bluuebunny/crossref_metadata_2025 huggingface dataset:
DFT Modeling of Organocatalytic Ring-Opening Polymerization of Cyclic Esters: A Crucial Role of Proton Exchange and Hydrogen Bonding
Authors: Nifant’ev Ilya , Ivchenko Pavel
Published: December 2019

Organocatalysis is highly efficient in the ring-opening polymerization (ROP) of cyclic esters. A variety of initiators broaden the areas of organocatalysis in polymerization of different monomers, such as lactones, cyclic carbonates, lactides or gycolides, ethylene phosphates and phosphonates, and others. The mechanisms of organocatalytic ROP are at least as diverse as the mechanisms of coordination ROP; the study of these mechanisms is critical in ensuring the polymer compositions and architectures. The use of density functional theory (DFT) methods for comparative modeling and visualization of organocatalytic ROP pathways, in line with experimental proof of the structures of the reaction intermediates, make it possible to establish these mechanisms. In the present review, which continues and complements our recent manuscript that focused on DFT modeling of coordination ROP, we summarized the results of DFT modeling of organocatalytic ROP of cyclic esters and some related organocatalytic processes, such as polyester transesterification.
Archaeology and Folk or Family Religion in Ancient Israel
Authors: Dever William G.
Published: December 2019

This article will summarize and interpret archaeological data that may be used to illuminate the religion of ancient Israel, ca. 1200–600 BCE, while using a phenomenal approach. The resultant portrait will be compared with one drawn from the texts of the Hebrew Bible, which suggests both convergences and significant differences. The conclusion will emphasize that archaeology does best in providing a real-life context for both artifact and texts. However, it is mostly limited to religious practice, rather than belief.
A Temporal Disaggregation Approach for TRMM Monthly Precipitation Products Using AMSR2 Soil Moisture Data
Authors: Fan Dong , Wu Hua , Dong Guotao , Jiang Xiaoguang , Xue Huazhu
Published: December 2019

Accurate and spatially-distributed precipitation information is vital to the study of the regional hydrological cycle and water resources, as well as for environmental management. To provide high spatio-temporal resolution precipitation estimates over insufficient rain-gauge areas, great efforts have been taken in using the Normalized Difference Vegetation Index (NDVI) and other land surface variables to improve the spatial resolution of satellite precipitation datasets. However, the strong spatio-temporal heterogeneity of precipitation and the “hysteresis phenomenon” of the relationship between precipitation and vegetation has limited the application of these downscaling methods to high temporal resolutions. To overcome this limitation, a new temporal downscaling method was proposed in this study by introducing daily soil moisture data to explore the relationship between precipitation and the soil moisture increment index. The performance of this proposed temporal downscaling was assessed by downscaling the Tropical Rainfall Measuring Mission (TRMM) precipitation data from a monthly scale to a daily scale over the Hekouzhen to Tongguan of the Yellow River in 2013, and the downscaled daily precipitation datasets were validated with in-situ measurement from 23 rainfall observation stations. The validation results indicate that the downscaled daily precipitation agrees with the rain gauge observations, with a correlation coefficient of 0.59, a mean error range of 1.70 mm, and a root mean square error of 5.93 mm. In general, the monthly precipitation decomposition method proposed in this paper has combined the advantage of both microwave remote sensing products. It has acceptable precision and can generate precipitation on a diurnal scale. It is an important development in the field of using auxiliary data to perform temporal downscaling. Furthermore, this method also provides a reference example for the temporal downscaling of other low temporal resolution datasets.
Sensitivity of Bistatic TanDEM-X Data to Stand Structural Parameters in Temperate Forests
Authors: Erasmi Stefan , Semmler Malte , Schall Peter , Schlund Michael
Published: December 2019

Synthetic aperture radar (SAR) satellite data provide a valuable means for the large-scale and long-term monitoring of structural components of forest stands. The potential of TanDEM-X interferometric SAR (InSAR) for the assessment of forest structural properties has been widely verified. However, present studies are mostly restricted to homogeneous forests and do not account for stratification in assessing model performance. A systematic sensitivity analysis of the TanDEM-X SAR signal to forest structural parameters was carried out with emphasis on different strata of forest stands (location of the study site, forest type, and development stage). Forest structure was parameterized by forest height metrics and stem volume. Results show that X-band volume coherence is highly sensitive to the forest canopy. Volume scattering within the canopy is dependent on the vertical heterogeneity of the forest stand. In general, TanDEM-X coherence is more sensitive to forest vertical structure compared to backscatter. The relations between TanDEM-X volume coherence and forest structural properties were significant at the level of a single test site as well as across sites in temperate forests in Germany. Forest type does not affect the overall relationship between the SAR signal and the forests’ vertical structure. The prediction of forest structural parameters based on the outcome of the sensitivity analysis yielded model accuracies between 15% (relative root mean square error) for Lorey’s height and 32% for stem volume. The global database of single-polarized bistatic TanDEM-X data provides an important source for mapping structural parameters in temperate forests at large scale, irrespective of forest type.
Evaluation of HY-2A Scatterometer Ocean Surface Wind Data during 2012–2018
Authors: Zhao Ke , Zhao Chaofang
Published: December 2019

