bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparable Bioavailability and Disposition of Pefloxacin in Patients with Cystic Fibrosis and Healthy Volunteers Assessed via Population Pharmacokinetics
Authors: Bulitta Jürgen B. , Jiao Yuanyuan , Landersdorfer Cornelia B. , Sutaria Dhruvitkumar S. , Tao Xun , Shin Eunjeong , Höhl Rainer , Holzgrabe Ulrike , Stephan Ulrich , Sörgel Fritz
Published: July 2019

Quinolone antibiotics present an attractive oral treatment option in patients with cystic fibrosis (CF). Prior studies have reported comparable clearances and volumes of distribution in patients with CF and healthy volunteers for primarily renally cleared quinolones. We aimed to provide the first pharmacokinetic comparison for pefloxacin as a predominantly nonrenally cleared quinolone and its two metabolites between both subject groups. Eight patients with CF (fat-free mass [FFM]: 36.3 ± 6.9 kg, average ± SD) and ten healthy volunteers (FFM: 51.7 ± 9.9 kg) received 400 mg pefloxacin as a 30 min intravenous infusion and orally in a randomized, two-way crossover study. All plasma and urine data were simultaneously modelled. Bioavailability was complete in both subject groups. Pefloxacin excretion into urine was approximately 74% higher in patients with CF compared to that in healthy volunteers, whereas the urinary excretion of metabolites was only slightly higher in patients with CF. After accounting for body size and composition via allometric scaling by FFM, pharmacokinetic parameter estimates in patients with CF divided by those in healthy volunteers were 0.912 for total clearance, 0.861 for nonrenal clearance, 1.53 for renal clearance, and 0.916 for volume of distribution. Nonrenal clearance accounted for approximately 90% of total pefloxacin clearance. Overall, bioavailability and disposition were comparable between both subject groups.
Oxygen-Resistant Electrochemiluminescence System with Polyhedral Oligomeric Silsesquioxane
Authors: Nakamura Ryota , Narikiyo Hayato , Gon Masayuki , Tanaka Kazuo , Chujo Yoshiki
Published: July 2019

We report the oxygen-resistant electrochemiluminescence (ECL) system from the polyhedral oligomeric silsesquioxane (POSS)-modified tris(2,2′-bipyridyl)ruthenium(II) complex (Ru-POSS). In electrochemical measurements, including cyclic voltammetry (CV), it is shown that electric current and ECL intensity increase in the mixture system containing Ru-POSS and tripropylamine (TPrA) on the indium tin oxide (ITO) working electrode. The lower onset potential (Eonset) in CV is observed with Ru-POSS compared to tris(2,2′-bipyridyl)ruthenium(II) complex (Ru(bpy)32+). From the series of mechanistic studies, it was shown that adsorption of Ru-POSS onto the ITO electrode enhances TPrA oxidation and subsequently the efficiency of ECL with lower voltage. Moreover, oxygen quenching of ECL was suppressed, and it is proposed that the enhancement to the production of the TPrA radical could contribute to improving oxygen resistance. Finally, the ECL-based detection for water pollutant is demonstrated without the degassing treatment. The commodity system with Ru(bpy)32+ is not applicable in the absence of degassing with the sample solutions due to critical signal suppression, meanwhile the present system based on Ru-POSS was feasible for estimating the amount of the target even under aerobic conditions by fitting the ECL intensity to the standard curve. One of critical disadvantages of ECL can be solved by the hybrid formation with POSS.
Development and Application of a Data-Driven System for Sensor Fault Diagnosis in an Oil Processing Plant
Authors: Clavijo Nayher , Melo Afrânio , Câmara Maurício M. , Feital Thiago , Anzai Thiago K. , Diehl Fabio C. , Thompson Pedro H. , Pinto José Carlos
Published: July 2019

Predictive analytics is usually cited as one of the most important pillars of the digital transformation. For the oil industry, specifically, it is a common belief that issues like integrity and maintenance could benefit from predictive analytics. This paper presents the development and the application of a process-monitoring tool in a real process facility. The PMA (Predictive Maintenance Application) system is a data-driven application that uses a multivariate analysis in order to predict the system behavior. Results show that the use of a multivariate approach for process monitoring could not only detect an early failure at a metering system days before the operation crew, but could also successfully identify, among hundreds of variables, the root cause of the abnormal situation. By applying such an approach, a better performance of the monitored equipment is expected, decreasing its downtime.
Optimal Design of Bioenergy Supply Chains Considering Social Benefits: A Case Study in Northeast China
Authors: Gao Cong , Qu Daogang , Yang Yang
Published: July 2019

