctic winters associated with elevated stratopause events, a specific parameterization has been developed for these episodes. This model accurately reproduces the observations from MIPAS and is also consistent with estimates from other satellite instruments. Since stratospheric EPP-NOy depositions lead to changes in stratospheric ozone with possible implications for climate, the model presented here can be utilized in climate simulations without the need to incorporate many thermospheric and upper mesospheric processes. By employing historical geomagnetic indices, the model also allows for reconstruction of the EPP indirect effect since 1850. We found secular variations of solar cycle-averaged stratospheric EPP-NOy depositions on the order of 1 GM. In particular, we model a reduction of the EPP-NOy deposition rate during the last 3 decades, related to the coincident decline of geomagnetic activity that corresponds to 1.8 % of the NOy production rate by N2O oxidation. As the decline of the geomagnetic activity level is expected to continue in the coming decades, this is
Outlier Detection in Structural Time Series Models
DEFF Research Database (Denmark)
Marczak, Martyna; Proietti, Tommaso
investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality......Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general...... and a stationary component. Further, we apply both kinds of indicator saturation to detect additive outliers and level shifts in the industrial production series in five European countries....
RTMOD: Real-Time MODel evaluation
DEFF Research Database (Denmark)
Graziani, G.; Galmarini, S.; Mikkelsen, Torben
2000-01-01
. At that time, the World Wide Web was not available to all the exercise participants, and plume predictions were therefore submitted to JRC-Ispra by fax andregular mail for subsequent processing. The rapid development of the World Wide Web in the second half of the nineties, together with the experience gained...... the RTMOD web page for detailed information on the actual release, and as soon as possible they then uploaded their predictions to the RTMOD server and could soon after start their inter-comparison analysis with other modellers. When additionalforecast data arrived, already existing statistical results...
A Stochastic-Dynamic Model for Real Time Flood Forecasting
Chow, K. C. A.; Watt, W. E.; Watts, D. G.
1983-06-01
A stochastic-dynamic model for real time flood forecasting was developed using Box-Jenkins modelling techniques. The purpose of the forecasting system is to forecast flood levels of the Saint John River at Fredericton, New Brunswick. The model consists of two submodels: an upstream model used to forecast the headpond level at the Mactaquac Dam and a downstream model to forecast the water level at Fredericton. Inputs to the system are recorded values of the water level at East Florenceville, the headpond level and gate position at Mactaquac, and the water level at Fredericton. The model was calibrated for the spring floods of 1973, 1974, 1977, and 1978, and its usefulness was verified for the 1979 flood. The forecasting results indicated that the stochastic-dynamic model produces reasonably accurate forecasts for lead times up to two days. These forecasts were then compared to those from the existing forecasting system and were found to be as reliable as those from the existing system.
Using Student-Produced Time-Lapse Plant Movies to Communicate Concepts in Plant Biology
Directory of Open Access Journals (Sweden)
Marcia Harrison-Pitaniello
2013-01-01
Full Text Available Why do students think plants are “boring”? One factor may be that they do not see plant movement in real (i.e., their time. This attitude may negatively impact their understanding of plant biology. Time-lapse movies of plants allow students to see the sophistication of movements involved in both organ development and orientation. The objective of this project was to develop simple methods to capture image sequences for lab analysis and for converting into movies. The technology for making time-lapse movies is now easily attainable and fairly inexpensive, allowing its use for skill levels from grade school through college undergraduates. Presented are example time-lapse movie exercises from both an undergraduate plant physiology course and outreach activities. The time-lapse plant exercises are adaptable to explore numerous topics that incorporate science standards core concepts, competencies, and disciplinary practices as well as to integrate higher order thinking skills and build skills in hypothesis development and communicating results to various audiences.
Brasted, P J; Döbrössy, M D; Robbins, T W; Dunnett, S B
1998-08-01
The dorsal striatum plays a crucial role in mediating voluntary movement. Excitotoxic striatal lesions in rats have previously been shown to impair the initiation but not the execution of movement in a choice reaction time task in an automated lateralised nose-poke apparatus (the "nine-hole box"). Conversely, when a conceptually similar reaction time task has been applied in a conventional operant chamber (or "Skinner box"), striatal lesions have been seen to impair the execution rather than the initiation of the lateralised movement. The present study was undertaken to compare directly these two results by training the same group of rats to perform a choice reaction time task in the two chambers and then comparing the effects of a unilateral excitotoxic striatal lesion in both chambers in parallel. Particular attention was paid to adopting similar parameters and contingencies in the control of the task in the two test chambers. After striatal lesions, the rats showed predominantly contralateral impairments in both tasks. However, they showed a deficit in reaction time in the nine-hole box but an apparent deficit in response execution in the Skinner box. This finding confirms the previous studies and indicates that differences in outcome are not simply attributable to procedural differences in the lesions, training conditions or tasks parameters. Rather, the pattern of reaction time deficit after striatal lesions depends critically on the apparatus used and the precise response requirements for each task.
A generic model for keeping quality of vegetable produce during storage and distribution
Tijskens, L.M.M.; Polderdijk, J.J.
1996-01-01
A generic model on the keeping quality of perishable produce was formulated, based on the kinetics of the decrease of individual quality attributes. The model includes the effects of temperature, chilling injury and different levels of initial quality and of quality acceptance limits. Keeping qualit
Borhan, M. Z.; Ahmad, R.; Rusop, M.; Abdullah, S.
2012-11-01
Centella Asiatica (C. Asiatica)contains asiaticoside as bioactive constituent which can be potentially used in skin healing process. Unfortunately, the normal powders are difficult to be absorbed by the body effectively. In order to improve the value of use, nano C. Asiatica powder was prepared. The influence of milling time was carried out at 0.5, 2, 4, 6, 8 hours and 10 hours. The effect of ball milling at different times was characterized using particles size analysis and FTIR Spectroscopy. The fineness of ground product was evaluated by recording the z-Average (nm), undersize distribution and polydispersity index (PdI). The results show that the smallest size particles by mean is 233 nm while FTIR spectra shows that there is no changing in the major component in the C. Asiatica powders with milling time.
A COMPARISON OF THE TENSILE STRENGTH OF PLASTIC PARTS PRODUCED BY A FUSED DEPOSITION MODELING DEVICE
Directory of Open Access Journals (Sweden)
Juraj Beniak
2015-12-01
Full Text Available Rapid Prototyping systems are nowadays increasingly used in many areas of industry, not only for producing design models but also for producing parts for final use. We need to know the properties of these parts. When we talk about the Fused Deposition Modeling (FDM technique and FDM devices, there are many possible settings for devices and models which could influence the properties of a final part. In addition, devices based on the same principle may use different operational software for calculating the tool path, and this may have a major impact. The aim of this paper is to show the tensile strength value for parts produced from different materials on the Fused Deposition Modeling device when the horizontal orientation of the specimens is changed.
Search for Standard Model Higgs Bosons Produced in Association with W Bosons
Aaltonen, T; Akimoto, T; Albrow, M G; Alvarez-Gonzalez, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P H; Bedeschi, F; Bednar, P; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bölla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, Yu A; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrerar, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillol, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerritop, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Cuenca Almenarr, C; Cuevaso, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; De Barbaro, P; De Cecco, S; Deisher, A; De Lentdeckerd, G; De Lorenzo, G; Dell'Orso, Mauro; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernández, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Forrester, S; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; García, J E; Garfinkel, A F; Gerberich, H; Gerdes, D; Giagu, S; Giakoumopoloua, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokarisa, N; Giordani, M; Giromini, P; Giunta, M; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gómez, G; Gómez-Ceballos, G; Goncharov, M; Gonzlez, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Group, R C; Grundler, U; Guimaraesda Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Hamilton, A; Han, B Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hillc, C S; Hirschbuehl, D; Höcker, A; Hou, S; Houlden, M; Hsu, S C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; Iyutin, B; James, E; Jayatilaka, B; Jeans, D; Jeon, E J; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Le Compte, T; Lee, J; Lee, J; Lee, Y J; Leeq, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Mäki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakisa, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, M; Martinj, V; Martínez, M; Martinez-Ballarin, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNultyi, R; Mehta, A; Mehtälä, P; Menzemerk, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M; Movilla-Fernández, P A; Mulmenstdt, J; Mukherjee, A; Müller, T; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsenf, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Österberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, Aldo L; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohosh, F; Punzi, G; Pursley, J; Rademackerc, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P B; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Salamanna, G; Salt, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyria, A; Shalhout, S Z; Shapiro, M D; Shears, T G; Shepard, P F; Sherman, D; Shimojiman, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Siegrist, J; Sinervo, P; Sisakian, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Söderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; Spreitzer, T; Squillacioti, P; Stanitzki, M; Saint-Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sun, H; Suslov, I; Suzuki, T; Taffarde, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thomg, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; Vallecorsa, S; Van Remortel, N; Varganov, A; Vataga, E; Vzquezl, F; Velev, G; Vellidisa, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouevq, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whitesone, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittichg, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yangm, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zhengb, Y; Zucchelli, S
2007-01-01
We report on the results of a search for standard model Higgs bosons produced in association with W bosons from p-pbar collisions at root s = 1.96 TeV. The search uses a data sample corresponding to approximately 1 fb-1 of integrated luminosity. Events consistent with the W to l-nu and H to b-bbar signature are selected by triggering on a high-pT electron or muon candidate and tagging one or two of the jet candidates as having originated from b quarks. A neural network filter rejects a fraction of tagged charm and light flavor jets, increasing the b-jet purity in the sample and thereby reducing the background to Higgs boson production. We observe no excess l-nu-b-bbar production beyond the background expectation, and we set 95% confidence level upper limits on the production cross section times branching fraction sigma(p-pbar to WH) times Br(H to b-bbar) ranging from 3.9 to 1.3 pb, for specific Higgs boson mass hypotheses in the range 110 to 150 GeV/c2, respectively.
Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal
2017-07-01
Fused Deposition Modeling (FDM) is one of the prominent additive manufacturing technologies for producing polymer products. FDM is a complex additive manufacturing process that can be influenced by many process conditions. The industrial demands required from the FDM process are increasing with higher level product functionality and properties. The functionality and performance of FDM manufactured parts are greatly influenced by the combination of many various FDM process parameters. Designers and researchers always pay attention to study the effects of FDM process parameters on different product functionalities and properties such as mechanical strength, surface quality, dimensional accuracy, build time and material consumption. However, very limited studies have been carried out to investigate and optimize the effect of FDM build parameters on wear performance. This study focuses on the effect of different build parameters on micro-structural and wear performance of FDM specimens using definitive screening design based quadratic model. This would reduce the cost and effort of additive manufacturing engineer to have a systematic approachto make decision among the manufacturing parameters to achieve the desired product quality.
Schreiner, Samuel S.; Dominguez, Jesus A.; Sibille, Laurent; Hoffman, Jeffrey A.
2015-01-01
We present a parametric sizing model for a Molten Electrolysis Reactor that produces oxygen and molten metals from lunar regolith. The model has a foundation of regolith material properties validated using data from Apollo samples and simulants. A multiphysics simulation of an MRE reactor is developed and leveraged to generate a vast database of reactor performance and design trends. A novel design methodology is created which utilizes this database to parametrically design an MRE reactor that 1) can sustain the required mass of molten regolith, current, and operating temperature to meet the desired oxygen production level, 2) can operate for long durations via joule heated, cold wall operation in which molten regolith does not touch the reactor side walls, 3) can support a range of electrode separations to enable operational flexibility. Mass, power, and performance estimates for an MRE reactor are presented for a range of oxygen production levels. The effects of several design variables are explored, including operating temperature, regolith type/composition, batch time, and the degree of operational flexibility.
Since it was first described in the mid-1990s, quantitative real time PCR (Q-PCR) has been widely used in many fields of biomedical research and molecular diagnostics. This method is routinely used to validate whole transcriptome analyses such as DNA microarrays, suppressive subtractive hybridizati...
Producing near-real-time intelligence: predicting the world of tomorrow
Barros, A.I.; Broek, A.C. van den; Dalen, J.A. van; Vecht, B. van der; Wevers, J.
2014-01-01
The complexity and dynamics of current military operations demand reliable and up-to-date intelligence and in particular near-real-time threat assessment. This paper explores the potential of operational analysis techniques in supporting military personnel in processing information from different so
Konishi, Kazuyuki; Yonai, Miharu; Kaneyama, Kanako; Ito, Satoshi; Matsuda, Hideo; Yoshioka, Hajime; Nagai, Takashi; Imai, Kei
2011-10-01
The reproductive ability, milk-producing capacity, survival time and relationships of these parameters with telomere length were investigated in 4 groups of cows produced by somatic cell nuclear transfer (SCNT). Each group was produced using the same donor cells (6 Holstein (1H), 3 Holstein (2H), 4 Jersey (1J) and 5 Japanese Black (1B) cows). As controls, 47 Holstein cows produced by artificial insemination were used. The SCNT cows were artificially inseminated, and multiple deliveries were performed after successive rounds of breeding and conception. No correlation was observed between the telomere length and survival time in the SCNT cows. Causes of death of SCNT cows included accidents, accident-associated infections, inappropriate management, acute mastitis and hypocalcemia. The lifetime productivity of SCNT cows was superior to those of the controls and cell donor cows. All SCNT beef cows with a relatively light burden of lactation remained alive and showed significantly prolonged survival time compared with the cows in the SCNT dairy breeds. These results suggest that the lifetime productivity of SCNT cows was favorable, and their survival time was more strongly influenced by environmental burdens, such as pregnancy, delivery, lactation and feeding management, than by the telomere length.
Harri, Liliya
2009-10-01
The digital thermal technology of producing flexographic printing plates from photopolymer plates is one of the newest technologies. This technology allows to develop flexographic plates without the use of any solvent. The process of producing flexographic printing plates by the digital thermal method consists of several main stages: back exposure, laser exposure, main exposure, thermal development, post exposure, and light finishing. The studies carried out with the use of optical stereoscopic microscopy allowed to determine the effect of time of main exposure to ultraviolet radiation on the dot area, diameter, and edge factor of halftone dots reproduced on flexographic printing plate produced by the digital thermal method, as well as on the quality of reproducing the surface and on the profiles of free-standing printing microelements. The results of the microscopic studies performed have allowed to define the criteria of establishing optimum time of main exposure of photopolymer plates used in the digital thermal technology of producing flexographic printing plates. A precise definition of the criteria for determining the optimum time of main exposure will enable to reduce the time-consuming control tests and to eliminate errors in both the process of manufacturing flexographic printing plates and in the printing process carried out with the use of such plates.
DEFF Research Database (Denmark)
Santillan, Arturo Orozco
2013-01-01
Results of numerical simulations of the sound field produced by a circular piston in a rigid baffled are presented. The aim was to calculate the acoustic streaming and the flow of mass generated by the sound field. For this purpose, the classical finite-difference time-domain method was implemented...
Real-time DIRCM system modeling
Petersson, Mikael
2004-12-01
Directed infrared countermeasures (DIRCM) play an increasingly important role in electronic warfare to counteract threats posed by infrared seekers. The usefulness and performance of such countermeasures depend, for example, on atmospheric conditions (attenuation and turbulence) and platform vibrations, causing pointing and tracking errors for the laser beam and reducing the power transferred to the seeker aperture. These problems make it interesting to simulate the performance of a DIRCM system in order to understand how easy or difficult it is to counteract an approaching threat and evaluate limiting factors in various situations. This paper describes a DIRCM model that has been developed, including atmospheric effects such as attenuation and turbulence as well as closed loop tracking algorithms, where the retro reflex of the laser is used for the pointing control of the beam. The DIRCM model is part of a large simulation framework (EWSim), which also incorporates several descriptions of different seekers (e.g. reticle, rosette, centroid, nutating cross) and models of robot dynamics. Effects of a jamming laser on a specific threat can be readily verified by simulations within this framework. The duel between missile and countermeasure is simulated in near real-time and visualized graphically in 3D. A typical simulation with a reticle seeker jammed by a modulated laser is included in the paper.
Directory of Open Access Journals (Sweden)
Machado R.A.F.
2000-01-01
Full Text Available Particle size distribution (PSD of polystyrene particles produced by suspension polymerization is of fundamental importance in determining suspension stability and product quality attributes. Within a population balance framework, a model is proposed for suspension polymerization reactors to describe the evolution of the PSD. The model includes description of breakage and coalescence rates in terms of reaction kinetics and rheology of the dispersed phase. The model is validated with experimental data of styrene suspension polymerization.
Neural network versus classical time series forecasting models
Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam
2017-05-01
Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.
Joint space-time geostatistical model for air quality surveillance
Russo, A.; Soares, A.; Pereira, M. J.
2009-04-01
Air pollution and peoples' generalized concern about air quality are, nowadays, considered to be a global problem. Although the introduction of rigid air pollution regulations has reduced pollution from industry and power stations, the growing number of cars on the road poses a new pollution problem. Considering the characteristics of the atmospheric circulation and also the residence times of certain pollutants in the atmosphere, a generalized and growing interest on air quality issues led to research intensification and publication of several articles with quite different levels of scientific depth. As most natural phenomena, air quality can be seen as a space-time process, where space-time relationships have usually quite different characteristics and levels of uncertainty. As a result, the simultaneous integration of space and time is not an easy task to perform. This problem is overcome by a variety of methodologies. The use of stochastic models and neural networks to characterize space-time dispersion of air quality is becoming a common practice. The main objective of this work is to produce an air quality model which allows forecasting critical concentration episodes of a certain pollutant by means of a hybrid approach, based on the combined use of neural network models and stochastic simulations. A stochastic simulation of the spatial component with a space-time trend model is proposed to characterize critical situations, taking into account data from the past and a space-time trend from the recent past. To identify near future critical episodes, predicted values from neural networks are used at each monitoring station. In this paper, we describe the design of a hybrid forecasting tool for ambient NO2 concentrations in Lisbon, Portugal.
2007-01-01
Video observation has shown that feeding-current-producing calanoid copepods modulate their feeding currents by displaying a sequence of different swimming behaviours during a time period of up to tens of seconds. In order to understand the feeding-current modulation process, we numerically modelled the steady feeding currents for different modes of observed copepod motion behaviours (i.e. free sinking, partial sinking, hovering, vertical swimming upward and horizontal swimming backward or fo...
Use of Real Time Satellite Infrared and Ocean Color to Produce Ocean Products
Roffer, M. A.; Muller-Karger, F. E.; Westhaver, D.; Gawlikowski, G.; Upton, M.; Hall, C.
2014-12-01
Real-time data products derived from infrared and ocean color satellites are useful for several types of users around the world. Highly relevant applications include recreational and commercial fisheries, commercial towing vessel and other maritime and navigation operations, and other scientific and applied marine research. Uses of the data include developing sampling strategies for research programs, tracking of water masses and ocean fronts, optimizing ship routes, evaluating water quality conditions (coastal, estuarine, oceanic), and developing fisheries and essential fish habitat indices. Important considerations for users are data access and delivery mechanisms, and data formats. At this time, the data are being generated in formats increasingly available on mobile computing platforms, and are delivered through popular interfaces including social media (Facebook, Linkedin, Twitter and others), Google Earth and other online Geographical Information Systems, or are simply distributed via subscription by email. We review 30 years of applications and describe how we develop customized products and delivery mechanisms working directly with users. We review benefits and issues of access to government databases (NOAA, NASA, ESA), standard data products, and the conversion to tailored products for our users. We discuss advantages of different product formats and of the platforms used to display and to manipulate the data.
On the use of shockwave models in laser produced plasma expansion
Energy Technology Data Exchange (ETDEWEB)
De Posada, E; Arronte, M A; Ponce, L; Rodriguez, E; Flores, T [Centro de Investigacion en Ciencia Aplicada y TecnologIa Avanzada, Unidad Altamira, Tamaulipas (Mexico); Lunney, J G, E-mail: edeposada@ipn.mx [School of Physics, Trinity College Dublin (Ireland)
2011-01-01
Interaction of medium to high peak power laser pulses with solid materials produces a plasma that expands supersonically. Expansions of such plasmas have been studied and several models have been proposed to describe it. This work presents a study of the expansion of laser produced plasmas in both vacuum and gas environment by using Langmuir probe and photography. It compares some of the most used models to identify that which better describes the expansion process. In vacuum, such process is properly described by the Anisimov model. However when expanding in a background gas it is found that the Sedov-Taylor model fits properly the position of generated shockwave but overestimates both kinetic energy and pressure of the expanding plasma. Such problem is solved by using a modification of the Freiwald-Axford model. Finally it is demonstrated that after the plasma stopping distance the plasma inters in a diffusive regime.
An Inventory Model with Price and Quality Dependent Demand Where Some Items Produced Are Defective
Directory of Open Access Journals (Sweden)
Tapan Kumar Datta
2013-01-01
Full Text Available This paper analyzes an inventory system for joint determination of product quality and selling price where a fraction of items produced are defective. It is assumed that only a fraction of defective items can be repaired/reworked. The demand rate depends upon both the quality and the selling price of the product. The production rate, unit price, and carrying cost depend upon the quality of the items produced. Quality index is used to determine the quality of the product. An algorithm is provided to solve the model with given values of model parameters. Sensitivity analysis has also been performed.
Time series models of symptoms in schizophrenia.
Tschacher, Wolfgang; Kupper, Zeno
2002-12-15
The symptom courses of 84 schizophrenia patients (mean age: 24.4 years; mean previous admissions: 1.3; 64% males) of a community-based acute ward were examined to identify dynamic patterns of symptoms and to investigate the relation between these patterns and treatment outcome. The symptoms were monitored by systematic daily staff ratings using a scale composed of three factors: psychoticity, excitement, and withdrawal. Patients showed moderate to high symptomatic improvement documented by effect size measures. Each of the 84 symptom trajectories was analyzed by time series methods using vector autoregression (VAR) that models the day-to-day interrelations between symptom factors. Multiple and stepwise regression analyses were then performed on the basis of the VAR models. Two VAR parameters were found to be associated significantly with favorable outcome in this exploratory study: 'withdrawal preceding a reduction of psychoticity' as well as 'excitement preceding an increase of withdrawal'. The findings were interpreted as generating hypotheses about how patients cope with psychotic episodes.
Upper D region chemical kinetic modeling of LORE relaxation times
Gordillo-Vázquez, F. J.; Luque, A.; Haldoupis, C.
2016-04-01
The recovery times of upper D region electron density elevations, caused by lightning-induced electromagnetic pulses (EMP), are modeled. The work was motivated from the need to understand a recently identified narrowband VLF perturbation named LOREs, an acronym for LOng Recovery Early VLF events. LOREs associate with long-living electron density perturbations in the upper D region ionosphere; they are generated by strong EMP radiated from large peak current intensities of ±CG (cloud to ground) lightning discharges, known also to be capable of producing elves. Relaxation model scenarios are considered first for a weak enhancement in electron density and then for a much stronger one caused by an intense lightning EMP acting as an impulsive ionization source. The full nonequilibrium kinetic modeling of the perturbed mesosphere in the 76 to 92 km range during LORE-occurring conditions predicts that the electron density relaxation time is controlled by electron attachment at lower altitudes, whereas above 79 km attachment is balanced totally by associative electron detachment so that electron loss at these higher altitudes is controlled mainly by electron recombination with hydrated positive clusters H+(H2O)n and secondarily by dissociative recombination with NO+ ions, a process which gradually dominates at altitudes >88 km. The calculated recovery times agree fairly well with LORE observations. In addition, a simplified (quasi-analytic) model build for the key charged species and chemical reactions is applied, which arrives at similar results with those of the full kinetic model. Finally, the modeled recovery estimates for lower altitudes, that is <79 km, are in good agreement with the observed short recovery times of typical early VLF events, which are known to be associated with sprites.
Directory of Open Access Journals (Sweden)
M. I. Gutierrez
2016-01-01
Full Text Available Objectives. To present a quantitative comparison of thermal patterns produced by the piston-in-a-baffle approach with those generated by a physiotherapy ultrasonic device and to show the dependency among thermal patterns and acoustic intensity distributions. Methods. The finite element (FE method was used to model an ideal acoustic field and the produced thermal pattern to be compared with the experimental acoustic and temperature distributions produced by a real ultrasonic applicator. A thermal model using the measured acoustic profile as input is also presented for comparison. Temperature measurements were carried out with thermocouples inserted in muscle phantom. The insertion place of thermocouples was monitored with ultrasound imaging. Results. Modeled and measured thermal profiles were compared within the first 10 cm of depth. The ideal acoustic field did not adequately represent the measured field having different temperature profiles (errors 10% to 20%. Experimental field was concentrated near the transducer producing a region with higher temperatures, while the modeled ideal temperature was linearly distributed along the depth. The error was reduced to 7% when introducing the measured acoustic field as the input variable in the FE temperature modeling. Conclusions. Temperature distributions are strongly related to the acoustic field distributions.
Lopez-Haro, S. A.; Leija, L.
2016-01-01
Objectives. To present a quantitative comparison of thermal patterns produced by the piston-in-a-baffle approach with those generated by a physiotherapy ultrasonic device and to show the dependency among thermal patterns and acoustic intensity distributions. Methods. The finite element (FE) method was used to model an ideal acoustic field and the produced thermal pattern to be compared with the experimental acoustic and temperature distributions produced by a real ultrasonic applicator. A thermal model using the measured acoustic profile as input is also presented for comparison. Temperature measurements were carried out with thermocouples inserted in muscle phantom. The insertion place of thermocouples was monitored with ultrasound imaging. Results. Modeled and measured thermal profiles were compared within the first 10 cm of depth. The ideal acoustic field did not adequately represent the measured field having different temperature profiles (errors 10% to 20%). Experimental field was concentrated near the transducer producing a region with higher temperatures, while the modeled ideal temperature was linearly distributed along the depth. The error was reduced to 7% when introducing the measured acoustic field as the input variable in the FE temperature modeling. Conclusions. Temperature distributions are strongly related to the acoustic field distributions. PMID:27999801
Mangun, G R; Buck, L A
1998-03-01
This study investigated the simple reaction time (RT) and event-related potential (ERP) correlates of biasing attention towards a location in the visual field. RTs and ERPs were recorded to stimuli flashed randomly and with equal probability to the left and right visual hemifields in the three blocked, covert attention conditions: (i) attention divided equally to left and right hemifield locations; (ii) attention biased towards the left location; or (iii) attention biased towards the right location. Attention was biased towards left or right by instructions to the subjects, and responses were required to all stimuli. Relative to the divided attention condition, RTs were significantly faster for targets occurring where more attention was allocated (benefits), and slower to targets where less attention was allocated (costs). The early P1 (100-140 msec) component over the lateral occipital scalp regions showed attentional benefits. There were no amplitude modulations of the occipital N1 (125-180 msec) component with attention. Between 200 and 500 msec latency, a late positive deflection (LPD) showed both attentional costs and benefits. The behavioral findings show that when sufficiently induced to bias attention, human observers demonstrate RT benefits as well as costs. The corresponding P1 benefits suggest that the RT benefits of spatial attention may arise as the result of modulations of visual information processing in the extrastriate visual cortex.
Factors affecting magnitude and time course of neuromuscular block produced by suxamethonium.
Vanlinthout, L E; van Egmond, J; de Boo, T; Lerou, J G; Wevers, R A; Booij, L H
1992-07-01
This study was designed to identify factors that significantly alter the magnitude and duration of suxamethonium-induced neuromuscular block in patients with an apparently normal genotype for pseudocholinesterase. One hundred and fifty-six adults (ages 18-65 yr) were allocated to 13 subgroups. Patients in each subgroup received suxamethonium 50-2000 micrograms kg-1. The mechanographic response of the adductor pollicis brevis muscle to ulnar nerve stimulation was recorded. The ED50 was found to be 167 micrograms kg-1, ED90 was 316 micrograms kg-1 and ED95 was 392 micrograms kg-1. The duration of action (delta t) was in agreement with earlier published results. The magnitude of block was dose-related and decreased with increasing onset time (ton) and pseudocholinesterase activity (PChA). Neither age nor gender affected the degree of suxamethonium-induced block. Delta t was dose-related, decreased with increasing PChA, and was shorter for women. Age and ton had no effect on delta t.
The Influence of Variation in Time and HCl Concentration to the Glucose Produced from Kepok Banana
Widodo M, Rohman; Noviyanto, Denny; RM, Faisal
2016-01-01
Kepok banana (Musa paradisiaca) is a plant that has many advantagesfrom its fruit, stems, leaves, flowers and cob. However, we just tend to take benefit from the fruit. We grow and harvest the fruit without taking advantages from other parts. So they would be a waste or detrimental to animal nest if not used. The idea to take the benefit from the banana crop yields, especially cob is rarely explored. This study is an introduction to the use of banana weevil especially from the glucose it contains. This study uses current methods of hydrolysis using HCl as a catalyst with the concentration variation of 0.4 N, 0.6 N and 0.8 N and hydrolysis times variation of 20 minutes, 25 minutes and 30 minutes. The stages in the hydrolysis include preparation of materials, the process of hydrolysis and analysis of test results using Fehling and titrate with standard glucose solution. HCl is used as a catalyst because it is cheaper than the enzyme that has the same function. NaOH 60% is used for neutralizing the pH of the filtrate result of hydrolysis. From the results of analysis, known thatthe biggest yield of glucose is at concentration 0.8 N and at 30 minutes reaction, it contains 6.25 gram glucose / 20 gram dry sampel, and the convertion is 27.22% at 20 gram dry sampel.
Modeling Departure Time Choice with Stochastic Networks
Li, H.; Bliemer, M.C.J.; Bovy, P.H.L.
2010-01-01
Stochastic supply and fluctuating travel demand lead to stochasticity in travel times and travel costs experienced by travelers from time to time within a day and at the same time from day to day. Many studies show that travel time un-reliability has significant impacts on traveler’s choice behavior
Computer Aided Continuous Time Stochastic Process Modelling
DEFF Research Database (Denmark)
Kristensen, N.R.; Madsen, Henrik; Jørgensen, Sten Bay
2001-01-01
A grey-box approach to process modelling that combines deterministic and stochastic modelling is advocated for identification of models for model-based control of batch and semi-batch processes. A computer-aided tool designed for supporting decision-making within the corresponding modelling cycle...
Search for standard model Higgs bosons produced in association with W bosons.
Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; González, B Alvarez; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Aoki, M; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzi-Bacchetta, P; Azzurri, P; Bacchetta, N; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Baroiant, S; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Behari, S; Bellettini, G; Bellinger, J; Belloni, A; Benjamin, D; Beretvas, A; Beringer, J; Berry, T; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bolshov, A; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cooper, B; Copic, K; Cordelli, M; Cortiana, G; Crescioli, F; Almenar, C Cuenca; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lentdecker, G; De Lorenzo, G; Dell'Orso, M; Demortier, L; Deng, J; Deninno, M; De Pedis, D; Derwent, P F; Di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Forrester, S; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Gerberich, H; Gerdes, D; Giagu, S; Giakoumopolou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Hamilton, A; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; Iyutin, B; James, E; Jayatilaka, B; Jeans, D; Jeon, E J; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Kerzel, U; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Klute, M; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kraus, J; Kreps, M; Kroll, J; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhlmann, S E; Kuhr, T; Kulkarni, N P; Kusakabe, Y; Kwang, S; Laasanen, A T; Lai, S; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, J; Lee, J; Lee, Y J; Lee, S W; Lefèvre, R; Leonardo, N; Leone, S; Levy, S; Lewis, J D; Lin, C; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, M; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzemer, S; Menzione, A; Merkel, P; Mesropian, C; Messina, A; Miao, T; Miladinovic, N; Miles, J; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M; Fernandez, P Movilla; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Oldeman, R; Orava, R; Osterberg, K; Griso, S Pagan; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Piedra, J; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Portell, X; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Salamanna, G; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyria, A; Shalhout, S Z; Shapiro, M D; Shears, T; Shepard, P F; Sherman, D; Shimojima, M; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Siegrist, J; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soderberg, M; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spinella, F; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Sun, H; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Tourneur, S; Trischuk, W; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Yagil, A; Yamamoto, K; Yamaoka, J; Yamashita, T; Yang, C; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S; Group, R C
2008-02-01
We report on the results of a search for standard model Higgs bosons produced in association with W bosons from pp[over] collisions at sqrt[s]=1.96 TeV. The search uses a data sample corresponding to approximately 1 fb(-1) of integrated luminosity. Events consistent with the W-->lnu and H-->bb[over] signature are selected by triggering on a high-p(T) electron or muon candidate and tagging one or two of the jet candidates as having originated from b quarks. A neural network filter rejects a fraction of tagged charm and light-flavor jets, increasing the b-jet purity in the sample. We observe no excess lnubb[over] production beyond the background expectation, and we set 95% confidence level upper limits on the production cross section times branching fraction sigma(pp[over]-->WH)Br(H-->bb[over]) ranging from 3.9 to 1.3 pb, for specific Higgs boson mass hypotheses in the range 110 to 150 GeV/c2, respectively.
Modeling of laser produced plasma and z-pinch x-ray lasers
Energy Technology Data Exchange (ETDEWEB)
Dunn, J; Frati, M; Gonzales, J J; Kalashnikov, M P; Marconi, M C; Moreno, C H; Nickels, P V; Osterheld, A L; Rocca, J J; Sandner, W; Shlyaptsev, V N
1999-02-07
In this work we describe our theoretical activities in two directions of interest. First, we discuss progress in modeling laser produced plasmas mostly related to transient collisional excitation scheme experiments with Ne- and recently with Ni-like ions. Calculations related to the delay between laser pulses, transient gain duration and hybrid laser/capillary approach are described in more detail. Second, the capillary discharge plasma research, extended to wider range of currents and rise-times has been outlined. We have systematically evaluated the major plasma and atomic kinetic properties by comparing near- and far-field X-ray laser output with that for the capillary Argon X-ray laser operating under typical current values. Consistent with the experiment insight was obtained for the 469{angstrom} X-ray laser shadowgraphy experiments with very small kiloamp currents. At higher currents, as much as {approximately}200 kA we evaluated plasma temperature, density and compared x-ray source size and emitted spectra.
