bluuebunny/crossref_metadata_2025 huggingface dataset:
Carceral Hermeneutics: Discovering the Bible in Prison and Prison in the Bible
Authors: Jobe Sarah
Published: February 2019

This essay introduces the concept of “carceral hermeneutics,” the art of interpreting Scripture from within prisons as, or alongside, incarcerated persons. Reading the Bible in prison reframes the Bible as a whole, highlighting how the original sites of textual production were frequently sites of exile, prison, confinement, and control. Drawing on the work of Lauren F. Winner, the author explores the “characteristic damages” of reading the Bible without attention to the carceral and suggests that physically re-locating the task of biblical interpretation can unmask interpretative damage and reveal alternative, life-giving readings. The essay concludes with an extended example, showing how the idea of cruciformity is a characteristically damaged reading that extracts Jesus’ execution from its carceral context. Carceral hermeneutics surfaces a Gospel counter-narrative in which Jesus flees violence and opts for his own safety. Jesus as a refugee (Matt 2), a fugitive (Matt 4:12–17), and a victim escaping violence (Luke 4:14–30) stand alongside Jesus as an executed person to offer a wider range of options for a “christoformity” in which people can image God while fleeing from violence in order to preserve their own lives and freedom.
Phase-Type Models in Life Insurance: Fitting and Valuation of Equity-Linked Benefits
Authors: Asmussen Søren , Laub Patrick J. , Yang Hailiang
Published: February 2019

Phase-type (PH) distributions are defined as distributions of lifetimes of finite continuous-time Markov processes. Their traditional applications are in queueing, insurance risk, and reliability, but more recently, also in finance and, though to a lesser extent, to life and health insurance. The advantage is that PH distributions form a dense class and that problems having explicit solutions for exponential distributions typically become computationally tractable under PH assumptions. In the first part of this paper, fitting of PH distributions to human lifetimes is considered. The class of generalized Coxian distributions is given special attention. In part, some new software is developed. In the second part, pricing of life insurance products such as guaranteed minimum death benefit and high-water benefit is treated for the case where the lifetime distribution is approximated by a PH distribution and the underlying asset price process is described by a jump diffusion with PH jumps. The expressions are typically explicit in terms of matrix-exponentials involving two matrices closely related to the Wiener-Hopf factorization, for which recently, a Lévy process version has been developed for a PH horizon. The computational power of the method of the approach is illustrated via a number of numerical examples.
PS-InSAR Analysis of Sentinel-1 Data for Detecting Ground Motion in Temperate Oceanic Climate Zones: A Case Study in the Republic of Ireland
Authors: Fiaschi Simone , Holohan Eoghan , Sheehy Michael , Floris Mario
Published: February 2019

Regions of temperate oceanic climate have historically represented a challenge for the application of satellite-based multi-temporal SAR interferometry. The landscapes of such regions are commonly characterized by extensive, seasonally-variable vegetation coverage that can cause low temporal coherence and limit the detection capabilities of SAR imagery as acquired, for instance, by previous ERS-1/2 and ENVISAT missions. In this work, we exploited the enhanced resolution in space and time of the recently deployed Sentinel-1A/B SAR satellites to detect and monitor ground motions occurring in two study areas in the Republic of Ireland. The first, is a ~1800 km2 area spanning the upland karst of the Clare Burren and the adjacent mantled lowland karst of east Galway. The second, is an area of 100 km2 in Co. Meath spanning an active mine site. The available datasets, consisting of more than 100 images acquired in both ascending and descending orbits from April 2015 to March 2018, were processed by using the Permanent Scatterer approach. The obtained results highlight the presence of small-scale ground motions in both urban and natural environments with displacement rates along the satellite line of sight up to −17 mm/year. Localized subsidence was detected in recently built areas, along the infrastructure (both roads and railways), and over the mine site, while zones of subsidence, uplift, or both, have been recorded in a number of peatland areas. Furthermore, several measured target points indicate the presence of unstable areas along the coastline. Many of the detected movements were previously unknown. These results demonstrate the feasibility of adopting multi-temporal interferometry based on Sentinel-1 data for the detection and monitoring of mm-scale ground movements even over small areas (<100 m2) in environments influenced by temperate oceanic climate.
High-Resolution Mapping of Redwood (Sequoia sempervirens) Distributions in Three Californian Forests
Authors: Francis Emily J. , Asner Gregory P.
Published: February 2019

High-resolution maps of redwood distributions could enable strategic land management to satisfy diverse conservation goals, but the currently-available maps of redwood distributions are low in spatial resolution and biotic detail. Classification of airborne imaging spectroscopy data provides a potential avenue for mapping redwoods over large areas and with high confidence. We used airborne imaging spectroscopy data collected over three redwood forests by the Carnegie Airborne Observatory, in combination with field training data and application of a gradient boosted regression tree (GBRT) machine learning algorithm, to map the distribution of redwoods at 2-m spatial resolution. Training data collected from the three sites showed that redwoods have spectral signatures distinct from the other common tree species found in redwood forests. We optimized a gradient boosted regression model for high performance and computational efficiency, and the resulting model was demonstrably accurate (81–98% true positive rate and 90–98% overall accuracy) in mapping redwoods in each of the study sites. The resulting maps showed marked variation in redwood abundance (0–70%) within a 1 square kilometer aggregation block, which match the spatial resolution of currently-available redwood distribution maps. Our resulting high-resolution mapping approach will facilitate improved research, conservation, and management of redwood trees in California.
Entropy-Mediated Decision Fusion for Remotely Sensed Image Classification
Authors: Guo Baofeng
Published: February 2019

