bluuebunny/crossref_metadata_2025 huggingface dataset:
Antibacterial Activity and Protection Efficiency of Polyvinyl Butyral Nanofibrous Membrane Containing Thymol Prepared through Vertical Electrospinning
Authors: Lu Wen-Chi , Chen Ching-Yi , Cho Chia-Jung , Venkatesan Manikandan , Chiang Wei-Hung , Yu Yang-Yen , Lee Chen-Hung , Lee Rong-Ho , Rwei Syang-Peng , Kuo Chi-Ching
Published: April 2021

Human safety, health management, and disease transmission prevention have become crucial tasks in the present COVID-19 pandemic situation. Masks are widely available and create a safer and disease transmission–free environment. This study presents a facile method of fabricating masks through electrospinning nontoxic polyvinyl butyral (PVB) polymeric matrix with the antibacterial component Thymol, a natural phenol monoterpene. Based on the results of Japanese Industrial Standards and American Association of Textile Chemists and Colorists methods, the maximum antibacterial value of the mask against Gram-positive and Gram-negative bacteria was 5.6 and 6.4, respectively. Moreover, vertical electrospinning was performed to prepare Thymol/PVB nanofiber masks, and the effects of parameters on the submicron particulate filtration efficiency (PFE), differential pressure, and bacterial filtration efficiency (BFE) were determined. Thorough optimization of the small-diameter nanofiber–based antibacterial mask led to denser accumulation and improved PFE and pressure difference; the mask was thus noted to meet the present pandemic requirements. The as-developed nanofibrous masks have the antibacterial activity suggested by the National Standard of the Republic of China (CNS 14774) for general medical masks. Their BFE reaches 99.4%, with a pressure difference of <5 mmH2O/cm2. The mask can safeguard human health and promote a healthy environment.
Urban Land Mapping Based on Remote Sensing Time Series in the Google Earth Engine Platform: A Case Study of the Teresina-Timon Conurbation Area in Brazil
Authors: Carneiro Eduilson , Lopes Wilza , Espindola Giovana
Published: April 2021

Teresina-Timon conurbation (TTC) area is an example of urban agglomeration, situated in the semiarid environment of the northeast region of Brazil, which has shown an accelerated process of urban development over the last four decades (1985–2019). In this study, we developed a semi-automatic urban land mapping framework at the Google Earth Engine (GEE) platform to (a) evaluate spatiotemporal sprawl of the TTC area (1985–2018); and (b) quantify current urban fabric structures of TTC area (2019). The main empirical results demonstrate that the use of the Landsat historical dataset is a suitable option for generating consistent urban land maps across the years in semiarid environments. Teresina and Timon expanded, respectively, from 70.34 km2 and 12.20 km2 in 1985 to 159.02 km2 and 30.68 km2 in 2018, increasing annually at 3.05% and 3.69% averaged rate, showing an underlying tendency of continuous growth, and magnitude similar to Asian cities. The results of the urban fabric (UF) structures mapping demonstrates a high complexity of the urbanized surfaces, characterized by irregular shapes and variability of urban coverage. In 2019, the TTC metropolitan area was covered by urban land use classes as ceramic roofs, other types of roofs, and impervious surface, in the proportions of 28.02%, 11.97%, and 5.67%, respectively.
Vicarious Calibration of FengYun-3D MERSI-II at Railroad Valley Playa Site: A Case for Sensors with Large View Angles
Authors: Chen Yepei , Sun Kaimin , Li Wenzhuo , Hu Xiuqing , Li Pengfei , Bai Ting
Published: April 2021

Vicarious calibration, as one on-orbit calibration method, is a supplement to onboard calibration of sensors. The application of vicarious calibration, however, is greatly limited due to the time- and effort-consuming field measurements of atmosphere and surface. Fortunately, the Radiometric Calibration Network (RadCalNet) provides automated in situ data at multiple sites, thus increasing the opportunities to achieve ongoing ground-reference calibration of in-orbit instruments. The MEdium Resolution Spectrum Imager-II (MERSI-II) onboard FengYun-3D (FY) has the temporal, spectral, spatial, and radiometric capacity for image capture at a level on par with other sensors used worldwide, such as the Moderate Resolution Imaging Spectroradiometer (MODIS). Its on-orbit radiometric performance, however, is assessed in a limited manner. In this study, the reflectance-based vicarious calibration method was employed to calibrate the MERSI-II sensor using ground measurements from RadCalNet at the Railroad Valley Playa site. The calibration of the MERSI-II sensor with large view angles presents difficulties due to the uncertainties introduced by surface bidirectional reflectance distribution function (BRDF) effects. Thus, we performed BRDF correction to harmonize the sensor and ground measurements to consistent observation geometries, before the in-situ measurements were taken as inputs for the 6SV radiative transfer model to predict at-sensor radiance. The calibration results were comprehensively validated with ground data and MODIS benchmark datasets. The results show that accounting for BRDF correction could improve the accuracy of vicarious calibration and ensure inter-consistency between different sensors. An analysis of the vicarious calibration of FY-3D MERSI-II yielded uncertainties of <5% for solar reflective bands, which meets the radiometric accuracy requirements typical for land-monitoring space missions. The proposed approach is also applicable to the calibration of other large footprint sensors.
A Comparison between Support Vector Machine and Water Cloud Model for Estimating Crop Leaf Area Index
Authors: Hosseini Mehdi , McNairn Heather , Mitchell Scott , Robertson Laura Dingle , Davidson Andrew , Ahmadian Nima , Bhattacharya Avik , Borg Erik , Conrad Christopher , Dabrowska-Zielinska Katarzyna , de Abelleyra Diego , Gurdak Radoslaw , Kumar Vineet , Kussul Nataliia , Mandal Dipankar , Rao Y. S. , Saliendra Nicanor , Shelestov Andrii , Spengler Daniel , Verón Santiago R. , Homayouni Saeid , Becker-Reshef Inbal
Published: April 2021

