bluuebunny/crossref_metadata_2025 huggingface dataset:
Different Rhizospheric pH Conditions Affect Nutrient Accumulations in Rice under Salinity Stress
Authors: Nampei Mami , Jiadkong Kamonthip , Chuamnakthong Sumana , Wangsawang Thanakorn , Sreewongchai Tanee , Ueda Akihiro
Published: June 2021

This study was conducted to determine the responses to saline-alkaline (SA) stress with regard to nutrient accumulation in two rice varieties having different tolerances to salt-stress. A salinity-tolerant landrace, Pokkali, and a salinity-sensitive variety, PTT1, were exposed to three levels of SA conditions, pH 7.0 (mild), pH 8.0 (moderate), and pH 9.0 (severe), under 50 mM Na stress. The results indicated that Pokkali had comparably greater SA tolerance than PTT1 owing to its higher biomass production. The maintenance of the lower Na/K ratio in Pokkali shoots was achieved by the higher expression of OsHKT1;5 encoding a Na+ transporter in the shoots, OsNHX1 encoding a tonoplast-localized Na+/H+ antiporter in the roots, and OsHAK16 encoding a K+ transporter in the roots under SA conditions. We propose that the high expression of Fe deficiency-responsive genes, OsIRT1, OsIRO2, OsYSL15, OsNAS1, and OsNAS2, in both rice varieties under all SA conditions should contribute to Fe homeostasis in the shoots. In addition, SA treatment increased the concentrations of Ca, Mn, Zn, and Cu in the roots but decreased their concentrations in the shoots of both varieties. Overall, the results indicated that high rhizospheric pH influenced nutrient uptake and translocation from the roots to the shoots in rice.
Crystallization of Random Metallocene-Catalyzed Propylene-Based Copolymers with Ethylene and 1-Hexene on Rapid Cooling
Authors: Mileva Daniela , Wang Jingbo , Androsch René , Jariyavidyanont Katalee , Gahleitner Markus , Bernreitner Klaus
Published: June 2021

Propylene-based random copolymers with either ethylene or 1-hexene as comonomer, produced using a metallocene catalyst, were studied regarding their crystallization behaviors, with a focus on rapid cooling. To get an impression of processing effects, fast scanning chip calorimetry (FSC) was used in addition to the characterization of the mechanical performance. When comparing the comonomer type and the relation to commercial grades based on Ziegler–Natta-type catalysts, both an interaction with the catalyst-related regio-defects and a significant difference between ethylene and 1-hexene was observed. A soluble-type nucleating agent was found to modify the behavior, but to an increasingly lesser degree at high cooling rates.
A Practical Numerical Approach to Characterizing Non-Linear Shrinkage and Optimizing Dimensional Deviation of Injection-Molded Small Module Plastic Gears
Authors: He Xiansong , Wu Wangqing
Published: June 2021

This paper was aimed at finding out the solution to the problem of insufficient dimensional accuracy caused by non-linear shrinkage deformation during injection molding of small module plastic gears. A practical numerical approach was proposed to characterize the non-linear shrinkage and optimize the dimensional deviation of the small module plastic gears. Specifically, Moldflow analysis was applied to visually simulate the shrinkage process of small module plastic gears during injection molding. A 3D shrinkage gear model was obtained and exported to compare with the designed gear model. After analyzing the non-linear shrinkage characteristics, the dimensional deviation of the addendum circle diameter and root circle diameter was investigated by orthogonal experiments. In the end, a high-speed cooling concept for the mold plate and the gear cavity was proposed to optimize the dimensional deviation. It was confirmed that the cooling rate is the most influential factor on the non-linear shrinkage of the injection-molded small module plastic gears. The dimensional deviation of the addendum circle diameter and the root circle diameter can be reduced by 22.79% and 22.99% with the proposed high-speed cooling concept, respectively.
Purification of Hollow Sporopollenin Microcapsules from Sunflower and Chamomile Pollen Grains
Authors: Ageitos Jose Manuel , Robla Sandra , Valverde-Fraga Lorena , Garcia-Fuentes Marcos , Csaba Noemi
Published: June 2021

Pollen grains are natural microcapsules comprised of the biopolymer sporopollenin. The uniformity and special tridimensional architecture of these sporopollenin structures confer them attractive properties such as high resistance and improved bioadhesion. However, natural pollen can be a source of allergens, hindering its biomedical applicability. Several methods have been developed to remove internal components and allergenic compounds, usually involving long and laborious processes, which often cannot be extended to other pollen types. In this work, we propose an abridged protocol to produce stable and pristine hollow pollen microcapsules, together with a complete physicochemical and morphological characterization of the intermediate and final products. The optimized procedure has been validated for different pollen samples, also producing sporopollenin microcapsules from Matricaria species for the first time. Pollen microcapsules obtained through this protocol presented low protein content (4.4%), preserved ornamented morphology with a nanoporous surface, and low product density (0.14 g/cm3). These features make them interesting candidates from a pharmaceutical perspective due to the versatility of this biomaterial as a drug delivery platform.
Experimental Dental Composites Containing a Novel Methacrylate-Functionalized Calcium Phosphate Component: Evaluation of Bioactivity and Physical Properties
Authors: Skaria Sunny , Berk Kenneth J.
Published: June 2021

