bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing Knowledge-Based Citizen Participation Platform to Support Smart City Decision Making: The Smarticipate Case Study
Authors: Khan Zaheer , Dambruch Jens , Peters-Anders Jan , Sackl Andreas , Strasser Anton , Fröhlich Peter , Templer Simon , Soomro Kamran
Published: April 2017

Citizen participation for social innovation and co-creating urban regeneration proposals can be greatly facilitated by innovative IT systems. Such systems can use Open Government Data, visualise urban proposals in 3D models and provide automated feedback on the feasibility of the proposals. Using such a system as a communication platform between citizens and city administrations provides an integrated top-down and bottom-up urban planning and decision-making approach to smart cities. However, generating automated feedback on citizens’ proposals requires modelling domain-specific knowledge i.e., vocabulary and rules, which can be applied on spatial and temporal 3D models. This paper presents the European Commission funded H2020 smarticipate project that aims to achieve the above challenge by applying it on three smart cities: Hamburg, Rome and RBKC-London. Whilst the proposed system architecture indicates various innovative features, a proof of concept of the automated feedback feature for the Hamburg use case ‘planting trees’ is demonstrated. Early results and lessons learned show that it is feasible to provide automated feedback on citizen-initiated proposals on specific topics. However, it is not straightforward to generalise this feature to cover more complex concepts and conditions which require specifying comprehensive domain languages, rules and appropriate tools to process them. This paper also highlights the strengths of the smarticipate platform, discusses challenges to realise its different features and suggests potential solutions.
A Framework for Stacked-Benefit Analysis of Distribution-Level Energy Storage Deployment
Authors: Dubey Anamika , Chirapongsananurak Pisitpol , Santoso Surya
Published: April 2017

This paper presents a planning framework for integrating energy storage (ES) systems into the distribution system. An ES system is deployed to simultaneously provide multiple benefits, also known as stacked-benefits, for the feeder. The primary and secondary application scenarios for the feeder are identified. The proposed ES deployment approach includes the following steps: (1) size the ES system for primary application; (2) identify optimal ES locations based on both primary and secondary application scenarios; (3) calculate the ES accommodation capacity for each potential location; and (4) develop control methods for ES units and conduct grid impact analysis to demonstrate ES applications. For the selected feeder, the primary application for ES deployment is to provide the N-1 contingency requirement. During normal operating conditions, ES is programmed for multiple secondary applications: voltage management and ancillary services by frequency regulation. A probabilistic approach is presented to obtain the optimal ES size for providing the N-1 contingency requirement. Optimal ES locations are obtained based on secondary application scenarios. Real and reactive power control methods are developed to demonstrate the viability of deploying an ES system for simultaneously providing multiple applications. The simulation results show that ES can successfully provide the stacked-benefits for the distribution circuit. The proposed framework is generic and can be employed for the ES integration analysis of any feeder, with different sets of primary and secondary applications.
Language Mixing and Diachronic Change: American Norwegian Noun Phrases Then and Now
Authors: Riksem Brita
Published: April 2017

This article investigates the diachronic development of language mixing within noun phrases in the heritage language American Norwegian. By comparing data collected in the 1930s and 1940s with recently collected data, I present and discuss patterns showing systematic changes, specifically concerning the categories number and definiteness. Moreover, I propose two potential analyses of these patterns based on an exoskeletal approach to grammar. This theoretical framework crucially separates the abstract syntactic structure from its phonological exponents, and the analyses that are discussed consider both the structure and the exponents as the origins of the change.
Preparation and Characterization of Silica Aerogel Microspheres
Authors: Chen Qifeng , Wang Hui , Sun Luyi
Published: April 2017

Silica aerogel microspheres based on alkali silica sol were synthesized using the emulsion method. The experimental results revealed that the silica aerogel microspheres (4–20 µm in diameter) were mesoporous solids with an average pore diameter ranging from 6 to 35 nm. The tapping densities and specific surface areas of the aerogel microspheres are in the range of 0.112–0.287 g/cm3 and 207.5–660.6 m2/g, respectively. The diameter of the silica aerogel microspheres could be tailored by varying the processing conditions including agitation rate, water/oil ratio, mass ratio of Span 80: Tween 80, and emulsifier concentration. The effects of these parameters on the morphology and textural properties of the synthesized silica aerogel microspheres were systematically investigated. Such silica aerogel microspheres can be used to prepare large-scale silica aerogels at an ambient pressure for applications in separation and high efficiency catalysis, which requires features of high porosity and easy fill and recovery.
Identification of Tight-Binding Plasmepsin II and Falcipain 2 Inhibitors in Aqueous Extracts of Marine Invertebrates by the Combination of Enzymatic and Interaction-Based Assays
Authors: Salas-Sarduy Emir , Guerra Yasel , Covaleda Cortés Giovanni , Avilés Francesc , Chávez Planes María
Published: April 2017

