bluuebunny/crossref_metadata_2025 huggingface dataset:
Super-Resolution Restoration of Spaceborne Ultra-High-Resolution Images Using the UCL OpTiGAN System
Authors: Tao Yu , Muller Jan-Peter
Published: June 2021

We introduce a robust and light-weight multi-image super-resolution restoration (SRR) method and processing system, called OpTiGAN, using a combination of a multi-image maximum a posteriori approach and a deep learning approach. We show the advantages of using a combined two-stage SRR processing scheme for significantly reducing inference artefacts and improving effective resolution in comparison to other SRR techniques. We demonstrate the optimality of OpTiGAN for SRR of ultra-high-resolution satellite images and video frames from 31 cm/pixel WorldView-3, 75 cm/pixel Deimos-2 and 70 cm/pixel SkySat. Detailed qualitative and quantitative assessments are provided for the SRR results on a CEOS-WGCV-IVOS geo-calibration and validation site at Baotou, China, which features artificial permanent optical targets. Our measurements have shown a 3.69 times enhancement of effective resolution from 31 cm/pixel WorldView-3 imagery to 9 cm/pixel SRR.
Study of Atmospheric Turbidity in a Northern Tropical Region Using Models and Measurements of Global Solar Radiation
Authors: Zaiani Mohamed , Irbah Abdanour , Djafer Djelloul , Listowski Constantino , Delanoe Julien , Kaskaoutis Dimitris , Boualit Sabrina Belaid , Chouireb Fatima , Mimouni Mohamed
Published: June 2021

Radiative transfer in the Earth’s atmosphere under clear-sky conditions strongly depends on turbidity due to aerosols and hydrometeors. It is therefore important to know its temporal radiative properties for a given site when the objective is to optimize the solar energy that is collected there. Turbidity can be studied via measurements and models of the global solar radiation reaching the ground in cloudless conditions. These models generally depend on two parameters, namely the Angström turbidity coefficient and the Linke factor. This article aims to do a comparative study of five models of global solar radiation, all dependent on the Linke factor, based on real data. The measurements are provided by the Tamanrasset Meteorological Center (Algeria), which has a long series of global solar radiation data recorded between 2005 and 2011. Additional data from AERONET and MODIS onboard the TERRA satellite were also used to perform the comparison between the two estimated parameters and those obtained from AERONET. The study shows that the ESRA models are the most reliable among the five models for estimating the Linke factor with a correlation coefficient R of the data fits of 0.9995, a RMSE of 13.44 W/m2, a MBE of −0.64 W/m2 and a MAPE of 6.44%. The maximum and minimum statistical values were reached, respectively, in June and during the autumn months. The best correlation is also observed in the case of ESRA models between the Linke parameter and the joint optical thickness of aerosols and the total column-integrated water vapor. The Angström turbidity coefficient β, calculated from the Linke factor and MODIS data, has values less than 0.02 at 9% of the cases, and 76% present values ranging between 0.02 and 0.15 and 13% higher than 0.15. These β values are validated by AERONET measurements since a very good correlation (R≈0.87) is observed between the two datasets. The temporal variations of β also show a maximum in June. Satellite observations confirm more aerosols during the summer season, which are mostly related to the African monsoon.
Linking Past and Present Land-Use Histories in Southern Amazonas, Peru
Authors: Plekhov Daniel , VanValkenburgh Parker , Abrams Paul , Cutler Amanda , Han Justin , Reátegui Díaz Alexis Jair , Sullivan Bryn , Wernke Steven
Published: June 2021

This paper analyzes remotely sensed data sources to evaluate land-use history within the Peruvian department of Amazonas and demonstrates the utility of comparing present and past land-use patterns using continuous datasets, as a complement to the often dispersed and discrete data produced by archaeological and paleoecological field studies. We characterize the distribution of ancient (ca. AD 1–1550) terracing based on data drawn from high-resolution satellite imagery and compare it to patterns of deforestation between 2001 and 2019, based on time-series Landsat data. We find that the patterns reflected in these two datasets are statistically different, indicating a distinctive shift in land-use, which we link to the history of Inka and Spanish colonialism and Indigenous depopulation in the 15th through 17th centuries AD as well as the growth of road infrastructure and economic change in the recent past. While there is a statistically significant relationship between areas of ancient terracing and modern-day patterns of deforestation, this relationship ultimately explains little (6%) of the total pattern of modern forest loss, indicating that ancient land-use patterns do not seem to be structuring modern-day trajectories of land-use. Together, these results shed light on the long-term history of land-use in Amazonas and their enduring legacies in the present.
Regularized CNN Feature Hierarchy for Hyperspectral Image Classification
Authors: Ahmad Muhammad , Mazzara Manuel , Distefano Salvatore
Published: June 2021

