bluuebunny/crossref_metadata_2025 huggingface dataset:
Polypropylene Pipe Compounds with Varying Post-Consumer Packaging Recyclate Content
Authors: Freudenthaler Paul J. , Fischer Joerg , Liu Yi , Lang Reinhold W.
Published: December 2022

The high recycling targets set by the European Commission will create an increased availability of polypropylene (PP) post-consumer recyclates (PCRs). However, no regulations mandate the use of recycled PP (rPP), so the industry is challenged to explore possibilities to utilize such materials. One option, as suggested by the European Commission, is the introduction of rPP in pipe applications. According to existing standards, the use of recyclate is not allowed in pressurized gas and drinking water systems. However, many other pipe and underground applications, such as stormwater systems, open the increased use of PCRs. Additionally, even for less-demanding applications, such as non-pressure sewage systems, highly durable solutions are needed to cover the requested lifetime and request an ambitious property profile to fulfill the application needs that cannot be met by PP packaging materials and even less by PCRs thereof. Hence, this work explores the possible use of commercially available PCRs out of polypropylene from packaging applications in compounds together with virgin PP pipe grades to meet the demands for less-demanding applications. Two different commercially available rPPs and one commercially available recycled polyolefin (rPO) from mixed polyethylene and PP waste were acquired and, together with two predefined virgin PP pipe grades, were blended to compounds in the range of 10 m%, 20 m%, and 30 m% recyclate content. The compounds and three virgin PP pipe grades, acting as benchmarks, were tested in terms of short- and long-term mechanical performance as well as for many other physical properties. All of the compounds showed good results regarding fatigue crack (FCG) resistance with virgin polymer as the reference. The factors influencing FCG resistance, such as melt flow rate and polyolefin cross-contamination, were thoroughly investigated as the used virgin grades and recyclates cover a broad range of these properties.
Study on the SPCC and CFRTP Hybrid Joint Performance Produced with Additional Nylon-6 Interlayer by Ultrasonic Plastic Welding
Authors: Wang Tai , Yasuda Kiyokazu , Nishikawa Hiroshi
Published: December 2022

Due to the high degree of dissimilarity in physicochemical properties between metal and carbon fiber, it presents a tremendous challenge to join them directly. In this paper, cold rolled steel (SPCC) and carbon fiber reinforced thermoplastic (CFRTP) chopped sheet hybrid joints were produced with the addition of Nylon 6 (PA6) thermoplastic film as an intermediate layer by the ultrasonic plastic welding method. The effect of ultrasonic welding energy and preheating temperature on the hybrid joint microstructure and mechanical behavior was well investigated. The suitable joining parameters could obtain a strong joint by adding the PA6 film as an intermediate layer between the SPCC and bare carbon fibers. Microstructural analysis revealed that the interface joining condition between the PA6 film and the SPCC component is the primary reason for the joint strength. The crevices generated at the interface were eliminated when the preheating temperature arrived at 200 °C, and the joint strength thus significantly increased. The lap shear test results under quasi-static loading showed that the welding energy and preheating temperature synergistically affect the joint performances. At 240 °C, the joint strength value reached the maximum. Through the analysis of the microstructure morphology, mechanical performance, and the failure mechanism of the joint, the optimized joining process window for ultrasonic plastic welding of SPCC-CFRTP by adding an intermediate layer, was obtained.
Modification of the Textural Properties of Chitosan to Obtain Biochars for CO2-Capture Processes
Authors: Barroso-Martín Isabel , Cecilia Juan Antonio , Vilarrasa-García Enrique , Ballesteros-Plata Daniel , Jiménez-Gómez Carmen Pilar , Vílchez-Cózar Álvaro , Infantes-Molina Antonia , Rodríguez-Castellón Enrique
Published: December 2022

Three chitosans with different morphologies have been used (commercial chitosan powder, chitosan in film form and chitosan in globular form synthesized by the freeze-dried method) for the synthesis of biochars. The pyrolytic treatment has revealed that the biochar synthesized from the chitosan formed by the freeze-dried method reaches the highest CO2-adsorption capacity (4.11 mmol/g at 0 °C and a pressure of 1 bar) due to this adsorbent is highly microporous. Moreover, this biochar is more resistant to the pyrolytic treatment in comparison to the biochars obtained from the commercial chitosan and chitosan in the form of film. CO2-adsorption studies at different temperatures have also shown that the adsorption capacity diminishes as the adsorption temperature increases, thus suggesting that the adsorption takes place by a physical process.
Hypoglycemic Effect and Experimental Validation of Scutellariae Radix based on Network Pharmacology and Molecular Docking
Authors: Liu Xiaolong , Li Chunyan , Chen Qijian , Xiao Xian , Li Manman , Xue Jintao
Published: December 2022

