bluuebunny/crossref_metadata_2025 huggingface dataset:
The Accuracy of Precipitation Forecasts at Timescales of 1–15 Days in the Volta River Basin
Authors: Gebremichael Mekonnen , Yue Haowen , Nourani Vahid
Published: February 2022

Medium-range (1–15 day) precipitation forecasts are increasingly available from global weather models. This study presents evaluation of the Global Forecast System (GFS) for the Volta river basin in West Africa. The evaluation was performed using two satellite-gauge merged products: NASA’s Integrated Multi-satellitE Retrievals (IMERG) “Final Run” satellite-gauge merged rainfall observations, and the University of California Santa Barbara’s Climate Hazard’s group Infrared Precipitation with Stations (CHIRPS). The performance of GFS depends on the climate zone, with underestimation bias in the dry Sahel climate, overestimation bias in the wet Guinea Coastal climate, and relatively no bias in the moderately wet Savannah climate. Averaging rainfall over the watershed of the Akosombo dam (i.e., averaging across all three climate zones), the GFS forecast indicates low skill (Kling-Gupta Efficiency KGE = 0.42 to 0.48) for the daily, 1-day, lead GFS forecast, which deteriorates further as the lead time increases. A sharp decrease in KGE occurred between 6 to 10 days. Aggregating the forecasts over long timescales improves the accuracy of the GFS forecasts. On a 15-day accumulation timescale, GFS shows higher skills (KGE = 0.74 to 0.88).
The Influence of Underlying Land Cover on the Accuracy of MODIS C6.1 Aerosol Products—A Case Study over the Yangtze River Delta Region of China
Authors: Sun Kun , Gao Yang , Qi Bing , Yu Zhifeng
Published: February 2022

Due to the significant spatial variation of the performance of Moderate Resolution Imaging Spectrometer (MODIS) aerosol optical depth (AOD) retrievals, validation is very important for applications of MODIS AOD products at regional scales. This study presents a comparative analysis of Collection 6.1 MODIS AOD retrievals and ground measurements from five local sites and one Aerosol Robotic Network (AERONET) site in the Yangtze River Delta (YRD) region, which significantly complements the previous validation that utilized limited AERONET measurements. Generally, MODIS AOD retrievals showed a reasonable agreement with collocated ground measurements (R2 > 0.7), with 66% of Dark Target (DT) 10 km retrievals, 56% of Deep Blue (DB) 10 km retrievals, and 69% of DT 3 km retrievals falling within the expected error (EE = ±(0.05 + 0.2 × AOD)). Nevertheless, it was found that the DT AOD retrievals tended to be overestimated over urbanized and lakeside sites, while the DB AOD retrievals tended to be underestimated over all ground sites except for lakeside sites. Such patterns appeared to be linked with the systematic biases of the single-scattering albedo estimation in the AOD retrieval algorithms. Another significant finding of this study is that the uncertainties of the MODIS AOD retrievals were highly correlated with the land cover proportions of urbanized features and water (LCP_UW) in the surrounding region, especially for the DT products. An empirical correction method based on these correlations could substantially reduce the uncertainties of DT AOD products over high LCP_UW areas. The results not only highlight the significant impacts of both urban and water areas on the MODIS AOD retrieval algorithms but also create new possibilities to correct such impacts once the universal correlations between LCP_UW and the uncertainty measures are established.
An Improved Infrared and Visible Image Fusion Using an Adaptive Contrast Enhancement Method and Deep Learning Network with Transfer Learning
Authors: Bhutto Jameel Ahmed , Tian Lianfang , Du Qiliang , Sun Zhengzheng , Yu Lubin , Soomro Toufique Ahmed
Published: February 2022

Deep learning (DL) has achieved significant attention in the field of infrared (IR) and visible (VI) image fusion, and several attempts have been made to enhance the quality of the final fused image. It produces better results than conventional methods; however, the captured image cannot acquire useful information due to environments with poor lighting, fog, dense smoke, haze, and the noise generated by sensors. This paper proposes an adaptive fuzzy-based preprocessing enhancement method that automatically enhances the contrast of images with adaptive parameter calculation. The enhanced images are then decomposed into base and detail layers by anisotropic diffusion-based edge-preserving filters that remove noise while smoothing the edges. The detailed parts are fed into four convolutional layers of the VGG-19 network through transfer learning to extract features maps. These features maps are fused by multiple fusion strategies to obtain the final fused detailed layer. The base parts are fused by the PCA method to preserve the energy information. Experimental results reveal that our proposed method achieves state-of-the-art performance compared with existing fusion methods in a subjective evaluation through the visual experience of experts and statistical tests. Moreover, the objective assessment parameters are conducted by various parameters (FMI, SSIMa, API, EN, QFAB, and NFAB) which were used in the comparison method. The proposed method achieves 0.2651 to 0.3951, 0.5827 to 0.8469, 56.3710 to 71.9081, 4.0117 to 7.9907, and 0.6538 to 0.8727 gain for FMI, SSIMa, API, EN, and QFAB, respectively. At the same time, the proposed method has more noise reduction (0.3049 to 0.0021) that further justifies the efficacy of the proposed method than conventional methods.
The Accuracy and Consistency of 3D Elevation Program Data: A Systematic Analysis
Authors: Stoker Jason , Miller Barry
Published: February 2022