The aim of this study was to synthesize and characterize a novel methacrylate-functionalized calcium phosphate (MCP) to be used as a bioactive compound for innovative dental composites. The characterization was accomplished by attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS). The incorporation of MCP as a bioactive filler in esthetic dental composite formulations and the ability of MCP containing dental composites to promote the precipitation of hydroxyapatite (HAp) on the surfaces of those dental composites was explored. The translucency parameter, depth of cure, degree of conversion, ion release profile, and other physical properties of the composites were studied with respect to the amount of MCP added to the composites. Composite with 3 wt.% MCP showed the highest flexural strength and translucency compared to the control composite and composites with 6 wt.% and 20 wt.% MCP. The progress of the surface precipitation of hydroxyapatite on the MCP containing dental composites was studied by systematically increasing the MCP content in the composite and the time of specimen storage in Dulbecco’s phosphate-buffered solution with calcium and magnesium. The results suggested that good bioactivity properties are exhibited by MCP containing composites. A direct correlation between the percentage of MCP in a composite formulation, the amount of time the specimen was stored in PBS, and the deposition of hydroxyapatite on the composite’s surface was observed.
The Optimization of Alternating Current Electrospun PA 6 Solutions Using a Visual Analysis System
Authors: Kalous Tomas , Holec Pavel , Erben Jakub , Bilek Martin , Batka Ondrej , Pokorny Pavel , Chaloupek Jiri , Chvojka Jiri
Published: June 2021

The electrospinning process that produces fine nanofibrous materials have a major disadvantage in the area of productivity. However, alternating current (AC) electrospinning might help to solve the problem via the modification of high voltage signal. The aforementioned productivity aspect can be observed via a camera system that focuses on the jet creation area and that measures the average lifespan. The paper describes the optimization of polyamide 6 (PA 6) solutions and demonstrates the change in the behavior of the process following the addition of a minor dose of oxoacid. This addition served to convert the previously unspinnable (using AC) solution to a high-quality electrospinning solution. The visual analysis of the AC electrospinning of polymeric solutions using a high-speed camera and a programmable power source was chosen as the method for the evaluation of the quality of the process. The solutions were exposed to high voltage applying two types of AC signal, i.e., the sine wave and the step change. All the recordings presented in the paper contained two sets of data: firstly, camera recordings that showed the visual expression of electrospinning and, secondly, signal recordings that provided information on the data position in the signal function.
Geopolymers and Fiber-Reinforced Concrete Composites in Civil Engineering
Authors: Mahmood Aamir , Noman Muhammad Tayyab , Pechočiaková Miroslava , Amor Nesrine , Petrů Michal , Abdelkader Mohamed , Militký Jiří , Sozcu Sebnem , Hassan Syed Zameer Ul
Published: June 2021

This paper discusses the influence of fiber reinforcement on the properties of geopolymer concrete composites, based on fly ash, ground granulated blast furnace slag and metakaolin. Traditional concrete composites are brittle in nature due to low tensile strength. The inclusion of fibrous material alters brittle behavior of concrete along with a significant improvement in mechanical properties i.e., toughness, strain and flexural strength. Ordinary Portland cement (OPC) is mainly used as a binding agent in concrete composites. However, current environmental awareness promotes the use of alternative binders i.e., geopolymers, to replace OPC because in OPC production, significant quantity of CO2 is released that creates environmental pollution. Geopolymer concrete composites have been characterized using a wide range of analytical tools including scanning electron microscopy (SEM) and elemental detection X-ray spectroscopy (EDX). Insight into the physicochemical behavior of geopolymers, their constituents and reinforcement with natural polymeric fibers for the making of concrete composites has been gained. Focus has been given to the use of sisal, jute, basalt and glass fibers.
Analysis of Cadmium-Stress-Induced microRNAs and Their Targets Reveals bra-miR172b-3p as a Potential Cd2+-Specific Resistance Factor in Brassica juncea
Authors: Liu Lili , Yin Hanqi , Liu Yanhui , Shen Lunhao , Yang Xiaojun , Zhang Dawei , Li Mei , Yan Mingli
Published: June 2021