Scutellariae Radix (SR) is a well-known traditional herb that has good pharmacological effects against diabetes. However, the mechanism of SR against diabetes is not clear. In this study, the ingredient–target–pathway relationship and hypoglycemic effect of SR on diabetes were explored using network pharmacology, molecular docking and an animal experiment. The targets of SR and diabetes were mined. The selected targets were studied using Gene Ontology (GO) enrichment analysis and pathway enrichment analysis. The network of active components, targets and pathways was integrated to analyze the ingredient–target–pathway relationship. Then, the correspondence between the active components and targets was verified using molecular docking. Finally, an animal experiment was used to verify the hypoglycemic effect of SR. There were 52 components and 22 targets for the hypoglycemic effect of SR. We identified 18 biological processes, 9 cellular components, 15 molecular functions and 25 signaling pathways. Molecular docking results indicated that the targets of diabetes bound strongly to the main components. The animal experiments showed that SR could significantly decrease the blood glucose level of diabetic rats (p ≤ 0.05). This study explored the potential targets and signaling pathways of SR in diabetes, and the results may help to illustrate the hypoglycemic mechanism of SR.
Chemical Analysis and Quality Assessment of Honey Obtained from Different Sources
Authors: Dobrinas Simona , Soceanu Alina , Birghila Semaghiul , Birghila Corina , Matei Nicoleta , Popescu Viorica , Constanda Luminita Mihaela
Published: December 2022

The purpose of this paper was to evaluate the quality of bee honey from different sources: beekeeper, local market and organic honey. Sensory analysis was performed and the water content, pH, acidity, protein content and total metal content (Cu, Cr, Mn, Co, Ni, Pb, Cd, Fe) were determined. The sensory analysis was carried out by a group of untrained panelists for quality assessment of honey. The metal content was determined by graphite atomic absorption spectrometry (GTAAS). Mineralization was carried out in a microwave digestion system, in a high-pressure polytetrafluoroethylene (PTFE) vessel, using a standard acid-digestion protocol. The results regarding the physico-chemical parameters showed that the honey samples were in accordance with the quality regulations for honey as a commercial product. The concentration of metals in the investigated honey samples varied in the order Cu > Cr > Pb > Fe > Ni > Mn > Co > Cd, the values being within the limits established by the EU Commission (No. 1881/2006). The variations observed in the evaluated parameters can be caused by the difference in plant species from which the honey comes, the harvesting period and the level of environmental pollutants. The Pearson correlations between the physico-chemical parameters and the metals indicate that water content (wc) is strongly negatively correlated with Cd and Ni, while pH is strongly positively correlated with Mn and Fe. Moreover, EC is strongly negatively correlated with Ni and Fe, and the Brix degrees are strongly positively correlated with Cd and Ni. Statistically significant positive correlation was found between Brix–Cd, Ni–Cd and Cu–Cr and a statistically significant negative correlation was detected between wc and Cd.
Transformational Dialogue and Christian Identity in a Multi-Religious Context: Nigeria in Focus
Authors: Okpaleke Ikenna Paschal
Published: December 2022

Dialogue within a multi-religious context presupposes the recognition of the many identities that are involved in mutual encounter and exchange. The understanding, shape or interpretation of each identity plays a critical role in the nature of the dialogical process as well as the outcome of the dialogue itself. This article re-assesses the Christian identity in the dialogue between Christians and Muslims, with a focus on how this plays out in the Nigerian context. It explores how a distinctive African worldview can shape the Christian identity towards an increased relationality, solidarity, and interdependence. Furthermore, the article critically investigates fundamentalist tendencies within Nigerian Christianity, and finally addresses how ‘a personalist approach’ could foster better intra- and inter-religious encounters in Nigeria in a manner that preserves identity while remaining open towards the other (Christian or religious).
Human Maternal-Fetal Interface Cellular Models to Assess Antiviral Drug Toxicity during Pregnancy
Authors: Herbek Savannah L. , Smithgall Marie C. , Murphy Elisabeth A. , Schwartz Robert E. , Chen Shuibing , Riley Laura E. , Stuhlmann Heidi , Yang Yawei J. , Goswami Ria
Published: December 2022

Pregnancy is a period of elevated risk for viral disease severity, resulting in serious health consequences for both the mother and the fetus; yet antiviral drugs lack comprehensive safety and efficacy data for use among pregnant women. In fact, pregnant women are systematically excluded from therapeutic clinical trials to prevent potential fetal harm. Current FDA-recommended reproductive toxicity assessments are studied using small animals which often do not accurately predict the human toxicological profiles of drug candidates. Here, we review the potential of human maternal-fetal interface cellular models in reproductive toxicity assessment of antiviral drugs. We specifically focus on the 2- and 3-dimensional maternal placental models of different gestational stages and those of fetal embryogenesis and organ development. Screening of drug candidates in physiologically relevant human maternal-fetal cellular models will be beneficial to prioritize selection of safe antiviral therapeutics for clinical trials in pregnant women.
The 8 January 2022, Menyuan Earthquake in Qinghai, China: A Representative Event in the Qilian-Haiyuan Fault Zone Observed Using Sentinel-1 SAR Images
Authors: Zhu Liangyu , Ji Lingyun , Liu Chuanjin , Xu Jing , Liu Xinkai , Liu Lei , Zhao Qiang
Published: December 2022