To better classify remotely sensed hyperspectral imagery, we study hyperspectral signatures from a different view, in which the discriminatory information is divided as reflectance features and absorption features, respectively. Based on this categorization, we put forward an information fusion approach, where the reflectance features and the absorption features are processed by different algorithms. Their outputs are considered as initial decisions, and then fused by a decision-level algorithm, where the entropy of the classification output is used to balance between the two decisions. The final decision is reached by modifying the decision of the reflectance features via the results of the absorption features. Simulations are carried out to assess the classification performance based on two AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) hyperspectral datasets. The results show that the proposed method increases the classification accuracy against the state-of-the-art methods.
Object-Based Change Detection Using Multiple Classifiers and Multi-Scale Uncertainty Analysis
Authors: Tan Kun , Zhang Yusha , Wang Xue , Chen Yu
Published: February 2019

The drawback of pixel-based change detection is that it neglects the spatial correlation with neighboring pixels and has a high commission ratio. In contrast, object-based change detection (OBCD) depends on the accuracy of the segmentation scale, which is of great significance in image analysis. Accordingly, an object-based approach for automatic change detection using multiple classifiers and multi-scale uncertainty analysis (OB-MMUA) in high-resolution (HR) remote sensing images is proposed in this paper. In this algorithm, the gray-level co-occurrence matrix (GLCM), morphological, and Gabor filter texture features are extracted to construct the input data, along with the spectral features, to utilize the respective advantages of the features and to compensate for the insufficient spectral information. In addition, random forest is used to select the features and determine the optimal feature vectors for the change detection. Change vector analysis (CVA) based on uncertainty analysis is then implemented to select the initial training samples. According to the diversity, support vector machine (SVM), k-nearest neighbor (KNN), and extra-trees (ExT) classifiers are then chosen as the base classifiers for Dempster-Shafer (D-S) evidence theory fusion, and unlabeled samples are selected using an active learning method with spatial information. Finally, multi-scale object-based D-S evidence theory fusion and uncertainty analysis is used to classify the difference image. To validate the proposed approach, we conducted experiments using multispectral images collected by the ZY-3 and GF-2 satellites. The experimental results confirmed the effectiveness and superiority of the proposed approach, which integrates the respective advantages of the pixel-based and object-based methods.
Temporal Variability of Precipitation and Biomass of Alpine Grasslands on the Northern Tibetan Plateau
Authors: Li Meng , Wu Jianshuang , Song Chunqiao , He Yongtao , Niu Ben , Fu Gang , Tarolli Paolo , Tietjen Britta , Zhang Xianzhou
Published: February 2019

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGBpeak) of alpine grasslands responds to the temporal variability of growing season precipitation (GSP) on the northern Tibetan Plateau. Here, the temporal variability of precipitation was defined as the number and intensity of precipitation events as well as the time interval between consecutive precipitation events. We conducted annual field measurements of AGBpeak between 2009 and 2016 at four sites that were representative of alpine meadow, meadow-steppe, alpine steppe, and desert-steppe. Thus, an empirical model was established with the time series of the field-measured AGBpeak and the corresponding enhanced vegetation index (EVI) (R2 = 0.78), which was used to estimate grassland AGBpeak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGBpeak was quantified by principal component regression and shown in a red–green–blue (RGB) composition map. The standardized importance values were used to calculate the vegetation sensitivity index to the temporal variability of precipitation (VSIP). Our results showed that the standardized VSIP was larger than 60 for only 15% of alpine grassland pixels and that AGBpeak did not change significantly for more than 60% of alpine grassland pixels over the past decades, which was likely due to the nonsignificant changes in the temporal variability of precipitation in most pixels. However, a U-shaped relationship was found between VSIP and GSP across the four representative grassland types, indicating that the sensitivity of grassland AGBpeak to precipitation was dependent on the types of grassland communities. Moreover, we found that the temporal variability of precipitation explained more of the field-measured AGBpeak variance than did the total amount of precipitation alone at the site scale, which implies that the mechanisms underlying how the temporal variability of precipitation controls the AGBpeak of alpine grasslands should be better understood at the local scale. We hypothesize that alpine grassland plants promptly respond to the temporal variability of precipitation to keep community biomass production more stable over time, but this conclusion should be further tested. Finally, we call for a long-term experimental study that includes multiple natural and anthropogenic factors together, such as warming, nitrogen deposition, and grazing and fencing, to better understand the mechanisms of alpine grassland stability on the Tibetan Plateau.
Theory and Statistical Description of the Enhanced Multi-Temporal InSAR (E-MTInSAR) Noise-Filtering Algorithm
Authors: Pepe Antonio
Published: February 2019

