bluuebunny/crossref_metadata_2025 huggingface dataset:
Compounding Plasmon–Exciton Strong Coupling System with Gold Nanofilm to Boost Rabi Splitting
Authors: Song Tingting , Chen Zhanxu , Zhang Wenbo , Lin Limin , Bao Yanjun , Wu Lin , Zhou Zhang-Kai
Published: April 2019

Various plasmonic nanocavities possessing an extremely small mode volume have been developed and applied successfully in the study of strong light-matter coupling. Driven by the desire of constructing quantum networks and other functional quantum devices, a growing trend of strong coupling research is to explore the possibility of fabricating simple strong coupling nanosystems as the building blocks to construct complex systems or devices. Herein, we investigate such a nanocube-exciton building block (i.e. AuNC@J-agg), which is fabricated by coating Au nanocubes with excitonic J-aggregate molecules. The extinction spectra of AuNC@J-agg assembly, as well as the dark field scattering spectra of the individual nanocube-exciton, exhibit Rabi splitting of 100–140 meV, which signifies strong plasmon–exciton coupling. We further demonstrate the feasibility of constructing a more complex system of AuNC@J-agg on Au film, which achieves a much stronger coupling, with Rabi splitting of 377 meV. This work provides a practical pathway of building complex systems from building blocks, which are simple strong coupling systems, which lays the foundation for exploring further fundamental studies or inventing novel quantum devices.
Pd Nanocatalyst Adorning Coral Reef Nanocomposite for the Synthesis of Nitriles: Utility of Cucurbita pepo Leaf Extract as a Stabilizing and Reducing Agent
Authors: Nasrollahzadeh Mahmoud , Ghorbannezhad Fatemeh , Sajadi S. , Varma Rajender
Published: April 2019

A simple procedure for the palladium-catalyzed cyanation of aryl halides is described via a nucleophilic non-toxic cyanide source, K4[Fe(CN)6] in the presence of Pd/coral reef nanocomposite as a heterogeneous catalyst; the protocol provides a useful and easy method for the synthesis of aryl nitriles that are generated from the corresponding variant aryl halides, with sodium carbonate as a base. The nanocatalyst was prepared by a biological process using aqueous extract of leaves of Cucurbita pepo as a stabilizing and reducing agent and coral reef as a natural support, without deploying any hazardous chemicals. The catalyst, that is easily separable from the reaction mixture and reused multiple times, was characterized by FT-IR (Fourier-Transform Infrared Spectroscopy), ICP-AES (Inductively Coupled Plasma Atomic Emission Spectroscopy), XRD (X-ray Diffraction), TEM (Transmission Electron Microscopy), FE-SEM (Field Emission Scanning Electron Microscopy), EDS (Energy Dispersive X-ray Spectroscopy) and elemental mapping.
Preparation of CdTe/Alginate Textile Fibres with Controllable Fluorescence Emission through a Wet-Spinning Process and Application in the Trace Detection of Hg2+ Ions
Authors: Zhao Zhihui , Geng Cunzhen , Zhao Xihui , Xue Zhixin , Quan Fengyu , Xia Yanzhi
Published: April 2019

Fluorescent textile fibres (FTFs) are widely used in many industrial fields. However, in addition to fibres with good fluorescence, fibres with excellent colour controllability, structural stability and appropriate mechanical strength still need to be developed. In this work, CdTe/alginate composite FTFs are prepared by taking advantage of the interactions between CdTe nanocrystals (NCs) and alginate macromolecules via a wet-spinning machine with a CaCl2 aqueous solution as the coagulation bath. CdTe NCs were chemically fixed in the fibre due to the interactions among surface ligands, macromolecules and coagulators (calcium ions), which ensured the excellent dispersity and good stability of the fibres. Förster resonance energy transfer (FRET) between NCs in the fibre was found to be restricted, which means that the emission colour of the fibres was totally controllable and could be predicted. Other properties of alginate fibres, such as flame retardance and mechanical strength, were also well preserved in the fluorescent fibres. Finally, FTFs showed good selectivity toward trace Hg2+ ions over other metallic ions, and the detection could be identified by the naked eye.
Synthesis Procedure of Highly Densely Packed Carbon Nanotube Forests on TiN
Authors: Campo Teresa , Pinilla Sergio , Gálvez Santos , Sanz José María , Márquez Francisco , Morant Carmen
Published: April 2019

The goal of this research was to obtain high-density single-walled carbon nanotube forests (SWNTs) on conductive substrates for different applications, including field emission. For this, dip-coating was chosen as the catalyst deposition method, to subsequently grow SWNTs by Alcohol Catalytic Chemical Vapor Deposition (AC-CVD). Si (100) was chosen as the substrate, which was then coated with a TiN thin film. By sputtering with Ar, it was possible to generate alternating TiN and Si lanes, with a different wettability and, therefore, a different affinity for the catalysts. As a result, the Mo-Co catalyst was mainly deposited on TiN and not on sputtered-Si, which allowed the selective growth of SWNT forests on the TiN conductive surfaces. These as-synthesized SWNTs were used for field emission measurements in a high vacuum chamber.
Suicide Gene Therapy By Amphiphilic Copolymer Nanocarrier for Spinal Cord Tumor
Authors: Gwak So-Jung , Lee Jeoung Soo
Published: April 2019

