bluuebunny/crossref_metadata_2025 huggingface dataset:
Hollow Microneedles on a Paper Fabricated by Standard Photolithography for the Screening Test of Prediabetes
Authors: Wu Tianwei , You Xueqiu , Chen Zhong
Published: June 2022

Microneedle (MN) is a novel technique of the biomedical engineering field because of its ability to evaluate bioinformation via minimal invasion. One of the urgent requirements for ground-breaking health care monitoring is persistent monitoring. Hollow microneedles are extremely attractive to extract skin interstitial fluid (ISF) for analysis, which makes them perfect for sensing biomarkers and facilitating diagnosis. Nevertheless, its intricate fabrication process has hampered its extensive application. The present research demonstrates an easy one-step preparation approach for hollow MNs on the foundation of the refraction index variations of polyethylene glycol diacrylate (PEGDA) in the process of photopolymerization. The fabricated hollow microneedle exhibited ideal mechanical characteristics to penetrate the skin. Hydrodynamic simulations showed that the liquid was risen in a hollow microneedle by capillary force. Furthermore, a paper-based glucose sensor was integrated with the hollow microneedle. We also observed that the MN array smoothly extracted ISF in vitro and in vivo by capillary action. The outcomes displayed the applicability of the MN patch to persistent blood glucose (GLU) monitoring, diagnosis-related tests for patients and pre-diabetic individuals.
RadArnomaly: Protecting Radar Systems from Data Manipulation Attacks
Authors: Cohen Shai , Levy Efrat , Shaked Avi , Cohen Tair , Elovici Yuval , Shabtai Asaf
Published: June 2022

Radar systems are mainly used for tracking aircraft, missiles, satellites, and watercraft. In many cases, information regarding the objects detected by a radar system is sent to, and used by, a peripheral consuming system, such as a missile system or a graphical user interface used by an operator. Those systems process the data stream and make real-time operational decisions based on the data received. Given this, the reliability and availability of information provided by radar systems have grown in importance. Although the field of cyber security has been continuously evolving, no prior research has focused on anomaly detection in radar systems. In this paper, we present an unsupervised deep-learning-based method for detecting anomalies in radar system data streams; we take into consideration the fact that a data stream created by a radar system is heterogeneous, i.e., it contains both numerical and categorical features with non-linear and complex relationships. We propose a novel technique that learns the correlation between numerical features and an embedding representation of categorical features in an unsupervised manner. The proposed technique, which allows for the detection of the malicious manipulation of critical fields in a data stream, is complemented by a timing-interval anomaly-detection mechanism proposed for the detection of message-dropping attempts. Real radar system data were used to evaluate the proposed method. Our experiments demonstrated the method’s high detection accuracy on a variety of data-stream manipulation attacks (an average detection rate of 88% with a false -alarm rate of 1.59%) and message-dropping attacks (an average detection rate of 92% with a false-alarm rate of 2.2%).
A Vibration Fault Identification Framework for Shafting Systems of Hydropower Units: Nonlinear Modeling, Signal Processing, and Holographic Identification
Authors: Shi Yousong , Zhou Jianzhong , Huang Jie , Xu Yanhe , Liu Baonan
Published: June 2022

The shafting systems of hydropower units work as the core component for the conversion of water energy to electric energy and have been running for a long time in the hostile hydraulic–mechanical–electrical-coupled environment—their vibration faults are frequent. How to quickly and accurately identify vibration faults to improve the reliability of the unit is a key issue. This study proposes a novel shafting vibration fault identification framework, which is divided into three coordinated stages: nonlinear modeling, signal denoising, and holographic identification. A nonlinear dynamical model of bending–torsion coupling vibration induced by multiple excitation vibration sources of the shafting system is established in the first stage. The multi-stage signal denoising method combines Savitzky–Golay (SG) smoothing filtering, singular value decomposition (SVD), and variational mode decomposition (VMD). SG-SVD-VMD is used for the guide bearing the vibration signals in the second stage. Further, the holospectrum theory is innovatively introduced to obtain the holospectra of the simulated and measured signals, and the shafting vibration faults of the real unit are identified by comparing the holospectrum of the measured signal with the simulated signal. These results show that the shafting nonlinear model can effectively reflect the vibration characteristics of the coupled vibration source and reveal the influence and fault characteristics of each external excitation on the shafting vibration. The shafting vibration faults of operating units can be identified by analyzing the holospectra of the shafting simulation signals and measuring the noise reduction signals. Thus, this framework can guide the safe and stable operation of hydropower units.
Task-Oriented Evaluation of the Feasible Kinematic Directional Capabilities for Robot Machining
Authors: Stradovnik Saša , Hace Aleš
Published: June 2022

Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities prior to task execution, for which we need efficient algorithms, especially in the case of flexible robot applications. To provide accurate and physically consistent information about the maximum kinematic capabilities while considering the requirements of the task, an approach called the Decomposed Twist Feasibility (DTF) method is proposed in this study. The evaluation of the maximum feasible end-effector velocity is based on the idea of decomposition into the linear and angular motion capabilities, considering a typical robot machining task with synchronous linear and angular motion. The proposed DTF method is presented by the well-known manipulability polytope concept. Unlike the existing methods that estimate the kinematic performance capabilities in arbitrarily weighted twist space, or separately in the translation and the rotation subspace, our approach offers an accurate and simple solution for the determination of the total kinematic performance capabilities, which is often highly required, especially in the case of robot machining tasks. The numerical results obtained in this study show the effectiveness of the proposed approach. Moreover, the proposed DTF method could represent suitable kinematic performance criteria for the optimal placement of predefined tasks within the robot workspace.
Edge-Computing and Machine-Learning-Based Framework for Software Sensor Development
Authors: Hanzelik Pál Péter , Kummer Alex , Abonyi János
Published: June 2022

The present research presents a framework that supports the development and operation of machine-learning (ML) algorithms to develop, maintain and manage the whole lifecycle of modeling software sensors related to complex chemical processes. Our motivation is to take advantage of ML and edge computing and offer innovative solutions to the chemical industry for difficult-to-measure laboratory variables. The purpose of software sensor models is to continuously forecast the quality of products to achieve effective quality control, maintain the stable production condition of plants, and support efficient, environmentally friendly, and harmless laboratory work. As a result of the literature review, quite a few ML models have been developed in recent years that support the quality assurance of different types of materials. However, the problems of continuous operation, maintenance and version control of these models have not yet been solved. The method uses ML algorithms and takes advantage of cloud services in an enterprise environment. Industrial 4.0 devices such as the Internet of Things (IoT), edge computing, cloud computing, ML, and artificial intelligence (AI) are core techniques. The article outlines an information system structure and the related methodology based on data from a quality-assurance laboratory. During the development, we encountered several challenges resulting from the continuous development of ML models and the tuning of their parameters. The article discusses the development, version control, validation, lifecycle, and maintenance of ML models and a case study. The developed framework can continuously monitor the performance of the models and increase the amount of data that make up the models. As a result, the most accurate, data-driven and up-to-date models are always available to quality-assurance engineers with this solution.
Sensor-Based Prototype of a Smart Assistant for Visually Impaired People—Preliminary Results
Authors: Șipoș Emilia , Ciuciu Cosmin , Ivanciu Laura
Published: June 2022

People with visual impairment are the second largest affected category with limited access to assistive products. A complete, portable, and affordable smart assistant for helping visually impaired people to navigate indoors, outdoors, and interact with the environment is presented in this paper. The prototype of the smart assistant consists of a smart cane and a central unit; communication between user and the assistant is carried out through voice messages, making the system suitable for any user, regardless of their IT skills. The assistant is equipped with GPS, electronic compass, Wi-Fi, ultrasonic sensors, an optical sensor, and an RFID reader, to help the user navigate safely. Navigation functionalities work offline, which is especially important in areas where Internet coverage is weak or missing altogether. Physical condition monitoring, medication, shopping, and weather information, facilitate the interaction between the user and the environment, supporting daily activities. The proposed system uses different components for navigation, provides independent navigation systems for indoors and outdoors, both day and night, regardless of weather conditions. Preliminary tests provide encouraging results, indicating that the prototype has the potential to help visually impaired people to achieve a high level of independence in daily activities.
Simulation Study of Radio Frequency Safety and the Optimal Size of a Single-Channel Surface Radio Frequency Coil for Mice at 9.4 T Magnetic Resonance Imaging
Authors: Seo Jeung-Hoon , Ryu Yeunchul , Chung Jun-Young
Published: June 2022

The optimized size of a single-channel surface radio frequency (RF) coil for mouse body images in a 9.4 T magnetic resonance imaging (MRI) system was determined via electromagnetic-field analysis of the signal depth according to the size of a single-channel coil. The single-channel surface RF coils used in electromagnetic field simulations were configured to operate in transmission/reception mode at a frequency of 9.4 T–400 MHz. Computational analysis using the finite-difference time-domain method was used to assess the single-channel surface RF coil by comparing single-channel surface RF coils of varying sizes in terms of |B1|-, |B1+|-, |B1−|- and |E|-field distribution. RF safety for the prevention of burn injuries to small animals was assessed using an analysis of the specific absorption rate. A single-channel surface RF coil with a 20 mm diameter provided optimal B1-field distribution and RF safety, thus confirming that single-channel surface RF coils with ≥25 mm diameter could not provide typical B1-field distribution. A single-channel surface RF coil with a 20 mm diameter for mouse body imaging at 9.4 T MRI was recommended to preserve the characteristics of single-channel surface RF coils, and ensured that RF signals were applied correctly to the target point within RF safety guidelines.
Multi-Group Gorilla Troops Optimizer with Multi-Strategies for 3D Node Localization of Wireless Sensor Networks
Authors: Liang Qingwei , Chu Shu-Chuan , Yang Qingyong , Liang Anhui , Pan Jeng-Shyang
Published: June 2022

