bluuebunny/crossref_metadata_2025 huggingface dataset:
Ballodiolic Acid A and B: Two New ROS, (•OH), (ONOO−) Scavenging and Potent Antimicrobial Constituents Isolated from Ballota pseudodictamnus (L.) Benth.
Authors: Fozia  , Shaheen Asmat , Ahmad Ijaz , Amin Syed , Ahmad Nisar , Ullah Riaz , Bari Ahmed , Sohaib Muhammad , Hafiz Majid Mahmood , Alobaid Abdulrahman
Published: March 2021

Bioassays guided phytochemical investigations on the ethyl acetate-soluble fraction of the root material of Ballota pseudodictamnus (L.) Benth. led to the isolation of two new compounds, ballodiolic acid A (1) and ballodiolic acid B (2), along with three known compounds ballodiolic acid (3), ballotenic acid (4), and β-amyrin (5), which were also isolated for the first time from this species by using multiple chromatographic techniques. The structures of the compounds (1–5) were determined by modern spectroscopic analysis including 1D and 2D NMR techniques and chemical studies. In three separate experiments, the isolated compounds (1–5) demonstrated potent antioxidant scavenging activity, with IC50 values ranging from 07.22–34.10 μM in the hydroxyl radical (•OH) inhibitory activity test, 58.10–148.55 μM in the total ROS (reactive oxygen species) inhibitory activity test, and 6.23–69.01 μM in the peroxynitrite (ONOO−) scavenging activity test. With IC50 values of (07.22 ± 0.03, 58.10 ± 0.07, 6.23 ± 0.04 μM) for •OH, total ROS, and scavenge ONOO−, respectively, ballodiolic acid B (2) showed the highest scavenging ability. Antibacterial and antifungal behaviors were also exposed to the pure compounds 1–5. In contrast to compounds 4 and 5, compounds 1–3 were active against all bacterial strains studied, with a good zone of inhibition proving these as a potent antibacterial agent. Similarly, compared to compounds 3–5, compounds 1 and 2 with a 47 percent and 45 percent respective inhibition zone were found to be more active against tested fungal strains.
Displacement Identification by Computer Vision for Condition Monitoring of Rail Vehicle Bearings
Authors: Lei Lei , Song Dongli , Liu Zhendong , Xu Xiao , Zheng Zejun
Published: March 2021

Bearings of rail vehicles bear various dynamic forces. Any fault of the bearing seriously threatens running safety. For fault diagnosis, vibration and temperature measured from the bogie and acoustic signals measured from trackside are often used. However, installing additional sensing devices on the bogie increases manufacturing cost while trackside monitoring is susceptible to ambient noise. For other application, structural displacement based on computer vision is widely applied for deflection measurement and damage identification of bridges. This article proposes to monitor the health condition of the rail vehicle bearings by detecting the displacement of bolts on the end cap of the bearing box. This study is performed based on an experimental platform of bearing systems. The displacement is monitored by computer vision, which can image real-time displacement of the bolts. The health condition of bearings is reflected by the amplitude of the detected displacement by phase correlation method which is separately studied by simulation. To improve the calculation rate, the computer vision only locally focuses on three bolts rather than the whole image. The displacement amplitudes of the bearing system in the vertical direction are derived by comparing the correlations of the image’s gray-level co-occurrence matrix (GLCM). For verification, the measured displacement is checked against the measurement from laser displacement sensors, which shows that the displacement accuracy is 0.05 mm while improving calculation rate by 68%. This study also found that the displacement of the bearing system increases with the increase in rotational speed while decreasing with static load.
A New Acoustic-Based Approach for Assessing Induced Adulteration in Bovine Milk
Authors: Messias dos Santos Junior Marcos , Albuquerque de Castro Bruno , Ardila-Rey Jorge Alfredo , de Souza Campos Fernando , Merino de Medeiros Maria Izabel , Covolan Ulson José Alfredo
Published: March 2021

Milk is an important dietary requirement for many populations due to its high nutritional value. However, increased demand has also made it prone to fraudulent activity. In this sense, scientists have sought to develop simple, low-cost, and portable techniques to achieve quality control of milk in industry and farms as well. This work proposes a new instrumentation system based on acoustic propagation and advanced signal processing techniques to identify milk adulteration by industrial contaminants. A pair of transmitter-receiver low-cost piezoelectric transducers, configured in a pitch-catch mode, propagated acoustic waves in the bovine milk samples contaminated with 0.5% of sodium bicarbonate, urea, and hydrogen peroxide. Signal processing approaches such as chromatic technique and statistical indexes like the correlation coefficient, Euclidian norm and cross-correlation square difference were applied to identify the contaminants. According to the presented results, CCSD and RMSD metrics presented more effectiveness to perform the identification of milk contaminants. However, CCSD was 2.28 × 105 more sensitivity to distinguish adulteration in relation to RMSD. For chromatic clustering technique, the major selectivity was observed between the contamination performed by sodium bicarbonate and urea. Therefore, results indicate that the proposed approach can be an effective and quick alternative to assess the milk condition and classify its contaminants.
Highly Sensitive Magnesium-Doped ZnO Nanorod pH Sensors Based on Electrolyte–Insulator–Semiconductor (EIS) Sensors
Authors: Al-Khalqi Ensaf Mohammed , Abdul Hamid Muhammad Azmi , Al-Hardan Naif H. , Keng Lim Kar
Published: March 2021