Spinal cord tumors (SCT) are uncommon neoplasms characterized by irregular growth of tissue inside the spinal cord that can result in non-mechanical back pain. Current treatments for SCT include surgery, radiation therapy, and chemotherapy, but these conventional therapies have many limitations. Suicide gene therapy using plasmid encoding herpes simplex virus-thymidine kinase (pHSV-TK) and ganciclovir (GCV) has been an alternative approach to overcome the limitations of current therapies. However, there is a need to develop a carrier that can deliver both pHSV-TK and GCV for improving therapeutic efficacy. Our group developed a cationic, amphiphilic copolymer, poly (lactide-co-glycolide) -graft-polyethylenimine (PgP), and demonstrated its efficacy as a drug and gene carrier in both cell culture studies and animal models. In this study, we evaluated PgP as a gene carrier and demonstrate that PgP can efficiently deliver reporter genes, pGFP in rat glioma (C6) cells in vitro, and pβ-gal in a rat T5 SCT model in vivo. We also show that PgP/pHSV-TK with GCV treatment showed significantly higher anticancer activity in C6 cells compared to PgP/pHSV-TK without GCV treatment. Finally, we demonstrate that PgP/pHSV-TK with GCV treatment increases the suicide effect and apoptosis of tumor cells and reduces tumor size in a rat T5 SCT model.
Analysis of Association between Vitamin D Deficiency and Insulin Resistance
Authors: Szymczak-Pajor Izabela , Śliwińska Agnieszka
Published: April 2019

Recent evidence revealed extra skeleton activity of vitamin D, including prevention from cardiometabolic diseases and cancer development as well as anti-inflammatory properties. It is worth noting that vitamin D deficiency is very common and may be associated with the pathogenesis of insulin-resistance-related diseases, including obesity and diabetes. This review aims to provide molecular mechanisms showing how vitamin D deficiency may be involved in the insulin resistance formation. The PUBMED database and published reference lists were searched to find studies published between 1980 and 2019. It was identified that molecular action of vitamin D is involved in maintaining the normal resting levels of ROS and Ca2+, not only in pancreatic β-cells, but also in insulin responsive tissues. Both genomic and non-genomic action of vitamin D is directed towards insulin signaling. Thereby, vitamin D reduces the extent of pathologies associated with insulin resistance such as oxidative stress and inflammation. More recently, it was also shown that vitamin D prevents epigenetic alterations associated with insulin resistance and diabetes. In conclusion, vitamin D deficiency is one of the factors accelerating insulin resistance formation. The results of basic and clinical research support beneficial action of vitamin D in the reduction of insulin resistance and related pathologies.
Evaluation of the Larvicidal Potential of the Essential Oil Pogostemon cablin (Blanco) Benth in the Control of Aedes aegypti
Authors: Lima Santos Lizandra , Barreto Brandão Lethicia , Lopes Martins Rosany , de Menezes Rabelo Erica , Lobato Rodrigues Alex , da Conceição Vieira Araújo Camila , Fernandes Sobral Talita , Ribeiro Galardo Allan , Moreira da Silva de Ameida Sheylla
Published: April 2019

The objective of this work was to collect information on the chemical constituents that demonstrate the larvicidal activity against Aedes aegypti, as well as the antioxidant, microbiological, and cytotoxicity potential of the essential oil of Pogostemon cablin leaves. The chemical characterization was performed by gas chromatography coupled to mass spectrometer (GC-MS). The larvicidal activity was performed according to the protocol of the World Health Organization. The antioxidant activity was evaluated through the sequestering capacity of 2,2-diphenyl-1-picryl-hydrazine (DPPH). As for the microbiological evaluation, the microdilution technique was used, according to the protocol of the Clinical and Laboratory Standards Institute. The cytotoxic activity was evaluated against the larvae of Artemia salina. The species P. cablin presented the following compounds: Patchouli alcohol (33.25%), Seyshellene (6.12%), α-bulnesene (4.11%), Pogostol (6.33%), and Norpatchoulenol (5.72%), which was in synergy with the other substances may significantly potentiate the larvicidal action of the species with the LC50 of 28.43 μg·mL−1. There was no antioxidant activity, however, it presented antimicrobial activity against all bacteria tested with Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of 62.5 μg·mL−1. The species demonstrated significant toxic action with LC50 of 24.25 μg·mL−1. Therefore, the P. cablin species showed significant larvicidal potential, antimicrobial activity, the absence of antioxidant action, and high toxicity.
LED-Cured Reflection Gratings Stored in an Acrylate-Based Photopolymer
Authors: Ramírez Manuel , Sirvent Daniel , Morales-Vidal Marta , Ortuño Manuel , Martínez-Guardiola Francisco , Francés Jorge , Pascual Inmaculada
Published: April 2019

The storage of volume holographic reflection gratings in low-toxicity photopolymers represents a challenge at present since they can be used in many important applications such as biosensors and holographic optical elements. In this context, an acrylate-based photopolymer developed in our research group was employed to study the recording of unslanted holographic reflection gratings at high spatial frequencies. The optimal preparation conditions of the photopolymer layers were determinated. The diffraction efficiencies are measured in both recording and curing stage and a comparative study of these values was realized. In addition, a theoretical study using Kogelnik’s coupled wave theory was carried out with the aim of understanding the diffraction efficiency behaviour of both processes. In this work, a maximum diffraction efficiency of 14.1% was reached after a curing process in 150 µm layers at a recording wavelength of 488 nm. This value represents a good result compared to that reported in the literature and opens the way to reflection mode holography research using low-toxicity material.
Simulation Studies on the Effect of Material Characteristics and Runners Layout Geometry on the Filling Imbalance in Geometrically Balanced Injection Molds
Authors: Wilczyński Krzysztof , Narowski Przemysław
Published: April 2019

