bluuebunny/crossref_metadata_2025 huggingface dataset:
MagIO: Magnetic Field Strength Based Indoor- Outdoor Detection with a Commercial Smartphone
Authors: Ashraf Imran , Hur Soojung , Park Yongwan
Published: October 2018

A wide range of localization techniques has been proposed recently that leverage smartphone sensors. Context awareness serves as the backbone of these localization techniques, which helps them to shift the localization technologies to improve efficiency and energy utilization. Indoor-outdoor (IO) context sensing plays a vital role for such systems, which serve both indoor and outdoor localization. IO systems work with collaborative technologies including the Global Positioning System (GPS), cellular tower signals, Wi-Fi, Bluetooth and a variety of smartphone sensors. GPS- and Wi-Fi-based systems are power hungry, and their accuracy is severed by limiting factors like multipath, shadowing, etc. On the other hand, various built-in smartphone sensors can be deployed for environmental sensing. Although these sensors can play a crucial role, yet they are very less studied. This research aims at investigating the use of ambient magnetic field data alone from a smartphone for IO detection. The research first investigates the feasibility of utilizing magnetic field data alone for IO detection and then extracts different features suitable for IO detection to be used in machine learning-based classifiers to discriminate between indoor and outdoor environments. The experiments are performed at three different places including a subway station, a shopping mall and Yeungnam University (YU), Korea. The training data are collected from one spot of the campus, and testing is performed with data from various locations of the above-mentioned places. The experiment involves Samsung Galaxy S8, LG G6 and Samsung Galaxy Round smartphones. The results show that the magnetic data from smartphone magnetic sensor embody enough information and can discriminate the indoor environment from the outdoor environment. Naive Bayes (NB) outperforms with a classification accuracy of 83.26%, as against Support vector machines (SVM), random induction (RI), gradient boosting machines (GBM), random forest (RF), k-nearest neighbor (kNN) and decision trees (DT), whose accuracies are 67.21%, 73.38%, 73.40%, 78.59%, 69.53% and 68.60%, respectively. kNN, SVM and DT do not perform well when noisy data are used for classification. Additionally, other dynamic scenarios affect the attitude of magnetic data and degrade the performance of SVM, RI and GBM. NB and RF prove to be more noise tolerant and environment adaptable and perform very well in dynamic scenarios. Keeping in view the performance of these classifiers, an ensemble-based stacking scheme is presented, which utilizes DT and RI as the base learners and naive Bayes as the ensemble classifier. This approach is able to achieve an accuracy of 85.30% using the magnetic data of the smartphone magnetic sensor. Moreover, with an increase in training data, the accuracy of the stacking scheme can be elevated by 0.83%. The performance of the proposed approach is compared with GPS-, Wi-Fi- and light sensor-based IO detection.
Organs-on-a-Chip Module: A Review from the Development and Applications Perspective
Authors: Sosa-Hernández Juan Eduardo , Villalba-Rodríguez Angel M. , Romero-Castillo Kenya D. , Aguilar-Aguila-Isaías Mauricio A. , García-Reyes Isaac E. , Hernández-Antonio Arturo , Ahmed Ishtiaq , Sharma Ashutosh , Parra-Saldívar Roberto , Iqbal Hafiz M. N.
Published: October 2018

In recent years, ever-increasing scientific knowledge and modern high-tech advancements in micro- and nano-scales fabrication technologies have impacted significantly on various scientific fields. A micro-level approach so-called “microfluidic technology” has rapidly evolved as a powerful tool for numerous applications with special reference to bioengineering and biomedical engineering research. Therefore, a transformative effect has been felt, for instance, in biological sample handling, analyte sensing cell-based assay, tissue engineering, molecular diagnostics, and drug screening, etc. Besides such huge multi-functional potentialities, microfluidic technology also offers the opportunity to mimic different organs to address the complexity of animal-based testing models effectively. The combination of fluid physics along with three-dimensional (3-D) cell compartmentalization has sustained popularity as organ-on-a-chip. In this context, simple humanoid model systems which are important for a wide range of research fields rely on the development of a microfluidic system. The basic idea is to provide an artificial testing subject that resembles the human body in every aspect. For instance, drug testing in the pharma industry is crucial to assure proper function. Development of microfluidic-based technology bridges the gap between in vitro and in vivo models offering new approaches to research in medicine, biology, and pharmacology, among others. This is also because microfluidic-based 3-D niche has enormous potential to accommodate cells/tissues to create a physiologically relevant environment, thus, bridge/fill in the gap between extensively studied animal models and human-based clinical trials. This review highlights principles, fabrication techniques, and recent progress of organs-on-chip research. Herein, we also point out some opportunities for microfluidic technology in the future research which is still infancy to accurately design, address and mimic the in vivo niche.
Molecular Tunnels in Enzymes and Thermophily: A Case Study on the Relationship to Growth Temperature
Authors: Gonzalez Juan Miguel
Published: October 2018

