bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of Soft Sensors in Anaerobic Digestion Process
Authors: Yan Pengfei , Gai Minghui , Wang Yuhong , Gao Xiaoyong
Published: August 2021

Anaerobic digestion is associated with various crucial variables, such as biogas yield, chemical oxygen demand, and volatile fatty acid concentration. Real-time monitoring of these variables can not only reflect the process of anaerobic digestion directly but also accelerate the efficiency of resource conversion and improve the stability of the reaction process. However, the current real-time monitoring equipment on the market cannot be widely used in the industrial production process due to its defects such as expensive equipment, low accuracy, and lagging analysis. Therefore, it is essential to conduct soft sensor modeling for unmeasurable variables and use auxiliary variables to realize real-time monitoring, optimization, and control of the an-aerobic digestion process. In this paper, the basic principle and process flow of anaerobic digestion are first briefly introduced. Subsequently, the development history of the traditional soft sensor is systematically reviewed, the latest development of soft sensors was detailed, and the obstacles of the soft sensor in the industrial production process are discussed. Finally, the future development trend of deep learning in soft sensors is deeply discussed, and future research directions are provided.
Research on Fault Location of Distribution Lines Based on the Standing Wave Principle
Authors: Hou Sizu , Guo Xiaoyi
Published: August 2021

Aiming at the fast and accurate location of a single-phase ground fault in the distribution network, a single terminal injection signal location method, based on the standing wave principle, is proposed. Firstly, the double conductor standing wave principle formation, based on uniform transmission line theory, is analyzed, and the mathematical model of the fault distance algorithm is established. Secondly, a fault detection circuit is built by simulation, and the distribution trend of the standing wave and its relationship with unit capacitance and unit inductance are studied. By setting the source signal frequency and detection point interval and other parameters, the fault location of this method under direct grounding fault and through grounding resistance fault is simulated and studied. Finally, the fault distance is calculated and located by an experiment. The results show that the positioning accuracy is high, which verifies the effectiveness of the standing wave positioning method.
Experimental Characterization and Energy Performance Assessment of a Sorption-Enhanced Steam–Methane Reforming System
Authors: Fatigati Fabio , Di Giuliano Andrea , Carapellucci Roberto , Gallucci Katia , Cipollone Roberto
Published: August 2021

The production of blue hydrogen through sorption-enhanced processes has emerged as a suitable option to reduce greenhouse gas emissions. Sorption-enhanced steam–methane reforming (SESMR) is a process intensification of highly endothermic steam–methane reforming (SMR), ensured by in situ carbon capture through a solid sorbent, making hydrogen production efficient and more environmentally sustainable. In this study, a comprehensive energy model of SESMR was developed to carry out a detailed energy characterization of the process, with the aim of filling a current knowledge gap in the literature. The model was applied to a bench-scale multicycle SESMR/sorbent regeneration test to provide an energy insight into the process. Besides the experimental advantages of higher hydrogen concentration (90 mol% dry basis, 70 mol% wet basis) and performance of CO2 capture, the developed energy model demonstrated that SESMR allows for substantially complete energy self-sufficiency through the process. In comparison to SMR with the same process conditions (650 °C, 1 atm) performed in the same experimental rig, SESMR improved the energy efficiency by about 10%, further reducing energy needs.
Online Temptations: Divorce and Extramarital Affairs in Kazakhstan
Authors: Dall’Agnola Jasmin , Thibault Hélène
Published: August 2021

In recent years, the institution of marriage in Muslim Central Asia has undergone profound transformations in terms of religious dynamics, migration patterns, and the impact of globalization. In Kazakhstan between 2014 and 2019, every third marriage ended in divorce. By examining how Muslim Kazakhs’ support for divorce and casual sex is related to their consumption of information obtained on the Internet, mobile phone, and social media, this study contributes to the growing body of literature on the transformative forces of information and communication technology (ICT) in Kazakhstan and Central Asia. It uses a mixed-method approach that contrasts wider statistical trends from the World Values Survey Wave 7 country dataset on Kazakhstan with empirical data from focus groups conducted in five different regions of the country in 2019, involving a total of 96 respondents. The findings from the statistical and non-statistical analysis show that frequent exposure to information online influences Muslim Kazakhs’ support for extramarital affairs and divorce. Yet, frequent use of ICTs does not necessarily weaken the institution of marriage. Apart from its effect on university-educated female Kazakh youth, it seems to reinforce traditional understanding of marriage obligations among older generations and young men.
What’s Love Got to Do with It? Religion and the Multiple Logic Tensions of Social Enterprise
Authors: Borquist Bruce R.
Published: August 2021