The contamination of soil with high levels of cadmium (Cd) is of increasing concern, as Cd is a heavy metal element that seriously limits crop productivity and quality, thus affecting human health. (1) Background: Some miRNAs play key regulatory roles in response to Cd stress, but few have been explored in the highly Cd-enriched coefficient oilseed crop, Brassica juncea. (2) Methods: The genome-wide identification and characterization of miRNAs and their targets in leaves and roots of Brassica juncea exposed to Cd stress was undertaken using strand specific transcript sequencing and miRNA sequencing. (3) Results: In total, 11 known and novel miRNAs, as well as 56 target transcripts, were identified as Cd-responsive miRNAs and transcripts. Additionally, four corresponding target transcripts of six miRNAs, including FLA9 (Fasciclin-Like Arabinogalactan-protein 9), ATCAT3 (catalase 3), DOX1 (dioxygenases) and ATCCS (copper chaperone for superoxide dismutase), were found to be involved in the plant’s biotic stress pathway. We further validated the expression of three miRNA and six target genes in response to Cd, hydrargyrum (Hg), manganese (Mn), plumbum (Pb) or natrium (Na) stress and Mucor infection by qRT-PCR, and show that ATCCS and FLA9 were significantly and differentially regulated in the Cd-treated leaves. In addition, our results showed that DOX1 was obviously induced by Pb stress. Among the respective target miRNAs, bra-miR172b-3p (target for ATCCS) and ra-miR398-3p (target for FLA9) were down-regulated in Cd-treated leaves. (4) Conclusions: We identified bra-miR172b-3p as a potential Cd-specific resistant inhibitor, which may be negatively regulated in ATCCS in response to Cd stress. These findings could provide further insight into the regulatory networks of Cd-responsive miRNA in Brassica juncea.
Current Strategies for Studying the Natural and Synthetic Bioactive Compounds in Food by Chromatographic Separation Techniques
Authors: Parys Wioletta , Dołowy Małgorzata , Pyka-Pająk Alina
Published: June 2021

The present study summarizes the new strategies including advanced equipment and validation parameters of liquid and gas chromatography methods i.e., thin-layer chromatography (TLC), column liquid chromatography (CLC), and gas chromatography (GC) suitable for the identification and quantitative determination of different natural and synthetic bioactive compounds present in food and food products, which play an important role in human health, within the period of 2019–2021 (January). Full characteristic of some of these procedures with their validation parameters is discussed in this work. The present review confirms the vital role of HPLC methodology in combination with different detection modes i.e., HPLC-UV, HPLC-DAD, HPLC-MS, and HPLC-MS/MS for the determination of natural and synthetic bioactive molecules for different purposes i.e., to characterize the chemical composition of food as well as in the multi-residue analysis of pesticides, NSAIDs, antibiotics, steroids, and others in food and food products.
Dynamic Characterization during Gas Initial Desorption of Coal Particles and Its Influence on the Initiation of Coal and Gas Outbursts
Authors: Wang Chaojie , Li Xiaowei , Xu Changhang , Chen Yujia , Tang Zexiang , Zhang Chao , Du Yang , Gao Xiangyang , Jiang Chenglin
Published: June 2021

The law of gas initial desorption from coals is greatly important for understanding the occurrence mechanism and predicting coal and gas outburst (hereinafter referred to as ‘outburst’). However, dynamic characterization of gas initial desorption remains to be investigated. In this study, by monitoring the gas pressure and temperature of tectonically deformed (TD) coal and primary-undeformed (PU) coal, we established the evolution laws of gas key parameters during the initial desorption. The results indicate that the gas pressure drop rate, mass flow rate, initial desorption rate, and gas velocity increase with increasing gas pressure, with stronger gas dynamic effect, generating a high pressure gradient on the coal surface. Under the same gas pressure, the pressure gradient formed on the TD coal surface is greater than that formed on the surface of the PU coal, resulting in easily initiating an outburst in the TD coal. Moreover, the increased gas pressure increases temperature change rates (falling rate and rising rate) of coal mass. The minimum and final stable temperatures in the TD coal are generally lower compared to the PU coal. The releasing process of gas expansion energy can be divided into two stages exhibiting two peaks which increase as gas pressure increases. The two peak values for the TD coal both are about 2–3 times of those of the PU coal. In addition, the total gas expansion energy released by TD coal is far greater than that released by PU coal. The two peaks and the total values of gas expansion energy also prove that the damage of gas pressure to coal mass increases with the increased pressure, more likely producing pulverized coals and more prone to initiate an outburst.
The Role of Globalization, Economic Growth and Natural Resources on the Ecological Footprint in Thailand: Evidence from Nonlinear Causal Estimations
Authors: Hussain Hafezali Iqbal , Haseeb Muhammad , Kamarudin Fakarudin , Dacko-Pikiewicz Zdzisława , Szczepańska-Woszczyna Katarzyna
Published: June 2021

The environmental issue has become a global problem that needs to be examined frequently, motivating researchers to investigate it. Thus, the present study has investigated the asymmetric impact of globalization, economic growth and natural resources on the ecological footprint in the presence of environmental Kuznets curve (EKC) in Thailand. The study has used annual time series data from 1970 to 2018. The study applied a novel method of nonlinear autoregressive distributive lag (ARDL). In particular, the current study has investigated the effect of positive and negative shocks on the independent variable on the dependent variable. The findings have confirmed that the effect of globalization and natural resources are significant and nonlinear. However, the effect of negative shocks of globalization and natural resources is more dominant on the ecological footprint in Thailand than the positive shocks of both variables. Moreover, the present study has also tested the presence of EKC in Thailand, and the findings confirm the presence of an inverted U-shape curve in the Thailand economy.
Condition Monitoring of Drive Trains by Data Fusion of Acoustic Emission and Vibration Sensors
Authors: Mey Oliver , Schneider André , Enge-Rosenblatt Olaf , Mayer Dirk , Schmidt Christian , Klein Samuel , Herrmann Hans-Georg
Published: June 2021

