bluuebunny/crossref_metadata_2025 huggingface dataset:
Similarities and Differences between Silver Ions and Silver in Nanoforms as Antibacterial Agents
Authors: Kędziora Anna , Speruda Mateusz , Krzyżewska Eva , Rybka Jacek , Łukowiak Anna , Bugla-Płoskońska Gabriela
Published: February 2018

Silver is considered as antibacterial agent with well-known mode of action and bacterial resistance against it is well described. The development of nanotechnology provided different methods for the modification of the chemical and physical structure of silver, which may increase its antibacterial potential. The physico-chemical properties of silver nanoparticles and their interaction with living cells differs substantially from those of silver ions. Moreover, the variety of the forms and characteristics of various silver nanoparticles are also responsible for differences in their antibacterial mode of action and probably bacterial mechanism of resistance. The paper discusses in details the aforementioned aspects of silver activity.
The Many Facets of Metzincins and Their Endogenous Inhibitors: Perspectives on Ovarian Cancer Progression
Authors: Escalona Ruth , Chan Emily , Kannourakis George , Findlay Jock , Ahmed Nuzhat
Published: February 2018

Approximately sixty per cent of ovarian cancer patients die within the first five years of diagnosis due to recurrence associated with chemoresistance. The metzincin family of metalloproteinases is enzymes involved in matrix remodeling in response to normal physiological changes and diseased states. Recently, there has been a mounting awareness of these proteinases and their endogenous inhibitors, the tissue inhibitors of metalloproteinases (TIMPs), as superb modulators of cellular communication and signaling regulating key biological processes in cancer progression. This review investigates the role of metzincins and their inhibitors in ovarian cancer. We propose that understanding the metzincins and TIMP biology in ovarian cancer may provide valuable insights in combating ovarian cancer progression and chemoresistance-mediated recurrence in patients.
The Application of Non-Invasive Apoptosis Detection Sensor (NIADS) on Histone Deacetylation Inhibitor (HDACi)-Induced Breast Cancer Cell Death
Authors: Hsu Kai-Wen , Huang Chien-Yu , Tam Ka-Wai , Lin Chun-Yu , Huang Li-Chi , Lin Ching-Ling , Hsieh Wen-Shyang , Chi Wei-Ming , Chang Yu-Jia , Wei Po-Li , Chen Shou-Tung , Lee Chia-Hwa
Published: February 2018

Breast cancer is the most common malignancy in women and the second leading cause of cancer death in women. Triple negative breast cancer (TNBC) subtype is a breast cancer subset without ER (estrogen receptor), PR (progesterone receptor) and HER2 (human epidermal growth factor receptor 2) expression, limiting treatment options and presenting a poorer survival rate. Thus, we investigated whether histone deacetylation inhibitor (HDACi) could be used as potential anti-cancer therapy on breast cancer cells. In this study, we found TNBC and HER2-enriched breast cancers are extremely sensitive to Panobinostat, Belinostat of HDACi via experiments of cell viability assay, apoptotic marker identification and flow cytometry measurement. On the other hand, we developed a bioluminescence-based live cell non-invasive apoptosis detection sensor (NIADS) detection system to evaluate the quantitative and kinetic analyses of apoptotic cell death by HDAC treatment on breast cancer cells. In addition, the use of HDACi may also contribute a synergic anti-cancer effect with co-treatment of chemotherapeutic agent such as doxorubicin on TNBC cells (MDA-MB-231), but not in breast normal epithelia cells (MCF-10A), providing therapeutic benefits against breast tumor in the clinic.
Finding Group-Based Skyline over a Data Stream in the Sensor Network
Authors: Dong Leigang , Liu Guohua , Cui Xiaowei , Li Tianyu
Published: February 2018

Along with the application of the sensor network, there will be large amount of dynamic data coming from sensors. How to dig the useful information from such data is significant. Skyline query is aiming to identify the interesting points from a large dataset. The group-based skyline query is to find the outstanding Pareto Optimal groups which cannot be g-dominated by any other groups with the group same size. However, the existing algorithms of group-based skyline (G-Skyline) focus on the static data set, how to conduct advanced research on data stream remains an open problem at large. In this paper, we propose the group-based skyline query over the data stream. In order to compute G-Skyline efficiently, we present a sharing strategy, and based on which we propose two algorithms to efficiently compute the G-Skyline over the data stream: the point-arriving algorithm and the point-expiring algorithm. In our experiments, three synthetic data sets are used to test our algorithms; the experiments results show that our algorithms perform efficiently over a data stream.
Embracing First-Person Perspectives in Soma-Based Design
Authors: Höök Kristina , Caramiaux Baptiste , Erkut Cumhur , Forlizzi Jodi , Hajinejad Nassrin , Haller Michael , Hummels Caroline , Isbister Katherine , Jonsson Martin , Khut George , Loke Lian , Lottridge Danielle , Marti Patrizia , Melcer Edward , Müller Florian , Petersen Marianne , Schiphorst Thecla , Segura Elena , Ståhl Anna , Svanæs Dag , Tholander Jakob , Tobiasson Helena
Published: February 2018

