bluuebunny/crossref_metadata_2025 huggingface dataset:
Temperature Effect of Water Coagulation Bath on Chitin Fiber Prepared through Wet-Spinning Process
Authors: Nguyen Khoa Dang
Published: June 2021

Chitin was chemically extracted from crab shell waste and dissolved in N,N-dimethyl acetamine/5% lithium chloride (DMAc/5% LiCl) at room temperature to obtain 1% and 2% concentrations of chitin solution. Chitin fibers were prepared by phase inversion at different temperatures of water coagulation bath at 5, 20, and 60 °C. The deconvolution of FTIR spectra indicated that the area portion of the intermolecular hydrogen bonding NH…OC increased at 60 °C due to the higher density of the chitin segment in the fiber. As a result, scanning electron microscope (SEM) measurement suggests that a denser structure of the chitin fiber was observed when the temperature of the coagulation bath increased. In addition, the resultant chitin fibers generated better mechanical properties relative to the amount of chitin concentration and temperature. At 2% of chitin solution, the tensile strength significantly increased from 80 to 182 MPa for the fiber obtained at temperatures of 5 and 60 °C of the water coagulation bath, respectively. Meanwhile, the water content in the fiber significantly decreased from 1101% to 335%. This green synthesis route has high potential for the fabrication of the fiber as future material of interest for biomedical application.
Effect of Counterions on the Interaction among Concentrated Spherical Polyelectrolyte Brushes
Authors: Wang Yunwei , Li Li , Wang Yiming , Yang Qingsong , Ye Zhishuang , Sun Liang , Yang Fan , Guo Xuhong
Published: June 2021

The effect of counterions on interactions among spherical polyelectrolyte brushes (SPBs) was systematically investigated by rheology, small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS). The SPB particles consist of a solid polystyrene (PS) core with a diameter of ca.100 nm and a chemically grafted poly-(acrylic acid) (PAA) brush layer. Metal ions of different valences (Na+, Mg2+ and Al3+) were used as counterions to study the interactions among concentrated SPBs. The so-called “structure factor peak” in SAXS, the “local ordered structure peak” in WAXS and rheological properties indicated the interactions among concentrated SPBs. Combining SAXS, WAXS and rheology, the formation mechanism of the local ordered structure among PAA chains in the overlapped area of adjacent SPB, which was generated due to the bridge function of counterions, was confirmed. In contrast, excessive counterions shielded the electrostatic interaction among PAA chains and destroyed the local ordered structure. This work enriches our understanding of the polyelectrolyte assembly in concentrated SPBs under the effect of counterions and lays the foundations for SPB applications.
Natural Fiber Reinforced Composite Material for Product Design: A Short Review
Authors: Azman M. A. , Asyraf M. R. M. , Khalina A. , Petrů Michal , Ruzaidi C. M. , Sapuan S. M. , Wan Nik W. B. , Ishak M. R. , Ilyas R. A. , Suriani M. J.
Published: June 2021

Natural fibers have attracted great attention from industrial players and researchers for the exploitation of polymer composites because of their “greener” nature and contribution to sustainable practice. Various industries have shifted toward sustainable technology in order to improve the balance between the environment and social and economic concerns. This manuscript aims to provide a brief review of the development of the foremost natural fiber-reinforced polymer composite (NFRPC) product designs and their applications. The first part of the manuscript presents a summary of the background of various natural fibers and their composites in the context of engineering applications. The behaviors of NFPCs vary with fiber type, source, and structure. Several drawbacks of NFPCs, e.g., higher water absorption rate, inferior fire resistance, and lower mechanical properties, have limited their applications. This has necessitated the development of good practice in systematic engineering design in order to attain optimized NRPC products. Product design and manufacturing engineering need to move in a mutually considerate manner in order to produce successful natural fiber-based composite material products. The design process involves concept design, material selection, and finally, the manufacturing of the design. Numerous products have been commercialized using natural fibers, e.g., sports equipment, musical instruments, and electronic products. In the end, this review provides a guideline for the product design process based on natural fibers, which subsequently leads to a sustainable design.
Rubbery-Modified CFRPs with Improved Mode I Fracture Toughness: Effect of Nanofibrous Mat Grammage and Positioning on Tanδ Behaviour
Authors: Maccaferri Emanuele , Mazzocchetti Laura , Benelli Tiziana , Brugo Tommaso Maria , Zucchelli Andrea , Giorgini Loris
Published: June 2021