Convolutional Neural Networks (CNN) have been rigorously studied for Hyperspectral Image Classification (HSIC) and are known to be effective in exploiting joint spatial-spectral information with the expense of lower generalization performance and learning speed due to the hard labels and non-uniform distribution over labels. Therefore, this paper proposed an idea to enhance the generalization performance of CNN for HSIC using soft labels that are a weighted average of the hard labels and uniform distribution over ground labels. The proposed method helps to prevent CNN from becoming over-confident. We empirically show that, in improving generalization performance, regularization also improves model calibration, which significantly improves beam-search. Several publicly available Hyperspectral datasets are used to validate the experimental evaluation, which reveals improved performance as compared to the state-of-the-art models with overall 99.29%, 99.97%, and 100.0% accuracy for Indiana Pines, Pavia University, and Salinas dataset, respectively.
Sentinel-2 Remote Sensed Image Classification with Patchwise Trained ConvNets for Grassland Habitat Discrimination
Authors: Fazzini Paolo , De Felice Proia Giuseppina , Adamo Maria , Blonda Palma , Petracchini Francesco , Forte Luigi , Tarantino Cristina
Published: June 2021

The present study focuses on the use of Convolutional Neural Networks (CNN or ConvNet) to classify a multi-seasonal dataset of Sentinel-2 images to discriminate four grassland habitats in the “Murgia Alta” protected site. To this end, we compared two approaches differing only by the first layer machinery, which, in one case, is instantiated as a fully-connected layer and, in the other case, results in a ConvNet equipped with kernels covering the whole input (wide-kernel ConvNet). A patchwise approach, tessellating training reference data in square patches, was adopted. Besides assessing the effectiveness of ConvNets with patched multispectral data, we analyzed how the information needed for classification spreads to patterns over convex sets of pixels. Our results show that: (a) with an F1-score of around 97% (5 × 5 patch size), ConvNets provides an excellent tool for patch-based pattern recognition with multispectral input data without requiring special feature extraction; (b) the information spreads over the limit of a single pixel: the performance of the network increases until 5 × 5 patch sizes are used and then ConvNet performance starts decreasing.
Improved the Accuracy of Seafloor Topography from Altimetry-Derived Gravity by the Topography Constraint Factor Weight Optimization Method
Authors: Sun Yongjin , Zheng Wei , Li Zhaowei , Zhou Zhiquan
Published: June 2021

Gravity geologic method is one of the important to derive seafloor topography by using altimetry-gravity, and its committed step is gridding of regional gravity anomaly. Hence, we proposed a topography constraint factor weight optimization (TCFWO) method based on ordinary kriging method. This method fully considers the influence of topography factors on the construction of regional gravity grid besides horizontal distance. The results of regional gravity anomaly models constructed in the Markus-Wake seamount area show that the TCFWO method is better than ordinary kriging method. Then, the above two regional gravity models were applied to invert the seafloor topography. The accuracy of derived topographic models was evaluated by using the shipborne depth data and existing seafloor topography models, including ETOPO1 and V19.1 model. The experimental results show that the accuracy of ST_TCFWO (seafloor topography model inverted by TCFWO method) is better than ST_KR (seafloor topography model inverted by kriging method) and ETOPO1 model. Compared with the ST_KR, the accuracy of the ST_TCFWO has improved about 26%. In addition, the accuracy of seafloor topography is affected by the variation of depth, the distribution of control points and the type of terrain. In different depth layers, the ST_TCFWO has better advantages than ST_KR. In the sparse shipborne measurements area, the accuracy of ST_TCFWO is better than that of V19.1, ETOPO1 and ST_KR. Moreover, compared to other models, ST_TCFWO performs better in flat submarine plain or rugged seamount area.
2D Wavelet Decomposition and F-K Migration for Identifying Fractured Rock Areas Using Ground Penetrating Radar
Authors: Jin Yang , Duan Yunling
Published: June 2021

The quality of the surrounding rock is crucial to the stability of underground caverns, thereby requiring an effective monitoring technology. Ground-penetrating radar (GPR) can reconstruct the subterranean profile by electromagnetic waves, but two significant issues, called clutter and hyperbola tails, affect the signal quality. We propose an approach to identify fractured rocks using 2D Wavelet transform (WT) and F-K migration. F-K migration can handle the hyperbola using Fourier analysis. WT can mitigate clutter, distinguish signal discontinuity, and provide signals with a good time-frequency resolution for F-K migration. In the simulation, the migration result from horizontal detail coefficients highlight the crack locations and reduce the scattering signals. Noise has been separated by 2D WT. Hyperbola tails are decomposed to vertical and diagonal detail coefficients. Similar promising results have been achieved in the field measurement. Therefore, the proposed approach can process GPR signals for identifying fractured rock areas.
Space-Time Evolutions of Land Subsidence in the Choushui River Alluvial Fan (Taiwan) from Multiple-Sensor Observations
Authors: Chen Yi-An , Chang Chung-Pai , Hung Wei-Chia , Yen Jiun-Yee , Lu Chih-Heng , Hwang Cheinway
Published: June 2021

