bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing Landsat and RADARSAT for Current and Historical Dynamic Flood Mapping
Authors: Olthof Ian , Tolszczuk-Leclerc Simon
Published: May 2018

Mapping the historical occurrence of flood water in time and space provides information that can be used to help mitigate damage from future flood events. In Canada, flood mapping has been performed mainly from RADARSAT imagery in near real-time to enhance situational awareness during an emergency, and more recently from Landsat to examine historical surface water dynamics from the mid-1980s to present. Here, we seek to integrate the two data sources for both operational and historical flood mapping. A main challenge of a multi-sensor approach is ensuring consistency between surface water mapped from sensors that fundamentally interact with the target differently, particularly in areas of flooded vegetation. In addition, automation of workflows that previously relied on manual interpretation is increasingly needed due to large data volumes contained within satellite image archives. Despite differences between data received from both sensors, common approaches to surface water and flooded vegetation mapping including multi-channel classification and region growing can be applied with sensor-specific adaptations for each. Historical open water maps from 202 Landsat scenes spanning the years 1985–2016 generated previously were enhanced to improve flooded vegetation mapping along the Saint John River in New Brunswick, Canada. Open water and flooded vegetation maps were created over the same region from 181 RADARSAT 1 and 2 scenes acquired between 2003–2016. Comparisons of maps from different sensors and hydrometric data were performed to examine consistency and robustness of products derived from different sensors. Simulations reveal that the methodology used to map open water from dual-pol RADARSAT 2 is insensitive to up to about 20% training error. Landsat depicts open water inundation well, while flooded vegetation can be reliably mapped in leaf-off conditions. RADARSAT mapped approximately 8% less open water area than Landsat and 0.5% more flooded vegetation, while the combined area of open water and flooded vegetation agreed to within 0.2% between sensors. Derived historical products depicting inundation frequency and trends were also generated from each sensor’s time-series of surface water maps and compared.
Region Merging Considering Within- and Between-Segment Heterogeneity: An Improved Hybrid Remote-Sensing Image Segmentation Method
Authors: Wang Yongji , Meng Qingyan , Qi Qingwen , Yang Jian , Liu Ying
Published: May 2018

Image segmentation is an important process and a prerequisite for object-based image analysis, but segmenting an image into meaningful geo-objects is a challenging problem. Recently, some scholars have focused on hybrid methods that employ initial segmentation and subsequent region merging since hybrid methods consider both boundary and spatial information. However, the existing merging criteria (MC) only consider the heterogeneity between adjacent segments to calculate the merging cost of adjacent segments, thus limiting the goodness-of-fit between segments and geo-objects because the homogeneity within segments and the heterogeneity between segments should be treated equally. To overcome this limitation, in this paper a hybrid remote-sensing image segmentation method is employed that considers the objective heterogeneity and relative homogeneity (OHRH) for MC during region merging. In this paper, the OHRH method is implemented in five different study areas and then compared to our region merging method using the objective heterogeneity (OH) method, as well as the full lambda-schedule algorithm (FLSA). The unsupervised evaluation indicated that the OHRH method was more accurate than the OH and FLSA methods, and the visual results showed that the OHRH method could distinguish both small and large geo-objects. The segments showed greater size changes than those of the other methods, demonstrating the superiority of considering within- and between-segment heterogeneity in the OHRH method.
Remotely Sensing the Biophysical Drivers of Sardinella aurita Variability in Ivorian Waters
Authors: Kassi Jean-Baptiste , Racault Marie-Fanny , Mobio Brice A. , Platt Trevor , Sathyendranath Shubha , Raitsos Dionysios E. , Affian Kouadio
Published: May 2018

The coastal regions of the Gulf of Guinea constitute one of the major marine ecosystems, producing essential living marine resources for the populations of Western Africa. In this region, the Ivorian continental shelf is under pressure from various anthropogenic sources, which have put the regional fish stocks, especially Sardinella aurita, the dominant pelagic species in Ivorian industrial fishery landings, under threat from overfishing. Here, we combine in situ observations of Sardinella aurita catch, temperature, and nutrient profiles, with remote-sensing ocean-color observations, and reanalysis data of wind and sea surface temperature, to investigate relationships between Sardinella aurita catch and oceanic primary producers (including biomass and phenology of phytoplankton), and between Sardinella aurita catch and environmental conditions (including upwelling index, and turbulent mixing). We show that variations in Sardinella aurita catch in the following year may be predicted, with a confidence of 78%, based on a bilinear model using only physical variables, and with a confidence of 40% when using only biological variables. However, the physics-based model alone is not sufficient to explain the mechanism driving the year-to-year variations in Sardinella aurita catch. Based on the analysis of the relationships between biological variables, we demonstrate that in the Ivorian continental shelf, during the study period 1998–2014, population dynamics of Sardinella aurita, and oceanic primary producers, may be controlled, mainly by top-down trophic interactions. Finally, based on the predictive models constructed here, we discuss how they can provide powerful tools to support evaluation and monitoring of fishing activity, which may help towards the development of a Fisheries Information and Management System.
Machine Learning Regression Approaches for Colored Dissolved Organic Matter (CDOM) Retrieval with S2-MSI and S3-OLCI Simulated Data
Authors: Ruescas Ana Belen , Hieronymi Martin , Mateo-Garcia Gonzalo , Koponen Sampsa , Kallio Kari , Camps-Valls Gustau
Published: May 2018