Search for Standard Model Higgs Bosons Produced in Association with W Bosons
Aaltonen, T.; Adelman, J.; Akimoto, T.; Albrow, M. G.; González, B. Álvarez; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Aoki, M.; Apollinari, G.; Apresyan, A.; Arisawa, T.; Artikov, A.; Ashmanskas, W.; Attal, A.; Aurisano, A.; Azfar, F.; Azzi-Bacchetta, P.; Azzurri, P.; Bacchetta, N.; Badgett, W.; Barbaro-Galtieri, A.; Barnes, V. E.; Barnett, B. A.; Baroiant, S.; Bartsch, V.; Bauer, G.; Beauchemin, P.-H.; Bedeschi, F.; Bednar, P.; Behari, S.; Bellettini, G.; Bellinger, J.; Belloni, A.; Benjamin, D.; Beretvas, A.; Beringer, J.; Berry, T.; Bhatti, A.; Binkley, M.; Bisello, D.; Bizjak, I.; Blair, R. E.; Blocker, C.; Blumenfeld, B.; Bocci, A.; Bodek, A.; Boisvert, V.; Bolla, G.; Bolshov, A.; Bortoletto, D.; Boudreau, J.; Boveia, A.; Brau, B.; Bridgeman, A.; Brigliadori, L.; Bromberg, C.; Brubaker, E.; Budagov, J.; Budd, H. S.; Budd, S.; Burkett, K.; Busetto, G.; Bussey, P.; Buzatu, A.; Byrum, K. L.; Cabrera, S.; Campanelli, M.; Campbell, M.; Canelli, F.; Canepa, A.; Carlsmith, D.; Carosi, R.; Carrillo, S.; Carron, S.; Casal, B.; Casarsa, M.; Castro, A.; Catastini, P.; Cauz, D.; Cavalli-Sforza, M.; Cerri, A.; Cerrito, L.; Chang, S. H.; Chen, Y. C.; Chertok, M.; Chiarelli, G.; Chlachidze, G.; Chlebana, F.; Cho, K.; Chokheli, D.; Chou, J. P.; Choudalakis, G.; Chuang, S. H.; Chung, K.; Chung, W. H.; Chung, Y. S.; Ciobanu, C. I.; Ciocci, M. A.; Clark, A.; Clark, D.; Compostella, G.; Convery, M. E.; Conway, J.; Cooper, B.; Copic, K.; Cordelli, M.; Cortiana, G.; Crescioli, F.; Cuenca Almenar, C.; Cuevas, J.; Culbertson, R.; Cully, J. C.; Dagenhart, D.; Datta, M.; Davies, T.; de Barbaro, P.; de Cecco, S.; Deisher, A.; de Lentdecker, G.; de Lorenzo, G.; Dell'Orso, M.; Demortier, L.; Deng, J.; Deninno, M.; de Pedis, D.; Derwent, P. F.; di Giovanni, G. P.; Dionisi, C.; di Ruzza, B.; Dittmann, J. R.; D'Onofrio, M.; Donati, S.; Dong, P.; Donini, J.; Dorigo, T.; Dube, S.; Efron, J.; Erbacher, R.; Errede, D.; Errede, S.; Eusebi, R.; Fang, H. C.; Farrington, S.; Fedorko, W. T.; Feild, R. G.; Feindt, M.; Fernandez, J. P.; Ferrazza, C.; Field, R.; Flanagan, G.; Forrest, R.; Forrester, S.; Franklin, M.; Freeman, J. C.; Furic, I.; Gallinaro, M.; Galyardt, J.; Garberson, F.; Garcia, J. E.; Garfinkel, A. F.; Gerberich, H.; Gerdes, D.; Giagu, S.; Giakoumopolou, V.; Giannetti, P.; Gibson, K.; Gimmell, J. L.; Ginsburg, C. M.; Giokaris, N.; Giordani, M.; Giromini, P.; Giunta, M.; Glagolev, V.; Glenzinski, D.; Gold, M.; Goldschmidt, N.; Golossanov, A.; Gomez, G.; Gomez-Ceballos, G.; Goncharov, M.; González, O.; Gorelov, I.; Goshaw, A. T.; Goulianos, K.; Gresele, A.; Grinstein, S.; Grosso-Pilcher, C.; Group, R. C.; Grundler, U.; Guimaraes da Costa, J.; Gunay-Unalan, Z.; Haber, C.; Hahn, K.; Hahn, S. R.; Halkiadakis, E.; Hamilton, A.; Han, B.-Y.; Han, J. Y.; Handler, R.; Happacher, F.; Hara, K.; Hare, D.; Hare, M.; Harper, S.; Harr, R. F.; Harris, R. M.; Hartz, M.; Hatakeyama, K.; Hauser, J.; Hays, C.; Heck, M.; Heijboer, A.; Heinemann, B.; Heinrich, J.; Henderson, C.; Herndon, M.; Heuser, J.; Hewamanage, S.; Hidas, D.; Hill, C. S.; Hirschbuehl, D.; Hocker, A.; Hou, S.; Houlden, M.; Hsu, S.-C.; Huffman, B. T.; Hughes, R. E.; Husemann, U.; Huston, J.; Incandela, J.; Introzzi, G.; Iori, M.; Ivanov, A.; Iyutin, B.; James, E.; Jayatilaka, B.; Jeans, D.; Jeon, E. J.; Jindariani, S.; Johnson, W.; Jones, M.; Joo, K. K.; Jun, S. Y.; Jung, J. E.; Junk, T. R.; Kamon, T.; Kar, D.; Karchin, P. E.; Kato, Y.; Kephart, R.; Kerzel, U.; Khotilovich, V.; Kilminster, B.; Kim, D. H.; Kim, H. S.; Kim, J. E.; Kim, M. J.; Kim, S. B.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kirsch, L.; Klimenko, S.; Klute, M.; Knuteson, B.; Ko, B. R.; Koay, S. A.; Kondo, K.; Kong, D. J.; Konigsberg, J.; Korytov, A.; Kotwal, A. V.; Kraus, J.; Kreps, M.; Kroll, J.; Krumnack, N.; Kruse, M.; Krutelyov, V.; Kubo, T.; Kuhlmann, S. E.; Kuhr, T.; Kulkarni, N. P.; Kusakabe, Y.; Kwang, S.; Laasanen, A. T.; Lai, S.; Lami, S.; Lammel, S.; Lancaster, M.; Lander, R. L.; Lannon, K.; Lath, A.; Latino, G.; Lazzizzera, I.; Lecompte, T.; Lee, J.; Lee, J.; Lee, Y. J.; Lee, S. W.; Lefèvre, R.; Leonardo, N.; Leone, S.; Levy, S.; Lewis, J. D.; Lin, C.; Lin, C. S.; Linacre, J.; Lindgren, M.; Lipeles, E.; Lister, A.; Litvintsev, D. O.; Liu, T.; Lockyer, N. S.; Loginov, A.; Loreti, M.; Lovas, L.; Lu, R.-S.; Lucchesi, D.; Lueck, J.; Luci, C.; Lujan, P.; Lukens, P.; Lungu, G.; Lyons, L.; Lys, J.; Lysak, R.; Lytken, E.; Mack, P.; MacQueen, D.; Madrak, R.; Maeshima, K.; Makhoul, K.; Maki, T.; Maksimovic, P.; Malde, S.; Malik, S.; Manca, G.; Manousakis, A.; Margaroli, F.; Marino, C.; Marino, C. P.; Martin, A.; Martin, M.; Martin, V.; Martínez, M.; Martínez-Ballarín, R.; Maruyama, T.; Mastrandrea, P.; Masubuchi, T.; Mattson, M. E.; Mazzanti, P.; McFarland, K. S.; McIntyre, P.; McNulty, R.; Mehta, A.; Mehtala, P.; Menzemer, S.; Menzione, A.; Merkel, P.; Mesropian, C.; Messina, A.; Miao, T.; Miladinovic, N.; Miles, J.; Miller, R.; Mills, C.; Milnik, M.; Mitra, A.; Mitselmakher, G.; Miyake, H.; Moed, S.; Moggi, N.; Moon, C. S.; Moore, R.; Morello, M.; Movilla Fernandez, P.; Mülmenstädt, J.; Mukherjee, A.; Muller, Th.; Mumford, R.; Murat, P.; Mussini, M.; Nachtman, J.; Nagai, Y.; Nagano, A.; Naganoma, J.; Nakamura, K.; Nakano, I.; Napier, A.; Necula, V.; Neu, C.; Neubauer, M. S.; Nielsen, J.; Nodulman, L.; Norman, M.; Norniella, O.; Nurse, E.; Oh, S. H.; Oh, Y. D.; Oksuzian, I.; Okusawa, T.; Oldeman, R.; Orava, R.; Osterberg, K.; Pagan Griso, S.; Pagliarone, C.; Palencia, E.; Papadimitriou, V.; Papaikonomou, A.; Paramonov, A. A.; Parks, B.; Pashapour, S.; Patrick, J.; Pauletta, G.; Paulini, M.; Paus, C.; Pellett, D. E.; Penzo, A.; Phillips, T. J.; Piacentino, G.; Piedra, J.; Pinera, L.; Pitts, K.; Plager, C.; Pondrom, L.; Portell, X.; Poukhov, O.; Pounder, N.; Prakoshyn, F.; Pronko, A.; Proudfoot, J.; Ptohos, F.; Punzi, G.; Pursley, J.; Rademacker, J.; Rahaman, A.; Ramakrishnan, V.; Ranjan, N.; Redondo, I.; Reisert, B.; Rekovic, V.; Renton, P.; Rescigno, M.; Richter, S.; Rimondi, F.; Ristori, L.; Robson, A.; Rodrigo, T.; Rogers, E.; Rolli, S.; Roser, R.; Rossi, M.; Rossin, R.; Roy, P.; Ruiz, A.; Russ, J.; Rusu, V.; Saarikko, H.; Safonov, A.; Sakumoto, W. K.; Salamanna, G.; Saltó, O.; Santi, L.; Sarkar, S.; Sartori, L.; Sato, K.; Savoy-Navarro, A.; Scheidle, T.; Schlabach, P.; Schmidt, E. E.; Schmidt, M. A.; Schmidt, M. P.; Schmitt, M.; Schwarz, T.; Scodellaro, L.; Scott, A. L.; Scribano, A.; Scuri, F.; Sedov, A.; Seidel, S.; Seiya, Y.; Semenov, A.; Sexton-Kennedy, L.; Sfyria, A.; Shalhout, S. Z.; Shapiro, M. D.; Shears, T.; Shepard, P. F.; Sherman, D.; Shimojima, M.; Shochet, M.; Shon, Y.; Shreyber, I.; Sidoti, A.; Siegrist, J.; Sinervo, P.; Sisakyan, A.; Slaughter, A. J.; Slaunwhite, J.; Sliwa, K.; Smith, J. R.; Snider, F. D.; Snihur, R.; Soderberg, M.; Soha, A.; Somalwar, S.; Sorin, V.; Spalding, J.; Spinella, F.; Spreitzer, T.; Squillacioti, P.; Stanitzki, M.; St. Denis, R.; Stelzer, B.; Stelzer-Chilton, O.; Stentz, D.; Strologas, J.; Stuart, D.; Suh, J. S.; Sukhanov, A.; Sun, H.; Suslov, I.; Suzuki, T.; Taffard, A.; Takashima, R.; Takeuchi, Y.; Tanaka, R.; Tecchio, M.; Teng, P. K.; Terashi, K.; Thom, J.; Thompson, A. S.; Thompson, G. A.; Thomson, E.; Tipton, P.; Tiwari, V.; Tkaczyk, S.; Toback, D.; Tokar, S.; Tollefson, K.; Tomura, T.; Tonelli, D.; Torre, S.; Torretta, D.; Tourneur, S.; Trischuk, W.; Tu, Y.; Turini, N.; Ukegawa, F.; Uozumi, S.; Vallecorsa, S.; van Remortel, N.; Varganov, A.; Vataga, E.; Vázquez, F.; Velev, G.; Vellidis, C.; Veszpremi, V.; Vidal, M.; Vidal, R.; Vila, I.; Vilar, R.; Vine, T.; Vogel, M.; Volobouev, I.; Volpi, G.; Würthwein, F.; Wagner, P.; Wagner, R. G.; Wagner, R. L.; Wagner-Kuhr, J.; Wagner, W.; Wakisaka, T.; Wallny, R.; Wang, S. M.; Warburton, A.; Waters, D.; Weinberger, M.; Wester, W. C., III; Whitehouse, B.; Whiteson, D.; Wicklund, A. B.; Wicklund, E.; Williams, G.; Williams, H. H.; Wilson, P.; Winer, B. L.; Wittich, P.; Wolbers, S.; Wolfe, C.; Wright, T.; Wu, X.; Wynne, S. M.; Yagil, A.; Yamamoto, K.; Yamaoka, J.; Yamashita, T.; Yang, C.; Yang, U. K.; Yang, Y. C.; Yao, W. M.; Yeh, G. P.; Yoh, J.; Yorita, K.; Yoshida, T.; Yu, G. B.; Yu, I.; Yu, S. S.; Yun, J. C.; Zanello, L.; Zanetti, A.; Zaw, I.; Zhang, X.; Zheng, Y.; Zucchelli, S.
2008-02-01
We report on the results of a search for standard model Higgs bosons produced in association with W bosons from pp¯ collisions at s=1.96TeV. The search uses a data sample corresponding to approximately 1fb-1 of integrated luminosity. Events consistent with the W→ℓν and H→bb¯ signature are selected by triggering on a high-pT electron or muon candidate and tagging one or two of the jet candidates as having originated from b quarks. A neural network filter rejects a fraction of tagged charm and light-flavor jets, increasing the b-jet purity in the sample. We observe no excess ℓνbb¯ production beyond the background expectation, and we set 95% confidence level upper limits on the production cross section times branching fraction σ(pp¯→WH)Br(H→bb¯) ranging from 3.9 to 1.3 pb, for specific Higgs boson mass hypotheses in the range 110 to 150GeV/c2, respectively.
Search for Standard Model Higgs Bosons Produced in Association with W Bosons
Energy Technology Data Exchange (ETDEWEB)
Aaltonen, T.
2007-10-01
The authors report on the results of a search for standard model Higgs bosons produced in association with W bosons from p{bar p} collisions at {radical}s = 1.96 TeV. The search uses a data sample corresponding to approximately 1 fb{sup -1} of integrated luminosity. Events consistent with the W {yields} {ell}{nu} and H {yields} b{bar b} signature are selected by triggering on a high-p{sub T} electron or muon candidate and tagging one or two of the jet candidates as having originated from b quarks. A neural network filter rejects a fraction of tagged charm and light flavor jets, increasing the b-jet purity in the sample and thereby reducing the background to Higgs boson production. They observe no excess {ell}{nu}b{bar b} production beyond the background expectation, and they set 95% confidence level upper limits on the production cross section times branching fraction {sigma}(p{bar p} {yields} WH) {center_dot} Br(H {yields} b{bar b}) ranging from 3.9 to 1.3 pb, for specific Higgs boson mass hypotheses in the range 110 to 150 GeV/c{sup 2}, respectively.
Time-varying parameter auto-regressive models for autocovariance nonstationary time series
Institute of Scientific and Technical Information of China (English)
FEI WanChun; BAI Lun
2009-01-01
In this paper,autocovariance nonstationary time series is clearly defined on a family of time series.We propose three types of TVPAR (time-varying parameter auto-regressive) models:the full order TVPAR model,the time-unvarying order TVPAR model and the time-varying order TVPAR model for autocovariance nonstationary time series.Related minimum AIC (Akaike information criterion) estimations are carried out.
Time-varying parameter auto-regressive models for autocovariance nonstationary time series
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
In this paper, autocovariance nonstationary time series is clearly defined on a family of time series. We propose three types of TVPAR (time-varying parameter auto-regressive) models: the full order TVPAR model, the time-unvarying order TVPAR model and the time-varying order TV-PAR model for autocovariance nonstationary time series. Related minimum AIC (Akaike information criterion) estimations are carried out.
Subeihi, Haitham
Introduction: Digital models of dental arches play a more and more important role in dentistry. A digital dental model can be generated by directly scanning intraoral structures, by scanning a conventional impression of oral structures or by scanning a stone cast poured from the conventional impression. An accurate digital scan model is a fundamental part for the fabrication of dental restorations. Aims: 1. To compare the dimensional accuracy of digital dental models produced by scanning of impressions versus scanning of stone casts. 2. To compare the dimensional accuracy of digital dental models produced by scanning of impressions made of three different materials (polyvinyl siloxane, polyether or vinyl polyether silicone). Methods and Materials: This laboratory study included taking addition silicone, polyether and vinyl polyether silicone impressions from an epoxy reference model that was created from an original typodont. Teeth number 28 and 30 on the typodont with a missing tooth number 29 were prepared for a metal-ceramic three-unit fixed dental prosthesis with tooth #29 being a pontic. After tooth preparation, an epoxy resin reference model was fabricated by duplicating the typodont quadrant that included the tooth preparations. From this reference model 12 polyvinyl siloxane impressions, 12 polyether impressions and 12 vinyl polyether silicone impressions were made. All 36 impressions were scanned before pouring them with dental stone. The 36 dental stone casts were, in turn, scanned to produce digital models. A reference digital model was made by scanning the reference model. Six groups of digital models were produced. Three groups were made by scanning of the impressions obtained with the three different materials, the other three groups involved the scanning of the dental casts that resulted from pouring the impressions made with the three different materials. Groups of digital models were compared using Root Mean Squares (RMS) in terms of their
Polarization of inclusively produced $\\Lambda_{c}$ in a QCD based hybrid model
Goldstein, G R
1999-01-01
A hybrid model is presented for hadron polarization that is based on perturbative QCD subprocesses and the recombination of polarized quarks to form polarized hadrons. The model, originally applied to polarized $\\Lambda$'s that were inclusively produced by proton beams, is extended to include pion beams and polarized $\\Lambda_c$'s. The resulting polarizations are calculated as functions of $x_F$ and $p_T$ for high energies and are found to be in fair agreement with recent experiments.
Directory of Open Access Journals (Sweden)
Oleksander I. Zaporozhets
2009-04-01
Full Text Available Experimental measuring of air pollution inside the airport, produced by aircraft engine emission during accelaration and take-off on the runway. Measurement data were used for verification of modelling results according to complex model «PolEmiCa». It consists of the following basic components: engine emission inventory calculation; transport of the contaminants by engine jets, dispersion of the contaminants in atmosphere due to wind and atmospheric turbulence.
A comparison of cosmological models using time delay lenses
Energy Technology Data Exchange (ETDEWEB)
Wei, Jun-Jie; Wu, Xue-Feng; Melia, Fulvio, E-mail: jjwei@pmo.ac.cn, E-mail: xfwu@pmo.ac.cn, E-mail: fmelia@email.arizona.edu [Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210008 (China)
2014-06-20
The use of time-delay gravitational lenses to examine the cosmological expansion introduces a new standard ruler with which to test theoretical models. The sample suitable for this kind of work now includes 12 lens systems, which have thus far been used solely for optimizing the parameters of ΛCDM. In this paper, we broaden the base of support for this new, important cosmic probe by using these observations to carry out a one-on-one comparison between competing models. The currently available sample indicates a likelihood of ∼70%-80% that the R {sub h} = ct universe is the correct cosmology versus ∼20%-30% for the standard model. This possibly interesting result reinforces the need to greatly expand the sample of time-delay lenses, e.g., with the successful implementation of the Dark Energy Survey, the VST ATLAS survey, and the Large Synoptic Survey Telescope. In anticipation of a greatly expanded catalog of time-delay lenses identified with these surveys, we have produced synthetic samples to estimate how large they would have to be in order to rule out either model at a ∼99.7% confidence level. We find that if the real cosmology is ΛCDM, a sample of ∼150 time-delay lenses would be sufficient to rule out R {sub h} = ct at this level of accuracy, while ∼1000 time-delay lenses would be required to rule out ΛCDM if the real universe is instead R {sub h} = ct. This difference in required sample size reflects the greater number of free parameters available to fit the data with ΛCDM.
The HTA core model: a novel method for producing and reporting health technology assessments
DEFF Research Database (Denmark)
Lampe, Kristian; Mäkelä, Marjukka; Garrido, Marcial Velasco
2009-01-01
OBJECTIVES: The aim of this study was to develop and test a generic framework to enable international collaboration for producing and sharing results of health technology assessments (HTAs). METHODS: Ten international teams constructed the HTA Core Model, dividing information contained in a compr...
A Comparison of Cosmological Models Using Time Delay Lenses
Wei, Jun-Jie; Melia, Fulvio
2014-01-01
The use of time-delay gravitational lenses to examine the cosmological expansion introduces a new standard ruler with which to test theoretical models. The sample suitable for this kind of work now includes 12 lens systems, which have thus far been used solely for optimizing the parameters of $\\Lambda$CDM. In this paper, we broaden the base of support for this new, important cosmic probe by using these observations to carry out a one-on-one comparison between {\\it competing} models. The currently available sample indicates a likelihood of $\\sim 70-80%$ that the $R_{\\rm h}=ct$ Universe is the correct cosmology versus $\\sim 20-30%$ for the standard model. This possibly interesting result reinforces the need to greatly expand the sample of time-delay lenses, e.g., with the successful implementation of the Dark Energy Survey, the VST ATLAS survey, and the Large Synoptic Survey Telescope. In anticipation of a greatly expanded catalog of time-delay lenses identified with these surveys, we have produced synthetic sa...
Modelling the world in real time: how robots engineer information.
Davison, Andrew J
2003-12-15
Programming robots and other autonomous systems to interact with the world in real time is bringing into sharp focus general questions about representation, inference and understanding. These artificial agents use digital computation to interpret the data gleaned from sensors and produce decisions and actions to guide their future behaviour. In a physical system, however, finite computational resources unavoidably impose the need to approximate and make selective use of the information available to reach prompt deductions. Recent research has led to widespread adoption of the methodology of Bayesian inference, which provides the absolute framework to understand this process fully via modelling as informed, fully acknowledged approximation. The performance of modern systems has improved greatly on the heuristic methods of the early days of artificial intelligence. We discuss the general problem of real-time inference and computation, and draw on examples from recent research in computer vision and robotics: specifically visual tracking and simultaneous localization and mapping.
Hopf Bifurcation in a Cobweb Model with Discrete Time Delays
Directory of Open Access Journals (Sweden)
Luca Gori
2014-01-01
Full Text Available We develop a cobweb model with discrete time delays that characterise the length of production cycle. We assume a market comprised of homogeneous producers that operate as adapters by taking the (expected profit-maximising quantity as a target to adjust production and consumers with a marginal willingness to pay captured by an isoelastic demand. The dynamics of the economy is characterised by a one-dimensional delay differential equation. In this context, we show that (1 if the elasticity of market demand is sufficiently high, the steady-state equilibrium is locally asymptotically stable and (2 if the elasticity of market demand is sufficiently low, quasiperiodic oscillations emerge when the time lag (that represents the length of production cycle is high enough.
Hybrid perturbation methods based on statistical time series models
San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario
2016-04-01
In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.
Verifying Real-time Commit Protocols Using Dense-time Model Checking Technology
Al-Bataineh, Omar I; French, Tim; Woodings, Terry
2012-01-01
The timed-based automata model, introduced by Alur and Dill, provides a useful formalism for describing real-time systems. Over the last two decades, several dense-time model checking tools have been developed based on that model. The paper considers the verification of real-time distributed commit protocols using dense-time model checking technology. More precisely, we model and verify the well-known timed two phase commit protocol in three different state-of-the-art real-time model checkers: UPPAAL, Rabbit, and RED, and compare the results.
Real time model for public transportation management
Directory of Open Access Journals (Sweden)
Ireneusz Celiński
2014-03-01
Full Text Available Background: The article outlines managing a public transportation fleet in the dynamic aspect. There are currently many technical possibilities of identifying demand in the transportation network. It is also possible to indicate legitimate basis of estimating and steering demand. The article describes a general public transportation fleet management concept based on balancing demand and supply. Material and methods: The presented method utilizes a matrix description of demand for transportation based on telemetric and telecommunication data. Emphasis was placed mainly on a general concept and not the manner in which data was collected by other researchers. Results: The above model gave results in the form of a system for managing a fleet in real-time. The objective of the system is also to optimally utilize means of transportation at the disposal of service providers. Conclusions: The presented concept enables a new perspective on managing public transportation fleets. In case of implementation, the project would facilitate, among others, designing dynamic timetables, updated based on observed demand, and even designing dynamic points of access to public transportation lines. Further research should encompass so-called rerouting based on dynamic measurements of the characteristics of the transportation system.
Real-Time Massive Model Rendering
Yoon, Sung-eui; Kasik, David
2008-01-01
Interactive display and visualization of large geometric and textured models is becoming a fundamental capability. There are numerous application areas, including games, movies, CAD, virtual prototyping, and scientific visualization. One of observations about geometric models used in interactive applications is that their model complexity continues to increase because of fundamental advances in 3D modeling, simulation, and data capture technologies. As computing power increases, users take advantage of the algorithmic advances and generate even more complex models and data sets. Therefore, the
Østergaard, Nina Bjerre; Christiansen, Lasse Engbo; Dalgaard, Paw
2015-07-02
A stochastic model was developed for simultaneous growth of low numbers of Listeria monocytogenes and populations of lactic acid bacteria from the aroma producing cultures applied in cottage cheese. During more than two years, different batches of cottage cheese with aroma culture were analysed for pH, lactic acid concentration and initial concentration of lactic acid bacteria. These data and bootstrap sampling were used to represent product variability in the stochastic model. Lag time data were estimated from observed growth data (lactic acid bacteria) and from literature on L. monocytogenes single cells. These lag time data were expressed as relative lag times and included in growth models. A stochastic model was developed from an existing deterministic growth model including the effect of five environmental factors and inter-bacterial interaction [Østergaard, N.B, Eklöw, A and Dalgaard, P. 2014. Modelling the effect of lactic acid bacteria from starter- and aroma culture on growth of Listeria monocytogenes in cottage cheese. International Journal of Food Microbiology. 188, 15-25]. Growth of L. monocytogenes single cells, using lag time distributions corresponding to three different stress levels, was simulated. The simulated growth was subsequently compared to growth of low concentrations (0.4-1.0 CFU/g) of L. monocytogenes in cottage cheese, exposed to similar stresses, and in general a good agreement was observed. In addition, growth simulations were performed using population relative lag time distributions for L. monocytogenes as reported in literature. Comparably good predictions were obtained as for the simulations performed using lag time data for individual cells of L. monocytogenes. Therefore, when lag time data for individual cells are not available, it was suggested that relative lag time distributions for L. monocytogenes can be used as a qualified default assumption when simulating growth of low concentrations of L. monocytogenes.
Quantitative Modeling of Human-Environment Interactions in Preindustrial Time
Sommer, Philipp S.; Kaplan, Jed O.
2017-04-01
Quantifying human-environment interactions and anthropogenic influences on the environment prior to the Industrial revolution is essential for understanding the current state of the earth system. This is particularly true for the terrestrial biosphere, but marine ecosystems and even climate were likely modified by human activities centuries to millennia ago. Direct observations are however very sparse in space and time, especially as one considers prehistory. Numerical models are therefore essential to produce a continuous picture of human-environment interactions in the past. Agent-based approaches, while widely applied to quantifying human influence on the environment in localized studies, are unsuitable for global spatial domains and Holocene timescales because of computational demands and large parameter uncertainty. Here we outline a new paradigm for the quantitative modeling of human-environment interactions in preindustrial time that is adapted to the global Holocene. Rather than attempting to simulate agency directly, the model is informed by a suite of characteristics describing those things about society that cannot be predicted on the basis of environment, e.g., diet, presence of agriculture, or range of animals exploited. These categorical data are combined with the properties of the physical environment in coupled human-environment model. The model is, at its core, a dynamic global vegetation model with a module for simulating crop growth that is adapted for preindustrial agriculture. This allows us to simulate yield and calories for feeding both humans and their domesticated animals. We couple this basic caloric availability with a simple demographic model to calculate potential population, and, constrained by labor requirements and land limitations, we create scenarios of land use and land cover on a moderate-resolution grid. We further implement a feedback loop where anthropogenic activities lead to changes in the properties of the physical
Transverse momentum spectra of the produced hadrons at SPS energy and a random walk model
Indian Academy of Sciences (India)
Bedangadas Mohanty
2014-05-01
The transverse momentum spectra of the produced hadrons have been compared to a model, which is based on the assumption that a nucleus–nucleus collision is a superposition of isotropically decaying thermal sources at a given freeze-out temperature. The freeze-out temperature in nucleus–nucleus collisions is fixed from the inverse slope of the transverse momentum spectra of hadrons in nucleon–nucleon collision. The successive collisions in the nuclear reaction lead to gain in transverse momentum, as the nucleons propagate in the nucleus following a random walk pattern. The average transverse rapidity shift per collision is determined from the nucleon–nucleus collision data. Using this information, we obtain parameter-free result for the transverse momentum distribution of produced hadrons in nucleus–nucleus collisions. It is observed that such a model is able to explain the transverse mass spectra of the produced pions at SPS energies. However, it fails to satisfactorily explain the transverse mass spectra of kaons and protons. This indicates the presence of collective effect which cannot be accounted for, by the initial state collision broadening of transverse momentum of produced hadrons, the basis of random walk model.
UML statechart based rigorous modeling of real-time system
Institute of Scientific and Technical Information of China (English)
LAI Ming-zhi; YOU Jin-yuan
2005-01-01
Rigorous modeling could ensure correctness and could verify a reduced cost in embedded real-time system development for models. Software methods are needed for rigorous modeling of embedded real-time systems. PVS is a formal method with precise syntax and semantics defined. System modeled by PVS specification could be verified by tools. Combining the widely used UML with PVS, this paper provides a novel modeling and verification approach for embedded real-time systems. In this approach, we provide 1 ) a time-extended UML statechart for modeling dynamic behavior of an embedded real-time system; 2) an approach to capture timed automata based semantics from a timed statechart; and 3) an algorithm to generate a finite state model expressed in PVS specification for model checking. The benefits of our approach include flexibility and user friendliness in modeling, extendability in formalization and verification content, and better performance. Time constraints are modeled and verified and is a highlight of this paper.
Infinite Time Cellular Automata: A Real Computation Model
Givors, Fabien; Ollinger, Nicolas
2010-01-01
We define a new transfinite time model of computation, infinite time cellular automata. The model is shown to be as powerful than infinite time Turing machines, both on finite and infinite inputs; thus inheriting many of its properties. We then show how to simulate the canonical real computation model, BSS machines, with infinite time cellular automata in exactly \\omega steps.
Do Fractal Models of Clouds Produces the Right 3D Radiative Effects?
Varnai, Tamas; Marshak, Alexander; Einaudi, Franco (Technical Monitor)
2001-01-01
Stochastic fractal models of clouds are often used to study 3D radiative effects and their influence on the remote sensing of cloud properties. Since it is important that the cloud models produce a correct radiative response, some researchers require the model parameters to match observed cloud properties such as scale-independent optical thickness variability. Unfortunately, matching these properties does not necessarily imply that the cloud models will cause the right 3D radiative effects. First, the matched properties alone only influence the 3D effects but do not completely determine them. Second, in many cases the retrieved cloud properties have been already biased by 3D radiative effects, and so the models may not match the true real clouds. Finally, the matched cloud properties cannot be considered independent from the scales at which they have been retrieved. This paper proposes an approach that helps ensure that fractal cloud models are realistic and produce the right 3D effects. The technique compares the results of radiative transfer simulations for the model clouds to new direct observations of 3D radiative effects in satellite images.
Time series modelling of overflow structures
DEFF Research Database (Denmark)
Carstensen, J.; Harremoës, P.
1997-01-01
to the overflow structures. The capacity of a pump draining the storage pipe has been estimated for two rain events, revealing that the pump was malfunctioning during the first rain event. The grey-box modelling approach is applicable for automated on-line surveillance and control. (C) 1997 IAWQ. Published......The dynamics of a storage pipe is examined using a grey-box model based on on-line measured data. The grey-box modelling approach uses a combination of physically-based and empirical terms in the model formulation. The model provides an on-line state estimate of the overflows, pumping capacities...
Anti-Lipid IgG Antibodies Are Produced via Germinal Centers in a Murine Model Resembling Human Lupus
Wong-Baeza, Carlos; Reséndiz-Mora, Albany; Donis-Maturano, Luis; Wong-Baeza, Isabel; Zárate-Neira, Luz; Yam-Puc, Juan Carlos; Calderón-Amador, Juana; Medina, Yolanda; Wong, Carlos; Baeza, Isabel; Flores-Romo, Leopoldo
2016-01-01
Anti-lipid IgG antibodies are produced in some mycobacterial infections and in certain autoimmune diseases [such as anti-phospholipid syndrome, systemic lupus erythematosus (SLE)]. However, few studies have addressed the B cell responses underlying the production of these immunoglobulins. Anti-lipid IgG antibodies are consistently found in a murine model resembling human lupus induced by chlorpromazine-stabilized non-bilayer phospholipid arrangements (NPA). NPA are transitory lipid associations found in the membranes of most cells; when NPA are stabilized they can become immunogenic and induce specific IgG antibodies, which appear to be involved in the development of the mouse model of lupus. Of note, anti-NPA antibodies are also detected in patients with SLE and leprosy. We used this model of lupus to investigate in vivo the cellular mechanisms that lead to the production of anti-lipid, class-switched IgG antibodies. In this murine lupus model, we found plasma cells (Gr1−, CD19−, CD138+) producing NPA-specific IgGs in the draining lymph nodes, the spleen, and the bone marrow. We also found a significant number of germinal center B cells (IgD−, CD19+, PNA+) specific for NPA in the draining lymph nodes and the spleen, and we identified in situ the presence of NPA in these germinal centers. By contrast, very few NPA-specific, extrafollicular reaction B cells (B220+, Blimp1+) were found. Moreover, when assessing the anti-NPA IgG antibodies produced during the experimental protocol, we found that the affinity of these antibodies progressively increased over time. Altogether, our data indicate that, in this murine model resembling human lupus, B cells produce anti-NPA IgG antibodies mainly via germinal centers. PMID:27746783
Trecarichi, Enrico Maria; Tumietto, Fabio; Del Bono, Valerio; De Rosa, Francesco Giuseppe; Bassetti, Matteo; Losito, Angela Raffaella; Tedeschi, Sara; Saffioti, Carolina; Corcione, Silvia; Giannella, Maddalena; Raffaelli, Francesca; Pagani, Nicole; Bartoletti, Michele; Spanu, Teresa; Marchese, Anna; Cauda, Roberto; Viscoli, Claudio; Viale, Pierluigi
2014-01-01
The production of Klebsiella pneumoniae carbapenemases (KPCs) by Enterobacteriaceae has become a significant problem in recent years. To identify factors that could predict isolation of KPC-producing K. pneumoniae (KPCKP) in clinical samples from hospitalized patients, we conducted a retrospective, matched (1:2) case-control study in five large Italian hospitals. The case cohort consisted of adult inpatients whose hospital stay included at least one documented isolation of a KPCKP strain from a clinical specimen. For each case enrolled, we randomly selected two matched controls with no KPCKP-positive cultures of any type during their hospitalization. Matching involved hospital, ward, and month/year of admission, as well as time at risk for KPCKP isolation. A subgroup analysis was also carried out to identify risk factors specifically associated with true KPCKP infection. During the study period, KPCKP was isolated from clinical samples of 657 patients; 426 of these cases appeared to be true infections. Independent predictors of KPCKP isolation were recent admission to an intensive care unit (ICU), indwelling urinary catheter, central venous catheter (CVC), and/or surgical drain, ≥2 recent hospitalizations, hematological cancer, and recent fluoroquinolone and/or carbapenem therapy. A Charlson index of ≥3, indwelling CVC, recent surgery, neutropenia, ≥2 recent hospitalizations, and recent fluoroquinolone and/or carbapenem therapy were independent risk factors for KPCKP infection. Models developed to predict KPCKP isolation and KPCKP infection displayed good predictive power, with the areas under the receiver-operating characteristic curves of 0.82 (95% confidence interval [CI], 0.80 to 0.84) and 0.82 (95% CI, 0.80 to 0.85), respectively. This study provides novel information which might be useful for the clinical management of patients harboring KPCKP and for controlling the spread of this organism. PMID:24733460
Favre, Mario; Wyndham, Edmund; Veloso, Felipe; Bhuyan, Heman; Reyes, Sebastian; Ruiz, Hugo Marcelo; Caballero-Bendixsen, Luis Sebastian
2016-10-01
We present further detailed studies of the dynamics and plasma properties of a laser produced Carbon plasma expanding in a static axial magnetic field. The laser plasmas are produced in vacuum, 1 .10-6 Torr, using a graphite target, with a Nd:YAG laser, 3.5 ns, 340 mJ at 1.06 μm, focused at 2 .109 W/cm2, and propagate in static magnetic fields of maximum value 0.2 T. 15 ns time and spaced resolved OES is used to investigate plasma composition. 50 ns time resolved plasma imaging is used to visualize the plasma dynamics. A mm size B-dot probe is used, in combination with a Faraday cup, to characterize the interaction between the expanding plasma and the magnetic field. As a result of time and space correlated measurements, unique features of the laser plasma dynamics in the presence of the magnetic field are identified, which highlight the confinement effects of the static magnetic field Funded by project FONDECYT 1141119.
Time of relaxation in dusty plasma model
Timofeev, A. V.
2015-11-01
Dust particles in plasma may have different values of average kinetic energy for vertical and horizontal motion. The partial equilibrium of the subsystems and the relaxation processes leading to this asymmetry are under consideration. A method for the relaxation time estimation in nonideal dusty plasma is suggested. The characteristic relaxation times of vertical and horizontal motion of dust particles in gas discharge are estimated by analytical approach and by analysis of simulation results. These relaxation times for vertical and horizontal subsystems appear to be different. A single hierarchy of relaxation times is proposed.
Forecasting the Reference Evapotranspiration Using Time Series Model
Directory of Open Access Journals (Sweden)
H. Zare Abyaneh
2016-10-01
evapotranspiration were obtained. The mean values of evapotranspiration in the study period were 4.42, 3.93, 5.05, 5.49, and 5.60 mm day−1 in Esfahan, Semnan, Shiraz, Kerman, and Yazd, respectively. The Augmented Dickey-Fuller (ADF test was performed to the time series. The results showed that in all stations except Shiraz, time series had unit root and were non-stationary. The non-stationary time series became stationary at 1st difference. Using the EViews 7 software, the seasonal ARIMA models were applied to the evapotranspiration time series and R2 coefficient of determination, Durbin–Watson statistic (DW, Hannan-Quinn (HQ, Schwarz (SC and Akaike information criteria (AIC were used to determine, the best models for the stations were selected. The selected models were listed in Table 2. Moreover, information criteria (AIC, SC, and HQ were used to assess model parsimony. The independence assumption of the model residuals was confirmed by a sensitive diagnostic check. Furthermore, the homoscedasticity and normality assumptions were tested using other diagnostics tests. Table 2- The selected time series models for the stations Station\tSeasonal ARIMA model\tInformation criteria\tR2\tDW SC\tHQ\tAIC Esfahan\tARIMA(1, 1, 1×(1, 0, 112\t1.2571\t1.2840\t1.2396\t0.8800\t1.9987 Semnan\tARIMA(5, 1, 2×(1, 0, 112\t1.5665\t1.5122\t1.4770\t0.8543\t1.9911 Shiraz\tARIMA(2, 0, 3×(1, 0, 112\t1.3312\t1.2881\t1.2601\t0.9665\t1.9873 Kerman\tARIMA(5, 1, 1×(1, 0, 112\t1.8097\t1.7608\t1.8097\t0.8557\t2.0042 Yazd\tARIMA(2, 1, 3×(1, 1, 112\t1.7472\t1.7032\t1.6746\t0.5264\t1.9943 The seasonal ARIMA models presented in Table 2, were used at the 12 months (2004-2005 forecasting horizon. The results showed that the models produce good out-of-sample forecasts, which in all the stations the lowest correlation coefficient and the highest root mean square error were obtained 0.988 and 0.515 mm day−1, respectively. Conclusion: In the presented paper, reference evapotranspiration in the five synoptic
Mouse model of sustained elevation in intraocular pressure produced by episcleral vein occlusion.
Ruiz-Ederra, Javier; Verkman, A S
2006-05-01
We have developed an inducible mouse model of glaucoma based on episcleral vein cauterization (EVC). Intraocular pressure (IOP) elevation in adult mice was produced by cauterizing three episcleral veins. Serial IOP measurements were done by induction-impact tonometry. IOP was significantly elevated by 104+/-20% in 20 out of 23 mice (87%) within the first day after EVC, and remained elevated for 4 weeks, with mean IOP 94% higher in EVC-treated vs. contralateral control eyes. Aqueous outflow blockade was verified from the IOP response to pulsed fluid infusions into the anterior chamber. Retinal ganglion cell (RGC) loss, determined by retrograde labelling using Fluoro-Gold applied to the superior colliculous, was approximately 20% at 2 weeks after EVC. We conclude that episcleral vein occlusion in mice produces significant and sustained elevation in IOP associated with increased outflow resistance and RGC loss, and thus may be useful to model glaucoma in genetically modified and drug-treated mice.
Hierarchical Bayes Models for Response Time Data
Craigmile, Peter F.; Peruggia, Mario; Van Zandt, Trisha
2010-01-01
Human response time (RT) data are widely used in experimental psychology to evaluate theories of mental processing. Typically, the data constitute the times taken by a subject to react to a succession of stimuli under varying experimental conditions. Because of the sequential nature of the experiments there are trends (due to learning, fatigue,…
Modeling and prediction of surgical procedure times
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
A new timing model for calculating the intrinsic timing resolution of a scintillator detector.
