Search results for "upe"
showing 10 items of 7447 documents
An AFLP clock for the absolute dating of shallow-time evolutionary history based on the intraspecific divergence of southwestern European alpine plan…
2009
The dating of recent events in the history of organisms needs divergence rates based on molecular fingerprint markers. Here, we used amplified fragment length polymorphisms (AFLPs) of three distantly related alpine plant species co-occurring in the Spanish Sierra Nevada, the Pyrenees and the southwestern Alps/Massif Central to establish divergence rates. Within each of these species (Gentiana alpina, Kernera saxatilis and Silene rupestris), we found that the degree of AFLP divergence (D(N72)) between mountain phylogroups was significantly correlated with their time of divergence (as inferred from palaeoclimatic/palynological data), indicating constant AFLP divergence rates. As these rates d…
Relaxation phenomena in mixed isomeric alcohols by Mandelstam-Brillouin scattering
1991
Mandelstam-Brillouin scattering data in mixed isomeric alcohols n-pentanol (nPe-OH) and 2-methyl-2-butanol (2Me-2BuOH) are presented. The hypersonic velocity and normalized absorption are measured as a function of the scattering angle, in the temperature range from - 15-degrees-C to + 45-degrees-C, and as a function of n-PeOH molar fraction going from the pure n-PeOH to the pure 2Me-2BuOH. The experimental results confirm the existence of a shear relaxation phenomenon in the GHz region, that has been previously detected in pure liquids. The temperature dependence of the relaxation time tau-s and of the shear modulus G-infinity evaluated within viscoelastic liquid models, support the existen…
Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening
2020
Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that co…
Anomalous transport effects on switching currents of graphene-based Josephson junctions
2017
We explore the effect of noise on the ballistic graphene-based small Josephson junctions in the framework of the resistively and capacitively shunted model. We use the non-sinusoidal current-phase relation specific for graphene layers partially covered by superconducting electrodes. The noise induced escapes from the metastable states, when the external bias current is ramped, give the switching current distribution, i.e. the probability distribution of the passages to finite voltage from the superconducting state as a function of the bias current, that is the information more promptly available in the experiments. We consider a noise source that is a mixture of two different types of proce…
Switching times in long-overlap Josephson junctions subject to thermal fluctuations and non-Gaussian noise sources
2014
We investigate the superconducting lifetime of long current-biased Josephson junctions, in the presence of Gaussian and non-Gaussian noise sources. In particular, we analyze the dynamics of a Josephson junction as a function of the noise signal intensity, for different values of the parameters of the system and external driving currents. We find that the mean lifetime of the superconductive state is characterized by nonmonotonic behavior as a function of noise intensity, driving frequency and junction length. We observe that these nonmonotonic behaviours are connected with the dynamics of the junction phase string during the switching towards the resistive state. An important role is played…
Dimensionality Reduction Techniques: An Operational Comparison On Multispectral Satellite Images Using Unsupervised Clustering
2006
Multispectral satellite imagery provides us with useful but redundant datasets. Using Dimensionality Reduction (DR) algorithms, these datasets can be made easier to explore and to use. We present in this study an objective comparison of five DR methods, by evaluating their capacity to provide a usable input to the K-means clustering algorithm. We also suggest a method to automatically find a suitable number of classes K, using objective "cluster validity indexes" over a range of values for K. Ten Landsat images have been processed, yielding a classification rate in the 70-80% range. Our results also show that classical linear methods, though slightly outperformed by more recent nonlinear al…
A New Approach to Investigate Students’ Behavior by Using Cluster Analysis as an Unsupervised Methodology in the Field of Education
2016
The problem of taking a set of data and separating it into subgroups where the ele- ments of each subgroup are more similar to each other than they are to elements not in the subgroup has been extensively studied through the statistical method of cluster analysis. In this paper we want to discuss the application of this method to the field of education: particularly, we want to present the use of cluster analysis to separate students into groups that can be recognized and characterized by common traits in their answers to a questionnaire, without any prior knowledge of what form those groups would take (unsupervised classification). We start from a detailed study of the data processing need…
Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis
2006
Inductive learning systems were successfully applied in a number of medical domains. Nevertheless, the effective use of these systems often requires data preprocessing before applying a learning algorithm. This is especially important for multidimensional heterogeneous data presented by a large number of features of different types. Dimensionality reduction (DR) is one commonly applied approach. The goal of this paper is to study the impact of natural clustering--clustering according to expert domain knowledge--on DR for supervised learning (SL) in the area of antibiotic resistance. We compare several data-mining strategies that apply DR by means of feature extraction or feature selection w…
Ar superformulu ģenerētu objektu īpašības un pielietojumi
2019
Bakalaura darba mērķis ir izpētīt ierobežojumus, kādi attiecas uz figūrām, kuras ģenerētas, izmantojot superformulu, kā arī pētīt praktiskus pielietojumus šādam figūru ģenerēšanas paņēmienam. Dabā sastopamu formu ģenerēšanai bieži vien nepieciešami netriviāli vienādojumi vai pārveidojumi, kas patērē gan laika, gan atmiņas resursus. Izmantojot superformulu, šādu formu ģenerēšanai nepieciešami tikai daži parametri. Tā kā visas šādi ģenerētas figūras apraksta viena formula, tad ir iespējams izmantot analītiskas metodes, lai noteiktu figūru un taišņu krustpunktus, kā arī attālumus starp šādi veidotām figūrām. Darbā vispirms tiek apskatītas superelipšu un superformulas īpašības, pēc tam tiek aps…
Design, construction and cooling system performance of a prototype cryogenic stopping cell for the Super-FRS at FAIR
2015
A cryogenic stopping cell for stopping energetic radioactive ions and extracting them as a low energy beam was developed. This first ever cryogenically operated stopping cell serves as prototype device for the Low-Energy Branch of the Super-FRS at FAIR. The cell has a stopping volume that is 1 m long and 25 cm in diameter. Ions are guided by a DC field along the length of the stopping cell and by a combined RF and DC fields provided by an RE carpet at the exit-hole side. The ultra-high purity of the stopping gas required for optimum ion survival is reached by cryogenic operation. The design considerations and construction of the cryogenic stopping cell, as well as some performance character…