Bioenergy supply chains can offer social benefits. In most related research, the total number of created jobs is used as the indicator of social benefits. Only a few of them quantify social benefits considering the different impact of economic activities in different locations. In this paper, a new method of measuring the social benefits of bioethanol supply chains is proposed that considers job creation, biomass purchase, and the different impacts of economic activities in different locations. A multi-objective mixed integer linear programming (MILP) model is developed to address the optimal design of a bioethanol supply chain that maximizes both economic and social benefits. The ε-constraint method is employed to solve the model and a set of Pareto-optimal solutions is obtained that shows the relationship between the two objectives. The developed model is applied to case studies in Liaoning Province in Northeast China. Actual data are collected as practical as possible for the feasibility and effectiveness of the results. The results show that the bioethanol supply chain can bring about both economic and social benefits in the given area and offers governments a better and more efficient way to create social benefits. The effect of the government subsidy on enterprises’ decisions about economic and social benefits is discussed.
Capacity of Caulerpa lentillifera in the Removal of Fish Culture Effluent in a Recirculating Aquaculture System
Authors: Bambaranda B. V. A. S. Manori , Tsusaka Takuji W. , Chirapart Anong , Salin Krishna R. , Sasaki Nophea
Published: July 2019

Aquaculture is one of the fastest growing food producing industries in the world. Aquaculture effluent contains high concentrations of inorganic nutrients. Reduction of these inorganic nutrients in aquaculture effluent is crucial for fulfilling the effluent standards or reuse of aquaculture effluent. This study investigated the effective use of green macroalga Caulerpa lentillifera as a bioremediatory species for nutrient removal from aquaculture effluent by conducting an on-station experiment and measurements. The effluent of a fish culture unit was circulated through a macroalgal culture unit every four days for a total of 60 days, allowing 15 circulations. Concentrations of inorganic nutrients (NO2−-N, NO3−-N, NH3-N, and PO43−) were measured in the integrated system consisting of a fish unit, settling unit, macroalgal unit and extra tank for water circulation in triplicates. Multiple linear regression analysis revealed that the application of the bioremediation system led to a significant reduction in nutrient concentrations within one day, and slightly further in the following two days. On average over the 15 circulations, the first one day of application decreased the concentrations of NO2−-N, NO3−-N, NH3-N, and PO43− by 0.247 mg/L, 81.6 mg/L, 0.682 mg/L, and 0.352 mg/L, respectively. Furthermore, the C:N ratio of macroalgae decreased during the 60-day application period, providing evidence of the nutrient uptake by macroalgae. Based on the European Union (EU) standard and quality criteria of France and the Joint FAO/WHO Expert Committee (JFWEC), the macroalgae grown in the integrated system were at the safe level for human consumption in terms of contents of Cd, Pb, and As. The results of our study imply that recirculating aquaculture systems utilizing C. lentillifera for biofiltration have the potential for effective treatment of aquaculture effluent integrating fish and macroalgae production.
Seeking Christian Theology in Modern Chinese Fiction: An Exercise for Sino-Christian Theology
Authors: Jasper David
Published: July 2019

The development of Christian theology in contemporary China can learn much from Chinese fiction beginning with Lu Xun and his dedication to writing for the spirit of the Chinese people. Increasingly, Chinese novelists have reflected the growth of spiritual life in the Chinese People’s Republic in spite of the burden placed on the Christian church and religious believers.
The Role of Pro-Adrenomedullin as a Marker of Severe Bacterial Infection in Children: A Review
Authors: Garazzino Silvia , Altieri Elena , Denina Marco
Published: July 2019

Sepsis is still related to high mortality and hospitalization rates in the paediatric population despite medical progress. Prompt recognition of sepsis and consequent initiation of an appropriate treatment are essential elements in securing a positive outcome in adults and children. In such scenario, various biomarkers have been studied to support the clinician in the diagnosis of severe infections, in the identification of patients at risk of progression towards sepsis as well as in the evaluation of the response to treatment. In children, the performance of C-reactive protein and procalcitonin has been largely investigated, whereas data on newer biomarkers of sepsis are scant. The aim of the present review is to summarise the available data on the use of pro-adrenomedullin in the paediatric age.
Ibero-American Research on Local Development. An Analysis of Its Evolution and New Trends
Authors: Ruiz-Real José Luis , Uribe-Toril Juan , De Pablo Valenciano Jaime , Pires Manso José Ramos
Published: July 2019

Local development is a subject that arouses significant interest in the international scientific community in general, and in the Ibero-American one, in particular. The process of globalization has transformed the management of local development, altering the role that is played by local and regional entities, and it is the object of an important follow-up and analysis by academia. This research uses a bibliometric methodology and a fractional counting method, reviewing the 738 articles from the Scopus database in order to understand the state of Ibero-American research on local development, and analyze the scientific literature on the topic. The results show a significant increase in the number of publications in the 21st century, with Spain and Brazil leading the way. In addition, this research provides interesting results regarding the most influential authors on this topic, the most relevant journals, and the most important institutions and funding organizations. There are several areas of knowledge involved since local development is a transversal field, such as Social Science, environment, business, economics, and agriculture. A deep analysis of authors’ keywords identified new trends, linking local development with tourism, education, geotourism, climate change, local sustainable development, social innovation, and creativity, which provides academia with potential new lines of research.
Automatic Identification of Shrub-Encroached Grassland in the Mongolian Plateau Based on UAS Remote Sensing
Authors: Dong Yu , Yan Huimin , Wang Na , Huang Mei , Hu Yunfeng
Published: July 2019

