bluuebunny/crossref_metadata_2025 huggingface dataset:
Issues with Publishing Abstracts in English: Challenges for Portuguese Linguists’ Authorial Voices
Authors: Santos Joana , Da Silva Paulo
Published: April 2016

This paper assesses the impact of publishing abstracts in English in the Portuguese Linguistics Association (APL) Proceedings from 2001 to 2010. The study was carried out with a corpus of 137 abstracts, follows a Text Linguistics model inspired by the Interactionnisme Sociodiscoursif and links text features to the social practices and genre repertoires of this community. Quantitative data show signs of a “Portuguese identity” in authors’ voices such as personal forms, move signaling, long sentences, profuse embedding, heavy subjects, and variations in content selection, but also signs of standard academic guideline-indexed choices in impersonal forms, template sentences, coordinated constituents, nominalizations, and conventional text plans. Standard genre models and writing features from “core” academic communities coexist with alternative and traditional ways of writing and of disseminating knowledge, which is typical of a semiperipheral non-native English-speaking community torn between conflicting language and cultural paradigms. These contrasting tendencies are linked to identity changes within the community, as APL authors try to achieve international recognition by publishing abstracts in English as a Foreign Language. Since the APL research topic is the Portuguese language, the process mirrors the authors’ struggle between standard internationalization in English and individual stance in Portuguese.
Monitoring Plastic-Mulched Farmland by Landsat-8 OLI Imagery Using Spectral and Textural Features
Authors: Hasituya  , Chen Zhongxin , Wang Limin , Wu Wenbin , Jiang Zhiwei , Li He
Published: April 2016

In recent decades, plastic-mulched farmland has expanded rapidly in China as well as in the rest of the world because it results in marked increases of crop production. However, plastic-mulched farmland significantly influences the environment and has so far been inadequately investigated. Accurately monitoring and mapping plastic-mulched farmland is crucial for agricultural production, environmental protection, resource management, and so on. Monitoring plastic-mulched farmland using moderate-resolution remote sensing data is technically challenging because of spatial mixing and spectral confusion with other ground objects. This paper proposed a new scheme that combines spectral and textural features for monitoring the plastic-mulched farmland and evaluates the performance of a Support Vector Machine (SVM) classifier with different kernel functions using Landsat-8 Operational Land Imager (OLI) imagery. The textural features were extracted from multi-bands OLI data using a Grey Level Co-occurrence Matrix (GLCM) algorithm. Then, six combined feature sets were developed for classification. The results indicated that Landsat-8 OLI data are well suitable for monitoring plastic-mulched farmland; the SVM classifier with a linear kernel function is superior both to other kernel functions and to two other widely used supervised classifiers: Maximum Likelihood Classifier (MLC) and Minimum Distance Classifier (MDC). For the SVM classifier with a linear kernel function, the highest overall accuracy was derived from combined spectral and textural features in the 90° direction (94.14%, kappa 0.92), followed by the combined spectral and textural features in the 45° (93.84%, kappa 0.92), 135° (93.73%, kappa 0.92), 0° (93.71%, kappa 0.92) directions, and the spectral features alone (93.57%, kappa 0.91). Spectral features make a more significant contribution to monitoring the plastic-mulched farmland; adding textural features from medium resolution imagery provide only limited improvement in accuracy.
Amazon Forests’ Response to Droughts: A Perspective from the MAIAC Product
Authors: Bi Jian , Myneni Ranga , Lyapustin Alexei , Wang Yujie , Park Taejin , Chi Chen , Yan Kai , Knyazikhin Yuri
Published: April 2016

Amazon forests experienced two severe droughts at the beginning of the 21st century: one in 2005 and the other in 2010. How Amazon forests responded to these droughts is critical for the future of the Earth’s climate system. It is only possible to assess Amazon forests’ response to the droughts in large areal extent through satellite remote sensing. Here, we used the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) data to assess Amazon forests’ response to droughts, and compared the results with those from the standard (Collection 5 and Collection 6) MODIS VI data. Overall, the MAIAC data reveal more realistic Amazon forests inter-annual greenness dynamics than the standard MODIS data. Our results from the MAIAC data suggest that: (1) the droughts decreased the greenness (i.e., photosynthetic activity) of Amazon forests; (2) the Amazon wet season precipitation reduction induced by El Niño events could also lead to reduced photosynthetic activity of Amazon forests; and (3) in the subsequent year after the water stresses, the greenness of Amazon forests recovered from the preceding decreases. However, as previous research shows droughts cause Amazon forests to reduce investment in tissue maintenance and defense, it is not clear whether the photosynthesis of Amazon forests will continue to recover after future water stresses, because of the accumulated damages caused by the droughts.
Remote Sensing-Based Exploration of Structurally-Related Mineralizations around Mount Isa, Queensland, Australia
Authors: Jakob Sandra , Gloaguen Richard , Laukamp Carsten
Published: April 2016

