bluuebunny/crossref_metadata_2025 huggingface dataset:
Immunoproteomic Analysis of Dirofilaria repens Microfilariae and Adult Parasite Stages
Authors: Zawistowska-Deniziak Anna , Powązka Katarzyna , Pękacz Mateusz , Basałaj Katarzyna , Klockiewicz Maciej , Wiśniewski Marcin , Młocicki Daniel
Published: February 2021

Dirofilariarepens is a parasitic nematode causing a vector-borne zoonotic infection (dirofilariosis), considered an emerging problem in human and veterinary medicine. Currently, diagnosis is based on the detection of the adult parasite and microfilariae in the host tissues. However, the efficacy of tests relying on microfilariae detection is limited by microfilariae periodic occurrence. Therefore, a new reliable and affordable serological diagnostic method is needed. Better characteristic of the parasite biology and its interaction with host immune system should help to achieve this goal. This study analyzes adult and microfilariae proteomes, and the use of one-dimensional electrophoresis (1-DE) and two-dimensional electrophoresis (2-DE) proteomics, immunoproteomics, and LC-MS/MS mass spectrometry allowed us to identify 316 potentially immunogenic proteins (75 belong to adult stage, 183 to microfilariae, and 58 are common for both). Classified by their ontology, the proteins showed important similarities and differences between both parasite stages. The most frequently identified proteins are structural, metabolic, and heat shock proteins. Additionally, real-time PCR analysis of some immunogenic targets revealed significant differences between microfilariae and adult life stages. We indicated molecules involved in parasite-host interactions and discussed their importance in parasite biology, which may help to reveal potential diagnostic antigens or select drug and vaccine targets.
Mercury Toxicity and Detection Using Chromo-Fluorogenic Chemosensors
Authors: Bhardwaj Vinita , Nurchi Valeria M. , Sahoo Suban K.
Published: February 2021

Mercury (Hg), this non-essential heavy metal released from both industrial and natural sources entered into living bodies, and cause grievous detrimental effects to the human health and ecosystem. The monitoring of Hg2+ excessive accumulation can be beneficial to fight against the risk associated with mercury toxicity to living systems. Therefore, there is an emergent need of novel and facile analytical approaches for the monitoring of mercury levels in various environmental, industrial, and biological samples. The chromo-fluorogenic chemosensors possess the attractive analytical parameters of low-cost, enhanced detection ability with high sensitivity, simplicity, rapid on-site monitoring ability, etc. This review was narrated to summarize the mercuric ion selective chromo-fluorogenic chemosensors reported in the year 2020. The design of sensors, mechanisms, fluorophores used, analytical performance, etc. are summarized and discussed.
Silicon Cycling in Soils Revisited
Authors: Schaller Jörg , Puppe Daniel , Kaczorek Danuta , Ellerbrock Ruth , Sommer Michael
Published: February 2021

Silicon (Si) speciation and availability in soils is highly important for ecosystem functioning, because Si is a beneficial element for plant growth. Si chemistry is highly complex compared to other elements in soils, because Si reaction rates are relatively slow and dependent on Si species. Consequently, we review the occurrence of different Si species in soil solution and their changes by polymerization, depolymerization, and condensation in relation to important soil processes. We show that an argumentation based on thermodynamic endmembers of Si dependent processes, as currently done, is often difficult, because some reactions such as mineral crystallization require months to years (sometimes even centuries or millennia). Furthermore, we give an overview of Si reactions in soil solution and the predominance of certain solid compounds, which is a neglected but important parameter controlling the availability, reactivity, and function of Si in soils. We further discuss the drivers of soil Si cycling and how humans interfere with these processes. The soil Si cycle is of major importance for ecosystem functioning; therefore, a deeper understanding of drivers of Si cycling (e.g., predominant speciation), human disturbances and the implication for important soil properties (water storage, nutrient availability, and micro aggregate stability) is of fundamental relevance.
Parametric Studies of a Mercury-Free DBD Lamp
Authors: Caillier Bruno , Therese Laurent , Belenguer Philippe , Guillot Philippe
Published: February 2021

Mercury discharge lamps are often used because of their high efficiency; however, the usage of mercury lamps will be restricted or forbidden for safety and environmental purposes. Finding alternative solutions to suppress mercury is of major interest. The aim of this work is to increase the luminous efficacy of a commercial-free mercury flat dielectric barrier discharge lamp (Planilum, St Gobain) in order to reach the necessary conditions for the lamp to be used as a daily lighting source. The lamp is made of two glass plates separated by a gap of 2 mm. The gap is filled by a neon xenon mixture. The external electrodes made of transparent ITO (indium tin oxide) are deposited on the lamp glass plates. The electrical signal applied to the electrodes generates a UV-emitting plasma inside the gap. Phosphors deposited on the glass allow the production of visible light. The original electrode geometry is plane-to-plane; this induces filamentary discharges. We show that changing the plane-to-plane geometry to a coplanar geometry allows the plasma to spread all over the electrode surface, and we can reach twice the efficacy of the lamp (32 lm/W) as compared to the original value. Using this new electrode geometrical configuration and changing the electrical signal from sinusoidal to a pulsed signal greatly improves the visual uniformity of the emitted light all over the lamp. Electrical and optical parametric measurements were performed to study the lamp characteristics. We show that it is possible to develop a free mercury lamp with an efficacy compatible with lighting purposes.
Thermal Delamination Modelling and Evaluation of Aluminium–Glass Fibre-Reinforced Polymer Hybrid
Authors: Chow Zhen Pei , Ahmad Zaini , Wong King Jye , Koloor Seyed Saeid Rahimian , Petrů Michal
Published: February 2021