Land subsidence is a significant problem around the world that can increase the risk of flooding, damage to infrastructure, and economic loss. Hence, the continual monitoring of subsidence is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. In this study, we used multiple-sensor observations from the Continuous Global Positioning System (CGPS), the small baseline subset (SBAS) algorithm, interferometric synthetic-aperture radar (InSAR), precise leveling, multi-layer compaction monitoring wells (MLCWs), and groundwater observation wells (GWs) to show the spatial and temporal details of land subsidence in the Choushui River alluvial fan (CRAF), Taiwan, from 1993 to 2019. The results showed that significant land subsidence has occurred along the coastal areas in the CRAF, and most of the inland subsidence areas have also experienced higher subsidence rates (>30 mm/yr). The analysis of subsidence along the Taiwan High Speed Rail (THSR) revealed a newly formed subsidence center between Tuku and Yuanchang Townships in Yunlin, with high subsidence rates ranging from 30 to 70 mm/yr. We propose a map showing, for the first time, the distribution of deep compactions occurring below 300 m depth in the CRAF.
Data Spine: A Federated Interoperability Enabler for Heterogeneous IoT Platform Ecosystems
Authors: Deshmukh Rohit A. , Jayakody Dileepa , Schneider Alexander , Damjanovic-Behrendt Violeta
Published: June 2021

Today, the Internet of Things (IoT) is pervasive and characterized by the rapid growth of IoT platforms across different application domains, enabling a variety of business models and revenue streams. This opens new opportunities for companies to extend their collaborative networks and develop innovative cross-platform and cross-domain applications. However, the heterogeneity of today’s platforms is a major roadblock for mass creation of IoT platform ecosystems, pointing at the current absence of technology enablers for an easy and innovative composition of tools/services from the existing platforms. In this paper, we present the Data Spine, a federated platform enabler that bridges IoT interoperability gaps and enables the creation of an ecosystem of heterogeneous IoT platforms in the manufacturing domain. The Data Spine allows the ecosystem to be extensible to meet the need for incorporating new tools/services and platforms. We present a reference implementation of the Data Spine and a quantitative evaluation to demonstrate adequate performance of the system. The evaluation suggests that the Data Spine provides a multitude of advantages (single sign-on, provision of a low-code development environment to support interoperability and an easy and intuitive creation of cross-platform applications, etc.) over the traditional approach of users joining multiple platforms separately.
An Ultrafast Active Quenching Active Reset Circuit with 50% SPAD Afterpulsing Reduction in a 28 nm FD-SOI CMOS Technology Using Body Biasing Technique
Authors: Dolatpoor Lakeh Mohammadreza , Kammerer Jean-Baptiste , Aguénounon Enagnon , Issartel Dylan , Schell Jean-Baptiste , Rink Sven , Cathelin Andreia , Calmon Francis , Uhring Wilfried
Published: June 2021

An ultrafast Active Quenching—Active Reset (AQAR) circuit is presented for the afterpulsing reduction in a Single Photon Avalanche Diode (SPAD). The proposed circuit is designed in a 28 nm Fully Depleted Silicon On Insulator (FD-SOI) CMOS technology. By exploiting the body biasing technique, the avalanche is detected very quickly and, consequently, is quenched very fast. The fast quenching decreases the avalanche charges, therefore resulting in the afterpulsing reduction. Both post-layout and experimental results are presented and are highly in accordance with each other. It is shown that the proposed AQAR circuit is able to detect the avalanche in less than 40 ps and reduce the avalanche charge and the afterpulsing up to 50%.
Location-Based Resource Allocation in Ultra-Dense Network with Clustering
Authors: Kim Seong-Jung , Kim Jeong-Gon
Published: June 2021

With the rapid deployment of present-day mobile communication systems, user traffic requirements have increased tremendously. An ultra-dense network is a configuration in which the density of small base stations is greater than or equal to that of the user equipment. Ultra-dense networks are considered as the key technology for 5th generation networks as they can improve the link quality and increase the system capacity. However, in an ultra-dense network, small base stations are densely positioned, so one user equipment may receive signals from two or more small base stations. This may cause a severe inter-cell interference problem. In this study, we considered a coordinated multi-point scenario, a cooperative technology between base stations to alleviate the interference. In addition, to suppress the occurrence of severe interference at the cell edges, link formation was carried out by considering the degree of cell load for each cluster. After the formation of links between all the base stations and user equipment, a subcarrier allocation procedure was performed. The subcarrier allocation method used in this study was based on the location of base stations with clustering to improve the data rate and reduce the interference between the clusters. Power allocation was based on the channel gain between the base station and user equipment. Simulation results showed that the proposed scheme delivered a higher sum rate than the other resource allocation methods reported previously for various types of user equipment.
Data-Driven Fault Diagnosis for Electric Drives: A Review
Authors: Gonzalez-Jimenez David , del-Olmo Jon , Poza Javier , Garramiola Fernando , Madina Patxi
Published: June 2021