In this work, the statistical fundaments of the recently proposed enhanced, multi-temporal interferometric synthetic aperture radar (InSAR) noise-filtering (E-MTInSAR) technique is addressed. The adopted noise-filtering algorithm is incorporated into the improved extended Minimum Cost Flow (EMCF) Small Baseline Subset (SBAS) differential interferometric SAR (InSAR) processing chain, which has extensively been used for the generation of Earth’s surface displacement time-series in several different contexts. Originally, the input of the InSAR EMCF-SBAS processing toolbox consisted of a sequence of multi-looked, small baseline interferograms, which were unwrapped using the space-time EMCF phase unwrapping algorithm. Subsequently, the unwrapped interferograms were inverted through the SBAS algorithm to retrieve the expected InSAR deformation products. The improved processing chain has complemented the original codes with two additional steps. In particular, a new multi-temporal noise-filtering algorithm for sequences of time-redundant multi-looked DInSAR interferograms, followed by a proper interferogram selection step, has been proposed. This research study is aimed at primarily assessing the performance of the E-MTInSAR noise-filtering algorithm from a theoretical perspective. To this aim, the principles of directional statistics and errors propagation are exploited. Experimental results, carried out by applying the E-MTInSAR algorithm to a sequence of SAR data collected over the Los Angeles bay area, have been used to corroborate the academic outcome of this research.
Ten Years of TerraSAR-X—Scientific Results
Authors: Eineder Michael , Moreira Alberto , Roth Achim
Published: February 2019

This special issue is a collection of papers addressing the scientific utilization of data acquired in the course of the TerraSAR-X mission. The articles deal with the mission itself, the accuracy of the products, with differential interferometry, and with applications in the domains cryosphere, oceans, wetlands, and urban areas. This editorial summarizes the content.
A Simplified SSY Estimate Method to Determine EPFM Constraint Parameter for Sensor Design
Authors: Ding Ping , Wang Xin
Published: February 2019

To implement a sensor structure analysis and design (as well as other engineering applications), a two-parameter approach using elastic–plastic fracture mechanics (EPFM) could be applied to analyze a structure more accurately than a one-parameter approach, especially for structures with low crack constraint. The application of the J-A two-parameter approach on sensors and other structures depends on the obtainment of a constraint parameter A. To conveniently and effectively obtain the A parameter values, the authors have developed a T-stress-based estimate method under a small-scale yielding (SSY) condition. Under a uniaxial external loading condition, a simplified format of the T-stress-based estimate has been proposed by the authors to obtain the parameter A much more conveniently and effectively. Generally, sensors and other practical engineering structures endure biaxial external loading instead of the uniaxial one. In the current work, the simplified formation of the estimate method is extended to a biaxial loading condition. By comparing the estimated A parameter values with their numerical solutions from a finite element analysis (FEA) results, the extension of the simplified formation of T-stress-based estimate method to biaxial loading was discussed and validated. The comparison procedure was completed using a wide variety of materials and geometrical properties on three types of specimens: single edge cracked plate (SECP), center cracked plate (CCP), and double edge cracked plate (DECP).
Why We Should Empty Pandora’s Box to Create a Sustainable Future: Hope, Sustainability and Its Implications for Education
Authors: Grund Julius , Brock Antje
Published: February 2019

(1) Hope and optimism are strongly connected to physical and psychological health and have been much researched in the field of positive psychology. Research has shown that hope is connected to pro-environmental behavior and plays an important role in ESD. (2) In order to operationalize hope and optimism, in a survey, 2564 young people and 525 teachers in Germany assessed the probability and desirability of predefined future scenarios. (3) Only every fourth respondent is optimistic regarding the global future. The biggest discrepancy between expectation and desirability exists with regard to climate change. Latent class analysis revealed four classes, whereby 50% of the participants are “sustainability-affine but disillusioned”. This half of the sample has great potential to promote a sustainable future: For them, a positive socio-ecological future has by far the highest value. They report the strongest emotions regarding SD and want to take the most responsibility for SD. Surprisingly, they do not disclose more sustainable behavior in comparison to the other classes. (4) The low expectation of positive socio-ecological developments might be a central factor in preventing half of the sample from behaving more sustainable and indicating a strong potential for hope. The implications for Education for Sustainable Development are discussed.
Contribution of the Vernacular Architecture to the Sustainability: A Comparative Study between the Contemporary Areas and the Old Quarter of a Mediterranean City
Authors: Tawayha Fajer Al , Braganca Luis , Mateus Ricardo
Published: February 2019

The strongest point of vernacular architecture is the harmony between environment and buildings. Mediterranean vernacular architecture is harmonized with its local context, including culture and traditions. In addition, it respects environmental and climatic factors, construction materials, and morphology. In the past, people in Palestine built their houses according to their possibilities, needs, available materials, topography, and culture. Without any control from the government or any legal limitations or architects, it was people’s architecture, simple architecture. This paper discusses the differences between vernacular and contemporary residential buildings of the city of Nablus at the building scale. The research methodology adopts explanatory qualitative analysis and comparative synthesis methods for both the old and the new buildings of the city of Nablus and considers many parameters of residential buildings such as building materials, interior spaces, openings and vegetation, and the effect of sociocultural values on each. The outcomes of this research allow understanding how the new city residential buildings are far away from the sustainability principles and how the old city is close to it and how the architects and stakeholders could learn from the strategies of vernacular architecture.
Mandatory Convertible Notes as a Sustainable Corporate Finance Instrument
Authors: Huerga Angel , Rodríguez-Monroy Carlos
Published: February 2019

