bluuebunny/crossref_metadata_2025 huggingface dataset:
pH-Responsive Micelles Assembled by Three-Armed Degradable Block Copolymers with a Cholic Acid Core for Drug Controlled-Release
Authors: Feng Jingjie , Wen Weiqiu , Jia Yong-Guang , Liu Sa , Guo Jianwei
Published: March 2019

One of the most famous anticancer drugs, paclitaxel (PTX), has often been used in drug controlled-release studies. The polymers derived from bio-compound bile acids and degradable poly(ε-caprolactone) (PCL) form a reservoir and have been used as a drug delivery system with great advantages. Herein, we grafted poly(N,N-diethylaminoethyl methacrylate) and poly(poly(ethylene glycol) methyl ether methacrylate) into the bile acid-derived three-armed macroinitiator CA-(PCL)3, resulting in the amphiphilic block copolymers CA-(PCL-b-PDEAEMA-b-PPEGMA)3. These pH-responsive three-armed block copolymers self-assembled into micelles in aqueous solution and PTX was encapsulated into the micellar core to form PTX-loaded micelles with a drug loading of 29.92 wt %. The micelles were stable in PBS at pH 7.4 and showed a pH-triggered release behavior of PTX under acidic environments, in which 55% of PTX was released at pH 5.0 in 80 h. These cholic acid-based functionalized three-armed block polymers present good biocompatibility, showing great potential for drug controlled-release.
Study of Various Aqueous and Non-Aqueous Amine Blends for Hydrogen Sulfide Removal from Natural Gas
Authors: Shoukat Usman , Pinto Diego D. D. , Knuutila Hanna K.
Published: March 2019

Various novel amine solutions both in aqueous and non-aqueous [monoethylene glycol (MEG)/triethylene glycol(TEG)] forms have been studied for hydrogen sulfide (H2S) absorption. The study was conducted in a custom build experimental setup at temperatures relevant to subsea operation conditions and atmospheric pressure. Liquid phase absorbed H2S, and amine concentrations were measured analytically to calculate H2S loading (mole of H2S/mole of amine). Maximum achieved H2S loadings as the function of pKa, gas partial pressure, temperature and amine concentration are presented. Effects of solvent type on absorbed H2S have also been discussed. Several new solvents showed higher H2S loading as compared to aqueous N-Methyldiethanolamine (MDEA) solution which is the current industrial benchmark compound for selective H2S removal in natural gas sweetening process.
Application of Parameter Optimization to Search for Oscillatory Mass-Action Networks Using Python
Authors: Porubsky Veronica L. , Sauro Herbert M.
Published: March 2019

Biological systems can be described mathematically to model the dynamics of metabolic, protein, or gene-regulatory networks, but locating parameter regimes that induce a particular dynamic behavior can be challenging due to the vast parameter landscape, particularly in large models. In the current work, a Pythonic implementation of existing bifurcation objective functions, which reward systems that achieve a desired bifurcation behavior, is implemented to search for parameter regimes that permit oscillations or bistability. A differential evolution algorithm progressively approximates the specified bifurcation type while performing a global search of parameter space for a candidate with the best fitness. The user-friendly format facilitates integration with systems biology tools, as Python is a ubiquitous programming language. The bifurcation–evolution software is validated on published models from the BioModels Database and used to search populations of randomly-generated mass-action networks for oscillatory dynamics. Results of this search demonstrate the importance of reaction enrichment to provide flexibility and enable complex dynamic behaviors, and illustrate the role of negative feedback and time delays in generating oscillatory dynamics.
Holocene Carbon Burial in Lakes of the Uinta Mountains, Utah, USA
Authors: Munroe Jeffrey , Brencher Quinn
Published: March 2019

Recent research suggests that organic matter sequestered in lake sediment comprises a larger component of the global carbon cycle than once thought, yet little is known about carbon storage in mountain lakes. Here, we used a set of sediment cores collected from lakes in the Uinta Mountains (Utah, USA) to inform a series of calculations and extrapolations leading to estimates of carbon accumulation rates and total lacustrine carbon storage in this mountain range. Holocene rates of carbon accumulation in Uinta lakes are between 0.1 and 20.5 g/m2/yr, with an average of 5.4 g/m2/yr. These rates are similar to those reported for lakes in Greenland and Finland and are substantially lower than estimates for lakes in Alberta and Minnesota. The carbon content of modern sediments of seven lakes is notably elevated above long-term Holocene values, suggesting recent changes in productivity. The lakes of the Uintas have accumulated from 6 to 10 × 105 Mt of carbon over the Holocene. This is roughly equivalent to the annual carbon emissions from Salt Lake City, Utah. Based on their long-term Holocene rates, lakes in the Uintas annually sequester an amount of carbon equivalent to the emissions of <20 average Americans.
Church-State Separation and Challenging Issues Concerning Religion
Authors: Batalla Eric Vincent , Baring Rito
Published: March 2019

