bluuebunny/crossref_metadata_2025 huggingface dataset:
CTAB-Assisted Fabrication of Bi2WO6 Thin Nanoplates with High Adsorption and Enhanced Visible Light-Driven Photocatalytic Performance
Authors: Zhou Yuxue , Lv Pengfei , Meng Xiangdong , Tang Yanping , Huang Pingping , Chen Xiaobing , Shen Xiaoshuang , Zeng Xianghua
Published: May 2017

Two-dimensional thin Bi2WO6 nanoplates have been fabricated using a cetyltrimethylammonium bromide (CTAB)-assisted hydrothermal method. We investigated the proposed formation mechanism based on the crystalline structures of the thin Bi2WO6 nanoplates. The high adsorption ability and excellent visible-light driven photocatalytic activities of the Bi2WO6 nanoplates were illustrated, in view of exposed (001) facets of nanoplates possessing faster separation of photo-generated charge carriers and increased catalytically active sites. Such a cost-effective way to obtain Bi2WO6 nanoplates offers new possibilities for the design of adsorptive semiconductor photocatalysts with strengthened photocatalytic activities.
Oriented Growth of α-MnO2 Nanorods Using Natural Extracts from Grape Stems and Apple Peels
Authors: Sanchez-Botero Lina , Herrera Adriana , Hinestroza Juan
Published: May 2017

We report on the synthesis of alpha manganese dioxide (α-MnO2) nanorods using natural extracts from Vitis vinifera grape stems and Malus domestica ‘Cortland’ apple peels. We used a two-step method to produce highly crystalline α-MnO2 nanorods: (1) reduction of KMnO4 in the presence of natural extracts to initiate the nucleation process; and (2) a thermal treatment to enable further solid-state growth of the nuclei. Transmission electron microscopy (TEM) and field emission scanning electron microscopy (FESEM) images provided direct evidence of the morphology of the nanorods and these images were used to propose nucleation and growth mechanisms. We found that the α-MnO2 nanorods synthesized using natural extracts exhibit structural and magnetic properties similar to those of nanoparticles synthesized via traditional chemical routes. Furthermore, Fourier transform infrared (FTIR) shows that the particle growth of the α-MnO2 nanorods appears to be controlled by the presence of natural capping agents during the thermal treatment. We also evaluated the catalytic activity of the nanorods in the degradation of aqueous solutions of indigo carmine dye, highlighting the potential use of these materials to clean dye-polluted water.
Potential Impact of Nutrition on Immune System Recovery from Heavy Exertion: A Metabolomics Perspective
Authors: Nieman David , Mitmesser Susan
Published: May 2017

This review describes effective and ineffective immunonutrition support strategies for the athlete, with a focus on the benefits of carbohydrates and polyphenols as determined from metabolomics-based procedures. Athletes experience regular cycles of physiological stress accompanied by transient inflammation, oxidative stress, and immune perturbations, and there are increasing data indicating that these are sensitive to nutritional influences. The most effective nutritional countermeasures, especially when considered from a metabolomics perspective, include acute and chronic increases in dietary carbohydrate and polyphenols. Carbohydrate supplementation reduces post-exercise stress hormone levels, inflammation, and fatty acid mobilization and oxidation. Ingestion of fruits high in carbohydrates, polyphenols, and metabolites effectively supports performance, with added benefits including enhancement of oxidative and anti-viral capacity through fruit metabolites, and increased plasma levels of gut-derived phenolics. Metabolomics and lipidomics data indicate that intensive and prolonged exercise is associated with extensive lipid mobilization and oxidation, including many components of the linoleic acid conversion pathway and related oxidized derivatives called oxylipins. Many of the oxylipins are elevated with increased adiposity, and although low in resting athletes, rise to high levels during recovery. Future targeted lipidomics-based studies will help discover whether n-3-polyunsaturated fatty acid (n-3-PUFA) supplementation enhances inflammation resolution in athletes post-exercise.
Effects of Ketogenic Diets on Cardiovascular Risk Factors: Evidence from Animal and Human Studies
Authors: Kosinski Christophe , Jornayvaz François
Published: May 2017

The treatment of obesity and cardiovascular diseases is one of the most difficult and important challenges nowadays. Weight loss is frequently offered as a therapy and is aimed at improving some of the components of the metabolic syndrome. Among various diets, ketogenic diets, which are very low in carbohydrates and usually high in fats and/or proteins, have gained in popularity. Results regarding the impact of such diets on cardiovascular risk factors are controversial, both in animals and humans, but some improvements notably in obesity and type 2 diabetes have been described. Unfortunately, these effects seem to be limited in time. Moreover, these diets are not totally safe and can be associated with some adverse events. Notably, in rodents, development of nonalcoholic fatty liver disease (NAFLD) and insulin resistance have been described. The aim of this review is to discuss the role of ketogenic diets on different cardiovascular risk factors in both animals and humans based on available evidence.
Advising Consumption of Green Vegetables, Beef, and Full-Fat Dairy Products Has No Adverse Effects on the Lipid Profiles in Children
Authors: Van der Gaag Ellen , Wieffer Romy , Van der Kraats Judith
Published: May 2017

