bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of Deep Learning Techniques for Land Use Land Cover Classification in Southern New Caledonia
Authors: Rousset Guillaume , Despinoy Marc , Schindler Konrad , Mangeas Morgan
Published: June 2021

Land use (LU) and land cover (LC) are two complementary pieces of cartographic information used for urban planning and environmental monitoring. In the context of New Caledonia, a biodiversity hotspot, the availability of up-to-date LULC maps is essential to monitor the impact of extreme events such as cyclones and human activities on the environment. With the democratization of satellite data and the development of high-performance deep learning techniques, it is possible to create these data automatically. This work aims at determining the best current deep learning configuration (pixel-wise vs. semantic labelling architectures, data augmentation, image prepossessing, …), to perform LULC mapping in a complex, subtropical environment. For this purpose, a specific data set based on SPOT6 satellite data was created and made available for the scientific community as an LULC benchmark in a tropical, complex environment using five representative areas of New Caledonia labelled by a human operator: four used as training sets, and the fifth as a test set. Several architectures were trained and the resulting classification was compared with a state-of-the-art machine learning technique: XGboost. We also assessed the relevance of popular neo-channels derived from the raw observations in the context of deep learning. The deep learning approach showed comparable results to XGboost for LC detection and over-performed it on the LU detection task (61.45% vs. 51.56% of overall accuracy). Finally, adding LC classification output of the dedicated deep learning architecture to the raw channels input significantly improved the overall accuracy of the deep learning LU classification task (63.61% of overall accuracy). All the data used in this study are available on line for the remote sensing community and for assessing other LULC detection techniques.
Canopy Density and Roughness Differentiate Resistance of a Tropical Dry Forest to Major Hurricane Damage
Authors: Gao Qiong , Yu Mei
Published: June 2021

Tropical dry forest is vulnerable to increased climate variability with more frequent and severe storms. Studies of hurricane impact on tropical dry forest often focused on individual tree traits. How trees in tropical dry forests work together to combat wind damage is still unclear. To address this, we integrated ground-observed ecosystem structure from National Ecological Observation Network (NEON) with airborne-LiDAR images and analyzed resistance in forest structure of Guánica dry forest in Puerto Rico to major hurricanes in 2017 at the forest-stand level. Using each plot instead of the individual tree as the base unit, we regressed mean changes in stem height and fractions of lost or damaged stems at 15 plots on mean stem diameter, mean and standard deviation of stem height, stem density, and topography. Meanwhile, using the LiDAR-derived canopy heights, we compared the changes in canopy height before and after the hurricanes and regressed spatially the canopy height change on prior-hurricane tree cover, canopy height, and rugosity. We found that the damage was small in places with high stem density or high tree cover. Ground-observed damage in terms of height reduction significantly increased with the standard deviation of stem height, an index of roughness, but decreased with the mean stem diameter of the plots. LiDAR-detected damage in terms of reduction in canopy height was also found to decrease with tree cover and mean canopy height when the canopy height was small or moderate but increase with the rugosity. The fraction of lost stems significantly decreased with the stem density, and the fraction of damaged stems significantly increased with the roughness and the plot elevation. The collective parameters of forest stand quantified from ground-observation and LiDAR, such as stem density, tree cover, and canopy roughness or rugosity, highlighted mutual supports of trees and played important roles in resisting damages to the tropical dry forest during major hurricanes.
A Preliminary Damage Assessment Using Dual Path Synthetic Aperture Radar Analysis for the M 6.4 Petrinja Earthquake (2020), Croatia
Authors: Karimzadeh Sadra , Matsuoka Masashi
Published: June 2021

On 29 December 2020, an earthquake with a magnitude of M 6.4 hit the central part of Croatia. The earthquake resulted in casualties and damaged buildings in the town of Petrinja (~6 km away from the epicenter) and surrounding areas. This study aims to characterize ground displacement and to estimate the location of damaged areas following the Petrinja earthquake using six synthetic aperture radar (SAR) images (C-band) acquired from both ascending and descending orbits of the Sentinel-1 mission. Phase information from both the ascending (Sentinel-1A) and descending (Sentinel-1B) datasets, acquired from SAR interferometry (InSAR), is used for estimation of ground displacement. For damage mapping, we use histogram information along with the RGB method to visualize the affected areas. In sparsely damaged areas, we also propose a method based on multivariate alteration detection (MAD) and naive Bayes (NB), in which pre-seismic and co-seismic coherence maps and geocoded intensity maps are the main independent variables, together with elevation and displacement maps. For training, approximately 70% of the data are employed and the rest of the data are used for validation. The results show that, despite the limitations of C-band SAR images in densely vegetated areas, the overall accuracy of MAD+NB is ~68% compared with the results from the Copernicus Emergency Management Service (CEMS).
Development of Magnetic-Based Navigation by Constructing Maps Using Machine Learning for Autonomous Mobile Robots in Real Environments
Authors: Takebayashi Takumi , Miyagusuku Renato , Ozaki Koichi
Published: June 2021

