bluuebunny/crossref_metadata_2025 huggingface dataset:
CAD Genes: Genome-Wide Identification, Evolution, and Their Contribution to Lignin Biosynthesis in Pear (Pyrus bretschneideri)
Authors: Qi Kaijie , Song Xiaofei , Yuan Yazhou , Bao Jianping , Gong Xin , Huang Xiaosan , Khanizadeh Shahrokh , Zhang Shaoling , Tao Shutian
Published: July 2021

The synthetic enzyme cinnamyl alcohol dehydrogenase (CAD) is involved in responses to various stresses during plant growth. It regulates the monolignol biosynthesis and catalyzes hydroxyl cinnamaldehyde reduction to the corresponding alcohols. Although the CAD gene families have been explored in some species, little known is in Rosaceae. In this study, we identified 149 genes in Pyrus bretschneideri (PbrCAD), Malus domestica (MDPCAD), Prunus mume (PmCAD) and Fragaria vesca (mrnaCAD). They were phylogenetically clustered into six subgroups. All CAD genes contained ADH-N and ADH-zinc-N domains and were distributed on chromosomes unevenly. Dispersed and WGD/segmental duplications accounted the highest number of evolutionary events. Eight collinear gene pairs were identified among the four Rosaceae species, and the highest number was recorded in pear as five pairs. The five PbrCAD gene pairs had undergone purifying selection under Ka/Ks analysis. Furthermore, nine genes were identified based on transcriptomic and stone cell content in pear fruit. In qRT-PCR, the expression patterns of PbrCAD1, PbrCAD20, PbrCAD27, and PbrCAD31 were consistent with variation in stone cell content during pear fruit development. These results will provide valuable information for understanding the relationship between gene expressions and stone cell number in fruit.
Mycelium Dispersion from Fusarium oxysporum f. sp. dianthi Elicits a Reduction of Wilt Severity and Influences Phenolic Profiles of Carnation (Dianthus caryophyllus L.) Roots
Authors: Santos-Rodríguez Janneth , Coy-Barrera Ericsson , Ardila Harold Duban
Published: July 2021

The fungal pathogen Fusarium oxysporum f. sp. dianthi (Fod) is the causal agent of the vascular wilt of carnation (Dianthus caryophyllus L.) and the most prevalent pathogen in the areas where this flower is grown. For this reason, the development of new control strategies against Fod in carnation has been continuously encouraged, in particular those based on the implementation of plant resistance inducers that can trigger defensive responses to reduce the disease incidence, even at lower economical and environmental cost. In the present study, the effect of the soil supplementation of a biotic elicitor (i.e., ultrasound-assisted dispersion obtained from Fod mycelium) on disease severity and phenolic-based profiles of roots over two carnation cultivars was evaluated. Results suggest that the tested biotic elicitor, namely, eFod, substantially reduced the progress of vascular wilting in a susceptible cultivar (i.e., ‘Mizuki’) after two independent in vivo tests. The LC-MS-derived semi-quantitative levels of phenolic compounds in roots were also affected by eFod, since particular anthranilate derivatives, conjugated benzoic acids, and glycosylated flavonols were upregulated by elicitation after 144 and 240 h post eFod addition. Our findings indicate that the soil-applied eFod has an effect as a resistance inducer, promoting a disease severity reduction and accumulation of particular phenolic-like compounds.
Vescalagin from Pink Wax Apple (Syzygium samarangense (Blume) Merrill and Perry) Protects Pancreatic β-Cells against Methylglyoxal-Induced Inflammation in Rats
Authors: Chang Wen-Chang , Wu James Swi-Bea , Shen Szu-Chuan
Published: July 2021

Methylglyoxal (MG) is the primary precursor of advanced glycation end products involved in the pathogenesis of inflammation and diabetes. A previous study in our laboratory found anti-inflammatory and anti-hyperglycemic effects of the polyphenol vescalagin (VES) in rats with MG-induced carbohydrate metabolic disorder. The present study further investigated the occurrence of inflammation in pancreatic β-cells in MG-induced diabetic rats and the mechanism by which VES prevents it. The results showed that VES downregulates the protein expression levels of advanced glycation end product receptors and CCAAT/enhancer binding protein-β and upregulates the protein expression levels of pancreatic duodenal homeobox-1, nuclear factor erythroid 2-related factor 2 and glyoxalase I from the pancreatic cells. The results also revealed that VES elevates glutathione and antioxidant enzyme contents and then downregulates c-Jun N-terminal kinase and p38 mitogen-activated protein kinases pathways to protect pancreatic β-cells in MG-administered rats.
Natural-Based Biomaterial for Skin Wound Healing (Gelatin vs. Collagen): Expert Review
Authors: Naomi Ruth , Bahari Hasnah , Ridzuan Pauzi Muhd , Othman Fezah
Published: July 2021

