bluuebunny/crossref_metadata_2025 huggingface dataset:
Soil Humus, Iron, Sulphate and Magnesium Content Affect Nectar Traits of Wild Garlic (Allium ursinum L.)
Authors: Bodó Alexandra , Farkas Ágnes , Nagy Dávid U. , Rudolf Kinga , Hoffmann Richárd , Kocsis Marianna , Morschhauser Tamás
Published: March 2021

Recent studies revealed that from various ecological factors influencing nectar yield and quality of a plant, soil properties can be as important as microclimatic features. To date, few studies have investigated the relationship of soil characters to nectar traits of bee pollinated plants growing in natural associations. Our study intended to reveal which soil properties had the most powerful impact on nectar variables of wild garlic (Allium ursinum L.). Specimens were collected from fourteen habitats in two different years, and were potted in their original soil under the same climatic conditions. Nectar volumes and sugar concentrations were measured and soil samples were analysed for fourteen parameters. Statistical analyses revealed that the number of nectar producing Allium flowers, as well as the nectar volume and sugar content of nectar in individual flowers were influenced by both year and habitat. The humus, iron and sulphate content of soil showed negative correlation with the number of flowers producing nectar; total nectar volumes were negatively correlated with humus and iron content, but positively affected by magnesium content of the soil. Our results suggest that in addition to the effect of microclimatic factors, certain soil properties can have significant impact on nectar traits.
Impact of Rising Temperature in the Deposition Patterns of Bioactive Compounds in Field Grown Food Barley Grains
Authors: Martínez-Subirà Mariona , Moralejo Marian , Puig Eva , Romero María-Paz , Savin Roxana , Romagosa Ignacio
Published: March 2021

High temperatures at the end of the season are frequent under Mediterranean conditions, affecting final grain quality. This study determined the deposition patterns throughout grain filling of dry matter, dietary fiber, phenolic compounds and antioxidant capacity for four barley genotypes under two contrasting temperatures. Deposition pattern for dietary fiber followed that of grain weight. Genotypic differences for duration were more significant than for rate. Anthocyanins followed a second-degree polynomial pattern, reaching a maximum before grain maturation. Free and bound phenols decreased as grain developed, suggesting that they are synthesized in early stages. Rate of bound phenols deposition was more sensitive to genotypic changes. Overall, antioxidant capacity decreased over time; the decay being less steep under stress for all genotypes. Heat stress negatively affected grain weight. It did not alter the profile of β-glucans and arabinoxylans deposition but positively changed the accumulation of some phenolic compounds, increasing the antioxidant capacity differentially across genotypes. These results support the growing of food barley in high-temperature stress-prone areas, as some bioactive compound and antioxidant capacity will increase, regardless of the smaller grain size. Moreover, if a market develops for food-barley ingredients, early harvesting of non-mature grain to maximize antioxidant capacity should be considered.
Study of the Impact of Nonionic Additives on the Composition and Structure of Petroleum Dispersed Systems by IR Spectroscopy
Authors: Lakhova Alfiya I. , Safiulina Aliya G. , Islamova Galiya G. , Amansaryev Abdykerim B. , Salakhov Ilzat I. , Petrov Sergey M. , Bashkirtseva Natalya Yu.
Published: March 2021

The article describes a technique for obtaining a quantitative assessment of the composition and structure of the petroleum dispersed system (PDS) and its individual structural formations based on the data of the component composition and infrared spectroscopy. In the PDS of heavy petroleum feedstock modified with a mixture of unsaturated carboxylic acids and four atomic alcohols, the components of the core and the inner solvation shell are different in structure. The degree of affinity of the components of the inner and outer solvation shells of the complex structural unit (CSU), as well as that of the outer solvation shell and the hydrocarbon components of the dispersion medium, increases. Nonionic additives are involved, to a greater degree, in structuring the solvation shell of the CSU and also increase the degree of its affinity with the hydrocarbon components, which leads to an increase in the dispersion of the system and a decrease in its mobility.
Droplet Dynamics on a Wettability Patterned Surface during Spray Impact
Authors: Thomas Tibin M. , Chowdhury Imdad Uddin , Dhivyaraja K. , Mahapatra Pallab Sinha , Pattamatta Arvind , Tiwari Manish K.
Published: March 2021

Wettability patterning of a surface is a passive method to manipulate the flow and heat transport mechanism in many physical processes and industrial applications. This paper proposes a rational wettability pattern comprised of multiple superhydrophilic wedges on a superhydrophobic background, which can continuously remove the impacted spray droplets from the horizontal surface. We observed that the spray droplets falling on the superhydrophilic wedge region spread and form a thin liquid film, which is passively transported away from the surface. However, most of the droplets falling on the superhydrophobic region move towards the wedge without any flooding. The physics of the passive transport of the liquid film on a wedge is also delved into using numerical modelling. In particular, we elucidate the different modes of droplet transport in the superhydrophobic region and the interaction of multiple droplets. The observed droplet dynamics could have profound implications in spray cooling systems and passive removal of liquid from a horizontal surface. This study’s findings will be beneficial for the optimization of efficient wettability patterned surfaces for spray cooling application.
The Devil’s Music: Satanism and Christian Rhetoric in the Lyrics of the Swedish Heavy Metal Band Ghost
Authors: Paulissen P.C.J.M. (Jarell)
Published: March 2021

