bluuebunny/crossref_metadata_2025 huggingface dataset:
Monitoring the Foliar Nutrients Status of Mango Using Spectroscopy-Based Spectral Indices and PLSR-Combined Machine Learning Models
Authors: Mahajan Gopal Ramdas , Das Bappa , Murgaokar Dayesh , Herrmann Ittai , Berger Katja , Sahoo Rabi N. , Patel Kiran , Desai Ashwini , Morajkar Shaiesh , Kulkarni Rahul M.
Published: February 2021

Conventional methods of plant nutrient estimation for nutrient management need a huge number of leaf or tissue samples and extensive chemical analysis, which is time-consuming and expensive. Remote sensing is a viable tool to estimate the plant’s nutritional status to determine the appropriate amounts of fertilizer inputs. The aim of the study was to use remote sensing to characterize the foliar nutrient status of mango through the development of spectral indices, multivariate analysis, chemometrics, and machine learning modeling of the spectral data. A spectral database within the 350–1050 nm wavelength range of the leaf samples and leaf nutrients were analyzed for the development of spectral indices and multivariate model development. The normalized difference and ratio spectral indices and multivariate models–partial least square regression (PLSR), principal component regression, and support vector regression (SVR) were ineffective in predicting any of the leaf nutrients. An approach of using PLSR-combined machine learning models was found to be the best to predict most of the nutrients. Based on the independent validation performance and summed ranks, the best performing models were cubist (R2 ≥ 0.91, the ratio of performance to deviation (RPD) ≥ 3.3, and the ratio of performance to interquartile distance (RPIQ) ≥ 3.71) for nitrogen, phosphorus, potassium, and zinc, SVR (R2 ≥ 0.88, RPD ≥ 2.73, RPIQ ≥ 3.31) for calcium, iron, copper, boron, and elastic net (R2 ≥ 0.95, RPD ≥ 4.47, RPIQ ≥ 6.11) for magnesium and sulfur. The results of the study revealed the potential of using hyperspectral remote sensing data for non-destructive estimation of mango leaf macro- and micro-nutrients. The developed approach is suggested to be employed within operational retrieval workflows for precision management of mango orchard nutrients.
A Method for Detection of Small Moving Objects in UAV Videos
Authors: Stojnić Vladan , Risojević Vladimir , Muštra Mario , Jovanović Vedran , Filipi Janja , Kezić Nikola , Babić Zdenka
Published: February 2021

Detection of small moving objects is an important research area with applications including monitoring of flying insects, studying their foraging behavior, using insect pollinators to monitor flowering and pollination of crops, surveillance of honeybee colonies, and tracking movement of honeybees. However, due to the lack of distinctive shape and textural details on small objects, direct application of modern object detection methods based on convolutional neural networks (CNNs) shows considerably lower performance. In this paper we propose a method for the detection of small moving objects in videos recorded using unmanned aerial vehicles equipped with standard video cameras. The main steps of the proposed method are video stabilization, background estimation and subtraction, frame segmentation using a CNN, and thresholding the segmented frame. However, for training a CNN it is required that a large labeled dataset is available. Manual labelling of small moving objects in videos is very difficult and time consuming, and such labeled datasets do not exist at the moment. To circumvent this problem, we propose training a CNN using synthetic videos generated by adding small blob-like objects to video sequences with real-world backgrounds. The experimental results on detection of flying honeybees show that by using a combination of classical computer vision techniques and CNNs, as well as synthetic training sets, the proposed approach overcomes the problems associated with direct application of CNNs to the given problem and achieves an average F1-score of 0.86 in tests on real-world videos.
Reconstruction of Snow Depth Data at Moderate Spatial Resolution (1 km) from Remotely Sensed Snow Data and Multiple Optimized Environmental Factors: A Case Study over the Qinghai-Tibetan Plateau
Authors: Wei Pengtao , Zhang Tingbin , Zhou Xiaobing , Yi Guihua , Li Jingji , Wang Na , Wen Bo
Published: February 2021

