bluuebunny/crossref_metadata_2025 huggingface dataset:
BBS Posts Time Series Analysis based on Sample Entropy and Deep Neural Networks
Authors: Chen Jindong , Du Yuxuan , Liu Linlin , Zhang Pinyi , Zhang Wen
Published: January 2019

The modeling and forecasting of BBS (Bulletin Board System) posts time series is crucial for government agencies, corporations and website operators to monitor public opinion. Accurate prediction of the number of BBS posts will assist government agencies or corporations in making timely decisions and estimating the future number of BBS posts will help website operators to allocate resources to deal with the possible hot events pressure. By combining sample entropy (SampEn) and deep neural networks (DNN), an approach (SampEn-DNN) is proposed for BBS posts time series modeling and forecasting. The main idea of SampEn-DNN is to utilize SampEn to decide the input vectors of DNN with smallest complexity, and DNN to enhance the prediction performance of time series. Selecting Tianya Zatan new posts as the data source, the performances of SampEn-DNN were compared with auto-regressive integrated moving average (ARIMA), seasonal ARIMA, polynomial regression, neural networks, etc. approaches for prediction of the daily number of new posts. From the experimental results, it can be found that the proposed approach SampEn-DNN outperforms the state-of-the-art approaches for BBS posts time series modeling and forecasting.
From Learning to Consciousness: An Example Using Expected Float Entropy Minimisation
Authors: Mason Jonathan W. D.
Published: January 2019

Over recent decades several mathematical theories of consciousness have been put forward including Karl Friston’s Free Energy Principle and Giulio Tononi’s Integrated Information Theory. In this article we further investigate theory based on Expected Float Entropy (EFE) minimisation which has been around since 2012. EFE involves a version of Shannon Entropy parameterised by relationships. It turns out that, for systems with bias due to learning, certain choices for the relationship parameters are isolated since giving much lower EFE values than others and, hence, the system defines relationships. It is proposed that, in the context of all these relationships, a brain state acquires meaning in the form of the relational content of the associated experience. EFE minimisation is itself an association learning process and its effectiveness as such is tested in this article. The theory and results are consistent with the proposition of there being a close connection between association learning processes and the emergence of consciousness. Such a theory may explain how the brain defines the content of consciousness up to relationship isomorphism.
Community of Inquiry on Facebook in a Formal Learning Setting in Higher Education
Authors: Nazir Masood , Brouwer Natasa
Published: January 2019

This study demonstrates an application of Facebook for higher education in science (STEM), and it clarifies its impact on students’ learning in a formal online learning setting. A combined qualitative and quantitative approach was used. Messages posted on Facebook were classified by qualitative transcript analysis. The perception and experience of students with Facebook were recorded by means of pre- and post-tests, using a treatment/control group approach. The results show that an integral Community of Inquiry (CoI) was formed on Facebook within the regular online course, encompassing all relevant CoI interactions leading to a powerful educational experience. Additionally, a type of CoI interaction “student–community” is observed, which was not reported before. The results show that the use of Facebook had positive effects on students’ learning, only when the activities on Facebook were constructively integrated in a course design, and a moderator was present. More research is needed to include larger group sizes and other course designs.
Modeling the Total Energy Consumption of Mobile Network Services and Applications
Authors: Yan Ming , Chan Chien Aun , Gygax André F. , Yan Jinyao , Campbell Leith , Nirmalathas Ampalavanapillai , Leckie Christopher
Published: January 2019

Reducing the energy consumption of Internet services requires knowledge about the specific traffic and energy consumption characteristics, as well as the associated end-to-end topology and the energy consumption of each network segment. Here, we propose a shift from segment-specific to service-specific end-to-end energy-efficiency modeling to align engineering with activity-based accounting principles. We use the model to assess a range of the most popular instant messaging and video play applications to emerging augmented reality and virtual reality applications. We demonstrate how measurements can be conducted and used in service-specific end-to-end energy consumption assessments. Since the energy consumption is dependent on user behavior, we then conduct a sensitivity analysis on different usage patterns and identify the root causes of service-specific energy consumption. Our main findings show that smartphones are the main energy consumers for web browsing and instant messaging applications, whereas the LTE wireless network is the main consumer for heavy data applications such as video play, video chat and virtual reality applications. By using small cell offloading and mobile edge caching, our results show that the energy consumption of popular and emerging applications could potentially be reduced by over 80%.
Analytical and Numerical Investigation of Fe3O4–Water Nanofluid Flow over a Moveable Plane in a Parallel Stream with High Suction
Authors: Chamkha A. J. , Rashad A. M. , EL-Zahar E. R. , EL-Mky Hamed A.
Published: January 2019

