bluuebunny/crossref_metadata_2025 huggingface dataset:
Pressure Sensor System for Customized Scoliosis Braces
Authors: Fuss Franz Konstantin , Ahmad Asliza , Tan Adin Ming , Razman Rizal , Weizman Yehuda
Published: February 2021

Hard-shell thoracolumbar sacral orthoses (TLSOs) are used for treating idiopathic scoliosis, a deformation of the spine with a sideways curvature. The pressure required inside the TLSO for ideal corrective results remains unclear. Retrofitting TLSOs with commercially available pressure measurement systems is expensive and can only be performed in a laboratory. The aim of this study was to develop a cost-effective but accurate pressure sensor system for TLSOs. The sensor was built from a piezoresistive polymer, placed between two closed-cell foam liners, and evaluated with a material testing machine. Because foams are energy absorbers, the pressure-conductance curve was affected by hysteresis. The sensor was calibrated on a force plate with the transitions from loading to unloading used to establish the calibration curve. The root mean square error was 12% on average within the required pressure range of 0.01–0.13 MPa. The sensor reacted to the changing pressure during breathing and different activities when tested underneath a chest belt at different tensions. The peak pressure reached 0.135 MPa. The sensor was further tested inside the scoliosis brace during different activities. The measured pressure was 0.014–0.124 MPa. The results from this study enable cheaper and mobile systems to be used for clinical studies on the comfort and pressure of braces during daily activities.
Influence of Precise Products on the Day-Boundary Discontinuities in GNSS Carrier Phase Time Transfer
Authors: Zhang Xiangbo , Guo Ji , Hu Yonghui , Sun Baoqi , Wu Jianfeng , Zhao Dangli , He Zaimin
Published: February 2021

Global navigation satellite system (GNSS) precise point positioning (PPP) has been widely used for high-precision time and frequency transfer. However, the day-boundary discontinuities at the boundary epochs of adjacent days or batches are the most significant obstacle preventing PPP from continuous time transfer. The day-boundary discontinuities in station estimates and time comparisons are mainly caused by the code-pseudorange noise during the analysis of observation data in daily batches, where the absolute clock offset is determined by the average code measurements. However, some discontinuities with amplitudes even more than 0.15 ns may still appear in station clock estimates and time comparisons, although several methods had been proposed to remove such discontinuities. The residual small amplitude of the day-boundary discontinuities in some PPP station clock estimates and time comparisons through new GNSSs like Galileo seems larger, especially using precise clock products with large discontinuities. To further understand the origin of the day-boundary discontinuities, the influence of GNSS precise products on the day-boundary discontinuities in PPP station clock estimates and time comparisons is investigated in this paper. Ten whole days of Multi-GNSS Experiment (MGEX) from modified Julian date (MJD) 59028 to 59037 are used as the observation data. For a comparative analysis, the station clock estimates are compared with global positioning system (GPS) and Galileo observations through PPP and network solutions, separately. The experimental results show that the daily discontinuities in current combined GPS final and rapid clock products are less than 0.1 ns, and their influence on the origin of day-boundary discontinuities in PPP station clock estimates and time comparison are statistically negligible. However, the daily discontinuities in individual Analysis Centers (ACs) GPS products are more extensive, and their influence on the origin of the day-boundary discontinuities in GPS PPP station clock estimates cannot be ignored. The day-boundary discontinuities demonstrate random walk noise characteristics and deteriorate the station clocks’ long-term frequency stability, especially at an average time of more than one day. Although Galileo clock daily discontinuities are different from those of GPS, their influence on the day-boundary discontinuities in station clock estimates is nearly similar to the GPS PPP. The influence of daily discontinuities of Galileo clocks on PPP time comparison is similar to GPS and is not particularly critical to time comparison. However, combined and weighted MGEX products should be developed or Galileo IPPP should be used for remote comparison of high-stability clocks.
mmW Rotman Lens-Based Sensing: An Investigation Study
Authors: Sethi Waleed T. , Ibrahim Ahmed B. , Issa Khaled , Alshebeili Saleh A.
Published: February 2021

A Rotman lens is a wideband true-time delay device. Due to its simplistic structure with wave/signal routing capabilities, it has been widely utilized as a beamforming device in numerous communication systems. Since the basic Rotman lens design incorporates multiple input, output, and dummy ports, in this study, and for the first time, we utilized a Rotman lens as a sensor. The main idea was to gather abundant information from available Rotman lens ports to obtain better sensing performance. The realized lens is optimized to work in the millimeter wave (mmW) band from 27 to 29 GHz with a focus on a central frequency of 28 GHz. The design has a footprint of 140 × 103 × 0.8 mm3. The polarity correlator was used to characterize the material under investigation.
High Sensitivity Plasmonic Sensor Based on Fano Resonance with Inverted U-Shaped Resonator
Authors: Xiao Gongli , Xu Yanping , Yang Hongyan , Ou Zetao , Chen Jianyun , Li Haiou , Liu Xingpeng , Zeng Lizhen , Li Jianqing
Published: February 2021