The localization problem of nodes in wireless sensor networks is often the focus of many researches. This paper proposes an opposition-based learning and parallel strategies Artificial Gorilla Troop Optimizer (OPGTO) for reducing the localization error. Opposition-based learning can expand the exploration space of the algorithm and significantly improve the global exploration ability of the algorithm. The parallel strategy divides the population into multiple groups for exploration, which effectively increases the diversity of the population. Based on this parallel strategy, we design communication strategies between groups for different types of optimization problems. To verify the optimized effect of the proposed OPGTO algorithm, it is tested on the CEC2013 benchmark function set and compared with Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Whale Optimization Algorithm (WOA) and Artificial Gorilla Troops Optimizer (GTO). Experimental studies show that OPGTO has good optimization ability, especially on complex multimodal functions and combinatorial functions. Finally, we apply OPGTO algorithm to 3D localization of wireless sensor networks in the real terrain. Experimental results proved that OPGTO can effectively reduce the localization error based on Time Difference of Arrival (TDOA).
Overcoming Identity Threat: Using Persona Pedagogy in Intersectionality and Inclusion Training
Authors: Thomas Cate
Published: June 2022

There are many efforts and strategies in place to increase the inclusivity of workplaces which is a positive approach, but little thought is provided to the personal cost of participants in undertaking some of these initiatives. Often due to the choice of pedagogy, participants may be placed in the situation to reveal hidden parts of their identity which leads to vulnerability and unpredicted exposure in the workplace and organisation. The paper examines the key issue of identity threat whilst undertaking inclusion and intersectional-type training. The paper highlights the continued need to challenge bias and other forms of exclusionary behavioural and cultural practices, however, this must be carried out in a cautious manner to uphold the safety of well-being of all individuals. A solution to minimize or overcome identity threat is offered via the use of persona pedagogy where personas are used expands one’s own world views and limits vulnerability exposure. The persona approach initiates experiences different to an individual’s lived experience which evokes critical reflection of one’s own positionality by taking on another persona. The paper concludes that the use of persona pedagogy leads to true transformative learning in the workplace whilst protecting the identity of individuals.
‘We Are Family’—How Urban Specialty Shops Portray the Consumers of Rural Provenance Foods
Authors: Forte Teresa , Figueiredo Elisabete
Published: June 2022

The literature on food consumption and marketing has been mainly concerned with identifying the appeal of the physical and sensorial features of food products, consumer choice determinants and their profiling according to socioeconomic characteristics, and perceptions and practices. This paper takes a different approach by analyzing how consumers are being represented and engaged with in the promotion of rural provenance foods, an overlooked topic within the literature. For this purpose, a content analysis was conducted on promotional materials (printed materials—including brochures, business cards and leaflets), website publications and social media (Facebook and Instagram) posts issued by 30 specialty shops located in three Portuguese cities (Aveiro, Lisbon and Porto). A total of 7491 files were analyzed. Empirical evidence shows that consumers are mainly portrayed through references to their symbolic features or as elements of a connection established and nurtured by the shops. Sociodemographic features lack relevance in opposition to the relevance attributed to the interaction between the shops and the consumers. All in all, the analysis highlights the significance of the interaction between the shops and the consumers in the promotion of products, fostering close and familiar relationships attentive to consumer preferences, emotions and values.
Multivariate Training Programs during Physical Education Classes in School Context: Theoretical Considerations and Future Perspectives
Authors: Silva Avelino , Ferraz Ricardo , Forte Pedro , Teixeira José E. , Branquinho Luís , Marinho Daniel A.
Published: June 2022

Physical Education plays a fundamental role in promoting healthy habits and lifestyles, as well as in the development of individual and cognitive skills. To date, several investigations have reported positive effects on indicators of physical fitness, motor proficiency, and creativity as a result of specific training programs during Physical Education classes. However, the effects of multivariate training programs on the improvement of the aforementioned skills remain unclear in the literature. Through this brief review, the benefit of applying multivariate training programs during Physical Education classes on indicators of physical fitness, motor proficiency and creativity was critically analyzed. A narrative approach was applied to summarize the availed research as following: (i) theoretical background; (ii) research gaps/issues; (iii) subject explanation about multivariate training programs in Physical Education; and (iv) practical application and further research. The evidence reported in this regard may be useful for the development of multivariate training programs that simultaneously enable the improvement of indicators of physical fitness, motor proficiency and creativity. However, there is still no consensus in the literature on the best strategies (i.e., type of program, duration, intensity) to enhance motor proficiency and creativity in the context of Physical Education classes using multivariate training programs.
Evaluating the Barriers to Industrial Symbiosis Using a Group AHP-TOPSIS Model
Authors: Yang Tian , Liu Changhao , Côté Raymond P. , Ye Jinwen , Liu Weifeng
Published: June 2022