This paper aims to propose a temperature-dependent cohesive model to predict the delamination of dissimilar metal–composite material hybrid under Mode-I and Mode-II delamination. Commercial nonlinear finite element (FE) code LS-DYNA was used to simulate the material and cohesive model of hybrid aluminium–glass fibre-reinforced polymer (GFRP) laminate. For an accurate representation of the Mode-I and Mode-II delamination between aluminium and GFRP laminates, cohesive zone modelling with bilinear traction separation law was implemented. Cohesive zone properties at different temperatures were obtained by applying trends of experimental results from double cantilever beam and end notched flexural tests. Results from experimental tests were compared with simulation results at 30, 70 and 110 °C to verify the validity of the model. Mode-I and Mode-II FE models compared to experimental tests show a good correlation of 5.73% and 7.26% discrepancy, respectively. Crack front stress distribution at 30 °C is characterised by a smooth gradual decrease in Mode-I stress from the centre to the edge of the specimen. At 70 °C, the entire crack front reaches the maximum Mode-I stress with the exception of much lower stress build-up at the specimen’s edge. On the other hand, the Mode-II stress increases progressively from the centre to the edge at 30 °C. At 70 °C, uniform low stress is built up along the crack front with the exception of significantly higher stress concentrated only at the free edge. At 110 °C, the stress distribution for both modes transforms back to the similar profile, as observed in the 30 °C case.
Special Issue “Materials Processing for Production of Nanostructured Thin Films”
Authors: Stine Keith J.
Published: February 2021

The field of thin film technology [...]
Graphene Nanoplatelets Suspended in Different Basefluids Based Solar Collector: An Experimental and Analytical Study
Authors: Alawi Omer , Kamar Haslinda , Mallah Abdul , Mohammed Hussein , Sabrudin Mohd , Hussein Omar , Kazi Salim , Najafi Gholamhassan
Published: February 2021

A flat plate solar collector (FPSC) was analytically studied, with functionalized graphene nanoplatelets (f-GNPs) as its working fluid. Four samples (wt % nanofluids) were prepared in different base fluids such as ethylene glycol (EG), distilled water (DW):EG (70:30), and DW:EG (50:50). Experimental results (via DW) were used to verify the effectiveness of the analytical model. Some of the operating conditions were taken into account in this research, including temperatures, power, and mass flow rates. Experimental techniques were used to elucidate the modified nanofluids’ physicochemical properties, such as its particle sizes, stability, and morphology, involving electron microscopes (EMs), UV–VIS, and X-ray techniques. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were applied to test the thermal analysis. The findings confirmed that the use of f-GNPs nanofluids enhanced the performance of the FPSC relative to the use of base fluids for all testing conditions. The maximum enhancement of the collector’s effectiveness at a mass flow rate of 1.5 kg min−1 and a weight concentration of 0.1 wt %, increased to 12.69%, 12.60%, and 12.62% in the case of EG, DW:EG (70:30), and DW:EG (50:50), respectively. The results also confirmed an improvement in both the heat gain (FR(τα)) and heat loss (FRUL) coefficients for the f-GNPs nanofluid.
Development of an Ultrasound Technology-Based Indoor-Location Monitoring Service System for Worker Safety in Shipbuilding and Offshore Industry
Authors: Park Jonghee , Kim Hanjune , Yoon Jaejun , Kim Hyoungmin , Park Chulgyun , Hong Daegeun
Published: February 2021

We have built a worker-safety monitoring system (WSMS) for use in the shipbuilding and offshore industry (S&OI). The WSMS combines metal-conductor communication wireless networks with location-estimation technology that uses ultrasound signals in the frequency band 18 to 22 kHz, which is above the normal range of hearing (<15 kHz) in human adults. This system can be used in environments that include many metal barriers. The developmental process included deriving stakeholder requirements, transforming system requirements, designing system architecture, and developing a prototype. The prototype WSMS was tested by applying it to H Company, a Korean S&OI. Use of the WSMS increased the productivity of workers and managers by reducing the cost of on-site patrols and handwritten input. As a result, the number of worker location information updates increased from 2/day to 20/min, and productivity increased by 30 min/day compared to the previous method. Therefore, shipyards that introduce worker-safety management systems may consider applying this method.
Smart Beta Allocation and Macroeconomic Variables: The Impact of COVID-19
Authors: Foglia Matteo , Recchioni Maria Cristina , Polinesi Gloria
Published: February 2021