The colored dissolved organic matter (CDOM) variable is the standard measure of humic substance in waters optics. CDOM is optically characterized by its spectral absorption coefficient, a C D O M at at reference wavelength (e.g., ≈ 440 nm). Retrieval of CDOM is traditionally done using bio-optical models. As an alternative, this paper presents a comparison of five machine learning methods applied to Sentinel-2 and Sentinel-3 simulated reflectance ( R r s ) data for the retrieval of CDOM: regularized linear regression (RLR), random forest regression (RFR), kernel ridge regression (KRR), Gaussian process regression (GPR) and support vector machines (SVR). Two different datasets of radiative transfer simulations are used for the development and training of the machine learning regression approaches. Statistics comparison with well-established polynomial regression algorithms shows optimistic results for all models and band combinations, highlighting the good performance of the methods, especially the GPR approach, when all bands are used as input. Application to an atmospheric corrected OLCI image using the reflectance derived form the alternative neural network (Case 2 Regional) is also shown. Python scripts and notebooks are provided to interested users.
Aerial and Ground Based Sensing of Tolerance to Beet Cyst Nematode in Sugar Beet
Authors: Joalland Samuel , Screpanti Claudio , Varella Hubert Vincent , Reuther Marie , Schwind Mareike , Lang Christian , Walter Achim , Liebisch Frank
Published: May 2018

The rapid development of image-based phenotyping methods based on ground-operating devices or unmanned aerial vehicles (UAV) has increased our ability to evaluate traits of interest for crop breeding in the field. A field site infested with beet cyst nematode (BCN) and planted with four nematode susceptible cultivars and five tolerant cultivars was investigated at different times during the growing season. We compared the ability of spectral, hyperspectral, canopy height- and temperature information derived from handheld and UAV-borne sensors to discriminate susceptible and tolerant cultivars and to predict the final sugar beet yield. Spectral indices (SIs) related to chlorophyll, nitrogen or water allowed differentiating nematode susceptible and tolerant cultivars (cultivar type) from the same genetic background (breeder). Discrimination between the cultivar types was easier at advanced stages when the nematode pressure was stronger and the plants and canopies further developed. The canopy height (CH) allowed differentiating cultivar type as well but was much more efficient from the UAV compared to manual field assessment. Canopy temperatures also allowed ranking cultivars according to their nematode tolerance level. Combinations of SIs in multivariate analysis and decision trees improved differentiation of cultivar type and classification of genetic background. Thereby, SIs and canopy temperature proved to be suitable proxies for sugar yield prediction. The spectral information derived from handheld and the UAV-borne sensor did not match perfectly, but both analysis procedures allowed for discrimination between susceptible and tolerant cultivars. This was possible due to successful detection of traits related to BCN tolerance like chlorophyll, nitrogen and water content, which were reduced in cultivars with a low tolerance to BCN. The high correlation between SIs and final sugar beet yield makes the UAV hyperspectral imaging approach very suitable to improve farming practice via maps of yield potential or diseases. Moreover, the study shows the high potential of multi- sensor and parameter combinations for plant phenotyping purposes, in particular for data from UAV-borne sensors that allow for standardized and automated high-throughput data extraction procedures.
Remotely Sensing the Morphometrics and Dynamics of a Cold Region Dune Field Using Historical Aerial Photography and Airborne LiDAR Data
Authors: Baughman Carson A. , Jones Benjamin M. , Bodony Karin L. , Mann Daniel H. , Larsen Chris F. , Himelstoss Emily , Smith Jeremy
Published: May 2018

This study uses an airborne Light Detection and Ranging (LiDAR) survey, historical aerial photography and historical climate data to describe the character and dynamics of the Nogahabara Sand Dunes, a sub-Arctic dune field in interior Alaska’s discontinuous permafrost zone. The Nogahabara Sand Dunes consist of a 43-km2 area of active transverse and barchanoid dunes within a 3200-km2 area of vegetated dune and sand sheet deposits. The average dune height in the active portion of the dune field is 5.8 m, with a maximum dune height of 28 m. Dune spacing is variable with average crest-to-crest distances for select transects ranging from 66–132 m. Between 1952 and 2015, dunes migrated at an average rate of 0.52 m a−1. Dune movement was greatest between 1952 and 1978 (0.68 m a−1) and least between 1978 and 2015 (0.43 m a−1). Dunes migrated predominantly to the southeast; however, along the dune field margin, net migration was towards the edge of the dune field regardless of heading. Better constraining the processes controlling dune field dynamics at the Nogahabara dunes would provide information that can be used to model possible reactivation of more northerly dune fields and sand sheets in response to climate change, shifting fire regimes and permafrost thaw.
Design and Evaluation of an Aerosol Electrometer with Low Noise and a Wide Dynamic Range
Authors: Yang Yixin , Yu Tongzhu , Zhang Jiaoshi , Wang Wenyu , Gui Huaqiao , Du Peng , Liu Jianguo
Published: May 2018