Simulation studies were performed on filling imbalance in geometrically balanced injection molds. A special simulation procedure was applied to simulate properly the phenomenon, including inertia effects and 3D tetrahedron meshing as well as meshing of the nozzle. The phenomenon was investigated by simulation using several different runner systems at various thermo-rheological material parameters and process operating conditions. It has been observed that the Cross-WLF parameters, index flow, critical shear stress (relaxation time), and zero viscosity, as well as thermal diffusivity and heat transfer coefficient strongly affect the filling imbalance. The effect is substantially dependent on the runners’ layout geometry, as well as on the operating conditions, flow rate, and shear rate. The standard layout geometry and the corrected layout with circled element induce positive imbalance which means that inner cavities fills out faster, and it is opposite for the corrected layouts with one/two overturn elements which cause negative imbalance. Generally, for the standard layout geometry and the corrected layout with circled element, an effect of the zero shear rate viscosity η0 is positive (imbalance increases with an increase of viscosity), and an effect of the power law index n and the relaxation time λ is negative (imbalance decreases with an increase of index n and relaxation time λ). An effect of the thermal diffusivity α and heat transfer coefficient h is negative while an effect of the shear rate is positive. For the corrected layouts with one/two overturn elements, the results of simulations indicate opposite relationships. A novel optimization approach solving the filling imbalance problem and a novel concept of global modeling of injection molding process are also discussed.
The Zooarchaeology of Israelite Religion: Methods and Practice
Authors: Greer Jonathan S.
Published: April 2019

This essay aims to provide a methodological framework for the application of zooarchaeology to the study of Israelite religion for the purpose of providing an overview of this growing subfield for the non-specialist and for inviting further conversation among practitioners. Definitions of “zooarchaeology” and “Israelite religion” are explored and the aim of reconstructing practices of Yahweh-centric religion is described. A methodology is suggested through a series of questions that may be applied to explorations of faunal remains, including those related to context, excavation technique and analysis, and engagement with the Hebrew Bible. The essay concludes with an illustration from Tel Dan and affirmation of integrated methodologies that critically engage archaeological and textual data to form new syntheses.
A Systems-Based Approach to Ecosystem Services Valuation of Various Atmospheric Calcium Deposition Flows
Authors: Mikhailova Elena A. , Post Christopher J. , Schlautman Mark A. , Groshans Garth R. , Cope Michael P. , Zhang Lisha
Published: April 2019

Atmospheric resources are very important for assessing ecosystem services at different administrative levels (e.g., state, region, etc.). Quantification of atmospheric calcium (Ca2+) deposition on the total basis provides incomplete information about the ecosystem services flows (both “natural” and “human-derived”), therefore lacking a systems approach to guide sustainable management of the flows which support many ecosystem services. This study assessed the value of wet, dry, and total atmospheric calcium deposition flows in the contiguous United States (U.S.) by different spatial aggregation levels (e.g., state, region) using information from the National Atmospheric Deposition Program (NRSP-3) and commodity prices of human-derived materials: agricultural limestone (CaCO3) and uncalcined gypsum (CaSO4•2H2O). The total provisioning ecosystem value of atmospheric calcium deposition flows was $66.7M (i.e., 66.7 million U.S. dollars) ($30M wet + $36.7M dry) based on an average 2014 price of $10.42 per U.S. ton of agricultural limestone (CaCO3) or nearly $364M ($164M wet + $200M dry) based on an average 2014 price of $33.00 per U.S. ton gypsum (CaSO4•2H2O). The quantified spatial distribution of wet, dry, and total atmospheric calcium deposition could be used to identify areas with opportunities for more efficient use of “human-derived” materials since they are already being supplied by atmospheric deposition.
An Efficient Framework for Mobile Lidar Trajectory Reconstruction and Mo-norvana Segmentation
Authors: Che Erzhuo , Olsen Michael J.
Published: April 2019

Mobile laser scanning (MLS, or mobile lidar) is a 3-D data acquisition technique that has been widely used in a variety of applications in recent years due to its high accuracy and efficiency. However, given the large data volume and complexity of the point clouds, processing MLS data can be still challenging with respect to effectiveness, efficiency, and versatility. This paper proposes an efficient MLS data processing framework for general purposes consisting of three main steps: trajectory reconstruction, scan pattern grid generation, and Mo-norvana (Mobile Normal Variation Analysis) segmentation. We present a novel approach to reconstructing the scanner trajectory, which can then be used to structure the point cloud data into a scan pattern grid. By exploiting the scan pattern grid, point cloud segmentation can be performed using Mo-norvana, which is developed based on our previous work for processing Terrestrial Laser Scanning (TLS) data, normal variation analysis (Norvana). In this work, with an unorganized MLS point cloud as input, the proposed framework can complete various tasks that may be desired in many applications including trajectory reconstruction, data structuring, data visualization, edge detection, feature extraction, normal estimation, and segmentation. The performance of the proposed procedures are experimentally evaluated both qualitatively and quantitatively using multiple MLS datasets via the results of trajectory reconstruction, visualization, and segmentation. The efficiency of the proposed method is demonstrated to be able to handle a large dataset stably with a fast computation speed (about 1 million pts/sec. with 8 threads) by taking advantage of parallel programming.
Estimating Daily PM2.5 Concentrations in Beijing Using 750-M VIIRS IP AOD Retrievals and a Nested Spatiotemporal Statistical Model
Authors: Yao Fei , Wu Jiansheng , Li Weifeng , Peng Jian
Published: April 2019

