bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Point Flexible Temperature Sensor Array and Thermoelectric Generator Made from Copper-Coated Textiles
Authors: Landsiedel Justus , Root Waleri , Aguiló-Aguayo Noemí , Duelli Heinz , Bechtold Thomas , Pham Tung
Published: May 2021

The integration of electrical functionality into flexible textile structures requires the development of new concepts for flexible conductive material. Conductive and flexible thin films can be generated on non-conductive textile materials by electroless metal deposition. By electroless copper deposition on lyocell-type cellulose fabrics, thin conductive layers with a thickness of approximately 260 nm were prepared. The total copper content of a textile fabric was analyzed to be 147 mg per g of fabric, so that the textile character of the material remains unchanged, which includes, for example, the flexibility and bendability. The flexible material could be used to manufacture a thermoelectric sensor array and generator. This approach enables the formation of a sensor textile with a large number of individual sensors and, at the same time, a reduction in the number of electrical connections, since the conductive textile serves as a common conductive line for all sensors. In combination with aluminum, thermoelectric coefficients of 3–4 µV/K were obtained, which are comparable with copper/aluminum foil and bulk material. Thermoelectric generators, consisting of six junctions using the same material combinations, led to electric output voltages of 0.4 mV for both setups at a temperature difference of 71 K. The results demonstrate the potential of electroless deposition for the production of thin-film-coated flexible textiles, and represent a key technology to achieve the direct integration of electrical sensors and conductors in non-conductive material.
A Sensor-Based Decision Support System for Transfemoral Socket Rectification
Authors: Karamousadakis Michalis , Porichis Antonis , Ottikkutti Suranjan , Chen DeJiu , Vartholomeos Panagiotis
Published: May 2021

A decision support system (DSS) was developed that outputs suggestions for socket-rectification actions to the prosthetist, aiming at improving the fitness of transfemoral prosthetic socket design and reducing the time needed for the final socket design. For this purpose, the DSS employs a fuzzy-logic inference engine (IE) which combines a set of rectification rules with pressure measurements generated by sensors embedded in the socket, for deciding the rectification actions. The latter is then processed by an algorithm that receives, manipulates and modifies a 3D digital socket model as a triangle mesh formatted inside an STL file. The DSS results were validated and tested in an FEA simulation environment, by simulating and comparing the donning process among a good-fitting socket, a loose socket (poor-fit) and several rectified sockets produced by the proposed DSS. The simulation results indicate that volume reduction improves the pressure distribution over the stump. However, as the intensity of socket rectification increases, i.e., as volume reduction increases, high pressures appear in other parts of the socket which generate discomfort. Therefore, a trade-off is required between the amount of rectification and the balance of the pressure distributions experienced at the stump.
Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor
Authors: Jeong Yeon-Keun , Baek Kwang-Ryul
Published: May 2021

Walking is one of the most basic human activities. Various diseases may be caused by abnormal walking, and abnormal walking is mostly caused by disease. There are various characteristics of abnormal walking, but in general, it can be judged as asymmetric walking. Generally, spatiotemporal parameters can be used to determine asymmetric walking. The spatiotemporal parameter has the disadvantage that it does not consider the influence of the diversity of patterns and the walking speed. Therefore, in this paper, we propose a method to analyze asymmetric walking using Dynamic Time Warping (DTW) distance, a time series analysis method. The DTW distance was obtained by combining gyroscope data and pressure data. The experiment was carried out by performing symmetrical walking and asymmetrical walking, and asymmetric walking was performed as a simulation of hemiplegic walking by fixing one ankle using an auxiliary device. The proposed method was compared with the existing asymmetric gait analysis method. As a result of the experiment, a p-value lower than 0.05 was obtained, which proved that there was a statistically significant difference.
GeoAir—A Novel Portable, GPS-Enabled, Low-Cost Air-Pollution Sensor: Design Strategies to Facilitate Citizen Science Research and Geospatial Assessments of Personal Exposure
Authors: Park Yoo Min , Sousan Sinan , Streuber Dillon , Zhao Kai
Published: May 2021

The rapid evolution of air sensor technologies has offered enormous opportunities for community-engaged research by enabling citizens to monitor the air quality at any time and location. However, many low-cost portable sensors do not provide sufficient accuracy or are designed only for technically capable individuals by requiring pairing with smartphone applications or other devices to view/store air quality data and collect location data. This paper describes important design considerations for portable devices to ensure effective citizen engagement and reliable data collection for the geospatial analysis of personal exposure. It proposes a new, standalone, portable air monitor, GeoAir, which integrates a particulate matter (PM) sensor, volatile organic compound (VOC) sensor, humidity and temperature sensor, LTE-M and GPS module, Wi-Fi, long-lasting battery, and display screen. The preliminary laboratory test results demonstrate that the PM sensor shows strong performance when compared to a reference instrument. The VOC sensor presents reasonable accuracy, while further assessments with other types of VOC are needed. The field deployment and geo-visualization of the field data illustrate that GeoAir collects fine-grained, georeferenced air pollution data. GeoAir can be used by all citizens regardless of their technical proficiency and is widely applicable in many fields, including environmental justice and health disparity research.
S3: An AI-Enabled User Continuous Authentication for Smartphones Based on Sensors, Statistics and Speaker Information
Authors: Espín López Juan Manuel , Huertas Celdrán Alberto , Marín-Blázquez Javier G. , Esquembre Francisco , Martínez Pérez Gregorio
Published: May 2021