Early damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing systems and industrial facilities. Data analysis can be improved by applying machine learning algorithms and fusion of data from heterogenous sensors. This paper presents an approach for a step-wise integration of classifications gained from vibration and acoustic emission sensors in order to combine the information from signals acquired in the low and high frequency ranges. A test rig comprising a drive train and bearings with small artificial damages is used for acquisition of experimental data. The results indicate that an improvement of damage classification can be obtained using the proposed algorithm of combining classifiers for vibrations and acoustic emissions.
FPGA-Based Implementation of an Optimization Algorithm to Maximize the Productivity of a Microbial Electrolysis Cell
Authors: Colín-Robles José de Jesús , Torres-Zúñiga Ixbalank , Ibarra-Manzano Mario A. , Alcaraz-González Víctor
Published: June 2021

In this work, the design of the hardware architecture to implement an algorithm for optimizing the Hydrogen Productivity Rate (HPR) in a Microbial Electrolysis Cell (MEC) is presented. The HPR in the MEC is maximized by the golden section search algorithm in conjunction with a super-twisting controller. The development of the digital architecture in the implementation step of the optimization algorithm was developed in the Very High Description Language (VHDL) and synthesized in a Field Programmable Gate Array (FPGA). Numerical simulations demonstrated the feasibility of the proposed optimization strategy embedded in an FPGA Cyclone II. Results showed that only 21% of the total logic elements, 5.19% of dedicated logic registers, and 64% of the total eight-bits multipliers of the FPGA were used. On the other hand, the estimated power consumption required by the FPGA-embedded optimization algorithm was only 146 mW.
Novel High-Efficiency High Step-Up DC–DC Converter with Soft Switching and Low Component Voltage Stress for Photovoltaic System
Authors: Wu Yu-En , Wang Jyun-Wei
Published: June 2021

This study developed a novel, high-efficiency, high step-up DC–DC converter for photovoltaic (PV) systems. The converter can step-up the low output voltage of PV modules to the voltage level of the inverter and is used to feed into the grid. The converter can achieve a high step-up voltage through its architecture consisting of a three-winding coupled inductor common iron core on the low-voltage side and a half-wave voltage doubler circuit on the high-voltage side. The leakage inductance energy generated by the coupling inductor during the conversion process can be recovered by the capacitor on the low-voltage side to reduce the voltage surge on the power switch, which gives the power switch of the circuit a soft-switching effect. In addition, the half-wave voltage doubler circuit on the high-voltage side can recover the leakage inductance energy of the tertiary side and increase the output voltage. The advantages of the circuit are low loss, high efficiency, high conversion ratio, and low component voltage stress. Finally, a 500-W high step-up converter was experimentally tested to verify the feasibility and practicability of the proposed architecture. The results revealed that the highest efficiency of the circuit is 98%.
Phase Transformation by 100 keV Electron Irradiation in Partially Stabilized Zirconia
Authors: Okuno Yasuki , Okubo Nariaki
Published: June 2021

Partially stabilized zirconia (PSZ) is considered for use as an oxygen-sensor material in liquid lead-bismuth eutectic (LBE) alloys in the radiation environment of an acceleration-driven system (ADS). To predict its lifetime for operating in an ADS, the effects of radiation on the PSZ were clarified in this study. A tetragonal PSZ was irradiated with 100 keV electrons and analyzed by X-ray diffraction (XRD). The results indicate that the phase transition in the PSZ, from the tetragonal to the monoclinic phase, was caused after the irradiation. The deposition energy of the lattice and the deposition energy for the displacement damage of a 100 keV electron in the PSZ are estimated using the particle and heavy ion transport code system and the non-ionizing energy loss, respectively. The results suggest that conventional radiation effects, such as stopping power, are not the main mechanism behind the phase transition. The phase transition is known to be caused by the low-temperature degradation of the PSZ and is attributed to the shift of oxygen ions to oxygen sites. When the electron beam is incident to the material, the kinetic energy deposition and excitation-related processes are caused, and it is suggested to be a factor of the phase transition.
Recognition and Responsibility
Authors: Haker Hille
Published: June 2021

While the concept of responsibility is a cornerstone of Christian ethics, recognition theory still lacks a thorough theological–ethical analysis. This essay seeks to fill the gap and develop normative ethics of recognition and responsibility. The first part provides a systematic analysis of the conceptual elements of recognition, emphasizing the need to focus on misrecognition as a heuristic tool and ethical priority. While recognition coincides with responsivity and attentiveness in the encounter of self and other, responsibility adds to this the moral accountability for acts, practices, structures, and institutions, rendering recognition and responsibility interrelated but also distinct principles of morality. This normative analysis is then correlated to the hermeneutical, narrative ethics of Christian ethics. The founding narrative of biblical ethics, the Cain and Abel narrative in Gen 4, is interpreted as a dialectic of recognition and responsibility. Both exegesis and ethics profit from this interdisciplinary and correlative approach between philosophical and biblical ethics. Finally, the ethics of recognition and responsibility, which emerges from the Frankfurt School critical theory, is confronted with exemplary indigenous approaches focusing on mutual responsibility as the foundation of ecological ethics. Christian ethics of recognition and responsibility resonates with this approach, yet emphasizes the distinctiveness of human interactions and the demands of moral responsibility.
Secularist Humanism, Law and Religion in Ian McEwan’s The Children Act
Authors: Ungureanu Camil
Published: June 2021