Carbon Fiber Reinforced Polymers (CFRPs) are widely used where high mechanical performance and lightweight are required. However, they suffer from delamination and low damping, severely affecting laminate reliability during the service life of components. CFRP laminates modified by rubbery nanofibers interleaving is a recently introduced way to increase material damping and to improve delamination resistance. In this work, nitrile butadiene rubber/poly(ε-caprolactone) (NBR/PCL) blend rubbery nanofibrous mats with 60 wt% NBR were produced in three different mat grammages (5, 10 and 20 g/m2) via single-needle electrospinning and integrated into epoxy CFRP laminates. The investigation demonstrated that both mat grammage and positioning affect CFRP tanδ behaviour, evaluated by dynamic mechanical analysis (DMA) tests, as well as the number of nano-modified interleaves. Double cantilever beam (DCB) tests were carried out to assess the mat grammage effect on the interlaminar fracture toughness. Results show an outstanding improvement of GI,R for all the tested reinforced laminates regardless of the mat grammage (from +140% to +238%), while the effect on GI,C is more dependent on it (up to +140%). The obtained results disclose the great capability of NBR/PCL rubbery nanofibrous mats at improving CFRP damping and interlaminar fracture toughness. Moreover, CFRP damping can be tailored by choosing the number and positioning of the nano-modified interleaves, besides choosing the mat grammage.
Leakage-Flow Models for Screw Extruders
Authors: Marschik Christian , Roland Wolfgang , Dörner Marius , Steinbichler Georg , Schöppner Volker
Published: June 2021

Many theoretical analyses of extrusion ignore the effect of the flight clearance when predicting the pumping capability of a screw. This might be reasonable for conventional extruder screws with “normal” clearances but leads to errors when more advanced screw designs are considered. We present new leakage-flow models that allow the effect of the flight clearance to be included in the analysis of melt-conveying zones. Rather than directly correcting the drag and pressure flows, we derived regression models to predict locally the shear-thinning flow through the flight clearance. Using a hybrid modeling approach that includes analytical, numerical, and data-based modeling techniques enabled us to construct fast and accurate regressions for calculating flow rate and dissipation rate in the leakage gap. Using the novel regression models in combination with network theory, the new approximations consider the effect of the flight clearance in the predictions of pumping capability, power consumption and temperature development without modifying the equations for the down-channel flow. Unlike other approaches, our method is not limited to any specific screw designs or processing conditions.
A Method for Characterizing the Chemical Heterogeneity of Comb-Copolymers and Its Dependence on Synthesis Routes
Authors: Weckwerth Stefanie Anne , Radke Wolfgang , Flatt Robert J.
Published: June 2021

The heterogeneity in chemical structure of polymers is difficult to characterize and consequently remains an often-overlooked factor in mechanistic studies of functional polymers, as well as in their industrial scale optimization. In this study, we present a method to characterize chemical heterogeneity and apply it to illustrate how it can be affected differently in different synthesis routes. The polymers used are comb-copolymer dispersants used in particulate suspensions which are composed of a polycarboxylate backbone onto which PEG side chains are grafted. The largest use of these polymers concerns concrete, where they are referred to as poly(carboxylate ether) (PCE) superplasticizers and produced at a very large industrial scale. Apart from their practical relevance, PCEs provide a good test case for studying the means and benefits of characterizing chemical heterogeneity. Indeed, the simple addition of a UV detector to a traditional SEC setup with RI detection allowed us to monitor variations in the grafting ratio in dependence on the molecular size. We show that the synthesis pathway significantly impacts the chemical heterogeneity. The suggested method is versatile and can be adapted for a wide range of hydrophilic copolymers. Thus, we present a tool to comprehensively analyze the molecular heterogeneity of dispersants and give a deep insight into their chemical dispersity.
Chain Propagation Mechanism of Fischer–Tropsch Synthesis: Experimental Evidence by Aldehyde, Alcohol and Alkene Addition
Authors: Zhou Liping , Gao Junhu , Hao Xu , Yang Yong , Li Yongwang
Published: June 2021

Fischer–Tropsch synthesis (FTS) produces hundreds of hydrocarbons and oxygenates by simple reactants (CO + H2) and the detailed chain propagation mechanism is still in dispute. An industrial iron-based catalyst was used to further clarify the mechanism by adding aldehyde, alcohol and alkene species into a fixed-bed tubular reactor. The added species were investigated in H2 and syngas atmospheres, respectively. 1-alkene in the H2 atmosphere presented an obvious hydrogenolysis, in which the produced C1 species participated in C–C bond formation simultaneously. Co-feeding Cn alkene with syngas showed remarkable Cn+1 alcohol selectivity compared to the normal FTS reaction. In addition, the carbonyl group of aldehyde was extremely unstable over the iron-based catalyst and could easily be hydrogenated to an alcohol hydroxyl group, which could even undergo dehydration for hydrocarbon species formation. Experimental data confirmed that both heavier alkenes and alcohols added can be converted to chain growth intermediates and then undergo monomer insertion for chain propagation. These results provide strong evidence that the chain propagation in the FTS reaction is simultaneously controlled by the surface carbide mechanism and the CO insertion mechanism, with surface CHx species and CO as monomers, respectively. The study is of guiding significance for FTS mechanism understanding and kinetic modeling.
The Sovereignty of Humanity and Social Responsibility for Evil Prevention
Authors: Salamon Janusz
Published: June 2021