Continuous authentication systems have been proposed as a promising solution to authenticate users in smartphones in a non-intrusive way. However, current systems have important weaknesses related to the amount of data or time needed to build precise user profiles, together with high rates of false alerts. Voice is a powerful dimension for identifying subjects but its suitability and importance have not been deeply analyzed regarding its inclusion in continuous authentication systems. This work presents the S3 platform, an artificial intelligence-enabled continuous authentication system that combines data from sensors, applications statistics and voice to authenticate users in smartphones. Experiments have tested the relevance of each kind of data, explored different strategies to combine them, and determined how many days of training are needed to obtain good enough profiles. Results showed that voice is much more relevant than sensors and applications statistics when building a precise authenticating system, and the combination of individual models was the best strategy. Finally, the S3 platform reached a good performance with only five days of use available for training the users’ profiles. As an additional contribution, a dataset with 21 volunteers interacting freely with their smartphones for more than sixty days has been created and made available to the community.
Design of an Innovative Methodology for Cerebrospinal Fluid Analysis: Preliminary Results
Authors: Schirinzi Tommaso , Cordella Alberto , Mercuri Nicola Biagio , D’Amico Arnaldo , Palombi Andrea , Zompanti Alessandro , Grasso Simone , Pennazza Giorgio , Santonico Marco
Published: May 2021

Cerebrospinal fluid (CSF) analysis supports diagnosis of neurodegenerative diseases (NDs), however a number of issues limits its potentialities in clinical practice. Here, a newly developed technique for fluid voltammetry, relying on a simple sensor (BIOsensor-based multisensorial system for mimicking Nose, Tongue and Eyes, BIONOTE), was used to test the applicability for CSF analysis. BIONOTE was initially calibrated on an artificial CSF-like solution and then applied on human CSF, either immediately after collection or after refrigerated storage. Following optimization, it was used to evaluate 11 CSF samples correlating the electrochemical dataset with CSF routine parameters and biomarkers of neurodegeneration. Multivariate data analysis was performed for model elaboration and calibration using principal component analysis and partial least squares discriminant analysis. BIONOTE presented a high capacity to predict both physiological and pathological constituents of artificial CSF. It differentiated distinct fresh human CSF samples well but lost accuracy after refrigerated storage. The electrochemical analysis-derived data correlated with either CSF routine cytochemical indexes or a biomarker of neurodegeneration. BIONOTE resulted as being a reliable system for electrochemical analysis of CSF. The CSF fingerprint provided by the sensor has shown itself to be sensitive to CSF modification, thus it is potentially representative of CSF alteration. This result opens the way to its testing in further study addressed at assessing the clinical relevance of the methodology. Because of its advantages due to the ease and rapidity of the methodology, a validation study is now required to translate the technique into clinical practice and improve diagnostic workup of NDs.
Sensitivity to Haptic Sound-Localization Cues at Different Body Locations
Authors: Fletcher Mark D. , Zgheib Jana , Perry Samuel W.
Published: May 2021

Cochlear implants (CIs) recover hearing in severely to profoundly hearing-impaired people by electrically stimulating the cochlea. While they are extremely effective, spatial hearing is typically severely limited. Recent studies have shown that haptic stimulation can supplement the electrical CI signal (electro-haptic stimulation) and substantially improve sound localization. In haptic sound-localization studies, the signal is extracted from the audio received by behind-the-ear devices and delivered to each wrist. Localization is achieved using tactile intensity differences (TIDs) across the wrists, which match sound intensity differences across the ears (a key sound localization cue). The current study established sensitivity to across-limb TIDs at three candidate locations for a wearable haptic device, namely: the lower tricep and the palmar and dorsal wrist. At all locations, TID sensitivity was similar to the sensitivity to across-ear intensity differences for normal-hearing listeners. This suggests that greater haptic sound-localization accuracy than previously shown can be achieved. The dynamic range was also measured and far exceeded that available through electrical CI stimulation for all of the locations, suggesting that haptic stimulation could provide additional sound-intensity information. These results indicate that an effective haptic aid could be deployed for any of the candidate locations, and could offer a low-cost, non-invasive means of improving outcomes for hearing-impaired listeners.
SDN-Based Network Slicing Mechanism for a Scalable 4G/5G Core Network: A Kubernetes Approach
Authors: Botez Robert , Costa-Requena Jose , Ivanciu Iustin-Alexandru , Strautiu Vlad , Dobrota Virgil
Published: May 2021