Recently, the increasing shrub-encroached grassland in the Mongolian Plateau partly indicates grassland quality decline and degradation. Accurate shrub identification and regional difference analysis in shrub-encroached grassland are significant for ecological degradation research. Object-oriented filter (OOF) and digital surface model (DSM)-digital terrain model (DTM) analyses were combined to establish a high-accuracy automatic shrub identification algorithm (CODA), which made full use of remote sensing products by unmanned aircraft systems (UASs). The results show that: (1) The overall accuracy of CODA in the Grain for Green test area is 89.96%, which is higher than that of OOF (84.52%) and DSM-DTM (78.44%), mainly due to the effective elimination of interference factors (such as shrub-like highland, well-grown grassland in terrain-depression area, etc.) by CODA. (2) The accuracy (87.5%) of CODA in the typical steppe test area is lower than that (92.5%) in the desert steppe test area, which may be related to the higher community structure complexity of typical steppe. Besides, the shrub density is smaller, and the regional difference is more massive in the typical steppe test area. (3) The ground sampling distance for best CODA accuracy in the Grain for Green test area is about 15 cm, while it is below 3 cm in the typical and desert steppe test area.
A New Method for Characterizing NOAA-20/S-NPP VIIRS Thermal Emissive Bands Response Versus Scan Using On-Orbit Pitch Maneuver Data
Authors: Wang Wenhui , Cao Changyong , Blonski Slawomir
Published: July 2019

The on-orbit calibration of Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Emissive Bands (TEB), onboard the National Oceanic and Atmospheric Administration-20 (NOAA-20) and the Suomi National Polar-orbiting Partnership (S-NPP) satellites, have been stable during nominal operations. However, larger than expected scan angle/scene temperature dependent biases, relative to the co-located Cross-track Infrared Sounder (CrIS) observations, were observed in the NOAA-20 longwave infrared (LWIR) bands. The Response Versus Scan (RVS) effect—the variation of instrument reflectance of source radiance with scan angle, is a significant contributor to VIIRS calibration. TEB RVS is characterized using prelaunch test data and verified on-orbit using pitch maneuver data. This study presents a new method that characterizes VIIRS on-orbit TEB RVS at both Earth View (EV) and Space View (SV) scan angles simultaneously. This method was compared with an existing on-orbit RVS method (the Wu et al. method), which derives RVS at EV scan angles using pitch maneuver data and extrapolates SV RVS from EV. The new method derived on-orbit RVS differ from prelaunch values up to 1.0% at the beginning of scan in the NOAA-20 LWIR bands, and ~0.5% in S-NPP M15. VIIRS–CrIS inter-comparison results indicates that the new method derived on-orbit RVS can effectively minimize LWIR scan angle/scene temperature dependent biases, with scan averaged biases reduced from 0.40K to 0.15K for NOAA-20 LWIR bands, and from 0.24K to 0.08K for S-NPP M15. The Wu et al. method can also reduce the scan angle dependent biases, but at the expense of increasing the scene temperature dependent biases.
Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China
Authors: Zhao Jing , Huang Shengzhi , Huang Qiang , Wang Hao , Leng Guoyong , Peng Jian , Dong Haixia
Published: July 2019

Understanding the changing relationships between vegetation coverage and precipitation/temperature (P/T) and then exploring their potential drivers are highly necessary for ecosystem management under the backdrop of a changing environment. The Jing River Basin (JRB), a typical eco-environmentally vulnerable region of the Loess Plateau, was chosen to identify abrupt variations of the relationships between seasonal Normalized Difference Vegetation Index (NDVI) and P/T through a copula-based method. By considering the climatic/large-scale atmospheric circulation patterns and human activities, the potential causes of the non-stationarity of the relationship between NDVI and P/T were revealed. Results indicated that (1) the copula-based framework introduced in this study is more reasonable and reliable than the traditional double-mass curves method in detecting change points of vegetation and climate relationships; (2) generally, no significant change points were identified during 1982–2010 at the 95% confidence level, implying the overall stationary relationship still exists, while the relationships between spring NDVI and P/T, autumn NDVI and P have slightly changed; (3) teleconnection factors (including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Niño 3.4, and sunspots) have a more significant influence on the relationship between seasonal NDVI and P/T than local climatic factors (including potential evapotranspiration and soil moisture); (4) negative human activities (expansion of farmland and urban areas) and positive human activities (“Grain For Green” program) were also potential factors affecting the relationship between NDVI and P/T. This study provides a new and reliable insight into detecting the non-stationarity of the relationship between NDVI and P/T, which will be beneficial for further revealing the connection between the atmosphere and ecosystems.
Influence of Topographic Resolution and Accuracy on Hydraulic Channel Flow Simulations: Case Study of the Versilia River (Italy)
Authors: Luppichini Marco , Favalli Massimiliano , Isola Ilaria , Nannipieri Luca , Giannecchini Roberto , Bini Monica
Published: July 2019