In its declaration of principles, the 1987 Philippine Constitution provides for the separation of Church and State. While the principle honors distinctions between temporal and spiritual functions, both Church and State maintain a unique and cooperative relationship geared towards the common good. However, traditional boundaries governing political and religious agency have been crossed during Duterte’s presidency causing a conflict between leaders of government and the Catholic hierarchy. In the process, the conflict has resurfaced issues about the principle of Church-State separation. What accounts for the changing Church-State relations in the Philippines? How will this conflict affect State policy towards religion, religious freedom, and religious education? In the present study we discuss the present context of the Church-State separation principle in the Philippines. We argue that institutional relations between Church and State remain stable despite the Duterte-Catholic Church conflict.
A Claim Forfeiting Its Own Right. Why Job Got It Wrong—and Why This Matters for the Rationality of Religion
Authors: Schulz Heiko
Published: March 2019

The article aims to uncover a deep ambivalence in the figure of Job, as it is presented in the book of the same title, especially in the latter’s “poetry” or dialogue section. This ambivalence corresponds to and in fact emerges from what appears to be a pragmatic paradox: Job is in the wrong (i.e., guilty) in relation to God, precisely by claiming to be right (i.e., innocent); conversely, he can be and must be considered right, if and to the extent that he honestly renounces the latter claim. Accordingly, he cannot both be right (or wrong) and claim to be right or (or wrong)—a special case of what is observed, within epistemology, as an incompatibility of truth and assertibility conditions. In the present text, this core thesis is developed in four steps: the first introduces and briefly contextualizes the claim; the second tries to demonstrate that it provides at least sufficient means for making narrative sense of the book as a whole and, in particular, the controversy between Job and his friends; a third paragraph tackles the (philosophical and/or theological) presuppositions and implications of the thesis from a Christian standpoint, whereas the conclusion addresses the question of if and how the previous findings bear upon the rationality issue. Here, a final paradox emerges: that which would appear to be most rational from a Christian perspective (the task of sin consciousness) must be deemed humanly impossible to fulfill; considering the latter possible renders the task futile, hence irrational.
Sufi and Bhakti Performers and Followers at the Margins of the Global South: Communication Strategies to Negotiate Situated Adversities
Authors: Dutta Uttaran
Published: March 2019

Throughout the globe (particularly in the global South), religious orthodoxy and their discriminatory intolerances are negatively impacting religious freedom of underserved populations, particularly those who practice/follow alternate spiritual praxis, like the Sufi and Bhakti performers from rural and geographically remote spaces of South Asia. Hindu and Islamic fundamentalist discourses/doctrines are propagating their conservative religious agendas and thereby creating tensions and separatism across the subcontinent. Such religious extremism is responsible for the threatening and even murdering of nonsectarian torchbearers, and their free thoughts. This study focused on various alternate communication strategies espoused by Sufi and bhakti performers and followers in order to negotiate and overcome their marginalized existence as well as to promote the plurality of voices and values in the society. This article identified the following communication strategies—innovative usages of language of inversion or enigmatic language; strategic camouflaging of authors’/writers’ identity, and intergenerational communication of discourses and spiritual values to ensure freedom and survival of their traditions.
Ziran: Authenticity or Authority?
Authors: Tadd Misha
Published: March 2019

This essay explores the core Daoist concept of ziran (commonly translated as spontaneity, naturalness, or self-so) and its relationship to authenticity and authority. Modern scholarship has often followed the interpretation of Guo Xiang (d. 312) in taking ziran as spontaneous individual authenticity completely unreliant on any external authority. This form of Daoism emphasizes natural transformations and egalitarian society. Here, the author draws on Heshanggong’s Commentary on the Daodejing to reveal a drastically dissimilar ziran conception based on the authority of the transcendent Way. The logic of this contrasting view of classical Daoism results not only in a vision of hierarchical society, but one where the ultimate state of human ziran becomes immortality. Expanding our sense of the Daodejing, this cosmology of authority helps unearths greater continuity of the text with Daoism’s later religious forms.
Correction: Yadav. K. and Congalton. R. Accuracy Assessment of Global Food Security-Support Analysis Data (GFSAD) Cropland Extent Maps Produced at Three Different Spatial Resolutions. Remote Sens. 2018, 10, 1800
Authors: Yadav Kamini , Congalton Russell G.
Published: March 2019

This research paper [...]
A Method for Landsat and Sentinel 2 (HLS) BRDF Normalization
Authors: Franch Belen , Vermote Eric , Skakun Sergii , Roger Jean-Claude , Masek Jeffrey , Ju Junchang , Villaescusa-Nadal Jose , Santamaria-Artigas Andres
Published: March 2019