On 8 January 2022, a Ms 6.9 earthquake occurred in Menyuan, Qinghai, China. This event provided important geodetic data before and after the earthquake, facilitating the investigation of the slip balance along the seismogenic faults to understand seismogenic behavior and assess seismic risk. In this study, we obtained the interseismic (2016–2021) and coseismic deformation fields of the 2022 earthquake using Sentinel-1 synthetic aperture radar (SAR) images and estimated the slip rate, fault locking, and coseismic slip of the seismogenic faults. The results indicated that the seismogenic fault of the 2022 Menyuan earthquake, i.e., the Tuolaishan–Lenglongling Fault, had shallow locked areas before the earthquake; its long-term slip rate could reach 6 ± 1.2 mm/yr. The earthquake ruptured a sinistral strike-slip fault with a high dip angle; the maximum slip magnitude reached 3.47 m, with a moment magnitude of 6.6. The area of coseismic slip > 1.5 m was equivalent to the range of the isoline, with a locking value of 0.6. The interseismic locking region can limit the approximate scope of the coseismic slip distribution. The 2022 Menyuan earthquake released energy that had accumulated over 482 years in the stepover region between the Lenglongling and Tuolaishan faults. The accumulated elastic strain power of the Tuolaishan Fault was equivalent to an Mw 6.79 earthquake. These circumstances in terms of the strain energy balance demonstrate that interseismic locking, as constrained from the geodetic data, and the elapsed time from the previous paleoseismic event are useful for earthquake location and energy predictions.
Spatiotemporal Land Use/Land Cover Mapping and Prediction Based on Hybrid Modeling Approach: A Case Study of Kano Metropolis, Nigeria (2020–2050)
Authors: Koko Auwalu Faisal , Han Zexu , Wu Yue , Abubakar Ghali Abdullahi , Bello Muhammed
Published: December 2022

The change dynamics of land use/land cover (LULC) is a vital factor that significantly modifies the natural environment. Therefore, mapping and predicting spatiotemporal LULC transformation is crucial in effectively managing the built environment toward achieving Sustainable Development Goal 11, which seeks to make cities all-inclusive, sustainable, and reliable. The study aims to examine the change dynamics of LULC in Kano Metropolis, Nigeria from 1991 to 2020 and predict the city’s future land uses over the next 15 and 30 years, i.e., 2035 and 2050. The maximum likelihood algorithm (MLA) of the supervised classification method was utilized to classify the study area’s land uses using Landsat satellite data and various geographic information system (GIS) techniques. A hybrid simulation model comprising cellular automata and Markov chain (CA-Markov) was then employed in validating and modeling the change dynamics of future LULC. The model integrated the spatial continuity of the CA model with the Markov chain’s ability to address the limitations of individual models in simulating long-term land use prediction. The study revealed substantial changes in the historical LULC pattern of Kano metropolis from 1991 to 2020. It indicated a considerable decline in the city’s barren land from approximately 413.47 km2 in 1991 to 240.89 km2 in 2020. Built-up areas showed the most extensive development over the past 29 years, from about 66.16 km2 in 1991 to 218.72 km2 in 2020. This trend of rapid urban growth is expected to continue over the next three decades, with prediction results indicating the city’s built-up areas expanding to approximately 307.90 km2 in 2035 and 364.88 km2 in 2050. The result also suggests that barren lands are anticipated to decline further with the continuous sustenance of various agricultural activities, while vegetation and water bodies will slightly increase between 2020 and 2050. The findings of this study will help decision-makers and city administrators formulate sustainable land use policies for a more inclusive, safe, and resilient city.
Drought in Northern Italy: Long Earth Observation Time Series Reveal Snow Line Elevation to Be Several Hundred Meters Above Long-Term Average in 2022
Authors: Koehler Jonas , Dietz Andreas J. , Zellner Peter , Baumhoer Celia A. , Dirscherl Mariel , Cattani Luca , Vlahović Živa , Alasawedah Mohammad Hussein , Mayer Konrad , Haslinger Klaus , Bertoldi Giacomo , Jacob Alexander , Kuenzer Claudia
Published: December 2022

The hydrological drought in Northern Italy in 2022 was, in large part, the consequence of a snow drought in the Italian Alps in the winter of 2021/22 and the resulting deficit of melt water runoff. In this communication, we assessed the snow-cover dynamics in nine Alpine Italian catchments using long time series of satellite-derived snow line elevation (SLE) measurements. We compared the SLE of the hydrological year 2021/22 to the long-term dynamics of 1985–2021. In early 2022, the SLE was located several hundred meters above the expected median values in all of the nine catchments. This resulted in deficits of snow-covered area of up to 83% in the Western Alps (catchment of Sesia, March 2022) and up to 61% in the Eastern Alps (Brenta, March 2022) compared to the long-term median. Although snow-cover data from optical satellite imagery do not contain information about snow depth and water content, in a preliminary qualitative analysis, the derived SLE dynamics show good agreement with the Standardized Snowpack Index (SSPI) which is based on the snow water equivalent (SWE). While the exact relationships between SLE, SWE, and runoff have to be explored further on the catchment basis, long-time series of SLE may have potential for use in drought early warning systems.
A Tiny Model for Fast and Precise Ship Detection via Feature Channel Pruning
Authors: Yang Yana , Xiao Shuai , Yang Jiachen , Cheng Chen
Published: December 2022