The need to manufacture more competitive equipment, together with the emergence of the digital technologies from the so-called Industry 4.0, have changed many paradigms of the industrial sector. Presently, the trend has shifted to massively acquire operational data, which can be processed to extract really valuable information with the help of Machine Learning or Deep Learning techniques. As a result, classical Condition Monitoring methodologies, such as model- and signal-based ones are being overcome by data-driven approaches. Therefore, the current paper provides a review of these data-driven active supervision strategies implemented in electric drives for fault detection and diagnosis (FDD). Hence, first, an overview of the main FDD methods is presented. Then, some basic guidelines to implement the Machine Learning workflow on which most data-driven strategies are based, are explained. In addition, finally, the review of scientific articles related to the topic is provided, together with a discussion which tries to identify the main research gaps and opportunities.
Robust Causal Estimation from Observational Studies Using Penalized Spline of Propensity Score for Treatment Comparison
Authors: Zhou Tingting , Elliott Michael R. , Little Roderick J. A.
Published: June 2021

Without randomization of treatments, valid inference of treatment effects from observational studies requires controlling for all confounders because the treated subjects generally differ systematically from the control subjects. Confounding control is commonly achieved using the propensity score, defined as the conditional probability of assignment to a treatment given the observed covariates. The propensity score collapses all the observed covariates into a single measure and serves as a balancing score such that the treated and control subjects with similar propensity scores can be directly compared. Common propensity score-based methods include regression adjustment and inverse probability of treatment weighting using the propensity score. We recently proposed a robust multiple imputation-based method, penalized spline of propensity for treatment comparisons (PENCOMP), that includes a penalized spline of the assignment propensity as a predictor. Under the Rubin causal model assumptions that there is no interference across units, that each unit has a non-zero probability of being assigned to either treatment group, and there are no unmeasured confounders, PENCOMP has a double robustness property for estimating treatment effects. In this study, we examine the impact of using variable selection techniques that restrict predictors in the propensity score model to true confounders of the treatment-outcome relationship on PENCOMP. We also propose a variant of PENCOMP and compare alternative approaches to standard error estimation for PENCOMP. Compared to the weighted estimators, PENCOMP is less affected by inclusion of non-confounding variables in the propensity score model. We illustrate the use of PENCOMP and competing methods in estimating the impact of antiretroviral treatments on CD4 counts in HIV+ patients.
Landscape Values as a Driving Force to Increase Nature Conservation. Environmental and Planning Policies as a Possible Integration
Authors: Cialdea Donatella , Privitera Sandro
Published: June 2021

Landscape values are addressed by planning tools in several diversified ways. Many European countries have joined the European Landscape Convention which just turned 20 last year. This work aims at investigating its implementations and relationships with general and local planning tools, focusing on two main objectives: the first one concerns the analysis of principles regulating regional strategies, deriving from European dictates and State norms. It has been focused in the Sicily region in Italy, the largest island in the Mediterranean basin. The second objective concerns the in-depth analysis of territories of a fragile nature in which the two terms that characterize the landscape, culture and nature, merge together. This paper consists in gathering information deriving from the various planning levels, proposing a comparison methodology which takes into account physical–environmental and landscape–visual features in some sample cases within protected areas, but in a highly urbanized context. A system and database were created and implemented within the geographic information system, drawing up a comparison between environmental requirements and development strategies.
The Influence of Person–Job Fit, Work–Life Balance, and Work Conditions on Organizational Commitment: Investigating the Mediation of Job Satisfaction in the Private Sector of the Emerging Market
Authors: Hasan Tania , Jawaad Mehwish , Butt Irfan
Published: June 2021

This study aims to provide critical managerial implications for human resource (HR) practitioners at private-sector organizations from an emerging economy perspective. The study helps to optimize organizational commitment in the assessment of work–life balance, person–job fit, work condition, and the mediation of job satisfaction. It also investigates the influence of certain demographic variables on organizational commitment. The population comprises employees working in private sector organizations across Pakistan. A total of 1100 survey questionnaires were sent to potential respondents; 843 responded, giving a response rate of 77%. SmartPLS 3 software and SPSS were used to perform structural equation modeling. The study revealed that work–life balance, person–job fit, and job satisfaction have a positive influence on organizational commitment. Job satisfaction intervenes complementarily with the relationship of work–life balance and person–job fit with organizational commitment, while full mediation of job satisfaction was found for work conditions. Age, female gender, experience with current employee, and total industry experience were positively related to organizational commitment. HR managers at private-sector organizations must strive to provide work–life balance, person–job fit, and better work conditions so that employees are optimally satisfied on the job and exercise strong affective organizational commitment.
Elevating Cultural Preservation Projects into Urban Regeneration: A Case Study of Bahrain’s Pearling Trail
Authors: Naseeb Haifa Tawfeeq , Lee Jongoh , Choi Heejae
Published: June 2021

