bluuebunny/crossref_metadata_2025 huggingface dataset:
A Future Study of an Environment Driving Force (EDR): The Impacts of Urmia Lake Water-Level Fluctuations on Human Settlements
Authors: Hamidi Somayeh Mohammadi , Fürst Christine , Nazmfar Hossein , Rezayan Ahad , Yazdani Mohammad Hassan
Published: October 2021

Lake Urmia, one of the world’s largest salt lakes, is rapidly losing water and drying up. This environmental hazard has raised concerns about the consequences and impact on the surrounding communities. In this paper, we use a futuristic view (horizon of 10 years based on medium-term planning) to identify the main environmental drivers in the surrounding settlements of the Urmia Lake basin. A qualitative method, based on cross-impact analysis, was used as a means of future research. We also used a Delphi-based expert panel method to collect data and extract the environmental impacts of Urmia Lake. After the three rounds of the Delphi process, the expert panel reached a high level of agreement (100%) on the top 17 environmental consequences. Then, these consequences were classified by driving force and dependency using the MICMAC method. The results show that reducing pasture area, soil and water salinity, groundwater decline and depletion, and destruction of surrounding agricultural lands play a significant role in environmental change in Urmia Lake. Overall, any small change in these variables may lead to fundamental changes in the entire system.
Urban Green Infrastructure and Sustainable Development: A Review
Authors: Hanna Elie , Comín Francisco A.
Published: October 2021

Urban green infrastructure (UGI) can alleviate many of the problems that the growing urban population is facing. This study performed a literature review about UGI and sustainable development (SD) using the Web of Science (WoS) and the software VOSviewer. Of 195 papers selected, 89 are qualitative, focusing on theoretical approaches and design; equally, 89 are quantitative, dealing with metrics and spatial analysis and 17 combined both approaches. A high connectivity between “green infrastructure”, “ecosystem services”, “urban planning” and “sustainable development” was observed. Only 39 of the documents embrace environmental, social and economic aspects. Most of the papers are related to Sustainable Development Goal (SDG) 11, “to make cities inclusive, safe, resilient and sustainable” and SDG 15, “protect, restore and promote sustainable use of terrestrial ecosystems”. Further research integrating the three pillars of sustainability and relating UGI to all the SDGs is recommended.
Influencing Factors on the Usefulness of an Earthquake Early Warning System during the 2017 Mexico City Earthquakes
Authors: Santos-Reyes Jaime
Published: October 2021

The paper presents the results of an ongoing research project on the performance of the SASMEX system following the two earthquakes that hit Mexico City in 2017, (a) the 7 September, and (b) the 19 September. In an earlier work, some preliminary findings on the perceived usefulness of the system have been reported. The aim of the present study is the identification of the precursors leading to the outcome variable (‘Usefulness of the SASMEX system’). An ordinal logistic regression analysis has been conducted. The influential factors leading to (a) are the following: the 1985 earthquake experience, drills participation, current knowledge, knowledge on what to do, fear during the tremors, education level, earthquake severity impact. The identified influential factors leading to (b) are the following: knowledge vs. drills, fear of building collapsing, and warning time. The main conclusion of the study is that the outcome is warning time dependent following an event. When there is ‘enough time’ to take protective actions, such as in (a), the probability of the system being considered Useful is higher than otherwise. Conversely, if there is not enough warning time, such as in (b), the probability of the system being considered Not useful is higher than otherwise.
Farmer Perceptions of Adopting Novel Legumes in Traditional Maize-Based Farming Systems in the Yucatan Peninsula
Authors: Pierre Jacques Fils , Latournerie-Moreno Luis , Garruña-Hernández René , Jacobsen Krista L. , Laboski Carrie A. M. , Salazar-Barrientos Lucila de Lourdes , Ruiz-Sánchez Esaú
Published: October 2021

Intercropping constitutes the traditional farming system practice used in various forms for maize production in the Yucatan peninsula. Although practiced for centuries, problems persist with competition for water, nutrients and light between crop species in traditional farming systems. Furthermore, little is known about farmers’ perceptions regarding changes to traditional maize-legume intercropping systems and their interest in novel crop adoption to increase yields in the system while maintaining the practice. The objective of this study was to investigate the maize-based traditional cropping system by assessing the underlying motives and concepts of farmers to practice intercropping in the Yucatan Peninsula and to examine the association between farmers’ level of knowledge about legumes and decisions to adopt intercropping and related practices therein. Farmer surveys were conducted in nine different regions of the Yucatan Peninsula. We selected Xoy, Euan, Muna, Mama, Tahdziú (Yucatan), Becal, Hecelchacam, Dzitbalché and San Antonio Sahcabchén (Campeche) which are representative of agroecological small-scale farming systems. We used a mixed methods case study analysis involving key informant interviews in eight associations of farmers. A sample frame with 73 farmers was selected in total during February 2021 and April 2021. Basic information such as land use, labor inputs, agricultural production and farmer’s perceptions regarding their intercropping systems were collected. Our research shows that the primary motives for intercropping were due to the ability of intercropping to offer a more diversified range of food for human and animal consumption, as well as to take advantage of different harvest periods that this practice offers. The majority of respondents were likely to favor the idea of introducing new legume species in their maize-based cropping systems. Factors such as the type of cropping system (i.e., intercropping or monocropping), access to water and level of knowledge about legumes influenced their decision to adopt intercropping in their farming systems considerably. This paper contributes to the knowledge on the current state and farmers’ perceptions of intercropping systems in the Yucatan Peninsula.
Evaluation of an Assertiveness Training Based on the Social Learning Theory for Occupational Health, Safety and Environment Practitioners
Authors: Cantero-Sánchez Francisco J. , León-Rubio José M. , Vázquez-Morejón Raquel , León-Pérez José M.
Published: October 2021