This paper is an inquiry into a contemporary heavy metal band from Sweden called Ghost. Ghost released its first studio album in 2010 and, while there is some discussion as to what their genre is exactly, they immediately became a rising star in the metal scene. Yet what is of particular interest from a storytelling point of view, especially with regard to theological answers to philosophical questions in popular culture, is that the band presents itself as a satanic version of the Catholic Church through their stage act and lyrics. This made me curious whether they are trying to convey a message and, if yes, what that message might be. For the present paper, I have focused on the latter by performing a non-exhaustive textual analysis of the lyrics in a selection of songs from each of the four studio albums released so far. Ghost turns Christian liturgy on its head by utilizing devout language that is normally reserved for God and Christ to describe Satan and the Antichrist, a strategy I have called the ”satanification” of Christian doctrine, and in doing so their songs evoke imagery of a satanic faith community at prayer. The band then uses this radical inversion of traditional Christian themes to criticize certain elements of society, especially those aspects they associate with organized religion.
Industrial Robot Trajectory Tracking Control Using Multi-Layer Neural Networks Trained by Iterative Learning Control
Authors: Chen Shuyang , Wen John T.
Published: March 2021

Fast and precise robot motion is needed in many industrial applications. Most industrial robot motion controllers allow externally commanded motion profiles, but the trajectory tracking performance is affected by the robot dynamics and joint servo controllers, to which users have no direct access and about which they have little information. The performance is further compromised by time delays in transmitting the external command as a setpoint to the inner control loop. This paper presents an approach for combining neural networks and iterative learning controls to improve the trajectory tracking performance for a multi-axis articulated industrial robot. For a given desired trajectory, the external command is iteratively refined using a high-fidelity dynamical simulator to compensate for the robot inner-loop dynamics. These desired trajectories and the corresponding refined input trajectories are then used to train multi-layer neural networks to emulate the dynamical inverse of the nonlinear inner-loop dynamics. We show that with a sufficiently rich training set, the trained neural networks generalize well to trajectories beyond the training set as tested in the simulator. In applying the trained neural networks to a physical robot, the tracking performance still improves but not as much as in the simulator. We show that transfer learning effectively bridges the gap between simulation and the physical robot. Finally, we test the trained neural networks on other robot models in simulation and demonstrate the possibility of a general purpose network. Development and evaluation of this methodology are based on the ABB IRB6640-180 industrial robot and ABB RobotStudio software packages.
A Novel Method Based on Headspace-Ion Mobility Spectrometry for the Detection and Discrimination of Different Petroleum Derived Products in Seawater
Authors: Jaén-González Lucas , Aliaño-González Ma José , Ferreiro-González Marta , Barbero Gerardo F. , Palma Miguel
Published: March 2021

The objective of the present study is to develop an optimized method where headspace-ion mobility spectrometry is applied for the detection and discrimination between four petroleum-derived products (PDPs) in water. A Box–Behnken design with a response surface methodology was used, and five variables (incubation temperature, incubation time, agitation, sample volume, and injection volume) with influences on the ion mobility spectrometry (IMS) response were optimized. An IMS detector was used as a multiple sensor device, in which, each drift time acts as a specific sensor. In this way, the total intensity at each drift time is equivalent to multiple sensor signals. According to our results, 2.5 mL of sample incubated for 5 min at 31 °C, agitated at 750 rpm, and with an injection volume of 0.91 mL were the optimal conditions for successful detection and discrimination of the PDPs. The developed method has exhibited good intermediate precision and repeatability with a coefficient of variation lower than 5%, (RSD (Relative Standard Deviation): 2.35% and 3.09%, respectively). Subsequently, the method was applied in the context of the detection and discrimination of petroleum-derived products added to water samples at low concentration levels (2 µL·L−1). Finally, the new method was applied to determine the presence of petroleum-derived products in seawater samples.
Interpretable Detection of Partial Discharge in Power Lines with Deep Learning
Authors: Michau Gabriel , Hsu Chi-Ching , Fink Olga
Published: March 2021

Partial discharge (PD) is a common indication of faults in power systems, such as generators and cables. These PDs can eventually result in costly repairs and substantial power outages. PD detection traditionally relies on hand-crafted features and domain expertise to identify very specific pulses in the electrical current, and the performance declines in the presence of noise or of superposed pulses. In this paper, we propose a novel end-to-end framework based on convolutional neural networks. The framework has two contributions: First, it does not require any feature extraction and enables robust PD detection. Second, we devise the pulse activation map. It provides interpretability of the results for the domain experts with the identification of the pulses that led to the detection of the PDs. The performance is evaluated on a public dataset for the detection of damaged power lines. An ablation study demonstrates the benefits of each part of the proposed framework.
Study of Spatial and Temporal Variations of Ionospheric Total Electron Content in Japan, during 2014–2019 and the 2016 Kumamoto Earthquake
Authors: Hu Tianyang , Yao Yibin , Kong Jian
Published: March 2021