Natural products from marine origin constitute a very promising and underexplored source of interesting compounds for modern biotechnological and pharmaceutical industries. However, their evaluation is quite challenging and requires specifically designed assays to reliably identify the compounds of interest in a highly heterogeneous and interfering context. In the present study, we describe a general strategy for the confident identification of tight-binding protease inhibitors in the aqueous extracts of 62 Cuban marine invertebrates, using Plasmodium falciparum hemoglobinases Plasmepsin II and Falcipain 2 as model enzymes. To this end, we first developed a screening strategy that combined enzymatic with interaction-based assays and then validated screening conditions using five reference extracts. Interferences were evaluated and minimized. The results from the massive screening of such extracts, the validation of several hits by a variety of interaction-based assays and the purification and functional characterization of PhPI, a multifunctional and reversible tight-binding inhibitor for Plasmepsin II and Falcipain 2 from the gorgonian Plexaura homomalla, are presented.
Polymorphs, Proteins, and Nucleation Theory: A Critical Analysis
Authors: Evans John
Published: April 2017

Over the last eight years new theories regarding nucleation, crystal growth, and polymorphism have emerged. Many of these theories were developed in response to observations in nature, where classical nucleation theory failed to account for amorphous mineral precursors, phases, and particle assembly processes that are responsible for the formation of invertebrate mineralized skeletal elements, such as the mollusk shell nacre layer (aragonite polymorph) and the sea urchin spicule (calcite polymorph). Here, we summarize these existing nucleation theories and place them within the context of what we know about biomineralization proteins, which are likely participants in the management of mineral precursor formation, stabilization, and assembly into polymorphs. With few exceptions, much of the protein literature confirms that polymorph-specific proteins, such as those from mollusk shell nacre aragonite, can promote polymorph formation. However, past studies fail to provide important mechanistic insights into this process, owing to variations in techniques, methodologies, and the lack of standardization in mineral assay experimentation. We propose that the way forward past this roadblock is for the protein community to adopt standardized nucleation assays and approaches that are compatible with current and emerging nucleation precursor studies. This will allow cross-comparisons, kinetic observations, and hopefully provide the information that will explain how proteins manage polymorph formation and stabilization.
Na/K Pump and Beyond: Na/K-ATPase as a Modulator of Apoptosis and Autophagy
Authors: Felippe Gonçalves-de-Albuquerque Cassiano , Ribeiro Silva Adriana , Ignácio da Silva Camila , Caire Castro-Faria-Neto Hugo , Burth Patrícia
Published: April 2017

Lung cancer is a leading cause of global cancer deaths. Na/K-ATPase has been studied as a target for cancer treatment. Cardiotonic steroids (CS) trigger intracellular signalling upon binding to Na/K-ATPase. Normal lung and tumour cells frequently express different pump isoforms. Thus, Na/K-ATPase is a powerful target for lung cancer treatment. Drugs targeting Na/K-ATPase may induce apoptosis and autophagy in transformed cells. We argue that Na/K-ATPase has a role as a potential target in chemotherapy in lung cancer treatment. We discuss the effects of Na/K-ATPase ligands and molecular pathways inducing deleterious effects on lung cancer cells, especially those leading to apoptosis and autophagy.
The Pharmacological Effects of Lutein and Zeaxanthin on Visual Disorders and Cognition Diseases
Authors: Jia Yu-Ping , Sun Lei , Yu He-Shui , Liang Li-Peng , Li Wei , Ding Hui , Song Xin-Bo , Zhang Li-Juan
Published: April 2017

Lutein (L) and zeaxanthin (Z) are dietary carotenoids derived from dark green leafy vegetables, orange and yellow fruits that form the macular pigment of the human eyes. It was hypothesized that they protect against visual disorders and cognition diseases, such as age-related macular degeneration (AMD), age-related cataract (ARC), cognition diseases, ischemic/hypoxia induced retinopathy, light damage of the retina, retinitis pigmentosa, retinal detachment, uveitis and diabetic retinopathy. The mechanism by which they are involved in the prevention of eye diseases may be due their physical blue light filtration properties and local antioxidant activity. In addition to their protective roles against light-induced oxidative damage, there are increasing evidences that L and Z may also improve normal ocular function by enhancing contrast sensitivity and by reducing glare disability. Surveys about L and Z supplementation have indicated that moderate intakes of L and Z are associated with decreased AMD risk and less visual impairment. Furthermore, this review discusses the appropriate consumption quantities, the consumption safety of L, side effects and future research directions.
Improved Synthesis of 1-O-Acyl-β-d-Glucopyranose Tetraacetates
Authors: Chen Yu , Lu Huan , Chen Yanyu , Yu Wansheng , Dai Hui , Pan Xianhua
Published: April 2017

An improved synthesis of 1-O-acyl glucosyl esters that avoids the use of expensive Ag reagents as well as the hydrolysis of unstable glucosyl bromides is reported. Notably, β-configuration products were obtained exclusively in good yields.
Nanomaterials as Assisted Matrix of Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for the Analysis of Small Molecules
Authors: Lu Minghua , Yang Xueqing , Yang Yixin , Qin Peige , Wu Xiuru , Cai Zongwei
Published: April 2017