Shao, Yiping
2007-02-21
The coincidence timing resolution is a critical parameter which to a large extent determines the system performance of positron emission tomography (PET). This is particularly true for time-of-flight (TOF) PET that requires an excellent coincidence timing resolution (scintillator detector: scintillation decay time and total photoelectron yield from the photon-electron conversion. However, this calculation has led to significant errors when the coincidence timing resolution reaches 1 ns or less. In this paper, a bi-exponential timing model is derived and evaluated. The new timing model includes an additional parameter of a scintillator detector: scintillation rise time. The effect of rise time on the timing resolution has been investigated analytically, and the results reveal that the rise time can significantly change the timing resolution of fast scintillators that have short decay time constants. Compared with measured data, the calculations have shown that the new timing model significantly improves the accuracy in the calculation of timing resolutions.
Yu, Chunxue; Yin, Xin'an; Yang, Zhifeng; Cai, Yanpeng; Sun, Tao
2016-09-01
The time step used in the operation of eco-friendly reservoirs has decreased from monthly to daily, and even sub-daily. The shorter time step is considered a better choice for satisfying downstream environmental requirements because it more closely resembles the natural flow regime. However, little consideration has been given to the influence of different time steps on the ability to simultaneously meet human and environmental flow requirements. To analyze this influence, we used an optimization model to explore the relationships among the time step, environmental flow (e-flow) requirements, and human water needs for a wide range of time steps and e-flow scenarios. We used the degree of hydrologic alteration to evaluate the regime's ability to satisfy the e-flow requirements of riverine ecosystems, and used water supply reliability to evaluate the ability to satisfy human needs. We then applied the model to a case study of China's Tanghe Reservoir. We found four efficient time steps (2, 3, 4, and 5 days), with a remarkably high water supply reliability (around 80%) and a low alteration of the flow regime (human needs under several e-flow scenarios. Our results show that adjusting the time step is a simple way to improve reservoir operation performance to balance human and e-flow needs.
Continuous Time Structural Equation Modeling with R Package ctsem
Directory of Open Access Journals (Sweden)
Charles C. Driver
2017-04-01
Full Text Available We introduce ctsem, an R package for continuous time structural equation modeling of panel (N > 1 and time series (N = 1 data, using full information maximum likelihood. Most dynamic models (e.g., cross-lagged panel models in the social and behavioural sciences are discrete time models. An assumption of discrete time models is that time intervals between measurements are equal, and that all subjects were assessed at the same intervals. Violations of this assumption are often ignored due to the difficulty of accounting for varying time intervals, therefore parameter estimates can be biased and the time course of effects becomes ambiguous. By using stochastic differential equations to estimate an underlying continuous process, continuous time models allow for any pattern of measurement occasions. By interfacing to OpenMx, ctsem combines the flexible specification of structural equation models with the enhanced data gathering opportunities and improved estimation of continuous time models. ctsem can estimate relationships over time for multiple latent processes, measured by multiple noisy indicators with varying time intervals between observations. Within and between effects are estimated simultaneously by modeling both observed covariates and unobserved heterogeneity. Exogenous shocks with different shapes, group differences, higher order diffusion effects and oscillating processes can all be simply modeled. We first introduce and define continuous time models, then show how to specify and estimate a range of continuous time models using ctsem.
Integrated use of NMR, petrel and modflow in the modeling of SAGD produced water re-injection
Energy Technology Data Exchange (ETDEWEB)
Campbell, K. [Miswaco(CANADA); Phair, C [Mneme Corp, CALGARY (Canada); Alloisio, S [SWS, Vancouver (CANADA); Novotny, M [SWS, Denver, (United States); Raven, S [Oilsands Quest Inc., Calgary (CANADA)
2011-07-01
In the oil industry, steam assisted gravity drainage (SAGD) is a method used to enhance oil recovery in which production water disposal is a challenge. During this process, production water is re-injected into the reservoir and operators have to verify that it will not affect the quality of the surrounding fresh groundwater. This research aimed at determining the flow path and the time that produced water would take to reach an adjacent aquifer. This study was carried out on a horizontal well pair at the Axe Lake Area in northwestern Saskatchewan, using existing site data in Petrel to create a static hydrogeological model which was then exported to Modflow to simulate injection scenarios. This innovative method provided flow path of the re-injected water and time to reach the fresh with advantages over conventional hydrogeological modeling. The innovative workflow presented herein successfully provided useful information to assess the feasibility of the SAGD project and could be used for other projects.
Forecasting electricity usage using univariate time series models
Hock-Eam, Lim; Chee-Yin, Yip
2014-12-01
Electricity is one of the important energy sources. A sufficient supply of electricity is vital to support a country's development and growth. Due to the changing of socio-economic characteristics, increasing competition and deregulation of electricity supply industry, the electricity demand forecasting is even more important than before. It is imperative to evaluate and compare the predictive performance of various forecasting methods. This will provide further insights on the weakness and strengths of each method. In literature, there are mixed evidences on the best forecasting methods of electricity demand. This paper aims to compare the predictive performance of univariate time series models for forecasting the electricity demand using a monthly data of maximum electricity load in Malaysia from January 2003 to December 2013. Results reveal that the Box-Jenkins method produces the best out-of-sample predictive performance. On the other hand, Holt-Winters exponential smoothing method is a good forecasting method for in-sample predictive performance.
Evaluation of Fast-Time Wake Vortex Prediction Models
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.
Time-dependent H-like and He-like Al lines produced by ultra-short pulse laser
Energy Technology Data Exchange (ETDEWEB)
Kato, Takako; Kato, Masatoshi [National Inst. for Fusion Science, Nagoya (Japan); Shepherd, R.; Young, B.; More, R.; Osterheld, Al
1998-03-01
We have performed numerical modeling of time-resolved x-ray spectra from thin foil targets heated by the LLNL Ultra-short pulse (USP) laser. The targets were aluminum foils of thickness ranging from 250 A to 1250 A, heated with 120 fsec pulses of 400 nm light from the USP laser. The laser energy was approximately 0.2 Joules, focused to a 3 micron spot size for a peak intensity near 2 x 10{sup 19} W/cm{sup 2}. Ly{alpha} and He{alpha} lines were recorded using a 900 fsec x-ray streak camera. We calculate the effective ionization, recombination and emission rate coefficients including density effects for H-like and He-like aluminum ions using a collisional radiative model. We calculate time-dependent ion abundances using these effective ionization and recombination rate coefficients. The time-dependent electron temperature and density used in the calculation are based on an analytical model for the hydrodynamic expansion of the target foils. During the laser pulse the target is ionized. After the laser heating stops, the plasma begins to recombine. Using the calculated time dependent ion abundances and the effective emission rate coefficients, we calculate the time dependent Ly{alpha} and He{alpha} lines. The calculations reproduce the main qualitative features of the experimental spectra. (author)
The XH-map algorithm: A method to process stereo video to produce a real-time obstacle map
Rosselot, Donald; Hall, Ernest L.
2005-10-01
This paper presents a novel, simple and fast algorithm to produce a "floor plan" obstacle map in real time using video. The XH-map algorithm is a transformation of stereo vision data in disparity map space into a two dimensional obstacle map space using a method that can be likened to a histogram reduction of image information. The classic floor-ground background noise problem is addressed with a simple one-time semi-automatic calibration method incorporated into the algorithm. This implementation of this algorithm utilizes the Intel Performance Primitives library and OpenCV libraries for extremely fast and efficient execution, creating a scaled obstacle map from a 480x640x256 stereo pair in 1.4 milliseconds. This algorithm has many applications in robotics and computer vision including enabling an "Intelligent Robot" robot to "see" for path planning and obstacle avoidance.
Velocity Structure Determination Through Seismic Waveform Modeling and Time Deviations
Savage, B.; Zhu, L.; Tan, Y.; Helmberger, D. V.
2001-12-01
Through the use of seismic waveforms recorded by TriNet, a dataset of earthquake focal mechanisms and deviations (time shifts) relative to a standard model facilitates the investigation of the crust and uppermost mantle of southern California. The CAP method of focal mechanism determination, in use by TriNet on a routine basis, provides time shifts for surface waves and Pnl arrivals independently relative to the reference model. These shifts serve as initial data for calibration of local and regional seismic paths. Time shifts from the CAP method are derived by splitting the Pnl section of the waveform, the first arriving Pn to just before the arrival of the S wave, from the much slower surface waves then cross-correlating the data with synthetic waveforms computed from a standard model. Surface waves interact with the entire crust, but the upper crust causes the greatest effect. Whereas, Pnl arrivals sample the deeper crust, upper mantle, and source region. This natural division separates the upper from lower crust for regional calibration and structural modeling and allows 3-D velocity maps to be created using the resulting time shifts. Further examination of Pnl and other arrivals which interact with the Moho illuminate the complex nature of this boundary. Initial attempts at using the first 10 seconds of the Pnl section to determine upper most mantle structure have proven insightful. Two large earthquakes north of southern California in Nevada and Mammoth Lakes, CA allow the creation of record sections from 200 to 600 km. As the paths swing from east to west across southern California, simple 1-D models turn into complex structure, dramatically changing the waveform character. Using finite difference models to explain the structure, we determine that a low velocity zone is present at the base of the crust and extends to 100 km in depth. Velocity variations of 5 percent of the mantle in combination with steeply sloping edges produces complex waveform variations
Auffret, Marc; Pilote, Alexandre; Proulx, Emilie; Proulx, Daniel; Vandenberg, Grant; Villemur, Richard
2011-12-15
Geosmin and 2-methylisoborneol (MIB) have been associated with off-flavour problems in fish and seafood products, generating a strong negative impact for aquaculture industries. Although most of the producers of geosmin and MIB have been identified as Streptomyces species or cyanobacteria, Streptomyces spp. are thought to be responsible for the synthesis of these compounds in indoor recirculating aquaculture systems (RAS). The detection of genes involved in the synthesis of geosmin and MIB can be a relevant indicator of the beginning of off-flavour events in RAS. Here, we report a real-time polymerase chain reaction (qPCR) protocol targeting geoA sequences that encode a germacradienol synthase involved in geosmin synthesis. New geoA-related sequences were retrieved from eleven geosmin-producing Actinomycete strains, among them two Streptomyces strains isolated from two RAS. Combined with geoA-related sequences available in gene databases, we designed primers and standards suitable for qPCR assays targeting mainly Streptomyces geoA. Using our qPCR protocol, we succeeded in measuring the level of geoA copies in sand filter and biofilters in two RAS. This study is the first to apply qPCR assays to detect and quantify the geosmin synthesis gene (geoA) in RAS. Quantification of geoA in RAS could permit the monitoring of the level of geosmin producers prior to the occurrence of geosmin production. This information will be most valuable for fish producers to manage further development of off-flavour events.
Adaptive Modeling and Real-Time Simulation
1984-01-01
34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in
Genetic programming-based chaotic time series modeling
Institute of Scientific and Technical Information of China (English)
张伟; 吴智铭; 杨根科
2004-01-01
This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.
Structure-selection techniques applied to continuous-time nonlinear models
Aguirre, Luis A.; Freitas, Ubiratan S.; Letellier, Christophe; Maquet, Jean
2001-10-01
This paper addresses the problem of choosing the multinomials that should compose a polynomial mathematical model starting from data. The mathematical representation used is a nonlinear differential equation of the polynomial type. Some approaches that have been used in the context of discrete-time models are adapted and applied to continuous-time models. Two examples are included to illustrate the main ideas. Models obtained with and without structure selection are compared using topological analysis. The main differences between structure-selected models and complete structure models are: (i) the former are more parsimonious than the latter, (ii) a predefined fixed-point configuration can be guaranteed for the former, and (iii) the former set of models produce attractors that are topologically closer to the original attractor than those produced by the complete structure models.
Aaltonen, T; Álvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Bae, T; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bedeschi, F; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Bisello, D; Bizjak, I; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Bromberg, C; Brucken, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Calamba, A; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chung, W H; Chung, Y S; Ciocci, M A; Clark, A; Clarke, C; Compostella, G; Connors, J; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuevas, J; Culbertson, R; Dagenhart, D; d'Ascenzo, N; Datta, M; de Barbaro, P; Dell'Orso, M; Demortier, L; Deninno, M; Devoto, F; d'Errico, M; Di Canto, A; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, M; Dorigo, T; Ebina, K; Elagin, A; Eppig, A; Erbacher, R; Errede, S; Ershaidat, N; Eusebi, R; Farrington, S; Feindt, M; Fernandez, J P; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Funakoshi, Y; Furic, I; Gallinaro, M; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Grinstein, S; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Hahn, S R; Halkiadakis, E; Hamaguchi, A; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Hewamanage, S; Hocker, A; Hopkins, W; Horn, D; Hou, S; Hughes, R E; Hurwitz, M; Husemann, U; Hussain, N; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kim, Y J; Kimura, N; Kirby, M; Klimenko, S; Knoepfel, K; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Kruse, M; Krutelyov, V; Kuhr, T; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lecompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lin, C-J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, H; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maeshima, K; Maestro, P; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Martínez, M; Mastrandrea, P; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Noh, S Y; Norniella, O; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Paramonov, A A; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Prokoshin, F; Pranko, A; Ptohos, F; Punzi, G; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Rescigno, M; Riddick, T; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Safonov, A; Sakumoto, W K; Sakurai, Y; Santi, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shochet, M; Shreyber-Tecker, I; Simonenko, A; Sinervo, P; Sliwa, K; Smith, J R; Snider, F D; Soha, A; Sorin, V; Song, H; Squillacioti, P; Stancari, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Ukegawa, F; Uozumi, S; Varganov, A; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wagner, R L; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Wester, W C; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Wick, F; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamato, D; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zhou, C; Zucchelli, S
2012-11-02
A search is presented for the standard model Higgs boson produced in association with top quarks using the full Run II proton-antiproton collision data set, corresponding to 9.45 fb(-1), collected by the Collider Detector at Fermilab. No significant excess over the expected background is observed, and 95% credibility-level upper bounds are placed on the cross section σ(ttH → lepton + missing transverse energy+jets). For a Higgs boson mass of 125 GeV/c(2), we expect to set a limit of 12.6 and observe a limit of 20.5 times the standard model rate. This represents the most sensitive search for a standard model Higgs boson in this channel to date.
Aaltonen, T.
2012-01-01
A search is presented for the standard model Higgs boson produced in association with top quarks using the full Run II proton-antiproton collision data set, corresponding to 9.45 inverse fb, collected by the Collider Detector at Fermilab. No significant excess over the expected background is observed, and 95% credibility-level upper bounds are placed on the cross section sigma(t\\bar{t}H --> lepton + missing transverse energy + jets). For a Higgs boson mass of 125 GeV, we expect to set a limit of 12.6, and observe a limit of 20.5 times the standard model rate. This represents the most sensitive search for a standard model Higgs boson in this channel to date.
DEFF Research Database (Denmark)
Kennedy, C.; Anderson, J.; Snyder, N.;
2010-01-01
residues based on limited data sets affords business value by enabling informed product development decisions about the likelihood for MRL compliance for varied product use scenarios. Predicted residues can additionally support the design and conduct of time-constrained interdependent studies required......Crop Protection Product (CPP) national registrations and/or international trade require magnitude and decline of residue data for treated produce. These data are used to assess human dietary risk and establish legal limits (Maximum Residue Limits, MRLs) for traded produce. The ability to predict...... for product registrations. While advances in predicting residues for the case of foliar applications of CPPs have been achieved, predictions for the case of soil applications of CPPs provide additional challenge. The adaptation of a newly developed dynamic model to CPP product use scenarios will be explored...
Stochastic Time Models of Syllable Structure
Shaw, Jason A.; Gafos, Adamantios I.
2015-01-01
Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography and X-ray microbeam methods. The essential variable in the models is syllable structure. When mapped to discrete coordination topologies, syllabic organization imposes systematic patterns of variability on the temporal dynamics of speech articulation. We simulated these dynamics under different syllabic parses and evaluated simulations against experimental data from Arabic and English, two languages claimed to parse similar strings of segments into different syllabic structures. Model simulations replicated several key experimental results, including the fallibility of past phonetic heuristics for syllable structure, and exposed the range of conditions under which such heuristics remain valid. More importantly, the modelling approach consistently diagnosed syllable structure proving resilient to multiple sources of variability in experimental data including measurement variability, speaker variability, and contextual variability. Prospects for extensions of our modelling paradigm to acoustic data are also discussed. PMID:25996153
A novel IL-10-producing innate lymphoid cells (ILC10) in a contact hypersensitivity mouse model
Kim, Hyuk Soon; Jang, Jong-Hwa; Lee, Min Bum; Jung, In Duk; Park, Yeong-Min; Kim, Young Mi; Choi, Wahn Soo
2016-01-01
The immunoregulatory cytokine Interleukin 10 (IL-10) protein is produced by various cells during the course of inflammatory disorders. Mainly, it downregulates pro-inflammatory cytokines, antigen presentation, and helper T cell activation. In this study, we show that the ratio of IL-10-producing cells was significantly increased in lineage negative (i.e., not T, B, or leukocyte cell lineages) cells than in lineage positive cells in lymphoid and peripheral tissues. We further observed that IL-10-producing innate lymphoid cells (ILCs), here called firstly ILC10, were increased in number in oxazolone-induced contact hypersensitivity (CHS) mice. In detail, IL-10-producing lineage negative cells were elevated in the axillary, inguinal lymph node, and ear tissues of CHS mice. Notably, the cells expressed classical ILC marker proteins such as CD45, CD127, and Sca-1. Altogether, our findings suggest for the first time that ILC10s are present in various physiological settings and could be involved in numerous immune responses as regulatory cells. [BMB Reports 2016; 49(5): 293-296] PMID:26949018
RELAXATION TIME LIMITS PROBLEM FOR HYDRODYNAMIC MODELS IN SEMICONDUCTOR SCIENCE
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In this article, two relaxation time limits, namely, the momentum relaxation time limit and the energy relaxation time limit are considered. By the compactness argument, it is obtained that the smooth solutions of the multidimensional nonisentropic Euler-Poisson problem converge to the solutions of an energy transport model or a drift diffusion model, respectively, with respect to different time scales.
Energy Technology Data Exchange (ETDEWEB)
Tastu, J.; Pinson, P.; Madsen, Henrik
2013-09-01
The emphasis in this work is placed on generating space-time trajectories (also referred to as scenarios) of wind power generation. This calls for prediction of multivariate densities describing wind power generation at a number of distributed locations and for a number of successive lead times. A modelling approach taking advantage of sparsity of precision matrices is introduced for the description of the underlying space-time dependence structure. The proposed parametrization of the dependence structure accounts for such important process characteristics as non-constant conditional precisions and direction-dependent cross-correlations. Accounting for the space-time effects is shown to be crucial for generating high quality scenarios. (Author)
Modeling and computation of mean field equilibria in producers' game with emission permits trading
Zhang, Shuhua; Wang, Xinyu; Shanain, Aleksandr
2016-08-01
In this paper, we present a mean field game to model the production behaviors of a very large number of producers, whose carbon emissions are regulated by government. Especially, an emission permits trading scheme is considered in our model, in which each enterprise can trade its own permits flexibly. By means of the mean field equilibrium, we obtain a Hamilton-Jacobi-Bellman (HJB) equation coupled with a Kolmogorov equation, which are satisfied by the adjoint state and the density of producers (agents), respectively. Then, we propose a so-called fitted finite volume method to solve the HJB equation and the Kolmogorov equation. The efficiency and the usefulness of this method are illustrated by the numerical experiments. Under different conditions, the equilibrium states as well as the effects of the emission permits price are examined, which demonstrates that the emission permits trading scheme influences the producers' behaviors, that is, more populations would like to choose a lower rather than a higher emission level when the emission permits are expensive.
Mathematical Modeling of Surface Roughness of Castings Produced Using ZCast Direct Metal Casting
Chhabra, M.; Singh, R.
2015-04-01
Aim of this investigation is to develop a mathematical model for predicting surface roughness of castings produced using ZCast process by employing Buckingham's π-theorem. A relationship has been proposed between surface roughness of castings and shell wall thickness of the shell moulds fabricated using 3D printer. Based on model, experiments were performed to obtain the surface roughness of aluminium, brass and copper castings produced using ZCast process based on 3D printing technique. Based on experimental data, three best fitted third-degree polynomial equations have been established for predicting the surface roughness of castings. The predicted surface roughness values were then calculated using established best fitted equations. An error analysis was performed to compare the experimental and predicted data. The average prediction errors obtained for aluminium, brass and copper castings are 10.6, 2.43 and 3.12 % respectively. The obtained average surface roughness (experimental and predicted) values of castings produced are acceptable with the sand cast surface roughness values range (6.25-25 µm).
Role of thyrotropin-releasing hormone in prolactin-producing cell models.
Kanasaki, Haruhiko; Oride, Aki; Mijiddorj, Tselmeg; Kyo, Satoru
2015-12-01
Thyrotropin-releasing hormone (TRH) is a hypothalamic hypophysiotropic neuropeptide that was named for its ability to stimulate the release of thyroid-stimulating hormone in mammals. It later became apparent that it exerts a number of species-dependent hypophysiotropic activities that regulate other pituitary hormones. TRH also regulates the synthesis and release of prolactin, although whether it is a physiological regulator of prolactin that remains unclear. Occupation of the Gq protein-coupled TRH receptor in the prolactin-producing lactotroph increases the turnover of inositol, which in turn activates the protein kinase C pathway and the release of Ca(2+) from storage sites. TRH-induced signaling events also include the activation of extracellular signal-regulated kinase (ERK) and induction of MAP kinase phosphatase, an inactivator of activated ERK. TRH stimulates prolactin synthesis through the activation of ERK, whereas prolactin release occurs via elevation of intracellular Ca(2+). We have been investigating the role of TRH in a pituitary prolactin-producing cell model. Rat pituitary somatolactotroph GH3 cells, which produce and release both prolactin and growth hormone (GH), are widely used as a model for the study of prolactin- and GH-secreting cells. In this review, we describe the general action of TRH as a hypophysiotropic factor in vertebrates and focus on the role of TRH in prolactin synthesis using GH3 cells.
Time-Dependent Networks as Models to Achieve Fast Exact Time-Table Queries
DEFF Research Database (Denmark)
Brodal, Gert Stølting; Jacob, Rico
2003-01-01
We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries for travelers using a train system. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models.......We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries for travelers using a train system. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models....
Time-dependent Networks as Models to Achieve Fast Exact Time-table Queries
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Jacob, Rico
2001-01-01
We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models.......We consider efficient algorithms for exact time-table queries, i.e. algorithms that find optimal itineraries. We propose to use time-dependent networks as a model and show advantages of this approach over space-time networks as models....
An Efficient Explicit-time Description Method for Timed Model Checking
Wang, Hao; 10.4204/EPTCS.14.6
2009-01-01
Timed model checking, the method to formally verify real-time systems, is attracting increasing attention from both the model checking community and the real-time community. Explicit-time description methods verify real-time systems using general model constructs found in standard un-timed model checkers. Lamport proposed an explicit-time description method using a clock-ticking process (Tick) to simulate the passage of time together with a group of global variables to model time requirements. Two methods, the Sync-based Explicit-time Description Method using rendezvous synchronization steps and the Semaphore-based Explicit-time Description Method using only one global variable were proposed; they both achieve better modularity than Lamport's method in modeling the real-time systems. In contrast to timed automata based model checkers like UPPAAL, explicit-time description methods can access and store the current time instant for future calculations necessary for many real-time systems, especially those with p...
Modeling Time Series Data for Supervised Learning
Baydogan, Mustafa Gokce
2012-01-01
Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…
Modelling biological pathway dynamics with Timed Automata
Schivo, Stefano; Scholma, Jetse; Wanders, B.; Urquidi Camacho, R.A.; van der Vet, P.E.; Karperien, Hermanus Bernardus Johannes; Langerak, Romanus; van de Pol, Jan Cornelis; Post, Janine Nicole
2012-01-01
When analysing complex interaction networks occurring in biological cells, a biologist needs computational support in order to understand the effects of signalling molecules (e.g. growth factors, drugs). ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that allows the user to create
Structural Equation Modeling of Multivariate Time Series
du Toit, Stephen H. C.; Browne, Michael W.
2007-01-01
The covariance structure of a vector autoregressive process with moving average residuals (VARMA) is derived. It differs from other available expressions for the covariance function of a stationary VARMA process and is compatible with current structural equation methodology. Structural equation modeling programs, such as LISREL, may therefore be…
Modelling the Timing and Location of Shallow Landslides and Debris Flows Using the SHETRAN Model
Bovolo, C. I.; Bathurst, J. C.
2006-12-01
Research on landslide incidence has tended to focus on threshold relationships and has only recently started to look into predicting the location, timing and magnitude of landslide events as a function of climate and geomorphology. In addition, only a few studies consider the post landslide effects of erosion or downstream sediment transport in rivers and most models are limited to areas of a few square kilometres or less. The SHETRAN landslide model is a physically based system which can predictively examine shallow landslide and debris flow incidence on a spatially distributed basis, at the scale of a catchment (New Zealand. A high intensity, single peak rainfall event produced similar number of landslides as a constant low intensity rainfall event of the same duration. Where rainfall increased to a peak at the end of the event, fewer landslides were produced, whilst the least number of landslides were produced where rainfall decreased from a peak at the start of the event. In general, landslides occur at the peak of the rainfall event or at the time of maximum soil saturation but vary according to rainfall distribution and magnitude patterns. Graphs of the number of landslides as a function of rainfall event intensity and duration are given as a series of curves which can be compared with existing thresholds and show the severity of the event in terms of the number of landslides for a given rainfall condition.
Evaluation and modelling of integral capacitors produced by interdigitated comb electrodes
Directory of Open Access Journals (Sweden)
Leandro Alfredo Ramajo
2008-12-01
Full Text Available Integral capacitors (IC of one or two-layer printed wiring board (PWB circuits were produced using comb electrodes fixtures and dielectric composites as the inter-electrode material. ICs were fabricated at laboratory scale, using copper comb electrodes and BaTiO3-epoxy composite materials deposited on a glass-Epoxy FR4 board. They were experimentally tested in order to obtain their electrical response. Furthermore, ICs behaviour was modelled through 2-dimensional models applying finite element method (FEM. Results showed that by this laboratory technique it was possible to obtained integral capacitors with low dielectric losses. Moreover, acceptable agreement was found between numerical and experimental capacitance results for all the different analysed ICs. In conclusion, 2D FEM models are a suitable tool to predict electric response of IC devices.
Modeling of wear behavior of Al/B{sub 4}C composites produced by powder metallurgy
Energy Technology Data Exchange (ETDEWEB)
Sahin, Ismail; Bektas, Asli [Gazi Univ., Ankara (Turkey). Dept. of Industrial Design Engineering; Guel, Ferhat; Cinci, Hanifi [Gazi Univ., Ankara (Turkey). Dept. of Materials and Metallurgy Engineering
2017-06-01
Wear characteristics of composites, Al matrix reinforced with B{sub 4}C particles percentages of 5, 10,15 and 20 produced by the powder metallurgy method were studied in this study. For this purpose, a mixture of Al and B{sub 4}C powders were pressed under 650 MPa pressure and then sintered at 635 C. The analysis of hardness, density and microstructure was performed. The produced samples were worn using a pin-on-disk abrasion device under 10, 20 and 30 N load through 500, 800 and 1200 mesh SiC abrasive papers. The obtained wear values were implemented in an artificial neural network (ANN) model having three inputs and one output using feed forward backpropagation Levenberg-Marquardt algorithm. Thus, the optimum wear conditions and hardness values were determined.
Time invariant scaling in discrete fragmentation models
Giraud, B G; Giraud, B G; Peschanski, R
1994-01-01
Linear rate equations are used to describe the cascading decay of an initial heavy cluster into fragments. We consider moments of arbitrary orders of the mass multiplicity spectrum and derive scaling properties pertaining to their time evolution. We suggest that the mass weighted multiplicity is a suitable observable for the discovery of scaling. Numerical tests validate such properties, even for moderate values of the initial mass (nuclei, percolation clusters, jets of particles etc.). Finite size effects can be simply parametrized.
Systematic comparison of the behaviors produced by computational models of epileptic neocortex.
Energy Technology Data Exchange (ETDEWEB)
Warlaumont, A. S.; Lee, H. C.; Benayoun, M.; Stevens, R. L.; Hereld, M. (CLS-CI); ( MCS); (Univ. of Chicago); (Univ. of Memphis)
2010-12-01
Two existing models of brain dynamics in epilepsy, one detailed (i.e., realistic) and one abstract (i.e., simplified) are compared in terms of behavioral range and match to in vitro mouse recordings. A new method is introduced for comparing across computational models that may have very different forms. First, high-level metrics were extracted from model and in vitro output time series. A principal components analysis was then performed over these metrics to obtain a reduced set of derived features. These features define a low-dimensional behavior space in which quantitative measures of behavioral range and degree of match to real data can be obtained. The detailed and abstract models and the mouse recordings overlapped considerably in behavior space. Both the range of behaviors and similarity to mouse data were similar between the detailed and abstract models. When no high-level metrics were used and principal components analysis was computed over raw time series, the models overlapped minimally with the mouse recordings. The method introduced here is suitable for comparing across different kinds of model data and across real brain recordings. It appears that, despite differences in form and computational expense, detailed and abstract models do not necessarily differ in their behaviors.
Modelling road accidents: An approach using structural time series
Junus, Noor Wahida Md; Ismail, Mohd Tahir
2014-09-01
In this paper, the trend of road accidents in Malaysia for the years 2001 until 2012 was modelled using a structural time series approach. The structural time series model was identified using a stepwise method, and the residuals for each model were tested. The best-fitted model was chosen based on the smallest Akaike Information Criterion (AIC) and prediction error variance. In order to check the quality of the model, a data validation procedure was performed by predicting the monthly number of road accidents for the year 2012. Results indicate that the best specification of the structural time series model to represent road accidents is the local level with a seasonal model.
Adversary Model: Adaptive Chosen Ciphertext Attack with Timing Attack
2014-01-01
We have introduced a novel adversary model in Chosen-Ciphertext Attack with Timing Attack (CCA2-TA) and it was a practical model because the model incorporates the timing attack. This paper is an extended paper for 'A Secure TFTP Protocol with Security Proofs'. Keywords - Timing Attack, Random Oracle Model, Indistinguishabilit, Chosen Plaintext Attack, CPA, Chosen Ciphertext Attack, IND-CCA1, Adaptive Chosen Ciphertext Attack, IND-CCA2, Trivial File Transfer Protocol, TFTP, Security, Trust, P...
With string model to time series forecasting
Pinčák, Richard; Bartoš, Erik
2015-01-01
Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate the real financial markets. Analyses are not conducted on the non equidistant date but rather on the aggregate date, which is also not a real financial case. In this paper, we would like to show a new way how to analyze and, moreover, forecast financial ma...
Time-of-Flight Measurement of a 355-nm Nd:YAG Laser-Produced Aluminum Plasma
Directory of Open Access Journals (Sweden)
M. F. Baclayon
2003-06-01
Full Text Available An aluminum target in air was irradiated by a 355-nm Nd:YAG laser with a pulse width of 10 ns and arepetition rate of 10 Hz. The emission spectra of the laser-produced aluminum plasma were investigatedwith varying distances from the target surface. The results show the presence of a strong continuum veryclose to the target surface, but as the plasma evolve in space, the continuum gradually disappears and theemitted spectra are dominated by stronger line emissions. The observed plasma species are the neutraland singly ionized aluminum and their speeds were investigated using an optical time-of-flight measurementtechnique. Results show that the speeds of the plasma species decreases gradually with distance from thetarget surface. Comparison of the computed speeds of the plasma species shows that the singly ionizedspecies have relatively greater kinetic energy than the neutral species.
With string model to time series forecasting
Pinčák, Richard; Bartoš, Erik
2015-10-01
Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate the real financial markets. Analyses are not conducted on the non equidistant date but rather on the aggregate date, which is also not a real financial case. In this paper, we would like to show a new way how to analyze and, moreover, forecast financial market. We utilize the projections of the real exchange rate dynamics onto the string-like topology in the OANDA market. The latter approach allows us to build the stable prediction models in trading in the financial forex market. The real application of the multi-string structures is provided to demonstrate our ideas for the solution of the problem of the robust portfolio selection. The comparison with the trend following strategies was performed, the stability of the algorithm on the transaction costs for long trade periods was confirmed.
A Provenance Model for Real-Time Water Information Systems
Liu, Q.; Bai, Q.; Zednik, S.; Taylor, P.; Fox, P. A.; Taylor, K.; Kloppers, C.; Peters, C.; Terhorst, A.; West, P.; Compton, M.; Shu, Y.; Provenance Management Team
2010-12-01
Generating hydrological data products, such as flow forecasts, involves complex interactions among instruments, data simulation models, computational facilities and data providers. Correct interpretation of the data produced at various stages requires good understanding of how data was generated or processed. Provenance describes the lineage of a data product. Making provenance information accessible to hydrologists and decision makers not only helps to determine the data’s value, accuracy and authorship, but also enables users to determine the trustworthiness of the data product. In the water domain, WaterML2 [1] is an emerging standard which describes an information model and format for the publication of water observations data in XML. The W3C semantic sensor network incubator group (SSN-XG) [3] is producing ontologies for the description of sensor configurations. By integrating domain knowledge of this kind into the provenance information model, the integrated information model will enable water domain researchers and water resource managers to better analyse how observations and derived data products were generated. We first introduce the Proof Mark Language (PML2) [2], WaterML2 and the SSN-XG sensor ontology as the proposed provenance representation formalism. Then we describe some initial implementations how these standards could be integrated to represent the lineage of water information products. Finally we will highlight how the provenance model for a distributed real-time water information system assists the interpretation of the data product and establishing trust. Reference [1] Taylor, P., Walker, G., Valentine, D., Cox, Simon: WaterML2.0: Harmonising standards for water observation data. Geophysical Research Abstracts. Vol. 12. [2] da Silva, P.P., McGuinness, D.L., Fikes, R.: A proof markup language for semantic web services. Inf. Syst. 31(4) (2006), 381-395. [3] W3C Semantic Sensor Network Incubator Group http://www.w3.org/2005/Incubator
Forecasting Daily Time Series using Periodic Unobserved Components Time Series Models
Koopman, Siem Jan; Ooms, Marius
2004-01-01
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend and seasonal. Periodic time series models allow dynamic characteristics to depend on the period of the year, month, week or day. In the stand
Forecasting Daily Time Series using Periodic Unobserved Components Time Series Models
Koopman, Siem Jan; Ooms, Marius
2004-01-01
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend and seasonal. Periodic time series models allow dynamic characteristics to depend on the period of the year, month, week or day. In the
Nechitailo, Galina S.; Yurov, S.; Cojocaru, A.; Revin, A.
The analysis of the lycopene and other carotenoids in tomatoes produced from seeds exposed under space flight conditions at the orbital station MIR for six years is presented in this work. Our previous experiments with tomato plants showed the germination of seeds to be 32%Genetic investigations revealed 18%in the experiment and 8%experiments were conducted to study the capacity of various stimulating factors to increase germination of seeds exposed for a long time to the action of space flight factors. An increase of 20%achieved but at the same time mutants having no analogues in the control variants were detected. For the present investigations of the third generation of plants produced from seeds stored for a long time under space flight conditions 80 tomatoes from forty plants were selected. The concentration of lycopene in the experimental specimens was 2.5-3 times higher than in the control variants. The spectrophotometric analysis of ripe tomatoes revealed typical three-peaked carotenoid spectra with a high maximum of lycopene (a medium maximum at 474 nm), a moderate maximum of its predecessor, phytoin, (a medium maximum at 267 nm) and a low maximum of carotenes. In green tomatoes, on the contrary, a high maximum of phytoin, a moderate maximum of lycopene and a low maximum of carotenes were observed. The results of the spectral analysis point to the retardation of biosynthesis of carotenes while the production of lycopene is increased and to the synthesis of lycopene from phytoin. Electric conduction of tomato juice in the experimental samples is increased thus suggesting higher amounts of carotenoids, including lycopene and electrolytes. The higher is the value of electric conduction of a specimen, the higher are the spectral maxima of lycopene. The hydrogen ion exponent of the juice of ripe tomatoes increases due to which the efficiency of ATP biosynthesis in cell mitochondria is likely to increase, too. The results demonstrating an increase in the content
Immersed boundary lattice Boltzmann model based on multiple relaxation times.
Lu, Jianhua; Han, Haifeng; Shi, Baochang; Guo, Zhaoli
2012-01-01
As an alterative version of the lattice Boltzmann models, the multiple relaxation time (MRT) lattice Boltzmann model introduces much less numerical boundary slip than the single relaxation time (SRT) lattice Boltzmann model if some special relationship between the relaxation time parameters is chosen. On the other hand, most current versions of the immersed boundary lattice Boltzmann method, which was first introduced by Feng and improved by many other authors, suffer from numerical boundary slip as has been investigated by Le and Zhang. To reduce such a numerical boundary slip, an immerse boundary lattice Boltzmann model based on multiple relaxation times is proposed in this paper. A special formula is given between two relaxation time parameters in the model. A rigorous analysis and the numerical experiments carried out show that the numerical boundary slip reduces dramatically by using the present model compared to the single-relaxation-time-based model.
An experimental model of tool mark striations in soft tissues produced by serrated blades.
Pounder, Derrick J; Cormack, Lesley
2011-03-01
Stab wounds produced by serrated blades are generally indistinguishable from stab wounds produced by non-serrated blades, except when visible tool mark striations are left on severed cartilage. We explored the possibility that similar striations may be produced on the soft tissues of internal organs. Loin of beef, bovine kidney, and pig heart, liver, and aorta were each stabbed 20 times with a coarsely serrated blade. The walls of the stab tracks were exposed and documented by photography, cast with dental impression material, and the casts photographed. Striations were identified in all of the tissues in every stabbing, but their consistency and quality varied between tissues. Striations were most easily seen in liver, heart, and aorta. Tool mark striations in soft tissues other than cartilage have not been described in homicidal stabbings, likely because they have not been sought. We suggest that the walls of stab wound tracks should be exposed, and tissue striations should be sought as a means of identifying the weapon as having a serrated blade.