The island of Muharraq in the Kingdom of Bahrain was previously in a state of socioeconomic disrepair and neglect, until the nine years-long “Pearling Trail” project revived the area. Historically, Muharraq’s importance inheres in it being the main trade center of the Middle East since the Mesopotamian period, especially as the source of the finest pearls in the world. However, the discovery of oil that led to the rapid urbanization of the region and Japan perfecting the production of cultured pearls had meant that Muharraq dwindled out of cultural significance. Due to the residents’ dissatisfaction and nostalgia for the island’s past glory, along with the government’s new policies towards cultural preservation, the “Pearling Trail” Project commenced in 2012. The Ministry of Culture of Bahrain repaired, renovated and preserved an area of 3.5 km, transforming it into an eco-museum with a thriving business and cultural community. The transformation of the island elevated the city into a trendy local attraction, hosting local and global cultural festivals and events, owing to the “Pearling Trail’s” Urban Regeneration Project’s success. By studying the “Pearling Trail” three success factors are identified: Project expansion beyond UNESCO preservation requirements, focus on sustainability and continuous use, and improved access to culture and cultural opportunities. Identifying these factors could allow for future preservation projects in Bahrain or elsewhere to be upgraded for urban regeneration or revitalization.
Beyond the Transition: Long-Term Population Trends in a Disadvantaged Region of Southern Europe, 1861–2017
Authors: Salvia Rosanna , Salvati Luca , Quaranta Giovanni
Published: June 2021

The long-term impact of demographic transitions on the spatial distribution of human settlements was occasionally evaluated in Europe. Assuming the distinctive role of urban–rural divides, our study investigates local-scale population trends (1861–2017) in Southern Italy, a disadvantaged region of Mediterranean Europe, as a result of long-term socioeconomic transformations. A quantitative analysis of municipal-scale population data based on descriptive and exploratory multivariate statistics, mapping, inferential approaches, and regression models identified four time intervals with distinctive demographic dynamics: (i) a spatially homogeneous population growth between 1861 and 1911, (ii) a moderate population increase rebalancing a traditional divide in coastal and internal areas (1911–1951), (iii) accelerated population growth enlarging spatial divides in urban and rural districts (1951–1981), and (iv) population stability (or slight decline) leading to heterogeneous demographic patterns since the early 1980s. The first three stages reflect a prolonged transition from high fertility and mortality to high fertility and low mortality, with accelerated population growth typical of the latest stage of the first demographic transition. Outcomes of time interval (iv) reflect the early stages of the second demographic transition, with lowest-low fertility and rising life expectancy. While the first transition reflected spatially homogeneous population trends along a considerable time spam, the second transition has been associated with heterogeneous (leapfrog) demographic patterns as a result of socially mixed (and spatially) fragmented dynamics of growth and change.
Partnering for Sustainability: Parent-Teacher-School (PTS) Interactions in the Qatar Education System
Authors: Al-Hail Maryam A. , Al-Fagih Luluwah , Koç Muammer
Published: June 2021

The interaction avenues, levels, and impacts between parents, schools and teachers have changed drastically due to the ever-increasing responsibilities, frequent and rapid changes in the curriculum, the invasive dominance of the internet and digital media in the lives of all stakeholders, and the digitization of learning materials, to name a few. This pilot study follows a design-thinking approach to investigate the current practices, needs, and challenges of parental involvement in public schools in Qatar to improve student achievements towards sustainable living and habits by identifying problems, developing solutions, and improving student achievement in conjunction with all local and relevant stakeholders. To this end, building on extensive and comparative studies on theories, models, and best practices within and outside the selected domain, a qualitative study is conducted to obtain insight from local teachers and parents in preparatory public schools. The grounded theory method is employed to analyze the data via the qualitative coding technique. The results indicate that parental involvement practices in Qatar public schools occur in different forms, including home-based and school-based learning. Furthermore, while almost all parents recognize the significance of parental involvement and show a high level of interest in being on the ‘Board of Trustees’, in reality, very few participate or volunteer in school activities, and they rarely visit classrooms or interact with teachers or schools, mainly due to their increasing job-related commitments. In addition, the majority of parents indicate the need for additional flexibility in communication with the school to increase their involvement. Meanwhile, the teachers highlight the significant lack of parental involvement in understanding, overcoming and improving student achievement in both academic subjects and sustainable living habits and actions. The study outlines a few key suggestions to overcome these challenges and improve the parent-teacher-school (PTS) partnership, including offering mandatory parenting classes, developing and implementing effective communication mechanisms to facilitate parent-school interactions, and involving parents in decision-making process relating to their children and other school-related activities. Despite the sampling limitation, this study’s findings represent a starting point for understanding the needs of PTS partnerships, current practices of parental involvement, and mechanisms to improve their contribution to Qatar’s schools.
The Valorization of Italian “Borghi” as a Tool for the Tourism Development of Rural Areas
Authors: Bizzarri Carmen , Micera Roberto
Published: June 2021

The paper comes from the need to search for criteria useful for the valorization of heritage towns, located in rural and/or inland areas of Italy, now affected by depression and depopulation process. To this end, the authors point out how territorial identity can constitute the theoretical foundation to influence development policies and, in particular, tourism development for the sustainability process. It was therefore decided to interview a number of stakeholders who could contribute, with their professionalism and expertise, to identifying possible paths and processes for the enhancement of these areas for tourism development. The methodology was based on in-depth interviews, which allowed for the identification of a of a Strength, Weakness, Opportunities and Threat (SWOT) analysis, offering a guideline for the correct governance of these rural areas for their tourist enhancement in terms of the sustainability of development and tourist attractiveness. The study is an observatory that will monitor the implementation of sustainable tourism enhancement of the “borghi”.
Sustainable Waste Management Innovations in Africa: New Perspectives and Research Agenda for Improving Global Health
Authors: Ahen Frederick , Amankwah-Amoah Joseph
Published: June 2021

