Neither exit nor voice : loyalty as a survival strategy for the Uzbeks in Kazakhstan

The June 2010 conflict between the Kyrgyz and Uzbek communities in southern Kyrgyzstan once again demonstrated the complexity of the ethnic question in Central Asia. Little is known, however, about the Uzbeks in Kazakhstan, whose settlements are concentrated in the south of the republic, in areas adjacent to Uzbekistan. What problems did the Kazakhstani Uzbeks face after the collapse of the Soviet Union and how did they seek to address these issues? This paper examines the attempts of Uzbek leaders to secure their share of power in their compact settlements and how they were co-opted or marginalized under the Nazarbaev administration. This paper shows that loyalty to the regime, not migration to the ethnic homeland or political mobilization, is an option available, and also preferable, for this ethnic minority in Kazakhstan.

PDR with a foot-mounted IMU and ramp detection

The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps.

Decelerator elements for ramp transfer points in fruit packing lines

Two different decelerator elements used to reduce impacts on fruits on ramp transfer points in fruit packing lines were designed and tested. The performance of these elements, a powered decelerator and a multiple curtain, was compared to commercial decelerators (blankets). A ramp of length 60 cm was placed at an angle of 30º in an experimental fruit packing line between a roller transporter and a conveyor. The decelerators were placed on top of the ramp. Different tests were carried out to study the performance of the decelerators using instrumented spheres (IS 100) of various sizes. Results showed that decelerators can reduce the impact intensity down to safe thresholds. The powered decelerator was the most effective because it reduced the speed of fruits and did not cause retention of the fruit, when correctly regulated.

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Application of noise analysis for sensor surveillance in Trillo NPP

It is a known fact that noise analysis is a suitable method for sensor performance surveillance. In particular, controlling the response time of a sensor is an efficient way to anticipate failures and to have the opportunity to prevent them. In this work the response times of several sensors of Trillo NPP are estimated by means of noise analysis. The procedure applied consists of modeling each sensor with autoregressive methods and getting the searched parameter by analyzing the response of the model when a ramp is simulated as the input signal. Core exit thermocouples and in core self-powered neutron detectors are the main sensors analyzed but other plant sensors are studied as well. Since several measurement campaigns have been carried out, it has been also possible to analyze the evolution of the estimated parameters during more than one fuel cycle. Some sensitivity studies for the sample frequency of the signals and its influence on the response time are also included. Calculations and analysis have been done in the frame of a collaboration agreement between Trillo NPP operator (CNAT) and the School of Mines of Madrid.

A wavelet-based approach for large wind power ramp characterisation

A wavelet-based approach for large wind power ramp characterisation

Effect of uncommon exit location in the emergency evacuation of transport airplanes

The objective of the present paper is to show the effect of uncommon exit arrangement in the evacuation process of narrow-body airliners, from the point of view of emergency evacuation certification, using the ETSIA model. Two main possibilities will be considered: large longitudinal shifting of the main embarking/disembarking doors; and suppression of some over-the-wing exits.

Storage requirements for PV power ramp-rate control

Short-term variability in the power generated by large grid-connected photovoltaic (PV) plants can negatively affect power quality and the network reliability. New grid-codes require combining the PV generator with some form of energy storage technology in order to reduce short-term PV power fluctuation. This paper proposes an effective method in order to calculate, for any PV plant size and maximum allowable ramp-rate, the maximum power and the minimum energy storage requirements alike. The general validity of this method is corroborated with extensive simulation exercises performed with real 5-s one year data of 500 kW inverters at the 38.5 MW Amaraleja (Portugal) PV plant and two other PV plants located in Navarra (Spain), at a distance of more than 660 km from Amaraleja.

Detecting and characterising ramp events in wind power time series

In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain

Ste6p Mutants Defective in Exit from the Endoplasmic Reticulum (ER) Reveal Aspects of an ER Quality Control Pathway in Saccharomyces cerevisiae

We are studying the intracellular trafficking of the multispanning membrane protein Ste6p, the a-factor transporter in Saccharomyces cerevisiae and a member of the ATP-binding cassette superfamily of proteins. In the present study, we have used Ste6p as model for studying the process of endoplasmic reticulum (ER) quality control, about which relatively little is known in yeast. We have identified three mutant forms of Ste6p that are aberrantly ER retained, as determined by immunofluorescence and subcellular fractionation. By pulse-chase metabolic labeling, we demonstrate that these mutants define two distinct classes. The single member of Class I, Ste6–166p, is highly unstable. We show that its degradation involves the ubiquitin–proteasome system, as indicated by its in vivo stabilization in certain ubiquitin–proteasome mutants or when cells are treated with the proteasome inhibitor drug MG132. The two Class II mutant proteins, Ste6–13p and Ste6–90p, are hyperstable relative to wild-type Ste6p and accumulate in the ER membrane. This represents the first report of a single protein in yeast for which distinct mutant forms can be channeled to different outcomes by the ER quality control system. We propose that these two classes of ER-retained Ste6p mutants may define distinct checkpoint steps in a linear pathway of ER quality control in yeast. In addition, a screen for high-copy suppressors of the mating defect of one of the ER-retained ste6 mutants has identified a proteasome subunit, Hrd2p/p97, previously implicated in the regulated degradation of wild-type hydroxymethylglutaryl-CoA reductase in the ER membrane.