Saturation and time dependence of geodynamo models
Schrinner, M; Cameron, R; Hoyng, P
2009-01-01
In this study we address the question under which conditions a saturated velocity field stemming from geodynamo simulations leads to an exponential growth of the magnetic field in a corresponding kinematic calculation. We perform global self-consistent geodynamo simulations and calculate the evolution of a kinematically advanced tracer field. The self-consistent velocity field enters the induction equation in each time step, but the tracer field does not contribute to the Lorentz force. This experiment has been performed by Cattaneo & Tobias (2009) and is closely related to the test field method by Schrinner et al. (2005, 2007). We find two dynamo regimes in which the tracer field either grows exponentially or approaches a state aligned with the actual self-consistent magnetic field after an initial transition period. Both regimes can be distinguished by the Rossby number and coincide with the dipolar and multipolar dynamo regimes identified by Christensen & Aubert (2006). Dipolar dynamos with low Ros...
Unified Modeling of Complex Real-Time Control Systems
Hai, He; Chi-Lan, Cai
2011-01-01
Complex real-time control system is a software dense and algorithms dense system, which needs modern software engineering techniques to design. UML is an object-oriented industrial standard modeling language, used more and more in real-time domain. This paper first analyses the advantages and problems of using UML for real-time control systems design. Then, it proposes an extension of UML-RT to support time-continuous subsystems modeling. So we can unify modeling of complex real-time control systems on UML-RT platform, from requirement analysis, model design, simulation, until generation code.
TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION
Directory of Open Access Journals (Sweden)
Goran Klepac
2007-12-01
Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.
A reference Earth model for the heat producing elements and associated geoneutrino flux
Huang, Yu; Mantovani, Fabio; Rudnick, Roberta L; McDonough, William F
2013-01-01
The recent geoneutrino experimental results from KamLAND and Borexino detectors reveal the usefulness of analyzing the Earth geoneutrino flux, as it provides a constraint on the strength of the radiogenic heat power and this, in turn, provides a test of compositional models of the bulk silicate Earth (BSE). This flux is dependent on the amount and distribution of heat producing elements (HPEs: U, Th and K) in the Earth interior. We have developed a geophysically-based, three-dimensional global reference model for the abundances and distributions of HPEs in the BSE. The structure and composition of the outermost portion of the Earth, the crust and underlying lithospheric mantle, is detailed in the reference model, this portion of the Earth has the greatest influence on the geoneutrino fluxes. The reference model combines three existing geophysical models of the global crust and yields an average crustal thickness of 34.4+-4.1 km in the continents and 8.0+-2.7 km in the oceans. In situ seismic velocity provided...
General expression for linear and nonlinear time series models
Institute of Scientific and Technical Information of China (English)
Ren HUANG; Feiyun XU; Ruwen CHEN
2009-01-01
The typical time series models such as ARMA, AR, and MA are founded on the normality and stationarity of a system and expressed by a linear difference equation; therefore, they are strictly limited to the linear system. However, some nonlinear factors are within the practical system; thus, it is difficult to fit the model for real systems with the above models. This paper proposes a general expression for linear and nonlinear auto-regressive time series models (GNAR). With the gradient optimization method and modified AIC information criteria integrated with the prediction error, the parameter estimation and order determination are achieved. The model simulation and experiments show that the GNAR model can accurately approximate to the dynamic characteristics of the most nonlinear models applied in academics and engineering. The modeling and prediction accuracy of the GNAR model is superior to the classical time series models. The proposed GNAR model is flexible and effective.
Time, models and narratives : Towards understanding the dynamics of life
van Geert, Paul
2006-01-01
Whereas Rudolph's (2006a) article provides a discussion of mathematical models of time, Yamado and Kato (2006a) present a particular image of time-circular time-as a key feature of an entirely different model of temporality, namely people life-span narratives. In the present article, I attempt to ap
Space-time modeling of electricity spot prices
DEFF Research Database (Denmark)
Abate, Girum Dagnachew; Haldrup, Niels
In this paper we derive a space-time model for electricity spot prices. A general spatial Durbin model that incorporates the temporal as well as spatial lags of spot prices is presented. Joint modeling of space-time effects is necessarily important when prices and loads are determined in a network...
Modeling dynamic effects of promotion on interpurchase times
D. Fok (Dennis); R. Paap (Richard); Ph.H.B.F. Franses (Philip Hans)
2002-01-01
textabstractIn this paper we put forward a duration model to analyze the dynamic effects of marketing-mix variables on interpurchase times. We extend the accelerated failure-time model with an autoregressive structure. An important feature of our model is that it allows for different long-run and
Modeling dynamic effects of promotion on interpurchase times
D. Fok (Dennis); R. Paap (Richard); Ph.H.B.F. Franses (Philip Hans)
2002-01-01
textabstractIn this paper we put forward a duration model to analyze the dynamic effects of marketing-mix variables on interpurchase times. We extend the accelerated failure-time model with an autoregressive structure. An important feature of our model is that it allows for different long-run and
A lognormal model for response times on test items
van der Linden, Willem J.
2006-01-01
A lognormal model for the response times of a person on a set of test items is investigated. The model has a parameter structure analogous to the two-parameter logistic response models in item response theory, with a parameter for the speed of each person as well as parameters for the time intensity
Structure and tensile properties evaluation of samples produced by Fused Deposition Modeling
Gajdoš, Ivan; Slota, Ján; Spišák, Emil; Jachowicz, Tomasz; Tor-Swiatek, Aneta
2016-05-01
This paper presents the result of a study evaluating the influence of alternative path generation strategy on structure and some mechanical properties of parts produced by Fused Deposition Modeling (FDM) technology. Several scientific investigations focused on resolving issues in FDM parts by modifying a path generation strategy to optimize its mechanical properties. In this study, an alternative strategy was proposed with the intention of minimizing internal voids and, thus, to improve mechanical properties. Polycarbonate samples made by this alternative path generation strategy were subjected to tensile strength test and metro-tomography structure evaluation. The results reveal that the structure observed on build models differs from a structure expected from path generation predicted by software Insight 9.1. This difference affected the tensile strength of samples.
Network model explains why cancer cells use inefficient pathway to produce energy
Lee, Joo Sang; Marko, John; Motter, Adilson
2012-02-01
The Warburg effect---the use of the (energetically inefficient) fermentative pathway as opposed to (energetically efficient) respiration even in the presence of oxygen---is a common property of cancer metabolism. Here, we propose that the Warburg effect is in fact a consequence of a trade-off between the benefit of rapid growth and the cost for protein synthesis. Using genome-scale metabolic networks, we have modeled the cellular resources for protein synthesis as a growth defect that increases with enzyme concentration. Based on our model, we demonstrate that the cost of protein production during rapid growth drives the cell to rely on fermentation to produce ATP. We also identify an intimate link between extensive fermentation and rapid biosynthesis. Our findings emphasize the importance of protein synthesis as a limiting factor on cell proliferation and provide a novel mathematical framework to analyze cancer metabolism.
Directory of Open Access Journals (Sweden)
Safakish R
2017-06-01
Full Text Available Ramin Safakish Allevio Pain Management Clinic, Toronto, ON, Canada Abstract: Lower back pain (LBP is a global public health issue and is associated with substantial financial costs and loss of quality of life. Over the years, different literature has provided different statistics regarding the causes of the back pain. The following statistic is the closest estimation regarding our patient population. The sacroiliac (SI joint pain is responsible for LBP in 18%–30% of individuals with LBP. Quadrapolar™ radiofrequency ablation, which involves ablation of the nerves of the SI joint using heat, is a commonly used treatment for SI joint pain. However, the standard Quadrapolar radiofrequency procedure is not always effective at ablating all the sensory nerves that cause the pain in the SI joint. One of the major limitations of the standard Quadrapolar radiofrequency procedure is that it produces small lesions of ~4 mm in diameter. Smaller lesions increase the likelihood of failure to ablate all nociceptive input. In this study, we compare the standard Quadrapolar radiofrequency ablation technique to a modified Quadrapolar ablation technique that has produced improved patient outcomes in our clinic. The methodology of the two techniques are compared. In addition, we compare results from an experimental model comparing the lesion sizes produced by the two techniques. Taken together, the findings from this study suggest that the modified Quadrapolar technique provides longer lasting relief for the back pain that is caused by SI joint dysfunction. A randomized controlled clinical trial is the next step required to quantify the difference in symptom relief and quality of life produced by the two techniques. Keywords: lower back pain, radiofrequency ablation, sacroiliac joint, Quadrapolar radiofrequency ablation
Reliability physics and engineering time-to-failure modeling
McPherson, J W
2013-01-01
Reliability Physics and Engineering provides critically important information that is needed for designing and building reliable cost-effective products. Key features include: · Materials/Device Degradation · Degradation Kinetics · Time-To-Failure Modeling · Statistical Tools · Failure-Rate Modeling · Accelerated Testing · Ramp-To-Failure Testing · Important Failure Mechanisms for Integrated Circuits · Important Failure Mechanisms for Mechanical Components · Conversion of Dynamic Stresses into Static Equivalents · Small Design Changes Producing Major Reliability Improvements · Screening Methods · Heat Generation and Dissipation · Sampling Plans and Confidence Intervals This textbook includes numerous example problems with solutions. Also, exercise problems along with the answers are included at the end of each chapter. Relia...
DEFF Research Database (Denmark)
Busato, P.; Sopegno, A.; Berruto, R.
2013-01-01
together to form a large size lot at some points in the supply-chain. Larger lot size could imply higher risk for the consumers in case of recall of the produce and much higher recall time and cost for the supply-chain. When a non-conformity occurs, the time to recall the produce depends on many factors...
Market volatility modeling for short time window
de Mattos Neto, Paulo S. G.; Silva, David A.; Ferreira, Tiago A. E.; Cavalcanti, George D. C.
2011-10-01
The gain or loss of an investment can be defined by the movement of the market. This movement can be estimated by the difference between the magnitudes of two stock prices in distinct periods and this difference can be used to calculate the volatility of the markets. The volatility characterizes the sensitivity of a market change in the world economy. Traditionally, the probability density function (pdf) of the movement of the markets is analyzed by using power laws. The contributions of this work is two-fold: (i) an analysis of the volatility dynamic of the world market indexes is performed by using a two-year window time data. In this case, the experiments show that the pdf of the volatility is better fitted by exponential function than power laws, in all range of pdf; (ii) after that, we investigate a relationship between the volatility of the markets and the coefficient of the exponential function based on the Maxwell-Boltzmann ideal gas theory. The results show an inverse relationship between the volatility and the coefficient of the exponential function. This information can be used, for example, to predict the future behavior of the markets or to cluster the markets in order to analyze economic patterns.
Continuous-time model of structural balance.
Marvel, Seth A; Kleinberg, Jon; Kleinberg, Robert D; Strogatz, Steven H
2011-02-01
It is not uncommon for certain social networks to divide into two opposing camps in response to stress. This happens, for example, in networks of political parties during winner-takes-all elections, in networks of companies competing to establish technical standards, and in networks of nations faced with mounting threats of war. A simple model for these two-sided separations is the dynamical system dX/dt = X(2), where X is a matrix of the friendliness or unfriendliness between pairs of nodes in the network. Previous simulations suggested that only two types of behavior were possible for this system: Either all relationships become friendly or two hostile factions emerge. Here we prove that for generic initial conditions, these are indeed the only possible outcomes. Our analysis yields a closed-form expression for faction membership as a function of the initial conditions and implies that the initial amount of friendliness in large social networks (started from random initial conditions) determines whether they will end up in intractable conflict or global harmony.
Directory of Open Access Journals (Sweden)
Luciano Ribeiro CORREA NETTO
2015-10-01
Full Text Available Marginal integrity is one of the most crucial aspects involved in the clinical longevity of resin composite restorations.Objective To analyze the marginal integrity of restorations produced with a model composite based on polyhedral oligomeric silsesquioxane (POSS.Material and Methods A base composite (B was produced with an organic matrix with UDMA/TEGDMA and 70 wt.% of barium borosilicate glass particles. To produce the model composite, 25 wt.% of UDMA were replaced by POSS (P25. The composites P90 and TPH3 (TP3 were used as positive and negative controls, respectively. Marginal integrity (%MI was analyzed in bonded class I cavities. The volumetric polymerization shrinkage (%VS and the polymerization shrinkage stress (Pss - MPa were also evaluated.Results The values for %MI were as follows: P90 (100% = TP3 (98.3% = B (96.9% > P25 (93.2%, (p<0.05. The %VS ranged from 1.4% (P90 to 4.9% (P25, while Pss ranged from 2.3 MPa (P90 to 3.9 MPa (B. For both properties, the composite P25 presented the worst results (4.9% and 3.6 MPa. Linear regression analysis showed a strong positive correlation between %VS and Pss (r=0.97, whereas the correlation between Pss and %MI was found to be moderate (r=0.76.Conclusions The addition of 25 wt.% of POSS in methacrylate organic matrix did not improve the marginal integrity of class I restorations. Filtek P90 showed lower polymerization shrinkage and shrinkage stress when compared to the experimental and commercial methacrylate composite.
Molecular Characterization of Growth Hormone-producing Tumors in the GC Rat Model of Acromegaly.
Martín-Rodríguez, Juan F; Muñoz-Bravo, Jose L; Ibañez-Costa, Alejandro; Fernandez-Maza, Laura; Balcerzyk, Marcin; Leal-Campanario, Rocío; Luque, Raúl M; Castaño, Justo P; Venegas-Moreno, Eva; Soto-Moreno, Alfonso; Leal-Cerro, Alfonso; Cano, David A
2015-11-09
Acromegaly is a disorder resulting from excessive production of growth hormone (GH) and consequent increase of insulin-like growth factor 1 (IGF-I), most frequently caused by pituitary adenomas. Elevated GH and IGF-I levels results in wide range of somatic, cardiovascular, endocrine, metabolic, and gastrointestinal morbidities. Subcutaneous implantation of the GH-secreting GC cell line in rats leads to the formation of tumors. GC tumor-bearing rats develop characteristics that resemble human acromegaly including gigantism and visceromegaly. However, GC tumors remain poorly characterized at a molecular level. In the present work, we report a detailed histological and molecular characterization of GC tumors using immunohistochemistry, molecular biology and imaging techniques. GC tumors display histopathological and molecular features of human GH-producing tumors, including hormone production, cell architecture, senescence activation and alterations in cell cycle gene expression. Furthermore, GC tumors cells displayed sensitivity to somatostatin analogues, drugs that are currently used in the treatment of human GH-producing adenomas, thus supporting the GC tumor model as a translational tool to evaluate therapeutic agents. The information obtained would help to maximize the usefulness of the GC rat model for research and preclinical studies in GH-secreting tumors.
Stimpert, Alison K; Wiley, David N; Au, Whitlow W L; Johnson, Mark P; Arsenault, Roland
2007-10-22
Humpback whales (Megaptera novaeangliae) exhibit a variety of foraging behaviours, but neither they nor any baleen whale are known to produce broadband clicks in association with feeding, as do many odontocetes. We recorded underwater behaviour of humpback whales in a northwest Atlantic feeding area using suction-cup attached, multi-sensor, acoustic tags (DTAGs). Here we describe the first recordings of click production associated with underwater lunges from baleen whales. Recordings of over 34000 'megapclicks' from two whales indicated relatively low received levels at the tag (between 143 and 154dB re 1 microPa pp), most energy below 2kHz, and interclick intervals often decreasing towards the end of click trains to form a buzz. All clicks were recorded during night-time hours. Sharp body rolls also occurred at the end of click bouts containing buzzes, suggesting feeding events. This acoustic behaviour seems to form part of a night-time feeding tactic for humpbacks and also expands the known acoustic repertoire of baleen whales in general.
Smith, Kirsty F; de Salas, Miguel; Adamson, Janet; Rhodes, Lesley L
2014-03-07
The identification of toxin-producing dinoflagellates for monitoring programmes and bio-compound discovery requires considerable taxonomic expertise. It can also be difficult to morphologically differentiate toxic and non-toxic species or strains. Various molecular methods have been used for dinoflagellate identification and detection, and this study describes the development of eight real-time polymerase chain reaction (PCR) assays targeting the large subunit ribosomal RNA (LSU rRNA) gene of species from the genera Gymnodinium, Karenia, Karlodinium, and Takayama. Assays proved to be highly specific and sensitive, and the assay for G. catenatum was further developed for quantification in response to a bloom in Manukau Harbour, New Zealand. The assay estimated cell densities from environmental samples as low as 0.07 cells per PCR reaction, which equated to three cells per litre. This assay not only enabled conclusive species identification but also detected the presence of cells below the limit of detection for light microscopy. This study demonstrates the usefulness of real-time PCR as a sensitive and rapid molecular technique for the detection and quantification of micro-algae from environmental samples.
A model with nonzero rise time for AE signals
Indian Academy of Sciences (India)
M A Majeed; C R L Murthy
2001-10-01
Acoustic emission (AE) signals are conventionally modelled as damped or decaying sinusoidal functions. A major drawback of this model is its negligible or zero rise time. This paper proposes an alternative model, which provides for the rising part of the signal without sacriﬁcing the analytical tractability and simplicity of the conventional model. Signals obtained from the proposed model through computer programs are illustrated for demonstrating their parity with actual AE signals. Analytic expressions for the time-domain parameters, viz., peak amplitude and rise time used in conventional AE signal analysis, are also derived. The model is believed to be also of use in modelling the output signal of any transducer that has ﬁnite rise time and fall time.
Evolution of a Voltage-Time Model of Thermal Batteries
1991-02-01
MARK I1 VOLTAGE-TIME MODEL 7 6 MARKt III VOLTAGE-TIME MODEL 10 6.1 Capacity degradation II 6,2 Allowance ’for time-dependent polarisation If 6,3...period is sub- divided into two or more segments in the model input data, in all of which the TM MS 1163 13 same current or resistor value operates as
Automated Predicate Abstraction for Real-Time Models
Directory of Open Access Journals (Sweden)
Bahareh Badban
2009-11-01
Full Text Available We present a technique designed to automatically compute predicate abstractions for dense real-timed models represented as networks of timed automata. We use the CIPM algorithm in our previous work which computes new invariants for timed automata control locations and prunes the model, to compute a predicate abstraction of the model. We do so by taking information regarding control locations and their newly computed invariants into account.
Modeling non-Gaussian time-varying vector autoregressive process
National Aeronautics and Space Administration — We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical...
Emergency Rescue Location Model with Uncertain Rescue Time
Directory of Open Access Journals (Sweden)
Jing Guan
2014-01-01
Full Text Available In order to model emergency rescue location problem with uncertain rescue time, an uncertain expected cost minimization model is proposed under uncertain environment. For solving this model, we convert the uncertain model to its equivalent deterministic form. Finally, a numerical example has been presented to illustrate the model. The computational results which were solved by the down mountain algorithm are provided to demonstrate the effectiveness of the model.
2016-12-01
computational power. Such simplifications can produce misleading results. For example, Radar Cross Section (RCS) effects in response to time-varying...and corresponding limitations of computational power. Such simplifications can produce misleading results. For example, Radar Cross Section (RCS...135 xvi Figure 6.1 The RCS of F-16 Falcon fighter model which is simulated by CST Studio software with signal frequency = 8 GHz. In (a), the RCS of
Directory of Open Access Journals (Sweden)
Yuhan Rao
2015-06-01
Full Text Available Due to technical limitations, it is impossible to have high resolution in both spatial and temporal dimensions for current NDVI datasets. Therefore, several methods are developed to produce high resolution (spatial and temporal NDVI time-series datasets, which face some limitations including high computation loads and unreasonable assumptions. In this study, an unmixing-based method, NDVI Linear Mixing Growth Model (NDVI-LMGM, is proposed to achieve the goal of accurately and efficiently blending MODIS NDVI time-series data and multi-temporal Landsat TM/ETM+ images. This method firstly unmixes the NDVI temporal changes in MODIS time-series to different land cover types and then uses unmixed NDVI temporal changes to predict Landsat-like NDVI dataset. The test over a forest site shows high accuracy (average difference: −0.0070; average absolute difference: 0.0228; and average absolute relative difference: 4.02% and computation efficiency of NDVI-LMGM (31 seconds using a personal computer. Experiments over more complex landscape and long-term time-series demonstrated that NDVI-LMGM performs well in each stage of vegetation growing season and is robust in regions with contrasting spatial and spatial variations. Comparisons between NDVI-LMGM and current methods (i.e., Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM, Enhanced STARFM (ESTARFM and Weighted Linear Model (WLM show that NDVI-LMGM is more accurate and efficient than current methods. The proposed method will benefit land surface process research, which requires a dense NDVI time-series dataset with high spatial resolution.
A Dynamic Travel Time Estimation Model Based on Connected Vehicles
Directory of Open Access Journals (Sweden)
Daxin Tian
2015-01-01
Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.
Parameter Optimisation for the Behaviour of Elastic Models over Time
DEFF Research Database (Denmark)
Mosegaard, Jesper
2004-01-01
Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method...... that will optimise parameters based on the behaviour of the elastic models over time....
A Model for Industrial Real-Time Systems
DEFF Research Database (Denmark)
Bin Waez, Md Tawhid; Wasowski, Andrzej; Dingel, Juergen
2015-01-01
Introducing automated formal methods for large industrial real-time systems is an important research challenge. We propose timed process automata (TPA) for modeling and analysis of time-critical systems which can be open, hierarchical, and dynamic. The model offers two essential features for larg...... establish safety and reachability properties of TPA by reduction to solving timed games. To mitigate the state-space explosion problem, an automated state-space reduction technique using compositional reasoning and aggressive abstractions is also proposed....
Sampson, Christopher; Smith, Andrew; Bates, Paul; Neal, Jeffrey; Trigg, Mark
2015-12-01
Global flood hazard models have recently become a reality thanks to the release of open access global digital elevation models, the development of simplified and highly efficient flow algorithms, and the steady increase in computational power. In this commentary we argue that although the availability of open access global terrain data has been critical in enabling the development of such models, the relatively poor resolution and precision of these data now limit significantly our ability to estimate flood inundation and risk for the majority of the planet's surface. The difficulty of deriving an accurate 'bare-earth' terrain model due to the interaction of vegetation and urban structures with the satellite-based remote sensors means that global terrain data are often poorest in the areas where people, property (and thus vulnerability) are most concentrated. Furthermore, the current generation of open access global terrain models are over a decade old and many large floodplains, particularly those in developing countries, have undergone significant change in this time. There is therefore a pressing need for a new generation of high resolution and high vertical precision open access global digital elevation models to allow significantly improved global flood hazard models to be developed.
Modelling and Simulation of Asynchronous Real-Time Systems using Timed Rebeca
Aceto, Luca; Ingolfsdottir, Anna; Reynisson, Arni Hermann; Sigurdarson, Steinar Hugi; Sirjani, Marjan; 10.4204/EPTCS.58.1
2011-01-01
In this paper we propose an extension of the Rebeca language that can be used to model distributed and asynchronous systems with timing constraints. We provide the formal semantics of the language using Structural Operational Semantics, and show its expressiveness by means of examples. We developed a tool for automated translation from timed Rebeca to the Erlang language, which provides a first implementation of timed Rebeca. We can use the tool to set the parameters of timed Rebeca models, which represent the environment and component variables, and use McErlang to run multiple simulations for different settings. Timed Rebeca restricts the modeller to a pure asynchronous actor-based paradigm, where the structure of the model represents the service oriented architecture, while the computational model matches the network infrastructure. Simulation is shown to be an effective analysis support, specially where model checking faces almost immediate state explosion in an asynchronous setting.
A framework to model real-time databases
Idoudi, Nizar; Duvallet, Claude; Sadeg, Bruno; Bouaziz, Rafik; Gargouri, Faiez
2010-01-01
Real-time databases deal with time-constrained data and time-constrained transactions. The design of this kind of databases requires the introduction of new concepts to support both data structures and the dynamic behaviour of the database. In this paper, we give an overview about different aspects of real-time databases and we clarify requirements of their modelling. Then, we present a framework for real-time database design and describe its fundamental operations. A case study demonstrates the validity of the structural model and illustrates SQL queries and Java code generated from the classes of the model
Genetic programming-based chaotic time series modeling
Institute of Scientific and Technical Information of China (English)
张伟; 吴智铭; 杨根科
2004-01-01
This paper proposes a Genetic Programming-Based Modeling(GPM)algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space,and the Particle Swarm Optimization(PSO)algorithm is used for Nonlinear Parameter Estimation(NPE)of dynamic model structures. In addition,GPM integrates the results of Nonlinear Time Series Analysis(NTSA)to adjust the parameters and takes them as the criteria of established models.Experiments showed the effectiveness of such improvements on chaotic time series modeling.
Hofstede, ter F.; Wedel, M.
1998-01-01
This study investigates the effects of time aggregation in discrete and continuous-time hazard models. A Monte Carlo study is conducted in which data are generated according to various continuous and discrete-time processes, and aggregated into daily, weekly and monthly intervals. These data are
Assessment of the Quality of Digital Terrain Model Produced from Unmanned Aerial System Imagery
Kosmatin Fras, M.; Kerin, A.; Mesarič, M.; Peterman, V.; Grigillo, D.
2016-06-01
Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.
A time fractional model to represent rainfall process
Directory of Open Access Journals (Sweden)
Jacques GOLDER
2014-01-01
Full Text Available This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered α-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation (FFPE with tempered α-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered α-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered α-stable waiting times is more efficient in reproducing the observed behavior.
Xu, Dake; Li, Yingchao; Gu, Tingyue
2016-08-01
Biocorrosion is also known as microbiologically influenced corrosion (MIC). Most anaerobic MIC cases can be classified into two major types. Type I MIC involves non-oxygen oxidants such as sulfate and nitrate that require biocatalysis for their reduction in the cytoplasm of microbes such as sulfate reducing bacteria (SRB) and nitrate reducing bacteria (NRB). This means that the extracellular electrons from the oxidation of metal such as iron must be transported across cell walls into the cytoplasm. Type II MIC involves oxidants such as protons that are secreted by microbes such as acid producing bacteria (APB). The biofilms in this case supply the locally high concentrations of oxidants that are corrosive without biocatalysis. This work describes a mechanistic model that is based on the biocatalytic cathodic sulfate reduction (BCSR) theory. The model utilizes charge transfer and mass transfer concepts to describe the SRB biocorrosion process. The model also includes a mechanism to describe APB attack based on the local acidic pH at a pit bottom. A pitting prediction software package has been created based on the mechanisms. It predicts long-term pitting rates and worst-case scenarios after calibration using SRB short-term pit depth data. Various parameters can be investigated through computer simulation.
Synthesis and Modeling of Temperature Distribution For Nanoparticles Produced Using Nd:YAG Lasers
Directory of Open Access Journals (Sweden)
Mu’ataz S. Hassan
2016-01-01
Full Text Available Nanosecond pulses of Nd:YAG laser were employed to produce silver and silicon nanoparticles by laser ablation process in liquid. Two Nd:YAG laser systems of 6 and 10 nanoseconds pulse duration with variable laser energy in the range 700–760 mJ were employed. Morphological investigation using AFM and TEM reveals the formation of silver and silicon nanoparticles with uniform size distribution. It is found that mean nanoparticles sizes of 50 and 70 nm for silver and silicon, respectively, are produced under similar laser parameters. Moreover, theoretical model was used to estimate the temperature distributions for both silver and silicon nanoparticles. It is also found that the maximum temperature of about 50 k K° and 70 k K° for silver and silicon nanoparticles, respectively, is generated when Nd:YAG of 10 ns is used to prepare nanoparticles. Zeta potential measurements reveal that silver nanoparticles are more stable than those of silicon prepared by similar conditions.
Pawelek, Kasia A.; Liu, Shengqiang; Pahlevani, Faranak; Rong, Libin
2011-01-01
Mathematical models have made considerable contributions to our understanding of HIV dynamics. Introducing time delays to HIV models usually brings challenges to both mathematical analysis of the models and comparison of model predictions with patient data. In this paper, we incorporate two delays, one the time needed for infected cells to produce virions after viral entry and the other the time needed for the adaptive immune response to emerge to control viral replication, into an HIV-1 mode...
Haywood, A.M.; Chandler, M.A.; Valdes, P.J.; Salzmann, U.; Lunt, D.J.; Dowsett, H.J.
2009-01-01
The mid-Pliocene warm period (ca. 3 to 3.3??million years ago) has become an important interval of time for palaeoclimate modelling exercises, with a large number of studies published during the last decade. However, there has been no attempt to assess the degree of model dependency of the results obtained. Here we present an initial comparison of mid-Pliocene climatologies produced by the Goddard Institute for Space Studies and Hadley Centre for Climate Prediction and Research atmosphere-only General Circulation Models (GCMAM3 and HadAM3). Whilst both models are consistent in the simulation of broad-scale differences in mid-Pliocene surface air temperature and total precipitation rates, significant variation is noted on regional and local scales. There are also significant differences in the model predictions of total cloud cover. A terrestrial data/model comparison, facilitated by the BIOME 4 model and a new data set of Piacenzian Stage land cover [Salzmann, U., Haywood, A.M., Lunt, D.J., Valdes, P.J., Hill, D.J., (2008). A new global biome reconstruction and data model comparison for the Middle Pliocene. Global Ecology and Biogeography 17, 432-447, doi:10.1111/j.1466-8238.2007.00381.x] and combined with the use of Kappa statistics, indicates that HadAM3-based biome predictions provide a closer fit to proxy data in the mid to high-latitudes. However, GCMAM3-based biomes in the tropics provide the closest fit to proxy data. ?? 2008 Elsevier B.V.
Sectoral Structure Change Modeling of European Oil and Gas Producing Country’S Economy
Directory of Open Access Journals (Sweden)
Perepelkin Viacheslav Alexandrovich
2015-12-01
Full Text Available In this paper, we consider identifying features of sectoral structuring within the national economy that has definite foreign trade product specialization. Examination of the sector-specific division methodology enabled identification of its strong association with certain sector dominance in the economy. It is against this background that we offer an explanation for the delay in transferring from the post-Soviet to the applicable international classification of economic structure elements in Russia and Belarus. We perform analysis of the three-component P-S-T model (primary, secondary, tertiary sector using statistical and econometric methods and define properties of the sectoral shares dynamics in national economies of oil and gas producing countries. Analysis of the Russian and Norwegian economies’ intersectoral changes suggests that it is necessary for the government to develop and implement selective structural policy to overcome the existing structural disproportions.
Modeling the Aerodynamic Lift Produced by Oscillating Airfoils at Low Reynolds Number
Khalid, Muhammad Saif Ullah
2015-01-01
For present study, setting Strouhal Number (St) as control parameter, numerical simulations for flow past oscillating NACA-0012 airfoil at 1,000 Reynolds Numbers (Re) are performed. Temporal profiles of unsteady forces; lift and thrust, and their spectral analysis clearly indicate the solution to be a period-1 attractor for low Strouhal numbers. This study reveals that aerodynamic forces produced by plunging airfoil are independent of initial kinematic conditions of airfoil that proves the existence of limit cycle. Frequencies present in the oscillating lift force are composed of fundamental (fs), even and odd harmonics (3fs) at higher Strouhal numbers. Using numerical simulations, shedding frequencies (f_s) were observed to be nearly equal to the excitation frequencies in all the cases. Unsteady lift force generated due to the plunging airfoil is modeled by modified van der Pol oscillator. Using method of multiple scales and spectral analysis of steady-state CFD solutions, frequencies and damping terms in th...
Reducing outpatient waiting time: a simulation modeling approach.
Aeenparast, Afsoon; Tabibi, Seyed Jamaleddin; Shahanaghi, Kamran; Aryanejhad, Mir Bahador
2013-09-01
The objective of this study was to provide a model for reducing outpatient waiting time by using simulation. A simulation model was constructed by using the data of arrival time, service time and flow of 357 patients referred to orthopedic clinic of a general teaching hospital in Tehran. The simulation model was validated before constructing different scenarios. In this study 10 scenarios were presented for reducing outpatient waiting time. Patients waiting time was divided into three levels regarding their physicians. These waiting times for all scenarios were computed by simulation model. According to the final scores the 9th scenario was selected as the best way for reducing outpatient's waiting time. Using the simulation as a decision making tool helps us to decide how we can reduce outpatient's waiting time. Comparison of outputs of this scenario and the based- case scenario in simulation model shows that combining physician's work time changing with patient's admission time changing (scenario 9) would reduce patient waiting time about 73.09%. Due to dynamic and complex nature of healthcare systems, the application of simulation for the planning, modeling and analysis of these systems has lagged behind traditional manufacturing practices. Rapid growth in health care system expenditures, technology and competition has increased the complexity of health care systems. Simulation is a useful tool for decision making in complex and probable systems.
Linear system identification via backward-time observer models
Juang, Jer-Nan; Phan, Minh
1993-01-01
This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) from which a backward-time state-space model is realized using the Eigensystem Realization Algorithm. Third, the obtained backward-time state space model is converted to the usual forward-time representation. Stochastic properties of this approach will be discussed. Experimental results are given to illustrate when and to what extent this concept works.
A model for quantification of temperature profiles via germination times
DEFF Research Database (Denmark)
Pipper, Christian Bressen; Adolf, Verena Isabelle; Jacobsen, Sven-Erik
2013-01-01
Current methodology to quantify temperature characteristics in germination of seeds is predominantly based on analysis of the time to reach a given germination fraction, that is, the quantiles in the distribution of the germination time of a seed. In practice interpolation between observed...... time and a specific type of accelerated failure time models is provided. As a consequence the observed number of germinated seeds at given monitoring times may be analysed directly by a grouped time-to-event model from which characteristics of the temperature profile may be identified and estimated...... germination fractions at given monitoring times is used to obtain the time to reach a given germination fraction. As a consequence the obtained value will be highly dependent on the actual monitoring scheme used in the experiment. In this paper a link between currently used quantile models for the germination...
Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2016-01-01
estimation approach that allows for the parameters of the estimated models to be time varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared daily returns that was previously believed to be the most difficult fact...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....
Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models
Price, Larry R.
2012-01-01
The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…
Characterization of Models for Time-Dependent Behavior of Soils
DEFF Research Database (Denmark)
Liingaard, Morten; Augustesen, Anders; Lade, Poul V.
2004-01-01
Different classes of constitutive models have been developed to capture the time-dependent viscous phenomena ~ creep, stress relaxation, and rate effects ! observed in soils. Models based on empirical, rheological, and general stress-strain-time concepts have been studied. The first part is a r...
Parameterizing unconditional skewness in models for financial time series
DEFF Research Database (Denmark)
He, Changli; Silvennoinen, Annastiina; Teräsvirta, Timo
In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. Therefore it is of importance to know what properties a model should possess if it is to accommodate...
Time Dependent Hadronic Modeling of Flat Spectrum Radio Quasars
Diltz, Christopher; Fossati, Giovanni
2015-01-01
We introduce a new time-dependent lepto-hadronic model for blazar emission that takes into account the radiation emitted by secondary particles, such as pions and muons, from photo hadronic interactions. Starting from a baseline parameter set guided by a fit to the spectral energy distribution of the blazar 3C 279, we perform a parameter study to investigate the effects of perturbations of the input parameters to mimic different flaring events to study the resulting lightcurves in the optical, X-ray, high energy (HE: E > 100 MeV) and very-high-energy (VHE: E > 100 GeV) gamma-rays as well as the neutrino emission associated with charged-pion and muon decay. We find that flaring events from an increase in the efficiency of Fermi II acceleration will produce a positive correlation between all bandpasses and a marked plateau in the HE gamma-ray lightcurve. We also predict a distinctive dip in the HE lightcurve for perturbations caused by a change in the proton injection spectral index. These plateaus / dips could...
Ramakrishnan, Vrinda; Goveas, Louella Concepta; Halami, Prakash M; Narayan, Bhaskar
2015-03-01
Enterococcus durans NCIM5427 (ED-27), capable of producing an intracellular acid stable lipase, was isolated from fish processing waste. Its growth and subsequent lipase production was optimized by Box Behneken design (optimized conditions: 5 % v/v fish waste oil (FWO), 0.10 mg/ml fish waste protein hydrolysates (FWPH) at 48 h of fermentation time). Under optimized conditions, ED-27 showed a 3.0 fold increase (207.6 U/ml to 612.53 U/ml) in lipase production, as compared to un-optimized conditions. Cell growth and lipase production was modeled using Logistic and Luedeking-Piret model, respectively; and lipase production by ED-27 was found to be growth-associated. Lipase produced by ED-27 showed stability at low pH ranges from 2 to 5 with its optimal activity at 30 °C , pH 4.6; showed metal ion dependent activity wherein its catalytic activity was activated by barium, sodium, lithium and potassium (10 mM); reduced by calcium and magnesium (10 mM). However, iron and mercury (5 mM) completely inactivated the enzyme. In addition, modifying agents like SDS, DTT, β-ME (1%v/v) increased activity of lipase of ED-27; while, PMSF, DEPC and ascorbic acid resulted in a marked decrease. ED-27 had maximum cell growth of 9.90309 log CFU/ml under optimized conditions as compared to 13 log CFU/ml in MRS. The lipase produced has potential application in poultry and slaughterhouse waste management.
Trend time-series modeling and forecasting with neural networks.
Qi, Min; Zhang, G Peter
2008-05-01
Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.