This study focuses on the evaluation of global Haiyang-2A satellite scatterometer (HSCAT) operational wind products from 2012 to 2018. In order to evaluate HSCAT winds, HSCAT operational wind products were collocated with buoy measurements and rainfall data. Error varieties under different atmospheric stratification and rainfall conditions were taken into consideration. After data quality control, the average bias and root mean square error (RMSE) between buoys and HSCAT data were 0.1 m/s and 1.3 m/s for wind speed, and 1° and 27° for wind direction, respectively. Especially, the varieties of the wind direction difference change a lot under non-neutral atmospheric conditions. HSCAT wind speeds are overestimated with an increasing rainfall rate while wind directions tend to be perpendicular to buoys’. In brief, the HSCAT wind product qualities are not stable during 2012 to 2018, especially for the data in 2015 and 2016. Atmospheric stratification and rain effects should be considered in wind retrieval and marine application.
Combining Measurements of Built-up Area, Nighttime Light, and Travel Time Distance for Detecting Changes in Urban Boundaries: Introducing the BUNTUS Algorithm
Authors: Luqman Muhammad , Rayner Peter J. , Gurney Kevin R.
Published: December 2019

This paper introduces a new algorithm (BUNTUS—Built-up, Nighttime Light, and Travel time for Urban Size) using remote sensing techniques to delineate urban boundaries. The paper is part of a larger study of the role of urbanisation in changing fossil fuel emissions. The method combines estimates of land cover, nighttime lights, and travel times to classify contiguous urban areas. The method is automatic, global and uses data sets with enough duration to establish trends. Validation using ground truth from Landsat-8 OLI images revealed an overall accuracy ranging from 60% to 95%. Thus, this approach is capable of describing spatial distributions and giving detailed information of urban extents. We demonstrate the method with examples from Brisbane, Australia, Melbourne, Australia, and Beijing, China. The new method meets the criteria for studying overall trends in urban emissions.
Geophysical Investigation of the Neolithic Calanais Landscape
Authors: Bates C. Richard. , Bates Martin , Gaffney Chris , Gaffney Vincent , Raub Timothy D.
Published: December 2019

The northern and western isles of Scotland have proved fertile ground for archaeological investigation over the last 100 years. However, the nature of the landscape with its rugged coastlines and irregular topography, together with rapid peat growth rates, make for challenging surveying. Commonly, an archaeological monument or series of monuments is identified but little is known about the surrounding areas and, in particular, the palaeo-landscapes within which the monuments are located. This situation is exemplified by the standing stones of Calanais in Lewis. Here, surrounding peat bogs have buried a significant portion of the landscape around which the stones were first erected. This project identifies remote sensing geophysical techniques that are effective in mapping the buried (lost) landscape and thus aid better contextualisation of the stone monuments within it. Further, the project demonstrates the most appropriate techniques for prospecting across these buried landscapes for as yet unidentified stone features associated with the lives of the people who constructed the monuments.
Spatiotemporal Analysis of Precipitation in the Sparsely Gauged Zambezi River Basin Using Remote Sensing and Google Earth Engine
Authors: Zeng Hongwei , Wu Bingfang , Zhang Ning , Tian Fuyou , Phiri Elijah , Musakwa Walter , Zhang Miao , Zhu Liang , Mashonjowa Emmanuel
Published: December 2019

Precipitation plays an important role in the food production of Southern Africa. Understanding the spatial and temporal variations of precipitation is helpful for improving agricultural management and flood and drought risk assessment. However, a comprehensive precipitation pattern analysis is challenging in sparsely gauged and underdeveloped regions. To solve this problem, Version 7 Tropical Rainfall Measuring Mission (TRMM) precipitation products and Google Earth Engine (GEE) were adopted in this study for the analysis of spatiotemporal patterns of precipitation in the Zambezi River Basin. The Kendall’s correlation and sen’s Slop reducers in GEE were used to examine precipitation trends and magnitude, respectively, at annual, seasonal and monthly scales from 1998 to 2017. The results reveal that 10% of the Zambezi River basin showed a significant decreasing trend of annual precipitation, while only 1% showed a significant increasing trend. The rainy-season precipitation appeared to have a dominant impact on the annual precipitation pattern. The rainy-season precipitation was found to have larger spatial, temporal and magnitude variation than the dry-season precipitation. In terms of monthly precipitation, June to September during the dry season were dominated by a significant decreasing trend. However, areas presenting a significant decreasing trend were rare (<12% of study area) and scattered during the rainy-season months (November to April of the subsequent year). Spatially, the highest and lowest rainfall regions were shifted by year, with extreme precipitation events (highest and lowest rainfall) occurring preferentially over the northwest side rather than the northeast area of the Zambezi River Basin. A “dry gets dryer, wet gets wetter” (DGDWGW) pattern was also observed over the study area, and a suggestion on agriculture management according to precipitation patterns is provided in this study for the region. This is the first study to use long-term remote sensing data and GEE for precipitation analysis at various temporal scales in the Zambezi River Basin. The methodology proposed in this study is helpful for the spatiotemporal analysis of precipitation in developing countries with scarce gauge stations, limited analytic skills and insufficient computation resources. The approaches of this study can also be operationally applied to the analysis of other climate variables, such as temperature and solar radiation.
TanDEM-X Forest Mapping Using Convolutional Neural Networks
Authors: Mazza Antonio , Sica Francescopaolo , Rizzoli Paola , Scarpa Giuseppe
Published: December 2019