A low-noise aerosol electrometer with a wide dynamic range has been designed for measuring the total net charge on high concentration aerosol particles within the range of −500 pA to +500 pA. The performance of the aerosol electrometer was evaluated by a series of experiments to determine linearity, sensitivity and noise. The relative errors were controlled within 5.0%, 1.0% and 0.3% at the range of −40 pA to +40 pA, ±40 pA to ±100 pA, and ±100 pA to ±500 pA respectively. The stability of the designed aerosol electrometer was found to be highly sensitive to temperature variations, but under temperature control, the root mean square noise and the peak-to-peak noise were 1.040 fA and 5.2 fA respectively, which are very close to the calculated theoretical limit of the current noise. The excellent correlation and the advantage of a wide dynamic range have been demonstrated by comparing with the designed aerosol electrometer to a commercial aerosol electrometer. A 99.7% (R2) statistical correlation was obtained; meanwhile, the designed aerosol electrometer operated well even when an overrange phenomenon appeared in the commercial aerosol electrometer.
Microfluidic Cultivation and Laser Tweezers Raman Spectroscopy of E. coli under Antibiotic Stress
Authors: Pilát Zdeněk , Bernatová Silvie , Ježek Jan , Kirchhoff Johanna , Tannert Astrid , Neugebauer Ute , Samek Ota , Zemánek Pavel
Published: May 2018

Analyzing the cells in various body fluids can greatly deepen the understanding of the mechanisms governing the cellular physiology. Due to the variability of physiological and metabolic states, it is important to be able to perform such studies on individual cells. Therefore, we developed an optofluidic system in which we precisely manipulated and monitored individual cells of Escherichia coli. We tested optical micromanipulation in a microfluidic chamber chip by transferring individual bacteria into the chambers. We then subjected the cells in the chambers to antibiotic cefotaxime and we observed the changes by using time-lapse microscopy. Separately, we used laser tweezers Raman spectroscopy (LTRS) in a different micro-chamber chip to manipulate and analyze individual cefotaxime-treated E. coli cells. Additionally, we performed conventional Raman micro-spectroscopic measurements of E. coli cells in a micro-chamber. We found observable changes in the cellular morphology (cell elongation) and in Raman spectra, which were consistent with other recently published observations. The principal component analysis (PCA) of Raman data distinguished between the cefotaxime treated cells and control. We tested the capabilities of the optofluidic system and found it to be a reliable and versatile solution for this class of microbiological experiments.
A 3D-Printed Multichannel Viscometer for High-Throughput Analysis of Frying Oil Quality
Authors: Oh Sein , Kim Byeongyeon , Choi Sungyoung
Published: May 2018

Viscosity as a sensitive measure of material changes is a potential quality-control parameter for simple and rapid assessment of frying oil quality. However, conventional viscometers require improvements in throughput, portability, cost-effectiveness and usability to be widely adopted for quality-control applications. Here we present a 3D-printed multichannel viscometer for simple, inexpensive and multiplexed viscosity measurement. The multichannel viscometer enables both parallel actuation of multiple fluid flows by pressing the plunger of the viscometer by hand and direct measurement of their relative volumes dispensed with naked eye. Thus, the unknown viscosities of test fluids can be simultaneously determined by the volume ratios between a reference fluid of known viscosity and the test fluids of unknown viscosity. With a 4-plex version of the multichannel viscometer, we demonstrated that the viscometer is effective for rapid examination of the degradation of a vegetable oil during deep frying of potato strips and the recovery of used frying oil after treatment with an adsorbent agent to remove frying by-products. The measurement results obtained by the multichannel viscometer were highly correlated with those obtained using a commercial oil tester. We also demonstrated the multiplexing capability of the viscometer, fabricating a 10-plex version of the viscometer and measuring the viscosities of ten test liquids at the same time. Collectively, these results indicate that the 3D-printed multichannel viscometer represents a valuable tool for high-throughput examination of frying oil quality in resource-limited settings.
Traceability in Patient Healthcare through the Integration of RFID Technology in an ICU in a Hospital
Authors: Martínez Pérez María , Dafonte Carlos , Gómez Ángel
Published: May 2018

Patient safety is a principal concern for health professionals in the care process and it is, therefore, necessary to provide information management systems to each unit of the hospital, capable of tracking patients and medication to reduce the occurrence of adverse events and therefore increase the quality of care received by patients during their stay in hospital. This work presents a tool for the Intensive Care Unit (ICU), a key service with special characteristics, which computerises and tracks admissions, care plans, vital monitoring, the prescription and medication administration process for patients in this service. To achieve this, it is essential that innovative and cutting-edge technologies are implemented such as Near Field Communication (NFC) technology which is now being implemented in diverse environments bringing a range of benefits to the tasks for which it is employed.
The Validity of External:Internal Training Load Ratios in Rested and Fatigued Soccer Players
Authors: Akubat Ibrahim , Barrett Steve , Sagarra Manuel Lapuente , Abt Grant
Published: May 2018