The Harmonized Landsat/Sentinel-2 (HLS) project aims to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2 remote sensing satellites. These satellites’ sampling characteristics provide nearly constant observation geometry and low illumination variation through the scene. However, the illumination variation throughout the year impacts the surface reflectance by producing higher values for low solar zenith angles and lower reflectance for large zenith angles. In this work, we present a model to derive the bidirectional reflectance distribution function (BRDF) normalization and apply it to the HLS product at 30 m spatial resolution. It is based on the BRDF parameters estimated from the MODerate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (M{O,Y}D09) at 1 km spatial resolution using the VJB method (Vermote et al., 2009). Unsupervised classification (segmentation) of HLS images is used to disaggregate the BRDF parameters to the HLS spatial resolution and to build a BRDF parameters database at HLS scale. We first test the proposed BRDF normalization for different solar zenith angles over two homogeneous sites, in particular one desert and one Peruvian Amazon forest. The proposed method reduces both the correlation with the solar zenith angle and the coefficient of variation (CV) of the reflectance time series in the red and near infrared bands to 4% in forest and keeps a low CV of 3% to 4% for the deserts. Additionally, we assess the impact of the view zenith angle (VZA) in an area of the Brazilian Amazon forest close to the equator, where impact of the angular variation is stronger because it occurs in the principal plane. The directional reflectance shows a strong dependency with the VZA. The current HLS BRDF correction reduces this dependency but still shows an under-correction, especially in the near infrared, while the proposed method shows no dependency with the view angles. We also evaluate the BRDF parameters using field surface albedo measurements as a reference over seven different sites of the US surface radiation budget observing network (SURFRAD) and five sites of the Australian OzFlux network.
Object-Based Window Strategy in Thermal Sharpening
Authors: Xia Haiping , Chen Yunhao , Quan Jinling , Li Jing
Published: March 2019

The trade-off between spatial and temporal resolutions has led to the disaggregation of remotely sensed land surface temperatures (LSTs) for better applications. The window used for regression is one of the primary factors affecting the disaggregation accuracy. Global window strategies (GWSs) and local window strategies (LWSs) have been widely used and discussed, while object-based window strategies (OWSs) have rarely been considered. Therefore, this study presents an OWS based on a segmentation algorithm and provides a basis for selecting an optimal window size balancing both accuracy and efficiency. The OWS is tested with Landsat 8 data and simulated data via the “aggregation-then-disaggregation” strategy, and compared with the GWS and LWS. Results tested with the Landsat 8 data indicate that the proposed OWS can accurately and efficiently generate high-resolution LSTs. In comparison to the GWS, the OWS improves the mean accuracy by 0.19 K at different downscaling ratios, in particular by 0.30 K over urban areas; compared with the LWS, the OWS performs better in most cases but performs slightly worse due to the increasing downscaling ratio in some cases. Results tested with the simulated data indicate that the OWS is always superior to both GWS and LWS regardless of the downscaling ratios, and the OWS improves the mean accuracy by 0.44 K and 0.19 K in comparison to the GWS and LWS, respectively. These findings suggest the potential ability of the OWS to generate super-high-resolution LSTs over heterogeneous regions when the pixels within the object-based windows derived via segmentation algorithms are more homogenous.
Cluster Analysis Applied to Spatiotemporal Variability of Monthly Precipitation over Paraíba State Using Tropical Rainfall Measuring Mission (TRMM) Data
Authors: Santos Celso Augusto Guimarães , Brasil Neto Reginaldo Moura , da Silva Richarde Marques , Costa Samir Gonçalves Fernandes
Published: March 2019

In Paraíba state, precipitation is strongly affected by several climate systems, such as trade winds, the intertropical convergence zone (ITCZ), easterly wave disturbances (EWDs), and the South Atlantic subtropical high. Accordingly, the objective of this study was to analyze the spatiotemporal variability in precipitation to identify homogeneous trends of that variable and the effects of climate systems in Paraíba state by cluster analysis. The precipitation data used in this study derive from the Tropical Rainfall Measuring Mission (TRMM) satellite for the period from January 1998 to December 2015, and hierarchical clustering was used to classify the sites into different groups with similar trends. The findings show an uneven spatiotemporal precipitation distribution in all mesoregions of the state and considerable monthly precipitation variation in space. The estimated precipitation depth was highest in coastal regions and in high-altitude areas due to orographic precipitation. In general, the precipitation over Paraíba is characterized by strong gradients in the coastal zone towards the continent (Agreste, Borborema, and Sertão mesoregions) and from north to south due to the physiography of the region and the effects of climate systems with different time scales. Finally, the proposed clustering method using TRMM data was effective in characterizing climatic systems.
Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM
Authors: Dou Jie , Yunus Ali P. , Tien Bui Dieu , Sahana Mehebub , Chen Chi-Wen , Zhu Zhongfan , Wang Weidong , Thai Pham Binh
Published: March 2019