Satellite-retrieved aerosol optical depth (AOD) data have been widely used to predict PM2.5 concentrations. Most of their spatial resolutions (~1 km or greater), however, are too coarse to support PM2.5-related studies at fine scales (e.g., urban-scale PM2.5 exposure assessments). Space-time regression models have been widely developed and applied to predict PM2.5 concentrations from satellite-retrieved AOD. Their accuracies, however, are not satisfactory particularly on days that lack a model dataset. The present study aimed to evaluate the effectiveness of recent high-resolution (i.e., ~750 m at nadir) AOD obtained from the Visible Infrared Imaging Radiometer Suite instrument (VIIRS) Intermediate Product (IP) in estimating PM2.5 concentrations with a newly developed nested spatiotemporal statistical model. The nested spatiotemporal statistical model consisted of two parts: a nested time fixed effects regression (TFER) model and a series of geographically weighted regression (GWR) models. The TFER model, containing daily, weekly, or monthly intercepts, used the VIIRS IP AOD as the main predictor alongside several auxiliary variables to predict daily PM2.5 concentrations. Meanwhile, the series of GWR models used the VIIRS IP AOD as the independent variable to correct residuals from the first-stage nested TFER model. The average spatiotemporal coverage of the VIIRS IP AOD was approximately 16.12%. The sample-based ten-fold cross validation goodness of fit (R2) for the first-stage TFER models with daily, weekly, and monthly intercepts were 0.81, 0.66, and 0.45, respectively. The second-stage GWR models further captured the spatial heterogeneities of the PM2.5-AOD relationships. The nested spatiotemporal statistical model produced more daily PM2.5 estimates and improved the accuracies of summer, autumn, and annual PM2.5 estimates. This study contributes to the knowledge of how well VIIRS IP AOD can predict PM2.5 concentrations at urban scales and offers strategies for improving the coverage and accuracy of daily PM2.5 estimates on days that lack a model dataset.
Canadian Wetland Inventory using Google Earth Engine: The First Map and Preliminary Results
Authors: Amani Meisam , Mahdavi Sahel , Afshar Majid , Brisco Brian , Huang Weimin , Mohammad Javad Mirzadeh Sayyed , White Lori , Banks Sarah , Montgomery Joshua , Hopkinson Christopher
Published: April 2019

Although wetlands provide valuable services to humans and the environment and cover a large portion of Canada, there is currently no Canada-wide wetland inventory based on the specifications defined by the Canadian Wetland Classification System (CWCS). The most practical approach for creating the Canadian Wetland Inventory (CWI) is to develop a remote sensing method feasible for large areas with the potential to be updated within certain time intervals to monitor dynamic wetland landscapes. Thus, this study aimed to create the first Canada-wide wetland inventory using Landsat-8 imagery and innovative image processing techniques available within Google Earth Engine (GEE). For this purpose, a large amount of field samples and approximately 30,000 Landsat-8 surface reflectance images were initially processed using several advanced algorithms within GEE. Then, the random forest (RF) algorithm was applied to classify the entire country. The final step was an original CWI map considering the five wetland classes defined by the CWCS (i.e., bog, fen, marsh, swamp, and shallow water) and providing updated and comprehensive information regarding the location and spatial extent of wetlands in Canada. The map had reasonable accuracy in terms of both visual and statistical analyses considering the large area of country that was classified (9.985 million km2). The overall classification accuracy and the average producer and user accuracies for wetland classes exclusively were 71%, 66%, and 63%, respectively. Additionally, based on the final classification map, it was estimated that 36% of Canada is covered by wetlands.
Classification of 3D Digital Heritage
Authors: Grilli Eleonora , Remondino Fabio
Published: April 2019

In recent years, the use of 3D models in cultural and archaeological heritage for documentation and dissemination purposes is increasing. The association of heterogeneous information to 3D data by means of automated segmentation and classification methods can help to characterize, describe and better interpret the object under study. Indeed, the high complexity of 3D data along with the large diversity of heritage assets themselves have constituted segmentation and classification methods as currently active research topics. Although machine learning methods brought great progress in this respect, few advances have been developed in relation to cultural heritage 3D data. Starting from the existing literature, this paper aims to develop, explore and validate reliable and efficient automated procedures for the classification of 3D data (point clouds or polygonal mesh models) of heritage scenarios. In more detail, the proposed solution works on 2D data (“texture-based” approach) or directly on the 3D data (“geometry-based approach) with supervised or unsupervised machine learning strategies. The method was applied and validated on four different archaeological/architectural scenarios. Experimental results demonstrate that the proposed approach is reliable and replicable and it is effective for restoration and documentation purposes, providing metric information e.g. of damaged areas to be restored.
A Compact Thévenin Model for a Rectenna and Its Application to an RF Harvester with MPPT
Authors: Gasulla Manel , Ripoll-Vercellone Edgar , Reverter Ferran
Published: April 2019