Industrial symbiosis (IS) can contribute to achieving a win-win situation between industry and environment for local and regional circular economies. Many authors have recognized that a variety of barriers can hinder the implementation of IS. However, there is very limited research on quantitatively evaluating the IS barriers. In this paper, we propose a model which combines the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate the IS barriers semi-quantitatively. This model assists in identifying and prioritizing the fundamental barriers for implementation of IS in a comprehensive manner. An operating IS, the Hai Hua Group (HHG), in Shandong Province, China is used as a case study to test the proposed model. The results show that the top four generic barriers are technological barriers, economic barriers, safety barriers, and informational barriers. More specifically, the barriers are information platforms, human safety and health, technology involved with extending industrial chains, product added value, and costs. The paper concludes by discussing managerial implications for promoting the establishment and operation of IS.
Endemic Plants Can Be Resources for Mountain Agro-Ecosystems: The Case of Sanguisorba dodecandra Moretti
Authors: Giupponi Luca , Leoni Valeria , Gianoncelli Carla , Tamburini Alberto , Giorgi Annamaria
Published: June 2022

Sanguisorba dodecandra Moretti is an endemic plant of the Alps of the Lombardy region (Northern Italy). Differently from most endemic species, this plant grows in diverse environments, and it is often very abundant and a distinctive element of some mountain and sub-alpine agro-ecosystems. The ecological features and the role of this species in some mountain agricultural activities are poorly investigated. This article shows the results of a synecological analysis of S. dodecandra and the evaluation of its functional strategy. Furthermore, its forage value was investigated and melissopalynological analysis was used to characterize the honey produced in an area where this species grows. The ecological analysis defined this plant as euriecious and ruderal/competitive-ruderal strategist. Bromatological analysis showed a good forage value, confirming the ethnobotanical knowledge concerning this species. In fact, it has good protein content (12.92 ± 1.89%) and non-fiber carbohydrates (47.12 ± 3.62%) in pre-flowering. S. dodecandra pollen was identified as a “frequent pollen” in the honey, showing that this plant is attractive to honeybees. This research allowed a deeper knowledge of S. dodecandra ecology and showed that this species is a resource for traditional and sustainable agricultural activities of the Lombardy Alps such as pastoralism and beekeeping.
Sport for Development Programs Contributing to Sustainable Development Goal 5: A Review
Authors: Chong Yong-Yee , Sherry Emma , Harith Sophia , Khoo Selina
Published: June 2022

In Sport for Development (SFD), sport is used as a cost-effective tool to facilitate the objectives of various organizations, not limited to increasing access to education, youth development, social cohesion, and gender equality. This review aims to systematically analyze SFD programs that contribute to gender equality and women empowerment under Sustainable Development Goal 5 (SDG 5). The PRISMA methodology was used to guide the screening and selection process. Fifteen studies were identified from the Web of Science, Scopus, and SPORTDiscus databases, the Journal of Sport for Development, forward–backward reference searches, and manual searches on four prominent sport, gender, and development researchers. The findings indicated that there was evidence of micro-level outcomes in every study and three achieved meso-level impact; however, none of these studies’ suggested changes have reached the macro-level of impact when the outcomes were reported in these articles. There was a lack of intervention studies that investigated the mechanisms and reported outcomes through a validated monitoring and evaluation process. This review provides significant insights into: (a) identifying future SFD research areas, (b) refining SFD program evaluations, (c) developing indicators of outcomes for sport programs contributing to SDG 5, and (d) reproducing sustainable development outcomes under SDG 5.
GIS-Based Model for Constructing Ecological Efficiency Maps of Urban Green Areas: The Case Study of Western Naples, Italy
Authors: D’Ambrosio Valeria , Di Martino Ferdinando , Rigillo Marina
Published: June 2022

This research implements a GIS framework model aimed at evaluating the ecological efficiency of urban green areas. The model classifies urban green areas by identifying those that can provide ecosystem services to sustain green infrastructure at an urban district level. This model can also guide decision makers in the proper placement of the green infrastructure. The model works on the interrelation of four indicators of size, shape, vegetation structure and vegetation diversity, and it was tested in the case study of the Western Urban Districts of Naples (Italy). The selection of this study area is because it presents four urban districts that are different for physiography, urban patterns, land use, land cover and for the existing building stock. The proposed GIS-based framework can be a useful tool for planning actions and measures to protect, implement and restore existing green areas through integration into urban green infrastructure.
3D-Printed Programmable Mechanical Metamaterials for Vibration Isolation and Buckling Control
Authors: Zolfagharian Ali , Bodaghi Mahdi , Hamzehei Ramin , Parr Liam , Fard Mohammad , Rolfe Bernard F.
Published: June 2022

