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Through numerical simulation, the blast-resistant performance of spray polyurea elastomer (SPUA) retrofitted concrete masonry unit (CMU) masonry infill walls under far-range blast loading was studied. From an engineering perspective, the effects of boundary conditions and thickness of a SPUA layer on enhancing the blast resistance of masonry infill walls are discussed, and the blast resistance of SPUA-retrofitted and grouted CMU masonry infill walls are compared. It is concluded that the boundary constraint conditions and the anchorage length of SPUA layer have limited improvement on the blast-resistant performance of the wall; the thickness of SPUA layer can significantly improve the blast-resistant performance of the wall as the blast loading increases. In addition, SPUA retrofitting shows relatively better performance to reinforce masonry infill walls.

Additional file 1: Table S1. Gene flow among different varieties.

Ultra-wideband (UWB) time-difference-of-arrival (TDOA)-based localization has recently emerged as a promising, low-cost, and scalable indoor localization solution, which is especially suited for multi-robot applications. However, there is a lack of public datasets to benchmark the emerging UWB TDOA positioning technology in cluttered indoor environments. To fill in this gap, we present a comprehensive dataset consists of UWB TDOA identification experiments and flight experiments based on Decawave's DWM1000 UWB modules. In the identification experiments, we collected low-level signal information, including signal-to-noise ratio (SNR) and power difference values, in various line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. For the flight experiments, we conducted a cumulative $\sim$150 minutes of real-world flights with an average speed of 0.45 m/s using four different anchor constellations. Raw sensor data including UWB TDOA, inertial measurement unit (IMU), optical flow, time-of-flight (ToF) laser, and millimeter-accurate ground truth data were collected during the flights. The dataset and development kit are available at https://utiasdsl.github.io/util-uwb-dataset/.

Energy and area-efficient sensor readouts have drawn increasing attention in the integrated circuit design field as the entering of the Internet-of-Things (IoT) era. Small form factor and extended battery life have become critical design targets as important as conventional analog and mixed-signal sensor readout specifications such as noise and dynamic range (DR). Technology advancement has brought extensive benefits to digital circuits, but analog circuits have been facing great design challenges due to the voltage supply and transistor intrinsic gain reduction in advanced processes. This presents a strong need for new design frameworks for sensor readouts that can leverage the properties of CMOS scaling instead of being limited by them. On the other hand, for sensor applications where multiple ADCs are required for multi-channel or parallel signal acquisition, the existence of a large number of ADCs usually causes area and power to grow linearly with the number of ADCs. For those applications, analog compression presents a great potential to become a valuable solution to further improve energy efficiency for sensor readouts on top of the advanced circuit design techniques. To address the challenges brought by the era of IoT, this dissertation explores solutions for IoT sensor readouts from two directions: area-/energy-efficient phase-domain VCO-based sensor readout circuit for single-channel general-purpose sensor interface and compressive sensing (CS) based analog compression scheme and readout circuits for multi-channel sensing scenarios. The first work presents a capacitively-coupled voltage-controlled oscillator (VCO)-based sensor readout featuring a hybrid phase-locked loop (PLL) - [Delta-Sigma] modulator structure. This work aims to propose a solution to the issues of analog sensor readout in advanced processes. It leverages phase-locking and phase-frequency detector (PFD) array to concurrently perform quantization and dynamic element matching (DEM), much reducing hardware/power compared to existing VCO-based readouts' counting scheme. A low-cost in-cell data weighted averaging (DWA) scheme is presented to enable highly linear tri-level digital-to-analog converter (DAC). Fabricated in 40 nm CMOS, the prototype readout achieves 78 dB SNDR in 10 kHz bandwidth, consuming 4.68 µW and 0.025 mm² active area. With 172 dB Schreier FoM, its efficiency advances state-of-the-art VCO-based readouts by 50 times. The second work presents a 4x compressive CMOS image sensor for always-on operation that achieves an energy efficiency of 51 pJ/pixel, while maintaining high image quality of PSNR > 32dB and SSIM > 0.84. This is enabled by an energy-efficient CS encoder, which replaces a densely populated CS encoding method with a highly sparse pseudo-diagonal one. Since the proposed CS encoder can be implemented with an energy-efficient switched-capacitor matrix multiplier at pixel outputs, data compression is achieved before to pixel digitization, thereby greatly reducing ADC power, data size, and I/O power. The energy efficiency of the image sensor is further improved by incorporating it into dynamic single-slope ADCs. A prototype VGA image sensor consumes only 0.7 mW at 45 fps. The corresponding energy per pixel (51 pJ/pixel) amounts to a 20x improvement over the previous low-energy benchmark on CS image sensors.