The 3D Elevation Program (3DEP) has created partnership opportunities to increase the collection of high-resolution elevation data across the United States, eventually leading to complete coverage of high-resolution, three-dimensional (3D) information from light detection and ranging (lidar) data across the entire country (interferometric synthetic aperture radar in Alaska). While 3DEP data are collected at different times and by varying producers, the assumption is that the use of the 3DEP Lidar Base Specification will provide standardized and consistent data across data collections. Another assumption is that the integration of lidar data into the seamless digital elevation models increases the accuracy of the derived products. This study tests these assumptions and updates some of the accuracy metrics that were done on previous versions of the standard products.
Turbulence Parameters in the Troposphere—Lower Stratosphere Observed by Beijing MST Radar
Authors: Chen Ze , Tian Yufang , Lü Daren
Published: February 2022

Based on three years of data observed by Beijing MST radar between 2012 and 2014, this study gives the distribution characteristics of the turbulence energy dissipation rate ε and the vertical turbulence diffusion coefficient Kz in the troposphere–lower stratosphere over Beijing based on the spectral width method. Additionally, from the perspective of atmospheric stability expressed by the Brunt–Väisälä frequency N and the gradient Richardson number Ri, the seasonal variations of turbulence parameters at different heights are analyzed. The results show that ε (Kz) is distributed in the range of 10−4 to 10−1.5 m2 s−3 (100 to 101 m2 s−1), with median values of 10−3 to 10−2.5 m2 s−3 (100.4 to 100.75 m2 s−1). In the height range of −1 km to about +1 km from the tropopause, the profiles of ε have no noticeable seasonal difference from October to next May, and ε increases sharply with the slope of linear regression ∇log(ε)/∇h = 0.25 (m2 s−3) km−1. The seasonal variation of turbulence parameters has noticeable differences at different atmospheric layers. Furthermore, the atmospheric static/dynamic stability and turbulence intensity are the influencing factors of turbulence parameters. From the tropopause to 14 km, the values of ε and N both have a peak from October to next May, and this peak layer disappears from July to August. Within the range of 2–4 km from the ground, Kz and the frequency of Ri < 0.25 have a significant positive correlation, with a Pearson correlation coefficient greater than 0.5, and both have large value layers in March to May and September to October. The turbulence intensity above 15 km is likely the main factor affecting the turbulence dissipation rate and vertical turbulence diffusion coefficient.
A Preliminary Study for Reference RF Coil at 11.7 T MRI: Based on Electromagnetic Field Simulation of Hybrid-BC RF Coil According to Diameter and Length at 3.0, 7.0 and 11.7 T
Authors: Seo Jeung-Hoon , Chung Jun-Young
Published: February 2022

Magnetic resonance imaging (MRI) systems must undergo quantitative evaluation through daily and periodic performance assessments. In general, the reference or standard radiofrequency (RF) coils for these performance assessments of 1.5 to 7.0 T MRI systems have been low-pass-type birdcage (LP-BC) RF coils. However, LP-BC RF coils are inappropriate for use as reference RF coils because of their relatively lower magnetic field (B1-field) sensitivity than other types of BC RF coils, especially in ultrahigh-field (UHF) MRI systems above 3.0 T. Herein, we propose a hybrid-type BC (Hybrid-BC) RF coil as a reference RF coil with improved B1-field sensitivity in UHF MRI system and applied it to an 11.7 T MRI system. An electromagnetic field (EM-field) analysis on the Hybrid-BC RF coil was performed to provide the proper dimensions for its use as a reference RF coil. Commercial finite difference time-domain program was used in EM-field simulation, and home-made analysis programs were used in analysis. The optimal specifications of the proposed Hybrid-BC RF coils for them to qualify as reference RF coils are proposed based on their B1+-field sensitivity under unnormalized conditions, as well as by considering their B1+-field uniformity and RF safety under normalized conditions.
High-Precision Low-Temperature Drift LDO Regulator Tailored for Time-Domain Temperature Sensors
Authors: Răducan Cristian , Neag Marius , Grăjdeanu Alina , Țopa Marina , Negoiță Andrei
Published: February 2022

This paper proposes a high-precision LDO with low-temperature drift suitable for sensitive time-domain temperature sensors. Its topology is based on multiple feedback loops and a novel approach to frequency compensation, that allows the LDO to maintain a large DC gain while handling capacitive loads that vary over a wide range. The key design constraints are derived by using a simplified, yet intuitive and effective, small-signal analysis devised for LDOs with multiple feedback loops. Simulation and measurement results are presented for implementation in a standard 130 nm CMOS process: the LDO outputs a stable 1 V voltage, when the input voltage varies between 1.25 V to 1.5 V, the load current between 0 and 100 mA, and the load capacitor between zero and 400 pF. It exhibits a DC load regulation of 1 µV/mA, a 288 µV output offset with a standard deviation of 9.5 mV. A key feature for the envisaged application is the very low thermal drift of the output offset: only 14.4 mV across the temperature range of −40 °C to +150 °C. Overall, the LDO output voltage stays within +/−3.5% of the nominal DC value over the entire line voltage, load, and temperature ranges, without trimming. The LDO requires only 1.4µA quiescent current, yet it provides excellent responses to load transients. The output voltage undershoot and overshoot caused by the load current jumping between 0 and 100 mA in 1 µs are: 10%/22% for CL = 0 and 12%/16% for CL = 400 pF, respectively. A comparative analysis against seven LDOs published in the last decade, designed for similar levels of supply voltage and output voltage and current, shows that the LDO presented here is the best option for supplying sensitive time-domain temperature sensors. The smallest thermal drift of the output offset, smaller than +/−15 mV, that is, 6.7 times smaller than its closest competitor, and the best overall performance when PSR up to 1 kHz, was considered.
Effect of Battery-Electric and Plug-In Hybrid Electric Vehicles on PM2.5 Emissions in 29 European Countries
Authors: Kazemzadeh Emad , Koengkan Matheus , Fuinhas José Alberto
Published: February 2022

