bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Adhesive Systems on the Mechanical and Physical Properties of Flax Fiber Reinforced Beech Plywood
Authors: Jorda Johannes , Kain Günther , Barbu Marius-Catalin , Petutschnigg Alexander , Král Pavel
Published: September 2021

In order to improve the acceptance of broader industrial application of flax fiber reinforced beech (Fagus sylvatica L.) plywood, five different industrial applicated adhesive systems were tested. Epoxy resin, urea-formaldehyde, melamine-urea formaldehyde, isocyanate MDI prepolymer, and polyurethane displayed a divergent picture in improving the mechanical properties—modulus of elasticity, modulus of rupture, tensile strength, shear strength and screw withdrawal resistance—of flax fiber-reinforced plywood. Epoxy resin is well suited for flax fiber reinforcement, whereas urea-formaldehyde, melamine urea-formaldehyde, and isocyanate prepolymer improved modulus of elasticity, modulus of rupture, shear strength, and screw withdrawal resistance, but lowered tensile strength. Polyurethane lowered the mechanical properties of flax fiber reinforced plywood. Flax fiber reinforced epoxy resin bonded plywood exceeded glass fiber reinforced plywood in terms of shear strength, modulus of elasticity, and modulus of rupture.
Highly Stretchable Fully Biomass Autonomic Self-Healing Polyamide Elastomers and Their Foam for Selective Oil Absorption
Authors: Ranganathan Palraj , Chen Chin-Wen , Rwei Syang-Peng
Published: September 2021

Renewable polymers with self-healing ability, excellent elongation, hydrophobicity, and selective oil absorption attributes are of interest for an extensive range of applications, such as e-skin, soft robots, wearable devices, and cleaning up oil spills. Herein, two fully renewable eco-friendly polyamide (PA)-based self-healing elastomers (namely, PA36,IA, and PA36,36) were prepared by a facile and green one-pot melt polycondensation of itaconic acid (IA), PripolTM 1009, and PriamineTM 1075 monomers. The molecular structures of these PAs were analyzed by FITR, 1H NMR, and 13C NMR. The distinct structure of these PAs shows superior strain values (above 2300%) and high ambient temperature autonomous self-healing ability. Interestingly, the synthesized renewable PA36,36 showed zero water absorption values and hydrophobic properties with a contact angle of θ = 91° compared to the synthesized PA36,IA and other previously reported PAs. These excellent attributes are due to the low concentration of amide groups, the highly entangled main chains, the intermolecular diffusion, the manifold dangling chains, and the numerous reversible physical bonds within the renewable PAs. Furthermore, the hydrophobic properties may aid in the selective oil absorption of the PA36,36-based foam, for which PA36,36 foam is produced by the green supercritical carbon dioxide (scCO2) batch foaming process. The PA36,36 foam with a microporous cellular structure showed better absorption capacity and high stability in repeated use. Due to these advantages, these bio-based PAs have potential for the production of eco-friendly self-healing materials, superabsorbent foams, and other polymeric materials.
Preparation of Large Conjugated Polybenzimidazole Fluorescent Materials and Their Application in Metal Ion Detection
Authors: Cao Xi-Ying , Pang Chu-Ming , Xiao Ying , Xiao Wan-Qing , Luo Shi-He , He Jin-Ping , Wang Zhao-Yang
Published: September 2021

A new type of conjugated polybenzimidazole (CPBI) was synthesized through a simple polycondensation reaction without metal catalysis, and N-alkylation modification was carried out to solve the problems of solubility and fluorescence properties. A series of nano-microsphere polymers CPBIn with large conjugation, good solubility, and strong fluorescence has been successfully used as “turn-off” fluorescent probes for the first time. The results show that, under suitable N-alkylation conditions, the obtained CPBIn can be used as a highly sensitive and selective fluorescent probe for the detection of Cu2+ and Zn2+ at the same time, and their detection limits are both nM levels. In addition, CPBI2 can be designed as an ultra-sensitive IMPLICATION logic gate at the molecular level, cyclically detecting Cu2+. With the test paper containing CPBI2, easy and quick on-site detection can be achieved. This research provides a new idea for the brief synthesis of multifunctional materials.
Application of Magnetic Composites in Removal of Tetracycline through Adsorption and Advanced Oxidation Processes (AOPs): A Review
Authors: Fan Beibei , Tan Yi , Wang Jingxin , Zhang Bangxi , Peng Yutao , Yuan Chengpeng , Guan Chungyu , Gao Xing , Cui Shihao
Published: September 2021