A set of prominent designers embarked on a research journey to explore aesthetics in movement-based design. Here we unpack one of the design sensitivities unique to our practice: a strong first person perspective—where the movements, somatics and aesthetic sensibilities of the designer, design researcher and user are at the forefront. We present an annotated portfolio of design exemplars and a brief introduction to some of the design methods and theory we use, together substantiating and explaining the first-person perspective. At the same time, we show how this felt dimension, despite its subjective nature, is what provides rigor and structure to our design research. Our aim is to assist researchers in soma-based design and designers wanting to consider the multiple facets when designing for the aesthetics of movement. The applications span a large field of designs, including slow introspective, contemplative interactions, arts, dance, health applications, games, work applications and many others.
A Simple Setup to Perform 3D Locomotion Tracking in Zebrafish by Using a Single Camera
Authors: Audira Gilbert , Sampurna Bonifasius , Juniardi Stevhen , Liang Sung-Tzu , Lai Yu-Heng , Hsiao Chung-Der
Published: February 2018

Generally, the measurement of three-dimensional (3D) swimming behavior in zebrafish relies on commercial software or requires sophisticated scripts, and depends on more than two cameras to capture the video. Here, we establish a simple and economic apparatus to detect 3D locomotion in zebrafish, which involves a single camera capture system that records zebrafish movement in a specially designed water tank with a mirror tilted at 45 degrees. The recorded videos are analyzed using idTracker, while spatial positions are calibrated by ImageJ software and 3D trajectories are plotted by Origin 9.1 software. This easy setting allowed scientists to track 3D swimming behavior of multiple zebrafish with low cost and precise spatial position, showing great potential for fish behavioral research in the future.
Discrete Element Simulation of Orthogonal Machining of Soda-Lime Glass
Authors: Yang Guang , Alkotami Hazem , Lei Shuting
Published: February 2018

Transparent, brittle materials, like glass, are used in various applications due to their advantages of mechanical and optical properties. However, their hard and brittle nature causes significant challenges to researchers when they design and test a new machining process. In order to optimize this time-consuming process, discrete element method (DEM) is applied to simulate the cutting process of soda-lime glass in this study. The first step is to create a synthetic material that behaves like soda-lime glass. Then, the macroproperties are calibrated by adjusting the microparameters of the DEM model to match the mechanical properties of the real soda-lime glass. Finally, orthogonal machining simulations are conducted and model validation are conducted by comparing the predicted cutting forces with those from the orthogonal cutting experiments.
N-Vinylation of Imidazole and Benzimidazole with a Paramagnetic Vinyl Bromide
Authors: Úr Györgyi , Gulyás Fekete Gergely , Hideg Kálmán , Kálai Tamás
Published: February 2018

An N-vinylation of imidazole and benzimidazole with a paramagnetic vinyl bromide was investigated. Among the tested procedures, Pd-catalyzed reaction was the most powerful one. The N-vinylation of 2-aminobenzimidazole with a β-bromo-α,β-unsaturated pyrroline nitroxide aldehyde offered 1,1,3,3-tetramethyl-1H-benzimidazo[1,2-a]pyrrolo[3,4-e]pyrimidin-2(3H)-yloxyl radical and the corresponding non-cyclized Schiff base. The reaction of a β-bromo-α,β-unsaturated pyrroline nitroxide aldehyde with imidazole gave β-imidazo-α,β-unsaturated pyrroline nitroxide aldehyde, which was reduced to the alcohol and converted to an unstable allyl chloride.
Efficacy of Octacalcium Phosphate Collagen Composite for Titanium Dental Implants in Dogs
Authors: Kawai Tadashi , Matsui Keiko , Ezoe Yushi , Kajii Fumihiko , Suzuki Osamu , Takahashi Tetsu , Kamakura Shinji
Published: February 2018

Background: Previous studies showed that octacalcium (OCP) collagen composite (OCP/Col) can be used to repair human jaw bone defects without any associated abnormalities. The present study investigated whether OCP/Col could be applied to dental implant treatment using a dog tooth extraction socket model. Methods: The premolars of dogs were extracted; each extraction socket was extended, and titanium dental implants were placed in each socket. OCP/Col was inserted in the space around a titanium dental implant. Autologous bone was used to fill the other sockets, while the untreated socket (i.e., no bone substitute material) served as a control. Three months after the operation, these specimens were analyzed for the osseointegration of each bone substitute material with the surface of the titanium dental implant. Results: In histomorphometric analyses, the peri-implant bone areas (BA%) and bone-implant contact (BIC%) were measured. There was no difference in BA% or BIC% between OCP/Col and autologous bone. Conclusion: These results suggested that OCP/Col could be used for implant treatment as a bone substitute.
Modal Parameters Evaluation in a Full-Scale Aircraft Demonstrator under Different Environmental Conditions Using HS 3D-DIC
Authors: Molina-Viedma Ángel , López-Alba Elías , Felipe-Sesé Luis , Díaz Francisco , Rodríguez-Ahlquist Javier , Iglesias-Vallejo Manuel
Published: February 2018