It is of great significance to accurately detect ships on the ocean. To obtain higher detection performance, many researchers use deep learning to identify ships from images instead of traditional detection methods. Nevertheless, the marine environment is relatively complex, making it quite difficult to determine features of ship targets. In addition, many detection models contain a large amount of parameters, which is not suitable to deploy in devices with limited computing resources. The two problems restrict the application of ship detection. In this paper, firstly, an SAR ship detection dataset is built based on several databases, solving the problem of a small number of ship samples. Then, we integrate the SPP, ASFF, and DIOU-NMS module into original YOLOv3 to improve the ship detection performance. SPP and ASFF help enrich semantic information of ship targets. DIOU-NMS can lower the false alarm. The improved YOLOv3 has 93.37% mAP, 4.11% higher than YOLOv3 on the self-built dataset. Then, we use the MCP method to compress the improved YOLOv3. Under the pruning ratio of 80%, the obtained compressed model has only 6.7 M parameters. Experiments show that MCP outperforms NS and ThiNet. With the size of 26.8 MB, the compact model can run at 15 FPS on an NVIDIA TX2 embedded development board, 4.3 times faster than the baseline model. Our work will contribute to the development and application of ship detection on the sea.
QoS-Aware Joint Task Scheduling and Resource Allocation in Vehicular Edge Computing
Authors: Cao Chenhong , Su Meijia , Duan Shengyu , Dai Miaoling , Li Jiangtao , Li Yufeng
Published: December 2022

Vehicular edge computing (VEC) has emerged in the Internet of Vehicles (IoV) as a new paradigm that offloads computation tasks to Road Side Units (RSU), aiming to thereby reduce the processing delay and resource consumption of vehicles. Ideal computation offloading policies for VEC are expected to achieve both low latency and low energy consumption. Although existing works have made great contributions, they rarely consider the coordination of multiple RSUs and the individual Quality of Service (QoS) requirements of different applications, resulting in suboptimal offloading policies. In this paper we present FEVEC, a Fast and Energy-efficient VEC framework, with the objective of realizing an optimal offloading strategy that minimizes both delay and energy consumption. FEVEC coordinates multiple RSUs and considers the application-specific QoS requirements. We formalize the computation offloading problem as a multi-objective optimization problem by jointly optimizing offloading decisions and resource allocation, which is a mixed-integer nonlinear programming (MINLP) problem and NP-hard. We propose MOV, a Multi-Objective computing offloading method for VEC. First, vehicle prejudgment is proposed to meet the requirements of different applications by considering the maximum tolerance delay related to the current vehicle speed. Second, an improved Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to obtain the Pareto-optimal solutions with low complexity. Finally, the optimal offloading strategy is selected for QoS maximization. Extensive evaluation results based on real and simulated vehicle trajectories verify that the average QoS value of MOV is improved by 20% compared with the state-of-the-art VEC mechanism.
Acoustic Sensing Based on Online Handwritten Signature Verification
Authors: Chen Mengqi , Lin Jiawei , Zou Yongpan , Wu Kaishun
Published: December 2022

Handwritten signatures are widely used for identity authorization. However, verifying handwritten signatures is cumbersome in practice due to the dependency on extra drawing tools such as a digitizer, and because the false acceptance of a forged signature can cause damage to property. Therefore, exploring a way to balance the security and user experiment of handwritten signatures is critical. In this paper, we propose a handheld signature verification scheme called SilentSign, which leverages acoustic sensors (i.e., microphone and speaker) in mobile devices. Compared to the previous online signature verification system, it provides handy and safe paper-based signature verification services. The prime notion is to utilize the acoustic signals that are bounced back via a pen tip to depict a user’s signing pattern. We designed the signal modulation stratagem carefully to guarantee high performance, developed a distance measurement algorithm based on phase shift, and trained a verification model. In comparison with the traditional signature verification scheme, SilentSign allows users to sign more conveniently as well as invisibly. To evaluate SilentSign in various settings, we conducted comprehensive experiments with 35 participants. Our results reveal that SilentSign can attain 98.2% AUC and 1.25% EER. We note that a shorter conference version of this paper was presented in Percom (2019). Our initial conference paper did not finish the complete experiment. This manuscript has been revised and provided additional experiments to the conference proceedings; for example, by including System Robustness, Computational Overhead, etc.
Wearable Soft Microtube Sensors for Quantitative Home-Based Erectile Dysfunction Monitoring
Authors: Sng Chee Ming Noel , Wee Li Min Camillus , Tang Kum Cheong , Lee King Chien Joe , Wu Qing Hui , Yeo Joo Chuan , Bhagat Ali Asgar S.
Published: December 2022