Developments in protein expression, analysis and computational capabilities are decisively contributing to a better understanding of the structure of proteins and their relationship to function. Proteins are known to be adapted to the growth rate of microorganisms and some microorganisms (named (hyper)thermophiles) thrive optimally at high temperatures, even above 100 °C. Nevertheless, some biomolecules show great instability at high temperatures and some of them are universal and required substrates and cofactors in multiple enzymatic reactions for all (both mesophiles and thermophiles) living cells. Only a few possibilities have been pointed out to explain the mechanisms that thermophiles use to successfully thrive under high temperatures. As one of these alternatives, the role of molecular tunnels or channels in enzymes has been suggested but remains to be elucidated. This study presents an analysis of channels in proteins (i.e., substrate tunnels), comparing two different protein types, glutamate dehydrogenase and glutamine phosphoribosylpyrophosphate amidotransferase, which are supposed to present a different strategy on the requirement for substrate tunnels with low and high needs for tunneling, respectively. The search and comparison of molecular tunnels in these proteins from microorganisms thriving optimally from 15 °C to 100 °C suggested that those tunnels in (hyper)thermophiles are required and optimized to specific dimensions at high temperatures for the enzyme glutamine phosphoribosylpyrophosphate amidotransferase. For the enzyme glutamate dehydrogenase, a reduction of empty spaces within the protein could explain the optimization at increasing temperatures. This analysis provides further evidence on molecular channeling as a feasible mechanism in hyperthermophiles with multiple relevant consequences contributing to better understand how they live under those extreme conditions.
Ultrasonic Irradiation Coupled with Microwave Treatment for Eco-friendly Process of Isolating Bacterial Cellulose Nanocrystals
Authors: Wardhono Endarto Yudo , Wahyudi Hadi , Agustina Sri , Oudet François , Pinem Mekro Permana , Clausse Danièle , Saleh Khashayar , Guénin Erwann
Published: October 2018

The isolation of crystalline regions from fibers cellulose via the hydrolysis route generally requires corrosive chemicals, high-energy demands, and long reaction times, resulting in high economic costs and environmental impact. From this basis, this work seeks to develop environment-friendly processes for the production of Bacterial Cellulose Nanocrystals (BC-NC). To overcome the aforementioned issues, this study proposes a fast, highly-efficient and eco-friendly method for the isolation of cellulose nanocrystals from Bacterial Cellulose, BC. A two-step processes is considered: (1) partial depolymerization of Bacterial Cellulose (DP-BC) under ultrasonic conditions; (2) extraction of crystalline regions (BC-NC) by treatment with diluted HCl catalyzed by metal chlorides (MnCl2 and FeCl3.6H2O) under microwave irradiation. The effect of ultrasonic time and reactant and catalyst concentrations on the index crystallinity (CrI), chemical structure, thermal properties, and surface morphology of DP-BC and BC-NC were evaluated. The results indicated that the ultrasonic treatment induced depolymerization of BC characterized by an increase of the CrI. The microwave assisted by MnCl2-catalyzed mild acid hydrolysis enhanced the removal of the amorphous regions, yielding BC-NC. A chemical structure analysis demonstrated that the chemical structures of DP-BC and BC-NC remained unchanged after the ultrasonic treatment and MnCl2-catalyzed acid hydrolysis process.
Antibacterial and Bioactive Surface Modifications of Titanium Implants by PCL/TiO2 Nanocomposite Coatings
Authors: Kiran A. Sandeep Kranthi , Kumar T.S. Sampath , Sanghavi Rutvi , Doble Mukesh , Ramakrishna Seeram
Published: October 2018

Surface modification of biomedical implants is an established strategy to improve tissue regeneration, osseointegration and also to minimize the bacterial accumulation. In the present study, electrospun poly(ε-caprolactone)/titania (PCL/TiO2) nanocomposite coatings were developed on commercially pure titanium (cpTi) substrates for an improved biological and antibacterial properties for bone tissue engineering. TiO2 nanoparticles in various amounts (2, 5, and 7 wt %) were incorporated into a biodegradable PCL matrix to form a homogeneous solution. Further, PCL/TiO2 coatings on cpTi were obtained by electrospinning of PCL/TiO2 solution onto the substrate. The resulted coatings were structurally characterized and inspected by employing scanning electron microscope (SEM), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy. Given the potential biological applications of PCL/TiO2 coated cpTi substrates, the apatite-forming capacity was examined by immersing in simulated body fluid (SBF) for upto 21 days. Biocompatibility has been evaluated through adhesion/proliferation of hFOB osteoblast cell lines and cytotoxicity by MTT assay. Antimicrobial activity of PCL/TiO2 nanocomposites has been tested using UV light against gram-positive Staphylococcus aureus (S.aureus). The resulting surface displays good bioactive properties against osteoblast cell lines with increased viability of 40% at day 3 and superior antibacterial property against S.aureus with a significant reduction of bacteria to almost 76%. Surface modification by PCL/TiO2 nanocomposites makes a viable approach for improving dual properties, i.e., biological and antibacterial properties on titanium implants which might be used to prevent implant-associated infections and promoting cell attachment of orthopedic devices at the same time.
Investigation of the Microstructures of Graphene Quantum Dots (GQDs) by Surface-Enhanced Raman Spectroscopy
Authors: Wu Junxiao , Wang Peijie , Wang Fuhe , Fang Yan
Published: October 2018