In real aircraft structures the comfort and the occupational performance of crewmembers and passengers are affected by the presence of noise. In this sense, special attention is focused on mechanical and material design for isolation and vibration control. Experimental characterization and, in particular, experimental modal analysis, provides information for adequate cabin noise control. Traditional sensors employed in the aircraft industry for this purpose are invasive and provide a low spatial resolution. This paper presents a methodology for experimental modal characterization of a front fuselage full-scale demonstrator using high-speed 3D digital image correlation, which is non-invasive, ensuring that the structural response is unperturbed by the instrumentation mass. Specifically, full-field measurements on the passenger window area were conducted when the structure was excited using an electrodynamic shaker. The spectral analysis of the measured time-domain displacements made it possible to identify natural frequencies and full-field operational deflection shapes. Changes in the modal parameters due to cabin pressurization and the behavior of different local structural modifications were assessed using this methodology. The proposed full-field methodology allowed the characterization of relevant dynamic response patterns, complementing the capabilities provided by accelerometers.
Effects of Ultrasonic-Aided Quenching on the Corrosion Resistance of GB 35CrMoV Steel in Seawater Environment
Authors: Jiang Xin , Zhou Yajun , Shi Chen , Mao Daheng
Published: February 2018

The effects of ultrasonic-aided quenching (USQ) on the microstructure and corrosion properties of 35CrMoV steel in a simulated seawater environment (wt % (NaCl) = 3.5) were studied. The corrosion properties of the steel were studied by electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization curves. The scanning electron microscope (SEM) and energy dispersive spectrometer (EDS) were used to characterize the microstructure and corrosion products. Combined with the EIS equivalent circuit, the corrosion mechanism was investigated. The results show that the microstructure of the USQ specimen is small martensite and that there was no residual ferrite compared with an un-ultrasonic-aided quenching (UUSQ) sample. It was also found that the corrosion products of USQ sample are less than the UUSQ sample, and the corrosion cracks are lighter and thinner than that of the UUSQ sample, which indicates that the corrosion resistance of 35CrMoV in a seawater environment has been obviously improved.
Mechanical Properties of Thixoforged In Situ Mg2Sip/AM60B Composite at Elevated Temperatures
Authors: Zhang Suqing , Chen Tijun , Zhou Jixue , Xiu Dapeng , Li Tao , Cheng Kaiming
Published: February 2018

The mechanical behaviors of the thixoforged in situ Mg2Sip/AM60B composite at elevated temperatures were evaluated. The results indicated that the thixoforged composite exhibits higher UTS (ultimate tensile strength) than that of the thixoforged AM60B at the cost of elongation. As the testing temperature rises from 25 to 300 °C, the UTS of both these two materials decreases while their elongations increases. The enhanced dislocation motion ability, the softened eutectic β phase at 120 °C, the activated non-basal slipping and the dynamic recovery and recrystallization mechanisms at 150 °C are responsible for the change in tensile properties with testing temperatures. The fracture mode transforms from the ductile into the brittle as the initial strain rate increases from 0.01 to 0.2 s−1 at 200 °C.
Investigation on Single-Molecule Junctions Based on Current–Voltage Characteristics
Authors: Isshiki Yuji , Matsuzawa Yuya , Fujii Shintaro , Kiguchi Manabu
Published: February 2018

The relationship between the current through an electronic device and the voltage across its terminals is a current–voltage characteristic (I–V) that determine basic device performance. Currently, I–V measurement on a single-molecule scale can be performed using break junction technique, where a single molecule junction can be prepared by trapping a single molecule into a nanogap between metal electrodes. The single-molecule I–Vs provide not only the device performance, but also reflect information on energy dispersion of the electronic state and the electron-molecular vibration coupling in the junction. This mini review focuses on recent representative studies on I–Vs of the single molecule junctions that cover investigation on the single-molecule diode property, the molecular vibration, and the electronic structure as a form of transmission probability, and electronic density of states, including the spin state of the single-molecule junctions. In addition, thermoelectronic measurements based on I–Vs and identification of the charged carriers (i.e., electrons or holes) are presented. The analysis in the single-molecule I–Vs provides fundamental and essential information for a better understanding of the single-molecule science, and puts the single molecule junction to more practical use in molecular devices.
Relativistic Mean-Field Models with Different Parametrizations of Density Dependent Couplings
Authors: Typel Stefan
Published: February 2018