Water pollution induced by the tetracycline (TC) has caused global increasing attention owing to its extensive use, environmental persistence, and potential harm for human health. Adsorption and advanced oxidation processes (AOPs) have been promising techniques for TC removal due to ideal effectiveness and efficiency. Magnetic composites (MCs) which exploit the combined advantages of nano scale, alternative sources, easy preparation, and separation from wastewater are widely used for catalysis and adsorption. Herein, we intensively reviewed the available literature in order to provide comprehensive insight into the applications and mechanisms of MCs for removal of TC by adsorption and AOPs. The synthesis methods of MCs, the TC adsorption, and removal mechanisms are fully discussed. MCs serve as efficient adsorbents and photocatalysts with superior performance of photocatalytic performance in TC degradation. In addition, the TC can be effectively decomposed by the Fenton-based and SO4•− mediated oxidation under catalysis of the reported MCs with excellent catalytic performance. Based on the existing literature, we further discuss the challenge and future perspectives in MCs-based adsorption and AOPs in removing TC.
Effects of Frying Processes on the Nutritional and Sensory Characteristics of Different Mackerel Products
Authors: Negara Bertoka Fajar Surya Perwira , Tirtawijaya Gabriel , Cho Woo-Hee , Harwanto Dicky , Sohn Jae-Hak , Kim Jin-Soo , Choi Jae-Suk
Published: September 2021

Studies have reported the impact of frying on the nutritional and sensory properties of mackerel. However, no study has reviewed this topic. This study reviewed the effects of different frying processes on the nutritional and sensory characteristics of mackerel, with and without batter, marinade, and spice. MEDLINE, Web of Science, PubMed, and ScienceDirect were used as online databases to find relevant articles. We found that the nutritional, physicochemical, and sensory properties of fried mackerel without treatment were influenced by frying methods. Deep frying affected the oxidation of lipids and degradation of proteins, while air frying increased the overall acceptance score. Frying can reduce perfluorinated compounds (PFCs), eliminate some toxins, lower the trypsin inhibitor (TI), and increase the sensory parameters of mackerel with batter, marinade, and spice treatment. The different ingredients of minced mackerel products preserved their nutritional and sensory parameters after frying. Interestingly, vacuum frying resulted in lower oxidation and maintenance of nutritional and sensory parameters of fried mackerel (with or without treatment) and minced mackerel products. Further research is needed to reveal the effectiveness of vacuum frying in maintaining the nutritional and sensory properties of fried and minced mackerel products.
Genome Attractors as Places of Evolution and Oases of Life
Authors: Kasperski Andrzej
Published: September 2021

So far, much effort has been made to understand evolution and life phenomena. However, the more we know, the more new puzzles appear. This article introduces some new approaches to understanding what drives evolution. Organism evolution has been examined using artificial neural networks and a semihomologous approach based on the sequences of cytochrome c. To realize this task, three and four-layer neural networks have been designed and then taught. It has been shown that the four-layer neural network more clearly recognizes evolutionary similarities, usually indicating greater (comparing to the three-layer network) similarities to the organisms that were used to train the neural networks. It has been noted that unified cell bioenergetics allows describing the manner in which the main engine that drives evolution works. Reasons for some diseases have been also interpreted to present considerations in a broader and more holistic view. The presented results point out that the evolution of organisms can be considered as a discontinuous process taking place mainly in genome attractors that define and stabilize organisms.
Do Everything for the Glory of God
Authors: Cleveland W. Scott
Published: September 2021

St. Paul writes, “whatever you do, do everything for the glory of God (1 Corinthians 10: 31 NABRE).” This essay employs the work of St. Thomas Aquinas and the recent philosophical work of Daniel Johnson (2020) on this command to investigate a series of questions that the command raises. What is glory? How does one properly act for glory and for the glory of another? How is it possible to do everything for the glory of God? I begin with Aquinas’ account of glory and the pursuit of glory for God’s glory and Aquinas’s answers to some of the above questions that can be drawn from his discussion in De Malo. I defend Aquinas against criticisms from Daniel Johnson and present his own interpretation of the command. I advance the discussion through adding two additional interpretations that do not rely on a controversial assumption Johnson makes. Next, I address the puzzle of how we can intend everything for the glory of God using Aquinas’s three-fold account of intention. Finally, I discuss the relation between charity and the desire for God’s glory and how regular, actual intentions of one’s actions for the glory of God increases charity.
Belief in God and Psychological Distress: Is It the Belief or Certainty of the Belief?
Authors: Magin Zachary E. , David Adam B. , Carney Lauren M. , Park Crystal L. , Gutierrez Ian A. , George Login S.
Published: September 2021

Research on the relationship between belief in God and mental health is scarce and often limited to comparing group differences in mental health across various self-reported religious identities (e.g., atheists, agnostics, believers). To advance this work, we focused on how the extent of belief in God related to three indices of psychological distress (depression, anxiety, and stress) in a sample of undergraduate students (N = 632) with a variety of religious identities. We used a model comparison approach to evaluate both linear and curvilinear relationships between belief in God and psychological distress and tested potential mediating pathways for linear relationships. The findings revealed that belief in God was negatively linearly related to depression; this relationship was fully mediated by meaning in life, feeling comforted by God, positive religious coping, positive reappraisal, and substance use coping. In contrast, belief in God was curvilinearly related to anxiety but unrelated to stress. These results suggest that both strength and certainty of the belief in God may be important in understanding religion’s relationship with psychological distress.
Daoist Cosmogony in the Kojiki 古事記 Preface
Authors: Richey Jeffrey L.
Published: September 2021