This paper develops a model that advances our understanding of how social enterprises respond to the complexity of a constellation of multiple, often competing goals, referred to here as institutional logics. Introducing a religious logic to the recognised social welfare and commercial logics of social enterprise, this model builds on a religious worldview foundation and incorporates religion-inspired altruistic love and non-transactional giving as its scaffolding. A comparative case study of faith-based, faith-inspired and secular organisations located in Southeast Asia demonstrates the origin and applicability of the model. Findings highlight that religion serves as an overarching logic, or “metalogic”, and frame of reference. Faith-based social enterprises use this religious logic to redefine perceived paradoxical tensions between the social welfare and commercial objectives they embody. Study results advance knowledge on organisational responses to multiple logic prescriptions, underscores the influence of religion, altruistic love and giving on organisational behaviour and contributes to the scarce literature on faith-based social enterprises.
The Impossible Spaces: A Commentary on Gen. 2:8–15
Authors: García-Jalón Santiago
Published: August 2021

A close analysis of the text of Gen. 2:8–15, pertaining to the Garden of Eden, shows the structural differences between said text and others from ancient mythologies that mention or describe a paradise. Likewise, that analysis suggests that the data provided by the Bible to locate paradise are merely a narrative device meant to dissipate all doubts as to the existence of a garden where God put human beings. Similar to other spaces that appear in the Bible, the Garden of Eden is, in fact, an impossible place. Throughout the centuries, however, recurring proposals have been made to locate paradise. As time went by, those proposals were progressively modified by the intellectual ideas dominant in any given era, thus leading the representations of the location of Paradise to be further and further away from the information provided by the biblical text.
From Archangels to Virtual Pilgrims: A Brief History of Papal Digital Mobilization as Soft Power
Authors: Löffler Johannes Ludwig
Published: August 2021

The perpetual public display of successful mass mobilization and pilgrimage has become a pillar of papal soft power. During the 20th century, the papacy had repeatedly demonstrated its ability to use new technologies for public communication, media content production and mass mobilization. John Paul II endorsed the establishment of the first Vatican website and an official papal e-mail account, which provided Catholics a new form of communication with the Holy Father. During the pontificate of Benedict XVI, the papacy created several Twitter accounts, which would become the backbone of papal digital mobilization. Francis built on the success of his predecessors as he initiated the modernization of the Holy See’s media department. However, with the growth of the Internet and the stress test of the COVID-19 pandemic, the mechanics of mobilization, pilgrimage and power have considerably changed. With the religious role of the popes taken as a given, the paper looks into the history of papal mobilization, the role of the Internet and why it is not used to its full potential yet.
“Only God Can Be”: Aleksandr Vvedensky, Kant, God, and Time
Authors: Pavlov Evgeny
Published: August 2021

This article discusses the place of God in the poetic system of Aleksandr Vvedensky. Vvedensky’s famous pronouncement on his “poetic critique” is more throughgoing than Kant’s critical enterprise, and invites a comparison between the movement of Kant’s thought in the Critique of Judgment, and what Vvedensky’s recourse to senselessness aims to achieve. Time in Vvedensky poetics may be seen as a radical extension of Kant’s philosophical system where it ultimately resides in an equally inaccessible realm on which its entire edifice is founded.
Pro-Violence Sermons of a Secular State: Turkey’s Diyanet on Islamist Militarism, Jihadism and Glorification of Martyrdom
Authors: Yilmaz Ihsan , Erturk Omer F.
Published: August 2021

The literature on martyrdom has not, so far, systematically analysed a constitutionally secular state’s extensive use of religion in propagating martyrdom narratives by using state-controlled religious institutions. This paper addresses this gap in martyrdom literature. In addition, even though some studies have analysed how martyrdom narratives have been used for political purposes in Turkey for mythmaking and building a collective memory, a religious institution’s active use by the state for the purposes of mythmaking and collective memory building has not been studied. This paper shows that the contents of the Friday sermons, that reach at least 50 percent of the country’s adult males every week, have moved from Turkish nationalist understanding of militarism and martyrdom to more radical, Islamist and pro-violence interpretations that actively promote dying for the nation, homeland, religion and God. The sermons also emphasise that new generations must be raised with this pro-violence religious spirit, which is also novel.
Ecology as a New Foundation for Natural Theology
Authors: Lind Andreas Gonçalves , Nobre Bruno
Published: August 2021

The erosion of metaphysics that began in Modernity has led to the discredit of the whole project of natural theology as a means to reach God, establish the classical divine attributes, and account for divine action. After the deconstruction of classical metaphysics propelled by thinkers associated with the Protestant tradition and by philosophers affiliated with the Nietzschean critique, it may appear that only an apophatic approach to God would then be possible. However, the attempt to establish a consensual foundation for the theological discourse has not lost its relevance. In this sense, the attempts to revitalize natural theology are most welcome. It would be naive, however, to think that approaches to natural theology based on classical metaphysics will easily gather consensus. This will not happen. The departing point for a renewed and credible approach to natural theology cannot be the theoretical universal reason associated with Modernity, which is no longer acknowledged as a common ground. As such, a viable approach to natural theology has to find a new consensual starting point. The goal of this article is to argue that the emergence of a new ecological urgency and sensibility, which nowadays gather a high degree of consensus, offers an opportunity for the renewal of natural theology. It is our aim: (i) to show the extent to which God grounds the intrinsic value of nature, which, as such, deserves respect, and (ii) to suggest that the reverence for nature may naturally lead contemporary human beings to God.
Evolution and Decline: Making Wholeness in a Time of Ecological Decline
Authors: Ormerod Neil
Published: August 2021