The contribution of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) to mitigating/reducing fine particulate matter (PM2.5) emissions was researched through a panel of 29 European countries from 2010 to 2019, using the econometric technique of method of moments quantile regression (MM-QR). This research is innovative by connecting the increasing use of electric vehicles with PM2.5 emissions and using the MM-QR to explore this relationship. Two models were estimated to analyse their contribution to reducing PM2.5 in European countries. The nonlinearity of the models were confirmed. The statistical significance of the variables is strong for the upper quantiles (75th and 90th), resulting from the effectiveness of European policies to improve the environment. Electric vehicles (BEVs and PHEVs), economic growth, and urbanisation reduce the PM2.5 problem, but energy intensity and fossil fuel consumption aggravate it. This research sheds light on how policymakers and governments can design proposals to encourage electric vehicle use in European countries. To achieve the long-term climate neutral strategy by 2050, it is imperative to implement effective policies to reduce the consumption of fossil fuels and promote the adoption of electric vehicles using renewable energy sources.
Carbon Emission Efficiency Network: Evolutionary Game and Sensitivity Analysis between Differentiated Efficiency Groups and Local Governments
Authors: Zhang Renjie , Tai Hsingwei , Cheng Kuotai , Dong Huizhong , Liu Wenhui , Hou Junjie
Published: February 2022

With its proposal of the “double carbon” (peak carbon dioxide emissions and carbon neutralization) goal, China has entered a new stage in creating an ecological civilization and achieving sustainable development. Based on the formation and evolution mechanism of the carbon emission efficiency network, in this study, a trilateral evolutionary game model—including efficiency groups (high- and low-efficiency groups) and local governments—was constructed, in an attempt to discuss the conditions needed for different players and trilateral interconnected systems to implement balanced and stable strategies. Furthermore, the sensitivity of the participants’ evolutionary trajectories toward factors such as the initial strategy ratio, transition cost, and network capital were tested via a system simulation. The main conclusions were as follows: (1) Efficiency groups form a virtuous circle when the initial proportion of the participants’ strategies reaches a certain threshold, and converge into a stable “win–win” state. Under these circumstances, high-efficiency groups tend to give full play to their efficiency advantages in terms of carbon emission reduction and green development, while low-efficiency groups tend to choose green transformation and accept the spillover effect from high-efficiency groups. (2) When efficiency groups achieve a “win–win” state or form good self-management, local governments move from active supervision to a passive supervision strategy in order to reduce supervision costs. (3) While different initial strategy proportions do not affect the stable convergence point of the evolutionary system, they have a differentiated impact on the convergence speed of the players. Under the condition of a low initial strategy ratio, transformation costs can reduce the green transformation enthusiasm of inefficient groups, while network capital can enhance the green transformation willingness of inefficient groups.
A Framework to Evaluate the Social Life Cycle Impact of Products under the Circular Economy Thinking
Authors: Tsalis Thomas , Stefanakis Alexandros I. , Nikolaou Ioannis
Published: February 2022

Today, the circular economy is regarded as a promising alternative for modern economies to preserve “virgin” natural resources for future generations by valorizing waste materials. The concept is also used to promote the goals of sustainable development, where, apart from the environmental dimension, the economic and social dimensions are also integrated. So far, the largest part of the related research has emphasized the environmental and economic dimensions, while little attention has been paid to the social dimension of circular economy. Thus, this paper develops a framework to evaluate the social impacts of circular products and materials throughout their life cycle, which is based on social life thinking, circular economy principles and strategies and social responsibility principles. Moreover, computational examples are presented to show the functionality and applicability of the proposed framework. Finally, critical points for future research are pinpointed in order to assist scholars in applying and improving such frameworks through case studies, helping them to better understand the social aspects of circular economy.
An Empirical Approach Analyzing the Socioeconomic Sustainability of the International Sugarcane Trade
Authors: Machado Ricardo Luiz , da Cruz Thiago Vizine
Published: February 2022