Smart beta strategies across economic regimes seek to address inefficiencies created by market-based indices, thereby enhancing portfolio returns above traditional benchmarks. Our goal is to develop a strategy for re-hedging smart beta portfolios that shows the connection between multi-factor strategies and macroeconomic variables. This is done, first, by analyzing finite correlations between the portfolio weights and macroeconomic variables and, more remarkably, by defining an investment tilting variable. The latter is analyzed with a discriminant analysis approach with a twofold application. The first is the selection of the crucial re-hedging thresholds which generate a strong connection between factors and macroeconomic variables. The second is forecasting portfolio dynamics (gain and loss). The capability of forecasting is even more evident in the COVID-19 period. Analysis is carried out on the iShares US exchange traded fund (ETF) market using monthly data in the period December 2013–May 2020, thereby highlighting the impact of COVID-19.
Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data
Authors: Ahmed A. A. Masrur , Deo Ravinesh C , Raj Nawin , Ghahramani Afshin , Feng Qi , Yin Zhenliang , Yang Linshan
Published: February 2021

Remotely sensed soil moisture forecasting through satellite-based sensors to estimate the future state of the underlying soils plays a critical role in planning and managing water resources and sustainable agricultural practices. In this paper, Deep Learning (DL) hybrid models (i.e., CEEMDAN-CNN-GRU) are designed for daily time-step surface soil moisture (SSM) forecasts, employing the gated recurrent unit (GRU), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and convolutional neural network (CNN). To establish the objective model’s viability for SSM forecasting at multi-step daily horizons, the hybrid CEEMDAN-CNN-GRU model is tested at 1st, 5th, 7th, 14th, 21st, and 30th day ahead period by assimilating a comprehensive pool of 52 predictor dataset obtained from three distinct data sources. Data comprise satellite-derived Global Land Data Assimilation System (GLDAS) repository a global, high-temporal resolution, unique terrestrial modelling system, and ground-based variables from Scientific Information Landowners (SILO) and synoptic-scale climate indices. The results demonstrate the forecasting capability of the hybrid CEEMDAN-CNN-GRU model with respect to the counterpart comparative models. This is supported by a relatively lower value of the mean absolute percentage and root mean square error. In terms of the statistical score metrics and infographics employed to test the final model’s utility, the proposed CEEMDAN-CNN-GRU models are considerably superior compared to a standalone and other hybrid method tested on independent SSM data developed through feature selection approaches. Thus, the proposed approach can be successfully implemented in hydrology and agriculture management.
Experimental Study on the Inverse Estimation of Horizontal Air Temperature Distribution in Built Spaces Using a Ground-Based Thermal Infrared Spectroradiometer
Authors: Tsurumi Ryuta , Asawa Takashi , Oshio Haruki
Published: February 2021

Air temperature is an important physical indicator for urban and architectural environments; however, it is difficult to obtain its distributive characteristics by field measurements owing to the limitations of current measuring instruments. In this context, this study was conducted to demonstrate whether a small and portable ground-based thermal infrared spectroradiometer can be used to estimate the horizontal air temperature distribution in built spaces. For this estimation, we first calculated a forward model using radiative transfer simulations, and the air temperature distribution was inversely estimated from the observed radiance using the model. To regularize the estimated air temperature, we used the maximum a posteriori method, which uses prior information. To verify this estimation method, we conducted measurement experiments in two types of built spaces that had different air temperature distributions within spaces that were approximately 20 m long. Moreover, we conducted a parametric case study on the prior information. As a result, we were able to estimate the air temperature distribution with an average root mean square error (RMSE) of 1.3 °C for all cases when the average RMSE of the prior information for all cases was 2.1 °C. This improvement in the RMSE indicates that this method is able to remotely estimate the horizontal air temperature distribution in built spaces.
Devising Digital Twins DNA Paradigm for Modeling ISO-Based City Services
Authors: Badawi Hawazin Faiz , Laamarti Fedwa , El Saddik Abdulmotaleb
Published: February 2021

Digital twins (DTs) technology has recently gained attention within the research community due to its potential to help build sustainable smart cities. However, there is a gap in the literature: currently no unified model for city services has been proposed that can guarantee interoperability across cities, capture each city’s unique characteristics, and act as a base for modeling digital twins. This research aims to fill that gap. In this work, we propose the DT-DNA model in which we design a city services digital twin, with the goal of reflecting the real state of development of a city’s services towards enhancing its citizens’ quality of life (QoL). As it was designed using ISO 37120, one of the leading international standards for city services, the model guarantees interoperability and allows for easy comparison of services within and across cities. In order to test our model, we built DT-DNA sequences of services in both Quebec City and Boston and then used a DNA alignment tool to determine the matching percentage between them. Results show that the DT-DNA sequences of services in both cities are 46.5% identical. Ground truth comparisons show a similar result, which provides a preliminary proof-of-concept for the applicability of the proposed model and framework. These results also imply that one city performs better than the other. Therefore, we propose an algorithm to compare cities based on the proposed DT-DNA and, using Boston and Quebec City as a case study, demonstrate that Boston has better services towards enhancing QoL for its citizens.
A Color Restoration Algorithm for Diffractive Optical Images of Membrane Camera
Authors: Du Yanlei , Yang Xiaofeng , Ma Yiping , Xu Chunxue
Published: February 2021