Photoluminescence (PL) is the most significant feature of graphene quantum dots (GQDs). However, the PL mechanism in GQDs has been debated due to the fact that the microstructures, such as edge and in-plane defects that are critical for PL emission, have not been convincingly identified due to the lack of effective detection methods. Conventional measures such as high-resolution transmission electron microscopy and infrared spectroscopy only show some localized lattice fringes of GQDs and the structures of some substituents, which have little significance in terms of thoroughly understanding the PL effect. Here, surface-enhanced Raman spectroscopy (SERS) was introduced as a highly sensitive surface technique to study the microstructures of GQDs. Pure GQDs were prepared by laser ablating and cutting highly oriented pyrolytic graphite (HOPG) parallel to the graphite layers. Consequently, abundant SERS signals of the GQDs were obtained on an Ag electrode in an electrochemical environment for the first time. The results convincingly and experimentally characterized the typical and detailed features of GQDs, such as the crystallinity of sp2 hexagons, the quantum confinement effect, various defects on the edges, sp3-like defects and disorders on the basal planes, and passivated structures on the periphery and surface of the GQDs. This work demonstrates that SERS is thus by far the most effective technique for probing the microstructures of GQDs.
HCMV miRNA Targets Reveal Important Cellular Pathways for Viral Replication, Latency, and Reactivation
Authors: Diggins Nicole L. , Hancock Meaghan H.
Published: October 2018

It is now well appreciated that microRNAs (miRNAs) play a critical role in the lifecycles of many herpes viruses. The human cytomegalovirus (HCMV) replication cycle varies significantly depending on the cell type infected, with lytic replication occurring in fully-differentiated cells such as fibroblasts, endothelial cells, or macrophages, and latent infection occurring in less-differentiated CD14+ monocytes and CD34+ hematopoietic progenitor cells where viral gene expression is severely diminished and progeny virus is not produced. Given their non-immunogenic nature and their capacity to target numerous cellular and viral transcripts, miRNAs represent a particularly advantageous means for HCMV to manipulate viral gene expression and cellular signaling pathways during lytic and latent infection. This review will focus on our current knowledge of HCMV miRNA viral and cellular targets, and discuss their importance in lytic and latent infection, highlight the challenges of studying HCMV miRNAs, and describe how viral miRNAs can help us to better understand the cellular processes involved in HCMV latency.
Cardiovascular Biomarkers in Association with Dietary Intake in a Longitudinal Study of Youth with Type 1 Diabetes
Authors: Sanjeevi Namrata , Lipsky Leah M. , Nansel Tonja R.
Published: October 2018

Despite cardioprotective effects of a healthy diet in the general population, few studies have investigated this relationship in individuals with type 1 diabetes, who are at elevated risks of cardiovascular disease (CVD) due to hyperglycemia. The objective of this study was to examine the association of CVD biomarkers with overall diet quality, as measured by the Healthy Eating Index-2015 (HEI-2015), and its dietary components in youth with type 1 diabetes. Youth with type 1 diabetes (n = 136, 8–16.9 years) were enrolled in an 18-month behavioral nutrition intervention trial. Dietary intake from three-day diet records, CVD biomarkers (total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C); triglycerides (TG), C-reactive protein (CRP), 8-iso-prostaglandin-F2alpha (8-iso-PGF2α), systolic and diastolic blood pressure (SBP and DBP, respectively), and glycated hemoglobin (HbA1c) were assessed at baseline, 6, 12 and 18 months. Linear mixed-effects models estimated associations of dietary intake with CVD biomarkers, adjusting for HbA1c and other covariates. Separate models estimated associations of time-varying change in dietary intake with time-varying change in CVD biomarkers. HEI-2015 was not associated with CVD biomarkers, but whole grain intake was inversely associated with TC, HDL-C and DBP, and a greater increase in whole fruit intake was associated with lower DBP. Added sugar, saturated fat and polyunsaturated fat were positively related to serum TG, HDL-C, and DBP, respectively. Findings suggest that the intake of specific dietary components, including whole grains, whole fruits, added sugar and PUFA, may influence cardiometabolic health in youth with type 1 diabetes, independent of glycemic control.
Peripheral Blood Mononuclear Cells Antioxidant Adaptations to Regular Physical Activity in Elderly People
Authors: Busquets-Cortés Carla , Capó Xavier , Bibiloni Maria del Mar , Martorell Miquel , Ferrer Miguel D. , Argelich Emma , Bouzas Cristina , Carreres Sandra , Tur Josep A. , Pons Antoni , Sureda Antoni
Published: October 2018