Snow depth distribution in the Qinghai-Tibetan plateau is important for atmospheric circulation and surface water resources. In-situ observations at meteorological stations and remote observation by passive microwave remote sensing technique are two main approaches for monitoring snow depth at regional or global levels. However, the meteorological stations are often scarce and unevenly distributed in mountainous regions because of inaccessibility, so are the in-situ snow depth measurements. Passive microwave remote sensing data can alleviate the unevenness issue, but accuracy and spatial (e.g., 25 km) and temporal resolutions are low; spatial heterogeneity in snow depth is thus hard to capture. On the other hand, optical sensors such as moderate resolution imaging spectroradiometer (MODIS) onboard Terra and Aqua satellites can monitor snow at moderate spatial resolution (1 km) and high temporal resolution (daily) but only snow area extent, not snow depth. Fusing passive microwave snow depth data with optical snow area extent data provides an unprecedented opportunity for generating snow depth data at moderate spatial resolution and high temporal resolution. In this article, a linear multivariate snow depth reconstruction (LMSDR) model was developed by fusing multisource snow depth data, optical snow area extent data, and environmental factors (e.g., spatial distribution, terrain features, and snow cover characteristics), to reconstruct daily snow depth data at moderate resolution (1 km) for 16 consecutive hydrological years, taking Qinghai-Tibetan Plateau (QTP) as a case study. We found that snow cover day (SCD) and environmental factors such as longitude, latitude, slope, surface roughness, and surface fluctuation have a significant impact on the variations of snow depth over the QTP. Relatively high accuracy (root mean square error (RMSE) = 2.26 cm) was observed in the reconstructed snow depth when compared with in-situ data. Compared with the passive microwave remote sensing snow depth product, constructing a nonlinear snow depletion curve product with an empirical formula and fusion snow depth product, the LMSDR model (RMSE = 2.28 cm, R2 = 0.63) demonstrated a significant improvement in accuracy of snow depth reconstruction. The overall spatial accuracy of the reconstructed snow depth was 92%. Compared with in-situ observations, the LMSDR product performed well regarding different snow depth intervals, land use, elevation intervals, slope intervals, and SCD and performed best, especially when the snow depth was less than 3 cm. At the same time, a long-time snow depth series reconstructed based on the LMSDR model reflected interannual variations of snow depth well over the QTP.
Repeatable Semantic Reef-Mapping through Photogrammetry and Label-Augmentation
Authors: Yuval Matan , Alonso Iñigo , Eyal Gal , Tchernov Dan , Loya Yossi , Murillo Ana C. , Treibitz Tali
Published: February 2021

In an endeavor to study natural systems at multiple spatial and taxonomic resolutions, there is an urgent need for automated, high-throughput frameworks that can handle plethora of information. The coalescence of remote-sensing, computer-vision, and deep-learning elicits a new era in ecological research. However, in complex systems, such as marine-benthic habitats, key ecological processes still remain enigmatic due to the lack of cross-scale automated approaches (mms to kms) for community structure analysis. We address this gap by working towards scalable and comprehensive photogrammetric surveys, tackling the profound challenges of full semantic segmentation and 3D grid definition. Full semantic segmentation (where every pixel is classified) is extremely labour-intensive and difficult to achieve using manual labeling. We propose using label-augmentation, i.e., propagation of sparse manual labels, to accelerate the task of full segmentation of photomosaics. Photomosaics are synthetic images generated from a projected point-of-view of a 3D model. In the lack of navigation sensors (e.g., a diver-held camera), it is difficult to repeatably determine the slope-angle of a 3D map. We show this is especially important in complex topographical settings, prevalent in coral-reefs. Specifically, we evaluate our approach on benthic habitats, in three different environments in the challenging underwater domain. Our approach for label-augmentation shows human-level accuracy in full segmentation of photomosaics using labeling as sparse as 0.1%, evaluated on several ecological measures. Moreover, we found that grid definition using a leveler improves the consistency in community-metrics obtained due to occlusions and topology (angle and distance between objects), and that we were able to standardise the 3D transformation with two percent error in size measurements. By significantly easing the annotation process for full segmentation and standardizing the 3D grid definition we present a semantic mapping methodology enabling change-detection, which is practical, swift, and cost-effective. Our workflow enables repeatable surveys without permanent markers and specialized mapping gear, useful for research and monitoring, and our code is available online. Additionally, we release the Benthos data-set, fully manually labeled photomosaics from three oceanic environments with over 4500 segmented objects useful for research in computer-vision and marine ecology.
Quantitative Assessment of the Influences of Snow Drought on Forest and Grass Growth in Mid-High Latitude Regions by Using Remote Sensing
Authors: Lou Hezhen , Wu Xijin , Ren Xiaoyu , Yang Shengtian , Cai Mingyong , Wang Pengfei , Guan Yabing
Published: February 2021

Global climate change, especially the snow drought events, is causing extreme weather events influencing regional vegetation growth and terrestrial ecosystem stability in a long-term and persistent way. In this study, the Sanjiang Plain was selected, as this area has been experiencing snow drought in the past two decades. Logistic models, combined with multisource remote sensing and unmanned aerial vehicle (UAV) data, as well as the meteorological data over the past 20 years, were used to calculate sixteen phenological periods and biomass. The results show that (1) over the past two decades, snow drought has been based on the snow accumulation and has been occurring more frequently, wider-ranging and more severely; (2) snow drought has advanced the forest start of season (SOS)/end of season (EOS) by 6/5 days, respectively; (3) if the snowfall is greater than 80% of a normal year, the SOS/EOS of grass is postponed by 8/6 days; conversely, if it is less than 80%, the SOS/EOS are advanced by 7/5 days; and (4) biomass decreased approximately 0.61%, compared with an abundant snowfall year. Overall, this study is the first to explore how snow drought impacts the phenological period in a mid-high latitude area, and more attention should be paid to these unknown risks to the ecosystem.
Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model
Authors: Liu Zhengchun , Xu Zhanjun , Bi Rutian , Wang Chao , He Peng , Jing Yaodong , Yang Wude
Published: February 2021