Matrix-assisted laser desorption/ionization (MALDI), a soft ionization method, coupling with time-of-flight mass spectrometry (TOF MS) has become an indispensible tool for analyzing macromolecules, such as peptides, proteins, nucleic acids and polymers. However, the application of MALDI for the analysis of small molecules (<700 Da) has become the great challenge because of the interference from the conventional matrix in low mass region. To overcome this drawback, more attention has been paid to explore interference-free methods in the past decade. The technique of applying nanomaterials as matrix of laser desorption/ionization (LDI), also called nanomaterial-assisted laser desorption/ionization (nanomaterial-assisted LDI), has attracted considerable attention in the analysis of low-molecular weight compounds in TOF MS. This review mainly summarized the applications of different types of nanomaterials including carbon-based, metal-based and metal-organic frameworks as assisted matrices for LDI in the analysis of small biological molecules, environmental pollutants and other low-molecular weight compounds.
Fructose Consumption in the Development of Obesity and the Effects of Different Protocols of Physical Exercise on the Hepatic Metabolism
Authors: Pereira Rodrigo , Botezelli José , Da Cruz Rodrigues Kellen , Mekary Rania , Cintra Dennys , Pauli José , Da Silva Adelino , Ropelle Eduardo , De Moura Leandro
Published: April 2017

Fructose consumption has been growing exponentially and, concomitant with this, the increase in the incidence of obesity and associated complications has followed the same behavior. Studies indicate that fructose may be a carbohydrate with greater obesogenic potential than other sugars. In this context, the liver seems to be a key organ for understanding the deleterious health effects promoted by fructose consumption. Fructose promotes complications in glucose metabolism, accumulation of triacylglycerol in the hepatocytes, and alterations in the lipid profile, which, associated with an inflammatory response and alterations in the redox state, will imply a systemic picture of insulin resistance. However, physical exercise has been indicated for the treatment of several chronic diseases. In this review, we show how each exercise protocol (aerobic, strength, or a combination of both) promote improvements in the obesogenic state created by fructose consumption as an improvement in the serum and liver lipid profile (high-density lipoprotein (HDL) increase and decrease triglyceride (TG) and low-density lipoprotein (LDL) levels) and a reduction of markers of inflammation caused by an excess of fructose. Therefore, it is concluded that the practice of aerobic physical exercise, strength training, or a combination of both is essential for attenuating the complications developed by the consumption of fructose.
Prenatal Exposure to a Maternal High-Fat Diet Affects Histone Modification of Cardiometabolic Genes in Newborn Rats
Authors: Upadhyaya Bijaya , Larsen Tricia , Barwari Shivon , Louwagie Eli , Baack Michelle , Dey Moul
Published: April 2017

Infants born to women with diabetes or obesity are exposed to excess circulating fuels during fetal heart development and are at higher risk of cardiac diseases. We have previously shown that late-gestation diabetes, especially in conjunction with a maternal high-fat (HF) diet, impairs cardiac functions in rat-offspring. This study investigated changes in genome-wide histone modifications in newborn hearts from rat-pups exposed to maternal diabetes and HF-diet. Chromatin-immunoprecipitation-sequencing revealed a differential peak distribution on gene promoters in exposed pups with respect to acetylation of lysines 9 and 14 and to trimethylation of lysines 4 and 27 in histone H3 (all, false discovery rate, FDR < 0.1). In the HF-diet exposed offspring, 54% of the annotated genes showed the gene-activating mark trimethylated lysine 4. Many of these genes (1) are associated with the “metabolic process” in general and particularly with “positive regulation of cholesterol biosynthesis” (FDR = 0.03); (2) overlap with 455 quantitative trait loci for blood pressure, body weight, serum cholesterol (all, FDR < 0.1); and (3) are linked to cardiac disease susceptibility/progression, based on disease ontology analyses and scientific literature. These results indicate that maternal HF-diet changes the cardiac histone signature in offspring suggesting a fuel-mediated epigenetic reprogramming of cardiac tissue in utero.
Response to Comments by Vuksan V. et al., Nutrients 2017, 9, 398, Regarding an Article by Solah V.A. et al., Nutrients 2017, 9, 149
Authors: Solah Vicky , Kerr Deborah , Hunt Wendy , Johnson Stuart , Boushey Carol , Delp Edward , Meng Xingqiong , Gahler Roland , James Anthony , Mukhtar Aqif , Fenton Haelee , Wood Simon
Published: April 2017

To the Editor: We have read the comments by Dr. Vuksan regarding our article entitled “Effect of Fibre Supplementation on Body Weight and Composition, Frequency of Eating and Dietary Choice in Overweight Individuals” as published in Nutrients in February 2017 [1].[...]
“Eat as If You Could Save the Planet and Win!” Sustainability Integration into Nutrition for Exercise and Sport
Authors: Meyer Nanna , Reguant-Closa Alba
Published: April 2017