This paper proposes a compact Thévenin model for a rectenna. This model is then applied to design a high-efficiency radio frequency harvester with a maximum power point tracker (MPPT). The rectenna under study consists of an L-matching network and a half-wave rectifier. The derived model is simpler and more compact than those suggested so far in the literature and includes explicit expressions of the Thévenin voltage (Voc) and resistance and of the power efficiency related with the parameters of the rectenna. The rectenna was implemented and characterized from −30 to −10 dBm at 808 MHz. Experimental results agree with the proposed model, showing a linear current–voltage relationship as well as a maximum efficiency at Voc/2, in particular 60% at −10 dBm, which is a remarkable value. An MPPT was also used at the rectenna output in order to automatically work at the maximum efficiency point, with an overall efficiency near 50% at −10 dBm. Further tests were performed using a nearby transmitting antenna for powering a sensor node with a power consumption of 4.2 µW.
Ultrasonic Detection Method for Grouted Defects in Grouted Splice Sleeve Connector Based on Wavelet Pack Energy
Authors: Li Zuohua , Zheng Lilin , Chen Chaojun , Long Zhili , Wang Ying
Published: April 2019

Grouted splice sleeve (GSS) connectors are mainly used in precast concrete structures. However, errors in manual operation during construction cause grouted defects in the GSS connector, which can lead to a negative effect on the overall mechanical properties of the structures. Owing to the complex structure of precast concrete members with a GSS connector, it is difficult to detect grouted defects effectively using traditional ultrasonic parameters. In this paper, a wavelet packet analysis algorithm was developed to effectively detect grouted defects using the ultrasonic method, and a verified experiment was carried out. Laboratory detection was performed on the concrete specimens with a GSS connector before grouting, in which the grouted defects were mimicked with five sizes in five GSS connectors of each specimen group. A simple and convenient ultrasonic detection system was developed, and the specimens were detected. According to the proposed grouted defect index, the results demonstrated that when the grouted defects reached certain sizes, the proposed method could detect the grouted defects effectively. The proposed method is effective and easy to implement at a construction site with simple instruments, and so provides an innovative method for grouted defects detection of precast concrete members.
Accelerometer-Based Human Fall Detection Using Convolutional Neural Networks
Authors: Santos Guto Leoni , Endo Patricia Takako , Monteiro Kayo Henrique de Carvalho , Rocha Elisson da Silva , Silva Ivanovitch , Lynn Theo
Published: April 2019

Human falls are a global public health issue resulting in over 37.3 million severe injuries and 646,000 deaths yearly. Falls result in direct financial cost to health systems and indirectly to society productivity. Unsurprisingly, human fall detection and prevention are a major focus of health research. In this article, we consider deep learning for fall detection in an IoT and fog computing environment. We propose a Convolutional Neural Network composed of three convolutional layers, two maxpool, and three fully-connected layers as our deep learning model. We evaluate its performance using three open data sets and against extant research. Our approach for resolving dimensionality and modelling simplicity issues is outlined. Accuracy, precision, sensitivity, specificity, and the Matthews Correlation Coefficient are used to evaluate performance. The best results are achieved when using data augmentation during the training process. The paper concludes with a discussion of challenges and future directions for research in this domain.
A Seven-Rod Dielectric Sensor for Determination of Soil Moisture in Well-Defined Sample Volumes
Authors: Szerement Justyna , Woszczyk Aleksandra , Szypłowska Agnieszka , Kafarski Marcin , Lewandowski Arkadiusz , Wilczek Andrzej , Skierucha Wojciech
Published: April 2019

This paper presents a novel seven-rod sensor used for time-domain reflectometry (TDR) and frequency-domain reflectometry (FDR) measurements of soil water content in a well-defined sample volume. The probe directly measures the complex dielectric permittivity spectrum and for this purpose requires three calibration media: air, water, and ethanol. Firstly, electromagnetic simulations were used to study the influence of the diameter of a container on the sensitivity zone of the probe with respect to the measured calibration media and isopropanol as a verification liquid. Next, the probe was tested in three soils—sandy loam and two silt loams—with six water contents from air-dry to saturation. The conversion from S 11 parameters to complex dielectric permittivity from vector network analyzer (VNA) measurements was obtained using an open-ended liquid procedure. The simulation and measurement results for the real part of the isopropanol dielectric permittivity obtained from four containers with different diameters were in good agreement with literature data up to 200 MHz. The real part of the dielectric permittivity was extracted and related to the moisture of the tested soil samples. Relations between the volumetric water content and the real part of the dielectric permittivity (by FDR) and apparent dielectric permittivity (by TDR) were compared with Topp’s equation. It was concluded that the best fit to Topp’s equation was observed in the case of a sandy loam. Data calculated according to the equation proposed by Malicki, Plagge, and Roth gave results closer to Topp’s calibration. The obtained results indicated that the seven-rod probe can be used to accurately measure of the dielectric permittivity spectrum in a well-defined sample volume of about 8 cm3 in the frequency range from 20 MHz to 200 MHz.
A Data-Driven Approach to SAR Data-Focusing
Authors: Guaragnella Cataldo , D’Orazio Tiziana
Published: April 2019

Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and used by space agencies. Such algorithms are model-based, i.e., the radiometric and geometric information about the specific sensor must be well known, together with the ancillary data information acquired on board the platform. In the development of low-cost and lightweight SAR sensors, to be used in several application fields, the precise mission parameters and the knowledge of all the specific geometric and radiometric information about the sensor might complicate the hardware and software requirements. Despite SAR data processing being a well-established imaging technique, the proposed algorithm aims to exploit the SAR coherent illumination, demonstrating the possibility of extracting the reference functions, both in range and azimuth directions, when a strong point scatterer (either natural or manmade) is present in the scene. The Singular Value Decomposition is used to exploit the inherent redundancy present in the raw data matrix, and phase unwrapping and polynomial fitting are used to reconstruct clean versions of the reference functions. Fairly focused images on both synthetic and real raw data matrices without the knowledge of mission parameters and ancillary data information can be obtained; as a byproduct, azimuth beam pattern and estimates of a few other parameters have been extracted from the raw data itself. In a previous paper, authors introduced a preliminary work dealing with this problem and able to obtain good-quality images, if compared to the standard processing techniques. In this work, the proposed technique is described, and performance parameters are extracted to compare the proposed approach to RD, showing good adherence of the focused images and pulse responses.
Tapered Fiber-Optic Mach-Zehnder Interferometer for Ultra-High Sensitivity Measurement of Refractive Index
Authors: Ahsani Vahid , Ahmed Farid , Jun Martin B.G. , Bradley Colin
Published: April 2019

A Mach-Zehnder interferometer (MZI) based fiberoptic refractive index (RI) sensor is constructed by uniformly tapering standard single mode fiber (SMF) for RI measurement. A custom flame-based tapering machine is used to fabricate microfiber MZI sensors directly from SMFs. The fabricated MZI device does not require any splicing of fibers and shows excellent RI sensitivity. The sensor with a cladding diameter of 35.5 µm and length of 20 mm exhibits RI sensitivity of 415 nm/RIU for RI range of 1.332 to 1.384, 1103 nm/RIU for RI range of 1.384 to 1.4204 and 4234 nm/RIU for RI range of 1.4204 to 1.4408, respectively. The sensor reveals a temperature sensitivity of 0.0097 nm/°C, which is relatively low in comparison to its ultra-high RI sensitivity. The proposed inexpensive and highly sensitive optical fiber RI sensors have numerous applications in chemical and biochemical sensing fields.
A Deep-Learning Model for Subject-Independent Human Emotion Recognition Using Electrodermal Activity Sensors
Authors: Al Machot Fadi , Elmachot Ali , Ali Mouhannad , Al Machot Elyan , Kyamakya Kyandoghere
Published: April 2019

One of the main objectives of Active and Assisted Living (AAL) environments is to ensure that elderly and/or disabled people perform/live well in their immediate environments; this can be monitored by among others the recognition of emotions based on non-highly intrusive sensors such as Electrodermal Activity (EDA) sensors. However, designing a learning system or building a machine-learning model to recognize human emotions while training the system on a specific group of persons and testing the system on a totally a new group of persons is still a serious challenge in the field, as it is possible that the second testing group of persons may have different emotion patterns. Accordingly, the purpose of this paper is to contribute to the field of human emotion recognition by proposing a Convolutional Neural Network (CNN) architecture which ensures promising robustness-related results for both subject-dependent and subject-independent human emotion recognition. The CNN model has been trained using a grid search technique which is a model hyperparameter optimization technique to fine-tune the parameters of the proposed CNN architecture. The overall concept’s performance is validated and stress-tested by using MAHNOB and DEAP datasets. The results demonstrate a promising robustness improvement regarding various evaluation metrics. We could increase the accuracy for subject-independent classification to 78% and 82% for MAHNOB and DEAP respectively and to 81% and 85% subject-dependent classification for MAHNOB and DEAP respectively (4 classes/labels). The work shows clearly that while using solely the non-intrusive EDA sensors a robust classification of human emotion is possible even without involving additional/other physiological signals.
Use of Surface-Enhanced Raman Scattering (SERS) Probes to Detect Fatty Acid Receptor Activity in a Microfluidic Device
Authors: Zhang Han , Zhang Wei , Xiao Lifu , Liu Yan , Gilbertson Timothy A. , Zhou Anhong
Published: April 2019

In this study, 4-mercaptobenzoic acid (MBA)-Au nanorods conjugated with a GPR120 antibody were developed as a highly sensitive surface-enhanced Raman spectroscopy (SERS) probe, and were applied to detect the interaction of fatty acids (FA) and their cognate receptor, GPR120, on the surface of human embryonic kidney cells (HEK293-GPRR120) cultured in a polydimethylsiloxane (PDMS) microfluidic device. Importantly, the two dominant characteristic SERS peaks of the Raman reporter molecule MBA, 1078 cm−1 and 1581 cm−1, do not overlap with the main Raman peaks from the PDMS substrate when the appropriate spectral scanning range is selected, which effectively avoided the interference from the PDMS background signals. The proposed microfluidic device consisted of two parts, that is, the concentration gradient generator (CGG) and the cell culture well array. The CGG part was fabricated to deliver five concentrations of FA simultaneously. A high aspect ratio well structure was designed to address the problem of HEK cells vulnerable to shear flow. The results showed a positive correlation between the SERS peak intensity and the FA concentrations. This work, for the first time, achieved the simultaneous monitoring of the Raman spectra of cells and the responses of the receptor in the cells upon the addition of fatty acid. The development of this method also provides a platform for the monitoring of cell membrane receptors on single-cell analysis using SERS in a PDMS-based microfluidic device.
Effect of Gamma-Ray Irradiation on the Growth of Au Nano-Particles Embedded in the Germano-Silicate Glass Cladding of the Silica Glass Fiber and its Surface Plasmon Resonance Response
Authors: Ju Seongmin , Han Won-Taek
Published: April 2019