For highly sensitive pH sensing, an electrolyte insulator semiconductor (EIS) device, based on ZnO nanorod-sensing membrane layers doped with magnesium, was proposed. ZnO nanorod samples prepared via a hydrothermal process with different Mg molar ratios (0–5%) were characterized to explore the impact of magnesium content on the structural and optical characteristics and sensing performance by X-ray diffraction analysis (XRD), atomic force microscopy (AFM), and photoluminescence (PL). The results indicated that the ZnO nanorods doped with 3% Mg had a high hydrogen ion sensitivity (83.77 mV/pH), linearity (96.06%), hysteresis (3 mV), and drift (0.218 mV/h) due to the improved crystalline quality and the surface hydroxyl group role of ZnO. In addition, the detection characteristics varied with the doping concentration and were suitable for developing biomedical detection applications with different detection elements.
Relation3DMOT: Exploiting Deep Affinity for 3D Multi-Object Tracking from View Aggregation
Authors: Chen Can , Zanotti Fragonara Luca , Tsourdos Antonios
Published: March 2021

Autonomous systems need to localize and track surrounding objects in 3D space for safe motion planning. As a result, 3D multi-object tracking (MOT) plays a vital role in autonomous navigation. Most MOT methods use a tracking-by-detection pipeline, which includes both the object detection and data association tasks. However, many approaches detect objects in 2D RGB sequences for tracking, which lacks reliability when localizing objects in 3D space. Furthermore, it is still challenging to learn discriminative features for temporally consistent detection in different frames, and the affinity matrix is typically learned from independent object features without considering the feature interaction between detected objects in the different frames. To settle these problems, we first employ a joint feature extractor to fuse the appearance feature and the motion feature captured from 2D RGB images and 3D point clouds, and then we propose a novel convolutional operation, named RelationConv, to better exploit the correlation between each pair of objects in the adjacent frames and learn a deep affinity matrix for further data association. We finally provide extensive evaluation to reveal that our proposed model achieves state-of-the-art performance on the KITTI tracking benchmark.
Towards a Sustainable City for Cyclists: Promoting Safety through a Mobile Sensing Application
Authors: Boronat Pablo , Pérez-Francisco Miguel , Calafate Carlos T. , Cano Juan-Carlos
Published: March 2021

Riding a bicycle is a great manner to contribute to the preservation of our ecosystem. Cycling helps to reduce air pollution and traffic congestion, and so, it is one of the simplest ways to lower the environmental footprint of people. However, the cohabitation of cars and vulnerable road users, such as bikes, scooters, or pedestrians, is prone to cause accidents with serious consequences. In this context, technological solutions are sought that enable the generation of alerts to prevent these accidents, thereby promoting a safer city for these road users, and a cleaner environment. Alert systems based on smartphones can alleviate these situations since nearly all people carry such a device while traveling. In this work, we test the suitability of a smartphone based alert system, determining the most adequate communications architecture. Two protocols have been designed to send position and alert messages to/from a centralized server over 4G cellular networks. One of the protocols is implemented using a REST architecture on top of the HTTP protocol, and the other one is implemented over the UDP protocol. We show that the proposed alarm system is feasible regarding communication response time, and we conclude that the application should be implemented over the UDP protocol, as response times are about three times better than for the REST implementation. We tested the applications in real deployments, finding that drivers are warned of the presence of bicycles when closer than 150 m, having enough time to pay attention to the situation and drive more carefully to avoid a collision.
Automatic Modulation Classification Based on Deep Feature Fusion for High Noise Level and Large Dynamic Input
Authors: Han Hui , Ren Zhiyuan , Li Lin , Zhu Zhigang
Published: March 2021

Automatic modulation classification (AMC) is playing an increasingly important role in spectrum monitoring and cognitive radio. As communication and electronic technologies develop, the electromagnetic environment becomes increasingly complex. The high background noise level and large dynamic input have become the key problems for AMC. This paper proposes a feature fusion scheme based on deep learning, which attempts to fuse features from different domains of the input signal to obtain a more stable and efficient representation of the signal modulation types. We consider the complementarity among features that can be used to suppress the influence of the background noise interference and large dynamic range of the received (intercepted) signals. Specifically, the time-series signals are transformed into the frequency domain by Fast Fourier transform (FFT) and Welch power spectrum analysis, followed by the convolutional neural network (CNN) and stacked auto-encoder (SAE), respectively, for detailed and stable frequency-domain feature representations. Considering the complementary information in the time domain, the instantaneous amplitude (phase) statistics and higher-order cumulants (HOC) are extracted as the statistical features for fusion. Based on the fused features, a probabilistic neural network (PNN) is designed for automatic modulation classification. The simulation results demonstrate the superior performance of the proposed method. It is worth noting that the classification accuracy can reach 99.8% in the case when signal-to-noise ratio (SNR) is 0 dB.
Different Metrics for Singular Value Optimization in Near-Field Antenna Characterization
Authors: Capozzoli Amedeo , Curcio Claudio , Liseno Angelo
Published: March 2021