Vibration isolation performance at low-frequency ranges before resonance is a vital characteristic that conventional springs cannot exhibit. This paper introduces a novel zero Poisson’s ratio graded cylindrical metamaterial to fulfill two main goals: (1) vibration isolation performance in low-frequency bands prior to resonance and (2) global buckling control of a long cylindrical tube. For this purpose, “soft and stiff” re-entrant unit cells with varying stiffness were developed. The cylindrical metamaterials were then fabricated using a multi-jet fusion HP three-dimensional (3D) printer. The finite element analyses (FEA) and experimental results demonstrate that the simultaneous existence of multi-stiffness unit cells leads to quasi-zero stiffness (QZS) regions in the force-displacement relationship of a cylindrical metamaterial under compression. They possess significant vibration isolation performance at frequency ranges between 10 and 30 Hz. The proposed multi-stiffness re-entrant unit cells also offer global buckling control of long cylindrical tubes (with a length to diameter ratio of 3.7). The simultaneous existence of multi-stiffness re-entrant unit cells provides a feature for designers to adjust and control the deformation patterns and unit cells’ densification throughout cylindrical tubes.
Topology and Robustness of Weighted Air Transport Networks in Multi-Airport Region
Authors: Qian Bingxue , Zhang Ning
Published: June 2022

Topological analyses of multi-airport regional air transport networks are the basis for the sustainable development of multi-airport systems. In this study, we modeled the Yangtze River Delta (YRD) region’s airport infrastructure as a network and presented a weighted approach by which to analyze the network structure and robustness from the perspective of complex network theory. The analysis of the Yangtze River Delta Airport Network (YRDAN) indicates that it is a small-world network, and its cumulative degree has a power-law distribution, suggesting that it has scale-free properties. As its weighted clustering coefficient was found to be much smaller than the non-weighted counterpart, this demonstrates that most of the network traffic is focused on a hub-and-spoke pattern. Furthermore, the over-centrality of the YRDAN suggests weak accessibility of small cities and high dependence of air transport on the hub-and-spoke pattern. The assessment of the robustness of the YRDAN in the face of intentional attacks found that domestic networks are more robust than foreign aviation networks. However, the isolation of a small fraction of selected nodes can cause serious problems in the functioning of the YRDAN.
The Valorisation of Selected Quarry and Mine Waste for Sustainable Cement Production within the Concept of Circular Economy
Authors: Fidanchevski Emilija , Šter Katarina , Mrak Maruša , Kljajević Ljiljana , Žibret Gorazd , Teran Klemen , Poletanovic Bojan , Fidanchevska Monika , Dolenec Sabina , Merta Ildiko
Published: June 2022

The cement industry could potentially consume large amounts of solid industrial waste in order to improve its sustainability. The suitability of selected quarry and mine waste as secondary raw materials (SRM) was examined for the sustainable production of cement following the concept of a circular economy. The chemical, mineralogical, and radiological characterization of SRM was conducted in this study. Its potential use in low-carbon and low-energy belite-sulfoaluminate cement was investigated by incorporating the examined SRM into cement clinker. Various characterization methods were used to characterize the cement, including X-ray powder diffraction (XRD), thermal analysis (DTA/TG), and isothermal calorimetry. Depending on the chemical composition of the waste, lower or higher amounts were allowed to be incorporated into the raw clinker mixture for a targeted clinker phase composition. Among the samples, differences were observed in the phase composition of synthesized clinkers, which slightly influenced the reactivity of the cement but did not significantly change the compressive strength of the final product.
Socio-Economic and Environmental Analyses of Solar Irrigation Systems for Sustainable Agricultural Production
Authors: Guno Charmaine Samala , Agaton Casper Boongaling
Published: June 2022

Solar irrigation is a climate mitigation technology to reduce greenhouse gas (GHG) emissions in agricultural production. Despite its potential, small-scale farmers are unable to afford photovoltaic (PV) systems and resort to using the traditional diesel-powered pumps for irrigation. This study aims to analyze the social, economic, and environmental aspects of introducing solar irrigation systems from the perspective of small-scale farmers in developing countries. Applying socio-economic and environmental analyses to the case of the Philippines, the study found the environmental benefits of solar irrigation in terms of the reduction in GHG emissions of up to 26.5 tons CO2eq/ha/year and the avoidance of emissions of air pollutants such as carbon monoxide, nitrogen oxides, sulfur oxides, and particulate matter. The energy savings between 11.36 and 378.54 L/ha of diesel per year resulted in a range of −USD 1255/ha to USD 68,582/ha net present value, 30% to 2958% with an average of 315% returns on investment, and 0.3 to 30 years payback period with an average of 2.88 years. Regardless of the low awareness of environmental sustainability, most farmers were interested to invest in solar irrigation systems with 69% social acceptance, while the 26% were not interested as they consume a minimal amount of fuel and cannot recover the high investment from the cost savings. This study provided policy recommendations to make solar irrigation accessible to small-scale farmers as well as broader implications to make the agricultural sector more sustainable.
Utilization of Recycled Plastic Waste in Fiber Reinforced Concrete for Eco-Friendly Footpath and Pavement Applications
Authors: Suksiripattanapong Cherdsak , Phetprapai Taweerat , Singsang Witawat , Phetchuay Chayakrit , Thumrongvut Jaksada , Tabyang Wisitsak
Published: June 2022