The need for green business practices and green innovations underscores a growing recognition that climate change is now an existential threat not just to population health but also to the survival of businesses that are unable to embrace green practices with a sense of urgency. This paper contributes to the literature on market violence as an inhibitor of green innovations for sustainable waste management to curb the unneeded health effects of wastes in Africa. Our purpose is to problematize received wisdom, unquestioned assumptions, and incorrect diagnosis of the sources and health consequences of various forms of wastes in Africa. Much of the discourse on this issue remains ahistorical, and that risks leaving aside a vital question of exploitative extraction. By including this ‘out-of-the-box’ explanation through major case references, we are able to shed light on the critical issues that have hitherto received limited attention, thus enabling us to propose useful research questions for future enquiries. We propose a framework that delineates the structural composition of costs imposed by market violence that ranges from extraction to e-waste disposal. We advocate for the engineering of policies that create conditions for doing more with less resources, eliminating waste, and recycling as crucial steps in creating sustainable waste management innovations. Additionally, we highlight a set of fundamental issues regarding enablers and inhibitors of sustainable innovations and policies for waste management worth considering for future research. These include programmed obsolescence, irresponsible extraction, production, and consumption, all seen through the theoretical lens of market violence.
Seniors’ Mobility and Perceptions in Different Urban Neighbourhoods: A Non-Aggregative Approach
Authors: Burlando Claudia , Ivaldi Enrico , Ciacci Andrea
Published: June 2021

In order to highlight the subjective criticality of each neighbourhood to inspire future policy actions, we propose an analysis comparing the perceptions of over-65s residents in the neighbourhoods that make up the Municipality of Genoa. We suggest a new approach based on a quantitative non-aggregative method, Partially Ordered Set (Poset), to measure the levels of satisfaction related to local public transport (LPT), pedestrian mobility, and quality of life in the 25 districts of Genoa. Final data of the analysis come from 401 questionnaires, distributed to residents over 65 years old in the Municipality of Genoa. This approach allows to address the multidimensionality of the phenomenon, as well as its different conceptual spheres. The findings highlight a great variance in local public transport needs perception between different neighbourhoods. In particular, the analysis shows that the types of intervention requested by respondents differ from district to district, so that a common urban transport policy would be ineffective. Some neighbourhoods stress the need for improving pedestrian mobility, whilst local public transport faults dominate in others. There is no significant relation between the three dimensions: Perceived quality of LPT, perceived quality of pedestrian mobility, and perceived quality of neighbourhood. Therefore, interventions should be carefully modulated, according to the specific needs expressed by the residents of each neighbourhood. We conclude that the importance of urban mobility intervention is reduced, whereas the concept of neighbourhood analysis and intervention becomes more relevant.
Pro197Thr Substitution in Ahas Gene Causing Resistance to Pyroxsulam Herbicide in Rigid Ryegrass (Lolium Rigidum Gaud.)
Authors: Kutasy Barbara , Takács Zsolt , Kovács Judit , Bogaj Verëlindë , Razak Syafiq A. , Hegedűs Géza , Decsi Kincső , Székvári Kinga , Virág Eszter
Published: June 2021

Lolium rigidum Gaud. is a cross-pollinated species characterized by high genetic diversity and it was detected as one of the most herbicide resistance-prone weeds, globally. Acetohydroxyacid synthase (AHAS) resistant populations cause significant problems in cereal production; therefore, monitoring the development of AHAS resistance is widely recommended. Using next-generation sequencing (NGS), a de novo transcriptome sequencing dataset was presented to identify the complete open reading frame (ORF) of AHAS enzyme in L. rigidum and design markers to amplify fragments consisting of all of the eight resistance-conferring amino acid mutation sites. Pro197Thr, Pro197Ala, Pro197Ser, Pro197Gln, and Trp574Leu amino acid substitutions have been observed in samples. Although the Pro197Thr amino acid substitution was already described in SU and IMI resistant populations, this is the first report to reveal that the Pro197Thr in AHAS enzyme confers a high level of resistance (ED50 3.569) to pyroxsulam herbicide (Triazolopyrimidine).
Current Status of Aged Public Buildings and Effect Analysis Prediction of Green Remodeling in South Korea
Authors: Nam Seunghoon , Kim Jaemoon , Lee Duwhan
Published: June 2021