We deal with the use of different metrics in the framework of the Singular Value Optimization (SVO) technique for near-field antenna characterization. SVO extracts the maximum amount of information on an electromagnetic field over a certain domain from field samples on an acquisition domain, with a priori information on the source, e.g., support information. It determines the field sample positions by optimizing a functional featuring the singular value dynamics of the radiation operator and representing a measure of the information collected by the field samples. Here, we discuss in detail and compare the use, in the framework of SVO, of different objective functionals and so of different information measures: Shannon number, mutual information, and Fisher information. The numerical results show that they yield a similar performance.
Towards Digital Sustainability: Profiles of Millennial Reviewers, Reputation Scores and Intrinsic Motivation Matter
Authors: García-Jurado Alejandro , Pérez-Barea José Javier , Fernández-Navarro Francisco
Published: March 2021

Profiles of millennial reviewers and gamification can contribute to digital sustainability as a driver of innovation and growth. The study aims to detect if there are profiles of reviewers that can be grouped together, in order to apply a specific gamification to them and to make it sustainable over time. In this way, more information will be generated through the reviews that will help responsible consumers to choose better in their purchase decisions. The objective of this study is twofold. First, it aims to characterize online product reviewers based on their intrinsic motivations and self-perception when they comment, identifying their main motivations. Second, it aims to classify these individuals based on the acceptance of gamification elements while commenting on and relating them to the intrinsic attributes that determine their behaviors. A survey method design was used to capture responses from 187 millennial reviewers of Amazon in Spain. The relationships between motivations and the types of reviewer were extracted from the accommodation of the dataset using decision trees (DTs), specifically, the J48 algorithm. To contribute to the second objective, this paper elaborates a typology of reviewer analysis based on cluster analysis and DTs. It is confirmed that online product reviewers can be characterized based on their intrinsic motivations, which are mainly egoistic motives, competence and social relatedness. The obtained results show that the J48 DT provides excellent classification accuracy of approximately 95% in identifying reviewers based on intrinsic motivations. Similarly, egoistic intrinsic motives are decisive in focusing gamification strategies.
Contributions of Subjective Well-Being and Good Living to the Contemporary Development of the Notion of Sustainable Human Development
Authors: González-Díaz Romel Ramón , Acevedo-Duque Ángel , Salazar-Sepúlveda Guido , Castillo Dante
Published: March 2021

The article analyzes the contributions of the notions of Good Living attributable to epistemologies, traditions, and subjective well-being at work, given the current changes in the working context, to enrich the concept of human development. The article is developed with an analytical-descriptive and synthetic approach, reconstructing the concept of Good Living through a theoretical-economic, ontological, and epistemological comparison and its dimensional axes. Methodologically, a systematic review of human development literature is used in Latin America through the Web of Science (WOS), comparing the UNDP Technical Notes (HDI) with the various approaches to Good Living published between 2010 and 2020. These documents were subjected to semantic contrast, with reference to the various dimensions and positions of human development as a generator of subjective well-being for the configuration of public labor policies. The main findings refer to the disagreement points evidenced in the two-axes dimensions of the Good Living measurement systems (mobility and safety, and cultural satisfaction within territories), an important factor being the sumak kawsay, the concept of Good Living. Sumak is fullness, the sublime, excellent, magnificent, beautiful, superior. Kawsay is life, being. However, it is dynamic, changing, and is not a passive question, and is thus not considered by the different evolutionary changes of the HDI.
Circular Economy and Internet of Things: Mapping Science of Case Studies in Manufacturing Industry
Authors: Cavalieri Adriane , Reis João , Amorim Marlene
Published: March 2021

This study investigates the “Internet of things” (IoT) and “Circular Economy” (CE) relationship in the current scientific literature focused on case studies or use cases on manufacturing context. To the best of our knowledge, this study is the first to map the science centered on “case studies” with respect to the “IoT” and “CE” connection, contributing to fill the gap of the subject that is already relevant to the scientific community and practitioners. The research methodology consists of developing a bibliometric study, employing PRISMA process, whose data is obtained from the Web of Science database. The VOSviewer was the computer program selected for the bibliometric analysis. The Web of Science (WoS) analysis tool supports VOSviewer. The papers were analyzed according to network analysis principles. The qualitative content analysis complements these results. The results show the high-frequency keywords and topics associated with the theme “IoT and CE”; the most cited papers; the intellectual structure of “IoT and CE”; the new emerging themes in scientific research; and social networks among the researchers. The paper’s contribution is the results of the bibliometric analysis and a better understanding of the relationship of “IoT” and “CE” by the “case studies” addressed in the empirical investigations.
The Implications and Effects of Medical Waste on Development of Sustainable Society—A Brief Review of the Literature
Authors: Bucătaru Costel , Săvescu Dan , Repanovici Angela , Blaga Larisa , Coman Ecaterina , Cocuz Maria-Elena
Published: March 2021