Hyperspectral imaging is a powerful tool for mineral mapping and increasingly used in poorly-accessible areas. It only requires a limited amount of validation sample points, but can fail to discriminate spectrally-similar features. In this manuscript, we show that we improve the identification of interesting targets by including geomorphological data in the spectral mapping scheme. We jointly use geomorphic and spectral features to locate gossanous ironstone ridges as an indicator for possible Pb-Zn-Ag-mineralization and provide an application around Mount Isa and George Fisher/Hilton mine, Queensland, Australia. We combine hyperspectral HyMap data using mixture tuned matched filtering with topographical indices, such as maximum curvature and the topographical position index. As it is often the case with structurally-controlled mineralization, the amount of training sites is limited, and supervised classification methods cannot be implemented. Therefore, we implement expert knowledge in a decision tree to take advantage of the relationship between mineralization, alteration and structure. Optimized rock sampling and spectral measurements provided data for validation. We are able to map sets of gossanous ridges with a minimum of validation points, not only within the Mount Isa mining area itself, but also outside the commonly-accepted host rocks. The ridges are parallel to north-south trending geomorphological features and probably associated with the Paroo fault zone. Similarities between the ridges were confirmed by field observations, spectral measurements and a qualitative rock sample analysis. We identified new mineralized ridges that we could subsequently attribute to a poorly-known and sub-economic deposit known as the Mount Novit Pb-Zn-deposit.
Design of Secure ECG-Based Biometric Authentication in Body Area Sensor Networks
Authors: Peter Steffen , Pratap Reddy Bhanu , Momtaz Farshad , Givargis Tony
Published: April 2016

Body area sensor networks (BANs) utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG) signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system.
A High-Speed Vision-Based Sensor for Dynamic Vibration Analysis Using Fast Motion Extraction Algorithms
Authors: Zhang Dashan , Guo Jie , Lei Xiujun , Zhu Changan
Published: April 2016

The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.
Protein Chips for Detection of Salmonella spp. from Enrichment Culture
Authors: Poltronieri Palmiro , Cimaglia Fabio , De Lorenzis Enrico , Chiesa Maurizio , Mezzolla Valeria , Reca Ida
Published: April 2016

Food pathogens are the cause of foodborne epidemics, therefore there is a need to detect the pathogens in food productions rapidly. A pre-enrichment culture followed by selective agar plating are standard detection methods. Molecular methods such as qPCR have provided a first rapid protocol for detection of pathogens within 24 h of enrichment culture. Biosensors also may provide a rapid tool to individuate a source of Salmonella contamination at early times of pre-enrichment culture. Forty mL of Salmonella spp. enrichment culture were processed by immunoseparation using the Pathatrix, as in AFNOR validated qPCR protocols. The Salmonella biosensor combined with immunoseparation showed a limit of detection of 100 bacteria/40 mL, with a 400 fold increase to previous results. qPCR analysis requires processing of bead-bound bacteria with lysis buffer and DNA clean up, with a limit of detection of 2 cfu/50 μL. Finally, a protein chip was developed and tested in screening and identification of 5 common pathogen species, Salmonella spp., E. coli, S. aureus, Campylobacter spp. and Listeria spp. The protein chip, with high specificity in species identification, is proposed to be integrated into a Lab-on-Chip system, for rapid and reproducible screening of Salmonella spp. and other pathogen species contaminating food productions.
Outlier Detection in GNSS Pseudo-Range/Doppler Measurements for Robust Localization
Authors: Zair Salim , Le Hégarat-Mascle Sylvie , Seignez Emmanuel
Published: April 2016