Herein, we propose a tunable plasmonic sensor with Fano resonators in an inverted U-shaped resonator. By manipulating the sharp asymmetric Fano resonance peaks, a high-sensitivity refractive index sensor can be realized. Using the multimode interference coupled-mode theory and the finite element method, we numerically simulate the influences of geometrical parameters on the plasmonic sensor. Optimizing the structure parameters, we can achieve a high plasmonic sensor with the maximum sensitivity for 840 nm/RIUand figure of merit for 3.9 × 105. The research results provide a reliable theoretical basis for designing high sensitivity to the next generation plasmonic nanosensor.
An Experimental and Numerical Study on the Use of Chirped FBG Sensors for Monitoring Fatigue Damage in Hybrid Composite Patch Repairs
Authors: Rito Rodolfo L. , Ogin Stephen L. , Crocombe Andrew D.
Published: February 2021

In this paper, chirped fibre Bragg grating (CFBG) sensors used to monitor the structural health of a composite patch used to repair an aluminium panel is presented. To introduce damage, a notch was produced at the centre of an aluminium panel. The repair consisted of bonding a pre-cured composite patch to the host panel using an aerospace-grade film adhesive; the sensor was embedded in the bond-line during fabrication of the repair. The repaired panels were subjected to tension-tension loading in fatigue. Cracks initiated and grew from both ends of the notch in the aluminium panels and the fatigue loading was stopped periodically for short periods of time to record the reflected spectra from the sensor. It was found that perturbations in the reflected spectra began to occur when the crack was within about 2 to 3 mm of the sensor location; after the crack passed the sensor location, the perturbations essentially stabilised. Predicted reflected spectra have been found to be in good agreement with the experiment, confirming that CFBG sensors can detect crack growth in patch-repaired panels.
Next-Generation Internet of Things (IoT): Opportunities, Challenges, and Solutions
Authors: Zikria Yousaf Bin , Ali Rashid , Afzal Muhammad Khalil , Kim Sung Won
Published: February 2021

It is predicted that by 2025, all devices will be connected to the Internet, subsequently causing the number of devices connected with the Internet to rise [...]
Use of Bispectrum Analysis to Inspect the Non-Linear Dynamic Characteristics of Beam-Type Structures Containing a Breathing Crack
Authors: Cui Li , Xu Hao , Ge Jing , Cao Maosen , Xu Yangmin , Xu Wei , Sumarac Dragoslav
Published: February 2021

A breathing crack is a typical form of structural damage attributed to long-term dynamic loads acting on engineering structures. Traditional linear damage identification methods suffer from the loss of valuable information when structural responses are essentially non-linear. To deal with this issue, bispectrum analysis is employed to study the non-linear dynamic characteristics of a beam structure containing a breathing crack, from the perspective of numerical simulation and experimental validation. A finite element model of a cantilever beam is built with contact elements to simulate a breathing crack. The effects of crack depth and location, excitation frequency and magnitude, and measurement noise on the non-linear behavior of the beam are studied systematically. The result demonstrates that bispectral analysis can effectively identify non-linear damage in different states with strong noise immunity. Compared with existing methods, the bispectral non-linear analysis can efficiently extract non-linear features of a breathing crack, and it can overcome the limitations of existing linear damage detection methods used for non-linear damage detection. This study’s outcome provides a theoretical basis and a paradigm for damage identification in cracked structures.
A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station
Authors: Sun Bo , Tan Bo , Wang Wenbo , Lohan Elena Simona
Published: February 2021

The 5G network is considered as the essential underpinning infrastructure of manned and unmanned autonomous machines, such as drones and vehicles. Besides aiming to achieve reliable and low-latency wireless connectivity, positioning is another function provided by the 5G network to support the autonomous machines as the coexistence with the Global Navigation Satellite System (GNSS) is typically supported on smart 5G devices. This paper is a pilot study of using 5G uplink physical layer channel sounding reference signals (SRSs) for 3D user equipment (UE) positioning. The 3D positioning capability is backed by the uniform rectangular array (URA) on the base station and by the multiple subcarrier nature of the SRS. In this work, the subspace-based joint angle-time estimation and statistics-based expectation-maximization (EM) algorithms are investigated with the 3D signal manifold to prove the feasibility of using SRSs for 3D positioning. The positioning performance of both algorithms is evaluated by estimation of the root mean squared error (RMSE) versus the varying signal-to-noise-ratio (SNR), the bandwidth, the antenna array configuration, and multipath scenarios. The simulation results show that the uplink SRS works well for 3D UE positioning with a single base station, by providing a flexible resolution and accuracy for diverse application scenarios with the support of the phased array and signal estimation algorithms at the base station.
An Open-Source Test Environment for Effective Development of MARG-Based Algorithms
Authors: Odry Ákos
Published: February 2021