Today’s industrial food production contributes significantly to environmental degradation. Meat production accounts for the largest impact, including greenhouse gas emissions, land and water use. While food production and consumption are important aspects when addressing climate change, this article focuses predominantly on dietary change that promotes both health for planet and people with focus on athletes. Healthy, sustainable eating recommendations begin to appear in various governmental guidelines. However, there remains resistance to the suggested reductions in meat consumption. While food citizens are likely to choose what is good for them and the planet, others may not, unless healthy eating initiatives integrate creative food literacy approaches with experiential learning as a potential vehicle for change. This concept paper is organized in three sections: (1) Environmental impact of food; (2) health and sustainability connections; and (3) application in sports and exercise. For active individuals, this article focuses on the quantity of protein, highlighting meat and dairy, and quality of food, with topics such as organic production and biodiversity. Finally, the timing of when to integrate sustainability principles in sport nutrition is discussed, followed by practical applications for education and inclusion in team, institutional, and event operations.
Curcumin Inhibits Apoptosis of Chondrocytes through Activation ERK1/2 Signaling Pathways Induced Autophagy
Authors: Li Xiaodong , Feng Kai , Li Jiang , Yu Degang , Fan Qiming , Tang Tingting , Yao Xiao , Wang Xiaoqing
Published: April 2017

Osteoarthritis (OA) is an inflammatory disease of load-bearing synovial joints that is currently treated with drugs that exhibit numerous side effects and are only temporarily effective in treating pain, the main symptom of the disease. Consequently, there is an acute need for novel, safe, and more effective chemotherapeutic agents for the treatment of osteoarthritis and related arthritic diseases. Curcumin, the principal curcuminoid and the most active component in turmeric, is a biologically active phytochemical. Evidence from several recent in vitro studies suggests that curcumin may exert a chondroprotective effect through actions such as anti-inflammatory, anti-oxidative stress, and anti-catabolic activity that are critical for mitigating OA disease pathogenesis and symptoms. In the present study, we investigated the protective mechanisms of curcumin on interleukin 1β (IL-1β)-stimulated primary chondrocytes in vitro. The treatment of interleukin (IL)-1β significantly reduces the cell viability of chondrocytes in dose and time dependent manners. Co-treatment of curcumin with IL-1β significantly decreased the growth inhibition. We observed that curcumin inhibited IL-1β-induced apoptosis and caspase-3 activation in chondrocytes. Curcumin can increase the expression of phosphorylated extracellular signal-regulated kinases 1/2 (ERK1/2), autophagy marker light chain 3 (LC3)-II, and Beclin-1 in chondrocytes. The expression of autophagy markers could be decreased when the chondrocytes were incubated with ERK1/2 inhibitor U0126. Our results suggest that curcumin suppresses apoptosis and inflammatory signaling through its actions on the ERK1/2-induced autophagy in chondrocytes. We propose that curcumin should be explored further for the prophylactic treatment of osteoarthritis in humans and companion animals.
Subverting Host Cell P21-Activated Kinase: A Case of Convergent Evolution across Pathogens
Authors: John Von Freyend Simona , Kwok-Schuelein Terry , Netter Hans , Haqshenas Gholamreza , Semblat Jean-Philippe , Doerig Christian
Published: April 2017

Intracellular pathogens have evolved a wide range of strategies to not only escape from the immune systems of their hosts, but also to directly exploit a variety of host factors to facilitate the infection process. One such strategy is to subvert host cell signalling pathways to the advantage of the pathogen. Recent research has highlighted that the human serine/threonine kinase PAK, or p21-activated kinase, is a central component of host-pathogen interactions in many infection systems involving viruses, bacteria, and eukaryotic pathogens. PAK paralogues are found in most mammalian tissues, where they play vital roles in a wide range of functions. The role of PAKs in cell proliferation and survival, and their involvement in a number of cancers, is of great interest in the context of drug discovery. In this review we discuss the latest insights into the surprisingly central role human PAK1 plays for the infection by such different infectious disease agents as viruses, bacteria, and parasitic protists. It is our intention to open serious discussion on the applicability of PAK inhibitors for the treatment, not only of neoplastic diseases, which is currently the primary objective of drug discovery research targeting these enzymes, but also of a wide range of infectious diseases.
An Ontological Solution to the Mind-Body Problem
Authors: Kastrup Bernardo
Published: April 2017

I argue for an idealist ontology consistent with empirical observations, which seeks to explain the facts of nature more parsimoniously than physicalism and bottom-up panpsychism. This ontology also attempts to offer more explanatory power than both physicalism and bottom-up panpsychism, in that it does not fall prey to either the ‘hard problem of consciousness’ or the ‘subject combination problem’, respectively. It can be summarized as follows: spatially unbound consciousness is posited to be nature’s sole ontological primitive. We, as well as all other living organisms, are dissociated alters of this unbound consciousness. The universe we see around us is the extrinsic appearance of phenomenality surrounding—but dissociated from—our alter. The living organisms we share the world with are the extrinsic appearances of other dissociated alters. As such, the challenge to artificially create individualized consciousness becomes synonymous with the challenge to artificially induce abiogenesis.
Synthesis, Characterization and Thermal Properties of Poly(ethylene oxide), PEO, Polymacromonomers via Anionic and Ring Opening Metathesis Polymerization
Authors: Theodosopoulos George , Zisis Christos , Charalambidis Georgios , Nikolaou Vasilis , Coutsolelos Athanassios , Pitsikalis Marinos
Published: April 2017