Collagen (Col) and gelatin are most extensively used in various fields, particularly in pharmaceuticals and therapeutics. Numerous researchers have proven that they are highly biocompatible to human tissues, exhibit low antigenicity and are easy to degrade. Despite their different sources both Col and gelatin have almost the same effects when it comes to wound healing mechanisms. Considering this, the bioactivity and biological effects of both Col and gelatin have been, and are being, constantly investigated through in vitro and in vivo assays to obtain maximum outcomes in the future. With regard to their proven nutritional values as sources of protein, Col and gelatin products exert various possible biological activities on cells in the extracellular matrix (ECM). In addition, a vast number of novel Col and gelatin applications have been discovered. This review compared Col and gelatin in terms of their structures, sources of derivatives, physicochemical properties, results of in vitro and in vivo studies, their roles in wound healing and the current challenges in wound healing. Thus, this review provides the current insights and the latest discoveries on both Col and gelatin in their wound healing mechanisms.
Geometric Optimization of an Extracorporeal Centrifugal Blood Pump with an Unshrouded Impeller Concerning Both Hydraulic Performance and Shear Stress
Authors: Huang Bo , Guo Miao , Lu Bin , Wu Qingyu , Zuo Zhigang , Liu Shuhong
Published: July 2021

Centrifugal blood pumps have provided a powerful artificial support system for patients with vascular diseases. In the design process, geometrical optimization is usually needed to acquire a more biocompatible model for clinical uses. In the current paper, we propose a method for multi-objective optimization concerning both the hydraulic and the hemolytic performances of the pump based on the near-orthogonal array in which the traditional hemolysis index (HI) is replaced with the maximum scalar shear stress criteria to reduce the computation load. The method is demonstrated with the optimization of an extracorporeal centrifugal blood pump with an unshrouded impeller. CFD studies on the original and nine modified pump models are carried out. The calculated hydraulic performances of the optimized model are also compared against the experiments for validation of the numeric method, with an error of 3.6% at the original design point. The resulting blood pump with low maximum scalar shear stress (132.2 Pa) shows a low degree of calculated HI (1.69 × 10−3).
Effects of Flow Baffles on Flow Profile, Pressure Drop and Classification Performance in Classifiers
Authors: Betz Michael , Gleiss Marco , Nirschl Hermann
Published: July 2021

This paper presents a study of the use of flow baffles inside a centrifugal air classifier. An air classifier belongs to the most widely used classification devices in mills in the mineral industry, which is why there is a great interest in optimizing the process flow and pressure loss. Using Computational Fluid Dynamics (CFD), the flow profile in a classifier without and with flow baffles is systematically compared. In the simulations, turbulence effects are modeled with the realizable k–ε model, and the Multiple Reference Frame approach (MRF) is used to represent the rotation of the classifier wheel. The discrete phase model is used to predict the collection efficiency. The effects on the pressure loss and the classification efficiency of the classifier are considered for two operating conditions. In addition, a comparison with experimental data is performed. Firstly, the simulations and experiments show good agreement. Furthermore, the investigations show that the use of flow baffles is suitable for optimizing the flow behavior in the classifier, especially in reducing the pressure loss and therefore energy costs. Moreover, the flow baffles have an impact on the classification performance. The impact depends on the operation conditions, especially the classifier speed. At low classifier speeds, the classifier without flow baffles separates more efficiently; as the speed increases, the classification performance of the classifier with flow baffles improves.
Experimental Analysis of a Heat Pump Dryer with an External Desiccant Wheel Dryer
Authors: Yang Kai-Shing , Hamid Khalid , Wu Shih-Kuo , Sajjad Uzair , Wang Chi-Chuan
Published: July 2021

This study examines the performance of three heat pump dryers: the original reference design, a modified drying chamber, and an external desiccant wheel design. Unlike most existing studies that normally adopt organic products as the drying materials, in this study we used moist sodium polyacrylate (Orbeez) as the drying material for consistent characterization of the heat pump performance. R-134a was adopted as the refrigerant for the heat pump system. The experiments were performed subject to different weights of Orbeez (drying material) at a constant volumetric flow rate of 100 m3/h. During experimentation, different parameters like the coefficient of performance (COPHP), drying rate, heat transfer rate by the condenser, moisture extraction rate, and specific moisture extraction rate were calculated. The average COPHP, mass transfer rate, heat transfer rate, MER, and SMER of the system were calculated as 3.9, 0.30 kg/s, 0.56 kW, 0.495 kg/h, and 1.614 kg/kWh, respectively. The maximum COP for the refrigeration system was achieved at lower test loads with the desiccant wheel. The moisture extraction rate for a lower test loading was higher than that for a higher test load due to the higher penetration of drying air at the lower test load, although the maximum test load showed the maximum relative humidity at the dryer outlet. The desiccant wheel showed good performance in terms of moisture extraction rate and COPHP, but it showed poor performance in terms of the specific moisture extraction rate due to the high power consumption (around 2.6 kW) of the desiccant dehumidifier. The moisture extraction rate (MER) for all designs increased to a maximum value, followed by consistent decline. However, the maximum MER for the desiccant design exceeded those for the other designs.
Effects of Hydrogen Addition on Design, Maintenance and Surveillance of Gas Networks
Authors: Guy Pluvinage , Laszlo Toth , Julien Capelle
Published: July 2021