Assertiveness is a fundamental type of behavior for the creation and maintenance of positive relationships at work and the facilitation of team functioning. Therefore, the promotion of assertiveness contributes to improving work performance, preventing harassment at work, facilitating the adoption of safe behaviors and making critical decisions in terms of occupational health and safety. However, few studies have evaluated the effectiveness of assertive training to train occupational health, safety and environment (OHSE) technicians to facilitate their work as agents of change in the attitudes and behaviors of other workers. Therefore, an assertive training was carried out to increase assertiveness and decrease social anxiety in this type of professional. The training effectiveness was evaluated following a pretest–posttest group design. The results from both a pilot study in a sample of 328 undergraduate students and a study in a sample of 155 OHSE technicians indicated that the training was effective in achieving both objectives. Moreover, Cohen’s d statistics suggest that the effect size was intermediate. These results are discussed with respect to their role in contributing to occupational health safety and environment practices as well as to the organizations’ sustainability.
Applying Artificial Neural Network and Response Surface Method to Forecast the Rheological Behavior of Hybrid Nano-Antifreeze Containing Graphene Oxide and Copper Oxide Nanomaterials
Authors: Melaibari Ammar A. , Khetib Yacine , Alanazi Abdullah K. , Sajadi S. Mohammad , Sharifpur Mohsen , Cheraghian Goshtasp
Published: October 2021

In this study, the efficacy of loading graphene oxide and copper oxide nanoparticles into ethylene glycol-water on viscosity was assessed by applying two numerical techniques. The first technique employed the response surface methodology based on the design of experiments, while in the second technique, artificial intelligence algorithms were implemented to estimate the GO-CuO/water-EG hybrid nanofluid viscosity. The nanofluid sample’s behavior at 0.1, 0.2, and 0.4 vol.% is in agreement with the Newtonian behavior of the base fluid, but loading more nanoparticles conforms with the behavior of the fluid with non-Newtonian classification. Considering the possibility of non-Newtonian behavior of nanofluid temperature, shear rate and volume fraction were effective on the target variable and were defined in the implementation of both techniques. Considering two constraints (i.e., the maximum R-square value and the minimum mean square error), the best neural network and suitable polynomial were selected. Finally, a comparison was made between the two techniques to evaluate their potential in viscosity estimation. Statistical considerations proved that the R-squared for ANN and RSM techniques could reach 0.995 and 0.944, respectively, which is an indication of the superiority of the ANN technique to the RSM one.
Determinants of Social Entrepreneurs in Southeast Europe: GEM Data Analysis
Authors: Leković Bojan , Uzelac Ozren , Fazekaš Tibor , Horvat Aleksandra Marcikić , Vrgović Petar
Published: October 2021

With this paper, we aim to examine the relationship between cognitive, social, and demographical factors, as well as national culture and its relationship with social entrepreneurial activity in Southeast Europe (SEE). The empirical research employs a binary logistic regression model, utilizing data obtained from the Global Entrepreneurship Monitor. For the purpose of the empirical research, we selected a sample of early-stage entrepreneurs who founded their businesses in Hungary, Romania, Slovenia, Croatia, or North Macedonia. The research sample in these five countries includes 10,012 examinees, of which 615 are social entrepreneurs. A statistically significant relationship was identified between observed phenomena in terms of entrepreneurial networking, risk aversion, individualism, entrepreneurial social image, media impact, gender, work status, and education. The results can be explained by the specific entrepreneurial context of the SEE region. We also point out recommendations for future research.
A Study of the Factors Affecting Multimodal Ridesharing with Choice-Based Conjoint Analysis
Authors: An Sunghi , Nam Daisik , Jayakrishnan R. , Lee Soongbong , McNally Michael G.
Published: October 2021