The farmland area in arid and semiarid regions accounts for about 40% of the total area of farmland in the world, and it continues to increase. It is critical for global food security to predict the crop yield in arid and semiarid regions. To improve the prediction of crop yields in arid and semiarid regions, we explored data assimilation-crop modeling strategies for estimating the yield of winter wheat under different water stress conditions across different growing areas. We incorporated leaf area index (LAI) and soil moisture derived from multi-source Sentinel data with the CERES-Wheat model using ensemble Kalman filter data assimilation. According to different water stress conditions, different data assimilation strategies were applied to estimate winter wheat yields in arid and semiarid areas. Sentinel data provided LAI and soil moisture data with higher frequency (<14 d) and higher precision, with root mean square errors (RMSE) of 0.9955 m2 m−2 and 0.0305 cm3 cm−3, respectively, for data assimilation-crop modeling. The temporal continuity of the CERES-Wheat model and the spatial continuity of the remote sensing images obtained from the Sentinel data were integrated using the assimilation method. The RMSE of LAI and soil water obtained by the assimilation method were lower than those simulated by the CERES-Wheat model, which were reduced by 0.4458 m2 m−2 and 0.0244 cm3 cm−3, respectively. Assimilation of LAI independently estimated yield with high precision and efficiency in irrigated areas for winter wheat, with RMSE and absolute relative error (ARE) of 427.57 kg ha−1 and 6.07%, respectively. However, in rain-fed areas of winter wheat under water stress, assimilating both LAI and soil moisture achieved the highest accuracy in estimating yield (RMSE = 424.75 kg ha−1, ARE = 9.55%) by modifying the growth and development of the canopy simultaneously and by promoting soil water balance. Sentinel data can provide high temporal and spatial resolution data for deriving LAI and soil moisture in the study area, thereby improving the estimation accuracy of the assimilation model at a regional scale. In the arid and semiarid region of the southeastern Loess Plateau, assimilation of LAI independently can obtain high-precision yield estimation of winter wheat in irrigated area, while it requires assimilating both LAI and soil moisture to achieve high-precision yield estimation in the rain-fed area.
Perceived Intimacy Differences of Daily Online and Offline Interactions in People’s Social Network
Authors: Croes Emmelyn A. J. , Antheunis Marjolijn L.
Published: February 2021

This study examined which media people use on a day-to-day basis to communicate and whether tie strength influenced this media use. Furthermore, we analyzed whether online and offline interactions differ in perceived intimacy and whether tie strength impacts perceived interaction intimacy: 347 real interactions of 9 participants (3 male, 6 female) were analyzed; 172 online (WhatsApp, Facebook Messenger, email, SMS interactions) and 175 offline (recorded phone and face-to-face conversations). The results revealed that the participants communicated most frequently face-to-face or via WhatsApp, especially with strong ties. Furthermore, participants rated their interactions with strong ties as more intimate compared to weak-tie interactions. Our findings have implications for Social Information Processing theory, as our findings show that people are equally able to communicate intimate messages online and offline.
An Exploratory Study on the Attitudes of the Greek Believers towards the State’s Measures during the First Wave of Coronavirus Pandemic
Authors: Michailidis Panagiotis , Vlasidis Vlasis , Karekla Sofia
Published: February 2021

During the first wave of the coronavirus pandemic (16 March–5 May 2020), the Greek government took measures to close churches in order to protect the public health of the population. In this case, the purpose of this paper is to explore the response of Greek believers and Churches to the measures of the state, and whether these attitudes are affected by sociodemographic characteristics. Moreover, there was a collection of data on the attitudes of 353 believers through questionnaires, and the proper examination of these data through descriptive analysis and cross-tabulation analysis. The survey results showed that most believers are convinced that national measures are necessary, and they also revealed that believers’ attitudes vary according to demographic variables.
Multi-Criteria Assessment for Defining Compatible New Use: Old Administrative Hospital, Kyrenia, Cyprus
Authors: Vehbi Beser Oktay , Günçe Kağan , Iranmanesh Aminreza
Published: February 2021

It is common for the original use of heritage buildings to become obsolete which in some cases can result in them becoming vacant and subject to deterioration. Adaptive reuse is an essential policy for achieving sustainability as it keeps a continuous building life cycle and avoids building destruction. It is one approach to sustainability where it retains the tangible and intangible values, resilience of the original building materials, and reduces waste and time. The decision-making criteria for compatible new use includes several criteria that affect sustainable development: economic, environment, social, legislative, and architecture. Several Multi-Criteria Decision Making (MCDM) methods have been established in order to aid the process of cultural heritage preservation. This research aims to present an assessment model to support the establishment of appropriate new use by employing an Analytic Hierarchy Process (AHP). The decision-making software used was Expert Choice 11. The administrative hospital in Kyrenia, Cyprus, was selected as the case study in this research. Using the application of AHP with the participation of different stakeholders (experts and locals), a more compatible use as a community centre is proposed and supported by the research methodology.
True and Fair Override: Accounting Expert Opinions, Explanations from Behavioural Theories, and Discussions for Sustainability Accounting
Authors: Garvey Anne Marie , Parte Laura , McNally Bridget , Gonzalo-Angulo José Antonio
Published: February 2021