Localization is fundamental to enable the use of autonomous mobile robots. In this work, we use magnetic-based localization. As Earth’s geomagnetic field is stable in time and is not affected by nonmagnetic materials, such as a large number of people in the robot’s surroundings, magnetic-based localization is ideal for service robotics in supermarkets, hotels, etc. A common approach for magnetic-based localization is to first create a magnetic map of the environment where the robot will be deployed. For this, magnetic samples acquired a priori are used. To generate this map, the collected data is interpolated by training a Gaussian Process Regression model. Gaussian processes are nonparametric, data-drive models, where the most important design choice is the selection of an adequate kernel function. These models are flexible and generate mean predictions as well as the confidence of those predictions, making them ideal for their use in probabilistic approaches. However, their computational and memory cost scales poorly when large datasets are used for training, making their use in large-scale environments challenging. The purpose of this study is to: (i) enable magnetic-based localization on large-scale environments by using a sparse representation of Gaussian processes, (ii) test the effect of several kernel functions on robot localization, and (iii) evaluate the accuracy of the approach experimentally on different large-scale environments.
Forecasting Air Temperature on Edge Devices with Embedded AI
Authors: Codeluppi Gaia , Davoli Luca , Ferrari Gianluigi
Published: June 2021

With the advent of the Smart Agriculture, the joint utilization of Internet of Things (IoT) and Machine Learning (ML) holds the promise to significantly improve agricultural production and sustainability. In this paper, the design of a Neural Network (NN)-based prediction model of a greenhouse’s internal air temperature, to be deployed and run on an edge device with constrained capabilities, is investigated. The model relies on a time series-oriented approach, taking as input variables the past and present values of the air temperature to forecast the future ones. In detail, we evaluate three different NN architecture types—namely, Long Short-Term Memory (LSTM) networks, Recurrent NNs (RNNs) and Artificial NNs (ANNs)—with various values of the sliding window associated with input data. Experimental results show that the three best-performing models have a Root Mean Squared Error (RMSE) value in the range 0.289÷0.402∘C, a Mean Absolute Percentage Error (MAPE) in the range of 0.87÷1.04%, and a coefficient of determination (R2) not smaller than 0.997. The overall best performing model, based on an ANN, has a good prediction performance together with low computational and architectural complexities (evaluated on the basis of the NetScore metric), making its deployment on an edge device feasible.
Multitemporal Mapping of Post-Fire Land Cover Using Multiplatform PRISMA Hyperspectral and Sentinel-UAV Multispectral Data: Insights from Case Studies in Portugal and Italy
Authors: Lazzeri Giacomo , Frodella William , Rossi Guglielmo , Moretti Sandro
Published: June 2021

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.
A Variable-Length Chromosome Genetic Algorithm for Time-Based Sensor Network Schedule Optimization
Authors: Ha Van-Phuong , Dao Trung-Kien , Pham Ngoc-Yen , Le Minh-Hoang
Published: June 2021

Scheduling sensor nodes has an important role in real monitoring applications using sensor networks, lowering the power consumption and maximizing the network lifetime, while maintaining the satisfaction to application requirements. Nevertheless, this problem is usually very complex and not easily resolved by analytical methods. In a different manner, genetic algorithms (GAs) are heuristic search strategies that help to find the exact or approximate global optimal solution efficiently with a stochastic approach. Genetic algorithms are advantageous for their robustness to discrete and noisy objective functions, as they are only evaluated at independent points without requirements of continuity or differentiability. However, as explained in this paper, a time-based sensor network schedule cannot be represented by a chromosome with fixed length that is required in traditional genetic algorithms. Therefore, an extended genetic algorithm is introduced with variable-length chromosome (VLC) along with mutation and crossover operations in order to address this problem. Simulation results show that, with help of carefully defined fitness functions, the proposed scheme is able to evolve the individuals in the population effectively and consistently from generation to generation towards optimal ones, and the obtained network schedules are better optimized in comparison with the result of algorithms employing a fixed-length chromosome.
First Step toward Gestural Recognition in Harsh Environments
Authors: Alon Omri , Rabinovich Sharon , Fyodorov Chana , Cauchard Jessica R.
Published: June 2021