The rapport between international trade and income inequality came to light after the Heckscher–Ohlin/Stolper–Samuelson theorem (HOS). Nevertheless, researchers have not concluded whether the HOS theory truly reflects reality. Even though the main focus provided by the HOS theory is on internal inequality (existing inside the country among its population), another way of analyzing the HOS theory is through income inequality among countries. This last possibility is also called income convergence. This work contributes to the topic of researching the relationship between the export of sugarcane-derived products and income to verify the income convergence effect. The cultivation of sugarcane is a relevant activity for many developing countries, including Brazil. In addition, no developed country is listed among the eight biggest sugarcane producers, which indicates that as a developing country product, it would be possible to analyze the relationship among the variables in a broader sense. The results obtained in the research indicate that the impact of the export of sugarcane products on income is minimal. Although positive, it is only perceived over time. Due to the characteristics of this research, which involves performing an analysis involving green production, green energy, and income inequality, this study is related to the seventh, eighth, and tenth United Nations’ SDG goals.
Catalytic Ozonation of the Secondary Effluents from the Largest Chinese Petrochemical Wastewater Treatment Plant—A Stability Assessment
Authors: Zhang Siyu , Wang Hao , Zhou Yuexi , Kamali Mohammadreza , He Xuwen , Khalaj Mohammadreza , Xia Yu
Published: February 2022

Effluents discharged from petrochemical facilities are complex and composed of various types of highly toxic contaminants, which necessitates the development of sustainable treatment technologies. Stability is among the most important sustainability criteria of the wastewater treatment processes. In the present manuscript, the standard-reaching rate (η) index was used to evaluate the stability of the catalytic ozonation process for treating the secondary effluent from the petrochemical industry. A pilot-scale device was designed and implemented for catalytic ozonation. The effluents were taken from the secondary sedimentation tank of a petrochemical wastewater treatment plant in China. A commercially available γ-Al2O3 was used as the catalyst after a pre-treatment heating step. The catalyst was characterized using scanning electron microscopy. Three mathematical statistics indexes, discrete coefficient (Vσ), skewness coefficient (Cso), and range coefficient (VR), were used to analyze the results achieved from the catalytic ozonation process. Continuous operation of the pilot-scale device was monitored for 9 months under an ozone concentration of 36 mg/L and the contact oxidation time of 1 h. The results demonstrated that the stability evaluation grades of chemical oxygen demand (COD) and suspended solids (SS) in the effluent of the catalytic ozonation system were both 3 and A, indicating that the process was relatively stable over a long period of application. The effluent COD compliance grade was also calculated as B, indicating that the effluent COD does not meet the standard and the process parameters need to be further optimized. When the reflux ratio is 150%, the removal rate of COD is the highest (38.2%) and the COD of effluent is 49.34 mg/L. Meanwhile, to enhance the efficiency and stability of the system, the ozone concentration and the two-stage aeration ratio are 40 mg/L and 4:1, respectively. Moreover, the presence of SS in the water of the catalytic ozonation system will result in the waste of ozone and reduce the utilization rate of ozone.
Optimal Design of a Hybrid Solar PV/BG-Powered Heterogeneous Network
Authors: Hossain Md. Sanwar , Islam Khondoker Ziaul , Alharbi Abdullah G. , Shafiullah Md , Islam Md. Rabiul , Fekih Afef
Published: February 2022

The increased penetration of renewable energy sources (RESs) along with the rise in demand for wireless communication had led to the need to deploy cellular base stations powered by locally accessible RESs. Moreover, networks powered by renewable energy sources have the ability to reduce the costs of generating electricity, as well as greenhouse gas emissions, thus maintaining the quality of service (QoS). This paper examines the techno-economic feasibility of developing grid-tied solar photovoltaic (PV)/biomass generator (BG)-powered heterogeneous networks in Bangladesh, taking into account the dynamic characteristics of RESs and traffic. To guarantee QoS, each macro and micro-base station is supplied through a hybrid solar PV/BG coupled with enough energy storage devices. In contrast, pico and femto BSs are powered through standalone solar PV units due to their smaller power rating. A hybrid optimization model for electric renewables (HOMER)-based optimization algorithm is considered to determine the optimum system architecture, economic and environmental analysis. MATLAB-based Monte-Carlo simulations are used to assess the system’s throughput and energy efficiency. A new weighted proportional-fair resource method is presented by trading power consumption and communication latency in non-real-time applications. Performance analysis of the proposed architecture confirmed its energy efficiency, economic soundness, reliability, and environmental friendliness. Additionally, the suggested method was shown to increase the battery life of the end devices.
Three Decades of Climate Policymaking in China: A View of Learning
Authors: Zhao Xiaofan , Qi Ye
Published: February 2022

Climate policymaking in China has gone through three major phases over the course of three decades. This paper applies the concept of policy learning to an analysis of what the Chinese government has learned about climate policymaking during this period. Our analysis shows that this thirty-year history of climate policymaking can be viewed as a conceptual learning process because the Chinese government has continuously adjusted the problem definition of climate change, redefined climate policy goals, and updated climate strategies. First, the Chinese leadership has redefined climate change from a scientific and diplomatic problem, to a developmental and strategic issue, and finally to an overarching grand strategy guiding national development in the next forty years. Second, the Chinese government has fundamentally redefined its climate policy goal from avoiding climate action so as to foster economic development to reinvigorating economic development through climate action. Third, the Chinese government has updated its climate change strategy from solely emphasizing climate mitigation to a more balanced consideration of mitigation and adaptation, and from state-dominant governance processes to more diversified governance processes that involve the participation of the corporate sector and a greater a role of the law.
Impact of Autonomous Vehicles on Roundabout Capacity
Authors: Boualam Othmane , Borsos Attila , Koren Csaba , Nagy Viktor
Published: February 2022