The sustainable development of humanity imposes precise norms regarding the management of natural resources, their extraction, use, and the introduction in a complex, innovative circuit of the waste resulting from exploitation. The paper deals with some aspects related to the sustainable management of general medical waste on the one hand and the medical waste specific to the COVID-19 pandemic, on the other hand. Medical waste requires special treatment given its impact on the environment and on humanity. The management of activities related to its storage, transport, destruction is an important point in the sustainable development of mankind, especially in the current context of the pandemic. Medical waste is in a continuous increase in quantity and involves many effects in various activity fields. Through a scientometric study in the Web of Science—WOS database, the authors identify clusters of keywords, analyze the articles identified in the WOS and identify the main research directions and existing concepts. Corroborating and interpreting the results obtained, three significant trends of approach to medical waste are identified: M—management (1); E—exposure (2); and D—distribution (3). An extensive map of the concepts is made, a narrow map of the concepts used, and a theoretical map of the concepts. The link between medical waste and the development of a sustainable society is demonstrated, and it is possible to open new research directions. The scientometric research undertaken on 1192 WOS articles that were published in 2020 led to the selection of 32, focused on issues related to hazardous medical waste, especially of COVID-19 patients. Following this approach, the authors were able to see, by comparison, the different forms of management of this waste in different countries, thus being able to contribute to the creation of procedures for the collection, storage, and destruction of this hazardous waste, with direct influence on the environment.
Modeling Renewable Energy Systems by a Self-Evolving Nonlinear Consequent Part Recurrent Type-2 Fuzzy System for Power Prediction
Authors: Tavoosi Jafar , Suratgar Amir Abolfazl , Menhaj Mohammad Bagher , Mosavi Amir , Mohammadzadeh Ardashir , Ranjbar Ehsan
Published: March 2021

A novel Nonlinear Consequent Part Recurrent Type-2 Fuzzy System (NCPRT2FS) is presented for the modeling of renewable energy systems. Not only does this paper present a new architecture of the type-2 fuzzy system (T2FS) for identification and behavior prognostication of an experimental solar cell set and a wind turbine, but also, it introduces an exquisite technique to acquire an optimal number of membership functions (MFs) and their corresponding rules. Using nonlinear functions in the “Then” part of fuzzy rules, introducing a new mechanism in structure learning, using an adaptive learning rate and performing convergence analysis of the learning algorithm are the innovations of this paper. Another novel innovation is using optimization techniques (including pruning fuzzy rules, initial adjustment of MFs). Next, a solar photovoltaic cell and a wind turbine are deemed as case studies. The experimental data are exploited and the consequent yields emerge as convincing. The root-mean-square-error (RMSE) is less than 0.006 and the number of fuzzy rules is equal to or less than four rules, which indicates the very good performance of the presented fuzzy neural network. Finally, the obtained model is used for the first time for a geographical area to examine the feasibility of renewable energies.
A Comparative Study of the Robustness and Resilience of Retail Areas in Seoul, Korea before and after the COVID-19 Outbreak, Using Big Data
Authors: Kim Dongjun , Yun Jinsung , Kim Kijung , Lee Seungil
Published: March 2021

This study aimed to assess the robustness and resilience of retail areas in Seoul, based on the changes in sales before and after the COVID-19 outbreak. The spatial range and temporal scope of the study were set as district- and community-level retail areas in Seoul, from January 2019 to August 2020, to consider the effect of the COVID-19 outbreak. The data used in this study comprised sales information from the retail sector, namely Shinhan Card sales data for domestic and foreigners by business type in Seoul, provided by Seoul Big Data Campus. We classified the retail areas based on the change in sales before and after the COVID-19 outbreak, using time series clustering. The results of this study showed that time series clustering based on the change in sales can be used to classify retail areas. The similarities and differences were confirmed by comparing the functional and structural characteristics of the district- and community-level retail areas by cluster and by retail area type. Furthermore, we derived knowledge on the decline and recovery of retail areas before and after a national crisis such as the emergence of a COVID-19 wave, which can provide significant information for sustainable retail area management and regional economic development.
Expectations and Interests of University Students in COVID-19 Times about Sustainable Development Goals: Evidence from Colombia, Ecuador, Mexico, and Peru
Authors: Alvarez-Risco Aldo , Del-Aguila-Arcentales Shyla , Rosen Marc A. , García-Ibarra Verónica , Maycotte-Felkel Sandra , Martínez-Toro Gabriel Mauricio
Published: March 2021

The coronavirus disease 2019 (COVID-19) pandemic has changed the world, creating the need for new actions from society, including universities and companies. The United Nations Sustainable Development Goals (SDGs) are part of a global agenda, but this priority is not significant to university students. Although some research has focused on SDGs and university students, there is a lack of evaluation and comparison in Latin American countries. The current study aims to evaluate student knowledge of the SDGs, the relation of student professional careers to the SDGs, the importance of the SDGs for economic development after the COVID-19 pandemic, and student interest research in SDG issues. The study is carried out with students in Colombia, Ecuador, Mexico, and Peru. The instrument was developed and validated. The highest score of level of knowledge was reported in Mexico and the lowest score in Colombia. This outcome can be explained by the availability of training programs in the universities about SDGs. The availability of programs created and promoted by the governments can also be a reason; however, students from Mexico are the ones who felt the most that the authorities are not making efforts to promote the SDGs. With research interests, interests in creating sustainable cities and communities, and responsible consumption and production were recognized for the four countries. The outcomes reveal several interesting insights through comparisons among the four countries considered according to descriptive analyses. Some SDGs were found to be more important for some countries than others. Interests were noted in research on some SDGs.
Rhizospheric Phosphate Solubilizing Bacillus atrophaeus GQJK17 S8 Increases Quinoa Seedling, Withstands Heavy Metals, and Mitigates Salt Stress
Authors: Mahdi Ismail , Fahsi Nidal , Hafidi Mohamed , Benjelloun Saad , Allaoui Abdelmounaaim , Biskri Latefa
Published: March 2021

