Chaos game representation （CGR）-walk model for DNA sequences

Chaos game representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features: one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA (p, d, q) model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA (p, d, q) model.     

Hawking effect and quantum nonthermal radiation of an arbitrarily accelerating charged black hole using a new tortoise coordinate transformation

Using a new tortoise coordinate transformation, this paper investigates the Hawking effect from an arbitrarily accelerating charged black hole by the improved Damour-Ruffini method. After the tortoise coordinate transformation, the Klein-Gordon equation can be written as the standard form at the event horizon. Then extending the outgoing wave from outside to inside of the horizon analytically, the surface gravity and Hawking temperature can be obtained automatically. It is found that the Hawking temperatures of different points on the surface are different. The quantum nonthermal radiation characteristics of a black hole near the event horizon is also discussed by studying the Hamilton-Jacobi equation in curved spacetime and the maximum overlap of the positive and negative energy levels near the event horizon is given. There is a dimensional problem in the standard tortoise coordinate and the present results may be more reasonable.     

The CDF Run II Disk Inventory Manager

The Collider Detector at Fermilab(CDF) experiment records and analyses proton-antiprotion interactions at a center-of -mass energy of 2 TeV,Run II of the Fermilab Tevatron started in April of this year,The duration of the run is expected to be over two years.One of the main data handling strategies of CDF for RUn II is to hide all tape access from the user and to facilitate sharing of data and thus disk space,A disk inventory manager was designed and developed over the past years to keep track of the data on disk.to coordinate user access to the data,and to stage data back from tape to disk as needed.The CDF Run II disk inventory manager consists of a server process,a user and administrator command line interfaces.and a library with the routines of the client API.Data are managed in filesets which are groups of one or more files.The system keeps track of user acess to the filesets and attempts to keep frequently accessed data on disk.Data that are not on disk are automatically staged back from tape as needed.For CDF the main staging method is based on the mt-tools package as tapes are written according to the ANSI standard.     

Hojman Conserved Quantities for Birkhoffian Systems in Event Space

This paper focuses on studying a Hojman conserved quantity directly derived from a Lie symmetry for a Birkhoffian system in the event space. The Birkhoffian parametric equations for the system are established, and the determining equations of Lie symmetry for the system are obtained. The conditions under which a Lie symmetry of Birkhoffian system in the event space can directly lead up to a Hojman conserved quantity and the form of the Hojman conserved quantity are given. An example is given to illustrate the application of the results.     

CDF Run Ⅱ Data File Catalog

The CDF experiment started data taking in April 2001,The data are organized into datasets which contain events of similar physics properties and reconstruction version.the information about datasets is stored in the Data File Catalog,a relational database.This information is presented to the data processing framework as objects which are retrieved using compound keys.The objects and the keys are designed to be the algorithms‘ view of information stored in the database.Objects may use several DB tables.A database interface management layer exists for the purpose of managing the mapping of persistent data to transient objects that can be used by the framework.This layer exists between the algorithm code and the code which reads directly from datanbase tables.At the user end,it places get/put interface on a top of a transient class for retrieval or storage of objects of this class using a key.Data File Catalog code makes use of this facility and contains all the code needed to manipulate CDF Data File Catalog from a C program or from the command prompt,It supports an Oracle interface using OTL,and a mSQL interface,This code and the Oravcle implementation of Data File Catalog were subjected to test during CDF Commissioning Run last fall and during first weeks of Run II in April.It performed exceptionally well.     

First Operation of the D0 Run Ⅱ Reconstruction Farm

We report on the first operations of the reconstruction farms for the D0 experiment.Data were read from a tape robot to 50 PC‘s running Linux,processed,spooled to a central disk buffer for merging and then written back to the tape robot.The farms are being used successfully to reconstruct the data as it comes in.Transfer rates well over the 12.5 MB/sec needed for full data rates have been achieved.     

Dynamics analysis on neural firing patterns by symbolic approach

Neural firing patterns are investigated by using symbolic dynamics. Bifurcation behaviour of the Hindmarsh--Rose (HR) neuronal model is simulated with the external stimuli gradually decreasing, and various firing activities with different topological structures are orderly numbered. Through constructing first-return maps of interspike intervals, all firing patterns are described and identified by symbolic expressions. On the basis of ordering rules of symbolic sequences, the corresponding relation between parameters and firing patterns is established, which will be helpful for encoding neural information. Moreover, using the operation rule of $\ast$ product, generation mechanisms and intrinsic configurations of periodic patterns can be distinguished in detail. Results show that the symbolic approach is a powerful tool to study neural firing activities. In particular, such a coarse-grained way can be generalized in neural electrophysiological experiments to extract much valuable information from complicated experimental data.     