In this paper, I suggest that James Sterba’s recent restatement of the logical problem of evil overlooks a plausible theistic interpretation of the divine–human relation, which allows for a theodicy impervious to his atheological argument, which boils down to God’s failure to meet Sterba’s “Evil Prevention Requirements”. I argue that such requirements need not apply to God in a world under full human sovereignty, which presupposes that God never intervenes to change the natural course of events to prevent evils, as God has a decisive “greater good justification” for not intervening, namely respecting human sovereignty. This non-interventionist view of divine providence can be made tenable by the great good and dignity of the God-granted human God-like self-creativity implied by human sovereignty (a concept inspired by Giovanni Pico della Mirandola). The Mirandolian theodicy can both accommodate and complement Dostoyevsky’s Russian Orthodox view of “beneficial suffering”, predicated against the background of the conception of “collective selfhood”, overlooked by Sterba despite “featuring” on the cover of his book, no doubt due to his libertarian–individualistic assumptions about human agency and human flourishing, which a proponent of a theistic theodicy may do well to resist.
Be(com)ing a Christian Is Not a Social Identity: Kierkegaard and the Refusal of Social Roles
Authors: Djordjevic Charles
Published: June 2021

This paper examines aspects of Kierkegaard’s authorship in relation to contemporary identity politics. Specifically, it argues that several pseudonymous voices in Kierkegaard’s works and identity politics share the contention that ethics presupposes concrete practical identities in order to function. Given this, one conception of liberalism, predicated on procedural equality, is not viable. However, it also argues that other voices in Kierkegaard’s oeuvres press beyond identities and proffer a radically new way to make sense of differences and equality, one predicated on infinity.
Buddhist Healthcare in Philadelphia: An Ethnographic Experiment in Student-Centered, Engaged, and Inclusive Pedagogy
Authors: Salguero C. Pierce
Published: June 2021

This essay describes the Jivaka Project, a pedagogical experiment undertaken at a public liberal arts college outside of Philadelphia. A multi-year ethnographic survey of Buddhist healthcare in the greater metropolitan area, this project has come to constitute a major part of my general education course on American Buddhism. As I argue, this project serves as a model for student-centered, engaged, and inclusive approaches to pedagogy. It is particularly notable for centering the intercultural competency of international and first-generation Asian American students. I discuss how this project was inspired by a bilingual Chinese American student; how it developed into a large-scale effort involving about a hundred students in ethnographic research in Philadelphia’s Asian American neighborhoods; how it was a transformational educational experience for a diverse group of participating students; and how in the process it pushed my pedagogy in a more relevant and personally fulfilling direction.
Twitter in Marketing Practice of the Religious Media. An Empirical Study on Catholic Weeklies in Poland
Authors: Leonowicz-Bukała Iwona , Adamski Andrzej , Jupowicz-Ginalska Anna
Published: June 2021

This article presents the partial conclusion of the research project devoted to marketing activity of Polish Catholic opinion-forming weeklies on the social media platforms. The main aim of this article is to present the results of the study on the use of Twitter as a marketing tool by Polish nationwide Catholic opinion-forming weeklies. The basic research questions concerned the extent of utilizing the platform by the magazines’ editors to create and distribute the content of their media product, maintain and develop brand communication and self-promotion. The case studies and the content analysis of the accounts of the three magazines—Gość Niedzielny, Tygodnik Katolicki Niedziela and Przewodnik Katolicki—show that there are three different ways in how the editors of the magazines understand the role of the Twitter account of the title they represent—as an ‘active communicator’, ‘active communicator and community supporter’ or ‘community supporter’. The conclusions show that the studied media fairly efficiently use the visual and distributional potential of the platform as well as some of its features, at the same time missing the chance to build a brand-loyal community. They also limit the role of Twitter to that of a supplement for the main communication channel, which is the printed weekly and its website.
A Virtual Dialogue between Gandhi and Levinas
Authors: Meir Ephraim
Published: June 2021