The water cloud model (WCM) can be inverted to estimate leaf area index (LAI) using the intensity of backscatter from synthetic aperture radar (SAR) sensors. Published studies have demonstrated that the WCM can accurately estimate LAI if the model is effectively calibrated. However, calibration of this model requires access to field measures of LAI as well as soil moisture. In contrast, machine learning (ML) algorithms can be trained to estimate LAI from satellite data, even if field moisture measures are not available. In this study, a support vector machine (SVM) was trained to estimate the LAI for corn, soybeans, rice, and wheat crops. These results were compared to LAI estimates from the WCM. To complete this comparison, in situ and satellite data were collected from seven Joint Experiment for Crop Assessment and Monitoring (JECAM) sites located in Argentina, Canada, Germany, India, Poland, Ukraine and the United States of America (U.S.A.). The models used C-Band backscatter intensity for two polarizations (like-polarization (VV) and cross-polarization (VH)) acquired by the RADARSAT-2 and Sentinel-1 SAR satellites. Both the WCM and SVM models performed well in estimating the LAI of corn. For the SVM, the correlation (R) between estimated LAI for corn and LAI measured in situ was reported as 0.93, with a root mean square error (RMSE) of 0.64 m2m−2 and mean absolute error (MAE) of 0.51 m2m−2. The WCM produced an R-value of 0.89, with only slightly higher errors (RMSE of 0.75 m2m−2 and MAE of 0.61 m2m−2) when estimating corn LAI. For rice, only the SVM model was tested, given the lack of soil moisture measures for this crop. In this case, both high correlations and low errors were observed in estimating the LAI of rice using SVM (R of 0.96, RMSE of 0.41 m2m−2 and MAE of 0.30 m2m−2). However, the results demonstrated that when the calibration points were limited (in this case for soybeans), the WCM outperformed the SVM model. This study demonstrates the importance of testing different modeling approaches over diverse agro-ecosystems to increase confidence in model performance.
Flexible Tactile Sensor Based on Patterned Ag-Nanofiber Electrodes through Electrospinning
Authors: Chen Mengxiao , Wang Zhe , Zheng Yu , Zhang Qichong , He Bing , Yang Jiao , Qi Miao , Wei Lei
Published: April 2021

The growing demand for intelligent equipment has greatly inspired the development of flexible devices. Thus, disparate flexible multifunctional devices, including pressure sensitive flexible/stretchable displays, have drawn worldwide research attention. Electrodes maintaining conductivity and mechanical strength against deformations are indispensable components in all prospective applications. In this work, a flexible pressure mapping sensor array is developed based on patterned Ag-nanofibers (Ag-NFs) electrode through electrospinning and lithography. The metallic Ag layer is sputtered onto the electrospinning polyvinyl alcohol (PVA) NFs. A uniform and super conductive electrode layer with outstanding mechanical performance is thus formed after dissolving PVA. Followed by the traditional lithography method, a patterned electrode array (4 × 4 sensors) is obtained. Based on the newly developed triboelectric nanogenerator (TENG) technology, a flexible pressure-mapping sensor with excellent stability towards bending deformations is further demonstrated. Moreover, a letter “Z” is successfully visualized by this pressure sensor array, encouraging more human–machine interactive implementations, such as multi-functional tactile screens.
An Improved Method for Stable Feature Points Selection in Structure-from-Motion Considering Image Semantic and Structural Characteristics
Authors: Wang Fei , Liu Zhendong , Zhu Hongchun , Wu Pengda , Li Chengming
Published: April 2021