A close reading of the cosmogony found in the preface to Ō no Yasumaro 太安萬侶’s Kojiki 古事記 (Record of Ancient Matters, 712 CE) reveals the ways in which Japan’s early Nara period elites appropriated aspects of China’s Daoist traditions for their own literary, mythological, and political purposes. This debt to Daoism on the part of the oldest Shintō 神道 scripture, in turn, reveals the extent to which Daoist traditions were eclectically mined for content that early Japanese elites found useful, rather than transmitted as intact lineages. This also raises questions about whether and how “Daoism” has functioned as a systematic body of doctrines and practices, whether in China or overseas. The essay argues that Ō no Yasumaro’s appropriation of the Daoist cosmogonic repertoire is consistent with Daoist traditions as they developed during China’s Six Dynasties and Tang periods—that is, with Daoism as it existed contemporaneously with the early Nara period, when the Kojiki was compiled.
COVID-19 Pandemic and Investor Herding in International Stock Markets
Authors: Bouri Elie , Demirer Riza , Gupta Rangan , Nel Jacobus
Published: September 2021

The aim of this study is to understand the effect of the recent novel coronavirus pandemic on investor herding behavior in global stock markets. Utilizing a daily newspaper-based index of financial uncertainty associated with infectious diseases, we examine the association between pandemic-induced market uncertainty and herding behavior in a set of 49 global stock markets. More specifically, we study the pattern of cross-sectional market behavior and examine whether the pandemic-induced uncertainty drives directional similarity across the global stock markets that cannot be explained by the standard asset pricing models. Utilizing a time-varying variation of the static herding model, we first identify periods during which herding is detected. We then employ probit models to examine the possible association between pandemic-induced uncertainty and the formation of herding. Our findings show a strong association between herd formation in stock markets and COVID-19 induced market uncertainty. The herding effect of COVID-19 induced market uncertainty is particularly strong for emerging stock markets as well as European PIIGS stock markets that include some of the hardest hit economies in Europe by the pandemic. The findings establish a direct link between the recent pandemic and herd formation among market participants in global financial markets. Considering the evidence that herding behavior can drive security prices away from equilibrium values supported by fundamentals and further contribute to price fluctuations in financial markets, our findings have significant implications for policy makers and investors in their efforts to monitor investor sentiment and mitigate mis-valuations that might occur as a result. Furthermore, the evidence on the behavioral pattern of stock investors in relation to infectious diseases uncertainty can be useful in studying price discovery in stock markets and might help market participants in forming hedging strategies to mitigate downside risk in their investment portfolios.
Reinforcement Learning for Pick and Place Operations in Robotics: A Survey
Authors: Lobbezoo Andrew , Qian Yanjun , Kwon Hyock-Ju
Published: September 2021

The field of robotics has been rapidly developing in recent years, and the work related to training robotic agents with reinforcement learning has been a major focus of research. This survey reviews the application of reinforcement learning for pick-and-place operations, a task that a logistics robot can be trained to complete without support from a robotics engineer. To introduce this topic, we first review the fundamentals of reinforcement learning and various methods of policy optimization, such as value iteration and policy search. Next, factors which have an impact on the pick-and-place task, such as reward shaping, imitation learning, pose estimation, and simulation environment are examined. Following the review of the fundamentals and key factors for reinforcement learning, we present an extensive review of all methods implemented by researchers in the field to date. The strengths and weaknesses of each method from literature are discussed, and details about the contribution of each manuscript to the field are reviewed. The concluding critical discussion of the available literature, and the summary of open problems indicates that experiment validation, model generalization, and grasp pose selection are topics that require additional research.
Socially Assistive Robots Helping Older Adults through the Pandemic and Life after COVID-19
Authors: Getson Cristina , Nejat Goldie
Published: September 2021

The COVID-19 pandemic has critically impacted the health and safety of the population of the world, especially the health and well-being of older adults. Socially assistive robots (SARs) have been used to help to mitigate the effects of the pandemic including loneliness and isolation, and to alleviate the workload of both formal and informal caregivers. This paper presents the first extensive survey and discussion on just how socially assistive robots have specifically helped this population, as well as the overall impact on health and the acceptance of such robots during the pandemic. The goal of this review is to answer research questions with respect to which SARs were used during the pandemic and what specific tasks they were used for, and what the enablers and barriers were to the implementation of SARs during the pandemic. We will also discuss lessons learned from their use to inform future SAR design and applications, and increase their usefulness and adoption in a post-pandemic world. More research is still needed to investigate and appreciate the user experience of older adults with SARs during the pandemic, and we aim to provide a roadmap for researchers and stakeholders.
Hyperspectral Dimensionality Reduction Based on Inter-Band Redundancy Analysis and Greedy Spectral Selection
Authors: Morales Giorgio , Sheppard John W. , Logan Riley D. , Shaw Joseph A.
Published: September 2021