Mahatma Gandhi and Emmanuel Levinas have much in common. They interpret religion in a radical ethical way and develop an ethical hermeneutics of religious sources. Levinas’s thoughts on a holy history, not to be confused with history, are comparable with Gandhi’s swaraj as the spiritual independence and self-transformation of India. Escaping war logics, they maintain a “beyond the state” in the state and insert ethics in politics. Yet, Gandhi’s ethico-politics works with radical interrelatedness, whereas Levinas differentiates more between the self and the other. Gandhi trusted that, in the end, the good would vanquish evil. Levinas, in turn, did not venture into the future: the present was under “eschatological judgment.” Gandhi’s love of the enemy and his attempt to soften the opponent’s heart are absent in Levinas’s metaphysics. In addition, Levinas does not radically deconstruct the term self-defense, although Gandhi notoriously made also exceptions to his ahimsa. A dialogue can be established between Levinas’s ethical metaphysics and Gandhi’s ahimsa and satyagraha. Both thinkers make a radical critique of a peace based on rational contracts and equate peace with universal brother- and sisterhood. Without underestimating the many similarities between Levinas and Gandhi, I also highlight their dissimilarities. I argue that precisely the differences between both thinkers allow for a “trans-different” dialogue, which respects specificities and promotes communication, in a movement of hospitality and mutual learning.
What Kind of Islamophobia? Representation of Muslims and Islam in Italian and Spanish Media
Authors: Cervi Laura , Tejedor Santiago , Gracia Monica
Published: June 2021

News media play a crucial role in the production and reproduction of stereotypes, influencing public opinions regarding different groups and minorities. Thus, acquiring a deeper understanding of media coverage of Muslims and Islam is decisive for understanding the sources of public attitudes towards Muslims. This study aims at displaying how Muslims and Islam are represented in Italian and Spanish media. Focusing on the online version of the two most influential newspapers in each country (El Mundo and El País for Spain and Il Corriere della Sera and La Repubblica for Italy) from 2015 to 2020, the results show how Muslims in both countries are mostly framed either related to terrorism or within the general discourse on immigration. In both cases, they are portrayed as “others”. The article also presents a novelty, defining and observing two different types of Islamophobia, Banal and Ontological Islamophobia.
A New Model Averaging Approach in Predicting Credit Risk Default
Authors: Jha Paritosh Navinchandra , Cucculelli Marco
Published: June 2021

The paper introduces a novel approach to ensemble modeling as a weighted model average technique. The proposed idea is prudent, simple to understand, and easy to implement compared to the Bayesian and frequentist approach. The paper provides both theoretical and empirical contributions for assessing credit risk (probability of default) effectively in a new way by creating an ensemble model as a weighted linear combination of machine learning models. The idea can be generalized to any classification problems in other domains where ensemble-type modeling is a subject of interest and is not limited to an unbalanced dataset or credit risk assessment. The results suggest a better forecasting performance compared to the single best well-known machine learning of parametric, non-parametric, and other ensemble models. The scope of our approach can be extended to any further improvement in estimating weights differently that may be beneficial to enhance the performance of the model average as a future research direction.
Forest Land Cover Mapping at a Regional Scale Using Multi-Temporal Sentinel-2 Imagery and RF Models
Authors: Alonso Laura , Picos Juan , Armesto Julia
Published: June 2021

Over the last several decades, thanks to improvements in and the diversification of open-access satellite imagery, land cover mapping techniques have evolved significantly. Notable changes in these techniques involve the automation of different steps, yielding promising results in terms of accuracy, class detection and efficiency. The most successful methodologies that have arisen rely on the use of multi-temporal data. Several different approaches have proven successful. In this study, one of the most recently developed methodologies is tested in the region of Galicia (in Northwestern Spain), with the aim of filling gaps in the mapping needs of the Galician forestry sector. The methodology mainly consists of performing a supervised classification of individual images from a selected time series and then combining them through aggregation using decision criteria. Several of the steps of the methodology can be addressed in multiple ways: pixel resolution selection, classification model building and aggregation methods. The effectiveness of these three tasks as well as some others are tested and evaluated and the most accurate and efficient parameters for the case study area are highlighted. The final land cover map that is obtained for Galicia has high accuracy metrics (an overall accuracy of 91.6%), which is in line with previous studies that have followed this methodology in other regions. This study has led to the development of an efficient open-access solution to support the mapping needs of the forestry sector.
Regional Ground Movement Detection by Analysis and Modeling PSI Observations
Authors: Mohammadivojdan Bahareh , Brockmeyer Marco , Jahn Cord-Hinrich , Neumann Ingo , Alkhatib Hamza
Published: June 2021

Any changes to the Earth’s surface should be monitored in order to maintain and update the spatial reference system. To establish a global model of ground movements for a large area, it is important to have consistent and reliable measurements. However, in dealing with mass data, outliers may occur and robust analysis of data is indispensable. In particular, this paper will analyse Synthetic Aperture Radar (SAR) data for detecting the regional ground movements (RGM) in the area of Hanover, Germany. The relevant data sets have been provided by the Federal Institute for Geo-sciences and Natural Resources (BGR) for the period of 2014 to 2018. In this paper, we propose a data adoptive outlier detection algorithm to preprocess the observations. The algorithm is tested with different reference data sets and as a binary classifier performs with 0.99 accuracy and obtains a 0.95 F1-score in detecting the outliers. The RGMs that are observed as height velocities are mathematically modeled as a surface based on a hierarchical B-splines (HB-splines) method. For the approximated surface, a 95% confidence interval is estimated based on a bootstrapping approach. In the end, the user is enabled to predict RGM at any point and is provided with a measure of quality for the prediction.
TomoSAR Mapping of 3D Forest Structure: Contributions of L-Band Configurations
Authors: Pardini Matteo , Cazcarra-Bes Victor , Papathanassiou Konstantinos P.
Published: June 2021

