bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Improved Semi-Automated Processing Algorithms for the Creation of Rockfall Databases
Authors: Schovanec Heather , Walton Gabriel , Kromer Ryan , Malsam Adam
Published: April 2021

While terrestrial laser scanning and photogrammetry provide high quality point cloud data that can be used for rock slope monitoring, their increased use has overwhelmed current data analysis methodologies. Accordingly, point cloud processing workflows have previously been developed to automate many processes, including point cloud alignment, generation of change maps and clustering. However, for more specialized rock slope analyses (e.g., generating a rockfall database), the creation of more specialized processing routines and algorithms is necessary. More specialized algorithms include the reconstruction of rockfall volumes from clusters and points and automatic classification of those volumes are both processing steps required to automate the generation of a rockfall database. We propose a workflow that can automate all steps of the point cloud processing workflow. In this study, we detail adaptions to commonly used algorithms for rockfall monitoring use cases, such as Multiscale Model to Model Cloud Comparison (M3C2). This workflow details the entire processing pipeline for rockfall database generation using terrestrial laser scanning.
Advection Fog over the Eastern Yellow Sea: WRF Simulation and Its Verification by Satellite and In Situ Observations
Authors: Lee Eunjeong , Kim Jung-Hoon , Heo Ki-Young , Cho Yang-Ki
Published: April 2021

An observed sea fog event over the Eastern Yellow Sea on 15–16 April 2012 was reproduced in the Weather Research and Forecasting (WRF) simulation with high-resolution to investigate the roles of physical processes and synoptic-scale flows on advection fog with phase transition. First, it was verified by a satellite-based fog detection algorithm and in situ observation data. In the simulation, longwave (infrared) radiative cooling (LRC) with a downward turbulent sensible heat flux (SHF), due to the turbulence after sunset, triggered cloud formation over the surface when warm-moist air advection occurred. At night, warm air advection with continuous cooling due to longwave radiation and SHF near the surface modulated the change of the SHF from downward to upward, resulting in a drastic increase in the turbulent latent heat flux (LHF) that provided sufficient moisture at the lower atmosphere (self-moistening). This condition represents a transition from cold-sea fog to warm-sea fog. Enhanced turbulent mixing driven by a buoyancy force increased the depth of the sea fog and the marine atmospheric boundary layer (MABL) height, even at nighttime. In addition, cold air advection with a prevailing northerly wind at the top of the MABL led to a drastic increase in turbulent mixing and the MABL height and rapid growth of the height of sea fog. After sunrise, shortwave radiative warming in the fog layers offsetting the LRC near the surface weakened thermal instability, which contributed to the reduction in the MABL height, even during the daytime. In addition, dry advection of the northerly wind induced dissipation of the fog via evaporation. An additional sensitivity test of sea surface salinity showed weaker and shallower sea fog than the control due to the decrease in both the LHF and local self-moistening. Detailed findings from the simulated fog event can help to provide better guidance for fog detection using remote sensing.
National Mapping of New Zealand Pasture Productivity Using Temporal Sentinel-2 Data
Authors: Amies Alexander C. , Dymond John R. , Shepherd James D. , Pairman David , Hoogendoorn Coby , Sabetizade Marmar , Belliss Stella E.
Published: April 2021

A national map of pasture productivity, in terms of mass of dry matter yield per unit area and time, enables evaluation of regional and local land-use suitability. Difficulty in measuring this quantity at scale directed this research, which utilises four years of Sentinel-2 satellite imagery and collected pasture yield measurements to develop a model of pasture productivity. The model uses a Normalised Difference Vegetation Index (NDVI), with spatio-temporal segmentation and averaging, to estimate mean annual pasture productivity across all of New Zealand’s grasslands with a standard error of prediction of 2.2 t/ha/y. Regional aggregates of pasture yield demonstrate expected spatial variations. The pasture productivity map may be used to classify grasslands objectively into stratified levels of production on a national scale. Due to its ability to highlight areas of land use intensification suitability, the national map of pasture productivity is of value to landowners, land users, and environmental scientists.
Eddy Current Sensor System for Tilting Independent In-Process Measurement of Magnetic Anisotropy
Authors: Wendler Frank , Munjal Rohan , Waqas Muhammad , Laue Robert , Härtel Sebastian , Awiszus Birgit , Kanoun Olfa
Published: April 2021

Modern production equipment is based on the results of quality control as well as process parameters. The magnetic anisotropy of materials is closely connected to internal mechanical stress by the Villari effect, and also to hardening effects due to plastic deformations, and could therefore provide an interesting basis for process control. Nevertheless, the analysis of anisotropic properties is extremely sensitive to sensor and workpiece misalignments, such as tilting. In this work, a novel eddy current sensor system is introduced, performing a non-contact measurement of the magnetic anisotropy of a workpiece and realizing a separation and correction of tilting effects. The measurement principle is demonstrated with the example of two samples with different magnetic anisotropy values induced by cold forming. Both samples are analyzed under different tilt angles between the sensor axis and the surface of the workpiece. In this work, digital signal processing is demonstrated on the acquired raw data in order to differentiate the effects of tilt and of anisotropy, with the use of preliminary results as an example of two prepared samples.
Automated Driving with Cooperative Perception Using Millimeter-Wave V2V Communications for Safe Overtaking
Authors: Fukatsu Ryuichi , Sakaguchi Kei
Published: April 2021