Branched polymers are a valuable class of polymeric materials. In the present study, anionic polymerization techniques were employed for the synthesis of low molecular weight poly(ethylene oxide) (PEO) macromonomers bearing norbornenyl end groups. The macromonomers were characterized by SEC, MALDI-TOF and NMR spectroscopy. Subsequent ring opening metathesis polymerization (ROMP) of the macromonomers using ruthenium catalysts (Grubbs catalysts of the 1st, 2nd and 3rd generations) afforded the corresponding polymacromonomers. The effects of the macromonomer molecular weight, the type of the catalyst, the nature of the solvent, the monomer concentration and the polymerization temperature on the molecular characteristics of the branched polymers were examined in detail. The crystallization behavior of the macromonomers and the corresponding polymacromonomers were studied by Differential Scanning Calorimetry (DSC). The thermal stability and the kinetics of the thermal decomposition of the samples were also studied by Thermogravimetric Analysis (TGA). The activation energies of the thermal decomposition were analyzed using the Ozawa–Flynn–Wall and Kissinger methodologies.
Coumarin- and Carboxyl-Functionalized Supramolecular Polybenzoxazines Form Miscible Blends with Polyvinylpyrrolidone
Authors: Lin Ruey-Chorng , Mohamed Mohamed , Chen Tao , Kuo Shiao-Wei
Published: April 2017

In this study, we synthesized a novel multifunctional benzoxazine monomer (Coumarin-COOH BZ), possessing both coumarin and COOH groups, through the reaction of 4-methyl-7-hydroxycoumarin, 4-aminobenzoic acid, and paraformaldehyde in 1,4-dioxane, with the structure confirmed using 1H and 13C nuclear magnetic resonance and Fourier transform infrared (FTIR) spectroscopy. Differential scanning calorimetry (DSC), FTIR spectroscopy, and thermogravimetric analysis were then employed to monitor the thermal curing behavior of Coumarin-COOH BZ and its blends with poly(N-vinyl-2-pyrrolidone) (PVP), both before and after photodimerization of the coumarin moieties. DSC revealed a single glass transition temperature for each Coumarin-COOH BZ/PVP blend composition; a large positive deviation based on the Kwei equation suggested that strong hydrogen bonding existed between the Coumarin-COOH BZ and PVP segments, confirmed through FTIR spectroscopic analyses. The thermal properties improved (i.e., increased glass transition and thermal degradation temperatures) as a result of the increased crosslinking density after photodimerization under UV exposure.
Effect of Cyclic Loading on Surface Instability of Silicone Rubber under Compression
Authors: Li Zhonglin , Zhou Zhiheng , Li Ying , Tang Shan
Published: April 2017

This work combines experiments and finite element simulations to study the effect of pre-imposed cyclic loading on surface instability of silicon rubber under compression. We first fabricate cuboid blocks of silicon rubber and pinch them cyclicly a few times. Then, an in-house apparatus is set to apply uniaxial compression on the silicon rubber under exact plane strain conditions. Surprisingly, we find multiple creases on the surface of silicone rubber, significantly different from what have been observed on the samples without the cyclic pinching. To reveal the underlying physics for these experimentally observed multiple creases, we perform detailed nanoindentation experiments to measure the material properties at different locations of the silicon rubber. The modulus is found to be nonuniform and varies along the thickness direction after the cyclic pinching. According to these experimental results, three-layer and multilayer finite element models are built with different materials properties informed by experiments. The three-layer finite element model can excellently explain the nucleation and pattern of multiple surface creases on the surface of compressed silicone rubber, in good agreement with experiments. Counterintuitively, the multilayer model with gradient modulus cannot be used to explain the multiple creases observed in our experiments. According to these simulations, the experimentally observed multiple creases should be attributed to a thin and stiff layer formed on the surface of silicon rubber after the pre-imposed cyclic loading.
Cloning of CHO Cells, Productivity and Genetic Stability—A Discussion
Authors: Wurm Florian , Wurm Maria
Published: April 2017