Quantifiable erectile dysfunction (ED) diagnosis involves the monitoring of rigidity and tumescence of the penile shaft during nocturnal penile tumescence (NPT). In this work, we introduce Erectile Dysfunction SENsor (EDSEN), a home-based wearable device for quantitative penile health monitoring based on stretchable microtubular sensing technology. Two types of sensors, the T- and R-sensors, are developed to effectively measure penile tumescence and rigidity, respectively. Conical models mimicking penile shaft were fabricated with polydimethylsiloxane (PDMS) material, using different base to curing agent ratios to replicate the different hardness properties of a penile shaft. A theoretical buckling force chart for the different penile models is generated to determine sufficiency criteria for sexual intercourse. An average erect penile length and circumference requires at least a Young’s modulus of 179 kPa for optimal buckling force required for satisfactory sexual intercourse. The conical penile models were evaluated using EDSEN. Our results verified that the circumference of a penile shaft can be accurately measured by T-sensor and rigidity using the R-sensor. EDSEN provides a private and quantitative method to detect ED within the comfortable confines of the user’s home.
Evaluation of Dynamic Spinal Morphology and Core Muscle Activation in Cyclists—A Comparison between Standing Posture and on the Bicycle
Authors: Muyor José M. , Antequera-Vique José A. , Oliva-Lozano José M. , Arrabal-Campos Francisco M.
Published: December 2022

(1) Background: Cycling is characterized by a sustained sitting posture on the bicycle, where physiologic spinal curvatures are modified from standing to cycling. Therefore, the main objective was to evaluate and compare the morphology of the spine and the core muscle activity in standing posture and cycling at low intensity. (2) Methods: Twelve competitive cyclists participated in the study. Spinal morphology was evaluated using an infrared-camera system. Muscle activation was recorded using a surface electromyography device. (3) Conclusions: The lumbar spine changes its morphology from lordosis in standing to kyphosis (lumbar flexion) when pedaling on the bicycle. The sacral tilt significantly increases its anterior tilt when cycling compared to when standing. The spinal morphology and sacral tilt are dynamic depending on the pedal’s position during the pedal stroke quadrants. The infraspinatus, latissimus dorsi, external oblique, and pectoralis major showed significantly higher activation pedaling than when standing, although with very low values.
Ambulation Mode Classification of Individuals with Transfemoral Amputation through A-Mode Sonomyography and Convolutional Neural Networks
Authors: Murray Rosemarie , Mendez Joel , Gabert Lukas , Fey Nicholas P. , Liu Honghai , Lenzi Tommaso
Published: December 2022

Many people struggle with mobility impairments due to lower limb amputations. To participate in society, they need to be able to walk on a wide variety of terrains, such as stairs, ramps, and level ground. Current lower limb powered prostheses require different control strategies for varying ambulation modes, and use data from mechanical sensors within the prosthesis to determine which ambulation mode the user is in. However, it can be challenging to distinguish between ambulation modes. Efforts have been made to improve classification accuracy by adding electromyography information, but this requires a large number of sensors, has a low signal-to-noise ratio, and cannot distinguish between superficial and deep muscle activations. An alternative sensing modality, A-mode ultrasound, can detect and distinguish between changes in superficial and deep muscles. It has also shown promising results in upper limb gesture classification. Despite these advantages, A-mode ultrasound has yet to be employed for lower limb activity classification. Here we show that A- mode ultrasound can classify ambulation mode with comparable, and in some cases, superior accuracy to mechanical sensing. In this study, seven transfemoral amputee subjects walked on an ambulation circuit while wearing A-mode ultrasound transducers, IMU sensors, and their passive prosthesis. The circuit consisted of sitting, standing, level-ground walking, ramp ascent, ramp descent, stair ascent, and stair descent, and a spatial–temporal convolutional network was trained to continuously classify these seven activities. Offline continuous classification with A-mode ultrasound alone was able to achieve an accuracy of 91.8±3.4%, compared with 93.8±3.0%, when using kinematic data alone. Combined kinematic and ultrasound produced 95.8±2.3% accuracy. This suggests that A-mode ultrasound provides additional useful information about the user’s gait beyond what is provided by mechanical sensors, and that it may be able to improve ambulation mode classification. By incorporating these sensors into powered prostheses, users may enjoy higher reliability for their prostheses, and more seamless transitions between ambulation modes.
Non-Standard Electrode Placement Strategies for ECG Signal Acquisition
Authors: Metshein Margus , Krivošei Andrei , Abdullayev Anar , Annus Paul , Märtens Olev
Published: December 2022

Background: Wearable technologies for monitoring cardiovascular parameters, including electrocardiography (ECG) and impedance cardiography (ICG), propose a challenging research subject. The expectancy for wearable devices to be unobtrusive and miniaturized sets a goal to develop smarter devices and better methods for signal acquisition, processing, and decision-making. Methods: In this work, non-standard electrode placement configurations (EPC) on the thoracic area and single arm were experimented for ECG signal acquisition. The locations were selected for joint acquisition of ECG and ICG, targeted to suitability for integrating into wearable devices. The methodology for comparing the detected signals of ECG was developed, presented, and applied to determine the R, S, and T waves and RR interval. An algorithm was proposed to distinguish the R waves in the case of large T waves. Results: Results show the feasibility of using non-standard EPCs, manifesting in recognizable signal waveforms with reasonable quality for post-processing. A considerably lower median sensitivity of R wave was verified (27.3%) compared with T wave (49%) and S wave (44.9%) throughout the used data. The proposed algorithm for distinguishing R wave from large T wave shows satisfactory results. Conclusions: The most suitable non-standard locations for ECG monitoring in conjunction with ICG were determined and proposed.
Effect of Autonomous Vehicles on Fatigue Life of Orthotropic Steel Decks
Authors: Zou Shengquan , Han Dayong , Wang Wei , Cao Ran
Published: December 2022