In order to verify the technology of the membrane diffractive imaging system for Chinese next generation geo-stationary earth orbit (GEO) satellite, a series of ground experiments have been carried out using a membrane optical camera with 80 mm aperture (Φ80) lens. The inherent chromatic aberration due to diffractive imaging appears in the obtained data. To address the issue, an effective color restoration algorithm framework by matching, tailoring, and non-linearly stretching the image histograms is proposed in this letter. Experimental results show the proposed approach has good performances in color restoration of the diffractive optical images than previous methods. The effectiveness and robustness of the algorithm are also quantitatively assessed using various color deviation indexes. The results indicate that the chromatic aberration of diffractive images can be effectively removed by about 85%. Also, the proposed method presents reasonable computational efficiency.
An Inertial Measurement Unit-Based Wireless System for Shoulder Motion Assessment in Patients with Cervical Spinal Cord Injury: A Validation Pilot Study in a Clinical Setting
Authors: Bravi Riccardo , Caputo Stefano , Jayousi Sara , Martinelli Alessio , Biotti Lorenzo , Nannini Ilaria , Cohen Erez James , Quarta Eros , Grasso Stefano , Lucchesi Giacomo , Righi Gabriele , Del Popolo Giulio , Mucchi Lorenzo , Minciacchi Diego
Published: February 2021

Residual motion of upper limbs in individuals who experienced cervical spinal cord injury (CSCI) is vital to achieve functional independence. Several interventions were developed to restore shoulder range of motion (ROM) in CSCI patients. However, shoulder ROM assessment in clinical practice is commonly limited to use of a simple goniometer. Conventional goniometric measurements are operator-dependent and require significant time and effort. Therefore, innovative technology for supporting medical personnel in objectively and reliably measuring the efficacy of treatments for shoulder ROM in CSCI patients would be extremely desirable. This study evaluated the validity of a customized wireless wearable sensors (Inertial Measurement Units—IMUs) system for shoulder ROM assessment in CSCI patients in clinical setting. Eight CSCI patients and eight healthy controls performed four shoulder movements (forward flexion, abduction, and internal and external rotation) with dominant arm. Every movement was evaluated with a goniometer by different testers and with the IMU system at the same time. Validity was evaluated by comparing IMUs and goniometer measurements using Intraclass Correlation Coefficient (ICC) and Limits of Agreement (LOA). inter-tester reliability of IMUs and goniometer measurements was also investigated. Preliminary results provide essential information on the accuracy of the proposed wireless wearable sensors system in acquiring objective measurements of the shoulder movements in CSCI patients.
GENDIS: Genetic Discovery of Shapelets
Authors: Vandewiele Gilles , Ongenae Femke , De Turck Filip
Published: February 2021

In the time series classification domain, shapelets are subsequences that are discriminative of a certain class. It has been shown that classifiers are able to achieve state-of-the-art results by taking the distances from the input time series to different discriminative shapelets as the input. Additionally, these shapelets can be visualized and thus possess an interpretable characteristic, making them appealing in critical domains, where longitudinal data are ubiquitous. In this study, a new paradigm for shapelet discovery is proposed, which is based on evolutionary computation. The advantages of the proposed approach are that: (i) it is gradient-free, which could allow escaping from local optima more easily and supports non-differentiable objectives; (ii) no brute-force search is required, making the algorithm scalable; (iii) the total amount of shapelets and the length of each of these shapelets are evolved jointly with the shapelets themselves, alleviating the need to specify this beforehand; (iv) entire sets are evaluated at once as opposed to single shapelets, which results in smaller final sets with fewer similar shapelets that result in similar predictive performances; and (v) the discovered shapelets do not need to be a subsequence of the input time series. We present the results of the experiments, which validate the enumerated advantages.
Ambient LED Light Noise Reduction Using Adaptive Differential Equalization in Li-Fi Wireless Link
Authors: Won Yong-Yuk , Yoon Sang Min , Seo Dongsun
Published: February 2021

For Li-Fi wireless links based on a white light emitting diode, an adaptive differential equalization (ADE) technique that reduces various noises such as interference noise and shot one generated from ambient light sources is pro-posed. The ADE technique reduces noise by taking advantage of the fact that the derivative between adjacent sampling points of signal with digital waveform is very different from that of noise with the random analog waveform. Furthermore, a weighting function that reflects the Poisson characteristics of shot noise is applied to the ADE technique in order to maximize the reduction efficiency of ambient noise. The signal-to-noise ratio of input non-return-to-zero-on–off keying (NRZ-OOK) signal is improved by 7.5 dB at the first-generation forward error correction (FEC) threshold (the bit error rate (BER) of 8 × 10−5) using the optical wireless experimental link. In addition, it is confirmed that it is possible to maintain the transmission performance corresponding to the BER of 1 × 10−5 by using the proposed ADE technique, even when the intensity of the ambient light source increases by 6 dB.
Effect of Oxygen Mole Fraction on Static Properties of Pressure-Sensitive Paint
Authors: Okudera Tomohiro , Nagata Takayuki , Kasai Miku , Saito Yuji , Nonomura Taku , Asai Keisuke
Published: February 2021