Drawing on three key elements in Lonergan’s thought—emergent probability, the triad of progress/decline/redemption, and the law of the cross—this paper explores the struggle to remake some sense of wholeness in an era of serve ecological decline and the cost to be paid to turn it around. It identifies political action as the most urgent arena for those seeking to redeem our present situation, while also acknowledging the important of personal and cultural resistance to the forces of decline.
Risk Mutualization in Central Clearing: An Answer to the Cross-Guarantee Phenomenon from the Financial Stability Viewpoint
Authors: Friesz Melinda , Muratov-Szabó Kira , Prepuk Andrea , Váradi Kata
Published: August 2021

Central counterparties’ (CCPs) role is to take over the counterparty risk during trading. To fulfill its role, a CCP needs to operate a multi-level guarantee system that can absorb losses of clearing members’ defaults. Our main question is how the size of the guarantee system changes and how the cross-guarantee undertaking changes between clearing members and markets if the CCP merges the guarantee systems of different markets. This question is essential from a financial stability perspective since the size and the structure of the guarantee system will affect the loss-absorbing capacity of a CCP. We used Monte Carlo simulation to simulate a 30 year time-series for three different products, which gave us the basis for the value-at-risk-based margin calculation and the stress-test-based default fund calculation. Results show that merging the guarantee systems will always decrease the total value of the guarantees because the margin will decrease, which cannot be offset by the increase in the default fund size. We conclude that it is not optimal from the financial stability perspective to merge the guarantee systems. However, if the CCP wants to provide cheaper services, or if the clearing members are willing to cross-guarantee each other, merging is more suitable.
Investors’ Trading Activity and Information Asymmetry: Evidence from the Romanian Stock Market
Authors: Tudor Cristiana
Published: August 2021

This paper examines the problem of information asymmetry between foreign, local, institutional and individual investors on the Bucharest Stock Exchange (BVB) for the period 2004–2011. Using monthly returns for individual companies listed on BVB, stock market indices during the seven years period, as well as aggregate data on foreign and domestic investors (both institutional and individual) sales and purchases on the Romanian stock market, this research intends to provide an answer to the following question: Are foreign investors better informed than the domestic ones and continually achieve higher rates of return on the Romanian stock market? We compare the information advantage of the different investors’ categories by separating the stock in our data sample into two categories, namely blue-chips stocks (mostly stocks that are part of the BET index, and also containing one international stock, Erste Bank), and “regular” stocks. Subsequently, we study the explanatory power for stock returns of potential impact factors, which reflect the monthly net position of four groups of investors on the Romanian Stock market (Purchases-Sales) by employing multivariate regression models and a five variable VAR system. Ultimately, we are interested in whether investors in one particular category are consistently net buyers just before stock returns increase and are net sellers before stock returns decrease, thus suggesting they have an information advantage as compared to the domestic ones. Our aim is to provide robust empirical evidence on the nature of investors’ information asymmetry by utilising a unique data set and directly assessing relevant inter-relationships.
Overcoming the Challenges of Thermal Infrared Orthomosaics Using a Swath-Based Approach to Correct for Dynamic Temperature and Wind Effects
Authors: Malbéteau Yoann , Johansen Kasper , Aragon Bruno , Al-Mashhawari Samir K. , McCabe Matthew F.
Published: August 2021

The miniaturization of thermal infrared sensors suitable for integration with unmanned aerial vehicles (UAVs) has provided new opportunities to observe surface temperature at ultra-high spatial and temporal resolutions. In parallel, there has been a rapid development of software capable of streamlining the generation of orthomosaics. However, these approaches were developed to process optical and multi-spectral image data and were not designed to account for the often rapidly changing surface characteristics inherent in the collection and processing of thermal data. Although radiometric calibration and shutter correction of uncooled sensors have improved, the processing of thermal image data remains difficult due to (1) vignetting effects on the uncooled microbolometer focal plane array; (2) inconsistencies between images relative to in-flight effects (wind-speed and direction); (3) unsuitable methods for thermal infrared orthomosaic generation. Here, we use thermal infrared UAV data collected with a FLIR-based TeAx camera over an agricultural field at different times of the day to assess inconsistencies in orthophotos and their impact on UAV-based thermal infrared orthomosaics. Depending on the wind direction and speed, we found a significant difference in UAV-based surface temperature (up to 2 °C) within overlapping areas of neighboring flight lines, with orthophotos collected with tail wind being systematically cooler than those with head wind. To address these issues, we introduce a new swath-based mosaicking approach, which was compared to three standard blending modes for orthomosaic generation. The swath-based mosaicking approach improves the ability to identify rapid changes of surface temperature during data acquisition, corrects for the influence of flight direction relative to the wind orientation, and provides uncertainty (pixel-based standard deviation) maps to accompany the orthomosaic of surface temperature. It also produced more accurate temperature retrievals than the other three standard orthomosaicking methods, with a root mean square error of 1.2 °C when assessed against in situ measurements. As importantly, our findings demonstrate that thermal infrared data require appropriate processing to reduce inconsistencies between observations, and thus, improve the accuracy and utility of orthomosaics.
Synergistic Calibration of a Hydrological Model Using Discharge and Remotely Sensed Soil Moisture in the Paraná River Basin
Authors: Fleischmann Ayan Santos , Al Bitar Ahmad , Oliveira Aline Meyer , Siqueira Vinícius Alencar , Colossi Bibiana Rodrigues , Paiva Rodrigo Cauduro Dias de , Kerr Yann , Ruhoff Anderson , Fan Fernando Mainardi , Pontes Paulo Rógenes Monteiro , Collischonn Walter
Published: August 2021

