Design of ℓ1 New Suboptimal Fractional Delays Controller for Discrete Non-Minimum Phase System under Unknown-but-Bounded Disturbance

ℓ1-regularization methodologies have appeared recently in many pattern recognition and image processing tasks frequently connected to ℓ1-optimization in the control theory. We consider the problem of optimal stabilizing controller synthesis for a discrete non-minimum phase dynamic plant described by a linear difference equation with an additive unknown-but-bounded noise. Under considering the “worst” case of noise, the solving of these optimization problem has a combinatorial complexity. The choosing of an appropriate sufficiently high sampling rate allows to achieve an arbitrarily small level of suboptimality using a noncombinatorial algorithm. In this paper, we suggest to use fractional delays to achieve a small level of suboptimality without increasing the sampling rate so much. We propose an approximation of the fractional lag with a combination of rounding and a first-order fractional lag filter. The suggested approximation of the fractional delay is illustrated via a simulation example with a non-minimum phase second-order plant. The proposed methodology appears to be suitable to be used in various pattern recognition approaches.

Faults in Oceanic Crust Contribute to Slow Seismic Waves

New high-sampling rate measurements of fluid pressures in oceanic crust reveal unresolved fractures and pathways for fluid flow.

Conception and Simulation of a 2-Then-1-Bit/Cycle Noise-Shaping SAR ADC

A 2-then-1-bit/cycle noise-shaping successive-approximation register (SAR) analog-to-digital converter (ADC) for high sampling rate and high resolution is presented. The conversion consists of two phases of a coarse 2-bit/cycle SAR conversion for high speed and a fine 1-bit/cycle noise-shaping SAR conversion for high accuracy. The coarse conversion is performed by both voltage and time comparison for low power consumption. A redundancy after the coarse conversion corrects the error caused by a jitter noise during the time comparison. Additionally, a mismatch error between signal and reference paths is eliminated with the help of a tail-current-sharing comparator. The proposed ADC was designed in a 28 nm CMOS process, and the simulation result shows a 68.2 dB signal-to-noise distortion (SNDR) for a sampling rate of 480 MS/s and a bandwidth of 60 MHz with good energy efficiency.

Chronic Study on Brainwave Authentication in a Real-Life Setting: An LSTM-Based Bagging Approach

With the advent of the digital age, concern about how to secure authorized access to sensitive data is increasing. Besides traditional authentication methods, there is an interest in biometric traits such as fingerprints, the iris, facial characteristics, and, recently, brainwaves, primarily based on electroencephalography (EEG). Current work on EEG-based authentication focuses on acute recordings in laboratory settings using high-end equipment, typically equipped with 64 channels and operating at a high sampling rate. In this work, we validated the feasibility of EEG-based authentication in a real-world, out-of-laboratory setting using a commercial dry-electrode EEG headset and chronic recordings on a population of 15 healthy people. We used an LSTM-based network with bootstrap aggregating (bagging) to decode our recordings in response to a multitask scheme consisting of performed and imagined motor tasks, and showed that it improved the performance of the standard LSTM approach. We achieved an authentication accuracy, false acceptance rate (FAR), and false rejection rate (FRR) of 92.6%, 2.5%, and 5.0% for the performed motor task; 92.5%, 2.6%, and 4.9% for the imagined motor task; and 93.0%, 1.9%, and 5.1% for the combined tasks, respectively. We recommend the proposed method for time- and data-limited scenarios.

Brief Introduce of Planetary K-index: An Indicator of Geomagnetic Storms

The planetary K-index (Kp index) was a geomagnetic index in the H-component field. This index was calculated from data collected by a network of 13 ground-based magnetometer stations at mid-latitude locations from the International Real-time Magnetic Observatory Network (INTERMAGNET). The magnitudes of Kp index could indicate geomagnetic activity using the integer K-scale from 0 to 9 without dimension because the K-scale was estimated using the quasi-logarithms algorithm. The Kp index indicated geomagnetic storms under the condition of K-scale＞4. The three-hourly Kp index has been commonly used. The three-hourly Kp index was relatively stable for low‐variability geomagnetic activity. The hourly Kp index represented the level of auroral absorption with a more accurate characterization. For future research, the Kp index with a high sampling rate (e.g., ＜1 hour) could be considered, so that a very accurate characterization was characterized the more detailed geomagnetic activity of global region.