Relativistic mean-field models are successfully used for the description of finite nuclei and nuclear matter. Approaches with density-dependent meson-nucleon couplings assume specific functional forms and a dependence on vector densities in most cases. In this work, parametrizations with a larger sample of functions and dependencies on vector and scalar densities are investigated. They are obtained from fitting properties of finite nuclei. The quality of the description of nuclei and the obtained equations of state of symmetric nuclear matter and neutron matter below saturation are very similar. However, characteristic nuclear matter parameters, the equations of state and the symmetry energy at suprasaturation densities show some correlations with the choice of the density dependence and functional form of the couplings. Conditions are identified that can lead to problems for some of the parametrizations.
Antibiotic Persistence as a Metabolic Adaptation: Stress, Metabolism, the Host, and New Directions
Authors: Cabral Damien , Wurster Jenna , Belenky Peter
Published: February 2018

Persistence is a phenomenon during which a small fraction of a total bacterial population survives treatment with high concentrations of antibiotics for an extended period of time. In conjunction with biofilms, antibiotic persisters represent a major cause of recalcitrant and recurring infections, resulting in significant morbidity and mortality. In this review, we discuss the clinical significance of persister cells and the central role of bacterial metabolism in their formation, specifically with respect to carbon catabolite repression, sugar metabolism, and growth regulation. Additionally, we will examine persister formation as an evolutionary strategy used to tolerate extended periods of stress and discuss some of the response mechanisms implicated in their formation. To date, the vast majority of the mechanistic research examining persistence has been conducted in artificial in vitro environments that are unlikely to be representative of host conditions. Throughout this review, we contextualize the existing body of literature by discussing how in vivo conditions may create ecological niches that facilitate the development of persistence. Lastly, we identify how the development of next-generation sequencing and other “big data” tools may enable researchers to examine persistence mechanisms within the host to expand our understanding of their clinical importance.
Maintaining Vitality: Pharmacists’ Continuing Professional Education Decision-Making in the Upper Midwest
Authors: Henkel Paul , Marvanova Marketa
Published: February 2018

Continuing professional education (CPE) plays an important role in continuing professional development of pharmacists for providing quality pharmaceutical care but also to maintain professional and organizational vitality and meet changing community/population needs. The study objective was to describe and understand factors of importance in selection of CPE credit hours among Upper Midwest pharmacists. A cross-sectional study of licensed pharmacists (n = 1239) in Iowa, Minnesota, Nebraska, North Dakota, and South Dakota included completion of a questionnaire on demographics and CPE decision-making. Factor analysis, t-test, and multivariate analyses were performed using Stata 10.1. Pharmacists placed greatest importance on maintaining licensure (mean = 2.72/3.00), personal interest (mean = 2.57), and self-improvement (mean = 2.42). Community/population need (mean = 1.83) was rated as slightly more important (p < 0.01) by retail/community pharmacists, females, and those with a Doctor of Pharmacy degree or pharmacy residency while business growth/development (mean = 1.33) was rated slightly more important (p < 0.01) by retail/community pharmacists. Despite findings that neither community/population need nor business development were among the most important factors in pharmacists’ CPE selection, there exists significant potential for pharmacists to utilize CPE to maintain professional and organizational vitality in the labor market, but more importantly to ensure continued provision of quality pharmaceutical care and patient education.
TeMoto: Intuitive Multi-Range Telerobotic System with Natural Gestural and Verbal Instruction Interface
Authors: Valner Robert , Kruusamäe Karl , Pryor Mitch
Published: February 2018

Teleoperated mobile robots, equipped with object manipulation capabilities, provide safe means for executing dangerous tasks in hazardous environments without putting humans at risk. However, mainly due to a communication delay, complex operator interfaces and insufficient Situational Awareness (SA), the task productivity of telerobots remains inferior to human workers. This paper addresses the shortcomings of telerobots by proposing a combined approach of (i) a scalable and intuitive operator interface with gestural and verbal input, (ii) improved Situational Awareness (SA) through sensor fusion according to documented best practices, (iii) integrated virtual fixtures for task simplification and minimizing the operator’s cognitive burden and (iv) integrated semiautonomous behaviors that further reduce cognitive burden and negate the impact of communication delays, execution latency and/or failures. The proposed teleoperation system, TeMoto, is implemented using ROS (Robot Operating System) to ensure hardware agnosticism, extensibility and community access. The operator’s command interface consists of a Leap Motion Controller for hand tracking, Griffin PowerMate USB as turn knob for scaling and a microphone for speech input. TeMoto is evaluated on multiple robots including two mobile manipulator platforms. In addition to standard, task-specific evaluation techniques (completion time, user studies, number of steps, etc.)—which are platform and task dependent and thus difficult to scale—this paper presents additional metrics for evaluating the user interface including task-independent criteria for measuring generalized (i) task completion efficiency and (ii) operator context switching.
Downscaling of Surface Soil Moisture Retrieval by Combining MODIS/Landsat and In Situ Measurements
Authors: Xu Chenyang , Qu John , Hao Xianjun , Cosh Michael , Prueger John , Zhu Zhiliang , Gutenberg Laurel
Published: February 2018