The combination of onboard sensors on vehicles with wireless communication has great advantages over the conventional driving systems in terms of safety and reliability. This technique is often called cooperative perception. Cooperative perception is expected to compensate for blind spots in dynamic maps, which are caused by obstacles. Few blind spots in dynamic maps can improve the safety and reliability of driving thanks to the additional information beyond the sensing of the onboard sensors. In this paper, we analyzed the required sensor data rate to be exchanged for the cooperative perception in order to enable a new level of safe and reliable automated driving in overtaking scenario. The required sensor data rate was calculated by the combination of recognition and vehicle movement to adopt realistic assumptions. In the end of the paper, we compared the required sensor data rate with the outage data rate realized by the conventional V2V communication and millimeter-wave communication. The results showed the indispensability of millimeter-wave communications in automated driving systems.
Ultra-Low-Power Wide Range Backscatter Communication Using Cellular Generated Carrier
Authors: Sheikh Muhammad Usman , Xie Boxuan , Ruttik Kalle , Yiğitler Hüseyin , Jäntti Riku , Hämäläinen Jyri
Published: April 2021

With the popularization of Internet-of-things (IoT) and wireless communication systems, a diverse set of applications in smart cities are emerging to improve the city-life. These applications usually require a large coverage area and minimal operation and maintenance cost. To this end, the recently emerging backscatter communication (BC) is gaining interest in both industry and academia as a new communication paradigm that provides high energy efficient communications that may even work in a battery-less mode and, thus, it is well suited for smart city applications. However, the coverage of BC in urban area deployments is not available, and the feasibility of its utilization for smart city applications is not known. In this article, we present a comprehensive coverage study of a practical cellular carrier-based BC system for indoor and outdoor scenarios in a downtown area of a Helsinki city. In particular, we evaluate the coverage outage performance of different low-power and wide area technologies, i.e., long range (LoRa) backscatter, arrow band-Internet of Things (NB-IoT), and Bluetooth low energy (BLE) based BC at different frequencies of operation. To do so, we carry out a comprehensive campaign of simulations while using a sophisticated three-dimensional (3D) ray tracing (RT) tool, ITU outdoor model, and 3rd generation partnership project (3GPP) indoor hotspot model. This study also covers the energy harvesting aspects of backscatter device, and it highlights the importance of future backscatter devices with high energy harvesting efficiency. The simulation results and discussion provided in this article will be helpful in understanding the coverage aspects of practical backscatter communication system in a smart city environment.
Designing Mid-Infrared Gold-Based Plasmonic Slot Waveguides for CO2-Sensing Applications
Authors: Saeidi Parviz , Jakoby Bernhard , Pühringer Gerald , Tortschanoff Andreas , Stocker Gerald , Dubois Florian , Spettel Jasmin , Grille Thomas , Jannesari Reyhaneh
Published: April 2021

Plasmonic slot waveguides have attracted much attention due to the possibility of high light confinement, although they suffer from relatively high propagation loss originating from the presence of a metal. Although the tightly confined light in a small gap leads to a high confinement factor, which is crucial for sensing applications, the use of plasmonic guiding at the same time results in a low propagation length. Therefore, the consideration of a trade-off between the confinement factor and the propagation length is essential to optimize the waveguide geometries. Using silicon nitride as a platform as one of the most common material systems, we have investigated free-standing and asymmetric gold-based plasmonic slot waveguides designed for sensing applications. A new figure of merit (FOM) is introduced to optimize the waveguide geometries for a wavelength of 4.26 µm corresponding to the absorption peak of CO2, aiming at the enhancement of the confinement factor and propagation length simultaneously. For the free-standing structure, the achieved FOM is 274.6 corresponding to approximately 42% and 868 µm for confinement factor and propagation length, respectively. The FOM for the asymmetric structure shows a value of 70.1 which corresponds to 36% and 264 µm for confinement factor and propagation length, respectively.
P4G2Go: A Privacy-Preserving Scheme for Roaming Energy Consumers of the Smart Grid-to-Go
Authors: Farao Aristeidis , Veroni Eleni , Ntantogian Christoforos , Xenakis Christos
Published: April 2021