There are a large number of excellent research cases in Global Navigation Satellite System (GNSS) positioning and disaster prediction in Japan region, where the simulation and prediction of total electron content (TEC) is a powerful research method. In this study, we used the data of the GNSS Earth Observation Network (GEONET) established by the Geographical Survey Institute of Japan (GSI) to compare the performance of two regional ionospheric models in Japan, in which the spherical cap harmonic (SCH) model has the best performance. In this paper, we investigated the spatial and temporal variations of ionospheric TEC in Japan and their relationship with latitude, longitude, seasons, and solar activity. The results show that the TEC in Japan increases as the latitude decreases, with the highest average TEC in spring and summer and the lowest in winter, and has a strong correlation with solar activity. In addition, the observation and analysis of ionospheric disturbances over Japan before the 2016 Kumamoto earthquake and geomagnetic storms showed that GNSS observing of ionospheric TEC seems to be very effective in forecasting natural disasters and monitoring space weather.
Error Prediction of Air Quality at Monitoring Stations Using Random Forest in a Total Error Framework
Authors: Lepioufle Jean-Marie , Marsteen Leif , Johnsrud Mona
Published: March 2021

Instead of a flag valid/non-valid usually proposed in the quality control (QC) processes of air quality (AQ), we proposed a method that predicts the p-value of each observation as a value between 0 and 1. We based our error predictions on three approaches: the one proposed by the Working Group on Guidance for the Demonstration of Equivalence (European Commission (2010)), the one proposed by Wager (Journal of MachineLearningResearch, 15, 1625–1651 (2014)) and the one proposed by Lu (Journal of MachineLearningResearch, 22, 1–41 (2021)). Total Error framework enables to differentiate the different errors: input, output, structural modeling and remnant. We thus theoretically described a one-site AQ prediction based on a multi-site network using Random Forest for regression in a Total Error framework. We demonstrated the methodology with a dataset of hourly nitrogen dioxide measured by a network of monitoring stations located in Oslo, Norway and implemented the error predictions for the three approaches. The results indicate that a simple one-site AQ prediction based on a multi-site network using Random Forest for regression provides moderate metrics for fixed stations. According to the diagnostic based on predictive qq-plot and among the three approaches used in this study, the approach proposed by Lu provides better error predictions. Furthermore, ensuring a high precision of the error prediction requires efforts on getting accurate input, output and prediction model and limiting our lack of knowledge about the “true” AQ phenomena. We put effort in quantifying each type of error involved in the error prediction to assess the error prediction model and further improving it in terms of performance and precision.
Motorway Measurement Campaign to Support R&D Activities in the Field of Automated Driving Technologies
Authors: Tihanyi Viktor , Tettamanti Tamás , Csonthó Mihály , Eichberger Arno , Ficzere Dániel , Gangel Kálmán , Hörmann Leander B. , Klaffenböck Maria A. , Knauder Christoph , Luley Patrick , Magosi Zoltán Ferenc , Magyar Gábor , Németh Huba , Reckenzaun Jakob , Remeli Viktor , Rövid András , Ruether Matthias , Solmaz Selim , Somogyi Zoltán , Soós Gábor , Szántay Dávid , Tomaschek Tamás Attila , Varga Pál , Vincze Zsolt , Wellershaus Christoph , Szalay Zsolt
Published: March 2021

A spectacular measurement campaign was carried out on a real-world motorway stretch of Hungary with the participation of international industrial and academic partners. The measurement resulted in vehicle based and infrastructure based sensor data that will be extremely useful for future automotive R&D activities due to the available ground truth for static and dynamic content. The aim of the measurement campaign was twofold. On the one hand, road geometry was mapped with high precision in order to build Ultra High Definition (UHD) map of the test road. On the other hand, the vehicles—equipped with differential Global Navigation Satellite Systems (GNSS) for ground truth localization—carried out special test scenarios while collecting detailed data using different sensors. All of the test runs were recorded by both vehicles and infrastructure. The paper also showcases application examples to demonstrate the viability of the collected data having access to the ground truth labeling. This data set may support a large variety of solutions, for the test and validation of different kinds of approaches and techniques. As a complementary task, the available 5G network was monitored and tested under different radio conditions to investigate the latency results for different measurement scenarios. A part of the measured data has been shared openly, such that interested automotive and academic parties may use it for their own purposes.
A Novel Upsampling and Context Convolution for Image Semantic Segmentation
Authors: Sediqi Khwaja Monib , Lee Hyo Jong
Published: March 2021