In this work, we face the problem of forest mapping from TanDEM-X data by means of Convolutional Neural Networks (CNNs). Our study aims to highlight the relevance of domain-related features for the extraction of the information of interest thanks to their joint nonlinear processing through CNN. In particular, we focus on the main InSAR features as the backscatter, coherence, and volume decorrelation, as well as the acquisition geometry through the local incidence angle. By using different state-of-the-art CNN architectures, our experiments consistently demonstrate the great potential of deep learning in data fusion for information extraction in the context of synthetic aperture radar signal processing and specifically for the task of forest mapping from TanDEM-X images. We compare three state-of-the-art CNN architectures, such as ResNet, DenseNet, and U-Net, obtaining a large performance gain over the baseline approach for all of them, with the U-Net solution being the most effective one.
Comparison of Continuous In-Situ CO2 Measurements with Co-Located Column-Averaged XCO2 TCCON/Satellite Observations and CarbonTracker Model Over the Zugspitze Region
Authors: Yuan Ye , Sussmann Ralf , Rettinger Markus , Ries Ludwig , Petermeier Hannes , Menzel Annette
Published: December 2019

Atmospheric CO2 measurements are important in understanding the global carbon cycle and in studying local sources and sinks. Ground and satellite-based measurements provide information on different temporal and spatial scales. However, the compatibility of such measurements at single sites is still underexplored, and the applicability of consistent data processing routines remains a challenge. In this study, we present an inter-comparison among representative surface and column-averaged CO2 records derived from continuous in-situ measurements, ground-based Fourier transform infrared measurements, satellite measurements, and modeled results over the Mount Zugspitze region of Germany. The mean annual growth rates agree well with around 2.2 ppm yr−1 over a 17-year period (2002–2018), while the mean seasonal amplitudes show distinct differences (surface: 11.7 ppm/column-averaged: 6.6 ppm) due to differing air masses. We were able to demonstrate that, by using consistent data processing routines with proper data retrieval and gap interpolation algorithms, the trend and seasonality can be well extracted from all measurement data sets.
Thunderstorm Classification Functions Based on Instability Indices and GNSS IWV for the Sofia Plain
Authors: Guerova Guergana , Dimitrova Tsvetelina , Georgiev Stefan
Published: December 2019

Bulgaria is a country with a high frequency of hail and thunderstorms from May to September. For the May–September 2010–2015 period, statistical regression analysis was applied to identify predictors/classification functions that contribute skills to thunderstorm forecasting in the Sofia plain. The functions are based on (1) instability indices computed from radiosonde data from Sofia station F1, and (2) combination of instability indices and Integrated Water Vapor (IWV), derived from the Global Navigation Satellite System (GNSS) station Sofia-Plana, F2. Analysis of the probability of detection and the false alarm ratio scores showed the superiority of the F2 classification function, with the best performance in May, followed by June and September. F1 and F2 scores were computed for independent data samples in the period 2017–2018 and confirmed the findings for the 2010–2015 period. Analysis of IWV and lightning flash rates for a multicell and supercell thunderstorm in June and July 2014 showed that the monthly IWV thresholds are reached 14.5 and 3.5 hours before the thunderstorm, respectively. The supercell IWV peak registered 40 min before the thunderstorm, followed by a local IWV minimum corresponding to a peak in the flash rate. In both cases, an increase of IWV during severe hail was registered, which is likely related to the hydrometeor contribution to GNSS path delay. The results of this study will be integrated into the Bulgarian Integrated NowCAsting tool for thunderstorm forecasting in the warm/convective season.
Thermohaline Structures and Heat/Freshwater Transports of Mesoscale Eddies in the Bay of Bengal Observed by Argo and Satellite Data
Authors: Lin Xinyu , Qiu Yun , Sun Dezheng
Published: December 2019