The effects of the oxygen mole fraction on the static properties of pressure-sensitive paint (PSP) were investigated. Sample coupon tests using a calibration chamber were conducted for poly(hexafluoroisopropyl methacrylate)-based PSP (PHFIPM-PSP), polymer/ceramic PSP (PC-PSP), and anodized aluminum PSP (AA-PSP). The oxygen mole fraction was set to 0.1–100%, and the ambient pressure (Pref) was set to 0.5–140 kPa. Localized Stern–Volmer coefficient Blocal increased and then decreased with increasing oxygen mole fraction. Although Blocal depends on both ambient pressure and the oxygen mole fraction, its effect can be characterized as a function of the partial pressure of oxygen. For AA-PSP and PHFIPM-PSP, which are low-pressure- and relatively low-pressure-type PSPs, respectively, Blocal peaks at PO2ref<12 kPa. In contrast, for PC-PSP, which is an atmospheric-pressure-type PSP in the investigated range, Blocal does not have a peak. Blocal has a peak at a relatively high partial pressure of oxygen due to the oxygen permeability of the polymer used in the binder. The peak of SPR, which is the emission intensity change with respect to normalized pressure fluctuation, appears at a lower partial pressure of oxygen than that of Blocal. This is because the intensity of PSP becomes quite low at a high partial pressure of oxygen even if Blocal is high. Hence, the optimal oxygen mole fraction depends on the type of PSP and the ambient pressure range of the experiment. This optimal value can be found on the basis of the partial pressure of oxygen.
Using a Low-Power Spiking Continuous Time Neuron (SCTN) for Sound Signal Processing
Authors: Bensimon Moshe , Greenberg Shlomo , Haiut Moshe
Published: February 2021

This work presents a new approach based on a spiking neural network for sound preprocessing and classification. The proposed approach is biologically inspired by the biological neuron’s characteristic using spiking neurons, and Spike-Timing-Dependent Plasticity (STDP)-based learning rule. We propose a biologically plausible sound classification framework that uses a Spiking Neural Network (SNN) for detecting the embedded frequencies contained within an acoustic signal. This work also demonstrates an efficient hardware implementation of the SNN network based on the low-power Spike Continuous Time Neuron (SCTN). The proposed sound classification framework suggests direct Pulse Density Modulation (PDM) interfacing of the acoustic sensor with the SCTN-based network avoiding the usage of costly digital-to-analog conversions. This paper presents a new connectivity approach applied to Spiking Neuron (SN)-based neural networks. We suggest considering the SCTN neuron as a basic building block in the design of programmable analog electronics circuits. Usually, a neuron is used as a repeated modular element in any neural network structure, and the connectivity between the neurons located at different layers is well defined. Thus, generating a modular Neural Network structure composed of several layers with full or partial connectivity. The proposed approach suggests controlling the behavior of the spiking neurons, and applying smart connectivity to enable the design of simple analog circuits based on SNN. Unlike existing NN-based solutions for which the preprocessing phase is carried out using analog circuits and analog-to-digital conversion, we suggest integrating the preprocessing phase into the network. This approach allows referring to the basic SCTN as an analog module enabling the design of simple analog circuits based on SNN with unique inter-connections between the neurons. The efficiency of the proposed approach is demonstrated by implementing SCTN-based resonators for sound feature extraction and classification. The proposed SCTN-based sound classification approach demonstrates a classification accuracy of 98.73% using the Real-World Computing Partnership (RWCP) database.
Lightweight Feature Enhancement Network for Single-Shot Object Detection
Authors: Jia Peng , Liu Fuxiang
Published: February 2021

At present, the one-stage detector based on the lightweight model can achieve real-time speed, but the detection performance is challenging. To enhance the discriminability and robustness of the model extraction features and improve the detector’s detection performance for small objects, we propose two modules in this work. First, we propose a receptive field enhancement method, referred to as adaptive receptive field fusion (ARFF). It enhances the model’s feature representation ability by adaptively learning the fusion weights of different receptive field branches in the receptive field module. Then, we propose an enhanced up-sampling (EU) module to reduce the information loss caused by up-sampling on the feature map. Finally, we assemble ARFF and EU modules on top of YOLO v3 to build a real-time, high-precision and lightweight object detection system referred to as the ARFF-EU network. We achieve a state-of-the-art speed and accuracy trade-off on both the Pascal VOC and MS COCO data sets, reporting 83.6% AP at 37.5 FPS and 42.5% AP at 33.7 FPS, respectively. The experimental results show that our proposed ARFF and EU modules improve the detection performance of the ARFF-EU network and achieve the development of advanced, very deep detectors while maintaining real-time speed.
Impact of Experimental Parameters on Cell–Cell Force Spectroscopy Signature
Authors: Oropesa-Nuñez Reinier , Mescola Andrea , Vassalli Massimo , Canale Claudio
Published: February 2021