This study focuses on true and fair view (TFV) and fair presentation (FP) in financial statements. It questions if attitudes towards the true and fair override (TFO) condition, included in European Union (EU) legislation and International Financial Reporting Standards (IFRS), is indicative of a principles-based approach or lip service to a concept that is rarely applied. We address this subject because we consider that there should be a consensus and harmonisation on TFV—that TFO has a vital role within the principles-based framework, and while the accounting standard development process should limit the application of the TFO concept, in practice, it is an important reporting option. TFV/TFO harmonisation also has an important role in sustainability accounting, to reveal company actions which are influenced by more than just the objective of complying with the standards. In the empirical part, accounting experts from 24 European countries were surveyed. Their responses suggest a lack of clarity around the distinction between TFV and FP and a reluctance to consider, in practice, the application of the TFO. Drawing on behavioural theories—ostrich effect and comfort theory—we find explanations and reasoning behind attitudes to these cornerstone concepts. Specifically, we try to explain behavioural attitudes to TFV/FP and TFO positions, which defend uncompromising compliance with standards.
Sustainability in Construction Projects: A Systematic Literature Review
Authors: Kiani Mavi Reza , Gengatharen Denise , Kiani Mavi Neda , Hughes Richard , Campbell Alistair , Yates Ross
Published: February 2021

This paper aims to identify the major research concepts studied in the literature of sustainability in construction projects. Two bibliometric analysis tools—(a) BibExcel and (b) Gephi, were used to analyze the bibliometrics indices of papers and visualize their interrelations as a network, respectively. Therefore, a research focus parallelship network (RFPN) analysis and keyword co-occurrence network (KCON) analysis were performed to uncover the primary research themes. The RFPN analysis clustered the studies into three major categories of evaluating sustainability, project management for sustainability, and drivers of sustainable construction. The KCON analysis revealed that while each paper had a different focus, the underlying concept of all clusters was sustainability, construction, and project management. We found that while ‘sustainability’ was the leading keyword in the first cluster, i.e., evaluating sustainability, it was the second top keyword with the eigenvector centrality of over 0.94 in the other two clusters. We also found that the concept of sustainability should be included in construction projects from the early stages of design and feasibility studies and must be monitored throughout the project life. This review showed that previous researchers used a variety of statistical and mathematical techniques such as structural equation modelling and fuzzy decision-making methods to study sustainability in construction projects. Using an integrated approach to identifying the research gaps in this area, this paper provides researchers with insights on how to frame new research to study sustainability in construction projects.
Innovative Renewable Technology Integration for Nearly Zero-Energy Buildings within the Re-COGNITION Project
Authors: Mancò Giulia , Guelpa Elisa , Colangelo Alessandro , Virtuani Alessandro , Morbiato Tommaso , Verda Vittorio
Published: February 2021

With the 2010/31/EU directive, all new buildings shall be nearly zero-energy buildings (nZEB) from 2020 onward, with the aim of strongly reducing the energy consumption related to the building sector. To achieve this goal, it is not sufficient to focus on the design of the building envelope; smart and efficient energy management is necessary. Moreover, to ensure the adoption of RES systems in the built environment, innovative technologies need to be further developed in order to increase their cost-effectiveness, energy efficiency and integration capability. This paper proposes a synthesis, design and operation optimization of an integrated multi-energy system composed of traditional and innovative renewable technologies, developed within the European project Re-COGNITION. A biogas-based micro cogeneration unit, lightweight glass-free photovoltaic modules, a passive variable geometry small wind turbine optimized for an urban environment and latent heat thermal storage based on phase change materials are some of the technologies developed within the Re-COGNITION project. The optimization problem is solved to contemporarily evaluate (a) the optimal design and (b) the optimal operations of the set of technologies considering both investment and operating costs, using mixed integer non-linear programming. The optimization is applied to the four pilots that are developed during the project, in various European cities (Turin (Italy), Corby (United Kingdom), Thessaloniki (Greece), Cluj-Napoca (Romania). Simulation results show that the development and optimal exploitation of new technologies through optimization strategies provide significant benefits in terms of cost (between 11% and 42%) and emissions (between 10% and 25%), managing building import/export energy and charge/discharge storage cycles.
Long-Term Impact of Study Abroad on Sustainability-Related Attitudes and Behaviors
Authors: Zhang Hongping , Gibson Heather J.
Published: February 2021