Hyperspectral imaging systems are becoming widely used due to their increasing accessibility and their ability to provide detailed spectral responses based on hundreds of spectral bands. However, the resulting hyperspectral images (HSIs) come at the cost of increased storage requirements, increased computational time to process, and highly redundant data. Thus, dimensionality reduction techniques are necessary to decrease the number of spectral bands while retaining the most useful information. Our contribution is two-fold: First, we propose a filter-based method called interband redundancy analysis (IBRA) based on a collinearity analysis between a band and its neighbors. This analysis helps to remove redundant bands and dramatically reduces the search space. Second, we apply a wrapper-based approach called greedy spectral selection (GSS) to the results of IBRA to select bands based on their information entropy values and train a compact convolutional neural network to evaluate the performance of the current selection. We also propose a feature extraction framework that consists of two main steps: first, it reduces the total number of bands using IBRA; then, it can use any feature extraction method to obtain the desired number of feature channels. We present classification results obtained from our methods and compare them to other dimensionality reduction methods on three hyperspectral image datasets. Additionally, we used the original hyperspectral data cube to simulate the process of using actual filters in a multispectral imager.
Camera Assisted Roadside Monitoring for Invasive Alien Plant Species Using Deep Learning
Authors: Dyrmann Mads , Mortensen Anders Krogh , Linneberg Lars , Høye Toke Thomas , Bjerge Kim
Published: September 2021

Invasive alien plant species (IAPS) pose a threat to biodiversity as they propagate and outcompete natural vegetation. In this study, a system for monitoring IAPS on the roadside is presented. The system consists of a camera that acquires images at high speed mounted on a vehicle that follows the traffic. Images of seven IAPS (Cytisus scoparius, Heracleum, Lupinus polyphyllus, Pastinaca sativa, Reynoutria, Rosa rugosa, and Solidago) were collected on Danish motorways. Three deep convolutional neural networks for classification (ResNet50V2 and MobileNetV2) and object detection (YOLOv3) were trained and evaluated at different image sizes. The results showed that the performance of the networks varied with the input image size and also the size of the IAPS in the images. Binary classification of IAPS vs. non-IAPS showed an increased performance, compared to the classification of individual IAPS. This study shows that automatic detection and mapping of invasive plants along the roadside is possible at high speeds.
A Novel Procedure of Enhancing the Throughput of a Mode-2 Sidelink Based on Partial Sensing
Authors: Kang Seokwon , Choi Seungwon
Published: September 2021

Partial sensing is used to reduce the power consumption of pedestrian user equipment (P-UE) that operates in the signal environment of a mode-2 sidelink. However, because the data trans-mission is allowed only for the window duration of each corresponding P-UE, the throughput of the P-UE decreases by the ratio between the width of the window and the entire data period. This paper presents a novel method for enhancing the throughput of the P-UE that operates with partial sensing in the mode-2 sidelink. The proposed technique employs an additional UE, denoted the roadside unit (RSU), to collect the sensing results from each P-UE that operates with partial sensing. The proposed RSU sequentially aligns all of the partial sensing windows, such that the combination of each partial sensing window can eventually provide an almost complete sensing result. In this study, extensive computer simulations were performed. The results reveal that the proposed method enhances the throughput of each P-UE operating with partial sensing almost to that of full sensing without increasing the required power consumption.
Benefits of a Switch from Intermittently Scanned Continuous Glucose Monitoring (isCGM) to Real-Time (rt) CGM in Diabetes Type 1 Suboptimal Controlled Patients in Real-Life: A One-Year Prospective Study §
Authors: Préau Yannis , Galie Sébastien , Schaepelynck Pauline , Armand Martine , Raccah Denis
Published: September 2021

The switch from intermittently scanned continuous glucose monitoring (isCGM) to real-time (rt) CGM could improve glycemic management in suboptimal controlled type 1 diabetes patients, but long-term study is lacking. We evaluated retrospectively the ambulatory glucose profile (AGP) in such patients after switching from Free Style Libre 1 (FSL1) to Dexcom G4 (DG4) biosensors over 1 year. Patients (n = 21, 43 ± 15 years, BMI 25 ± 5, HbA1c 8.1 ± 1.0%) had severe hypoglycemia and/or HbA1c ≥ 8%. AGP metrics (time-in-range (TIR) 70–180 mg/dL, time-below-range (TBR) <70 mg/dL or <54 mg/dL, glucose coefficient of variation (%CV), time-above-range (TAR) >180 mg/dL or >250 mg/dL, glucose management indicator (GMI), average glucose) were collected the last 3 months of FSL1 use (M0) and of DG4 for 3, 6 (M6) and 12 (M12) months of use. Values were means ± standard deviation or medians [Q1;Q3]. At M12 versus M0, the higher TIR (50 ± 17 vs. 45 ± 16, p = 0.036), and lower TBR < 70 mg/dL (2.5 [1.6;5.5] vs. 7.0 [4.5;12.5], p = 0.0007), TBR < 54 mg/dL (0.7 [0.4;0.8] vs. 2.3 [0.8;7.0], p = 0.007) and %CV (39 ± 5 vs. 45 ± 8, p = 0.0009), evidenced a long-term effectiveness of the switch. Compared to M6, TBR < 70 mg/dL decreased, %CV remained stable, while the improvement on hyperglycemia exposure decreased (higher GMI, TAR and average glucose). This switch was a relevant therapeutic option, though a loss of benefit on hyperglycemia stressed the need for optimized management of threshold alarms. Nevertheless, few patients attained the recommended values for AGP metrics, and the reasons why some patients are “responders” vs. “non-responders” warrant to be investigated.
Ports Digitalization Level Evaluation
Authors: Paulauskas Vytautas , Filina-Dawidowicz Ludmiła , Paulauskas Donatas
Published: September 2021