Atomic force microscopy is an extremely versatile technique, featuring atomic-scale imaging resolution, and also offering the possibility to probe interaction forces down to few pN. Recently, this technique has been specialized to study the interaction between single living cells, one on the substrate, and a second being adhered on the cantilever. Cell–cell force spectroscopy offers a unique tool to investigate in fine detail intra-cellular interactions, and it holds great promise to elucidate elusive phenomena in physiology and pathology. Here we present a systematic study of the effect of the main measurement parameters on cell–cell curves, showing the importance of controlling the experimental conditions. Moreover, a simple theoretical interpretation is proposed, based on the number of contacts formed between the two interacting cells. The results show that single cell–cell force spectroscopy experiments carry a wealth of information that can be exploited to understand the inner dynamics of the interaction of living cells at the molecular level.
Experimental Evaluation of the Packet Reception Performance of LoRa
Authors: Guo Qingjie , Yang Fengxu , Wei Jianming
Published: February 2021

LoRa technology is currently one of the most popular Internet of Things (IoT) technologies. A substantial number of LoRa devices have been applied in a wide variety of real-world scenarios, and developers can adjust the packet reception performance of LoRa through physical layer parameter configuration to meet the requirements. However, since the important details of the relationship between the physical layer parameters and the packet reception performance of LoRa remain unknown, it is a challenge to choose the appropriate parameter configuration to meet the requirements of the scenarios. Moreover, with the increase in application scenarios, the requirements for energy consumption become increasingly high. Therefore, it is also a challenge to know how to configure the parameters to maximize the energy efficiency while maintaining a high data rate. In this work, a complex evaluation experiment on the communication capability under a negative Signal to Noise Ratio is presented, and the specific details of the relationship between physical layer parameters and the packet reception performance of LoRa are clarified. Furthermore, we study the impact of the packet length on the packet reception performance of LoRa, and the experimental results show that when there is a large amount of data to be transmitted, it is better to choose long packets instead of short packets. Finally, considering the influence of physical layer parameters and the packet length on the packet reception performance of LoRa, the optimal parameter combination is explored, so as to propose a transmission scheme with a balanced reliability, delay, and energy consumption. This scheme is the first to consider the physical layer parameters and packet length together to study the communication transmission scheme, which reduces the communication time by 50% compared with the traditional transmission scheme and greatly reduces the energy consumption.
Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration
Authors: Miyake Tamon , Yamamoto Shintaro , Hosono Satoshi , Funabashi Satoshi , Cheng Zhengxue , Zhang Cheng , Tamaki Emi , Sugano Shigeki
Published: February 2021

Gait phase detection, which detects foot-contact and foot-off states during walking, is important for various applications, such as synchronous robotic assistance and health monitoring. Gait phase detection systems have been proposed with various wearable devices, sensing inertial, electromyography, or force myography information. In this paper, we present a novel gait phase detection system with static standing-based calibration using muscle deformation information. The gait phase detection algorithm can be calibrated within a short time using muscle deformation data by standing in several postures; it is not necessary to collect data while walking for calibration. A logistic regression algorithm is used as the machine learning algorithm, and the probability output is adjusted based on the angular velocity of the sensor. An experiment is performed with 10 subjects, and the detection accuracy of foot-contact and foot-off states is evaluated using video data for each subject. The median accuracy is approximately 90% during walking based on calibration for 60 s, which shows the feasibility of the static standing-based calibration method using muscle deformation information for foot-contact and foot-off state detection.
Trajectory Planning of Flexible Walking for Biped Robots Using Linear Inverted Pendulum Model and Linear Pendulum Model
Authors: Li Long , Xie Zhongqu , Luo Xiang , Li Juanjuan
Published: February 2021

Linear inverted pendulum model (LIPM) is an effective and widely used simplified model for biped robots. However, LIPM includes only the single support phase (SSP) and ignores the double support phase (DSP). In this situation, the acceleration of the center of mass (CoM) is discontinuous at the moment of leg exchange, leading to a negative impact on walking stability. If the DSP is added to the walking cycle, the acceleration of the CoM will be smoother and the walking stability of the biped will be improved. In this paper, a linear pendulum model (LPM) for the DSP is proposed, which is similar to LIPM for the SSP. LPM has similar characteristics to LIPM. The dynamic equation of LPM is also linear, and its analytical solution can be obtained. This study also proposes different trajectory-planning methods for different situations, such as periodic walking, adjusting walking speed, disturbed state recovery, and walking terrain-blind. These methods have less computation and can plan trajectory in real time. Simulation results verify the effectiveness of proposed methods and that the biped robot can walk stably and flexibly when combining LIPM and LPM.
Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios
Authors: Madariaga Diego , Madariaga Javier , Bustos-Jiménez Javier , Bustos Benjamin
Published: February 2021