Managing the large volumes of IoT and M2M traffic requires the evaluation of the scalability and reliability for all the components in the end-to-end system. This includes connectivity, mobile network functions, and application or services receiving and processing the data from end devices. Firstly, this paper discusses the design of a containerized IoT and M2M application and the mechanisms for delivering automated scalability and high availability when deploying it in: (1) the edge using balenaCloud; (2) the Amazon Web Services cloud with EC2 instances; and (3) the dedicated Amazon Web Services IoT service. The experiments showed that there are no significant differences between edge and cloud deployments regarding resource consumption. Secondly, the solutions for scaling the 4G/5G network functions and mobile backhaul that provide the connectivity between devices and IoT/M2M applications are analyzed. In this case, the scalability and high availability of the 4G/5G components are provided by Kubernetes. The experiments showed that our proposed scaling algorithm for network slicing managed with SDN guarantees the necessary radio and network resources for end-to-end high availability.
Evaluation of a Low-Cost Commercial Actigraph and Its Potential Use in Detecting Cultural Variations in Physical Activity and Sleep
Authors: Topalidis Pavlos , Florea Cristina , Eigl Esther-Sevil , Kurapov Anton , Leon Carlos Alberto Beltran , Schabus Manuel
Published: May 2021

The purpose of the present study was to evaluate the performance of a low-cost commercial smartwatch, the Xiaomi Mi Band (MB), in extracting physical activity and sleep-related measures and show its potential use in addressing questions that require large-scale real-time data and/or intercultural data including low-income countries. We evaluated physical activity and sleep-related measures and discussed the potential application of such devices for large-scale step and sleep data acquisition. To that end, we conducted two separate studies. In Study 1, we evaluated the performance of MB by comparing it to the GT3X (ActiGraph, wGT3X-BT), a scientific actigraph used in research, as well as subjective sleep reports. In Study 2, we distributed the MB across four countries (Austria, Germany, Cuba, and Ukraine) and investigated physical activity and sleep among these countries. The results of Study 1 indicated that MB step counts correlated highly with the scientific GT3X device, but did display biases. In addition, the MB-derived wake-up and total-sleep-times showed high agreement with subjective reports, but partly deviated from GT3X predictions. Study 2 revealed similar MB step counts across countries, but significant later wake-up and bedtimes for Ukraine than the other countries. We hope that our studies will stimulate future large-scale sensor-based physical activity and sleep research studies, including various cultures.
Recent Advancements in Receptor Layer Engineering for Applications in SPR-Based Immunodiagnostics
Authors: Drozd Marcin , Karoń Sylwia , Malinowska Elżbieta
Published: May 2021

The rapid progress in the development of surface plasmon resonance-based immunosensing platforms offers wide application possibilities in medical diagnostics as a label-free alternative to enzyme immunoassays. The early diagnosis of diseases or metabolic changes through the detection of biomarkers in body fluids requires methods characterized by a very good sensitivity and selectivity. In the case of the SPR technique, as well as other surface-sensitive detection strategies, the quality of the transducer-immunoreceptor interphase is crucial for maintaining the analytical reliability of an assay. In this work, an overview of general approaches to the design of functional SPR-immunoassays is presented. It covers both immunosensors, the design of which utilizes well-known and often commercially available substrates, as well as the latest solutions developed in-house. Various approaches employing chemical and passive binding, affinity-based antibody immobilization, and the introduction of nanomaterial-based surfaces are discussed. The essence of their influence on the improvement of the main analytical parameters of a given immunosensor is explained. Particular attention is paid to solutions compatible with the latest trends in the development of label-free immunosensors, such as platforms dedicated to real-time monitoring in a quasi-continuous mode, the use of in situ-generated receptor layers (elimination of the regeneration step), and biosensors using recombinant and labelled protein receptors.
Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges
Authors: Malik Sumbal , Khan Manzoor Ahmed , El-Sayed Hesham
Published: May 2021

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.
A Review of EEG Signal Features and Their Application in Driver Drowsiness Detection Systems
Authors: Stancin Igor , Cifrek Mario , Jovic Alan
Published: May 2021

Detecting drowsiness in drivers, especially multi-level drowsiness, is a difficult problem that is often approached using neurophysiological signals as the basis for building a reliable system. In this context, electroencephalogram (EEG) signals are the most important source of data to achieve successful detection. In this paper, we first review EEG signal features used in the literature for a variety of tasks, then we focus on reviewing the applications of EEG features and deep learning approaches in driver drowsiness detection, and finally we discuss the open challenges and opportunities in improving driver drowsiness detection based on EEG. We show that the number of studies on driver drowsiness detection systems has increased in recent years and that future systems need to consider the wide variety of EEG signal features and deep learning approaches to increase the accuracy of detection.
Development and Proof of Concept of a Miniaturized MEMS Quantum Tunneling Accelerometer Based on PtC Tips by Focused Ion Beam 3D Nano-Patterning
Authors: Haub Michael , Bogner Martin , Guenther Thomas , Zimmermann André , Sandmaier Hermann
Published: May 2021