The Versilia plain, a well-known and populated tourist area in northwestern Tuscany, is historically subject to floods. The last hydrogeological disaster of 1996 resulted in 13 deaths and in loss worth hundreds of millions of euros. A valid management of the hydraulic and flooding risks of this territory is therefore mandatory. A 7.5 km-long stretch of the Versilia River was simulated in one-dimension using river cross-sections with the FLO-2D Basic model. Simulations of the channel flow and of its maximum flow rate under different input conditions highlight the key role of topography: uncertainties in the topography introduce much larger errors than the uncertainties in roughness. The best digital elevation model (DEM) available for the area, a 1-m light detection and ranging (LiDAR) DEM dating back to 2008–2010, does not reveal all the hydraulic structures (e.g., the 40 cm thick embankment walls), lowering the maximum flow rate to only 150 m3/s, much lower than the expected value of 400 m3/s. In order to improve the already existing input topography, three different possibilities were considered: (1) to add the embankment walls to the LiDAR data with a targeted Differential GPS (DGPS) survey, (2) to acquire the cross section profiles necessary for simulation with a targeted DGPS survey, and (3) to achieve a very high resolution topography using structure from motion techniques (SfM) from images acquired using an unmanned aerial vehicle (UAV). The simulations based on all these options deliver maximum flow rates in agreement with estimated values. Resampling of the 10 cm cell size SfM-DSM allowed us to investigate the influence of topographic resolution on hydraulic channel flow, demonstrating that a change in the resolution from 30 to 50 cm alone introduced a 10% loss in the maximum flow rate. UAV-SfM-derived DEMs are low cost, relatively fast, very accurate, and they allow for the monitoring of the channel morphology variations in real time and to keep the hydraulic models updated, thus providing an excellent tool for managing hydraulic and flooding risks.
Evaluation of Four Atmospheric Correction Algorithms for GOCI Images over the Yellow Sea
Authors: Huang Xiaocan , Zhu Jianhua , Han Bing , Jamet Cédric , Tian Zhen , Zhao Yili , Li Jun , Li Tongji
Published: July 2019

Atmospheric correction (AC) for coastal waters is an important issue in ocean color remote sensing. AC performance is fundamental in retrieving reliable water-leaving radiances and then bio-optical parameters. Unlike polar-orbiting satellites, geostationary ocean color sensors allow high-frequency (15–60 min) monitoring of ocean color over the same area. The first geostationary ocean color sensor, i.e., the Geostationary Ocean Color Imager (GOCI), was launched in 2010. Using GOCI data acquired over the Yellow Sea in summer 2017 at three principal overpass times (02:16, 03:16, 04:16 UTC) with ±1 and ±3 h match-up times, this study compared four GOCI AC algorithms: (1) the standard near infrared (NIR) algorithm of NASA (NASA-STD), (2) the Korea Ocean Satellite Center (KOSC) standard algorithm for GOCI (KOSC-STD), (3) the diffuse attenuation coefficient at 490 nm Kd (490)-based NIR correction algorithm (Kd-based), and (4) the Management Unit of the North Sea Mathematical Models (MUMM). The GOCI-estimated remote sensing reflectance (Rrs), aerosol parameters [aerosol optical thickness (AOT), Angström Exponent (AE)], and chlorophyll-a (Chla) were validated using in situ data. For Rrs, AOT, AE, and Chla, GOCI-retrieved results performed well within the ±1 h temporal window, but the number of match-ups was extended within the ±3 h match-up window. For ±3 h GOCI-derived Rrs, all algorithms had an absolute percentage difference (APD) at 490 and 555 nm of <40%, while other bands showed larger differences (APD > 60%). Compared with in situ values, the APD of the Rrs(490)/Rrs(555) band ratio was <20% for all ACs. For AOT and AE, the APD was >40% and >200%, respectively. Of the four algorithms, the KOSC-STD algorithm demonstrated satisfactory performance in deriving Rrs for the region of interest (Rrs APD: 22.23%–73.95%) in the visible bands. The Kd-based algorithm worked well obtaining Ocean Color 3 GOCI Chla because Rrs(443) is more accurate than the KOSC-STD. The poorest Rrs retrievals were achieved using the NASA-STD and the MUMM algorithms. Statistical analysis indicated that all methods had optimal performance at 04:16 UTC.
GPU-Based Lossless Compression of Aurora Spectral Data using Online DPCM
Authors: Li Jiaojiao , Wu Jiaji , Jeon Gwanggil
Published: July 2019

It is well known that aurorae have very high research value, but the data volume of aurora spectral data is very large, which brings great challenges to storage and transmission. To alleviate this problem, compression of aurora spectral data is indispensable. This paper presents a parallel Compute Unified Device Architecture (CUDA) implementation of the prediction-based online Differential Pulse Code Modulation (DPCM) method for the lossless compression of the aurora spectral data. Two improvements are proposed to improve the compression performance of the online DPCM method. One is on the computing of the prediction coefficients, and the other is on the encoding of the residual. In the CUDA implementation, we proposed a decomposition method for the matrix multiplication to avoid redundant data accesses and calculations. In addition, the CUDA implementation is optimized with a multi-stream technique and multi-graphics processing unit (GPU) technique, respectively. Finally, the average compression time of an aurora spectral image reaches about 0.06 s, which is much less than the 15 s aurora spectral data acquisition time interval and can save a lot of time for transmission and other subsequent tasks.
Long Time Series Land Cover Classification in China from 1982 to 2015 Based on Bi-LSTM Deep Learning
Authors: Wang Haoyu , Zhao Xiang , Zhang Xin , Wu Donghai , Du Xiaozheng
Published: July 2019