Landslides are typically triggered by earthquakes or rainfall occasionally a rainfall event followed by an earthquake or vice versa. Yet, most of the works presented in the past decade have been largely focused at the single event-susceptibility model. Such type of modeling is found insufficient in places where the triggering mechanism involves both factors such as one found in the Chuetsu region, Japan. Generally, a single event model provides only limited enlightenment of landslide spatial distribution and thus understate the potential combination-effect interrelation of earthquakes- and rainfall-triggered landslides. This study explores the both-effect of landslides triggered by Chuetsu-Niigata earthquake followed by a heavy rainfall event through examining multiple traditional statistical models and data mining for understanding the coupling effects. This paper aims to compare the abilities of the statistical probabilistic likelihood-frequency ratio (PLFR) model, information value (InV) method, certainty factors (CF), artificial neural network (ANN) and ensemble support vector machine (SVM) for the landslide susceptibility mapping (LSM) using high-resolution-light detection and ranging digital elevation model (LiDAR DEM). Firstly, the landslide inventory map including 8459 landslide polygons was compiled from multiple aerial photographs and satellite imageries. These datasets were then randomly split into two parts: 70% landslide polygons (5921) for training model and the remaining polygons for validation (2538). Next, seven causative factors were classified into three categories namely topographic factors, hydrological factors and geological factors. We then identified the associations between landslide occurrence and causative factors to produce LSM. Finally, the accuracies of five models were validated by the area under curves (AUC) method. The AUC values of five models vary from 0.77 to 0.87. Regarding the capability of performance, the proposed SVM is promising for constructing the regional landslide-prone potential areas using both types of landslides. Additionally, the result of our LSM can be applied for similar areas which have been experiencing both rainfall-earthquake landslides.
Multi-Level Classification Based on Trajectory Features of Time Series for Monitoring Impervious Surface Expansions
Authors: Wang Beibei , Chen Zhenjie , Zhu A-Xing , Hao Yuzhu , Xu Changqing
Published: March 2019

As urbanization has profound effects on global environmental changes, quick and accurate monitoring of the dynamic changes in impervious surfaces is of great significance for environmental protection. The increased spatiotemporal resolution of imagery makes it possible to construct time series to obtain long-time-period and high-accuracy information about impervious surface expansion. In this study, a three-step monitoring method based on time series trajectory segmentation was developed to extract impervious surface expansion using Landsat time series and was applied to the Xinbei District, Changzhou, China, from 2005 to 2017. Firstly, the original time series was segmented and fitted to remove the noise caused by clouds, shadows, and interannual differences, leaving only the trend information. Secondly, the time series trajectory features of impervious surface expansion were described using three phases and four types with nine parameters by analyzing the trajectory characteristics. Thirdly, a multi-level classification method was used to determine the scope of impervious surface expansion, and the expansion time was superimposed to obtain a spatiotemporal distribution map. The proposed method yielded an overall accuracy of 90.58% and a Kappa coefficient of 0.90, demonstrating that Landsat time series remote sensing images could be used effectively in this approach to monitor the spatiotemporal expansion of impervious surfaces.
Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning
Authors: Safonova Anastasiia , Tabik Siham , Alcaraz-Segura Domingo , Rubtsov Alexey , Maglinets Yuriy , Herrera Francisco
Published: March 2019

Invasion of the Polygraphus proximus Blandford bark beetle causes catastrophic damage to forests with firs (Abies sibirica Ledeb) in Russia, especially in Central Siberia. Determining tree damage stage based on the shape, texture and colour of tree crown in unmanned aerial vehicle (UAV) images could help to assess forest health in a faster and cheaper way. However, this task is challenging since (i) fir trees at different damage stages coexist and overlap in the canopy, (ii) the distribution of fir trees in nature is irregular and hence distinguishing between different crowns is hard, even for the human eye. Motivated by the latest advances in computer vision and machine learning, this work proposes a two-stage solution: In a first stage, we built a detection strategy that finds the regions of the input UAV image that are more likely to contain a crown, in the second stage, we developed a new convolutional neural network (CNN) architecture that predicts the fir tree damage stage in each candidate region. Our experiments show that the proposed approach shows satisfactory results on UAV Red, Green, Blue (RGB) images of forest areas in the state nature reserve “Stolby” (Krasnoyarsk, Russia).
Multi-Feature Manifold Discriminant Analysis for Hyperspectral Image Classification
Authors: Huang Hong , Li Zhengying , Pan Yinsong
Published: March 2019

Hyperspectral image (HSI) provides both spatial structure and spectral information for classification, but many traditional methods simply concatenate spatial features and spectral features together that usually lead to the curse-of-dimensionality and unbalanced representation of different features. To address this issue, a new dimensionality reduction (DR) method, termed multi-feature manifold discriminant analysis (MFMDA), was proposed in this paper. At first, MFMDA explores local binary patterns (LBP) operator to extract textural features for encoding the spatial information in HSI. Then, under graph embedding framework, the intrinsic and penalty graphs of LBP and spectral features are constructed to explore the discriminant manifold structure in both spatial and spectral domains, respectively. After that, a new spatial-spectral DR model for multi-feature fusion is built to extract discriminant spatial-spectral combined features, and it not only preserves the similarity relationship between spectral features and LBP features but also possesses strong discriminating ability in the low-dimensional embedding space. Experiments on Indian Pines, Heihe and Pavia University (PaviaU) hyperspectral data sets demonstrate that the proposed MFMDA method performs significantly better than some state-of-the-art methods using only single feature or simply stacking spectral features and spatial features together, and the classification accuracies of it can reach 95.43%, 97.19% and 96.60%, respectively.
Novel Aerial Manipulator for Accurate and Robust Industrial NDT Contact Inspection: A New Tool for the Oil and Gas Inspection Industry
Authors: Trujillo Miguel Ángel , Martínez-de Dios José Ramiro , Martín Carlos , Viguria Antidio , Ollero Aníbal
Published: March 2019