This paper presents an open-source environment for development, tuning, and performance evaluation of magnetic, angular rate, and gravity-based (MARG-based) filters, such as pose estimators and classification algorithms. The environment is available in both ROS/Gazebo and MATLAB/Simulink, and it contains a six-degrees of freedom (6 DOF) test bench, which simultaneously moves and rotates an MARG unit in the three-dimensional (3D) space. As the quality of MARG-based estimation becomes crucial in dynamic situations, the proposed test platform intends to simulate different accelerating and vibrating circumstances, along with realistic magnetic perturbation events. Moreover, the simultaneous acquisition of both the real pose states (ground truth) and raw sensor data is supported during these simulated system behaviors. As a result, the test environment executes the desired mixture of static and dynamic system conditions, and the provided database fosters the effective analysis of sensor fusion algorithms. The paper systematically describes the structure of the proposed test platform, from mechanical properties, over mathematical modeling and joint controller synthesis, to implementation results. Additionally, a case study is presented of the tuning of popular attitude estimation algorithms to highlight the advantages of the developed open-source environment.
Enhancement of Photoacoustic Signal Strength with Continuous Wave Optical Pre-Illumination: A Non-Invasive Technique
Authors: Thomas Anjali , Paul Souradip , Mitra Joy , Singh Mayanglambam Suheshkumar
Published: February 2021

Use of portable and affordable pulse light sources (light emitting diodes (LED) and laser diodes) for tissue illumination offers an opportunity to accelerate the clinical translation of photoacoustic imaging (PAI) technology. However, imaging depth in this case is limited because of low output (optical) power of these light sources. In this work, we developed a noninvasive technique for enhancing strength (amplitude) of photoacoustic (PA) signal. This is a photothermal-based technique in which a continuous wave (CW) optical beam, in addition to short-pulse ~ nsec laser beam, is employed to irradiate and, thus, raise the temperature of sample material selectively over a pre-specified region of interest (we call the process as pre-illumination). The increase in temperature, in turn enhances the PA-signal strength. Experiments were conducted in methylene blue, which is one of the commonly used contrast agents in laboratory research studies, to validate change in temperature and subsequent enhancement of PA-signal strength for the following cases: (1) concentration or optical absorption coefficient of sample, (2) optical power of CW-optical beam, and (3) time duration of pre-illumination. A theoretical hypothesis, being validated by numerical simulation, is presented. To validate the proposed technique for clinical and/or pre-clinical applications (diagnosis and treatments of cancer, pressure ulcers, and minimally invasive procedures including vascular access and fetal surgery), experiments were conducted in tissue-mimicking Agar phantom and ex-vivo animal tissue (chicken breast). Results demonstrate that pre-illumination significantly enhances PA-signal strength (up to ~70% (methylene blue), ~48% (Agar phantom), and ~40% (chicken tissue)). The proposed technique addresses one of the primary challenges in the clinical translation of LED-based PAI systems (more specifically, to obtain a detectable PA-signal from deep-seated tissue targets).
Abdominal Stiffness Evaluation in Massage for Constipation
Authors: Wang Yunyi , Sakakibara Chiaki , Shogenji Miho , Yoshida Mikako , Watanabe Tetsuyou
Published: February 2021

According to the experience of nurses and physiotherapists, the abdomen of constipated people becomes softer after abdominal massage. However, the relationship between the decrease in abdominal stiffness and the benefits of abdominal massage has not been examined quantitatively and is unclear. Furthermore, devices for measuring stiffness have been designed to measure relatively hard areas such as the shoulders and do not take into account the lateral outflow of the target tissue, which can be a problem when measuring the stiffness of soft areas such as the abdomen. To address these issues, this study presents a stiffness sensor suitable for measuring abdominal stiffness and investigates the relationship between the reduction in abdominal stiffness and the benefits of abdominal massage. The solution to prevent the lateral outflow of the target is the realization of a stopper, including a contact detection device, which enables a wide-area contact around the targeted area. The sensor consists of a stopper, probe, spring, and time-of-flight (ToF) sensors. The probe and spring provide appropriate pressure and deformation to the abdomen, whereas the stopper prevents the probe from being pushed into the abdomen more than necessary. The ToF sensor measures the deformation length when the deformation is stopped by the stopper. The abdominal stiffness can be derived from the deformation length. The investigation results indicate that the reduction in abdominal stiffness corresponds to the improvement of the stool condition or the maintenance of a healthy stool condition, whereas the maintenance of abdominal stiffness indicates the maintenance or deterioration of the stool condition.
Optimal Data Collection Time in LoRa Networks—A Time-Slotted Approach
Authors: Zorbas Dimitrios , Caillouet Christelle , Abdelfadeel Hassan Khaled , Pesch Dirk
Published: February 2021