Using study abroad as a vehicle for sustainable education is a growing trend. However, an examination of the impact of study abroad on participants’ sustainability-related attitudes and behaviors years after their programs is scarce. Therefore, the purpose of this study was to explore how a short-term sustainability themed study abroad program impacted students’ sustainability-related attitudes and behaviors. Since long-term personal development and change of attitudes are complex and multidimensional, a qualitative approach was used allowing participants to share their experiences and reflections on the process of learning and internalizing sustainability. A total of 31 study abroad participants were interviewed (20 to 33 years of age) and a grounded theory method was used throughout the study. Participants’ behavioral changes were identified, and the specific study abroad program designs that were associated with such changes were identified and discussed. The three behavioral changes identified by the participants were lifestyle, professional development, and responsible travel behaviors. The effective program design elements include emotion, cognition, and action. Furthermore, the findings suggested revisions to the Value–Belief–Norm model in that more motives should be added whereas, weight of responsibility might need to be reevaluated. This study contributes to the educational tourism and sustainability literature with practical implications for program design, and a better understanding of students’ long-term learning outcomes regarding sustainability.
Investigation of Dye Removal Capability of Blast Furnace Slag in Wastewater Treatment
Authors: Yasipourtehrani Sara , Strezov Vladimir , Kan Tao , Evans Tim
Published: February 2021

Blast Furnace Slag (BFS) is a by-product of the iron ore processing industry with potential to be used in different industrial applications. In this research, BFS was used to examine its ability for dye removal from wastewater. The efficiency of two types of BFS samples for removal of cationic methylene blue (MB) and acidic methyl orange (MO) dyes was investigated and results found that the optimal conditions for treatment of wastewater were 80 g/L of adsorbent dose and 1 h of treatment time for both dyes. BFS was found to be more effective for removal of the acidic MO dye than the cationic MB dye. Under shorter residence times, the results showed reverse trends with BFS samples removing higher concentrations of MB than MO. The BFS chemistry had additional impacts on the efficiency of dye removal. Higher basicity of BFS had lower dye removal ability for adsorption of acidic dye when applied at smaller concentrations, while for cationic dye when applied at higher concentrations. The results showed that BFS has potential role for pre-treatment of industrial wastewater contaminated with dyes and may contribute to reduced use of more expensive adsorbents, such as activated carbons.
Are Jobs Available in the Market? A Perspective from the Supply Side
Authors: Jamaludin Salwaty , Said Rusmawati , Ismail Normaz Wana , Nor Norashidah Mohamed
Published: February 2021

Graduate unemployment exhibits a clear increasing global trend, and Malaysia is no exception. The unemployment rate among graduates is witnessing a considerable upsurge, growing from 43,800 in 2000 (15% of total unemployed) to more than 175,500 in 2017 (35%). Numerous programmes have been implemented in order to secure jobs for the unemployed in the labour market; however, the number of unemployed graduates keeps on increasing. It is significant to recognise the main reason behind this issue to tackle the risk of long-term unemployment, specifically from the supply side. Using the Relative Importance Index (RII), this study investigated 402 respondents at selected job fairs to identify the cause of their difficulty in entering the labour market. The findings revealed that the unemployed people believe that the principal cause of their unemployment is the lack of suitable jobs for them in the market. This circumstance sends a signal of asymmetric information between demand and supply in the labour market, especially to young graduates.
Ethical Management of Artificial Intelligence
Authors: Brendel Alfred Benedikt , Mirbabaie Milad , Lembcke Tim-Benjamin , Hofeditz Lennart
Published: February 2021

With artificial intelligence (AI) becoming increasingly capable of handling highly complex tasks, many AI-enabled products and services are granted a higher autonomy of decision-making, potentially exercising diverse influences on individuals and societies. While organizations and researchers have repeatedly shown the blessings of AI for humanity, serious AI-related abuses and incidents have raised pressing ethical concerns. Consequently, researchers from different disciplines widely acknowledge an ethical discourse on AI. However, managers—eager to spark ethical considerations throughout their organizations—receive limited support on how they may establish and manage AI ethics. Although research is concerned with technological-related ethics in organizations, research on the ethical management of AI is limited. Against this background, the goals of this article are to provide a starting point for research on AI-related ethical concerns and to highlight future research opportunities. We propose an ethical management of AI (EMMA) framework, focusing on three perspectives: managerial decision making, ethical considerations, and macro- as well as micro-environmental dimensions. With the EMMA framework, we provide researchers with a starting point to address the managing the ethical aspects of AI.
An SEM Approach for the Barrier Analysis in Lean Implementation in Manufacturing Industries
Authors: Abu Falah , Gholami Hamed , Saman Muhamad Zameri Mat , Zakuan Norhayati , Streimikiene Dalia , Kyriakopoulos Grigorios L.
Published: February 2021

This paper investigates the barriers that hinder the implementation of lean manufacturing in wood and furniture industries as the adoption of this philosophy in such industries is not promising especially in emerging economies. To this end, a comprehensive review of the literature was performed to identify the barriers and develop a conceptual model. Next, structural equation modeling is employed to examine the model using the collected data from 131 wood and furniture companies. The findings revealed a synergetic effect between three key factors—culture and human attitude, knowledge, and resources—which play a crucial role in implementing lean. The analyses indicated the reasons of companies refused or not ready to implement lean on knowledge and culture and human attitudinal issues, particularly in companies that have limited resources. It is believed that resource issues are an obstacle to lean implementation, but not as important as knowledge and culture and human attitudinal issues. Sufficient knowledge is needed to deploy lean practices as well as changes in culture and human attitude. Investigating the relationships between these three key barriers is a contribution that this study intends to become a forward step for promoting lean manufacturing among under-studied industries. This paper also proposes that through adopting the activities for lean implementation, small and medium enterprises can experience and quantify the positive impacts of lean practices. Government agencies, universities, and professional bodies can support such enterprises in this transition through targeted interventions that address the barriers presented.
Construction of Leisure Consumer Loyalty from Cultural Identity—A Case of Cantonese Opera
Authors: Yang Jian , Luo Jian Ming , Lai Ivan Ka Wai
Published: February 2021