Most accelerometers today are based on the capacitive principle. However, further miniaturization for micro integration of those sensors leads to a poorer signal-to-noise ratio due to a small total area of the capacitor plates. Thus, other transducer principles should be taken into account to develop smaller sensors. This paper presents the development and realization of a miniaturized accelerometer based on the tunneling effect, whereas its highly sensitive effect regarding the tunneling distance is used to detect small deflections in the range of sub-nm. The spring-mass-system is manufactured by a surface micro-machining foundry process. The area of the shown polysilicon (PolySi) sensor structures has a size smaller than 100 µm × 50 µm (L × W). The tunneling electrodes are placed and patterned by a focused ion beam (FIB) and gas injection system (GIS) with MeCpPtMe3 as a precursor. A dual-beam system enables maximum flexibility for post-processing of the spring-mass-system and patterning of sharp tips with radii in the range of a few nm and initial distances between the electrodes of about 30–300 nm. The use of metal–organic precursor material platinum carbon (PtC) limits the tunneling currents to about 150 pA due to the high inherent resistance. The measuring range is set to 20 g. The sensitivity of the sensor signal, which depends exponentially on the electrode distance due to the tunneling effect, ranges from 0.4 pA/g at 0 g in the sensor operational point up to 20.9 pA/g at 20 g. The acceleration-equivalent thermal noise amplitude is calculated to be 2.4–3.4 mg/Hz. Electrostatic actuators are used to lead the electrodes in distances where direct quantum tunneling occurs.
On Differential Imaging Using Electromagnetic Simulation for Vehicular Antenna Signature Analysis
Authors: Solano-Perez Jose Antonio , Martínez-Inglés María-Teresa , Molina-Garcia-Pardo Jose-Maria , Romeu Jordi , Jofre-Roca Lluis , Ballesteros-Sánchez Christian , Rodríguez José-Víctor , Mateo-Aroca Antonio , Guzmán-Quirós Raúl
Published: May 2021

The current trend in vehicles is to integrate a wide number of antennae and sensors operating at a variety of frequencies for sensing and communications. The integration of these antennae and sensors in the vehicle platform is complex because of the way in which the antenna radiation patterns interact with the vehicle structure and other antennae/sensors. Consequently, there is a need to study the radiation pattern of each antenna or, alternatively, the currents induced on the surface of the vehicle to optimize the integration of multiple antennae. The novel concept of differential imaging represents one method by which it is possible to obtain the surface current distribution without introducing any perturbing probe. The aim of this study was to develop and confirm the assumptions that underpin differential imaging by means of full-wave electromagnetic simulation, thereby providing additional verification of the concept. The simulation environment and parameters were selected to replicate the conditions in which real measurements were taken in previous studies. The simulations were performed using Ansys HFSS simulation software. The results confirm that the approximations are valid, and the differential currents are representative of the induced surface currents generated by a monopole positioned on the top of a vehicle.
Effect of Different Head Hole Position on the Rotational Resistance and Stability of Orthodontic Miniscrews: A Three-Dimensional Finite Element Study
Authors: Choi Jin-Young , Kim Min-Jung , Kim Seong-Hun , Chung Kyu-Rhim , Nelson Gerald
Published: May 2021

The orthodontic miniscrew is driven into bone in a clockwise direction. Counter-clockwise rotational force applied to the implanted miniscrew can degrade the stability. The purpose of this three-dimensional finite element study was to figure out the effect of shifting the miniscrew head hole position from the long axis. Two miniscrew models were developed, one with the head hole at the long axis and the other with an eccentric hole position. One degree of counter-clockwise rotation was applied to both groups, and the maximum Von-Mises stress and moment was measured under various wire insertion angles from −60° to +60°. All Von-Mises stress and moments increased with an increase in rotational angle or wire insertion angle. The increasing slope of moment in the eccentric hole group was significantly higher than that in the centric hole group. Although the maximum Von-Mises stress was higher in the eccentric hole group, the distribution of stress was not very different from the centric hole group. As the positive wire insertion angles generated a higher moment under a counter-clockwise rotational force, it is recommended to place the head hole considering the implanting direction of the miniscrew. Clinically, multidirectional and higher forces can be applied to the miniscrew with an eccentric head hole position.
Experimental Analysis in Hadoop MapReduce: A Closer Look at Fault Detection and Recovery Techniques
Authors: Saadoon Muntadher , Hamid Siti Hafizah Ab , Sofian Hazrina , Altarturi Hamza , Nasuha Nur , Azizul Zati Hakim , Sani Asmiza Abdul , Asemi Adeleh
Published: May 2021