In urban areas or space-constrained environments with obstacles, vehicle localization using Global Navigation Satellite System (GNSS) data is hindered by Non-Line Of Sight (NLOS) and multipath receptions. These phenomena induce faulty data that disrupt the precise localization of the GNSS receiver. In this study, we detect the outliers among the observations, Pseudo-Range (PR) and/or Doppler measurements, and we evaluate how discarding them improves the localization. We specify a contrario modeling for GNSS raw data to derive an algorithm that partitions the dataset between inliers and outliers. Then, only the inlier data are considered in the localization process performed either through a classical Particle Filter (PF) or a Rao-Blackwellization (RB) approach. Both localization algorithms exclusively use GNSS data, but they differ by the way Doppler measurements are processed. An experiment has been performed with a GPS receiver aboard a vehicle. Results show that the proposed algorithms are able to detect the ‘outliers’ in the raw data while being robust to non-Gaussian noise and to intermittent satellite blockage. We compare the performance results achieved either estimating only PR outliers or estimating both PR and Doppler outliers. The best localization is achieved using the RB approach coupled with PR-Doppler outlier estimation.
Localized Electrical Impedance Myography of the Biceps Brachii Muscle during Different Levels of Isometric Contraction and Fatigue
Authors: Li Le , Shin Henry , Li Xiaoyan , Li Sheng , Zhou Ping
Published: April 2016

This study assessed changes in electrical impedance myography (EIM) at different levels of isometric muscle contraction as well as during exhaustive exercise at 60% maximum voluntary contraction (MVC) until task failure. The EIM was performed on the biceps brachii muscle of 19 healthy subjects. The results showed that there was a significant difference between the muscle resistance (R) measured during the isometric contraction and when the muscle was completely relaxed. Post hoc analysis shows that the resistance increased at higher contractions (both 60% MVC and MVC), however, there were no significant changes in muscle reactance (X) during the isometric contractions. The resistance also changed during different stages of the fatigue task and there were significant decreases from the beginning of the contraction to task failure as well as between task failure and post fatigue rest. Although our results demonstrated an increase in resistance during isometric contraction, the changes were within 10% of the baseline value. These changes might be related to the modest alterations in muscle architecture during a contraction. The decrease in resistance seen with muscle fatigue may be explained by an accumulation of metabolites in the muscle tissue.
Optimizing Colorimetric Assay Based on V2O5 Nanozymes for Sensitive Detection of H2O2 and Glucose
Authors: Sun Jiaheng , Li Chunyan , Qi Yanfei , Guo Shuanli , Liang Xue
Published: April 2016

Nanozyme-based chemical sensing is a rapidly emerging field of research. Herein, a simple colorimetric assay for the detection of hydrogen peroxide and glucose based on the peroxidase-like activity of V2O5 nanozymes has been established. In this assay, the effects of pH, substrate, nanozyme concentrations and buffer solution have been investigated. It was found that compared with 3,3′,5,5′-tetramethylbenzidine (TMB), the enzyme substrate o-phenylenediamine (OPD) seriously interfered with the H2O2 detection. Under the optimal reaction conditions, the resulting sensor displayed a good response to H2O2 with a linear range of 1 to 500 μM, and a detection limit of 1 μM at a signal-to-noise ratio of 3. A linear correlation was established between absorbance intensity and concentration of glucose from 10 to 2000 μM, with a detection limit of 10 μM. The current work presents a simple, cheap, more convenient, sensitive, and easy handling colorimetric assay.
VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine
Authors: De Bei Roberta , Fuentes Sigfredo , Gilliham Matthew , Tyerman Steve , Edwards Everard , Bianchini Nicolò , Smith Jason , Collins Cassandra
Published: April 2016

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants.
HybridPLAY: A New Technology to Foster Outdoors Physical Activity, Verbal Communication and Teamwork
Authors: Díaz Diego , Boj Clara , Portalés Cristina
Published: April 2016

This paper presents HybridPLAY, a novel technology composed of a sensor and mobile-based video games that transforms urban playgrounds into game scenarios. With this technology we aim to stimulate physical activity and playful learning by creating an entertaining environment in which users can actively participate and collaborate. HybridPLAY is different from other existing technologies that enhance playgrounds, as it is not integrated in them but can be attached to the different elements of the playgrounds, making its use more ubiquitous (i.e., not restricted to the playgrounds). HybridPLAY was born in 2007 as an artistic concept, and evolved after different phases of research and testing by almost 2000 users around the world (in workshops, artistic events, conferences, etc.). Here, we present the temporal evolution of HybridPLAY with the different versions of the sensors and the video games, and a detailed technical description of the sensors and the way interactions are produced. We also present the outcomes after the evaluation by users at different events and workshops. We believe that HybridPLAY has great potential to contribute to increased physical activity in kids, and also to improve the learning process and monitoring at school centres by letting users create the content of the apps, leading to new narratives and fostering creativity.
Healthcare4VideoStorm: Making Smart Decisions Based on Storm Metrics
Authors: Zhang Weishan , Duan Pengcheng , Chen Xiufeng , Lu Qinghua
Published: April 2016