Due to its huge impact on the overall quality of service (QoS) of wireless networks, both academic and industrial research have actively focused on analyzing the received signal strength in areas of particular interest. In this paper, we propose the improvement of signal-strength aggregation with a special focus on Mobile Crowdsourcing scenarios by avoiding common issues related to the mishandling of log-scaled signal values, and by the proposal of a novel aggregation method based on interpolation. Our paper presents two clear contributions. First, we discuss the misuse of log-scaled signal-strength values, which is a persistent problem within the mobile computing community. We present the physical and mathematical formalities on how signal-strength values must be handled in a scientific environment. Second, we present a solution to the difficulties of aggregating signal strength in Mobile Crowdsourcing scenarios, as a low number of measurements and nonuniformity in spatial distribution. Our proposed method obtained consistently lower Root Mean Squared Error (RMSE) values than other commonly used methods at estimating the expected value of signal strength over an area. Both contributions of this paper are important for several recent pieces of research that characterize signal strength for an area of interest.
Inverted L-Shaped CP Patch Antenna with Corner-Truncated Partial Ground Plane Diagonally Adjoined with Square Branch for L-Band Applications
Authors: Boontamchauy Phanuphong , Lertwiriyaprapa Titipong , Phongcharoenpanich Chuwong
Published: February 2021

This research proposes an inverted L-shaped patch antenna with a corner-truncated partial ground plane diagonally adjoined to a square branch for L-band applications. The adjoining square branch was used to perturb linear polarization for circular polarization, and the corner-truncated partial ground plane was utilized to enhance the axial ratio bandwidth (ARBW). Simulations were performed, an antenna prototype was fabricated, and experiments were carried out. The simulation and measured results were in good agreement. The proposed antenna could achieve an ARBW of 77.87% (1.09–2.48 GHz). The novelty of this research lies in the concurrent use of a square branch and a corner-truncated partial ground plane to realize wide ARBW in an L-band, rendering the technology suitable for satellite communication and navigation applications.
Dynamic Indoor Localization Using Maximum Likelihood Particle Filtering
Authors: Wang Wenxu , Marelli Damián , Fu Minyue
Published: February 2021

A popular approach for solving the indoor dynamic localization problem based on WiFi measurements consists of using particle filtering. However, a drawback of this approach is that a very large number of particles are needed to achieve accurate results in real environments. The reason for this drawback is that, in this particular application, classical particle filtering wastes many unnecessary particles. To remedy this, we propose a novel particle filtering method which we call maximum likelihood particle filter (MLPF). The essential idea consists of combining the particle prediction and update steps into a single one in which all particles are efficiently used. This drastically reduces the number of particles, leading to numerically feasible algorithms with high accuracy. We provide experimental results, using real data, confirming our claim.
Electric-Contact Tilt Sensors: A Review
Authors: Łuczak Sergiusz , Ekwińska Magdalena
Published: February 2021

A review of various kinds of solid tilts sensors, using a free mechanical member for generation of electric-contact (mostly a ball), is presented. Standard and original solutions are discussed. The latest patents are described. A classification of the existing solutions with respect to their sensing principle is proposed. Possible types of the electric/electronic circuits are discussed. Advantages of these sensors are emphasized: mainly optional operation without power supply, resistance to electrostatic discharges, and simplicity of signal processing. Technological details are briefly introduced, along with miniaturization prospects. Additionally, liquid tilt sensors are succinctly characterized. The most typical tilt sensing techniques are concisely compared.
An Investigation on Design and Characterization of a Highly Selective LED Optical Sensor for Copper Ions in Aqueous Solutions
Authors: Hung Sheng-Chun , Lu Chih-Cheng , Wu Yu-Ting
Published: February 2021

The optical characteristics of copper ion detection, such as the photometric absorbance of specific wavelengths, exhibit significant intensity change upon incident light into the aqueous solutions with different concentrations of metal ions due to the electron transition in the orbit. In this study, we developed a low-cost, small-size and fast-response photoelectric sensing prototype as an optic sensor for copper (Cu) ions detection by utilizing the principle of optical absorption. We quantified the change of optical absorbance from infra-red (IR) light emitting diodes (LEDs) upon different concentrations of copper ions and the transmitted optical signals were transferred to the corresponding output voltage through a phototransistor and circuit integrated in the photoelectric sensing system. The optic sensor for copper (Cu) ions demonstrated not only excellent specificity with other metal ions such as cadmium (Cd), nickel (Ni), iron (Fe) and chloride (Cl) ions in the same aqueous solution but also satisfactory linearity and reproducibility. The sensitivity of the preliminary sensing system for copper ions was 29 mV/ppm from 0 to 1000 ppm. In addition, significant ion-selective characteristics and anti-interference capability were also observed in the experiments by the proposed approach.
Autonomous Water Quality Monitoring and Water Surface Cleaning for Unmanned Surface Vehicle
Authors: Chang Hsing-Cheng , Hsu Yu-Liang , Hung San-Shan , Ou Guan-Ru , Wu Jia-Ron , Hsu Chuan
Published: February 2021