Hadoop MapReduce reactively detects and recovers faults after they occur based on the static heartbeat detection and the re-execution from scratch techniques. However, these techniques lead to excessive response time penalties and inefficient resource consumption during detection and recovery. Existing fault-tolerance solutions intend to mitigate the limitations without considering critical conditions such as fail-slow faults, the impact of faults at various infrastructure levels and the relationship between the detection and recovery stages. This paper analyses the response time under two main conditions: fail-stop and fail-slow, when they manifest with node, service, and the task at runtime. In addition, we focus on the relationship between the time for detecting and recovering faults. The experimental analysis is conducted on a real Hadoop cluster comprising MapReduce, YARN and HDFS frameworks. Our analysis shows that the recovery of a single fault leads to an average of 67.6% response time penalty. Even though the detection and recovery times are well-turned, data locality and resource availability must also be considered to obtain the optimum tolerance time and the lowest penalties.
LTCC-Integrated Dielectric Resonant Antenna Array for 5G Applications
Authors: Niayesh Mohsen , Kouki Ammar
Published: May 2021

A millimeter-wave dielectric resonator antenna array with an integrated feeding network and a novel alignment superstrate in Low Temperature Cofired Ceramics (LTCC) technology is presented. The antenna array consists of 16 cylindrical DR antenna (CDRA) elements operating at 28 GHz for mm-Wave 5G applications. The array is fed by an inverted microstrip corporate feeding network designed and built in the same LTCC stack as the resonators. A grooved and grounded superstrate is introduced to facilitate the alignment of the individual array elements while enhancing the overall performance of the antenna array. The performance of the proposed stack is evaluated numerically and compared with measured data. Measured results show an impedance bandwidth of 9.81% at 28.72 GHz with a maximum realized gain of 15.68 dBi and an efficiency of 88%, and are in excellent agreement with simulations.
Design and Evaluation of Korean Electropalatography (K-EPG)
Authors: Woo Seong-Tak , Ha Ji-Wan , Na Sungdae , Choi Hyunjoo , Pyun Sung-Bom
Published: May 2021

Recently, the development of medical rehabilitation technology has resulted in an increased interest in speech therapy equipment. In particular, research on articulation therapy for communication disorders is being actively conducted. The existing methods for the diagnosis and treatment of speech disorders, such as traditional tactile perception tests and methods based on the empirical judgment of speech therapists, have many limitations. Moreover, the position and contact force of the tongue are key factors in speech disorders with regards to articulation. This is a very important factor in the distinction of Korean characters such as lax, tense and aspirated consonants. In this study, we proposed a Korean-electropalatography (EPG) system to easily measure and monitor the position and contact force of the tongue during articulation treatment and diagnosis. In our proposed K-EPG system, a sensor was fabricated using an AgCl electrode and biocompatible silicon. Furthermore, the measured signal was analyzed by implementing a bio-signal processing module and monitoring program. In particular, the bio-signal was measured by inserting the device into the palate of an experimental healthy test group (four subjects). Through these experiments, we confirmed that our K-EPG system could be applied to clinical treatment in speech therapy.
Heterologous Biosynthesis of Artemisinin in Chrysanthemum morifolium Ramat
Authors: Firsov Aleksey , Pushin Alexander , Motyleva Svetlana , Pigoleva Svetlana , Shaloiko Lyubov , Vainstein Alexander , Dolgov Sergey
Published: May 2021

Artemisinin-based drugs are the most effective medicine against multidrug-resistant Plasmodium spp., the parasite that causes malaria. To this day, wormwood A. annua L. is the sole commercial source of artemisinin, where it is produced in minor amounts. The artemisinin yield depends on numerous poorly regulated agricultural factors and the genetic variability of this non-domesticated plant. This has aroused significant interest in the development of heterologous expression platforms for artemisinin production. Previously, we obtained lines of Chrysanthemum morifolium Ramat. (C. morifolium Ramat.), cvs. White Snowdon and Egyptianka, transformed with artemisinin biosynthesis genes. Here, we report the results of an analysis of artemisinin production in transgenic chrysanthemums. Transcription of heterologous amorpha-4,11-diene monooxygenase and cytochrome P450 reductase genes in transgenic lines was confirmed using high-resolution melting analysis. Artemisinin accumulation was detected using GC-MS in White Snowdon plants, but not in Egyptianka ones, thereby demonstrating the possibility of transplanting active artemisinin biosynthetic pathway into chrysanthemum. Ways of increasing its content in producer plants are discussed.
Impact of Industry 4.0 on Corporate Financial Performance: A Moderated Mediation Model
Authors: Chen Hong-Long
Published: May 2021