As public perception about the shared economy evolves, peer-to-peer ridesharing has been gaining increased attention worldwide. Both private and public sector entities have launched mobile app-based ridesharing services, while a range of methodologies and system architectures have been proposed in academia. Whereas traditional ridesharing methods match drivers and riders when their origin and destination are similar, recently proposed algorithms often feature multi-hop and multimodal properties that allow riders to be connected by multiple modes. Such algorithms can reduce travel time and/or travel cost; however, they may also add other travel impedances, such as requiring multiple transfers. Understanding user behavior toward such new ridesharing systems is essential for successful service design. For policymakers and service planners, identifying factors that impact traveler choices can lead to better design and improved services. This research involved a web-based survey to capture traveler preferences using a conjoint analysis framework. A choice-based method was adopted to identify factors for the estimation model and to analyze traveler willingness to pay. Among the proposed factors, the number-of-transfers was shown to be the most important, as was expected. When a multimodal ridesharing system provides less travel time, low travel cost, and sufficient ridesharing incentive, people are more likely to pay for the service.
Patterns of Structural and Functional Bacterioplankton Metacommunity along a River under Anthropogenic Pressure
Authors: Małecka-Adamowicz Marta , Kubera Łukasz
Published: October 2021

Bacteria, an integral part of aquatic ecosystems, are responsible for the circulation of matter and flow of energy. Since bacterioplankton rapidly responds to any natural and human-induced disturbances in the environment, it can serve as a bioindicator of these changes. Knowing factors that shape the microbial community structure may help the sustainable management of the water environment. However, the identification of environmental signals affecting the structure and function of bacterioplankton is still a challenge. The study analyses the impact of environmental variables on basic microbial parameters, which determines the effectiveness of ecological processes in rivers. Measurements of bacterioplankton abundance (BA) and extracellular enzyme activity (EEA) were based on fluorescent markers. The bacterial community structure was determined by 16S rRNA gene amplicon sequencing (Illumina). The results indicate spatial variation in bacterioplankton abundance. Temporal variation was not significant. Lipase and aminopeptidase had the highest level of activity. EEA was not correlated with bacterial abundance but was significantly correlated with temperature. Moreover, differences in lipase, α-glucosidase and β-glucosidase activity levels between spring and summer were noted. At the same time, the location of sampling site had a significant influence on aminopeptidase activity. The taxonomic analysis of bacterioplankton communities in the Brda River indicated that, although different numbers of OTUs were recorded in the studied river sections, bacterioplankton biodiversity did not change significantly along the river with distance downstream. Anthropogenically modified river sections were characterized by the dominance of Flavobacterium (Bacterioidetes) and hgcl clade (Actinobacteria) taxa, known for their ability to produce extracellular enzymes. PCoA analysis revealed that the sites located in the lower river course (urban area) had the most similar bacterial community structure (β-diversity). The study provides new insight into the changes in microbial communities along the river and emphasizes the potential impact of anthropogenization on these processes.
Correlation between Generation Z in Hungary and the Motivating Factors to Do Volunteer Work in a Value-Based Approach
Authors: Garai-Fodor Mónika , Varga János , Csiszárik-Kocsir Ágnes
Published: October 2021

The knowledge-based voluntary activity covered by the research, the pro bono, which will be introduced from the aspect of employer branding. The primary results of the research described in the study are the outcome of a quantitative data collection process, where 840 evaluable questionnaires were processed in the course of a pretested standardized questionnaire survey. On top of that, during the research we were able to confirm that the motivation of volunteering is connected to the individual values, hence it can be stated that the reason behind the unwillingness of young people less motivated towards volunteer work is the immature value orientation and often the lack of information, instead of the sharp isolation rooted in the values or the lack of empathy. The introduced results may provide practical guidance to the institutions and companies organizing pro bono activities, and especially to the organizations that intend to address the young generation.
Evaluating the Effects of Access to Air Quality Data on Household Air Pollution and Exposure—An Interrupted Time Series Experimental Study in Rwanda
Authors: Iribagiza Chantal , Sharpe Taylor , Coyle Jeremy , Nkubito Pie , Piedrahita Ricardo , Johnson Michael , Thomas Evan A.
Published: October 2021

In Sub-Saharan Africa, around 80% of residential energy demand is for cooking, with over 760 million people without access to clean cooking fuels and stoves. Particulate matter smaller than 2.5 microns (PM2.5) is a significant pollutant from biomass burning and is linked to respiratory and cardiovascular diseases, as well as adverse pregnancy outcomes. Energy poverty further reinforces gender disparities, keeps children from schools, causes environmental degradation, and interferes with social and economic development. Lack of access to and inadequate adoption of clean cooking stoves and fuels are key barriers to improved air quality. This paper presents a field experiment nested within a large-scale health efficacy trial. The aim of the experiment was to evaluate the effects of access to air quality data and dynamic feedback on indoor air pollution (IAP) and personal exposure. Ninety households in Rwanda were enrolled and provided with an air quality sensor and feedback device, which measured real-time indoor air quality as PM2.5 for sixteen weeks. After six weeks, PM2.5 levels were provided dynamically to households through a display and an auditory alarm. We examined the effects of receiving this feedback on IAP and personal exposure. While access to air quality data did not, in aggregate, improve PM2.5 levels, we did observe several promising correlations worthy of further investigation. The associations between personal exposure or rainfall and increased PM2.5 were reduced after households had access to air quality data. We hypothesized that the behavior changes required to observe these effects—opening doors and windows and moving away from cooking sources—are easy and immediate, in contrast to the costs and complex logistics of entirely eliminating biomass cooking. The types of behavior changes that would directly impact household air pollution and exposure require more than just awareness and willingness to act.
For Learning Analytics to Be Sustainable under GDPR—Consequences and Way Forward
Authors: Karunaratne Thashmee
Published: October 2021