Introduction of quinoa (Chenopodium quinoa willd.), a gluten-free nutritious pseudo-cereal, outside its traditional growing areas exposed it to seedling damping-off. Here, we isolated eleven phosphate-solubilizing bacteria from the quinoa rhizosphere and assessed their effect on germination and seedlings growth. All isolates solubilized phosphate, produced indole3-acetic acid, hydrocyanic acid, siderophores, and ammonia. Genotypic analysis revealed that our strains are related to the genus of Bacillus, Pseudomonas, and Enterobacter. Strains Enterobacter asburiae (QD14, QE4, QE6, and QE16), Enterobacter sp. QE3, and Enterobacter hormaechei QE7 withstood 1.5 mg·L−1 of cadmium sulfate, 0.5 mg·mL−1 of nickel nitrate, and 1 mg·mL−1 of copper sulfate. Moreover, all strains solubilized zinc from ZnO; P. Stutzeri QD1 and E. asburiae QD14 did not solubilize Zn3(PO4)2 and CO3Zn, whereas CO3Zn was not solubilized by E. asburiae QE16. Bacillus atrophaeus S8 tolerated 11% NaCl. P. frederiksbergensis S6 and Pseudomonas sp. S7 induced biofilm formation. Anti-fusarium activity was demonstrated for E.asburiae QE16, P. stutzeri QD1, P. frederiksbergensis S6, Pseudomonas sp. S7, and B. atrophaeus S8. Lastly, inoculation of quinoa seeds with B. atrophaeus S8 and E. asburiae QB1 induced the best germination rate and seedling growth, suggesting their potential use as inoculants for salty and heavy metal or zinc contaminated soils.
Gender Roles in Sourcing and Sharing of Banana Planting Material in Communities with and without Banana Bunchy Top Disease in Nigeria
Authors: Nkengla-Asi Lilian , Eforuoku Favour , Olaosebikan Olamide , Adejoju Ladigbolu Temitope , Amah Delphine , Hanna Rachid , Kumar P. Lava
Published: March 2021

Banana bunchy top disease (BBTD) is the most devastating disease of banana and plantain (Musa spp.). The disease spreads through the use of infected vegetative propagules and the banana aphid (Pentalonia nigronervosa) is the virus vector. This study seeks to understand the gender dimensions and sociocultural aspects of banana seed (vegetative propagule) sourcing and sharing practices among men and women farmers, and its influence on BBTD spread and disease control efforts. Data were collected from 300 banana farmers (187 men and 113 women) in BBTD and non-BBTD areas in southwest Nigeria. The results revealed that seed sharing within the communities is a social responsibility with members expected to share banana seed with the needy mainly as gifts rather than sold for cash. Men farmers mostly sourced seed from old fields, while women sourced seed from relatives. Harvesting of banana seed was predominantly the responsibility of men with women as helpers. Both men and women farmers in the non-BBTD area cultivated larger farm sizes and harvested more banana planting material than farmers in the BBTD area. The existing seed sourcing practices among men and women farmers heighten the risk of BBTD spread. Awareness raising on disease spread through infected seeds should consider gender-differentiated roles and social practices to reduce its spread within communities.
Conducting Population Health Research during the COVID-19 Pandemic: Impacts and Recommendations
Authors: Villarosa Amy R. , Ramjan Lucie M. , Maneze Della , George Ajesh
Published: March 2021

The COVID-19 pandemic has resulted in many changes, including restrictions on indoor gatherings and visitation to residential aged care facilities, hospitals and certain communities. Coupled with potential restrictions imposed by health services and academic institutions, these changes may significantly impact the conduct of population health research. However, the continuance of population health research is beneficial for the provision of health services and sometimes imperative. This paper discusses the impact of COVID-19 restrictions on the conduct of population health research. This discussion unveils important ethical considerations, as well as potential impacts on recruitment methods, face-to-face data collection, data quality and validity. In addition, this paper explores potential recruitment and data collection methods that could replace face-to-face methods. The discussion is accompanied by reflections on the challenges experienced by the authors in their own research at an oral health service during the COVID-19 pandemic and alternative methods that were utilised in place of face-to-face methods. This paper concludes that, although COVID-19 presents challenges to the conduct of population health research, there is a range of alternative methods to face-to-face recruitment and data collection. These alternative methods should be considered in light of project aims to ensure data quality is not compromised.
Animal Welfare and the United Nations’ Sustainable Development Goals—Broadening Students’ Perspectives
Authors: Olmos Antillón Gabriela , Tunón Håkan , de Oliveira Daiana , Jones Michael , Wallenbeck Anna , Swanson Janice , Blokhuis Harry , Keeling Linda
Published: March 2021