A Directed Continuous Time Random Walk Model with Jump Length Depending on Waiting Time
Directory of Open Access Journals (Sweden)
Long Shi
2014-01-01
Full Text Available In continuum one-dimensional space, a coupled directed continuous time random walk model is proposed, where the random walker jumps toward one direction and the waiting time between jumps affects the subsequent jump. In the proposed model, the Laplace-Laplace transform of the probability density function P(x,t of finding the walker at position x at time t is completely determined by the Laplace transform of the probability density function φ(t of the waiting time. In terms of the probability density function of the waiting time in the Laplace domain, the limit distribution of the random process and the corresponding evolving equations are derived.
Support for the Logical Execution Time Model on a Time-predictable Multicore Processor
DEFF Research Database (Denmark)
Kluge, Florian; Schoeberl, Martin; Ungerer, Theo
2016-01-01
The logical execution time (LET) model increases the compositionality of real-time task sets. Removal or addition of tasks does not influence the communication behavior of other tasks. In this work, we extend a multicore operating system running on a time-predictable multicore processor to support...... the LET model. For communication between tasks we use message passing on a time-predictable network-on-chip to avoid the bottleneck of shared memory. We report our experiences and present results on the costs in terms of memory and execution time....
Holladay, Robert; Griffith, Alec; Murillo, Michael S.
2016-10-01
A computational model has been developed to study the evolution of a plasma generated by next-generation advanced light sources such as SLAC's LCLS and LANL's proposed MaRIE. Smoothed Particle Hydrodynamics (SPH) is used to model the plasma evolution because of the ease with which it handles the open boundary conditions and large deformations associated with these experiments. Our work extends the basic SPH method by utilizing a two-fluid model of an electron-ion plasma that also incorporates time dependent ionization and recombination by allowing the SPH fluid particles to have an evolving mass based on the mean ionization state of the plasma. Additionally, inter-species heating, thermal conduction, and electric fields are also accounted for. The effects of various initial conditions and model parameters will be presented, with the goal of using this framework to develop a model that can be used in the design and interpretation of future experiments. This work was supported by the Los Alamos National Laboratory Computational Physics Workshop.
Multi-model Cross Pollination in Time via Data Assimilation
Du, H.; Smith, L. A.
2015-12-01
Nonlinear dynamical systems are frequently used to model physical processes including the fluid dynamics, weather and climate. Uncertainty in the observations makes identification of the exact state impossible for a chaotic nonlinear system, this suggests forecasts based on an ensemble of initial conditions to reflect the inescapable uncertainty in the observations. In general, when forecasting real systems the model class from which the particular model equations are drawn does not contain a process that is able to generate trajectories consistent with the data. Multi-model ensembles have become popular tools to account for uncertainties due to observational noise and structural model error in weather and climate simulation-based predictions on time scales from days to seasons and centuries. There have been some promising results suggesting that the multi-model ensemble forecasts outperform the single model forecasts. The current multi-model ensemble forecasts are focused on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently, every single model is likely to contain different local dynamical information from that of other models. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information from each individual model operationally in time. The proposed method generates model states in time via applying advanced nonlinear data assimilation scheme(s) over the multi-model forecasts. The proposed approach is demonstrated to outperform the traditional statistically post-processing in the 40-dimensional Lorenz96 flow. It is suggested that this illustration could form the basis for more general results which
Lagrangian Time Series Models for Ocean Surface Drifter Trajectories
Sykulski, Adam M; Lilly, Jonathan M; Danioux, Eric
2016-01-01
This paper proposes stochastic models for the analysis of ocean surface trajectories obtained from freely-drifting satellite-tracked instruments. The proposed time series models are used to summarise large multivariate datasets and infer important physical parameters of inertial oscillations and other ocean processes. Nonstationary time series methods are employed to account for the spatiotemporal variability of each trajectory. Because the datasets are large, we construct computationally efficient methods through the use of frequency-domain modelling and estimation, with the data expressed as complex-valued time series. We detail how practical issues related to sampling and model misspecification may be addressed using semi-parametric techniques for time series, and we demonstrate the effectiveness of our stochastic models through application to both real-world data and to numerical model output.
Model for the distribution of aftershock interoccurrence times.
Shcherbakov, Robert; Yakovlev, Gleb; Turcotte, Donald L; Rundle, John B
2005-11-18
In this work the distribution of interoccurrence times between earthquakes in aftershock sequences is analyzed and a model based on a nonhomogeneous Poisson (NHP) process is proposed to quantify the observed scaling. In this model the generalized Omori's law for the decay of aftershocks is used as a time-dependent rate in the NHP process. The analytically derived distribution of interoccurrence times is applied to several major aftershock sequences in California to confirm the validity of the proposed hypothesis.
Shape parameter estimate for a glottal model without time position
Degottex, Gilles; Roebel, Axel; Rodet, Xavier
2009-01-01
cote interne IRCAM: Degottex09a; None / None; National audience; From a recorded speech signal, we propose to estimate a shape parameter of a glottal model without estimating his time position. Indeed, the literature usually propose to estimate the time position first (ex. by detecting Glottal Closure Instants). The vocal-tract filter estimate is expressed as a minimum-phase envelope estimation after removing the glottal model and a standard lips radiation model. Since this filter is mainly b...
Modelling, simulation and inference for multivariate time series of counts
Veraart, Almut E. D.
2016-01-01
This article presents a new continuous-time modelling framework for multivariate time series of counts which have an infinitely divisible marginal distribution. The model is based on a mixed moving average process driven by L\\'{e}vy noise - called a trawl process - where the serial correlation and the cross-sectional dependence are modelled independently of each other. Such processes can exhibit short or long memory. We derive a stochastic simulation algorithm and a statistical inference meth...
Experimental modeling of polymer latex spray coating for producing controlled-release urea
Institute of Scientific and Technical Information of China (English)
Rui Lan; Yonghui Liu; Guanda Wang; Tingjie Wang; Chengyou Kan; Yong Jin
2011-01-01
Spray coating of polymer latex onto fertilizer particles in a fluidized bed for producing controlled-release urea is an environment friendly technology as it does not need any toxic organic solvent.Since the spray coating process in a fluidized bed occurs in the presence of particle collisions,the coating of the particles is random,intermittent and multiple,thus making it difficult to investigate the film formation process.In this paper,an experimental model apparatus was designed and used to investigate the effects of the key factors in the spray coating process.This apparatus reasonably simplified the complex process to avoid particle collisions and randomness in the coating.The intermittent coating in the fluidized bed was modeled by periodic coating and dewatering in the experimental apparatus.A large area film was obtained,and the film permeability was measured.The effects of atomizing gas flow rate,spray rate of latex,solid content of latex and gas temperature on film structure and film permeability were investigated.It was found that water transfer played a dominant role in the spray coating process.
Proposed SPAR Modeling Method for Quantifying Time Dependent Station Blackout Cut Sets
Energy Technology Data Exchange (ETDEWEB)
John A. Schroeder
2010-06-01
Abstract: The U.S. Nuclear Regulatory Commission’s (USNRC’s) Standardized Plant Analysis Risk (SPAR) models and industry risk models take similar approaches to analyzing the risk associated with loss of offsite power and station blackout (LOOP/SBO) events at nuclear reactor plants. In both SPAR models and industry models, core damage risk resulting from a LOOP/SBO event is analyzed using a combination of event trees and fault trees that produce cut sets that are, in turn, quantified to obtain a numerical estimate of the resulting core damage risk. A proposed SPAR method for quantifying the time-dependent cut sets is sometimes referred to as a convolution method. The SPAR method reflects assumptions about the timing of emergency diesel failures, the timing of subsequent attempts at emergency diesel repair, and the timing of core damage that may be different than those often used in industry models. This paper describes the proposed SPAR method.
Parameterizing unconditional skewness in models for financial time series
DEFF Research Database (Denmark)
He, Changli; Silvennoinen, Annastiina; Teräsvirta, Timo
In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. Therefore it is of importance to know what properties a model should possess if it is to accommodate...... unconditional skewness. We consider modelling the unconditional mean and variance using models that respond nonlinearly or asymmetrically to shocks. We investigate the implications of these models on the third-moment structure of the marginal distribution as well as conditions under which the unconditional...
A multivariate heuristic model for fuzzy time-series forecasting.
Huarng, Kun-Huang; Yu, Tiffany Hui-Kuang; Hsu, Yu Wei
2007-08-01
Fuzzy time-series models have been widely applied due to their ability to handle nonlinear data directly and because no rigid assumptions for the data are needed. In addition, many such models have been shown to provide better forecasting results than their conventional counterparts. However, since most of these models require complicated matrix computations, this paper proposes the adoption of a multivariate heuristic function that can be integrated with univariate fuzzy time-series models into multivariate models. Such a multivariate heuristic function can easily be extended and integrated with various univariate models. Furthermore, the integrated model can handle multiple variables to improve forecasting results and, at the same time, avoid complicated computations due to the inclusion of multiple variables.
Finite Time Blowup in a Realistic Food-Chain Model
Parshad, Rana
2013-05-19
We investigate a realistic three-species food-chain model, with generalist top predator. The model based on a modified version of the Leslie-Gower scheme incorporates mutual interference in all the three populations and generalizes several other known models in the ecological literature. We show that the model exhibits finite time blowup in certain parameter range and for large enough initial data. This result implies that finite time blowup is possible in a large class of such three-species food-chain models. We propose a modification to the model and prove that the modified model has globally existing classical solutions, as well as a global attractor. We reconstruct the attractor using nonlinear time series analysis and show that it pssesses rich dynamics, including chaos in certain parameter regime, whilst avoiding blowup in any parameter regime. We also provide estimates on its fractal dimension as well as provide numerical simulations to visualise the spatiotemporal chaos.
Compositional Modeling and Minimization of Time-Inhomogeneous Markov Chains
Han, T.; Katoen, J.P.; Mereacre, A.
2008-01-01
This paper presents a compositional framework for the modeling of interactive continuous-time Markov chains with time-dependent rates, a subclass of communicating piecewise deterministic Markov processes. A poly-time algorithm is presented for computing the coarsest quotient under strong bisimulatio
Modeling stochastic lead times in multi-echelon systems
Diks, E.B.; van der Heijden, Matthijs C.
1997-01-01
In many multi-echelon inventory systems, the lead times are random variables. A common and reasonable assumption in most models is that replenishment orders do not cross, which implies that successive lead times are correlated. However, the process that generates such lead times is usually not well
Combined forecasts from linear and nonlinear time series models
N. Terui (Nobuhiko); H.K. van Dijk (Herman)
1999-01-01
textabstractCombined forecasts from a linear and a nonlinear model are investigated for time series with possibly nonlinear characteristics. The forecasts are combined by a constant coefficient regression method as well as a time varying method. The time varying method allows for a locally (non)line
Modeling Change Over Time: Conceptualization, Measurement, Analysis, and Interpretation
2009-11-12
2007 to 29-11-2008 4. TITLE AND SUBTITLE Modeling Change Over Time: Conceptualization, Measurement, Analysis, and Interpretation 5a. CONTRACT NUMBER...Multilevel Modeling Portal (www.ats.ucla.edu/stat/ mlm /) and the Web site of the Center for Multilevel Modeling (http://multilevel.ioe.ac.uk/index.html
On frequency and time domain models of traveling wave tubes
Théveny, Stéphane; Elskens, Yves
2016-01-01
We discuss the envelope modulation assumption of frequency-domain models of traveling wave tubes (TWTs) and test its consistency with the Maxwell equations. We compare the predictions of usual frequency-domain models with those of a new time domain model of the TWT.
A Model for Industrial Real-Time Systems
DEFF Research Database (Denmark)
Bin Waez, Md Tawhid; Wasowski, Andrzej; Dingel, Juergen;
2015-01-01
Introducing automated formal methods for large industrial real-time systems is an important research challenge. We propose timed process automata (TPA) for modeling and analysis of time-critical systems which can be open, hierarchical, and dynamic. The model offers two essential features for larg...... establish safety and reachability properties of TPA by reduction to solving timed games. To mitigate the state-space explosion problem, an automated state-space reduction technique using compositional reasoning and aggressive abstractions is also proposed.......Introducing automated formal methods for large industrial real-time systems is an important research challenge. We propose timed process automata (TPA) for modeling and analysis of time-critical systems which can be open, hierarchical, and dynamic. The model offers two essential features for large...... industrial systems: (i) compositional modeling with reusable designs for different contexts, and (ii) an automated state-space reduction technique. Timed process automata model dynamic networks of continuous-time communicating control processes which can activate other processes. We show how to automatically...
Bayesian dynamic modeling of time series of dengue disease case counts.
Directory of Open Access Journals (Sweden)
Daniel Adyro Martínez-Bello
2017-07-01
Full Text Available The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease
Modelling and Formal Verification of Timing Aspects in Large PLC Programs
Fernandez Adiego, B; Blanco Vinuela, E; Tournier, J-C; Gonzalez Suarez, V M; Blech, J O
2014-01-01
One of the main obstacle that prevents model checking from being widely used in industrial control systems is the complexity of building formal models out of PLC programs, especially when timing aspects need to be integrated. This paper brings an answer to this obstacle by proposing a methodology to model and verify timing aspects of PLC programs. Two approaches are proposed to allow the users to balance the trade-off between the complexity of the model, i.e. its number of states, and the set of specifications possible to be verified. A tool supporting the methodology which allows to produce models for different model checkers directly from PLC programs has been developed. Verification of timing aspects for real-life PLC programs are presented in this paper using NuSMV.
Bone invading NSCLC cells produce IL-7: mice model and human histologic data
Directory of Open Access Journals (Sweden)
Quarto Rodolfo
2010-01-01
Full Text Available Abstract Background Bone metastases are a common and dismal consequence of lung cancer that is a leading cause of death. The role of IL-7 in promoting bone metastases has been previously investigated in NSCLC, but many aspects remain to be disclosed. To further study IL-7 function in bone metastasis, we developed a human-in-mice model of bone aggression by NSCLC and analyzed human bone metastasis biopsies. Methods We used NOD/SCID mice implanted with human bone. After bone engraftment, two groups of mice were injected subcutaneously with A549, a human NSCLC cell line, either close or at the contralateral flank to the human bone implant, while a third control group did not receive cancer cells. Tumor and bone vitality and IL-7 expression were assessed in implanted bone, affected or not by A549. Serum IL-7 levels were evaluated by ELISA. IL-7 immunohistochemistry was performed on 10 human bone NSCLC metastasis biopsies for comparison. Results At 12 weeks after bone implant, we observed osteogenic activity and neovascularization, confirming bone vitality. Tumor aggressive cells implanted close to human bone invaded the bone tissue. The bone-aggressive cancer cells were positive for IL-7 staining both in the mice model and in human biopsies. Higher IL-7 serum levels were found in mice injected with A549 cells close to the bone implant compared to mice injected with A549 cells in the flank opposite to the bone implant. Conclusions We demonstrated that bone-invading cells express and produce IL-7, which is known to promote osteoclast activation and osteolytic lesions. Tumor-bone interaction increases IL-7 production, with an increase in IL-7 serum levels. The presented mice model of bone invasion by contiguous tumor is suitable to study bone-tumor cell interaction. IL-7 plays a role in the first steps of metastatic process.
Mossessian, George
2011-01-01
A quantitative study of the observable radio signatures of the sausage, kink, and torsional MHD oscillation modes in flaring coronal loops is performed. Considering first non-zero order effect of these various MHD oscillation modes on the radio source parameters such as magnetic field, line of sight, plasma density and temperature, electron distribution function, and the source dimensions, we compute time dependent radio emission (spectra and light curves). The radio light curves (of both flux density and degree of polarization) at all considered radio frequencies are than quantified in both time domain (via computation of the full modulation amplitude as a function of frequency) and in Fourier domain (oscillation spectra, phases, and partial modulation amplitude) to form the signatures specific to a particular oscillation mode and/or source parameter regime. We found that the parameter regime and the involved MHD mode can indeed be distinguished using the quantitative measures derived in the modeling. We app...
Rodríguez Miranda, Á.; Valle Melón, J. M.
2017-02-01
Three-dimensional models with photographic textures have become a usual product for the study and dissemination of elements of heritage. The interest for cultural heritage also includes evolution along time; therefore, apart from the 3D models of the current state, it is interesting to be able to generate models representing how they were in the past. To that end, it is necessary to resort to archive information corresponding to the moments that we want to visualize. This text analyses the possibilities of generating 3D models of surfaces with photographic textures from old collections of analog negatives coming from works of terrestrial stereoscopic photogrammetry of historic buildings. The case studies presented refer to the geometric documentation of a small hermitage (done in 1996) and two sections of a wall (year 2000). The procedure starts with the digitization of the film negatives and the processing of the images generated, after which a combination of different methods for 3D reconstruction and texture wrapping are applied: techniques working simultaneously with several images (such as the algorithms of Structure from Motion - SfM) and single image techniques (such as the reconstruction based on vanishing points). Then, the features of the obtained models are described according to the geometric accuracy, completeness and aesthetic quality. In this way, it is possible to establish the real applicability of the models in order to be useful for the aforementioned historical studies and dissemination purposes. The text also wants to draw attention to the importance of preserving the documentary heritage available in the collections of negatives in archival custody and to the increasing difficulty of using them due to: (1) problems of access and physical conservation, (2) obsolescence of the equipment for scanning and stereoplotting and (3) the fact that the software for processing digitized photographs is discontinued.
He, Yuning
2015-01-01
Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.
van der Heijden, Sven; Callau Poduje, Ana; Müller, Hannes; Shehu, Bora; Haberlandt, Uwe; Lorenz, Manuel; Wagner, Sven; Kunstmann, Harald; Müller, Thomas; Mosthaf, Tobias; Bárdossy, András
2015-04-01
For the design and operation of urban drainage systems with numerical simulation models, long, continuous precipitation time series with high temporal resolution are necessary. Suitable observed time series are rare. As a result, intelligent design concepts often use uncertain or unsuitable precipitation data, which renders them uneconomic or unsustainable. An expedient alternative to observed data is the use of long, synthetic rainfall time series as input for the simulation models. Within the project SYNOPSE, several different methods to generate synthetic precipitation data for urban drainage modelling are advanced, tested, and compared. The presented study compares four different approaches of precipitation models regarding their ability to reproduce rainfall and runoff characteristics. These include one parametric stochastic model (alternating renewal approach), one non-parametric stochastic model (resampling approach), one downscaling approach from a regional climate model, and one disaggregation approach based on daily precipitation measurements. All four models produce long precipitation time series with a temporal resolution of five minutes. The synthetic time series are first compared to observed rainfall reference time series. Comparison criteria include event based statistics like mean dry spell and wet spell duration, wet spell amount and intensity, long term means of precipitation sum and number of events, and extreme value distributions for different durations. Then they are compared regarding simulated discharge characteristics using an urban hydrological model on a fictitious sewage network. First results show a principal suitability of all rainfall models but with different strengths and weaknesses regarding the different rainfall and runoff characteristics considered.
Models for Pooled Time-Series Cross-Section Data
Directory of Open Access Journals (Sweden)
Lawrence E Raffalovich
2015-07-01
Full Text Available Several models are available for the analysis of pooled time-series cross-section (TSCS data, defined as “repeated observations on fixed units” (Beck and Katz 1995. In this paper, we run the following models: (1 a completely pooled model, (2 fixed effects models, and (3 multi-level/hierarchical linear models. To illustrate these models, we use a Generalized Least Squares (GLS estimator with cross-section weights and panel-corrected standard errors (with EViews 8 on the cross-national homicide trends data of forty countries from 1950 to 2005, which we source from published research (Messner et al. 2011. We describe and discuss the similarities and differences between the models, and what information each can contribute to help answer substantive research questions. We conclude with a discussion of how the models we present may help to mitigate validity threats inherent in pooled time-series cross-section data analysis.
Time representation in reinforcement learning models of the basal ganglia
Directory of Open Access Journals (Sweden)
Samuel Joseph Gershman
2014-01-01
Full Text Available Reinforcement learning models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still no theoretical consensus about what kind of time representation is used by the basal ganglia. We review several theoretical accounts and their supporting evidence. We then discuss the relationship between reinforcement learning models and the timing mechanisms that have been attributed to the basal ganglia. We hypothesize that a single computational system may underlie both reinforcement learning and interval timing—the perception of duration in the range of seconds to hours. This hypothesis, which extends earlier models by incorporating a time-sensitive action selection mechanism, may have important implications for understanding disorders like Parkinson's disease in which both decision making and timing are impaired.
Long memory of financial time series and hidden Markov models with time-varying parameters
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
facts have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time-varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared...... daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step predictions....
Modeling and Real-Time Simulation of UPFC
Kimura, Misao; Takahashi, Choei; Kishibe, Hideto; Miyazaki, Yasuyuki; Noro, Yasuhiro; Iio, Naotaka
We have developed a digital real time simulator of Power Electronics Controllers, so called FACTS (Flexible AC Transmission Systems) Controllers and/or Custom Power by using MATLABTM/SIMULINKTM and dSPACETM System. This paper describes the modeling and the calculation accuracy of a UPFC (Unified Power Flow Controller) model. Hence the developed simulator operates at a large time step, in order to improve simulation accuracy, a correction processing of the switching delay is implemented into the UPFC model. Calculation accuracy of the real time UPFC model is the same level as EMTDCTM results. We confirm stable operation of the developed UPFC model with connecting a commercial real time digital simulator (RTDSTM).
A traffic model of optical networks based on time-space complexity and traffic grooming
Institute of Scientific and Technical Information of China (English)
Zhao Yongli; Zhang Jie; Han Dahai; Wang Lei; Chen Xiuzhong; Gu Wanyi
2009-01-01
This paper researched the traffic of optical networks in time-space complexity, proposed a novel traffic model for complex optical networks based on traffic grooming, designed a traffic generator GTS (generator based on time and space) with "centralized + distributed" idea, and then made a simulation in C language. Experiments results show that GTS can produce the virtual network topology which can change dynamically with the characteristic of scaling-free network. GTS can also groom the different traffic and trigger them under real-time or scheduling mechanisms, generating different optical connections. This traffic model is convenient for the simulation of optical networks considering the traffic complexity.
Time-symmetric universe model and its observational implication
Energy Technology Data Exchange (ETDEWEB)
Futamase, T.; Matsuda, T.
1987-08-01
A time-symmetric closed-universe model is discussed in terms of the radiation arrow of time. The time symmetry requires the occurrence of advanced waves in the recontracting phase of the Universe. We consider the observational consequences of such advanced waves, and it is shown that a test observer in the expanding phase can observe a time-reversed image of a source of radiation in the future recontracting phase.
Pasko, V. P.
2011-12-01
It is well established by now that large charge transfers between cloud and ground in positive cloud-to-ground lightning discharges (+CGs) can lead to transient electric field enhancements at mesospheric and lower ionospheric altitudes. In these events the electric field can exceed the conventional breakdown field and lead to formation of transient luminous events referred to as sprites and sprite halos [e.g., Qin et al., JGR, 116, A06305, 2011, and references therein]. Stanley and Heavner [Proc. 12th International Conference on Atmospheric Electricity, Versailles, France, 2003] reported that the large and rapid charge transfer of +CGs producing sprites can also initiate upward positive leaders from tall structures. These authors also presented data analysis indicating that structures with >400 m height have a significantly enhanced probability of launching upward positive leaders that may culminate in a -CG return stroke to the structure. The effect can be understood by considering the field intensification at the top of the tall structure combined with fast application of the field preventing formation and shielding effects of ion corona [Brook et al., JGR, 66, 3967, 1961]. In the present work we utilize the most recent modeling approaches developed at Penn State [e.g., Riousset et al., JGR, 115, A00E10, 2010] to quantify the conditions leading to initiation of positive leaders from tall structures following sprite-producing +CGs. Experiments show that the streamer zone transforms into leader when voltage drop along the streamer zone exceeds 400 kV [e.g., Aleksandrov et al., J. Phys. D: Appl. Phys., 38, 1225, 2005]. For a formed leader half of the voltage drops in the streamer zone, and another half in free space ahead of the streamer zone [Bazelyan and Raizer, Lightning physics and lightning protection, p. 62, 2000]. In our analysis therefore we assume that minimum voltage at the tip of the tower should exceed 800 kV for sustainment of upward propagating leader
Energy Technology Data Exchange (ETDEWEB)
Rucci, A.; Vasco, D.W.; Novali, F.
2010-04-01
Deformation in the overburden proves useful in deducing spatial and temporal changes in the volume of a producing reservoir. Based upon these changes we estimate diffusive travel times associated with the transient flow due to production, and then, as the solution of a linear inverse problem, the effective permeability of the reservoir. An advantage an approach based upon travel times, as opposed to one based upon the amplitude of surface deformation, is that it is much less sensitive to the exact geomechanical properties of the reservoir and overburden. Inequalities constrain the inversion, under the assumption that the fluid production only results in pore volume decreases within the reservoir. We apply the formulation to satellite-based estimates of deformation in the material overlying a thin gas production zone at the Krechba field in Algeria. The peak displacement after three years of gas production is approximately 0.5 cm, overlying the eastern margin of the anticlinal structure defining the gas field. Using data from 15 irregularly-spaced images of range change, we calculate the diffusive travel times associated with the startup of a gas production well. The inequality constraints are incorporated into the estimates of model parameter resolution and covariance, improving the resolution by roughly 30 to 40%.
A Multiclass, Multimodal Dynamic Traffic Assignment Model with Departure Time
Directory of Open Access Journals (Sweden)
Meng Meng
2014-01-01
Full Text Available The paper develops a multiclass, multimodal dynamic traffic equilibrium model with consideration of the departure time choice problem. Travelers choose the departure time and the route simultaneously with a Logit-based structure. The route travel cost is a summation of travel time and schedule delay which is associated with arrival time at destination. In addition, the travelers are classified into three groups according to their value of time. A variational inequality (VI formulation is proposed based on the equilibrium conditions. Two examples are given to testify the effectiveness of the model and the solution algorithm. The model can give the optimal travel route as well as the best departure time, which would contribute to traffic control and dynamic route guidance.
Dark energy models with time-dependent gravitational constant
Ray, S; Ray, Saibal; Mukhopadhyay, Utpal
2005-01-01
Two phenomenological models of $\\Lambda$, viz. $\\Lambda \\sim (\\dot a/a)^2$ and $\\Lambda \\sim \\ddot a/a$ are studied under the assumption that $G$ is a time-variable parameter. Both models show that $G$ is inversely proportional to time as suggested earlier by others including Dirac. The models considered here can be matched with observational results by properly tuning the parameters of the models. Our analysis shows that $\\Lambda \\sim \\ddot a/a$ model corresponds to a repulsive situation and hence correlates with the present status of the accelerating Universe. The other model $\\Lambda \\sim (\\dot a/a)^2$ is, in general, attractive in nature. Moreover, it is seen that due to the combined effect of time-variable $\\Lambda$ and $G$ the Universe evolved with acceleration as well as deceleration. This later one indicates a Big Crunch.
Dark Energy Models with a Time-Dependent Gravitational Constant
Ray, Saibal; Mukhopadhyay, Utpal; Choudhury, S. B. Dutta
Two phenomenological models of Λ, viz. Λ ˜ (˙ a/a)2 and Λ ˜ ḋ a/a, are studied under the assumption that G is a time-variable parameter. Both models show that G is inversely proportional to time, as suggested earlier by others, including Dirac. The models considered here can be matched with observational results by properly tuning the parameters of the models. Our analysis shows that the Λ ˜ ḋ a/a model corresponds to a repulsive situation and hence correlates with the present status of the accelerating Universe. The other model, Λ ˜ (˙ a/a)2, is in general attractive in nature. Moreover, it is seen that due to the combined effect of time-variable Λ and G the Universe evolved with acceleration as well as deceleration. Deceleration indicates a "big crunch".
Continuous-time discrete-space models for animal movement
Hanks, Ephraim M.; Hooten, Mevin B.; Alldredge, Mat W.
2015-01-01
The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.
Real-Time Statistical Modeling of Blood Sugar.
Otoom, Mwaffaq; Alshraideh, Hussam; Almasaeid, Hisham M; López-de-Ipiña, Diego; Bravo, José
2015-10-01
Diabetes is considered a chronic disease that incurs various types of cost to the world. One major challenge in the control of Diabetes is the real time determination of the proper insulin dose. In this paper, we develop a prototype for real time blood sugar control, integrated with the cloud. Our system controls blood sugar by observing the blood sugar level and accordingly determining the appropriate insulin dose based on patient's historical data, all in real time and automatically. To determine the appropriate insulin dose, we propose two statistical models for modeling blood sugar profiles, namely ARIMA and Markov-based model. Our experiment used to evaluate the performance of the two models shows that the ARIMA model outperforms the Markov-based model in terms of prediction accuracy.
NASA AVOSS Fast-Time Wake Prediction Models: User's Guide
Ahmad, Nash'at N.; VanValkenburg, Randal L.; Pruis, Matthew
2014-01-01
The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.
Finite-frequency model reduction of continuous-time switched linear systems with average dwell time
Ding, Da-Wei; Du, Xin
2016-11-01
This paper deals with the model reduction problem of continuous-time switched linear systems with finite-frequency input signals. The objective of the paper is to propose a finite-frequency model reduction method for such systems. A finite-frequency ? performance index is first defined in frequency domain, and then a finite-frequency performance analysis condition is derived by Parseval's theorem. Combined with the average dwell time approach, sufficient conditions for the existence of exponentially stable reduced-order models are derived. An algorithm is proposed to construct the desired reduced-order models. The effectiveness of the proposed method is illustrated by a numerical example.
Space-Time Structures from IIB Matrix Model
Aoki, H; Kawai, H; Kitazawa, Y; Tada, T
1998-01-01
We derive a long distance effective action for space-time coordinates from a IIB matrix model. It provides us an effective tool to study the structures of space-time. We prove the finiteness of the theory for finite $N$ to all orders of the perturbation theory. Space-time is shown to be inseparable and its dimensionality is dynamically determined. The IIB matrix model contains a mechanism to ensure the vanishing cosmological constant which does not rely on the manifest supersymmetry. We discuss possible mechanisms to obtain realistic dimensionality and gauge groups from the IIB matrix model.
Modeling Microwave Structures in Time Domain Using Laguerre Polynomials
Directory of Open Access Journals (Sweden)
Z. Raida
2006-09-01
Full Text Available The paper is focused on time domain modeling of microwave structures by the method of moments. Two alternative schemes with weighted Laguerre polynomials are presented. Thanks to their properties, these schemes are free of late time oscillations. Further, the paper is aimed to effective and accurate evaluation of Green's functions integrals within these schemes. For this evaluation, a first- and second-order polynomial approximation is developed. The last part of the paper deals with modeling microstrip structures in the time domain. Conditions of impedance matching are derived, and the proposed approach is verified by modeling a microstrip filter.
Gaibani, Paolo; Galea, Anna; Fagioni, Marco; Ambretti, Simone; Sambri, Vittorio; Landini, Maria Paola
2016-10-01
We evaluated a real-time single-peak (11.109-Da) detection assay based on matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) for the identification of Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae Our results demonstrated that the 11.109-Da peak was detected in 88.2% of the KPC producers. Analysis of blaKPC-producing K. pneumoniae showed that the gene encoding the 11.109-Da protein was commonly (97.8%) associated with the Tn4401a isoform.
Galea, Anna; Fagioni, Marco; Ambretti, Simone; Sambri, Vittorio; Landini, Maria Paola
2016-01-01
We evaluated a real-time single-peak (11.109-Da) detection assay based on matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) for the identification of Klebsiella pneumoniae carbapenemase (KPC)-producing K. pneumoniae. Our results demonstrated that the 11.109-Da peak was detected in 88.2% of the KPC producers. Analysis of blaKPC-producing K. pneumoniae showed that the gene encoding the 11.109-Da protein was commonly (97.8%) associated with the Tn4401a isoform. PMID:27413192
Quality Quandaries- Time Series Model Selection and Parsimony
DEFF Research Database (Denmark)
Bisgaard, Søren; Kulahci, Murat
2009-01-01
Some of the issues involved in selecting adequate models for time series data are discussed using an example concerning the number of users of an Internet server. The process of selecting an appropriate model is subjective and requires experience and judgment. The authors believe an important...... consideration in model selection should be parameter parsimony. They favor the use of parsimonious mixed ARMA models, noting that research has shown that a model building strategy that considers only autoregressive representations will lead to non-parsimonious models and to loss of forecasting accuracy....
Quality Quandaries- Time Series Model Selection and Parsimony
DEFF Research Database (Denmark)
Bisgaard, Søren; Kulahci, Murat
2009-01-01
Some of the issues involved in selecting adequate models for time series data are discussed using an example concerning the number of users of an Internet server. The process of selecting an appropriate model is subjective and requires experience and judgment. The authors believe an important...... consideration in model selection should be parameter parsimony. They favor the use of parsimonious mixed ARMA models, noting that research has shown that a model building strategy that considers only autoregressive representations will lead to non-parsimonious models and to loss of forecasting accuracy....
A biologically plausible model of time-scale invariant interval timing.
Almeida, Rita; Ledberg, Anders
2010-02-01
The temporal durations between events often exert a strong influence over behavior. The details of this influence have been extensively characterized in behavioral experiments in different animal species. A remarkable feature of the data collected in these experiments is that they are often time-scale invariant. This means that response measurements obtained under intervals of different durations coincide when plotted as functions of relative time. Here we describe a biologically plausible model of an interval timing device and show that it is consistent with time-scale invariant behavior over a substantial range of interval durations. The model consists of a set of bistable units that switch from one state to the other at random times. We first use an abstract formulation of the model to derive exact expressions for some key quantities and to demonstrate time-scale invariance for any range of interval durations. We then show how the model could be implemented in the nervous system through a generic and biologically plausible mechanism. In particular, we show that any system that can display noise-driven transitions from one stable state to another can be used to implement the timing device. Our work demonstrates that a biologically plausible model can qualitatively account for a large body of data and thus provides a link between the biology and behavior of interval timing.
Modeling of Incubation Time for Austenite to Ferrite Phase Transformation
Institute of Scientific and Technical Information of China (English)
ZHOU Xiao-guang; LIU Zhen-yu; WU Di; WANG Wei; JIAO Si-hai
2006-01-01
On the basis of the classical nucleation theory, a new model of incubation time for austenite to ferrite transformation has been developed, in which the effect of deformation on austenite has been taken into consideration. To prove the precision of modeling, ferrite transformation starting temperature (Ar3) has been calculated using the Scheil′s additivity rule, and the Ar3 values were measured using a Gleeble 1500 thermomechanical simulator. The Ar3 values provided by the modeling method coincide with the measured ones, indicating that the model is precise in predicting the incubation time for austenite to ferrite transformation in hot deformed steels.
Rodrigues, E V; Daher, R F; Dos Santos, A; Vivas, M; Machado, J C; Gravina, G do A; de Souza, Y P; Vidal, A K; Rocha, A Dos S; Freitas, R S
2017-05-18
Brazil has great potential to produce bioenergy since it is located in a tropical region that receives high incidence of solar energy and presents favorable climatic conditions for such purpose. However, the use of bioenergy in the country is below its productivity potential. The aim of the current study was to select full-sib progenies and families of elephant grass (Pennisetum purpureum S.) to optimize phenotypes relevant to bioenergy production through mixed models (REML/BLUP). The circulating diallel-based crossing of ten elephant grass genotypes was performed. An experimental design using the randomized block methodology, with three repetitions, was set to assess both the hybrids and the parents. Each plot comprised 14-m rows, 1.40 m spacing between rows, and 1.40 m spacing between plants. The number of tillers, plant height, culm diameter, fresh biomass production, dry biomass rate, and the dry biomass production were assessed. Genetic-statistical analyses were performed through mixed models (REML/BLUP). The genetic variance in the assessed families was explained through additive genetic effects and dominance genetic effects; the dominance variance was prevalent. Families such as Capim Cana D'África x Guaçu/I.Z.2, Cameroon x Cuba-115, CPAC x Cuba-115, Cameroon x Guaçu/I.Z.2, and IAC-Campinas x CPAC showed the highest dry biomass production. The family derived from the crossing between Cana D'África and Guaçu/I.Z.2 showed the largest number of potential individuals for traits such as plant height, culm diameter, fresh biomass production, dry biomass production, and dry biomass rate. The individual 5 in the family Cana D'África x Guaçu/I.Z.2, planted in blocks 1 and 2, showed the highest dry biomass production.
Micov, Ana; Tomić, Maja; Pecikoza, Uroš; Ugrešić, Nenad; Stepanović-Petrović, Radica
2015-07-01
Painful diabetic neuropathy is difficult to treat. Single analgesics often have insufficient efficacy and poor tolerability. Combination therapy may therefore be of particular benefit, because it might provide optimal analgesia with fewer adverse effects. This study aimed to examine the type of interaction between levetiracetam, a novel anticonvulsant with analgesic properties, and commonly used analgesics (ibuprofen, aspirin and paracetamol) in a mouse model of painful diabetic neuropathy. Diabetes was induced in C57BL/6 mice with a single high dose of streptozotocin, applied intraperitoneally (150 mg/kg). Thermal (tail-flick test) and mechanical (electronic von Frey test) nociceptive thresholds were measured before and three weeks after diabetes induction. The antinociceptive effects of orally administered levetiracetam, analgesics, and their combinations were examined in diabetic mice that developed thermal/mechanical hypersensitivity. In combination experiments, the drugs were co-administered in fixed-dose fractions of single drug ED50 and the type of interaction was determined by isobolographic analysis. Levetiracetam (10-100 mg/kg), ibuprofen (2-50 mg/kg), aspirin (5-75 mg/kg), paracetamol (5-100 mg/kg), and levetiracetam-analgesic combinations produced significant, dose-dependent antinociceptive effects in diabetic mice in both tests. In the tail-flick test, isobolographic analysis revealed 15-, and 19-fold reduction of doses of both drugs in the combination of levetiracetam with aspirin/ibuprofen, and paracetamol, respectively. In the von Frey test, approximately 7- and 9-fold reduction of doses of both drugs was detected in levetiracetam-ibuprofen and levetiracetam-aspirin/levetiracetam-paracetamol combinations, respectively. These results show synergism between levetiracetam and ibuprofen/aspirin/paracetamol in a model of painful diabetic neuropathy and might provide a useful approach to the treatment of patients suffering from painful diabetic neuropathy.