LoRa is a low-power and long range radio communication technology designed for low-power Internet of Things devices. These devices are often deployed in remote areas where the end-to-end connectivity provided through one or more gateways may be limited. In this paper, we examine the case where the gateway is not available at all times. As a consequence, the sensing data need to be buffered locally and transmitted as soon as a gateway becomes available. However, due to the Aloha-style transmission policy of current LoRa-based standards, such as the LoRaWAN, delivering a large number of packets in a short period of time by a large number of nodes becomes impossible. To avoid bursts of collisions and expedite data collection, we propose a time-slotted transmission scheduling mechanism. We formulate the data scheduling optimisation problem, taking into account LoRa characteristics, and compare its performance to low complexity heuristics. Moreover, we conduct a set of simulations to show the benefits of synchronous communications on the data collection time and the network performance. The results show that the data collection can reliably be achieved at least 10 times faster compared to an Aloha-based approach for networks with 100 or more nodes. We also develop a proof-of-concept to assess the overhead cost of communicating the schedule to the nodes and we present experimental results.
An Anatomical Thermal 3D Model in Preclinical Research: Combining CT and Thermal Images
Authors: Schollemann Franziska , Barbosa Pereira Carina , Rosenhain Stefanie , Follmann Andreas , Gremse Felix , Kiessling Fabian , Czaplik Michael , Abreu de Souza Mauren
Published: February 2021

Even though animal trials are a controversial topic, they provide knowledge about diseases and the course of infections in a medical context. To refine the detection of abnormalities that can cause pain and stress to the animal as early as possible, new processes must be developed. Due to its noninvasive nature, thermal imaging is increasingly used for severity assessment in animal-based research. Within a multimodal approach, thermal images combined with anatomical information could be used to simulate the inner temperature profile, thereby allowing the detection of deep-seated infections. This paper presents the generation of anatomical thermal 3D models, forming the underlying multimodal model in this simulation. These models combine anatomical 3D information based on computed tomography (CT) data with a registered thermal shell measured with infrared thermography. The process of generating these models consists of data acquisition (both thermal images and CT), camera calibration, image processing methods, and structure from motion (SfM), among others. Anatomical thermal 3D models were successfully generated using three anesthetized mice. Due to the image processing improvement, the process was also realized for areas with few features, which increases the transferability of the process. The result of this multimodal registration in 3D space can be viewed and analyzed within a visualization tool. Individual CT slices can be analyzed axially, sagittally, and coronally with the corresponding superficial skin temperature distribution. This is an important and successfully implemented milestone on the way to simulating the internal temperature profile. Using this temperature profile, deep-seated infections and inflammation can be detected in order to reduce animal suffering.
Hyperdimensional Imaging Contrast Using an Optical Fiber
Authors: Chacko Jenu V. , Lee Han Nim , Wu Wenxin , Otegui Marisa S. , Eliceiri Kevin W.
Published: February 2021

Fluorescence properties of a molecule can be used to study the structural and functional nature of biological processes. Physical properties, including fluorescence lifetime, emission spectrum, emission polarization, and others, help researchers probe a molecule, produce desired effects, and infer causes and consequences. Correlative imaging techniques such as hyperdimensional imaging microscopy (HDIM) combine the physical properties and biochemical states of a fluorophore. Here we present a fiber-based imaging system that can generate hyper-dimensional contrast by combining multiple fluorescence properties into a single fluorescence lifetime decay curve. Fluorescence lifetime imaging microscopy (FLIM) with controlled excitation polarization and temporally dispersed emission can generate a spectrally coded, polarization-filtered lifetime distribution for a pixel. This HDIM scheme generates a better contrast between different molecules than that from individual techniques. This setup uses only a single detector and is simpler to implement, modular, cost-efficient, and adaptable to any existing FLIM microscope. We present higher contrast data from Arabidopsis thaliana epidermal cells based on intrinsic anthocyanin emission properties under multiphoton excitation. This work lays the foundation for an alternative hyperdimensional imaging system and demonstrates that contrast-based imaging is useful to study cellular heterogeneity in biological samples.
OpenADR and Agreement Audit Architecture for a Complete Cycle of a Flexibility Solution
Authors: Parejo Antonio , García Sebastián , Personal Enrique , Guerrero Juan Ignacio , García Antonio , Leon Carlos
Published: February 2021

Nowadays, the presence of renewable generation systems and mobile loads (i.e., electric vehicle) spread throughout the distribution network is increasing. The problem is that this type of system introduces an added difficulty since they present a strong dependence on the meteorology and the mobility needs of the users. This problem forces the distribution system operators to seek tools that make it possible to balance the relationship between consumption and generation. In this sense, automated demand response systems are an appropriate solution that allow the operator to request specific reductions in customers’ consumption, offering a discount to the customer and avoiding network congestion. This paper analyzes the implementation and architecture of a demand response solution based on OpenADR standard and its possible integration with a building management system through a use case. As will be analyzed, a key part of the architecture is the measurement system based on smart meters acting as sensors. This is the base of the auditing system which makes it possible to verify compliance with the consumption reduction agreements. Additionally, this study is completed with a parallel auditing system which makes it possible to verify compliance with the consumption reduction agreements. All of the proposed demand response cycle is implemented as a proof of concept in a classroom in the Escuela Politécnica Superior at the University of Seville, which makes it possible to identify the advantages of this architecture in the ambit of connection between distribution network and buildings.
Deep Learning-Based Detection of Articulatory Features in Arabic and English Speech
Authors: Algabri Mohammed , Mathkour Hassan , Alsulaiman Mansour M. , Bencherif Mohamed A.
Published: February 2021