In children, little is known about lipid profiles and the influence of dietary habits. In the past, we developed a dietary advice for optimizing the immune system, which comprised green vegetables, beef, whole milk, and full-fat butter. However, there are concerns about a possible negative influence of the full-fat dairy products of the diet on the lipid profile. We investigated the effect of the developed dietary advice on the lipid profile and BMI (body mass index)/BMI-z-score of children. In this retrospective cohort study, we included children aged 1–16 years, of whom a lipid profile was determined in the period between June 2011 and November 2013 in our hospital. Children who adhered to the dietary advice were assigned to the exposed group and the remaining children were assigned to the unexposed group. After following the dietary advice for at least three months, there was a statistically significant reduction in the cholesterol/HDL (high-density lipoproteins) ratio (p < 0.001) and non-HDL-cholesterol (p = 0.044) and a statistically significant increase in the HDL-cholesterol (p = 0.009) in the exposed group, while there was no difference in the BMI and BMI z-scores. The dietary advice has no adverse effect on the lipid profile, BMI, and BMI z-scores in children, but has a significant beneficial effect on the cholesterol/HDL ratio, non-HDL-cholesterol, and the HDL-cholesterol.
Multifaceted Health Benefits of Mangifera indica L. (Mango): The Inestimable Value of Orchards Recently Planted in Sicilian Rural Areas
Authors: Lauricella Marianna , Emanuele Sonia , Calvaruso Giuseppe , Giuliano Michela , D’Anneo Antonella
Published: May 2017

Historically, Mangifera indica L. cultivations have been widely planted in tropical areas of India, Africa, Asia, and Central America. However, at least 20 years ago its spreading allowed the development of some cultivars in Sicily, an island to the south of Italy, where the favourable subtropical climate and adapted soils represent the perfect field to create new sources of production for the Sicilian agricultural supply chain. Currently, cultivations of Kensington Pride, Keitt, Glenn, Maya, and Tommy Atkins varieties are active in Sicily and their products meet the requirements of local and European markets. Mango plants produce fleshy stone fruits rich in phytochemicals with an undisputed nutritional value for its high content of polyphenolics and vitamins. This review provides an overview of the antioxidant, anti-inflammatory, and anticancer properties of mango, a fruit that should be included in everyone’s diet for its multifaceted biochemical actions and health-enhancing properties.
Urban–Rural Disparities in Energy Intake and Contribution of Fat and Animal Source Foods in Chinese Children Aged 4–17 Years
Authors: Zhang Ji , Wang Dantong , Eldridge Alison , Huang Feifei , Ouyang Yifei , Wang Huijun , Zhang Bing
Published: May 2017

Objective: Excessive energy intake and poor food choices are major health concerns associated with overweight and obesity risk. This study aims to explore disparities in energy intake and the contributions from fat and animal source foods among Chinese school-aged children and adolescents in different communities based on urbanization levels. Design: Three consecutive 24 h recalls were used to assess dietary intake. Subjects’ height and weight were measured using standard equipment. Standardized questionnaires were used to collect household demographic and socioeconomic characteristics by trained interviewers. Setting: The 2011 China Health and Nutrition Survey is part of an ongoing longitudinal household survey across 228 communities in nine provinces and three mega-cities in China. Subjects consisted of children aged 4–17 years (n = 1866; 968 boys and 898 girls). Results: The estimated average energy intake was 1604 kcal/day (1706 kcal/day for boys and 1493 kcal/day for girls). Proportions of energy from fat and animal source foods were 36.8% and 19.8% respectively and did not differ by gender. Total energy intake showed no significant disparity, but the proportion of energy from fat and animal source foods increased with increasing urbanization levels and increasing household income level. The largest difference in consumption percentages between children in rural areas and those in highly urban areas was for milk and dairy products (14.8% versus 74.4%) and the smallest difference was seen in percent consuming meat and meat products (83.1% versus 97.1%). Conclusions: Results of this study highlight the need for developing and implementing community-specific strategies to improve Chinese children’s diet quality.
Intensification of Electrochemical Performance of AA7075 Aluminum Alloys Using Rare Earth Functionalized Water-Based Polymer Coatings
Authors: Ferrel-Álvarez Atzin , Domínguez-Crespo Miguel , Torres-Huerta Aidé , Cong Hongbo , Brachetti-Sibaja Silvia , López-Oyama Ana
Published: May 2017