We are witnessing a rise in the use of ground and aerial robots in first response missions. These robots provide novel opportunities to support first responders and lower the risk to people’s lives. As these robots become increasingly autonomous, researchers are seeking ways to enable natural communication strategies between robots and first responders, such as using gestural interaction. First response work often takes place in harsh environments, which hold unique challenges for gesture sensing and recognition, including in low-visibility environments, making the gestural interaction non-trivial. As such, an adequate choice of sensors and algorithms needs to be made to support gestural recognition in harsh environments. In this work, we compare the performances of three common types of remote sensors, namely RGB, depth, and thermal cameras, using various algorithms, in simulated harsh environments. Our results show 90 to 96% recognition accuracy (respectively with or without smoke) with the use of protective equipment. This work provides future researchers with clear data points to support them in their choice of sensors and algorithms for gestural interaction with robots in harsh environments.
Physical Health of Food Consumers during the COVID-19 Pandemic
Authors: Oliveira José , Santos Tânia , Sousa Marlene , Lopes João M. , Gomes Sofia , Oliveira Márcio
Published: June 2021

The present research aims to analyze the habits observed in the perception of the general physical health condition of Portuguese food consumers in the COVID-19 pandemic. The investigation is focused on indicators such as weight, physical activity, and consumption habits through the adoption of healthy and not healthy food. Centered on a quantitative approach, the research is based on the application of a questionnaire to a sample of 741 Portuguese consumers, between November 2020 and February 2021, a period during which the most severe measures of social isolation were imposed by the Portuguese government, since the beginning of the pandemic. Moreover, the questionnaire was applied to consumers over 18 years old. According to this population, and considering a 95% confidence level and a margin of error of 4%, the sample has a minimum of 601 responses. Being so, the results of this research are representative for the Portuguese food consumers. The theoretical model was estimated using Partial Least Squares (PLS) in the Smart PLS 3.0 software. The obtained results allowed us to conclude that the Portuguese perception of their weight did not change in the pandemic, despite showing that in general, the pandemic had a negative impact on their physical condition. On the other hand, the results show that the Portuguese associate the practice of physical exercise with physical well-being. Respondents also confirm a positive relationship between “positive eating behaviors (such as consumption of fruits and vegetables, low saturated foods and rich in monounsaturated and polyunsaturated fats” and water consumption) and “the perception of physical health in general”. On the contrary, respondents’ perception of the choice of negative eating behaviors (measured by the consumption of products with a high content of salt and sugar, snacks, and processed frozen and pre-cooked foods) have a negative impact on the “assessment of physical health, in the COVID-19 pandemic”. Hence, it was concluded that the Portuguese consider that an eventual increase in weight does not necessarily correspond to a perception of worse physical health; the practice of physical exercise and good eating habits corresponds to a perception of better physical health; the adoption of bad eating habits corresponds to the perception of bad physical health.
Sustainable Partnership: Operational Condition Analysis for Brand Value Co-Creation
Authors: Hsiung Tzu-Fei , Cheng Yueh-Hsiu , Han Zi-Xun
Published: June 2021

Enterprises are the origin of social innovation. Enterprises implement sustainable relations through “people-oriented” social value creation, particularly other economic developments in the post-2020 COVID-19 pandemic no longer show linear development but more diversity. On the one hand, enterprises must face the fast social transformation towards AI and superintelligence. On the other hand, enterprises must cope with green sustainable development, emphasizing corporate social responsibility in innovative research and development. An increasing number of enterprises respond to the service-oriented and green sustainability-based consumer market today by expanding and collaborating between the upstream and downstream relations in supply chains. Therefore, enterprises must construct a healthy and sustainable dynamic value chain through value co-creation. The study analyzes the types of the dynamic brand value chain and the operational conditions that provide enterprises with the direction in searching for and establishing a sustainable partnership. We employ literature review, case analysis, and in-depth interviews to determine the types and causes of the dynamic brand value chain, followed by integrating sustainable design to verify the sustainability in the dynamic brand value chain model. The study findings show that growth in quadrants of culture for the tandem brand value chain acts as the primary motivation to strengthen a sustainable relationship. Subsequently, the development in pursuit of brand value creation will intensify the sustainable relationships and activities of the brand, causing sustainable partnerships to be more intense. The primary motivation for the branch brand value chain lies in the growth in quadrants of culture; the more extensive the development system, the more diverse the participating niche brand, and the brand value innovation of pursuit climbs higher.
Interrogating Climate Adaptation Financing in Zimbabwe: Proposed Direction
Authors: Chirisa Innocent , Gumbo Trynos , Gundu-Jakarasi Veronica N. , Zhakata Washington , Karakadzai Thomas , Dipura Romeo , Moyo Thembani
Published: June 2021

