Design and Fabrication of 3.5 GHz Band-Pass Film Bulk Acoustic Resonator Filter.

With the development of wireless communication, increasing signal processing presents higher requirements for radio frequency (RF) systems. Piezoelectric acoustic filters, as important elements of an RF front-end, have been widely used in 5G-generation systems. In this work, we propose a Sc0.2Al0.8N-based film bulk acoustic wave resonator (FBAR) for use in the design of radio frequency filters for the 5G mid-band spectrum with a passband from 3.4 to 3.6 GHz. With the excellent piezoelectric properties of Sc0.2Al0.8N, FBAR shows a large Keff2 of 13.1%, which can meet the requirement of passband width. Based on the resonant characteristics of Sc0.2Al0.8N FBAR devices, we demonstrate and fabricate different ladder-type FBAR filters with second, third and fourth orders. The test results show that the out-of-band rejection improves and the insertion loss decreases slightly as the filter order increases, although the frequency of the passband is lower than the predicted ones due to fabrication deviation. The passband from 3.27 to 3.47 GHz is achieved with a 200 MHz bandwidth and insertion loss lower than 2 dB. This work provides a potential approach using ScAlN-based FBAR technology to meet the band-pass filter requirements of 5G mid-band frequencies.

Beyond the individual: An improved telecom fraud detection approach based on latent synergy graph learning.

The development of telecom technology not only facilitates social interactions but also inevitably provides the breeding ground for telecom fraud crimes. However, telecom fraud detection is a challenging task as fraudsters tend to commit co-fraud and disguise themselves within the mass of benign ones. Previous approaches work by unearthing differences in calling sequential patterns between independent fraudsters, but they may ignore synergic fraud patterns and oversimplify fraudulent behaviors. Fortunately, graph-like data formed by traceable telecom interaction provides opportunities for graph neural network (GNN)-based telecom fraud detection methods. Therefore, we develop a latent synergy graph (LSG) learning-based telecom fraud detector, named LSG-FD, to model both sequential and interactive fraudulent behaviors. Specifically, LSG-FD introduces (1) a multi-view LSG extractor to reconstruct synergy relationship-oriented graphs from the meta-interaction graph based on second-order proximity assumption; (2) an LSTM-based calling behavior encoder to capture the sequential patterns from the perspective of local individuals; (3) a dual-channel based graph learning module to alleviate the disassortativity issue (caused by the camouflages of fraudsters) by incorporating the dual-channel frequency filters and the learnable controller to adaptively aggregate high- and low-frequency information from their neighbors; (4) an imbalance-resistant model trainer to remedy the graph imbalance issue by developing a label-aware sampler. Experiment results on the telecom fraud dataset and another two widely used fraud datasets have verified the effectiveness of our model.

Various-Order Low-Pass Filter with the Electronic Change of Its Approximation.

The design of a low-pass-frequency filter with the electronic change of the approximation characteristics of resulting responses is presented. The filter also offers the reconnection-less reconfiguration of the order (1st-, 2nd-, 3rd- and 4th-order functions are available). Furthermore, the filter offers the electronic control of the cut-off frequency of the output response. The feature of the electronic change in the approximation characteristics is investigated for the Butterworth, Bessel, Elliptic, Chebyshev and Inverse Chebyshev approximations. The design is verified by PSpice simulations and experimental measurements. The results are also supported by the transient domain response (response to the square waveform), comparison of the group delay, sensitivity analysis and implementation feasibility based on given approximation. The benefit of the proposed electronic change in the approximation characteristics feature (in general signal processing or for sensors in particular) is presented and discussed for an exemplary scenario.

Improving Image Quality by Deconvolution Recovery Filter in Ultrasound Imaging.