There is a strong demand in the oil and gas industry to develop alternatives to manual inspection. This paper presents AeroX, a novel aerial robotic manipulator that provides physical contact inspection with unprecedented capabilities. AeroX has a semi-autonomous operation, which provides interesting advantages in contact inspection. In the free-flight mode, the pilot guides the robot until performing contact with its end-effector on the surface to be inspected. During contact, AeroX is in its fully-autonomous global navigation satellite system (GNSS)-free contact–flight mode, in which the robot keeps its relative position w.r.t. the surface contact point using only its internal sensors. During autonomous flight, the inspector can move—with uninterrupted contact—the end-effector on the surface for accurately selecting the points where to perform A-scan measurements or continuous B-scan or C-scan inspections. AeroX adopts an eight-tilted rotor configuration and a simple and efficient design, which provides high stability, maneuverability, and robustness to rotor failure. It can perform contact inspection on surfaces at any orientation, including vertical, inclined, horizontal-top or horizontal-bottom, and its operation can be easily integrated into current maintenance operations in many industries. It has been extensively validated in outdoor experiments including a refinery and has been awarded the EU Innovation Radar Prize 2017.
Multi-Vehicle Tracking via Real-Time Detection Probes and a Markov Decision Process Policy
Authors: Zou Yi , Zhang Weiwei , Weng Wendi , Meng Zhengyun
Published: March 2019

Online multi-object tracking (MOT) has broad applications in time-critical video analysis scenarios such as advanced driver-assistance systems (ADASs) and autonomous driving. In this paper, the proposed system aims at tracking multiple vehicles in the front view of an onboard monocular camera. The vehicle detection probes are customized to generate high precision detection, which plays a basic role in the following tracking-by-detection method. A novel Siamese network with a spatial pyramid pooling (SPP) layer is applied to calculate pairwise appearance similarity. The motion model captured from the refined bounding box provides the relative movements and aspects. The online-learned policy treats each tracking period as a Markov decision process (MDP) to maintain long-term, robust tracking. The proposed method is validated in a moving vehicle with an onboard NVIDIA Jetson TX2 and returns real-time speeds. Compared with other methods on KITTI and self-collected datasets, our method achieves significant performance in terms of the “Mostly-tracked”, “Fragmentation”, and “ID switch” variables.
Magnetometer-Based Drift Correction During Rest in IMU Arm Motion Tracking
Authors: Wittmann Frieder , Lambercy Olivier , Gassert Roger
Published: March 2019

Real-time motion capture of the human arm in the home environment has many use cases, such as video game and therapy applications. The required tracking can be based on off-the-shelf Inertial Measurement Units (IMUs) with integrated three-axis accelerometers, gyroscopes, and magnetometers. However, this usually requires a homogeneous magnetic field to correct for orientation drift, which is often not available inside buildings. In this paper, RPMC (Rest Pose Magnetometer-based drift Correction), a novel method that is robust to long term drift in environments with inhomogeneous magnetic fields, is presented. The sensor orientation is estimated by integrating the angular velocity measured by the gyroscope and correcting drift around the pitch and roll axes with the acceleration information. This commonly leads to short term drift around the gravitational axis. Here, during the calibration phase, the local magnetic field direction for each sensor, and its orientation relative to the inertial frame, are recorded in a rest pose. It is assumed that arm movements in free space are exhausting and require regular rest. A set of rules is used to detect when the user has returned to the rest pose, to then correct for the drift that has occurred with the magnetometer. Optical validations demonstrated accurate (root mean square error R M S = 6.1 °), low latency ( 61 m s ) tracking of the user’s wrist orientation, in real time, for a full hour of arm movements. The reduction in error relative to three alternative methods implemented for comparison was between 82.5 % and 90.7 % for the same movement and environment. Therefore, the proposed arm tracking method allows for the correction of orientation drift in an inhomogeneous magnetic field by exploiting the user’s need for frequent rest.
Towards Void Hole Alleviation by Exploiting the Energy Efficient Path and by Providing the Interference-Free Proactive Routing Protocols in IoT Enabled Underwater WSNs
Authors: Awais Muhammad , Javaid Nadeem , Rehman Amjad , Qasim Umar , Alhussein Musaed , Aurangzeb Khursheed
Published: March 2019