Synthetic Aperture Radar (SAR) measurements are unique for mapping forest 3D structure and its changes in time. Tomographic SAR (TomoSAR) configurations exploit this potential by reconstructing the 3D radar reflectivity. The frequency of the SAR measurements is one of the main parameters determining the information content of the reconstructed reflectivity in terms of penetration and sensitivity to the individual vegetation elements. This paper attempts to review and characterize the structural information content of L-band TomoSAR reflectivity reconstructions, and their potential to forest structure mapping. First, the challenges in the accurate TomoSAR reflectivity reconstruction of volume scatterers (which are expected to dominate at L-band) and to extract physical structure information from the reconstructed reflectivity is addressed. Then, the L-band penetration capability is directly evaluated by means of the estimation performance of the sub-canopy ground topography. The information content of the reconstructed reflectivity is then evaluated in terms of complementary structure indices. Finally, the dependency of the TomoSAR reconstruction and of its structural information to both the TomoSAR acquisition geometry and the temporal change of the reflectivity that may occur in the time between the TomoSAR measurements in repeat-pass or bistatic configurations is evaluated. The analysis is supported by experimental results obtained by processing airborne acquisitions performed over temperate forest sites close to the city of Traunstein in the south of Germany.
Tropospheric Correction of Sentinel-1 Synthetic Aperture Radar Interferograms Using a High-Resolution Weather Model Validated by GNSS Measurements
Authors: Roukounakis Nikolaos , Elias Panagiotis , Briole Pierre , Katsanos Dimitris , Kioutsioukis Ioannis , Argiriou Athanassios A. , Retalis Adrianos
Published: June 2021

Synthetic Aperture Radar Interferometry (InSAR) is a space geodetic technique used for mapping deformations of the Earth’s surface. It has been developed and used increasingly during the last thirty years to measure displacements produced by earthquakes, volcanic activity and other crustal deformations. A limiting factor to this technique is the effect of the troposphere, as spatial and temporal variations in temperature, pressure, and relative humidity introduce significant phase delays in the microwave imagery, thus “masking” surface displacements due to tectonic or other geophysical processes. The use of Numerical Weather Prediction (NWP) models as a tropospheric correction method in InSAR can tackle several of the problems faced with other correction techniques (such as timing, spatial coverage and data availability issues). High-resolution tropospheric modelling is particularly useful in the case of single interferograms, where the removal of the atmospheric phase screen (and especially the highly variable turbulent component) can reveal large-amplitude deformation signals (as in the case of an earthquake). In the western Gulf of Corinth, prominent topography makes the removal of both the stratified and turbulent atmospheric phase screens a challenging task. Here, we investigate the extent to which a high-resolution WRF 1-km re-analysis can produce detailed tropospheric delay maps of the required accuracy by coupling its output (in terms of Zenith Total Delay or ZTD) with the vertical delay component in GNSS measurements. The model is operated with varying physical parameterization in order to identify the best configuration, and validated with GNSS zenithal tropospheric delays, providing a benchmark of real atmospheric conditions. We correct sixteen Sentinel-1A interferograms with differential delay maps at the line-of-sight (LOS) produced by WRF re-analysis. In most cases, corrections lead to a decrease in the phase gradient, with average root-mean-square (RMS) and standard deviation (SD) reductions in the wrapped phase of 6.0% and 19.3%, respectively. Results suggest a high potential of the model to reproduce both the long-wavelength stratified atmospheric signal and the short-wave turbulent atmospheric component which are evident in the interferograms.
DeepIndices: Remote Sensing Indices Based on Approximation of Functions through Deep-Learning, Application to Uncalibrated Vegetation Images
Authors: Vayssade Jehan-Antoine , Paoli Jean-Noël , Gée Christelle , Jones Gawain
Published: June 2021

