Location dependence of a MEMS electromagnetic transducer with respect to an AC power source

A MEMS, silicon based device with a cantilever oscillationsand an integrated magnet is presented for magnetic to electrical transduction. The cantilever structure can be configured either as an energy harvester to harvest power from an AC power line or as an AC current sensor. The positioning of the transducer with respect to the AC conductor is critical in both scenarios. For the energy scavenger, correct positioning is required to optimize the harvested power. For the current sensor, it is necessary to optimise the sensitivity of the sensor. This paper considers the effect of the relative position of the transducer with respect to the wire on the resulting electromagnetic forces and torques driving the device. It is shown here that the magnetic torque acting on a cantilever beam with an integrated magnet and in the vicinity of an alternating electromagnetic field is a very significant driver of the cantilever oscillations.

Two methods for voltage sag source location

This paper presents and compares two approaches to estimate the origin (upstream or downstream) of voltage sag registered in distribution substations. The first approach is based on the application of a single rule dealing with features extracted from the impedances during the fault whereas the second method exploit the variability of waveforms from an statistical point of view. Both approaches have been tested with voltage sags registered in distribution substations and advantages, drawbacks and comparative results are presented

A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

Two methods for voltage sag source location

This paper presents and compares two approaches to estimate the origin (upstream or downstream) of voltage sag registered in distribution substations. The first approach is based on the application of a single rule dealing with features extracted from the impedances during the fault whereas the second method exploit the variability of waveforms from an statistical point of view. Both approaches have been tested with voltage sags registered in distribution substations and advantages, drawbacks and comparative results are presented

A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

A study of the effect of heat source location in a ventilated room using multiple regression analysis

Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

The conservation of number and location of 18S sites indicates the relative stability of rDNA in species of Pentatomomorpha (Heteroptera)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Affective attitudes to face images associated with intracerebral EEG source location before face viewing

We investigated whether different, personality-related affective attitudes are associated with different brain electric field (EEG) sources before any emotional challenge (stimulus exposure). A 27-channel EEG was recorded in 15 subjects during eyes-closed resting. After recording, subjects rated 32 images of human faces for affective appeal. The subjects in the first (i.e., most negative) and fourth (i.e., most positive) quartile of general affective attitude were further analyzed. The EEG data (mean=25±4.8 s/subject) were subjected to frequency-domain model dipole source analysis (FFT-Dipole-Approximation), resulting in 3-dimensional intracerebral source locations and strengths for the delta–theta, alpha, and beta EEG frequency band, and for the full range (1.5–30 Hz) band. Subjects with negative attitude (compared to those with positive attitude) showed the following source locations: more inferior for all frequency bands, more anterior for the delta–theta band, more posterior and more right for the alpha, beta and 1.5–30 Hz bands. One year later, the subjects were asked to rate the face images again. The rating scores for the same face images were highly correlated for all subjects, and original and retest affective mean attitude was highly correlated across subjects. The present results show that subjects with different affective attitudes to face images had different active, cerebral, neural populations in a task-free condition prior to viewing the images. We conclude that the brain functional state which implements affective attitude towards face images as a personality feature exists without elicitors, as a continuously present, dynamic feature of brain functioning.

Pollen spectra and relative pollen productivity estimates for common taxa of the northern Siberian Arctic

Pollen productivity estimates (PPE) are used to quantitatively reconstruct variations in vegetation within a specific distance of the sampled pollen archive. Here, for the first time, PPEs from Siberia are presented. The study area (Khatanga region, Krasnoyarsk territory, Russia) is located in the Siberian Sub-arctic where Larixis the sole forest-line forming tree taxon. Pollen spectra from two different sedimentary environments, namely terrestrial mosses (n=16) and lakes (n=15, median radius ~100 m) and their surrounding vegetation were investigated to extract PPEs. Our results indicate some differences in pollen spectra between moss and lake pollen. Larix and Cyperaceae for example obtained higher representation in the lacustrine than in terrestrial moss samples. This highlights that in calibration studies modern and fossil dataset should be of similar sedimentary origin. The results of the Extended R-Value model were applied to assess the relevant source area of pollen (RSAP) and to calculate the PPEs for both datasets. As expected, the RSAP of the moss samples was very small (about 10 m) compared to the lacustrine samples (about 25 km). Calculation of PPEs for the six most common taxa yielded generally similar results for both datasets. Relative to Poaceae (reference taxon, PPE=1) Betula nana-type (PPEmoss: 1.8, PPElake: 1.8) and Alnusfruticosa-type (PPEmoss: 6.4, PPElake: 2.9) were overrepresented while Cyperaceae (PPEmoss: 0.5, PPElake: 0.1), Ericaceae (PPEmoss: 0.3, PPElake <0.01), Salix (PPEmoss: 0.03, PPElake <0.01) and Larix (PPEmoss <0.01, PPElake: 0.2) were under-represented in the pollen spectra compared to the vegetation in the RSAP. The estimation for the dominant tree in the region, Larixgmelinii, is the first published result for this species, but need to be considered very preliminary. The inferred sequence from over- to under-representation is mostly consistent with results from Europe; however, still the absolute values show some differences. Gathering vegetation data was limited by flowering season and low resolute satellite imagery and accessibility of the remote location of our study area. Therefore, our estimate may serve as first reference to strengthen future vegetation reconstructions in this climate-sensitive region.

Relative Concerns on Visible Consumption: A Source of Economic Distortions

Do relative concerns on visible consumption give rise to economic distortions? We re-examine the question posited by Arrow and Dasgupta (2009) building upon their general framework but recognizing that relative concerns can only apply to visible goods (e.g., cars, clothing, jewelry) and that households consume both visible and non-visible goods. Contrary to Arrow and Dasgupta (2009), the answer to this question turns to be always affirmative: the competitive equilibrium will always be different than the socially optimal one, since individuals do not take into account the negative externality they exert on others through the consumption of the visible good, while the social planner does. If one invokes separability assumptions, then the steady state competitive equilibrium consumption of non-visible goods will be strictly lower than the socially optimal one.