Personalized learning is one of the main focuses in 21st-century education, and Learning Analytics (LA) has been recognized as a supportive tool for enhancing personalization. Meanwhile, the General Data Protection Regulations (GDPR), which concern the protection of personal data, came into effect in 2018. However, contemporary research lacks the essential knowledge of how and in which ways the presence of GDPR influence LA research and practices. Hence, this study intends to examine the requirements for sustaining LA under the light of GDPR. According to the study outcomes, the legal obligations for LA could be simplified to data anonymization with consequences of limitations to personalized interventions, one of the powers of LA. Explicit consent from the data subjects (students) prior to any data processing is mandatory under GDPR. The consent agreements must include the purpose, types of data, and how, when and where the data is processed. Moreover, transparency of the complete process of storing, retrieving, and analysing data as well as how the results are used should be explicitly documented in LA applications. The need for academic institutions to have specific regulations for supporting LA is emphasized. Regulations for sharing data with third parties is left as a further extension of this study.
Historical Ecology in Brazil: A Systematic Mapping of Scientific Articles (1998–2021)
Authors: Lazos-Ruíz Adi Estela , Rodrigues Aline Furtado , Sales Gabriel Paes da Silva , Brasil Lucas Santa Cruz de Assis , Fraga Joana Stingel , D’Orey Martim , Solórzano Alexandro , Oliveira Rogério Ribeiro de
Published: October 2021

Historical Ecology is a multidisciplinary field that studies long-term relationships between humanity and the environment. There is a missing synthesis effort to organize and present the state of the scholarship in Historical Ecology in Brazil. We aimed to characterize by whom, when, where, what, and how research in Historical Ecology has been conducted in Brazil. We made a systematic mapping of 118 scientific articles published in Portuguese, Spanish, and English that fit our inclusion criteria. The results showed articles from 1998 to May 2021, published in 79 different journals. We found 264 national and international authors (60% men and 40%women); 91% of all investigations were carried out in the Amazon and Atlantic Forest biomes. There are few works about Cerrado, Caatinga, and Pampa, and none for Pantanal. The most mentioned keywords were historical ecology, Amazon, forest, and archaeology. Twenty-three articles focused on a particular species, primarily plants; 37% of all articles used Historical Ecology as its central axis of research, and 63% as auxiliary. We found more than 35 methodological procedures, both from the social and natural sciences. This overview revealed achievements, research gaps, and opportunities in this field.
Implementation of Fire Policies in Brazil: An Assessment of Fire Dynamics in Brazilian Savanna
Authors: de Andrade Ananda Santa Rosa , Ramos Rossano Marchetti , Sano Edson Eyji , Libonati Renata , Santos Filippe Lemos Maia , Rodrigues Julia Abrantes , Giongo Marcos , da Franca Rafael Rodrigues , Laranja Ruth Elias de Paula
Published: October 2021

In 2012, the Brazilian government implemented the Federal Brigades Program (FBP), a fire policy strategy to hire and train firefighters to combat wildfires. This study analyzed the impact of this program on fire behavior before (2008–2012) and after (2013–2017) its implementation in the Parque do Araguaia Indigenous Land, the largest indigenous territory with the highest occurrence of fires in the Brazilian tropical savanna. We analyzed the annual pattern of fire incidence in the dry season, the fire impact per vegetation type, the recurrence, and the relationship between fire and precipitation. The datasets were based on active fire products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Landsat and Resourcesat-based burned area products, and the records of the fire combat operations. Our results showed that FBP contributed to the reduction of the number of areas affected by fires and to the formation of a more heterogeneous environment composed of fire-resistant and fire-sensitive native vegetation fragments. On the other hand, after the implementation of the FBP, there was an increase in the recurrence of 3–4 years of fires. We concluded that the FBP is an important public policy capable of providing improvements in fire management activities.
Data-Driven Forecasting and Modeling of Runoff Flow to Reduce Flood Risk Using a Novel Hybrid Wavelet-Neural Network Based on Feature Extraction
Authors: Malekpour Heydari Salimeh , Aris Teh Noranis Mohd , Yaakob Razali , Hamdan Hazlina
Published: October 2021