Land cover classification data have a very important practical application value, and long time series land cover classification datasets are of great significance studying environmental changes, urban changes, land resource surveys, hydrology and ecology. At present, the starting point of continuous land cover classification products for many years is mostly after the year 2000, and there is a lack of long-term continuously annual land cover classification products before 2000. In this study, a long time series classification data extraction model is established using a bidirectional long-term and short-term memory network (Bi-LSTM). In the model, quantitative remote sensing products combined with DEM, nighttime lighting data, and latitude and longitude elevation data were used. We applied this model in China and obtained China’s 1982–2017 0.05° land cover classification product. The accuracy assessment results of the test data show that the overall accuracy is 84.2% and that the accuracies of wetland, water, glacier, tundra, city and bare soil reach 92.1%, 92.0%, 94.3%, 94.6% and 92.4%, respectively. For the first time, this study used a variety of long time series data, especially quantitative remote sensing products, for the classification of features. At the same time, it also acquired long time series land cover classification products, including those from the year 2000. This study provides new ideas for the establishment of higher-resolution long time series land cover classification products.
Remote Sensing to Detect Nests of the Leaf-Cutting Ant Atta sexdens (Hymenoptera: Formicidae) in Teak Plantations
Authors: Santos Isabel Carolina de Lima , Santos Alexandre dos , Oumar Zakariyyaa , Soares Marcus Alvarenga , Silva Július César Cerqueira , Zanetti Ronald , Zanuncio José Cola
Published: July 2019

Leaf-cutting ants of the genus Atta are an important insect pest in forest plantations in many countries of South America. The objective of this work was to evaluate the potential for using Landsat-8 images, with medium spatial resolution and distributed free of charge, to detect leaf-cutting ant nests in Tectona grandis plantations in Brazil, using partial least squares discriminant analysis (PLS-DA). The regression model adjusted by PLS-DA selected three principal components with a cross-validation error of 0.275 to map and predict the presence of leaf-cutting ant nests in these plantations. The most important bands and vegetation indices were selected using the main variables in the projection (VIP) and predicted pixels with the presence or absence of leaf-cutting ant nests with an accuracy of 72.3% on an independent validation data set. The study indicates that Landsat-8 OLI images have the potential to detect and map leaf-cutting ant nests in T. grandis plantations.
Spatial Analysis of Surface Urban Heat Islands in Four Rapidly Growing African Cities
Authors: Simwanda Matamyo , Ranagalage Manjula , Estoque Ronald , Murayama Yuji
Published: July 2019

Africa’s unprecedented, uncontrolled and unplanned urbanization has put many African cities under constant ecological and environmental threat. One of the critical ecological impacts of urbanization likely to adversely affect Africa’s urban dwellers is the urban heat island (UHI) effect. However, UHI studies in African cities remain uncommon. Therefore, this study attempts to examine the relationship between land surface temperature (LST) and the spatial patterns, composition and configuration of impervious surfaces/green spaces in four African cities, Lagos (Nigeria), Nairobi (Kenya), Addis Ababa (Ethiopia) and Lusaka (Zambia). Landsat OLI/TIRS data and various geospatial approaches, including urban–rural gradient, urban heat island intensity, statistics and urban landscape metrics-based techniques, were used to facilitate the analysis. The results show significantly strong correlation between mean LST and the density of impervious surface (positive) and green space (negative) along the urban–rural gradients of the four African cities. The study also found high urban heat island intensities in the urban zones close (0 to 10 km) to the city center for all cities. Generally, cities with a higher percentage of the impervious surface were warmer by 3–4 °C and vice visa. This highlights the crucial mitigating effect of green spaces. We also found significant correlations between the mean LST and urban landscape metrics (patch density, size, shape, complexity and aggregation) of impervious surfaces (positive) and green spaces (negative). The study revealed that, although most African cities have relatively larger green space to impervious surface ratio with most green spaces located beyond the urban footprint, the UHI effect is still evident. We recommend that urban planners and policy makers should consider mitigating the UHI effect by restoring the urban ecosystems in the remaining open spaces in the urban area and further incorporate strategic combinations of impervious surfaces and green spaces in future urban and landscape planning.
A Hovercraft-Borne LiDAR and a Comprehensive Filtering Method for the Topographic Survey of Mudflats
Authors: Zhao Jianhu , Chen Mingyi , Zhang Hongmei , Zheng Gen
Published: July 2019

To obtain the mudflat topography when existing measuring systems and data processing methods are impracticable under special conditions, this paper presents a hovercraft-borne LiDAR (light detection and ranging) system and a novel comprehensive filtering method. The system is based on a hovercraft and equipped with a laser scanner and a POS (position and orientation system). The filtering method firstly segments the point cloud into different segments by combining the geometric and intensity information, then fitting the ground surface by cloth simulation method, and finally synthetically extracts the ground points with three constraints. These constraints are the distance of the point to the fitting surface, the normal difference between the point and the fitting surface, and the proportion of the possible ground points in the total points of each segment. The effectiveness of the measurement system and the development of the post-processing results were verified on the basis of field measurements, in which a total filtering error of 0.3% and the elevation accuracy of 6.4 cm were obtained. The proposed system and methods provide a new way for efficient and accurate topographic survey on mudflats.
Fault Detection in Power Equipment via an Unmanned Aerial System Using Multi Modal Data
Authors: Jalil Bushra , Leone Giuseppe Riccardo , Martinelli Massimo , Moroni Davide , Pascali Maria Antonietta , Berton Andrea
Published: July 2019