The fatigue life of orthotropic steel decks (OSDs) is significantly affected by vehicle loads, and the local stress response of OSDs is sensitive to the transverse position of vehicle loads. However, the presence of autonomous vehicles is likely to change the transverse distribution of vehicles within the lane, thereby affecting vehicle-induced fatigue damage to OSDs. Therefore, it is necessary to evaluate the potential effect of autonomous vehicles on the fatigue life of OSDs so that appropriate strategies can be implemented to control the transverse positions of autonomous vehicles passing the bridge deck. To this end, fatigue damages of several typical fatigue details in a conventional OSD (COSD) and a lightweight composite OSD (LWCD) induced by vehicle loads were calculated based on finite element analysis, and their fatigue lives were evaluated based on Miner’s Rule, in which different transverse distribution patterns of autonomous vehicles and their proportions in the mixed traffic flow were considered. The results indicate that fatigue lives of both the COSD and the LWCD can be negatively affected by autonomous vehicles traveling across the bridge without any constraints on the transverse distribution, especially when their proportion in the mixed traffic flow exceeds 30%. Compared to the scenario without autonomous vehicles, the fatigue damage of most fatigue details in OSDs may increase by 51% to 210% in the most unfavorable case due to the presence of autonomous vehicles. Nevertheless, it is feasible to extend the fatigue life of OSDs by optimizing the transverse distribution of autonomous vehicles. Specifically, the fatigue life of most fatigue details in the COSD could be extended by more than 86% in the most favorable case when a bimodal Gaussian distribution is adopted as the transverse distribution pattern of autonomous vehicles. Moreover, both the negative and positive effects of autonomous vehicles on the fatigue life of the COSD are more significant than those of the LWCD in most cases. The results can provide references for the maintenance of OSDs under the action of autonomous vehicles.
Terahertz Time-Domain Spectroscopic Study of Tricalcium Silicate
Authors: Zhang Wentao , Chen Ya , Tian Lidan , Wang Linhao , Li Xiangyu
Published: December 2022

In this study, the terahertz (THz) spectra of C3S were obtained in the 0.4–2.3 THz frequency range using different sample preparation methods. In the spectra, a sharp absorption peak of C3S was found at 2.03 THz. Under controlled conditions, the mass ratio of C3S was the most critical factor affecting the strength of the absorption peak, and the absorption coefficient followed the Beer–Lambert law, exhibiting a linear relationship with the mass ratio of C3S. The intrinsic dielectric constants of C3S and polyethylene (PE) were calculated in accordance with the Maxwell–Garnett (MG), Bruggeman (BM), and Landau–Lifshitz–Loovenga (LLL) models, using two-phase composite samples. The results show that the LLL model had the highest accuracy.
Optical Temperature Sensor Based on Polysilicon Waveguides
Authors: Xu Xinru , Yin Yuexin , Sun Chunlei , Li Lan , Lin Hongtao , Tang Bo , Zhang Peng , Chen Changming , Zhang Daming
Published: December 2022

Traditional temperature detection has limitations in terms of sensing accuracy and response time, while chip-level photoelectric sensors based on the thermo-optic effect can improve measurement sensitivity and reduce costs. This paper presents on-chip temperature sensors based on polysilicon (p-Si) waveguides. Dual-microring resonator (MRR) and asymmetric Mach–Zehnder interferometer (AMZI) sensors are demonstrated. The experimental results show that the sensitivities of the sensors based on AMZI and MRR are 86.6 pm/K and 85.7 pm/K, respectively. The temperature sensors proposed in this paper are compatible with the complementary metal-oxide-semiconductor (CMOS) fabrication technique. Benefitting from high sensitivity and a compact footprint, these sensors show great potential in the field of photonic-electronic applications.
Crack Unet: Crack Recognition Algorithm Based on Three-Dimensional Ground Penetrating Radar Images
Authors: Tang Jiaming , Chen Chunhua , Huang Zhiyong , Zhang Xiaoning , Li Weixiong , Huang Min , Deng Linghui
Published: December 2022

Three-dimensional (3D) ground-penetrating radar is an effective method for detecting internal crack damage in pavement structures. Inefficient manual interpretation of radar images and high personnel requirements have substantially restrained the generalization of 3D ground-penetrating radar. An improved Crack Unet model based on the Unet semantic segmentation model is proposed herein for 3D ground-penetrating radar crack image processing. The experiment showed that the MPA, MioU, and accuracy of the model were improved, and it displayed better capacity in the radar image crack segmentation task than current mainstream algorithms do, such as deepLabv3, PSPNet, and Unet. In the test dataset without cracks, Crack Unet is on the same level as deepLabv3 and PSPNet, which can meet engineering requirements and display a significant improvement compared with Unet. According to the ablation experiment, the MPA and MioU of Unet configured with PMDA, MC-FS, and RS modules were larger than those of Unet configured with one or two modules. The PMDA module adopted by the Crack Unet model showed a higher MPA and MioU than the SE module and the CBAM module did, respectively. The results show that the Crack Unet model has a better segmentation ability than the current mainstream algorithms do in the task of the crack segmentation of radar images, and the performance of crack segmentation is significantly improved compared with the Unet model. The Crack Unet model has excellent engineering application value in the task of the crack segmentation of radar images.
Sensitivity Optimization of Surface Acoustic Wave Yarn Tension Sensor Based on Elastic Beam Theory
Authors: Ding Yong , Gao Lili , Lu Wenke
Published: December 2022