The mutually beneficial relationships between improving animal welfare (AW) and achieving the United Nations (UN) sustainable development goals (SDGs) were further explored and compared to previous work. This was done in the context of a doctoral training course where students selected at least six SDGs and reasoned around their impact on AW and vice versa. Then, students rated the strength of the SDG—AW links. Lastly, students engaged in an assessment exercise. Students reported an overall mutually beneficial relationship between AW and all SDGs, yet with significant differences in strength for SDGs 4, 11, 10, 12 and 13 to that previously found by experts. Students considered SDG 12: Responsible consumption and production the most promising way to integrate AW targets. This study further supports the positive role of AW in the success of the UN’s strategy. Still, the magnitude of the anticipated impacts is modified by stakeholder, context and experience.
Utilisation of Waste-Based Geopolymer in Asphalt Pavement Modification and Construction—A Review
Authors: Milad Abdalrhman , Ali Ahmed Suliman B. , Babalghaith Ali Mohammed , Memon Zubair Ahmed , Mashaan Nuha S. , Arafa Salaheddin , Md. Yusoff Nur Izzi
Published: March 2021

The use of geopolymer in pavement constructions is strongly encouraged. Many studies have demonstrated the vast potential of using industrial-by-products-based geopolymers. This paper discusses the modification of asphalt binders with geopolymers, namely geopolymer-modified asphalt (GMA) and geopolymer-modified asphalt mixture (GMAM). In addition, curing geopolymer materials, engineering properties, production techniques, and prospective utilisation in the pavement construction, such as durability and sustainability, are also discussed. The literature review showed that many industrial by-products, including red mud, blast furnace slag, fly ash, and mine waste, are used to produce geopolymers because of the metal components such as silicon and aluminium in these materials. The geopolymers from these materials influence the rheological and physical properties of asphalt binders. Geopolymers can enhance asphalt mixture performance, such as stability, fatigue, rutting, and low-temperature cracking. The use of geopolymers in asphalt pavement has beneficial impacts on sustainability and economic and environmental benefits.
Time as a Subject in Sustainable Consumption
Authors: Jouzi Fatemeh , Koistinen Katariina , Linnanen Lassi
Published: March 2021

The aim of this paper was to assess the use and consistency of the time concept in the sustainable consumption context. In this field, time is generally defined as a limited resource, such as money, which is allocated to activities and understood by the activities that it is allocated to. We assessed time as a subject matter in the reviewed articles to verify how it was conceptualized and used in sustainable consumption. During this analysis, we defined six categories: time-use, time of use, time-related rebound effects, time-related value-action gap, time pressure, and time-related well-being. Despite identical definitions, there are some inconsistencies in the essential assumptions regarding time, and we observed that the current recognition of time in sustainable consumption debates is not comprehensive. Clarifying the difference between an objective definition of time and the practical knowledge that people have about time has applications in terms of developing sustainable consumption strategies and policies.
Solar Gain Influence on the Thermal and Energy Performance of Existing Mosque Buildings in the Hot-Arid Climate of Riyadh City
Authors: Shohan Ahmed Ali A. , Al-Khatri Hanan , Bindajam Ahmed Ali , Gadi Mohamed B.
Published: March 2021

The required cooling energy in buildings exceeds 65% of the total energy consumed inside buildings under the extreme climatic conditions of Saudi Arabia. The proper design of buildings’ envelopes has a considerable potential in reducing such levels, especially in public buildings. The reported study evaluated the thermal performance of mosque buildings with focus on the solar gains through the envelope elements. Computer simulations were carried out using Thermal Analysis Software (TAS). In addition, the thermal and comfort votes of the worshippers in one mosque were collected. The findings revealed uncomfortable thermal conditions, especially during summer months. The required cooling energy ranged between 37% and 55% in the investigated mosques. Investigating the solar gains of the envelope elements of one mosque indicated that the roof is the largest contributor to solar gain, which highlights the potential for future research to explore new constructional alternatives with the aim of improving the roofs’ thermal performance.
Effects of Incorporating Augmented Reality into a Board Game for High School Students’ Learning Motivation and Acceptance in Health Education
Authors: Lin Hao-Chiang Koong , Lin Yu-Hsuan , Wang Tao-Hua , Su Lun-Ke , Huang Yueh-Min
Published: March 2021