Currently, seaports are actively searching for methods and ways to improve their operational efficiency. Digitalization is considered as one of the main directions of current ports’ development. Ports’ digitalization levels are varied and may depend on different factors, including port size, traditions, turnover and handled cargo type, etc. Ports often face decision-making challenges related to assessment of their digitization level and choice of development directions. The article aims to develop a methodology to evaluate ports’ digitalization level. A marketing research tool was used to collect the data needed for the analysis. A mathematical model allowing simulations is proposed and a case study of 30 ports located in the Baltic, North and Mediterranean Seas regions is explored. Based on conducted calculations, a ranking of analysed ports considering their digitalization level was created. The ports were compared within groups of small, medium-sized and large ports. It was estimated that the digitalization level in small and medium-sized ports is about 30% lower than the level of large seaports. The research results may be of interest to seaports striving to assess their level of digitalization and choose the best digital improvement solutions.
Assessment of the Effect of Cleanliness on the Visual Inspection of Aircraft Engine Blades: An Eye Tracking Study
Authors: Aust Jonas , Mitrovic Antonija , Pons Dirk
Published: September 2021

Background—The visual inspection of aircraft parts such as engine blades is crucial to ensure safe aircraft operation. There is a need to understand the reliability of such inspections and the factors that affect the results. In this study, the factor ‘cleanliness’ was analysed among other factors. Method—Fifty industry practitioners of three expertise levels inspected 24 images of parts with a variety of defects in clean and dirty conditions, resulting in a total of N = 1200 observations. The data were analysed statistically to evaluate the relationships between cleanliness and inspection performance. Eye tracking was applied to understand the search strategies of different levels of expertise for various part conditions. Results—The results show an inspection accuracy of 86.8% and 66.8% for clean and dirty blades, respectively. The statistical analysis showed that cleanliness and defect type influenced the inspection accuracy, while expertise was surprisingly not a significant factor. In contrast, inspection time was affected by expertise along with other factors, including cleanliness, defect type and visual acuity. Eye tracking revealed that inspectors (experts) apply a more structured and systematic search with less fixations and revisits compared to other groups. Conclusions—Cleaning prior to inspection leads to better results. Eye tracking revealed that inspectors used an underlying search strategy characterised by edge detection and differentiation between surface deposits and other types of damage, which contributed to better performance.
A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals
Authors: Ponsiglione Alfonso Maria , Cosentino Carlo , Cesarelli Giuseppe , Amato Francesco , Romano Maria
Published: September 2021

The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents inter- and intra-observer variability as well as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical relevance of the interpretation of FHR traces as well as the role of FHR as a marker of fetal wellbeing autonomous nervous system development, many different approaches for computerized processing and analysis of FHR patterns have been proposed in the literature. The objective of this review is to describe the techniques, methodologies, and algorithms proposed in this field so far, reporting their main achievements and discussing the value they brought to the scientific and clinical community. The review explores the following two main approaches to the processing and analysis of FHR signals: traditional (or linear) methodologies, namely, time and frequency domain analysis, and less conventional (or nonlinear) techniques. In this scenario, the emerging role and the opportunities offered by Artificial Intelligence tools, representing the future direction of EFM, are also discussed with a specific focus on the use of Artificial Neural Networks, whose application to the analysis of accelerations in FHR signals is also examined in a case study conducted by the authors.
An Artificial-Intelligence-Driven Predictive Model for Surface Defect Detections in Medical MEMS
Authors: Amini Amin , Kanfoud Jamil , Gan Tat-Hean
Published: September 2021

With the advancement of miniaturization in electronics and the ubiquity of micro-electro-mechanical systems (MEMS) in different applications including computing, sensing and medical apparatus, the importance of increasing production yields and ensuring the quality standard of products has become an important focus in manufacturing. Hence, the need for high-accuracy and automatic defect detection in the early phases of MEMS production has been recognized. This not only eliminates human interaction in the defect detection process, but also saves raw material and labor required. This research developed an automated defects recognition (ADR) system using a unique plenoptic camera capable of detecting surface defects of MEMS wafers using a machine-learning approach. The developed algorithm could be applied at any stage of the production process detecting defects at both entire MEMS wafer and single component scale. The developed system showed an F1 score of 0.81 U on average for true positive defect detection, with a processing time of 18 s for each image based on 6 validation sample images including 371 labels.
Evaluation of Multivariable Modeling Methods for Monitoring the Health of Guyed Towers in Overhead Power Lines
Authors: Mendes Alexandre Schalch , Ferreira Janito Vaqueiro , Meirelles Pablo Siqueira , de Oliveira Nóbrega Eurípedes Guilherme , de Lima Eduardo Rodrigues , de Almeida Larissa Medeiros
Published: September 2021