Due to the advantages of non-radiation and real-time performance, ultrasound imaging is essential in medical imaging. Image quality is affected by the performance of the transducer in an ultrasound imaging system. For example, the bandwidth controls the pulse length, resulting in different axial resolutions. Therefore, a transducer with a large bandwidth helps to improve imaging quality. However, large bandwidths lead to increased system cost and sometimes a loss of sensitivity and lateral resolution in attenuating media. In this paper, a deconvolution recovery method combined with a frequency-domain filtering technique (DRF) is proposed to improve the imaging quality, especially for the axial resolution. In this method, the received low-bandwidth echo signals are converted into high-bandwidth signals, which is similar to the echo signals produced by a high-bandwidth transducer, and the imaging quality is improved. Simulation and experiment results show that, compared with Delay-and-sum (DAS) method, the DRF method improved axial resolution from 0.60 to 0.41 mm in simulation and from 0.62 to 0.47 mm in the tissue-mimicking phantom experiment. The contrast ratio performance is improved to some extent compared with the DAS in experimental and in-vivo images. Besides, the proposed method has the potential to further improve image quality by combining it with adaptive weightings, such as the minimum variance method.

Correction of the skull density ratio for transcranial MRI-guided focused ultrasound thalamotomy: clinical significance of predicting therapeutic temperature.

OBJECTIVE: In transcranial magnetic resonance imaging-guided focused ultrasound (TcMRgFUS), a high skull density ratio (SDR) is advantageous to achieve a sufficiently high temperature at the target. However, it is not easy to estimate the temperature rise because the SDR shows different values depending on the reconstruction filter used. The resolution characteristic of a computed tomography (CT) image depends on a modulation transfer function (MTF) defined by the reconstruction filter. Differences in MTF induce unstable SDRs. The purpose of this study was both to standardize SDR by developing a method to correct the MTF and to enable effective patient screening prior to TcMRgFUS treatment and more accurate predictions of focal temperature. METHODS: CT images of a skull phantom and five subjects were obtained using eight different reconstruction filters. A frequency filter (FF) was calculated using the MTF of each reconstruction filter, and the validity of SDR standardization was evaluated by comparing the variation in SDR before and after FF correction. Subsequently, FF processing was similarly performed using the CT images of 18 patients who had undergone TcMRgFUS, and statistical analyses were performed comparing the relationship between the SDRs before and after correction and the maximum temperature in the target during TcMRgFUS treatment. RESULTS: The FF was calculated for each reconstruction filter based on one manufacturer's BONE filter. In the CT images of the skull phantom, the SDR before FF correction with five of the other seven reconstruction filters was significantly smaller than that with the BONE filter (p < 0.01). After FF correction, however, a significant difference was recognized under only one condition. In the CT images of the five subjects, variation of the SDR due to imaging conditions was significantly improved after the FF correction. In 18 cases treated with TcMRgFUS, there was no correlation between SDR before FF correction and maximum temperature (rs = 0.31, p > 0.05); however, a strong positive correlation was observed after FF correction (rs = 0.71, p < 0.01). CONCLUSIONS: After FF correction, the difference in SDR due to the reconstruction filter used is smaller, and the correlation with temperature is stronger. Therefore, the SDR can be standardized by applying the FF, and the maximum temperature during treatment may be predicted more accurately.

Reconnection-less reconfigurable low-pass filtering topology suitable for higher-order fractional-order design.

The paper discusses a new design of a current-mode reconnection-less reconfigurable fractional-order (FO) low-pass filter of various orders. The filtering structure is based on a 4th-order leap-frog topology using operational transconductance amplifiers as basic building blocks. The resulting order of the filter is given by the setting of current gains (allowing the reconnection-less reconfiguration) alongside with the values of the fractional-order capacitors realized by the RC ladder networks. For this purpose, RC ladder networks of orders 0.3, 0.4, 0.5, 0.6 and 0.7 have been designed. The fractional-order form of the filter contains from one up to four FO capacitors (remaining capacitors (if there are any) are of integer-order) allowing to obtain low-pass functions of order of 3 + α, 2 + α, 1 + α, 2 + α + ß, 1 + α + ß, α + ß, 1 + α + ß + Î³, α + ß + Î³ and α + ß + Î³ + Î´. The proposed filter offers a wide variety of possible order combinations with an increasing degree of freedom as the number of fractional-order capacitors within the structure increases. The proposal is supported by the PSpice simulations of magnitude and phase characteristics, pole frequency adjustment and stability analysis. Moreover, the experimental measurements of the implemented filter were carried out and compared with the simulation results. The possibility of the electronic control of the fractional order is also discussed and presented.