Reducing vulnerability to climate change and enhancing the long-term coping capacities of rural or urban settlements to negative climate change impacts have become urgent issues in developing countries. Developing countries do not have the means to cope with climate hazards and their economies are highly dependent on climate-sensitive sectors such as agriculture, water, and coastal zones. Like most countries in Southern Africa, Zimbabwe suffers from climate-induced disasters. Therefore, this study maps critical aspects required for setting up a strong financial foundation for sustainable climate adaptation in Zimbabwe. It discusses the frameworks required for sustainable climate adaptation finance and suggests the direction for success in leveraging global climate financing towards building a low-carbon and climate-resilient Zimbabwe. The study involved a document review and analysis and stakeholder consultation methodological approach. The findings revealed that Zimbabwe has been significantly dependent on global finance mechanisms to mitigate the effects of climate change as its domestic finance mechanisms have not been fully explored. Results revealed the importance of partnership models between the state, individuals, civil society organisations, and agencies. Local financing institutions such as the Infrastructure Development Bank of Zimbabwe (IDBZ) have been set up. This operates a Climate Finance Facility (GFF), providing a domestic financial resource base. A climate change bill is also under formulation through government efforts. However, numerous barriers limit the adoption of adaptation practices, services, and technologies at the scale required. The absence of finance increases the vulnerability of local settlements (rural or urban) to extreme weather events leading to loss of life and property and compromised adaptive capacity. Therefore, the study recommends an adaptation financing framework aligned to different sectoral policies that can leverage diverse opportunities such as blended climate financing. The framework must foster synergies for improved impact and implementation of climate change adaptation initiatives for the country.
Valorisation of Brewer’s Spent Yeasts’ Hydrolysates as High-Value Bioactive Molecules
Authors: San Martin David , Ibarruri Jone , Iñarra Bruno , Luengo Nagore , Ferrer Jorge , Alvarez-Ossorio Carmen , Bald Carlos , Gutierrez Monica , Zufía Jaime
Published: June 2021

Brewer’s spent yeast (BSY) is produced by the beer industry and has high nutritional value and great potential for producing high-value molecules, such as peptides, for nutraceutical, food and feed applications. In the present research, Flavourzyme® and Protamex® enzymes were selected for protein hydrolysis based on previous studies. The optimum conditions for the enzymatic hydrolysis were defined by response surface methodology (RSM) by the Box–Behnken design composed of four variables: temperature, pH, enzyme dosage and time. Protein content, hydrolysis degree and the anti-microbial and antioxidant bioactivities of obtained hydrolysates were quantified. Obtained results show that time, enzyme dosage and pH had the highest effect on protein extraction yield (PEY), degree of hydrolysis (DH) and antioxidant activity. Response variables ranged from 13.7 to 29.7% for PEY, from 6.3 to 35.7% for DH and from 0.65 to 1.65 g for Trolox equivalent antioxidant capacity. Antimicrobial activity, measured as minimum inhibitory concentration, against Aeromonas salmonicida, Bacillus cereus, Bacillus subtilis and Salmonella enterica, ranged from 6.25 to 50 mg/mL. Antioxidant and antimicrobial activity showed the potential use of BSY hydrolysates as an ingredient for functional foods.
More Than Two Decades of Research on Selective Traditions in Environmental and Sustainability Education—Seven Functions of the Concept
Authors: Sund Per J. , Gericke Niklas
Published: June 2021

This study investigates functions of the concept of selective traditions by means of a qualitative systematic review synthesis of earlier research. The study is based on a review method for integrating qualitative studies and looks for “themes” in or across them. In this case, it is about how the identified publications (twenty-four in total) use the concept of selective traditions. All but two studies stem from the Swedish context. The selective traditions relate to teachers’ approaches to the content, methods and purposes of environmental and sustainability education (ESE). Teachers mainly work within one specific selective tradition. Seven different functions were found in the publications of which five are claimed to be valuable for the development of ESE teaching, while the other two functions are useful in monitoring changes and development in ESE teaching. The results are discussed in terms of the consequences for research, practice and teacher education aiming at offering suggestions on how to develop future (transformative) ESE teaching.
The Impact of Mergers and Acquisitions and Sustainability on Company Performance in the Pharmaceutical Sector
Authors: Mihaiu Diana Marieta , Șerban Radu-Alexandru , Opreana Alin , Țichindelean Mihai , Brătian Vasile , Barbu Liliana
Published: June 2021

The primary goal of this study was to determine the impact of mergers and acquisitions (M&A) and the environmental, social, and governance (ESG) sustainability scores of companies. In this regard, efforts to measure and analyze the evolution of a company’s performance, taking into account financial and non-financial measures using a score function, are adapted to the pharmaceutical sector. The sample consisted of 100 leading pharmaceutical companies, ranked by stock market capitalization, who registered 30% (n = 492) of the total M&A transactions over the study period (2010–2020). There was a direct and positive link between the M&A process and the evolution of company performance. The ESG score, as an indicator for measuring sustainability, has a positive and direct impact on company performance, indicating that a high ESG score determines an increase in company performance. A similar impact is identified for companies involved in M&A processes, meaning that companies in the pharmaceutical sector tend to register a performance improvement.
A Fixed Bed Pervious Concrete Anaerobic Bioreactor for Biological Sulphate Remediation of Acid Mine Drainage Using Simple Organic Matter
Authors: Thisani Sandisiwe Khanyisa , Kallon Daramy Vandi Von , Byrne Patrick
Published: June 2021

