Physical degrees of freedom in stabilized brane world models

We consider brane world models with interbrane separation stabilized by the Goldberger-Wise scalar field. For arbitrary background, or vacuum configurations of the gravitational and scalar fields in such models, we construct the second variation Lagrangian, study its gauge invariance, find the corresponding equations of motion and decouple them in a suitable gauge. We also derive an effective four-dimensional Lagrangian for such models, which describes the massless graviton, a tower of massive gravitons and a tower of massive scalars. It is shown that for a special choice of the background solution the masses of the graviton excitations may be of the order of a few TeV, the radion mass of the order of 100 GeV, the inverse size of the extra dimension being tens of GeV. In this case the coupling of the radion to matter on the negative tension brane is approximately the same as in the unstabilized model with the same values of the fundamental five-dimensional energy scale and the interbrane distance.Comment: 17 pages, LaTeX, corrected typos, amended the normalization constants of the scalar modes and their coupling constants to matte

Red neuronal para el reconocimiento de escritura a mano

Hoy, en la era digital, el problema del reconocimiento de patrones es muy relevante. En particular, la tarea de reconocimiento de texto es importante en la banca, para la lectura automática de documentos y su control; en sistemas de control de video, por ejemplo, para identificar la matrícula de un automóvil que violó las reglas de tránsito; en los sistemas de seguridad, por ejemplo, para verificar los billetes en un cajero automático y en muchas otras áreas. Se conocen una gran cantidad de métodos para resolver el problema del reconocimiento de patrones, pero la principal ventaja de las redes neuronales sobre otros métodos es su capacidad de aprendizaje. Es esta característica la que hace que las redes neuronales sean atractivas para estudiar. El artículo propone un modelo básico de red neuronal. Se consideran los principales algoritmos y se implementa un modelo de programación en el lenguaje de programación Python. En el curso de la investigación, se revelaron las siguientes deficiencias del modelo básico: baja tasa de aprendizaje (el número de dígitos reconocidos correctamente en las primeras épocas de aprendizaje); reentrenamiento: la red no ha aprendido a generalizar los conocimientos adquiridos; baja probabilidad de reconocimiento: 95,13%. Para resolver las desventajas anteriores, se utilizaron varias técnicas que aumentan la precisión y la velocidad del trabajo, así como también reducen el efecto del reentrenamiento de la red

Red neuronal para el reconocimiento de escritura a mano

Today, in the digital age, the problem of pattern recognition is very relevant. In particular, the task of text recognition is important in banking, for the automatic reading of documents and their control; in video control systems, for example, to identify the license plate of a car that violated traffic rules; in security systems, for example, to check banknotes at an ATM and in many other areas. A large number of methods are known for solving the problem of pattern recognition, but the main advantage of neural networks over other methods is their learning ability. It is this feature that makes neural networks attractive to study. The article proposes a basic neural network model. The main algorithms are considered and a programming model is implemented in the Python programming language. In the course of research, the following shortcomings of the basic model were revealed: low learning rate (the number of correctly recognized digits in the first epochs of learning); retraining - the network has not learned to generalize the knowledge gained; low probability of recognition - 95.13%.To solve the above disadvantages, various techniques were used that increase the accuracy and speed of work, as well as reduce the effect of network retraining.Hoy, en la era digital, el problema del reconocimiento de patrones es muy relevante. En particular, la tarea de reconocimiento de texto es importante en la banca, para la lectura automática de documentos y su control; en sistemas de control de video, por ejemplo, para identificar la matrícula de un automóvil que violó las reglas de tránsito; en los sistemas de seguridad, por ejemplo, para verificar los billetes en un cajero automático y en muchas otras áreas. Se conocen una gran cantidad de métodos para resolver el problema del reconocimiento de patrones, pero la principal ventaja de las redes neuronales sobre otros métodos es su capacidad de aprendizaje. Es esta característica la que hace que las redes neuronales sean atractivas para estudiar. El artículo propone un modelo básico de red neuronal. Se consideran los principales algoritmos y se implementa un modelo de programación en el lenguaje de programación Python. En el curso de la investigación, se revelaron las siguientes deficiencias del modelo básico: baja tasa de aprendizaje (el número de dígitos reconocidos correctamente en las primeras épocas de aprendizaje); reentrenamiento: la red no ha aprendido a generalizar los conocimientos adquiridos; baja probabilidad de reconocimiento: 95,13%. Para resolver las desventajas anteriores, se utilizaron varias técnicas que aumentan la precisión y la velocidad del trabajo, así como también reducen el efecto del reentrenamiento de la red