Reaction kinetic model for a recent co-produced water treatment technology
Institute of Scientific and Technical Information of China (English)
Abdulwahab M Ali Tuwati; Maohong Fan; Mark A. Bentley
2011-01-01
With the increasing demand for fossil based energy and implementation of progressively strict environmental pollution control standards, treatment of a large amount of co-produced waters (CPWs) from fossil based energy production has become increasingly important.Removal of bicarbonate with H2SO4 has been recently studied as a simple and cost-effective method to decrease the alkalinity of CPWs.The present work investigates the kinetics of the reaction between H2SO4 and NaHCO3, which could provide the base for scaling-up the CPW treatment technology.Based on the measured quantity change of the CO2 gas generated from the reaction between H2SO4 and NaHCO3 with time under specified initial reaction conditions, the reaction orders with respect to H2SO4 and NaHCO3 were determined.Experiments were also conducted within the temperature of 15-30℃ to find various global rate coefficients of the reaction to calculate the activation energy and the pre-exponential factor of the empirical Arrhenius form of the bicarbonate removal reaction,which are 197.7 kJ/mol and 3.13× 1034 (mol-3.7×L3.7×sec-1), respectively.
Mastitis Pathogens with High Virulence in a Mouse Model Produce a Distinct Cytokine Profile In Vivo
Johnzon, Carl-Fredrik; Artursson, Karin; Söderlund, Robert; Guss, Bengt; Rönnberg, Elin; Pejler, Gunnar
2016-01-01
Mastitis is a serious medical condition of dairy cattle. Here, we evaluated whether the degree of virulence of mastitis pathogens in a mouse model can be linked to the inflammatory response that they provoke. Clinical isolates of Staphylococcus aureus (S. aureus) (strain 556 and 392) and Escherichia coli (E. coli) (676 and 127), and laboratory control strains [8325-4 (S. aureus) and MG1655 (E. coli)], were injected i.p. into mice, followed by the assessment of clinical scores and inflammatory parameters. As judged by clinical scoring, E. coli 127 exhibited the largest degree of virulence among the strains. All bacterial strains induced neutrophil recruitment. However, whereas E. coli 127 induced high peritoneal levels of CXCL1, G-CSF, and CCL2, strikingly lower levels of these were induced by the less virulent bacterial strains. High concentrations of these compounds were also seen in blood samples taken from animals infected with E. coli 127, suggesting systemic inflammation. Moreover, the levels of CXCL1 and G-CSF, both in the peritoneal fluid and in plasma, correlated with clinical score. Together, these findings suggest that highly virulent clinical mastitis isolates produce a distinct cytokine profile that shows a close correlation with the severity of the bacterial infection. PMID:27713743
A REGIONAL ANALYSIS OF THE USE OF TRACTORS ON MODEL FARMS PRODUCING ENERGY CROPS
Directory of Open Access Journals (Sweden)
Benedykt Pepliński
2015-06-01
Full Text Available The potential area of energy crops in Poland is estimated at 1.0–4.5 million ha. The decrease in the prices of energy reduces the high pressure to cut the costs of biomass production. The aim of this study is an analysis of the use of tractors on model farms producing energy crops, which have different areas, intensity of production and quality of soils from different regions of Poland. The use of tractors increased along with the farm area, the soil quality and production intensity. The use of tractors on the smallest farms is low, so they should buy old tractors. A large share of crops for biogas leads to the situation where it takes 20–30 years of work for tractors to achieve full wear of 12,000 hours on farms with 130 ha of farmland, whereas it takes only 8–14 years on farms with 600 and 1500 ha of farmland. Regional differences in the use of tractors increased along with the farm area from 4.7–5.7% on the smallest farms to 10.1–14.8% on the largest farms.
Empirical modeling of plasma clouds produced by the Metal Oxide Space Clouds experiment
Pedersen, Todd R.; Caton, Ronald G.; Miller, Daniel; Holmes, Jeffrey M.; Groves, Keith M.; Sutton, Eric
2017-05-01
The Advanced Research Project Agency (ARPA) Long-Range Tracking And Instrumentation Radar (ALTAIR) radar at Kwajalein Atoll was used in incoherent scatter mode to measure plasma densities within two artificial clouds created by the Air Force Research Laboratory (AFRL) Metal Oxide Space Clouds (MOSC) experiment in May 2013. Optical imager, ionosonde, and ALTAIR measurements were combined to create 3-D empirical descriptions of the plasma clouds as a function of time, which match the radar measurements to within 15%. The plasma clouds closely track the location of the optical clouds, and the best fit plasma cloud widths are generally consistent with isotropic neutral diffusion. Cloud plasma densities decreased as a power of time, with exponents between -0.5 and -1.0, or much more slowly than the -1.5 predicted by diffusion. These exponents and estimates of total ion number from integration through the model volume are consistent with a scenario of slow ionization and a gradually increasing total number of ions with time, reaching a net ionization fraction of 20% after approximately half an hour. These robust representations of the plasma density are being used to study impacts of the artificial clouds on the dynamics of the background ionosphere and on RF propagation.
A Real-time Data Model Based on Temporal Data
Institute of Scientific and Technical Information of China (English)
ZHANG Xiao-fang; LIU Yun-sheng
2006-01-01
Real-time database systems contain not only transaction timing constraints, but also data timing constraints. This paper discusses the temporal characteristics of data in real-time databases and offers a definition of absolute and relative temporal consistency. In real-time database systems, it is often the case that the policies of transaction schedules only consider the deadline of real-time transactions, making it insufficient to ensure temporal correctness of transactions. A policy is given by considering both the deadlines of transactions and the "data deadline" to schedule real-time transactions. A real-time relational data model and a real-time relational algebra based on the characteristics of temporal data are also proposed. In this model, the temporal data has not only corresponding values, but also validity intervals corresponding to the data values. At the same time, this model is able to keep historical data values. When validity interval of a relation is[NOW,NOW], real-time relational algebra will transform to traditional relational algebra.
El Salvador - Education Quality, Full-Time Inclusive Model
Millennium Challenge Corporation — Mathematica Policy Research (MPR) was contracted by MCC to conduct an impact evaluation of the Integrated Systems of Full-Time Inclusive Schools model (SI-EITP for...
Characterization of Models for Time-Dependent Behavior of Soils
DEFF Research Database (Denmark)
Liingaard, Morten; Augustesen, Anders; Lade, Poul V.
2004-01-01
Different classes of constitutive models have been developed to capture the time-dependent viscous phenomena ~ creep, stress relaxation, and rate effects ! observed in soils. Models based on empirical, rheological, and general stress-strain-time concepts have been studied. The first part...... is a review of the empirical relations, which apply only to problems of specific boundary conditions and frequently involve natural time alone. The second part deals with different rheological models used for describing the viscous effects in the field of solid mechanics. The rheological models are typically...... developed for metals and steel but are, to some extent, used to characterize time effects in geomaterials. The third part is a review of constitutive laws that describe not only viscous effects but also the inviscid ( rate-independent) behavior of soils, in principle, under any possible loading condition...
Time Aquatic Resources Modeling and Analysis Program (STARMAP)
Federal Laboratory Consortium — Colorado State University has received funding from the U.S. Environmental Protection Agency (EPA) for its Space-Time Aquatic Resources Modeling and Analysis Program...
Study on the Bus Real-time Dispatching Model
Institute of Scientific and Technical Information of China (English)
YingZou; JianguoLi; JianhuaHuang; ZhenminTang
2004-01-01
The real-time dispatching model on bus system is studied in this article. Realtime dispatching can resume the planned schedule quickly, and then to ensure the reliability of the public transport service and to well raise the service quality.
Adaptive time-variant models for fuzzy-time-series forecasting.
Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching
2010-12-01
A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.
Nonlinear time reversal of classical waves: experiment and model.
Frazier, Matthew; Taddese, Biniyam; Xiao, Bo; Antonsen, Thomas; Ott, Edward; Anlage, Steven M
2013-12-01
We consider time reversal of electromagnetic waves in a closed, wave-chaotic system containing a discrete, passive, harmonic-generating nonlinearity. An experimental system is constructed as a time-reversal mirror, in which excitations generated by the nonlinearity are gathered, time-reversed, transmitted, and directed exclusively to the location of the nonlinearity. Here we show that such nonlinear objects can be purely passive (as opposed to the active nonlinearities used in previous work), and we develop a higher data rate exclusive communication system based on nonlinear time reversal. A model of the experimental system is developed, using a star-graph network of transmission lines, with one of the lines terminated by a model diode. The model simulates time reversal of linear and nonlinear signals, demonstrates features seen in the experimental system, and supports our interpretation of the experimental results.
Modeling Persistence In Hydrological Time Series Using Fractional Differencing
Hosking, J. R. M.
1984-12-01
The class of autoregressive integrated moving average (ARIMA) time series models may be generalized by permitting the degree of differencing d to take fractional values. Models including fractional differencing are capable of representing persistent series (d > 0) or short-memory series (d = 0). The class of fractionally differenced ARIMA processes provides a more flexible way than has hitherto been available of simultaneously modeling the long-term and short-term behavior of a time series. In this paper some fundamental properties of fractionally differenced ARIMA processes are presented. Methods of simulating these processes are described. Estimation of the parameters of fractionally differenced ARIMA models is discussed, and an approximate maximum likelihood method is proposed. The methodology is illustrated by fitting fractionally differenced models to time series of streamflows and annual temperatures.
Models of G time variations in diverse dimensions
Institute of Scientific and Technical Information of China (English)
Vitaly N. MELNIKOV
2009-01-01
A review of different cosmological models n diverse dimensions leading to a relatively small time ariation in the effective gravitational constant G is pre- ented. Among them: the 4-dimensional (4-D) gen- ral scalar-tensor model, the multidimensional vacuum odel with two curved Einstein spaces, the multidimen- ional model with the multicomponent anisotropic "per- ect fluid", the S-brane model with scalar fields and two orm fields, etc. It is shown that there exist different ossible ways of explaining relatively small time varia- ions of the effective gravitational constant G compat- ble with present cosmological data (e.g. Acceleration): -dimensional scalar-tensor theories or multidimensional osmological models with different matter sources. The xperimental bounds on G may be satisfied either in ome restricted interval or for all allowed values of the ynchronous time variable.
Modelling Social-Technical Attacks with Timed Automata
DEFF Research Database (Denmark)
David, Nicolas; David, Alexandre; Hansen, Rene Rydhof
2015-01-01
in our model and perform analysis and simulation of both model and attack, revealing details about the specific interaction between attacker and victim. Using timed automata also allows for intuitive modelling of systems, in which quantities like time and cost can be easily added and analysed.......Attacks on a system often exploit vulnerabilities that arise from human behaviour or other human activity. Attacks of this type, so-called socio-technical attacks, cover everything from social engineering to insider attacks, and they can have a devastating impact on an unprepared organisation....... In this paper we develop an approach towards modelling socio-technical systems in general and socio-technical attacks in particular, using timed automata and illustrate its application by a complex case study. Thanks to automated model checking and automata theory, we can automatically generate possible attacks...
Time domain modeling of tunable response of graphene
DEFF Research Database (Denmark)
Prokopeva, Ludmila; Emani, Naresh K.; Boltasseva, Alexandra
2013-01-01
We present a causal numerical model for time domain simulations of the optical response of graphene. The dielectric function is approximated with a conductivity term, a Drude term and a number of the critical points terms.......We present a causal numerical model for time domain simulations of the optical response of graphene. The dielectric function is approximated with a conductivity term, a Drude term and a number of the critical points terms....
THE DLSTRIBOTED MCU MODEL FOR SYNCHRONOUS REAL-TIME TELETEACHING
Institute of Scientific and Technical Information of China (English)
刘均; 李人厚; 郑庆华
2004-01-01
Aiming at issues on multimedia communication in synchronous real-time teleteaching (SRT) systems over IP network, a 4-tuple structural mode of multimedia communication is proposed in the paper, and an SRT-oriented distributed MCU model is built according to the mode. Moreover, the mechanism of multicast communication across subnets is discussed. The distributed MCU model has been applied successfully in our interactive synchronous real-time telesteaching system RealClass and has shown good extendibility in operation.
Integral-Value Models for Outcomes over Continuous Time
DEFF Research Database (Denmark)
Harvey, Charles M.; Østerdal, Lars Peter
Models of preferences between outcomes over continuous time are important for individual, corporate, and social decision making, e.g., medical treatment, infrastructure development, and environmental regulation. This paper presents a foundation for such models. It shows that conditions...... on preferences between real- or vector-valued outcomes over continuous time are satisfied if and only if the preferences are represented by a value function having an integral form...
Study of Network Traffic Analysis Model Based on Time Granularity
Institute of Scientific and Technical Information of China (English)
Tan,Xi-aoling; Xu,Yong; Mei,Chenggang; Liu,Lan
2005-01-01
An analytic research on establishing different traffic models on the traffic nature of different time granularity can provide necessary academic foundation for network design and simulation as well as ensuring the quality of service and network management. This paper aims to make simulant predication by means of corresponding math tools on the modeling of real traftic of the different time granularity. The experimental results indicate that the predicated traffic is close to the real traffic distribution.
Distributed Time Delay Goodwin's Models of the Business Cycle
Antonova, A. O.; Reznik, S. N.; Todorov, M. D.
2011-11-01
We consider continuously distributed time delay Goodwin's model of the business cycle. We show that the delay induced sawtooth oscillations, similar to those detected by R. H. Strotz, J. C. McAnulty, J. B. Naines, Econometrica, 21, 390-411 (1953) for Goodwin's model with fixed investment time lag, exist only for very narrow delay distribution when the variance of the delay distribution much less than the average delay.
Traffic Incident Clearance Time and Arrival Time Prediction Based on Hazard Models
Directory of Open Access Journals (Sweden)
Yang beibei Ji
2014-01-01
Full Text Available Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an effective input for travel time prediction. In this paper, the hazard based prediction models are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.
Stylised facts of financial time series and hidden Markov models in continuous time
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2015-01-01
Hidden Markov models are often applied in quantitative finance to capture the stylised facts of financial returns. They are usually discrete-time models and the number of states rarely exceeds two because of the quadratic increase in the number of parameters with the number of states. This paper...
Murray, K. E.
2016-12-01
Management of produced fluids has become an important issue in Oklahoma because large volumes of saltwater are co-produced with oil and gas, and disposed into saltwater disposal wells at high rates. Petroleum production increased from 2009-2015, especially in central and north-central Oklahoma where the Mississippian and Hunton zones were redeveloped using horizontal wells and dewatering techniques that have led to a disproportional increase in produced water volumes. Improved management of co-produced water, including desalination for beneficial reuse and decreased saltwater disposal volumes, is only possible if spatial and temporal trends can be defined and related to the producing zones. It is challenging to quantify the volumes of co-produced water by region or production zone because co-produced water volumes are generally not reported. Therefore, the goal of this research is to estimate co-produced water volumes for 2008-present with an approach that can be replicated as petroleum production shifts to other regions. Oil and gas production rates from subsurface zones were multiplied by ratios of H2O:oil and H2O:gas for the respective zones. Initial H2O:oil and H2O:gas ratios were adjusted/calibrated, by zone, to maximize correlation of county-scale produced H2O estimates versus saltwater disposal volumes from 2013-2015. These calibrated ratios were then used to compute saltwater disposal volumes from 2008-2012 because of apparent data gaps in reported saltwater disposal volumes during that timeframe. This research can be used to identify regions that have the greatest need for produced water treatment systems. The next step in management of produced fluids is to explore optimal energy-efficient strategies that reduce deleterious effects.
Stochastic modeling of hourly rainfall times series in Campania (Italy)
Giorgio, M.; Greco, R.
2009-04-01
Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil
Shin, Jimin; Lee, Chaeyoung
2015-04-01
Population stratification can produce spurious genetic associations in genome-wide association studies (GWASs). Mixed model methodology has been regarded useful for correcting population stratification. This study explored statistical power and false discovery rate (FDR) with the data simulated for dichotomous traits. Empirical FDRs and powers were estimated using fixed models with and without genomic control and using mixed models with and without reflecting loci linked to the candidate marker in genetic relationships. Population stratification with admixture degree ranged from 1% to 10% resulted in inflated FDRs from the fixed model analysis without genomic control and decreased power from the fixed model analysis with genomic control (Ppopulation stratification could not change FDR and power estimates from the mixed model analyses (P>0.05). We suggest that the mixed model methodology was useful to reduce spurious genetic associations produced by population stratification in GWAS, even with a high degree of admixture (10%). Copyright © 2015 Elsevier Inc. All rights reserved.
Using time-varying covariates in multilevel growth models
Directory of Open Access Journals (Sweden)
D. Betsy McCoach
2010-06-01
Full Text Available This article provides an illustration of growth curve modeling within a multilevel framework. Specifically, we demonstrate coding schemes that allow the researcher to model discontinuous longitudinal data using a linear growth model in conjunction with time varying covariates. Our focus is on developing a level-1 model that accurately reflects the shape of the growth trajectory. We demonstrate the importance of adequately modeling the shape of the level-1 growth trajectory in order to make inferences about the importance of both level-1 and level-2 predictors.
LARGE SIGNAL DISCRETE-TIME MODEL FOR PARALLELED BUCK CONVERTERS
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
As a number of switch-combinations are involved in operation of multi-converter-system, conventional methods for obtaining discrete-time large signal model of these converter systems result in a very complex solution. A simple sampled-data technique for modeling distributed dc-dc PWM converters system (DCS) was proposed. The resulting model is nonlinear and can be linearized for analysis and design of DCS. These models are also suitable for fast simulation of these networks. As the input and output of dc-dc converters are slow varying, suitable model for DCS was obtained in terms of the finite order input/output approximation.
Numerical bifurcation analysis of immunological models with time delays
Luzyanina, Tatyana; Roose, Dirk; Bocharov, Gennady
2005-12-01
In recent years, a large number of mathematical models that are described by delay differential equations (DDEs) have appeared in the life sciences. To analyze the models' dynamics, numerical methods are necessary, since analytical studies can only give limited results. In turn, the availability of efficient numerical methods and software packages encourages the use of time delays in mathematical modelling, which may lead to more realistic models. We outline recently developed numerical methods for bifurcation analysis of DDEs and illustrate the use of these methods in the analysis of a mathematical model of human hepatitis B virus infection.
Pineux, N.; Lisein, J.; Swerts, G.; Bielders, C. L.; Lejeune, P.; Colinet, G.; Degré, A.
2017-03-01
Erosion and deposition modelling should rely on field data. Currently these data are seldom available at large spatial scales and/or at high spatial resolution. In addition, conventional erosion monitoring approaches are labour intensive and costly. This calls for the development of new approaches for field erosion data acquisition. As a result of rapid technological developments and low cost, unmanned aerial vehicles (UAV) have recently become an attractive means of generating high resolution digital elevation models (DEMs). The use of UAV to observe and quantify gully erosion is now widely established. However, in some agro-pedological contexts, soil erosion results from multiple processes, including sheet and rill erosion, tillage erosion and erosion due to harvest of root crops. These diffuse erosion processes often represent a particular challenge because of the limited elevation changes they induce. In this study, we propose to assess the reliability and development perspectives of UAV to locate and quantify erosion and deposition in a context of an agricultural watershed with silt loam soils and a smooth relief. Erosion and deposition rates derived from high resolution DEM time series are compared to field measurements. The UAV technique demonstrates a high level of flexibility and can be used, for instance, after a major erosive event. It delivers a very high resolution DEM (pixel size: 6 cm) which allows us to compute high resolution runoff pathways. This could enable us to precisely locate runoff management practices such as fascines. Furthermore, the DEMs can be used diachronically to extract elevation differences before and after a strongly erosive rainfall and be validated by field measurements. While the analysis for this study was carried out over 2 years, we observed a tendency along the slope from erosion to deposition. Erosion and deposition patterns detected at the watershed scale are also promising. Nevertheless, further development in the
Time-varying priority queuing models for human dynamics.
Jo, Hang-Hyun; Pan, Raj Kumar; Kaski, Kimmo
2012-06-01
Queuing models provide insight into the temporal inhomogeneity of human dynamics, characterized by the broad distribution of waiting times of individuals performing tasks. We theoretically study the queuing model of an agent trying to execute a task of interest, the priority of which may vary with time due to the agent's "state of mind." However, its execution is disrupted by other tasks of random priorities. By considering the priority of the task of interest either decreasing or increasing algebraically in time, we analytically obtain and numerically confirm the bimodal and unimodal waiting time distributions with power-law decaying tails, respectively. These results are also compared to the updating time distribution of papers in arXiv.org and the processing time distribution of papers in Physical Review journals. Our analysis helps to understand human task execution in a more realistic scenario.
Time-Varying Priority Queuing Models for Human Dynamics
Jo, Hang-Hyun; Kaski, Kimmo
2011-01-01
Queuing models provide insight into the temporal inhomogeneity of human dynamics, characterized by the broad distribution of waiting times of individuals performing tasks. We study the queuing model of an agent trying to execute a task of interest, the priority of which may vary with time due to the agent's "state of mind." However, its execution can be disrupted by other tasks of random priorities. By considering the priority of the task of interest either decreasing or increasing algebraically in time, we analytically obtain and numerically confirm the bimodal and unimodal waiting time distributions with power-law decaying tails, respectively. These results are also compared to the updating time distribution of papers in the arXiv and the processing time distribution of papers in Physical Review journals. Our analysis helps to understand the human task execution behavior in a more realistic scenario.
EOQ Model for Time-Deteriorating Items Using Penalty cost
Directory of Open Access Journals (Sweden)
Meenakshi Srivastava
2009-01-01
Full Text Available In inventory, the utility of the deteriorating items decreases with time. The degree ofdeterioration of product utility can be treated as penalty cost in the inventory replenishmentsystem. In this paper, we present EOQ model for those perishable products, which do notdeteriorate for some period of time and after that time they continuously deteriorate with time andloose their importance. This loss can be incurred as penalty cost to the wholesaler / retailer. Theprime focus of our paper is to develop the EOQ model for time-deteriorating items using penaltycost with finite and infinite production rate. For simplicity, linear and exponential penalty costfunctions have been considered as a measurement of the utility of the product. The theoreticalexpressions are obtained for optimum inventory level and cycle time. All the theoreticaldevelopments are numerically justified.
Robust Real-Time Musculoskeletal Modeling driven by Electromyograms
Durandau, Guillaume; Farina, Dario; Sartori, Massimo
2017-01-01
Objective: Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses and current biomechanical models cannot be used for real-time control in man-machine interfaces. We developed a method that enables online analysis of neuromusculoskeletal function in vivo
STUDY ON AN SIS EPIDEMIC MODEL WITH TIME VARIANT DELAY
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In this paper,we study an SIS epidemic model with a time variant delay.By means of Liapunov functional,some sufficient conditions of global stability to endemic equilibrium and disease free equilibrium have been obtained.The influence of time delay on the stability of equilibria is displayed.
STUDY ON AN SIS EPIDEMIC MODEL WITH TIME VARIANT DELAY
Institute of Scientific and Technical Information of China (English)
YUAN Sanling; MA Zhien
2002-01-01
In this paper, we study an SIS epidemic model with a time variant delay.By means of Liapunov functional, some sufficient conditions of global stability to endemic equilibrium and disease free equilibrium have been obtained. The influence of time delay on the stability of equilibria is displayed.
Hidden Markov Models for Time Series An Introduction Using R
Zucchini, Walter
2009-01-01
Illustrates the flexibility of HMMs as general-purpose models for time series data. This work presents an overview of HMMs for analyzing time series data, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts and categorical observations.
A model of interval timing by neural integration.
Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip
2011-06-22
We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.
Sparse time series chain graphical models for reconstructing genetic networks
Abegaz, Fentaw; Wit, Ernst
2013-01-01
We propose a sparse high-dimensional time series chain graphical model for reconstructing genetic networks from gene expression data parametrized by a precision matrix and autoregressive coefficient matrix. We consider the time steps as blocks or chains. The proposed approach explores patterns of co
Optimization of recurrent neural networks for time series modeling
DEFF Research Database (Denmark)
Pedersen, Morten With
1997-01-01
The present thesis is about optimization of recurrent neural networks applied to time series modeling. In particular is considered fully recurrent networks working from only a single external input, one layer of nonlinear hidden units and a li near output unit applied to prediction of discrete time...
An Efficient MIP Model for Locomotive Scheduling with Time Windows
Aronsson, Martin; Kreuger, Per; Gjerdrum, Jonatan
2006-01-01
This paper presents an IP model for a vehicle routing and scheduling problem from the domain of freight railways. The problem is non-capacitated but allows non-binary integer flows of vehicles between transports with departure times variable within fixed intervals. The model has been developed with and has found practical use at Green Cargo, the largest freight rail operator in Sweden.
A multivariate approach to modeling univariate seasonal time series
Ph.H.B.F. Franses (Philip Hans)
1994-01-01
textabstractA seasonal time series can be represented by a vector autoregressive model for the annual series containing the seasonal observations. This model allows for periodically varying coefficients. When the vector elements are integrated, the maximum likelihood cointegration method can be used
Integral-Value Models for Outcomes over Continuous Time
DEFF Research Database (Denmark)
Harvey, Charles M.; Østerdal, Lars Peter
Models of preferences between outcomes over continuous time are important for individual, corporate, and social decision making, e.g., medical treatment, infrastructure development, and environmental regulation. This paper presents a foundation for such models. It shows that conditions on prefere...
Time-Limited Psychotherapy: An Interactional Stage Model.
Tracey, Terence J.
One model of successful time-limited psychotherapy characterizes the therapy as a movement through three interactional stages: the early rapport attainment stage, the middle conflict stage, and the final resolution stage. According to this model, these stages are indicated by the relative presence of communicational harmony. To examine the…
The Targets/IMage Energy (TIME) 1.0 Model
Vries B de; Wijngaart RA van den; MNV
1996-01-01
Documentation of the five submodels of Targets/IMage Energy (TIME) 1.0 model are presented. Energy Demand, Liquid Fuel (LF), Gaseous Fuel (GF), Solid Fuel (SF) and Electric Power Generation (EPG) are described in detail. Some results of the model calibration for the world 1900-1990 are presented as
A fire management simulation model using stochastic arrival times
Eric L. Smith
1987-01-01
Fire management simulation models are used to predict the impact of changes in the fire management program on fire outcomes. As with all models, the goal is to abstract reality without seriously distorting relationships between variables of interest. One important variable of fire organization performance is the length of time it takes to get suppression units to the...
Transition times in the Landau-Zener model
Vitanov, N V
1999-01-01
This paper presents analytic formulas for various transition times in the Landau-Zener model. Considerable differences are found between the transition times in the diabatic and adiabatic bases, and between the jump time (the time for which the transition probability rises to the region of its asymptotic value) and the relaxation time (the characteristic damping time of the oscillations which appear in the transition probability after the crossing). These transition times have been calculated by using the exact values of the transition probabilities and their derivatives at the crossing point and approximations to the time evolutions of the transition probabilities in the diabatic basis, derived earlier \\protect{[}N. V. Vitanov and B. M. Garraway, Phys. Rev. A {\\bf 53}, 4288 (1996)\\protect{]}, and similar results in the adiabatic basis, derived in the present paper.
Reactive Aggregate Model Protecting Against Real-Time Threats
2014-09-01
SQL server and has four tables: Accumulator, BlockState, Epoc , Signature, and Weight. Accumulator columns were RemoteIP, Test1, Test2, Test3 and Time...block occurred. The Epoc table was a pivot necessary to convert the time stamps to Epoch time format. The Signature table held values indicative of...processing unit” of the RAMPART Figure 6. model. The RAMPART database exists on a Windows SQL server and has four tables: Accumulator, BlockState, Epoc
Barrier traversal times using a phenomenological track formation model
Palao, J P; Brouard, S; Jadczyk, A
1997-01-01
A phenomenological model for a measurement of barrier traversal times for particles is proposed. Two idealized detectors for passage and arrival provide entrance and exit times for the barrier traversal. The averaged traversal time is computed over the ensemble of particles detected twice, before and after the barrier. The Hartman effect can still be found when passage detectors that conserve the momentum distribution of the incident packet are used.
Kālī: Time series data modeler
Kasliwal, Vishal P.
2016-07-01
The fully parallelized and vectorized software package Kālī models time series data using various stochastic processes such as continuous-time ARMA (C-ARMA) processes and uses Bayesian Markov Chain Monte-Carlo (MCMC) for inferencing a stochastic light curve. Kālimacr; is written in c++ with Python language bindings for ease of use. K¯lī is named jointly after the Hindu goddess of time, change, and power and also as an acronym for KArma LIbrary.
Directory of Open Access Journals (Sweden)
B. Kayisoglu
2006-01-01
Full Text Available This study was conducted to investigate the effect of storage period and conditions on chemical properties of boiled grape juice (pekmez produced from the grape variety of Kınalı Yapıncak using classical and vacuum methods. Pekmez samples were stored in 250 cc volumed jars. Products obtained using two different production methods were stored for 10 months in room conditions and at +4 ºC temperature. Starting from the beginning of the storage, mineral analyses were repeated in every two months. Average copper, manganese, phosphorus, and sodium contents in pekmez samples produced by vacuum method were higher than by classical method at the end of storage period. But, calcium content in pekmez samples produced by classical method was higher than that of the other. Zinc, iron, and potassium contents in either vacuum method or classical method were not significantly different. In conclusion; in general, mineral contents were better in pekmez produced by vacuum method than classical method. Phosphor, sodium, potassium, calcium, copper, zinc and manganese contents were affected significantly by storage period, but iron was not. In addition, storage condition did not affect sodium, zinc and iron contents.
Parametric time delay modeling for floating point units
Fahmy, Hossam A. H.; Liddicoat, Albert A.; Flynn, Michael J.
2002-12-01
A parametric time delay model to compare floating point unit implementations is proposed. This model is used to compare a previously proposed floating point adder using a redundant number representation with other high-performance implementations. The operand width, the fan-in of the logic gates and the radix of the redundant format are used as parameters to the model. The comparison is done over a range of operand widths, fan-in and radices to show the merits of each implementation.
Examining the Fidelity of Climate model via Shadowing Time
Du, H.; Smith, L. A.
2015-12-01
Fully fledged climate models provide the best available simulations for reflecting the future, yet we have scant insight into their fidelity, in particular as to the duration into the future at which the real world should be expected to evolve in a manner today's models cannot foresee. We know now that our best available models are not adequate for many sought after purposes. To throw some light on the maximum fidelity expected from a given generation of models, and thereby aid both policy making and model development, we can test the weaknesses of a model as a dynamical system to get an informed idea of its potential applicability at various lead times. Shadowing times reflect the duration on which a GCM reflects the observations; extracting the shortcomings of the model which limit shadowing times allows informed speculation regarding the fidelity of the model in the future. More specifically, the relevant phenomena limiting model fidelity can be learned by identifying the reasons models cannot shadow; the time scales on which feedbacks on the system (which are not active in the model) are likely to result in model irrelevance can be discerned. The methodology is developed in the "low dimensional laboratory" of relatively simple dynamical systems, for example Lorenz 95 systems. The results are presented in Lorenz 95 systems, high dimensional fluid dynamical simulations of rotating annulus and GCMs. There are severe limits on the light shadowing experiments can shine on GCM predictions. Never the less, they appear to be one of the brightest lights we can shine to illuminate the likely fidelity of GCM extrapolations into the future.
Double time lag combustion instability model for bipropellant rocket engines
Liu, C. K.
1973-01-01
A bipropellant stability model is presented in which feed system inertance and capacitance are treated along with injection pressure drop and distinctly different propellant time lags. The model is essentially an extension of Crocco's and Cheng's monopropellant model to the bipropellant case assuming that the feed system inertance and capacitance along with the resistance are located at the injector. The neutral stability boundaries are computed in terms of these parameters to demonstrate the interaction among them.
Analyzing the Dynamics of Nonlinear Multivariate Time Series Models
Institute of Scientific and Technical Information of China (English)
DenghuaZhong; ZhengfengZhang; DonghaiLiu; StefanMittnik
2004-01-01
This paper analyzes the dynamics of nonlinear multivariate time series models that is represented by generalized impulse response functions and asymmetric functions. We illustrate the measures of shock persistences and asymmetric effects of shocks derived from the generalized impulse response functions and asymmetric function in bivariate smooth transition regression models. The empirical work investigates a bivariate smooth transition model of US GDP and the unemployment rate.
Continuous time modelling of dynamical spatial lattice data observed at sparsely distributed times
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl; Møller, Jesper
2007-01-01
Summary. We consider statistical and computational aspects of simulation-based Bayesian inference for a spatial-temporal model based on a multivariate point process which is only observed at sparsely distributed times. The point processes are indexed by the sites of a spatial lattice, and they ex......Summary. We consider statistical and computational aspects of simulation-based Bayesian inference for a spatial-temporal model based on a multivariate point process which is only observed at sparsely distributed times. The point processes are indexed by the sites of a spatial lattice......, and they exhibit spatial interaction. For specificity we consider a particular dynamical spatial lattice data set which has previously been analysed by a discrete time model involving unknown normalizing constants. We discuss the advantages and disadvantages of using continuous time processes compared...
Directory of Open Access Journals (Sweden)
F. Yasmeen
2009-10-01
Full Text Available Aqueous-phase oligomer formation from methylglyoxal, a major atmospheric photooxidation product, has been investigated in a simulated cloud matrix under dark conditions. The aim of this study was to explore an additional path producing secondary organic aerosol (SOA through cloud processes without photochemistry during night-time. Indeed, atmospheric models still underestimate SOA formation, as field measurements have revealed more SOA than predicted. Soluble oligomers (n=1–8 formed in the course of acid-catalyzed aldol condensation and acid-catalyzed hydration followed by acetal formation have been detected and characterized by positive and negative ion electrospray ionization mass spectrometry. Aldol condensation proved to be a favorable mechanism under simulated cloud conditions, while hydration/acetal formation was found to strongly depend on the pH of the system. The aldol oligomer series starts with a β-hydroxy ketone via aldol condensation, where oligomers are formed by multiple additions of C_{3}H_{4}O_{2} units (72 Da to the parent β-hydroxy ketone. Ion trap mass spectrometry experiments were performed to structurally characterize the major oligomer species. A mechanistic pathway for the growth of oligomers under cloud conditions and in the absence of UV-light and OH radicals, which could substantially enhance in-cloud SOA yields, is proposed here for the first time.
Energy Technology Data Exchange (ETDEWEB)
Mossessian, George; Fleishman, Gregory D. [Center For Solar-Terrestrial Research, New Jersey Institute of Technology, Newark, NJ 07102 (United States)
2012-04-01
A quantitative study of the observable radio signatures of the sausage, kink, and torsional magnetohydrodynamic (MHD) oscillation modes in flaring coronal loops is performed. Considering first non-zero order effect of these various MHD oscillation modes on the radio source parameters such as magnetic field, line of sight, plasma density and temperature, electron distribution function, and the source dimensions, we compute time-dependent radio emission (spectra and light curves). The radio light curves (of both flux density and degree of polarization) at all considered radio frequencies are then quantified in both time domain (via computation of the full modulation amplitude as a function of frequency) and in Fourier domain (oscillation spectra, phases, and partial modulation amplitude) to form the signatures specific to a particular oscillation mode and/or source parameter regime. We found that the parameter regime and the involved MHD mode can indeed be distinguished using the quantitative measures derived in the modeling. We apply the developed approach to analyze radio burst recorded by Owens Valley Solar Array and report possible detection of the sausage mode oscillation in one (partly occulted) flare and kink or torsional oscillations in another flare.
Application of radiosurgical techniques to produce a primate model of brain lesions
Directory of Open Access Journals (Sweden)
Jun eKunimatsu
2015-04-01
Full Text Available Behavioral analysis of subjects with discrete brain lesions provides important information about the mechanisms of various brain functions. However, it is generally difficult to experimentally produce discrete lesions in deep brain structures. Here we show that a radiosurgical technique, which is used as an alternative treatment for brain tumors and vascular malformations, is applicable to create non-invasive lesions in experimental animals for the research in systems neuroscience. We delivered highly focused radiation (130–150 Gy at ISO center to the frontal eye field of macaque monkeys using a clinical linear accelerator (LINAC. The effects of irradiation were assessed by analyzing oculomotor performance along with magnetic resonance (MR images before and up to 8 months following irradiation. In parallel with tissue edema indicated by MR images, deficits in saccadic and smooth pursuit eye movements were observed during several days following irradiation. Although initial signs of oculomotor deficits disappeared within a month, damage to the tissue and impaired eye movements gradually developed during the course of the subsequent 6 months. Postmortem histological examinations showed necrosis and hemorrhages within a large area of the white matter and, to a lesser extent, in the adjacent gray matter, which was centered at the irradiated target. These results indicated that the LINAC system was useful for making brain lesions in experimental animals, while the suitable radiation parameters to generate more focused lesions need to be further explored. We propose the use of a radiosurgical technique for establishing animal models of brain lesions, and discuss the possible uses of this technique for functional neurosurgical treatments in humans.
A model for the distribution of aftershock waiting times
Shcherbakov, R; Turcotte, D L; Yakovlev, G
2005-01-01
In this work the distribution of inter-occurrence times between earthquakes in aftershock sequences is analyzed and a model based on a non-homogeneous Poisson (NHP) process is proposed to quantify the observed scaling. In this model the generalized Omori's law for the decay of aftershocks is used as a time-dependent rate in the NHP process. The analytically derived distribution of inter-occurrence times is applied to several major aftershock sequences in California to confirm the validity of the proposed hypothesis.