Knowledge of mesoscale eddies in the Bay of Bengal (BOB) is key for further understanding the climate variability in this region and beyond, but little is known about the vertical structure of these eddies. In this study, the three−dimensional structure and transport characteristics of mesoscale eddies in the BOB were comprehensively investigated by the combined use of Argo profiles and satellite data. The composite analysis showed that eddy−induced ocean anomalies are mainly confined to the upper 300 m of the water. The spatial structure of eddy−induced thermohaline perturbations is characterized by a dominant dipole structure in the near surface layer, arising from horizontal advection of the background thermohaline gradient by eddy rotation, and a monopole structure in the subsurface layer, caused by eddy−induced vertical displacements of the isopycnal surfaces. In the eddy core, the maximum temperature anomalies induced by a cyclonic eddy (CE) and an anticyclonic eddy (AE) are about −1.2 °C and +1.2 °C, respectively. The anomalies are located at approximately 100 m. The corresponding salinity anomalies are located at approximately 50 m with a value of −0.1 psu (0.1 psu) for CE (AE). The eddy thermohaline structure has a seasonal character. A deeper temperature and salinity core occurs in both CE and AE in spring compared to that in other seasons, which is primarily caused by the relatively deep thermocline and halocline during that season. In addition, unique warming anomalies induced by CE are present in the mixed layer during winter due to the vertical advection of the BL (Barrier Layer) warmer water by eddies. The total meridional heat transport induced by the composite eddy is poleward (equatorward) south (north) to 10°N with a value of 0.01 PW (−0.013 PW), whereas the total meridional freshwater transport is equatorward with a value of 0.046 Sv over a one−year period. The volume of freshwater export out of the bay is approximately 35% of the annual net freshwater input from local precipitation and river discharge.
Quantitative Evaluations and Error Source Analysis of Fengyun-2-Based and GPM-Based Precipitation Products over Mainland China in Summer, 2018
Authors: Xu Jintao , Ma Ziqiang , Tang Guoqiang , Ji Qingwen , Min Xiaoxiao , Wan Wei , Shi Zhou
Published: December 2019

Satellite-based quantitative precipitation estimates (QPE) with a fine quality are of great importance to global water cycle and matter and energy exchange research. In this study, we firstly apply various statistical indicators to evaluate and compare the main current satellite-based precipitation products from Chinese Fengyun (FY)-2 and the Global Precipitation Measurement (GPM), respectively, over mainland China in summer, 2018. We find that (1) FY-2G QPE and Integrated Multi-satellitE Retrievals for GPM (IMERG) perform significantly better than FY-2E QPE, using rain gauge data, with correlation coefficients (CC) varying from 0.65 to 0.90, 0.80 to 0.90, and 0.40 to 0.53, respectively; (2) IMERG agrees well with rain gauge data at monthly scale, while it performs worse than FY-2G QPE at hourly and daily scales, which may be caused by its algorithms; (3) FY-2G QPE underestimates the precipitation in summer, while FY-2E QPE and IMERG generally overestimate the precipitation; (4) there is an interesting error phenomenon in that both FY-based and GPM-based precipitation products perform more poorly during the period from 06:00 to 10:00 UTC than other periods at diurnal scale; and (5) FY-2G QPE agrees well with IMERG in terms of spatial patterns and consistency (CC of ~0.81). These findings can provide valuable preliminary references for improving next generation satellite-based QPE retrieval algorithms and instructions for applying these data in various practical fields.
An Approach to Segment and Track-Based Pedestrian Detection from Four-Layer Laser Scanner Data
Authors: Zhang Mingfang , Fu Rui , Cheng Wendong , Wang Li , Ma Yong
Published: December 2019

Pedestrian detection is a critical perception task for autonomous driving and intelligent vehicle, and it is challenging due to the potential variation of appearance and pose of human beings as well as the partial occlusion. In this paper, we present a novel pedestrian detection method via four-layer laser scanner. The proposed approach deals with the occlusion problem by fusing the segment classification results with past knowledge integration from tracking process. First, raw point cloud is segmented into the clusters of independent objects. Then, three types of features are proposed to capture the comprehensive cues, and 18 effective features are extracted with the combination of the univariate feature selection algorithm and feature correlation analysis process. Next, based on the segment classification at individual frame, the track classification is conducted further for consecutive frames using particle filter and probability data association filter. Experimental results demonstrate that both back-propagation neural network and Adaboost classifiers based on 18 selected features have their own advantages at the segment classification stage in terms of pedestrian detection performance and computation time, and the track classification procedure can improve the detection performance particularly for partially occluded pedestrians in comparison with the single segment classification procedure.
1/f Noise Modelling and Characterization for CMOS Quanta Image Sensors
Authors: Deng Wei , Fossum Eric R.
Published: December 2019

This work fits the measured in-pixel source-follower noise in a CMOS Quanta Image Sensor (QIS) prototype chip using physics-based 1/f noise models, rather than the widely-used fitting model for analog designers. This paper discusses the different origins of 1/f noise in QIS devices and includes correlated double sampling (CDS). The modelling results based on the Hooge mobility fluctuation, which uses one adjustable parameter, match the experimental measurements, including the variation in noise from room temperature to –70 °C. This work provides useful information for the implementation of QIS in scientific applications and suggests that even lower read noise is attainable by further cooling and may be applicable to other CMOS analog circuits and CMOS image sensors.
Evaluation of Long-Term Performance of a Solar Home System (SHS) Monitoring System on Harsh Environments
Authors: López-Vargas Ascensión , Fuentes Manuel , Vivar Marta
Published: December 2019

Dataloggers installed in rural regions of developing countries need to be autonomous, robust, and have good recording capacity as they may be exposed to harsh environmental conditions. An extremely hot, dry, and dusty climate can imply additional wear and tear toequipment. A test procedurewas designed and run in a confined space to control climate conditions to test the datalogger. An outdoor campaign lasting more than three years was performed at the Instituto Madrileño de Estudios Avanzados (IMDEA) Water Institute, in Alcalá de Henares (Madrid, Spain) and at the Escuela Politécnica Superior (EPS) Linares (Jaén, Spain) to test the low-cost datalogger under real conditions. The results demonstrated that it was robust and endured extreme weather conditions. In order to avoid the loss of data, a new version with a redundant system based on an SD card was implemented and tested under real conditions.
Privacy-Preserving Broker-ABE Scheme for Multiple Cloud-Assisted Cyber Physical Systems
Authors: Chi Po-Wen , Wang Ming-Hung
Published: December 2019