Storm-based stream processing is widely used for real-time large-scale distributed processing. Knowing the run-time status and ensuring performance is critical to providing expected dependability for some applications, e.g., continuous video processing for security surveillance. The existing scheduling strategies’ granularity is too coarse to have good performance, and mainly considers network resources without computing resources while scheduling. In this paper, we propose Healthcare4Storm, a framework that finds Storm insights based on Storm metrics to gain knowledge from the health status of an application, finally ending up with smart scheduling decisions. It takes into account both network and computing resources and conducts scheduling at a fine-grained level using tuples instead of topologies. The comprehensive evaluation shows that the proposed framework has good performance and can improve the dependability of the Storm-based applications.
Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review
Authors: Ding Sandrine , Schumacher Michael
Published: April 2016

Diabetic individuals need to tightly control their blood glucose concentration. Several methods have been developed for this purpose, such as the finger-prick or continuous glucose monitoring systems (CGMs). However, these methods present the disadvantage of being invasive. Moreover, CGMs have limited accuracy, notably to detect hypoglycemia. It is also known that physical exercise, and even daily activity, disrupt glucose dynamics and can generate problems with blood glucose regulation during and after exercise. In order to deal with these challenges, devices for monitoring patients’ physical activity are currently under development. This review focuses on non-invasive sensors using physiological parameters related to physical exercise that were used to improve glucose monitoring in type 1 diabetes (T1DM) patients. These devices are promising for diabetes management. Indeed they permit to estimate glucose concentration either based solely on physical activity parameters or in conjunction with CGM or non-invasive CGM (NI-CGM) systems. In these last cases, the vital signals are used to modulate glucose estimations provided by the CGM and NI-CGM devices. Finally, this review indicates possible limitations of these new biosensors and outlines directions for future technologic developments.
Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application
Authors: Mur Angel , Dormido Raquel , Vega Jesús , Duro Natividad , Dormido-Canto Sebastian
Published: April 2016

In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG) recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised method. To this end an example of the performance of the algorithm to detect artifacts is shown. The results show that although both methods obtain similar classification, the proposed method allows detecting events without training data and can also be applied in signals whose events are unknown a priori. Furthermore, the proposed method provides an optimal window whereby an optimal detection and characterization of events is found. The detection of events can be applied in real-time.
Color-Space-Based Visual-MIMO for V2X Communication
Authors: Kim Jai-Eun , Kim Ji-Won , Park Youngil , Kim Ki-Doo
Published: April 2016

In this paper, we analyze the applicability of color-space-based, color-independent visual-MIMO for V2X. We aim to achieve a visual-MIMO scheme that can maintain the original color and brightness while performing seamless communication. We consider two scenarios of GCM based visual-MIMO for V2X. One is a multipath transmission using visual-MIMO networking and the other is multi-node V2X communication. In the scenario of multipath transmission, we analyze the channel capacity numerically and we illustrate the significance of networking information such as distance, reference color (symbol), and multiplexing-diversity mode transitions. In addition, in the V2X scenario of multiple access, we may achieve the simultaneous multiple access communication without node interferences by dividing the communication area using image processing. Finally, through numerical simulation, we show the superior SER performance of the visual-MIMO scheme compared with LED-PD communication and show the numerical result of the GCM based visual-MIMO channel capacity versus distance.
How Can I Trust You if You Don’t Know Who You Are? The Consequences of a Fluid Identity on Cross-Racial Organizing between African American Women and Latinas in Atlanta
Authors: González Belisa
Published: April 2016