Regular physical activity prescription is a key point for healthy aging and chronic disease management and prevention. Our aim was to evaluate the antioxidant defense system and the mitochondrial status in peripheral blood mononuclear cells (PBMCs) and the level of oxidative damage in plasma in active, intermediate and inactive elderly. In total, 127 healthy men and women >55 years old participated in the study and were classified according on their level of declared physical activity. A more active lifestyle was accompanied by lower weight, fat mass and body mass index when compared to a more sedentary life-style. Active participants exhibited lower circulating PBMCs than inactive peers. Participants who reported higher levels of exercise had increased antioxidant protein levels when compared to more sedentary partakers. Carbonylated protein levels exhibited similar behavior, accompanied by a significant raise in expression of cytochrome c oxidase subunit IV in PBMCs. No significant changes were found in the activities of antioxidant enzymes and in the expression of structural (MitND5) and mitochondrial dynamic-related (PGC1α and Mitofusins1/2.) proteins. Active lifestyle and daily activities exert beneficial effects on body composition and it enhances the antioxidant defenses and oxidative metabolism capabilities in PBMCs from healthy elderly.
Polyunsaturated Fatty Acids and Their Potential Therapeutic Role in Cardiovascular System Disorders—A Review
Authors: Sokoła-Wysoczańska Ewa , Wysoczański Tomasz , Wagner Jolanta , Czyż Katarzyna , Bodkowski Robert , Lochyński Stanisław , Patkowska-Sokoła Bożena
Published: October 2018

Cardiovascular diseases are described as the leading cause of morbidity and mortality in modern societies. Therefore, the importance of cardiovascular diseases prevention is widely reflected in the increasing number of reports on the topic among the key scientific research efforts of the recent period. The importance of essential fatty acids (EFAs) has been recognized in the fields of cardiac science and cardiac medicine, with the significant effects of various fatty acids having been confirmed by experimental studies. Polyunsaturated fatty acids are considered to be important versatile mediators for improving and maintaining human health over the entire lifespan, however, only the cardiac effect has been extensively documented. Recently, it has been shown that omega-3 fatty acids may play a beneficial role in several human pathologies, such as obesity and diabetes mellitus type 2, and are also associated with a reduced incidence of stroke and atherosclerosis, and decreased incidence of cardiovascular diseases. A reasonable diet and wise supplementation of omega-3 EFAs are essential in the prevention and treatment of cardiovascular diseases prevention and treatment.
Post-Modernism, Agency, and Democracy
Authors: McManus Matthew
Published: October 2018

This essay presents a general summary of post-modern philosophy’s conception of agency. It argues that while post-modern philosophers offer formidable intellectual tools for criticizing contemporary restrictions on agency, their conception falters for a variety of philosophical and political reasons. This implies we should develop a more robust conception of agency to provide a foundation for progressive politics. The essay concludes by analyzing several recent steps to develop such a conception.
Natural Philosophy and the Sciences: Challenging Science’s Tunnel Vision
Authors: Gare Arran
Published: October 2018

Prior to the nineteenth century, those who are now regarded as scientists were referred to as natural philosophers. With empiricism, science was claimed to be a superior form of knowledge to philosophy, and natural philosophy was marginalized. This claim for science was challenged by defenders of natural philosophy, and this debate has continued up to the present. The vast majority of mainstream scientists are comfortable in the belief that through applying the scientific method, knowledge will continue to accumulate, and that claims to knowledge outside science apart from practical affairs should not be taken seriously. This is referred to as scientism. It is incumbent on those who defend natural philosophy against scientism not only to expose the illusions and incoherence of scientism, but to show that natural philosophers can make justifiable claims to advancing knowledge. By focusing on a recent characterization and defense of natural philosophy along with a reconstruction of the history of natural philosophy, showing the nature and role of Schelling’s conception of dialectical thinking, I will attempt to identify natural philosophy as a coherent tradition of thought and defend it as something different from science and as essential to it, and essential to the broader culture and to civilization.
High-Performance PEDOT:PSS/Hexamethylene Diisocyanate-Functionalized Graphene Oxide Nanocomposites: Preparation and Properties
Authors: Luceño Sánchez José Antonio , Peña Capilla Rafael , Díez-Pascual Ana Maria
Published: October 2018

Graphene oxide (GO) has emerged as an ideal filler to reinforce polymeric matrices owing to its large specific surface area, transparency, flexibility, and very high mechanical strength. Nonetheless, functionalization is required to improve its solubility in common solvents and expand its practical uses. In this work, hexamethylene diisocyanate (HDI)-functionalized GO (HDI-GO) has been used as filler of a conductive polymer matrix, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). The nanocomposites have been prepared via a simple solution casting method, and have been characterized by scanning electron microscopy (SEM), UV–Vis and Raman spectroscopies, X-ray diffraction (XRD), thermogravimetric analysis (TGA), tensile tests, and four-point probe measurements to get information about how the HDI-GO functionalization degree (FD) and the HDI-GO concentration in the nanocomposite influence the final properties. SEM analysis showed a very homogenous dispersion of the HDI-GO nanosheets with the highest FD within the matrix, and the Raman spectra revealed the existence of very strong HDI-GO-PEDOT:PSS interactions. A gradual improvement in thermal stability was found with increasing HDI-GO concentration, with only a small loss in transparency. A reduction in the sheet resistance of PEDOT:PSS was found at low HDI-GO contents, whilst increasing moderately at the highest loading tested. The nanocomposites showed a good combination of stiffness, strength, ductility, and toughness. The optimum balance of properties was attained for samples incorporating 2 and 5 wt % HDI-GO with the highest FD. These solution-processed nanocomposites show considerably improved performance compared to conventional PEDOT:PSS nanocomposites filled with raw GO, and are highly suitable for applications in various fields, including flexible electronics, thermoelectric devices, and solar energy applications.
Seasonal Operation Strategy Optimization for Integrated Energy Systems with Considering System Cooling Loads Independently
Authors: Li Kecheng , Yan Huaguang , He Guixiong , Zhu Chengzhi , Liu Kaicheng , Liu Yuting
Published: October 2018