Ian McEwan’s The Children Act focuses on a real-life conflict between religion and children’s rights in a pluralist society. By drawing on Charles Taylor’s work on religion in the “secular age”, I argue that McEwan’s narrative is ultimately built on secularist assumptions that devalue religious experience. McEwan’s approach aims to build a bridge between literary imagination and scientific rationality: religion is, from this perspective, reducible to a “fable” and an authority structure incongruous with legal rationality and the quest for meaning in the modern-secular society. In The Children Act, art substitutes religion and its aspiration to transcendence: music in particular is a universal idiom that can overcome barriers of communication and provides “ecstatic” experiences in a godless world.
A Brief History of Medieval Monasticism in Denmark (with Schleswig, Rügen and Estonia)
Authors: Jakobsen Johnny Grandjean Gøgsig
Published: June 2021

Monasticism was introduced to Denmark in the 11th century. Throughout the following five centuries, around 140 monastic houses (depending on how to count them) were established within the Kingdom of Denmark, the Duchy of Schleswig, the Principality of Rügen and the Duchy of Estonia. These houses represented twelve different monastic orders. While some houses were only short lived and others abandoned more or less voluntarily after some generations, the bulk of monastic institutions within Denmark and its related provinces was dissolved as part of the Lutheran Reformation from 1525 to 1537. This chapter provides an introduction to medieval monasticism in Denmark, Schleswig, Rügen and Estonia through presentations of each of the involved orders and their history within the Danish realm. In addition, two subchapters focus on the early introduction of monasticism to the region as well as on the dissolution at the time of the Reformation. Along with the historical presentations themselves, the main and most recent scholarly works on the individual orders and matters are listed.
Between Basilea and Utopia: Exploring the Impact of Kingdom Theology in US Latinx Pentecostalism
Authors: Morales Juan C.
Published: June 2021

This article is a general exploration of US Latinx Pentecostalism’s explicit and implicit theology of the Kingdom of God and how it can contribute to US Latinx Pentecostalism’s socio-political engagement. An overview will be provided of traditional, US Pentecostal Kingdom theology and Kingdom theology in Latin American Liberation Theology. These will be contrasted with US Latinx Pentecostal perspectives. To locate US Latinx Pentecostal theology of the Kingdom of God, this paper will first provide a wide-ranging description of a traditional evangelical hermeneutical process. Afterward, an understanding of the Kingdom that is generally taught and accepted in most evangelical contexts will be discussed. This will be followed by a survey of dominant US Pentecostal theology of the Kingdom of God through the lens of the Assemblies of God doctrinal statements and Pentecostal scholars. The life and work of various Pentecostal ministers and author Piri Thomas will provide a Kingdom perspective of US Latinx Pentecostal practitioners. I will provide an analysis based on their life experiences and some of their writings. The writings of Orlando Costas will set the stage in order to examine the works of other US Latinx Pentecostal scholars. Thereafter, the theologies of Latin American Liberation Theologians Clodivis and Leonardo Boff and others will be surveyed. Before concluding, the article will provide a historical overview of Latinx Pentecostal social engagement in the northeast US with the goal of identifying Kingdom values and priorities.
The Participation of God and the Torah in Early Kabbalah
Authors: Afterman Adam , Hayut-man Ayal
Published: June 2021

All Abrahamic religions have developed hypostatic and semi-divine perceptions of scripture. This article presents an integrated picture of a rich tradition developed in early kabbalah (twelfth–thirteenth century) that viewed the Torah as participating and identifying with the Godhead. Such presentation could serve scholars of religion as a valuable tool for future comparisons between the various perceptions of scripture and divine revelation. The participation of God and Torah can be divided into several axes: the identification of Torah with the Sefirot, the divine gradations or emanations according to kabbalah; Torah as the name of God; Torah as the icon and body of God; and the commandments as the substance of the Godhead. The article concludes by examining the mystical implications of this participation, particularly the notion of interpretation as eros in its broad sense, both as the “penetration” of a female Torah and as taking part in the creation of the world and of God, and the notion of unification with Torah and, through it, with the Godhead.
Religiously Disaffiliated, Religiously Indifferent, or Believers without Religion? Morphology of the Unaffiliated in Argentina
Authors: Esquivel Juan Cruz
Published: June 2021