This work reports the effect of different amounts of ceria nanoparticles on UV resistance and barrier properties of water-based polyurethane (WPU) on glass and AA7075 aluminum alloy substrates. Hybrid coatings were synthesized from an aliphatic WPU–HDI (1,6-hexamethylene di-isocyanate) and cerium oxide nanoparticles (CeO2) with an average particle size distribution of about 25 nm. Different nanoceria amounts (1, 3 and 5 wt %), mixing times (30, 60 and 120 min) and methods to disperse the nanostructures into the polymer matrix (magnetic stirring and sonication) were evaluated. Initially, the dispersion of CeO2 nanoparticles embedded in the polymer matrix and displacement in the corrosion potential (Ecorr) were analyzed by confocal scanning laser microscopy (CLSM) and open circuit potential (Eocp) measurements. According to this behavior, the dispersion and water ratio required during the polymerization process were established. Coated samples obtained after the second stage were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM) and optical light microscopy. In addition, optical measurements on glass substrates were evaluated with UV-vis spectroscopy. The effect of the synthesis parameters on the corrosion behavior of WPU–CeO2/AA7075 systems was investigated with Eocp and electrochemical impedance spectroscopy (EIS) in a 3 wt % NaCl solution. In addition, the films were subjected to 180 h of accelerated weathering. The results show that the combination of specific nanoceria addition with the optimal synthesis parameters enhances optical transparence of WPU as well as barrier properties. From these, the coated specimens prepared with 3 wt % of ceria content and sonicated for 30 min showed a highly dispersed system, which results in a high charge transfer resistance. The observed properties in clear coats deposited on metallic substrates suggested an improvement in the appearance and less deterioration in UV exposure in comparison with pure WPU, enhancing the protective properties of the AA7075 aluminum alloy when exposed to a corrosive medium.
Synthesis and Study of Shape-Memory Polymers Selectively Induced by Near-Infrared Lights via In Situ Copolymerization
Authors: Fang Tianyu , Fang Liang , Chen Shunping , Li Lingyu , Huang Hengming , Lu Chunhua , Xu Zhongzi
Published: May 2017

Shape-memory polymers (SMPs) selectively induced by near-infrared lights of 980 or 808 nm were synthesized via free radical copolymerization. Methyl methacrylate (MMA) monomer, ethylene glycol dimethylacrylate (EGDMA) as a cross-linker, and organic complexes of Yb(TTA)2AAPhen or Nd(TTA)2AAPhen containing a reactive ligand of acrylic acid (AA) were copolymerized in situ. The dispersion of the organic complexes in the copolymer matrix was highly improved, while the transparency of the copolymers was negligibly influenced in comparison with the pristine cross-linked PMMA. In addition, the thermal resistance of the copolymers was enhanced with the complex loading, while their glass transition temperature, cross-linking level, and mechanical properties were to some extent reduced. Yb(TTA)2AAPhen and Nd(TTA)2AAPhen provided the prepared copolymers with selective photothermal effects and shape-memory functions for 980 and 808 nm NIR lights, respectively. Finally, smart optical devices which exhibited localized transparency or diffraction evolution procedures were demonstrated based on the prepared copolymers, owing to the combination of good transparency and selective light wavelength responsivity.
Osteochondral Regeneration Induced by TGF-β Loaded Photo Cross-Linked Hyaluronic Acid Hydrogel Infiltrated in Fused Deposition-Manufactured Composite Scaffold of Hydroxyapatite and Poly (Ethylene Glycol)-Block-Poly(ε-Caprolactone)
Authors: Hsieh Yi-Ho , Hsieh Ming-Fa , Fang Chih-Hsiang , Jiang Cho-Pei , Lin Bojain , Lee Hung-Maan
Published: May 2017

The aim of this study was to report the fabrication of porous scaffolds with pre-designed internal pores using a fused deposition modeling (FDM) method. Polycaprolactone (PCL) is a suitable material for the FDM method due to the fact it can be melted and has adequate flexural modulus and strength to be formed into a filament. In our study, the filaments of methoxy poly(ethylene glycol)-block-poly(ε-caprolactone) having terminal groups of carboxylic acid were deposited layer by layer. Raw materials having a weight ratio of hydroxyapatite (HAp) to polymer of 1:2 was used for FDM. To promote cell adhesion, amino groups of the Arg-Gly-Asp(RGD) peptide were condensed with the carboxylic groups on the surface of the fabricated scaffold. Then the scaffold was infiltrated with hydrogel of glycidyl methacrylate hyaluronic acid loading with 10 ng/mL of TGF-β1 and photo cross-linked on the top of the scaffolds. Serious tests of mechanical and biological properties were performed in vitro. HAp was found to significantly increase the compressive strength of the porous scaffolds. Among three orientations of the filaments, the lay down pattern 0°/90° scaffolds exhibited the highest compressive strength. Fluorescent staining of the cytoskeleton found that the osteoblast-like cells and stem cells well spread on RGD-modified PEG-PCL film indicating a favorable surface for the proliferation of cells. An in vivo test was performed on rabbit knee. The histological sections indicated that the bone and cartilage defects produced in the knees were fully healed 12 weeks after the implantation of the TGF-β1 loaded hydrogel and scaffolds, and regenerated cartilage was hyaline cartilage as indicated by alcian blue and periodic acid-schiff double staining.
Investigation on the Influence of Chain Extenders on the Performance of One-Component Moisture-Curable Polyurethane Adhesives
Authors: Tan Chen , Tirri Teija , Wilen Carl-Eric
Published: May 2017