The power transmission lines are the link between power plants and the points of consumption, through substations. Most importantly, the assessment of damaged aerial power lines and rusted conductors is of extreme importance for public safety; hence, power lines and associated components must be periodically inspected to ensure a continuous supply and to identify any fault and defect. To achieve these objectives, recently, Unmanned Aerial Vehicles (UAVs) have been widely used; in fact, they provide a safe way to bring sensors close to the power transmission lines and their associated components without halting the equipment during the inspection, and reducing operational cost and risk. In this work, a drone, equipped with multi-modal sensors, captures images in the visible and infrared domain and transmits them to the ground station. We used state-of-the-art computer vision methods to highlight expected faults (i.e., hot spots) or damaged components of the electrical infrastructure (i.e., damaged insulators). Infrared imaging, which is invariant to large scale and illumination changes in the real operating environment, supported the identification of faults in power transmission lines; while a neural network is adapted and trained to detect and classify insulators from an optical video stream. We demonstrate our approach on data captured by a drone in Parma, Italy.
Barrier Access Control Using Sensors Platform and Vehicle License Plate Characters Recognition
Authors: Ullah Farman , Anwar Hafeez , Shahzadi Iram , Ur Rehman Ata , Mehmood Shizra , Niaz Sania , Mahmood Awan Khalid , Khan Ajmal , Kwak Daehan
Published: July 2019

The paper proposes a sensors platform to control a barrier that is installed for vehicles entrance. This platform is automatized by image-based license plate recognition of the vehicle. However, in situations where standardized license plates are not used, such image-based recognition becomes non-trivial and challenging due to the variations in license plate background, fonts and deformations. The proposed method first detects the approaching vehicle via ultrasonic sensors and, at the same time, captures its image via a camera installed along with the barrier. From this image, the license plate is automatically extracted and further processed to segment the license plate characters. Finally, these characters are recognized with the help of a standard optical character recognition (OCR) pipeline. The evaluation of the proposed system shows an accuracy of 98% for license plates extraction, 96% for character segmentation and 93% for character recognition.
Pure SH1 Guided-Wave Generation Method with Dual Periodic-Permanent-Magnet Electromagnetic Acoustic Transducers for Plates Inspection
Authors: Qiu Gongzhe , Song Xiaochun , Zhang Xu , Tu Jun , Chen Tao
Published: July 2019

High frequency guided-waves offer a trade-off between the high sensitivity of local bulk ultrasonic thickness measurements and the large area scanning of lower frequency guided-waves, so it has been a growing interest for corrosion inspection with the dispersive SH1 mode. However, according to the dispersive curve, it is hard to generate the pure SH1 mode since the non-dispersive SH0 mode will be excited simultaneously. Thus, this paper investigates a transducer design method to generate a pure SH1 guided-wave, where the dual periodic-permanent-magnet electromagnetic acoustic transducers (PPM EMATs) are placed on exactly opposite positions either side of the plate symmetrically. The suppression effect for SH0 and the enhancement effect for SH1 of the dual PPM EMATs are mainly discussed by theoretical analysis and simulation analysis, and the influence of positioning errors of PPM EMATs placed on opposite sides of the plate on its performances are analyzed. Employing the proposed dual PPM EMATs, some experiments are performed to verify the reliability of finite element simulation. The results indicate that the dual PPM EMATs can suppress the SH0 mode and generate the pure SH1 mode effectively. Moreover, the longitudinal and lateral positioning errors can affect the dual PPM EMATs performances significantly.
Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System
Authors: Manogaran Gunasekaran , Shakeel P. , Fouad H. , Nam Yunyoung , Baskar S. , Chilamkurti Naveen , Sundarasekar Revathi
Published: July 2019

According to the survey on various health centres, smart log-based multi access physical monitoring system determines the health conditions of humans and their associated problems present in their lifestyle. At present, deficiency in significant nutrients leads to deterioration of organs, which creates various health problems, particularly for infants, children, and adults. Due to the importance of a multi access physical monitoring system, children and adolescents’ physical activities should be continuously monitored for eliminating difficulties in their life using a smart environment system. Nowadays, in real-time necessity on multi access physical monitoring systems, information requirements and the effective diagnosis of health condition is the challenging task in practice. In this research, wearable smart-log patch with Internet of Things (IoT) sensors has been designed and developed with multimedia technology. Further, the data computation in that smart-log patch has been analysed using edge computing on Bayesian deep learning network (EC-BDLN), which helps to infer and identify various physical data collected from the humans in an accurate manner to monitor their physical activities. Then, the efficiency of this wearable IoT system with multimedia technology is evaluated using experimental results and discussed in terms of accuracy, efficiency, mean residual error, delay, and less energy consumption. This state-of-the-art smart-log patch is considered as one of evolutionary research in health checking of multi access physical monitoring systems with multimedia technology.
Analyzing Passive BCI Signals to Control Adaptive Automation Devices
Authors: Al-Hudhud Ghada , Alqahtani Layla , Albaity Heyam , Alsaeed Duaa , Al-Turaiki Isra
Published: July 2019