Studying the impact of AVs on our road infrastructure offers a lot of potential in the transportation domain; one of these issues is how capacity will be affected. This paper presents a contribution to this research area by investigating the impact of AVs on the capacity of single-lane roundabouts using a microsimulation model. For the development of the model, a roundabout situated in Győr (Hungary) was selected and field data on the roundabout geometric characteristics as well as traffic volumes were used. Simulations using Vissim were run for various scenarios based on varying input traffic volumes and market penetration rates of AVs to assess queue lengths. The highway capacity manual (HCM) roundabout model was used to estimate the capacity of the existing roundabout. Values of follow-up times and critical gaps were set to decreasing as the penetration rate of AVs increases. The results demonstrated that 20% and 40% AVs in the flow would increase leg capacities by about 10% and 20%, respectively. Furthermore, a reduction in excessive queue lengths was estimated and capacities and queue lengths were calculated by legs. It was found that these are highly influenced by the distribution of flows among legs, and the share of flows in various directions.
Effect of Zeolite on the Methane Production from Chicken Manure Leachate
Authors: Spyridonidis Apostolos , Vasiliadou Ioanna A. , Stamatelatou Katerina
Published: February 2022

This study demonstrates the leachate characteristics derived from bench-scale leach-bed reactors (LBRs) filled with chicken manure (CM) and zeolite. Zeolite was used to maintain the necessary porosity for the leaching process and to adsorb ammonia. Fresh water was added for leachate production and removed daily, in order to estimate the readily leachable organic and nitrogen matter of the CM. Tests were conducted at two ratios of zeolite to bed (10% and 3.5% v/v CMbed). Other operating parameters studied were the amount of water added in the LBRs, the leachate recirculation rate, and the hydraulic retention time (HRT). A control LBR with river pebbles at a similar size and ratio (10% v/v) with zeolite was also studied. Some experiments were repeated with CM, which had different characteristics. Compared to the control test, the LBR with zeolite at 10% v/v yielded leachate with less NH3 and a higher biochemical methane potential (BMP). However, free ΝH3 in the control experiment was below the inhibition threshold, proving that zeolite contributes to the higher BMP of leachate, and that this effect is not only due to NH3 adsorption.
Understanding Recent Trends in Global Sustainable Development Goal 6 Research: Scientometric, Text Mining and an Improved Framework for Future Research
Authors: Roy Ajishnu , Basu Aman , Su Yanyu , Li Yan , Dong Xuhui
Published: February 2022

The fulfilment of Sustainable Development Goal (SDG) 6, concerning water and sanitation, is critical in itself and also conditional for the other 16 SDGs being met. The purpose of this study was to understand the scientific research trajectories, spatiotemporal development, scientific collaboration, ongoing research themes, and gaps related to SDG 6. We propose a coupling of bibliometric and text mining methods in this work, to statistically portray the impact of water research on the accomplishment of SDG 6. Through the Web of Science database, we focused on a single UN SDG goal (i.e., six related publications that were current (2015–2021)). The study was performed on the chosen 289 publications. With the analysis of Keywords Plus, abstracts, titles, as well as author keywords, we looked at the performance of authors, publications, journals, institutions, and nations in terms of publishing. To obtain an insight into the water and sanitation study topic, we used co-citation, co-occurrence, cooperation networks, theme networks and cluster analysis, word dynamics, thematic evolution, and other techniques. We filtered out five distinguishing themes using text mining and showed their temporal trends. The main outcome is that participation, as well as collaboration with countries of the Global South, is still lacking in the SDG 6 research sphere. Therefore, as an insight from this study, we proposed a conceptual framework, the sustainable development of water and sanitation (SDWS) framework, to classify the research domain of water and sanitation regarding its connections to the environment, economy, and society (i.e., sustainable development). The scientometric and text analysis results provide the contemporary state and overview of the water and sanitation research field, whereas the second, conceptual framework section, provides a better understanding of qualitative contents, by revealing the insights gained, as well as the important work to be done in future water and sanitation studies.
Application of Best Available Techniques to Remove Air and Water Pollutants from Textile Dyeing and Finishing in South Korea
Authors: Kim Gahee , Kang Phil-Goo , Kim Eunseok , Seo Kyungae
Published: February 2022