In this work, a number of chain extended moisture-curable urethane prepolymers were synthesized in order to develop isocyanate terminated urethane prepolymer formulations that would simultaneously display both high adhesive strength and low viscosity. Proton nuclear magnetic resonance spectroscopy (1H-NMR), size exclusion chromatography (SEC), differential scanning calorimetry (DSC), and Brookfield viscometry were utilized for characterizing the prepared urethane prepolymers. In addition, the adhesion strength of the cured prepolymers was determined by tensile shear strength test according to the DIN EN (Deutsches Institut für Normung, the German Institute for Standardization) 1465 standard. Especially, the role of different types of linear (butanediol, pentanediol) and branched chain extenders (dipropyleneglycol (di-PPG), tripropyleneglycol (tri-PPG) and the influence of their dosage on the degree of microphase separation between hard segments (HS) and soft segments (SS) in urethane prepolymers were studied. Furthermore, the benefits of utilizing either a one-step versus a two-step polymerization process were investigated. The results revealed that the extent of phase separation of different urethane prepolymers was dependent on the extent of hydrogen bonding interactions which was extensively studied by attenuated total reflectance infrared spectroscopy (ATR-FTIR). The incorporation of branched chain extenders (di-PPG and tri-PPG) did not result in notable phase separation between hard segments and soft segments, while linear chain extenders (pentanediol and butanediol) readily promoted phase separation. The degree of phase separation was particularly pronounced for butanediol, and when the linear chain extender ratio was higher than or equal to 0.74. Compared with a two-stage process, one-stage process produced more randomly distributed polymer chains with highly dispersed hard segments. Thus, urethane prepolymers exhibiting strong adhesive strength with simultaneously low viscosity were successfully developed by systematic adjustment of structural parameters.
Growing Economic Inequality and Its (Partially) Political Roots
Authors: Schlozman Kay , Brady Henry , Verba Sidney
Published: May 2017

Growing economic inequality fosters inequality in the political processes of American democracy. Since the 1970’s inequalities in earnings and wealth have increased dramatically in the United States creating a higher level of inequality in disposable income than in other developed democracies. The United States also lags behind other rich nations in the way it provides for those at the bottom of the income distribution, and there is no evidence that the opportunities for success promised by the American Dream compensate for inequality in America. Technological and economic developments are significant causes of this growing economic inequality. The role of politics is more controversial, but government policy influences the distribution of income and education by the way it determines government benefits, taxes and the way markets function. For a number of reasons—including, most importantly, the relationship between education and income and the ability of the affluent to make large campaign donations—those who are economically well-off speak more loudly in politics. They are more likely to engage in most forms of individual political participation—not only ones that involve using cash but also ones that cost nothing except time. Moreover, when it comes to political voice through organizations, a professionalized domain dominated by hired experts in which the volume of political voice can be altered to reflect available economic resources, affluent interests are more likely to be organized and active. This essay considers the growing economic inequalities that form an important part of the backdrop for unequal political voice.
The Limits of Machine Ethics
Authors: Lumbreras Sara
Published: May 2017

Machine Ethics has established itself as a new discipline that studies how to endow autonomous devices with ethical behavior. This paper provides a general framework for classifying the different approaches that are currently being explored in the field of machine ethics and introduces considerations that are missing from the current debate. In particular, law-based codes implemented as external filters for action—which we have named filtered decision making—are proposed as the basis for future developments. The emergence of values as guides for action is discussed, and personal language –together with subjectivity- are indicated as necessary conditions for this development. Last, utilitarian approaches are studied and the importance of objective expression as a requisite for their implementation is stressed. Only values expressed by the programmer in a public language—that is, separate of subjective considerations—can be evolved in a learning machine, therefore establishing the limits of present-day machine ethics.
Monstrosities: Religion, Identity and Belief
Authors: Davies Douglas , Thate Michael
Published: May 2017

In the summer of 1816, a young woman of nineteen eloped with the poet Percy Bysshe Shelley to Geneva, Switzerland.[...]
Object-Based Detection of Linear Kinematic Features in Sea Ice
Authors: Linow Stefanie , Dierking Wolfgang
Published: May 2017