Hydrological models are useful tools for water resources studies, yet their calibration is still a challenge, especially if aiming at improved estimates of multiple components of the water cycle. This has led the hydrologic community to look for ways to constrain models with multiple variables. Remote sensing estimates of soil moisture are very promising in this sense, especially in large areas for which field observations may be unevenly distributed. However, the use of such data to calibrate hydrological models in a synergistic way is still not well understood, especially in tropical humid areas such as those found in South America. Here, we perform multiple scenarios of multiobjective model optimization with in situ discharge and the SMOS L4 root zone soil moisture product for the Upper Paraná River Basin in South America (drainage area > 900,000 km²), for which discharge data for 136 river gauges are used. An additional scenario is used to compare the relative impacts of using all river gauges and a small subset containing nine gauges only. Across the basin, the joint calibration (CAL-DS) using discharge and soil moisture leads to improved precision and accuracy for both variables. The discharges estimated by CAL-DS (median KGE improvement for discharge was 0.14) are as accurate as those obtained with the calibration with discharge only (median equal to 0.14), while the CAL-DS soil moisture retrieval is practically as accurate (median KGE improvement for soil moisture was 0.11) as that estimated using the calibration with soil moisture only (median equal to 0.13). Nonetheless, the individual calibration with discharge rates is not able to retrieve satisfactory soil moisture estimates, and vice versa. These results show the complementarity between these two variables in the model calibration and highlight the benefits of considering multiple variables in the calibration framework. It is also shown that, by considering only nine gauges instead of 136 in the model optimization, the model is able to estimate reasonable discharge and soil moisture, although relatively less accurately and with less precision than for the entire dataset. In summary, this study shows that, for poorly gauged tropical basins, the joint calibration of SMOS soil moisture and a few in situ discharge gauges is capable of providing reasonable discharge and soil moisture estimates basin-wide and is more preferable than performing only a discharge-oriented optimization process.
Converting Optical Videos to Infrared Videos Using Attention GAN and Its Impact on Target Detection and Classification Performance
Authors: Uddin Mohammad Shahab , Hoque Reshad , Islam Kazi Aminul , Kwan Chiman , Gribben David , Li Jiang
Published: August 2021

To apply powerful deep-learning-based algorithms for object detection and classification in infrared videos, it is necessary to have more training data in order to build high-performance models. However, in many surveillance applications, one can have a lot more optical videos than infrared videos. This lack of IR video datasets can be mitigated if optical-to-infrared video conversion is possible. In this paper, we present a new approach for converting optical videos to infrared videos using deep learning. The basic idea is to focus on target areas using attention generative adversarial network (attention GAN), which will preserve the fidelity of target areas. The approach does not require paired images. The performance of the proposed attention GAN has been demonstrated using objective and subjective evaluations. Most importantly, the impact of attention GAN has been demonstrated in improved target detection and classification performance using real-infrared videos.
The Detection of Active Sinkholes by Airborne Differential LiDAR DEMs and InSAR Cloud Computing Tools
Authors: Guerrero Jesús , Sevil Jorge , Desir Gloria , Gutiérrez Francisco , Arnay Ángel García , Galve Jorge Pedro , Reyes-Carmona Cristina
Published: August 2021

InSAR (Interferometric Synthetic Aperture Radar) cloud computing and the subtraction of LiDAR (Light Detection and Ranging) DEMs (Digital Elevation Models) are innovative approaches to detect subsidence in karst areas. InSAR cloud computing allows for analyzing C-band Envisat and Sentinel S1 SAR images through web platforms to produce displacement maps of the Earth’s surface in an easy manner. The subtraction of serial LiDAR DEMs results in the same product but with a different level of accuracy and precision than InSAR maps. Here, we analyze the capability of these products to detect active sinkholes in the mantled evaporite karst of the Ebro Valley (NE Spain). We found that the capability of the displacement maps produced with open access, high-resolution airborne LiDAR DEMs was up to four times higher than InSAR displacement maps generated by the Geohazard Exploitation Platform (GEP). Differential LiDAR maps provide accurate information about the location, active sectors, maximum subsidence rate and growing trend of the most rapid and damaging sinkholes. Unfortunately, artifacts and the subsidence detection limit established at −4 cm/yr entailed important limitations in the precise mapping of the sinkhole edges and the detection of slow-moving sinkholes and small collapses. Although InSAR maps provided by GEP show a worse performance when identifying active sinkholes, in some cases they can serve as a complementary technique to overcome LiDAR limitations in urban areas.
A Systematic Review on the Integration of Remote Sensing and GIS to Forest and Grassland Ecosystem Health Attributes, Indicators, and Measures
Authors: Soubry Irini , Doan Thuy , Chu Thuan , Guo Xulin
Published: August 2021