In the current framework, a model is constituted to explore the impacts of high suction and partial slip on Fe3O4–water nanoliquid flow over a porous moveable surface in a parallel free stream. The mechanisms of heat transfer are also modeled in the existence of Newtonian heating effect. The obtaining PDEs are transformed into a non-linear ODE system employing appropriate boundary conditions to diverse physical parameters. The governing ODE system is solved using a singular perturbation technique that results in an analytical asymptotic solution as a function of the physical parameters. The obtained solution allows us to carry out an analytical parametric study to investigate the impact of the physical parameters on the nonlinear attitude of the system. The precision of the proposed method is verified by comparisons between the numerical and analytical results. The results confirm that the proposed technique yields a good approximation to the solution as well as the solution calculation has no CPU time-consuming or round off error. Numerical solutions are computed and clarified in graphs for the model embedded parameters. Moreover, profiles of the skin friction coefficient and the heat transfer rate are also portrayed and deliberated. The data manifests that both solid volume fraction and slip impact significantly alter the flow profiles. Moreover, an upward trend in temperature is anticipated for enhancing Newtonian heating strength. Additionally, it was found that both the nanofluid velocity and temperature distributions are decelerated when the solid volume fraction and suction parameters increase. Furthermore, a rise in slip parameter causes an increment in velocity profiles, and a rise in Biot number causes an increment in the temperature profiles.
Issues with Data Quality for Wind Turbine Condition Monitoring and Reliability Analyses
Authors: Leahy Kevin , Gallagher Colm , O’Donovan Peter , O’Sullivan Dominic T. J.
Published: January 2019

In order to remain competitive, wind turbines must be reliable machines with efficient and effective maintenance strategies. However, thus far, wind turbine reliability information has been closely guarded by the original equipment manufacturers (OEMs), and turbine reliability studies often rely on data that are not always in a usable or consistent format. In addition, issues with turbine maintenance logs and alarm system data can make it hard to identify historical periods of faulty operation. This means that building new and effective data-driven condition monitoring techniques and methods can be challenging, especially those that rely on supervisory control and data acquisition (SCADA) system data. Such data are rarely standardised, resulting in challenges for researchers in contextualising these data. This work aims to summarise some of the issues seen in previous studies, highlighting the common problems seen by researchers working in the areas of condition monitoring and reliability analysis. Standards and policy initiatives that aim to alleviate some of these problems are given, and a summary of their recommendations is presented. The main finding from this work is that industry would benefit hugely from unified standards for turbine taxonomies, alarm codes, SCADA operational data and maintenance and fault reporting.
Hydraulic Fracture Design with a Proxy Model for Unconventional Shale Gas Reservoir with Considering Feasibility Study
Authors: Kim Kyoungsu , Choe Jonggeun
Published: January 2019

Shale gas is a natural gas trapped in shale formation and is being actively developed in North America. Due to the low permeability of a shale gas reservoir in the range from 10−8 to 10−6 Darcy, horizontal drilling and multi-stage hydraulic fracturing are needed for its development. This paper presents a fast and reliable proxy model to forecast shale gas productions and an optimum hydraulic fracturing design for its development. The proxy model uses a robust regression scheme and can replace a commercial reservoir simulator. The proxy model proposed can determine the influence of impact factors on the production at each production time. The calculation speed of the proposed proxy model is about 1.4 million times faster than that of a reservoir simulator compared. The most economical hydraulic fracture design using the proxy model has a length of 168 m at each stage, which is determined by examining a large number of hydraulic fracturing designs considering economic feasibility.
Water and Energy Efficiency Improvement of Steel Wire Manufacturing by Circuit Modelling and Optimisation
Authors: Iten Muriel , Oliveira Miguel , Costa Diogo , Michels Jochen
Published: January 2019

Industrial water circuits (IWC) are frequently neglected as they are auxiliary circuits of industrial processes, leading to a missing awareness of their energy- and water-saving potential. Industrial sectors such as steel, chemicals, paper and food processing are notable in their water-related energy requirements. Improvement of energy efficiency in industrial processes saves resources and reduces manufacturing costs. The paper presents a cooling IWC of a steel wire processing plant in which steel billets are transformed into wire. The circuit was built in object-oriented language in OpenModelica and validated with real plant data. Several improvement measures have been identified and an optimisation methodology has been proposed. A techno-economic analysis has been carried out to estimate the energy savings and payback time for the proposed improvement measures. The suggested measures allow energy savings up to 29% in less than 3 years’ payback time and water consumption savings of approximately 7.5%.
Maintenance Models Applied to Wind Turbines. A Comprehensive Overview
Authors: Merizalde Yuri , Hernández-Callejo Luis , Duque-Perez Oscar , Alonso-Gómez Víctor
Published: January 2019

Wind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models.
Effect of Rotor Thrust on the Average Tower Drag of Downwind Turbines
Authors: Yoshida Shigeo , Fujii Kazuyuki , Hamasaki Masahiro , Takada Ao
Published: January 2019