Inhomogenities in the sea ice motion field cause deformation zones, such as leads, cracks and pressure ridges. Due to their long and often narrow shape, those structures are referred to as Linear Kinematic Features (LKFs). In this paper we specifically address the identification and characterization of variations and discontinuities in the spatial distribution of the total deformation, which appear as LKFs. The distribution of LKFs in the ice cover of the polar oceans is an important factor influencing the exchange of heat and matter at the ocean-atmosphere interface. Current analyses of the sea ice deformation field often ignore the spatial/geographical context of individual structures, e.g., their orientation relative to adjacent deformation zones. In this study, we adapt image processing techniques to develop a method for LKF detection which is able to resolve individual features. The data are vectorized to obtain results on an object-based level. We then apply a semantic postprocessing step to determine the angle of junctions and between crossing structures. The proposed object detection method is carefully validated. We found a localization uncertainty of 0.75 pixel and a length error of 12% in the identified LKFs. The detected features can be individually traced to their geographical position. Thus, a wide variety of new metrics for ice deformation can be easily derived, including spatial parameters as well as the temporal stability of individual features.
Cost-Effective Class-Imbalance Aware CNN for Vehicle Localization and Categorization in High Resolution Aerial Images
Authors: Li Feimo , Li Shuxiao , Zhu Chengfei , Lan Xiaosong , Chang Hongxing
Published: May 2017

Joint vehicle localization and categorization in high resolution aerial images can provide useful information for applications such as traffic flow structure analysis. To maintain sufficient features to recognize small-scaled vehicles, a regions with convolutional neural network features (R-CNN) -like detection structure is employed. In this setting, cascaded localization error can be averted by equally treating the negatives and differently typed positives as a multi-class classification task, but the problem of class-imbalance remains. To address this issue, a cost-effective network extension scheme is proposed. In it, the correlated convolution and connection costs during extension are reduced by feature map selection and bi-partite main-side network construction, which are realized with the assistance of a novel feature map class-importance measurement and a new class-imbalance sensitive main-side loss function. By using an image classification dataset established from a set of traditional real-colored aerial images with 0.13 m ground sampling distance which are taken from the height of 1000 m by an imaging system composed of non-metric cameras, the effectiveness of the proposed network extension is verified by comparing with its similarly shaped strong counter-parts. Experiments show an equivalent or better performance, while requiring the least parameter and memory overheads are required.
Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing
Authors: Chen Wei , Fan Aiping , Yan Lei
Published: May 2017

The newly released MODIS Collection 6 aerosol products have been widely used to evaluate fine particulate matter with a 10 km Dark Target aerosol optic depth (DT AOD) product, a new 3 km DT AOD product and an enhanced Deep Blue (DB) AOD product. However, the representativeness of MODIS AOD products under different air quality conditions remains unclear. In this study, we obtained all three types of MODIS Terra AOD from 2001 to 2015 and Aqua AOD from 2003 to 2015 for the Beijing region to study the performance of the different AOD products (Collection 6) under different air quality situations. The validation of three MODIS AOD products suggests that DB AOD has the highest accuracy with an expected error (EE) envelope (containing at least 67% of the matchups on a scatter plot) of 0.05 + 0.15τ, followed by 10 km DT AOD (0.08 + 0.2τ) and 3 km DT AOD (0.35 + 0.15τ), specifically for Beijing. Near-surface PM2.5 concentrations during the passage of MODIS from 2013 to 2015 were also obtained to categorize air quality as unpolluted, moderately, and heavily polluted, as well as to analyze the performance of the different AOD products under different air quality conditions. Very few MODIS 3 km DT retrievals appeared on heavily polluted days, making it almost impossible to play an effective role in air quality applications in Beijing. While the DB AOD allowed for considerable retrievals under all air quality conditions, it had a coarse spatial resolution. These results demonstrate that the MODIS 3 km DT AOD product may not be the appropriate proxy to be used in the satellite retrieval of surface PM2.5, especially for those areas with frequent haze-fog events like Beijing.
Classification for High Resolution Remote Sensing Imagery Using a Fully Convolutional Network
Authors: Fu Gang , Liu Changjun , Zhou Rong , Sun Tao , Zhang Qijian
Published: May 2017

As a variant of Convolutional Neural Networks (CNNs) in Deep Learning, the Fully Convolutional Network (FCN) model achieved state-of-the-art performance for natural image semantic segmentation. In this paper, an accurate classification approach for high resolution remote sensing imagery based on the improved FCN model is proposed. Firstly, we improve the density of output class maps by introducing Atrous convolution, and secondly, we design a multi-scale network architecture by adding a skip-layer structure to make it capable for multi-resolution image classification. Finally, we further refine the output class map using Conditional Random Fields (CRFs) post-processing. Our classification model is trained on 70 GF-2 true color images, and tested on the other 4 GF-2 images and 3 IKONOS true color images. We also employ object-oriented classification, patch-based CNN classification, and the FCN-8s approach on the same images for comparison. The experiments show that compared with the existing approaches, our approach has an obvious improvement in accuracy. The average precision, recall, and Kappa coefficient of our approach are 0.81, 0.78, and 0.83, respectively. The experiments also prove that our approach has strong applicability for multi-resolution image classification.
Impacts of Thermal Time on Land Surface Phenology in Urban Areas
Authors: Krehbiel Cole , Zhang Xiaoyang , Henebry Geoffrey
Published: May 2017