This study proposes using object detection techniques to recognize sequences of articulatory features (AFs) from speech utterances by treating AFs of phonemes as multi-label objects in speech spectrogram. The proposed system, called AFD-Obj, recognizes sequence of multi-label AFs in speech signal and localizes them. AFD-Obj consists of two main stages: firstly, we formulate the problem of AFs detection as an object detection problem and prepare the data to fulfill requirement of object detectors by generating a spectral three-channel image from the speech signal and creating the corresponding annotation for each utterance. Secondly, we use annotated images to train the proposed system to detect sequences of AFs and their boundaries. We test the system by feeding spectrogram images to the system, which will recognize and localize multi-label AFs. We investigated using these AFs to detect the utterance phonemes. YOLOv3-tiny detector is selected because of its real-time property and its support for multi-label detection. We test our AFD-Obj system on Arabic and English languages using KAPD and TIMIT corpora, respectively. Additionally, we propose using YOLOv3-tiny as an Arabic phoneme detection system (i.e., PD-Obj) to recognize and localize a sequence of Arabic phonemes from whole speech utterances. The proposed AFD-Obj and PD-Obj systems achieve excellent results for Arabic corpus and comparable to the state-of-the-art method for English corpus. Moreover, we showed that using only one-scale detection is suitable for AFs detection or phoneme recognition.
Abnormal Gait Detection Using Wearable Hall-Effect Sensors
Authors: Chheng Courtney , Wilson Denise
Published: February 2021

Abnormalities and irregularities in walking (gait) are predictors and indicators of both disease and injury. Gait has traditionally been monitored and analyzed in clinical settings using complex video (camera-based) systems, pressure mats, or a combination thereof. Wearable gait sensors offer the opportunity to collect data in natural settings and to complement data collected in clinical settings, thereby offering the potential to improve quality of care and diagnosis for those whose gait varies from healthy patterns of movement. This paper presents a gait monitoring system designed to be worn on the inner knee or upper thigh. It consists of low-power Hall-effect sensors positioned on one leg and a compact magnet positioned on the opposite leg. Wireless data collected from the sensor system were used to analyze stride width, stride width variability, cadence, and cadence variability for four different individuals engaged in normal gait, two types of abnormal gait, and two types of irregular gait. Using leg gap variability as a proxy for stride width variability, 81% of abnormal or irregular strides were accurately identified as different from normal stride. Cadence was surprisingly 100% accurate in identifying strides which strayed from normal, but variability in cadence provided no useful information. This highly sensitive, non-contact Hall-effect sensing method for gait monitoring offers the possibility for detecting visually imperceptible gait variability in natural settings. These nuanced changes in gait are valuable for predicting early stages of disease and also for indicating progress in recovering from injury.
A Survey of Rain Attenuation Prediction Models for Terrestrial Links—Current Research Challenges and State-of-the-Art
Authors: Samad Md Abdus , Diba Feyisa Debo , Choi Dong-You
Published: February 2021

Millimeter-wave (30–300 GHz) frequency is a promising candidate for 5G and beyond wireless networks, but atmospheric elements limit radio links at this frequency band. Rainfall is the significant atmospheric element that causes attenuation in the propagated wave, which needs to estimate for the proper operation of fade mitigation technique (FMT). Many models have been proposed in the literature to estimate rain attenuation. Various models have a distinct set of input parameters along with separate estimation mechanisms. This survey has garnered multiple techniques that can generate input dataset for the rain attenuation models. This study extensively investigates the existing terrestrial rain attenuation models. There is no survey of terrestrial rain mitigation models to the best of our knowledge. In this article, the requirements of this survey are first discussed, with various dataset developing techniques. The terrestrial links models are classified, and subsequently, qualitative and quantitative analyses among these terrestrial rain attenuation models are tabulated. Also, a set of error performance evaluation techniques is introduced. Moreover, there is a discussion of open research problems and challenges, especially the exigency for developing a rain attenuation model for the short-ranged link in the E-band for 5G and beyond networks.
Functional Self-Awareness and Metacontrol for Underwater Robot Autonomy
Authors: Aguado Esther , Milosevic Zorana , Hernández Carlos , Sanz Ricardo , Garzon Mario , Bozhinoski Darko , Rossi Claudio
Published: February 2021