Hydrogen, when is blended with natural gas over time, degrades the materials used for pipe transport. Degradation is dependent on the proportion of hydrogen added to the natural gas. The assessment is made according to hydrogen permeation, risk to the integrity of structures, adaptation of surveillance and maintenance of equipment. The paper gives a survey of HE and its consequence on the design and maintenance. It is presented in a logical sequence: the design before use; the hydrogen embrittlement (HE) effects on Maximum Allowable Operating Pressure (MAOP); maintenance and surveillance during use of smooth and damaged pipes; and, particularly, for crack-like defects, corrosion defects and dents.
Sustainable Syntheses and Sources of Nanomaterials for Microbial Fuel/Electrolysis Cell Applications: An Overview of Recent Progress
Authors: Frattini Domenico , Karunakaran Gopalu , Cho Eun-Bum , Kwon Yongchai
Published: July 2021

The use of microbial fuel cells (MFCs) is quickly spreading in the fields of bioenergy generation and wastewater treatment, as well as in the biosynthesis of valuable compounds for microbial electrolysis cells (MECs). MFCs and MECs have not been able to penetrate the market as economic feasibility is lost when their performances are boosted by nanomaterials. The nanoparticles used to realize or decorate the components (electrodes or the membrane) have expensive processing, purification, and raw resource costs. In recent decades, many studies have approached the problem of finding green synthesis routes and cheap sources for the most common nanoparticles employed in MFCs and MECs. These nanoparticles are essentially made of carbon, noble metals, and non-noble metals, together with a few other few doping elements. In this review, the most recent findings regarding the sustainable preparation of nanoparticles, in terms of syntheses and sources, are collected, commented, and proposed for applications in MFC and MEC devices. The use of naturally occurring, recycled, and alternative raw materials for nanoparticle synthesis is showcased in detail here. Several examples of how these naturally derived or sustainable nanoparticles have been employed in microbial devices are also examined. The results demonstrate that this approach is valuable and could represent a solid alternative to the expensive use of commercial nanoparticles.
Biolubricant Production through Double Transesterification: Reactor Design for the Implementation of a Biorefinery Based on Rapeseed
Authors: Encinar José María , Nogales-Delgado Sergio , Pinilla Antonio
Published: July 2021

The production and use of biolubricants as replacements for mineral lubricants align with the promotion of sustainable development goals, contributing to the sustainable economic growth of developing countries as well as the preservation of the environment. The implementation of biorefineries (where the production of biolubricants through transesterification could play an important role) is becoming important for these purposes, using natural feedstocks such as rapeseed, which is an interesting crop that can adapt to different climates under extreme weather conditions. The aim of this research work was to study the design of a reactor to produce rapeseed biolubricant through double transesterification of the corresponding vegetable oil. Thus, the kinetics to design a reactor was studied, sizing it according to the properties of the biolubricant and the demand in Spain. As a result, a SAE 10W30 biolubricant was obtained, which was suitable for Diesel engines. A batch reactor was selected for the production of this biolubricant at a national level, with a pseudo-first reaction order and a reactor volume of 9.66 m3.
Meta-FSEO: A Meta-Learning Fast Adaptation with Self-Supervised Embedding Optimization for Few-Shot Remote Sensing Scene Classification
Authors: Li Yong , Shao Zhenfeng , Huang Xiao , Cai Bowen , Peng Song
Published: July 2021

The performance of deep learning is heavily influenced by the size of the learning samples, whose labeling process is time consuming and laborious. Deep learning algorithms typically assume that the training and prediction data are independent and uniformly distributed, which is rarely the case given the attributes and properties of different data sources. In remote sensing images, representations of urban land surfaces can vary across regions and by season, demanding rapid generalization of these surfaces in remote sensing data. In this study, we propose Meta-FSEO, a novel model for improving the performance of few-shot remote sensing scene classification in varying urban scenes. The proposed Meta-FSEO model deploys self-supervised embedding optimization for adaptive generalization in new tasks such as classifying features in new urban regions that have never been encountered during the training phase, thus balancing the requirements for feature classification tasks between multiple images collected at different times and places. We also created a loss function by weighting the contrast losses and cross-entropy losses. The proposed Meta-FSEO demonstrates a great generalization capability in remote sensing scene classification among different cities. In a five-way one-shot classification experiment with the Sentinel-1/2 Multi-Spectral (SEN12MS) dataset, the accuracy reached 63.08%. In a five-way five-shot experiment on the same dataset, the accuracy reached 74.29%. These results indicated that the proposed Meta-FSEO model outperformed both the transfer learning-based algorithm and two popular meta-learning-based methods, i.e., MAML and Meta-SGD.
Fiber Optic Based Distributed Mechanical Vibration Sensing
Authors: Novotný Vít , Sysel Petr , Prokeš Aleš , Hanák Pavel , Slavíček Karel , Přinosil Jiří
Published: July 2021