Urban areas alter local atmospheric conditions by modifying surface albedo and consequently the surface radiation and energy balances, releasing waste heat from anthropogenic uses, and increasing atmospheric aerosols, all of which combine to increase temperatures in cities, especially overnight, compared with surrounding rural areas, resulting in a phenomenon called the “urban heat island” effect. Recent rapid urbanization of the planet has generated calls for remote sensing research related to the impacts of urban areas and urbanization on the natural environment. Spatially extensive, high spatial resolution data products are needed to capture phenological patterns in regions with heterogeneous land cover and external drivers such as cities, which are comprised of a mixture of land cover/land uses and experience microclimatic influences. Here we use the 30 m normalized difference vegetation index (NDVI) product from the Web-Enabled Landsat Data (WELD) project to analyze the impacts of urban areas and their surface heat islands on the seasonal development of the vegetated land surface along an urban–rural gradient for 19 cities located in the Upper Midwest of the United States. We fit NDVI observations from 2003–2012 as a quadratic function of thermal time as accumulated growing degree-days (AGDD) calculated from the Moderate-resolution Imaging Spectroradiometer (MODIS) 1 km land surface temperature product to model decadal land surface phenology metrics at 30 m spatial resolution. In general, duration of growing season (measured in AGDD) in green core areas is equivalent to duration of growing season in urban extent areas, but significantly longer than duration of growing season in areas outside of the urban extent. We found an exponential relationship in the difference of duration of growing season between urban and surrounding rural areas as a function of distance from urban core areas for perennial vegetation, with an average magnitude of 669 AGDD (base 0 °C) and the influence of urban areas extending greater than 11 km from urban core areas. At the regional scale, relative change in duration of growing season does not appear to be significantly related to total area of urban extent, population, or latitude. The distance and magnitude that urban areas exert influence on vegetation in and near cities is relatively uniform.
A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data
Authors: Lamprecht Sebastian , Hill Andreas , Stoffels Johannes , Udelhoven Thomas
Published: May 2017

Determining the exact position of a forest inventory plot—and hence the position of the sampled trees—is often hampered by a poor Global Navigation Satellite System (GNSS) signal quality beneath the forest canopy. Inaccurate geo-references hamper the performance of models that aim to retrieve useful information from spatially high remote sensing data (e.g., species classification or timber volume estimation). This restriction is even more severe on the level of individual trees. The objective of this study was to develop a post-processing strategy to improve the positional accuracy of GNSS-measured sample-plot centers and to develop a method to automatically match trees within a terrestrial sample plot to aerial detected trees. We propose a new method which uses a random forest classifier to estimate the matching probability of each terrestrial-reference and aerial detected tree pair, which gives the opportunity to assess the reliability of the results. We investigated 133 sample plots of the Third German National Forest Inventory (BWI, 2011–2012) within the German federal state of Rhineland-Palatinate. For training and objective validation, synthetic forest stands have been modeled using the Waldplaner 2.0 software. Our method has achieved an overall accuracy of 82.7% for co-registration and 89.1% for tree matching. With our method, 60% of the investigated plots could be successfully relocated. The probabilities provided by the algorithm are an objective indicator of the reliability of a specific result which could be incorporated into quantitative models to increase the performance of forest attribute estimations.
Annual and Seasonal Glacier-Wide Surface Mass Balance Quantified from Changes in Glacier Surface State: A Review on Existing Methods Using Optical Satellite Imagery
Authors: Rabatel Antoine , Sirguey Pascal , Drolon Vanessa , Maisongrande Philippe , Arnaud Yves , Berthier Etienne , Davaze Lucas , Dedieu Jean-Pierre , Dumont Marie
Published: May 2017

Glaciers are one of the terrestrial essential climate variables (ECVs) as they respond very sensitively to climate change. A key driver of their response is the glacier surface mass balance that is typically derived from field measurements. It deserves to be quantified over long time scales to better understand the accumulation and ablation processes at the glacier surface and their relationships with inter-annual changes in meteorological conditions and long-term climate changes. Glaciers with in situ monitoring of surface mass balance are scarce at the global scale, and satellite remote sensing provides a powerful tool to increase the number of monitored glaciers. In this study, we present a review of three optical remote sensing methods developed to quantify seasonal and annual glacier surface mass balances. These methodologies rely on the multitemporal monitoring of the end-of-summer snow line for the equilibrium-line altitude (ELA) method, the annual cycle of glacier surface albedo for the albedo method and the mapping of the regional snow cover at the seasonal scale for the snow-map method. Together with a presentation of each method, an application is illustrated. The ELA method shows promising results to quantify annual surface mass balance and to reconstruct multi-decadal time series. The other two methods currently need a calibration on the basis of existing in situ data; however, a generalization of these methods (without calibration) could be achieved. The two latter methods show satisfying results at the annual and seasonal scales, particularly for the summer surface mass balance in the case of the albedo method and for the winter surface mass balance in the case of the snow-map method. The limits of each method (e.g., cloud coverage, debris-covered glaciers, monsoon-regime and cold glaciers), their complementarities and the future challenges (e.g., automating of the satellite images processing, generalization of the methods needing calibration) are also discussed.
Using Space-Time Features to Improve Detection of Forest Disturbances from Landsat Time Series
Authors: Hamunyela Eliakim , Reiche Johannes , Verbesselt Jan , Herold Martin
Published: May 2017