This article aims to characterize the socioeconomic and demographic profile of the population without religious affiliation in Argentina as well as their beliefs, practices, and attitudes toward a range of issues related to public and private life. This is a social conglomerate that has grown exponentially in the region and worldwide, but it has been little explored by the social sciences of religion in Latin America. The research was based on the Second National Survey on Religious Beliefs and Attitudes in Argentina, which was carried out in 2019. The study universe was made up of the population of the Argentine Republic aged 18 years or more, living in localities or urban agglomerations with at least 5000 inhabitants. A total of 2421 cases were selected through a multistage sampling. The analysis of the data reveals that it would be inaccurate to say that the religiously unaffiliated do not convey religious beliefs. Almost three out of 10 (most of those who responded do not belong to any religion but neither defined themselves as agnostics or atheists) believe in God and in Jesus Christ. Given that they are the most numerous sub-group and with the highest growth rate within the religiously unaffiliated, it would be unwise to consider this fringe of the Argentine citizenry as a-religious. Nor can we unify them under the category of disaffiliates. Although six out of 10 have a history identified with some religion (and in those cases, it is indeed possible to observe a process of religious disaffiliation), the remaining 40% show paths defined by the alienation from the institutionalized religious spaces since their earliest age.
Skills for “Marriage of a Lifetime”: An Examination of Muslim Marriage Preparation Handbooks in Singapore, 1974 to 2018
Authors: Suratman Suriani
Published: June 2021

High divorce rates in Muslim marriages continue to be a concern for Malay community leaders and policy makers in Singapore. Since 1969, Malay community organisations here have offered marriage preparation courses to reduce the incidence of divorce. Today, a range of such pre-marriage courses continue to be provided by the Ministry of Social and Family Development, Muslim organisations and private educational groups that are involved in marriage counselling and consultation. In this article, I examine the handbooks that have accompanied courses sponsored by the Ministry. Their content spells out the skills needed to realise a “marriage of a lifetime”. Whilst prescriptions have responded to societal changes, a closer scrutiny of instructions in these manuals unfolds notions of the ‘ideal’ Muslim husband and wife that continue to stress men as providers and women as primary caregivers. Prioritising communication skills of the individual, as these manuals do, does little to change household gender inequalities in the long run.
Improving Urban Impervious Surfaces Mapping through Integrating Statistical Methods and Spectral Mixture Analysis
Authors: Li Wenliang
Published: June 2021

Impervious surfaces have been widely considered as the key indicator for evaluating urbanization and environmental quality. As one of the most widely applied methods, spectral mixture analysis (SMA) has been commonly used for mapping urban impervious surface fractions. When implementing SMA, the original multispectral remote-sensing reflectance images are served as the foundation and key to successful SMA. However, the limited spectral variances among different land covers from the original reflectance images make it challenging in information extraction and results in unsatisfactory mapping results. To address this issue, a new method has been proposed in this study to improve urban impervious surface mapping through integrating statistical methods and SMA. In particular, two traditional statistical methods, principal component analysis (PCA) and minimum noise fraction rotation (MNF) were applied to highlight the spectral variances among different land covers. Three endmember classes (impervious surface, soil, and vegetation) and corresponding spectra were identified and extracted from the vertices of the 2-D space plots generated by the first three components of each of the statistical analysis methods, PCA and MNF. A new dataset was generated by stacking the first three components of the PCA and MNF (in a total of six components), and a fully constrained linear SMA was implemented to map the fractional impervious surfaces. Results indicate that a promising performance has been achieved by the proposed new method with the systematic error (SE) of −3.45% and mean absolute error (MAE) of 11.52%. Comparative analysis results also show a much better performance achieved by the proposed statistical method-based SMA than the conventional SMA.
Interpretation of Spectral LiDAR Backscattering off the Florida Coast
Authors: Montes Martin A. , Vuorenkoski Anni K. , Metzger Ben , Botson Bryan
Published: June 2021

A multispectral backscattering LiDAR (Light detection and range) system (hereafter Oculus) was integrated into a wave glider and used to estimate the scattering order (i.e., single vs multiple collisions) of LIDAR backscattering, the water inherent optical properties (IOPs), the biogeo-chemical characteristics of particulate scatterers (i.e., relative size, composition) and their motion) on shelf waters of South East Florida. Oculus has a dual-wavelength configuration (473 and 532 nm) and two detection geometries (off- and on-axis). Characteristics of scatterers were investigated based on two complementary LiDAR-derived proxies (the Structural Dissimilarity Index and the spectral slope of LiDAR backscattering). In March 2017, field measurements showed a covariation between direct and diffuse backscattering contributions during morning hours and away from shore. LiDAR attenuation coefficients explained up to 57% of IOPs variability. The analysis of LiDAR-derived proxies suggested higher turbidity and larger particulates near the coast
Efficient Calculation Method for Tree Stem Traits from Large-Scale Point Clouds of Forest Stands
Authors: Masuda Hiroshi , Hiraoka Yuichiro , Saito Kazuto , Eto Shinsuke , Matsushita Michinari , Takahashi Makoto
Published: June 2021