The use of concrete in road construction has grown over the past decade due to the material’s great durability. However, concrete has poor tensile strength, ductility, and energy absorption. This paper aims to investigate the utilization of plastic waste, namely polypropylene (PP), to create a novel fiber to enhance the engineering properties of fiber reinforced concrete (FRC), an eco-friendly concrete that can reduce environmental problems. The 28-day design strengths of 28 and 32 MPa were used in this study because the compressive strength requirements for concrete footpaths and pavement specified by Austroads and the Department of Highways, Thailand, were at least 25 and 32 MPa, respectively. The fiber (F) was a mixture of virgin PP and recycled PP (RPP). The study used F contents of 0.25, 0.50, 0.75, and 1% by weight of cement and PP:RPP ratios of 100:0, 75:25, 50:50, 25:75, and 0:100. The compressive strength, flexural strength, leaching, and CO2 emissions savings of FRC were evaluated. Improvements in the compressive strength, flexural strength, and toughness of the samples with F were observed in comparison to the control concrete samples for all design strengths. All mixtures met the compressive strength requirements for concrete footpaths, except for F contents of 0.75 and 1% and a PP:RPP ratio of 0:100. By contrast, the 32 MPa FRC samples with F contents of 0.25 and 0.5% and all PP:RPP ratios met the requirements for rigid pavement. From an environmental perspective, the heavy metal contaminants of the 32 MPa FRC sample were within the allowable limits for all mixtures. Regarding incineration disposal, the maximum CO2 emissions savings of 28 MPa and 32 MPa FRC with an F content of 0.5% and a PP:RPP ratio of 0:100 were 1.0 and 1.11 kg CO2-e/m3, respectively. This research will enable plastic waste, traditionally destined for incineration and landfill disposal, to be used as a sustainable fiber in the construction industry.
The Contribution of Oil Palm Smallholders Farms to the Implementation of the Sustainable Development Goals-Measurement Attempt
Authors: Sukiyono Ketut , Romdhon Muhammad Mustopa , Mulyasari Gita , Yuliarso M. Zulkarnain , Nabiu Musriyadi , Trisusilo Agung , Reflis  , Napitupulu Dompak M. T. , Nugroho Yoga , Puspitasari May Shiska , Sugiardi Sigit , Arifudin  , Masliani
Published: June 2022

Smallholder oil palm plantations play an essential role in the Indonesian economy, both on a national, regional, local, and household scale. However, no data or studies show how much smallholder oil palm plantations contribute to achieving in each sustainable development goals (SDGs). The development of smallholder oil palm plantations, like other economic developments, wherever conducted needs to provide benefits to the community such that it exceeds the costs incurred, including the costs of preserving and protecting the environment. To assess its contribution, it is essential to examine the Sustainable Development targets in which smallholder oil palm plantations contribute. Therefore, this study is aimed at examining sustainable development goals to which smallholder oil palm plantations can contribute. Based on focus group discussion and the literature review, there are 13 SDGs for smallholder oil palm plantations that contribute and play a role in achieving the targets set by the United Nations in sustainable development. These results are significant as a basis for further studies to prove the presumption concerning the role and positive contribution of smallholder oil palm plantations in each of the existing SDG targets.
The Role of Digital Collaboration in Student Engagement towards Enhancing Student Participation during COVID-19
Authors: Gopinathan Sharmini , Kaur Anisha Haveena , Veeraya Segaran , Raman Murali
Published: June 2022

As Malaysia’s educational landscape continues to evolve, there is a need to rethink the models and practices involved in the teaching and learning process. The coronavirus disease (COVID-19) pandemic, subsequent lockdowns, and movement control restrictions have contributed to the shift in education, especially in teaching and learning. Educational institutions were instructed to close during the lockdowns and this forced educators and students to communicate and engage using digital technologies. Students have no issues when it comes to embracing technology, but their ability to stay engaged and participate during lessons was of concern to educators. According to recent research, collaborative learning has been shown to be enjoyable and engaging for students, especially when it is conducted digitally using innovative learning technologies. When students show an increased level of engagement, it shows that they are actively participating and are more involved during lessons. This quantitative study looks into the relationship between variables pertaining to digital collaboration (personal factors, environmental factors, social media support, digital collaborative tools, interactivity, motivation) and student engagement toward enhanced student participation during COVID-19. The study utilizes Lev Vygotsky’s Collaborative Learning Theory alongside Albert Bandura’s Social Learning Theory. The data analysis revealed that there is a positive significant relationship between digital collaborative tools, interactivity, and motivation towards student engagement, which in turn proved that there is a positive significant relationship that can be drawn between student engagement and enhanced student participation during COVID-19.
When Scent Becomes a Weapon—Plant Essential Oils as Potent Bioinsecticides
Authors: Devrnja Nina , Milutinović Milica , Savić Jelena
Published: June 2022