Scholarship in the area of cross-racial organizing between Latina/o and African Americans has increased substantially over the past ten years. Within that literature, scholars have identified many reasons why cross-racial coalitions both succeed and fail. Among the factors most often cited is the issue of trust. Despite the recognition of the crucial role trust plays in cross-racial organizing, little attention has been paid to what contributes to actually building trust between African Americans and Latina/o. I argue that one factor contributing to the distrust of Latinas among African American women involved in cross-racial organizing in Atlanta is the perceived discrepancy between Latinas’ own asserted identity and the identity assigned to them by African American women organizers. Using data gathered from six years of participant observation and forty interviews conducted with African American women and Latinas organizing in Georgia, I discuss the consequences of identity construction for cross-racial organizing. I find that within cross-racial organizing spaces in Atlanta, perceived racial identities are used by African American women as proxies for determining Latina organizers’ commitment to social justice and, correspondingly, how much individual Latinas can be trusted. Specifically, I find that African American respondents view Latina identity as optional and potentially white. Latina respondents, on the other hand, assert strong identities and contend that their perceived “optional” identities are a function of what Anzaldúa calls a mestiza consciousness or the straddeling of multiple identities. I argue that understanding how these identities are assigned and asserted by Latinas and African American women is a crucial and often-overlooked component to building trust, and by extension, to building sustainable cross-racial coalitions.
Political Experience and the Success of Female Gubernatorial Candidates
Authors: O’Regan Valerie , Stambough Stephen
Published: April 2016

This research examines the effect that political experience has on the success of female gubernatorial candidates by analyzing the female vs. male gubernatorial elections from 1976–2014. The study questions whether prior statewide political office experience is advantageous for female candidates and is this consistent across party lines. This research builds on the political pipeline theory, which suggests that the shortage of women holding higher level political office, such as governor, is due to the lack of qualified and motivated women running for political office. We argue that women who hold lower level statewide office develop the necessary experience and name recognition that provides them with the qualifications and motivation, both within themselves and from other sources such as political parties, to run for and win the office of governor. Our findings suggest that statewide office experience is important for the success of Democratic women gubernatorial candidates but not for Republican women gubernatorial candidates.
Sustainability of Smallholder Agriculture in Semi-Arid Areas under Land Set-aside Programs: A Case Study from China’s Loess Plateau
Authors: Li Qirui , Amjath-Babu T. , Zander Peter , Liu Zhen , Müller Klaus
Published: April 2016

This article analyzes agricultural sustainability in the context of land degradation, rural poverty and social inequality, taking China’s Loess Hills as an example. The analysis attempts to understand the multi-dimensionality of sustainability at the farm level and its relationship with physical-socio-economic-infrastructural-technological framework conditions in the context of the land set-aside program viz. the Grain for Green Project (GGP). We developed composite indices of sustainability and its environmental, economic and social dimensions using a principal component analysis (PCA)-based weighting scheme. Regression analyses were conducted to examine the relationship between the estimated sustainability indicators and the variables representing framework conditions of knowledge, demographics, resource endowment and production techniques. The stated analysis was conducted on a dataset collected by means of household surveys in 2014 in valleys and flood plain areas in Yanhe Township. Findings reveal hidden correlations among the indicators of environmental, economic, and social pillars of sustainability. The ratio of land under the conservation program to actual farmland emerged as a key determinant of overall agricultural sustainability and its social dimension, which reaches the maximum when the ratio is around 0.56 and 0.64, respectively. The results also show that there is need to balance off-farm and on-farm income diversification as well as highlight the role of women in ensuring the sustainability of farming households. The core achievement of the article is the definition of the thresholds for the land set-aside program and the identification of major determinants of agricultural sustainability in the rural Chinese context in particular and in rural farming communities in general.
An Approach to Assess the Effectiveness of Smart Growth in Achieving Sustainable Development
Authors: Mohammed Ishak , Alshuwaikhat Habib , Adenle Yusuf
Published: April 2016

Smart Growth has become an evident concept in public policy debates and provides answers to the enduring problems of sprawling development and its many adverse consequences. While the concept has widely been touted to promote an urban development pattern characterized by compact and mixed-use development, walkable and bikeable neighborhoods, preserved green spaces, and the availability of mass transit, not much has been written about its contribution to sustainable development. This paper is an attempt to explore the concepts of smart growth and sustainable development and the extent to which the former contributes to the achievement of the latter. The various debates surrounding the smart growth movement have also been explored. The 2003 general plan guideline by the US State of California is used as the basis for determining the sustainable development role of smart growth policies in Portland (Oregon), Arlington (Virginia), Boulder (Colorado) and Lancaster County (Pennsylvania). The paper concludes that it would be inappropriate to equate smart growth to sustainable development as the latter is a much broader concept and cuts across myriad disciplines. Notwithstanding, the implementation of smart growth policies in the cases studied have been observed to promote compact, infill and transit-oriented development and to conserve and protect open spaces and natural areas. All these are pro-sustainable development. While this paper has observed that smart growth serves as one of the approaches for achieving sustainable development goals, it calls for a more quantitative study to be able to measure the magnitude of the contribution associated with the smart growth policies.
The Sustainable Improvement of Manufacturing for Nano-Titanium
Authors: Wang Chia-Nan , Lin Han-Sung , Hsueh Ming-Hsien , Wang Yen-Hui , Vu Thi-Hao , Lin Tsung-Fu
Published: April 2016