The reliable forecasting of river flow plays a key role in reducing the risk of floods. Regarding nonlinear and variable characteristics of hydraulic processes, the use of data-driven and hybrid methods has become more noticeable. Thus, this paper proposes a novel hybrid wavelet-neural network (WNN) method with feature extraction to forecast river flow. To do this, initially, the collected data are analyzed by the wavelet method. Then, the number of inputs to the ANN is determined using feature extraction, which is based on energy, standard deviation, and maximum values of the analyzed data. The proposed method has been analyzed by different input and various structures for daily, weekly, and monthly flow forecasting at Ellen Brook river station, western Australia. Furthermore, the mean squares error (MSE), root mean square error (RMSE), and the Nash-Sutcliffe efficiency (NSE) is used to evaluate the performance of the suggested method. Furthermore, the obtained findings were compared to those of other models and methods in order to examine the performance and efficiency of the feature extraction process. It was discovered that the proposed feature extraction model outperformed their counterparts, especially when it came to long-term forecasting.
On the Dependence of Acoustic Pore Shape Factors on Porous Asphalt Volumetrics
Authors: Praticò Filippo Giammaria , Fedele Rosario , Briante Paolo Giovanni
Published: October 2021

The sound absorption of a road pavement depends not only on geometric and volumetric factors but also on pore shape factors. In turn, pore shape factors mainly refer to thermal and viscous factors (i.e., thermal and viscous effects that usually occur inside porous materials). Despite the presence of a number of studies and researches, there is a lack of information about how to predict or estimate pore shape factors. This greatly affects mixture design, where a physical-based or correlation-based link between volumetrics and acoustics is vital and plays an important role also during quality assurance and quality control (QA/QC) procedures. Based on the above, the objective of this study is to link mixture volumetrics and pore shape factors. In particular, 10 samples of a porous asphalt concrete were tested in order to estimate their thickness, air voids content (vacuum-sealing method, ASTM D6857/D6857M), sound absorption coefficient (Kundt’s tube, ISO 10354-2), airflow resistivity (ISO 9053-2), and permeability (ASTM PS 129). Subsequently, two models (herein called STIN and JCAL) were used to derive both volumetrics and pore shape factors from the estimated parameters listed above, and statistical analysis was carried out to define correlations among the parameters and models performance. Results confirm the complexity of the tasks and point out that estimates of the pore shape factors can be derived based on mixture volumetrics. Results can benefit researchers (in acoustic and pavement mixtures) and practitioners involved in mix design and pavement acceptance processes.
Identification of the Dominant Factors in Groundwater Recharge Process, Using Multivariate Statistical Approaches in a Semi-Arid Region
Authors: Castillo José Luis Uc , Ramos Leal José Alfredo , Martínez Cruz Diego Armando , Cervantes Martínez Adrián , Marín Celestino Ana Elizabeth
Published: October 2021

Identifying contributing factors of potential recharge zones is essential for sustainable groundwater resources management in arid regions. In this study, a data matrix with 66 observations of climatic, hydrogeological, morphological, and land use variables was analyzed. The dominant factors in groundwater recharge process and potential recharge zones were evaluated using K-means clustering, principal component analysis (PCA), and geostatistical analysis. The study highlights the importance of multivariate methods coupled with geospatial analysis to identify the main factors contributing to recharge processes and delineate potential groundwater recharge areas. Potential recharge zones were defined into cluster 1 and cluster 3; these were classified as low potential for recharge. Cluster 2 was classified with high potential for groundwater recharge. Cluster 1 is located on a flat land surface with nearby faults and it is mostly composed of ignimbrites and volcanic rocks of low hydraulic conductivity (K). Cluster 2 is located on a flat lowland agricultural area, and it is mainly composed of alluvium that contributes to a higher hydraulic conductivity. Cluster 3 is located on steep slopes with nearby faults and is formed of rhyolite and ignimbrite with interbedded layers of volcanic rocks of low hydraulic conductivity. PCA disclosed that groundwater recharge processes are controlled by geology, K, temperature, precipitation, potential evapotranspiration (PET), humidity, and land use. Infiltration processes are restricted by low hydraulic conductivity, as well as ignimbrites and volcanic rocks of low porosity. This study demonstrates that given the climatic and geological conditions found in the Sierra de San Miguelito Volcanic Complex (SSMVC), this region is not working optimally as a water recharge zone towards the deep aquifer of the San Luis Potosí Valley (SLPV). This methodology will be useful for water resource managers to develop strategies to identify and define priority recharge areas with greater certainty.
Participatory Guarantee System and Social Capital for Sustainable Development in Brazil: The Case Study of OPAC Orgânicos Sul de Minas
Authors: Torquati Biancamaria , Pedini Sergio , Santucci Fabio Maria , Da Re Riccardo
Published: October 2021