Cloud-assisted cyber–physical systems (CCPSs) integrate the physical space with cloud computing. To do so, sensors on the field collect real-life data and forward it to clouds for further data analysis and decision-making. Since multiple services may be accessed at the same time, sensor data should be forwarded to different cloud service providers (CSPs). In this scenario, attribute-based encryption (ABE) is an appropriate technique for securing data communication between sensors and clouds. Each cloud has its own attributes and a broker can determine which cloud is authorized to access data by the requirements set at the time of encryption. In this paper, we propose a privacy-preserving broker-ABE scheme for multiple CCPSs (MCCPS). The ABE separates the policy embedding job from the ABE task. To ease the computational burden of the sensors, this scheme leaves the policy embedding task to the broker, which is generally more powerful than the sensors. Moreover, the proposed scheme provides a way for CSPs to protect data privacy from outside coercion.
Wearable Electronics Assess the Effectiveness of Transcranial Direct Current Stimulation on Balance and Gait in Parkinson’s Disease Patients
Authors: Ricci Mariachiara , Di Lazzaro Giulia , Pisani Antonio , Scalise Simona , Alwardat Mohammad , Salimei Chiara , Giannini Franco , Saggio Giovanni
Published: December 2019

Currently, clinical evaluation represents the primary outcome measure in Parkinson’s disease (PD). However, clinical evaluation may underscore some subtle motor impairments, hidden from the visual inspection of examiners. Technology-based objective measures are more frequently utilized to assess motor performance and objectively measure motor dysfunction. Gait and balance impairments, frequent complications in later disease stages, are poorly responsive to classic dopamine-replacement therapy. Although recent findings suggest that transcranial direct current stimulation (tDCS) can have a role in improving motor skills, there is scarce evidence for this, especially considering the difficulty to objectively assess motor function. Therefore, we used wearable electronics to measure motor abilities, and further evaluated the gait and balance features of 10 PD patients, before and (three days and one month) after the tDCS. To assess patients’ abilities, we adopted six motor tasks, obtaining 72 meaningful motor features. According to the obtained results, wearable electronics demonstrated to be a valuable tool to measure the treatment response. Meanwhile the improvements from tDCS on gait and balance abilities of PD patients demonstrated to be generally partial and selective.
Block-Based Development of Mobile Learning Experiences for the Internet of Things
Authors: Ruiz-Rube Iván , Mota José Miguel , Person Tatiana , Corral José María Rodríguez , Dodero Juan Manuel
Published: December 2019

The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions to the block-based programming language used in App Inventor to make the creation of mobile apps for smart learning experiences less challenging. Such apps are used to process and graphically represent data streams from sensors by applying map-reduce operations. A workshop with students without previous experience with Internet of Things (IoT) and mobile app programming was conducted to evaluate the propositions. As a result, students were able to create small IoT apps that ingest, process and visually represent data in a simpler form as using App Inventor’s standard features. Besides, an experimental study was carried out in a mobile app development course with academics of diverse disciplines. Results showed it was faster and easier for novice programmers to develop the proposed app using new stream processing blocks.
Uncalibrated Visual Servoing for Underwater Vehicle Manipulator Systems with an Eye in Hand Configuration Camera
Authors: Li Jiyong , Huang Hai , Xu Yang , Wu Han , Wan Lei
Published: December 2019

This paper presents an uncalibrated visual servoing scheme for underwater vehicle manipulator systems (UVMSs) with an eye-in-hand camera under uncertainties. These uncertainties contain vision sensor parameters, UVMS kinematics and feature position information. At first, a linear separation approach is addressed to collect these uncertainties into vectors, and this approach can also be utilized in other free-floating based manipulator systems. Secondly, a novel nonlinear adaptive controller is proposed to achieve image error convergence by estimating these vectors, the gradient projection method is utilized to optimize the restoring moments. Thirdly, a high order disturbance observer is addressed to deal with time-varying disturbances, and the convergence of the image errors is proved under the Lyapunov theory. Finally, in order to illustrate the effectiveness of the proposed method, numerical simulations based on a 9 degrees of freedom (DOFs) UVMS with an eye-in-hand camera are conducted. In simulations, the UVMS is expected to track a circle trajectory on the image plane, meanwhile, time-varying disturbances are exerted on the system. The proposed scheme can achieve accurate and smooth tracking results during simulations.
Optical-Resolution Photoacoustic Microscopy Using Transparent Ultrasound Transducer
Authors: Chen Haoyang , Agrawal Sumit , Dangi Ajay , Wible Christopher , Osman Mohamed , Abune Lidya , Jia Huizhen , Rossi Randall , Wang Yong , Kothapalli Sri-Rajasekhar
Published: December 2019