Debt securities are often an efficient and inexpensive resource to finance the balance sheet of companies; however, one of the causes of the global financial crisis was the excessive leverage taken by companies. Hybrid capital instruments share characteristics of equity and debt, and allow companies to finance its balance sheet in a more sustainable way by reducing leverage, but tend to increase its overall cost of capital. Mandatory convertible notes (MCNs) are hybrid financing instruments that are very close to equity; rating agencies assign them a high equity component and are commonly treated as equity by accounting standards. Despite the high nominal coupon that MCNs seem to pay in some cases, a deeper analysis shows that the cost of issuing MCNs can be similar and even lower than the cost of issuing senior debt. This research performs an empirical study of the implicit cost of the MCNs issued between 2010 and 2018. The study shows the relationship between the implicit yield of MCNs, the senior debt yield, and the convertible arbitrage investors. MCNs can be a sustainable capital alternative that offers a reasonable cost not only for high-yield companies but also for well-established investment grade issuers. The access to efficient and not very expensive capital to finance the balance sheet of companies can promote sustainable growth, industrialization, and innovation.
Antiaging Cosmeceuticals in Korea and Open Innovation in the Era of the 4th Industrial Revolution: From Research to Business
Authors: Shin Kyu-Ok , Park Hang-Sik
Published: February 2019

The importance of the healthcare industry has increased and it has thrived, although the cosmetic industry of Korea has been in depression. A recently issued group of items in Korea, ‘cosmeceuticals’, is defined as a combination of pharmaceuticals and cosmetics proven to have medical effectiveness. Antiaging cosmeceuticals in Korea have performed well in terms of expanding business by combining with beauty services, so they are viewed as high-valued items. This fact supports the evidence that there are various studies on cosmeceuticals. Therefore, this paper shows that the global status and growth potential of cosmeceuticals are documented and the concepts of the application of the demonstration complex and open innovation will be linked together based on research of antiaging cosmeceuticals in Korea for an aging society. This paper intends to provide the basic information for forming a ‘lab to market’ which connects the future cosmeceutical laboratory to the market.
Thermodynamic Analysis and Experimental Study of Selective Dehydrogenation of 1,2-cyclohexanediol over Cu2+1O/MgO Catalysts
Authors: Wang Haiou , Yang Qiusheng , Song Yucong , Wang Yanji
Published: February 2019

The dehydrogenation of 1,2-cyclohexanediol (CHD) helps in the effective utilization of not only fossil derivatives but also vicinal diols and polyols from sustainable biomass-derived resources. A thermodynamic analysis of CHD dehydrogenation was computed with density functional theory (DFT) calculation using Gaussian 09. The result indicates that CHD can be converted to 2-hydroxy cyclohexanone (HCO), 2-hydroxy-2-cyclohexen-1-one (HCEO) and pyrocatechol depending on the degree of dehydrogenation. HCO and HCEO are the stable products of the primary and secondary dehydrogenation. Experimentally, Cu/MgO catalysts were prepared using glucose as a reductant, and were characterized by SEM, TEM, XRD, XPS, TPR, BET and ICP. Furthermore, their catalytic performance regarding the oxygen-free dehydrogenation of CHD was investigated. The results indicate that the primary active crystalline phase of Cu/MgO was Cu2+1O, and that the dehydrogenation products were mainly HCO and HCEO, in accordance with thermodynamic predictions. Upon optimizing the reaction conditions, the total selectivity of HCO and HCEO exceeded 90% and the conversion of CHD was approximately 95%.
Spatiotemporal Changes and the Driving Forces of Sloping Farmland Areas in the Sichuan Region
Authors: Xiao Meijia , Zhang Qingwen , Qu Liqin , Hussain Hafiz Athar , Dong Yuequn , Zheng Li
Published: February 2019

Sloping farmland is an essential type of the farmland resource in China. In the Sichuan province, livelihood security and social development are particularly sensitive to changes in the sloping farmland, due to the region’s large portion of hilly territory and its over-dense population. In this study, we focused on spatiotemporal change of the sloping farmland and its driving forces in the Sichuan province. Sloping farmland areas were extracted from geographic data from digital elevation model (DEM) and land use maps, and the driving forces of the spatiotemporal change were analyzed using a principal component analysis (PCA). The results indicated that, from 2000 to 2015, sloping farmland decreased by 3263 km2 in the Sichuan province. The area of gently sloping farmland (<10°) decreased dramatically by 1467 km2, especially in the capital city, Chengdu, and its surrounding areas. However, the steep sloping farmland (>25°) decreased by 302 km2, and was still the largest portion of total farmland in the area. The PCA analysis indicated that the main driving forces behind the changes were social and economic factors. The influence of agricultural intensification factors, such as the multiple cropping index and sown areas of crops, was relatively weak. Given the decrease in the overall slope cultivated area and the increased portion of moderately steep slope land (10–25°) in the cultivated area, special attention should be paid to the scientific conservation of sloping farmland during rapid social and economic development.
Livelihoods Strategies and Household Resilience to Food Insecurity: A Case Study from Rural Tunisia
Authors: Dhraief Mohamed Zied , Dhehibi Boubaker , Daly Hassen Hamed , Zlaoui Meriem , Khatoui Chaima , Jemni Sondes , Jebali Ouessama , Rekik Mourad
Published: February 2019