With the rapid growth of energy consumption, how to utilize energy in an efficient and cheap way becomes an intensive problem. This paper proposes an optimal operation strategy to reduce system fuel costs and increase system stability by independently considering cooling loads and adjusting CHP heat to power ratio seasonally. In this paper, a mathematical model of CHP operation is introduced to reveal the relationship between the supplementary volume of diesel oil and CHP heat to power ratio. Meanwhile, by analyzing the influence of seasonal factor on energy consumption, CHP heat to power ratio is optimized seasonally. Then, by independently considering the impacts of the cooling loads on system operation, the particle swarm optimization (PSO) algorithm is used to optimize the operation strategy of each device. Finally, this paper validates the positive effects of storage devices on improving system economy and stability under the premise of the time-of-use gas price. Results show that system fuel costs can be reduced by 5.2% if the seasonal factor is considered. Additionally, by optimizing the operation strategy, the peak valley gap of electrical loads in summer reduces by 40.7%. Moreover, the proposed strategy successfully utilizes storage capacity to shift loads and respond to gas price.
Geotechnical Properties of Effluent-Contaminated Cohesive Soils and Their Stabilization Using Industrial By-Products
Authors: Irfan Muhammad , Chen Yulong , Ali Muhammad , Abrar Muhammad , Qadri Ahmed , Bhutta Osama
Published: October 2018

The unchecked and unnoticed disposal of industrial leachates is a common malpractice in developing countries. Untreated effluents from industries drastically deteriorate the soil, altering nearly all of its characteristics. An increase in urbanization has led to construction on these deteriorated lands. In this study, the chemical impact of two industrial effluents, dyeing (acidic) and tannery (basic), is studied on two cohesive soils, i.e., high plastic clay (CH) and low plastic clay (CL). Properties such as liquid limit, plasticity index, specific gravity, maximum dry density, unconfined compressive strength, swell potential, swell pressure, and compression indices decrease with effluent contamination, with the exception of the basic effluent, for which the trend changes after a certain percentage. This study also examines the time variation of properties at different effluent percentages, finding that unconfined compressive strength of both soils increases with time upon dyeing (acidic) contamination and decreases with tannery (basic). The stabilizing effect of two industrial by-products, i.e., marble dust and ground granulated blast furnace slag (GGBFS) have been evaluated. Unlike their proven positive effect on uncontaminated soils, these industrial by-products did not show any significant stabilization effect on leachate-contaminated cohesive soils, thereby emphasizing the need to utilize special remediation measures for effluent treated soils.
Using Single- and Multi-Date UAV and Satellite Imagery to Accurately Monitor Invasive Knotweed Species
Authors: Martin François-Marie , Müllerová Jana , Borgniet Laurent , Dommanget Fanny , Breton Vincent , Evette André
Published: October 2018

Understanding the spatial dynamics of invasive alien plants is a growing concern for many scientists and land managers hoping to effectively tackle invasions or mitigate their impacts. Consequently, there is an urgent need for the development of efficient tools for large scale mapping of invasive plant populations and the monitoring of colonization fronts. Remote sensing using very high resolution satellite and Unmanned Aerial Vehicle (UAV) imagery is increasingly considered for such purposes. Here, we assessed the potential of several single- and multi-date indices derived from satellite and UAV imagery (i.e., UAV-generated Canopy Height Models—CHMs; and Bi-Temporal Band Ratios—BTBRs) for the detection and mapping of the highly problematic Asian knotweeds (Fallopia japonica; Fallopia × bohemica) in two different landscapes (i.e., open vs. highly heterogeneous areas). The idea was to develop a simple classification procedure using the Random Forest classifier in eCognition, usable in various contexts and requiring little training to be used by non-experts. We also rationalized errors of omission by applying simple “buffer” boundaries around knotweed predictions to know if heterogeneity across multi-date images could lead to unfairly harsh accuracy assessment and, therefore, ill-advised decisions. Although our “crisp” satellite results were rather average, our UAV classifications achieved high detection accuracies. Multi-date spectral indices and CHMs consistently improved classification results of both datasets. To the best of our knowledge, it was the first time that UAV-generated CHMs were used to map invasive plants and their use substantially facilitated knotweed detection in heterogeneous vegetation contexts. Additionally, the “buffer” boundary results showed detection rates often exceeding 90–95% for both satellite and UAV images, suggesting that classical accuracy assessments were overly conservative. Considering these results, it seems that knotweed can be satisfactorily mapped and monitored via remote sensing with moderate time and money investment but that the choice of the most appropriate method will depend on the landscape context and the spatial scale of the invaded area.
Upscaling Solar-Induced Chlorophyll Fluorescence from an Instantaneous to Daily Scale Gives an Improved Estimation of the Gross Primary Productivity
Authors: Hu Jiaochan , Liu Liangyun , Guo Jian , Du Shanshan , Liu Xinjie
Published: October 2018