The development of low-operational-cost and low-operational-complexity active sulphate (SO4) reducing bioremediation for Acid Mine Drainage (AMD) is an ongoing pursuit towards sustainable mining. This study introduces a fixed bed pervious concrete anaerobic bioreactor as a second stage AMD remediation process. The study investigated the pH self-regulation capabilities, SO4 remediation capabilities and the rate limiting parameters of the bioreactor using glucose as an organic matter source. The AMD was pre-treated using a permeable reactive barrier. A 21-day trial comprised of an increase in the SO4 loading rate while reducing the organic loading rate was undertaken to identify performance limiting conditions. A daily average SO4 concentration reduction rate of 55.2% was achieved over the initial 13 days of the experiments. The study found that a COD to SO4 ratio and VFA to alkalinity ratio below 5:1 and 0.5:1 respectively were performance limiting. The bioreactor was capable of self-regulating pH within the neutral range of 6.5 and 7.5. The study findings indicate that the bioreactor design can reduce operational costs and operational complexity of active AMD bioremediation.
From Challenges to Creativity: Enhancing SMEs’ Resilience in the Context of COVID-19
Authors: Zutshi Ambika , Mendy John , Sharma Gagan Deep , Thomas Asha , Sarker Tapan
Published: June 2021

COVID-19 pandemic has brought significant and multiple challenges for SMEs. While SMEs have traditionally faced financial and non-financial crises, the pandemic has brought about additional uncertainties on how to maintain business continuity. The purpose of this paper is to examine how SMEs can mitigate against COVID-19-related crisis by examining the impacts that the pandemic has had on them through a review of 34 articles. The thematic analysis from the literature covered three overarching and inter-related challenges including (i) cost and finance-related challenges, (ii) disruption of activities, and (iii) existential difficulties. The paper’s value lies in addressing the gap between the espoused literature’s claim of the beneficial impact of new technological advancements and SMEs’ ability to survive in the context of the COVID-19 pandemic. The additional value of this paper is a framework of recommendations to help enhance SMEs’ resilience and responsiveness in the context of COVID-19. These recommendations include collaboration, openness, taking advantage of opportunities/victory, and durability.
Drivers, Barriers and Benefits of Product Carbon Footprinting: A State-of-the-Art Survey of Thai Manufacturers
Authors: Sureeyatanapas Panitas , Yodprang Kanittha , Varabuntoonvit Viganda
Published: June 2021

Emerging strategies to respond to public awareness of the environment include carbon emission reporting and labelling. In Thailand, however, only a small proportion of manufacturers have implemented carbon footprint programmes, and some have decided not to continue the programme after their labels expired. This situation mirrors that of many developing countries. This study aims to investigate the factors that drive the implementation of the footprint programme and obstacles that may hinder its long-term implementation. Benefits gained from this programme are also explored. A questionnaire was sent to companies that were or have been certified for the Thai carbon footprint label. Interviews with experts were also conducted to supplement the survey data. According to the statistical analysis, companies expected the carbon footprint programme to enhance their green image, increase their sales and reduce costs. However, benefits derived only in terms of the company’s image, employee development and satisfaction, and production costs returned, while no sales and marketing benefits were evident. The lack of social awareness of the label and of the climate change issue was the most significant challenge the implementers faced, as its rating scores were significantly higher than those of other barriers. Small companies also encountered difficulties due to the required initial investment. This study provides insight into the reasons many developing countries fail to pursue carbon labelling programmes. These issues have not yet been clarified by previous studies. The findings can help prospective companies overcome potential barriers and facilitate their strategic decision making. They can also help governments to develop appropriate policies to promote the carbon footprint label and enhance national sustainability.
The Bike-Sharing System in Slovakia and the Impact of COVID-19 on This Shared Mobility Service in a Selected City
Authors: Kubaľák Stanislav , Kalašová Alica , Hájnik Ambróz
Published: June 2021

The current COVID-19 pandemic situation has a very significant impact on urban mobility, as evidenced by fundamental changes in passengers’ behavior. In many cases, passengers have switched to other modes of transport to minimize the risk of infection (particularly cycling and walking). This paper aims to point out the analysis results of the impacts of a bike-sharing system in the city of Košice before and during the COVID-19 pandemic. Additionally, this paper describes an analysis of the current state of bike-sharing in the Slovak Republic. We have stated a timeline of significant dates related to the COVID-19 pandemic. COVID-19 had a significant impact on people’s mobility and bike-sharing, as evidenced by the graphs and results in this paper.
Reimagining Corporate Social Responsibility in the Era of COVID-19: Embedding Resilience and Promoting Corporate Social Competence
Authors: Zhao Jingchen
Published: June 2021