Feature matching plays a crucial role in the process of 3D reconstruction based on the structure from motion (SfM) technique. For a large collection of oblique images, feature matching is one of the most time-consuming steps, and the matching result directly affects the accuracy of subsequent tasks. Therefore, how to extract the reasonable feature points robustly and efficiently to improve the matching speed and quality has received extensive attention from scholars worldwide. Most studies perform quantitative feature point selection based on image Difference-of-Gaussian (DoG) pyramids in practice. However, the stability and spatial distribution of feature points are not considered enough, resulting in selected feature points that may not adequately reflect the scene structures and cannot guarantee the matching rate and the aerial triangulation accuracy. To address these issues, an improved method for stable feature point selection in SfM considering image semantic and structural characteristics is proposed. First, the visible-band difference vegetation index is used to identify the vegetation areas from oblique images, and the line feature in the image is extracted by the optimized line segment detector algorithm. Second, the feature point two-tuple classification model is established, in which the vegetation area recognition result is used as the semantic constraint, the line feature extraction result is used as the structural constraint, and the feature points are divided into three types. Finally, a progressive selection algorithm for feature points is proposed, in which feature points in the DoG pyramid are selected by classes and levels until the number of feature points is satisfied. Oblique images of a 40-km2 area in Dongying city, China, were used for validation. The experimental results show that compared to the state-of-the-art method, the method proposed in this paper not only effectively reduces the number of feature points but also better reflects the scene structure. At the same time, the average reprojection error of the aerial triangulation decrease by 20%, the feature point matching rate increase by 3%, the selected feature points are more stable and reasonable.
Computational Strategies for the Identification of a Transcriptional Biomarker Panel to Sense Cellular Growth States in Bacillus subtilis
Authors: Huang Yiming , Smith Wendy , Harwood Colin , Wipat Anil , Bacardit Jaume
Published: April 2021

A goal of the biotechnology industry is to be able to recognise detrimental cellular states that may lead to suboptimal or anomalous growth in a bacterial population. Our current knowledge of how different environmental treatments modulate gene regulation and bring about physiology adaptations is limited, and hence it is difficult to determine the mechanisms that lead to their effects. Patterns of gene expression, revealed using technologies such as microarrays or RNA-seq, can provide useful biomarkers of different gene regulatory states indicative of a bacterium’s physiological status. It is desirable to have only a few key genes as the biomarkers to reduce the costs of determining the transcriptional state by opening the way for methods such as quantitative RT-PCR and amplicon panels. In this paper, we used unsupervised machine learning to construct a transcriptional landscape model from condition-dependent transcriptome data, from which we have identified 10 clusters of samples with differentiated gene expression profiles and linked to different cellular growth states. Using an iterative feature elimination strategy, we identified a minimal panel of 10 biomarker genes that achieved 100% cross-validation accuracy in predicting the cluster assignment. Moreover, we designed and evaluated a variety of data processing strategies to ensure our methods were able to generate meaningful transcriptional landscape models, capturing relevant biological processes. Overall, the computational strategies introduced in this study facilitate the identification of a detailed set of relevant cellular growth states, and how to sense them using a reduced biomarker panel.
Pulsed Thermal Method for Monitoring Cell Proliferation in Real-Time
Authors: Bormans Seppe , Oudebrouckx Gilles , Vandormael Patrick , Vandenryt Thijs , Wagner Patrick , Somers Veerle , Thoelen Ronald
Published: April 2021

The study of cell proliferation is of great importance for medical and biological research, as well as for industrial applications. To render the proliferation process accurately over time, real-time cell proliferation assay methods are required. This work presents a novel real-time and label-free approach for monitoring cell proliferation by continuously measuring changes in thermal properties that occur at the sensor interface during the process. The sensor consists of a single planar resistive structure deposited on a thin foil substrate, integrated at the bottom of a cell culture reservoir. During measurement, the structure is excited with square wave current pulses. Meanwhile, the temperature-induced voltage change measured over the structure is used to derive variations in the number of cells at the interface. This principle is demonstrated first by performing cell sedimentation measurements to quantify the presence of cells at the sensor interface in the absence of cell growth. Later, cell proliferation experiments were performed, whereby parameters such as the available nutrient content and the cell starting concentration were modified. Results from these experiments show that the thermal-based sensor is able to accurately measure variations in the number of cells at the interface. Moreover, the influence of the modified parameters could be observed in the obtained proliferation curves. These findings highlight the potential for the presented thermal method to be incorporated in a standardized well plate format for high-throughput monitoring of cell proliferation.
Easy Computation of the Various Topologies and Modes of Liquid–Liquid Partition Chromatography by the Theory of Random Walks
Authors: Dijoux Frédéric R. , Mandova Tsvetelina
Published: April 2021

The article revisits the discrete recurrence method to model the instruments of liquid–liquid partition chromatography as counter-current chromatography (CCC) and centrifugal partition chromatography (CPC). The purpose is to simplify the computation of the concentration profiles without supplementary approximations, rather by going back to the seminal model of binomial random walks, associated with the stochastic master equation that generates simple discrete recurrence relations. It fits the model of the prototype of liquid–liquid chromatography: the Craig’s apparatus. Three emblematic separation technique group cases are computed in batch injection, batch multiple dual mode (MDM), and continuous injection by the “True Moving Bed” (TMB) in CPC.
A Study on the Reaction Kinetics of Anaerobic Microbes Using Batch Anaerobic Sludge Technique for Beverage Industrial Wastewater
Authors: Um-e-Habiba  , Khan Muhammad Saleem , Raza Waseem , Gul Hajera , Hussain Maham , Malik Barizah , Azam Mudassar , Winter Franz
Published: April 2021