Due to the decrease of household incomes, the increase of food prices, and the negative effects of climate change on agricultural production, Tunisia faces a food insecurity challenge, especially in rural and arid areas. The purpose of our research is to understand and explore household resilience to food insecurity in two villages, Selta and Zoghmar, in central Tunisia. A cross-sectional survey of 250 sample households was conducted in the villages. Factor analysis and regression models were employed to analyze the data using SPSS version 21. The results indicate that only around 36% of the households were resilient at different levels. In Selta, 62.8% and in Zoghmar 66.7% of the households were vulnerable. As indicated by the factor loadings and beta coefficients, income and food access, adaptive capacity, and the social safety net were important dimensions of household resilience to food insecurity, being positively correlated with the resilience index. However, asset possession, and climate change negatively affect household resilience. Therefore, interventions must target strategies that address the different levels of resilience reflected by the resilience estimators. These estimators were generated by focusing mainly on building farmers’ knowledge of how to face the different difficulties and challenges.
Semi-Dry Carbonation Process Using Fly Ash from Solid Refused Fuel Power Plant
Authors: Kim Jung Hyun , Kwon Woo Teck
Published: February 2019

The increasing CO2 concentration in the Earth’s atmosphere, mainly caused by fossil fuel combustion, has led to concerns about global warming. Carbonation is a technique that can be used as a carbon capture and storage (CCS) technology for CO2 sequestration. In this study, the utilization of the fly ash from a solid refused fuel (SRF) power plant as a solid sorbent material for CO2 capture via semi-dry carbonation reaction was evaluated as a simple process to reduce CO2. The fly ash was exposed to accelerated carbonation conditions at a relative humidity of 25, 50, 75, and 100%, to investigate the effects of humidity on the carbonation kinetics of the fly ash. The reaction conditions such as moisture, concentration of CO2, and reaction time can affect CO2 capture performance of fly ash. Due to a short diffusion length of H2CO3 in water, the semi-dry process exhibits faster carbonation reaction than the wet process. Especially, the semi-dry process does not require a wastewater treatment plant because it uses a small amount of water. This study may have important implications, illustrating the possibility of replacing the wet process with the semi-dry process.
Sustainability and Dimensions of a Nexus Approach in a Sharing Economy
Authors: Schneider Petra , Folkens Lukas , Meyer Andreas , Fauk Tino
Published: February 2019

Increasing global resource consumption puts the availability of natural mineral resources under significant pressure. One strategy to overcome this trend is the decoupling of economic growth and resource consumption and the application of circular economy approaches. These approaches aim at closing material cycles across sectoral boundaries. Beside these attempts, there are further options for action aimed at minimization of resource consumption through resource sharing approaches. This study investigates resource-saving potentials on different scales namely on a personal scale through sharing goods and services, but also in the frame of industrial symbiosis through sharing of secondary resources at a company scale. The environmental effects have been quantified using life cycle assessment examples for these two simulated cases. The results show for both resource consumption levels, resource savings potentials of up to 2 powers of ten, that can particularly be proven regarding the impact category ‘fossil resource depletion’. The emergence of industrial symbiosis can be identified by six factors: Resource, government, economy, company, technology, and society. The cases simulated in the study are supported by empirical evidence from real-life examples, which consider the mentioned factors.
Thermal Behavior and Measures to Prevent Condensation of a Newly Developed External Wall Panel
Authors: Hong Goopyo , Lee Suk-Won , Kang Ji-Yeon , Kim Hyung-Geun
Published: February 2019

An external wall panel (EWP) as a novel alternative to provide spatial flexibility and improve the performance of external walls was developed. The purpose of this study was to analyze the thermal performance of this EWP. A simulation analysis was carried out to scrutinize whether it was vulnerable to condensation, considering South Korea’s weather conditions, and find countermeasures to prevent this. Results indicated that the indoor surface temperature with the measures of added insulation materials and an inserted thermal-breaker was over 16.5 °C and that these methods could prevent condensation. In addition, this study assessed unsteady-state thermal characteristics, linear thermal transmittance, and the effective thermal transmittance of EWP. Effective thermal transmittance was estimated in consideration of the heat transmittance of EWP and the linear thermal transmittance of its slabs and its connection parts. The thermal characteristics of the building envelope are needed to analyze effective thermal transmittance and linear thermal transmittance-associated thermal bridges.
Sales Prediction by Integrating the Heat and Sentiments of Product Dimensions
Authors: Lyu Xiaozhong , Jiang Cuiqing , Ding Yong , Wang Zhao , Liu Yao
Published: February 2019