Brain computer interfaces are currently considered to greatly enhance assistive technologies and improve the experiences of people with special needs in the workplace. The proposed adaptive control model for smart offices provides a complete prototype that senses an environment’s temperature and lighting and responds to users’ feelings in terms of their comfort and engagement levels. The model comprises the following components: (a) sensors to sense the environment, including temperature and brightness sensors, and a headset that collects electroencephalogram (EEG) signals, which represent workers’ comfort levels; (b) an application that analyzes workers’ feelings regarding their willingness to adjust to a space based on an analysis of collected data and that determines workers’ attention levels and, thus, engagement; and (c) actuators to adjust the temperature and/or lighting. This research implemented independent component analysis to remove eye movement artifacts from the EEG signals and used an engagement index to calculate engagement levels. This research is expected to add value to research on smart city infrastructures and on assistive technologies to increase productivity in smart offices.
Correction: Ye, T.; et al. Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode. Sensors 2018, 18, 1916
Authors: Ye Tao , Wang Baocheng , Song Ping , Li Juan
Published: July 2019

The authors wish to make the following corrections to this paper [...]
Malaria-Infected Red Blood Cell Analysis through Optical and Biochemical Parameters Using the Transport of Intensity Equation and the Microscope’s Optical Properties
Authors: Agnero Marcel , Konan Kouakou , Tokou Zan , Kossonou Yao , Dion Bienvenue , Kaduki Kenneth , Zoueu Jérémie
Published: July 2019

The accuracy, reliability, speed and cost of the methods used for malaria diagnosis are key to the diseases’ treatment and eventual eradication. However, improvement in any one of these requirements can lead to deterioration of the rest due to their interdependence. We propose an optical method that provides fast detection of malaria-infected red blood cells (RBCs) at a lower cost. The method is based on the combination of deconvolution, topography and three-dimensional (3D) refractive index reconstruction of the malaria-infected RBCs by use of the transport of intensity equation. Using our method, healthy RBCs were identified by their biconcave shape, quasi-uniform spatial distribution of their refractive indices and quasi-uniform concentration of hemoglobin. The values of these optical and biochemical parameters were found to be in agreement with the values reported in the literature. Results for the malaria-infected RBCs were significantly different from those of the healthy RBCs. The topography of the cells and their optical and biochemical parameters enabled identification of their stages of infection. This work introduces a significant method of analyzing malaria-infected RBCs at a lower cost and without the use of fluorescent labels for the parasites.
Identity-Based Encryption with Filtered Equality Test for Smart City Applications
Authors: Ming Yang , Wang Erxiu
Published: July 2019

With the growth of the urban population, the rapid development of smart cities has become the focus of urban regional development. Smart medical care is an indispensable part of smart city construction, which promotes the development of the medical industry. However, the security of data and timely service are the current problems faced by intelligent medical systems. Based on the public key encryption with filtered equality test and identity-based cryptography, an identity-based encryption with the filtered equality test (IBE-FET) is proposed for smart healthcare, in which a data receiver can use the private key and the message set to generate a warrant and send it to the cloud server. A cloud server can verify the equality between ciphertexts without decryption and check whether the encrypted message belongs to the same message set. Furthermore, the security analysis shows that the proposed scheme satisfies one-way security against the chosen identity and ciphertext attack in the random oracle model under the computational bilinear Diffie-Hellman assumption. The performance comparison shows that the scheme is feasible and practical in real life.
Transfer Printing Technology as a Straightforward Method to Fabricate Chemical Sensors Based on Tin Dioxide Nanowires
Authors: Sosada-Ludwikowska Florentyna , Wimmer-Teubenbacher Robert , Sagmeister Martin , Köck Anton
Published: July 2019

Metal oxide multi-nanowire-based chemical gas sensors were manufactured by a fast and simple transfer printing technology. A two-step method employing spray pyrolysis deposition and a thermal annealing process was used for SnO 2 nanowires fabrication. A polydimethylsiloxane stamp was used to transfer the SnO 2 nanowires on two different gas sensing devices—Si-based substrates and microhotplate-based platform chips. Both contained a metallic inter-digital electrode structure (IDES), on which the SnO 2 nanowires were transferred for realization of multi-NW gas sensor devices. The gas sensor devices show a very high response towards H 2 S down to the 10 ppb range. Furthermore, a good response towards CO has been achieved, where in particular the microhotplate-based devices exhibit almost no cross sensitivity to humidity.
Hydrogen Sensing Using Paper Sensors with Pencil Marks Decorated with Palladium
Authors: Lee Nam Hee , Baek Un-Bong , Nahm Seung-Hoon
Published: July 2019