On reevaluation rate in discrete time Hogg-Huberman model
Tanaka, Toshijiro; Shibata, Junko; Inoue, Masayoshi
2002-06-01
The discrete time Hogg-Huberman model is extended to a case with time-dependent reevaluation rate at which agents using one resource decide to evaluate their resource choice. In this paper the time dependence of the reevaluation rate is determined by states of the system. The dynamical behavior of the extended Hogg-Huberman model is discussed. It is found that the change of fraction of agents using resource 1 is suppressed to be smaller than that in the case of constant reevaluation rate.
Study on autonomous navigation based on pulsar timing model
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
The basic principle of pulsar timing model was introduced, and the general relativistic corrections were analyzed when pulse time of arrival (TOA) was transferred to coordinate TOA at the Solar System Barycentre. Based on the shifting, an iterative method of autonomous position determination for spacecraft was developed. Accordingly, the linear form of the position offset equation was evolved. Using the initial estimated value of spacecraft’s position as the input of pulsar timing equation, through calculation of the offset between measured or transferred and predicted TOA, the position offset can be solved by Least Squares. At last, the main error sources including modeling error and parameters error were discussed.
Study on autonomous navigation based on pulsar timing model
Institute of Scientific and Technical Information of China (English)
LI JianXun; KE XiZheng
2009-01-01
The basic principle of pulsar timing model was introduced, and the general relativistic corrections were analyzed when pulse time of arrival (TOA) was transferred to coordinate TOA at the Solar System Barycentre. Based on the shifting, an iterative method of autonomous position determination for spacecraft was developed. Accordingly, the linear form of the position offset equation was evolved. Using the initial estimated value of spacecraft's position as the input of pulsar timing equation, through calculation of the offset between measured or transferred and predicted TOA, the position offset can be solved by Least Squares. At last, the main error sources including modeling error and parameters error were discussed.
High Precision Time Domain Forward Modeling for Crosshole Electromagnetic Tomography
Institute of Scientific and Technical Information of China (English)
Lin Shuhai; Zhao Liying
2007-01-01
To improve the resolution of crosshole electromagnetic tomography, high precision of forward modeling is necessary. A pseudo-spectral time domain (PSTD) forward modeling was used to simulate electromagnetic wave propagation between two boreholes. The PSTD algorithm is based on the finite difference time domain (FDTD) method and uses the fast Fourier transform (FFT) algorithm for spatial derivatives in Maxwell's equations. Besides having the strongpoint of the FDTD method, the calculation precision of the PSTD algorithm is higher than that of the FDTD method under the same calculation condition. The forward modeling using the PSTD method will play an important role in enhancing the resolution of crosshole electromagnetic tomography.
Bowling, T. J.; Calais, E.; Dautermann, T.
2010-12-01
Rocket launches are known to produce infrasonic pressure waves that propagate into the ionosphere where coupling between electrons and neutral particles induces fluctuations in ionospheric electron density observable in GPS measurements. We have detected ionospheric perturbations following the launch of space shuttle Atlantis on 11 May 2009 using an array of continually operating GPS stations across the Southeastern coast of the United States and in the Caribbean. Detections are prominent to the south of the westward shuttle trajectory in the area of maximum coupling between the acoustic wave and Earth’s magnetic field, move at speeds consistent with the speed of sound, and show coherency between stations covering a large geographic range. We model the perturbation as an explosive source located at the point of closest approach between the shuttle path and each sub-ionospheric point. The neutral pressure wave is propagated using ray tracing, resultant changes in electron density are calculated at points of intersection between rays and satellite-to-reciever line-of-sight, and synthetic integrated electron content values are derived. Arrival times of the observed and synthesized waveforms match closely, with discrepancies related to errors in the apriori sound speed model used for ray tracing. Current work includes the estimation of source location and energy.
Short-term time step convergence in a climate model.
Wan, Hui; Rasch, Philip J; Taylor, Mark A; Jablonowski, Christiane
2015-03-01
This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral-element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process-coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid-scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full-physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4-considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid-scale physical parameterizations, the stratiform cloud schemes are associated with the largest time-stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time-stepping errors and identify the related model sensitivities.
Equilibrium Model Constraints on Baryon Cycling Across Cosmic Time
Mitra, Sourav; Finlator, Kristian
2014-01-01
Galaxies strongly self-regulate their growth via energetic feedback from stars, supernovae, and black holes, but these processes are among the least understood aspects of galaxy formation theory. We present an analytic galaxy evolution model that directly constrains such feedback processes from observed galaxy scaling relations. The equilibrium model, which is broadly valid for star-forming central galaxies that dominate cosmic star formation, is based on the ansatz that galaxies live in a slowly-evolving equilibrium between inflows, outflows, and star formation. Using a Bayesian Monte Carlo Markov chain approach, we constrain our model to match observed galaxy scaling relations between stellar mass and halo mass, star formation rate, and metallicity from 0
Spatio-temporal modeling for real-time ozone forecasting.
Paci, Lucia; Gelfand, Alan E; Holland, David M
2013-05-01
The accurate assessment of exposure to ambient ozone concentrations is important for informing the public and pollution monitoring agencies about ozone levels that may lead to adverse health effects. High-resolution air quality information can offer significant health benefits by leading to improved environmental decisions. A practical challenge facing the U.S. Environmental Protection Agency (USEPA) is to provide real-time forecasting of current 8-hour average ozone exposure over the entire conterminous United States. Such real-time forecasting is now provided as spatial forecast maps of current 8-hour average ozone defined as the average of the previous four hours, current hour, and predictions for the next three hours. Current 8-hour average patterns are updated hourly throughout the day on the EPA-AIRNow web site. The contribution here is to show how we can substantially improve upon current real-time forecasting systems. To enable such forecasting, we introduce a downscaler fusion model based on first differences of real-time monitoring data and numerical model output. The model has a flexible coefficient structure and uses an efficient computational strategy to fit model parameters. Our hybrid computational strategy blends continuous background updated model fitting with real-time predictions. Model validation analyses show that we are achieving very accurate and precise ozone forecasts.
Stochastic modelling of dissolved inorganic nitrogen in space and time
DEFF Research Database (Denmark)
Lophaven, Søren Nymand; Carstensen, Niels Jacob; Rootzen, Helle
2006-01-01
Environmental monitoring datasets often contain a large amount of missing values, and are characterized as being sampled over time on a distinct number of locations in the area of interest. This paper proposes a stochastic approach for modelling such data in space and time, by taking the spatial...... and temporal correlations in data into account. It has been applied to observations of dissolved inorganic nitrogen in the Kattegat during the period 1993-1997. Modelling results are shown as maps of the spatial distribution of dissolved inorganic nitrogen (DIN) in 4 weeks, representing the four seasons......, and as time series of DIN at three different locations. However, the model approach could be applied to any space-time point given by a location in the Kattegat area and a week in the 5-year period 1993-1997. The results can be interpreted from a biological and physical point of view. Thus for the specific...
Recursive Bayesian recurrent neural networks for time-series modeling.
Mirikitani, Derrick T; Nikolaev, Nikolay
2010-02-01
This paper develops a probabilistic approach to recursive second-order training of recurrent neural networks (RNNs) for improved time-series modeling. A general recursive Bayesian Levenberg-Marquardt algorithm is derived to sequentially update the weights and the covariance (Hessian) matrix. The main strengths of the approach are a principled handling of the regularization hyperparameters that leads to better generalization, and stable numerical performance. The framework involves the adaptation of a noise hyperparameter and local weight prior hyperparameters, which represent the noise in the data and the uncertainties in the model parameters. Experimental investigations using artificial and real-world data sets show that RNNs equipped with the proposed approach outperform standard real-time recurrent learning and extended Kalman training algorithms for recurrent networks, as well as other contemporary nonlinear neural models, on time-series modeling.
Directory of Open Access Journals (Sweden)
Loyko V. I.
2015-06-01
Full Text Available Agricultural producers interested in marketing of raw materials, whereas processing companies are interested in the establishment of raw material zones, providing capacity utilization; therefore, the establishment of sustainable linkages between producers and processors of raw materials is an objective necessity. In the article, with the help of mathematical methods we examine the conditions of mutually beneficial economic relations between agricultural producers and processing enterprises. Mathematical model for estimating the profits of the company is built of the following conditions: producers sell processing plants raw materials, determined by the coefficient of the interest in the partnership at an agreed purchase price, and the remaining raw materials are processed, so they can sell their products independently. Profit of the processing plant is determined by the mathematical model. To describe the nonlinear market-based sales of goods from its retail price we used a hyperbolic demand function
Logic Model Checking of Time-Periodic Real-Time Systems
Florian, Mihai; Gamble, Ed; Holzmann, Gerard
2012-01-01
In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.
Multi-scale gravity field modeling in space and time
Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric
2016-04-01
The Earth constantly deforms as it undergoes dynamic phenomena, such as earthquakes, post-glacial rebound and water displacement in its fluid envelopes. These processes have different spatial and temporal scales and are accompanied by mass displacements, which create temporal variations of the gravity field. Since 2002, the GRACE satellite missions provide an unprecedented view of the gravity field spatial and temporal variations. Gravity models built from these satellite data are essential to study the Earth's dynamic processes (Tapley et al., 2004). Up to present, time variations of the gravity field are often modelled using spatial spherical harmonics functions averaged over a fixed period, as 10 days or 1 month. This approach is well suited for modeling global phenomena. To better estimate gravity related to local and/or transient processes, such as earthquakes or floods, and adapt the temporal resolution of the model to its spatial resolution, we propose to model the gravity field using localized functions in space and time. For that, we build a model of the gravity field in space and time with a four-dimensional wavelet basis, well localized in space and time. First we design the 4D basis, then, we study the inverse problem to model the gravity field from the potential differences between the twin GRACE satellites, and its regularization using prior knowledge on the water cycle. Our demonstration of surface water mass signals decomposition in time and space is based on the use of synthetic along-track gravitational potential data. We test the developed approach on one year of 4D gravity modeling and compare the reconstructed water heights to those of the input hydrological model. Perspectives of this work is to apply the approach on real GRACE data, addressing the challenge of a realistic noise, to better describe and understand physical processus with high temporal resolution/low spatial resolution or the contrary.
TIME SERIES FORECASTING WITH MULTIPLE CANDIDATE MODELS: SELECTING OR COMBINING?
Institute of Scientific and Technical Information of China (English)
YU Lean; WANG Shouyang; K. K. Lai; Y.Nakamori
2005-01-01
Various mathematical models have been commonly used in time series analysis and forecasting. In these processes, academic researchers and business practitioners often come up against two important problems. One is whether to select an appropriate modeling approach for prediction purposes or to combine these different individual approaches into a single forecast for the different/dissimilar modeling approaches. Another is whether to select the best candidate model for forecasting or to mix the various candidate models with different parameters into a new forecast for the same/similar modeling approaches. In this study, we propose a set of computational procedures to solve the above two issues via two judgmental criteria. Meanwhile, in view of the problems presented in the literature, a novel modeling technique is also proposed to overcome the drawbacks of existing combined forecasting methods. To verify the efficiency and reliability of the proposed procedure and modeling technique, the simulations and real data examples are conducted in this study.The results obtained reveal that the proposed procedure and modeling technique can be used as a feasible solution for time series forecasting with multiple candidate models.
Uniformed model of networked control systems with long time delay
Institute of Scientific and Technical Information of China (English)
Zhu Qixin; Liu Hongli; Hu Shousong
2008-01-01
Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCS). The defining feature of an NCS is that information is exchanged using a network among control system components. Two new concepts including long time delay and short time delay are proposed.The sensor is almost always clock driven. The controller or the actuator is either clock driven or event driven. Four possible driving modes of networked control systems are presented. The open loop mathematic models of networked control systems with long time delay are developed when the system is driven by anyone of the four different modes.The uniformed modeling method of networked control systems with long time delay is proposed. The simulation results are given in the end.
Model Checking Real-Time Value-Passing Systems
Institute of Scientific and Technical Information of China (English)
Jing Chen; Zio-Ning Cao
2004-01-01
In this paper,to model check real-time value-passing systems,a formal language Timed Symbolic Transition Graph and a logic system named Timed Predicate μ-Calculus are proposed.An algorithm is presented which is local in that it generates and investigates the reachable state space in top-down fashion and maintains the partition for time evaluations as coarse as possible while on-the-fly instantiating data variables.It can deal with not only data variables with finite value domain,but also the so called data independent variables with infinite value domain.To authors knowledge,this is the first algorithm for model checking timed systems containing value-passing features.
Emergent Semiclassical Time in Quantum Gravity. I. Mechanical Models
Anderson, E
2006-01-01
Strategies intended to resolve the problem of time in quantum gravity by means of emergent or hidden timefunctions are considered in the arena of relational particle toy models. In situations with `heavy' and `light' degrees of freedom, two notions of emergent semiclassical WKB time emerge; these are furthermore equivalent to two notions of emergent classical `Leibniz--Mach--Barbour' time. I futhermore study the semiclassical approach, in a geometric phase formalism, extended to include linear constraints, and with particular care to make explicit those approximations and assumptions used. I propose a new iterative scheme for this in the cosmologically-motivated case with one heavy degree of freedom. I find that the usual semiclassical quantum cosmology emergence of time comes hand in hand with the emergence of other qualitatively significant terms, including back-reactions on the heavy subsystem and second time derivatives. I illustrate my analysis by taking it further for relational particle models with lin...
Modeling of the Response Time of Thermal Flow Sensors
Directory of Open Access Journals (Sweden)
Walter Lang
2011-10-01
Full Text Available This paper introduces a simple theoretical model for the response time of thermal flow sensors. Response time is defined here as the time needed by the sensor output signal to reach 63.2% of amplitude due to a change of fluid flow. This model uses the finite-difference method to solve the heat transfer equations, taking into consideration the transient conduction and convection between the sensor membrane and the surrounding fluid. Program results agree with experimental measurements and explain the response time dependence on the velocity and the sensor geometry. Values of the response time vary from about 5 ms in the case of stagnant flow to 1.5 ms for a flow velocity of 44 m/s.
Hypersurface-deformation algebroids and effective space-time models
Bojowald, Martin; Buyukcam, Umut; D'Ambrosio, Fabio
2016-01-01
In canonical gravity, covariance is implemented by brackets of hypersurface-deformation generators forming a Lie algebroid. Lie algebroid morphisms therefore allow one to relate different versions of the brackets that correspond to the same space-time structure. An application to examples of modified brackets found mainly in models of loop quantum gravity can in some cases map the space-time structure back to the classical Riemannian form after a field redefinition. For one type of quantum corrections (holonomies), signature change appears to be a generic feature of effective space-time, and is shown here to be a new quantum space-time phenomenon which cannot be mapped to an equivalent classical structure. In low-curvature regimes, our constructions prove the existence of classical space-time structures assumed elsewhere in models of loop quantum cosmology, but also shows the existence of additional quantum corrections that have not always been included.
Modelling and analysis of real-time and hybrid systems
Energy Technology Data Exchange (ETDEWEB)
Olivero, A.
1994-09-29
This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.
Model and Variable Selection Procedures for Semiparametric Time Series Regression
Directory of Open Access Journals (Sweden)
Risa Kato
2009-01-01
Full Text Available Semiparametric regression models are very useful for time series analysis. They facilitate the detection of features resulting from external interventions. The complexity of semiparametric models poses new challenges for issues of nonparametric and parametric inference and model selection that frequently arise from time series data analysis. In this paper, we propose penalized least squares estimators which can simultaneously select significant variables and estimate unknown parameters. An innovative class of variable selection procedure is proposed to select significant variables and basis functions in a semiparametric model. The asymptotic normality of the resulting estimators is established. Information criteria for model selection are also proposed. We illustrate the effectiveness of the proposed procedures with numerical simulations.
Multiaxial Temperature- and Time-Dependent Failure Model
Richardson, David; McLennan, Michael; Anderson, Gregory; Macon, David; Batista-Rodriquez, Alicia
2003-01-01
A temperature- and time-dependent mathematical model predicts the conditions for failure of a material subjected to multiaxial stress. The model was initially applied to a filled epoxy below its glass-transition temperature, and is expected to be applicable to other materials, at least below their glass-transition temperatures. The model is justified simply by the fact that it closely approximates the experimentally observed failure behavior of this material: The multiaxiality of the model has been confirmed (see figure) and the model has been shown to be applicable at temperatures from -20 to 115 F (-29 to 46 C) and to predict tensile failures of constant-load and constant-load-rate specimens with failure times ranging from minutes to months..
The average rate of change for continuous time models.
Kelley, Ken
2009-05-01
The average rate of change (ARC) is a concept that has been misunderstood in the applied longitudinal data analysis literature, where the slope from the straight-line change model is often thought of as though it were the ARC. The present article clarifies the concept of ARC and shows unequivocally the mathematical definition and meaning of ARC when measurement is continuous across time. It is shown that the slope from the straight-line change model generally is not equal to the ARC. General equations are presented for two measures of discrepancy when the slope from the straight-line change model is used to estimate the ARC in the case of continuous time for any model linear in its parameters, and for three useful models nonlinear in their parameters.
A continuous-time neural model for sequential action.
Kachergis, George; Wyatte, Dean; O'Reilly, Randall C; de Kleijn, Roy; Hommel, Bernhard
2014-11-01
Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions.
Numerical modeling of space-time wave extremes using WAVEWATCH III
Barbariol, Francesco; Alves, Jose-Henrique G. M.; Benetazzo, Alvise; Bergamasco, Filippo; Bertotti, Luciana; Carniel, Sandro; Cavaleri, Luigi; Chao, Yung Y.; Chawla, Arun; Ricchi, Antonio; Sclavo, Mauro; Tolman, Hendrik
2017-01-01
A novel implementation of parameters estimating the space-time wave extremes within the spectral wave model WAVEWATCH III (WW3) is presented. The new output parameters, available in WW3 version 5.16, rely on the theoretical model of Fedele (J Phys Oceanogr 42(9):1601-1615, 2012) extended by Benetazzo et al. (J Phys Oceanogr 45(9):2261-2275, 2015) to estimate the maximum second-order nonlinear crest height over a given space-time region. In order to assess the wave height associated to the maximum crest height and the maximum wave height (generally different in a broad-band stormy sea state), the linear quasi-determinism theory of Boccotti (2000) is considered. The new WW3 implementation is tested by simulating sea states and space-time extremes over the Mediterranean Sea (forced by the wind fields produced by the COSMO-ME atmospheric model). Model simulations are compared to space-time wave maxima observed on March 10th, 2014, in the northern Adriatic Sea (Italy), by a stereo camera system installed on-board the "Acqua Alta" oceanographic tower. Results show that modeled space-time extremes are in general agreement with observations. Differences are mostly ascribed to the accuracy of the wind forcing and, to a lesser extent, to the approximations introduced in the space-time extremes parameterizations. Model estimates are expected to be even more accurate over areas larger than the mean wavelength (for instance, the model grid size).
Multiple-relaxation-time model for the correct thermohydrodynamic equations.
Zheng, Lin; Shi, Baochang; Guo, Zhaoli
2008-08-01
A coupling lattice Boltzmann equation (LBE) model with multiple relaxation times is proposed for thermal flows with viscous heat dissipation and compression work. In this model the fixed Prandtl number and the viscous dissipation problems in the energy equation, which exist in most of the LBE models, are successfully overcome. The model is validated by simulating the two-dimensional Couette flow, thermal Poiseuille flow, and the natural convection flow in a square cavity. It is found that the numerical results agree well with the analytical solutions and/or other numerical results.
Virtual sensor models for real-time applications
Hirsenkorn, Nils; Hanke, Timo; Rauch, Andreas; Dehlink, Bernhard; Rasshofer, Ralph; Biebl, Erwin
2016-09-01
Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.
Time series ARIMA models for daily price of palm oil
Ariff, Noratiqah Mohd; Zamhawari, Nor Hashimah; Bakar, Mohd Aftar Abu
2015-02-01
Palm oil is deemed as one of the most important commodity that forms the economic backbone of Malaysia. Modeling and forecasting the daily price of palm oil is of great interest for Malaysia's economic growth. In this study, time series ARIMA models are used to fit the daily price of palm oil. The Akaike Infromation Criterion (AIC), Akaike Infromation Criterion with a correction for finite sample sizes (AICc) and Bayesian Information Criterion (BIC) are used to compare between different ARIMA models being considered. It is found that ARIMA(1,2,1) model is suitable for daily price of crude palm oil in Malaysia for the year 2010 to 2012.
Simplified Model of Brushless Synchronous Generator for Real Time Simulation
Lopez, M D; Rebollo, E; Blanquez, F R
2015-01-01
This paper presents a simplified model of brushless synchronous machine for saving hardware resources in a real time simulation system. Firstly, a brushless excitation system model is described. Thereafter, the simplified transfer function of an AC exciter and rotating diodes of the brushless excitation system is estimated. Finally, the complete system is simulated, comparing the main generator's voltage with both detailed and simplified excitation systems in several scenarios. These results show the accuracy of the simplified model against the detailed simulation model, resulting on an important hardware resources savings.
A novel trauma leadership model reflective of changing times.
DʼHuyvetter, Cecile; Cogbill, Thomas H
2014-01-01
As a result of generational changes in the health care workforce, we sought to evaluate our current Trauma Medical Director Leadership model. We assessed the responsibilities, accountability, time requirements, cost, and provider satisfaction with the current leadership model. Three new providers who had recently completed fellowship training were hired, each with unique professional desires, skill sets, and experience. Our goal was to establish a comprehensive, cost-effective, accountable leadership model that enabled provider satisfaction and equalized leadership responsibilities. A 3-pronged team model was established with a Medical Director title and responsibilities rotating per the American College of Surgeons verification cycle to develop leadership skills and lessen hierarchical differences.
Real time modeling, simulation and control of dynamical systems
Mughal, Asif Mahmood
2016-01-01
This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.
Generating survival times to simulate Cox proportional hazards models with time-varying covariates.
Austin, Peter C
2012-12-20
Simulations and Monte Carlo methods serve an important role in modern statistical research. They allow for an examination of the performance of statistical procedures in settings in which analytic and mathematical derivations may not be feasible. A key element in any statistical simulation is the existence of an appropriate data-generating process: one must be able to simulate data from a specified statistical model. We describe data-generating processes for the Cox proportional hazards model with time-varying covariates when event times follow an exponential, Weibull, or Gompertz distribution. We consider three types of time-varying covariates: first, a dichotomous time-varying covariate that can change at most once from untreated to treated (e.g., organ transplant); second, a continuous time-varying covariate such as cumulative exposure at a constant dose to radiation or to a pharmaceutical agent used for a chronic condition; third, a dichotomous time-varying covariate with a subject being able to move repeatedly between treatment states (e.g., current compliance or use of a medication). In each setting, we derive closed-form expressions that allow one to simulate survival times so that survival times are related to a vector of fixed or time-invariant covariates and to a single time-varying covariate. We illustrate the utility of our closed-form expressions for simulating event times by using Monte Carlo simulations to estimate the statistical power to detect as statistically significant the effect of different types of binary time-varying covariates. This is compared with the statistical power to detect as statistically significant a binary time-invariant covariate.
A model for discriminating reinforcers in time and space.
Cowie, Sarah; Davison, Michael; Elliffe, Douglas
2016-06-01
Both the response-reinforcer and stimulus-reinforcer relation are important in discrimination learning; differential responding requires a minimum of two discriminably-different stimuli and two discriminably-different associated contingencies of reinforcement. When elapsed time is a discriminative stimulus for the likely availability of a reinforcer, choice over time may be modeled by an extension of the Davison and Nevin (1999) model that assumes that local choice strictly matches the effective local reinforcer ratio. The effective local reinforcer ratio may differ from the obtained local reinforcer ratio for two reasons: Because the animal inaccurately estimates times associated with obtained reinforcers, and thus incorrectly discriminates the stimulus-reinforcer relation across time; and because of error in discriminating the response-reinforcer relation. In choice-based timing tasks, the two responses are usually highly discriminable, and so the larger contributor to differences between the effective and obtained reinforcer ratio is error in discriminating the stimulus-reinforcer relation. Such error may be modeled either by redistributing the numbers of reinforcers obtained at each time across surrounding times, or by redistributing the ratio of reinforcers obtained at each time in the same way. We assessed the extent to which these two approaches to modeling discrimination of the stimulus-reinforcer relation could account for choice in a range of temporal-discrimination procedures. The version of the model that redistributed numbers of reinforcers accounted for more variance in the data. Further, this version provides an explanation for shifts in the point of subjective equality that occur as a result of changes in the local reinforcer rate. The inclusion of a parameter reflecting error in discriminating the response-reinforcer relation enhanced the ability of each version of the model to describe data. The ability of this class of model to account for a
The comparison of immobility time in experimental rat swimming models.
Calil, Caroline Morini; Marcondes, Fernanda Klein
2006-09-27
Rat swimming models have been used in studies about stress and depression. However, there is no consensus about interpreting immobility (helplessness or adaptation) in the literature. In the present study, immobility time, glucose and glycogen mobilization, corticosterone and the effect of desipramine and diazepam were investigated in two different models: swimming stress and the forced swimming test. Immobility time was lower in swimming stress than in the forced swimming test. Both swimming models increased corticosterone levels in comparison with control animal levels. Moreover, swimming stress induced higher corticosterone levels than the forced swimming test did [F(2,14)=59.52; pswimming stressswimming testswimming stress in comparison with the forced swimming test and control. The immobility time was recorded and measured in another group treated with desipramine and diazepam in two protocols: a single session of forced swimming test or swimming stress and two sessions (pre- and retest) of forced swimming model or swimming stress. Desipramine decreased the immobility time in the forced swimming test in both the single [F(2,25)=20.63; pswimming session, without changes in the swimming stress model. Diazepam increased the immobility time in the swimming stress but not in the forced swimming test during the single [F(2,26)=11.24; p=0.0003] and retest sessions [F(2,38)=4.17; p=0.02]. It was concluded that swimming stress and the forced swimming test induced different behavior, hormonal and metabolic responses and represented different situations to the animal.
Muthyala, Sudhakar; Raj, V R Rana; Mohanty, Mira; Mohanan, P V; Nair, Prabha D
2011-05-01
Type 1 diabetes is a chronic disorder resulting from the autoimmune destruction of insulin-producing cells, a leading cause of morbidity and mortality all over the world. In this study a tissue engineering approach was compared with a macroencapsulation approach to reverse type 1 diabetes in a rat model, using mouse pancreatic progenitor cell (PPC)-derived islet-like clusters and mouse islets. For the tissue engineering approach the cells were cultured on gelatin scaffolds cross-linked with EDC in the presence of polyvinylpyrrolidone in vitro (GPE scaffolds), while for the macroencapsulation approach the cells were encapsulated in polyurethane-polyvinylpyrrolidone semi-interpenetrating networks. In the combination approach the cells cultured on GPE scaffolds were further encapsulated in a polyurethane-polyvinylpyrrolidone capsule. Real time PCR studies and the glucose challenge assay have shown that cells on GPE scaffolds could express and secrete insulin and glucagon in vitro. However, under in vivo conditions the animals treated by the tissue engineering approach died within 15-20 days and showed no reversal of their diabetes, due to infiltration of immune cells such as CD4 and CD8 cells and macrophages. In the macroencapsulation approach the animals showed euglycemia within 25 days, which was maintained for further 20 days, but after that the animals died. Interestingly, in the combination approach the animals showed reversal of hyperglycemia, and remained euglycemic for up to 3 months. The time needed to achieve initial euglycemia was different with different cell types, i.e. the combination approach with mouse islets achieved euglycemia within 15 days, whereas with PPC-derived islet-like clusters euglycemia was achieved within 25 days. This study confirmed that a combination of tissue engineering and macroencapsulation with mouse islets could reverse diabetes and maintain euglycemia in an experimental diabetes rat model for 90 days.
Seismic hazard assessment over time: Modelling earthquakes in Taiwan
Chan, Chung-Han; Wang, Yu; Wang, Yu-Ju; Lee, Ya-Ting
2017-04-01
To assess the seismic hazard with temporal change in Taiwan, we develop a new approach, combining both the Brownian Passage Time (BPT) model and the Coulomb stress change, and implement the seismogenic source parameters by the Taiwan Earthquake Model (TEM). The BPT model was adopted to describe the rupture recurrence intervals of the specific fault sources, together with the time elapsed since the last fault-rupture to derive their long-term rupture probability. We also evaluate the short-term seismicity rate change based on the static Coulomb stress interaction between seismogenic sources. By considering above time-dependent factors, our new combined model suggests an increased long-term seismic hazard in the vicinity of active faults along the western Coastal Plain and the Longitudinal Valley, where active faults have short recurrence intervals and long elapsed time since their last ruptures, and/or short-term elevated hazard levels right after the occurrence of large earthquakes due to the stress triggering effect. The stress enhanced by the February 6th, 2016, Meinong ML 6.6 earthquake also significantly increased rupture probabilities of several neighbouring seismogenic sources in Southwestern Taiwan and raised hazard level in the near future. Our approach draws on the advantage of incorporating long- and short-term models, to provide time-dependent earthquake probability constraints. Our time-dependent model considers more detailed information than any other published models. It thus offers decision-makers and public officials an adequate basis for rapid evaluations of and response to future emergency scenarios such as victim relocation and sheltering.
Space and Time Ontology: New Models for New Physics
Directory of Open Access Journals (Sweden)
Sara Lumbreras Sancho
2015-02-01
Full Text Available Nickel proposes a model for movement – and in general, for change – in which each instant in time (characterized as the set of real numbers is assigned to one point in a configuration space. As much as this model seems to intuitively fit to our experience, it implies a number of assumptions about the nature of space and time that are interesting to explore. Different perspectives have been developed across History, and it could well be that the next scientific revolution is set in motion by an innovative conception of space and time. One of this alternative perspectives was proposed by Julian Barbour, who has developed a new model of Physics where time does not exist [Barbour, 1999]. This paper reviews not only this concept but also other similarly provocative ideas that might prove useful for improving our understanding of the universe. Prior to this, the relevance of the philosophy of space and time will be briefly outlined and its history reviewed to provide some background for the discussed models. Finally, an approach where space and time are only defined by convention will be considered.
Mechatronic modeling of real-time wheel-rail contact
Bosso, Nicola; Gugliotta, Antonio; Somà, Aurelio
2013-01-01
Real-time simulations of the behaviour of a rail vehicle require realistic solutions of the wheel-rail contact problem which can work in a real-time mode. Examples of such solutions for the online mode have been well known and are implemented within standard and commercial tools for the simulation codes for rail vehicle dynamics. This book is the result of the research activities carried out by the Railway Technology Lab of the Department of Mechanical and Aerospace Engineering at Politecnico di Torino. This book presents work on the project for the development of a real-time wheel-rail contact model and provides the simulation results obtained with dSpace real-time hardware. Besides this, the implementation of the contact model for the development of a real-time model for the complex mechatronic system of a scaled test rig is presented in this book and may be useful for the further validation of the real-time contact model with experiments on a full scale test rig.
DEFF Research Database (Denmark)
Tastu, Julija; Pinson, Pierre; Madsen, Henrik
The emphasis in this work is placed on generating space-time trajectories (also referred to as scenarios) of wind power generation. This calls for prediction of multivariate densities describing wind power generation at a number of distributed locations and for a number of successive lead times. ...
Model Passengers’ Travel Time for Conventional Bus Stop
Directory of Open Access Journals (Sweden)
Guangzhao Xin
2014-01-01
Full Text Available Limited number of berths can result in a subsequent bus stopping at the upstream of a bus stop when all berths are occupied. When this traffic phenomenon occurs, passengers waiting on the platform usually prefer walking to the stopped bus, which leads to additional walking time before boarding the bus. Therefore, passengers’ travel time consumed at a bus stop is divided into waiting time, additional walking time, and boarding time. This paper proposed a mathematical model for analyzing passengers’ travel time at conventional bus stop based on theory of stochastic service system. Field-measured and simulated data were designated to demonstrate the effectiveness of the proposed model. By analyzing the results, conclusion was conducted that short headway can reduce passengers’ waiting time at bus stop. Meanwhile, the theoretical analysis explained the inefficiency of bus stops with more than three berths from the perspective of passengers’ additional walking time. Additional walking time will increase in a large scale when the number of berths at a bus stop exceedsthe threshold of three.
Abazajian, Kevork N
2014-04-25
Sterile neutrinos produced through a resonant Shi-Fuller mechanism are arguably the simplest model for a dark matter interpretation of the origin of the recent unidentified x-ray line seen toward a number of objects harboring dark matter. Here, I calculate the exact parameters required in this mechanism to produce the signal. The suppression of small-scale structure predicted by these models is consistent with Local Group and high-z galaxy count constraints. Very significantly, the parameters necessary in these models to produce the full dark matter density fulfill previously determined requirements to successfully match the Milky Way Galaxy's total satellite abundance, the satellites' radial distribution, and their mass density profile, or the "too-big-to-fail problem." I also discuss how further precision determinations of the detailed properties of the candidate sterile neutrino dark matter can probe the nature of the quark-hadron transition, which takes place during the dark matter production.
Pinacho, Daniel G; Sánchez-Baeza, Francisco; Marco, M-Pilar
2012-05-15
Antibodies with a wide recognition profile of fluoroquinolone antibiotics have been produced based on chemical criteria, theoretical studies, and molecular modeling assisted hapten design. The immunizing hapten preserves the most important and characteristic epitopes of this antibiotic family. The studies have taken into consideration the zwitterionic character of most of the fluoroquinolones and the relative concentration of the different species in equilibrium at physiologic pH. The hapten is prepared in the form of a stable prehapten through a 5 step synthetic pathway. Immediately before conjugation, the immunizing hapten is obtained by removing the diphenylmethane protecting group. The specificity of the antibodies obtained is directed toward the common area defined by the fluorine atom at position 6 and the β-ketoacid moiety. The ELISA developed is able to recognize with very good detectability important fluoroquinolones used in the veterinary field such as ciprofloxacin (CPFX, IC(50), 0.35 μg L(-1)), enrofloxacin (ERFX, IC(50), 0.65 μg L(-1)), danofloxacin (DNFX, IC(50), 7.31 μg L(-1)), difloxacin (DFX, IC(50), 0.91 μg L(-1)), sarafloxacin (SRFX, IC(50), 0.96 μg L(-1)), norfloxacin (NRFX, IC(50), 0.78 μg L(-1)), ofloxacin (OFX, IC(50), 1.84 μg L(-1)), flumequine (Flume, IC(50), 3.91 μ gL(-1)), marbofloxacin (MBFX, IC(50), 4.30 μ gL(-1)), and oxolinic acid (OXO, IC(50), 23.53 μg L(-1)). The results presented here demonstrate that the antibody affinity is strongly affected by the presence of divalent cations, owing to their complexation with the fluoroquinolone molecules. Moreover, the outcome from the effect of the pH on the immunochemical assays suggests that the selectivity could be modulated with the pH due to the zwitterionic character of the fluoroquinolones and as a function of their different pK(a) values.
HIGH ORDER FUZZY TIME SERIES MODEL AND ITS APLICATION TO IMKB
Directory of Open Access Journals (Sweden)
Çağdaş Hakan ALADAĞ
2010-12-01
Full Text Available The observations of some real time series such as temperature and stock market can take different values in a day. Instead of representing the observations of these time series by real numbers, employing linguistic values or fuzzy sets can be more appropriate. In recent years, many approaches have been introduced to analyze time series consisting of observations which are fuzzy sets and such time series are called fuzzy time series. In this study, a novel approach is proposed to analyze high order fuzzy time series model. The proposed method is applied to IMKB data and the obtained results are discussed. IMKB data is also analyzed by using some other fuzzy time series methods available in the literature and obtained results are compared to results obtained from the proposed method. As a result of the comparison, it is seen that the proposed method produce accurate forecasts.
Pola, Giordano; Di Benedetto, Maria Domenica
2010-01-01
Time-delay systems are an important class of dynamical systems that provide a solid mathematical framework to deal with many application domains of interest. In this paper we focus on nonlinear control systems with unknown and time-varying delay signals and we propose one approach to the control design of such systems, which is based on the construction of symbolic models. Symbolic models are abstract descriptions of dynamical systems in which one symbolic state and one symbolic input correspond to an aggregate of states and an aggregate of inputs. We first introduce the notion of incremental input-delay-to-state stability and characterize it by means of Liapunov-Krasovskii functionals. We then derive sufficient conditions for the existence of symbolic models that are shown to be alternating approximately bisimilar to the original system. Further results are also derived which prove the computability of the proposed symbolic models in a finite number of steps.
Model of observed stochastic balance between work and free time supporting the LQTAI definition
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2008-01-01
A balance differential equation between free time and money-producing work time on the national economy level is formulated in a previous paper in terms of two dimensionless quantities, the fraction of work time and the total productivity factor defined as the ratio of the Gross Domestic Product...... to the total salary paid in return for work. Among the solutions there is one relation that compares surprisingly well with the relevant sequences of Danish data spanning from 1948 to 2003, and also with similar data from several other countries except for slightly different model parameter values. Statistical...
An economic production model for time dependent demand with rework and multiple production setups
Directory of Open Access Journals (Sweden)
S.R. Singh
2014-04-01
Full Text Available In this paper, we present a model for time dependent demand with multiple productions and rework setups. Production is demand dependent and greater than the demand rate. Production facility produces items in m production setups and one rework setup (m, 1 policy. The major reason of reverse logistic and green supply chain is rework, so it reduces the cost of production and other ecological problems. Most of the researchers developed a rework model without deteriorating items. A numerical example and sensitivity analysis is shown to describe the model.
Model for Predicting End User Web Page Response Time
Nagarajan, Sathya Narayanan
2012-01-01
Perceived responsiveness of a web page is one of the most important and least understood metrics of web page design, and is critical for attracting and maintaining a large audience. Web pages can be designed to meet performance SLAs early in the product lifecycle if there is a way to predict the apparent responsiveness of a particular page layout. Response time of a web page is largely influenced by page layout and various network characteristics. Since the network characteristics vary widely from country to country, accurately modeling and predicting the perceived responsiveness of a web page from the end user's perspective has traditionally proven very difficult. We propose a model for predicting end user web page response time based on web page, network, browser download and browser rendering characteristics. We start by understanding the key parameters that affect perceived response time. We then model each of these parameters individually using experimental tests and statistical techniques. Finally, we d...
