La cooperación en América del Norte : de las seguridades económica y militar a la bioseguridad (2001-2009)

El nuevo orden internacional derivado de la Guerra Fría se caracterizó por la multiplicación de nuevas amenazas a la seguridad y la construcción de bloques regionales con el propósito de enfrentarlas. Esta investigación plantea que bajo tales circunstancias, en América del Norte, fue adoptada una agenda ampliada y profundizada en materia de seguridad que permitió articular las seguridades económica, militar y la bioseguridad. En este sentido, la configuración de dicha agenda fue posible gracias a la adopción de una retórica neoliberal de seguridad económica desde la puesta en marcha del Tratado de Libre Comercio en 1994, la cual luego del 11 de septiembre de 2001 fue articulada con la agenda de seguridad militar propuesta por el gobierno estadounidense en materia de lucha antiterrorista, que a su turno permitió la adopción de una retórica y unas medidas extraordinarias en materia de bioseguridad, motivada por los ataques bioterroristas con ántrax en EE.UU., el brote de SARS en Canadá y la pandemia de AH1N1 en México.

An implicit pole-assignment self-tuning regulator

A new self-tuning implicit pole-assignment algorithm is presented which, through the use of a pole compression factor and different RLS model and control structures, overcomes stability and convergence problems encountered in previously available algorithms. Computational requirements of the technique are much reduced when compared to explicit pole-assignment schemes, whereas the inherent robustness of the strategy is retained.

Return periods of losses associated with European windstorm series in a changing climate

Possible future changes of clustering and return periods (RPs) of European storm series with high potential losses are quantified. Historical storm series are identified using 40 winters of reanalysis. Time series of top events (1, 2 or 5 year return levels (RLs)) are used to assess RPs of storm series both empirically and theoretically. Additionally, 800 winters of general circulation model simulations for present (1960–2000) and future (2060–2100) climate conditions are investigated. Clustering is identified for most countries, and estimated RPs are similar for reanalysis and present day simulations. Future changes of RPs are estimated for fixed RLs and fixed loss index thresholds. For the former, shorter RPs are found for Western Europe, but changes are small and spatially heterogeneous. For the latter, which combines the effects of clustering and event ranking shifts, shorter RPs are found everywhere except for Mediterranean countries. These changes are generally not statistically significant between recent and future climate. However, the RPs for the fixed loss index approach are mostly beyond the range of pre-industrial natural climate variability. This is not true for fixed RLs. The quantification of losses associated with storm series permits a more adequate windstorm risk assessment in a changing climate.

Zero attracting recursive least squares algorithms

The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity. In order to achieve a closed-form solution, the l1-norm of the parameter vector is approximated by an adaptively weighted l2-norm, in which the weighting factors are set as the inversion of the associated l1-norm of parameter estimates that are readily available in the adaptive learning environment. ZA-RLS-II is computationally more efficient than ZA-RLS-I by exploiting the known results from linear algebra as well as the sparsity of the system. The proposed algorithms are proven to converge, and adaptive sparse channel estimation is used to demonstrate the effectiveness of the proposed approach.

A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.

Improving the performance of equalization in communication systems

In this paper, research on exploring the potential of several popular equalization techniques while overcoming their disadvantages has been conducted. First, extensive literature survey on equalization is conducted. The focus has been placed on several popular linear equalization algorithm such as the conventional least-mean-square (LMS) algorithm, the recursive least squares (RLS) algorithm, the fi1tered-X LMS algorithm and their development. The approach in analysing the performance of the filtered-X LMS Algorithm, a heuristic method based on linear time-invariant operator theory is provided to analyse the robust perfonnance of the filtered-X structure. It indicates that the extra filter could enhance the stability margin of the corresponding non filtered X structure. To overcome the slow convergence problem while keeping the simplicity of the LMS based algorithms, an H2 optimal initialization is proposed.

Application of fast and robust equalization in communication technology

In this paper, the authors explore the potential of several popular equalization techniques while overcoming their disadvantages. First, extensive literature survey on equalization is conducted. The focus is on popular linear equalization algorithms such as the conventional least-mean-square (LMS) algorithm , The recursive least-squares (RLS) algorithm, the filtered-X LMS algorithm and their development. To overcome the slow convergence problem while keeping the simplicity of the LMS based algorithms, an H2 optimal initialization is proposed.