Current research on forest change monitoring using medium spatial resolution Landsat satellite data aims for accurate and timely detection of forest disturbances. However, producing forest disturbance maps that have both high spatial and temporal accuracy is still challenging because of the trade-off between spatial and temporal accuracy. Timely detection of forest disturbance is often accompanied by many false detections, and existing approaches for reducing false detections either compromise the temporal accuracy or amplify the omission error for forest disturbances. Here, we propose to use a set of space-time features to reduce false detections. We first detect potential forest disturbances in the Landsat time series based on two consecutive negative anomalies, and subsequently use space-time features to confirm forest disturbances. A probability threshold is used to discriminate false detections from forest disturbances. We demonstrated this approach in the UNESCO Kafa Biosphere Reserve located in the southwest of Ethiopia by detecting forest disturbances between 2014 and 2016. Our results show that false detections are reduced significantly without compromising temporal accuracy. The user’s accuracy was at least 26% higher than the user’s accuracies obtained when using only temporal information (e.g., two consecutive negative anomalies) to confirm forest disturbances. We found the space-time features related to change in spatio-temporal variability, and spatio-temporal association with non-forest areas, to be the main predictors for forest disturbance. The magnitude of change and two consecutive negative anomalies, which are widely used to distinguish real changes from false detections, were not the main predictors for forest disturbance. Overall, our findings indicate that using a set of space-time features to confirm forest disturbances increases the capacity to reject many false detections, without compromising the temporal accuracy.
Flexible, Low-Cost Sensor Based on Electrolyte Gated Carbon Nanotube Field Effect Transistor for Organo-Phosphate Detection
Authors: Bhatt Vijay , Joshi Saumya , Becherer Markus , Lugli Paolo
Published: May 2017

A flexible enzymatic acetylcholinesterase biosensor based on an electrolyte-gated carbon nanotube field effect transistor is demonstrated. The enzyme immobilization is done on a planar gold gate electrode using 3-mercapto propionic acid as the linker molecule. The sensor showed good sensing capability as a sensor for the neurotransmitter acetylcholine, with a sensitivity of 5.7 μA/decade, and demonstrated excellent specificity when tested against interfering analytes present in the body. As the flexible sensor is supposed to suffer mechanical deformations, the endurance of the sensor was measured by putting it under extensive mechanical stress. The enzymatic activity was inhibited by more than 70% when the phosphate-buffered saline (PBS) buffer was spiked with 5 mg/mL malathion (an organophosphate) solution. The biosensor was successfully challenged with tap water and strawberry juice, demonstrating its usefulness as an analytical tool for organophosphate detection.
Optimal Fusion Estimation with Multi-Step Random Delays and Losses in Transmission
Authors: Caballero-Águila Raquel , Hermoso-Carazo Aurora , Linares-Pérez Josefa
Published: May 2017

This paper is concerned with the optimal fusion estimation problem in networked stochastic systems with bounded random delays and packet dropouts, which unavoidably occur during the data transmission in the network. The measured outputs from each sensor are perturbed by random parameter matrices and white additive noises, which are cross-correlated between the different sensors. Least-squares fusion linear estimators including filter, predictor and fixed-point smoother, as well as the corresponding estimation error covariance matrices are designed via the innovation analysis approach. The proposed recursive algorithms depend on the delay probabilities at each sampling time, but do not to need to know if a particular measurement is delayed or not. Moreover, the knowledge of the signal evolution model is not required, as the algorithms need only the first and second order moments of the processes involved. Some of the practical situations covered by the proposed system model with random parameter matrices are analyzed and the influence of the delays in the estimation accuracy are examined in a numerical example.
An Improved RD Algorithm for Maneuvering Bistatic Forward-Looking SAR Imaging with a Fixed Transmitter
Authors: Yuan Yue , Chen Si , Zhao Huichang
Published: May 2017

In order to improve the azimuth resolution beyond what monostatic synthetic aperture radar (SAR) can achieve in the forward-looking area, an asymmetric configuration bistatic SAR system and its imaging algorithm are proposed in this paper. The transmitter is mounted on a fixed platform in side-looking mode while the receiver moves along a nonlinear trajectory in forward-looking mode. Due to the high velocity and acceleration of the maneuvering platform in both along-track and height direction, the traditional algorithms are no longer applicable. In this paper, a new algorithm based on the high precise 2-D frequency spectrum is proposed, which takes high-order Taylor series expansion terms of the slant range into consideration. The proposed algorithm compensates high-order range-azimuth coupling terms to guarantee the focus accuracy in SAR imaging. The simulation results and error analysis validate the effectiveness of the proposed algorithm and the correctness of our analysis.
Low Power Multi-Hop Networking Analysis in Intelligent Environments
Authors: Etxaniz Josu , Aranguren Gerardo
Published: May 2017