The purpose of this study is to analyze the scope of the expected improvement effect of office buildings and educational research facilities according to green remodeling. Thus, in order to quantitatively grasp the architectural performance of the existing buildings, the building thermal performance, the airtightness, the indoor environment, and the air quality were measured using equipment. The analysis indicated that the envelope performance and the indoor environment were unsatisfactory compared to the current legal standards, and for indoor air quality, CO2 and formaldehyde were measured to be dissatisfactory in some buildings. The energy analysis results indicated that the improvement range differed according to the renovation history for each building, resulting in differences in the energy-saving rate for each alternative. The reduction rates of primary energy consumption using energy simulation were 38.5–67.4% for office buildings and 23.7–66.3% for educational research facilities, and the payback periods were 14 to 27 years for office buildings and 12 to 30 years for educational research facilities. These results are expected to contribute to the activation of green remodeling because they can be used as indicators to predict the expected construction cost, the payback period, and the expected effect required for green remodeling.
Time Distribution Simulation of Household Power Load Based on Travel Chains and Monte Carlo–A Study of Beijing in Summer
Authors: Liu Jinpeng , Yang Hao , Wei Delin , Song Xiaohua
Published: June 2021

In recent years, China’s residential electricity consumption has continued to grow at high speed, and its contribution to the growth of the total electricity consumption has become more prominent. The peak-to-valley gap is also gradually increasing, which reduces the efficiency of electricity—an increasingly important terminal energy form. The resident travel chain is a major influencing factor of residents’ electricity consumption, and it is of great significance to dig deeper into the mechanism of its influence on residents’ electricity consumption behavior. In this paper, the time distribution model of household power load in summer in Beijing is constructed by comprehensively considering the difference of travel chain, electricity consumption behavior, and load level. The Monte Carlo simulation method is introduced for the simulation of the model. According to the results, both household type and temperature have a significant impact on the peak load, while the difference in the choice of mode of transportations does not. It is also found that the household appliance with the most potential for regulation is the air conditioning, followed by the water heater, which where regulation and optimization should be mainly carried out.
Sublime Experience for Sustainable Underground Space: Integration of the Artists’ Works in Chichu Art Museum
Authors: Park Eun Joo , Kang Eunki
Published: June 2021

This paper investigates a vision of the underground environment associated with an aesthetic discipline. Its fundamental notion is sublimity, which was a phenomenon that involved a number of artworks engaged with changing the perception of the underground experience. This paper seeks to clarify how the idea of the living environment underground has changed by examining the works of writers, painters, and architects who have drawn inspiration from the concept of imaginary underworlds. Through a case study of the Chichu Art Museum, a representative underground space in terms of a sustainable relationship between architectural spaces and nature that could be experienced as sublime, this paper considers how to integrate visitors to distribute their awareness of artists’ work. It also stimulates visitors’ perceptions of a more sustainable future through sublime experiences, offering a way to understand underground integration with artworks. Therefore, this paper contributes to the knowledge of the relationship between architecture and artwork by increasing the aesthetic value of the underground space and considering how art intervenes in architecture to create a sustainable didactic.
Impact of Ultrashort Laser Nanostructuring on Friction Properties of AISI 314 LVC
Authors: Alnusirat Walid , Kyrychok Maksym , Bellucci Stefano , Gnilitskyi Iaroslav
Published: June 2021

Laser irradiation yields a powerful tool to modify the symmetry and asymmetry features of materials surfaces. In this paper, femtosecond laser-induced periodic surface structures were applied on stainless steel AISI 314, specially hardened by a low-vacuum carburizing procedure. Symmetry modifications in the surface’s morphology and chemistry before and after the laser treatment were investigated by SEM and EDS, respectively. Coefficient of friction (COF) was observed in dry sliding condition by using block-on-ring sliding test. The results show that COF values are substantially lower after laser-induced periodic surface structures (LIPSS) surface treatment.
A Damage Model to Trabecular Bone and Similar Materials: Residual Resource, Effective Elasticity Modulus, and Effective Stress under Uniaxial Compression
Authors: Kolesnikov Gennady , Meltser Rudolf
Published: June 2021

Experimental research of bone strength remains costly and limited for ethical and technical reasons. Therefore, to predict the mechanical state of bone tissue, as well as similar materials, it is desirable to use computer technology and mathematical modeling. Yet, bone tissue as a bio-mechanical object with a hierarchical structure is difficult to analyze for strength and rigidity; therefore, empirical models are often used, the disadvantage of which is their limited application scope. The use of new analytical solutions overcomes the limitations of empirical models and significantly improves the way engineering problems are solved. Aim of the paper: the development of analytical solutions for computer models of the mechanical state of bone and similar materials. Object of research: a model of trabecular bone tissue as a quasi-brittle material under uniaxial compression (or tension). The new ideas of the fracture mechanics, as well as the methods of mathematical modeling and the biomechanics of bone tissues were used in the work. Compression and tension are considered as asymmetric mechanical states of the material. Results: a new nonlinear function that simulates both tension and compression is justified, analytical solutions for determining the effective and apparent elastic modulus are developed, the residual resource function and the damage function are justified, and the dependences of the initial and effective stresses on strain are obtained. Using the energy criterion, it is proven that the effective stress continuously increases both before and after the extremum point on the load-displacement plot. It is noted that the destruction of bone material is more likely at the inflection point of the load-displacement curve. The model adequacy is explained by the use of the energy criterion of material degradation. The results are consistent with the experimental data available in the literature.
Interval Valued T-Spherical Fuzzy Information Aggregation Based on Dombi t-Norm and Dombi t-Conorm for Multi-Attribute Decision Making Problems
Authors: Ullah Kifayat , Garg Harish , Gul Zunaira , Mahmood Tahir , Khan Qaisar , Ali Zeeshan
Published: June 2021