Soil moisture, especially surface soil moisture (SSM), plays an important role in the development of various natural hazards that result from extreme weather events such as drought, flooding, and landslides. There have been many remote sensing methods for soil moisture retrieval based on microwave or optical thermal infrared (TIR) measurements. TIR remote sensing has been popular for SSM retrieval due to its fine spatial and temporal resolutions. However, because of limitations in the penetration of optical TIR radiation and cloud cover, TIR methods can only be used under clear sky conditions. Microwave SSM retrieval is based on solid physical principles, and has advantages in cases of cloud cover, but it has low spatial resolution. For applications at the local scale, SSM data at high spatial and temporal resolutions are important, especially for agricultural management and decision support systems. Current remote sensing measurements usually have either a high spatial resolution or a high temporal resolution, but not both. This study aims to retrieve SSM at both high spatial and temporal resolutions through the fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and Land Remote Sensing Satellite (Landsat) data. Based on the universal triangle trapezoid, this study investigated the relationship between land surface temperature (LST) and the normalized difference vegetation index (NDVI) under different soil moisture conditions to construct an improved nonlinear model for SSM retrieval with LST and NDVI. A case study was conducted in Iowa, in the United States (USA) (Lat: 42.2°~42.7°, Lon: −93.6°~−93.2°), from 1 May 2016 to 31 August 2016. Daily SSM in an agricultural area during the crop-growing season was downscaled to 120-m spatial resolution by fusing Landsat 8 with MODIS, with an R2 of 0.5766, and RMSE from 0.0302 to 0.1124 m3/m3.
SAR Target Recognition via Local Sparse Representation of Multi-Manifold Regularized Low-Rank Approximation
Authors: Yu Meiting , Dong Ganggang , Fan Haiyan , Kuang Gangyao
Published: February 2018

The extraction of a valuable set of features and the design of a discriminative classifier are crucial for target recognition in SAR image. Although various features and classifiers have been proposed over the years, target recognition under extended operating conditions (EOCs) is still a challenging problem, e.g., target with configuration variation, different capture orientations, and articulation. To address these problems, this paper presents a new strategy for target recognition. We first propose a low-dimensional representation model via incorporating multi-manifold regularization term into the low-rank matrix factorization framework. Two rules, pairwise similarity and local linearity, are employed for constructing multiple manifold regularization. By alternately optimizing the matrix factorization and manifold selection, the feature representation model can not only acquire the optimal low-rank approximation of original samples, but also capture the intrinsic manifold structure information. Then, to take full advantage of the local structure property of features and further improve the discriminative ability, local sparse representation is proposed for classification. Finally, extensive experiments on moving and stationary target acquisition and recognition (MSTAR) database demonstrate the effectiveness of the proposed strategy, including target recognition under EOCs, as well as the capability of small training size.
Exploring Machine Learning to Correct Satellite-Derived Sea Surface Temperatures
Authors: Saux Picart Stéphane , Tandeo Pierre , Autret Emmanuelle , Gausset Blandine
Published: February 2018

Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work is an attempt at using advanced statistical methods of machine learning to predict the bias between Sea Surface Temperature (SST) derived from infrared remote sensing and ground “truth” from drifting buoy measurements. A large dataset of collocation between satellite SST and in situ SST is explored. Four regression models are used: Simple multi-linear regression, Least Square Shrinkage and Selection Operator (LASSO), Generalised Additive Model (GAM) and random forest. In the case of geostationary satellites for which a large number of collocations is available, results show that the random forest model is the best model to predict the systematic errors and it is computationally fast, making it a good candidate for operational processing. It is able to explain nearly 31% of the total variance of the bias (in comparison to about 24% for the multi-linear regression model).
Detecting Neolithic Burial Mounds from LiDAR-Derived Elevation Data Using a Multi-Scale Approach and Machine Learning Techniques
Authors: Guyot Alexandre , Hubert-Moy Laurence , Lorho Thierry
Published: February 2018

Airborne LiDAR technology is widely used in archaeology and over the past decade has emerged as an accurate tool to describe anthropomorphic landforms. Archaeological features are traditionally emphasised on a LiDAR-derived Digital Terrain Model (DTM) using multiple Visualisation Techniques (VTs), and occasionally aided by automated feature detection or classification techniques. Such an approach offers limited results when applied to heterogeneous structures (different sizes, morphologies), which is often the case for archaeological remains that have been altered throughout the ages. This study proposes to overcome these limitations by developing a multi-scale analysis of topographic position combined with supervised machine learning algorithms (Random Forest). Rather than highlighting individual topographic anomalies, the multi-scalar approach allows archaeological features to be examined not only as individual objects, but within their broader spatial context. This innovative and straightforward method provides two levels of results: a composite image of topographic surface structure and a probability map of the presence of archaeological structures. The method was developed to detect and characterise megalithic funeral structures in the region of Carnac, the Bay of Quiberon, and the Gulf of Morbihan (France), which is currently considered for inclusion on the UNESCO World Heritage List. As a result, known archaeological sites have successfully been geo-referenced with a greater accuracy than before (even when located under dense vegetation) and a ground-check confirmed the identification of a previously unknown Neolithic burial mound in the commune of Carnac.
Estimation of Chlorophyll-a Concentration from Optimizing a Semi-Analytical Algorithm in Productive Inland Waters
Authors: Watanabe Fernanda , Alcântara Enner , Imai Nilton , Rodrigues Thanan , Bernardo Nariane
Published: February 2018