In this study, a low-cost, efficient, and environmentally friendly anaerobic sludge process for the treatment of industrial beverage wastewater was investigated to analyze the effect of bacteria growth on the degradation of organic matter (chemical oxygen demand). Additionally, the mechanism, interactions between the microbe’s growth, and operating conditions of an anaerobic batch reactor along with the wastewater treatment efficiency were evaluated via microbial kinetics. The kinetic coefficients based on chemical oxygen demand (COD) by conventional techniques such as kinetic coefficients growth yield (0.46 mg VSS/mg COD), saturation coefficient (3500 mg/L COD), the maximum rate of substrate utilization per unit mass of biomass (0.0066 mg/L COD), growth rate by Monod equation, M (0.03833 L/h), and maximum growth rate, μm (0.03672 L/h) were calculated. The results show a higher rate of substrate degradation (0.54 day−1) due to the high COD removal efficiency (CRE) of 99.31% during 13 days that was achieved, which can be attributed to the active involvement of anaerobic microbes in the process of degradation. Based on these results, it can be concluded that the current study can be used as an effective way to analyze the industrial beverage wastewater at commercial levels.
Strategies for Gaining Full Citizenship in the First Generation of Indochinese Students
Authors: Fossard Brice
Published: April 2021

The history of the acquisition of French citizenship by Indochinese university élites remains yet to be written because few researchers have looked at the role played by sport and physical education in developing the Vietnamese élite. These young students discovered such physical activities at school and many of them claimed judicial/legal equality with the French. This article will demonstrate that sports and physical education were the key stages in a strategy for certain Indochinese students to become French citizens. At the same time, this tactic generated much tension within the Vietnamese student community between the two world wars.
HRV in Active-Duty Special Forces and Public Order Military Personnel
Authors: Gancitano Giuseppe , Baldassarre Antonio , Lecca Luigi Isaia , Mucci Nicola , Petranelli Marco , Nicolia Mario , Brancazio Antonio , Tessarolo Andrea , Arcangeli Giulio
Published: April 2021

Heart rate variability (HRV) is a simple, non-invasive, real-time analyzable, and highly reproducible measurement that captures incidences for assessing a person’s health and physical condition. Public security jobs are characterized by major exposure to risk factors known to influence the cardiovascular response to stimuli, e.g., night shifts, highly physically demanding activity, and acute stress activity. This study aimed to evaluate the HRV parameters in a population of 112 male personnel of the special forces and public order of the Carabinieri, aged 25–59, when engaged in several duty tasks, such as paratroopers, night shift police station officers, night shift patrol, dynamic precision shooting evaluative team, dynamic precision shooting non-evaluative team, and office clerks (used as control group). During the specific task of each participant, the HRV parameters were collected with wearable devices and processed. The HRV parameters in the time and frequency domains collected were average heart rate, standard deviation of all normal RR intervals, root mean square of successive differences in adjacent normal-to-normal (NN) intervals, very-low-frequency power, low-frequency power, high-frequency power, stress index, parasympathetic nervous system activity index, and sympathetic nervous system activity index. Parametric tests for independent series to compare the HRV parameters by subgroups within the study subjects were used. A multivariate linear regression analysis was conducted to evaluate the association between the HRV parameters and some personal and organizational factors. The comparison between different subgroups showed that activities with a high demand for concentration and precision, as is the case with paratroopers and dynamic precision shooters, differ significantly from activities that can be defined as routine, such as office work. Other activities, such as patrolling or remote management from operations centers, although including critical elements, did not deviate significantly from the control group. The study of HRV parameters is therefore a useful tool for occupational physicians, both for addressing work suitability assessments and for better targeting health promotion campaigns, to be considered as being aimed at monitoring the subject’s physiological parameters, and not at the diagnosis of any pathological condition, which should always be carried out by the medical specialist.
Meta-Analysis on Energy-Use Patterns of Cropping Systems in Iran
Authors: Zangeneh Morteza , Banaeian Narges , Clark Sean
Published: April 2021

We present a meta-analysis of energy-consumption and environmental-emissions patterns in Iranian cropping systems using data collected from articles published between 2008 and 2018 for 21 different crops. The results show that the crops consuming the most energy per hectare are tomato, sugarcane, cucumber and alfalfa, while sunflower consumed the least. The average total energy input for all crops in Iran during the study period was 48,029 MJ ha−1. Our analysis revealed that potato has the highest potential to reduce energy consumption and that electricity and fertilizer inputs have the most potential for energy savings in cropping systems. Not all studies reviewed addressed the factors that create energy consumption patterns and environmental emissions. Therefore, eight indicators were modeled in this meta-analysis, which include Total Energy Input, Energy Productivity, Energy Use Efficiency, Net Energy, Greenhouse Gas Emissions, Technical Efficiency, Pure Technical Efficiency and Scale Efficiency. The effects of region (which was analyzed in terms of climate), year and crop or product type on these eight indicators were modeled using meta-regression and the nonparametric Kruskal–Wallis test. To create a comprehensive picture and roadmap for future research, the process of the agricultural-systems analysis cycle is discussed. This review and meta-analysis can be used as a guide to provide useful information to researchers working on the energy dynamics of agricultural systems, especially in Iran, and in making their choices of crop types and regions in need of study.
Improving the Tourist’s Perception of the Tourist Destinations Image: An Analysis of Chinese Kung Fu Film and Television
Authors: Chen Huan , Zuo Yifan , Law Rob , Zhang Mu
Published: April 2021