With the use of terrestrial laser scanning (TLS) in forest stands, surveys are now equipped to obtain dense point cloud data. However, the data range, i.e., the number of points, often reaches the billions or even higher, exceeding random access memory (RAM) limits on common computers. Moreover, the processing time often also extends beyond acceptable processing lengths. Thus, in this paper, we present a new method of efficiently extracting stem traits from huge point cloud data obtained by TLS, without subdividing or downsampling the point clouds. In this method, each point cloud is converted into a wireframe model by connecting neighboring points on the same continuous surface, and three-dimensional points on stems are resampled as cross-sectional points of the wireframe model in an out-of-core manner. Since the data size of the section points is much smaller than the original point clouds, stem traits can be calculated from the section points on a common computer. With the study method, 1381 tree stems were calculated from 3.6 billion points in ~20 min on a common computer. To evaluate the accuracy of this method, eight targeted trees were cut down and sliced at 1-m intervals; actual stem traits were then compared to those calculated from point clouds. The experimental results showed that the efficiency and accuracy of the proposed method are sufficient for practical use in various fields, including forest management and forest research.
A Method for Quantifying the Impacts of Human Activities on Net Primary Production of Grasslands in Northwest China
Authors: Li Chuanhua , Dou Tianbao , Wang Yutao , Zhu Tongbin , Yin Huanhuan , Zhou Min , Liu Lihui , Wu Xiaodong
Published: June 2021

Accurately assessing the impact of human activities on net primary productivity (NPP) of vegetation is of great significance to the achievement of sustainable development. However, it is difficult to disentangle the effects of climate conditions and human activities on NPP, and bridging this knowledge gap largely depends on the calculation of the NPP under natural conditions. Here, we propose a method for calculating natural vegetation NPP (NNPP) based on non-human influence grids, which are obtained according to the consistent rate of climate and actual NPP (ANPP) temporal changes. We selected Northwest China as study area, and we used a light use efficiency (LUE) model to estimate ANPP and used the random forest algorithm (RF) to estimate the NNPP. The results show that NNPP is very close to ANPP, and the human activities on NPP (HNPP) based on NNPP is close to the actual situation of human activities on NPP. From 2001 to 2017, the positive HNPP accounts for 40.28% of the total grassland area, with an average value of 28.65 gC·m−2·yr−1, while the negative HNPP accounts for 59.72% of the total area, with an average value of −31.19 gC·m−2·yr−1. The grassland NPP shows an increasing trend, which is dominated by climate factors. Human activity is the dominant factor for the grassland degradation, accounting for 42.78% of the degraded area, but promoting grassland growth in 11.4% of the restored area. This study provides a new method to estimate the impacts of human activities on vegetation, and the results can be used to evaluate the effectiveness of ecological environmental governance, providing a quantitative basis for scientifically building the harmonious relationship between human and nature.
Analysis of Crustal Movement and Deformation in Mainland China Based on CMONOC Baseline Time Series
Authors: Wu Jicang , Song Xinyou , Wu Weiwei , Meng Guojie , Ren Yingying
Published: June 2021

In this paper, we propose a method for the analysis of tectonic movement and crustal deformation by using GNSS baseline length change rates or baseline linear strain rates. The method is applied to daily coordinate solutions of continuous GNSS stations of the Crustal Movement Observation Network of China (CMONOC). The results show that: (a) The baseline linear strain rates are uneven in space, which is prominent in the Tianshan, Sichuan-Yunnan, Qinghai-Tibet Plateau, and Yanjing areas, with a maximum value of 1 × 10−7 a−1, and about two orders smaller in the South China block, the Northeast block, and the inner area of the Tarim basin, where the average baseline linear strain rates are 1.471 × 10−9 a−1, 2.242 × 10−9 a−1, and 3.056 × 10−9 a−1, respectively; (b) Active crustal deformation and strong earthquakes in the Xinjiang area are mainly located in the north and south sides of the Tianshan block; the compression deformations both inside the Tarim block and in the southern Tianshan fault zone are all increasing from east to west, and the Tarim block is not a completely “rigid block”, with the shrinkage rate in the west part at about 1~2 mm/a; (c) The principal directions of crustal deformation in the Xinjiang, Tibet, and Sichuan-Yunnan regions are generally in the north—south compression and east—west extension, indicating that the collision and wedging between the Indian and Eurasian plates are still the main source of tectonic movements in mainland China.
Mapping of Kobresia pygmaea Community Based on Umanned Aerial Vehicle Technology and Gaofen Remote Sensing Data in Alpine Meadow Grassland: A Case Study in Eastern of Qinghai–Tibetan Plateau
Authors: Meng Baoping , Yang Zhigui , Yu Hongyan , Qin Yu , Sun Yi , Zhang Jianguo , Chen Jianjun , Wang Zhiwei , Zhang Wei , Li Meng , Lv Yanyan , Yi Shuhua
Published: June 2021

The Kobresia pygmaea (KP) community is a key succession stage of alpine meadow degradation on the Qinghai–Tibet Plateau (QTP). However, most of the grassland classification and mapping studies have been performed at the grassland type level. The spatial distribution and impact factors of KP on the QTP are still unclear. In this study, field measurements of the grassland vegetation community in the eastern part of the QTP (Counties of Zeku, Henan and Maqu) from 2015 to 2019 were acquired using unmanned aerial vehicle (UAV) technology. The machine learning algorithms for grassland vegetation community classification were constructed by combining Gaofen satellite images and topographic indices. Then, the spatial distribution of KP community was mapped. The results showed that: (1) For all field observed sites, the alpine meadow vegetation communities demonstrated a considerable spatial heterogeneity. The traditional classification methods can hardly distinguish those communities due to the high similarity of their spectral characteristics. (2) The random forest method based on the combination of satellite vegetation indices, texture feature and topographic indices exhibited the best performance in three counties, with overall accuracy and Kappa coefficient ranged from 74.06% to 83.92% and 0.65 to 0.80, respectively. (3) As a whole, the area of KP community reached 1434.07 km2, and accounted for 7.20% of the study area. We concluded that the combination of satellite remote sensing, UAV surveying and machine learning can be used for KP classification and mapping at community level.
Optimization of Aerosol Model Selection for TROPOMI/S5P
Authors: Rao Lanlan , Xu Jian , Efremenko Dmitry S. , Loyola Diego G. , Doicu Adrian
Published: June 2021