The form of a remote sensing index is generally empirically defined, whether by choosing specific reflectance bands, equation forms or its coefficients. These spectral indices are used as preprocessing stage before object detection/classification. But no study seems to search for the best form through function approximation in order to optimize the classification and/or segmentation. The objective of this study is to develop a method to find the optimal index, using a statistical approach by gradient descent on different forms of generic equations. From six wavebands images, five equations have been tested, namely: linear, linear ratio, polynomial, universal function approximator and dense morphological. Few techniques in signal processing and image analysis are also deployed within a deep-learning framework. Performances of standard indices and DeepIndices were evaluated using two metrics, the dice (similar to f1-score) and the mean intersection over union (mIoU) scores. The study focuses on a specific multispectral camera used in near-field acquisition of soil and vegetation surfaces. These DeepIndices are built and compared to 89 common vegetation indices using the same vegetation dataset and metrics. As an illustration the most used index for vegetation, NDVI (Normalized Difference Vegetation Indices) offers a mIoU score of 63.98% whereas our best models gives an analytic solution to reconstruct an index with a mIoU of 82.19%. This difference is significant enough to improve the segmentation and robustness of the index from various external factors, as well as the shape of detected elements.
Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset
Authors: Turk F. Joseph , Ringerud Sarah E. , Camplani Andrea , Casella Daniele , Chase Randy J. , Ebtehaj Ardeshir , Gong Jie , Kulie Mark , Liu Guosheng , Milani Lisa , Panegrossi Giulia , Padullés Ramon , Rysman Jean-François , Sanò Paolo , Vahedizade Sajad , Wood Norman B.
Published: June 2021

The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) (Ku- and Ka-band, or 14 and 35 GHz) provides the capability to resolve the precipitation structure under moderate to heavy precipitation conditions. In this manuscript, the use of near-coincident observations between GPM and the CloudSat Profiling Radar (CPR) (W-band, or 94 GHz) are demonstrated to extend the capability of representing light rain and cold-season precipitation from DPR and the GPM passive microwave constellation sensors. These unique triple-frequency data have opened up applications related to cold-season precipitation, ice microphysics, and light rainfall and surface emissivity effects.
Grouping and Sponsoring Centric Green Coverage Model for Internet of Things
Authors: Kumar Vinod , Kumar Sushil , AlShboul Rabah , Aggarwal Geetika , Kaiwartya Omprakash , Khasawneh Ahmad M. , Lloret Jaime , Al-Khasawneh Mahmoud Ahmad
Published: June 2021

Recently, green computing has received significant attention for Internet of Things (IoT) environments due to the growing computing demands under tiny sensor enabled smart services. The related literature on green computing majorly focuses on a cover set approach that works efficiently for target coverage, but it is not applicable in case of area coverage. In this paper, we present a new variant of a cover set approach called a grouping and sponsoring aware IoT framework (GS-IoT) that is suitable for area coverage. We achieve non-overlapping coverage for an entire sensing region employing sectorial sensing. Non-overlapping coverage not only guarantees a sufficiently good coverage in case of large number of sensors deployed randomly, but also maximizes the life span of the whole network with appropriate scheduling of sensors. A deployment model for distribution of sensors is developed to ensure a minimum threshold density of sensors in the sensing region. In particular, a fast converging grouping (FCG) algorithm is developed to group sensors in order to ensure minimal overlapping. A sponsoring aware sectorial coverage (SSC) algorithm is developed to set off redundant sensors and to balance the overall network energy consumption. GS-IoT framework effectively combines both the algorithms for smart services. The simulation experimental results attest to the benefit of the proposed framework as compared to the state-of-the-art techniques in terms of various metrics for smart IoT environments including rate of overlapping, response time, coverage, active sensors, and life span of the overall network.
Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection
Authors: Pu Han , Huang Tianqiang , Weng Bin , Ye Feng , Zhao Chenbin
Published: June 2021

Digital video forensics plays a vital role in judicial forensics, media reports, e-commerce, finance, and public security. Although many methods have been developed, there is currently no efficient solution to real-life videos with illumination noises and jitter noises. To solve this issue, we propose a detection method that adapts to brightness and jitter for video inter-frame forgery. For videos with severe brightness changes, we relax the brightness constancy constraint and adopt intensity normalization to propose a new optical flow algorithm. For videos with large jitter noises, we introduce motion entropy to detect the jitter and extract the stable feature of texture changes fraction for double-checking. Experimental results show that, compared with previous algorithms, the proposed method is more accurate and robust for videos with significant brightness variance or videos with heavy jitter on public benchmark datasets.
A Single-Trial P300 Detector Based on Symbolized EEG and Autoencoded-(1D)CNN to Improve ITR Performance in BCIs
Authors: De Venuto Daniela , Mezzina Giovanni
Published: June 2021