The debate over corporate objectives and how companies deal with amplified existing societal inequalities and vulnerabilities has received increasing attention in recent years, especially in the wake of the COVID-19 crisis. The pandemic encouraged companies and policy makers to consider ways to develop a more enabling institutional environment, not only to tackle the ongoing crisis but also to prepare for similar future tests. Against this backdrop, the purpose of this paper is to focus on the significance and effectiveness of ex ante corporate social responsibility (CSR) law approaches in tackling the challenges brought by the pandemic. We investigate the uniqueness of the sustainable development challenges in the era of the pandemic, and introduce “corporate social competence” as a compliance principle in response to the need for forward-looking approaches to risk management and strategic planning. We use two ex ante legislative approaches in company law, namely mandatory CSR policy and legally recognised inclusive business models, as examples to illuminate the contribution of company law to navigate the pandemic beyond philanthropic CSR actions.
Dilemma of Geoconservation of Monogenetic Volcanic Sites under Fast Urbanization and Infrastructure Developments with Special Relevance to the Auckland Volcanic Field, New Zealand
Authors: Németh Károly , Gravis Ilmars , Németh Boglárka
Published: June 2021

Geoheritage is an important aspect in developing workable strategies for natural hazard resilience. This is reflected in the UNESCO IGCP Project (# 692. Geoheritage for Geohazard Resilience) that continues to successfully develop global awareness of the multifaced aspects of geoheritage research. Geohazards form a great variety of natural phenomena that should be properly identified, and their importance communicated to all levels of society. This is especially the case in urban areas such as Auckland. The largest socio-economic urban center in New Zealand, Auckland faces potential volcanic hazards as it sits on an active Quaternary monogenetic volcanic field. Individual volcanic geosites of young eruptive products are considered to form the foundation of community outreach demonstrating causes and consequences of volcanism associated volcanism. However, in recent decades, rapid urban development has increased demand for raw materials and encroached on natural sites which would be ideal for such outreach. The dramatic loss of volcanic geoheritage of Auckland is alarming. Here we demonstrate that abandoned quarry sites (e.g., Wiri Mountain) could be used as key locations to serve these goals. We contrast the reality that Auckland sites are underutilized and fast diminishing, with positive examples known from similar but older volcanic regions, such as the Mio/Pliocene Bakony–Balaton UNESCO Global Geopark in Hungary.
Facilitating Aligned Co-Decisions for More Sustainable Food Value Chains
Authors: Petit Gaëlle , Yannou-Le Bris Gwenola , Eckert Claudia , Liu Yan
Published: June 2021

The transition of existing food value chains towards greater sustainability is a societal imperative and a potential competitive factor. To succeed, some actors in the chains define new practices to establish common sustainability goals. To date, there is little evidence that the visions and values of the various actors in the chains have been leading to common solutions. This work explores the impact of collaboration on the value chain actors’ ability to jointly decide strategies for redesigning their activities. It reports on an empirical approach, which elicits the values and priorities of different stakeholders. The case takes place in the context of a value chain of the production/processing/sale of pork products. This value chain involves two French production-processing and redistribution cooperatives. Stakeholders were questioned about their prioritization of sustainability issues and these weights were applied to evaluate 12 animal feed solutions that vary in terms of the composition and geographical origin of rations, and the means and locations of their production. The results show that despite several years of cooperation, the objectives of the upstream and downstream actors remain different. The objectives of the upstream actors are driven by the economic difficulties of production and those of the downstream actors by the multiplicity of consumer demands and cost control objectives. In a reversal of the current practice marked by the economic difficulties of the actors upstream of the chain, an integrated culture could be led by bottom-up approaches to create a shared vision. Public policy would be then essential in regulating the sharing of value among actors; and in promoting chain models that help the required investments.
Complex Socio-Ecological Systems: Translating Narratives into Future Land Use and Land Cover Scenarios in the Kilombero Catchment, Tanzania
Authors: Proswitz Katharina , Edward Mamkwe Claudia , Evers Mariele , Mombo Felister , Mpwaga Alexander , Näschen Kristian , Sesabo Jennifer , Höllermann Britta
Published: June 2021