The distributed long-range sensing system, using the standard telecommunication single-mode optical fiber for the distributed sensing of mechanical vibrations, is described. Various events generating vibrations, such as a walking or running person, moving car, train, and many other vibration sources, can be detected, localized, and classified. The sensor is based on phase-sensitive optical time-domain reflectometry (ϕ-OTDR). Related sensing system components were designed and constructed, and the system was tested both in the laboratory and in the real deployment, with an 88 km telecom optical link, and the results are presented in this paper. A two-fiber sensor unit, with a double-sensing range was also designed, and its scheme is described. The unit was constructed and the initial measurement results are presented.
Cooperative Object Transportation Using Curriculum-Based Deep Reinforcement Learning
Authors: Eoh Gyuho , Park Tae-Hyoung
Published: July 2021

This paper presents a cooperative object transportation technique using deep reinforcement learning (DRL) based on curricula. Previous studies on object transportation highly depended on complex and intractable controls, such as grasping, pushing, and caging. Recently, DRL-based object transportation techniques have been proposed, which showed improved performance without precise controller design. However, DRL-based techniques not only take a long time to learn their policies but also sometimes fail to learn. It is difficult to learn the policy of DRL by random actions only. Therefore, we propose two curricula for the efficient learning of object transportation: region-growing and single- to multi-robot. During the learning process, the region-growing curriculum gradually extended to a region in which an object was initialized. This step-by-step learning raised the success probability of object transportation by restricting the working area. Multiple robots could easily learn a new policy by exploiting the pre-trained policy of a single robot. This single- to multi-robot curriculum can help robots to learn a transporting method with trial and error. Simulation results are presented to verify the proposed techniques.
Multiple Access-Enabled Relaying with Piece-Wise and Forward NOMA: Rate Optimization under Reliability Constraints
Authors: Khodakhah Farnaz , Mahmood Aamir , Österberg Patrik , Gidlund Mikael
Published: July 2021

The increasing proliferation of Internet-of-things (IoT) networks in a given space requires exploring various communication solutions (e.g., cooperative relaying, non-orthogonal multiple access, spectrum sharing) jointly to increase the performance of coexisting IoT systems. However, the design complexity of such a system increases, especially under the constraints of performance targets. In this respect, this paper studies multiple-access enabled relaying by a lower-priority secondary system, which cooperatively relays the incoming information to the primary users and simultaneously transmits its own data. We consider that the direct link between the primary transmitter–receiver pair uses orthogonal multiple access in the first phase. In the second phase, a secondary transmitter adopts a relaying strategy to support the direct link while it uses non-orthogonal multiple access (NOMA) to serve the secondary receiver. As a relaying scheme, we propose a piece-wise and forward (PF) relay protocol, which, depending on the absolute value of the received primary signal, acts similar to decode-and-forward (DF) and amplify-and-forward (AF) schemes in high and low signal-to-noise ratio (SNR), respectively. By doing so, PF achieves the best of these two relaying protocols using the adaptive threshold according to the transmitter-relay channel condition. Under PF-NOMA, first, we find the achievable rate region for primary and secondary receivers, and then we formulate an optimization problem to derive the optimal PF-NOMA time and power fraction that maximize the secondary rate subject to reliability constraints on both the primary and the secondary links. Our simulation results and analysis show that the PF-NOMA outperforms DF-NOMA and AF-NOMA-based relaying techniques in terms of achievable rate regions and rate-guaranteed relay locations.
Research on Network Security Situation Awareness Based on the LSTM-DT Model
Authors: Zhang Haofang , Kang Chunying , Xiao Yao
Published: July 2021

To better understand the behavior of attackers and describe the network state, we construct an LSTM-DT model for network security situation awareness, which provides risk assessment indicators and quantitative methods. This paper introduces the concept of attack probability, making prediction results more consistent with the actual network situation. The model is focused on the problem of the time sequence of network security situation assessment by using the decision tree algorithm (DT) and long short-term memory(LSTM) network. The biggest innovation of this paper is to change the description of the network situation in the original dataset. The original label only has attack and normal. We put forward a new idea which regards attack as a possibility, obtaining the probability of each attack, and describing the network situation by combining the occurrence probability and attack impact. Firstly, we determine the network risk assessment indicators through the dataset feature distribution, and we give the network risk assessment index a corresponding weight based on the analytic hierarchy process (AHP). Then, the stack sparse auto-encoder (SSAE) is used to learn the characteristics of the original dataset. The attack probability can be predicted by the processed dataset by using the LSTM network. At the same time, the DT algorithm is applied to identify attack types. Finally, we draw the corresponding curve according to the network security situation value at each time. Experiments show that the accuracy of the network situation awareness method proposed in this paper can reach 95%, and the accuracy of attack recognition can reach 87%. Compared with the former research results, the effect is better in describing complex network environment problems.
Laser Scanning and Parametrization of Weld Grooves with Reflective Surfaces
Authors: Cibicik Andrej , Tingelstad Lars , Egeland Olav
Published: July 2021