Semantic segmentation, which refers to pixel-wise classification of an image, is a fundamental topic in computer vision owing to its growing importance in the robot vision and autonomous driving sectors. It provides rich information about objects in the scene such as object boundary, category, and location. Recent methods for semantic segmentation often employ an encoder-decoder structure using deep convolutional neural networks. The encoder part extracts features of the image using several filters and pooling operations, whereas the decoder part gradually recovers the low-resolution feature maps of the encoder into a full input resolution feature map for pixel-wise prediction. However, the encoder-decoder variants for semantic segmentation suffer from severe spatial information loss, caused by pooling operations or stepwise convolutions, and does not consider the context in the scene. In this paper, we propose a novel dense upsampling convolution method based on a guided filter to effectively preserve the spatial information of the image in the network. We further propose a novel local context convolution method that not only covers larger-scale objects in the scene but covers them densely for precise object boundary delineation. Theoretical analyses and experimental results on several benchmark datasets verify the effectiveness of our method. Qualitatively, our approach delineates object boundaries at a level of accuracy that is beyond the current excellent methods. Quantitatively, we report a new record of 82.86% and 81.62% of pixel accuracy on ADE20K and Pascal-Context benchmark datasets, respectively. In comparison with the state-of-the-art methods, the proposed method offers promising improvements.
Performance Evaluation of the Highway Radar Occupancy Grid
Authors: Porębski Jakub , Kogut Krzysztof
Published: March 2021

The quality of environmental perception is crucial for automated vehicle capabilities. In order to ensure the required accuracy, the occupancy grid mapping algorithm is often utilised to fuse data from multiple sensors. This paper focuses on the radar-based occupancy grid for highway applications and describes how to measure effectively the quality of the occupancy map. The evaluation was performed using the novel grid pole-like object analysis method. The proposed assessment is versatile and can be applied without detailed ground truth information. The evaluation was tested with a simulation and real vehicle experiments on the highway.
SlideAugment: A Simple Data Processing Method to Enhance Human Activity Recognition Accuracy Based on WiFi
Authors: Li Junyan , Yin Kang , Tang Chengpei
Published: March 2021

Currently, there are various works presented in the literature regarding the activity recognition based on WiFi. We observe that existing public data sets do not have enough data. In this work, we present a data augmentation method called window slicing. By slicing the original data, we get multiple samples for one raw datum. As a result, the size of the data set can be increased. On the basis of the experiments performed on a public data set and our collected data set, we observe that the proposed method assists in improving the results. It is notable that, on the public data set, the activity recognition accuracy improves from 88.13% to 97.12%. Similarly, the recognition accuracy is also improved for the data set collected in this work. Although the proposed method is simple, it effectively enhances the recognition accuracy. It is a general channel state information (CSI) data augmentation method. In addition, the proposed method demonstrates good interpretability.
Biomimicking Covert Communication by Time-Frequency Shift Modulation for Increasing Mimicking and BER Performances
Authors: Ahn Jongmin , Lee Hojun , Kim Yongcheol , Kim Wanjin , Chung Jaehak
Published: March 2021

Underwater acoustic (UWA) biomimicking communications have been developed for covert communications. For the UWA covert communications, it is difficult to achieve the bit error rate (BER) and the degree of mimic (DoM) performances at the same time. This paper proposes a biomimicking covert communication method to increase both BER and DoM (degree of mimic) performances based on the Time Frequency Shift Keying (TFSK). To increase DoM and BER performances, the orthogonality requirements of the time- and frequency-shifting units of the TFSK are theoretically derived, and the whistles are multiplied by the sequence with a large correlation. Two-step DoM assessments are also developed for the long-term whistle signals. Computer simulations and practical lake and ocean experiments demonstrate that the proposed method increases the DoM by 35% and attains a zero BER at −6 dB of Signal to Noise Ratio (SNR).
Accurate Imputation of Greenhouse Environment Data for Data Integrity Utilizing Two-Dimensional Convolutional Neural Networks
Authors: Moon Taewon , Lee Joon Woo , Son Jung Eek
Published: March 2021

Greenhouses require accurate and reliable data to interpret the microclimate and maximize resource use efficiency. However, greenhouse conditions are harsh for electrical sensors collecting environmental data. Convolutional neural networks (ConvNets) enable complex interpretation by multiplying the input data. The objective of this study was to impute missing tabular data collected from several greenhouses using a ConvNet architecture called U-Net. Various data-loss conditions with errors in individual sensors and in all sensors were assumed. The U-Net with a screen size of 50 exhibited the highest coefficient of determination values and the lowest root-mean-square errors for all environmental factors used in this study. U-Net50 correctly learned the changing patterns of the greenhouse environment from the training dataset. Therefore, the U-Net architecture can be used for the imputation of tabular data in greenhouses if the model is correctly trained. Growers can secure data integrity with imputed data, which could increase crop productivity and quality in greenhouses.
A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling
Authors: Farouq Muhamed Wael , Boulila Wadii , Hussain Zain , Rashid Asrar , Shah Moiz , Hussain Sajid , Ng Nathan , Ng Dominic , Hanif Haris , Shaikh Mohamad Guftar , Sheikh Aziz , Hussain Amir
Published: March 2021