In this paper, we propose a breakthrough single-trial P300 detector that maximizes the information translate rate (ITR) of the brain–computer interface (BCI), keeping high recognition accuracy performance. The architecture, designed to improve the portability of the algorithm, demonstrated full implementability on a dedicated embedded platform. The proposed P300 detector is based on the combination of a novel pre-processing stage based on the EEG signals symbolization and an autoencoded convolutional neural network (CNN). The proposed system acquires data from only six EEG channels; thus, it treats them with a low-complexity preprocessing stage including baseline correction, windsorizing and symbolization. The symbolized EEG signals are then sent to an autoencoder model to emphasize those temporal features that can be meaningful for the following CNN stage. This latter consists of a seven-layer CNN, including a 1D convolutional layer and three dense ones. Two datasets have been analyzed to assess the algorithm performance: one from a P300 speller application in BCI competition III data and one from self-collected data during a fluid prototype car driving experiment. Experimental results on the P300 speller dataset showed that the proposed method achieves an average ITR (on two subjects) of 16.83 bits/min, outperforming by +5.75 bits/min the state-of-the-art for this parameter. Jointly with the speed increase, the recognition performance returned disruptive results in terms of the harmonic mean of precision and recall (F1-Score), which achieve 51.78 ± 6.24%. The same method used in the prototype car driving led to an ITR of ~33 bit/min with an F1-Score of 70.00% in a single-trial P300 detection context, allowing fluid usage of the BCI for driving purposes. The realized network has been validated on an STM32L4 microcontroller target, for complexity and implementation assessment. The implementation showed an overall resource occupation of 5.57% of the total available ROM, ~3% of the available RAM, requiring less than 3.5 ms to provide the classification outcome.
Recent Advances in Imaging Sensors and Applications
Authors: Yoon Changhan , Lee Changho
Published: June 2021

Recent advances in sensor technology have allowed us to develop many interesting applications and enhance the quality of human life [...]
Respiration Monitoring via Forcecardiography Sensors
Authors: Andreozzi Emilio , Centracchio Jessica , Punzo Vincenzo , Esposito Daniele , Polley Caitlin , Gargiulo Gaetano D. , Bifulco Paolo
Published: June 2021

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R2 = 0.98) vs. 0.98, 0.11 s (R2 = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.
Kin Ties and Market Integration in a Yucatec Mayan Village
Authors: Hackman Joseph V. , Kramer Karen L.
Published: June 2021

The importance of kin relationships varies with socioecological demands. Among subsistence agriculturalists, people commonly manage fluctuations in food availability by relying on family members to share resources and pool labor. However, the process of market integration may disrupt these support networks, which may begin to carry costs or liabilities in novel market environments. The current study aims to address (1) how kin are distributed in household support networks (2) how kin support varies as households become more engaged in market activities, and (3) how variation in kin support is associated with income disparities within a Yucatec Maya community undergoing rapid market integration. Using long-term census data combined with social networks and detailed household economic data, we find that household support networks are primarily composed of related households. Second, households engaged predominantly in wage labor rely less on kin support than agricultural or mixed economy households. Finally, kin support is associated with lower household net income and income per capita. Understanding how kin support systems shift over the course of market integration and in the face of new opportunities for social and economic production provides a unique window into the social and economic drivers of human family formation.
Agro-Livestock Farming System Sustainability during the COVID-19 Era: A Cross-Sectional Study on the Role of Information and Communication Technologies
Authors: Hashem Nesrein M. , Hassanein Eman M. , Hocquette Jean-François , Gonzalez-Bulnes Antonio , Ahmed Fayrouz A. , Attia Youssef A. , Asiry Khalid A.
Published: June 2021

In the near future, the year 2050, agricultural production should expand to fulfill the needs of approximately 9.7 billion inhabitants. Such an objective should be harmonized with social, economic, and environmental sustainability aspects to maintain safe food production and food security worldwide. For more than a year, the COVID-19 pandemic has raised and is still strongly disrupting the agro-livestock production sector, similar to several other economic sectors. In this sector, the relationships between suppliers, producers, and consumers should always continue to maintain the activity of the production chain, which are impaired by social distancing decisions taken following the emergence of the COVID-19 pandemic. In this study, a global cross-sectional survey (translated into four languages: Arabic, English, French, and Spanish) was shared with people belonging to the agricultural sector to identify: (1) the role of the agricultural information and communication technologies (ICTs) in agro-livestock farming systems sustainability during the period of COVID-19 pandemic, (2) the need for such technologies in the agricultural sector, and (3) the factors that affect the use of such technologies. The results showed that the most frequently used agricultural ICTs were social media (Facebook and/or WhatsApp; 27.3%) and online platforms and Internet services (26.3%), whereas robotic vehicles and/or drones (6.6%) were less frequently used. During the emergence of the pandemic, the major reasons impacting agro-livestock farming systems’ sustainability were social distancing (30.0%), shortage of labor (17.7%), maintaining precision farm management (14.8%), product marketing (14.2%), access production inputs (7.2%), and others (16.1%). Applying agricultural ICTs solved many obstacles related to the production process, such as maintaining precision farm management (25.6%), product marketing (23.6%), and access production inputs (16.1%). The subgroup analyses of the results considering the degree of country advancement, size of agribusinesses, and role/position of respondents in the farm highlighted the importance of supporting the use, availability, and awareness of agricultural ICTs at least for some groups of people such as those belong to developing countries, laborers, and small-scale agri-business holders. This cross-sectional study highlights the urgent need to turn to and to expand the use of new agricultural ICTs to meet the growing demand for food production in the world and to ensure the resilience and sustainability of farming systems, specifically under unexpected and extreme conditions.
Integrated Analysis of the Geotechnical Factors Impeding Sustainable Building Construction—The Case of the Eastern Province of Saudi Arabia
Authors: Kazmi Zaheer Abbas , Sodangi Mahmoud
Published: June 2021