Reading Time as Evidence for Mental Models in Understanding Physics
Brookes, David T.; Mestre, José; Stine-Morrow, Elizabeth A. L.
2007-11-01
We present results of a reading study that show the usefulness of probing physics students' cognitive processing by measuring reading time. According to contemporary discourse theory, when people read a text, a network of associated inferences is activated to create a mental model. If the reader encounters an idea in the text that conflicts with existing knowledge, the construction of a coherent mental model is disrupted and reading times are prolonged, as measured using a simple self-paced reading paradigm. We used this effect to study how "non-Newtonian" and "Newtonian" students create mental models of conceptual systems in physics as they read texts related to the ideas of Newton's third law, energy, and momentum. We found significant effects of prior knowledge state on patterns of reading time, suggesting that students attempt to actively integrate physics texts with their existing knowledge.
Reaction times to weak test lights. [psychophysics biological model
Wandell, B. A.; Ahumada, P.; Welsh, D.
1984-01-01
Maloney and Wandell (1984) describe a model of the response of a single visual channel to weak test lights. The initial channel response is a linearly filtered version of the stimulus. The filter output is randomly sampled over time. Each time a sample occurs there is some probability increasing with the magnitude of the sampled response - that a discrete detection event is generated. Maloney and Wandell derive the statistics of the detection events. In this paper a test is conducted of the hypothesis that the reaction time responses to the presence of a weak test light are initiated at the first detection event. This makes it possible to extend the application of the model to lights that are slightly above threshold, but still within the linear operating range of the visual system. A parameter-free prediction of the model proposed by Maloney and Wandell for lights detected by this statistic is tested. The data are in agreement with the prediction.
Minimal state space realisation of continuous-time linear time-variant input-output models
Goos, J.; Pintelon, R.
2016-04-01
In the linear time-invariant (LTI) framework, the transformation from an input-output equation into state space representation is well understood. Several canonical forms exist that realise the same dynamic behaviour. If the coefficients become time-varying however, the LTI transformation no longer holds. We prove by induction that there exists a closed-form expression for the observability canonical state space model, using binomial coefficients.
Model Reduction via Time-Interval Balanced Stochastic Truncation for Linear Time Invariant Systems
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Shaker, Hamid Reza
2013-01-01
In this article, a new method for model reduction of linear dynamical systems is presented. The proposed technique is from the family of gramian-based relative error model reduction methods. The method uses time-interval gramians in the reduction procedure rather than ordinary gramians and in suc...... player example. The numerical results show that the method is more accurate than ordinary balanced stochastic truncation....
Modeling and Analysis of Time-Varying Graphs
Basu, Prithwish; Ramanathan, Ram; Johnson, Matthew P
2010-01-01
We live in a world increasingly dominated by networks -- communications, social, information, biological etc. A central attribute of many of these networks is that they are dynamic, that is, they exhibit structural changes over time. While the practice of dynamic networks has proliferated, we lag behind in the fundamental, mathematical understanding of network dynamism. Existing research on time-varying graphs ranges from preliminary algorithmic studies (e.g., Ferreira's work on evolving graphs) to analysis of specific properties such as flooding time in dynamic random graphs. A popular model for studying dynamic graphs is a sequence of graphs arranged by increasing snapshots of time. In this paper, we study the fundamental property of reachability in a time-varying graph over time and characterize the latency with respect to two metrics, namely store-or-advance latency and cut-through latency. Instead of expected value analysis, we concentrate on characterizing the exact probability distribution of routing l...
A flexible coefficient smooth transition time series model.
Medeiros, Marcelo C; Veiga, Alvaro
2005-01-01
In this paper, we consider a flexible smooth transition autoregressive (STAR) model with multiple regimes and multiple transition variables. This formulation can be interpreted as a time varying linear model where the coefficients are the outputs of a single hidden layer feedforward neural network. This proposal has the major advantage of nesting several nonlinear models, such as, the self-exciting threshold autoregressive (SETAR), the autoregressive neural network (AR-NN), and the logistic STAR models. Furthermore, if the neural network is interpreted as a nonparametric universal approximation to any Borel measurable function, our formulation is directly comparable to the functional coefficient autoregressive (FAR) and the single-index coefficient regression models. A model building procedure is developed based on statistical inference arguments. A Monte Carlo experiment showed that the procedure works in small samples, and its performance improves, as it should, in medium size samples. Several real examples are also addressed.
Model predictive control of P-time event graphs
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.
Directory of Open Access Journals (Sweden)
Rilda LEÓN
2014-05-01
Full Text Available Cerebral ischemia is a major cause of death, for this reason animal models of cerebral ischemia are widely used to study both the pathophysiology of ischemic phenomenon and the evaluation of possible therapeutic agents with protective or regenerative properties. The objectives of this study were to examine the presence of neuronal damage in different brain areas following the ischemic event, and assess consequences of such activities on the processes of memory and learning. The study group included an experimental group ischemic animals (30 rats with permanent bilateral occlusion of the carotids, and a control group. Was evaluated gene expression and inflammatory ischemic by qPCR techniques 24h post injury, brain tissue morphology in areas of cortex, striatum and hippocampus seven days post injury and processes of memory and learning, 12 days post injury. The morphological studies showed that the procedure induces death of cell populations in cortex, striatum and hippocampus, ischemia modified gfap gene expression and ho, il-6, il-17 and ifn-γ, which can be used as a marker of early ischemic process. Additionally, the ischemic injury caused spatial memory decline. This characterization gives us an experimental model to develop future studies on the pathophysiology of ischemic events and assessing therapeutic strategies.MODELO EXPERIMENTAL DE HIPOPERFUSIÓN CEREBRAL PRODUCE DÉFICIT DE LA MEMORIA Y APRENDIZAJE Y MODIFICACIONES EN LA EXPRESIÓN DE GENES.A escala mundial, la isquemia cerebral constituye una de las principales causas de muerte, por lo que los modelos animales de isquemia cerebral son extensamente usados tanto en el estudio de la pato-fisiología del fenómeno isquémico; como en la evaluación de agentes terapéuticos con posible efecto protector o regenerador. Los objetivos de este estudio fueron examinar la presencia de daño neuronal en diferentes áreas cerebrales como consecuencia del evento isquémico; así como evaluar
DEFF Research Database (Denmark)
Busato, P.; Sopegno, A.; Berruto, R.
2013-01-01
together to form a large size lot at some points in the supply-chain. Larger lot size could imply higher risk for the consumers in case of recall of the produce and much higher recall time and cost for the supply-chain. When a non-conformity occurs, the time to recall the produce depends on many factors...... the consumer. Each of these is a system itself that interacts with the other components of the supply-chain. The nonconformity could occur in each of these links. Because of processing plant requirement, storage requirements, and because of savings in the traceability process, often small size lots are merged...
Olhaye, Omar
2013-01-01
Produced water is one of the biggest environmental challenges in gas and crude oil production, and the stability of oil in water emulsions makes separation during treatments difficult.The objective of this work is to find out how interfacial active compounds contribute to the stability of oil/water emulsions. A model naphthenic acid dissolved in model oil was used together with a synthetic aqueous brine of different pH values in order to mimic produced water conditions. The experiment was con...
Candidate main-field models for producing the 9th generation IGRF
Mandea, Mioara
2005-12-01
This paper presents the various candidate models used in deriving the 9th generation IGRF. Based on notes submitted to the IAGA working group V-MOD with the Gauss coefficients, a brief description of the data used and the method of modelling for each of the candidate models is given. The six candidate models for epoch 1995.0 and the five for epoch 2000.0 are presented. Improvements gained by the new models are also discussed.
From Safety Critical Java Programs to Timed Process Models
DEFF Research Database (Denmark)
Thomsen, Bent; Luckow, Kasper Søe; Thomsen, Lone Leth
2015-01-01
built and the tools have been used to analyse a number of systems for properties such as worst case execution time, schedulability and energy optimization [12–14,19,34,36,38]. In this paper we will elaborate on the theoretical underpinning of the translation from Java programs to timed automata models...... frameworks, we have in recent years pursued an agenda of translating hard-real-time embedded safety critical programs written in the Safety Critical Java Profile [33] into networks of timed automata [4] and subjecting those to automated analysis using the UPPAAL model checker [10]. Several tools have been...... and briefly summarize some of the results based on this translation. Furthermore, we discuss future work, especially relations to the work in [16,24] as Java recently has adopted first class higher order functions in the form of lambda abstractions....
Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis
Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.
2015-06-01
This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.
A Simple Pile-up Model for Time Series Analysis
Sevilla, Diego J. R.
2017-07-01
In this paper, a simple pile-up model is presented. This model calculates the probability P(n| N) of having n counts if N particles collide with a sensor during an exposure time. Through some approximations, an analytic expression depending on only one parameter is obtained. This parameter characterizes the pile-up magnitude, and depends on features of the instrument and the source. The statistical model obtained permits the determination of probability distributions of measured counts from the probability distributions of incoming particles, which is valuable for time series analysis. Applicability limits are discussed, and an example of the improvement that can be achieved in the statistical analysis considering the proposed pile-up model is shown by analyzing real data.
Time Delay in the Kuramoto Model of Coupled Oscillators
Yeung, M K S; Strogatz, Steven H.
1999-01-01
We generalize the Kuramoto model of coupled oscillators to allow time-delayed interactions. New phenomena include bistability between synchronized and incoherent states, and unsteady solutions with time-dependent order parameters. We derive exact formulas for the stability boundaries of the incoherent and synchronized states, as a function of the delay, in the special case where the oscillators are identical. The experimental implications of the model are discussed for populations of chirping crickets, where the finite speed of sound causes communication delays, and for physical systems such as coupled phase-locked loops or lasers.
Time fractional capital-induced labor migration model
Ali Balcı, Mehmet
2017-07-01
In this study we present a new model of neoclassical economic growth by considering that workers move from regions with lower density of capital to regions with higher density of capital. Since the labor migration and capital flow involves self-similarities in long range time, we use the fractional order derivatives for the time variable. To solve this model we proposed Variational Iteration Method, and studied numerically labor migration flow data from Turkey along with other countries throughout the period of 1966-2014.
A Real-Time Performance Analysis Model for Cryptographic Protocols
Directory of Open Access Journals (Sweden)
Amos Olagunju
2012-12-01
Full Text Available Several encryption algorithms exist today for securing data in storage and transmission over network systems. The choice of encryption algorithms must weigh performance requirements against the call for protection of sensitive data. This research investigated the processing times of alternative encryption algorithms under specific conditions. The paper presents the architecture of a model multiplatform tool for the evaluation of candidate encryption algorithms based on different data and key sizes. The model software was used to appraise the real-time performance of DES, AES, 3DES, MD5, SHA1, and SHA2 encryption algorithms.
Time variability of α from realistic models of Oklo reactors
Gould, C. R.; Sharapov, E. I.; Lamoreaux, S. K.
2006-08-01
We reanalyze Oklo Sm149 data using realistic models of the natural nuclear reactors. Disagreements among recent Oklo determinations of the time evolution of α, the electromagnetic fine structure constant, are shown to be due to different reactor models, which led to different neutron spectra used in the calculations. We use known Oklo reactor epithermal spectral indices as criteria for selecting realistic reactor models. Two Oklo reactors, RZ2 and RZ10, were modeled with MCNP. The resulting neutron spectra were used to calculate the change in the Sm149 effective neutron capture cross section as a function of a possible shift in the energy of the 97.3-meV resonance. We independently deduce ancient Sm149 effective cross sections and use these values to set limits on the time variation of α. Our study resolves a contradictory situation with previous Oklo α results. Our suggested 2σ bound on a possible time variation of α over 2 billion years is stringent: -0.11≤Δα/α≤0.24, in units of 10-7, but model dependent in that it assumes only α has varied over time.
Detailed models for timing and efficiency in resistive plate chambers
Riegler, Werner
2003-01-01
We discuss detailed models for detector physics processes in Resistive Plate Chambers, in particular including the effect of attachment on the avalanche statistics. In addition, we present analytic formulas for average charges and intrinsic RPC time resolution. Using a Monte Carlo simulation including all the steps from primary ionization to the front-end electronics we discuss the dependence of efficiency and time resolution on parameters like primary ionization, avalanche statistics and threshold.
Tactical Atmospheric Modeling System-Real Time (TAMS-RT)
2016-06-07
subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 30...mesoscale model analysis and forecast fields as inputs. OBJECTIVES Support the NRL Tactical Atmospheric Modeling System-Real Time (TAMS-RT) installed in...installation at NCMOC, the Space and Naval Warfare Systems Command (SPAWAR), who has configuration management oversight for TEDS, has changed the TEDS
Real time detection of structural breaks in GARCH models
He, Zhongfang; Maheu, John M.
2009-01-01
This paper proposes a sequential Monte Carlo method for estimating GARCH models subject to an unknown number of structural breaks. We use particle filtering techniques that allow for fast and efficient updates of posterior quantities and forecasts in real-time. The method conveniently deals with the path dependence problem that arises in these type of models. The performance of the method is shown to work well using simulated data. Applied to daily NASDAQ returns, the evidence favors a partia...
A model for discussing entropy and time reversibility
Castellani, Tommaso
2014-01-01
In this article we discuss a model used to introduce the concept of entropy with secondary school students. It can be used to discuss with students the reversibility of time, the tendency towards homogeneity and the link between probability theory and second law of thermodynamics. The model is useful to introduce crucial epistemological issues and helps student to understand the deep connection between the macroscopic and the microscopic.
The time-dependent one-zone hadronic model - First principles
Dimitrakoudis, S; Protheroe, R J; Reimer, A
2012-01-01
We present a time-dependent approach to the one-zone hadronic model in the case where the photon spectrum is produced by ultrarelativistic protons interacting with soft photons that are produced from protons and low magnetic fields. Assuming that protons are injected at a certain rate in a homogeneous spherical volume containing a magnetic field, the evolution of the system can be described by five coupled kinetic equations, for protons, electrons, photons, neutrons, and neutrinos. Photopair and photopion interactions are modelled using the results of Monte-Carlo simulations and, in particular from the SOPHIA code for the latter. The coupling of energy losses and injection introduces a self-consistency in our approach and allows the study of the comparative relevancy of processes at various conditions, the efficiency of the conversion of proton luminosity to radiation, the resulting neutrino spectra, and the effects of time variability on proton injection, among other topics. We present some characteristic ex...
She, M.; Jiang, L. P.
2014-12-01
In this paper, an oscillating dark energy model is presented in an isotropic but inhomogeneous plane symmetric space-time by considering a time periodic varying deceleration parameter. We find three different types of new solutions which describe different scenarios of oscillating universe. The first two solutions show an oscillating universe with singularities. For the third one, the universe is singularity-free during the whole evolution. Moreover, the Hubble parameter oscillates and keeps positive which explores an interesting possibility to unify the early inflation and late time acceleration of the universe.
Motivation and timing: clues for modeling the reward system.
Galtress, Tiffany; Marshall, Andrew T; Kirkpatrick, Kimberly
2012-05-01
There is growing evidence that a change in reward magnitude or value alters interval timing, indicating that motivation and timing are not independent processes as was previously believed. The present paper reviews several recent studies, as well as presenting some new evidence with further manipulations of reward value during training vs. testing on a peak procedure. The combined results cannot be accounted for by any of the current psychological timing theories. However, in examining the neural circuitry of the reward system, it is not surprising that motivation has an impact on timing because the motivation/valuation system directly interfaces with the timing system. A new approach is proposed for the development of the next generation of timing models, which utilizes knowledge of the neuroanatomy and neurophysiology of the reward system to guide the development of a neurocomputational model of the reward system. The initial foundation along with heuristics for proceeding with developing such a model is unveiled in an attempt to stimulate new theoretical approaches in the field.
LATEST: A model of saccadic decisions in space and time.
Tatler, Benjamin W; Brockmole, James R; Carpenter, R H S
2017-04-01
Many of our actions require visual information, and for this it is important to direct the eyes to the right place at the right time. Two or three times every second, we must decide both when and where to direct our gaze. Understanding these decisions can reveal the moment-to-moment information priorities of the visual system and the strategies for information sampling employed by the brain to serve ongoing behavior. Most theoretical frameworks and models of gaze control assume that the spatial and temporal aspects of fixation point selection depend on different mechanisms. We present a single model that can simultaneously account for both when and where we look. Underpinning this model is the theoretical assertion that each decision to move the eyes is an evaluation of the relative benefit expected from moving the eyes to a new location compared with that expected by continuing to fixate the current target. The eyes move when the evidence that favors moving to a new location outweighs that favoring staying at the present location. Our model provides not only an account of when the eyes move, but also what will be fixated. That is, an analysis of saccade timing alone enables us to predict where people look in a scene. Indeed our model accounts for fixation selection as well as (and often better than) current computational models of fixation selection in scene viewing. (PsycINFO Database Record
Breeding return times and abundance in capture-recapture models.
Pledger, Shirley; Baker, Edward; Scribner, Kim
2013-12-01
For many long-lived animal species, individuals do not breed every year, and are often not accessible during non-breeding periods. Individuals exhibit site fidelity if they return to the same breeding colony or spawning ground when they breed. If capture and recapture is only possible at the breeding site, temporary emigration models are used to allow for only a subset of the animals being present in any given year. Most temporary emigration models require the use of the robust sampling design, and their focus is usually on probabilities of annual survival and of transition between breeding and non-breeding states. We use lake sturgeon (Acipenser fulvescens) data from a closed population where only a simple (one sample per year) sampling scheme is possible, and we also wish to estimate abundance as well as sex-specific survival and breeding return time probabilities. By adding return time parameters to the Schwarz-Arnason version of the Jolly-Seber model, we have developed a new likelihood-based model which yields plausible estimates of abundance, survival, transition and return time parameters. An important new finding from investigation of the model is the overestimation of abundance if a Jolly-Seber model is used when Markovian temporary emigration is present.
Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin
2015-01-01
Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280
Models of emergency departments for reducing patient waiting times.
Laskowski, Marek; McLeod, Robert D; Friesen, Marcia R; Podaima, Blake W; Alfa, Attahiru S
2009-07-02
In this paper, we apply both agent-based models and queuing models to investigate patient access and patient flow through emergency departments. The objective of this work is to gain insights into the comparative contributions and limitations of these complementary techniques, in their ability to contribute empirical input into healthcare policy and practice guidelines. The models were developed independently, with a view to compare their suitability to emergency department simulation. The current models implement relatively simple general scenarios, and rely on a combination of simulated and real data to simulate patient flow in a single emergency department or in multiple interacting emergency departments. In addition, several concepts from telecommunications engineering are translated into this modeling context. The framework of multiple-priority queue systems and the genetic programming paradigm of evolutionary machine learning are applied as a means of forecasting patient wait times and as a means of evolving healthcare policy, respectively. The models' utility lies in their ability to provide qualitative insights into the relative sensitivities and impacts of model input parameters, to illuminate scenarios worthy of more complex investigation, and to iteratively validate the models as they continue to be refined and extended. The paper discusses future efforts to refine, extend, and validate the models with more data and real data relative to physical (spatial-topographical) and social inputs (staffing, patient care models, etc.). Real data obtained through proximity location and tracking system technologies is one example discussed.
An Expectation Maximization Algorithm to Model Failure Times by Continuous-Time Markov Chains
Directory of Open Access Journals (Sweden)
Qihong Duan
2010-01-01
Full Text Available In many applications, the failure rate function may present a bathtub shape curve. In this paper, an expectation maximization algorithm is proposed to construct a suitable continuous-time Markov chain which models the failure time data by the first time reaching the absorbing state. Assume that a system is described by methods of supplementary variables, the device of stage, and so on. Given a data set, the maximum likelihood estimators of the initial distribution and the infinitesimal transition rates of the Markov chain can be obtained by our novel algorithm. Suppose that there are m transient states in the system and that there are n failure time data. The devised algorithm only needs to compute the exponential of m×m upper triangular matrices for O(nm2 times in each iteration. Finally, the algorithm is applied to two real data sets, which indicates the practicality and efficiency of our algorithm.
Lambert, Max R.
2015-01-01
In amphibians, abnormal metamorph sex ratios and sexual development have almost exclusively been considered in response to synthetic compounds like pesticides or pharmaceuticals. However, endocrine-active plant chemicals (i.e. phytoestrogens) are commonly found in agricultural and urban waterways hosting frog populations with deviant sexual development. Yet the effects of these compounds on amphibian development remain predominantly unexplored. Legumes, like clover, are common in agricultural fields and urban yards and exude phytoestrogen mixtures from their roots. These root exudates serve important ecological functions and may also be a source of phytoestrogens in waterways. I show that clover root exudate produces male-biased sex ratios and accelerates male metamorphosis relative to females in low and intermediate doses of root exudate. My results indicate that root exudates are a potential source of contaminants impacting vertebrate development and that humans may be cultivating sexual abnormalities in wildlife by actively managing certain plant species. PMID:27019728
Robust Real-Time Musculoskeletal Modeling driven by Electromyograms.
Durandau, Guillaume; Farina, Dario; Sartori, Massimo
2017-05-12
Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses and current biomechanical models cannot be used for real-time control in man-machine interfaces. We developed a method that enables online analysis of neuromusculoskeletal function in vivo in the intact human. We used electromyography (EMG)-driven musculoskeletal modeling to simulate all transformations from muscle excitation onset (EMGs) to mechanical moment production around multiple lower-limb degrees of freedom (DOFs). We developed a calibration algorithm that enables adjusting musculoskeletal model parameters specifically to an individual's anthropometry and force-generating capacity. We incorporated the modeling paradigm into a computationally efficient, generic framework that can be interfaced in real-time with any movement data collection system. The framework demonstrated the ability of computing forces in 13 lower-limb muscle-tendon units and resulting moments about three joint DOFs simultaneously in real-time. Remarkably, it was capable of extrapolating beyond calibration conditions, i.e. predicting accurate joint moments during six unseen tasks and one unseen DOF. The proposed framework can dramatically reduce evaluation latency in current clinical biomechanics and open up new avenues for establishing prompt and personalized treatments, as well as for establishing natural interfaces between patients and rehabilitation systems. The integration of EMG with numerical modeling will enable simulating realistic neuromuscular strategies in conditions including muscular/orthopedic deficit, which could not be robustly simulated via pure modeling formulations. This will enable translation to clinical settings and development of healthcare technologies including real-time bio-feedback of internal mechanical forces and direct patient-machine interfacing.
A simple physical model for deep moonquake occurrence times
Weber, R.C.; Bills, B.G.; Johnson, C.L.
2010-01-01
The physical process that results in moonquakes is not yet fully understood. The periodic occurrence times of events from individual clusters are clearly related to tidal stress, but also exhibit departures from the temporal regularity this relationship would seem to imply. Even simplified models that capture some of the relevant physics require a large number of variables. However, a single, easily accessible variable - the time interval I(n) between events - can be used to reveal behavior not readily observed using typical periodicity analyses (e.g., Fourier analyses). The delay-coordinate (DC) map, a particularly revealing way to display data from a time series, is a map of successive intervals: I(n+. 1) plotted vs. I(n). We use a DC approach to characterize the dynamics of moonquake occurrence. Moonquake-like DC maps can be reproduced by combining sequences of synthetic events that occur with variable probability at tidal periods. Though this model gives a good description of what happens, it has little physical content, thus providing only little insight into why moonquakes occur. We investigate a more mechanistic model. In this study, we present a series of simple models of deep moonquake occurrence, with consideration of both tidal stress and stress drop during events. We first examine the behavior of inter-event times in a delay-coordinate context, and then examine the output, in that context, of a sequence of simple models of tidal forcing and stress relief. We find, as might be expected, that the stress relieved by moonquakes influences their occurrence times. Our models may also provide an explanation for the opposite-polarity events observed at some clusters. ?? 2010.
On Transaction-Cost Models in Continuous-Time Markets
Directory of Open Access Journals (Sweden)
Thomas Poufinas
2015-04-01
Full Text Available Transaction-cost models in continuous-time markets are considered. Given that investors decide to buy or sell at certain time instants, we study the existence of trading strategies that reach a certain final wealth level in continuous-time markets, under the assumption that transaction costs, built in certain recommended ways, have to be paid. Markets prove to behave in manners that resemble those of complete ones for a wide variety of transaction-cost types. The results are important, but not exclusively, for the pricing of options with transaction costs.
Modeling Large Time Series for Efficient Approximate Query Processing
DEFF Research Database (Denmark)
Perera, Kasun S; Hahmann, Martin; Lehner, Wolfgang
2015-01-01
Evolving customer requirements and increasing competition force business organizations to store increasing amounts of data and query them for information at any given time. Due to the current growth of data volumes, timely extraction of relevant information becomes more and more difficult...... these issues, compression techniques have been introduced in many areas of data processing. In this paper, we outline a new system that does not query complete datasets but instead utilizes models to extract the requested information. For time series data we use Fourier and Cosine transformations and piece...
A Real-time Modeling of Photovoltaic Array
Institute of Scientific and Technical Information of China (English)
王魏; 李柠; 李少远
2012-01-01
This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV array. The relationship of PV cell and PV array is obtained and the solution for PV array model is unique. The PV grid-connected generation system is used to demonstrate the effectiveness of the proposed method by comparing the calculated values with the actual output of the system.
Time-dependent Integrated Predictive Modeling of ITER Plasmas
Institute of Scientific and Technical Information of China (English)
R.V. Budny
2007-01-01
@@ Introduction Modeling burning plasmas is important for speeding progress toward practical Tokamak energy production. Examples of issues that can be elucidated by modelinginclude requirements for heating, fueling, torque, and current drive systems, design of diagnostics, and estimates of the plasma performance (e.g., fusion power production) in various plasma scenarios. The modeling should be time-dependent to demonstrate that burning plasmas can be created, maintained (controlled), and terminated successfully. The modeling also should be integrated to treat self-consistently the nonlinearities and strong coupling between the plasma, heating, current drive, confinement, and control systems.
The efficiency of the packaging system in inactivating food borne pathogens and prolonging the shelf life of fresh-cut produce is influenced by the design of the package apart from material and atmospheric conditions. Three different designs were considered to determine a specific package design ens...
Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions
Energy Technology Data Exchange (ETDEWEB)
Huddleston, R L
2004-01-27
A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.
Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions
Energy Technology Data Exchange (ETDEWEB)
Huddleston, R L
2004-01-27
A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.
State-time spectrum of signal transduction logic models
MacNamara, Aidan; Terfve, Camille; Henriques, David; Peñalver Bernabé, Beatriz; Saez-Rodriguez, Julio
2012-08-01
Despite the current wealth of high-throughput data, our understanding of signal transduction is still incomplete. Mathematical modeling can be a tool to gain an insight into such processes. Detailed biochemical modeling provides deep understanding, but does not scale well above relatively a few proteins. In contrast, logic modeling can be used where the biochemical knowledge of the system is sparse and, because it is parameter free (or, at most, uses relatively a few parameters), it scales well to large networks that can be derived by manual curation or retrieved from public databases. Here, we present an overview of logic modeling formalisms in the context of training logic models to data, and specifically the different approaches to modeling qualitative to quantitative data (state) and dynamics (time) of signal transduction. We use a toy model of signal transduction to illustrate how different logic formalisms (Boolean, fuzzy logic and differential equations) treat state and time. Different formalisms allow for different features of the data to be captured, at the cost of extra requirements in terms of computational power and data quality and quantity. Through this demonstration, the assumptions behind each formalism are discussed, as well as their advantages and disadvantages and possible future developments.
Shen, Jiajian; Tryggestad, Erik; Younkin, James E; Keole, Sameer R; Furutani, Keith M; Kang, Yixiu; Herman, Michael G; Bues, Martin
2017-08-04
To accurately model the beam delivery time (BDT) for a synchrotron-based proton spot scanning system using experimentally determined beam parameters. A model to simulate the proton spot delivery sequences was constructed, and BDT was calculated by summing times for layer switch, spot switch, and spot delivery. Test plans were designed to isolate and quantify the relevant beam parameters in the operation cycle of the proton beam therapy delivery system. These parameters included the layer switch time, magnet preparation and verification time, average beam scanning speeds in x- and y-directions, proton spill rate, and maximum charge and maximum extraction time for each spill. The experimentally determined parameters, as well as the nominal values initially provided by the vendor, served as inputs to the model to predict BDTs for 602 clinical proton beam deliveries. The calculated BDTs (TBDT ) were compared with the BDTs recorded in the treatment delivery log files (TLog ): ∆t = TLog -TBDT . The experimentally determined average layer switch time for all 97 energies was 1.91 s (ranging from 1.9 to 2.0 s for beam energies from 71.3 to 228.8 MeV), average magnet preparation and verification time was 1.93 ms, the average scanning speeds were 5.9 m/s in x-direction and 19.3 m/s in y-direction, the proton spill rate was 8.7 MU/s, and the maximum proton charge available for one acceleration is 2.0 ± 0.4 nC. Some of the measured parameters differed from the nominal values provided by the vendor. The calculated BDTs using experimentally determined parameters matched the recorded BDTs of 602 beam deliveries (∆t = -0.49 ± 1.44 s), which were significantly more accurate than BDTs calculated using nominal timing parameters (∆t = -7.48 ± 6.97 s). An accurate model for BDT prediction was achieved by using the experimentally determined proton beam therapy delivery parameters, which may be useful in modeling the interplay effect and patient throughput. The model may provide
Directory of Open Access Journals (Sweden)
Ladeesh V. G.
2017-01-01
Full Text Available Grinding aided electrochemical discharge machining is a hybrid technique, which combines the grinding action of an abrasive tool and thermal effects of electrochemical discharges to remove material from the workpiece for producing complex contours. The present study focuses on developing fluidic channels on borosilicate glass using G-ECDM and attempts to develop a mathematical model for surface roughness of the machined channel. Preliminary experiments are conducted to study the effect of machining parameters on surface roughness. Voltage, duty factor, frequency and tool feed rate are identified as the significant factors for controlling surface roughness of the channels produced by G-ECDM. A mathematical model was developed for surface roughness by considering the grinding action and thermal effects of electrochemical discharges in material removal. Experiments are conducted to validate the model and the results obtained are in good agreement with that predicted by the model.
Single-Index Additive Vector Autoregressive Time Series Models
LI, YEHUA
2009-09-01
We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided for stationarity of such models. We also study estimation of the proposed model using P-splines, hypothesis testing, asymptotics, selection of the order of the autoregression and of the smoothing parameters and nonlinear forecasting. We perform simulation experiments to evaluate our model in various settings. We illustrate our methodology on a climate data set and show that our model provides more accurate yearly forecasts of the El Niño phenomenon, the unusual warming of water in the Pacific Ocean. © 2009 Board of the Foundation of the Scandinavian Journal of Statistics.
Late time attractors of some varying Chaplygin gas cosmological models
Khurshudyan, M
2015-01-01
Varying Chaplygin gas is one of the dark fluids actively studied in modern cosmology. It does belong to the group of the fluids which has an explicitly given EoS. From the other hand phase space does contain all possible states of the system. Therefore, phase space analysis of the cosmological models does allow to understand qualitative behavior and estimate required characteristics of the models. Phase space analysis is a convenient approach to study a cosmological model, because we do not need to solve a system of differential equations for a given initial conditions, instead, we need to deal with appropriate algebraic equations. The goal of this paper is to find late time attractors for the cosmological models, where a varying Chaplygin gas is one of the components of the large sale universe. We will pay our attention to some non linear interacting models.
Holographic Space-time Models in $1 + 1$ Dimensions
Banks, T
2015-01-01
We construct Holographic Space-time models that reproduce the dynamics of $1 + 1$ dimensional string theory. The necessity for a dilaton field in the $1 + 1$ effective Lagrangian for classical geometry, the appearance of fermions, and even the form of the universal potential in the canonical $1$ matrix model, follow from general HST considerations. We note that 't Hooft's ansatz for the leading contribution to the black hole S-matrix, accounts for the entire S-matrix in these models in the limit that the string scale coincides with the Planck scale, up to transformations between near horizon and asymptotic coordinates. These $1 + 1$ dimensional models are describable as decoupling limits of the near horizon geometry of higher dimensional extremal black holes or black branes, and this suggests that deformations of the simplest model are equally physical. After proposing a notion of "relevant deformations", we describe deformations, which contain excitations corresponding to linear dilaton black holes, some of ...
Stability Analysis and H∞ Model Reduction for Switched Discrete-Time Time-Delay Systems
Directory of Open Access Journals (Sweden)
Zheng-Fan Liu
2014-01-01
Full Text Available This paper is concerned with the problem of exponential stability and H∞ model reduction of a class of switched discrete-time systems with state time-varying delay. Some subsystems can be unstable. Based on the average dwell time technique and Lyapunov-Krasovskii functional (LKF approach, sufficient conditions for exponential stability with H∞ performance of such systems are derived in terms of linear matrix inequalities (LMIs. For the high-order systems, sufficient conditions for the existence of reduced-order model are derived in terms of LMIs. Moreover, the error system is guaranteed to be exponentially stable and an H∞ error performance is guaranteed. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
According to the theory given in the paper[1], the long time electrolysis experiment with titanium cathode in heavy water (D2O) were done for many times by using the open-loop multi-parameters electrolysis calorimetry system, which is established by us. The specialty is that the cathode is titanium rod and the anode is platinum wire. The early experiment result[3] is still repeated in our recent experiment. The obvious "excess heat" phenomenon can take place only when the electrolysis last more than ten days and amount of "excess heat" increased with the electrolysis time. The "excess heat" can also be obtained from the "boiling to dry" experiment. In the recent experiment, we obtain the results that the amount of "excess heat" is about 3.6 times the input energy, the "excess heat" power is 76.5 W, and the "excess heat" power density is 121.7 W/cm3. After the electrolysis, the crystal structure of the Ti cathode was measured with x-ray diffraction apparatus. We found that the crystal structure of Ti cathode was changed to face-centered cubic structure of TiD2 from its hexagonal structure. This result is in agreement with the Gou's theory mentioned in reference[1].
Neagoe, Cristian; Grecu, Bogdan; Manea, Liviu
2016-04-01
National Institute for Earth Physics (NIEP) operates a real time seismic network which is designed to monitor the seismic activity on the Romanian territory, which is dominated by the intermediate earthquakes (60-200 km) from Vrancea area. The ability to reduce the impact of earthquakes on society depends on the existence of a large number of high-quality observational data. The development of the network in recent years and an advanced seismic acquisition are crucial to achieving this objective. The software package used to perform the automatic real-time locations is Seiscomp3. An accurate choice of the Seiscomp3 setting parameters is necessary to ensure the best performance of the real-time system i.e., the most accurate location for the earthquakes and avoiding any false events. The aim of this study is to optimize the algorithms of the real-time system that detect and locate the earthquakes in the monitored area. This goal is pursued by testing different parameters (e.g., STA/LTA, filters applied to the waveforms) on a data set of representative earthquakes of the local seismicity. The results are compared with the locations from the Romanian Catalogue ROMPLUS.
New meteorological data assimilation model for real-time emergency response
Energy Technology Data Exchange (ETDEWEB)
Sugiyama, G.; Chan, S.T.
1997-09-01
We are developing a new meteorological data assimilation model for the Atmospheric Release Advisory Capability (ARAC) project at Lawrence Livermore National Laboratory, which provides real-time dose assessments of airborne pollutant releases. The model, ADAPT (Atmospheric Data Assimilation and Parameterization Techniques), builds three-dimensional meteorological fields, which can be used to drive dispersion models or to initialize or evaluate mesoscale models. ADAPT incorporates many new features and substantial improvements over the current ARAC operational models MEDIC/MATHEW, including the use of continuous-terrain variable-resolution grids, the ability to treat assorted meteorological data such as temperatures, pressure, and relative humidity, and a new algorithm to produce mass-consistent wind fields. In this paper, we will describe the main features of the model, current work on a new atmospheric stability parameterization, and show example results.
Directory of Open Access Journals (Sweden)
Yaqin eQiao
2015-10-01
Full Text Available For the large-scale cultivation of microalgae for biodiesel production, one of the key problems is the determination of the optimum time for algal harvest when algae cells are saturated with neutral lipids. In this study, a method to determine the optimum harvest time in oil-producing microalgal cultivations by measuring the maximum photochemical efficiency of photosystem II (PSII, also called Fv/Fm, was established. When oil-producing Chlorella strains were cultivated and then treated with nitrogen starvation, it not only stimulated neutral lipid accumulation, but also affected the photosynthesis system, with the neutral lipid contents in all four algae strains – Chlorella sorokiniana C1, Chlorella sp. C2, C. sorokiniana C3, C. sorokiniana C7 – correlating negatively with the Fv/Fm values. Thus, for the given oil-producing algae, in which a significant relationship between the neutral lipid content and Fv/Fm value under nutrient stress can be established, the optimum harvest time can be determined by measuring the value of Fv/Fm. It is hoped that this method can provide an efficient way to determine the harvest time rapidly and expediently in large-scale oil-producing microalgae cultivations for biodiesel production.
DEFF Research Database (Denmark)
Rodríguez, Alicia; Rodríguez, Mar; Luque, M. Isabel
2011-01-01
Ochratoxin A (OTA) is a mycotoxin synthesized by a variety of different fungi, most of them from the genera Penicillium and Aspergillus. Early detection and quantification of OTA producing species is crucial to improve food safety. In the present work, two protocols of real-time qPCR based on SYBR...
DEFF Research Database (Denmark)
Cattani, Mirko; Maccarana, Laura; Hansen, Hanne Helene
2013-01-01
This experiment compared linear relationships among end-products of rumen fermentation measured at the time (t½) at which a feed produces half of its asymptotic gas production) or at 48 h. Meadow hay and corn grain were incubated for t½ (16 and 9 h, respectively) or for 48 h into glass bottles. E...