Nowadays, the Internet of Things enabled Underwater Wireless Sensor Network (IoT-UWSN) is suffering from serious performance restrictions, i.e., high End to End (E2E) delay, low energy efficiency, low data reliability, etc. The necessity of efficient, reliable, collision and interference-free communication has become a challenging task for the researchers. However, the minimum Energy Consumption (EC) and low E2E delay increase the performance of the IoT-UWSN. Therefore, in the current work, two proactive routing protocols are presented, namely: Bellman–Ford Shortest Path-based Routing (BF-SPR-Three) and Energy-efficient Path-based Void hole and Interference-free Routing (EP-VIR-Three). Then we formalized the aforementioned problems to accomplish the reliable data transmission in Underwater Wireless Sensor Network (UWSN). The main objectives of this paper include minimum EC, interference-free transmission, void hole avoidance and high Packet Delivery Ratio (PDR). Furthermore, the algorithms for the proposed routing protocols are presented. Feasible regions using linear programming are also computed for optimal EC and to enhance the network lifespan. Comparative analysis is also performed with state-of-the-art proactive routing protocols. In the end, extensive simulations have been performed to authenticate the performance of the proposed routing protocols. Results and discussion disclose that the proposed routing protocols outperformed the counterparts significantly.
Dynamic Assessment of Masonry Towers Based on Terrestrial Radar Interferometer and Accelerometers
Authors: Castagnetti Cristina , Bassoli Elisa , Vincenzi Loris , Mancini Francesco
Published: March 2019

This paper discusses the performance of a terrestrial radar interferometer for the structural monitoring of ancient masonry towers. High-speed radar interferometry is an innovative and powerful remote sensing technique for the dynamic monitoring of large structures since it is contactless, non-destructive, and able to measure fast displacements on the order of tenths of millimeters. This methodology was tested on a masonry tower of great historical interest, the Saint Prospero bell tower (Northern Italy). To evaluate the quality of the results, data collected from the interferometer were compared and validated with those provided by two types of accelerometer-based measuring systems directly installed on the tower. Dynamic tests were conducted in operational conditions as well as during a bell concert. The first aimed at characterizing the dynamic behavior of the tower, while the second allowed to evaluate the bell swinging effects. Results showed a good agreement among the different measuring systems and demonstrated the potential of the radar interferometry for the dynamic monitoring of structures, with special focus on the need for an accurate design of the geometric aspects of the surveys.
Temperature-Dependent Resistive Properties of Vanadium Pentoxide/Vanadium Multi-Layer Thin Films for Microbolometer & Antenna-Coupled Microbolometer Applications
Authors: Abdel-Rahman Mohamed , Zia Muhammad , Alduraibi Mohammad
Published: March 2019

In this study, vanadium oxide (VxOy) semiconducting resistive thermometer thin films were developed, and their temperature-dependent resistive behavior was examined. Multilayers of 5-nm-thick vanadium pentoxide (V2O5) and 5-nm-thick vanadium (V) films were alternately sputter-deposited, at room temperature, to form 105-nm-thick VxOy films, which were post-deposition annealed at 300 °C in O2 and N2 atmospheres for 30 and 40 min. The synthesized VxOy thin films were then patterned into resistive thermometer structures, and their resistance versus temperature (R-T) characteristics were measured. Samples annealed in O2 achieved temperature coefficients of resistance (TCRs) of −3.0036 and −2.4964%/K at resistivity values of 0.01477 and 0.00819 Ω·cm, respectively. Samples annealed in N2 achieved TCRs of −3.18 and −1.1181%/K at resistivity values of 0.04718 and 0.002527 Ω·cm, respectively. The developed thermometer thin films had TCR/resistivity properties suitable for microbolometer and antenna-coupled microbolometer applications. The employed multilayer synthesis technique was shown to be effective in tuning the TCR/resistivity properties of the thin films by varying the annealing conditions.
Detection of Glaze Icing Load and Temperature of Composite Insulators Using Fiber Bragg Grating
Authors: Wei Jie , Hao Yanpeng , Fu Yuan , Yang Lin , Gan Jiulin , Yang Zhongmin
Published: March 2019

Conventional methods for the online monitoring of icing conditions of composite insulators suffer from difficulties. To solve this issue, a novel method is first proposed to detect glaze icing load via embedding three optical fibers with fiber Bragg gratings (FBGs) into a 10 kV composite insulator. Specifically, FBG temperature compensation sensors were packaged in ceramic tubes to solve strain and temperature cross-sensitivity. Temperature effect experiments and simulated glaze icing load experiments were performed to verify the feasibility of the proposed method. The results show that temperature sensitivities of all FBGs are identical (i.e., 10.68 pm/°C), which achieves a simultaneous measurement of temperature and strain. In addition, the proposed method can detect glaze icing load of the composite insulator above 0.5 N (i.e., 15% of icicle bridged degree) in the laboratory.
Monitoring Pilot’s Mental Workload Using ERPs and Spectral Power with a Six-Dry-Electrode EEG System in Real Flight Conditions
Authors: Dehais Frédéric , Duprès Alban , Blum Sarah , Drougard Nicolas , Scannella Sébastien , Roy Raphaëlle N. , Lotte Fabien
Published: March 2019