Due to its flexibility in terms of charging and billing, the smart grid is an enabler of many innovative energy consumption scenarios. One such example is when a landlord rents their property for a specific period to tenants. Then the electricity bill could be redirected from the landlord’s utility to the tenant’s utility. This novel scenario of the smart grid ecosystem, defined in this paper as Grid-to-Go (G2Go), promotes a green economy and can drive rent reductions. However, it also creates critical privacy issues, since utilities may be able to track the tenant’s activities. This paper presents P4G2Go, a novel privacy-preserving scheme that provides strong security and privacy assertions for roaming consumers against honest but curious entities of the smart grid. At the heart of P4G2Go lies the Idemix cryptographic protocol suite, which utilizes anonymous credentials and provides unlinkability of the consumer activities. Our scheme is complemented by the MASKER protocol, used to protect the consumption readings, and the FIDO2 protocol for strong and passwordless authentication. We have implemented the main components of P4G2Go, to quantitatively assess its performance. Finally, we reason about its security and privacy properties, proving that P4G2Go achieves to fulfill the relevant objectives.
Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks
Authors: Lai Chih-Ching , Wang Hsin-Kai , Wang Fu-Nien , Peng Yu-Ching , Lin Tzu-Ping , Peng Hsu-Hsia , Shen Shu-Huei
Published: April 2021

The accuracy in diagnosing prostate cancer (PCa) has increased with the development of multiparametric magnetic resonance imaging (mpMRI). Biparametric magnetic resonance imaging (bpMRI) was found to have a diagnostic accuracy comparable to mpMRI in detecting PCa. However, prostate MRI assessment relies on human experts and specialized training with considerable inter-reader variability. Deep learning may be a more robust approach for prostate MRI assessment. Here we present a method for autosegmenting the prostate zone and cancer region by using SegNet, a deep convolution neural network (DCNN) model. We used PROSTATEx dataset to train the model and combined different sequences into three channels of a single image. For each subject, all slices that contained the transition zone (TZ), peripheral zone (PZ), and PCa region were selected. The datasets were produced using different combinations of images, including T2-weighted (T2W) images, diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) images. Among these groups, the T2W + DWI + ADC images exhibited the best performance with a dice similarity coefficient of 90.45% for the TZ, 70.04% for the PZ, and 52.73% for the PCa region. Image sequence analysis with a DCNN model has the potential to assist PCa diagnosis.
Subsentence Extraction from Text Using Coverage-Based Deep Learning Language Models
Authors: Lim JongYoon , Sa Inkyu , Ahn Ho Seok , Gasteiger Norina , Lee Sanghyub John , MacDonald Bruce
Published: April 2021

Sentiment prediction remains a challenging and unresolved task in various research fields, including psychology, neuroscience, and computer science. This stems from its high degree of subjectivity and limited input sources that can effectively capture the actual sentiment. This can be even more challenging with only text-based input. Meanwhile, the rise of deep learning and an unprecedented large volume of data have paved the way for artificial intelligence to perform impressively accurate predictions or even human-level reasoning. Drawing inspiration from this, we propose a coverage-based sentiment and subsentence extraction system that estimates a span of input text and recursively feeds this information back to the networks. The predicted subsentence consists of auxiliary information expressing a sentiment. This is an important building block for enabling vivid and epic sentiment delivery (within the scope of this paper) and for other natural language processing tasks such as text summarisation and Q&A. Our approach outperforms the state-of-the-art approaches by a large margin in subsentence prediction (i.e., Average Jaccard scores from 0.72 to 0.89). For the evaluation, we designed rigorous experiments consisting of 24 ablation studies. Finally, our learned lessons are returned to the community by sharing software packages and a public dataset that can reproduce the results presented in this paper.
Haptic Manipulation of 3D Scans for Geometric Feature Enhancement
Authors: Turlapati Sri Harsha , Accoto Dino , Campolo Domenico
Published: April 2021

Localisation of geometric features like holes, edges, slots, etc. is vital to robotic planning in industrial automation settings. Low-cost 3D scanners are crucial in terms of improving accessibility, but pose a practical challenge to feature localisation because of poorer resolution and consequently affect robotic planning. In this work, we address the possibility of enhancing the quality of a 3D scan by a manual ’touch-up’ of task-relevant features, to ensure their automatic detection prior to automation. We propose a framework whereby the operator (i) has access to both the actual work-piece and its 3D scan; (ii) evaluates the missing salient features from the scan; (iii) uses a haptic stylus to physically interact with the actual work-piece, around such specific features; (iv) interactively updates the scan using the position and force information from the haptic stylus. The contribution of this work is the use of haptic mismatch for geometric update. Specifically, the geometry from the 3D scan is used to predict haptic feedback at a point on the work-piece surface. The haptic mismatch is derived as a measure of error between this prediction and the real interaction forces from physical contact at that point on the work-piece. The geometric update is driven until the haptic mismatch is minimised. Convergence of the proposed algorithm is first numerically verified on an analytical surface with simulated physical interaction. Error analysis of the surface position and orientations were also plotted. Experiments were conducted using a motion capture system providing sub-mm accuracy in position and a 6 axis F/T sensor. Missing features are successfully detected after the update of the scan using the proposed method in an experiment.
Cityscape LoRa Signal Propagation Predicted and Tested Using Real-World Building-Data Based O-FDTD Simulations and Experimental Characterization
Authors: Adão Ricardo M. R. , Balvís Eduardo , Carpentier Alicia V. , Michinel Humberto , Nieder Jana B.
Published: April 2021