Microfluidic Bioreactor Made of Cyclo-Olefin Polymer for Observing On-Chip Platelet Production

We previously proposed a microfluidic bioreactor with glass–Si–glass layers to evaluate the effect of the fluid force on platelet (PLT) production and fabricated a three-dimensional (3D) microchannel by combining grayscale photolithography and deep reactive ion etching. However, a challenge remains in observing the detailed process of PLT production owing to the low visibility of the microfluidic bioreactor. In this paper, we present a transparent microfluidic bioreactor made of cyclo-olefin polymer (COP) with which to observe the process of platelet-like particle (PLP) production under a bright-field, which allows us to obtain image data at a high sampling rate. We succeeded in fabricating the COP microfluidic bioreactor with a 3D microchannel. We investigated the bonding strength of COP-COP layers and confirmed the effectiveness of the microfluidic bioreactor. Results of on-chip PLP production using immortalized megakaryocyte cell lines (imMKCLs) derived from human-induced pluripotent stem cells show that the average total number of produced PLPs per imMKCL was 17.6 PLPs/imMKCL, which is comparable to that of our previous glass–Si–glass microfluidic bioreactor (17.4 PLPs/imMKCL). We succeeded in observing PLP production under a bright-field using the presented microfluidic bioreactor and confirmed that PLP fragmented in a narrow area of proplatelet-like protrusions.

Sampling Rate Impact on Precise Point Positioning with a Low-Cost GNSS Receiver

Nowadays, with the incursion of low-cost GNSS receivers with modern characteristics, it is common to investigate and apply new methodologies and solutions with different receivers of this nature. Based on this fact, the performance of the solution obtained from the low-cost GNSS receiver is evaluated compared to a geodetic grade GNSS receiver at different sampling frequencies for the PPP-static and PPP-kinematic modes. For this, the original RINEX observation files were analyzed and decimated into different sampling rates as 0.1, 0.2, 1, 5, 15 and 30 s with TEQC software. All RINEX files were submitted to the Canadian Spatial Reference System Precise Point Positioning (CSRS-PPP) online service for processing with static and kinematic modes. The PPP-derived coordinates from the low-cost GNSS receiver were compared with the geodetic receiver to evaluate the obtained solution. The results reveal that the behavior of all studied sampling rates from the low-cost GNSS receiver are constant in achieved positioning. In addition, the achieved precision shows that it is recommendable to use a high sampling rate to obtain a cm level in PPP-static mode by using a low-cost GNSS receiver, this mode being the most accurate and potential alternative for structural health monitoring studies, mapping and positioning in urban areas.

Sticky Pi, an AI-powered smart insect trap for community chronoecology

Circadian clocks are paramount to insect survival and drive many aspects of their physiology and behaviour. While insect circadian behaviours have been extensively studied in the laboratory, their circadian activity within natural settings is poorly understood. The study of circadian activity necessitates measuring biological variables (e.g., locomotion) at high frequency (i.e., at least several times per hour) over multiple days, which has mostly confined insect chronobiology to the laboratory. In order to study insect circadian biology in the field, we developed the Sticky Pi, a novel, autonomous, open-source, insect trap that acquires images of sticky cards every twenty minutes. Using custom deep-learning algorithms, we automatically and accurately scored where, when and which insects were captured. First, we validated our device in controlled laboratory conditions with a classic chronobiological model organism, Drosophila melanogaster. Then, we deployed an array of Sticky Pis to the field to characterise the daily activity of an agricultural pest, Drosophila suzukii, and its parasitoid wasps. Finally, we demonstrate the wide scope of our smart trap by describing the sympatric arrangement of insect temporal niches in a community, without targeting particular taxa a priori. Together, the automatic identification and high sampling rate of our tool provide biologists with unique data that impacts research far beyond chronobiology; with applications to biodiversity monitoring and pest control as well as fundamental implications for phenology, behavioural ecology, and ecophysiology. We released the Sticky Pi project as an open community resource on https://doc.sticky-pi.com.