Crop protection still mostly relies on synthetic pesticides for crop pest control. However, the rationale for their continued use is shaded by the revealed adverse effects, such as relatively long environmental persistence that leads to water and soil contamination and retention of residues in food that brings high risks to human and animal health. As part of integrated pest management, biopesticides may provide crop protection, being eco-friendly and safe for humans and non-target organisms. Essential oils, complex mixtures of low-molecular-weight, highly volatile compounds, have been highlighted as major candidates for plant-derived bioinsecticides that are up to the sustainable biological standard. In this review, we screened the insecticidal activity of essential oils or their purified compounds, with focus given to their modes of action, along with the analyzed advantages and problems associated with their wider usage as plant-derived insecticides in agriculture.
Evaluation of Green Logistics Efficiency in Northwest China
Authors: Qin Wen , Qi Xiaolie
Published: June 2022

This paper develops an index system for assessing green logistics efficiency in Northwest China with the goal of “double carbon” (peak carbon dioxide emissions and carbon neutrality). The study employs a three-stage data envelopment analysis model of super efficiency to assess the spatial and temporal efficiency of the green logistics industry in Northwest China from 2010 to 2019. Our findings reveal that the overall logistics efficiency in Northwest China fluctuates. Each province has a high pure technical efficiency, but significant regional differences in comprehensive technical efficiency and scale efficiency are apparent. In Northwest China, government support and science and technology levels have a greater impact on green logistics efficiency. Based on the implementation of the “double carbon” strategy, this study offers pertinent insights and suggestions for the high-quality development of the green logistics industry in Northwest China.
Does Knowledge Evolution Matter? Reflection on Alpine Tribes Industry, Development, and Transformation
Authors: Pan Ssu-Chi , Hu Tai-Shan , Chia Ben-Zin , Chang Su-Li , Lin Hai-Ping
Published: June 2022

Young aboriginals are emigrating from their homelands to cities to become laborers working in basic production-related jobs, hampering the sustainability of the alpine tribes. This study examines the critical demands of Tungpu Daigaz, an alpine tribe in Taiwan, through in-depth interviews and questionnaires. Based on the analytical results, we propose that for the alpine tribe, the government should further improve transportation, add value to featured tribal products, and close the consensus gap among tribes. Whereas previous studies have recommended strategies, including loans and human resource training, we believe that the improvements should be accomplished through acquisition, transmission, creation, and use. This study establishes a KBD model to construct industrial knowledge for Tungpu Daigaz. Knowledge translation is carried out by integrating new hunter knowledge with tribal opinions. Knowledge transmission is then performed to encourage group learning. Long-term development depends on knowledge creation by tribes. We suggest that the government build a hub for the industries connecting Tungpu hot spring with the tribal resources and enhance sustainable development through tribal mountain guides and the hunting culture of Tungpu Daigaz. The knowledge-hunting developmental model can balance Tungpu Daigaz while developing the culture and wisdom of alpine tribes, solve the problems of tribal development, and ensure environmental protection and sustainable development. This study establishes a circulation system of new hunter knowledge based on a comprehensive understanding of the demands of local development for knowledge creation and skill integration, cooperation with external expertise and young innovative knowledge of tribal youths, and co-management with self-media. This novel KBD model can promote tribe sustainability.
Review of the Law Popularizing Education on Administrative Compulsion in Response to Major Epidemic Situations in China
Authors: Zhang Yujia , Chu Zuwang , Song Dongdong
Published: June 2022

The popularization of education on the administrative compulsion law in response to major epidemic situations in China refers to the educational activities carried out by an educational subject aimed at an educational object promoting understanding and mastery of knowledge of administrative compulsion. The goal is to improve the government’s legal ability to prevent and control behavior, enhance people’s awareness of the rule of law, and provide a strong legal basis for the rule of law in the context of major epidemics. Other aims are to cultivate citizens’ legal beliefs, restrain citizens’ conduct, and maintain a stable social order. However, problems arise in the subject, content, and mode of the educational activities. Therefore, we need to discuss compulsory education in the context of major epidemic situations, including the need for a favorable educational environment, the strengthening of information distribution, and the guidance of public opinion on administrative enforcement. We should also improve education subjects to enhance the legal quality of administrative organs, perfect the education content, encourage people to support administrative compulsion in epidemic situations, and deliver education in campus online classes.
Artisanal and Small-Scale Gold Mining (ASGM): Management and Socioenvironmental Impacts in the Northern Amazon of Ecuador
Authors: Mestanza-Ramón Carlos , Mora-Silva Demmy , D’Orio Giovanni , Tapia-Segarra Enrique , Gaibor Isabel Dominguez , Esparza Parra José Fernando , Chávez Velásquez Carlos Renato , Straface Salvatore
Published: June 2022