Online word-of-mouth (eWOM) disseminated on social media contains a considerable amount of important information that can predict sales. However, the accuracy of sales prediction models using big data on eWOM is still unsatisfactory. We argue that eWOM contains the heat and sentiments of product dimensions, which can improve the accuracy of prediction models based on multiattribute attitude theory. In this paper, we propose a dynamic topic analysis (DTA) framework to extract the heat and sentiments of product dimensions from big data on eWOM. Ultimately, we propose an autoregressive heat-sentiment (ARHS) model that integrates the heat and sentiments of dimensions into the benchmark predictive model to forecast daily sales. We conduct an empirical study of the movie industry and confirm that the ARHS model is better than other models in predicting movie box-office revenues. The robustness check with regard to predicting opening-week revenues based on a back-propagation neural network also suggests that the heat and sentiments of dimensions can improve the accuracy of sales predictions when the machine-learning method is used.
Rating the Raters: Evaluating how ESG Rating Agencies Integrate Sustainability Principles
Authors: Escrig-Olmedo Elena , Fernández-Izquierdo María Ángeles , Ferrero-Ferrero Idoya , Rivera-Lirio Juana María , Muñoz-Torres María Jesús
Published: February 2019

Environmental, social, and governance (ESG) rating agencies, acting as relevant financial market actors, should take a stand on working towards achieving a more sustainable development. In this context, the objective of this paper is, on the one hand, to understand how criteria used by ESG rating agencies in their assessment processes have evolved over the last ten years and, on the other hand, to analyze whether ESG rating agencies are contributing to fostering sustainable development by the inclusion of sustainability principles into their assessment processes and practices according to the ESG criteria. This research is based on a comparative descriptive analysis of the public information provided by the most representative ESG rating and information provider agencies in the financial market in two periods: 2008 and 2018. The findings show that ESG rating agencies have integrated new criteria into their assessment models to measure corporate performance more accurately and robustly in order to respond to new global challenges. However, a deep analysis of the criteria also shows that ESG rating agencies do not fully integrate sustainability principles into the corporate sustainability assessment process.
Detecting Indicators for Startup Business Success: Sentiment Analysis Using Text Data Mining
Authors: Saura Jose Ramon , Palos-Sanchez Pedro , Grilo Antonio
Published: February 2019

The main aim of this study is to identify the key factors in User Generated Content (UGC) on the Twitter social network for the creation of successful startups, as well as to identify factors for sustainable startups and business models. New technologies were used in the proposed research methodology to identify the key factors for the success of startup projects. First, a Latent Dirichlet Allocation (LDA) model was used, which is a state-of-the-art thematic modeling tool that works in Python and determines the database topic by analyzing tweets for the #Startups hashtag on Twitter (n = 35.401 tweets). Secondly, a Sentiment Analysis was performed with a Supervised Vector Machine (SVM) algorithm that works with Machine Learning in Python. This was applied to the LDA results to divide the identified startup topics into negative, positive, and neutral sentiments. Thirdly, a Textual Analysis was carried out on the topics in each sentiment with Text Data Mining techniques using Nvivo software. This research has detected that the topics with positive feelings for the identification of key factors for the startup business success are startup tools, technology-based startup, the attitude of the founders, and the startup methodology development. The negative topics are the frameworks and programming languages, type of job offers, and the business angels’ requirements. The identified neutral topics are the development of the business plan, the type of startup project, and the incubator’s and startup’s geolocation. The limitations of the investigation are the number of tweets in the analyzed sample and the limited time horizon. Future lines of research could improve the methodology used to determine key factors for the creation of successful startups and could also study sustainable issues.
Association between New Urbanization and Sustainable Transportation: A Symmetrical Coupling Perspective
Authors: Ma Fei , Guo Yanru , Yuen Kum Fai , Woo Suhan , Shi Wenjing
Published: February 2019

New urbanization (NU) and sustainable transportation (ST) are two important issues in urbanization, and their symmetrical coupling is an important factor for measuring the development of the urbanization process. To comprehensively explore the symmetrical coupling level of NU and ST in the urbanization process, this study proposed a coupling coordination degree (CCD) model and calculated the CCD values of China’s nine metropolises using panel data from 2007 to 2016. The results showed that: (1) From the perspective of each city’s development, the CCD values for Beijing, Tianjin and Chongqing showed a downward trend, and those for Shanghai, Guangzhou, Chengdu and Wuhan exhibited a rising trend, while the CCD values for Zhengzhou and Xi’an fell initially and then rose gradually; (2) Based on the regions of the nine cities, the CCD values of the eastern cities and the central cities all demonstrated a growth trend, while those of the western cities were consistently lower than the central and eastern cities; however, the western cities experienced the highest growth rate. (3) Predictive results showed that the CCD levels of new urbanization and sustainable transportation in the eastern, central and western cities are projected to remain unchanged. Finally, it is expected that regionally balanced development will be realized in 2025. From the symmetrical coupling perspective, this study measured and predicted the coupling coordination level of NU and ST of nine metropolises undergoing the urbanization process, which provides a theoretical basis for effective decision-making for comprehensive and sustainable development of China’s urbanization.
Inspection Strategy under Indeterminacy Based on Neutrosophic Coefficient of Variation
Authors: Aslam Muhammad , Aldosari Mansour Sattam
Published: February 2019