Frequency-splitting dynamic MRI reconstruction using multi-scale 3D convolutional sparse coding and automatic parameter selection.

In this paper, we propose a novel image reconstruction algorithm using multi-scale 3D convolutional sparse coding and a spectral decomposition technique for highly undersampled dynamic Magnetic Resonance Imaging (MRI) data. The proposed method recovers high-frequency information using a shared 3D convolution-based dictionary built progressively during the reconstruction process in an unsupervised manner, while low-frequency information is recovered using a total variation-based energy minimization method that leverages temporal coherence in dynamic MRI. Additionally, the proposed 3D dictionary is built across three different scales to more efficiently adapt to various feature sizes, and elastic net regularization is employed to promote a better approximation to the sparse input data. We also propose an automatic parameter selection technique based on a genetic algorithm to find optimal parameters for our numerical solver which is a variant of the alternating direction method of multipliers (ADMM). We demonstrate the performance of our method by comparing it with state-of-the-art methods on 15 single-coil cardiac, 7 single-coil DCE, and a multi-coil brain MRI datasets at different sampling rates (12.5%, 25% and 50%). The results show that our method significantly outperforms the other state-of-the-art methods in reconstruction quality with a comparable running time and is resilient to noise.

Wheat ear counting in-field conditions: high throughput and low-cost approach using RGB images.

BACKGROUND: The number of ears per unit ground area (ear density) is one of the main agronomic yield components in determining grain yield in wheat. A fast evaluation of this attribute may contribute to monitoring the efficiency of crop management practices, to an early prediction of grain yield or as a phenotyping trait in breeding programs. Currently the number of ears is counted manually, which is time consuming. Moreover, there is no single standardized protocol for counting the ears. An automatic ear-counting algorithm is proposed to estimate ear density under field conditions based on zenithal color digital images taken from above the crop in natural light conditions. Field trials were carried out at two sites in Spain during the 2014/2015 crop season on a set of 24 varieties of durum wheat with two growing conditions per site. The algorithm for counting uses three steps: (1) a Laplacian frequency filter chosen to remove low and high frequency elements appearing in an image, (2) a Median filter to reduce high noise still present around the ears and (3) segmentation using Find Maxima to segment local peaks and determine the ear count within the image. RESULTS: The results demonstrate high success rate (higher than 90%) between the algorithm counts and the manual (image-based) ear counts, and precision, with a low standard deviation (around 5%). The relationships between algorithm ear counts and grain yield was also significant and greater than the correlation with manual (field-based) ear counts. In this approach, results demonstrate that automatic ear counting performed on data captured around anthesis correlated better with grain yield than with images captured at later stages when the low performance of ear counting at late grain filling stages was associated with the loss of contrast between canopy and ears. CONCLUSIONS: Developing robust, low-cost and efficient field methods to assess wheat ear density, as a major agronomic component of yield, is highly relevant for phenotyping efforts towards increases in grain yield. Although the phenological stage of measurements is important, the robust image analysis algorithm presented here appears to be amenable from aerial or other automated platforms.

The effect of different low-frequency filters on concentric needle jitter in stimulated orbicularis oculi.