A new analysis method to calculate the rotor-induced average tower drag of downwind turbines in the blade element momentum (BEM) method was developed in this study. The method involves two parts: calculation of the wind speed distribution using computational fluid dynamics, with the rotor modeled as a uniform loaded actuator disc, and calculation of the tower drag via the strip theory. The latter calculation considers two parameters, that is, the decrease in wind speed and the pressure gradient caused by the rotor thrust. The present method was validated by a wind tunnel test. Unlike the former BEM, which assumes the tower drag to be constant, the results obtained by the proposed method demonstrate much better agreement with the results of the wind tunnel test, with an accuracy of 30%.
Maximum Sensitivity-Constrained Data-Driven Active Disturbance Rejection Control with Application to Airflow Control in Power Plant
Authors: He Ting , Wu Zhenlong , Shi Rongqi , Li Donghai , Sun Li , Wang Lingmei , Zheng Song
Published: January 2019

The increasing energy demand and the changing of energy structure have imposed higher requirements on the conventional large-scale power plants control. Complexity of the power plant processes and the frequent change of operation condition make the accurate physical models hard to obtain for control design. To this end, a data-driven control strategy, the active disturbance rejection control (ADRC) has received much attention for the estimation and mitigation of uncertain dynamics beyond the canonical form of cascaded integrators. However, the robustness of ADRC is seldom discussed in a quantitative manner. In this study, the maximum sensitivity is used to evaluate and then constrain the robustness of ADRC applied to high-order processes. Firstly, by using the new idea of the vertical asymptote of the Nyquist curve, a preliminary one-parameter-tuning method is developed. Secondly, a quantitative relationship between the maximum sensitivity and the tuning parameter is established using optimization methods. Then, the feasibility and effectiveness of the proposed method is initially verified in the total air flow control of a power plant simulator. Finally, field tests on the secondary airflow control in a 330 MWe circulating fluidized bed confirm the merit of the proposed maximum sensitivity-constrained ADRC tuning.
Bio-Based Chemicals from Renewable Biomass for Integrated Biorefineries
Authors: Kohli Kirtika , Prajapati Ravindra , Sharma Brajendra K.
Published: January 2019

The production of chemicals from biomass, a renewable feedstock, is highly desirable in replacing petrochemicals to make biorefineries more economical. The best approach to compete with fossil-based refineries is the upgradation of biomass in integrated biorefineries. The integrated biorefineries employed various biomass feedstocks and conversion technologies to produce biofuels and bio-based chemicals. Bio-based chemicals can help to replace a large fraction of industrial chemicals and materials from fossil resources. Biomass-derived chemicals, such as 5-hydroxymethylfurfural (5-HMF), levulinic acid, furfurals, sugar alcohols, lactic acid, succinic acid, and phenols, are considered platform chemicals. These platform chemicals can be further used for the production of a variety of important chemicals on an industrial scale. However, current industrial production relies on relatively old and inefficient strategies and low production yields, which have decreased their competitiveness with fossil-based alternatives. The aim of the presented review is to provide a survey of past and current strategies used to achieve a sustainable conversion of biomass to platform chemicals. This review provides an overview of the chemicals obtained, based on the major components of lignocellulosic biomass, sugars, and lignin. First, important platform chemicals derived from the catalytic conversion of biomass were outlined. Later, the targeted chemicals that can be potentially manufactured from the starting or platform materials were discussed in detail. Despite significant advances, however, low yields, complex multistep synthesis processes, difficulties in purification, high costs, and the deactivation of catalysts are still hurdles for large-scale competitive biorefineries. These challenges could be overcome by single-step catalytic conversions using highly efficient and selective catalysts and exploring purification and separation technologies.
Is China’s Energy Supply Sustainable? New Research Model Based on the Exponential Smoothing and GM(1,1) Methods
Authors: Li Pin , Zhang Jinsuo
Published: January 2019

Energy supply sustainability is an important issue in the field of energy security. To successfully achieve the goals of sustainable economic and social development and to implement the “Paris Agreement”, we need to accurately evaluate and predict the energy supply sustainability of countries or regions. However, it is very difficult to evaluate and predict energy supply sustainability, because it belongs to a complex multi-attribute decision-making problem. This paper proffered a new definition of the energy supply sustainability in China and put forward sixteen indicators for it from the four dimensions of energy availability, economic sustainability, environmental sustainability and technical sustainability. First, the energy supply sustainability index (ESSI) was quantified by a comprehensive evaluation method. Secondly, based on the exponential smoothing and GM(1,1) prediction models, two ideas were put forward to predict the sustainable level of China’s energy supply, enriching the theoretical study of energy security prediction. The study found that: (1) China’s energy supply sustainability index changes dynamically; it has an asymmetric “W” trend from 2000 to 2016. The energy supply sustainability level of China is low; it cannot satisfy the Chinese people’s need for high-quality eco-energy products or the needs of social sustainable development. The three indicators of reserve and production ratio, production diversity and clean power generation are very important to China’s energy supply sustainability. (2) Referring to the accuracy criteria, the Mean absolute percentage error (MAPE) of the Exponential smoothing-GM(1,1) hybrid model for forecasting China’s energy supply sustainability is only 2%, and the Root mean square error (RMSE) is 0.0278; therefore, it is suitable for use in the forecasting of the energy supply sustainability level in China. (3) In the short term, from 2017 to 2020, many unsustainable factors remain within China’s energy supply, and the sustainable level is level II. In the long term, the sustainable level of China’s energy supply will be greatly improved and will increase to 0.8765 by 2030, attaining a sustainable level. However, China remains far behind other countries, with high levels of energy sustainability and energy security in the world.
Emission Reduction and Energy Performance Improvement with Different Regional Treatment Intensity in China
Authors: Teng Xiangyu , Lu Danting , Chiu Yung-ho
Published: January 2019