This paper presents a novel weld groove parametrization algorithm, which is developed specifically for weld grooves in typical stub and butt joints between large tubular elements. The procedure is based on random sample consensus (RANSAC) with additionally proposed correction steps, including a corner correction step for grooves with narrow root weld, and an iterative error elimination step for improving the initially obtained data fit. The problem of curved groove sides (due to the pipe geometry) is attributed and solved. In addition, the procedure detects and eliminates several types of data noise due to laser line reflections. The performance of the procedure is studied experimentally using small-scale test objects, which have been ground using typical industrial power tools to achieve a realistic level of reflections. The execution times and data fit errors of the proposed procedure are compared to a procedure based on a more conventional RANSAC approach for line segment detection.
Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems
Authors: Docquier Nicolas , Timmermans Sébastien , Fisette Paul
Published: July 2021

Multibody modeling of mechanical systems can be applied to various applications. Human-in-the-loop interfaces represent a growing research field, for which increasingly more devices include a dynamic multibody model to emulate the system physics in real-time. In this scope, reliable and highly dynamic sensors, to both validate those models and to measure in real-time the physical system behavior, have become crucial. In this paper, a multibody modeling approach in relative coordinates is proposed, based on symbolic equations of the physical system. The model is running in a ROS environment, which interacts with sensors and actuators. Two real-time applications with haptic feedback are presented: a piano key and a car simulator. In the present work, several sensors are used to characterize and validate the multibody model, but also to measure the system kinematics and dynamics within the human-in-the-loop process, and to ultimately validate the haptic device behavior. Experimental results for both developed devices confirm the interest of an embedded multibody model to enhance the haptic feedback performances. Besides, model parameters variations during the experiments illustrate the infinite possibilities that such model-based configurable haptic devices can offer.
Combining Genetic Algorithms and SVM for Breast Cancer Diagnosis Using Infrared Thermography
Authors: Resmini Roger , Silva Lincoln , Araujo Adriel S. , Medeiros Petrucio , Muchaluat-Saade Débora , Conci Aura
Published: July 2021

Breast cancer is one of the leading causes of mortality globally, but early diagnosis and treatment can increase the cancer survival rate. In this context, thermography is a suitable approach to help early diagnosis due to the temperature difference between cancerous tissues and healthy neighboring tissues. This work proposes an ensemble method for selecting models and features by combining a Genetic Algorithm (GA) and the Support Vector Machine (SVM) classifier to diagnose breast cancer. Our evaluation demonstrates that the approach presents a significant contribution to the early diagnosis of breast cancer, presenting results with 94.79% Area Under the Receiver Operating Characteristic Curve and 97.18% of Accuracy.
Efficient and Consumer-Centered Item Detection and Classification with a Multicamera Network at High Ranges
Authors: Mandischer Nils , Huhn Tobias , Hüsing Mathias , Corves Burkhard
Published: July 2021

In the EU project SHAREWORK, methods are developed that allow humans and robots to collaborate in an industrial environment. One of the major contributions is a framework for task planning coupled with automated item detection and localization. In this work, we present the methods used for detecting and classifying items on the shop floor. Important in the context of SHAREWORK is the user-friendliness of the methodology. Thus, we renounce heavy-learning-based methods in favor of unsupervised segmentation coupled with lenient machine learning methods for classification. Our algorithm is a combination of established methods adjusted for fast and reliable item detection at high ranges of up to eight meters. In this work, we present the full pipeline from calibration, over segmentation to item classification in the industrial context. The pipeline is validated on a shop floor of 40 sqm and with up to nine different items and assemblies, reaching a mean accuracy of 84% at 0.85 Hz.
Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes’ Location and Motion Artifacts Reduction for Wearable Monitoring Applications
Authors: Castaño Fabian Andres , Hernández Alher Mauricio
Published: July 2021

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by World Health Organization. Some wearables devices have been developed to monitor the Electrocardiographic in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an Electrocardiographic signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effects of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain Electrocardiographic signals, the result was compared with a computational model of the heart behavior through the Ensemble Average Electrocardiographic, Dynamic Time Warping and Signal-to-Noise Ratio methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the Electrocardiographic signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6 cm at most from the suggested location by the Einthoven triangle in Mason–Likar’s method.
Underwater In Situ Dissolved Gas Detection Based on Multi-Reflection Raman Spectroscopy
Authors: Li Meng , Liu Qingsheng , Yang Dewang , Guo Jinjia , Si Ganshang , Wu Lulu , Zheng Ronger
Published: July 2021