Many studies advance the contemporary technologies of Industry 4.0. However, relatively little is known about how Industry 4.0 affects corporate financial performance. Using a survey, bootstrap sampling, and structural-equation modeling, this study evaluates the moderated mediation effects of Industry 4.0 maturity on financial performance. The results show that Industry 4.0 maturity significantly affects internal business process performance (IBPP), which influences customer performance through the mediating effect of supply chain performance (SCP), and IBPP and SCP affect financial performance fully through the mediating effect of customer performance. The results also show that Industry 4.0 maturity moderates the positive relationship between customer performance and financial performance. Customer performance and IBPP have the largest direct and total effects on financial performance in the context of Industry 4.0 implementation, respectively. The results indicate that Industry 4.0 magnifies the potential returns to companies mainly through IBPP, SCP, and customer performance. This study offers an enhanced understanding of the financial implications of Industry 4.0 implementation and provides insights into the factors through which Industry 4.0 maturity influences financial performance.
How Do We Manage a Just Transition? A Comparative Review of National and Regional Just Transition Initiatives
Authors: Krawchenko Tamara Antonia , Gordon Megan
Published: May 2021

The concept of a ‘just transition’ encompasses political and policy imperatives to minimize the harmful impacts of industrial and economic transitions on workers, communities, and society more generally, and to maximize their potential benefits. This imperative has gained heightened importance as governments commit to reducing greenhouse gas emissions. A wide range of policies, strategies and initiatives have been adopted by national and regional governments to facilitate and help manage a just transition. It is a concept that is increasingly being put into practice. This scoping study identifies and compares strategies, policies, and practices that are presently being implemented in order to manage a just transition across 25 countries and 74 regions alongside European Union-level policies. This work develops a typology of policy instruments to manage just transitions and identifies implementation gaps and leading practices.
No Tradeoff in Fiber Quality with Increased Cotton Yield Due to Outcross Pollination
Authors: Cusser Sarah , Jha Shalene
Published: May 2021

The societal and economic benefits of ecosystem services are both immense and multi-faceted. To holistically quantify the contribution of pollinators to agriculture requires measuring multiple indices of crop production beyond crop yield. Here, we conduct a field-based hand pollination experiment to measure the effects of self and outcross pollen on fiber yield and quality in conventionally managed cotton crops. First, we determine how different pollination treatments affect specific indices of fiber yield and fiber quality, including fiber length and fineness. Second, we investigate the suggested tradeoff between fiber yield and quality. We find that flowers receiving outcross pollen produce larger, heavier bolls than either self-crossed or non-crossed flowers. However, contrary to expectation, flowers of different treatments are indistinguishable in terms of fiber quality. Overall, we find that pollination treatment has no discernable effect on either fiber length or fiber fineness. Understanding the contribution of ecosystem services across multiple axes provides growers with information concerning potential tradeoffs or synergies, and offers insight into management decisions.
Improving Energy Efficiency of Barley Production Using Joint Data Envelopment Analysis (DEA) and Life Cycle Assessment (LCA): Evaluation of Greenhouse Gas Emissions and Optimization Approach
Authors: Payandeh Zahra , Jahanbakhshi Ahmad , Mesri-Gundoshmian Tarahom , Clark Sean
Published: May 2021

Eco-efficiency has become a cornerstone in improving the environmental and economic performance of farms. The joint use of life cycle assessment (LCA) and data envelopment analysis (DEA), known as LCA + DEA methodology, is an expanding area of research in this quest. LCA estimates the environmental impacts of the products or services, while DEA evaluates their efficiency, providing targets and benchmarks for the inefficient ones. Because energy consumption and environmental quality are highly interdependent, we carried out a study to examine energy efficiency and environmental emissions associated with rain-fed barley farms in Kermanshah Province, Iran. Fifty-four rain-fed barley farms were randomly selected, and production data were collected using questionnaires and interviews. DEA and LCA were used to quantify and compare environmental indicators before and after efficiency improvements were applied to the farms. To accomplish this, efficient and inefficient farms were identified using DEA. Then environmental emissions were measured again after inefficient farms reached the efficiency limit through management improvements. The results showed that by managing resource use, both energy consumption and environmental emissions can be reduced without yield loss. The initial amount of energy consumed averaged 13,443 MJ/ha while that consumed in the optimal state was determined to be 12,509 MJ/h, resulting in a savings of 934 MJ/ha. Based on the results of DEA, reductions in nitrogen fertilizer, diesel fuel, and phosphate fertilizer offered the greatest possibilities for energy savings. Combining DEA and LCA showed that efficient resource management could reduce emissions important to abiotic depletion (fossil fuels), human toxicity, marine aquatic ecotoxicity, global warming (GWP100a), freshwater aquatic ecotoxicity, and terrestrial ecotoxicity. This study contributes toward systematically building knowledge about crop production with the joint use of LCA + DEA for eco-efficiency assessment.
Enablers and Barriers to Online Learning among Medical Students during COVID-19 Pandemic: An Explanatory Mixed-Method Study
Authors: Roslan Nurhanis Syazni , Halim Ahmad Sukari
Published: May 2021