This article proposes a methodology for monitoring the structural stability of each tower of an electric power transmission line through sensor measurements which estimates the different situations that may indicate the need for intervention to prevent the structure collapsing. The extended Kalman filter was adopted to predict the failures, considering sensor fusion techniques such as the displacements of the upper central position of the tower above certain limits. The load of the stay cables is calculated from the natural frequencies, which are determined by the accelerometers connected to the cables. The average value of these forces, which must be higher than a normal limit, were calculated to predict a failure. All guyed towers of a power transmission line thousands of kilometers long will be individually monitored considering the methodology described in this study, which makes this article one of the first relevant research studies in this area. Typically, guyed towers must often be manually inspected to ensure that the stay cables have acceptable pretension to prevent a lack of stability in the transmission line towers.
Directional Field-Dependence of Magnetoimpedance Effect on Integrated YIG/Pt-Stripline System
Authors: Souza Arthur L. R. , Gamino Matheus , Ferreira Armando , de Oliveira Alexandre B. , Vaz Filipe , Bohn Felipe , Correa Marcio A.
Published: September 2021

We investigated the magnetization dynamics through the magnetoimpedance effect in an integrated YIG/Pt-stripline system in the frequency range of 0.5 up to 2.0 GHz. Specifically, we explore the dependence of the dynamic magnetic behavior on the field orientation by analyzing beyond the traditional longitudinal magnetoimpedance effect of the transverse and perpendicular setups. We disclose here the strong dependence of the effective damping parameter on the field orientation, as well as verification of the very-low damping parameter values for the longitudinal and transverse configurations. We find considerable sensitivity results, bringing to light the facilities to integrate ferrimagnetic insulators in current and future technological applications.
High Quantum Efficiency and Broadband Photodetector Based on Graphene/Silicon Nanometer Truncated Cone Arrays
Authors: Zhao Jijie , Liu Huan , Deng Lier , Bai Minyu , Xie Fei , Wen Shuai , Liu Weiguo
Published: September 2021

Light loss is one of the main factors affecting the quantum efficiency of photodetectors. Many researchers have attempted to use various methods to improve the quantum efficiency of silicon-based photodetectors. Herein, we designed highly anti-reflective silicon nanometer truncated cone arrays (Si NTCAs) as a light-trapping layer in combination with graphene to construct a high-performance graphene/Si NTCAs photodetector. This heterojunction structure overcomes the weak light absorption and severe surface recombination in traditional silicon-based photodetectors. At the same time, graphene can be used both as a broad-spectrum absorption layer and as a transparent electrode to improve the response speed of heterojunction devices. Due to these two mechanisms, this photodetector had a high quantum efficiency of 97% at a wavelength of 780 nm and a short rise/fall time of 60/105µs. This device design promotes the development of silicon-based photodetectors and provides new possibilities for integrated photoelectric systems.
Artificial Intelligence for Pigment Classification Task in the Short-Wave Infrared Range
Authors: Pouyet Emeline , Miteva Tsveta , Rohani Neda , de Viguerie Laurence
Published: September 2021

Hyperspectral reflectance imaging in the short-wave infrared range (SWIR, “extended NIR”, ca. 1000 to 2500 nm) has proven to provide enhanced characterization of paint materials. However, the interpretation of the results remains challenging due to the intrinsic complexity of the SWIR spectra, presenting both broad and narrow absorption features with possible overlaps. To cope with the high dimensionality and spectral complexity of such datasets acquired in the SWIR domain, one data treatment approach is tested, inspired by innovative development in the cultural heritage field: the use of a pigment spectral database (extracted from model and historical samples) combined with a deep neural network (DNN). This approach allows for multi-label pigment classification within each pixel of the data cube. Conventional Spectral Angle Mapping and DNN results obtained on both pigment reference samples and a Buddhist painting (thangka) are discussed.
Flow Rate Control by Means of Flow Meter and PLC Controller
Authors: Włodarczak Sylwia , Ochowiak Marek , Doligalski Michał , Kwapisz Bartosz , Krupińska Andżelika , Mrugalski Marcin , Matuszak Magdalena
Published: September 2021