Purpose: To examine the relationship of external:internal training load ratios with fitness and assess the impact of fatigue. Method: Ten soccer players performed a lactate threshold test followed by two soccer simulations (BEAST90mod) 48 h apart. Recovery (TQR) and muscle soreness (DOMS) was measured before each trial. Internal Training load (TL) (iTRIMP) and external load total distance (TD), high intensity distance (HID), PlayerLoad™ (PL) mean metabolic power (MMP) high metabolic power distance (HP) were collected for each trial and external:internal ratios produced. The relationships between ratios and velocity at lactate threshold (vLT) and velocity at Onset of Blood Lactate Accumulation (vOBLA) were examined in both trials along with changes in ratios. Results: Total Quality of Recovery and DOMS showed large changes. There were trivial to large decreases in TL from trial 1 to 2. Moderate increases in ratios for TD:iTRIMP, PL:iTRIMP and MMP:iTRIMP were seen but only small/trivial for HP:iTRIMP and HID:iTRIMP. In rested conditions all ratios show large relationships with vLT and vOBLA. However vLT vs. HID:iTRIMP; PL:iTRIMP; HP:iTRIMP and vOBLA vs. TD:iTRIMP; PL:iTRIMP; MMP:iTRIMP became weaker under fatigue. Conclusions: Acute changes in the ratios have implications forthe use of ratios as fitness measures but also as indicators of fatigue.
A New Extended Birnbaum–Saunders Model: Properties, Regression and Applications
Authors: Cordeiro Gauss , De Lima Maria , Ortega Edwin , Suzuki Adriano
Published: May 2018

We propose an extended fatigue lifetime model called the odd log-logistic Birnbaum–Saunders–Poisson distribution, which includes as special cases the Birnbaum–Saunders and odd log-logistic Birnbaum–Saunders distributions. We obtain some structural properties of the new distribution. We define a new extended regression model based on the logarithm of the odd log-logistic Birnbaum–Saunders–Poisson random variable. For censored data, we estimate the parameters of the regression model using maximum likelihood. We investigate the accuracy of the maximum likelihood estimates using Monte Carlo simulations. The importance of the proposed models, when compared to existing models, is illustrated by means of two real data sets.
Under the Volcano: Responses of a Community-Based Tourism Village to the 2010 Eruption of Mount Merapi, Indonesia
Authors: Rindrasih Erda
Published: May 2018

This paper assesses the responses of community-based tourism (CBT) and local governments to natural disasters. The tourism community in rural areas that are at high risk of natural disasters is largely overlooked in the literature on tourism and disaster management. It can be argued that CBT management is vulnerable to such natural disasters and, therefore, its presence should be considered in the recovery process. Time series observations and in-depth interviews were performed in Pentingsari village on the slopes of Mount Merapi, a stratovolcano in Yogyakarta, Indonesia. The findings show that the local government’s preparation plans were focused only on disaster management, in general, and that it had only reactive programmes for tourism recovery. Moreover, CBT was able to respond and recover from the disaster by transforming the tourism destination with support from external agencies. In other words, it is concluded that transformation of the destination, organization, and human and community factors have taken place in the community-based tourism that leads to the post-disaster resilience.
Sustainability in an Emerging Nation: The Bhutan Case Study
Authors: Yangka Dorji , Newman Peter , Rauland Vanessa , Devereux Peter
Published: May 2018

With the onset of the 17 Sustainable Development Goals (SDGs) and the Paris Agreement on climate change, the world’s nations were to create economic development integrating environmental and social improvement. However, there is still much uncertainty in the world of politics and academia as to whether these integrated goals are achievable and how they can fit best with diverse national and local contexts. Thus, there is always a need to find nations that can show how it can be achieved in different settings shaped by local experiences, challenges, and opportunities. Bhutan could be one of these nations as it could be argued that it has, to an extent, simplified the task to fit its values and aspirations. Bhutan has three major goals that need to be integrated: Wealth (GDP) to align with their middle-income aspiration, thus providing opportunities for employment, Greenhouse Gas emissions (GHG) that are maintained at a carbon neutral level, which is beyond most national commitments, and Bhutan’s renowned Gross National Happiness (GNH) index, which covers their socio-economic goals. We show this integration and then synthesize some core findings from a literature review on the theory and practice of sustainable development through the lens of the three integrated goals of Bhutan, thereby placing the case of Bhutan into the wider literature. This paper seeks to show how one emerging nation can model an operational sustainability policy. The paper highlights some plausible synergies between the 17 SDGs and the domains and indicators of GNH that could help nations struggling with how they can create sensible sustainability outcomes from these new global agendas. Bhutan has framed the GNH as its contribution to sustainability. However, this paper suggests that it may be the integration of the GNH with GDP and GHG that is its real contribution. Furthermore, Bhutan’s 3G model of fully integrating GNH, GDP, and GHG suggests a way forward for achieving their imperatives of economic growth, whilst enabling the SDGs and achieving the difficult climate change goal. It may also suggest a model for other nations wanting to find a complementary way of framing economic growth, the 17 SDGs, and the Paris Agreement into a coherent set of policies.
Environmental Sustainability in Third-Party Logistics Service Providers: A Systematic Literature Review from 2000–2016
Authors: Evangelista Pietro , Santoro Lodovico , Thomas Antonio
Published: May 2018