Autonomous systems are expected to maintain a dependable operation without human intervention. They are intended to fulfill the mission for which they were deployed, properly handling the disturbances that may affect them. Underwater robots, such as the UX-1 mine explorer developed in the UNEXMIN project, are paradigmatic examples of this need. Underwater robots are affected by both external and internal disturbances that hamper their capability for autonomous operation. Long-term autonomy requires not only the capability of perceiving and properly acting in open environments but also a sufficient degree of robustness and resilience so as to maintain and recover the operational functionality of the system when disturbed by unexpected events. In this article, we analyze the operational conditions for autonomous underwater robots with a special emphasis on the UX-1 miner explorer. We then describe a knowledge-based self-awareness and metacontrol subsystem that enables the autonomous reconfiguration of the robot subsystems to keep mission-oriented capability. This resilience augmenting solution is based on the deep modeling of the functional architecture of the autonomous robot in combination with ontological reasoning to allow self-diagnosis and reconfiguration during operation. This mechanism can transparently use robot functional redundancy to ensure mission satisfaction, even in the presence of faults.
Pulsed Optically Pumped Magnetometers: Addressing Dead Time and Bandwidth for the Unshielded Magnetorelaxometry of Magnetic Nanoparticles
Authors: Jaufenthaler Aaron , Kornack Thomas , Lebedev Victor , Limes Mark E. , Körber Rainer , Liebl Maik , Baumgarten Daniel
Published: February 2021

Magnetic nanoparticles (MNP) offer a large variety of promising applications in medicine thanks to their exciting physical properties, e.g., magnetic hyperthermia and magnetic drug targeting. For these applications, it is crucial to quantify the amount of MNP in their specific binding state. This information can be obtained by means of magnetorelaxometry (MRX), where the relaxation of previously aligned magnetic moments of MNP is measured. Current MRX with optically pumped magnetometers (OPM) is limited by OPM recovery time after the shut-off of the external magnetic field for MNP alignment, therewith preventing the detection of fast relaxing MNP. We present a setup for OPM-MRX measurements using a commercially available pulsed free-precession OPM, where the use of a high power pulsed pump laser in the sensor enables a system recovery time in the microsecond range. Besides, magnetometer raw data processing techniques for Larmor frequency analysis are proposed and compared in this paper. Due to the high bandwidth (≥100 kHz) and high dynamic range of our OPM, a software gradiometer in a compact enclosure allows for unshielded MRX measurements in a laboratory environment. When operated in the MRX mode with non-optimal pumping performance, the OPM shows an unshielded gradiometric noise floor of about 600 fT/cm/Hz for a 2.3 cm baseline. The noise floor is flat up to 1 kHz and increases then linearly with the frequency. We demonstrate that quantitative unshielded MRX measurements of fast relaxing, water suspended MNP is possible with the novel OPM-MRX concept, confirmed by the accurately derived iron amount ratios of MNP samples. The detection limit of the current setup is about 1.37 μg of iron for a liquid BNF-MNP-sample (Bionized NanoFerrite) with a volume of 100 μL.
3D Object Detection and Instance Segmentation from 3D Range and 2D Color Images
Authors: Shen Xiaoke , Stamos Ioannis
Published: February 2021

Instance segmentation and object detection are significant problems in the fields of computer vision and robotics. We address those problems by proposing a novel object segmentation and detection system. First, we detect 2D objects based on RGB, depth only, or RGB-D images. A 3D convolutional-based system, named Frustum VoxNet, is proposed. This system generates frustums from 2D detection results, proposes 3D candidate voxelized images for each frustum, and uses a 3D convolutional neural network (CNN) based on these candidates voxelized images to perform the 3D instance segmentation and object detection. Results on the SUN RGB-D dataset show that our RGB-D-based system’s 3D inference is much faster than state-of-the-art methods, without a significant loss of accuracy. At the same time, we can provide segmentation and detection results using depth only images, with accuracy comparable to RGB-D-based systems. This is important since our methods can also work well in low lighting conditions, or with sensors that do not acquire RGB images. Finally, the use of segmentation as part of our pipeline increases detection accuracy, while providing at the same time 3D instance segmentation.
Calculation of Stopping-Power Ratio from Multiple CT Numbers Using Photon-Counting CT System: Two- and Three-Parameter-Fitting Method
Authors: Lee Sung Hyun , Sunaguchi Naoki , Nagao Akie , Hirano Yoshiyuki , Sakurai Hiroshi , Kano Yosuke , Torikoshi Masami , Kanai Tatsuaki , Tashiro Mutsumi
Published: February 2021

The two-parameter-fitting method (PFM) is commonly used to calculate the stopping-power ratio (SPR). This study proposes a new formalism: a three-PFM, which can be used in multiple spectral computed tomography (CT). Using a photon-counting CT system, seven rod-shaped samples of aluminium, graphite, and poly(methyl methacrylate) (PMMA), and four types of biological phantom materials were placed in a water-filled sample holder. The X-ray tube voltage and current were set at 150 kV and 40 μμA respectively, and four CT images were obtained at four threshold settings. A semi-empirical correction method that corrects the difference between the CT values from the photon-counting CT images and theoretical values in each spectral region was also introduced. Both the two- and three-PFMs were used to calculate the effective atomic number and electron density from multiple CT numbers. The mean excitation energy was calculated via parameterisation with the effective atomic number, and the SPR was then calculated from the calculated electron density and mean excitation energy. Then, the SPRs from both methods were compared with the theoretical values. To estimate the noise level of the CT numbers obtained from the photon-counting CT, CT numbers, including noise, were simulated to evaluate the robustness of the aforementioned PFMs. For the aluminium and graphite, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 17.1% and 7.1%, respectively. For the PMMA and biological phantom materials, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 5.5% and 2.0%, respectively. It was concluded that the three-PFM, compared with the two-PFM, can yield SPRs that are closer to the theoretical values and is less affected by noise.
Variation of Low-Frequency Time-Code Signal Field Strength during the Annular Solar Eclipse on 21 June 2020: Observation and Analysis
Authors: Wang Xin , Li Bo , Zhao Fan , Luo Xinyu , Huang Luxi , Feng Ping , Li Xiaohui
Published: February 2021