Solar-induced chlorophyll fluorescence (SIF) is closely linked to the photosynthesis of plants and has the potential to estimate gross primary production (GPP) at different temporal and spatial scales. However, remotely sensed SIF at a ground or space level is usually instantaneous, which cannot represent the daily total SIF. The temporal mismatch between instantaneous SIF (SIFinst) and daily GPP (GPPdaily) impacts their correlation across space and time. Previous studies have upscaled SIFinst to the daily scale based on the diurnal cycle in the cosine of the solar zenith angle ( cos ( SZA ) ) to correct the effects of latitude and length of the day on the variations in the SIF-GPP correlation. However, the important effects of diurnal weather changes due to cloud and atmospheric scattering were not considered. In this study, we present a SIF upscaling method using photosynthetically active radiation (PAR) as a driving variable. First, a conversion factor (i.e., the ratio of the instantaneous PAR (PARinst) to daily PAR (PARdaily)) was used to upscale in-situ SIF measurements from the instantaneous to daily scale. Then, the performance of the SIF upscaling method was evaluated under changing weather conditions and different latitudes using continuous tower-based measurements at two sites. The results prove that our PAR-based method can reduce not only latitude-dependent but also the weather-dependent variations in the SIF-GPP model. Specifically, the PAR-based method gave a more accurate prediction of diurnal and daily SIF (SIFdaily) than the cos ( SZA ) -based method, with decreased relative root mean square error (RRMSE) values from 42.2% to 25.6% at half-hour intervals and from 25.4% to 13.3% at daily intervals. Moreover, the PAR-based upscaled SIFdaily had a stronger correlation with the daily absorbed PAR (APAR) than both the SIFinst and cos ( SZA ) -based upscaled SIFdaily, especially for cloudy days with a coefficient of determination (R2) that increased from approximately 0.5 to 0.8. Finally, the PAR-based SIFdaily was linked to GPPdaily and compared to the SIFinst or cos ( SZA ) -based SIFdaily. The results indicate that the SIF-GPP correlation can obviously be improved, with an increased R2 from approximately 0.65 to 0.75. Our study confirms the importance of upscaling SIF from the instantaneous to daily scale when linking SIF with GPP and emphasizes the need to take diurnal weather changes into account for SIF temporal upscaling.
Change Detection Based on Multi-Feature Clustering Using Differential Evolution for Landsat Imagery
Authors: Song Mi , Zhong Yanfei , Ma Ailong
Published: October 2018

Change detection (CD) of natural land cover is important for environmental protection and to maintain an ecological balance. The Landsat series of satellites provide continuous observation of the Earth’s surface and is sensitive to reflection of water, soil and vegetation. It offers fine spatial resolutions (15–80 m) and short revisit times (16–18 days). Therefore, Landsat imagery is suitable for monitoring natural land cover changes. Clustering-based CD methods using evolutionary algorithms (EAs) can be applied to Landsat images to obtain optimal changed and unchanged clustering centers (clusters) with minimum clustering index. However, they directly analyze difference image (DI), which finds itself subject to interference by Gaussian noise and local brightness distortion in Landsat data, resulting in false alarms in detection results. In order to reduce image interferences and improve CD accuracy, we proposed an unsupervised CD method based on multi-feature clustering using the differential evolution algorithm (M-DECD) for Landsat Imagery. First, according to characteristics of Landsat data, a multi-feature space is constructed with three elements: Wiener de-noising, detail enhancement, and structural similarity. Then, a CD method based on differential evolution (DE) algorithm and fuzzy clustering is proposed to obtain global optimal clusters in the multi-feature space, and generate a binary change map (CM). In addition, the control parameters of the DE algorithm are adjusted to improve the robustness of M-DECD. The experimental results obtained with four Landsat datasets confirm the effectiveness of M-DECD. Compared with the results of conventional methods and the current state-of-the-art methods based on evolutionary clustering, the detection accuracies of the M-DECD on the Mexico dataset and the Sardinia dataset are very close to the best results. The accuracies of the M-DECD in the Alaska dataset and the large Canada dataset increased by about 3.3% and 11.9%, respectively. This indicates that multiple features are suitable for Landsat images and the DE algorithm is effective in searching for an optimal CD result.
Laboratory Measurements of Subsurface Spatial Moisture Content by Ground-Penetrating Radar (GPR) Diffraction and Reflection Imaging of Agricultural Soils
Authors: Shamir Omer , Goldshleger Naftaly , Basson Uri , Reshef Moshe
Published: October 2018