INTRODUCTION: Our objective was to compare the effect of different low-frequency filters on jitter parameters when stimulating the orbicularis oculi. METHODS: Ten healthy volunteers were studied. Jitter was expressed as the mean consecutive difference (MCD). The low filter settings compared were 1, 2, and 3 kHz. RESULTS: No significant difference in mean MCD or outliers was found with the different filter settings. No significant difference in mean MCD was seen when the number of potentials analyzed was reduced. CONCLUSION: Different low-frequency settings do not influence the mean MCD when using a peak detection system. Muscle Nerve 54: 317-319, 2016.

Reduction in Unnecessary Clinical Laboratory Testing Through Utilization Management at a US Government Veterans Affairs Hospital.

OBJECTIVES: To implement an electronic laboratory utilization management system (laboratory expert system [LES]) to provide safe and effective reductions in unnecessary clinical laboratory testing. METHODS: The LES is a set of frequency filter subroutines within the Veterans Affairs hospital and laboratory information system that was formulated by an interdisciplinary medical team. RESULTS: Since implementing the LES, total test volume has decreased by a mean of 11.18% per year compared with our pre-LES test volume. This change was not attributable to fluctuations in outpatient visits or inpatient days of care. Laboratory cost savings were estimated at $151,184 and $163,751 for 2012 and 2013, respectively. A significant portion of these cost savings was attributable to reductions in high-volume, large panel testing. No adverse effects on patient care were reported, and mean length of stay for patients remained unchanged. CONCLUSIONS: Electronic laboratory utilization systems can effectively reduce unnecessary laboratory testing without compromising patient care.

Steal phenomenon in Sturge-Weber syndrome imitating an ictal electroencephalography change in the contralateral hemisphere: report of 2 cases.

Infants with Sturge-Weber syndrome (SWS) are considered for surgery if they develop seizures and the seizures prove medically refractory. The authors report on 2 infants (15 and 19 months old) with SWS who underwent scalp video electroencephalography (EEG) and subsequent functional hemispherotomy for intractable partial motor seizures due to extensive left hemispheric angiomatosis. They presented with similar interictal and ictal EEG findings. Ictal EEG showed abrupt high-amplitude delta slow waves, without evolution on the contralateral hemisphere before the build-up of ictal EEG changes on the lesional hemisphere. The patients became seizure free after hemispherotomy. The ictal contralateral slow waves were not a sign of an ictal hemisphere and may indicate prominent ischemic changes resulting from a steal phenomenon of hemispheric angiomatosis during seizure.

Percepção visual de contraste em humanos: evidência psicofísica para canais de freqüência angular alta / Visual contrast perception in human beings: psychophysical evidence for high angular frequency channels

O objetivo deste trabalho foi mensurar curvas de resposta ao contraste para os filtros de freqüências angulares de banda estreita de 32, 48, 64 e 96 ciclos/360º. Foram estimadas nove curvas para cada filtro com o método psicofísico de somação de resposta de supralimiar aliado ao método da escolha forçada. Participaram deste experimento seis participantes adultos com acuidade visual normal ou corrigida. Os resultados demonstraram somações máximas de limiar de contraste na freqüência de teste dos filtros de 32, 48, 64 e 96 ciclos/360º circundadas por inibições nas freqüências vizinhas às freqüências angulares de teste de cada filtro. Estes resultados são consistentes com a existência de filtros de freqüências angulares de banda estreita no sistema visual humano através do processo de somação ou inibição na faixa de freqüência angular alta.

The aim of this study was to measure narrow-band frequency response curves for four angular frequency filters. The test frequencies were 32, 48, 64 and 96 cycles/360º. Six humans observers with normal or corrected visual acuity measured nine curves for each filter, with a supra-threshold response summation psychophysical method allied with a forced-choice method. The results showed maximum summation effects at test frequency for filter frequencies 32, 48, 64 and 96 cycles/360º, as well as a strong inhibition for neighboring frequencies. These results are consistent with the existence of narrow-band angular frequency filters in the human visual system either through summation or the inhibition of specific high angular frequency ranges.