Many regions and countries hope to employ cultural leisure products to obtain economic benefits. However, in the process of globalisation, cultural standardisation has posed difficulties for vulnerable cultures in terms of cultural inheritance and sustainable development. As with many intangible cultural heritages, Cantonese opera is also facing a shrinking market. Hence, to develop the strategy of sustainable development of Cantonese opera, this research aims to clarify the connection between cultural identity and loyalty in cultural leisure consumption in the context of Cantonese opera as a leisure product. The results show that each dimension of cultural identity has a positive effect on perceived value, and two dimensions positively affect satisfaction. The path of cultural identity building loyalty is also confirmed to be through perceived value and satisfaction. Future studies and the consequences of future practices are discussed.
Social Sustainability Work in Product Development Organizations: An Empirical Study of Three Sweden-Based Companies
Authors: Mesquita Patricia Lagun , Missimer Merlina
Published: February 2021

Companies responsible for product development (PD) and manufacturing play an important role in supporting society in achieving sustainability, and yet they do not always include full sustainability considerations in PD decisions. The social dimension of sustainability has been largely neglected in the PD field and there is very little empirical evidence of social sustainability implementation in general. The aim of this paper is to investigate how social sustainability is currently included in PD organizations and what their motivations are to do so. Results from a comparative case study approach with three organizations include rich descriptions across four dimensions: The scope of the work and their view of interdependencies with other social systems, their definition of social sustainability and the issues they work with, what guides strategic decisions, and how this internal work is structured. The results reveal that the three product development organizations are heterogenous in their approaches to social sustainability and that the more advanced approach shows a better understanding of the complexity of social sustainability and a broader perspective of its interdependencies, which goes hand-in-hand with a way of organizing that overcomes traditional hierarchies and allows for more collaborative and strategic work in this area. This systems perspective also drives what issues are included in an organization’s work; scope and definition of social sustainability become more encompassing and aligned. Finally, our study shows that social sustainability impacts connected to products’ lifecycles, when addressed, are done so by functions outside design activities, as opposed to product developers. A greater understanding of how companies currently approach social sustainability and what challenges they might face in integrating it in organizational and design related practices has been called for; our paper contributes to this but acknowledges that more work is needed.
A Questionnaire Case Study of Opinions of Chinese Agricultural Workers on the Coordinated Control of Emissions of Ammonia
Authors: Liang Muxue , Liao Hong , Huang Yue , Qiao Zifang , Tan Chenchen , Liu Ruoxin
Published: February 2021

So far, China’s particulate pollution control is principally focused on primary particles and sulfur dioxide from coal combustion. The contribution of ammonia emissions to particulate matter with an aerodynamic equivalent diameter of less than or equal to 2.5 microns (PM2.5) has been increasingly emphasized. As a world-famous agricultural country with 523 million farmers (2017, National Bureau of Statistics of China), approximately 70.0–90.0% of China’s ammonia emissions come from agriculture. With such a huge population, agriculture industrialization (socioeconomic policies and technology upgrades to reduce ammonia emissions from fertilizers and livestock) has a large potential but is more vulnerable to costs compared to other industries. We need a solution involving both economic benefits and environmental protection. For this purpose, we sent out an anonymous questionnaire consisting of 16 questions to 420 farmers and conducted a field visit survey in a rural area of Jiangsu Province. Through statistical analysis, we found that the use of nitrogen fertilizers in agriculture, which are an important source of ammonia through volatilization, is normal (200/420 × 100% = 47.62% of farmers use such fertilizers). Among the 420 farmers surveyed, 90.71% of them have knowledge of air pollution from agricultural activities and 92.15% of them have certain understanding of agricultural industrialization policies, indicating that coordinated control of ammonia emissions can be achieved together with policy propaganda. Through factor analysis and correlation analysis, we find that the early propaganda of policies can help farmers to be more willing to accept the policies. The correlation coefficient between awareness of pollution and policy approval is 0.94, and that between policy publicity and policy approval is 0.95. Generally speaking, the promotion of policies is worth carrying out during the implementation process.
Restore or Get Restored: The Effect of Control on Stress Reduction and Restoration in Virtual Nature Settings
Authors: Reese Gerhard , Kohler Elias , Menzel Claudia
Published: February 2021