The existing sampling plans which use the coefficient of variation (CV) are designed under classical statistics. These available sampling plans cannot be used for sentencing if the sample or the population has indeterminate, imprecise, unknown, incomplete or uncertain data. In this paper, we introduce the neutrosophic coefficient of variation (NCV) first. We design a sampling plan based on the NCV. The neutrosophic operating characteristic (NOC) function is then given and used to determine the neutrosophic plan parameters under some constraints. The neutrosophic plan parameters such as neutrosophic sample size and neutrosophic acceptance number are determined through the neutrosophic optimization solution. We compare the efficiency of the proposed plan under the neutrosophic statistical interval method with the sampling plan under classical statistics. A real example which has indeterminate data is given to illustrate the proposed plan.
Some Results for Split Equality Equilibrium Problems in Banach Spaces
Authors: Ma Zhaoli , Wang Lin , Cho Yeol Je
Published: February 2019

In this paper, a new algorithm for finding a common element of a split equality fixed point problem for nonexpansive mappings and split equality equilibrium problem in three Banach spaces is introduced. Also, some strong and weak convergence theorems for the proposed algorithm are proved. Finally, the main results obtained in this paper are applied to solve the split equality convex minimization problem.
MFBS: Multiple Factor Bandwidth Strategy Scheme for Anonymity Assessment
Authors: Lu Tianbo , Luo Meng , Yan Ru , Lin Zhimin
Published: February 2019

This paper proposes a multiple factor bandwidth strategy (MFBS), an anonymity assessment scheme based on bandwidth strategy. We first analyzed the path selection algorithm mechanism based on bandwidth strategy and anonymity constraint conditions and then elaborated the overall architecture and the key module design of the MFBS scheme. A detailed design was carried out so that it can be applied for the evaluation of Tor’s anonymous communication system. Finally, according to the running data in the node resource file in the anonymous network, we analyzed anonymity from different dimensions. By evaluating the bandwidth consumed by Tor in the actual network, the anonymity of the Tor could be calculated, and a more comprehensive anonymity assessment could be performed.
Co-Occurrence of Beauvericin and Enniatins in Edible Vegetable Oil Samples, China
Authors: Han Xiaomin , Xu Wenjing , Zhang Jing , Xu Jin , Li Fengqin
Published: February 2019

A total of 470 edible vegetable oil samples including peanut, soybean, rapeseed, sesame seed, corn, blend, and others collected from eight provinces of China were analyzed for the concentrations of beauvericin (BEA), enniatin A (ENA), A1 (ENA1), B (ENB), and B1 (ENB1) by ultraperformance liquid chromatography/electrospray ionization tandem mass spectrometry (UPLC/ESI-MS/MS). Concentrations of BEA, ENB, and ENB1 (average = 5.59 μg/kg, 5.16 μg/kg, and 4.61 μg/kg) in all positive samples were higher than those for ENA and ENA1 (average = 0.85 μg/kg and 1.88 μg/kg). Frequencies of BEA and ENNs in all analyzed samples were all higher than 50% with the exception of ENA1 (36.6%, 172/470). Levels of BEA and ENNs in all analyzed samples varied based on their sample types and geographical distributions (Kruskal–Wallis test, p < 0.05). The soybean and peanut oil samples were found to be more easily contaminated by BEA and ENNs than other oil samples. Concentrations of BEA and ENNs in samples obtained from Heilongjiang, Shandong and Guizhou were higher than those found in samples from other provinces. Besides, frequencies of mycotoxin co-contaminations were high and their co-contamination types also varied by oil types. BEA-ENA-ENA1-ENB-ENB1 was the most commonly found toxin combination type, almost in one third of the analyzed samples (30%, 141/470). Overall, these results indicate that co-occurrence of BEA and ENNs in analyzed Chinese edible vegetable oil samples is highly common, and it is vital to monitor them, both simultaneously and on a widespread level.
Pseudomonas putida Responds to the Toxin GraT by Inducing Ribosome Biogenesis Factors and Repressing TCA Cycle Enzymes
Authors: Ainelo Andres , Porosk Rando , Kilk Kalle , Rosendahl Sirli , Remme Jaanus , Hõrak Rita
Published: February 2019