The detection of dissolved gases in seawater plays an important role in oceanic observations and exploration. As a potential technique for oceanic applications, Raman spectroscopy has been successfully applied in hydrothermal vents and cold seep fluids, but it has not yet been used in common seawater due to the technique’s lower sensitivity. In this work, we present a highly sensitive underwater in situ Raman spectroscopy system for dissolved gas detection in common seawater. Considering the difficulty of underwater degassing and in situ detection, we designed a near-concentric cavity to improve the sensitivity, with a miniature gas sample chamber featuring an inner volume of 1 mL placed inside the cavity to reach equilibrium in a short period of time. According to the 3σ criteria, the detection limits of this system for CO2, O2, and H2 were calculated to be 72.8, 44.0, and 27.7 ppm, respectively. Using a hollow fiber membrane degasser with a large surface area, the CO2 signal was found to be clearly visible in 30 s at a flow rate of 550 mL/min. Moreover, we deployed the system in Qingdao’s offshore seawater, and the field test showed that this system is capable of successfully detecting in situ the multiple gases dissolved in the seawater simultaneously.
Non-Invasive Driver Drowsiness Detection System
Authors: Siddiqui Hafeez Ur Rehman , Saleem Adil Ali , Brown Robert , Bademci Bahattin , Lee Ernesto , Rustam Furqan , Dudley Sandra
Published: July 2021

Drowsiness when in command of a vehicle leads to a decline in cognitive performance that affects driver behavior, potentially causing accidents. Drowsiness-related road accidents lead to severe trauma, economic consequences, impact on others, physical injury and/or even death. Real-time and accurate driver drowsiness detection and warnings systems are necessary schemes to reduce tiredness-related driving accident rates. The research presented here aims at the classification of drowsy and non-drowsy driver states based on respiration rate detection by non-invasive, non-touch, impulsive radio ultra-wideband (IR-UWB) radar. Chest movements of 40 subjects were acquired for 5 m using a lab-placed IR-UWB radar system, and respiration per minute was extracted from the resulting signals. A structured dataset was obtained comprising respiration per minute, age and label (drowsy/non-drowsy). Different machine learning models, namely, Support Vector Machine, Decision Tree, Logistic regression, Gradient Boosting Machine, Extra Tree Classifier and Multilayer Perceptron were trained on the dataset, amongst which the Support Vector Machine shows the best accuracy of 87%. This research provides a ground truth for verification and assessment of UWB to be used effectively for driver drowsiness detection based on respiration.
IoT-Enabled Solid Waste Management in Smart Cities
Authors: Vishnu S. , Ramson S. R. Jino , Senith Samson , Anagnostopoulos Theodoros , Abu-Mahfouz Adnan M. , Fan Xiaozhe , Srinivasan S. , Kirubaraj A. Alfred
Published: July 2021

The Internet of Things (IoT) paradigm plays a vital role for improving smart city applications by tracking and managing city processes in real-time. One of the most significant issues associated with smart city applications is solid waste management, which has a negative impact on our society’s health and the environment. The traditional waste management process begins with waste created by city residents and disposed of in garbage bins at the source. Municipal department trucks collect garbage and move it to recycling centers on a fixed schedule. Municipalities and waste management companies fail to keep up with outdoor containers, making it impossible to determine when to clean them or when they are full. This work proposes an IoT-enabled solid waste management system for smart cities to overcome the limitations of the traditional waste management systems. The proposed architecture consists of two types of end sensor nodes: PBLMU (Public Bin Level Monitoring Unit) and HBLMU (Home Bin Level Monitoring Unit), which are used to track bins in public and residential areas, respectively. The PBLMUs and HBLMUs measure the unfilled level of the trash bin and its location data, process it, and transmit it to a central monitoring station for storage and analysis. An intelligent Graphical User Interface (GUI) enables the waste collection authority to view and evaluate the unfilled status of each trash bin. To validate the proposed system architecture, the following significant experiments were conducted: (a) Eight trash bins were equipped with PBLMUs and connected to a LoRaWAN network and another eight trash bins were equipped with HBLMUs and connected to a Wi-Fi network. The trash bins were filled with wastes at different levels and the corresponding unfilled levels of every trash bin were monitored through the intelligent GUI. (b) An experimental setup was arranged to measure the sleep current and active current contributions of a PBLMU to estimate its average current consumption. (c) The life expectancy of a PBLMU was estimated as approximately 70 days under hypothetical conditions.
The Socio-Educational Adaptation of Secondary School Migrant Students in Sicily: Migrant Generation, School Linguistic Mediation and Teacher Proactivity Factors
Authors: Carrión-Martínez José Juan , Ciaccio Stefania , Fernández-Martínez María del Mar , Hernández-Garre Carmen María , Pérez-Esteban María Dolores
Published: July 2021

This study aims to analyze the implications of linguistic mediation processes and educational proactivity in schools for the socio-educational adaptation of immigrant students. The study is based on empirical research and the perspectives of the main actors: the immigrant students themselves. To this end, a non-experimental and descriptive quantitative methodology was used. The sample consisted of 100 students of foreign origin enrolled in an Italian school located in a typical socio-cultural environment. The results show significant differences in linguistic mediation and socio-educational variables and differences in expectations of progress and social adaptation of students born outside Italy vis-a-vis students who, although born in Italy, are still considered foreigners. It will also analyze teaching proactivity as a communication facilitator for first-generation immigrant pupils born outside Italy. In conclusion, it is noted that, to favor multicultural environments where all students, regardless of their origin, feel accepted, integrated, and welcomed, it is necessary to utilize all available resources to promote improvements in teaching-learning processes and strengthen social relations.
Global Spaces for Local Politics: An Exploratory Analysis of Facebook Ads in Spanish Election Campaigns
Authors: Calvo Dafne , Cano-Orón Lorena , Baviera Tomás
Published: July 2021