The age of the Internet of Things (IoT) and smart cities calls for low-power wireless communication networks, for which the Long-Range (LoRa) is a rising star. Efficient network engineering requires the accurate prediction of the Received Signal Strength Indicator (RSSI) spatial distribution. However, the most commonly used models either lack the physical accurateness, resolution, or versatility for cityscape real-world building distribution-based RSSI predictions. For this purpose, we apply the 2D electric field wave-propagation Oscillator Finite-Difference Time-Domain (O-FDTD) method, using the complex dielectric permittivity to model reflection and absorption effects by concrete walls and the receiver sensitivity as the threshold to obtain a simulated coverage area in a 600 × 600 m2 square. Further, we report a simple and low-cost method to experimentally determine the signal coverage area based on mapping communication response-time delays. The simulations show a strong building influence on the RSSI, compared against the Free-Space Path (FSPL) model. We obtain a spatial overlap of 84% between the O-FDTD simulated and experimental signal coverage maps. Our proof-of-concept approach is thoroughly discussed compared to previous works, outlining error sources and possible future improvements. O-FDTD is demonstrated to be most promising for both indoors and outdoors applications and presents a powerful tool for IoT and smart city planners.
Monitoring of Remaining Thiophenic Compounds in Liquid Fuel Desulphurization Studies Using a Fast HPLC-UV Method
Authors: Kapsali Vasiliki , Triantafyllidis Konstantinos , Deliyanni Eleni , Samanidou Victoria
Published: April 2021

Thiophenic compounds constitute a class of sulfur compounds derived by thiophene, containing at least one thiophenic ring. Their presence in fuels (crude oil, etc.) is important and can reach 3% m/m. The combustion of fuels leads to the formation of sulfur oxides a severe source of environmental pollution issues, such as acid rain with adverse effects both to humans and to the environment. To reduce such problems, the EU and other regulatory agencies worldwide set increasingly stringent regulations for sulfur content in fuels resulting in the necessity for intense desulphurization processes. However, most of these processes are inefficient in the total removal of sulfur compounds. Therefore, thiophenic compounds such as benzothiophenes and dibenzothiophenes are still present in heavier fractions of petroleum, therefore, their determination is of great importance. Until now, all HPLC methods applied in similar studies use gradient elution programs that may last more than 25 min with no validation results provided. To fill this gap, the aim of the present study was to develop and validate a simple and fast HPLC-UV method in order to be used as a useful monitoring tool in the evaluation studies of novel desulfurization technologies by means of simultaneous determination of dibenzothiophene (DBT) and 4,6-dimethyl-dibenzothiophene and dibenzothiophene sulfone in the desulfurization effluents.
Accumulation and Phytotoxicity of Two Commercial Biocides in the Lichen Evernia prunastri and the Moss Brachythecium sp.
Authors: Vannini Andrea , Canali Giulia , Favero-Longo Sergio Enrico , Loppi Stefano
Published: April 2021

This study investigated the accumulation and phytotoxicity of two commercial biocides widely used for the removal of biological colonization from monuments, namely Biotin T® (3%) and Preventol RI80® (2%), on lichen and moss model species, specifically, Evernia prunastri and Brachythecium sp. The active compounds, benzalkonium chloride (BAC) for Preventol RI80 and isothiazolinone (OIT) for Biotin T, were accumulated in similar amounts in both species without significant changes for up to 21 days. Both compounds caused a severe impairment of the photosynthetic apparatus of these species, without any recovery over time, although Biotin T showed a faster and stronger action, and the moss was more sensitive than the lichen. By shedding light on the accumulation of BAC and OIT in lichens and mosses and quantifying their effectiveness to photosynthetically devitalize these organisms, the obtained results are a useful comparison for the implementation of green alternative products for the control of biodeteriogens.
Supervisor Knowledge Sharing and Employee Knowledge Sharing: The Moderating Roles of Learning Goal Orientation and Affective Organizational Commitment
Authors: Kim Seckyoung Loretta
Published: April 2021

Recognizing the importance of knowledge sharing, this study adopted social learning and social exchange perspectives to understand when employees may engage in knowledge sharing. Using data collected from 192 employees in various South Korean organizations, the findings demonstrate that there is a positive relationship between supervisor knowledge sharing and employee knowledge sharing. As employees perceive a high level of supervisor knowledge sharing, they are likely to engage in knowledge sharing based on social learning and social exchange theories. Furthermore, the study explores the moderating effects of learning goal orientation and affective organizational commitment in the relationship between supervisor knowledge sharing and employee knowledge sharing. The result supports the hypothesis that the relationship between supervisor knowledge sharing and employee knowledge sharing is strengthened when there is a high level of affective organizational commitment. Employees who obtain valuable knowledge from their supervisors are likely to engage in knowledge sharing when they are emotionally attached to their organization. However, in contrast to the hypothesis, the positive relationship between supervisor knowledge sharing and employee knowledge sharing was stronger at the lower levels of learning goal orientation (LGO) than at the higher levels of LGO.
Decentralized Economic Complexity in Switzerland and Its Contribution to Inclusive and Sustainable Change
Authors: Aerni Philipp
Published: April 2021