To retrieve aerosol properties from satellite measurements, micro-physical aerosol models have to be assumed. Due to the spatial and temporal inhomogeneity of aerosols, choosing an appropriate aerosol model is an important task. In this paper, we use a Bayesian algorithm that takes into account model uncertainties to retrieve the aerosol optical depth and layer height from synthetic and real TROPOMI O2A band measurements. The results show that in case of insufficient information for an appropriate micro-physical model selection, the Bayesian algorithm improves the accuracy of the solution.
Mapping Potential Plant Species Richness over Large Areas with Deep Learning, MODIS, and Species Distribution Models
Authors: Choe Hyeyeong , Chi Junhwa , Thorne James H.
Published: June 2021

The spatial patterns of species richness can be used as indicators for conservation and restoration, but data problems, including the lack of species surveys and geographical data gaps, are obstacles to mapping species richness across large areas. Lack of species data can be overcome with remote sensing because it covers extended geographic areas and generates recurring data. We developed a Deep Learning (DL) framework using Moderate Resolution Imaging Spectroradiometer (MODIS) products and modeled potential species richness by stacking species distribution models (S-SDMs) to ask, “What are the spatial patterns of potential plant species richness across the Korean Peninsula, including inaccessible North Korea, where survey data are limited?” First, we estimated plant species richness in South Korea by combining the probability-based SDM results of 1574 species and used independent plant surveys to validate our potential species richness maps. Next, DL-based species richness models were fitted to the species richness results in South Korea, and a time-series of the normalized difference vegetation index (NDVI) and leaf area index (LAI) from MODIS. The individually developed models from South Korea were statistically tested using datasets that were not used in model training and obtained high accuracy outcomes (0.98, Pearson correlation). Finally, the proposed models were combined to estimate the richness patterns across the Korean Peninsula at a higher spatial resolution than the species survey data. From the statistical feature importance tests overall, growing season NDVI-related features were more important than LAI features for quantifying biodiversity from remote sensing time-series data.
Sensitivity of Spectral Indices on Burned Area Detection using Landsat Time Series in Savannas of Southern Burkina Faso
Authors: Liu Jinxiu , Maeda Eduardo Eiji , Wang Du , Heiskanen Janne
Published: June 2021

Accurate and efficient burned area mapping and monitoring are fundamental for environmental applications. Studies using Landsat time series for burned area mapping are increasing and popular. However, the performance of burned area mapping with different spectral indices and Landsat time series has not been evaluated and compared. This study compares eleven spectral indices for burned area detection in the savanna area of southern Burkina Faso using Landsat data ranging from October 2000 to April 2016. The same reference data are adopted to assess the performance of different spectral indices. The results indicate that Burned Area Index (BAI) is the most accurate index in burned area detection using our method based on harmonic model fitting and breakpoint identification. Among those tested, fire-related indices are more accurate than vegetation indices, and Char Soil Index (CSI) performed worst. Furthermore, we evaluate whether combining several different spectral indices can improve the accuracy of burned area detection. According to the results, only minor improvements in accuracy can be attained in the studied environment, and the performance depended on the number of selected spectral indices.
ATARI: A Graph Convolutional Neural Network Approach for Performance Prediction in Next-Generation WLANs
Authors: Soto Paola , Camelo Miguel , Mets Kevin , Wilhelmi Francesc , Góez David , Fletscher Luis A. , Gaviria Natalia , Hellinckx Peter , Botero Juan F. , Latré Steven
Published: June 2021

IEEE 802.11 (Wi-Fi) is one of the technologies that provides high performance with a high density of connected devices to support emerging demanding services, such as virtual and augmented reality. However, in highly dense deployments, Wi-Fi performance is severely affected by interference. This problem is even worse in new standards, such as 802.11n/ac, where new features such as Channel Bonding (CB) are introduced to increase network capacity but at the cost of using wider spectrum channels. Finding the best channel assignment in dense deployments under dynamic environments with CB is challenging, given its combinatorial nature. Therefore, the use of analytical or system models to predict Wi-Fi performance after potential changes (e.g., dynamic channel selection with CB, and the deployment of new devices) are not suitable, due to either low accuracy or high computational cost. This paper presents a novel, data-driven approach to speed up this process, using a Graph Neural Network (GNN) model that exploits the information carried in the deployment’s topology and the intricate wireless interactions to predict Wi-Fi performance with high accuracy. The evaluation results show that preserving the graph structure in the learning process obtains a 64% increase versus a naive approach, and around 55% compared to other Machine Learning (ML) approaches when using all training features.