Cultural media, film, and television works can increase the popularity of the image of tourist destinations, thereby promoting the sustainable development of the tourism industry and obtaining economic benefits. This study takes Chinese kung fu film and television as examples to explore the mechanism of audience participation in the perception of tourist destinations. It further explores the mediating effect of cultural contact. The study took the image perception of tourist destinations as the dependent variable and audience participation as the independent variable. A total of 331 subjects were surveyed, and a multi-layer regression model was established to test the rationality and validity of the hypothetical theoretical model. The research results show that audience participation in martial arts films and television tourism can directly and indirectly affect the audience’s perception of martial arts culture. At the same time, the viewer can achieve contact with martial arts culture through film and television, accordingly forming his or her perception of the destination. In other words, film and television audience participation can bring more cultural contact to the audience. In turn, cultural contact can enhance the image perception of tourist destinations and play an important intermediary role in the process of audience participation by enhancing the perception of tourist destinations. By confirming the variable relationship in Wushu film and television tourism, this research fills the gap between the two aspects, which contributes to promoting the two-way interaction between Wushu film and television works and tourism marketing and achieving the long-term sustainable development of tourism destinations.
Alfalfa for a Sustainable Ovine Farming System: Proposed Research for a New Feeding Strategy Based on Alfalfa and Ecological Leftovers in Drought Conditions
Authors: Viti Carlo , Bellabarba Agnese , Daghio Matteo , Mengoni Alessio , Mele Marcello , Buccioni Arianna , Pacini Gaio Cesare , Bekki Abdelkader , Azim Khalid , Hafidi Majida , Pini Francesco
Published: April 2021

In the past 10 years, the average demand for meat and milk across the world has significantly increased, especially in developing countries. Therefore, to support the production of animal-derived food products, a huge quantity of feed resources is needed. This paper does not present original research, but rather provides a conceptual strategy to improve primary production in a sustainable way, in relation to forthcoming issues linked to climate change. Increases in meat and milk production could be achieved by formulating balanced diets for ovines based on alfalfa integrated with local agricultural by-products. As the central component of the diet is alfalfa, one goal of the project is increasing the yield of alfalfa in a sustainable way via inoculating seeds with symbiotic rhizobia (i.e., Sinorhizobium meliloti). Seed inoculants are already present on the market but have not been optimized for arid soils. Furthermore, a part of the project is focused on the selection of elite symbiotic strains that show increased resistance to salt stress and competitiveness. The second component of the experimental diets is bio-waste, especially that obtained from olive oil manufacturing (i.e., pomace). The addition of agro-by-products allows us to use such waste as a resource for animal feeding, and possibly, to modulate rumen metabolism, thereby increasing the nutritional quality of milk and meat.
When GIS Joins the Conservation Management Plan of a 20th-Century Architectural Heritage
Authors: Garzulino Andrea , Borgarino Maria Paola , Del Curto Davide
Published: April 2021

The paper discusses how a Geographic Information System (GIS) contributes to set up a Conservation Management Plan (CMP) for the sustainable preservation of a 20th-century architectural masterpiece. The National Art Schools of Cuba are presented as a case study. The complex consists of five iconic buildings built in the early 1960s within a 56-hectare city-park. Since they are today underused and in a poor state of conservation, a research project among Italy, Cuba, and the US addressed a CMP’s preparation between 2018 and 2020. A GIS was prepared to collect and manage the whole data, based on graphic support consistent with both the site’s features and the research’s goal, to set up a comprehensive Conservation Management Plan. By illustrating this experience’s pros and cons, the paper discusses how GIS may contribute to the conservation and sustainable management of such extensive 20th-century architectural complexes.
Asking the Right Questions for Sustainable Development Goals: Performance Assessment Approaches for the Qatar Education System
Authors: Al-Kuwari Mona M. , Al-Fagih Luluwah , Koç Muammer
Published: April 2021