This paper presents a design of a flow meter based on a programmable logic controller (PLC). The new construction of a flow meter controlled by PLC increases the possibilities for the control and automation of fluid flow. Additionally, the didactic potential of the use of simple automation in the form of a programmable logic controller was considered. A device enabling the measurement of fluid flow rate based on a PLC controller was designed, constructed, and tested. The choice of device was the Gems Sensors FT-210 series turbine flow sensor, which is characterized by low purchase and maintenance costs. The properties and the chemical resistance of polyamide-12, the material the sensor is made of, make it possible to test the flow of various types of fluids. As part of the work, an algorithm and a program controlling the device was developed based on the APB Soft software, enabling the accurate reading of the number of impulses sent by the turbine flow sensor. The results of the designed flow meter were compared with the results obtained for the Krohne VA-40 high accuracy rotameter.
Determination of Formaldehyde Yields in E-Cigarette Aerosols: An Evaluation of the Efficiency of the DNPH Derivatization Method
Authors: Jin Xiaohong C. , Ballentine Regina M. , Gardner William P. , Melvin Matt S. , Pithawalla Yezdi B. , Wagner Karl A. , Avery Karen C. , Sharifi Mehran
Published: September 2021

Recent reports have suggested that (1) formaldehyde levels (measured as a hydrazone derivative using the DNPH derivatization method) in Electronic Nicotine Delivery Systems (ENDS) products were underreported because formaldehyde may react with propylene glycol (PG) and glycerin (Gly) in the aerosol to form hemiacetals; (2) the equilibrium would shift from the hemiacetals to the acetals in the acidic DNPH trapping solution. In both cases, neither the hemiacetal nor the acetal would react with DNPH to form the target formaldehyde hydrazone, due to the lack of the carbonyl functional group, thus underreporting formaldehyde. These reports were studied in our laboratory. Our results showed that the aerosol generated from formaldehyde-fortified e-liquids provided a near-quantitative recovery of formaldehyde in the aerosol, suggesting that if any hemiacetal was formed in the aerosol, it would readily hydrolyze to free formaldehyde and, consequently, form formaldehyde hydrazone in the acidic DNPH trapping solution. We demonstrated that custom-synthesized Gly and PG hemiacetal adducts added to the DNPH trapping solution would readily hydrolyze to form the formaldehyde hydrazone. We demonstrated that acetals of PG and Gly present in e-liquid are almost completely transferred to the aerosol during aerosolization. The study results demonstrate that the DNPH derivatization method allows for an accurate measurement of formaldehyde in vapor products.
Magnetic Ionic Liquids in Sample Preparation: Recent Advances and Future Trends
Authors: Chatzimitakos Theodoros , Anagnostou Phoebe , Constantinou Ioanna , Dakidi Kalliroi , Stalikas Constantine
Published: September 2021

In the last decades, a myriad of materials has been synthesized and utilized for the development of sample preparation procedures. The use of their magnetic analogues has gained significant attention and many procedures have been developed using magnetic materials. In this context, the benefits of a new class of magnetic ionic liquids (MILs), as non-conventional solvents, have been reaped in sample preparation procedures. MILs combine the advantageous properties of ionic liquids along with the magnetic properties, creating an unsurpassed combination. Owing to their unique nature and inherent benefits, the number of published reports on sample preparation with MILs is increasing. This fact, along with the many different types of extraction procedures that are developed, suggests that this is a promising field of research. Advances in the field are achieved both by developing new MILs with better properties (showing either stronger response to external magnetic fields or tunable extractive properties) and by developing and/or combining methods, resulting in advanced ones. In this advancing field of research, a good understanding of the existing literature is needed. This review aims to provide a literature update on the current trends of MILs in different modes of sample preparation, along with the current limitations and the prospects of the field. The use of MILs in dispersive liquid–liquid microextraction, single drop microextraction, matrix solid-phase dispersion, etc., is discussed herein among others.
Reflections for a Sociological Representation of the Eater
Authors: Corbeau Jean Pierre
Published: September 2021

Professor Jean Pierre Corbeau is an important author of the French sociology of food. He played a decisive role in the emergence of the concept of the eater. This essay is a reflexive discussion by the author of one of his theoretical articles published in 1997. It is an opportunity for the English-speaking sociological community to become better acquainted with this current in the sociology of food.
An Integrated Method to Evaluate Sustainability for Vulnerable Buildings Addressing Life Cycle Embodied Impacts and Resource Use
Authors: Keskin Fatma Seyma , Martinez-Vazquez Pedro , Baniotopoulos Charalampos
Published: September 2021

The vulnerability of buildings faces further scrutiny as gaps in design, construction, operation, and maintenance remain. Although there has been noticeable progress in the field, the frequency and magnitude of building damage during natural events highlight the fact that sustainable infrastructure has not yet reached all targets. In this study, sustainability aspects of vulnerable buildings are revisited to propose more robust measures to prevent damage and a lack of functionality. Those measured are underpinned by the merging of environmental and structural sustainability for one novel integrated approach. The method devises structural intervention scenarios based on damage levels and service period. It also aims at reducing resource use and embodied impacts through the discretization of standard life cycle analysis into customized stages. The integrated method to evaluate sustainability is tested on two vulnerable buildings in Turkey and Mexico, built with different codes of practice and having experienced low to medium damage during severe earthquake events. Research findings indicate that although embodied impacts form a minor part of the building life cycle environmental impacts, sustainable structural interventions can further reduce both embodied impacts and demands on natural resources. Hence strengthening vulnerable buildings can provide an advantage to help the sustainable transformation of cities.
Electricity Consumption in China: The Effects of Financial Development and Trade Openness
Authors: Duan Ruijun , Guo Peng
Published: September 2021