The effect of γ-ray irradiation on the surface plasmon resonance (SPR) sensing capability of refractive index (n = 1.418–1.448) of the silica glass optical fiber comprised of germano-silicate glass cladding embedded with Au nano-particles (NPs) was investigated. As the γ-ray irradiation increased from 1 h to 3 h with the dose rate of 1190 Gy/h, the morphology of the Au NPs and the SPR spectrum were found to change. The average diameter of Au NPs increased with the aspect ratio from 1 to 2, and the nano-particles became grown to the clusters. The SPR band wavelength shifted towards a longer wavelength with the increase of total dose of γ-ray irradiation regardless of the corresponding refractive indices. The SPR sensitivities (wavelength/refractive index unit, nm/RIU) also increased from 407 nm/RIU to 3553 nm/RIU, 1483 nm/RIU, and 2335 nm/RIU after the γ-ray irradiation at a total dose of 1190 Gy, 2380 Gy, and 3570 Gy, respectively.
Wide Swath and High Resolution Airborne HyperSpectral Imaging System and Flight Validation
Authors: Zhang Dong , Yuan Liyin , Wang Shengwei , Yu Hongxuan , Zhang Changxing , He Daogang , Han Guicheng , Wang Jianyu , Wang Yueming
Published: April 2019

Wide Swath and High Resolution Airborne Pushbroom Hyperspectral Imager (WiSHiRaPHI) is the new-generation airborne hyperspectral imager instrument of China, aimed at acquiring accurate spectral curve of target on the ground with both high spatial resolution and high spectral resolution. The spectral sampling interval of WiSHiRaPHI is 2.4 nm and the spectral resolution is 3.5 nm (FWHM), integrating 256 channels coving from 400 nm to 1000 nm. The instrument has a 40-degree field of view (FOV), 0.125 mrad instantaneous field of view (IFOV) and can work in high spectral resolution mode, high spatial resolution mode and high sensitivity mode for different applications, which can adapt to the Velocity to Height Ratio (VHR) lower than 0.04. The integration has been finished, and several airborne flight validation experiments have been conducted. The results showed the system’s excellent performance and high efficiency.
The Applicability of 2-amino-4,6-diphenyl-pyridine-3-carbonitrile Sensors for Monitoring Different Types of Photopolymerization Processes and Acceleration of Cationic and Free-Radical Photopolymerization Under Near UV Light
Authors: Ortyl Joanna , Fiedor Paweł , Chachaj-Brekiesz Anna , Pilch Maciej , Hola Emilia , Galek Mariusz
Published: April 2019

The performance of a series of 2-amino-4,6-diphenyl-pyridine-3-carbonitrile derivatives as fluorescent molecular sensors for monitoring photopolymerization processes of different monomers by the Fluorescence Probe Technique (FPT) was studied. It has been shown that the new derivatives are characterized by much higher sensitivity than the commercially available 7-diethylamino-4-methylcoumarin (Coumarin 1) and trans-2-(2′,5′-dimethoxyphenyl)ethenyl-2,3,4, 5,6-pentafluorobenzene (25ST) probes. It has been discovered that the 2-amino-4,6-diphenyl-pyridine-3-carbonitrile derivatives accelerate the cationic photopolymerization process initiated with diphenyliodonium photoinitiators at the wavelength where the photoinitiator alone does not work. They are particularly efficient for the photoinitiation of cationic photopolymerization of an epoxide and vinyl monomers. Consequently, the application of the 2-amino-4,6-diphenyl-pyridine-3-carbonitrile derivatives in a dual role: (a) as fluorescent sensors for monitoring the free-radical, thiol-ene and cationic polymerization progress, and (b) as long-wavelength co-initiators for diphenyliodonium salts initiators, is proposed.
Comparison between Concentration and Immersion Based on EEG Analysis
Authors: Lim Seokbeen , Yeo Mina , Yoon Gilwon
Published: April 2019

Concentration and immersion belong to a similar mental state in which a person is preoccupied with a particular task. In this study, we investigated a possibility of diagnosing two mental states with a subtle difference. Concentration and immersion states were induced to analyze the electroencephalography (EEG) changes during these states. Thirty-two college students in their 20s participated in the study. For concentration, subjects were asked to focus on a red dot at the center of a white screen, and for immersion they were asked to focus on playing a computer game. Relative to rest, Alpha waves decreased during concentration and immersion. Relative to rest, Theta waves decreased at almost all channels during concentration and, on the other hand, increased at all channels during immersion. Beta waves increased during concentration and immersion in the frontal and occipital lobes, with a higher increase in immersion. In the temporal lobe, Beta waves decreased during concentration and increased during immersion. In the central region, Beta waves decreased during concentration and immersion, and the decrease during immersion was larger. Such evident differences between the EEG results for concentration and immersion can imply diagnostic capabilities of various other mental states.
Simulating Dynamic Driving Behavior in Simulation Test for Unmanned Vehicles via Multi-Sensor Data
Authors: Zhao Danchen , Li Yaochen , Liu Yuehu
Published: April 2019