The textile industry in South Korea is characterized by excessive water consumption, high concentrations of wastewater, hazardous chemicals, and high energy consumption. This study aimed to analyze Best Available Techniques Reference Documents (BREFs) based on best available techniques (BATs) and BAT-associated emission levels (BAT-AELs) and identify potential solutions for tackling environmental pressure from the South Korean textile industry. Therefore, the existing practices of the textile dyeing and finishing industry in South Korea were compared with those from the BREFs of the European Union. Many existing BATs in South Korea are related to reducing water consumption. There is also a strong focus on BATs for reducing wastewater discharge and achieving energy-saving during treatment rather than after treatment, which differs from other industries. Moreover, BAT-AELs were derived for chemical oxygen demand, suspended solids, and total nitrogen for treating non-biodegradable, highly polluted wastewater. Furthermore, BREFs related to atmospheric pollution included dust generated from the heated fabrics in the finishing process that contained cadmium and phenolic hydrogen chloride from dyes and raw materials in the fabrics. Notably, the European Union has not specified BAT-AELs for the textile industry, whereas South Korea has tailored BAT-AELs for toxic and hazardous chemicals. Thus, numerous green techniques to reduce emissions and energy consumption are being implemented in South Korea.
The Influence of Institutional Support on the Innovation Performance of New Ventures: The Mediating Mechanism of Entrepreneurial Orientation
Authors: Yang Jie , Yu Mingxing
Published: February 2022

Existing research on enterprise innovation focuses on internal perspectives such as resource and capabilities. However, enterprise innovation needs not only the input of enterprises themselves, but also the support of institutional environments. Based on the institution–strategy–performance research paradigm, which combines perspectives from both institutional theory and resource-based theory, this research explores the mechanism of institutional support on the innovation performance of new ventures, focusing on the mediating role of entrepreneurial orientation and the moderating role of innovative resource acquisition. An empirical analysis based on 278 survey samples shows that: (formal/informal) institutional support positively affects the innovation performance of new ventures; entrepreneurial orientation plays an intermediary role between institutional support and the innovation performance of new ventures; innovation resource acquisition not only positively regulates the relationship between entrepreneurial orientation and the innovation performance of new ventures, but also enhances the mediation of entrepreneurial orientation between institutional support and innovation performance. The conclusion shows that institutional support plays an important role in the innovation practice of new ventures, and can provide guidance for the innovation management practices of new ventures. This study discusses the theoretical and managerial implications for enterprise innovation research in detail by identifying and testing the relationships among these constructs.
The Resilient Community: Strengthening People-Centered Disaster Risk Reduction in the Merapi Volcano Community, Java, Indonesia
Authors: Mutiarni Yosi S. , Nakamura Hitoshi , Bhattacharya Yasmin
Published: February 2022

Local communities generally play a crucial role during a disaster, so their involvement in pre-disaster capacity development may prove beneficial in the face of a disaster threat. Thus, People-Centered Disaster Risk Reduction (PCDRR) programs could enable communities living in disaster-prone areas to become more resilient. This study examines how relationships among individual attributes of the community (and their pre-event Disaster Risk Reduction (DRR) context (risk knowledge, information access, and network and stakeholders) could give insight into how communities can be transformed to make them more resilient in the case of the Merapi Volcano community. Based on data collected through online survey platform by non-probability sampling, this study uses non-parametric goodness fit tests and parametric regression to assess the dependencies between various indicators and find the predictor variables. The findings indicate that the individual attributes of the Merapi Volcano community, as perceived through the pre-event DRR context has led to a better understanding of the function of people exposure to prepare more people-centered preparedness and disaster mitigation. However, since the sub-variables did not show any significance for being predictors, this implies that, even though there is a significant reliance between the pre-event DRR context and the individual attributes, the individual attribute could be regarded more as a modifier than a predictor.
Predicting User Behaviour Based on the Level of Interactivity Implemented in Blockchain Technologies in Websites and Used Devices
Authors: Jevremović Milica , Staletić Nada , Orzan Gheorghe , Ilić Milena P. , Jelić Zorica , Bălăceanu Cristina Teodora , Paraschiv Oana Valeria
Published: February 2022

Today’s business development processes force companies to find ways to increase the level of interactivity of their products with consumers. One of the ways that companies communicate interactively with users is communication via websites; another way is using a channel that makes the customer more loyal to the company. The aim of this paper is to point out the differences between the effects that interactive and non-interactive blockchain technologies have on users and their behavior, as well as to determine whether the same degree of interactivity is achieved with users who use the same site via computers or mobile phones. For this purpose, three models by Song, Liu, and Wu were compared, which gives this paper a superior precision and depth of research regarding the above-mentioned problem. Furthermore, the contributions of the paper are reflected in a comprehensive and detailed review of previous research on the topic of interactivity and the importance of using a website, showing the specific effects expected from users after the introduction of interactive website features, as well as indicating a difference in customer perception and behavior after using a different site search device.
How to Enhance Smart Work Effectiveness as a Sustainable HRM Practice in the Tourism Industry
Authors: Choi Hyunjung (Helen) , Lee Jin Young , Choi Youngjoon , Juan Yuxian , Lee Choong-Ki
Published: February 2022