Position estimation and tracking of an autonomous mobile sensor using received signal strength

In this paper, an algorithm for approximating the path of a moving autonomous mobile sensor with an unknown position location using Received Signal Strength (RSS) measurements is proposed. Using a Least Squares (LS) estimation method as an input, a Maximum-Likelihood (ML) approach is used to determine the location of the unknown mobile sensor. For the mobile sensor case, as the sensor changes position the characteristics of the RSS measurements also change; therefore the proposed method adapts the RSS measurement model by dynamically changing the pass loss value alpha to aid in position estimation. Secondly, a Recursive Least-Squares (RLS) algorithm is used to estimate the path of a moving mobile sensor using the Maximum-Likelihood position estimation as an input. The performance of the proposed algorithm is evaluated via simulation and it is shown that this method can accurately determine the position of the mobile sensor, and can efficiently track the position of the mobile sensor during motion.

A generalized data windowing scheme for adaptive conjugate gradient algorithms

The performance of the modified adaptive conjugate gradient (CG) algorithms based on the iterative CG method for adaptive filtering is highly related to the ways of estimating the correlation matrix and the cross-correlation vector. The existing approaches of implementing the CG algorithms using the data windows of exponential form or sliding form result in either loss of convergence or increase in misadjustment. This paper presents and analyzes a new approach to the implementation of the CG algorithms for adaptive filtering by using a generalized data windowing scheme. For the new modified CG algorithms, we show that the convergence speed is accelerated, the misadjustment and tracking capability comparable to those of the recursive least squares (RLS) algorithm are achieved. Computer simulations demonstrated in the framework of linear system modeling problem show the improvements of the new modifications.

Restless leg syndrome caused by olanzapine: a case series

Restless leg syndrome (RLS) is a common disorder associated with significant distress. We report three cases of drug induced RLS caused by olanzapine. In each case, RLS commenced after initiation of treatment with olanzapine and resolved after ceasing olanzapine. All three patients were subsequently treated with other atypical antipsychotics, risperidone, quetiapine or aripiprazole, without re-emergence of RLS. RLS is associated with central dopaminergic dysfunction. Dopamine agonists and l-dopa reduce the symptoms of RLS, and some agents that block the dopaminergic system aggravate RLS. Greater awareness of potential causes of RLS, and its differentiation from akathisia and illness related agitation might help in reducing the distress associated with it and improving patient compliance.

Quality of life in restless legs syndrome: A systematic review of clinical trials and a critical review of instruments

Restless legs syndrome (RLS) is a neurological movement disorder characterized by sensory symptoms and motor disturbances. While the underlying cause remains unknown, it is suggested that 20–25% of people with RLS are affected seriously enough to require pharmacological treatment. Dopamine agonists (DAs) are the most common treatment and act by increasing the low levels of dopamine to which RLS is often attributed. A growing literature highlights the debilitating and distressing nature of this condition from the patient's perspective. While sleep problems are most commonly reported, the impact of RLS on quality of life (QOL) is wide ranging, affecting relationships with partners, sex life, family life, social life, leisure activities, friendships, everyday activities, concentration, travel, career/work, sleep, and health.

We conducted a systematic review of clinical trials in which DAs have been evaluated in terms of RLS-specific QOL, i.e. their impact on the QOL of people with RLS, and critically reviewed the development history and measurement properties of RLS-specific QOL instruments.

A systematic search using terms synonymous with RLS, DAs and QOL was conducted using Scopus software, which includes MEDLINE, PsycINFO, EMBASE, and CINAHL. Our search covered publications from 2000 (prior to which RLS-specific QOL measures did not exist) to August 2009. Trials were included in our review if they evaluated DAs for the treatment of adults with RLS and reported evaluation using an RLS-specific QOL measure. We also ran citation searches to identify papers reporting the development history and measurement properties of the identified RLS-specific QOL instruments.

Three measures of RLS-specific QOL have been developed in recent years and are reviewed here: the Restless Legs Syndrome Quality of Life (RLSQOL) questionnaire, the Restless Legs Syndrome Quality of Life Instrument (RLS-QLI), and the Quality of Life Restless Legs Syndrome (QOL-RLS) measure. Critical review indicates that each has limitations (particularly in terms of published developmental history and content validity). Eleven trials of DAs were identified that included assessment of RLS-specific QOL (nine using the RLSQOL and two using the QOL-RLS). In all studies, significant improvements in RLS-specific QOL were observed, although these were mostly short term (12 weeks) and large placebo effects were also noted.