Scientists have found that nanomaterials possess many outstanding features in their tiny grain structure compared to other common materials. Titanium at the nano-grain scale shows many novel characteristics which demonstrate suitability for use in surgical implants. In general, equal channel angular pressing (ECAP) is the most popular and simple process to produce nano-titanium. However, ECAP is time-consuming, power-wasting, and insufficiently produces the ultrafine grain structure. Therefore, the objective of this research is to propose a new method to improve the ECAP’s performances to reach the ultrafine grain structure, and also to save production costs, based on the innovation theory of Teoriya Resheniya Izobreatatelskih Zadatch (TRIZ). Research results show that the process time is reduced by 80%, and 94% of the energy is saved. Moreover, the grain size of the diameter for nano-titanium can be reduced from 160 nanometers (nm) to 80 nm. The results are a 50% reduction of diameter and a 75% improvement of volume. At the same time, the method creates a refined grain size and good mechanical properties in the nano-titanium. The proposed method can be applied to produce any nanomaterial as well as biomaterials.
Urban Resilience in Climate Change Adaptation: A Conceptual Framework
Authors: Kim Donghyun , Lim Up
Published: April 2016

This study presents a conceptual framework for analyzing urban resilience in the context of climate change. The key conceptual elements of resilience are first identified and then reorganized with a focus on cities and climate change adaptation. This study covers not only ecological and engineering resilience but also resilience as a sociopolitical process from an evolutionary perspective. The study’s conceptual framework centers on resilience as it relates to cities and climate change. Its findings are expected to shed light on future urban planning and policies for adapting to climate change.
Research on the Relationship between Urban Development Intensity and Eco-Environmental Stresses in Bohai Rim Coastal Area, China
Authors: Wang Dongchuan , Chen Wengang , Wei Wei , W. Bird Broxton , Zhang Lihui , Sang Mengqin , Wang Qianqian
Published: April 2016

To realize sustainable urban development that minimizes environmental impacts, the relationship between urban development intensity and eco-environmental stresses should be clearly revealed. This paper focused on the Bohai Rim coastal area, where cities have experienced significant development in the last decade. An index system was developed to quantify the comprehensive urban development intensity (CDI) and comprehensive eco-environment stresses (CES). Remote sensing imagery and statistical data were used to provide indices for CDI and CES. Spatiotemporal analysis was carried out on the correlation between the two indices. The coupling between the CDI and CES was then investigated to explore the urban development characteristics of each city in the study area, its development level, and the trend of urban development. Results showed that human activities surrounding urban development were partly dependent on the use of ecological resources to a certain degree, and that the degree of dependence increased with year. To promote a sustainable level of urban development, the government should focus on not only the high development intensity, but also the high quality of the eco-environment. Dalian was a good model of how to achieve a balance between the two.
Urban Environment and Nature. A Methodological Proposal for Spaces’ Reconnection in an Ecosystem Function
Authors: Prestamburgo Sonia , Premrù Tommaso , Secondo Giorgia
Published: April 2016

Our main objective is to highlight the profound disconnect between natural and anthropic elements within urban areas, with particular reference to the morpho-functional dimensions of the urban and territorial pattern. Heterogeneity in the elements underpinning relations in urban environments, absent governing principles, predisposes to conditions of widespread dysfunction and inefficiency in the modalities of anthropic utilization of the various contexts. As a result, the functions inherent to ecological and natural networks tend to be undermined, negatively impacting the environment. To this end, this paper proposes the adoption of ecoducts, on the one hand as a means to support planning and a measure aimed at reactivating the complex functions typical of urban environments and, on the other hand, as a two-way correlation between anthropic and ecological interactions at the territorial scale. Finally, the analysis of an Italian case study will highlight the potential of such instruments in terms of creating an integrated eco-systemic service, capable of significantly contributing to long-term improvement in the quality of life of urban systems.
Urban Cultivation and Its Contributions to Sustainability: Nibbles of Food but Oodles of Social Capital
Authors: Martin George , Clift Roland , Christie Ian
Published: April 2016