The KLOE Online Calibration System

Based on all the features of the KLOE online software,the online calibration system performs current calibration quality checking in real time and starts automatically new calibration procedures when needed.Acalibration manager process controls the system,implementing the interface to the online system,receiving information from the run control and translating its state transitions to a separate state machine.It acts as a “ calibration run controller“and performs failure recovery when requested by a set of process checkers.The core of the system is a multi-threaded OO histogram server that receives histogramming commands by remote processes and operates on local ROOT histograms.A client library and C,fortran and C application interface libraries allow the user to connect and define his own histogram or read histograms owned by others using an bool-like interface.Several calibration processes running in parallel in a destributed,multiplatform environment can fill the same histograms,allowing fast external information check.A monitor thread allow remote browsing for visual inspection,Pre-filtered data are read in nonprivileged spy mode from the data acquisition system via the Kloe Integrated Dataflow,privileged spy mode from the data acquisiton system via the Kole Integrated Dataflow.The main characteristics of the system are presented.     

Cosmological Expansion and Its Effect on Small Systems

In order to study the effect of large scale cosmological expansion on small systems, we assume a FriedmannRobertson-Walker type coordinate system in presence of a nonzero cosmological constant and derive a non-static Reissner-Nrdstr(o)m metric. It is an analytic function of r for all values except at r = 0, which is singular. By determining the equation of motion in this metric we can estimate how expansion of the universe may affect Pioneer‘smotion. Because the metric does not have any event horizon and so high potential regions are accessible, this may help us in better understanding AGN phenomenon.     

Cosmological Expansion and Its Effect on Small Systems

In order to study the effect of large scale cosmological expansion on small systems, we assume a Friedmann- Robertson-Walker type coordinate system in presence of a nonzero cosmological constant and derive a non-static Reissner-Nrdstr6m metric. It is an analytic function of r for all values except at r = O, which is singular. By determining the equation of motion in this metric we can estimate how expansion of the universe may affect Pioneer＇s motion. Because the metric does not have any event horizon and so high potential regions are accessible, this may help us in better understanding AGN phenomenon.     

Charge fluctuations in Au+Au collisions at RHIC energy

A hadron and string cascade model, JPCIAE, together with the corresponding Monte Carlo event generator, has been employed in this paper to investigate further the charge fluctuations in Au+Au collisions at Snn = 130 GeV. The default JPCIAE calculations are in good agreement with PHENIX and STAR data. We found that the thermal predictions for the π gas, the resonance π gas and quark matter deviate, respectively, from the corresponding dynamical simulations from the JPCIAE model. The discrepancies were also found between the π charge fluctuations and the charge fluctuations of all species of hadrons. However the charge fluctuations for "π from ρ and ω decay" and for all the hadrons from resonance decay are close to each other, indicating the correlation between positively and negatively charged hadrons is not sensitive to the species of hadrons. This work shows further that it is questionable to use the charge fluctuations as a signature of QGP.     

Putting It All Together：Experience and Challenges at the DELPHI off—line Processing Farm

After over 10 years of existence,DELPHI off-line software counts altogether over 1500k lines.Being written by multitude of authorsk,many of them having already left,it is very incoherent and extremely difficult to maintain:it is written in Fortran,it relies on obsolete tools and it has to run in a distributed multi-os computing environment.Still.as the analysis of LEP data will continue during the next 5-6 years,this code will have to be used and be ported to yet another platforms.In order to ensure high efficiency in use of our resources,we have developed several tools which hide from the user most of the intricaices of the operating system,batch system and data access.These tools are well integrated and easy to maintain.As the problems are quite typical for the High Energy Physics software,we believe that the ideas we have implemented can be useful also for the next generation of experiments.     

Investigations of the dynamics of road pavement reflectance

Road pavement reflectance is usually assumed to be invariant in short periods of time in some quantitative remote sensing applications.To examine its variability,reflectance sequences of concrete and asphalt pavement are measured in field for half a day in visible and near-infarecd(VNIR)spectral range using dual-beam method.As much as 20.7%and 3.52%of relative changes are found in asphalt and concrete reflectance data at 550 nm,and all VNIR bands demonstrate similar variations found to correlate with both illumination geometry and the relative portion of diffuse irradiance.In this letter,this effect is interpreted from a mathematic view.Further studies are needed to model the dynamics of reflectance physically.     