The opacity of conventional ultrasound transducers can impede the miniaturization and workflow of current photoacoustic systems. In particular, optical-resolution photoacoustic microscopy (OR-PAM) requires the coaxial alignment of optical illumination and acoustic-detection paths through complex beam combiners and a thick coupling medium. To overcome these hurdles, we developed a novel OR-PAM method on the basis of our recently reported transparent lithium niobate (LiNbO3) ultrasound transducer (Dangi et al., Optics Letters, 2019), which was centered at 13 MHz ultrasound frequency with 60% photoacoustic bandwidth. To test the feasibility of wearable OR-PAM, optical-only raster scanning of focused light through a transducer was performed while the transducer was fixed above the imaging subject. Imaging experiments on resolution targets and carbon fibers demonstrated a lateral resolution of 8.5 µm. Further, we demonstrated vasculature mapping using chicken embryos and melanoma depth profiling using tissue phantoms. In conclusion, the proposed OR-PAM system using a low-cost transparent LiNbO3 window transducer has a promising future in wearable and high-throughput imaging applications, e.g., integration with conventional optical microscopy to enable a multimodal microscopy platform capable of ultrasound stimulation.
Fiber-Optic Multipoint Sensor System with Low Drift for the Long-Term Monitoring of High-Temperature Distributions in Chemical Reactors
Authors: Dutz Franz J. , Heinrich Andreas , Bank Rolf , Koch Alexander W. , Roths Johannes
Published: December 2019

A low-drift fiber-optic sensor system, consisting of 24 regenerated fiber Bragg gratings (RFBG), equally distributed over a length of 2.3 m, is presented here. The sensor system can monitor spatially extended temperature profiles with a time resolution of 1 Hz at temperatures of up to 500 °C. The system is intended to be used in chemical reactors for both the control of the production ramp-up, where a fast time response is needed, as well as for production surveillance, where low sensor drifts over several years are required. The fiber-optic sensor system was installed in a pilot test reactor and was exposed to a constant temperature profile, with temperatures in the range of 150–500 °C for more than two years. During this period, the temperature profile was measured every three to five months and the fiber-optic temperature data were compared with data from a three-point thermocouple array and a calibrated single-point thermocouple. A very good agreement between all temperature measurements was found. The drift rates of the 24 RFBG sensor elements were determined by comparing the Bragg wavelengths at a precisely defined reference temperature near room temperature before and after the two-year deployment. They were found to be in the range of 0.0 K/a to 2.3 K/a, with an average value of 1.0 K/a. These low drift rates were achieved by a dedicated temperature treatment of the RFBGs during fabrication. Here, the demonstrated robustness, accuracy, and low drift characteristics show the potential of fiber-optic sensors for future industrial applications.
Effect of Palladium Electrode Patterns on Hydrogen Response Characteristics from a Sensor Based on Ta2O5 Film on SiC at High Temperatures
Authors: Choi Kyeong-Keun , Kim Seongjeen
Published: December 2019

Our study aims to fabricate a hydrogen sensor based on thermal stability analysis of Ta2O5 film, and to determine the effect of Pd electrodes on the hydrogen sensor at high temperatures. First, in order to ensure high-temperature stability of silicon carbide (SiC)-based hydrogen sensors, the thermal stability of Ta2O5 dielectric thin film at temperatures above 900 °C was studied. The sensor structure consisted of a metal-insulator-semiconductor (MIS) and a tantalum oxide (Ta2O5) dielectric film was formed by rapid thermal oxidation (RTO). The Ta2O5 film was assessed through SEM, TEM, SIMS, and dielectric breakdown strength to observe thermal stability. Secondly, hydrogen sensors using a SiC substrate were fabricated, with the process considering thermal stability. The response characteristics for hydrogen were evaluated using three types of sensors with different Pd electrode patterns. The patterns of the Pd electrode were designed as squares or grid shapes, and were characterized by 100%, 75%, and 50% area ratios of Pd electrodes covering the Ta2O5 layer. The results showed that the sensor with a 100% area ratio of the Pd electrode had better sensitivity and linear response characteristics compared to sensors with a 50% area ratio of the Pd electrode.
Most Relevant Spectral Bands Identification for Brain Cancer Detection Using Hyperspectral Imaging
Authors: Martinez Beatriz , Leon Raquel , Fabelo Himar , Ortega Samuel , Piñeiro Juan F. , Szolna Adam , Hernandez Maria , Espino Carlos , J. O’Shanahan Aruma , Carrera David , Bisshopp Sara , Sosa Coralia , Marquez Mariano , Camacho Rafael , Plaza Maria de la Luz , Morera Jesus , M. Callico Gustavo
Published: December 2019