China’s industrial sector, which has a significant position in the world, is the main sector of China’s energy consumption and waste gas emission. China’s government has promulgated a Guiding Opinion, setting key regions to establish an emission reduction target of air pollutants during the 12th five year plan (2011–2015). Thus, there is a different regional treatment of industrial waste gas in China. This study considers the waste gas treatment expenditure as a new input and employs the non-radial directional distance function in the framework of the meta-frontier model to investigate the energy and emission reduction performance of China’s industrial sectors. The study is aimed at finding a significant and expanded technical gap between key and non-key regions in the energy and emission reduction efficiencies. The empirical result presents an effective method to improve the performance by increasing the emission treatment expenditure to reduce emissions.
Evaluation of Alternatives for Improving the Thermal Resistance of Window Glazing Edges
Authors: Park Sihyun , Song Seung-Yeong
Published: January 2019

To reduce condensation and ensure occupant comfort, the Korean Design Standard for Preventing Condensation in Apartment Buildings was enacted in 2014. However, glazing edges remain vulnerable to condensation. Because this design standard is recent, few window products satisfy the condensation resistance requirement for glazing edges, especially in the coldest region, and there have been limited investigations on improvement measures. This study evaluates and verifies various treatments for improving the glazing edge thermal resistance of double-glazed four-track horizontal sliding windows to reduce condensation risk and satisfy the design standard. Three-dimensional heat transfer simulations are performed for each alternative to obtain the surface temperature and temperature difference ratio (TDR) for the bottom edge of the glazing. The U-factors of the alternatives satisfying the required TDR for the coldest region are simulated, and the effects of increased local thermal resistance in the glazing edge on the U-factor of the window are analyzed. Mock-up tests are performed on the most economical and best-performing alternatives satisfying the coldest region TDR, and the TDRs and U-factors from the simulations and mock-up tests are compared to verify the performance of the most economical alternative. Insulating spacers, frame extensions, and low-emissivity coatings are effective in various cases.
Acknowledgement to Reviewers of Epigenomes in 2018
Authors:   Epigenomes Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Carbon Footprint Analysis of Bamboo Scrimber Flooring—Implications for Carbon Sequestration of Bamboo Forests and Its Products
Authors: Gu Lei , Zhou Yufeng , Mei Tingting , Zhou Guomo , Xu Lin
Published: January 2019

Bamboo forest is characterized by large carbon sequestration capability and it plays an important role in mitigating climate change and global carbon cycling. Previous studies have mostly focused on carbon cycling and carbon stocks in bamboo forest ecosystems, whereas the carbon footprints of bamboo products have not received attention. China is the largest exporting country of bamboo flooring in the world. Estimating the carbon footprint of bamboo flooring is of essential importance for the involved enterprises and consumers to evaluate their own carbon footprints. In this study, we investigated the production processes of bamboo scrimber flooring for outdoor use, a typical bamboo flooring in China. Based on business-to-business (B2B) evaluation method, we assessed CO2 emission and carbon transfer ratio in each step of the production process, including transporting bamboo culms and producing and packing the products. We found that to produce 1 m3 of bamboo scrimber flooring, direct carbon emissions from fossil fuels during transporting raw materials/semi-finished products, from power consumptions during production, and indirect emissions from applying additives were 30.94 kg CO2 eq, 143.37 kg CO2 eq, and 78.34 kg CO2 eq, respectively. After subtracting the 267.54 kg CO2 eq carbon stocks in the product from the 252.65 kg CO2 eq carbon emissions derived within the defined boundary, we found that the carbon footprint of 1 m3 bamboo scrimber flooring was −14.89 kg CO2 eq. Our results indicated that the bamboo scrimber flooring is a negative carbon-emission product. Finally, we discussed factors that influence the carbon footprint of the bamboo flooring and gave suggestions on carbon emission reduction during production processes. This study provided a scientific basis for estimating carbon stocks and carbon footprints of bamboo products and further expanded knowledge on carbon cycling and lifespan of carbon in the bamboo forest ecosystem.
DNA Barcoding Analysis and Phylogenetic Relation of Mangroves in Guangdong Province, China
Authors: Wu Feng , Li Mei , Liao Baowen , Shi Xin , Xu Yong
Published: January 2019