The Kilombero wetland in Tanzania is affected by advancing land use and land cover changes (LULCC), where we observe a conflict between development interests and the necessity of conservation measures to maintain the functionalities of the ecosystem. Thus, assessing patterns of LULCC is crucial to foresee potential future developments and to develop sustainable future management strategies. In this study, we use a multi-method scenario approach to assess the spatial implications and underlying driving forces of potential change by (1) developing a System Dynamics Causal Loop Diagram (CLD) to disentangle the underlying socio-economic and ecologic driving forces, (2) deriving a qualitative business-as-usual (BAU) and a conservation scenario from participatory narratives elaborated during a stakeholder workshop, and (3) quantifying the spatial implications of these scenarios with the Land Change Modeler (LCM). Results indicate that under the BAU assumption only 37% of the natural vegetation is expected to persist until 2030 in the wetland. In contrast, strict enforcement of protected areas (conservation scenario) halts further conversion of the wetland. However, both scenarios pinpoint considerable expansions of cropland in the western highlands with potentially serious impacts on catchment-wide hydrological processes. The produced qualitative and quantitative outputs reveal hotspots of possible future change and starting points for advisable further research and management interventions.
Electrospun Nanofibre Air Filters for Particles and Gaseous Pollutants
Authors: Orlando Roberta , Polat Merve , Afshari Alireza , Johnson Matthew S. , Fojan Peter
Published: June 2021

Nanofibre filters may offer new properties not available in commercial fibre filters. These include a higher surface area and the ability to include novel materials within the fibres. In addition the small size allows potential gains in performance due to the slip-flow phenomenon in which normal gas viscosity does not apply to objects smaller than the mean free path of the gas. We tested the properties of novel electrospun fibre filters generated from polyvinyl alcohol solutions, optionally embedded with nano-grains of photocatalytic TiO2 and activated charcoal. The tested materials exhibited pressure drops in the range of 195 Pa to 2693 Pa for a face velocity of 5.3 cm/s and a removal efficiency greater than 97% for 12–480 nm particles. Basis weights for the filters ranged from 16.6 to 67.6 g/m2 and specific surface areas ranged from 1.4 to 17.4 m2/g. Reactivity towards volatile organic compounds (VOCs) was achieved by irradiating the photocatalytic filters with ultraviolet light. It is necessary to solve the problems connected to the absorbance of VOCs and further reduce the resistance to airflow in order for these filters to achieve widespread use. The incorporation of reactive air filtration into building ventilation systems will contribute to improved indoor air quality.
Replacing Maize Grain with Ancient Wheat Lines By-Products in Organic Laying Hens’ Diet Affects Intestinal Morphology and Enzymatic Activity
Authors: Addeo Nicola Francesco , Randazzo Basilio , Olivotto Ike , Messina Maria , Tulli Francesca , Musco Nadia , Piccolo Giovanni , Nizza Antonino , Di Meo Carmelo , Bovera Fulvia
Published: June 2021

The effects of replacement of maize grain with ancient wheat by-products on intestinal morphometry and enzymatic activity in laying hens was studied. Eighty hens were divided into two groups (40 each, 8 replicates, 5 hens/replicate) fed two isoproteic and isoenergetic diets. In the treated group, part of the maize was replaced by a mix of ancient grains (AGs) middling, in a 50:50 ratio of Triticum aestivum L. var. spelta (spelt) and Triticum durum dicoccum L. (emmer wheat). The AG diet affected the weight of all the large intestine tracts, decreasing the weight of caeca (p < 0.01) and increasing those of colon (p < 0.01), rectum and cloaca (p < 0.05). Villus height in the AG group was higher (p < 0.01) than the control for the duodenum and jejunum, while for the ileum, the control group showed the highest values (p < 0.01). The submucosa thickness was higher (p < 0.01) in the control group for the duodenum and ileum, while the jejunum for the AG group showed the highest (p < 0.05) submucosa thickness. The crypts depth was higher (p < 0.01) in the control group for the duodenum and ileum. Enzyme activity was enhanced by AGs (p < 0.01) in the duodenum. Regarding the jejunum, sucrase-isomaltase and alkaline phosphatase had higher activity (p < 0.05 and p < 0.01, respectively) in the AG group. In the ileum, sucrase-isomaltase showed higher activity (p < 0.01) in the control group, while alkaline phosphatase showed the highest values (p < 0.05) in the AG group. Overall, results suggested that the dietary inclusion of AGs exerted positive effects in hens, showing an improved intestinal function.
Potentialities of the Asian Watergrass (Hygroryza aristata) as Feed in Aquaculture
Authors: Hossain Md. Moazzem , Shahjahan Md. , Khan Saleha , Juraimi Abdul Shukor , Uddin Md. Kamal , Hasan Mahmudul
Published: June 2021