The high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.
Interferometric SAR DEMs for Forest Change in Uganda 2000–2012
Authors: Solberg Svein , May Johannes , Bogren Wiley , Breidenbach Johannes , Torp Torfinn , Gizachew Belachew
Published: February 2018

Monitoring changes in forest height, biomass and carbon stock is important for understanding the drivers of forest change, clarifying the geography and magnitude of the fluxes of the global carbon budget and for providing input data to REDD+. The objective of this study was to investigate the feasibility of covering these monitoring needs using InSAR DEM changes over time and associated estimates of forest biomass change and corresponding net CO2 emissions. A wall-to-wall map of net forest change for Uganda with its tropical forests was derived from two Digital Elevation Model (DEM) datasets, namely the SRTM acquired in 2000 and TanDEM-X acquired around 2012 based on Interferometric SAR (InSAR) and based on the height of the phase center. Errors in the form of bias, as well as parallel lines and belts having a certain height shift in the SRTM DEM were removed, and the penetration difference between X- and C-band SAR into the forest canopy was corrected. On average, we estimated X-band InSAR height to decrease by 7 cm during the period 2000–2012, corresponding to an estimated annual CO2 emission of 5 Mt for the entirety of Uganda. The uncertainty of this estimate given as a 95% confidence interval was 2.9–7.1 Mt. The presented method has a number of issues that require further research, including the particular SRTM biases and artifact errors; the penetration difference between the X- and C-band; the final height adjustment; and the validity of a linear conversion from InSAR height change to AGB change. However, the results corresponded well to other datasets on forest change and AGB stocks, concerning both their geographical variation and their aggregated values.
Optimal Estimation of Sea Surface Temperature from AMSR-E
Authors: Nielsen-Englyst Pia , L. Høyer Jacob , Toudal Pedersen Leif , L. Gentemann Chelle , Alerskans Emy , Block Tom , Donlon Craig
Published: February 2018

The Optimal Estimation (OE) technique is developed within the European Space Agency Climate Change Initiative (ESA-CCI) to retrieve subskin Sea Surface Temperature (SST) from AQUA’s Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E). A comprehensive matchup database with drifting buoy observations is used to develop and test the OE setup. It is shown that it is essential to update the first guess atmospheric and oceanic state variables and to perform several iterations to reach an optimal retrieval. The optimal number of iterations is typically three to four in the current setup. In addition, updating the forward model, using a multivariate regression model is shown to improve the capability of the forward model to reproduce the observations. The average sensitivity of the OE retrieval is 0.5 and shows a latitudinal dependency with smaller sensitivity for cold waters and larger sensitivity for warmer waters. The OE SSTs are evaluated against drifting buoy measurements during 2010. The results show an average difference of 0.02 K with a standard deviation of 0.47 K when considering the 64% matchups, where the simulated and observed brightness temperatures are most consistent. The corresponding mean uncertainty is estimated to 0.48 K including the in situ and sampling uncertainties. An independent validation against Argo observations from 2009 to 2011 shows an average difference of 0.01 K, a standard deviation of 0.50 K and a mean uncertainty of 0.47 K, when considering the best 62% of retrievals. The satellite versus in situ discrepancies are highest in the dynamic oceanic regions due to the large satellite footprint size and the associated sampling effects. Uncertainty estimates are available for all retrievals and have been validated to be accurate. They can thus be used to obtain very good retrieval results. In general, the results from the OE retrieval are very encouraging and demonstrate that passive microwave observations provide a valuable alternative to infrared satellite observations for retrieving SST.
Sensitivity Analysis of Arctic Sea Ice Extent Trends and Statistical Projections Using Satellite Data
Authors: Peng Ge , Matthews Jessica , Yu Jason
Published: February 2018

An ice-free Arctic summer would have pronounced impacts on global climate, coastal habitats, national security, and the shipping industry. Rapid and accelerated Arctic sea ice loss has placed the reality of an ice-free Arctic summer even closer to the present day. Accurate projection of the first Arctic ice-free summer year is extremely important for business planning and climate change mitigation, but the projection can be affected by many factors. Using an inter-calibrated satellite sea ice product, this article examines the sensitivity of decadal trends of Arctic sea ice extent and statistical projections of the first occurrence of an ice-free Arctic summer. The projection based on the linear trend of the last 20 years of data places the first Arctic ice-free summer year at 2036, 12 years earlier compared to that of the trend over the last 30 years. The results from a sensitivity analysis of six commonly used curve-fitting models show that the projected timings of the first Arctic ice-free summer year tend to be earlier for exponential, Gompertz, quadratic, and linear with lag fittings, and later for linear and log fittings. Projections of the first Arctic ice-free summer year by all six statistical models appear to converge to the 2037 ± 6 timeframe, with a spread of 17 years, and the earliest first ice-free Arctic summer year at 2031.
Random Access for Underwater Acoustic Cellular Systems
Authors: Pec Rothna , Khan Mohammed , Asim Muhammad , Cho Yong
Published: February 2018