Multi-attribute decision-making (MADM) is commonly used to investigate fuzzy information effectively. However, selecting the best alternative information is not always symmetric because the alternatives do not have complete information, so asymmetric information is often involved. Expressing the information under uncertainty using closed subintervals of [0, 1] is beneficial and effective instead of using crisp numbers from [0, 1]. The goal of this paper is to enhance the notion of Dombi aggregation operators (DAOs) by introducing the DAOs in the interval-valued T-spherical fuzzy (IVTSF) environment where the uncertain and ambiguous information is described with the help of membership grade (MG), abstinence grade (AG), non-membership grade (NMG), and refusal grade (RG) using closed sub-intervals of [0, 1]. One of the key benefits of the proposed work is that in the environment of information loss is reduced to a negligible limit. We proposed concepts of IVTSF Dombi weighted averaging (IVTSFDWA) and IVTSF Dombi weighted geometric (IVTSFDWG) operators. The diversity of the IVTSF DAOs is proved and the influences of the parameters, associated with DAOs, on the ranking results are observed in a MADM problem where it is discussed how a decision can be made when there is asymmetric information about alternatives.
Adapting an Agent-Based Model of Infectious Disease Spread in an Irish County to COVID-19
Authors: Hunter Elizabeth , Kelleher John D.
Published: June 2021

The dynamics that lead to the spread of an infectious disease through a population can be characterized as a complex system. One way to model such a system, in order to improve preparedness, and learn more about how an infectious disease, such as COVID-19, might spread through a population, is agent-based epidemiological modelling. When a pandemic is caused by an emerging disease, it takes time to develop a completely new model that captures the complexity of the system. In this paper, we discuss adapting an existing agent-based model for the spread of measles in Ireland to simulate the spread of COVID-19. The model already captures the population structure and commuting patterns of the Irish population, and therefore, once adapted to COVID-19, it can provide important insight on the pandemic, specifically in Ireland. We first investigate the different disease parameters that need to be adjusted to simulate the spread of COVID-19 instead of measles and then run a set of experiments initially comparing the model output for our original measles model with that from the adjusted COVID-19 model. We then report on experiments on how the different values of the basic reproductive number, R0, influence the simulated outbreaks, and find that our model behaves as expected: the higher the R0, the more agents are infected. Then, we demonstrate how different intervention strategies, such as vaccinations and school closures, influence the spread of measles and COVID-19 and how we can simulate real pandemic timings and interventions in our model. We show that with the same society, environment and transportation components among the different disease components lead to very different results for the two diseases, and that our COVID-19 model, when run for Leitrim County, Ireland, predicts a similar outbreak length to a real outbreak in Leitrim County, Ireland, but the model results in a higher number of infected agents compared to the real outbreak. This difference in cases is most likely due to identifying all cases of COVID-19 in the model opposed to only those tested. Once an agent-based model is created to simulate a specific complex system or society, the disease component can be adapted to simulate different infectious disease outbreaks. This makes agent-based models a powerful tool that can be used to help understand the spread of new and emerging infectious diseases.
Necessity of Assessing Biological Exposure to Arsenic Species by Two Representative Analytical Methods
Authors: Seo Jeong-Wook , Hong Young-Seoub
Published: June 2021

Arsenic (As) exists as highly toxic chemical species. Chronic exposure to its inorganic form can cause multiple organ failure and skin cancer in humans, warranting the need to determine the toxicity of each chemical species. This study evaluated the proportions of exposure to four chemical species of As (cAs), namely arsenite (AsIII), arsenate (AsV), monomethylarsinic acid (MMA), and dimethylarsenic acid (DMA), and it confirmed the necessity of evaluating biological exposure to cAs. Urine samples were collected from 457 subjects residing near 103 abandoned metal mines. Hydride generation atomic absorption spectroscopy (HG-AAS) was performed to measure the combined concentration of four cAs (hAsAAS). High-performance liquid chromatography and inductively coupled plasma-mass spectrometry (HPLC-ICP-MS) were performed to determine the concentrations of the individual cAs and the sum of the four cAs (hAsICP). The proportions of AsV and MMA were relatively higher in the low-hAsICP concentration section. These findings suggest that hAsAAS, which is mainly used for its cost-efficiency, is limited for evaluating exposure. Though hAsAAS was found to exist in a low concentration, highly toxic AsV and MMA could be observed in high concentrations. Therefore, HPLC-ICP-MS is recommended for assessing cAs in environmentally vulnerable areas such as abandoned metal mines.