Machine learning (ML)-based algorithms are playing an important role in cancer diagnosis and are increasingly being used to aid clinical decision-making. However, these commonly operate as ‘black boxes’ and it is unclear how decisions are derived. Recently, techniques have been applied to help us understand how specific ML models work and explain the rational for outputs. This study aims to determine why a given type of cancer has a certain phenotypic characteristic. Cancer results in cellular dysregulation and a thorough consideration of cancer regulators is required. This would increase our understanding of the nature of the disease and help discover more effective diagnostic, prognostic, and treatment methods for a variety of cancer types and stages. Our study proposes a novel explainable analysis of potential biomarkers denoting tumorigenesis in non-small cell lung cancer. A number of these biomarkers are known to appear following various treatment pathways. An enhanced analysis is enabled through a novel mathematical formulation for the regulators of mRNA, the regulators of ncRNA, and the coupled mRNA–ncRNA regulators. Temporal gene expression profiles are approximated in a two-dimensional spatial domain for the transition states before converging to the stationary state, using a system comprised of coupled-reaction partial differential equations. Simulation experiments demonstrate that the proposed mathematical gene-expression profile represents a best fit for the population abundance of these oncogenes. In future, our proposed solution can lead to the development of alternative interpretable approaches, through the application of ML models to discover unknown dynamics in gene regulatory systems.
Passive Source Localization Using Acoustic Intensity in Multipath-Dominant Shallow-Water Waveguide
Authors: Kim Sunhyo , Cho Sungho , Jung Seom-kyu , Choi Jee Woong
Published: March 2021

The array invariant technique has been recently proposed for passive source localization in the ocean. It has successfully estimated the source–receiver horizontal range in multipath-dominant shallow-water waveguides. However, it requires a relatively large-scale hydrophone array. This study proposes an array invariant method that uses acoustic intensity, which is a vector quantity that has the same direction as the sound wave propagating through a water medium. This method can be used to estimate not only the source–receiver horizontal range, but also the azimuth to an acoustic source. The feasibility of using a vector quantity for the array invariant method is examined through a simulation and an acoustic experiment in which particle velocity signals are obtained using a finite difference approximation of the pressure signals at two adjacent points. The source localization results estimated using acoustic intensity are compared with those obtained from beamforming of the acoustic signals acquired by the vertical line array.
Analysis of the Ordinary and Extraordinary Ionospheric Modes for NVIS Digital Communications Channels
Authors: Male Jordi , Porte Joaquim , Gonzalez Tomas , Maso Josep M. , Pijoan Joan L. , Badia David
Published: March 2021

Sensor networks have become more popular in recent years, now featuring plenty of options and capabilities. Notwithstanding this, remote locations present many difficulties for their study and monitoring. High-frequency (HF) communications are presented as an alternative to satellite communications, being a low-cost and easy-to-deploy solution. Near vertical incidence skywave (NVIS) technology provides a coverage of approximately 250 km (depending on the frequency being used and the ionospheric conditions) without a line of sight using the ionosphere as a communication channel. This paper centers on the study of the ionosphere and its characteristic waves as two independent channels in order to improve any NVIS link, increasing its robustness or decreasing the size of the node antennas through the appliance of specific techniques. We studied the channel sounding of both the ordinary and extraordinary waves and their respective channels, analyzing parameters such as the delay spread and the channel’s availability for each wave. The frequency instability of the hardware used was also measured. Furthermore, the correlation coefficient of the impulse response between both signals was studied. Finally, we applied polarization diversity and two different combining techniques. These measurements were performed on a single frequency link, tuned to 5.4 MHz. An improvement on the mean bit energy-to-noise power spectral density (Eb/N0) was received and the bit error rate (BER) was achieved. The results obtained showed that the extraordinary mode had a higher availability throughout the day (15% more availability), but a delayed spread (approximately 0.3 ms mean value), similar to those of the ordinary wave. Furthermore, an improvement of up to 4 dB was achieved with the usage of polarization diversity, thus reducing transmission errors.
Insight into the Organizational Culture and Challenges Faced by Women STEM Leaders in Africa
Authors: Babalola Olubukola Oluranti , du Plessis Yvonne , Babalola Sunday Samson
Published: March 2021

Compared to their men counterparts, women do not rapidly climb up the leadership ladder due to a glass ceiling obstacle. This study aims to explore the inhibiting factors demotivating Africa women’s leadership pursuit in Science, Technology, Engineering, and Mathematics (STEM). A qualitative approach was adopted using online open-ended questions to seek narratives from African women leaders on their roles and experiences of a STEM career. Data were collected using a non-probability, purposive sample of African women leaders in STEM in African research institutes and universities. Forty-two women in leadership positions in 12 African countries participated in the study, which was content analyzed, seeking patterns and themes to explore the narratives. A common thread exists in the tone and life experiences of the African women leaders in STEM. Scholarship, supportive organizational structure, commitment, hard work, and tenacity were all experienced as enablers of the career path process and their attained positions. The education level contributed to a strong leadership position. Women experience less acceptance than males in STEM leadership as the organizational culture still devalues women in leadership positions in several African countries. The study’s contribution, limitations, recommendations, and managerial implications are discussed, with suggestions for further research are made.
Urban Child Labor in Bangladesh: Determinants and Its Possible Impacts on Health and Education
Authors: Ahad Md Abdul , Chowdhury Mitu , Parry Yvonne K. , Willis Eileen
Published: March 2021