In traditional schools, where education and teaching tend to be subject-oriented, the standardization of the teaching materials of health education courses would be obscurely related to know-how of daily life. This frustrates the learners from developing the awareness of engagement, thereby decreasing their willingness to acquire new information or skill. Therefore, in this study, a board game assimilating augmented reality (AR) into health education is presented. It associates the card game, slides, and learning sheets gamification teaching model with the learning experience; and proposes the efficacy of the board games mingled with augmented reality to enhance the motivation in learning and confidence in technology. In this experiment for a health education board game, 52 high school students participated in this experiment. There were 25 in the experimental group (with AR) and 27 in the control group (without AR). The IMMS (instructional material motivation survey) and the TAM (technology acceptance model) are applied to acquire quantitative data for examination. The findings are as follows: (1) The acceptance was significantly affected by the integration of AR into the health education board game and (2) the learning motivation was significantly affected by the integration of AR into the health education board game.
Effects of Soil Water Deficit on Three Tree Species of the Arid Environment: Variations in Growth, Physiology, and Antioxidant Enzyme Activities
Authors: Rasheed Fahad , Gondal Adnan , Kudus Kamziah Abdul , Zafar Zikria , Nawaz Muhammad Farrakh , Khan Waseem Razzaq , Abdullah Muhammad , Ibrahim Faridah Hanum , Depardieu Claire , Pazi Ahmad Mustapha Mohamad , Anjum Khayyam , Afzal Shazia , Akram Seemab , Nazre Mohd
Published: March 2021

Low water availability predicted under climate change is a major abiotic factor limiting plants growth and productivity. In this study a greenhouse experiment was conducted on three important tree species of arid environment: Conocarpus erectus (CE), Acacia modesta (AM), and Salix tetrasperma (ST). Young saplings were subjected to control (C), medium (MWD) and severe soil water deficit (SWD) treatments and response was evaluated. Results showed that in all the three species leaf, stem and root dry weight production remained similar to C under MWD treatment but decreased significantly under SWD. The highest decrease in total dry weight was noticed in ST and the lowest was evidenced in AM under SWD. Root:shoot ratio increased significantly in both CE and AM under MWD and SWD. Furthermore, chlorophyll content decreased while proline content increased significantly in both MWD and SWD treatments. The production of oxidants (hydrogen peroxide and superoxide anions) and antioxidants (superoxide dismutase, catalase, peroxidase and ascorbate peroxidase) increased significantly under both MWD and SWD treatments and were the highest in AM in both MWD and SWD treatments. Therefore, we may conclude that all the three species can tolerate medium water stress due to increased root production and an effective antioxidant defense mechanism.
Re-Thinking Soil Bioengineering to Address Climate Change Challenges
Authors: Mickovski Slobodan B.
Published: March 2021

Soil bioengineering includes the sustainable use of vegetation for civil engineering purposes, including addressing climate change challenges. Previous research in this area has been focused on determination of the strength and stability that vegetation provides for the soil it grows in. The industry, on the other hand, has concentrated on mainly empirical approaches in the design and construction of nature-based solutions. The aim of this paper is to attempt a reconciliation of the scientific and technical aspects of soil bioengineering with a view of proposing broad guidelines for management of soil bioengineering projects aimed at combatting climate change and achievement of the United Nations Sustainable Development Goals (UN SDGs). More than 20 case studies of civil engineering projects addressing climate change challenges, such as erosion, shallow landslides, and flooding, were critically reviewed against the different project stages and the UN SDGs. The gaps identified in the review are addressed from civil engineering and asset management perspectives, with a view of implementing the scientific and technical nexus in the future. Recommendations are formulated to help civil engineers embrace the multidisciplinary nature of soil bioengineering and effectively address climate change challenges in the future.
New Study of the Existence and Dimension of the Set of Solutions for Nonlocal Impulsive Differential Inclusions with a Sectorial Operator
Authors: Alsarori Nawal , Ghadle Kirtiwant , Sessa Salvatore , Saleh Hayel , Alabiad Sami
Published: March 2021

In this article, we are interested in a new generic class of nonlocal fractional impulsive differential inclusions with linear sectorial operator and Lipschitz multivalued function in the setting of finite dimensional Banach spaces. By modifying the definition of PC-mild solutions initiated by Shu, we succeeded to determine new conditions that sufficiently guarantee the existence of the solutions. The results are obtained by combining techniques of fractional calculus and the fixed point theorem for contraction maps. We also characterize the topological structure of the set of solutions. Finally, we provide a demonstration to address the applicability of our theoretical results.
Skin Sensitization Evaluation of Carbon-Based Graphene Nanoplatelets
Authors: Kim Sung-Hyun , Hong So-Hye , Lee Jin Hee , Lee Dong Han , Jung Kikyung , Yang Jun-Young , Shin Hyo-Sook , Lee JeongPyo , Jeong Jayoung , Oh Jae-Ho
Published: March 2021

Graphene nanoplatelets (GNPs) are one of the major types of carbon based nanomaterials that have different industrial and biomedical applications. There is a risk of exposure to GNP material in individuals involved in their large-scale production and in individuals who use products containing GNPs. Determining the exact toxicity of GNP nanomaterials is a very important agenda. This research aimed to evaluate the skin sensitization potentials induced by GNPs using two types of alternative to animal testing. We analyzed the physicochemical characteristics of the test material by selecting a graphene nanomaterial with a nano-size on one side. Thereafter, we evaluated the skin sensitization effect using an in vitro and an in vivo alternative test method, respectively. As a result, we found that GNPs do not induce skin sensitization. In addition, it was observed that the administration of GNPs did not induce cytotoxicity and skin toxicity. This is the first report of skin sensitization as a result of GNPs obtained using alternative test methods. These results suggest that GNP materials do not cause skin sensitization, and these assays may be useful in evaluating the skin sensitization of some nanomaterials.
Characteristic Distribution of Ciguatoxins in the Edible Parts of a Grouper, Variola louti
Authors: Oshiro Naomasa , Nagasawa Hiroya , Kuniyoshi Kyoko , Kobayashi Naoki , Sugita-Konishi Yoshiko , Asakura Hiroshi , Yasumoto Takeshi
Published: March 2021