While many perceive mammalian cell culture-based manufacturing for biopharmaceuticals an established technology, numerous open questions remain to be solved. Genetic diversity and mutation rates in CHO cells have been underestimated since progeny of a clonal CHO cell become genetically diverse with each cell division. This is an important issue since products are made in bioreactors containing up to 1014 cells that have divided for weeks. Regulatory interest in “Proof of Clonality” is a misguided and misunderstood concern in this context. We revisit decades of research on scope and rate of genetic changes in CHO cells and suggest approaches to minimize trends for genomic instability when establishing reliable manufacturing processes. A concept is proposed for transfection-derived cell populations containing relatively stable (The term “stable” will always be used in a context of relative stability—considering time frames of weeks to months at best.) “CHO master sequence” genomes (containing the desired DNAs of interest). Stable cell populations are to be selected for and maintained for the various phases of manufacturing under specific culture conditions reducing trends for the selection of diverse subpopulations. Such conditions are based on insights gained from population genetics, evolutionary landscape fitness principles, and a 40-year old model for evolution of error prone replicating systems—the Quasi-Species concept.
A Fuzzy-GA Based Decision Making System for Detecting Damaged Buildings from High-Spatial Resolution Optical Images
Authors: Janalipour Milad , Mohammadzadeh Ali
Published: April 2017

In this research, a semi-automated building damage detection system is addressed under the umbrella of high-spatial resolution remotely sensed images. The aim of this study was to develop a semi-automated fuzzy decision making system using Genetic Algorithm (GA). Our proposed system contains four main stages. In the first stage, post-event optical images were pre-processed. In the second stage, textural features were extracted from the pre-processed post-event optical images using Haralick texture extraction method. Afterwards, in the third stage, a semi-automated Fuzzy-GA (Fuzzy Genetic Algorithm) decision making system was used to identify damaged buildings from the extracted texture features. In the fourth stage, a comprehensive sensitivity analysis was performed to achieve parameters of GA leading to more accurate results. Finally, the accuracy of results was assessed using check and test samples. The proposed system was tested over the 2010 Haiti earthquake (Area 1 and Area 2) and the 2003 Bam earthquake (Area 3). The proposed system resulted in overall accuracies of 76.88 ± 1.22%, 65.43 ± 0.29%, and 90.96 ± 0.15% over Area 1, Area 2, and Area 3, respectively. On the one hand, based on the concept of the proposed Fuzzy-GA decision making system, the automation level of this system is higher than other existing systems. On the other hand, based on the accuracy of our proposed system and four advanced machine learning techniques, i.e., bagging, boosting, random forests, and support vector machine, in the detection of damaged buildings, it seems that our proposed system is robust and efficient.
Unassisted Quantitative Evaluation of Despeckling Filters
Authors: Gomez Luis , Ospina Raydonal , Frery Alejandro
Published: April 2017

SAR (Synthetic Aperture Radar) imaging plays a central role in Remote Sensing due to, among other important features, its ability to provide high-resolution, day-and-night and almost weather-independent images. SAR images are affected from a granular contamination, speckle, that can be described by a multiplicative model. Many despeckling techniques have been proposed in the literature, as well as measures of the quality of the results they provide. Assuming the multiplicative model, the observed image Z is the product of two independent fields: the backscatter X and the speckle Y. The result of any speckle filter is X ^ , an estimator of the backscatter X, based solely on the observed data Z. An ideal estimator would be the one for which the ratio of the observed image to the filtered one I = Z / X ^ is only speckle: a collection of independent identically distributed samples from Gamma variates. We, then, assess the quality of a filter by the closeness of I to the hypothesis that it is adherent to the statistical properties of pure speckle. We analyze filters through the ratio image they produce with regards to first- and second-order statistics: the former check marginal properties, while the latter verifies lack of structure. A new quantitative image-quality index is then defined, and applied to state-of-the-art despeckling filters. This new measure provides consistent results with commonly used quality measures (equivalent number of looks, PSNR, MSSIM, β edge correlation, and preservation of the mean), and ranks the filters results also in agreement with their visual analysis. We conclude our study showing that the proposed measure can be successfully used to optimize the (often many) parameters that define a speckle filter.
Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa
Authors: Alemayehu Tadesse , Griensven Ann van , Senay Gabriel B. , Bauwens Willy
Published: April 2017

Actual evapotranspiration (ET) is a major water use flux in a basin water balance with crucial significance for water resources management and planning. Mapping ET with good accuracy has been the subject of ongoing research. Such mapping is even more challenging in heterogeneous and data-scarce regions. The main objective of our research is to estimate ET using daily Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and Global Land Data Assimilation System (GLDAS) weather datasets based on the operational simplified surface energy balance (SSEBop) algorithm at a 1-km spatial scale and 8-day temporal resolution for the Mara Basin (Kenya/Tanzania). Unlike previous studies where the SSEBop algorithm was used, we use a seasonally-varying calibration coefficient for determining the “cold” reference temperature. Our results show that ET is highly variable, with a high inter-quartile range for wetlands and evergreen forest (24% to 29% of the median) and even up to 52% of the median for herbaceous land cover and rainfed agriculture. The basin average ET accounts for about 66% of the rainfall with minimal inter-annual variability. The basin scale validation using nine-years of monthly, gridded global flux tower-based ET (GFET) data reveals that our ET is able to explain 64% of the variance in GFET while the MOD16-NB (Nile Basin) explains 72%. We also observe a percent of bias (PBIAS) of 1.1% and 2.8%, respectively for SSEBop ET and MOD16-NB, indicating a good reliability in the ET estimates. Additionally, the SSEBop ET explains about 52% of the observed variability in the Normalized Difference Vegetation Index (NDVI) for a 16-day temporal resolution and 81% for the annual resolution, pointing to an increased reliability for longer aggregation periods. The annual SSEBop ET estimates are also consistent with the underlying primary (i.e., water and energy) and secondary (i.e., soil, topography, geology, land cover, etc.) controlling factors across the basin. This paper demonstrated how to effectively estimate and evaluate spatially-distributed and temporally-varying ET in data-scarce regions that can be applied elsewhere in the world where observed hydro-meteorological variables are limited.
Modeling Biomass Production in Seasonal Wetlands Using MODIS NDVI Land Surface Phenology
Authors: Lumbierres Maria , Méndez Pablo , Bustamante Javier , Soriguer Ramón , Santamaría Luis
Published: April 2017