It is important to protect forest and grassland ecosystems because they are ecologically rich and provide numerous ecosystem services. Upscaling monitoring from local to global scale is imperative in reaching this goal. The SDG Agenda does not include indicators that directly quantify ecosystem health. Remote sensing and Geographic Information Systems (GIS) can bridge the gap for large-scale ecosystem health assessment. We systematically reviewed field-based and remote-based measures of ecosystem health for forests and grasslands, identified the most important ones and provided an overview on remote sensing and GIS-based measures. We included 163 English language studies within terrestrial non-tropical biomes and used a pre-defined classification system to extract ecological stressors and attributes, collected corresponding indicators, measures, and proxy values. We found that the main ecological attributes of each ecosystem contribute differently in the literature, and that almost half of the examined studies used remote sensing to estimate indicators. The major stressor for forests was “climate change”, followed by “insect infestation”; for grasslands it was “grazing”, followed by “climate change”. “Biotic interactions, composition, and structure” was the most important ecological attribute for both ecosystems. “Fire disturbance” was the second most important for forests, while for grasslands it was “soil chemistry and structure”. Less than a fifth of studies used vegetation indices; NDVI was the most common. There are monitoring inconsistencies from the broad range of indicators and measures. Therefore, we recommend a standardized field, GIS, and remote sensing-based approach to monitor ecosystem health and integrity and facilitate land managers and policy-makers.
MARE: Self-Supervised Multi-Attention REsu-Net for Semantic Segmentation in Remote Sensing
Authors: Marsocci Valerio , Scardapane Simone , Komodakis Nikos
Published: August 2021

Scene understanding of satellite and aerial images is a pivotal task in various remote sensing (RS) practices, such as land cover and urban development monitoring. In recent years, neural networks have become a de-facto standard in many of these applications. However, semantic segmentation still remains a challenging task. With respect to other computer vision (CV) areas, in RS large labeled datasets are not very often available, due to their large cost and to the required manpower. On the other hand, self-supervised learning (SSL) is earning more and more interest in CV, reaching state-of-the-art in several tasks. In spite of this, most SSL models, pretrained on huge datasets like ImageNet, do not perform particularly well on RS data. For this reason, we propose a combination of a SSL algorithm (particularly, Online Bag of Words) and a semantic segmentation algorithm, shaped for aerial images (namely, Multistage Attention ResU-Net), to show new encouraging results (i.e., 81.76% mIoU with ResNet-18 backbone) on the ISPRS Vaihingen dataset.
Automated Detection of Animals in Low-Resolution Airborne Thermal Imagery
Authors: Ulhaq Anwaar , Adams Peter , Cox Tarnya E. , Khan Asim , Low Tom , Paul Manoranjan
Published: August 2021

Detecting animals to estimate abundance can be difficult, particularly when the habitat is dense or the target animals are fossorial. The recent surge in the use of thermal imagers in ecology and their use in animal detections can increase the accuracy of population estimates and improve the subsequent implementation of management programs. However, the use of thermal imagers results in many hours of captured flight videos which require manual review for confirmation of species detection and identification. Therefore, the perceived cost and efficiency trade-off often restricts the use of these systems. Additionally, for many off-the-shelf systems, the exported imagery can be quite low resolution (<9 Hz), increasing the difficulty of using automated detections algorithms to streamline the review process. This paper presents an animal species detection system that utilises the cost-effectiveness of these lower resolution thermal imagers while harnessing the power of transfer learning and an enhanced small object detection algorithm. We have proposed a distant object detection algorithm named Distant-YOLO (D-YOLO) that utilises YOLO (You Only Look Once) and improves its training and structure for the automated detection of target objects in thermal imagery. We trained our system on thermal imaging data of rabbits, their active warrens, feral pigs, and kangaroos collected by thermal imaging researchers in New South Wales and Western Australia. This work will enhance the visual analysis of animal species while performing well on low, medium and high-resolution thermal imagery.
Sentinel-1&2 Multitemporal Water Surface Detection Accuracies, Evaluated at Regional and Reservoirs Level
Authors: Peña-Luque Santiago , Ferrant Sylvain , Cordeiro Mauricio C. R. , Ledauphin Thomas , Maxant Jerome , Martinez Jean-Michel
Published: August 2021