Hyperspectral imaging (HSI) is a non-ionizing and non-contact imaging technique capable of obtaining more information than conventional RGB (red green blue) imaging. In the medical field, HSI has commonly been investigated due to its great potential for diagnostic and surgical guidance purposes. However, the large amount of information provided by HSI normally contains redundant or non-relevant information, and it is extremely important to identify the most relevant wavelengths for a certain application in order to improve the accuracy of the predictions and reduce the execution time of the classification algorithm. Additionally, some wavelengths can contain noise and removing such bands can improve the classification stage. The work presented in this paper aims to identify such relevant spectral ranges in the visual-and-near-infrared (VNIR) region for an accurate detection of brain cancer using in vivo hyperspectral images. A methodology based on optimization algorithms has been proposed for this task, identifying the relevant wavelengths to achieve the best accuracy in the classification results obtained by a supervised classifier (support vector machines), and employing the lowest possible number of spectral bands. The results demonstrate that the proposed methodology based on the genetic algorithm optimization slightly improves the accuracy of the tumor identification in ~5%, using only 48 bands, with respect to the reference results obtained with 128 bands, offering the possibility of developing customized acquisition sensors that could provide real-time HS imaging. The most relevant spectral ranges found comprise between 440.5–465.96 nm, 498.71–509.62 nm, 556.91–575.1 nm, 593.29–615.12 nm, 636.94–666.05 nm, 698.79–731.53 nm and 884.32–902.51 nm.
Synergetic Sensing Effect of Sodium Carboxymethyl Cellulose and Bismuth on Cadmium Detection by Differential Pulse Anodic Stripping Voltammetry
Authors: Ning Jingheng , Luo Xin , Wang Faxiang , Huang Shouen , Wang Jianhui , Liu Dongmin , Liu Donglin , Chen Donger , Wei Jiaqian , Liu Yongle
Published: December 2019

In the present work, a novel electrochemical sensor was developed for the detection of trace cadmium with high sensitivity and selectivity in an easy and eco-friendly way. Firstly, a glassy carbon electrode (GCE) was modified with nontoxic sodium carboxymethyl cellulose (CMC) by a simple drop-casting method, which was applied to detect cadmium by differential pulse anodic stripping voltammetry (DPASV) in a solution containing both target cadmium and eco-friendly bismuth ions, based on a quick electro-codeposition of these two metal ions on the surface of the modified electrode (CMC-GCE). Investigated by scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and Fourier transform infrared spectroscopy (FT-IR), both CMC (with good film-forming ability) and bismuth (with well-defined stripping signal) were found to be well complexed with target cadmium, leading to vital signal amplification for cadmium detection at a sub-nanomolar level. Under the optimal conditions, the proposed sensor exhibited a good linear stripping signal response to cadmium (Ⅱ) ion, in a concentration range of 0.001 μmol/L–1 μmol/L with a limit of detection of 0.75 nmol/L (S/N = 3). Meanwhile, the results demonstrate that this novel electrochemical sensor has excellent sensitivity and reproducibility, which can be used as a promising detection technique for testing natural samples such as tap water.
Assessing Global Ionosphere TEC Maps with Satellite Altimetry and Ionospheric Radio Occultation Observations
Authors: Li Wei , Huang Longqiang , Zhang Shaocheng , Chai Yanju
Published: December 2019

As global navigation satellite system (GNSS)stations are sparsely distributed in oceanic area, oceanic areas usually have lower precision than continental areas on a global ionosphere maps (GIM). On the other hand, space-borne observations like satellite altimetry (SA) and ionospheric radio occultation (IRO) have substantial dual-frequency observations in oceanic areas, which could be used for total electron content (TEC) retrieval. In this paper, the Jason-2 SA and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) IRO products were used to assess the precision of IGS GIM products. Both the systematic biases and scaling factors between the international GNSS service (IGS) GIM TEC and space-borne TEC were calculated, and the statistical results show that the biases and the scaling factors obviously vary under different temporal-spatial conditions. This analysis shows that these differences are variable with diurnal and latitude factors, that is, the differences in biases during the day time are higher than those during the night time, and larger biases are experienced at lower latitude areas than at high latitude areas. The results also show that in the southern hemisphere middle-high latitude area and some other central oceanic areas, the space-borne TEC values are even higher than GIM TEC values. As the precision of space-borne TEC should be evenly distributed around different areas on Earth, it can be explain that the TEC in these areas is undervalued by the current GIM model, and the space-borne SA and IRO techniques could be used as complementary observations to improve the accuracy and reliability of TEC values in these areas.
Vehicle-to-Vehicle (V2V) Message Content Plausibility Check for Platoons through Low-Power Beaconing
Authors: Kim Hyogon , Kim Taeho
Published: December 2019

Although the IEEE Wireless Access in Vehicular Environment (WAVE) and 3GPP Cellular V2X deployments are imminent, their standards do not yet cover an important security aspect; the message content plausibility check. In safety-critical driving situations, vehicles cannot blindly trust the content of received safety messages, because an attacker may have forged false values in it in order to cause unsafe response from the receiving vehicles. In particular, the attacks mounted from remote, well-hidden positions around roads are considered the most apparent danger. So far, there have been three approaches to validating V2X message content: checking based on sensor fusion, behavior analysis, and communication constraints. This paper discusses the three existing approaches. In addition, it discusses a communication-based checking scheme that supplements the existing approaches. It uses low-power transmission of vehicle identifiers to identify remote attackers. We demonstrate its potential address in the case of an autonomous vehicle platooning application.
Development of a Lateral Flow Highway: Ultra-Rapid Multitracking Immunosensor for Cardiac Markers
Authors: Byzova Nadezhda A. , Vengerov Yuri Yu. , Voloshchuk Sergey G. , Zherdev Anatoly V. , Dzantiev Boris B.
Published: December 2019