The UN Sustainable Development Goals (SDGs) aim at harnessing economic complexity for sustainable and inclusive economic growth by calling for a decade of joint action. In this paper, we show how the action-oriented collaborative culture of complex and competitive economic ecosystems in places outside the major population centers may generate significant positive external effects for society and the environment at large. We illustrate this by means of two small case studies in Switzerland, a country with a federal system that enables decentralized economic development. The first case study investigates the economic ecosystem of the small town Monthey to show how productive migrants and embedded multinational companies increase the knowledge and know-how of local small and medium-sized enterprises (SMEs). The successful collaboration of insiders and outsiders accounts for the internal economic complexity that makes the region innovative and competitive. The second case study highlights the importance of the federalist system by showing how the canton of Solothurn succeeded in nurturing globally competitive export-oriented SMEs. We conclude that the success of these inclusive economic ecosystems in unexpected places may only be understood in the specific geographical, historical and political context, as well as the general openness of these regions toward entrepreneurial migrants and global business. The importance of local social capital makes it hard to replicate such success stories. Nevertheless, they indicate that the global knowledge economy may not just pose a threat, but also offer great opportunities for productive regions beyond the major global high-tech clusters of economic complexity.
Sustainability and Stakeholder Awareness: A Case Study of a Scottish University
Authors: Raji Abdulhakeem , Hassan Abeer
Published: April 2021

This paper adopted a case study approach to investigate the sustainability practices of a Scottish university in order to understand if sustainability forms part of its central policy agenda. As such, the paper focuses on the levels of awareness and disclosure of their sustainable practices, measuring the impacts and effectiveness of those initiatives. This paper introduces signaling theory to explore the idea that appropriate communication via integrated thinking can close the gap between the organization and its stakeholders. We believe that the provision of this relevant information will lead to better communication between the organization and its stakeholders, supporting a signaling theory interpretation. Therefore, we are suggesting that integrated thinking is an internal process that organizations can follow to increase the level of disclosure as a communication tool with stakeholders. From the literature reviewed, four themes were identified (definition of university sustainability, sustainability awareness, disclosure framework within universities, and level of accountability). The research adopted a pragmatic view and conducted individual interviews with participants belonging to three stakeholder groups (members of the university’s senior management, the governing council, and the student union executive). Although this study focused on just one Scottish university, it should still provide some insight for the better understanding of the underpinning issues surrounding the sustainability accountability practices of Scottish universities in general. The research findings indicated that the university prioritized only two sustainability dimensions—economic and environmental—and that the university still perceived sustainability as a voluntary exercise. Additionally, it is evident that the university had no framework in place for measuring its sustainability delivery—and therefore had no established medium of communicating these activities to its stakeholders. Moreover, research findings showed that the social and educational context of sustainability was lacking at the university. The university has done little or nothing to educate its stakeholders on sustainability.
Influence of Vision on Educational Performance: A Multivariate Analysis
Authors: Alvarez-Peregrina Cristina , Villa-Collar Cesar , Andreu-Vázquez Cristina , Sánchez-Tena Miguel Ángel
Published: April 2021

(1) Background: According to the World Report on Vision published by WHO, 123.7 million people around the world have vision impairment due to uncorrected refractive errors. Vision impairment affects many aspects of our lives, and it is related to low academic performance; (2) Methods: A prospective and multicenter study has been carried out in 1400 optical centers in Spain. A visual screening was carried out by optometrists on children aged between 6 and 12; (3) Results: 6673 children of primary school have been checked. The multivariate analysis reveals that 5.2% of the poor academic performance is related to vision. Poor academic performance was independent and significantly affected by sex, age, near vision, hyperopia, binocular dysfunctions, and bad ocular motility; (4) Conclusions: Vision plays a key role in optimum academic performance; consequently, the early detection of refractive errors and other visual problems is essential to improve the academic performance of schoolchildren.
Financial Literacy and Exercise Behavior: Evidence from Japan
Authors: Ono Shunsuke , Yuktadatta Pattaphol , Taniguchi Takafumi , Iitsuka Tomoe , Noguchi Masafumi , Tanaka Sawa , Ito Haruka , Nakamura Kousei , Yasuhara Nanako , Miyawaki Chihiro , Mikura Katsumi , Khan Mostafa Saidur Rahim , Kadoya Yoshihiko
Published: April 2021