Water is one of the most precious resources. However, industrial development has made water pollution a critical problem today and thus water quality monitoring and surface cleaning are essential for water resource protection. In this study, we have used the sensor fusion technology as a basis to develop a multi-function unmanned surface vehicle (MF-USV) for obstacle avoidance, water-quality monitoring, and water surface cleaning. The MF-USV comprises a USV control unit, a locomotion module, a positioning module, an obstacle avoidance module, a water quality monitoring system, a water surface cleaning system, a communication module, a power module, and a remote human–machine interface. We equip the MF-USV with the following functions: (1) autonomous obstacle detection, avoidance, and navigation positioning, (2) water quality monitoring, sampling, and positioning, (3) water surface detection and cleaning, and (4) remote navigation control and real-time information display. The experimental results verified that when the floating garbage located in the visual angle ranged from −30° to 30° on the front of the MF-USV and the distances between the floating garbage and the MF-USV were 40 and 70 cm, the success rates of floating garbage detection are all 100%. When the distance between the floating garbage and the MF-USV was 130 cm and the floating garbage was located on the left side (15°~30°), left front side (0°~15°), front side (0°), right front side (0°~15°), and the right side (15°~30°), the success rates of the floating garbage collection were 70%, 92%, 95%, 95%, and 75%, respectively. Finally, the experimental results also verified that the applications of the MF-USV and relevant algorithms to obstacle avoidance, water quality monitoring, and water surface cleaning were effective.
Defect Filling Method of Sensor Encapsulation Based on Micro-Nano Composite Structure with Parylene Coating
Authors: Yao Jialin , Qiang Wenjiang , Guo Xingqi , Fan Hanshui , Zheng Yushuang , Xu Yan , Yang Xing
Published: February 2021

The demand for waterproofing of polymer (parylene) coating encapsulation has increased in a wide variety of applications, especially in the waterproof protection of electronic devices. However, parylene coatings often produce pinholes and cracks, which will reduce the waterproof effect as a protective barrier. This characteristic has a more significant influence on sensors and actuators with movable parts. Thus, a defect filling method of micro-nano composite structure is proposed to improve the waterproof ability of parylene coatings. The defect filling method is composed of a nano layer of Al2O3 molecules and a micro layer of parylene polymer. Based on the diffusion mechanism of water molecules in the polymer membrane, defects on the surface of polymer encapsulation will be filled and decomposed into smaller areas by Al2O3 nanoparticles to delay or hinder the penetration of water molecules. Accordingly, the dense Al2O3 nanoparticles are utilized to fill and repair the surface of the organic polymer by low-rate atomic layer deposition. This paper takes the pressure sensor as an example to carry out the corresponding research. Experimental results show that the proposed method is very effective and the encapsulated sensors work properly in a saline solution after a period of time equivalent to 153.9 days in body temperature, maintaining their accuracy and precision of 2 mmHg. Moreover, the sensors could improve accuracy by about 43% after the proposed encapsulation. Therefore, the water molecule anti-permeability encapsulation would have broad application prospects in micro/nano-device protection.
Head-Mounted Display-Based Therapies for Adults Post-Stroke: A Systematic Review and Meta-Analysis
Authors: Palacios-Navarro Guillermo , Hogan Neville
Published: February 2021

Immersive virtual reality techniques have been applied to the rehabilitation of patients after stroke, but evidence of its clinical effectiveness is scarce. The present review aims to find studies that evaluate the effects of immersive virtual reality (VR) therapies intended for motor function rehabilitation compared to conventional rehabilitation in people after stroke and make recommendations for future studies. Data from different databases were searched from inception until October 2020. Studies that investigated the effects of immersive VR interventions on post-stroke adult subjects via a head-mounted display (HMD) were included. These studies included a control group that received conventional therapy or another non-immersive VR intervention. The studies reported statistical data for the groups involved in at least the posttest as well as relevant outcomes measuring functional or motor recovery of either lower or upper limbs. Most of the studies found significant improvements in some outcomes after the intervention in favor of the virtual rehabilitation group. Although evidence is limited, immersive VR therapies constitute an interesting tool to improve motor learning when used in conjunction with traditional rehabilitation therapies, providing a non-pharmacological therapeutic pathway for people after stroke.
Embedded Computation Architectures for Autonomy in Unmanned Aircraft Systems (UAS)
Authors: Mejias Luis , Diguet Jean-Philippe , Dezan Catherine , Campbell Duncan , Kok Jonathan , Coppin Gilles
Published: February 2021

This paper addresses the challenge of embedded computing resources required by future autonomous Unmanned Aircraft Systems (UAS). Based on an analysis of the required onboard functions that will lead to higher levels of autonomy, we look at most common UAS tasks to first propose a classification of UAS tasks considering categories such as flight, navigation, safety, mission and executing entities such as human, offline machine, embedded system. We then analyse how a given combination of tasks can lead to higher levels of autonomy by defining an autonomy level. We link UAS applications, the tasks required by those applications, the autonomy level and the implications on computing resources to achieve that autonomy level. We provide insights on how to define a given autonomy level for a given application based on a number of tasks. Our study relies on the state-of-the-art hardware and software implementations of the most common tasks currently used by UAS, also expected tasks according to the nature of their future missions. We conclude that current computing architectures are unlikely to meet the autonomy requirements of future UAS. Our proposed approach is based on dynamically reconfigurable hardware that offers benefits in computational performance and energy usage. We believe that UAS designers must now consider the embedded system as a masterpiece of the system.