Due to the occlusion of the moon, an annular solar eclipse will have an effect on the ionosphere above the earth. The change of the ionosphere, for the low-frequency time-code signal that relies on it as a reflection medium for long-distance propagation, the signal field strength, and other parameters will also produce corresponding changes, which will affect the normal operation of the low-frequency time-code time service system. This paper selects the solar eclipse that occurred in China on 21 June 2020, and uses the existing measurement equipment to carry out experimental research on the low-frequency time-code signal. We measured and analyzed the signal field strength from 20 June 2020 to 23 June 2020, and combined solar activity data, ionospheric data, and geomagnetic data, and attempted to explore the reasons and rules of the change of signal parameters. The results showed that the field strength of the low-frequency time-code signal changed dramatically within a short time period, the max growth value can reach up to 17 dBμV/m and the variation trend yielded ‘three mutations’. This change in signal field strength is probably due to the occurrence of a solar eclipse that has an effect on the ionosphere. When the signal propagation conditions change, the signal strength will also change accordingly.
A Modified Sparrow Search Algorithm with Application in 3d Route Planning for UAV
Authors: Liu Guiyun , Shu Cong , Liang Zhongwei , Peng Baihao , Cheng Lefeng
Published: February 2021

The unmanned aerial vehicle (UAV) route planning problem mainly centralizes on the process of calculating the best route between the departure point and target point as well as avoiding obstructions on route to avoid collisions within a given flight area. A highly efficient route planning approach is required for this complex high dimensional optimization problem. However, many algorithms are infeasible or have low efficiency, particularly in the complex three-dimensional (3d) flight environment. In this paper, a modified sparrow search algorithm named CASSA has been presented to deal with this problem. Firstly, the 3d task space model and the UAV route planning cost functions are established, and the problem of route planning is transformed into a multi-dimensional function optimization problem. Secondly, the chaotic strategy is introduced to enhance the diversity of the population of the algorithm, and an adaptive inertia weight is used to balance the convergence rate and exploration capabilities of the algorithm. Finally, the Cauchy–Gaussian mutation strategy is adopted to enhance the capability of the algorithm to get rid of stagnation. The results of simulation demonstrate that the routes generated by CASSA are preferable to the sparrow search algorithm (SSA), particle swarm optimization (PSO), artificial bee colony (ABC), and whale optimization algorithm (WOA) under the identical environment, which means that CASSA is more efficient for solving UAV route planning problem when taking all kinds of constraints into consideration.
Deskilled and Rapid Drug-Resistant Gene Detection by Centrifugal Force-Assisted Thermal Convection PCR Device
Authors: Espulgar Wilfred Villariza , Saito Masato , Takahashi Kazuya , Ushiro Sakiko , Yamamoto Norihisa , Akeda Yukihiro , Hamaguchi Shigeto , Tomono Kazunori , Tamiya Eiichi
Published: February 2021

Here we report the improved Cyclo olefin polymer (COP) microfluidic chip and polymerase chain reaction (PCR) amplification system for point-of-care testing (POCT) in rapid detection of Carbapenem-resistant Enterobacteriaceae (CRE). The PCR solution and thermal cycling is controlled by the relative gravitational acceleration (7G) only and is expected to pose minimal problem in operation by non-expert users. Detection is based on identifying the presence of carbapenemase encoding gene through the corresponding fluorescence signal after amplification. For preliminary tests, the device has been demonstrated to detect blaIMP-6 from patients stool samples. From the prepared samples, 96.4 fg/µL was detected with good certainty within 15 min (~106 thermocycles,) which is significantly faster than the conventional culture plate method. Moreover, the device is expected to detect other target genes in parallel as determination of the presence of blaNDM-1 and blaOXA-23 from control samples has also been demonstrated. With the rising threat of drug-resistant bacteria in global healthcare, this technology can greatly aid the health sector by enabling the appropriate use of antibiotics, accelerating the treatment of carriers, and suppressing the spread.
Symmetry Analysis of Oriental Polygonal Pagodas Using 3D Point Clouds for Cultural Heritage
Authors: Chan Ting On , Xia Linyuan , Chen Yimin , Lang Wei , Chen Tingting , Sun Yeran , Wang Jing , Li Qianxia , Du Ruxu
Published: February 2021