Despite the increasing interest toward environmental issues in the freight transport and logistics service sector, a comprehensive and updated assessment of the existing literature is still missing. This paper aims to fill this gap by presenting the results of a systematic literature review of publications in the area of environmental sustainability in third-party logistics service providers (3PLs) between the years 2000 and 2016. The review offers insight into the critical dimensions of green matters in transport and logistics service companies using an analytical framework based on the following five topic areas: influencing factors, green actions and the impact on performance, Information and Communication Technology (ICT) tools supporting the green actions, energy efficiency in road freight transport and shipper’s perspective and collaboration. The results indicate that, despite the number of published papers having grown significantly from 2008 onward, some areas remain highly under-researched such as ICT and performance measurement. Several research gaps have been identified in each topic area, and a set of propositions forming an agenda for future research directions has been suggested.
Assessing the Cost of Damage and Effect of Adaptation to Landslides Considering Climate Change
Authors: Kim Ho Gul , Lee Dong Kun , Park Chan
Published: May 2018

The amount of damage caused by landslides has increased due to climate change. Adaptation plans are required to help cope with landslides in order to reduce the extent of the damage. Landslide hazard analysis can help create adaptation plans. Analyzing the cost of damage of and the effect of adaptation to landslides is an effective way to support decision makers. The cost of damage is calculated using the costs of damage incurred in residential and transportation areas in the past, based on data from annual reports. Spatial distribution models are used to analyze landslide hazard areas in the present and the future. Future or potential landslide hazards are estimated by using climate change scenarios through representative concentration pathways. The effects of adaptation measures are assessed using modified variables and a cost-benefit analysis. The uncertainty of the cost of damage is considered using average, minimum, and maximum values. As a result, the methods used to estimate future costs of damage are developed, and the effects of adaptation are analyzed. The future cost of damage is calculated for every climate change scenario. The effect of adaptation are analyzed and areas with a reduced risk of landslides are identified, reducing the cost of damage and adaptation costs, as well as the costs and benefits of adaptation measures. Improving soil drainage is the most effective measure among the four measures analyzed. This study can help estimate future costs of damage and analyze the effect of adaptation in creating effective adaptation plans.
Quantitative Analysis of the Determinants Influencing Urban Expansion: A Case Study in Beijing, China
Authors: Xu Qiurong , Zheng Xinqi , Zhang Chunxiao
Published: May 2018

A quantitative analysis of spatial influencing factors on urban sprawl can offer better support for urban planning and management. There are many concerns regarding the influence of each factor. However, a quantitative analysis to detect the interactions between factors is limited because of the complexity of the urban systems, especially the role of planning. Additionally, spatial heterogeneity is often overlooked. This study aims to improve and strengthen the knowledge in this field through a spatial statistical method known as GeoDetector. A new spatial quantification of urban expansion was presented in this study and the spatio-temporal characteristics and mechanism of urban growth in Beijing from 2010 to 2015 were also analyzed. The results show that urban expansion presents spatial heterogeneity with different grid cells, and the optimal scale was 4500 m. At this scale, urban expansion in Beijing linearly expands along the traffic trunk. In addition, urban expansion in Beijing is jointly influenced by socioeconomic, geographical, and policy factors. Population density has had the greatest influence on urban expansion from 2010 to 2015, and policy factors rank first. The impact of economic factors on urban growth is gradually weakening. It is important for urban geographical research to further plans and guide urban development.
Sustainable Situation-Aware Recommendation Services with Collective Intelligence
Authors: Jung Yuchul , Hur Cinyoung , Kim Mucheol
Published: May 2018

With the recent advances of information and communication technology, people communicate with each other through online communities or social networking services, such as PatientsLikeMe and Facebook. One of the key challenges in aspects of providing sustainable situation-aware services is how to utilize peoples’ experiences shared as reusable social-intelligence. If domain-specific collective intelligence is well constructed, the knowledge usages can be extended to situation-awareness-based personal situation understanding, and sustainable recommendation services with user intent. In this paper, we introduce a sustainable situation-awareness supporting framework based on text-mining techniques and a domain-specific knowledge model, the so-called Service Quality Model for Hospitals (SQM-H). Different from obtaining sustainable contexts from heterogeneous sensors surrounding users, it aggregates SQM-H based service-specific knowledge from online health communities. Our framework includes a set of components: data aggregation, text-mining, service quality analysis, and open Application Programming Interface (APIs) for recommendation services. Those components have been designed to deal with users’ immediate request, providing service quality related information reflected in collective intelligence and analyzed information based on that along with the SQM-H. As a proof of concept, we implemented a prototype system which interacts with users through smartphone user interface. Our framework supports qualitative and quantitative information based on SQM-H and statistical analyses for the given user queries. Through the implementation and user tests, we confirmed an increased knowledge support for decision-making and an easy mashup with provided Open APIs. We believe that the suggested situation-awareness supporting framework can be applied to numerous sustainable applications related to healthcare and wellness domain areas if domain-specific knowledge models are redesigned.
Opportunities and Barriers for Water Co-Governance—A Critical Analysis of Seven Cases of Diffuse Water Pollution from Agriculture in Europe, Australia and North America
Authors: Graversgaard Morten , Hedelin Beatrice , Smith Laurence , Gertz Flemming , Højberg Anker Lajer , Langford John , Martinez Grit , Mostert Erik , Ptak Emilia , Peterson Heidi , Stelljes Nico , Van den Brink Cors , Refsgaard Jens Christian
Published: May 2018