As the coronavirus disease 2019 (COVID-19) trajectory remains unknown, online learning (OL) has replaced face-to-face teaching strategies in education institutions. Research and training focus on harnessing educators, but less is understood at the students’ ends. This study examines the OL readiness components, self-regulation, enablers, and barriers to OL at home among medical students during the COVID-19 pandemic through an explanatory mixed-method study. We conducted a cross-sectional study with 178 students and an in-depth interview with 10 students from a public medical school in Malaysia. We found that while all students owned at least one learning device, 22.5% of the students did not have a learning space at home. 21.9% students did not have Wi-Fi access, and 11.2% did not receive mobile broadband coverage at home. Despite these barriers, students had a suitable OL self-regulation level. Significantly higher self-regulation was observed among pre-clinical year students, students with higher grades, and students who had designated learning space at home. We found that high-immediacy and low-bandwidth applications such as WhatsApp and Telegram, and YouTube as the most accessible and easiest platforms to navigate in OL. Our qualitative findings yielded a conceptual model of OL enablers at learners, educators, and institution levels. This framework may serve as one of the guides in faculty development planning and policymaking, especially in promoting a more socially inclusive OL.
Utilisation of Recycled Silt from Water Treatment and Palm Oil Fuel Ash as Geopolymer Artificial Lightweight Aggregate
Authors: Kwek Shi Ying , Awang Hanizam
Published: May 2021

The global consumption of aggregate in the construction field is increasing annually, especially in concrete production. With the development of the economy and increase of the population, the demand for concrete and, therefore, a huge amount of aggregate has increased significantly. This issue is pressing and needs to be addressed. Lightweight aggregate (LWA) is one possible solution. This study investigated the potential use of artificial LWA manufactured from alkaline-activated palm oil fuel ash (POFA) with silt due to its properties and performances. Six mixes containing up to 60% silt by total weight combined with optimised activated POFA were analysed. The artificial LWA was synthesised through a pelletising and sintering process at 1150 °C. The increase in the activated POFA proportion in the mixture induced changes in the properties of artificial LWA, including the physical and mechanical properties, durability, and microstructure. The analytical results showed that all of the artificial aggregates were categorised as LWA, based on BS EN 13055. The artificial LWA with 40% activated POFA and 60% silt had the highest crushing strength and acceptable properties for construction applications. This study summarised the performances of the final products and highlighted the different uses of imported silt and POFA as building materials for minimising environmental impacts.
G-Donic Happiness: An Alternative to Hedonic and Eudemonic Happiness for Sustainable Consumption
Authors: Aydin Necati , Khan Hayat
Published: May 2021

This paper provides a spiritual perspective on happiness referred to as the G-donic approach to happiness which is fundamentally different from the hedonic and eudemonic approaches. The G-donic approach identifies the importance of the spiritual self and argues that it embodies the technology that converts physical resources into happiness. We argue that with G-donic preferences, it is possible to achieve a higher level of happiness with moderate consumption. The G-donic approach encourages living a virtuous life by fulfilling the biological, social, emotional, intellectual, moral, and spiritual needs in a balanced manner. It urges spiritual people to go beyond phenomenal reality to perceive transcendental reality in pursuit of authentic happiness. We use a multi-dimensional human nature model to highlight the relevance and importance of this approach, and modify standard utility models to show how it might result in higher happiness with lower consumption and compare and contrast it with outcomes under hedonic and eudemonic approaches to happiness. The G-donic approach contends that resources and spirituality are substitutes, as well as complements and that a reasonable approach to happiness should seek an optimal mix of both. Unlike popular convention, this deviation from hedonic pleasure due to lower consumption does not result in lower happiness. In fact, we show that, theoretically, it results in an overall increase in happiness as any loss in hedonic is compensated by greater eudemonic and G-donic rewards which increases utility.
Effect of Seedling Provenance and Site Heterogeneity on Abies cephalonica Performance in a Post-Fire Environment
Authors: Ioannidis Kostas , Tsakaldimi Marianthi , Koutsovoulou Katerina , Daskalakou Evangelia N. , Ganatsas Petros
Published: May 2021

Reforestation constitutes a challenge in post-fire ecosystem restoration, although there are limitations such as species and genotype selection, planting and management design, and environmental conditions. In the present study, the basic issue is the longevity of Abies cephalonica Loudon—the Greek fir seedlings planted extensively in Parnitha National Park (Central Greece), located near the metropolitan city of Athens, following the large-scale wildfire of 2007. Seedling performance was assessed for a 3-year monitoring period (2013–2015) through the establishment of 8 permanent transects, including 400 seedlings at the burned, reforested sites. According to the long-term reforestation project, two seedling provenances were used: (a) from Mt. Mainalon (South Greece, Vytina provenance) and (b) the local one from Mt. Parnitha. Both provenances showed a relatively successful survival rate reaching, in average, 73.8%, with the first summer after planting being crucial for seedling survival. The overall mean seedling height was 39.2 ± 1.1 cm, with a mean crown diameter of 47.3 ± 1.4 cm in the last monitoring survey. Although Parnitha seedlings seem to perform better in terms of growth, seedling performance in both provenances was affected by reforestation site characteristics, mainly altitude and aspect. Approximately one third of seedlings exhibited damage in their crown architecture (29.8%), while apical bud damage was less extensive (12.2%) in the final field measurement. Data indicate that seedling performance has proved to be quite promising for post-fire restoration, although long-term monitoring data should be considered.
A Planning Tool for Reliability Assessment of Overhead Distribution Lines in Hybrid AC/DC Grids
Authors: Adinolfi Giovanna , Ciavarella Roberto , Graditi Giorgio , Ricca Antonio , Valenti Maria
Published: May 2021