The contemporary interest in urban cultivation in the global North as a component of sustainable food production warrants assessment of both its quantitative and qualitative roles. This exploratory study weighs the nutritional, ecological, and social sustainability contributions of urban agriculture by examining three cases—a community garden in the core of New York, a community farm on the edge of London, and an agricultural park on the periphery of San Francisco. Our field analysis of these sites, confirmed by generic estimates, shows very low food outputs relative to the populations of their catchment areas; the great share of urban food will continue to come from multiple foodsheds beyond urban peripheries, often far beyond. Cultivation is a more appropriate designation than agriculture for urban food growing because its sustainability benefits are more social than agronomic or ecological. A major potential benefit lies in enhancing the ecological knowledge of urbanites, including an appreciation of the role that organic food may play in promoting both sustainability and health. This study illustrates how benefits differ according to local conditions, including population density and demographics, operational scale, soil quality, and access to labor and consumers. Recognizing the real benefits, including the promotion of sustainable diets, could enable urban food growing to be developed as a component of regional foodsheds to improve the sustainability and resilience of food supply, and to further the process of public co-production of new forms of urban conviviality and wellbeing.
Membrane-Cryogenic Post-Combustion Carbon Capture of Flue Gases from NGCC
Authors: Scholes Colin , Ho Minh , Wiley Dianne
Published: April 2016

Membrane gas separation for carbon capture has traditionally been focused on high pressure applications, such as pre-combustion capture and natural gas sweetening. Recently a membrane-cryogenic combined process has been shown to be cost competitive for post-combustion capture from coal fired power stations. Here, the membrane-cryogenic combined process is investigated for application to post-combustion carbon capture from the flue gas of a Natural Gas Combined Cycle (NGCC) process. This process involves a three-membrane process, where the combustion air is used as the sweep gas on the second membrane stage to recycle CO2 through the turbine. This ensures high CO2 recovery and also increases the CO2 partial pressure in the flue gas. The three-CO2-selective membrane process with liquefaction and O2-enrichment was found to have a cost of capture higher than the corresponding process for coal post-combustion capture. This was attributed to the large size and energy duty of the gas handling equipment, especially the feed blower, because of the high gas throughput in the system caused by significant CO2 recycling. In addition, the economics were uncompetitive compared to a modelled solvent absorption processes for NGCC.
A Disintegrin and Metalloprotease (ADAM): Historical Overview of Their Functions
Authors: Giebeler Nives , Zigrino Paola
Published: April 2016

Since the discovery of the first disintegrin protein from snake venom and the following identification of a mammalian membrane-anchored metalloprotease-disintegrin implicated in fertilization, almost three decades of studies have identified additional members of these families and several biochemical mechanisms regulating their expression and activity in the cell. Most importantly, new in vivo functions have been recognized for these proteins including cell partitioning during development, modulation of inflammatory reactions, and development of cancers. In this review, we will overview the a disintegrin and metalloprotease (ADAM) family of proteases highlighting some of the major research achievements in the analysis of ADAMs’ function that have underscored the importance of these proteins in physiological and pathological processes over the years.
The Correlation between the Virus- and Brain Antigen-Specific B Cell Response in the Blood of Patients with Multiple Sclerosis
Authors: Wunsch Marie , Hohmann Christopher , Milles Bianca , Rostermund Christina , Lehmann Paul , Schroeter Michael , Bayas Antonios , Ulzheimer Jochen , Mäurer Mathias , Ergün Süleyman , Kuerten Stefanie
Published: April 2016

There is a largely divergent body of literature regarding the relationship between Epstein-Barr virus (EBV) infection and brain inflammation in multiple sclerosis (MS). Here, we tested MS patients during relapse (n = 11) and in remission (n = 19) in addition to n = 22 healthy controls to study the correlation between the EBV- and brain-specific B cell response in the blood by enzyme-linked immunospot (ELISPOT) and enzyme-linked immunosorbent assay (ELISA). Cytomegalovirus (CMV) was used as a control antigen tested in n = 16 MS patients during relapse and in n = 35 patients in remission. Over the course of the study, n = 16 patients were untreated, while n = 33 patients received immunomodulatory therapy. The data show that there was a moderate correlation between the frequencies of EBV- and brain-reactive B cells in MS patients in remission. In addition we could detect a correlation between the B cell response to EBV and disease activity. There was no evidence of an EBV reactivation. Interestingly, there was also a correlation between the frequencies of CMV- and brain-specific B cells in MS patients experiencing an acute relapse and an elevated B cell response to CMV was associated with higher disease activity. The trend remained when excluding seronegative subjects but was non-significant. These data underline that viral infections might impact the immunopathology of MS, but the exact link between the two entities remains subject of controversy.
Development of a Triple-Color Pseudovirion-Based Assay to Detect Neutralizing Antibodies against Human Papillomavirus
Authors: Nie Jianhui , Liu Yangyang , Huang Weijin , Wang Youchun
Published: April 2016