Diffuse Water Pollution from Agriculture (DWPA) and its governance has received increased attention as a policy concern across the globe. Mitigation of DWPA is a complex problem that requires a mix of policy instruments and a multi-agency, broad societal response. In this paper, opportunities and barriers for developing co-governance, defined as collaborative societal involvement in the functions of government, and its suitability for mitigation of DWPA are reviewed using seven case studies in Europe (Poland, Denmark, Sweden, The Netherlands and UK), Australia (Murray-Darling Basin) and North America (State of Minnesota). An analytical framework for assessing opportunities and barriers of co-governance was developed and applied in this review. Results indicated that five key issues constitute both opportunities and barriers, and include: (i) pressure for change; (ii) connected governance structures and allocation of resources and funding; (iii) leadership and establishment of partnerships through capacity building; (iv) use and co-production of knowledge; and (v) time commitment to develop water co-governance.
Prediction of the Heights of the Water-Conducting Fracture Zone in the Overlying Strata of Shortwall Block Mining Beneath Aquifers in Western China
Authors: Zhang Yun , Cao Shenggen , Gao Rui , Guo Shuai , Lan Lixin
Published: May 2018

Longwall mining leaves pillars and irregular blocks of coal behind in its aftermath. In this study, a shortwall block mining (SBM) technique for recovering these coal resources has been proposed. A mechanical analysis model for calculating the heights of the water-conducting fracture zone (HWFZ) in overlying strata of SBM was established based on the theory of beams on elastic foundations. Using this model and the data acquired from a working face in the experimental area, a height of 50.30 m was calculated for HWFZ corresponding to this working face. This observation indicates that the equation for predicting HWFZ in working faces specified by the Hydrogeological Procedures for Mines (HPM) standard is not suitable for application in SBM. For this reason, the Universal Distinct Element Code (UDEC) modeling program was used to analyze the developmental behavior of the water-conducting fracture zone under various determining factors in SBM. The UDEC simulations indicated that the HWFZ increase linearly with an increase in mining height, decrease linearly with an increase in the width of the protective coal pillars, and increase logarithmically with block length. A nonlinear regression analysis of HWFZ was performed using the SPSS software suite, from which a model for predicting HWFZ in SBM was constructed. This model predicted that the HWFZ was 52.58 m in the experimental area, while field measurements yielded HWFZ values varying from 47.98 to 50.06 m, which was basically consistent with the results of the prediction model and the mechanical model, thus confirming the accuracy of the mechanical model and the reliability of the regression model. The results of this study will provide critical practical references for the enhancement of coal recovery rates in mining areas and enhance theories on aquifer protection during mining operations.
Do Customers Value CSR Disclosure? Evidence from Italian Family and Non-Family Firms
Authors: Gavana Giovanna , Gottardo Pietro , Moisello Anna Maria
Published: May 2018

CSR reporting is a relevant part of a firm’s dialogue with stakeholders, therefore it is of interest to study whether this form of communication is an effective tool for gaining customers’ support. This paper addresses this issue by comparing the effect of CSR disclosure on family and non-family firms’ revenues. In doing so, we analyze a sample of Italian non-financial listed firms and we control for the effect of visibility to stakeholders, governance characteristics, risk, and several accounting variables. We find that CSR reporting has a significant effect on revenues when a company is characterized by consumer proximity, in terms of product or services visibility for consumers, but that the effect is positive for family firms and negative for non-family companies.
Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid
Authors: Tephiruk Naowarat , Kanokbannakorn Weerawoot , Kerdphol Thongchart , Mitani Yasunori , Hongesombut Komsan
Published: May 2018

In this study, the active and reactive power control of a battery energy storage system (BESS) using fuzzy logic control to maintain the voltage and frequency stability of the islanded Mae Sariang microgrid is presented. The main scope of the presented study is to cogitate the effectiveness of the BESS controller in view of fluctuations of frequency/voltage subjected to a disturbance occurring in the islanded microgrid. In the Mae Sariang microgrid system, the electricity is produced from two renewable energy resources (RESs), i.e., hydro and solar PV. The use of these clean energy sources has become a main problem, envisaging the output power uncertainties from RESs. Further, such power uncertainty raises power quality problems and leads to power failure. To overcome such problems, the proposed fuzzy logic control (FLC) approach is applied for the BESS controller to improve the stability of the islanded Mae Sariang microgrid. The proposed FLC is intended to provide the BESS with well-established attributes of dynamical response to disturbance, which is analyzed by a predictive model. The proposed FLC has been investigated and compared with the robust control method, which is analyzed by a mathematical model using the system identification technique. The modeling of the microgrid system with BESS is implemented and verified on the DIgSILENT PowerFactory software. The simulation result illustrates that both of the control approaches allow the dynamic stability of the microgrid and the maintenance of frequency and voltage within acceptable ranges. However, the proposed BESS fuzzy logic control is less prone to uncertainty than the BESS robust control. Furthermore, in the proposed BESS fuzzy logic control, the microgrid frequency and voltage rapidly return to their normal steady-state condition and the size of the BESS is smaller than the BESS robust control.
Decision Making of Non-Agricultural Work by Rural Residents in Weifang, China
Authors: Cheng Yang , Lv Yuxia , Rosenberg Mark , Hou Linke
Published: May 2018