Questions determine our fate as individuals and societies. Asking the right questions at the right time and in the right amount makes our choices and decisions meaningful. As human beings we all experience this from an early age. In education, in order to evaluate, learn and inform the growth of students, the professional development of teachers and the overall efficiency of the system, questions become an integral element of the complex, non-linear and social system at different levels. The purpose of this article is to investigate how performance assessment strategies play a role in the education system, and to understand how progressive performance assessments can be set up with sustainable thinking and designed in alignment with the United Nation’s (UN) Development Goals (SGDs) for a given context. To aid Qatar’s pursuit in transitioning from a resource-based economy to a knowledge-based one, this study aims to design and develop a proper performance assessment (PA) framework that is aligned with the SDGs and education goals (EGs) to help achieve social and human development as envisioned in Qatar’s national vision. This article: (i) presents a theoretical and qualitative analysis of PA practices in the Qatar Education System (QES); (ii) provides a comparative analysis among the best PA practices at the global level; and (iii) examines the methodology, conditions, and findings based on learning from: (a) the successful experiences of other countries, (b) documented analyses of local past experiences, (c) local stakeholders (through a qualitative investigation) in order to understand the needs, develop recommendations and design a tailored PA strategy. The results indicate that there are misalignments between the core educational components such as EGs and the assessment methods used to evaluate them. The analysis and findings reveal that the QES urgently needs to develop a PA strategy that is appropriate for its stakeholders to meet the EGs and enhance their sustainability competencies. Finally, this study proposes a PA framework for the QES to align its core elements with SDGs and EGs.
Evaluating Nature-Based Solution for Flood Reduction in Spercheios River Basin under Current and Future Climate Conditions
Authors: Spyrou Christos , Loupis Michael , Charizopoulos Νikos , Apostolidou Ilektra , Mentzafou Angeliki , Varlas George , Papadopoulos Anastasios , Dimitriou Elias , Panga Depy , Gkeka Lamprini , Bowyer Paul , Pfeifer Susanne , Debele Sisay E. , Kumar Prashant
Published: April 2021

Nature-based solutions (NBS) are being deployed around the world in order to address hydrometeorological hazards, including flooding, droughts, landslides and many others. The term refers to techniques inspired, supported and copied from nature, avoiding large constructions and other harmful interventions. In this work the development and evaluation of an NBS applied to the Spercheios river basin in Central Greece is presented. The river is susceptible to heavy rainfall and bank overflow, therefore the intervention selected is a natural water retention measure that aims to moderate the impact of flooding and drought in the area. After the deployment of the NBS, we examine the benefits under current and future climate conditions, using various climate change scenarios. Even though the NBS deployed is small compared to the rest of the river, its presence leads to a decrease in the maximum depth of flooding, maximum velocity and smaller flooded areas. Regarding the subsurface/groundwater storage under current and future climate change and weather conditions, the NBS construction seems to favor long-term groundwater recharge.
A Multi-Dimensional Hybrid Learning Environment for Business Education: A Knowledge Dynamics Perspective
Authors: Pavlidou Ioanna , Dragicevic Nikolina , Tsui Eric
Published: April 2021

The main promise of new, digitally enabled and hybrid learning environments is to enable future-ready knowledge workers by equipping them with business and digital competences. However, business education (BE) research often focuses on the problems of instructional design and individual disciplines, rather than on the challenges of developing a holistic knowledge and competences required to ensure students’ long-term employability. This paper, to address this gap, approaches BE as a knowledge dynamics field that consists of rational, emotional and spiritual knowledge and proposes a related framework to serve as a guide for developing and analyzing a hybrid learning environment (HLE) that would support BE. Then, it uses the developed framework in an interview-based study to understand the students’ perceptions of how the implementation of an HLE in postgraduate course stimulated knowledge dynamics for BE. The results show that the HLE stimulated different aspects of knowledge due to the diversity of modes of learning-Face-to-Face (F2F) and online, the diversification of learning sources and the internationalization of the course-level curriculum. These results pave the direction for teachers to use the knowledge framework as a compass for future implementations and evaluations of similar methods.
The Effect of Open Innovation on Eco-Innovation Performance: The Role of Market Knowledge Sources
Authors: Sanchez-Henriquez Fernando , Pavez Ignacio
Published: April 2021

Organizations use multiple strategies to increase the number and impact of eco-innovations as a path to achieve competitive advantage. In this article, we study the role of open innovation activities, specifically related to market sources, as a driver of eco-innovation performance. While studies have looked at the relationship between these two emergent innovation phenomena from a broad perspective, we explore whether specific market knowledge sources—clients, suppliers, competitors, and consultants—and their combined use—affect eco-innovation performance. We rely on insights from theories of open innovation and sustainable and environmental innovation to build a theoretical framework about the determinants of eco-innovation performance from a market-driven open innovation perspective. Our sample consists of 3047 firm-year observations obtained from three consecutive panels of the Chilean Innovation Survey (2009–2014). We found that clients, suppliers, competitors, and consultants as knowledge sources positively influence eco-innovation performance in firms. In addition, our results suggest that a combination of client sourcing with supplier and consultant sources of knowledge positively affect eco-innovation performance. We discuss the implications of our findings for open innovation activities on eco-innovation and suggest ideas for future research.
Novel Fuzzy Composite Indicators for Locating a Logistics Platform under Sustainability Perspectives
Authors: Ayadi Hana , Hamani Nadia , Kermad Lyes , Benaissa Mounir
Published: April 2021