(1) Background: A significant proportion of child laborers are compelled to work in exploitative environments, and experience both deteriorating health and financial loss. The present study sought to determine the factors affecting child labor and the characteristics of their working environment. (2) Methods: A questionnaire survey was conducted with 80 child laborers aged 5 to 17 years. Alongside descriptive statistics, a newly devised technique known as the Influencing Causes Index (ICI) was administered and tested. (3) Results: The demographic findings reveal that most child laborers are young children (12–14 years) and 32.5% of child laborers have never attended school. The thorough assessment of determinants reflects that not only poverty but schooling expenses and a lack of access to opportunities in primary schools are also the top-ranked push factors to trigger children towards labor. Around 72.5% of children work for over 8 h a day. A significant proportion of participants received no leave, training, or access to hygiene facilities. The existing pattern of employment and working conditions resulted in musculoskeletal pain and dermatological infections among child laborers (p < 0.05). (4) Conclusions: This research suggests that income measures for households and an education program for both children and parents would expedite the abolition of child labor.
Noncontact and Full-Field Measurement of Residual and Thermal Stress in Film/Substrate Structures
Authors: Yang Dong , Zhang Xumeng , Zhu Jianguo
Published: March 2021

Residual stress and thermal stress of a film/substrate system are determined based on the curvature measurement with a 3D digital image correlation method (DIC) and calculation of the thin-film stresses by the extension of Stoney’s formula. A Ni film electroplated on a H62Cu plate is used to verify the proposed method. The full fields of nonuniform thin-film stresses are obtained in a room temperature to high-temperature environment of 200 °C, which can be potentially extended to higher temperatures. These results provide a fundamental approach to understanding thin-film stresses and a feasible measurement method for high temperature.
Presentation of SARS-CoV-2 in a Pediatric Heart Transplant Recipient with Multiple Underlying Comorbidities
Authors: Das Bibhuti
Published: March 2021

A six-year-old heart transplant recipient with additional significant co-morbidities, including severe hypoxic-ischemic injury, gastrostomy, tracheostomy, and mechanical ventilation dependency, encountered SARS-CoV-2 infection. The patient received tacrolimus and mycophenolate to prevent graft rejection, presented initially with SARS-CoV-2 positive and presumed pseudomonas aeruginosa pneumonia. Twenty-three days later, the patient presented with fever recurrence with evidence for systemic inflammation, which resolved rapidly with high-dose methylprednisolone. Interestingly, while IgM to SARS-CoV-2 was present, IgG was not detected even three months after his first positive test for SARS-CoV-2. The author discusses potential immune mechanisms that might have affected the course of multi-system inflammatory syndrome children (MIS-C) in this patient.
Zika E Glycan Loop Region and Guillain–Barré Syndrome-Related Proteins: A Possible Molecular Mimicry to Be Taken in Account for Vaccine Development
Authors: Lebeau Grégorie , Frumence Etienne , Turpin Jonathan , Begue Floran , Hoarau Jean-Jacques , Gadea Gilles , Krejbich-Trotot Pascale , Desprès Philippe , Viranaicken Wildriss
Published: March 2021

The neurological complications of infection by the mosquito-borne Zika virus (ZIKV) include Guillain–Barré syndrome (GBS), an acute inflammatory demyelinating polyneuritis. GBS was first associated with recent ZIKV epidemics caused by the emergence of the ZIKV Asian lineage in South Pacific. Here, we hypothesize that ZIKV-associated GBS relates to a molecular mimicry between viral envelope E (E) protein and neural proteins involved in GBS. The analysis of the ZIKV epidemic strains showed that the glycan loop (GL) region of the E protein includes an IVNDT motif which is conserved in voltage-dependent L-type calcium channel subunit alpha-1C (Cav1.2) and Heat Shock 70 kDa protein 12A (HSP70 12A). Both VSCC-alpha 1C and HSP70 12A belong to protein families which have been associated with neurological autoimmune diseases in central nervous system. The purpose of our in silico analysis is to point out that IVNDT motif of ZIKV E-GL region should be taken in consideration for the development of safe and effective anti-Zika vaccines by precluding the possibility of adverse neurologic events including autoimmune diseases such as GBS through a potent mimicry with Heat Shock 70 kDa protein 12A (HSP70 12A).
Perception of COVID-19 Vaccination Amongst Physicians in Colombia
Authors: Alvarado-Socarras Jorge L. , Vesga-Varela Andrea Liliana , Quintero-Lesmes Doris Cristina , Fama-Pereira Marcela M. , Serrano-Diaz Norma C. , Vasco Mauricio , Carballo-Zarate Virgil , Zambrano Lysien I. , Paniz-Mondolfi Alberto , Rodriguez-Morales Alfonso J.
Published: March 2021