Since the 1990s, the rapid urbanization of China has been fueled by the massive movement of workers from the countryside to cities. Using descriptive statistics and binary regression analysis, we investigate the factors underlying rural residents’ decision making to seek non-agricultural work, their work time, and work location based on data collected in Weifang, a city in the Shandong Province of China. The results show that economic factors play a pivotal role in rural residents’ decision making to seek non-agricultural employment, full-time non-agricultural employment, or employment outside of their home county. Non-economic factors such as age, gender, social ties, education, access to arable land, geographical location, neighborhood effects, and self-perception are also significant factors in the decision-making process. The findings of this study shed light on future research regarding the impact of urbanization on rural residents. It also provides knowledge for future policy making on rural development and management.
Examining Vulnerability Factors to Natural Disasters with a Spatial Autoregressive Model: The Case of South Korea
Authors: Jeong Seunghoo , Yoon D. K.
Published: May 2018

Socially and economically marginalized people and environmentally vulnerable areas are disproportionately affected by natural hazards. Identifying populations and places vulnerable to disasters is important for disaster management, and crucial for mitigating their economic consequences. From the fields of geography, emergency management, and urban planning, several approaches and methodologies have been used to identify significant vulnerability factors affecting the incidence and impact of disasters. This study performs a regression analysis to examine several factors associated with disaster damage in 230 local communities in South Korea, using ten vulnerability indicators for social, economic, and environmental aspects, and a single indicator for disaster characteristics. A Lagrange Multiplier diagnostic test-based spatial autoregressive model (SAM) was applied to assess the potential spatial autocorrelation in the ordinary least squares (OLS) residuals. This study compared the OLS regression results with those of a spatial autoregressive model, for both presence of spatial autocorrelation, and model performance. The conclusion of this study is that Korean communities with a higher vulnerability to disasters, as a result of their socioeconomic and environmental characteristics, are more likely to experience economic losses from natural disasters.
An Automated Vulnerability Detection and Remediation Method for Software Security
Authors: Jurn Jeesoo , Kim Taeeun , Kim Hwankuk
Published: May 2018

As hacking techniques become more sophisticated, vulnerabilities have been gradually increasing. Between 2010 and 2015, around 80,000 vulnerabilities were newly registered in the CVE (Common Vulnerability Enumeration), and the number of vulnerabilities has continued to rise. While the number of vulnerabilities is increasing rapidly, the response to them relies on manual analysis, resulting in a slow response speed. It is necessary to develop techniques that can detect and patch vulnerabilities automatically. This paper introduces a trend of techniques and tools related to automated vulnerability detection and remediation. We propose an automated vulnerability detection method based on binary complexity analysis to prevent a zero-day attack. We also introduce an automatic patch generation method through PLT/GOT table modification to respond to zero-day vulnerabilities.
Neutrosophic Hesitant Fuzzy Subalgebras and Filters in Pseudo-BCI Algebras
Authors: Shao Songtao , Zhang Xiaohong , Bo Chunxin , Smarandache Florentin
Published: May 2018

The notions of the neutrosophic hesitant fuzzy subalgebra and neutrosophic hesitant fuzzy filter in pseudo-BCI algebras are introduced, and some properties and equivalent conditions are investigated. The relationships between neutrosophic hesitant fuzzy subalgebras (filters) and hesitant fuzzy subalgebras (filters) is discussed. Five kinds of special sets are constructed by a neutrosophic hesitant fuzzy set, and the conditions for the two kinds of sets to be filters are given. Moreover, the conditions for two kinds of special neutrosophic hesitant fuzzy sets to be neutrosophic hesitant fuzzy filters are proved.
Theory of an Emerging-State Actor: The Islamic State of Iraq and Syria (ISIS) Case †
Authors: Clancy Timothy
Published: May 2018

This paper proposes a new theory of non-state actors who engage in irregular warfare to seize territory and govern openly, called emerging-state actors. Emerging-state actors arise in periods of irregular conflict, such as the so-called Islamic State of Iraq and Syria (ISIS). The theory tries to answer “what is/was” the Islamic State because emerging-state actors differ notably from other non-state actors and insurgencies in irregular conflict. Causal diagrams as well as key propositions present the theory. Testing occurs against a system dynamics simulation called the “Emerging-State Actor Model” (E-SAM), loaded with the ISIS historical case in Syria and Iraq. Through experiments the simulation confirms evidence of emerging-state actor behavior as well as a range of contingencies showing their applicability. The novelty of E-SAM as a simulation for irregular conflict is its ability to handle multiple forms of conflict including political grievance, terrorism, insurgencies and emerging-state actors. E-SAM can also simulate multiple actors within each conflict: domestic and foreign state actors, local conflict actors, as well as different ethnographic groups. It can be parameterized with scenarios to simulate a variety of scenarios: ISIS in Libya, Boko Haram in Nigeria, Taliban in Afghanistan and even expatriated ISIS fighters returning to pursue new conflicts such as in Indonesia.
Effects of Dietary Arginine, Ornithine, and Zeolite Supplementation on Uremic Toxins in Cats
Authors: Paßlack Nadine , Zentek Jürgen
Published: May 2018