Endogenous E2F-1 promotes timely G0 exit of resting mouse embryo fibroblasts

Much evidence strongly suggests a positive role for one or more E2F species in the control of exit from G0/G1. Results described here provide direct evidence that endogenous E2F-1, as predicted, contributes to progression from G0 to S. By contrast, cycling cells lacking an intact E2F-1 gene demonstrated normal cell cycle distribution. Therefore, E2F-1 exerts a unique function leading to timely G0 exit of resting cultured primary cells, while at the same time being unnecessary for normal G1 to S phase progression of cycling cells.

Antisense-mediated depletion of p300 in human cells leads to premature G1 exit and up-regulation of c-MYC

The cAMP-response element-binding protein (CREB)-binding protein and p300 are two highly conserved transcriptional coactivators and histone acetyltransferases that integrate signals from diverse signal transduction pathways in the nucleus and also link chromatin remodeling with transcription. In this report, we have examined the role of p300 in the control of the G1 phase of the cell cycle in nontransformed immortalized human breast epithelial cells (MCF10A) and fibroblasts (MSU) by using adenovirus vectors expressing p300-specific antisense sequences. Quiescent MCF10A and MSU cells expressing p300-specific antisense sequences synthesized p300 at much reduced levels and exited G1 phase without serum stimulation. These cells also showed an increase in cyclin A and cyclin A- and E-associated kinase activities characteristic of S phase induction. Further analysis of the p300-depleted quiescent MCF10A cells revealed a 5-fold induction of c-MYC and a 2-fold induction of c-JUN. A direct target of c-MYC, CAD, which is required for DNA synthesis, was also found to be up-regulated, indicating that up-regulation of c-MYC functionally contributed to DNA synthesis. Furthermore, S phase induction in p300-depleted cells was reversed when antisense c-MYC was expressed in these cells, indicating that up-regulation of c-MYC may directly contribute to S phase induction. Adenovirus E1A also induced DNA synthesis and increased the levels of c-MYC and c-JUN in serum-starved MCF10A cells in a p300-dependent manner. Our results suggest an important role of p300 in cell cycle regulation at G1 and raise the possibility that p300 may negatively regulate early response genes, including c-MYC and c-JUN, thereby preventing DNA synthesis in quiescent cells.

Quantitative ER ↔ Golgi Transport Kinetics and Protein Separation upon Golgi Exit Revealed by Vesicular Integral Membrane Protein 36 Dynamics in Live CellsV⃞

To quantitatively investigate the trafficking of the transmembrane lectin VIP36 and its relation to cargo-containing transport carriers (TCs), we analyzed a C-terminal fluorescent-protein (FP) fusion, VIP36-SP-FP. When expressed at moderate levels, VIP36-SP-FP localized to the endoplasmic reticulum, Golgi apparatus, and intermediate transport structures, and colocalized with epitope-tagged VIP36. Temperature shift and pharmacological experiments indicated VIP36-SP-FP recycled in the early secretory pathway, exhibiting trafficking representative of a class of transmembrane cargo receptors, including the closely related lectin ERGIC53. VIP36-SP-FP trafficking structures comprised tubules and globular elements, which translocated in a saltatory manner. Simultaneous visualization of anterograde secretory cargo and VIP36-SP-FP indicated that the globular structures were pre-Golgi carriers, and that VIP36-SP-FP segregated from cargo within the Golgi and was not included in post-Golgi TCs. Organelle-specific bleach experiments directly measured the exchange of VIP36-SP-FP between the Golgi and endoplasmic reticulum (ER). Fitting a two-compartment model to the recovery data predicted first order rate constants of 1.22 ± 0.44%/min for ER → Golgi, and 7.68 ± 1.94%/min for Golgi → ER transport, revealing a half-time of 113 ± 70 min for leaving the ER and 1.67 ± 0.45 min for leaving the Golgi, and accounting for the measured steady-state distribution of VIP36-SP-FP (13% Golgi/87% ER). Perturbing transport with AlF4− treatment altered VIP36-SP-GFP distribution and changed the rate constants. The parameters of the model suggest that relatively small differences in the first order rate constants, perhaps manifested in subtle differences in the tendency to enter distinct TCs, result in large differences in the steady-state localization of secretory components.

Surface antigen cross-linking triggers forced exit of a protozoan parasite from its host.

We used the common fish pathogen Ichthyophthirius multifiliis as a model for studying interactions between parasitic ciliates and their vertebrate hosts. Although highly pathogenic, Ichthyophthirius can elicit a strong protective immune response in fish after exposure to controlled infections. To investigate the mechanisms underlying host resistance, a series of passive immunization experiments were carried out using mouse monoclonal antibodies against a class of surface membrane proteins, known as immobilization antigens (or i-antigens), thought to play a role in the protective response. Such antibodies bind to cilia and immobilize I. multifiliis in vitro. Surprisingly, we found that passive antibody transfer in vivo caused rapid exit of parasites from the host. The effect was highly specific for a given I. multifiliis serotype. F(ab)2 subfragments had the same effect as intact antibody, whereas monovalent Fab fragments failed to protect. The activity of Fab could, nevertheless, be restored after subsequent i.p. injection of bivalent goat anti-mouse IgG. Parasites that exit the host had detectable antibody on their surface and appeared viable in all respects. These findings represent a novel instance among protists in which protective immunity (and evasion of the host response) result from an effect of antibody on parasite behavior.