The purpose of this paper is to help decision-makers choose the location of a logistics platform with sustainability perspectives. This study presents a compensatory and partially compensatory approach to build composite indicators, using mainly fuzzy multi-criteria decision-making methods. In the first instance, the fuzzy full consistency method (F-FUCOM) was used to calculate the weight of the criteria and sub-criteria. In the second instance, two aggregation methods, namely the fuzzy multi-attribute ideal-real comparative analysis (F-MAIRCA) and the fuzzy preference ranking organization method for enrichment evaluation (F-PROMETHEE), were used to rank the location of a logistics platform. The novelty of the work lays in studying the impact of limited sustainability and weak sustainability on the location of a logistics platform. In this respect, the aggregation of various sustainability criterion in fuzzy compensatory and partially compensatory composite indicators is an innovative and interesting approach used to locate a logistics platform. The obtained results show that economic sustainability is the most important criterion for the selection of a logistics platform, followed by the environmental criterion. Obviously, the F-MAIRCA and F-PROMETHEE methods provided the same ranking orders. Finally, sensitivity analyses were performed to validate the robustness of the proposed approach.
Food Plastic Packaging Transition towards Circular Bioeconomy: A Systematic Review of Literature
Authors: Beltran Macarena , Tjahjono Benny , Bogush Anna , Julião Jorge , Teixeira Evandro L. S.
Published: April 2021

Advancement in packaging technology has played an essential role in reducing food waste and losses; however, most of this technology relies mostly on the use of plastics. Thus, there is an imminent need to think seriously about the transition towards a circular bioeconomy of innovative biobased materials with biodegradability potentials. This paper examines the driving forces behind the changes in food plastic packaging regimes and specifically seeks to understand how socio-technical configurations may influence niches to transition to a circular bioeconomy, particularly biobased biodegradable plastic materials. By employing a systematic review of the literature, we find that coordination with other back-end socio-technical systems that provide valorization of packaging waste is crucial to enable the transition. The literature indicates that one possible transition path is that the biobased biodegradable materials serve as “carriers of food waste”. The paper contributes to the discussion on the dynamics of food packaging in the transition to a bioeconomy viewed through the lenses of a socio-technical system (niche–regime–landscape), which continues to reinforce future actions, leading to better management of packaging end-of-life.
Tourism and Air Quality during COVID-19 Pandemic: Lessons for the Future
Authors: Monteiro Alexandra , Eusébio Celeste , Carneiro Maria João , Madaleno Mara , Robaina Margarita , Rodrigues Vitor , Gama Carla , Relvas Hélder , Russo Michael , Oliveira Kevin , Lopes Myriam , Borrego Carlos
Published: April 2021

The pandemic caused by coronavirus SARS-CoV-2 (associated to the disease named COVID-19) is having a global impact that affects health, the economy and the environment. These impacts are negative in most of the sectors but benefits also occurred in specific fields. Tourism was one of the most negatively affected economic sectors, and in terms of benefits, the improvement of air quality can be highlighted, with positive health implications. This paper aims to evaluate the impacts on these two particular fields—tourism and air quality—focusing on Portugal due to the relevance of tourism in the country. The research carried out in this paper enables us to find the most critical areas and identifies lessons learnt and recommendations for the post-COVID period. Tourism and air quality data were collected for both 2019 and 2020 and compared in terms of quantitative and spatial analysis. The Lisbon metropolitan area—the geographical area where the capital of the country is located—was the area that suffered the most negative impacts in terms of tourism activity but was also the one where highest benefits in terms of air pollution reduction and human exposure were felt. Recommendations for future strategies are suggested, including new concepts of tourism connected to the environment; the investment in online/virtual tourism activities; promotion of the domestic market; mitigation of the over-tourism problem and using environmental issues, such as air quality, as new attractiveness criteria for tourism destinations.
Identification of Road Traffic Injury Risk Prone Area Using Environmental Factors by Machine Learning Classification in Nonthaburi, Thailand
Authors: Worachairungreung Morakot , Ninsawat Sarawut , Witayangkurn Apichon , Dailey Matthew N.
Published: April 2021

Road traffic injuries are a major cause of morbidity and mortality worldwide and currently rank ninth globally among the leading causes of disease burden regarding disability-adjusted life years lost. Nonthaburi and Pathum Thani are parts of the greater Bangkok metropolitan area, and the road traffic injury rate is very high in these areas. This study aimed to identify the environmental factors affecting road traffic injury risk prone areas and classify road traffic injuries from an environmental factor dataset using machine learning algorithms. Road traffic injury risk prone areas were set as the dependent variables for the analysis, with other factors that influence road traffic injury risk prone areas being set as independent variables. A total of 20 environmental factors were selected from the spatial datasets. Then, machine learning algorithms were applied using a grid search. The first experiment from 2017 in Nonthaburi and Pathum Thani was used for training the model, and then, 2018 data from Nonthaburi and Pathum Thani were used for validation. The second experiment used 2018 Nonthaburi data for the training, and 2018 Pathum Thani data were used for the validation. The important factors were grocery stores, convenience stores, electronics stores, drugstores, schools, gas stations, restaurants, supermarkets, and road geometrics, with length being the most critical factor that influenced the road traffic injury risk prone model. The first and second experiments in a random forest model provided the best model environmental factors affecting road traffic injury risk prone areas, and machine learning can classify such road traffic injuries.
Food Values, Satisfaction, and Loyalty: Some Evidence in Grocery Retailing Acquired during the COVID-19 Pandemic
Authors: Muro-Rodríguez Ana Isabel , Pérez-Jiménez Israel Roberto , Esteban-Dorado Andrea , Martínez-Ruiz María Pilar
Published: April 2021