Paper-based sensors fabricated using the pencil-on-paper method are expected to find wide usage in many fields owing to their low cost and high reproducibility. Here, hydrogen (H2) detection was realized by applying palladium (Pd) nanoparticles (NPs) to electronic circuits printed on paper using a metal mask and a pencil. We confirmed that multilayered graphene was produced by the pencil, and then characterized Pd NPs were added to the pencil marks. To evaluate the gas-sensing ability of the sensor, its sensitivities and reaction rates in the presence and absence of H2 were measured. In addition, sensing tests performed over a wide range of H2 concentrations confirmed that the sensor had a detection limit as low as 1 ppm. Furthermore, the sensor reacted within approximately 50 s at all H2 concentrations tested. The recovery time of the sensor was 32 s at 1 ppm and 78 s at 1000 ppm. Sensing tests were also performed using Pd NPs of different sizes to elucidate the relationship between the sensing rate and catalyst size. The experimental results confirmed the possibility of fabricating paper-based gas sensors with a superior sensing capability and response rate.
A New Approach to the Assessment of the Reduction in Visibility Caused by Fires of Electrical Cables
Authors: Martinka Jozef , Rantuch Peter , Rolinec Marek , Pokorny Jiri , Balog Karol , Kucera Petr , Rybakowski Marek , Sulova Janka
Published: July 2019

Electricity is the most important form of household energy and one of the most important forms of energy for industry and transport. Electrical distribution in construction and transport is almost exclusively implemented using electrical cables. One of the unresolved problems associated with electrical cables is the release of smoke and the resulting reduction of visibility in case of fire in the area. In this study, a new approach was developed to assess the reduction of visibility in an area affected by an electrical cable fire. This approach is based on the determination of the critical ratio of smoke volume (in the smoke layer and exhausted from the fire compartment) to the length of the burning cable, through which the visibility of reflective and illuminated signs was reduced to a lower limit value (a standard of 10 m). The input data for this approach was the extinction area of the smoke released from one meter of burning cable and the length of the cables in the area. This approach was used to test two power cables (CHKE-V J3x1.5 and CHKE-R J3x1.5) and one signal cable J-H(St)H 1 × 2 × 0.8 with the B2ca, s1, d1, a1 fire reaction class. The smoke extinction area of the examined cables was determined using a cone calorimeter at a heat flux of 50 kW/m2. The obtained data showed that in order to maintain a visibility of 10 m for reflective signs, the critical ratio of smoke volume to length of burning cable was 7.5 m3/m. For illuminated signs, the critical ratio was 2.8 m3/m. The relationship between burning length and visibility allows the calculation of visibility in the fire compartment affected by cable fire only from cables length.
Data Fusion of Scanned Black and White Aerial Photographs with Multispectral Satellite Images
Authors: Kaimaris Dimitris , Patias Petros , Mallinis Giorgos , Georgiadis Charalampos
Published: July 2019

To date, countless satellite image fusions have been made, mainly with panchromatic spatial resolution to a multispectral image ratio of 1/4, fewer fusions with lower ratios, and relatively recently fusions with much higher spatial resolution ratios have been published. Apart from this, there is a small number of publications studying the fusion of aerial photographs with satellite images, with the year of image acquisition varying and the dates of acquisition not mentioned. In addition, in these publications, either no quantitative controls are performed on the composite images produced, or the aerial photographs are recent and colorful and only the RGB bands of the satellite images are used for data fusion purposes. The objective of this paper is the study of the addition of multispectral information from satellite images to black and white aerial photographs of the 2nd half of the 20th century (1950–1999) with small difference (just a few days) in their image acquisition date, the same year and season. Quantitative tests are performed in two case studies and the results are encouraging, as the accuracy of the classification of the features and objects of the Earth’s surface is improved and the automatic digital extraction of their form and shape from the archived aerial photographs is now allowed. This opens up a new field of use for the black and white aerial photographs and archived multispectral satellite images of the same period in a variety of applications, such as the temporal changes of cities, forests and archaeological sites.
Chronic Fish Oil Consumption with Resistance Training Improves Grip Strength, Physical Function, and Blood Pressure in Community-Dwelling Older Adults
Authors: Lee Sang-Rok , Jo Edward , Khamoui Andy V.
Published: July 2019

Fish oil (FO) has received great attention for its health-enhancing properties. However, its potential synergistic effects with resistance training (RT) are not well established. The purpose of this study was to investigate the effects of FO supplementation during 12-weeks of RT on handgrip strength, physical function, and blood pressure (BP) in community-dwelling older adults. Twenty-eight healthy older adults (10 males, 18 females; 66.5 ± 5.0 years) were randomly assigned to three groups: Control (CON), resistance training (RT), resistance training with FO (RTFO). Handgrip strength, physical function [five times sit-to-stand (5T-STS), timed up and go (TUG), 6-m walk (6MW), 30-s sit-to-stand (30S-STS)], and BP were measured pre- and post-intervention. ANOVA was used with significance set at P ≤ 0.05. Handgrip strength significantly increased in RT (+5.3%) and RTFO (+9.4%) but decreased in CON (−3.9%). All physical function outcomes increased in RT and RTFO. CON exhibited significantly decreased TUG and 30S-STS with no change in 5T-STS and 6MW. BP substantially decreased only in RTFO, systolic blood pressure (−7.8 mmHg), diastolic blood pressure (−4.5 mmHg), mean arterial pressure (−5.6 mmHg), while no change was found in CON and RT. Chronic RT enhanced strength and physical function, while FO consumption combined with RT improved BP in community-dwelling older adults.