Water stock monitoring is a major issue for society on a local and global scale. Sentinel-1&2 satellites provide frequent acquisitions to track water surface dynamics, proxy variables to enable water surface volume monitoring. How do we combine such observations along time for each sensor? What advantages and disadvantages of single-date, monthly or time-windowed estimations? In this context, we analysed the impact of merging information through different types and lengths of time-windows. Satellite observations were processed separately on optical (Sentinel-2) and radar (Sentinel-1) water detectors at 10 m resolution. The analysis has been applied at two scales. First, validating with 26 large scenes (110 × 110 km) in different climatic zones in France, time-windows yielded an improvement on radar detection (F1-score improved from 0.72 to 0.8 for 30 days on average logic) while optical performances remained stable (F1-score 0.89). Second, validating reservoir area estimations with 29 instrumented reservoirs (20–1250 ha), time-windows presented in all cases an improvement on both optical and radar error for any window length (5–30 days). The mean relative absolute error in optical area detection improved from 16.9% on single measurements to 12.9% using 15 days time-windows, and from 22.15% to 15.1% in radar detection). Regarding reservoir filling rates, we identified an increased negative bias for both sensors when the reservoir is nearly full. This work helped to compare accuracies of separate optical and radar capabilities, where optical statistically outperforms radar at both local and large scale to the detriment of less frequent measurements. Furthermore, we propose a geomorphological indicator of reservoirs to predict the quality of radar area monitoring (R2 = 0.58). In conclusion, we suggest the use of time-windows on operational water mapping or reservoir monitoring systems, using 10–20 days time-windows with average logic, providing more frequent and faster information to water managers in periods of crisis (e.g., water shortage) compared to monthly estimations.
Landslide Susceptibility Modeling: An Integrated Novel Method Based on Machine Learning Feature Transformation
Authors: Al-Najjar Husam A. H. , Pradhan Biswajeet , Kalantar Bahareh , Sameen Maher Ibrahim , Santosh M. , Alamri Abdullah
Published: August 2021

Landslide susceptibility modeling, an essential approach to mitigate natural disasters, has witnessed considerable improvement following advances in machine learning (ML) techniques. However, in most of the previous studies, the distribution of input data was assumed as being, and treated, as normal or Gaussian; this assumption is not always valid as ML is heavily dependent on the quality of the input data. Therefore, we examine the effectiveness of six feature transformations (minimax normalization (Std-X), logarithmic functions (Log-X), reciprocal function (Rec-X), power functions (Power-X), optimal features (Opt-X), and one-hot encoding (Ohe-X) over the 11conditioning factors (i.e., altitude, slope, aspect, curvature, distance to road, distance to lineament, distance to stream, terrain roughness index (TRI), normalized difference vegetation index (NDVI), land use, and vegetation density). We selected the frequent landslide-prone area in the Cameron Highlands in Malaysia as a case study to test this novel approach. These transformations were then assessed by three benchmark ML methods, namely extreme gradient boosting (XGB), logistic regression (LR), and artificial neural networks (ANN). The 10-fold cross-validation method was used for model evaluations. Our results suggest that using Ohe-X transformation over the ANN model considerably improved performance from 52.244 to 89.398 (37.154% improvement).
Dynamic Cooling Effects of Permanent Urban Green Spaces in Beijing, China
Authors: Zhao Jiacheng , Zhao Xiang , Liang Shunlin , Wang Haoyu , Liu Naijing , Liu Ping , Wu Donghai
Published: August 2021

Urban green spaces (UGSs) play a critical role in human thermal comfort, energy consumption and urban ecology. Although the heat mitigation capability of UGSs has been frequently reported, many of the current understandings are based on short-term observations, and the long-term temporal dynamics of UGS cooling effects are still lacking. This gap may cause over- or underestimation and largely ignores how the cooling effects change with climate change and urban growth. Accordingly, we used Landsat-based time series data to analyze the changes in permanent UGS greenness, surface-cooling effects and their biophysical responses in Beijing in the past 40 years (1984–2020). The results demonstrate segmented changes in UGS surface cooling that were mainly linked to the responses of canopy transpiration and albedo to vegetation conditions. During a rapid greening of UGSs in the recent two decades, transpiration cooling dominated albedo-induced warming to provide a discernable cooling enhancement. In addition, such enhancement showed seasonal differences ranging from less than 1 °C to more than 2 °C, and the most evident enhancement occurred on summer days (~2.4 °C) when vegetation is most needed to provide cooling. The highlighted dynamics of UGSs help urban planners better balance the maintenance costs and the environmental gains for UGS management.
How Do Two- and Three-Dimensional Urban Structures Impact Seasonal Land Surface Temperatures at Various Spatial Scales? A Case Study for the Northern Part of Brooklyn, New York, USA
Authors: He Wen , Cao Shisong , Du Mingyi , Hu Deyong , Mo You , Liu Manqing , Zhao Jianghong , Cao Yuee
Published: August 2021

