Compact, wideband impedance tuner using a three-line-microstrip structure

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A novel three-line-microstrip compact impedance tuner is presented. It is based on a multimodal structure wherein six variable capacitances, implemented with two parallel-connected varactors each, create multiple interactions among the three-line-microstrip modes in a reduced circuit area. Experimental results show better-than-70% coverage of the Smith chart in an 85% frequency bandwidth from 1.4 to 3.2 GHz.Peer ReviewedPostprint (author's final draft

Quantum computation with phase drift errors

We present results of numerical simulations of the evolution of an ion trap quantum computer made out of 18 ions which are subject to a sequence of nearly 15000 laser pulses in order to find the prime factors of N=15. We analyze the effect of random and systematic phase drift errors arising from inaccuracies in the laser pulses which induce over (under) rotation of the quantum state. Simple analytic estimates of the tolerance for the quality of driving pulses are presented. We examine the use of watchdog stabilization to partially correct phase drift errors concluding that, in the regime investigated, it is rather inefficient.Comment: 5 pages, RevTex, 2 figure

Assessment of nutritional status by dual X-Ray absorptiometry in women with rheumatoid arthritis: a case-control study

Rheumatoid arthritis (RA) has been related to an impairment of the nutritional status. Body mass index (BMI) has been used but questions arise about how to properly evaluate nutritional status in RA patients. Few studies have evaluated it by dual-energy X-ray absorptiometry.In women with RA, to analyze:Case-control study including 89 women with RA. The control group was composed by 100 patients affected by non-inflammatory rheumatic disorders. Study variables included age, RA duration, history, activity and disability, and in relation to nutritional status: BMI, serum albumin (ALB), whole body DXA assessment, and skeletal muscle index (SMI).Mean age of patients was 62 ± 8 years, mean duration of RA was 14 ± 9 years, mean disease activity score (DAS28) was 3.7 ± 1.4 and mean Health Assessment Questionnaire was 0.88 ± 0.77. BMI was 27.43 ± 5.16 Kg/m in patients and 27.78 ± 3.98 Kg/m in controls (P: ns). ALB was within normal range in all patients.By whole body DXA, RA patients presented a statistically significant lower lean mass in all locations and lower fat mass in limbs than controls. Patients had a redistribution of fat mass to trunk. Lean mass directly correlated with fat mass.Neither BMI nor ALB correlated with DXA parameters.BMI, appendicular lean mass and SMI correlated inversely with disease duration. Trunk lean mass correlated inversely, and fat mass directly, with RA disability parameters.RA patients fulfilled criteria of sarcopenia in 44% of cases versus 19% of controls (P <.001). In RA patients, regarding SMI, BMI showed a high specificity to detect sarcopenia (94% of the patients with low BMI had sarcopenia) but low sensitivity (47% of the patients with normal BMI or overweight had sarcopenia).RA patients have an impairment of nutritional status associated to disease duration that looks like sarcopenia and that is not predicted by BMI

AI-Friendly.com: Artificial Intelligence Made Friendly

AI-Friendly is a web application that allows to easily perform binary classification with a neural network. It is free and allows network customization, making it a useful tool for machine learning courses.Sociedad Argentina de Informática e Investigación Operativ

Application of the Standardized Precipitation Evapotranspiration Index (SPEI) for drought analysis and monitoring: characteristics, recommendations and comparison with other indices

The complexity of drought quantification and analysis: • Droughts are difficult to pinpoint in time and space given different economic sectors and natural systems affected. • We identify a drought by its effects or impacts on different types of systems (agriculture, water resources, ecology, forestry, economy, etc.), but there is not a physical variable we can measure to quantify droughts. • Long-term drought objective metrics (streamflows, soil moisture, lake levels, etc.) are commonly not available. Moreover, using only objective metrics other relevant variables to determine drought severity (e.g. the atmospheric water demand) are not taken into account. • We use the so-called “DROUGHT INDICES” for drought quantification and analysis. Standardized Precipitation Evapotranspiration Index (SPEI): The SPEI uses the difference between precipitation and ETo. This represents a simple climatic water balance which is calculated at different time scales to obtain the SPEI. With a value for ETo, the difference between the precipitation (P) and PET for the month i is calculated according to: Di = Pi-EToi, The calculated D values are aggregated at different time scalesPeer Reviewe

Condition monitoring system for characterization of electric motor ball bearings with distributed fault using fuzzy inference tools

The present work shows a condition monitoring system applied to electric motors ball bearings. Unlike most of the previous work on this area, which is mainly focused on the location of single-point defects in bearing components – inner and outer races, cage or ball faults -, this research covers wide range irregularities which are very often more difficult to analyse. In addition to traditional techniques like vibration and current signals, high frequency current bearing pulses and acoustic emissions are also analysed. High frequency bearings current pulses are acquired using motors especially modified. This modification isolates ball bearings from the motor stator frame, except for a bearing housing single point connected to ground through a proper cable where the pulses signal is measured. A multivariable fuzzy inference analysis approach is presented to get around the diagnosis difficulty.Peer ReviewedPostprint (published version

Evaluation of machine learning techniques for electro-mechanical system diagnosis

The application of intelligent algorithms, in electro-mechanical diagnosis systems, is increasing in order to reach high Reliability and performance ratios in critical and complex scenarios. In this context, different multidimensional intelligent diagnosis systems, based on different machine learning techniques, are presented and evaluated in an electro-mechanical actuator diagnosis scheme. The used diagnosis methodology includes the acquisition of different physical magnitudes from the system, such as machine vibrations and stator currents, to enhance the monitoring capabilities. The features calculation process is based on statistical time and frequency domains features, as well as timefrequency fault indicators. A features reduction stage is, additionally, included to compress the descriptive fault information in a reduced feature set. After, different classification algorithms such as Support Vector Machines, Neural Network, k-Nearest Neighbors and Classification Trees are implemented. Classification ratios over inputs corresponding to previously learnt classes, and generalization capabilities with inputs corresponding to learnt classes slightly modified are evaluated in an experimental test bench to analyze the suitability of each algorithm for this kind of application.Peer ReviewedPostprint (author’s final draft

RF-MEMS switches for a full control of the propagating modes in uniplanar microwave circuits and their application to reconfigurable multimodal microwave filters

This is a copy of the author 's final draft version of an article published in the journal Microsystem technologies. The final publication is available at Springer via http://dx.doi.org/10.1007/s00542-017-3379-8In this paper, new RF-MEMS switch configurations are proposed to enable control of the propagating (even and odd) modes in multimodal CPW transmission structures. Specifically, a switchable air bridge (a switchable short-circuit for the CPW odd mode) and switchable asymmetric shunt impedances (for transferring energy between modes) are studied and implemented using bridge-type and cantilever-type ohmic-contact switches, respectively. The switchable air bridge is based in a novel double ohmic-contact bridge-type structure. Optimized-shape suspension configurations, namely folded-beam or diagonal-beam for bridge-type switches, and straight-shaped or semicircular-shaped for cantilever-type switches, are used to obtain robust structures against fabrication-stress gradients. The switches are modelled using a coupled-field 3D finite-element mechanical analysis showing a low to moderate pull-in voltage. The fabricated switches are experimentally characterized using S-parameter and DC measurements. The measured pull-in voltages agree well with the simulated values. From S-parameter measurements, an electrical model with a very good agreement for both switch states (ON and OFF) has been obtained. The model is used in the design of reconfigurable CPW multimodal microwave filters.Peer ReviewedPostprint (author's final draft