Ancient pagodas are usually parts of hot tourist spots in many oriental countries due to their unique historical backgrounds. They are usually polygonal structures comprised by multiple floors, which are separated by eaves. In this paper, we propose a new method to investigate both the rotational and reflectional symmetry of such polygonal pagodas through developing novel geometric models to fit to the 3D point clouds obtained from photogrammetric reconstruction. The geometric model consists of multiple polygonal pyramid/prism models but has a common central axis. The method was verified by four datasets collected by an unmanned aerial vehicle (UAV) and a hand-held digital camera. The results indicate that the models fit accurately to the pagodas’ point clouds. The symmetry was realized by rotating and reflecting the pagodas’ point clouds after a complete leveling of the point cloud was achieved using the estimated central axes. The results show that there are RMSEs of 5.04 cm and 5.20 cm deviated from the perfect (theoretical) rotational and reflectional symmetries, respectively. This concludes that the examined pagodas are highly symmetric, both rotationally and reflectionally. The concept presented in the paper not only work for polygonal pagodas, but it can also be readily transformed and implemented for other applications for other pagoda-like objects such as transmission towers.
Calibration Analysis of High-G MEMS Accelerometer Sensor Based on Wavelet and Wavelet Packet Denoising
Authors: Shi Yunbo , Zhang Juanjuan , Jiao Jingjing , Zhao Rui , Cao Huiliang
Published: February 2021

High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.
Publishing Patterns in Greek Media Websites
Authors: Avraam Evangelia , Veglis Andreas , Dimoulas Charalampos
Published: February 2021

The concept of different publishing patterns during a day has been employed for many decades in the broadcasting industry. These patterns are close related with dayparts, which are defined as sequential time blocks on comparable days during which the audience size is homogeneous, as is the group depiction using the specific medium. During the first decade of the World Wide Web, Internet media strategy was focused on total web reach, demographics and affinity of content without particular attention to how the nature of the audience changes by time of day. This paper studies the variation of publishing patterns of the top 22 Greek media websites. More than 550 thousand articles were indexed in a period of four and a half months. The study identified distinct WWW time periods that exhibit specific publishing characteristics. Specifically, different categories of news articles present different publishing patterns during weekdays and weekends. The results appear to be in agreement with findings of previous studies.
International Nets and National Links: The Global Rise of the Extreme Right—Introduction to Special Issue
Authors: Campion Kristy , Poynting Scott
Published: February 2021

Work on this special issue has spanned two years, bookended by two highly mediatized, violent, extreme right-wing attacks, perpetrated on opposite sides of the globe [...]
COVID-19 Campus Closures in the United States: American Student Perceptions of Forced Transition to Remote Learning
Authors: Parker Susan W. , Hansen Mary A. , Bernadowski Carianne
Published: February 2021

As colleges and universities rapidly closed due to COVID-19, students and faculty were faced with unique challenges. The pandemic forced the cancellation of all campus activities, both extra-curricular and program-focused, such as student teaching experiences and nursing clinical rotations. Additionally, instructors were forced to rethink content delivery as coursework was quickly moved online and administered remotely via virtual platforms. Students were impacted as university level programs underwent a major paradigm shift within a matter of days or weeks. This study examined perspectives of undergraduate and graduate students regarding their experiences with rapid conversion from on-ground, in-person courses to remote instruction during the spring 2020 semester. The researchers employed a QUAN-QUAL descriptive mixed methods design. Using questionnaires and semi-structured interviews, the researchers examined general perspectives on in-person learning before the pandemic; initial perceptions about remote learning; and perceptions of the students about effort, engagement, needs, and ethical behavior as they engaged in totally remote learning. Results, analyzed using SPSS (QUAN) and inter-coder agreement (QUAL), indicated that initially students were engaged and satisfied with their in-person instruction, but became less satisfied and engaged during remote instruction. Undergraduate students experienced feelings of increased frustration, decreased accountability and engagement during remote learning, and turned to collaboration to earn points as they finished the semester.
Intersections of Immigration and Sexual/Reproductive Health: An Umbrella Literature Review with a Focus on Health Equity
Authors: Alarcão Violeta , Stefanovska-Petkovska Miodraga , Virgolino Ana , Santos Osvaldo , Costa Andreia
Published: February 2021

Identifying the opportunities and barriers of promoting and fulfilling the sexual health rights of migrants remains a challenge that requires systematic assessment. Such an assessment would include estimating the influence of acculturation processes on sexual and reproductive health, and mapping intersectional inequities that influence migrants’ sexual and reproductive health in comparison with the native population. The aim of this research was to locate, select, and critically assess/summarize scientific evidence regarding the social, cultural, and structural factors influencing migrants’ sexual and reproductive health outcomes in comparison with native population. An umbrella review of systematic reviews and/or meta-analyses, following preferred reporting items for systematic reviews and meta-analysis (PRISMA) standards was undertaken. Medline, Scopus, Web of Science, and the Cochrane Database of Systematic Reviews were searched from their start date until June 2019. The quality of the included articles was determined using the assessment of multiple systematic reviews tool (AMSTAR 2). From the 36 selected studies, only 12 compared migrant with native populations. Overall, the findings indicated that migrants tend to underuse maternal health services and have an increased risk of poor sexual and reproductive health outcomes. Specific intersectional inequities were identified and discussed.