Sponsored content on Facebook has become an indispensable tool for implementing political campaign strategies. However, in political communication research, this channel is still unexplored due to its advertising model in which only target audiences are exposed to sponsored content. The launching of the Facebook Ad Library in May 2018 can be considered a turning point in this regard, inasmuch as it now offers users direct access to ads paid for by political parties, among other advertisers. This paper analyzes some aspects of the strategies implemented by six national parties during the campaigns running up to the two general elections held in Spain in 2019, by performing an analysis on a corpus of 14,684 ads downloaded directly from the Facebook Ad Library. It also provides evidence of the different emphasis placed by the parties on sponsored content. For its part, an analysis of ad scheduling shows how the publishing of ads was stepped up as polling day approached, while also revealing the practice of posting political content way in advance of election campaigns.
Individual Subjective Well-Being during the COVID-19 Pandemic
Authors: Long Trinh Q.
Published: July 2021

This paper examines how contextual and institutional factors are associated with individual subjective well-being, which is measured by individuals’ happiness, during the early stage of the COVID-19 pandemic. Using data collected in the People’s Republic of China (PRC), the Republic of Korea, Japan, Italy, the United Kingdom (UK), and the four biggest states of the United States (US) in April 2020, we find that the financial effects (represented by employment and income change) and nonfinancial effects (represented by experiencing negative nonfinancial effects including mental health issues and enjoying positive benefits) caused by nonpharmaceutical measures to contain the spread of COVID-19 are associated with individual subjective well-being. Moreover, positive benefits could reduce the likelihood of becoming unhappy for those who have experienced negative nonfinancial effects or those who have lost their jobs. The results also suggest that the degree to which people agree with their government’s approach to dealing with the COVID-19 pandemic is positively correlated with their happiness. The risks associated with the pandemic, however, are only slightly associated with people’s happiness. We also find that the correlation between the above factors and individual well-being varies from country to country.
Competitor Identification for Sustainable Survival Strategies: Illustration with Supply Chain Versus Supply Chain Competition
Authors: Antai Imoh , Mutshinda Crispin M.
Published: July 2021

We describe a methodology for identifying competitors from first principles, drawing on the ecological niche theory which stipulates that competition arises from the dependence of interacting entities on the same limiting resources or, in ecological terms, from overlap in their niches. Depending on the context, the entities of interest may be species, products, firms, countries, or supply chains. We discuss the concepts of niche breadth and niche overlap and provide a mathematical expression for computing the competitive effects of interacting entities on one another from niche breadth and overlap measures. We illustrate the competitor identification procedure with simulated data mimicking a situation where supply chains compete over logistics modes on which they rely for moving goods from point to point. Competition identification is invaluable to business sustainability as it allows the entities involved to remain sustainable and persist in a competitive environment by crafting effective strategies that allow them to continuously adapt to changes and mitigate the negative impacts of competition.
Study on the Influence of EGR on the Combustion Performance of Biofuel Diesel at Different Ambient Simulated Pressures
Authors: Tan Zefei , Wang Jun , Chen Wengang , Shen Lizhong , Bi Yuhua
Published: July 2021

In order to explore the influence of EGR at different altitudes on the performance of biofuel diesel engines, a comparative experimental study is conducted with the biodiesel–ethanol–diesel B15E5 (biodiesel with 15% volume fraction, ethanol with 5% volume fraction and diesel with 80% volume fraction) mixed fuel at different EGR rate and different atmospheric pressure. The experimental results show that diesel engine power performance and economy goes up with the increase of atmospheric pressure, and it decreases with the increase of EGR rate. At 2200 rpm, the improvement range of medium and high diesel engine load is 1.5–6.8%, and that of 1800 rpm is 2.8–11.7%. At the same atmospheric pressure, with the increase of EGR rate, the power and economy turn worse. The peak combustion pressure and heat release rate both increased with the increase of the atmospheric pressure at full load. At the same atmospheric pressure, peak combustion pressure and peak heat release rate fall with the increase of EGR rate. At part load, firstly, smoke emissions fall with the increase of the load and then rise. As the atmospheric pressure goes up, the smoke emissions show a downward trend, with a decline of 6.6–40%, while the NOx emissions show a rising trend, with an increase of 1.2–8.5%. At the same atmospheric pressure, the smoke emission increase with the increase of EGR rate by 9–12.5%, and the NOx emissions increase with the decrease of EGR rate by 2.5–6.8%. The HC and CO Emissions decrease with the increase of atmospheric pressure. HC emission decreases by 9.3–19.1%, and CO emission decreases by 2.9–16.6%. At the same atmospheric pressure, the HC emission decreases with the increase of the EGR rate by 3.3–4.5% at medium and high loads, and the CO emission increases with the EGR rate by 3.1–4.5%.
Risk, Recessions, and Resilience: Towards Sustainable Local Labor Markets through Employment Portfolio Analysis
Authors: Gulati Bharman , Weiler Stephan
Published: July 2021