A coordinate rotation digital computation (CORDIC) based synthetic aperture radar (SAR) signal generation method is proposed to replace the traditional ROM-based direct digital synthesis (DDS) architecture in large scene electromagnetical echo simulation application. Considering the restriction and low-efficiency of general mathematical calculation, we find the CORDIC algorithm can maintain high precision result in transcedental function calculation and fast speed in reachable way. Both senarios in square root and trigonometic computation are analyzed. A combined CORDIC-I, II, III structure is applied in SAR signal generation named SAR-CORDIC, meanwhile, it is shown that this method can operate in wide range of input and sustain convergence. Relevant signal processing principles and procedures are also discussed in our works. We believe this method beyond its signal form can achieve resourceful accomplishment in future FPGA or ASIC signal processing application.

Accurate indoor localization is a crucial enabling technology for many robotics applications, from warehouse management to monitoring tasks. Ultra-wideband (UWB) ranging is a promising solution which is low-cost, lightweight, and computationally inexpensive compared to alternative state-of-the-art approaches such as simultaneous localization and mapping, making it especially suited for resource-constrained aerial robots. Many commercially-available ultra-wideband radios, however, provide inaccurate, biased range measurements. In this article, we propose a bias correction framework compatible with both two-way ranging and time difference of arrival ultra-wideband localization. Our method comprises of two steps: (i) statistical outlier rejection and (ii) a learning-based bias correction. This approach is scalable and frugal enough to be deployed on-board a nano-quadcopter's microcontroller. Previous research mostly focused on two-way ranging bias correction and has not been implemented in closed-loop nor using resource-constrained robots. Experimental results show that, using our approach, the localization error is reduced by ~18.5% and 48% (for TWR and TDoA, respectively), and a quadcopter can accurately track trajectories with position information from UWB only., 6 pages, 8 figures

Glaciation and mountain orogeny have generated new ecologic opportunities for plants, favoring an increase in the speciation rate. Moreover, they also act as corridors or barriers for plant lineages and populations. High genetic diversity ensures that species are able to survive and adapt. Gene flow is one of the most important determinants of the genetic diversity and structure of out-crossed species, and it is easily affected by biotic and abiotic factors. The aim of this study was to characterize the genetic diversity and structure of an alpine species, Festuca ovina L., in Xingjiang, China. A total of 100 individuals from 10 populations were analyzed using six amplified fragment length polymorphism (AFLP) primer pairs. A total of 583 clear bands were generated, of which 392 were polymorphic; thus, the percentage of polymorphic bands (PPB) was 67.24%. The total and average genetic diversities were 0.2722 and 0.2006 (0.1686-0.2225), respectively. The unweighted group method with arithmetic mean (UPGMA) tree, principal coordinates analysis (PCoA) and STRUCTURE analyses revealed that these populations or individuals could be clustered into two groups. The analysis of molecular variance analysis (AMOVA) suggested that most of the genetic variance existed within a population, and the genetic differentiation (Fst) among populations was 20.71%. The Shannon differentiation coefficient (G’st) among populations was 0.2350. Limited gene flow (Nm = 0.9571) was detected across all sampling sites. The Fst and Nm presented at different levels under the genetic barriers due to fragmentation. The population genetic diversity was significant relative to environmental factors such as temperature, altitude and precipitation.

Glaciation and mountain orogeny have generated new ecologic opportunities for plants, favoring an increase in the speciation rate. Moreover, they also act as corridors or barriers for plant lineages and populations. High genetic diversity ensures that species are able to survive and adapt. Gene flow is one of the most important determinants of the genetic diversity and structure of out-crossed species, and it is easily affected by biotic and abiotic factors. The aim of this study was to characterize the genetic diversity and structure of an alpine species, Festuca ovina L., in Xingjiang, China. A total of 100 individuals from 10 populations were analyzed using six amplified fragment length polymorphism (AFLP) primer pairs. A total of 583 clear bands were generated, of which 392 were polymorphic; thus, the percentage of polymorphic bands (PPB) was 67.24%. The total and average genetic diversities were 0.2722 and 0.2006 (0.1686-0.2225), respectively. The unweighted group method with arithmetic mean (UPGMA) tree, principal coordinates analysis (PCoA) and STRUCTURE analyses revealed that these populations or individuals could be clustered into two groups. The analysis of molecular variance analysis (AMOVA) suggested that most of the genetic variance existed within a population, and the genetic differentiation (Fst) among populations was 20.71%. The Shannon differentiation coefficient (G’st) among populations was 0.2350. Limited gene flow (Nm = 0.9571) was detected across all sampling sites. The Fst and Nm presented at different levels under the genetic barriers due to fragmentation. The population genetic diversity was significant relative to environmental factors such as temperature, altitude and precipitation.

Physicochemical Problems of Mineral Processing; 49; 387-395; ISSN 2084-4735