Recent technological progress has allowed the development of low-cost and highly portable brain sensors such as pre-amplified dry-electrodes to measure cognitive activity out of the laboratory. This technology opens promising perspectives to monitor the “brain at work” in complex real-life situations such as while operating aircraft. However, there is a need to benchmark these sensors in real operational conditions. We therefore designed a scenario in which twenty-two pilots equipped with a six-dry-electrode EEG system had to perform one low load and one high load traffic pattern along with a passive auditory oddball. In the low load condition, the participants were monitoring the flight handled by a flight instructor, whereas they were flying the aircraft in the high load condition. At the group level, statistical analyses disclosed higher P300 amplitude for the auditory target (Pz, P4 and Oz electrodes) along with higher alpha band power (Pz electrode), and higher theta band power (Oz electrode) in the low load condition as compared to the high load one. Single trial classification accuracy using both event-related potentials and event-related frequency features at the same time did not exceed chance level to discriminate the two load conditions. However, when considering only the frequency features computed over the continuous signal, classification accuracy reached around 70% on average. This study demonstrates the potential of dry-EEG to monitor cognition in a highly ecological and noisy environment, but also reveals that hardware improvement is still needed before it can be used for everyday flight operations.
Enhanced Electrochemical Response of Diclofenac at a Fullerene–Carbon Nanofiber Paste Electrode
Authors: Motoc Sorina , Manea Florica , Orha Corina , Pop Aniela
Published: March 2019

The requirements of the Water Framework Directive to monitor diclofenac (DCF) concentration in surface water impose the need to find advanced fast and simple analysis methods. Direct voltammetric/amperometric methods could represent efficient and practical solutions. Fullerene–carbon nanofibers in paraffin oil as a paste electrode (F–CNF) was easily obtained by simple mixing and tested for DCF detection using voltammetric and amperometric techniques. The lowest limit of detection of 0.9 nM was achieved by applying square-wave voltammetry operated under step potential (SP) of 2 mV, modulation amplitude (MA) of 10 mV, and frequency of 25 Hz, and the best sensitivity was achieved by four-level multiple pulsed amperometry (MPA) that allowed in situ reactivation of the F–CNF electrode. The selection of the method must take into account the environmental quality standard (EQS), imposed through the “watchlist” of the Water Framework Directive as 0.1 µg·L−1 DCF. A good improvement of the electroanalytical parameters for DCF detection on the F–CNF electrode was achieved by applying the preconcentration step for 30 min before the detection step, which assured about 30 times better sensitivity, recommending its application for the monitoring of trace levels of DCF. The electrochemical behavior of F–CNF as a pseudomicroelectrode array makes it suitable for practical application in the in situ and real-time monitoring of DCF concentrations in water.
Absolute Radiometric Calibration of TESS-W and SQM Night Sky Brightness Sensors
Authors: Bará Salvador , Tapia Carlos E. , Zamorano Jaime
Published: March 2019

We develop a general optical model and describe the absolute radiometric calibration of the readings provided by two widely-used night sky brightness sensors based on irradiance-to-frequency conversion. The calibration involves the precise determination of the overall spectral sensitivity of the devices and also the constant G relating the output frequency of the light-to-frequency converter chip to the actual band-weighted and field-of-view averaged spectral radiance incident on the detector (brightness). From these parameters, we show how to define a rigorous astronomical absolute photometric system in which the sensor measurements can be reported in units of magnitudes per square arcsecond with precise physical meaning.
Communication Rate Increase in Drill Strings of Oil and Gas Wells Using Multiple Actuators
Authors: Zhang Erjian , Abdi Ali
Published: March 2019

Wireless data communication and telemetry during drilling deep oil and gas wells are important enablers for safe and timely drilling operations. The transmission of information through drill strings and pipes using sound waves is a useful and practical approach. However, given the limited available bandwidth, transmission rates are typically smaller than what is needed. In this paper, a new method and system are proposed to increase the transmission rate over the same bandwidth, by deploying more than one actuator. Upon using multiple actuators, several data streams can be transmitted simultaneously. This increases the data rate without the need for additional bandwidth. The experimental results of a testbed with two actuators are presented, where the transmission rate is doubled with no bandwidth increase. A strain sensor receiver and accelerometer receivers are used to separate and demodulate the two data streams. It is demonstrated that it is possible to recover the data in the new faster system benefiting from two actuators, while having about the same bit error probability performance as a one-actuator system. Various combinations of strain and acceleration sensors are considered at the receive side. Due to some properties of strain channels (e.g., smaller delay spreads and their less-frequency-selective behavior) presented in this paper, it appears that a strain sensor receiver and an accelerometer receiver together can offer a good performance when separating and demodulating the two actuators’ data in the testbed. Overall, the experimental results from the proposed system suggest that upon using more than one actuator, it is feasible to increase the data rate over the limited bandwidth of pipes and drill strings.
Measuring the Wave Height Based on Binocular Cameras
Authors: Cang Yan , He Hengxiang , Qiao Yulong
Published: March 2019