Mixing MC events in a reactor neutrino experiment

In reactor neutrino experiments, the analysis of time correlations between different physical events is an important task. Such analysis can help to understand the physical mechanisms of the signal and background events as well as the details of event selection and background estimation. This study investigates a "sampling and mixing" method used for producing large MC data samples for the Daya Bay reactor neutrino experiment. We designed a simple, generic mixing algorithm and generated large MC data samples for physics analysis from several samples according to their respective event rates. Basic plots based on the mixed data are shown.     

Mixing MC events in reactor neutrino experiment

In reactor neutrino experiments, the analysis of time correlations between different physical events is an important task. Such analysis can help to understand the physical mechanisms of the signal and background events as well as the details of event selection and background estimation. This study investigates a "sampling and mixing" method used for producing large MC data samples for the Daya Bay reactor neutrino experiment. We designed a simple, generic mixing algorithm and generated large MC data samples for physics analysis from several samples according to their respective event rates. Basic plots based on the mixed data are shown.     

Exo-atmospheric target discrimination using probabilistic neural network

Exo-atmospheric targets are especially difficult to distinguish using currently available techniques, because all target parts follow the same spatial trajectory. The feasibility of distinguishing multiple type components of exo-atmospheric targets is demonstrated by applying the probabilistic neural network. Differences in thermal behavior and time-varying signals of space-objects are analyzed during the selection of features used as inputs of the neural network. A novel multi-colorimetric technology is introduced to measure precisely the temporal evolutional characteristics of temperature and emissivity-area products. To test the effectiveness of the recognition algorithm, the results obtained from a set of synthetic multispectral data set are presented and discussed. These results indicate that the discrimination algorithm can obtain a remarkable success rate.     

Protein structural classification and family identification by multifractal analysis and wavelet spectrum

Family identification is helpful for predicting protein functions. It has been known from the literature that longer sequences of base pairs or amino acids are required to study patterns in biological sequences. Since most protein sequences are relatively short, we randomly concatenate or link the protein sequences from the same family or superfamily together to form longer protein sequences. The 6-letter model, 12-letter model, 20-letter model, the revised Schneider and Wrede scale hydrophobicity, solvent accessibility and stochastic standard state accessibility are used to convert linked protein sequences into numerical sequences. Then multifractal analyses and wavelet analysis are performed on these numerical sequences. The parameters from these analyses can be used to construct parameter spaces where each linked protein is represented by a point. The four classes of proteins, namely the α,β, α+βand α /β classes, are then distinguished in these parameter spaces. The Fisher linear discriminant algorithm is used to assess the discriminant accuracy. Numerical results indicate that the discriminant accuracies are satisfactory in separating these classes. We find that the linked proteins from the same family or superfamily tend to group together and can be separated from other linked proteins. The methods are helpful for identifying the family of an unknown protein.     

An artificial neural network for proton identification in HERMES data

The HERMES time-of-flight （TOF） system is used for proton identification, but must be carefully calibrated for systematic biases in the equipment. This paper presents an artificial neural network （ANN） trained to recognize protons from ∧^0 decay using only raw event data such as time delay, momentum, and trajectory. To avoid the systematic errors associated with Monte Carlo models, we collect a sample of raw experimental data from the year 2000. We presume that when for a positive hadron （assigned one proton mass） and a negative hadron （assigned one π^- mass） the reconstructed invariant mass lies within the ∧^0 resonance, the positive hadron is more likely to be a proton. Such events are assigned an output value of one during the training process; all others were assigned the output value zero.
The trained ANN is capable of identifying protons in independent experimental data, with an efficiency equivalent to the traditional TOF calibration. By modifying the threshold for proton identification, a researcher can trade off between selection efficiency and background rejection power. This simple and convenient method is applicable to similar detection problems in other experiments.     

HepPDT：encapsulating the Particle Data Table

As a result of discussions within the HEP community,we have written a C package which can be used to maintain a table of particle properties,including decay mode information.The classes allow for multiple tables and accept inpu from a number of standard sources,In addition,They provide a mechanism by which an event generator can employ the tabulated information to actually direct the decay of particles.     

A unified algorithm for target detection and tracing based on data of array sensors

A unified method for target detection and tracing based on data from sensors of array is presented in order to improve detection and tracking abilities of the weak targets with low signal-to-noise ratio. Assuming that the multiple targets are uncorrelated each other and the number of the targets is known a priori, the status of the targets can be estimated with the maximum a-posteriori （MAP） method directly through the sensors data. The proposed method is different from the classical method, by which it can detect and track targets simultaneously by adding the target＇s signal energy information besides its direction of arrivM（DOA） information. Simulated and sea trial data results show that the detection and tracing capabilities of weak targets can be improved and wrong tracing and missing tracing problems, which exist in the classical tracing method when it is faced with the crossing targets, can be resolved by the proposed method.