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.
Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms
Authors: Martinek Radek , Kahankova Radana , Nazeran Homer , Konecny Jaromir , Jezewski Janusz , Janku Petr , Bilik Petr , Zidek Jan , Nedoma Jan , Fajkus Marcel
Published: May 2017

This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size μ and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters. The main criterion for optimal parameter selection was the Signal-to-Noise Ratio (SNR). We conducted experiments using signals supplied by the latest version of our LabVIEW-Based Multi-Channel Non-Invasive Abdominal Maternal-Fetal Electrocardiogram Signal Generator, which provides the flexibility and capability of modeling the principal distribution of maternal/fetal ECGs in the human body. Our novel algorithm enabled us to find the optimal settings of the adaptive filters based on maternal surface ECG electrode placements. The experimental results further confirmed the theoretical assumption that the optimal settings of these adaptive filters are dependent on the ECG electrode positions on the maternal body, and therefore, we were able to achieve far better results than without the use of optimization. These improvements in turn could lead to a more accurate detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to establish recommendations for standard electrode placement and find the optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing. Ultimately, diagnostic-grade fetal ECG signals would ensure the reliable detection of fetal hypoxia.
Structural Analysis of Polymer Composites Using Spectral Domain Optical Coherence Tomography
Authors: Shirazi Muhammad , Jeon Mansik , Kim Jeehyun
Published: May 2017

The structural analysis of nylon/graphene oxide (NY/GO) and polyetherblockamide/ trisilinolphenyl-polyhederal oligomeric silsesquioxane (PEBA/t-POSS) composites were performed using high-resolution spectral domain optical coherence tomography (SD-OCT). This optical technology revealed both cross-sectional, as well as sub-layer depth information of sample. The non-destructive real-time imaging demonstrated the nature of defects in the composites. The thickness and location of each defect point in the composites were measured using A-scan analysis on the SD-OCT images. The cross-sectional and volumetric images clearly demonstrate the effectiveness of SD-OCT for composite research, as well as the for industrial quality assurance of polymer materials.
Bath-Ambience—A Mechatronic System for Assisting the Caregivers of Bedridden People
Authors: Bezerra Karolina , Machado José , Carvalho Vítor , Castro Marcelo , Costa Pedro , Matos Demétrio , Soares Filomena
Published: May 2017

The health of older people is receiving special attention and dedication nowadays, with the aim of increasing their general wellbeing and quality of life. Studies into different aspects of the care of the elderly have found that emphasis should be given to solving problems related to bathing in different situations and environments. In particular, it is important to develop new assistive technologies to streamline and ease the burden of a caregiver’s daily tasks. Generally-speaking, in the case of bedridden patients, bathing is typically carried out manually by a caregiver, using towels, sponges, and a water basin. Nevertheless, this apparently simple task needs some precautions in order to avoid the risk of microbial infections, falls and other injuries. With that in mind, this paper presents the design of a portable washing system, called Bath-Ambience, which enables bedridden patients to be bathed efficiently without having to be moved from their position. This portable system can be installed in different situations, both in a domestic setting, and in specialized institutions, and allows the caregiver to perform the bathing tasks without compromising health and safety, thereby making it possible to offer a comfortable and hygienic procedure to patients, improving their quality of life. This paper presents the design of the portable Bath-Ambience washing system, which provides efficient assistance for bathing bedridden patients without moving them to another place. This system is mainly dedicated for integration a smart home application in to allow bathing everywhere.
Multispectral, Fluorescent and Photoplethysmographic Imaging for Remote Skin Assessment
Authors: Spigulis Janis
Published: May 2017

Optical tissue imaging has several advantages over the routine clinical imaging methods, including non-invasiveness (it does not change the structure of tissues), remote operation (it avoids infections) and the ability to quantify the tissue condition by means of specific image parameters. Dermatologists and other skin experts need compact (preferably pocket-size), self-sustaining and easy-to-use imaging devices. The operational principles and designs of ten portable in-vivo skin imaging prototypes developed at the Biophotonics Laboratory of Institute of Atomic Physics and Spectroscopy, University of Latvia during the recent five years are presented in this paper. Four groups of imaging devices are considered. Multi-spectral imagers offer possibilities for distant mapping of specific skin parameters, thus facilitating better diagnostics of skin malformations. Autofluorescence intensity and photobleaching rate imagers show a promising potential for skin tumor identification and margin delineation. Photoplethysmography video-imagers ensure remote detection of cutaneous blood pulsations and can provide real-time information on cardiovascular parameters and anesthesia efficiency. Multimodal skin imagers perform several of the abovementioned functions by taking a number of spectral and video images with the same image sensor. Design details of the developed prototypes and results of clinical tests illustrating their functionality are presented and discussed.