Ciguatera fish poisoning (CFP) is one of the most frequently encountered seafood poisoning syndromes; it is caused by the consumption of marine finfish contaminated with ciguatoxins (CTXs). The majority of CFP cases result from eating fish flesh, but a traditional belief exists among people that the head and viscera are more toxic and should be avoided. Unlike the viscera, scientific data to support the legendary high toxicity of the head is scarce. We prepared tissue samples from the fillet, head, and eyes taken from five yellow-edged lyretail (Variola louti) individuals sourced from Okinawa, Japan, and analyzed the CTXs by LC-MS/MS. Three CTXs, namely, CTX1B, 52-epi-54-deoxyCTX1B, and 54-deoxyCTX1B, were confirmed in similar proportions. The toxins were distributed nearly evenly in the flesh, prepared separately from the fillet and head. Within the same individual specimen, the flesh in the fillet and the flesh from the head, tested separately, had the same level and composition of toxins. We, therefore, conclude that flesh samples for LC-MS/MS analysis can be taken from any part of the body. However, the tissue surrounding the eyeball displayed CTX levels two to four times higher than those of the flesh. The present study is the first to provide scientific data demonstrating the high toxicity of the eyes.
A Novel Method for Regional Short-Term Forecasting of Water Level
Authors: Tu Zejie , Gao Xingguo , Xu Jun , Sun Weikang , Sun Yuewen , Su Dianpeng
Published: March 2021

The water level forecasting system represented by the hydrodynamic model relies too much on the input data and the forecast value of the boundary, therefore introducing uncertainty in the prediction results. Tide tables ignore the effect of the residual water level, which is usually significant. Therefore, to solve this problem, a water level forecasting method for the regional short-term (3 h) is proposed in this study. First, a simplified MIKE21 flow model (FM) was established to construct the regional major astronomical tides after subdividing the model residuals into stationary constituents (surplus astronomical tides, simulation deviation) and nonstationary constituents (residual water level). Harmonic analysis (HA) and long short-term memory (LSTM) were adopted to forecast these model residuals, respectively. Finally, according to different spatial background information, the prediction for each composition was corrected by the inverse distance weighting (IDW) algorithm and its improved IDW interpolation algorithm based on signal energy and the spatial distance (IDWSE) from adjacent observation stations to nonmeasured locations. The developed method was applied to Narragansett Bay in Rhode Island. Compared with the assimilation model, the root-mean-square error (RMSE) of the proposed method decreased from 12.3 to 5.0 cm, and R2 increased from 0.932 to 0.988. The possibility of adding meteorological features into the LSTM network was further explored as an extension of the prediction of the residual water level. The results show that the accuracy was limited to a moderate level, which is related to the difficulty presented by using only wind features to completely characterize the regional dynamic energy equilibrium process.
Variation of Diatoms at Different Scales in the Brazilian Pantanal Basin
Authors: Nardelli Margaret S. , Padial André A. , Bicudo Denise C. , Cordovil Claudia M. d. S. , Sampaio Silvio C.
Published: March 2021

(1) Background: We analyzed the diatom community structure of the surface sediments, in three permanent ponds in the Pantanal of Mato Grosso, Brazil, to better understand how biota in these aquatic environments depend on structural connectivity and functional connectivity: (2) Methods: Ten samples sites were established in each pond, water and the sediment were taken during the flood period. Abiotic–biotic variables were determined and standardized; (3) Results: The three ponds presented acidic water and high concentration of nitrogen, with the highest acidity for Ferradura Pond (P1) and the highest trophic status index for Burro Pond (P2), but the greatest environmental variations occurred in Caracará Pond (P3). The variation in diversity between sites in the same pond is what contributes the most to gamma diversity. The most abundant species was Aulacoseiraitalica (Ehrenberg) Simonsen and the genus Eunotia Ehrenberg was the most representative in species. Ferradura Pond, there was a relationship between compositional and environmental dissimilarities with geographic distance, but there was no independent. Burro Pond, the relationship the compositional variation with environmental variables was not significant. Caracará Pond, there was a relationship of compositional dissimilarity both with geographical distance and with environmental; (4) Conclusions: The set of results suggests that the mechanisms that determine the metacommunity of each pond are different and that the environmental conditions and dispersion influenced the structure and composition. Since, diatom species were different between ponds, and ponds more eutrophic showed less diversity. The pH and oligotrophy were the main factors to maintain the greatest diversity of species of the genus Eunotia and the greatest abundance of Aulacoseira italica. Knowing the dynamics and structure of diatoms, which are at the beginning of the food chain, is essential for conserving, maintaining, or rehabilitating wetland ecosystems, such as the Pantanal, which is part La Plata river basin, which represents the second largest surface for water resources in South America and the Guarani Aquifer System, the biggest unified groundwater aquifer in the world.