The potentially self-poisonous toxin-antitoxin modules are widespread in bacterial chromosomes, but despite extensive studies, their biological importance remains poorly understood. Here, we used whole-cell proteomics to study the cellular effects of the Pseudomonas putida toxin GraT that is known to inhibit growth and ribosome maturation in a cold-dependent manner when the graA antitoxin gene is deleted from the genome. Proteomic analysis of P. putida wild-type and ΔgraA strains at 30 °C and 25 °C, where the growth is differently affected by GraT, revealed two major responses to GraT at both temperatures. First, ribosome biogenesis factors, including the RNA helicase DeaD and RNase III, are upregulated in ΔgraA. This likely serves to alleviate the ribosome biogenesis defect of the ΔgraA strain. Secondly, proteome data indicated that GraT induces downregulation of central carbon metabolism, as suggested by the decreased levels of TCA cycle enzymes isocitrate dehydrogenase Idh, α-ketoglutarate dehydrogenase subunit SucA, and succinate-CoA ligase subunit SucD. Metabolomic analysis revealed remarkable GraT-dependent accumulation of oxaloacetate at 25 °C and a reduced amount of malate, another TCA intermediate. The accumulation of oxaloacetate is likely due to decreased flux through the TCA cycle but also indicates inhibition of anabolic pathways in GraT-affected bacteria. Thus, proteomic and metabolomic analysis of the ΔgraA strain revealed that GraT-mediated stress triggers several responses that reprogram the cell physiology to alleviate the GraT-caused damage.
Exploring the Diversity and Novelty of Toxin Genes in Naja sumatrana, the Equatorial Spitting Cobra from Malaysia through De Novo Venom-Gland Transcriptomics
Authors: Chong Ho Phin , Tan Kae Yi , Tan Nget Hong , Tan Choo Hock
Published: February 2019

The equatorial spitting cobra, Naja sumatrana, is a distinct species of medically important venomous snakes, listed as WHO Category 1 in Southeast Asia. The diversity of its venom genes has not been comprehensively examined, although a few toxin sequences annotated to Naja sputatrix were reported previously through cloning studies. To investigate this species venom genes’ diversity, de novo venom-gland transcriptomics of N. sumatrana from West Malaysia was conducted using next-generation sequencing technology. Genes encoding toxins represented only 60 of the 55,396 transcripts, but were highly expressed, contributing to 79.22% of total gene expression (by total FPKM) in the venom-glands. The toxin transcripts belong to 21 families, and 29 transcripts were further identified as full-length. Three-finger toxins (3FTx) composed of long, short, and non-conventional groups, constituted the majority of toxin transcripts (91.11% of total toxin FPKM), followed by phospholipase A2 (PLA2, 7.42%)—which are putatively pro-inflammatory and cytotoxic. The remaining transcripts in the 19 families were expressed at extremely low levels. Presumably, these toxins were associated with ancillary functions. Our findings unveil the diverse toxin genes unique to N. sumatrana, and provide insights into the pathophysiology of N. sumatrana envenoming.
Molecular Evidence of Drug-Resistant Tuberculosis in the Balimo Region of Papua New Guinea
Authors: Diefenbach-Elstob Tanya , Guernier Vanina , Burgess Graham , Pelowa Daniel , Dowi Robert , Gula Bisato , Puri Munish , Pomat William , McBryde Emma , Plummer David , Rush Catherine , Warner Jeffrey
Published: February 2019

Papua New Guinea (PNG) has a high burden of tuberculosis (TB), including drug-resistant TB (DR-TB). DR-TB has been identified in patients in Western Province, although there has been limited study outside the provincial capital of Daru. This study focuses on the Balimo region of Western Province, aiming to identify the proportion of DR-TB, and characterise Mycobacterium tuberculosis (MTB) drug resistance-associated gene mutations. Sputum samples were investigated for MTB infection using published molecular methods. DNA from MTB-positive samples was amplified and sequenced, targeting the rpoB and katG genes to identify mutations associated with rifampicin and isoniazid resistance respectively. A total of 240 sputum samples were collected at Balimo District Hospital (BDH). Of these, 86 were classified as positive based on the results of the molecular assays. For samples where rpoB sequencing was successful, 10.0% (5/50, 95% CI 4.4–21.4%) were considered rifampicin-resistant through detection of drug resistance-associated mutations. We have identified high rates of presumptive DR-TB in the Balimo region of Western Province, PNG. These results emphasise the importance of further surveillance, and strengthening of diagnostic and treatment services at BDH and throughout Western Province, to facilitate detection and treatment of DR-TB, and limit transmission in this setting.
Detection of RNA-Dependent RNA Polymerase of Hubei Reo-Like Virus 7 by Next-Generation Sequencing in Aedes aegypti and Culex quinquefasciatus Mosquitoes from Brazil
Authors: Ribeiro Geovani de Oliveira , Monteiro Fred Julio Costa , Rego Marlisson Octavio da S , Ribeiro Edcelha Soares D’Athaide , Castro Daniela Funayama de , Caseiro Marcos Montani , Souza Marinho Robson dos Santos , Komninakis Shirley Vasconcelos , Witkin Steven S. , Deng Xutao , Delwart Eric , Sabino Ester Cerdeira , da Costa Antonio Charlys , Leal Élcio
Published: February 2019

Advancements in next-generation sequencing and bioinformatics have expanded our knowledge of the diversity of viruses (pathogens and non-pathogens) harbored by mosquitoes. Hubei reo-like virus 7 (HRLV 7) was recently detected by the virome analysis of fecal samples from migratory birds in Australia. We now report the detection of RNA-dependent RNA polymerase sequences of HRLV 7 in pools of Aedes aegypti and Culex quinquefasciatus mosquitoes species from the Brazilian Amazon forest. Phylogenetic inferences indicated that all HRLV 7 strains fall within the same independent clade. In addition, HRLV 7 shared a close ancestral lineage with the Dinovernavirus genus of the Reoviridae family. Our findings indicate that HRLV 7 is present in two species of mosquitoes.