In recent years there has been a growing international interest in alternative certification strategies for organic products. Specifically, participatory guarantee systems (PGS) have proved to be particularly suitable not only to simplify bureaucratic procedures for small organic producers and reduce the cost of certification, but also to generate empowerment, social inclusion and mutual support among farmers. The purpose of this paper is to study the elements of social capital (SC) found in a PGS through the use of social network indicators using the Organizaçao Participativa de Acreditaçao e Certificaçao “Orgânicos Sul de Minas” (OPAC-OSM) as a case study. The research was carried out in the southern part of Minas Gerais, one of the states of the Brazilian Federation, where organic production represents a viable alternative for small and medium-sized farmers. In particular, a survey was carried out to capture the opinions of managers (presidents or directors) about their participation in the OPAC-OSM, and about the level of interaction and degree of trust between members. Relational skills, which are the basis of structural SC, were analyzed both at the level of individual units and at the level of the general network of the OPAC-OSM. An in-degree centrality score assigned to OPAC-OSM members was obtained from each network. These scores have been correlated with variables of the database that were chosen due to their relevance in assessing the level of social capital. According to the results, the factors that most reinforced the proof of SC among the OPAC-OSM members were the level of information and the degree of trust and collaboration networks, with special emphasis on female participation. From the analysis carried out, it is possible to conclude that PGS are powerful tools in the strengthening of SC far beyond the aspect of quality assurance, which remains the main objective of the OPAC.
Removal of Pharmaceuticals from Water by Tomato Waste as Novel Promising Biosorbent: Equilibrium, Kinetics, and Thermodynamics
Authors: Mutavdžić Pavlović Dragana , Ćurković Lidija , Mandić Vilko , Macan Jelena , Šimić Iva , Blažek Dijana
Published: October 2021

Tomato waste was studied as a low-cost biosorbent for the removal of five pharmaceuticals (dexamethasone, febantel, procaine, praziquantel, and tylosin) from water. Tomato waste was characterized chemically and microstructurally before and after simulated sorption. Sorption performance was interpreted as a function of the initial pharmaceuticals concentration, temperature, and physicochemical properties of the tomato waste. The linear, Freundlich, and Dubinin–Radushkevich (D-R) isotherms were used to describe the experimental results at different temperatures (298, 303, and 308 K). Thermodynamic parameters such as standard free energy (ΔG°), enthalpy change (ΔH°), and entropy change (ΔS°) were determined. Negative values of ΔG° in the temperature range of 298–308 K strongly indicate the spontaneous nature of the biosorption process. In addition, the values of ΔH° for the biosorption of dexamethasone, procaine, praziquantel, and tylosin on tomato waste were negative, indicating exothermic processes, while the positive value for febantel indicated an endothermic process. The kinetic data were analyzed using (i) kinetic models to determine the kinetic parameters (Lagergren’s pseudo-first order and Ho’s pseudo-second order) and (ii) adsorption–diffusion models to the describe transport mechanisms of pharmaceuticals from aqueous solution onto tomato waste as adsorbent (Weber–Morris intraparticle diffusion and Boyd film diffusion models).
Impact of an Innovative Solution for the Interruption of 3-D Point Thermal Bridges in Buildings on Sustainability
Authors: Ingeli Rastislav , Gašparík Jozef , Paulovičová Lucia
Published: October 2021

During the design of the external cladding, it is possible to use different materials and compositions. One of these possibilities is also a ventilated facade, which consists of a supporting structure, a thermal insulation, a supporting grid, an air gap for ventilation and a cladding layer. The construction of the supporting grid in the ventilated facade must be mechanically anchored into the supporting structure of the external cladding. This mechanical anchoring causes 3-D point thermal bridges in the external cladding itself. Therefore, the aim of this work is to assess and analyze the influence of these 3-D point thermal bridges on transmission heat losses through the external cladding. A Finite Element Mesh analysis has been used for this analysis. Different types of external cladding compositions were modeled in the simulation program, and the effect on the heat transfer coefficient was determined. In addition to the analysis of the existing anchoring systems, an innovative solution has been suggested that is more economical and easier to implement. The results show that the application of anchors and their number impacts significantly on the thermal properties of the envelope. The difference between the anchoring element with a thermal insulation pad and the patented method is minimal. This is a 1.29% difference. The last variant was a proposal (patent) that the anchoring element is only plastic-coated and thus its thermal engineering properties are improved, which is manifested mainly in heat conduction but also from the radiant point of view, as plasticizing the emissivity changes. Compared to the perimeter cladding without the ap-plication of an anchoring element, the heat loss increases by 29.37%. In addition to the energy savings, there are also financial savings. While the plastic pads costs about EUR 0.3, the plastic coating (patent) represents a price of around EUR 0.03. If we had a building with 10,000 m2 of wall area where 6 pieces of anchors per 1 m2 are applied, the savings would be EUR 16,200. Such savings are already significant. The conclusion of this work is that these point thermal bridges have a significant impact on the overall transmission heat loss coefficient and therefore they have overall heat demand and energy demand.
Research on the Collaborative Evolution of Blockchain Industry Ecosystems in Terms of Value Co-Creation
Authors: Zhang Hui , Yi Jin-Biao , Wang Qian
Published: October 2021