Introduction: The SARS-CoV-2/COVID-19 pandemic has triggered the need to develop rapidly effective and safe vaccines to prevent infection, particularly in those at-risk populations such as medical personnel. This study’s objective was to assess the perception of COVID-19 vaccination amongst Colombian physicians featuring two different scenarios of COVID-19 vaccination. Methods: A cross-sectional analytical study was carried out through an online survey directed at medical staff in several cities in Colombia. The percentage of physicians who have a positive perception to be vaccinated and the associated factors that determine that decision were determined. A binomial regression analysis adjusted for age and sex was carried out, taking as a dependent variable the acceptance of free vaccination with an effectiveness of 60 and 80%. The most significant factors were determined in the non-acceptance of vaccination. Results: Between 77.0% and 90.7% of physicians in Colombia accept COVID-19 vaccination, according to the scenario evaluated where the vaccine’s effectiveness was 60 or 80%, respectively. Medical specialty, having never paid for a vaccine, recommending the administration of the vaccine to their parents or people over 70 years, and dispensing the vaccine to their children, were the factors to consider to be vaccinated for free with an effectiveness of 60% and 80%. Conclusions: There is a high perception of the intention to vaccinate physicians in Colombia against COVID-19, and this is very similar to that of the general population.
Factors Associated with Post-Transplant Active Epstein-Barr Virus Infection and Lymphoproliferative Disease in Hematopoietic Stem Cell Transplant Recipients: A Systematic Review and Meta-Analysis
Authors: Enok Bonong Pascal Roland , Zahreddine Monica , Buteau Chantal , Duval Michel , Laporte Louise , Lacroix Jacques , Alfieri Caroline , Trottier Helen
Published: March 2021

This systematic review was undertaken to identify risk factors associated with post-transplant Epstein–Barr virus (EBV) active infection and post-transplant lymphoproliferative disease (PTLD) in pediatric and adult recipients of hematopoietic stem cell transplants (HSCT). A literature search was conducted in PubMed and EMBASE to identify studies published until 30 June 2020. Descriptive information was extracted for each individual study, and data were compiled for individual risk factors, including, when possible, relative risks with 95% confidence intervals and/or p-values. Meta-analyses were planned when possible. The methodological quality and potential for bias of included studies were also evaluated. Of the 3362 titles retrieved, 77 were included (62 for EBV infection and 22 for PTLD). The overall quality of the studies was strong. Several risk factors were explored in these studies, but few statistically significant associations were identified. The use of anti-thymocyte globulin (ATG) was identified as the most important risk factor positively associated with post-transplant active EBV infection and with PTLD. The pooled relative risks obtained using the random-effect model were 5.26 (95% CI: 2.92–9.45) and 4.17 (95% CI: 2.61–6.68) for the association between ATG and post-transplant EBV infection and PTLD, respectively. Other risk factors for EBV and PTLD were found in the included studies, such as graft-versus-host disease, type of conditioning regimen or type of donor, but results are conflicting. In conclusion, the results of this systematic review indicate that ATG increases the risk of EBV infection and PTLD, but the link with all other factors is either nonexistent or much less convincing.
The Impact of a Single Educational Lecture on the Vaccine Confidence among Pregnant Women and Young Mothers
Authors: Tkaczyszyn Katarzyna , Kuchar Ernest , Augustynowicz Ewa , Szenborn Leszek
Published: March 2021

Background: We investigated the impact of a single unstructured educational lecture about vaccinations on the vaccine confidence in volunteer participants. Methods: We conducted a survey-based study during a series of open meetings related to pregnancy and parenting. Before and after the pediatrician’s lecture related to vaccinations, listeners completed the visual analogue scales (VAS, 0–15 cm), evaluating (1) self-declared knowledge on vaccinations and (2) how they perceive the safety and efficacy of this preventive method. Results: In total, 484 women aged 30 ± 4 years participated in the lecture (pregnant = 68%; ≥1 children = 56%). Participants declared to have more comprehensive knowledge on preventive vaccinations and perceived vaccines to be safer and more useful (the role for the immunity) after vs. before the lecture (median VAS: 10.4 vs. 7.2, 10.8 vs. 8.7, and 11.0 vs. 10.4 cm, all p < 0.001). Importantly, the prevalence of vaccine-related adverse events was also assessed as being higher after the lecture (median VAS: 9.9 vs. 8.0 cm, p < 0.001). The increase in self-declared knowledge on vaccinations and perceived need for vaccinations (delta VAS—VAS after minus before the lecture, expressed as % of baseline) was lower among participants who rated the lecture less vs. more useful. Importantly, both participants who liked vs. did not like the lecture comparably rated vaccines safer after vs. before the lecture (delta VAS (median, interquartile range): 16% (0–39%) vs. 18% (2–42%), p = 0.39). Conclusions: An educational lecture on vaccinations positively impacts vaccine confidence in young adult women. Irrespective of the subjective rating of the lecture, all listeners perceived vaccinations to be safer after vs. before the speech.
Mechanisms of Hepatitis C Virus Escape from Vaccine-Relevant Neutralizing Antibodies
Authors: Velázquez-Moctezuma Rodrigo , Augestad Elias H. , Castelli Matteo , Holmboe Olesen Christina , Clementi Nicola , Clementi Massimo , Mancini Nicasio , Prentoe Jannick
Published: March 2021