Integration of DC grids into AC networks will realize hybrid AC/DC grids, a new energetic paradigm which will become widespread in the future due to the increasing availability of DC-based generators, loads and storage systems. Furthermore, the huge connection of intermittent renewable sources to distribution grids could cause security and congestion issues affecting line behaviour and reliability performance. This paper aims to propose a planning tool for congestion forecasting and reliability assessment of overhead distribution lines. The tool inputs consist of a single line diagram of a real or synthetic grid and a set of 24-h forecasting time series concerning climatic conditions and grid resource operative profiles. The developed approach aims to avoid congestions criticalities, taking advantage of optimal active power dispatching among “congestion-nearby resources”. A case study is analysed to validate the implemented control strategy considering a modified IEEE 14-Bus System with introduction of renewables. The tool also implements reliability prediction formulas to calculate an overhead line reliability function in congested and congestions-avoided conditions. A quantitative evaluation underlines the reliability performance achievable after the congestion strategy action.
Sustainability and Politics: Explaining the Emergence of the 2020 Budapest Climate Assembly
Authors: Oross Daniel , Mátyás Eszter , Gherghina Sergiu
Published: May 2021

The relationship between political participation and the pursuit of sustainability at the local level has been investigated extensively in the literature. In this content, the emergence and extensive use of citizens’ assemblies receive particular attention. Much research focuses on the functioning of these assemblies and potential impact in the community. However, we know very little about why such initiatives occur. This article fills that gap in the literature and aims to explain why a citizens’ assembly on climate change was organized. It focuses on the Citizens’ Assembly in Budapest (Hungary), organized in the fall of 2020 with randomly selected citizens. The findings illustrate that although civil society initiated the deliberative process, the prime mover of the Citizens’ Assembly was political. Local politicians pursued this objective to fulfil their election pledges, ensure ideological consistency and promote sustainability.
A Crash Prediction Method Based on Artificial Intelligence Techniques and Driving Behavior Event Data
Authors: Kim Yunjong , Park Juneyoung , Oh Cheol
Published: May 2021

Various studies on how to prevent and deal with traffic accidents are ongoing. In the past, the key research emphasis was on passive accident response measures that analyzed roadway-based historical data to identify road sections with high crash risk. Through assessing crash risks by analyzing simulation data and actual vehicle driving trajectory data, this study suggests a method of effectively preventing accidents before they happen. In this analysis, using digital tachograph (DTG) data, which is the vehicle trajectory data for commercial vehicles running on Korean highways, hazardous and normal traffic flows were identified and extracted. Driving behavior event data for both types of traffic flow was processed by measuring safety indicators through the extracted data. Safety indicators with a high impact on traffic flow classification were then extracted using gradient boosting, a representative ensemble technique. A neural network analysis was performed using the extracted safety indicators as independent variables to create a traffic flow classifier, which had a high accuracy of 94.59%. The DTG data set was also classified based on the severity of each accident that occurred in the studied roadway, the time of the accident, and the weather; the results were compiled to enable comprehensive accident prediction. It is expected that proactive crash prevention will be possible in the future by evaluating real-time accident risks using the findings and ensemble-based methodologies of this paper.
The Impacts of Design Heuristics on Concept Generation for a COVID-19 Brief
Authors: Jin Xiaoneng , Dong Hua , Evans Mark
Published: May 2021

Design heuristics (DHS) as a tool can help boost designers’ creativity in early conceptual design phases. We have developed a set of DHS for digital innovation (DHS10). There are numerous studies on DHS impacts/outcomes in the recent years. However, little research has been conducted to identify whether DHS has lasting benefits on designers’ ideation performance. This paper explores whether DHS10 can help designers achieve more creative ideas based on different design briefs, and if DHS has lasting impacts on or benefits for students. An empirical study was conducted with two groups (i.e., 32 students who learned DHS10 five weeks ago, and 24 students who studied DHS10 instantly). They were asked to address an open-ended design brief on COVID-19 and generate as many innovative ideas as possible. The results suggest DHS has impacts on students who learned DHS just now and five weeks ago. The effect is stronger on those who just learned DHS10. We suggest that DHS10 be provided for ideation as it provides texts and visual stimuli for designers. DHS10 also has the potential to help students understand digital innovation and generate ideas accordingly.