To test if arginine and ornithine, both components of the Krebs-Henseleit cycle, or zeolite, a potential ammonium absorber, can modulate the excretion of harmful bacterial metabolites, intestinal microbial protein fermentation was stimulated by feeding a high-protein (60.3%) diet as a single daily meal to 10 adult cats. The diet was supplemented without or with arginine (+50, 75, 100% compared to arginine in the basal diet), ornithine (+100, 150, 200% compared to arginine in the basal diet), or zeolite (0.125, 0.25, 0.375 g/kg body weight/day). The cats received each diet for 11 days. Urine, feces, and blood were collected during the last 4 days. Arginine and ornithine enhanced the postprandial increase of blood urea, but renal urea excretion was not increased. Zeolite decreased renal ammonium excretion and fecal biogenic amines. The data indicate an increased detoxification rate of ammonia by arginine and ornithine supplementation. However, as urea was not increasingly excreted, detrimental effects on renal function cannot be excluded. Zeolite had beneficial effects on the intestinal nitrogen metabolism, which should be further evaluated in diseased cats. Clinical studies should investigate whether dietary arginine and ornithine might improve hepatic ammonia detoxification or could be detrimental for renal function.
Domain II of Pseudomonas Exotoxin Is Critical for Efficacy of Bolus Doses in a Xenograft Model of Acute Lymphoblastic Leukemia
Authors: Müller Fabian , Cunningham Tyler , Beers Richard , Bera Tapan K. , Wayne Alan S. , Pastan Ira
Published: May 2018

Moxetumomab pasudotox is a fusion protein of a CD22-targeting antibody and Pseudomonas exotoxin. Minutes of exposure to Moxetumomab achieves similar cell killing than hours of exposure to a novel deimmunized variant against some acute lymphoblastic leukemia (ALL). Because blood levels fall quickly, Moxetumomab is more than 1000-fold more active than the deimmunized variant in vivo. We aimed to identify which part of Moxetumomab increases in vivo efficacy and generated five immunotoxins, tested time-dependent activity, and determined the efficacy in a KOPN-8 xenograft model. Full domain II shortened the time cells had to be exposed to die to only a few minutes for some ALL; deimmunized domain III consistently extended the time. Against KOPN-8, full domain II accelerated time to arrest protein synthesis by three-fold and tripled PARP-cleavage. In vivo efficacy was increased by more than 10-fold by domain II and increasing size, and therefore half-life enhanced efficacy two- to four-fold. In summary, in vivo efficacy is determined by the time cells have to be exposed to immunotoxin to die and serum half-life. Thus, domain II is most critical for activity against some ALL treated with bolus doses; however, immunotoxins lacking all but the furin-cleavage site of domain II may be advantageous when treating continuously.
Discovery and Biochemical Characterization of PlyP56, PlyN74, and PlyTB40—Bacillus Specific Endolysins
Authors: Etobayeva Irina , Linden Sara B. , Alem Farhang , Harb Laith , Rizkalla Lucas , Mosier Philip D. , Johnson Allison A. , Temple Louise , Hakami Ramin M. , Nelson Daniel C.
Published: May 2018

Three Bacillus bacteriophage-derived endolysins, designated PlyP56, PlyN74, and PlyTB40, were identified, cloned, purified, and characterized for their antimicrobial properties. Sequence alignment reveals these endolysins have an N-terminal enzymatically active domain (EAD) linked to a C-terminal cell wall binding domain (CBD). PlyP56 has a Peptidase_M15_4/VanY superfamily EAD with a conserved metal binding motif and displays biological dependence on divalent ions for activity. In contrast, PlyN74 and PlyTB40 have T7 lysozyme-type Amidase_2 and carboxypeptidase T-type Amidase_3 EADs, respectively, which are members of the MurNAc-LAA superfamily, but are not homologs and thus do not have a shared protein fold. All three endolysins contain similar SH3-family CBDs. Although minor host range differences were noted, all three endolysins show relatively broad antimicrobial activity against members of the Bacillus cereus sensu lato group with the highest lytic activity against B. cereus ATCC 4342. Characterization studies determined the optimal lytic activity for these enzymes was at physiological pH (pH 7.0–8.0), over a broad temperature range (4–55 °C), and at low concentrations of NaCl (<50 mM). Direct comparison of lytic activity shows the PlyP56 enzyme to be twice as effective at lysing the cell wall peptidoglycan as PlyN74 or PlyTB40, suggesting PlyP56 is a good candidate for further antimicrobial development as well as bioengineering studies.