Virtual nature experiences can improve physiological and psychological well-being. Although there is ample research on the positive effects of nature, both in virtual and physical settings, we know little about potential moderators of restoration effects in virtual reality settings. According to theories of needs and control beliefs, it is plausible to assume that control over one’s actions affects how people respond to nature experiences. In this virtual reality (VR) experiment, 64 participants either actively navigated through a VR landscape or they were navigated by the experimenter. We measured their perceived stress, mood, and vitality before and after the VR experience as well as the subjective restoration outcome and the perceived restorativeness of the landscape afterwards. Results revealed that participants’ positive affective states increased after the VR experience, regardless of control. There was a main effect such that participants reported lower stress after the VR experience; however, this was qualified by an interaction showing that this result was only the case in the no control condition. These results unexpectedly suggest that active VR experiences may be more stressful than passive ones, opening pathways for future research on how handling of and navigating in VR can attenuate the effects of virtual nature.
Environmental and Social Goals in Spanish SMEs: The Moderating Effect of Family Influence
Authors: Rojas Alvaro , Lorenzo Daniel
Published: February 2021

Small and medium-sized enterprises (SMEs) are the predominant form of firm in the economy worldwide, so it is becoming increasingly important to understand the role they play in the green transition. It is urgent to understand how SMEs establish their goals that reorient their strategies and activities towards the creation of greater environmental value. From a stakeholder perspective, this study analyzes the environmental and social goals that create value in SMEs. We identify family influence as an important determinant for the establishment of environmental goals in SMEs that has not been sufficiently studied. We tested the hypotheses in a sample of 132 Spanish SMEs. Our findings indicate that setting social goals and having family characteristics have a direct positive effect on the environmental goals of SMEs. In addition, family influence positively moderates the effect of social goals, increasing its effect in the establishment of environmental goals for the creation of value in SMEs. This is due to the desire of family SMEs to increase their socio-emotional wealth and their transgenerational intention by incorporating the requirements of stakeholders. These findings highlight the importance of particularly considering the family characteristics of SMEs when analyzing the role that SMEs play in the green transition and should also be important for policy makers when designing environmental policies.
Coefficient Bounds for Certain Classes of Analytic Functions Associated with Faber Polynomial
Authors: Attiya Adel A. , Lashin Abdel Moneim , Ali Ekram E. , Agarwal Praveen
Published: February 2021

In this paper, we intorduce a family of analytic functions in the open unit disk which is bi-univalent. By the virtue of the Faber polynomial expansions, the estimation of n−th(n≥3) Taylor–Maclaurin coefficients an is obtained. Furthermore, the bounds value of the first two coefficients of such functions is established.
Half Logistic Inverse Lomax Distribution with Applications
Authors: Al-Marzouki Sanaa , Jamal Farrukh , Chesneau Christophe , Elgarhy Mohammed
Published: February 2021

The last years have revealed the importance of the inverse Lomax distribution in the understanding of lifetime heavy-tailed phenomena. However, the inverse Lomax modeling capabilities have certain limits that researchers aim to overcome. These limits include a certain stiffness in the modulation of the peak and tail properties of the related probability density function. In this paper, a solution is given by using the functionalities of the half logistic family. We introduce a new three-parameter extended inverse Lomax distribution called the half logistic inverse Lomax distribution. We highlight its superiority over the inverse Lomax distribution through various theoretical and practical approaches. The derived properties include the stochastic orders, quantiles, moments, incomplete moments, entropy (Rényi and q) and order statistics. Then, an emphasis is put on the corresponding parametric model. The parameters estimation is performed by six well-established methods. Numerical results are presented to compare the performance of the obtained estimates. Also, a simulation study on the estimation of the Rényi entropy is proposed. Finally, we consider three practical data sets, one containing environmental data, another dealing with engineering data and the last containing insurance data, to show how the practitioner can take advantage of the new half logistic inverse Lomax model.
Distribution of Human Papillomavirus (HPV) Genotypes in HIV-Negative and HIV-Positive Women with Cervical Intraepithelial Lesions in the Eastern Cape Province, South Africa
Authors: Taku Ongeziwe , Mbulawa Zizipho Z. A. , Phohlo Keletso , Garcia-Jardon Mirta , Businge Charles B. , Williamson Anna-Lise
Published: February 2021