Mangroves are distributed in the transition zone between sea and land, mostly in tropical and subtropical areas. They provide important ecosystem services and are therefore economically valuable. DNA barcoding is a useful tool for species identification and phylogenetic reconstruction. To evaluate the effectiveness of DNA barcoding in identifying mangrove species, we sampled 135 individuals representing 23 species, 22 genera, and 17 families from Zhanjiang, Shenzhen, Huizhou, and Shantou in the Guangdong province, China. We tested the universality of four DNA barcodes, namely rbcL, matK, trnH-psbA, and the internal transcribed spacer of nuclear ribosomal DNA (ITS), and examined their efficacy for species identification and the phylogenetic reconstruction of mangroves. The success rates for PCR amplification of rbcL, matK, trnH-psbA, and ITS were 100%, 80.29% ± 8.48%, 99.38% ± 1.25%, and 97.18% ± 3.25%, respectively, and the rates of DNA sequencing were 100%, 75.04% ± 6.26%, 94.57% ± 5.06%, and 83.35% ± 4.05%, respectively. These results suggest that both rbcL and trnH–psbA are universal in mangrove species from the Guangdong province. The highest success rate for species identification was 84.48% ± 12.09% with trnH-psbA, followed by rbcL (82.16% ± 9.68%), ITS (66.48% ± 5.97%), and matK (65.09% ± 6.00%), which increased to 91.25% ± 9.78% with the addition of rbcL. Additionally, the identification rate of mangroves was not significantly different between rbcL + trnH-psbA and other random fragment combinations. In conclusion, rbcL and trnH-psbA were the most suitable DNA barcode fragments for species identification in mangrove plants. When the phylogenetic relationships were constructed with random fragment combinations, the optimal evolutionary tree with high supporting values (86.33% ± 4.16%) was established using the combination of matK + rbcL + trnH-psbA + ITS in mangroves. In total, the 476 newly acquired sequences in this study lay the foundation for a DNA barcode database of mangroves.
Genetic Variation of Growth Traits and Genotype-by-Environment Interactions in Clones of Catalpa bungei and Catalpa fargesii f. duclouxii
Authors: Xiao Yao , Ma Wenjun , Lu Nan , Wang Zhi , Wang Nan , Zhai Wenji , Kong Lisheng , Qu Guanzheng , Wang Qiuxia , Wang Junhui
Published: January 2019

Clones of Catalpa bungei and Catalpa fargesii f. duclouxii were studied over several years in central China to explore genetic variation in growth traits and to identify clones of high wood yield and high stability. The genetic parameters for height, diameter at breast height (DBH), and stem volume of clones, were estimated. The effect of clone × year on the increment of stem volume in the two species was analyzed by genotype and genotype × environment (GGE) biplot methods. Significant differences in growth traits among clones and between species were found. The growth of C. bungei exceeded that of C. fargesii f. duclouxii after 4 years. Furthermore, from the 5th year, the repeatability and genetic variation coefficient (GCV) of the C. bungei clones were higher than those of the C. fargesii f. duclouxii clones in most cases. The phenotypic variation coefficient (PCV) of the C. fargesii f. duclouxii clones was significantly lower than that of the C. bungei clones. The repeatability of stem volume was intermediate or high in the two species. ANOVA revealed significant effects of the clone by year interaction in these two species. GGE biplot analysis revealed that wood yield and stability were largely independent in C. bungei; clones 22-03, 19-27, and 20-01 were the optimal clones in this species. In contrast, the optimal clones 63 and 128 of C. fargesii f. duclouxii combined the desired characteristics of high yield and high stability. In conclusion, our results indicated that the height and stem volume of C. bungei was under strong genetic control, whereas that of C. fargesii f. duclouxii was influenced by the environment more than by genetic effects. Genetic improvement by clone selection can be expected to be effective, as the repeatability of stem volume was high. Francis and Kannenberg’s method and GGE biplot analysis were used in combination to evaluate the clones. C. bungei clone 22-03 and C. fargesii f. duclouxii clones 63 and 128 were identified as the optimal clones, which exhibited both a high increment of stem volume and high stability.
Associations between Road Density, Urban Forest Landscapes, and Structural-Taxonomic Attributes in Northeastern China: Decoupling and Implications
Authors: Yang Yanbo , Lv Hailiang , Fu Yujie , He Xingyuan , Wang Wenjie
Published: January 2019