Soil moisture content (SMC) down to the root zone is a major factor for the efficient cultivation of agricultural crops, especially in arid and semi-arid regions. Precise SMC can maximize crop yields (both quality and quantity), prevent crop damage, and decrease irrigation expenses and water waste, among other benefits. This study focuses on the subsurface spatial electromagnetic mapping of physical properties, mainly moisture content, using a ground-penetrating radar (GPR). In the laboratory, GPR measurements were carried out using an 800 MHz central-frequency antenna and conducted in soil boxes with loess soil type (calcic haploxeralf) from the northern Negev, hamra soil type (typic rhodoxeralf) from the Sharon coastal plain, and grumusol soil type (typic chromoxerets) from the Jezreel valley, Israel. These measurements enabled highly accurate, close-to-real-time evaluations of physical soil qualities (i.e., wave velocity and dielectric constant) connected to SMC. A mixture model based mainly on soil texture, porosity, and effective dielectric constant (permittivity) was developed to measure the subsurface spatial volumetric soil moisture content (VSMC) for a wide range of moisture contents. The analysis of the travel times for GPR reflection and diffraction waves enabled calculating electromagnetic velocities, effective dielectric constants, and spatial SMC under laboratory conditions, where the required penetration depth is low (root zone). The average VSMC was determined with an average accuracy of ±1.5% and was correlated to a standard oven-drying method, making this spatial method useful for agricultural practice and for the design of irrigation plans for different interfaces.
Ultra-Light Aircraft-Based Hyperspectral and Colour-Infrared Imaging to Identify Deciduous Tree Species in an Urban Environment
Authors: Mozgeris Gintautas , Juodkienė Vytautė , Jonikavičius Donatas , Straigytė Lina , Gadal Sébastien , Ouerghemmi Walid
Published: October 2018

One may consider the application of remote sensing as a trade-off between the imaging platforms, sensors, and data gathering and processing techniques. This study addresses the potential of hyperspectral imaging using ultra-light aircraft for vegetation species mapping in an urban environment, exploring both the engineering and scientific aspects related to imaging platform design and image classification methods. An imaging system based on simultaneous use of Rikola frame format hyperspectral and Nikon D800E adopted colour infrared cameras installed onboard a Bekas X32 manned ultra-light aircraft is introduced. Two test imaging flight missions were conducted in July of 2015 and September of 2016 over a 4000 ha area in Kaunas City, Lithuania. Sixteen and 64 spectral bands in 2015 and 2016, respectively, in a spectral range of 500–900 nm were recorded with colour infrared images. Three research questions were explored assessing the identification of six deciduous tree species: (1) Pre-treatment of spectral features for classification, (2) testing five conventional machine learning classifiers, and (3) fusion of hyperspectral and colour infrared images. Classification performance was assessed by applying leave-one-out cross-validation at the individual crown level and using as a reference at least 100 field inventoried trees for each species. The best-performing classification algorithm—multilayer perceptron, using all spectral properties extracted from the hyperspectral images—resulted in a moderate classification accuracy. The overall classification accuracy was 63%, Cohen’s Kappa was 0.54, and the species-specific classification accuracies were in the range of 51–72%. Hyperspectral images resulted in significantly better tree species classification ability than the colour infrared images and simultaneous use of spectral properties extracted from hyperspectral and colour infrared images improved slightly the accuracy over the 2015 image. Even though classifications using hyperspectral data cubes of 64 bands resulted in relatively larger accuracies than with 16 bands, classification error matrices were not statistically different. Alternative imaging platforms (like an unmanned aerial vehicle and a Cessna 172 aircraft) and settings of the flights were discussed using simulated imaging projects assuming the same study area and field of application. Ultra-light aircraft-based hyperspectral and colour-infrared imaging was considered to be a technically and economically sound solution for urban green space inventories to facilitate tree mapping, characterization, and monitoring.
Adaptive Beamforming Applied to OFDM Systems
Authors: De Sousa Tiago F. B. , Arantes Dalton S. , Fernandes Marcelo A. C.
Published: October 2018

This work proposes an adaptive beamforming scheme applied to time domain, pre-FFT (Fast Fourier Transformation), Orthogonal Frequency-Division Multiplexing (OFDM) systems. This scheme improves the performance and the capacity of OFDM systems, using a supervised adaptive algorithm, with frequency domain multiplexed pilots of the OFDM system as a reference. The simplicity of the proposed structure, as well as the method used to obtain reference signals for the adaptive beamforming, are essential aspects that distinguish this paper from other publications. Details on the operation of the proposed scheme, as well as the performance curves, are presented in this manuscript. The proposal investigated here allows a significant reduction in the guard interval of the OFDM system, thereby increasing its robustness or transmission capacity.
Improved Point-Line Feature Based Visual SLAM Method for Indoor Scenes
Authors: Wang Runzhi , Di Kaichang , Wan Wenhui , Wang Yongkang
Published: October 2018

In the study of indoor simultaneous localization and mapping (SLAM) problems using a stereo camera, two types of primary features—point and line segments—have been widely used to calculate the pose of the camera. However, many feature-based SLAM systems are not robust when the camera moves sharply or turns too quickly. In this paper, an improved indoor visual SLAM method to better utilize the advantages of point and line segment features and achieve robust results in difficult environments is proposed. First, point and line segment features are automatically extracted and matched to build two kinds of projection models. Subsequently, for the optimization problem of line segment features, we add minimization of angle observation in addition to the traditional re-projection error of endpoints. Finally, our model of motion estimation, which is adaptive to the motion state of the camera, is applied to build a new combinational Hessian matrix and gradient vector for iterated pose estimation. Furthermore, our proposal has been tested on EuRoC MAV datasets and sequence images captured with our stereo camera. The experimental results demonstrate the effectiveness of our improved point-line feature based visual SLAM method in improving localization accuracy when the camera moves with rapid rotation or violent fluctuation.
Three-Dimensional Imaging Method for Array ISAR Based on Sparse Bayesian Inference
Authors: Jiao Zekun , Ding Chibiao , Chen Longyong , Zhang Fubo
Published: October 2018