Design, Performance, and Calibration of CMS Hadron Endcap Calorimeters

Detailed measurements have been made with the CMS hadron calorimeter endcaps (HE) in response to beams of muons, electrons, and pions. Readout of HE with custom electronics and hybrid photodiodes (HPDs) shows no change of performance compared to readout with commercial electronics and photomultipliers. When combined with lead-tungstenate crystals, an energy resolution of 8\% is achieved with 300 GeV/c pions. A laser calibration system is used to set the timing and monitor operation of the complete electronics chain. Data taken with radioactive sources in comparison with test beam pions provides an absolute initial calibration of HE to approximately 4\% to 5\%

Design, Performance and Calibration of the CMS Forward Calorimeter Wedges

We report on the test beam results and calibration methods using charged particles of the CMS Forward Calorimeter (HF). The HF calorimeter covers a large pseudorapidity region (3\l |\eta| \le 5), and is essential for large number of physics channels with missing transverse energy. It is also expected to play a prominent role in the measurement of forward tagging jets in weak boson fusion channels. The HF calorimeter is based on steel absorber with embedded fused-silica-core optical fibers where Cherenkov radiation forms the basis of signal generation. Thus, the detector is essentially sensitive only to the electromagnetic shower core and is highly non-compensating (e/h \approx 5). This feature is also manifest in narrow and relatively short showers compared to similar calorimeters based on ionization. The choice of fused-silica optical fibers as active material is dictated by its exceptional radiation hardness. The electromagnetic energy resolution is dominated by photoelectron statistics and can be expressed in the customary form as a/\sqrt{E} + b. The stochastic term a is 198% and the constant term b is 9%. The hadronic energy resolution is largely determined by the fluctuations in the neutral pion production in showers, and when it is expressed as in the electromagnetic case, a = 280% and b = 11%

Design, Performance, and Calibration of the CMS Hadron-Outer Calorimeter

The CMS hadron calorimeter is a sampling calorimeter with brass absorber and plastic scintillator tiles with wavelength shifting fibres for carrying the light to the readout device. The barrel hadron calorimeter is complemented with an outer calorimeter to ensure high energy shower containment in the calorimeter. Fabrication, testing and calibration of the outer hadron calorimeter are carried out keeping in mind its importance in the energy measurement of jets in view of linearity and resolution. It will provide a net improvement in missing \et measurements at LHC energies. The outer hadron calorimeter will also be used for the muon trigger in coincidence with other muon chambers in CMS

Selection of mixed conducting oxides for oxidative dehydrogenation of propane with pulse experiments

In this study, propane pulse experiments at 550 °C are used as a method to select suitable oxides for further operation of catalytic dense membrane reactor (CDMR) for oxidative dehydrogenation of propane. Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSCF), La2NiO4+δ (LN) and PrBaCo2O5+δ (PBC) powders were used as model catalysts to explore the catalytic properties of membrane surfaces in terms of activity and selectivity. Furthermore, as propane pulses induce removal of oxygen from the sample, which is therefore depleted in oxygen by reducing the oxide, crucial information on the effect of the oxygen content in the samples (i.e. the oxidation degree) on reactivity and selectivity is obtained. It will be shown that LN is the most promising material for membrane application, provided that it is operated in the optimal window of reduction degree, to ensure high selectivity towards C3H6. Contrary, PBC and BSCF are not suitable for CDMR. In fact, PBC showed low selectivity to C3H6 due to significant formation of CO2, independent of the oxidation degree of the material and BSCF appears to adsorb CO2 by forming carbonates, which might be detrimental for long term operation. However, pulse experiments revealed the remarkable stability of BSCF catalyst's activity towards CO2 adsorption. Despite the presence of carbonate, the material preserved the ability to act as an oxygen source for propane and can be completely regenerated via oxidation. Additionally, the onset temperature in TPR appears to correlate well with the reactivity of lattice oxygen ions with propane, for the three materials studied.\ud \u