A better understanding on the associations between road density (RD), urban forest structural-taxonomic attributes, and landscape metrics is vital for forest ecological service evaluations and suitable management in sprawling urban areas with increasing road networks. We chose Harbin, a fast growing provincial capital city in northeast China, as a case study to address this issue. We utilized ArcGIS software (Esri, version 10.0; Redlands, CA, USA) and FRAGSTATS (V4.2.589) to digitize GF-1 images (Gaofen No.1 remote sensing images) to acquire road net characteristic information and landscape metrics of urban forests in Harbin. Together with forest structural-taxonomic attributes from a stratified random sampling survey, statistical methods such as an analysis of variance, a regression analysis, and a redundancy analysis were used to determine the road-dependent differences and to decouple the associations between them. The results indicated that road area percentages, road length/imperious surface area (ISA) ratios, road area/ISA ratios, and road cross-points sharply increased from low to heavy RD areas. This road intensification was strongly associated with increased urban forest area, patch density, and diverse patch shapes; smaller tree sizes, lower tree densities, and diverse tree species compositions were generally observed. Redundancy-based variation partitioning showed that part of the variations in structural-taxonomic attributes of forests could be explained by road intensity characteristics. In low RD (0–1.5 km/km2) regions, the road characteristics significantly affected forest characteristics (Shannon Wiener diversity index, species richness, and evenness index); however, such associations weakened with increasing forest landscape-related associations in medium to heavy RD (1.5–6 km/km2) regions. Our findings highlighted that road development is strongly associated with forest characteristics in Harbin city, and RD-dependent forest landscape regulating management could favor the maximization of forest ecological services that are related to structural and species identities.
Acknowledgement to Reviewers of Future Internet in 2018
Authors:   Future Internet Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Modelling of the Radiant Heat Flux and Rate of Spread of Wildfire within the Urban Environment
Authors: Penney Greg , Richardson Steven
Published: January 2019

One approach to increase community resilience to wildfire impacts is the enhancement of residential construction standards in an effort to provide protective shelters for families within their own homes. Current wildfire models reviewed in this study assume fire growth is unrestricted by vegetation fuel bed geometry; the head fire has attained a quasi-steady rate of spread; and the shielding effects of urban development are ignored. As a result, radiant heat flux may be significantly overestimated for small vegetation fires in road reserves, urban parklands, and similar scenarios. This paper proposes two new models to address this issue, and utilises two case studies for comparison against existing approaches. The findings are significant as this is the first study to analyse these factors from a fire engineering perspective, and to demonstrate that the use of landscape scale or siege wildfire models may not be appropriate within the urban context. The development of enhanced wildfire models will have a significant impact on town planning and construction practices in areas prone to wildfires, as well as firefighting suppression efforts when these events occur.
Acknowledgement to Reviewers of Fire in 2018
Authors:   Fire Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
On Contraction of Three-Dimensional Multiple Shear Mechanism Model for Evaluation of Large Scale Liquefaction Using High Performance Computing
Authors: Hotta Wataru , Suzuki Shunichi , Hori Muneo
Published: January 2019

For more reliable evaluation of liquefaction, an analysis model of higher fidelity should be used even though it requires more numerical computation. We developed a parallel finite element method (FEM), implemented with the non-linear multiple shear mechanism model. A bottleneck experienced when implementing the model is the use of vast amounts of CPU memory for material state parameters. We succeeded in drastically reducing the computation requirements of the model by suitably approximating the formulation of the model. An analysis model of high fidelity was constructed for a soil-structure system, and the model was analyzed by using the developed parallel FEM on a parallel computer. The amount of required CPU memory was reduced. The computation time was reduced as well, and the practical applicability of the developed parallel FEM is demonstrated.
Integrating Non-Destructive Testing, Laser Scanning, and Numerical Modeling for Damage Assessment: The Room of the Elements
Authors: Napolitano Rebecca , Hess Michael , Glisic Branko
Published: January 2019

For preservation efforts and stability assessment of historic structures it is imperative to understand the extent of existing damages and possible modes for how they could have occurred. The aim of this work is to illustrate the importance of integrating documentation, non-destructive testing, and numerical modeling for damage assessment of heritage structures. In particular, this work explores the synthesis of these techniques on a plastered masonry wall in Palazzo Vecchio. Laser scanning was used to capture the geometry of the wall while terrestrial photogrammetry and high-resolution images were used to document the magnitude of cracking in the plaster layer. High resolution thermal images were used to document the distribution of stones and additional cracks not visible through the plaster layer. The results of documentation and non-destructive testing were used to generate an as-built model for structural analysis. Finite distinct element modeling was used to simulate the response of the wall to a series of loading conditions. By comparing the results of simulation to existing crack patterns, theories for how the damage occurred were generated.
Acknowledgement to Reviewers of Hydrology in 2018
Authors:   Hydrology Editorial Office
Published: January 2019

Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Estimation of the Spatial Suitability of Winter Tourism Destinations Based on Copula Functions
Authors: Cai Weiying , Di Hui , Liu Xingpeng
Published: January 2019

Climate and weather are important factors that determine winter tourism destinations and snow resources and temperature affect the income of the winter tourism industry. Against the background of climate change, abnormal fluctuations in climate elements bring a series of challenges for winter tourism and cause potential losses to the tourism industry. To effectively assess and plan winter tourism destinations, this study establishes the snow abundance and meteorological suitability indices from snow resource and weather conditions to express winter tourism resources, respectively. The coupling relationship of the two indices was used to analyze the spatial suitability of winter tourism destinations based on the copula function. By case analysis, it was found that the Frank copula one is the best fitting function for winter tourism suitability analysis. The Yushu–Jiutai–Yitong–Dongliao line is the boundary of spatial suitability in the study area. The eastern areas of the boundary have great potential for winter tourism and could strive to develop ice-snow projects, whereas the western regions are relatively weak. This study has guiding significance for winter tourism destination development and resource spatial layout.
A Non-Liner Decision Model for Green Crowdfunding Project Success: Evidence from China
Authors: Yang Jinbi , Liu Libo , Yin Chunxiao
Published: January 2019

Green growth and environmental sustainability have become a significant focus in today’s living. We believe that green crowdfunding project can make an important contribution to the creation and evaluation of environmental systems. This study aims to investigate the determinants of green crowdfunding project success. Contrary to the linear relationship in previous literature, we propose a non-liner decision model that includes three determinants, funds pledge, goal setting, and project duration to predict project success. The quantitative approach method was employed. We crawl data on 1389 green crowdfunding projects from Tencent Lejuan, a crowdfunding platform in China. By using ordinary least square method to conduct data analysis, we find that the effect of goal setting on project success is non-linear as low and moderate levels of goal setting are not always likely to have a significant impact on project success, but the presence of a higher goal is likely to exert a positive effect on project success. Moreover, results show that the effect of project duration on project success is non-linear as short and moderate levels of duration is not always certain to have significant impact on project success, but the presence of a long duration is likely to exert a positive effect on project success. This study has implications for fund-seekers for green crowdfunding projects and managers of crowdfunding platforms.
Causes of Delays during Housing Adaptation for Healthy Aging in the UK
Authors: Zhou Wusi , Oyegoke Adekunle Sabitu , Sun Ming
Published: January 2019

Housing adaptation is a rehabilitation intervention that removes environmental barriers to help older people accommodate changing needs and age in place. In the UK, funding application for home adaptations to local authorities is subject to several procedural steps, including referral, allocation, assessment, funding and installation. The five stages need to complete in a sequential manner, often cause long delays. This study aims to investigate the timelines across these key stages of the adaptation process and examine the main causes of delays in current practice. A mixed-methods research strategy was employed. A questionnaire survey was first undertaken with all 378 local authorities in England, Scotland and Wales; it was followed by 5 semi-structured interviews and 1 focus group meeting with selected service providers, and 2 case studies of service users. The results showed that the average length of time taken to complete the whole process is relatively long, with the longest waiting time being observed at the funding decision stage. Delays were found in each of the key stages. Main causes of delay include insufficient resources, lack of joint work, legal requirements, shortage of competent contractors and the client’s decisions. These issues need to be addressed in order to improve the efficiency and effectiveness of future housing adaptation practice.
Are Sedentary Behaviors Associated with Sleep Duration? A Cross-Sectional Case from Croatia
Authors: Štefan Lovro , Horvatin Maja , Baić Mario
Published: January 2019

Although both sedentary behavior and sleep duration are risk factors for obesity, little evidence is provided regarding their mutual associations in young adults, who are at extreme risk of spending more time sitting and having irregular sleeping hygiene. Thus, the main purpose of the present study was to explore the associations between different sedentary behaviors and sleep duration. In this cross-sectional study, we recruited 2100 university students from the city of Zagreb. To assess sedentary behaviors and sleep duration, we used validated questionnaires. The associations between sedentary behaviors and sleep duration were analyzed using logistic regression analyses and were adjusted for sex, body-mass index, self-rated health, socioeconomic status, smoking status, binge drinking, psychological distress and chronic disease/s. Participants being in the third (OR = 1.45; 95% CI 1.05 to 2.01) and fourth (OR = 1.82; 95% CI 1.26 to 2.61) quartile of the screen-time, in the third (OR = 1.49; 95% CI 1.05 to 2.13) and fourth (OR = 1.72; 95% CI 1.22 to 2.42) quartile of the leisure-time sedentary behavior and in the fourth (OR = 1.45; 95% CI 1.04 to 2.02) quartile of the total sedentary behavior were more likely to be ‘short’ sleepers (<7 h). Also, participants being in the third (OR = 1.63; 95% CI 1.16 to 2.30) and fourth (OR = 1.93; 95% CI 1.33 to 2.81) quartile of the screen-time and in the fourth (OR = 1.45; 95% CI 1.05 to 2.00) quartile of the total sedentary behavior were more likely to be ‘long’ sleepers (>9 h). Our study shows that sedentary behavior in screen-time and total sedentary behavior are associated with both ‘short’ and ‘long’ sleep duration.
Investigation of the Synergistic Toxicity of Binary Mixtures of Pesticides and Pharmaceuticals on Aliivibrio fischeri in Major River Basins in South Korea
Authors: Baek In-Hyuk , Kim Youngjun , Baik Seungyun , Kim Jongwoon
Published: January 2019