In this paper, a random access preamble (RAP) design technique for underwater acoustic cellular systems is proposed. After showing that the conventional RAP used in long term evolution (LTE) systems is not appropriate for underwater acoustic cellular systems, two different types of RAPs (RAP 1 and RAP 2) are proposed to detect the identity of underwater equipment/nodes (UEs) and estimate the time delay between a UE and an underwater base station (UBS) at the physical layer. RAP 1 is generated using a Zadoff-Chu (ZC) sequence where the identity of the UE is mapped to its root index, whereas RAP 2 is generated using a linear frequency modulation (LFM) waveform where the identity of the UE is mapped to its frequency sweeping parameter and frequency shifting parameter. Ambiguity functions (AFs) and cross-ambiguity functions (CAFs) of RAP 1 and RAP 2 are derived to investigate their correlation properties under the effect of time delay and Doppler shift. The performance of RAP detection is investigated by analyzing the detection probabilities and false alarm probabilities of RAP 1 and RAP 2 in a Doppler environment. By evaluating the performances of RAP 1 and RAP 2 in various situations, it is concluded that RAP 2 is more suitable for underwater acoustic cellular systems. The AF and CAF analytically obtained in this paper are shown to be similar to those obtained using experimental data.
A Real-Time Construction Safety Monitoring System for Hazardous Gas Integrating Wireless Sensor Network and Building Information Modeling Technologies
Authors: Cheung Weng-Fong , Lin Tzu-Hsuan , Lin Yu-Cheng
Published: February 2018

In recent years, many studies have focused on the application of advanced technology as a way to improve management of construction safety management. A Wireless Sensor Network (WSN), one of the key technologies in Internet of Things (IoT) development, enables objects and devices to sense and communicate environmental conditions; Building Information Modeling (BIM), a revolutionary technology in construction, integrates database and geometry into a digital model which provides a visualized way in all construction lifecycle management. This paper integrates BIM and WSN into a unique system which enables the construction site to visually monitor the safety status via a spatial, colored interface and remove any hazardous gas automatically. Many wireless sensor nodes were placed on an underground construction site and to collect hazardous gas level and environmental condition (temperature and humidity) data, and in any region where an abnormal status is detected, the BIM model will alert the region and an alarm and ventilator on site will start automatically for warning and removing the hazard. The proposed system can greatly enhance the efficiency in construction safety management and provide an important reference information in rescue tasks. Finally, a case study demonstrates the applicability of the proposed system and the practical benefits, limitations, conclusions, and suggestions are summarized for further applications.
Improvement in Limit of Detection of Enzymatic Biogas Sensor Utilizing Chromatography Paper for Breath Analysis
Authors: Motooka Masanobu , Uno Shigeyasu
Published: February 2018

Breath analysis is considered to be an effective method for point-of-care diagnosis due to its noninvasiveness, quickness and simplicity. Gas sensors for breath analysis require detection of low-concentration substances. In this paper, we propose that reduction of the background current improves the limit of detection of enzymatic biogas sensors utilizing chromatography paper. After clarifying the cause of the background current, we reduced the background current by improving the fabrication process of the sensors utilizing paper. Finally, we evaluated the limit of detection of the sensor with the sample vapor of ethanol gas. The experiment showed about a 50% reduction of the limit of detection compared to previously-reported sensor. This result presents the possibility of the sensor being applied in diagnosis, such as for diabetes, by further lowering the limit of detection.
Specim IQ: Evaluation of a New, Miniaturized Handheld Hyperspectral Camera and Its Application for Plant Phenotyping and Disease Detection
Authors: Behmann Jan , Acebron Kelvin , Emin Dzhaner , Bennertz Simon , Matsubara Shizue , Thomas Stefan , Bohnenkamp David , Kuska Matheus , Jussila Jouni , Salo Harri , Mahlein Anne-Katrin , Rascher Uwe
Published: February 2018