The wave is an important hydrological element in marine research. Accurately describing the characteristics of waves is therefore significant to the study of marine power. The contents of this article are as follows: (1) a wave height measurement system using binocular cameras is proposed, and the small tank experiments are conducted to prove the efficacy of the proposed system; (2) based on the scale invariant feature transition (SIFT) algorithm, sub-pixel Harris corners are calculated in the difference-of-Gaussian (DOG) space to locate key points more accurately; and (3) a bi-directional epipolar constraint is employed to decrease the mismatch rate and computation time.
A First-Order Differential Data Processing Method for Accuracy Improvement of Complementary Filtering in Micro-UAV Attitude Estimation
Authors: Wen Xudong , Liu Chunwu , Huang Zhiping , Su Shaojing , Guo Xiaojun , Zuo Zhen , Qu Hao
Published: March 2019

There are many algorithms that can be used to fuse sensor data. The complementary filtering algorithm has low computational complexity and good real-time performance characteristics. It is very suitable for attitude estimation of small unmanned aerial vehicles (micro-UAVs) equipped with low-cost inertial measurement units (IMUs). However, its low attitude estimation accuracy severely limits its applications. Though, many methods have been proposed by researchers to improve attitude estimation accuracy of complementary filtering algorithms, there are few studies that aim to improve it from the data processing aspect. In this paper, a real-time first-order differential data processing algorithm is proposed for gyroscope data, and an adaptive adjustment strategy is designed for the parameters in the algorithm. Besides, the differential-nonlinear complementary filtering (D-NCF) algorithm is proposed by combine the first-order differential data processing algorithm with the basic nonlinear complementary filtering (NCF) algorithm. The experimental results show that the first-order differential data processing algorithm can effectively correct the gyroscope data, and the Root Mean Square Error (RMSE) of attitude estimation of the D-NCF algorithm is smaller than when the NCF algorithm is used. The RMSE of the roll angle decreases from 1.1653 to 0.5093, that of the pitch angle decreases from 2.9638 to 1.5542, and that of the yaw angle decreases from 0.9398 to 0.6827. In general, the attitude estimation accuracy of D-NCF algorithm is higher than that of the NCF algorithm.
VisNet: Deep Convolutional Neural Networks for Forecasting Atmospheric Visibility
Authors: Palvanov Akmaljon , Cho Young Im
Published: March 2019

Visibility is a complex phenomenon inspired by emissions and air pollutants or by factors, including sunlight, humidity, temperature, and time, which decrease the clarity of what is visible through the atmosphere. This paper provides a detailed overview of the state-of-the-art contributions in relation to visibility estimation under various foggy weather conditions. We propose VisNet, which is a new approach based on deep integrated convolutional neural networks for the estimation of visibility distances from camera imagery. The implemented network uses three streams of deep integrated convolutional neural networks, which are connected in parallel. In addition, we have collected the largest dataset with three million outdoor images and exact visibility values for this study. To evaluate the model’s performance fairly and objectively, the model is trained on three image datasets with different visibility ranges, each with a different number of classes. Moreover, our proposed model, VisNet, evaluated under dissimilar fog density scenarios, uses a diverse set of images. Prior to feeding the network, each input image is filtered in the frequency domain to remove low-level features, and a spectral filter is applied to each input for the extraction of low-contrast regions. Compared to the previous methods, our approach achieves the highest performance in terms of classification based on three different datasets. Furthermore, our VisNet considerably outperforms not only the classical methods, but also state-of-the-art models of visibility estimation.
Sensing by Molecularly Imprinted Polymer: Evaluation of the Binding Properties with Different Techniques
Authors: Pesavento Maria , Marchetti Simone , De Maria Letizia , Zeni Luigi , Cennamo Nunzio
Published: March 2019

The possibility of investigating the binding properties of the same molecularly imprinted polymer (MIP), most probably heterogeneous, at various concentration levels by different methods such as batch equilibration and sensing, is examined, considering two kinds of sensors, based respectively on electrochemical and surface plasmon resonance (SPR) transduction. As a proof of principle, the considered MIP was obtained by non-covalent molecular imprinting of 2-furaldehyde (2-FAL). It has been found that different concentration ranges of 2-FAL in aqueous matrices can be measured by the two sensing methods. The SPR sensor responds in a concentration range from 1 × 10−4 M down to about 1 × 10−7 M, while the electrochemical sensor from about 5 × 10−6 M up to about 9 × 10−3 M. The binding isotherms have been fit to the Langmuir adsorption model, in order to evaluate the association constant. Three kinds of sites with different affinity for 2-FAL have been detected. The sites at low affinity are similar to the interaction sites of the corresponding NIP since they have a similar association constant. This is near to the affinity evaluated by batch equilibration too. The same association constant has been evaluated in the same concentration range. The sensing methods have been demonstrated to be very convenient for the characterization of the binding properties of MIP in comparison to the batch equilibration, in terms of reproducibility and low amount of material required for the investigation.