Identifying the driving factors of urban land surface temperatures (U-LSTs) is critical in improving urban thermal environments and in supporting the sustainable development of cities. Previous studies have demonstrated that two- and three-dimensional (2D and 3D) urban structure parameters (USPs) largely influence seasonal U-LSTs. However, the effects of 2D and 3D USPs on seasonal U-LSTs at different spatial scales still await a general explanation. In this study, we used very-high-resolution remotely sensed data to investigate how 2D and 3D USPs impact seasonal U-LSTs at different spatial scales (including pixel and city block scales). In addition, the influences of various functional zones on U-LSTs were analyzed. The results show that, (1) generally, the links between USPs and U-LSTs at the city block scale were more obvious than those at the pixel scale, e.g., the Pearson correlation coefficient (r) between U-LST and the mean building height at the city block scale (summer: r = −0.156) was higher than that at the pixel scale (summer: r = −0.081). Tree percentage yielded a considerable cooling effect on summer U-LSTs on both the pixel (r = −0.199) and city block (r = −0.369) scales, and the effect was more obvious in regions with tall trees. (2) The independently total explained variances (R2) of 3D USPs on seasonal U-LSTs were considerably higher than those of 2D USPs in most urban functional zones (UFZs), suggesting the distinctive roles of 3D USPs in U-LST regulation at the local scale. Three-dimensional USPs (R2 value = 0.66) yielded more decisive influences on summer U-LSTs than 2D USPs did (R2 value = 0.48). (3) Manufacturing zones yielded the highest U-LST, followed by residential and commercial zones. Notably, it is found that the explained variances of the total study area for seasonal U-LSTs were significantly lower than those of each UFZ, suggesting the different roles of 2D and 3D USPs played in various UFZs and that it is critical to explain U-LST variations by using UFZs.
Efficient Sub-1 Minute Analysis of Selected Biomarker Catecholamines by Core-Shell Hydrophilic Interaction Liquid Chromatography (HILIC) with Nanomolar Detection at a Boron-Doped Diamond (BDD) Electrode
Authors: Alsaeedi Majidah , Alghamdi Huda , Hayes Phyllis , Hogan Anna , Glennon Jeremy
Published: August 2021

A rapid, sensitive method for the separation of catecholamine biomarkers (CAs), of importance in traumatic brain injury (TBI) and in Parkinson’s disease (PD), has been successfully developed using hydrophilic interaction liquid chromatography (HILIC). Dopamine (DA), epinephrine (EPI), and norepinephrine (NE) are known to be three to fivefold elevated above normal in traumatic brain injury (TBI) patients. HILIC facilitates the rapid and efficient separation of these polar biomarkers, which can be poorly retained by reversed-phase liquid chromatography (RPLC), while electrochemical detection (ECD) at the boron-doped diamond (BDD) electrode provides enhanced nanomolar detection. Three HILIC columns were compared, namely the superficially porous (core-shell) Z-HILIC column and the Z-cHILIC and Z-HILIC fully porous columns. The core-shell Z-HILIC showed the highest efficiency with a rapid separation within 60 s. The HILIC method utilizing the core-shell Z-HILIC column was initially optimized for the simultaneous analysis of DA, EPI, and NE using UV detection. The advantages of using the BDD electrode over UV detection were explored, and the improved limits of detection (LODs, S/N = 3) measured were 40, 50, and 50 nM for DA, EPI, and NE, respectively. Method validation is reported in terms of the linearity, repeatability, reproducibility, and LODs. Furthermore, the proposed method was successfully applied to the real sample analysis of urinary CAs following phenylboronic acid (PBA) solid phase extraction (SPE) pretreatment.
The Impact of Coparenting on Mothers’ COVID-19-Related Stressors
Authors: Pruett Marsha Kline , Alschech Jonathan , Saini Michael
Published: August 2021

To test and explore whether more positive coparenting will significantly predict lower COVID-19-related stress across family configurations and dynamics and across both higher- and lower-income mothers, we developed and circulated an online survey among mothers from the U.S. and Canada. Coparenting was measured using the Coparenting Across Family Structures (CoPAFS) short form (27 items) scale, comprised of factors representing five coparenting dimensions: communication, respect, trust, animosity, and valuing the other parent. Items specific to COVID-19 stressors assessed the types of stressors each parent faced. The sample consisted of 236 North American mothers, mostly white (n = 187, 79.2%) and aged 30–50 years. The surveyed mothers reported a consistent and significant relation between more positive coparenting and less COVID-19-related stressors whether parents were living together or not, married or divorced, and with a lower or higher income level, suggesting the importance and centrality of positive coparenting as a key factor for family well-being. Coparenting was especially predictive among mothers who were never married and those with lower incomes.
Does the Sustainability of the Anthropocene Technosphere Imply an Existential Risk for Our Species? Thinking with Peter Haff
Authors: Mendes João Ribeiro
Published: August 2021

Throughout the 20th century, several thinkers noticed that Technology was becoming a global phenomenon. More recently, US geologist Peter Haff claimed that a Technosphere is now in place and can be conceived as a new Earth geological system. This unprecedented situation is creating enormous challenges not only for our species, since more and more of its members are now dependent on the subsistence of this man-made sphere, but also for other species and natural ecosystems that have become increasingly dependent on it. Perhaps the most crucial of these challenges is the sustainability of the Technosphere itself. In the first part of the article, I attempted a critical reconstruction of Haff’s Technosphere concept. The second part is dedicated to analyzing how the unsustainability of the Technosphere represents a global catastrophic risk and ultimately an existential risk.
Fertilisation with Potassium Silicate Exerted Little Effect on Production Parameters of Cucumbers Exposed to UV and Drought
Authors: Grašič Mateja , Germ Mateja , Vogel-Mikuš Katarina , Ojdanič Nik , Gaberščik Alenka , Golob Aleksandra
Published: August 2021