The formation of blockchain industrial ecology can help improve the open and efficient value synergy network, and this paper seeks to clarify the value relationship among industrial units and the trend of synergistic evolution of blockchain industrial ecosystem. Based on value co-creation theory, the blockchain industrial ecosystem synergy evolution process is analyzed, and the composite system synergy model is used to empirically investigate the evolution synergy of China’s blockchain industrial ecosystem from 2015 to 2020. The results show that: although the development level of China’s blockchain industry ecosystem continues to improve, it is still at a low level, and the policy-driven effect is obvious. There is a large disparity in the orderliness level of each subsystem of the blockchain industry ecosystem, and the industrial integration and application implementation are in a good situation, while the blockchain enterprises, located in the value pivot subsystem, are in a relatively tough position, and China’s blockchain industry ecosystem is overall in a state of reconciliation and has not yet formed a synergistic effect. Handling the synergistic relationship between the government, the market and other value-supporting units, and blockchain enterprises is the top priority for further promoting the synergistic evolution of the blockchain industry ecosystem.
Recycling Waste Classification Using Vision Transformer on Portable Device
Authors: Huang Kai , Lei Huan , Jiao Zeyu , Zhong Zhenyu
Published: October 2021

Recycling resources from waste can effectively alleviate the threat of global resource strain. Due to the wide variety of waste, relying on manual classification of waste and recycling recyclable resources would be costly and inefficient. In recent years, automatic recyclable waste classification based on convolutional neural network (CNN) has become the mainstream method of waste recycling. However, due to the receptive field limitation of the CNN, the accuracy of classification has reached a bottleneck, which restricts the implementation of relevant methods and systems. In order to solve the above challenges, in this study, a deep neural network architecture only based on self-attention mechanism, named Vision Transformer, is proposed to improve the accuracy of automatic classification. Experimental results on TrashNet dataset show that the proposed method can achieve the highest accuracy of 96.98%, which is better than the existing CNN-based method. By deploying the well-trained model on the server and using a portable device to take pictures of waste in order to upload to the server, automatic waste classification can be expediently realized on the portable device, which broadens the scope of application of automatic waste classification and is of great significance with respect to resource conservation and recycling.
Creditworthiness Assessment for Credit Institutions and for the Risk Associated with Excessive Leverage toward Sustainable Performance
Authors: Șerbu Razvan Sorin , Baranga Laurentiu Paul , Petru Ovidiu Gheorghe
Published: October 2021

With the development of financial transactions, it has become necessary for parties to assess the creditworthiness of their counterparty before entering into an agreement. In this respect, z-scoring methods for assessing creditworthiness have been developed, credit risks have been regulated, and rating providers have emerged to ensure a certain level of independence. This article introduces a z-scoring methodology, developed using principal component analysis, for assessing the creditworthiness of credit institutions; a methodology for determining the rating corresponding to the scoring obtained by the entities, developed through expert judgement; and an analysis of the existence of a significant correlation between z-scoring and the level of the leverage and capital adequacy ratios. Furthermore, considering that excessive leverage can have a negative impact on the creditworthiness of an entity, a methodology for assessing the leverage ratio is presented, along with a method for determining any additional own fund requirements where this ratio is above the regulated maximum level. The results obtained by applying the described methodologies to the data of the entities showed stable character. All these methodologies can be implemented by credit institutions to achieve better creditworthiness and business sustainability.
Coastal Cities Seen from Loyalty and Their Tourist Motivations: A Study in Lima, Peru
Authors: Carvache-Franco Mauricio , Alvarez-Risco Aldo , Carvache-Franco Wilmer , Carvache-Franco Orly , Estrada-Merino Alfredo , Rosen Marc A.
Published: October 2021

The objective of this empirical study is to determine: (a) the underlying variables of the travel motivations related to a coastal city; and (b) the motivational dimensions that predict return, recommendation, and saying positive things about a coastal city as loyalty variables. This project utilized an in situ investigation carried out in Lima, a coastal city located on the Pacific Ocean near Peru with important natural and cultural attractions. The researchers used 381 questionnaires that were analyzed through factor analysis, in addition to the stepwise multiple regression method. Reesults identified six underlying variables or motivational factors: “culture and nature”, “authentic coastal experience”, “novelty and social interaction”, “learning”, “sun and beach”, and “nightlife”. Regarding loyalty, the “novelty and social interaction” dimension is the most important predictor of return and the “authentic coastal experience” dimension is the most important predictor of recommending and saying positive things about a coastal city. To motivate a return, events could be created on the beach to motivate novelty, as well as increase recommendations and the amount of positive things said about the destination; educational and sports activities and workshops could also be created with the community and the coastal environment. Results can be used by firms for preparing information for new customers in order to increase trip intention and improve guides for destination marketing organizations (DMOs).
How Is the Sustainable Consumption Intention Model in Food Industry under Preference Uncertainties? The Consumer Willingness to Pay on Recycled Packaging Material
Authors: Chen Chih-Cheng , Sujanto Raditia Yudistira , Tseng Ming-Lang , Chiu Anthony S. F. , Lim Ming K.
Published: October 2021