Asian watergrass (Hygroryza aristata) is an herbaceous glabrous aquatic-rooted floating grass naturally growing in the tidally inundated coastal marshes, beels and canals. The ecology and growth performance of Asian watergrass were evaluated in the coastal wetland (CWL), in an artificially created canal (ACC) within the coastal wetland and in the university research ponds (URP). The study was conducted with three replications in each area. The proximate compositions of the leaves, roots and stems of the grass were determined. Important water and soil quality parameters were found favorable for the growth and production of Asian watergrass. The growth performance and total production of the grass were significantly higher in ACC (length: 2.78 m and weight: 386.86 metric ton ha−1) in comparison with those in CWL (2.36 m and 256.67 metric ton ha−1) and URP (2.22 m and 137.10 metric ton ha−1). Higher content of crude protein was found in leaves (17.49%) followed by roots (12.17%) and stems (9.39%), while the minerals (ash) and fiber contents were found higher in stems (25.68% and 9.53%) in comparison with those in leaves and roots. The findings indicate that the coastal wetlands of Bangladesh having available nutrients in both water and soil are suitable for higher growth and production of Asian watergrass. Considering the nutrient compositions, the Asian watergrass may be an important potential source of feed ingredient that may be used as fish feed in aquaculture throughout the world.
Towards Sustainability in Higher-Education Institutions: Analysis of Contributing Factors and Appropriate Strategies
Authors: Budihardjo Mochamad Arief , Ramadan Bimastyaji Surya , Putri Soraya Annisa , Wahyuningrum Indah Fajarini Sri , Muhammad Fadel Iqbal
Published: June 2021

To depict detailed sustainability efforts that have been implemented in campus environments, research was conducted at the Universitas Diponegoro (UNDIP), a leading green campus in Indonesia. The aim of the current study was to explore how sustainable development has been conducted by UNDIP and to identify factors that may indicate the existence of sustainability activity in higher-education institutions (HEIs). Factors affecting sustainability implementation in HEIs were derived using bibliometric analysis. Information on the implemented strategies to maintain the sustainability of HEIs was obtained via a closed questionnaire to 40 relevant experts, and analyzed using strengths, weaknesses, opportunities, and threats (SWOT) analysis, and quantitative strategic-planning matrix (QSPM) analysis. Institutional commitment to sustainability and guidance to implement sustainability in HEIs were found to have the highest scores with regard to internal and external factors. The respondents selected more aggressive strategies for the enhancement of sustainability implementation at UNDIP. Fostering external collaboration should be a priority for UNDIP since this can provide mutual benefits and significant improvement towards achieving Sustainable Development Goals (SDGs). The current study provides a robust self-assessment method for selecting appropriate strategies to maintain HEI sustainability.
Customer Experience Management: A Study of Mechanic versus Humanic Clues and Student Loyalty in Nigerian Higher Education Institution
Authors: Borishade Taiye Tairat , Worlu Rowland , Ogunnaike Olaleke Oluseye , Aka Deborah Oluwaseun , Dirisu Joy Ifiavor
Published: June 2021

This study surveyed customer experience management (CEM) and student’s loyalty in higher education institution (HEI) sector using a private university in Ogun State, Nigeria as a case study. The primary intent of this study was to determine the roles of humanic and mechanic clues on student’s loyalty. The two hypotheses formulated to address the research questions and objectives raised in this study were analysed with Categorical Regression, which is also known as CATREG analysis. This study applied survey research design and the data were spawned via designed questionnaire. An overall of 215 copies of the questionnaires were regained from the student of the private university in Ogun State. Multi-stage sampling methods were engaged in this study. The research findings of this study show that mechanic clues significantly influence students’ retention, while humanic clues significantly influence students’ disposition to endorse the institution of higher education to others. As part of the recommendations of the study, it was suggested that the university management should deliberately focus on mechanic clues in terms of providing a conducive environment, especially one that is clean for its students at all times.
Best Content Standards in Sports Career Education for Adolescents: A Delphi Survey of Korean Professional Views
Authors: You Jeongae , Kim Woosuk , Lee Hyun-Suk , Kwon Minjung
Published: June 2021

Sports careers are an interesting field for adolescents who enjoy participating in sports. Sports career education provides special support to learners by educating them about occupational sustainability and even discontinuation possibilities. Most sports career education programs implemented in schools and other institutions are unsystematic and ineffective. That is, the lack of systematic guidance by educators or counselors at schools make promising adolescents with talents and/or interests in sports look for different career paths. This study developed the best content standards in sports career education for adolescents using a Delphi survey from Korean professional views. The Delphi survey included three rounds and was conducted with 20 professionals from the field. Five content domains and 30 sub-content elements were identified as the best content standards in sports. Based on the consensus, the five content domains identified were as follows: (a) understanding sports careers, (b) self-understanding in sports, (c) understanding sports-related occupations, (d) exploring sports careers, and (e) designing sports careers. The best content standards identified in this study provided important data regarding the educational resources that educators or counselors could use to assist adolescents who enjoy playing sports or who consider sports as their future career path. These standards could guide the decision-making of educators or counselors regarding the best educational content and activities for sports careers. Furthermore, these standards could play a significant role in discovering and nurturing the needs and aptitudes of a diverse group of adolescents in sports.