This paper explores the role of local labor market dynamics on the survival of new businesses. The characteristics of the local labor market are likely to influence the survival of new businesses, the level of entrepreneurship, and the resilience of the regional economy. We apply portfolio theory to evaluate employment-based and income-based measures of risk-and-return trade-offs in local labor markets on new business survival in the United States. Our results show that volatility in local labor markets has a positive impact on new business survival, especially in Metropolitan Statistical Areas. The results are robust across different timeframes, including during economic downturns, thus highlighting the contribution of new businesses in developing the resilience of the local economy, and further promoting sustainable regional economic development.
Comparison of Immunochromatographic Test (ICT) and Filariasis Test Strip (FTS) for Detecting Lymphatic Filariasis Antigen in American Samoa, 2016
Authors: Sheel Meru , Lau Colleen L. , Sheridan Sarah , Fuimaono Saipale , Graves Patricia M.
Published: July 2021

Circulating filarial antigen (Ag) prevalence, measured using rapid point-of-care tests, is the standard indicator used for monitoring and surveillance in the Global Program to Eliminate Lymphatic Filariasis. In 2015, the immunochromatographic test (ICT) was replaced with the filariasis test strip (FTS), which has higher reported sensitivity. Despite differences in sensitivity, no changes in recommended surveillance targets were made when the FTS was introduced. In 2016, we conducted lymphatic filariasis surveys in American Samoa using FTS, which found higher Ag prevalence than previous surveys that used ICT. To determine whether the increase was real, we assessed the concordance between FTS and ICT results by paired testing of heparinised blood from 179 individuals (63% FTS-positive). ICT had 93.8% sensitivity and 100% specificity for identifying FTS-positive persons, and sensitivity was not associated with age, gender, or presence of microfilariae. Based on these findings, if ICT had been used in the 2016 surveys, the results and interpretation would have been similar to those reported using FTS. American Samoa would have failed Transmission Assessment Survey (TAS) of Grade 1 and 2 children with either test, and community prevalence would not have been significantly different (4.1%, 95% CI, 3.3–4.9% with FTS vs. predicted 3.8%, 95%, CI: 3.1–4.6% with ICT).
Assessing the Vulnerability and Risks of Adolescent Girls and Young Women in East and Southern Africa: A Preliminary Review of the Tools in Use
Authors: Ferguson Jane , Mathur Sanyukta , Armstrong Alice
Published: July 2021

The sexual and reproductive health (SRH) needs of adolescent girls and young women (AGYW) aged 10–24 years remain a cause for concern in the countries of East and Southern Africa (ESA). High rates of adolescent pregnancy and HIV prevalence prevail, and prevention programmes are challenged to identify those at greatest risk. This review aimed to identify tools being used in ESA countries that support the recording of factors that make AGYW vulnerable to SRH risks and document their use. A mixed-methods approach was used to find available English language tools that had been designed to assess the vulnerability of AGYW SRH risks including literature reviews and key informant interviews with thirty-five stakeholders. Twenty-two tools were identified, and experiences of their use obtained through the interviews. All but one tool focused on HIV prevention, and most aimed at establishing eligibility for programmes, though not aligned with programme type. Analyses of the content of seventeen tools showed information collection related to behavioral, biological, and structural risk factors of HIV and other aspects of AGYWs’ lives. There was considerable diversity in the ways in which these questions were framed. Aspects of the processes involved in undertaking the risk and vulnerability assessments are presented.
A Precessing Jet Scenario for the Multi-Wavelength Long-Term Modulation of LS I +61°303
Authors: Jaron Frédéric
Published: July 2021

The high-mass X-ray binary LS I +61°303 is detected across the electromagnetic spectrum from radio until the very high energy γ-ray regime. The emission is not only highly variable on many time scales, but is also periodic at all observed wavelengths. Periodic modulation was observed on different time-scales, ranging from hours, over months to several years. The subject of this article is a super-orbital, long-term modulation of ∼4.6 years. We review the observation of this periodic modulation at multiple wavelengths and investigate systematic relationships between them. IN particular, radio observations reveal that the long-term modulation is a very stable feature of the source. Observations at other wavelengths result in a phase-shift of the modulationpattern that is a systematic function of energy. The stability of this period favors a scenario in which the long-term modulation is the result of a precessing jet giving rise to periodic changes in the Doppler factor, beating with the orbital modulation of the accretion rate. We explain the phase-shifts across energy bands in a scenario with shorter wavelengths originating closer to the base of the presessing jet. A significant deviation of the TeV emission from this trend possibly requires a different explanation related to magnetic reconnection events.