With the development of information technologies and increasing interest in sustainability, many companies have adopted smart work as a sustainable human resource practice. Moreover, the outbreak of COVID-19 has further promoted smart work in the workplace. However, the benefits and disadvantages of smart work are still under debate. In this regard, this study attempted to delve into how to enhance smart work implementation by exploring employees’ subjectivity. Hana Tour, which is considered a good model of smart work in South Korea, was selected as a sample company. Q-methodology was employed to listen to employees’ subjective opinions about smart work that they experienced. This study identified five types of smart work perceptions, namely, “self-development and energy saving,” “quality of personal life,” “job satisfaction,” “work engagement,” and “work–life balance”. Based on these five types, the theoretical and practical implications are discussed in the last chapter. Interestingly, the results showed that employees were not well aware of smart work effectiveness as one of the environmental protection practices in sustainability management paradigms. Another notable result was that employees were not concerned about the potential penalties of their engagement in smart work. During the current COVID-19 pandemic, the study’s findings are beneficial to the improvement of smart work implementation as a sustainable HRM practice in business.
Feasibility Analysis of Promoting Wind and Solar Energy in Texas Farms
Authors: Cruz Mendoza Mariee , Martinez-Gomez Erick , Li Hua
Published: February 2022

Since the 1970s, agricultural lands have served as useful locations for the installation of renewable energy generators, such as wind turbines, photovoltaic modules, biodigesters, and others. Likewise, agriculture is one of the five industries with the highest annual energy consumption in the US. Energy is a vital component in farms’ daily activities, which is involved in the harvesting of crops and the growth of livestock. Due to the current rapidly growing energy consumption trends, renewable energy sources have become a potential solution for energy generation. This paper focuses on the feasibility analysis of promoting the utilization of solar and wind energy generation to provide power for the operational activities involved in diverse agricultural processes through the performance of a geospatial analysis and an in-depth numerical analysis to study the patterns in the estimation of energy potential across the 254 counties located in the state of Texas. Furthermore, different patterns surrounding the thousand farms are analyzed, such as the distance to the largest cities and the location of heavily populated areas with higher energy potential. The results show that farms in several regions in Texas have significant potential to utilize wind and solar energy for their farm operations, and to supply electricity to the nearby population.
How Transverse Waves Drive Turbulence in the Solar Corona
Authors: Howson Thomas
Published: February 2022

Oscillatory power is pervasive throughout the solar corona, and magnetohydrodynamic (MHD) waves may carry a significant energy flux throughout the Sun’s atmosphere. As a result, over much of the past century, these waves have attracted great interest in the context of the coronal heating problem. They are a potential source of the energy required to maintain the high-temperature plasma and may accelerate the fast solar wind. Despite many observations of coronal waves, large uncertainties inhibit reliable estimates of their exact energy flux, and as such, it remains unclear whether they can contribute significantly to the coronal energy budget. A related issue concerns whether the wave energy can be dissipated over sufficiently short time scales to balance the atmospheric losses. For typical coronal parameters, energy dissipation rates are very low and, thus, any heating model must efficiently generate very small-length scales. As such, MHD turbulence is a promising plasma phenomenon for dissipating large quantities of energy quickly and over a large volume. In recent years, with advances in computational and observational power, much research has highlighted how MHD waves can drive complex turbulent behaviour in the solar corona. In this review, we present recent results that illuminate the energetics of these oscillatory processes and discuss how transverse waves may cause instability and turbulence in the Sun’s atmosphere.
Heuristic EPnP-Based Pose Estimation for Underground Machine Tracking
Authors: Su Lingling , Zheng Xianhua , Song Yongshi , Liu Ge , Chen Nana , Feng Shang , Zhang Lin
Published: February 2022

Pose estimation is one of the most complicated and compromising problems for underground mining machine tracking, and it is particularly important for hydraulic support autonomous following mining machine (AFM) policy-making system. In this paper, a low-cost infrared vision-based system through an Efficient Perspective-n-Point (EPnP) algorithm is proposed. To improve efficiency and simplify computation, a traditional EPnP algorithm is modified through a nature-inspired heuristic optimization algorithm. The optimized algorithm is integrated into the AFM policy-making system to estimate the relative pose (R-Pose) estimation between hydraulic support and the mining machine’s shearer drum. Simple yet effective numerical simulations and industrial experiments were carried out to validate the proposed method. The pose estimation error was ≤1% under normal lighting and illuminance, and ≤2% in a simulated underground environment, which was accurate enough to meet the needs of practical applications. Both numerical simulation and industrial experiment proved the superiority of the approach.
Semi-Analytical Method for Unsymmetrical Doublet Flow Using Sink- and Source-Dominant Formulation
Authors: Tey Wah Yen , Lam Wei Haur , Teng Kah Hou , Wong Keng Yinn
Published: February 2022

Potential flow formed by doublet flow has been well applied in environmental applications and geothermal designs such as reservoir and fuel injectors. Most of the doublet flow is assumed based on the sink and source with equivalent strength and distance from the origin, forming the well-known Rankine oval structure when a far-field flow is superposed. A semi-analytical method is formulated to systematically investigate the unsymmetrical doublet flow with different strengths of sink and source. The general mathematical expression for unsymmetrical doublet flow is derived analytically before the streamline and the potential line can be visualised via a numerical approach. The results revealed that the doublet flows altered the Rankine oval structure to form aerofoil-like geometry. When the far-field flow interferes with the general Doublet configuration, unique flow structures such as convex, concave, and various wing shapes could be generated. The current study provides new insight on producing aerodynamic curves for the design of bio-inspired structures.
Immunomodulatory Effects of Pure Cylindrospermopsin in Rats Orally Exposed for 28 Days
Authors: Diez-Quijada Leticia , Casas-Rodriguez Antonio , Guzmán-Guillén Remedios , Molina-Hernández Verónica , Albaladejo Rafael G. , Cameán Ana María , Jos Angeles
Published: February 2022