The integration of several controlled parameters within a single test system is experiencing increased demand. However, multiplexed test systems typically require complex manufacturing. Here, we describe a multiplexed immunochromatographic assay that incorporates a conventional nitrocellulose membrane, which is used together with microspot printing, to construct adjacent microfluidic “tracks” for multiplexed detection. The 1 mm distance between tracks allows for the detection of up to four different analytes. The following reagents are applied in separate zones: (a) gold nanoparticle conjugates with antibodies against each analyte, (b) other antibodies against each analyte, and (c) antispecies antibodies. The immersion of the test strip in the sample initiates the lateral flow, during which reagents of different specificities move along their tracks without track erosion or reagent mixing. An essential advantage of the proposed assay is its extreme rapidity (1–1.5 min compared with 10 min for common test strips). This assay format was applied to the detection of cardiac and inflammatory markers (myoglobin, D-dimer, and C-reactive protein) in human blood, and was characterized by high reproducibility (8%–15% coefficient of variation) with stored working ranges of conventional tests. The universal character of the proposed approach will facilitate its use for various analytes.
Leader-Following Consensus and Formation Control of VTOL-UAVs with Event-Triggered Communications
Authors: Guerrero-Castellanos J. Fermi , Vega-Alonzo Argel , Durand Sylvain , Marchand Nicolas , Gonzalez-Diaz Victor R. , Castañeda-Camacho Josefina , Guerrero-Sánchez W. Fermin
Published: December 2019

This article presents the design and implementation of an event-triggered control approach, applied to the leader-following consensus and formation of a group of autonomous micro-aircraft with capabilities of vertical take-off and landing (VTOL-UAVs). The control strategy is based on an inner–outer loop control approach. The inner control law stabilizes the attitude and position of one agent, whereas the outer control follows a virtual leader to achieve position consensus cooperatively through an event-triggered policy. The communication topology uses undirected and connected graphs. With such an event-triggered control, the closed-loop trajectories converge to a compact sphere, centered in the origin of the error space. Furthermore, the minimal inter-sampling time is proven to be below bounded avoiding the Zeno behavior. The formation problem addresses the group of agents to fly in a given shape configuration. The simulation and experimental results highlight the performance of the proposed control strategy.
A Determination Method for Gait Event Based on Acceleration Sensors
Authors: Mei Chang , Gao Farong , Li Ying
Published: December 2019

A gait event is a crucial step towards the effective assessment and rehabilitation of motor dysfunctions. However, for the data acquisition of a three-dimensional motion capture (3D Mo-Cap) system, the high cost of setups, such as the high standard laboratory environment, limits widespread clinical application. Inertial sensors are increasingly being used to recognize and classify physical activities in a variety of applications. Inertial sensors are now sufficiently small in size and light in weight to be part of a body sensor network for the collection of human gait data. The acceleration signal has found important applications in human gait recognition. In this paper, using the experimental data from the heel and toe, first the wavelet method was used to remove noise from the acceleration signal, then, based on the threshold of comprehensive change rate of the acceleration signal, the signal was primarily segmented. Subsequently, the vertical acceleration signals, from heel and toe, were integrated twice, to compute their respective vertical displacement. Four gait events were determined in the segmented signal, based on the characteristics of the vertical displacement of heel and toe. The results indicated that the gait events were consistent with the synchronous record of the motion capture system. The method has achieved gait event subdivision, while it has also ensured the accuracy of the defined gait events. The work acts as a valuable reference, to further study gait recognition.
Geometrical Matching of SAR and Optical Images Utilizing ASIFT Features for SAR-based Navigation Aided Systems
Authors: Markiewicz Jakub , Abratkiewicz Karol , Gromek Artur , Ostrowski Wojciech , Samczyński Piotr , Gromek Damian
Published: December 2019

This article presents a new approach to the estimation of shift and rotation between two images from different kinds of imaging sensors. The first of the image is an orthophotomap that is created using optical sensors with georeference information. The second one is created utilizing a Synthetic Aperture Radar (SAR) sensor.The proposed solution can be mounted on a flying platform, and, during the flight, the obtained SAR images are compared with the reference optical images, and thus it is possible to calculate the shift and rotation between these two images and then the direct georeferencing error. Since both images have georeference information, it is possible to calculate the navigation correction in cases when the drift of the calculated trajectory is expected. The method can be used in platforms where there is no satellite navigation signal and the trajectory is calculated on the basis of an inertial navigation system, which is characterized by a significant error. The proposed method of estimating the navigation error utilizing Affine Scale-Invariant Feature Transform (ASIFT) and Structure from Motion (SfM) is described, and techniques for improving the quality of SAR imaging using despeckling filters are presented. The methodology was tested and verified using real-life SAR images. Differences between the results obtained for a few selected despeckling methods were compared and commented on. Deep investigation of the nature of the SAR imaging technique and noise creation character allows new algorithms to be developed, which can be implemented on flying platforms to support existing navigation systems in which trajectory error occurs.