The measurement of yarn tension has a direct impact on the product quality and production efficiency in the textile manufacturing process, and the surface acoustic wave (SAW) yarn tension sensor is a good option for detecting the yarn tension. For SAW yarn tension sensors, sensitivity is an important indicator to assess their performance. In this paper, a new type of SAW yarn tension sensor based on a simply supported beam structure is studied to improve the sensitivity of the fixed beam SAW yarn tension sensor. The sensitivity analysis method based on elastic beam theory is proposed to illustrate the sensitivity optimization. According to the analysis results, the sensitivity of the SAW yarn tension sensor can be greatly improved by using a simply supported beam structure compared to the s fixed beam structure. Moreover, from the calibration experiment, the sensitivity of the simply supported beam SAW yarn tension sensor is 2.5 times higher than that of the fixed beam sensor.
An AVMD-DBN-ELM Model for Bearing Fault Diagnosis
Authors: Lei Xue , Lu Ningyun , Chen Chuang , Wang Cunsong
Published: December 2022

Rotating machinery often works under complex and variable working conditions; the vibration signals that are widely used for the health monitoring of rotating machinery show extremely complicated dynamic frequency characteristics. It is unlikely that a few certain frequency components are used as the representative fault signatures for all working conditions. Aiming at a general solution, this paper proposes an intelligent bearing fault diagnosis method that integrates adaptive variational mode decomposition (AVMD), mode sorting based deep belief network (DBN) and extreme learning machine (ELM). It can adaptively decompose non-stationery vibration signals into temporary frequency components and sort out a set of effective frequency components for online fault diagnosis. For online implementation, a similarity matching method is proposed, which can match the online-obtained frequency-domain fault signatures with the historical fault signatures, and the parameters of AVMD-DBN-ELM model are set to be the same as the most similar case. The proposed method can decompose vibration signals into different modes adaptively and retain effective modes, and it can learn from the idea of an attention mechanism and fuse the results according to the weight of MIV. It also can improve the timeliness of the fault diagnosis. For comprehensive verification of the proposed method, the bearing dataset from the University of Ottawa is used, and some recent methods are repeated for comparative analysis. The results can prove that our proposed method has higher reliability, higher accuracy and higher efficiency.
Seed Water Absorption, Germination, Emergence and Seedling Phenotypic Characterization of the Common Bean Landraces Differing in Seed Size and Color
Authors: Vidak Monika , Lazarević Boris , Javornik Tomislav , Šatović Zlatko , Carović-Stanko Klaudija
Published: December 2022

Common bean (Phaseolus vulgaris L.) is the most widespread legume in Croatia and its production is based on landraces of great morphological diversity. Landraces morphologically differ the most in the seed coat color and size. Because plant emergence and crop establishment represent the most sensitive stage in crop development, the aim of this study was to determine whether the seed coat color and seed size of Croatian common bean landraces affect the water absorption rate, seed germination, emergence and phenotypic characteristics of the seedlings. In this study seeds of four common bean landraces with different seed color and size, ‘Biser’ (white-colored, small-seeded), ‘Bijeli’ (white-colored, large-seeded), ‘Kornjača’ (dark-colored, small-seeded) and ‘Trešnjevac’ (dark-colored, large-seeded) were evaluated in three different experiments: (i) water uptake, (ii) seed germination and (iii) emergence and seedling phenotypic characterization. The results show that white-colored seeds have a higher absorption rate and release more electrolytes compared to dark-colored seeds of similar size (and weight). The germination results show that white-colored and smaller seeds germinate faster compared to dark-colored and large seeds. On the other hand, the white-colored landrace ‘Bijeli’ took the longest time to emerge, probably due to cell damage that occurred during the fast initial water absorption. Using multispectral imaging, chlorophyll fluorescence imaging and stomatal conductance analysis, the seedlings of the dark-colored and large-seeded landraces were found to contain more photosynthetic pigments and have higher light absorption. In contrast, seedlings of white-colored and large seeds have lower stomatal conductance and transpiration and higher photochemical efficiency (despite possible cell damage during water absorption and germination). Results suggest that dark-colored seeds could survive better under unfavorable soil conditions without absorbing water, swelling, emergence or molding than white-colored seeds. Despite all this, white-colored common bean landraces remain popular in human diets and are often grown on small-scale farms.
Complex Tasks, Delegation, and Flexibility: What Role for Engagement and Shared Leadership?
Authors: Dionísio António Luis , Dionísio Andreia , Sousa Maria José , Moreira Ana
Published: December 2022