Lack of exercise, which increases the risk of many serious physical and mental illness, has been a common health issue in Japan. Recent studies confirm that financial literacy discourages irrational behavior like gambling and smoking. We therefore investigate how financial literacy, as a rational decision-making instrument, relates to peoples’ exercise behavior in Japan. We hypothesize that financial literacy encourages people to exercise regularly. Using Osaka University’s Preference Parameters Study (PPS) for 2010, we categorized respondents into two groups: those who exercise regularly or at least once a week and those who do not. Our probit estimation results show that financial literacy is positively related with exercise behavior, meaning that financially literate people are more likely to exercise regularly. As the COVID-19 health pandemic seems to exacerbate peoples’ physical inactivity, the results of our study show an alternative approach to encourage exercise. We therefore recommend that governments implement a financial literacy improvement policy to alleviate the lack of exercise.
Assessing Yield Response and Relationship of Soil Boron Fractions with Its Accumulation in Sorghum and Cowpea under Boron Fertilization in Different Soil Series
Authors: Javed Muhammad Babar , Malik Zaffar , Kamran Muhammad , Abbasi Ghulam Hassan , Majeed Asma , Riaz Muhammad , Bukhari Muhammad Adnan , Mustafa Adnan , Ahmar Sunny , Mora-Poblete Freddy , Rafay Muhammad , Bukhari Syed Asad Hussain
Published: April 2021

Boron (B) is an essential micronutrient in the growth of reproductive plant parts. Its deficiency and/or toxicity are widespread in arid and semi-arid soils with low clay contents. This study was planned to determine the response of sorghum (Sorghum bicolor L., non-leguminous crop) and cowpea (Vigna sinensis L., leguminous crop) to boron (0, 2, 4, and 16 µg g−1) on four distinct soil series from Punjab, Pakistan i.e., Udic Haplustalf (Pindorian region), Typic Torrifluvent (Shahdra region), Halic Camborthid (Khurianwala region), and Udic Haplustalf (Gujranwala region). Overall, there was a significant difference (p < 0.05) in yield between the sorghum (3.8 to 5.5 g pot−1 of 5 kg dry soil) and cowpea (0.2 to 3.2 g pot−1 of 5 kg dry soil) in response to B application. The highest yield was observed in both sorghum and cowpea either in control or at 2 µg g−1 B application in all four soils. Cowpea showed the same yield trend in all four soils (i.e., an increase in yield at 2 µg g−1 B application, followed by a significant decrease at the higher B levels). In contrast, sorghum exhibited greater variability of response on different soils; Udic Haplustalf (Pindorian region) produced the greatest yield at low levels of B application. However, Halic Camborthid produced its lowest yield at that level. Boron concentration in shoots increased with the levels of B application, particularly in sorghum. In cowpea, the plant growth was extremely retarded—and most of the plants died at higher levels of B application even if a lower concentration of B was measured within the shoot. Hot water-extractable B was the most available fraction for cowpea (R2 = 0.96), whereas the easily exchangeable B was most available for sorghum (R2 = 0.90). Overall, these results have implications for micronutrient uptake for both leguminous and non-leguminous crops.
Effect of Lead Zirconate Titanate Bimorph on Soil Microorganisms: A Preliminary Study
Authors: Li Tianxin , Zhang Fang , Wang Xu , Su Ying
Published: April 2021

Lead zirconate titanate (PZT) has been widely used because of its electrochemical effect, but its effect on soil microorganisms is rarely studied. In this study, laboratory soil microcosms with different soil moisture content and pH were established to explore the effects of the PZT-5H bimorph with different quantities and states on soil microorganisms after 49 days. Plate counting was used to study the number changes of soil bacteria, fungi and actinomycetes. Isothermal microcalorimetry was used to evaluate microbial activity. High-throughput sequencing was used to analyze soil microbial diversity and community structure. The results showed that the number and activity of microorganisms could be significantly promoted by two vibrating PZT bimorphs under the appropriate soil moisture content (20%) and pH (7). At the same time, it promoted the growth of non- dominant microorganisms and increased the diversity of microorganisms. These results indicate that it is possible for PZT bimorphs to be used in soil field.
Mental Well-Being of Chinese Immigrants in the Netherlands during the COVID-19 Pandemic: A Survey Investigating Personal and Societal Antecedents
Authors: Ming Xin , De Jong Menno
Published: April 2021

The COVID-19 pandemic has profoundly impacted people’s lives worldwide, with negative consequences for mental health and well-being. Antecedents of mental health and well-being in times of COVID-19 have been underresearched, especially among minority groups. Therefore, an online survey was conducted investigating the personal and societal antecedents of mental well-being among Chinese immigrants in the Netherlands (N = 268). Constructs included perceived decrease of mental well-being and attitude toward the Netherlands as dependent variables and a range of potential antecedents as independent variables. Results show that participants judged the Chinese COVID-19 situation significantly more positively than the Dutch situation. Five antecedents of decreased mental well-being were found: financial concerns, social isolation, feelings of lost time, experienced racism, and distrust of Dutch COVID-19 information and figures. The antecedents of participants’ attitude toward the Netherlands were largely different: missing China, perceived difficulty of traveling to China, distrust of Dutch government measures, trust in Chinese government measures, and distrust of Dutch COVID-19 information and figures. Fear of the virus itself did not significantly affect either of the dependent variables. The results call for a broad perspective on factors associated with mental well-being and for special attention for minority groups in the societal dynamics.
Different Causal Factors Occur between Land Use/Cover and Vegetation Classification Systems but Not between Vegetation Classification Levels in the Highly Disturbed Jing-Jin-Ji Region of China
Authors: Yi Sangui , Zhou Jihua , Lai Liming , Sun Qinglin , Liu Xin , Liu Benben , Guo Jiaojiao , Zheng Yuanrun
Published: April 2021