South African women have a high rate of cervical cancer cases, but there are limited data on human papillomavirus (HPV) genotypes in cervical intraepithelial neoplasia (CIN) in the Eastern Cape province, South Africa. A total of 193 cervical specimens with confirmed CIN from women aged 18 years or older, recruited from a referral hospital, were tested for HPV infection. The cervical specimens, smeared onto FTA cards, were screened for 36 HPV types using an HPV direct flow kit. HPV prevalence was 93.5% (43/46) in CIN2 and 96.6% (142/147) in CIN3. HIV-positive women had a significantly higher HPV prevalence than HIV-negative women (98.0% vs. 89.1%, p = 0.012). The prevalence of multiple types was significantly higher in HIV-positive than HIV-negative women (p = 0.034). The frequently detected genotypes were HPV35 (23.9%), HPV58 (23.9%), HPV45 (19.6%), and HPV16 (17.3%) in CIN2 cases, while in CIN3, HPV35 (22.5%), HPV16 (21.8%), HPV33 (15.6%), and HPV58 (14.3%) were the most common identified HPV types, independent of HIV status. The prevalence of HPV types targeted by the nonavalent HPV vaccine was 60.9% and 68.7% among women with CIN2 and CIN3, respectively, indicating that vaccination would have an impact both in HIV-negative and HIV-positive South African women, although it will not provide full protection in preventing HPV infection and cervical cancer lesions.
Berberine and Obatoclax Inhibit SARS-Cov-2 Replication in Primary Human Nasal Epithelial Cells In Vitro
Authors: Varghese Finny , van Woudenbergh Esther , Overheul Gijs , Eleveld Marc , Kurver Lisa , van Heerbeek Niels , van Laarhoven Arjan , Miesen Pascal , den Hartog Gerco , de Jonge Marien , van Rij Ronald
Published: February 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged as a new human pathogen in late 2019 and it has infected over 100 million people in less than a year. There is a clear need for effective antiviral drugs to complement current preventive measures, including vaccines. In this study, we demonstrate that berberine and obatoclax, two broad-spectrum antiviral compounds, are effective against multiple isolates of SARS-CoV-2. Berberine, a plant-derived alkaloid, inhibited SARS-CoV-2 at low micromolar concentrations and obatoclax, which was originally developed as an anti-apoptotic protein antagonist, was effective at sub-micromolar concentrations. Time-of-addition studies indicated that berberine acts on the late stage of the viral life cycle. In agreement, berberine mildly affected viral RNA synthesis, but it strongly reduced infectious viral titers, leading to an increase in the particle-to-pfu ratio. In contrast, obatoclax acted at the early stage of the infection, which is in line with its activity to neutralize the acidic environment in endosomes. We assessed infection of primary human nasal epithelial cells that were cultured on an air-liquid interface and found that SARS-CoV-2 infection induced and repressed expression of specific sets of cytokines and chemokines. Moreover, both obatoclax and berberine inhibited SARS-CoV-2 replication in these primary target cells. We propose berberine and obatoclax as potential antiviral drugs against SARS-CoV-2 that could be considered for further efficacy testing.
Development and In Vivo Evaluation of a MGF110-1L Deletion Mutant in African Swine Fever Strain Georgia
Authors: Ramirez-Medina Elizabeth , Vuono Elizabeth , Pruitt Sarah , Rai Ayushi , Silva Ediane , Espinoza Nallely , Zhu James , Velazquez-Salinas Lauro , Borca Manuel V. , Gladue Douglas P.
Published: February 2021

African swine fever (ASF) is currently causing an epizootic, affecting pigs throughout Eurasia, and causing significant economic losses in the swine industry. ASF is caused by African swine fever virus (ASFV) that consists of a large dsDNA genome that encodes for more than 160 genes; few of these genes have been studied in detail. ASFV contains four multi-gene family (MGF) groups of genes that have been implicated in regulating the immune response and host specificity; however, the individual roles of most of these genes have not been well studied. Here, we describe the evaluation of the previously uncharacterized ASFV MGF110-1L open reading frame (ORF) using a deletion mutant of the ASFV currently circulating throughout Eurasia. The recombinant ASFV lacking the MGF110-1L gene (ASFV-G-ΔMGF110-1L) demonstrated in vitro that the MGF110-1L gene is non-essential, since ASFV-G-ΔMGF110-1L had similar replication kinetics in primary swine macrophage cell cultures when compared to parental highly virulent field isolate Georgia2007 (ASFV-G). Experimental infection of domestic pigs with ASFV-G-ΔMGF110-1L produced a clinical disease similar to that caused by the parental ASFV-G, confirming that deletion of the MGF110-1L gene from the ASFV genome does not affect viral virulence.
Diversity and Structure of Pelagic Zooplankton (Crustacea, Rotifera) in NE Poland
Authors: Karpowicz Maciej , Ejsmont-Karabin Jolanta
Published: February 2021

This study presents the diversity and structure of pelagic zooplankton in north-eastern Poland. The research was conducted in 47 lakes with different trophic conditions in the middle of summer. Samples were collected close to the deepest part of the lakes to avoid the diverse benthic and littoral zones. We found 119 zooplankton species of which 32 were Cladocera, 16 were Cyclopoida, 4 were Calanoida, and 67 were Rotifera. We determined which species occurred most frequently in the region, as well as the species that were characteristic of different trophic conditions. We also recorded the presence of eight cold-adapted species which some of them are considered as glacial relicts (e.g., Eurytemora lacustris, Heterocope appendiculata, Cyclops lacustris). Our research revealed potential glacial refugia for planktonic species in 14 lakes of NE Poland. Our study suggests that the presence of stenotherm species may be an excellent indicator of the ecological status of deep lakes and could be considered in lake monitoring programs. Furthermore, we did not find Bythotrephes longimanus which has been reported from Poland. Instead, we found that B. brevimanus was the most common representative of the genus in the study area.