The effect of V in La2Ni1−xVxO4+1.5x+δ on selective oxidative dehydrogenation of propane: Stabilization of lattice oxygen

In this study, the non-stoichiometric redox compounds La2NiO4+δ and La2Ni0.9V0.1O4.15+δ have been tested as an oxidant in selective oxidation of propane in pulse experiments at temperatures between 450 and 650 °C. The oxygen contents in the samples at different temperatures were calculated based on back-titration with O2 pulses as well as on TGA. In the case of La2Ni0.9V0.1O4.15+δ over-stoichiometric oxygen was the only active species, responsible for the formation of CO2, C3H6, C2H4 and CH4 while pulsing propane at all investigated temperatures. Contrary, the reactive species in La2NiO4+δ changed from over-stoichiometric oxygen only at 450 °C, to both over-stoichiometric and lattice oxygen at 550 °C, to lattice oxygen only at 650 °C. The activation of lattice oxygen and the consequent formation of Ni metal were detrimental for selectivity to propylene as formation of COx, CH4 and coke mainly occurred and no olefins were formed

Presence of Lithium Ions in MgO Lattice: Surface Characterization by Infrared Spectroscopy and Reactivity towards Oxidative Conversion of Propane

The surface morphology of Li-promoted MgO catalysts prepared using the sol−gel method (sg) and wet impregnation procedure (imp), respectively, has been studied by low-temperature infrared spectroscopy of adsorbed CO molecules. The results show that step sites, as unselective catalytic centers, are the major features existing on the surface of pure MgO, and those are active toward the oxidative conversion of propane. However, the concentration of these sites is drastically reduced by the incorporation of lithium ions in the MgO lattice. In fact, the incorporated Li+ ions tend to move into the surface region and occupy sites associated with lower coordination number (e.g., step sites). Li/MgO-sg catalysts are characterized by a higher concentration of incorporation of lithium compared to Li/MgO-imp. In the case of oxidative dehydrogenation/cracking of propane, Li/MgO-sg catalysts show higher activity and selectivity to olefins compared to materials prepared using wet impregnation. Catalytic performance differs strongly regarding (i) the amount of olefins formed, and (ii) the ratio of C3H6/C2H4. It is shown that high density of active sites is essential for further oxidative dehydrogenation of propyl radicals to propylene and suppression of cracking reactions pathway

Development of active, and stable water-gas-shift reaction catalysts for fuel cell applications

Water-gas-shift (WGS) reaction CO + H2O = CO2 + H2, is a key step in the generation of H2 for fuel cells. Noble metal-based catalysts are promising single stage WGS catalysts because they less sensitive than LTS catalysts (Cu based) and more active than the HTS (Ni) catalysts. High activity in CO conversion at moderate temperatures and stability during start-up - shutdown cycles is essential, especially in transport applications. A series of supported Pt catalysts was studied. Zirconia based catalysts were stable but catalyst activity was low. Pt/TiO2 and Pt/Ti0.5Ce0.5O2 gave the required commercial activity (8.10-5 mole H2 g-1cat/sec, based on a 2 kg catalyst for a 100 kw fuel cell) at 300°C. However, 35 % of initial activity was lost after 24 hr. A new promising catalyst developed has high activity as Pt/TiO2 and was very stable. The reasons for the different activities, deactivation mechanism, and the stability of the newly developed catalysts were discussed. This is an abstract of a paper presented at the 231st ACS National Meeting (Atlanta, GA 3/26-30/2006)