Driving behavior is the main basis for evaluating the performance of an unmanned vehicle. In simulation tests of unmanned vehicles, in order for simulation results to be approximated to the actual results as much as possible, model of driving behaviors must be able to exhibit actual motion of unmanned vehicles. We propose an automatic approach of simulating dynamic driving behaviors of vehicles in traffic scene represented by image sequences. The spatial topological attributes and appearance attributes of virtual vehicles are computed separately according to the constraint of geometric consistency of sparse 3D space organized by image sequence. To achieve this goal, we need to solve three main problems: Registration of vehicle in a 3D space of road environment, vehicle’s image observed from corresponding viewpoint in the road scene, and consistency of the vehicle and the road environment. After the proposed method was embedded in a scene browser, a typical traffic scene including the intersections was chosen for a virtual vehicle to execute the driving tasks of lane change, overtaking, slowing down and stop, right turn, and U-turn. The experimental results show that different driving behaviors of vehicles in typical traffic scene can be exhibited smoothly and realistically. Our method can also be used for generating simulation data of traffic scenes that are difficult to collect.
Impacts of Inter-Basin Water Transfer Projects on Optimal Water Resources Allocation in the Hanjiang River Basin, China
Authors: Tian Jing , Liu Dedi , Guo Shenglian , Pan Zhengke , Hong Xingjun
Published: April 2019

Inter-basin water transfer project is an effective engineering countermeasure to alleviate the pressure of water supply in water-deficient areas and balance the uneven distribution of water resources. To assess the impacts of inter-basin water transfer projects on optimal water resources allocation, an integrated water resources management framework is proposed, and is applied to the middle and lower reaches of the Hanjiang River Basin in China. Firstly, future water demands are analyzed as inputs. Then, a multi-objective water resources allocation model is formulated mitigating the negative impacts of water transfer projects on downstream water quantity and quality by using the non-dominated sorting genetic algorithm-II (NSGA-II). Finally, the indicators of water supply reliability, vulnerability and resilience are evaluated under different scenarios of inter-basin water transfer projects. The results indicate that: (1) the reliability and resilience of the water donor system will be gradually reduced while the vulnerability will be increased with the expansion of water transfer projects and the increase of water demand, (2) water supply risk is likely to increase in all zones (because zones at the boundary cannot obtain sufficient water due to limitations of local inflow and reservoir operation, while the amount of water available in the zones along the mainstream river is directly decreased by the water transfer projects), (3) more water supply measures and compensation measures will need to be implemented in the water donor areas. The framework proposed in this study to evaluate the comprehensive impact of inter-basin water transfer projects is conducive to water resources management.
Conservation Opportunities of the Land Restitution Program Areas in the Colombian Post-Conflict Period
Authors: Unda Mariana , Etter Andrés
Published: April 2019

The Land Restitution Program (LRP) is one of the greatest challenges for Colombia’s post-conflict period; it implies the recognition of the victims of dispossession or abandonment of lands and sets the discussion for future land use planning in these areas. The 1,119,959 Ha of LRP areas (August 2018) require knowledge of their state to promote land uses that favor the conservation of priority ecosystems and forest cover. Spatial and statistical analyzes where used to study the land-cover change in and around LRP areas at the national and regional level. An index of naturalness using a multi-criteria framework was used to identify important areas for conservation. Within areas, forest cover changes, resulting from deforestation and regeneration processes, decreased between 1990 and 2017. A total of 9.4% of their area show high naturalness, while 20% of them show high importance for conservation. The results show that, despite their dispossession/abandonment, these areas continued a deforestation process. Most of the areas show low naturalness, but conservation priorities can be identified in the Andes, Amazon, and Orinoco regions.
Enhancing the Teaching and Learning Process Using Video Streaming Servers and Forecasting Techniques
Authors: Hasan Raza , Palaniappan Sellappan , Mahmood Salman , Shah Babar , Abbas Ali , Sarker Kamal Uddin
Published: April 2019

Higher educational institutes (HEI) are adopting ubiquitous and smart equipment such as mobile devices or digital gadgets to deliver educational content in a more effective manner than the traditional approaches. In present works, a lot of smart classroom approaches have been developed, however, the student learning experience is not yet fully explored. Moreover, module historical data over time is not considered which could provide insight into the possible outcomes in the future, leading new improvements and working as an early detection method for the future results within the module. This paper proposes a framework by taking into account module historical data in order to predict module performance, particularly the module result before the commencement of classes with the goal of improving module pass percentage. Furthermore, a video streaming server along with blended learning are sequentially integrated with the designed framework to ensure correctness of teaching and learning pedagogy. Simulation results demonstrate that by considering module historical data using time series forecasting helps in improving module performance in terms of module delivery and result outcome in terms of pass percentage. Furthermore, the proposed framework provides a mechanism for faculties to adjust their teaching style according to student performance level to minimize the student failure rate.