As China is facing the double pressure of economic growth as well as energy-saving and reduction of emissions, reducing electricity consumption without affecting economic development is a challenging and critical issue. Based on 31 provincial panel’s data in China from 2004 to 2018, this study empirically analyzes the direction and degree of the impact of financial development and trade openness on electricity consumption using the spatial econometric approach and panel vector autoregression (PVAR) model. The results indicate that China’s electricity consumption presents a significant spatial spill over effect, and the spatial agglomeration of electricity consumption in local regions is mainly HH clusters. A 1% positive change in financial development causes an increase of 0.089% in electricity consumption, but a 1% rise in financial development reduces electricity consumption of neighboring regions by 0.051%. A 1% positive change in trade openness decreases electricity consumption by 0.051%, while the spatial spillover effect of trade openness is not significant. It is also found that financial development has a long-term promoting effect on electricity consumption, while trade openness has a long-term inhibiting effect on electricity consumption.
Sustainable Coatings on Metallic Alloys as a Nowadays Challenge
Authors: Nartita Radu , Ionita Daniela , Demetrescu Ioana
Published: September 2021

Starting with a description of the meaning of sustainable coating nowadays, this review presents a selection of methods for sustainable coatings manufacture using raw materials, saving energy and costs. This selection creates an introduction for the coatings performances of intensively investigated coated alloys and their multifunctionality. There are many examples and EU recommendations to be discussed, and we especially chose to introduce sustainable coatings with both industrial and medical functions, such as bioinspired films and coatings on high-entropy alloys, biodegradable metallic alloys, etc. A special focus is on nanotechnology and nanomaterials in green procedures, enhancing coatings’ multifunctionality, introducing green corrosion inhibitors, smart additives, and coatings based on superhydrophobicity. The conclusions and future perspectives of sustainable and multifunctional coatings, as expressions of sustainable advanced materials, are based on important motivations of such studies.
Zigbee and Long-Range Architecture Based Monitoring System for Oil Pipeline Monitoring with the Internet of Things
Authors: Singh Rajesh , Baz Mohammed , Narayana Ch. Lakshmi , Rashid Mamoon , Gehlot Anita , Akram Shaik Vaseem , Alshamrani Sultan S. , Prashar Deepak , AlGhamdi Ahmed Saeed
Published: September 2021

Oil pipeline monitoring is having a significant role in minimizing the impact on the environment and humans during pipeline accidents. The real-time monitoring of oil pipelines empowers the authorities to have continuous supervision of the oil pipeline. The Internet of Things (IoT) provides an opportunity for realizing the real-time monitoring system by deploying the IoT-enabled end devices on the oil pipeline. In this study, we propose a hybrid architecture based on 2.4 GHz-based Zigbee and LoRa communication for oil pipeline monitoring. Moreover, customized end devices and LoRa based gateway are designed and implemented for sensing the critical parameters of an oil pipeline. Here, we have performed the simulation of ZigBee communication on the OPNET simulator for evaluating the parameters such as packet delivery ratio (PDR), retransmission attempts, throughput, medium access (MAC) queue size, and queue delay. Furthermore, the distinct evaluation metrics of LoRa such as bit rate, link budget, and receiver sensitivity are also included. Finally, a real-time experiment is implemented with customized end devices and a gateway for evaluating the proposed architecture. In the real-time experiment, the devices and gateway are logging the pressure sensory data into the Cayenne cloud.
Influence of Population Income on Energy Consumption and CO2 Emissions in Buildings of Cities
Authors: Zarco-Soto Irene M. , Zarco-Soto Fco. Javier , Zarco-Periñán Pedro J.
Published: September 2021

More than half of the world’s population lives in cities. A large part of the emissions and energy consumption corresponds to buildings, both in the residential sector and in the service sector. This means that a large part of the measures taken by governments to reduce energy consumption and greenhouse gas emissions are focused on this sector. With this background, this paper studies energy consumption in city buildings and the CO2 emissions they produce. It only makes use of publicly available data. The analysis is made from the point of view of income per inhabitant, and the results are obtained per inhabitant and household. To facilitate the analysis of the results, an index has been defined. The main contributions of this work are to analyze energy consumption and emissions due to buildings, study them from the point of view of the income of their inhabitants, and consider cities individually. The proposed methodology has been applied to the case of Spain. A total of 145 Spanish cities that have more than 50,000 inhabitants have been studied. The results show that the higher the income, the higher the consumption and emissions. Electricity consumptions are almost inelastic, while those of thermal origin are greatly influenced by the level of income. Regarding CO2 emissions, the percentage of emissions of electrical origin with respect to total emissions is higher than that of thermal origin. In addition, the lower the income, the higher the percentage of emissions of electrical origin.