Pseudovirion-based neutralization assay is considered the gold standard method for evaluating the immune response to human papillomavirus (HPV) vaccines. In this study, we developed a multicolor neutralization assay to simultaneously detect the neutralizing antibodies against different HPV types. FluoroSpot was used to interpret the fluorescent protein expression instead of flow cytometry. The results of FluoroSpot and flow cytometry showed good consistency, with R2 > 0.98 for the log-transformed IC50 values. Regardless of the reporter color, the single-, dual-, and triple-color neutralization assays reported identical results for the same samples. In low-titer samples from naturally HPV-infected individuals, there was strong agreement between the single- and triple-color assays, with kappa scores of 0.92, 0.89, and 0.96 for HPV16, HPV18, and HPV58, respectively. Good reproducibility was observed for the triple-color assay, with coefficients of variation of 2.0%–41.5% within the assays and 8.3%–36.2% between the assays. Three triple-color systems, HPV16-18-58, HPV6-33-45, and HPV11-31-52, were developed that could evaluate the immunogenicity of a nonavalent vaccine in three rounds of the assay. With the advantages of an easy-to-use procedure and less sample consumption, the multiple-color assay is more suitable than classical assays for large sero-epidemiological studies and clinical trials and is more amenable to automation.
Vaccination with the Secreted Glycoprotein G of Herpes Simplex Virus 2 Induces Protective Immunity after Genital Infection
Authors: Önnheim Karin , Ekblad Maria , Görander Staffan , Bergström Tomas , Liljeqvist Jan-Åke
Published: April 2016

Herpes simplex virus 2 (HSV-2) infects the genital mucosa and establishes a life-long infection in sensory ganglia. After primary infection HSV-2 may reactivate causing recurrent genital ulcerations. HSV-2 infection is prevalent, and globally more than 400 million individuals are infected. As clinical trials have failed to show protection against HSV-2 infection, new vaccine candidates are warranted. The secreted glycoprotein G (sgG-2) of HSV-2 was evaluated as a prophylactic vaccine in mice using two different immunization and adjuvant protocols. The protocol with three intramuscular immunizations combining sgG-2 with cytosine-phosphate-guanine dinucleotide (CpG) motifs and alum induced almost complete protection from genital and systemic disease after intra-vaginal challenge with HSV-2. Robust immunoglobulin G (IgG) antibody titers were detected with no neutralization activity. Purified splenic CD4+ T cells proliferated and produced interferon-γ (IFN-γ) when re-stimulated with the antigen in vitro. sgG-2 + adjuvant intra-muscularly immunized mice showed a significant reduction of infectious HSV-2 and increased IFN-γ levels in vaginal washes. The HSV-2 DNA copy numbers were significantly reduced in dorsal root ganglia, spinal cord, and in serum at day six or day 21 post challenge. We show that a sgG-2 based vaccine is highly effective and can be considered as a novel candidate in the development of a prophylactic vaccine against HSV-2 infection.
Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines
Authors: Torres-Rua Alfonso , Ticlavilca Andres , Bachour Roula , McKee Mac
Published: April 2016

Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains challenging due to coarse spatial and temporal resolution of existing remotely-sensed products. Furthermore, while preceding research on soil moisture using remote sensing (surface energy balance, weather parameters, and vegetation indices) has demonstrated a relationship between these factors and soil moisture, practical continuous spatial quantification of the latter is still unavailable for use in water and agricultural management. In this study, a methodology is presented to estimate volumetric surface soil moisture by statistical selection from potential predictors that include vegetation indices and energy balance products derived from satellite (Landsat) imagery and weather data as identified in scientific literature. This methodology employs a statistical learning machine called a Relevance Vector Machine (RVM) to identify and relate the potential predictors to soil moisture by means of stratified cross-validation and forward variable selection. Surface soil moisture measurements from irrigated agricultural fields in Central Utah in the 2012 irrigation season were used, along with weather data, Landsat vegetation indices, and energy balance products. The methodology, data collection, processing, and estimation accuracy are presented and discussed.