Land use/cover and vegetation patterns are influenced by many ecological factors. However, the effect of various factors on different classification systems and different levels of the same system is unclear. We conducted a redundancy analysis with 10 landscape metrics and ecological factors in four periods (1986–2005/2007, 1991–2005/2007, 1996–2005/2007, 2001–2005/2007) to explore their effects on the land use/cover system, vegetation group and vegetation type, and formation and subformation levels of the vegetation classification system in the Jing-Jin-Ji region. Soil, temperature and precipitation from 1986–2005, 1991–2005, and 2001–2005 were the important causal factors, and anthropogenic disturbance and atmospheric factors in 1996–2005 were causal factors at the land use/cover level. The total explained variance from 1996–2005 and 2001–2005 was higher than that from 1986–2005 and 1991–2005 at the land use/cover level. Causal factors and the variance explained by causal factors at the vegetation group, vegetation type, and formation and subformation levels were similar but different in the land use/cover system. Geography, soil and anthropogenic disturbance were the most important causal factors at the three vegetation levels, and the total explained variance from 2001–2007 was higher than that from 1986–2007, 1991–2007, and 1996–2007 at the three vegetation levels. In environmental research, natural resource management and urban or rural planning, geographic factors should be considered at the vegetation group, vegetation type and formation and subformation levels while atmospheric and temperature factors should be considered at the land use/cover level.
Multicriteria Decision-Making to Determine the Optimal Energy Management Strategy of Hybrid PV–Diesel Battery-Based Desalination System
Authors: Rezk Hegazy , Alamri Basem , Aly Mokhtar , Fathy Ahmed , Olabi Abdul G. , Abdelkareem Mohammad Ali , Ziedan Hamdy A.
Published: April 2021

This paper identifies the best energy management strategy of hybrid photovoltaic–diesel battery-based water desalination systems in isolated regions using technical, economic and techno–economic criteria. The employed procedures include Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) as tools for the solution. Twelve alternatives, containing three–four energy management strategies; four energy management strategies, load following (LF), cycle charging (CC), combined LF–CC, and predictive strategy; and three different sizes of brackish water reverse osmosis (BWRO) water desalination units, BWRO-150, BWRO-250, and BWRO-500, are investigated with capacity of 150, 250, and 500 m3/day, respectively. Eight attributes comprising different technical and economic metrics are considered during the evaluation procedure. HOMER Pro® software is utilized to perform the simulation and optimization. The main findings confirmed that the best energy management strategies are predictive strategies and the reverse osmosis (RO) unit’s optimal size is RO-250. For such an option, the annual operating cost and initial costs are $4590 and $78,435, respectively, whereas the cost of energy is $0.156/kWh. The excess energy and unmet loads are 27,532 kWh and 20.3 kWh, respectively. The breakeven grid extension distance and the amount of CO2 are 6.02 km and 14,289 kg per year, respectively. Compared with CC–RO-150, the amount of CO2 has been sharply decreased by 61.2%.
COVID-19 Risk Assessment: Contributing to Maintaining Urban Public Health Security and Achieving Sustainable Urban Development
Authors: Zhang Jun , Yuan Xiaodie
Published: April 2021

As the most infectious disease in 2020, COVID-19 is an enormous shock to urban public health security and to urban sustainable development. Although the epidemic in China has been brought into control at present, the prevention and control of it is still the top priority of maintaining public health security. Therefore, the accurate assessment of epidemic risk is of great importance to the prevention and control even to overcoming of COVID-19. Using the fused data obtained from fusing multi-source big data such as POI (Point of Interest) data and Tencent-Yichuxing data, this study assesses and analyzes the epidemic risk and main factors that affect the distribution of COVID-19 on the basis of combining with logistic regression model and geodetector model. What’s more, the following main conclusions are obtained: the high-risk areas of the epidemic are mainly concentrated in the areas with relatively dense permanent population and floating population, which means that the permanent population and floating population are the main factors affecting the risk level of the epidemic. In other words, the reasonable control of population density is greatly conducive to reducing the risk level of the epidemic. Therefore, the control of regional population density remains the key to epidemic prevention and control, and home isolation is also the best means of prevention and control. The precise assessment and analysis of the epidemic conducts by this study is of great significance to maintain urban public health security and achieve the sustainable urban development.
Evaluation of the Water Quality and Farming Growth Benefits of an Intelligence Aquaponics System
Authors: Huang Chien-Che , Lu Hsiao-Ling , Chang Yuan-Hsiou , Hsu Tsung-Hsien
Published: April 2021