Hyperspectral imaging sensors are promising tools for monitoring crop plants or vegetation in different environments. Information on physiology, architecture or biochemistry of plants can be assessed non-invasively and on different scales. For instance, hyperspectral sensors are implemented for stress detection in plant phenotyping processes or in precision agriculture. Up to date, a variety of non-imaging and imaging hyperspectral sensors is available. The measuring process and the handling of most of these sensors is rather complex. Thus, during the last years the demand for sensors with easy user operability arose. The present study introduces the novel hyperspectral camera Specim IQ from Specim (Oulu, Finland). The Specim IQ is a handheld push broom system with integrated operating system and controls. Basic data handling and data analysis processes, such as pre-processing and classification routines are implemented within the camera software. This study provides an introduction into the measurement pipeline of the Specim IQ as well as a radiometric performance comparison with a well-established hyperspectral imager. Case studies for the detection of powdery mildew on barley at the canopy scale and the spectral characterization of Arabidopsis thaliana mutants grown under stressed and non-stressed conditions are presented.
Profit Allocation of Hybrid Power System Planning in Energy Internet: A Cooperative Game Study
Authors: Liu Jicheng , He Dandan
Published: February 2018

The rapid development of Energy Internet (EI) has prompted numbers of generators to participate, leading to a hybrid power system. Hence, how to plan the hybrid power system and allocate its profit becomes necessary. In this paper, the cooperative game theory is introduced to discuss this problem. We first design the basic structure of EI, and point out the object of this study—coal power plant-wind farm-photovoltaic power station-energy storage provider (CWPE) alliance. Subsequently, average allocation strategy (AAS), capacity-based allocation strategy (CAS) and Shapley value allocation strategy (SAS) are proposed, and then the modified disruption propensity (MDP) index is constructed to judge the advantages and disadvantages of the three schemes. Thirdly, taking a certain area of A Province as an example, the profits of CWPE under three strategies are calculated respectively. Finally, by analyzing individual rationality and collective rationality of cooperative game and the MDP index of the three profit allocation schemes, we find that SAS is the most stable.
Community Awareness on Rabies Prevention and Control in Bicol, Philippines: Pre- and Post-Project Implementation
Authors: Barroga Toni , Basitan Ilene , Lobete Themis , Bernales Rona , Gordoncillo Mary , Lopez Emelinda , Abila Ronello
Published: February 2018

Rabies is endemic in the Philippines. To support the rabies campaign in the Bicol region at the southeastern part of Luzon, the BAI-OIE Stop Transboundary Animal Diseases and Zoonoses (STANDZ) Rabies project was implemented in the pilot provinces of Camarines Norte, Camarines Sur, Albay, and Masbate. A community awareness survey was conducted with the residents of these provinces to determine their knowledge, attitude, and practices (KAP) on rabies during the start and end of the project. Qualitative, descriptive research was done with a structured KAP questionnaire. Pet owners in the pilot provinces were chosen as respondents. Results showed that respondents know that they can acquire rabies in animals through the bite of a rabid dog (pre-project implementation (PRI): 19.6%, post-project implementation (POI): 38.0%). Vaccination was the top rabies preventive measure (PRI: 61.8%, POI: 92.8%). Biting incidents were noted in some respondents, and observing the dog and killing it immediately were some of the actions taken by bite victims. If a supposed rabid dog was seen, respondents would either: immediately kill the dog (PRI: 20.3%, POI: 13.7%), report it to authorities (PRI: 26.3%, POI: 63.1%), and capture and observe the dog concerned (PRI: 13.5%, POI: 6.0%). Pet owners increased their KAP about rabies prevention and control as compared to the pre-implementation study. However, certain gaps in their KAP need to be given attention; thus continuous education of pet owners must be done.
The ‘Influenza’ Vaccine Used during the Samoan Pandemic of 1918
Authors: Shanks G.
Published: February 2018

In 1918, a crude influenza vaccine made from chemically inactivated, mixed cultures of respiratory bacteria was widely used prior to the understanding that influenza was caused by a virus. Such vaccines contained no viral material and probably consisted largely of bacterial endotoxin. The Australian military used such a vaccine on Samoa in December 1918 and thought it was valuable. Post hoc analyses suggest that the mixed respiratory bacteria vaccine may have actually been of some benefit, but the mechanism of such protection is unknown. Although such a crude vaccine would not be considered in a modern setting, the rapid use of problematic vaccines still remains a risk when new influenza types suddenly appear, as in 1976 and 2009.
Social Innovation Systems for Building Resilient Communities
Authors: Horgan Donagh , Dimitrijević Branka
Published: February 2018

Social innovation—while not a new practice in itself—has re-emerged since the global financial crisis in 2008 as an approach to solving our collective intractable global challenges. Despite its renewed popularity, there is no common definition for the phenomenon, not least in the context of its application when planning the built environment or civic infrastructures. This paper seeks to position the practice of social innovation as a means for holistic collaboration between disciplines to develop sustainable social ecologies and systems that provide for resilient communities. It tests a hypothesis that social innovation develops over phases (feedback loops)—that of the network, framework and architecture phase—to design for social, environmental and economic resilience. It looks to theories emerging in other subject areas like sociology and technology, that can inform its application in a planning context, such as Actor-Network and Adaptive Complexity theories. It explores the mechanisms that provide for resilience through action research and engagement with a number of international case studies and scenarios. Lastly, the paper identifies further avenues of research pertaining to networks, frameworks and architectures to develop models of best practice for inclusive, sustainable and iterative community development.