Task complexity is one of the main factors studied by academics and is at the center of leaders’ concerns. It is related to delegation and flexibility, which are enhanced by workers’ engagement and depend on how leadership is shared. In this context, this research was carried out with the main objective of testing the serial mediating effect of engagement and shared leadership on the relationship between task complexity and flexibility and the relationship between task complexity and delegation. The sample for this study consists of 368 participants, all of whom work in organizations based in Portugal. The results indicate that task complexity is positively and significantly associated with engagement, shared leadership, flexibility, and delegation. Shared leadership has a positive and significant association with flexibility and delegation. The serial mediating effect of engagement and shared leadership on the relationship between task complexity and flexibility was confirmed. The serial mediating effect of engagement and shared leadership on the relationship between task complexity and delegation was not confirmed.
Employing Nanosafety Standards in a Nanomaterial Research Environment: Lessons Learned and Refinement Potential
Authors: Kokkinopoulos Ioannis , Karayannis Panagiotis , Saliakas Stratos , Damilos Spyridon , Koumoulos Elias P.
Published: December 2022

Extensive research is currently being conducted on nanotechnologies worldwide, and the applications of nanomaterials are continuously expanding. Given their unique intrinsic characteristics, such as their small size and increased reactivity, nanomaterials may pose an occupational, environmental or consumer hazard. Therefore, a highly important aspect of ensuring the sustainable use of nanotechnologies is the establishment of proper health and safety practices. The area of nanosafety research has produced significant outcomes the last decades, and many of these achievements have been reflected in the standardization field. In this work, a discussion of prominent nanosafety standards (ISO/TS 12901-2:2014 and ISO/TR 12885:2018) is presented, based on the barriers faced during the endeavor to apply their principles within a research context. A critical viewpoint regarding their application is presented, and gaps faced in adapting the standards to the materials and processes applied are noted. Additionally, approaches that were followed to circumvent these gaps are also highlighted as suggestions to potentially overcome these barriers in future standardization efforts.
A Machine Learning Ensemble Approach for Predicting Factors Affecting STEM Students’ Future Intention to Enroll in Chemistry-Related Courses
Authors: Ong Ardvin Kester S.
Published: December 2022

The need for chemistry-related professionals has been evident with the rise of global issues such as the pandemic and global warming. Studies have indicated how an increase in the amount of professionals should start within the classroom setting, enhancing the interest and motivation of students to pursue higher education in the related field. This study aimed to evaluate and predict factors affecting STEM students’ future intention to enroll in chemistry-related courses. Through the use of machine learning algorithms such as a random forest classifier and an artificial neural network, a total of 40,782 datasets were analyzed. Results showed that attitude toward chemistry and perceived behavioral control represent the most influential factors, followed by autonomy and affective behavior. This demonstrated that students’ interest, application in real life, and the development of knowledge and skills are key indicators that would lead to a positive future intention for pursuing the course in higher education. This is the first study that has analyzed students’ future intentions using a machine learning algorithm ensemble. The methodology and results may be applied and extended among other human factor studies worldwide. Lastly, the presented discussion and analysis may be considered by other universities for their education strategies across different countries.
SMEs’ Innovativeness and Technology Adoption as Downsizing Strategies during COVID-19: The Moderating Role of Financial Sustainability in the Tourism Industry Using Structural Equation Modelling
Authors: Shwedeh Fanar , Aburayya Ahmad , Alfaisal Raghad , Adelaja Ayotunde Adetola , Ogbolu Gbemisola , Aldhuhoori Abid , Salloum Said
Published: December 2022

This study aims to identify why firms, specifically SMEs in the hospitality and tourism industry, downsized during the recent global economic distress caused by COVID-19. This study applied a quantitative methodology by distributing online questionnaires to SME owners and managers who operate in the tourism industry of the UAE. We analysed the collected data using structural equation modelling. A total of 320 questionnaires were analysed using the PLS-SEM analytic tool. Our findings revealed that the investigated constructs, namely financial sustainability, SMEs’ innovativeness, and technology adoption predict the implementation of downsizing strategies during economic distress. However, financial sustainability failed to expedite SMEs’ innovativeness and technology adoption during this period. Therefore, the findings of this study show the impacts of financial strength, technology adoption, and innovativeness on implementing downsizing strategies, and provide suggested recommendations in light of the observed results.
University Incubator Support and Entrepreneurial Intention among Tourism Graduates: Mediating Role of Personal Attitude
Authors: Ayad Tamer , Sobaih Abu Elnasr E. , Elshaer Ibrahim A.
Published: December 2022

The Saudi Arabian government has promoted the tourism industry as a way to achieve the Kingdom’s Vision 2030 by diversifying the economy and reducing overdependence on the oil sector. To align with this, several universities in Saudi Arabia have started providing tourism education. Accordingly, several academic programs and university incubators were launched to prepare workers and entrepreneurs for the industry. This study examines the role of support given by university incubators—embedded in networking support, financial support, and training support—in enhancing entrepreneurship intention among tourism graduates. Furthermore, the study examines the mediating role of personal attitude in the aforementioned relationship. Data were collected from a sample of 750 senior students at tourism and hospitality management colleges in Saudi Arabian public universities. All of the research participants have had access to these incubators. Using structural equation modeling, the study shows that the personal attitude of graduates partially mediates the impact of networking support as a dimension of university incubator support and entrepreneurship intention. However, the personal attitude of graduates was found to fully mediate the relationships between financial and training support and entrepreneurship. Future research implications and limitations are elaborated.