Plant primary production is a key driver of several ecosystem functions in seasonal marshes, such as water purification and secondary production by wildlife and domestic animals. Knowledge of the spatio-temporal dynamics of biomass production is therefore essential for the management of resources—particularly in seasonal wetlands with variable flooding regimes. We propose a method to estimate standing aboveground plant biomass using NDVI Land Surface Phenology (LSP) derived from MODIS, which we calibrate and validate in the Doñana National Park’s marsh vegetation. Out of the different estimators tested, the Land Surface Phenology maximum NDVI (LSP-Maximum-NDVI) correlated best with ground-truth data of biomass production at five locations from 2001–2015 used to calibrate the models (R2 = 0.65). Estimators based on a single MODIS NDVI image performed worse (R2 ≤ 0.41). The LSP-Maximum-NDVI estimator was robust to environmental variation in precipitation and hydroperiod, and to spatial variation in the productivity and composition of the plant community. The determination of plant biomass using remote-sensing techniques, adequately supported by ground-truth data, may represent a key tool for the long-term monitoring and management of seasonal marsh ecosystems.
Hyperspectral and Multispectral Retrieval of Suspended Sediment in Shallow Coastal Waters Using Semi-Analytical and Empirical Methods
Authors: Zhou Xiaochi , Marani Marco , Albertson John , Silvestri Sonia
Published: April 2017

Natural lagoons and estuaries worldwide are experiencing accelerated ecosystem degradation due to increased anthropogenic pressure. As a key driver of coastal zone dynamics, suspended sediment concentration (SSC) is difficult to monitor with adequate spatial and temporal resolutions both in the field and using remote sensing. In particular, the spatial resolutions of currently available remote sensing data generated by satellite sensors designed for ocean color retrieval, such as MODIS (Moderate Resolution Imaging Spectroradiometer) or SeaWiFS (Sea-Viewing Wide Field-of-View Sensor), are too coarse to capture the dimension and geomorphological heterogeneity of most estuaries and lagoons. In the present study, we explore the use of hyperspectral (Hyperion) and multispectral data, i.e., the Landsat TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), and ALOS (Advanced Land Observing Satellite), to estimate SSC through semi-analytical and empirical approaches in the Venice lagoon (Italy). Key parameters of the retrieval models are calibrated and cross-validated by matching the remote sensing estimates of SSC with in situ data from a network of water quality sensors. Our analysis shows that, despite the higher spectral resolution, hyperspectral data provide limited advantages over the use of multispectral data, mainly due to information redundancy and cross-band correlation. Meanwhile, the limited historical archive of hyperspectral data (usually acquired on demand) severely reduces the chance of observing high turbidity events, which are relatively rare but critical in controlling the coastal sediment and geomorphological dynamics. On the contrary, retrievals using available multispectral data can encompass a much wider range of SSC values due to their frequent acquisitions and longer historical archive. For the retrieval methods considered in this study, we find that the semi-analytical method outperforms empirical approaches, when applied to both the hyperspectral and multispectral dataset. Interestingly, the improved performance emerges more clearly when the data used for testing are kept separated from those used in the calibration, suggesting a greater ability of semi-analytical models to “generalize” beyond the specific data set used for model calibration.
Connectivity Restoration in Wireless Sensor Networks via Space Network Coding
Authors: Uwitonze Alfred , Huang Jiaqing , Ye Yuanqing , Cheng Wenqing
Published: April 2017

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.
Robot-Beacon Distributed Range-Only SLAM for Resource-Constrained Operation
Authors: Torres-González Arturo , Martínez-de Dios Jose , Ollero Anibal
Published: April 2017