In 2019, the degree of food self-support in Taiwan was 32.08%, which was lower than that in the previous year by 2.4%. Taiwan does not have the ability to control the availability of food in the face of a food crisis. This study used an aquaponics system to implement the mutualism of fish, flowers, vegetables, and water, as well as to implement the cyclic utilization of water, so that vegetables and fruit could be produced to relieve food shortages in the world. The simulation site of this study was located on a gentle grassy slope alongside Li-tze Lake in Changhua County, Taiwan. In the simulation, three light-tight experimental buckets, with an upper rim diameter of 130 cm, a bottom rim diameter of 125 cm, and a height of 180 cm, were embedded in the ground. The target vegetables and flowers were planted in pots at 17 cm apart, and they were planted on the water surface using the floating island principle. A solar power system enabled a motorized pump to irrigate the plants. An aerator provided adequate aeration to achieve an elementary purifying effect. The experimental results showed that, in terms of the dissolved oxygen, the mean difference of the experimental group was about 1 mg/L, that of the control group was 2 mg/L, and the maximum difference was 6.5 mg/L. As the fish died in April, the ammonia nitrogen value of the control group was 68 times higher than that of the experimental group. Due to the nitrification in July, the ammonia nitrogen decomposed into NO2, which suddenly increased to 13 mg/L and was extremely unsuitable for the existence of aquatic organisms. This amount was five to six times higher than that of the experimental group. In terms of the fish growth rate, the control group could not bear the drastic changes in the water body at the intermediate stage, and all the fish died, whereas the fish in the experimental group were not affected. The results of this study could provide useful data for gardening, aquatic products, and space design staff.
Analysis of the System of Controlling Paid Parking Zones
Authors: Kozłowski Maciej , Czerepicki Andrzej , Jaskowski Piotr , Aniszewski Kamil
Published: April 2021

Urban traffic can be curbed in various ways, for instance, by introducing paid unguarded parking zones (PUPZ). The operational functionality of this system depends on whether or not the various system features used to document parking cases function properly, including those which enable positioning of vehicles parked in the PUPZ, recognition of plate numbers, event time recording, and the correct anonymisation of persons and other vehicles. The most fundamental problem of this system is its reliability, understood as the conformity of control results with the actual state of matters. This characteristic can be studied empirically, and this article addresses the methodology proposed for such an examination, discussed against a case study. The authors have analysed the statistical dependence of the e-control system’s measurement errors based on operational data. The results of this analysis confirm the rationale behind the deployment of the e-control system under the implementation of the smart city concept in Warsaw.
Impacts of the Sharing Economy on Urban Sustainability: The Perceptions of Municipal Governments and Sharing Organisations
Authors: Enochsson Lucie , Voytenko Palgan Yuliya , Plepys Andrius , Mont Oksana
Published: April 2021

By changing the institutionalised practices associated with resource distribution, the sharing economy could support sustainable urban transformations. However, its impacts on urban sustainability are unknown and contested, and key actors hold different perceptions about them. Understanding how they frame these impacts could help solve conflicts and outline what can be done to influence the development of the sharing economy in a way that fosters urban sustainability. This study explores the diversity of these frames across actors (sharing economy organisations and municipalities), segments (accommodation, bicycle, and car sharing), and cities (Amsterdam and Toronto). A framework of the impacts on urban sustainability was developed following a systematic literature review. This then guided the analysis of secondary data and 51 interviews with key actors. Results show that accommodation sharing is framed most negatively due to its impact on urban liveability. Bicycle sharing is surrounded by less conflict. Still, in Amsterdam, which has a well-functioning bicycle infrastructure, it is viewed less positively than in Toronto. Car sharing is the most positively framed segment in Amsterdam as its potentials to lower emissions align with municipal sustainability agendas. Practical insights for negotiations between sharing economy organisations and municipalities to advance urban sustainability are proposed.
The Lithium Wars: From Kokkola to the Congo for the 500 Mile Battery
Authors: Cooke Philip
Published: April 2021

This paper presents an analysis and interpretation of the current state of play in the global value network of minerals mining, refining and transformation processes in the contemporary battery industry, which will power potentially crucial future industries for manufacture of electric vehicles (EVs) and solar-storage energy systems. The dark influence of the carbon lock-in landscape is gradually being mitigated under the challenge of achieving the “500 mile” battery charge, which would make a transformational difference in the replacement of renewably fuelled vehicles and storage systems, currently still predominantly driven by fossil fuels. The challenge has led to a “war” between manufacturers, miners and refiners, who have realised that the challenge has come alive while most have been vacillating. At an “individualist” rather than an “institutionalist” level, Elon Musk, for all his faults, deserves credit for “moving the market” in these two important industry sectors. This paper anatomises key events and processes stimulating change in this global economic activity through an “abductive” reasoning model and a qualitative “pattern recognition” methodology that proves valuable in achieving rational, probabilistic forecasts. Established incremental innovation characterises first responses in the “war” but research agencies like ARPA are active in funding research that may produce radical battery innovation in future.