Sustainable building construction in the Eastern Province of Saudi Arabia is fraught with issues, ranging from groundwater table fluctuation to inappropriate earthwork techniques, particularly in areas that were previously reclaimed. This paper analyzes the geotechnical factors that affect the safety and serviceability of infrastructure construction on reclaimed land. The data were collected mainly from expert-based surveys and semi-structured interviews with geotechnical experts across the Eastern Province of Saudi Arabia. Ten critical factors were identified, and an integrated assessment was conducted using the Interpretive Structural Modelling (ISM) technique to examine the hierarchical structure of the relations between the factors. In addition, the Cross-impact Matrix Multiplication Applied to Classification (MICMAC) technique was used to classify the factors from a driving to driven perspective. Findings of the study reveal the driving factors, which have the propensity to affect other factors and are the most crucial factors hindering the safety and serviceability of sustainable building construction. These factors are the presence of low-bearing sabkha soil, shallow and fluctuating depth of the groundwater table, and the lack of soil improvement applications. It is expected that concerned authorities may find the outcomes of this study useful in formulating effective policies, standards, and regulations that will protect infrastructure construction from safety and serviceability problems. While the evidence on which the results of this study are based is from experiences related to coastal areas of Saudi Arabia, the outcomes of this paper could be adopted in other coastal areas in the Gulf region. This paper adds to the current knowledge on safety and serviceability management of infrastructure constructed on reclaimed lands.
Seasonal Variation of the Mobility and Toxicity of Metals in Beijing’s Municipal Solid Waste Incineration Fly Ash
Authors: Zhao Hang , Tian Yang , Wang Rong , Wang Rui , Zeng Xiangfei , Yang Feihua , Wang Zhaojia , Chen Mengjun , Shu Jiancheng
Published: June 2021

Metal mobility and toxicity of the municipal solid waste incineration (MSWI) fly ash from different seasons in Beijing were studied using leaching toxicity procedures, sequential extraction procedures, and bioavailability procedures. The X-ray diffraction results showed that MSWI fly ash contained CaSO4, CaCO3, and KCl. The Pb, Zn, and Cd contents of MSWI fly ash were high, especially during autumn, being 42, 77, and 1260 times higher than that of their soil backgrounds, respectively. Leaching toxicity experiments showed that MSWI fly ash is hazardous, since Pb exceeded the maximum threshold (5 mg/L). The main alkali metal ions and anions, heavy metals total content, leaching concentration, chemical speciation, and bioavailability varied seasonally. The Pb and Zn leaching concentrations in summer and autumn were higher than that of the other two seasons. Sequential extraction procedures indicated that Pb, Zn, and Cd showed extremely high metal mobility, i.e., the residual states of Pb and Cd in spring were 5.83% and 1.21%, respectively, and that of Zn in autumn was 10.68%. These results will help industries, governments, and the public better understand the risk of MSWI fly ash and will urge them to pay more attention to preventing harm to the ecosystem and human beings.
Public Information, Traditional Media and Social Networks during the COVID-19 Crisis in Spain
Authors: Baraybar-Fernández Antonio , Arrufat-Martín Sandro , Rubira-García Rainer
Published: June 2021

This research presents a diachronic study of the information given about COVID-19 by the main Spanish mass media through their accounts on social networks. The time frame of the analysis ranges from 1 March to 21 June 2020. Data were collected from the days prior to the proclamation of the state of alarm in Spain, in order to observe the growth in the demand for information about COVID-19, and ended on the day that the Spanish government allowed mobility between provinces and, consequently, the expiration of the alarm. It begins with a quantitative and qualitative analysis, the results of which allow us to explain the demand for public information, the degree of interest in the news and the level of interaction that developed. By adapting the Kübler-Ross model, it has been possible to identify the different stages of this public health and communication crisis in relation to public information and media sustainability. It has established the effectiveness of Facebook as an information platform with direct links to news, superior to other networks; the users’ predilection for issues of a social nature over political and technical–health issues; or the relationship found between the rate of publication of messages and the number of deaths from COVID-19.