Hepatitis C virus (HCV) is a major causative agent of acute and chronic hepatitis. It is estimated that 400,000 people die every year from chronic HCV infection, mostly from severe liver-related diseases such as cirrhosis and liver cancer. Although HCV was discovered more than 30 years ago, an efficient prophylactic vaccine is still missing. The HCV glycoprotein complex, E1/E2, is the principal target of neutralizing antibodies (NAbs) and, thus, is an attractive antigen for B-cell vaccine design. However, the high genetic variability of the virus necessitates the identification of conserved epitopes. Moreover, the high intrinsic mutational capacity of HCV allows the virus to continually escape broadly NAbs (bNAbs), which is likely to cause issues with vaccine-resistant variants. Several studies have assessed the barrier-to-resistance of vaccine-relevant bNAbs in vivo and in vitro. Interestingly, recent studies have suggested that escape substitutions can confer antibody resistance not only by direct modification of the epitope but indirectly through allosteric effects, which can be grouped based on the breadth of these effects on antibody susceptibility. In this review, we summarize the current understanding of HCV-specific NAbs, with a special focus on vaccine-relevant bNAbs and their targets. We highlight antibody escape studies pointing out the different methodologies and the escape mutations identified thus far. Finally, we analyze the antibody escape mechanisms of envelope protein escape substitutions and polymorphisms according to the most recent evidence in the HCV field. The accumulated knowledge in identifying bNAb epitopes as well as assessing barriers to resistance and elucidating relevant escape mechanisms may prove critical in the successful development of an HCV B-cell vaccine.
COVID-19 Vaccination Willingness among Chinese Adults under the Free Vaccination Policy
Authors: Liu Rugang , Zhang Yuxun , Nicholas Stephen , Leng Anli , Maitland Elizabeth , Wang Jian
Published: March 2021

(1) Background: China will provide free coronavirus disease 2019 (COVID-19) vaccinations for the entire population. This study analyzed the COVID-19 vaccination willingness rate (VWR) and its determinants under China’s free vaccination policy compared to a paid vaccine. (2) Methods: Data on 2377 respondents were collected through a nationwide questionnaire survey. Multivariate ordered logistic regression models were specified to explore the correlation between the VWR and its determinants. (3) Results: China’s free vaccination policy for COVID-19 increased the VWR from 73.62% to 82.25% of the respondents. Concerns about the safety and side-effects were the primary reason for participants’ unwillingness to be vaccinated against COVID-19. Age, medical insurance and vaccine safety were significant determinants of the COVID-19 VWR for both the paid and free vaccine. Income, occupation and vaccine effectiveness were significant determinants of the COVID-19 VWR for the free vaccine. (4) Conclusions: Free vaccinations increased the COVID-19 VWR significantly. People over the age of 58 and without medical insurance should be treated as the target intervention population for improving the COVID-19 VWR. Contrary to previous research, high-income groups and professional workers should be intervention targets to improve the COVID-19 VWR. Strengthening nationwide publicity and education on COVID-19 vaccine safety and effectiveness are recommended policies for decision-makers.
Low Seroprevalence of Measles-Specific IgG in Children of Three Ethnic Groups from Mexico: Influence of Age, Sex, Malnutrition and Family Size
Authors: Sánchez-Alemán Miguel A. , Gutiérrez-Pérez Ilse A. , Díaz-Salgado Nayeli , Zaragoza-García Oscar , Olamendi-Portugal María , Castro-Alarcón Natividad , Parra-Rojas Isela , Guzmán-Guzmán Iris P.
Published: March 2021

Background: The reemergence of measles represents a public health problem. The aim of the study was to determine the seroprevalence of IgG antibodies against measles in children of three ethnic groups in southern Mexico and the nutritional status and demographic risk factors associated. Methods: A cross-sectional study in 416 school-age children, 207 belonging to the Tlapaneco ethnic group, 101 to the Mixteco group and 108 were considered Mestizo. Sociodemographic data were collected, an anthropometric evaluation of the children was performed and a fasting blood sample was obtained from each child for the measurement of measles IgG antibodies by Enzyme-Linked Immunosorbent Assay (ELISA). Results: From the total sample, 59% of the children were seropositive for IgG antibodies against measles; in contrast, 41% lacked IgG antibodies. Measles antibody seropositivity was higher in girls (64%). 90.5% of 6-year-old children had higher antibodies seroprevalence, compared to the children between 10 and 13 years old (45.5%). In the three ethnic groups, age was negatively correlated with the index standard ratio (ISR) of measles antibody levels and the families with ≥8 members showed less seropositivity. According to the antibodies levels, most of the positive cases remained around 1 Standard Deviation (SD) of the ISR values and no underweight children had antibody levels above 2 SD. Conclusions: The Anti-Measles serological coverage is low in children of three ethnic groups from Southern Mexico and the age, sex, malnutrition and family size are associated factors. Therefore, it is important to strengthen immunization campaigns, principally in vulnerable groups.