In people with RLS, the use of DAs has been shown to improve RLS-specific QOL. Longer-term, large-scale studies may be needed to confirm these findings and demonstrate statistically significant improvements in RLS-specific QOL at lower doses. Further development of the RLS-specific QOL measures is needed to ensure that the full impact of RLS (and the full benefit of new treatments) on aspects of life identified as important to individuals is captured in future studies.

Impact of HIV-associated conditions on mortality in people commencing anti-retroviral therapy in resource limited settings

Objectives: To identify associations between specific WHO stage 3 and 4 conditions diagnosed after ART initiation and all cause mortality for patients in resource-limited settings (RLS).

Design, Setting: Analysis of routine program data collected prospectively from 25 programs in eight countries between 2002 and 2010.

Subjects, Participants: 36,664 study participants with median ART follow-up of 1.26 years (IQR 0.55–2.27).

Outcome Measures: Using a proportional hazards model we identified factors associated with mortality, including the occurrence of specific WHO clinical stage 3 and 4 conditions during the 6-months following ART initiation.

Results: There were 2922 deaths during follow-up (8.0%). The crude mortality rate was 5.41 deaths per 100 person-years (95% CI: 5.21–5.61). The diagnosis of any WHO stage 3 or 4 condition during the first 6 months of ART was associated with
increased mortality (HR: 2.21; 95% CI: 1.97–2.47). After adjustment for age, sex, region and pre-ART CD4 count, a diagnosis of extrapulmonary cryptococcosis (aHR: 3.54; 95% CI: 2.74–4.56), HIV wasting syndrome (aHR: 2.92; 95%CI: 2.21 -3.85), nontuberculous mycobacterial infection (aHR: 2.43; 95% CI: 1.80–3.28) and Pneumocystis pneumonia (aHR: 2.17; 95% CI 1.80–3.28) were associated with the greatest increased mortality. Cerebral toxoplasmosis, pulmonary and extra-pulmonary
tuberculosis, Kaposi’s sarcoma and oral and oesophageal candidiasis were associated with increased mortality, though at lower rates.

Conclusions: A diagnosis of certain WHO stage 3 and 4 conditions is associated with an increased risk of mortality in those initiating ART in RLS. This information will assist initiatives to reduce excess mortality, including prioritization of resources for
diagnostics, therapeutic interventions and research.

Estudo do efeito de dipolos em arranjos de antenas adaptativas de sistemas de comunicação DS-CDMA

This master dissertation introduces a study about some aspects that determine the aplication of adaptative arrays in DS-CDMA cellular systems. Some basics concepts and your evolution in the time about celular systems was detailed here, meanly the CDMA tecnique, specialy about spread-codes and funtionaly principies. Since this, the mobile radio enviroment, with your own caracteristcs, and the basics concepts about adaptive arrays, as powerfull spacial filter was aborded. Some adaptative algorithms was introduced too, these are integrants of the signals processing, and are answerable for weights update that influency directly in the radiation pattern of array. This study is based in a numerical analysis of adaptative array system behaviors related to the used antenna and array geometry types. All the simulations was done by Mathematica 4.0 software. The results for weights convergency, square mean error, gain, array pattern and supression capacity based the analisis made here, using RLS (supervisioned) and LSDRMTA (blind) algorithms

Estudo do efeito de dipolos em arranjos de antenas adaptativas de sistemas de comunicação DS-CDMA

This master dissertation introduces a study about some aspects that determine the aplication of adaptative arrays in DS-CDMA cellular systems. Some basics concepts and your evolution in the time about celular systems was detailed here, meanly the CDMA tecnique, specialy about spread-codes and funtionaly principies. Since this, the mobile radio enviroment, with your own caracteristcs, and the basics concepts about adaptive arrays, as powerfull spacial filter was aborded. Some adaptative algorithms was introduced too, these are integrants of the signals processing, and are answerable for weights update that influency directly in the radiation pattern of array. This study is based in a numerical analysis of adaptative array system behaviors related to the used antenna and array geometry types. All the simulations was done by Mathematica 4.0 software. The results for weights convergency, square mean error, gain, array pattern and supression capacity based the analisis made here, using RLS (supervisioned) and LSDRMTA (blind) algorithms.