The problem of synthesis scatterers in inverse synthetic aperture radar (ISAR) make it difficult to realize high-resolution three-dimensional (3D) imaging. Radar array provides an available solution to this problem, but the resolution is restricted by limited aperture size and number of antennas, leading to deterioration of the 3D imaging performance. To solve these problems, we propose a novel 3D imaging method with an array ISAR system based on sparse Bayesian inference. First, the 3D imaging model using a sparse linear array is introduced. Then the elastic net estimation and Bayesian information criterion are introduced to fulfill model order selection automatically. Finally, the sparse Bayesian inference is adopted to realize super-resolution imaging and to get the 3D image of target of interest. The proposed method is used to process real radar data of a Ku band array ISAR system. The results show that the proposed method can effectively solve the problem of synthesis scatterers and realize super-resolution 3D imaging, which verify the practicality of our proposed method.
Research on a Handheld 3D Laser Scanning System for Measuring Large-Sized Objects
Authors: Wang Xiaomin , Xie Zexiao , Wang Kun , Zhou Liqin
Published: October 2018

A handheld 3D laser scanning system is proposed for measuring large-sized objects on site. This system is mainly composed of two CCD cameras and a line laser projector, in which the two CCD cameras constitute a binocular stereo vision system to locate the scanner’s position in the fixed workpiece coordinate system online, meanwhile the left CCD camera and the laser line projector constitute a structured light system to get the laser lines modulated by the workpiece features. The marked points and laser line are both obtained in the coordinate system of the left camera in each moment. To get the workpiece outline, the handheld scanner’s position is evaluated online by matching up the marked points got by the binocular stereo vision system and those in the workpiece coordinate system measured by a TRITOP system beforehand; then the laser line with workpiece’s features got at this moment is transformed into the fixed workpiece coordinate system. Finally, the 3D information composed by the laser lines can be reconstructed in the workpiece coordinate system. A ball arm with two standard balls, which is placed on a glass plate with many marked points randomly stuck on, is measured to test the system accuracy. The distance errors between the two balls are within ±0.05 mm, the radius errors of the two balls are all within ±0.04 mm, the distance errors from the scatter points to the fitted sphere are distributed evenly, within ±0.25 mm, without accumulated errors. Measurement results of two typical workpieces show that the system can measure large-sized objects completely with acceptable accuracy and have the advantage of avoiding some deficiencies, such as sheltering and limited measuring range.
Underwater Target Detection and 3D Reconstruction System Based on Binocular Vision
Authors: Huo Guanying , Wu Ziyin , Li Jiabiao , Li Shoujun
Published: October 2018

To better solve the problem of target detection in marine environment and to deal with the difficulty of 3D reconstruction of underwater target, a binocular vision-based underwater target detection and 3D reconstruction system is proposed in this paper. Two optical sensors are used as the vision of the system. Firstly, denoising and color restoration are performed on the image sequence acquired by the vision of the system and the underwater target is segmented and extracted according to the image saliency using the super-pixel segmentation method. Secondly, aiming to reduce mismatch, we improve the semi-global stereo matching method by strictly constraining the matching in the valid target area and then optimizing the basic disparity map within each super-pixel area using the least squares fitting interpolation method. Finally, based on the optimized disparity map, triangulation principle is used to calculate the three-dimensional data of the target and the 3D structure and color information of the target can be given by MeshLab. The experimental results show that for a specific size underwater target, the system can achieve higher measurement accuracy and better 3D reconstruction effect within a suitable distance.
Efficient Hybrid Emergency Aware MAC Protocol for Wireless Body Sensor Networks
Authors: Bou Dargham Nadine , Makhoul Abdallah , Bou Abdo Jacques , Demerjian Jacques , Guyeux Christophe
Published: October 2018

In Body Sensor Networks (BSNs), two types of events should be addressed: periodic and emergency events. Traffic rate is usually low during periodic observation, and becomes very high upon emergency. One of the main and challenging requirements of BSNs is to design Medium Access Control (MAC) protocols that guarantee immediate and reliable transmission of data in emergency situations, while maintaining high energy efficiency in non-emergency conditions. In this paper, we propose a new emergency aware hybrid DTDMA/DS-CDMA protocol that can accommodate BSN traffic variations by addressing emergency and periodic traffic requirements. It takes advantage of the high delay efficiency of DS-CDMA in traffic burst, and the high energy efficiency of DTDMA in periodic traffic. The proposed scheme is evaluated in terms of delay, packet drop percentage, and energy consumption. Different OPNET simulations are performed for various number of nodes carrying emergency data, and for various payload sizes. The protocol performance is compared to other existing hybrid protocols. Results show that the proposed scheme outperforms the others in terms of delay and packet drop percentage for different number of nodes carrying emergency data, as well as for different payload sizes. It also offers the highest energy efficiency during periodic observation, while adjusting the energy consumption during emergency by assigning spreading codes only to nodes holding emergency data.