Cylindrospermopsin (CYN) is a ubiquitous cyanotoxin showing increasing incidence worldwide. CYN has been classified as a cytotoxin and, among its toxic effects, its immunotoxicity is scarcely studied. This work investigates for the first time the influence of oral CYN exposure (18.75; 37.5 and 75 µg/kg b.w./day, for 28 days) on the mRNA expression of selected interleukin (IL) genes (IL-1β, IL-2, IL-6, Tumor Necrosis Factor alpha (TNF-α), Interferon gamma (IFN-γ)) in the thymus and the spleen of male and female rats, by quantitative real-time polymerase chain reaction (RT-qPCR). Moreover, their serum levels were also measured by a multiplex-bead-based immunoassay, and a histopathological study was performed. CYN produced immunomodulation mainly in the thymus of rats exposed to 75 μg CYN/kg b.w./day in both sexes. However, in the spleen only IL-1β and IL-2 (males), and TNF-α and IFN-γ (females) expression was modified after CYN exposure. Only female rats exposed to 18.75 μg CYN/kg b.w./day showed a significant decrease in TNF-α serum levels. There were no significant differences in the weight or histopathology in the organs studied. Further research is needed to obtain a deeper view of the molecular mechanisms involved in CYN immunotoxicity and its consequences on long-term exposures.
Differential Modulation of Innate Antiviral Profiles in the Intestinal Lamina Propria Cells of Chickens Infected with Infectious Bursal Disease Viruses of Different Virulence
Authors: Chen Rui , Chen Jinnan , Xiang Yanhua , Chen Yanyan , Shen Weiwei , Wang Weiwei , Li Yihai , Wei Ping , He Xiumiao
Published: February 2022

Infectious bursal disease virus (IBDV) is one of the most important infectious diseases of poultry around the world. Gut-associated lymphoid tissues (GALT) are the first line of defense of the host against the infection. The purpose of this study was to investigate the role of innate immune antiviral signaling triggered by Toll-like receptor 3 (TLR3), as well as macrophage activation and cytokine response in the intestinal lamina propria (ILP) cells after the oral challenge of IBDV in relation to IBDV virulence and disease pathogenesis. The results showed that the expression levels of TLR3, IRF7, IFN-α/β and the corresponding downstream antiviral factors OAS, PKR and Mx were all upregulated in the SPF chicken ILP cells at 8 h post-infection (hpi) and 12 hpi. Similarly, macrophages were activated, with the initial macrophage M1 activation observed at 8 hpi, but then it rapidly shifted to a non-protective M2-type. Both Th1 (IFN-γ, TNF-α, IL-12) and Th2 (IL-4 and IL-10) types of cytokines were differentially upregulated during the early stage of infection; however, the Th1 cytokines exhibited stronger activation before 8 hpi compared to those of the Th2 cytokines. Interestingly, differential regulations of gene expression induced by different IBDV strains with different virulence were detected. The HLJ0504-like very virulent (vv) IBDV strain NN1172 induced stronger activation of TLR3-IFN-α/β pathway, macrophages and the Th1/2 cytokines’ expression, compared to those induced by the attenuated strain B87 at 8 hpi and 12 hpi in the ILP cells. In conclusion, the innate antiviral response mediated by the TLR3-IRF7 pathway, macrophage activation and cytokine expression in the GALT cells at the early stage of IBDV infection was differentially modulated, and the HLJ0504-like vvIBDV strain triggered stronger activation than the attenuated vaccine strain, and that may play an important role in the progression of disease.
African Swine Fever Virus K205R Induces ER Stress and Consequently Activates Autophagy and the NF-κB Signaling Pathway
Authors: Wang Qi , Zhou Luyu , Wang Jiang , Su Dan , Li Dahua , Du Yongkun , Yang Guoyu , Zhang Gaiping , Chu Beibei
Published: February 2022

African swine fever virus (ASFV) is responsible for enormous economic losses in the global swine industry. The ASFV genome encodes approximate 160 proteins, most of whose functions remain largely unknown. In this study, we examined the roles of ASFV K205R in endoplasmic reticulum (ER) stress, autophagy, and inflammation. We observed that K205R was located in both the cytosolic and membrane fractions, and formed stress granules in cells. Furthermore, K205R triggered ER stress and activated the unfolded protein response through activating the transcription factor 6, ER to nucleus signaling 1, and eukaryotic translation initiation factor 2 alpha kinase 3 (EIF2AK3/PERK) signaling pathways. Moreover, K205R inhibited the serine/threonine kinase 1 and the mechanistic target of the rapamycin kinase signaling pathway, thereby activating unc-51 like autophagy activating kinase 1, and hence autophagy. In addition, K205R stimulated the translocation of P65 into the nucleus and the subsequent activation of the nuclear factor kappa B (NF-κB) signaling pathway. Inhibition of ER stress with a PERK inhibitor attenuated K205R-induced autophagy and NF-κB activation. Our data demonstrated a previously uncharacterized role of ASFV K205R in ER stress, autophagy, and the NF-κB signaling pathway.