Food packaging is costly to consumers and generates a huge volume of packaging waste, especially in Indonesia. Prior studies have neglected to construct a causal sustainable consumption intention model in food industry and link to the consumer willingness to pay under preference uncertainties. To address the gaps, this study explores consumer attributes to build a causal sustainable consumption intention model and takes the model to address the consumer willingness to pay under preference uncertainties. This study proposes a causal model that integrates five aspects of sustainable consumption intention model: (1) sustainable consumption knowledge, attitudes, and behaviors; (2) government policy and regulation on sustainable consumption; (3) recycled packaging eco-labeling certification; (4) supply chain innovation and infrastructure; and (5) sustainable product purchasing features. This study uses the fuzzy Delphi method to confirm the reliability and validate the criteria and applies cause and effect model to address the causal model. In addition, this study collects 428 valid responses to address the willingness to pay for causal sustainable consumption intention model and a cognitive best-worst choice experiment to confirm the model in the food industry. The result reveals that recycled packaging eco-labeling certification is the major aspect for enhancing the model, followed by government policy and regulation and supply chain innovation and infrastructure. In practice, consumers incur inconvenience in purchasing sustainable food products but prefer recycled packaging material at a standardized price.
Climate Youth Activism Initiatives: Motivations and Aims, and the Potential to Integrate Climate Activism into ESD and Transformative Learning
Authors: Kowasch Matthias , Cruz Joana P. , Reis Pedro , Gericke Niklas , Kicker Katharina
Published: October 2021

For about two years, the climate youth activism initiative Fridays for Future has addressed climate emergency, receiving considerable attention because of their consistent protests every week in many different locations worldwide. Based on empirical studies in Austria and Portugal, this paper investigates the motivations of students to participate in the movement and the solutions proposed by young activists to fight against climate emergency. Moreover, we discuss the integration of climate change activism into ESD (education for sustainable development) and transformative learning processes, and how this enables environmental citizenship. The results of the studies reveal that emotions and feelings of solidarity and collective aims are motives to participate in the strikes. The young activists sometimes propose innovative and sometimes radical solutions to climate emergency. Both demonstrations and exhibitions as forms of bottom-up climate activism initiatives contribute to engagement in political dialogue and scientific knowledge transfer. They can be seen as “triggers of change” for transformative learning.
Psychological Barriers to Pro-Environmental Behaviour Change: A Review of Meat Consumption Behaviours
Authors: Graves Catherine , Roelich Katy
Published: October 2021

Meat consumption behaviours contribute significantly to global greenhouse gas emissions. Interventions to enable meat consumption reductions need to consider the psychological barriers preventing behavioural changes. Our aims were twofold; (1) to explore the psychological barriers to reducing meat consumption and how they can be overcome through a Rapid Evidence Review; and (2) to explore the usefulness of integrating the Kollmuss and Agyeman (K&A) model of pro-environmental behaviour and psychological distance, which provides the analytical framework. This review utilised three databases, focussing on empirical studies since 2010, which returned 277 results with seven eligible studies. We found that habit is the most significant psychological barrier to change, however, values and attitudes could act as moderating variables. We found gaps in the behavioural mechanism, indicating the presence of direct and indirect psychological barriers. We identified several actionable policy recommendations, such as utilising co-benefits, the importance of values in messaging, and targeting repeated behaviours. We found that study outcomes did not always translate into policy recommendations, and they were limited by existing policy paradigms. Psychological distance provides additional explanatory power, when combined with the K&A model, therefore, integrating psychological distance across pro-environmental behavioural research and policy could improve the effectiveness of interventions.
Analysis of Energy Consumption in Commercial and Residential Buildings in New York City before and during the COVID-19 Pandemic
Authors: Deiss Branden M. , Herishko Mallori , Wright Lauren , Maliborska Michelle , Abulencia J. Patrick
Published: October 2021

This study compares the energy burden of New York City office buildings versus personal residences before and during the stay-at-home period of the COVID-19 pandemic. The scope is comprised of employees that, prior to the stay-at-home order, underwent a daily commute to and from a representative midtown Manhattan office building. Energy consumed by these employees with respect to the office building they work in, their transportation there, and their personal residence was determined using publicly available data. Energy usage and cost per person per day were compared in both remote and in-person work settings. The results of this study demonstrated that remote working conditions consume 39.7% less energy and required less personal expense compared to in-person working conditions. Additionally, the results found that a building occupancy of 65% is where the energy burden shifts from residential to commercial sectors. This study can be a starting point of discussion for businesses regarding staffing of commercial buildings and energy efficiency. Future work on this topic would benefit from having a more robust data set compared to the publicly available data used in this study.