(1) Background: Cucumbers are highly sensitive to drought and UV-B radiation, which may also act synergistically. Silicon is a beneficial element for plants, as it can alleviate negative effects of different environmental constraints. Studies revealed that fertilisation of cucumbers with silicon showed a variety of positive effects, which increased plant vitality. The aim of this study was to investigate the role of potassium silicate in shaping cucumber traits and in mitigating potential adverse effects of drought and UV radiation. (2) Methods: Plants were exposed to different treatments regarding water availability, UV radiation, and potassium silicate addition. During the experiment, the level of plant-available silicon and total silicon content in the soil were monitored along with soil moisture. At the end of the experiment, the leaf element composition, leaf biochemical and leaf physiological properties were analysed in addition to growth and production parameters of these cucumbers. (3) Results: Among the three studied factors, insufficient water supply had the most negative impact on measured parameters, causing a significant decline in cucumber growth and production. UV radiation had an adverse impact on various studied parameters, while potassium silicate addition negatively affected production parameters. Fertilisation with potassium silicate increased the level of plant-available silicon in the soil and leaf silicon content. (4) Conclusions: Fertilisation with potassium silicate exerted little impact on production parameters of cucumbers exposed to ambient UV radiation and drought. Significant interactions between the studied factors were detected for the aboveground vegetative plant parts.
The Integrated Role of Personal Values and Theory of Planned Behavior to Form a Sustainable Entrepreneurial Intention
Authors: Yasir Nosheena , Mahmood Nasir , Mehmood Hafiz Shakir , Rashid Osama , Liren An
Published: August 2021

Intentions have been described as a key driver of sustainable entrepreneurial opportunity recognition and eventually activity. As a result of this study, interest may increase in entrepreneurship intentions across numerous entrepreneurial levels and styles, specifically from the point of view of sustainability. However, research to date has not been able to completely determine how the intrinsic complications of instantaneously producing social, environmental, and economic means will have an impact on the intentions of university students. This study sought to inspect the impact of self-transcending and self-enhancing value on the advent of intentions. The theory of planned behavior is an adaptive theory that this study quantitatively analyzed using a structural equation model and survey data from 577 university students in Punjab, Pakistan. The empirical findings show that altruistic, biospheric, hedonic, and egoistic values all have an indirect effect on sustainability-driven entrepreneurial intentions, which is important to understand when assessing attitudes toward sustainable entrepreneurship and perceived behavior control. In essence, attitudes, perceived behavior, and social norms all affect aspirations to become a sustainable entrepreneur. In real-world terms, the findings indicate that by using value activation techniques to increase attitudes and educational interest, practitioners may promote sustainable entrepreneurial intentions. It is also suggested how government services could be improved as part of the strategy.
Understanding the Role of Leadership Styles of Erdogan and Merkel in Sustainability of Turkey-European Union Relations: A Leadership Trait Analysis
Authors: Kutlu Erdi , Cengiz Çağdaş , Arman Murat Necip , Ozeren Emir
Published: August 2021

This study aims to understand the role of the leadership styles of Turkish President Recep Tayyip Erdogan and German Chancellor Angela Merkel in European Union-Turkey relations by conducting a Leadership Trait Analysis (LTA), which takes into account the leaders’ personalities in foreign policy. The article makes use of the verbal records of the two leaders regarding the bilateral relations between their countries and the European Union. The results unveil that the two leaders’ personal characteristics bear similarities to a considerable extent; i.e., both leaders are sceptical in inter-personal relations, discernibly intuitive, self-confident and so forth. The study suggests that those personal traits of the leaders which have occasionally outweighed crude rationality have been some of the important factors enabling the sustainability of relations between Turkey and the EU against all odds.
Benefits of Legume Species in an Agroforestry Production System of Yellow Pitahaya in the Ecuadorian Amazon
Authors: Vargas-Tierras Yadira , Díaz Alejandra , Caicedo Carlos , Macas Julio , Suárez-Tapia Alfonso , Viera William
Published: August 2021

Agroforestry systems have become an alternative that promotes the conservation of natural resources and the sustainable production of fruit crops in the Ecuadorian Amazon. However, it is required to demonstrate the benefit of the companion species that make up these production systems. The objective of this research was to determine how the legume species within an agroforestry system influence the yield of yellow dragon fruit (pitahaya), carbon sequestration and nutritional contribution. The experiment was carried out in Palora (province of Morona Santiago) and organized in a randomized complete block design with three replications. The treatments were two agroforestry arrangements and the monoculture as a control treatment. Erythrina poeppigiana, Gliricidia sepium and Flemingia macrophylla were used in the agroforestry arrangements for the contribution of biomass. Results showed that during the five years of study, pitahaya yield was influenced by the quality of the leaf litter (biomass) incorporated in to the fruit crop. Biomass from E. poeppigiana and F. macrophylla as companion crops contributed a greater amount of Ca and Mg, increased C sequestration and crop yield. The results suggest that the use of legume species in agroforestry systems positively affects pitahaya productivity, enabling sustainable agriculture in the Ecuadorian Amazon.