This work deals with robot-sensor network cooperation where sensor nodes (beacons) are used as landmarks for Range-Only (RO) Simultaneous Localization and Mapping (SLAM). Most existing RO-SLAM techniques consider beacons as passive devices disregarding the sensing, computational and communication capabilities with which they are actually endowed. SLAM is a resource-demanding task. Besides the technological constraints of the robot and beacons, many applications impose further resource consumption limitations. This paper presents a scalable distributed RO-SLAM scheme for resource-constrained operation. It is capable of exploiting robot-beacon cooperation in order to improve SLAM accuracy while meeting a given resource consumption bound expressed as the maximum number of measurements that are integrated in SLAM per iteration. The proposed scheme combines a Sparse Extended Information Filter (SEIF) SLAM method, in which each beacon gathers and integrates robot-beacon and inter-beacon measurements, and a distributed information-driven measurement allocation tool that dynamically selects the measurements that are integrated in SLAM, balancing uncertainty improvement and resource consumption. The scheme adopts a robot-beacon distributed approach in which each beacon participates in the selection, gathering and integration in SLAM of robot-beacon and inter-beacon measurements, resulting in significant estimation accuracies, resource-consumption efficiency and scalability. It has been integrated in an octorotor Unmanned Aerial System (UAS) and evaluated in 3D SLAM outdoor experiments. The experimental results obtained show its performance and robustness and evidence its advantages over existing methods.
Chemical Source Localization Fusing Concentration Information in the Presence of Chemical Background Noise
Authors: Pomareda Víctor , Magrans Rudys , Jiménez-Soto Juan , Martínez Dani , Tresánchez Marcel , Burgués Javier , Palacín Jordi , Marco Santiago
Published: April 2017

We present the estimation of a likelihood map for the location of the source of a chemical plume dispersed under atmospheric turbulence under uniform wind conditions. The main contribution of this work is to extend previous proposals based on Bayesian inference with binary detections to the use of concentration information while at the same time being robust against the presence of background chemical noise. For that, the algorithm builds a background model with robust statistics measurements to assess the posterior probability that a given chemical concentration reading comes from the background or from a source emitting at a distance with a specific release rate. In addition, our algorithm allows multiple mobile gas sensors to be used. Ten realistic simulations and ten real data experiments are used for evaluation purposes. For the simulations, we have supposed that sensors are mounted on cars which do not have among its main tasks navigating toward the source. To collect the real dataset, a special arena with induced wind is built, and an autonomous vehicle equipped with several sensors, including a photo ionization detector (PID) for sensing chemical concentration, is used. Simulation results show that our algorithm, provides a better estimation of the source location even for a low background level that benefits the performance of binary version. The improvement is clear for the synthetic data while for real data the estimation is only slightly better, probably because our exploration arena is not able to provide uniform wind conditions. Finally, an estimation of the computational cost of the algorithmic proposal is presented.
An Efficient Distributed Compressed Sensing Algorithm for Decentralized Sensor Network
Authors: Liu Jing , Huang Kaiyu , Zhang Guoxian
Published: April 2017

We consider the joint sparsity Model 1 (JSM-1) in a decentralized scenario, where a number of sensors are connected through a network and there is no fusion center. A novel algorithm, named distributed compact sensing matrix pursuit (DCSMP), is proposed to exploit the computational and communication capabilities of the sensor nodes. In contrast to the conventional distributed compressed sensing algorithms adopting a random sensing matrix, the proposed algorithm focuses on the deterministic sensing matrices built directly on the real acquisition systems. The proposed DCSMP algorithm can be divided into two independent parts, the common and innovation support set estimation processes. The goal of the common support set estimation process is to obtain an estimated common support set by fusing the candidate support set information from an individual node and its neighboring nodes. In the following innovation support set estimation process, the measurement vector is projected into a subspace that is perpendicular to the subspace spanned by the columns indexed by the estimated common support set, to remove the impact of the estimated common support set. We can then search the innovation support set using an orthogonal matching pursuit (OMP) algorithm based on the projected measurement vector and projected sensing matrix. In the proposed DCSMP algorithm, the process of estimating the common component/support set is decoupled with that of estimating the innovation component/support set. Thus, the inaccurately estimated common support set will have no impact on estimating the innovation support set. It is proven that under the condition the estimated common support set contains the true common support set, the proposed algorithm can find the true innovation set correctly. Moreover, since the innovation support set estimation process is independent of the common support set estimation process, there is no requirement for the cardinality of both sets; thus, the proposed DCSMP algorithm is capable of tackling the unknown sparsity problem successfully.
Enhancing the Responsivity of Uncooled Infrared Detectors Using Plasmonics for High-Performance Infrared Spectroscopy
Authors: Ahmed Amr , Kim Hye , Kim Jinsik , Hwang Kyo , Kim Seonghwan
Published: April 2017

A lead zirconate titanate (PZT;Pb(Zr0.52Ti0.48)O3) layer embedded infrared (IR) detector decorated with wavelength-selective plasmonic crystals has been investigated for high-performance non-dispersive infrared (NDIR) spectroscopy. A plasmonic IR detector with an enhanced IR absorption band has been designed based on numerical simulations, fabricated by conventional microfabrication techniques, and characterized with a broadly tunable quantum cascade laser. The enhanced responsivity of the plasmonic IR detector at specific wavelength band has improved the performance of NDIR spectroscopy and pushed the limit of detection (LOD) by an order of magnitude. In this paper, a 13-fold enhancement in the LOD of a methane gas sensing using NDIR spectroscopy is demonstrated with the plasmonic IR detector.