This work introduces the potential synergistic toxicity of binary mixtures of pesticides and pharmaceuticals, which have been detected in substantial amounts in major river basins in South Korea. Different dose-response curve functions were employed in each experimental toxicity dataset for Aliivibrio fischeri. We tested the toxicity of 30 binary mixtures at two effect concentrations: high effect concentration [EC50] and low effect concentration (EC10) ranges. Thus, the toxicological interactions were evaluated at 60 effected concentration data points in total and based on model deviation ratios (MDRs) between predicted and observed toxicity values (e.g., three types of combined effects: synergistic (MDR > 2), additive (0.5 ≤ MDR ≤ 2), and antagonistic (MDR < 0.5)). From the 60 data points, MDRs could not be applied to 17 points, since their toxicities could not be measured. The result showed 48%-additive (n = 20), 40%-antagonistic (n = 17), and 12%-synergistic (n = 6) toxicity effects from 43 binaries (excluding the 17 combinations without MDRs). In this study, EC10 ratio mixtures at a low overall effect range showed a general tendency to have more synergistic effects than the EC50 ratio mixtures at a high effect range. We also found an inversion phenomenon, which detected three binaries of the combination of synergism at low concentrations and additive antagonism at high concentrations.
Human Germ Cell Tumors are Developmental Cancers: Impact of Epigenetics on Pathobiology and Clinic
Authors: Lobo João , Gillis Ad J. M. , Jerónimo Carmen , Henrique Rui , Looijenga Leendert H. J.
Published: January 2019

Current (high throughput omics-based) data support the model that human (malignant) germ cell tumors are not initiated by somatic mutations, but, instead through a defined locked epigenetic status, representative of their cell of origin. This elegantly explains the role of both genetic susceptibility as well as environmental factors in the pathogenesis, referred to as ‘genvironment’. Moreover, it could also explain various epidemiological findings, including the rising incidence of this type of cancer in Western societies. In addition, it allows for identification of clinically relevant and informative biomarkers both for diagnosis and follow-up of individual patients. The current status of these findings will be discussed, including the use of high throughput DNA methylation profiling for determination of differentially methylated regions (DMRs) as well as chromosomal copy number variation (CNV). Finally, the potential value of methylation-specific tumor DNA fragments (i.e., XIST promotor) as well as embryonic microRNAs as molecular biomarkers for cancer detection in liquid biopsies will be presented.
Activation of Sirtuin 3 and Maintenance of Mitochondrial Integrity by N-Acetylcysteine Protects Against Bisphenol A-Induced Kidney and Liver Toxicity in Rats
Authors: Peerapanyasut Wachirasek , Kobroob Anongporn , Palee Siripong , Chattipakorn Nipon , Wongmekiat Orawan
Published: January 2019

Mitochondrial impairment ensuing from oxidative imbalance is related to adverse consequences of bisphenol A (BPA), a globally utilized industrial chemical. Recent evidence reveals sirtuin 3 (SIRT3) as a key regulator of mitochondrial homeostasis; however, its role in BPA toxicity remains unidentified. This study explored the potential benefits of N-acetylcysteine (NAC), an effective antioxidant, against BPA toxicity in the kidney and liver, and examined whether SIRT3 was involved in this condition. Male Wistar rats were fed with vehicle, BPA (5, 50 mg/kg), BPA (50 mg/kg) plus NAC (100 mg/kg) and were evaluated after 5 weeks. NAC treatment significantly diminished BPA-induced kidney and liver functional disorders, histopathological alterations, oxidative stress, and apoptosis. The increased mitochondrial reactive oxygen species, the disrupted membrane potential, the swelling, and the impaired mitochondrial fission caused by BPA were also mitigated upon concurrent treatment with NAC. The benefits of NAC were associated with enhanced AMPK-PGC-1α-SIRT3 signaling protein expressions, which led to decreased acetylation of superoxide dismutase 2 (SOD2) and increased expression of mitochondrial antioxidant manganese superoxide dismutase (MnSOD). The findings demonstrate the efficacy of NAC in protecting BPA-induced kidney and liver injury, which, in part, is mediated by activating SIRT3 and improving mitochondrial function, dynamics, and oxidative imbalance.