Recent evidence illuminates the importance of relatively new concepts in grocery retailing, such as the concept of food values. The present work aims at analyzing the influence of: (i) food values on key non-financial results, particularly satisfaction and loyalty; and (ii) satisfaction on loyalty. The paper makes a further delineation for both satisfaction and loyalty (i.e., with the product and with the grocery store), as well as considers the potential implications derived from the COVID-19 pandemic. With these objectives in mind, the paper distributed an online survey to the residents of Toledo (Spain) during April and May 2020 (a period characterized by a national lockdown, where grocery stores and essential business were open to the public). This effort produced 303 valid questionnaires and the resulting data were analyzed by using descriptive statistics alongside linear parametric regressions. The findings show how food values have a positive and significant influence on both types of satisfaction and loyalty; there is also a significant and positive influence of both types of satisfaction on both types of loyalty. Moreover, the results corroborate previous works about the most influential food values. These findings highlight the importance of considering food values in grocery retailing in order to achieve key non-financial benefits. The paper ends with a discussion of several interesting managerial guidelines, particularly in light of situations like the COVID-19 pandemic.
Water-Stressed Plants Do Not Cool: Leaf Surface Temperature of Living Wall Plants under Drought Stress
Authors: Gräf Michael , Immitzer Markus , Hietz Peter , Stangl Rosemarie
Published: April 2021

Urban green infrastructures offer thermal regulation to mitigate urban heat island effects. To gain a better understanding of the cooling ability of transpiring plants at the leaf level, we developed a method to measure the time series of thermal data with a miniaturized, uncalibrated thermal infrared camera. We examined the canopy temperature of four characteristic living wall plants (Heuchera x cultorum, Bergenia cordifolia, Geranium sanguineum, and Brunnera macrophylla) under increasing drought stress and compared them with a well-watered control group. The method proved suitable to evaluate differences in canopy temperature between the different treatments. Leaf temperatures of water-stressed plants were 6 to 8 °C higher than those well-watered, with differences among species. In order to cool through transpiration, vegetation in green infrastructures must be sufficiently supplied with water. Thermal cameras were found to be useful to monitor vertical greening because leaf surface temperature is closely related to drought stress. The usage of thermal cameras mounted on unmanned aerial vehicles could be a rapid and easy monitoring system to cover large façades.
The Unexplored Socio-Cultural Benefits of Coffee Plants: Implications for the Sustainable Management of Ethiopia’s Coffee Forests
Authors: Bulitta Bikila Jabessa , Duguma Lalisa A.
Published: April 2021

Coffee is among the most popular commodity crops around the globe and supports the livelihoods of millions of households along its value chain. Historically, the broader understanding of the roles of coffee has been limited to its commercial value, which largely is derived from coffee, the drink. This study, using in-depth interviews and focus group discussions, explores some of the unrevealed socio-cultural services of coffee of which many people are not aware. The study was conducted in Gomma district, Jimma Zone, Oromia National Regional state, Ethiopia, where arabica coffee was first discovered in its natural habitat. Relying on a case study approach, our study uses ethnographic study methods whereby results are presented from the communities’ perspectives and the subsequent discussions with the communities on how the community perspectives could help to better manage coffee ecosystems. Coffee’s utilities and symbolic functions are numerous—food and drink, commodity crop, religious object, communication medium, heritage and inheritance. Most of the socio-cultural services are not widely known, and hence are not part of the benefits accounting of coffee systems. Understanding and including such socio-cultural benefits into the wider benefits of coffee systems could help in promoting improved management of the Ethiopian coffee forests that are the natural gene pools of this highly valuable crop.
Water Quality Analysis of Drinking Water Resource Lake Sapanca and Suggestions for the Solution of the Pollution Problem in the Context of Sustainable Environment Approach
Authors: Akıner Muhammed Ernur , Akıner İlknur
Published: April 2021

Lake Sapanca is the drinking water source of the Sakarya province of Turkey. Intensive urbanization in the region is the main obstacle to implementing appropriate physical planning and measures to adapt to rapid change. The monitoring of the water quality parameters in the planning and management of the lakes is significant. The Artificial Neural Network (ANN), a mathematical representation of the human brain’s functioning, was employed to estimate the Lake’s Dissolved Oxygen (DO) concentration. pH, Magnesium (Mg), Temperature (Temp), Chemical Oxygen Demand (COD), Orthophosphate (o-PO4), Nitrite Nitrogen (NO2-N), and Nitrate Nitrogen (NO3-N) were used as independent parameters. The successful ANN model gives better results compared to the traditional multiple linear regression (MLR) analysis. The developed model can be used for forecast purposes to complete the missing data in the future and support the decision process for pollution reduction through sustainable environmental management. The eutrophication threat for Lake Sapanca has been revealed. The main objective is to create the scientific infrastructure that will draw attention to the rapid urbanization problem with ANN and eutrophication models’ outputs. It has been understood that the protection of the water budget of Lake Sapanca is the primary solution method in terms of ecological sustainability to eliminate the existing pollution.