Mining is one of the oldest economic activities of mankind. Within this activity, artisanal and small-scale gold mining (ASGM) is one of the most studied sectors due to its high level of environmental contamination and the social problems it causes. In recent years, ASGM in the northern Amazon of Ecuador has increased significantly, and studies that describe its current situation and impact are scarce. In this sense, the present study aimed to analyze the current status and socioenvironmental impacts caused by ASGM gold mining activities in the Cascales canton in the province of Sucumbíos in northeastern Ecuador. The methodological tools used in the present study were a literature review of scientific and gray literature, field visits to assess perceived impacts and an expert judgment to discuss the results and establish challenges. The main results indicate that illegal and informal activities continue to be carried out in the upper zone of the Cascales and Duvino rivers; 90% of local miners still use mercury in this activity, although it is legally prohibited. Among the main impacts evidenced are the contamination of water bodies, soil and atmosphere due to the use of mercury and disturbance to flora and fauna due to the use of machinery in the exploration process. Finally, the government should focus efforts on strengthening public policies to socialize the importance of good environmental practices in ASGM and the effects of the impacts on human health and environmental issues, all this with the support of social actors, such as ministries, universities, NGOs, ASGM associations and private enterprise.
Preparation and Characterization of Insulating Panels from Recycled Polylaminate (Tetra Pak) Materials
Authors: Bonocore Gregorio , De Luca Pierantonio
Published: June 2022

Eco-sustainability and the reuse of materials are highly topical issues. In fact, in recent years, much study and research has been developed on this aspect, making the eco-sustainability of materials a real need. Polylaminate containers, more commonly called Tetra Pak containers, represent the most used packaging in the world. This work proposes a new strategy for the reuse of discarded polylaminate containers in order to create panels that can be used in construction and in particular as insulating panels. The proposed thermal method has been optimized in terms of operating variables such as time, temperature, pressure, number of polylaminate sheets. The results obtained show that the proposed thermal method is suitable for obtaining panels with characteristics suitable for use in green building. The advantage of the thermal method is that it does not use chemical or other binders and moreover uses only and exclusively sheets of recycled polylaminate.
Rare Romanian Ethnographic Textiles—Reverse Engineering of Fabrics for Fashion Trends
Authors: Elnashar ElSayed A. , Indrie Liliana , Ilieş Dorina Camelia , Zlatev Zlatin , Herman Grigore Vasile , Secan Cristina , Wendt Jan A.
Published: June 2022

(1) Investigating, collecting data with specific character, as well as registering and investigating data concerning ornaments and colors, patterns as expressive possibilities of designs of Romanian folk textile are important activities to do. The first goal of the research undertaken was to collect, preserve, and protect knowledge about old patterns and weaving techniques in selected regions of Romania, and the second to use old patterns for the modern needs of folk handicraft weaving and the clothing industry. (2) In the undertaken research, material was obtained from antique textiles, clothes, and paintings on canvas, from selected objects in the Maramureș region and Bihor region. The selection was made by the ReliefF method. The specimens of specification throw weight by the geometry method was used to characterize the types of weaving techniques. Principal component analysis methods were used to reduce the amount of data of the vector of textural features. (3) The research on selected Romanian textiles allowed for the construction of a model of texture features that describes them. The results include the specimens’ measurements, analysis of fabric structures, yarn specification, and the reconstruction of the fabrics. Based on the obtained results, a simulation of fashion trends was performed. (4) The analysis of individual components increased the knowledge of weaving techniques in the studied regions and may be an inspiration for contemporary design in local and regional handicrafts as well as in the clothing industry.
Model Selection Using K-Means Clustering Algorithm for the Symmetrical Segmentation of Remote Sensing Datasets
Authors: Ali Ishfaq , Rehman Atiq Ur , Khan Dost Muhammad , Khan Zardad , Shafiq Muhammad , Choi Jin-Ghoo
Published: June 2022

The importance of unsupervised clustering methods is well established in the statistics and machine learning literature. Many sophisticated unsupervised classification techniques have been made available to deal with a growing number of datasets. Due to its simplicity and efficiency in clustering a large dataset, the k-means clustering algorithm is still popular and widely used in the machine learning community. However, as with other clustering methods, it requires one to choose the balanced number of clusters in advance. This paper’s primary emphasis is to develop a novel method for finding the optimum number of clusters, k, using a data-driven approach. Taking into account the cluster symmetry property, the k-means algorithm is applied multiple times to a range of k values within which the balanced optimum k value is expected. This is based on the uniqueness and symmetrical nature among the centroid values for the clusters produced, and we chose the final k value as the one for which symmetry is observed. We evaluated the proposed algorithm’s performance on different simulated datasets with controlled parameters and also on real datasets taken from the UCI machine learning repository. We also evaluated the performance of the proposed method with the aim of remote sensing, such as in deforestation and urbanization, using satellite images of the Islamabad region in Pakistan, taken from the Sentinel-2B satellite of the United States Geological Survey. From the experimental results and real data analysis, it is concluded that the proposed algorithm has better accuracy and minimum root mean square error than the existing methods.