bluuebunny/crossref_metadata_2025 huggingface dataset:
Cloud Detection of Remote Sensing Image Based on Multi-Scale Data and Dual-Channel Attention Mechanism
Authors: Yan Qing , Liu Hu , Zhang Jingjing , Sun Xiaobing , Xiong Wei , Zou Mingmin , Xia Yi , Xun Lina
Published: August 2022

Cloud detection is one of the critical tasks in remote sensing image preprocessing. Remote sensing images usually contain multi-dimensional information, which is not utilized entirely in existing deep learning methods. This paper proposes a novel cloud detection algorithm based on multi-scale input and dual-channel attention mechanisms. Firstly, we remodeled the original data to a multi-scale layout in terms of channels and bands. Then, we introduced the dual-channel attention mechanism into the existing semantic segmentation network, to focus on both band information and angle information based on the reconstructed multi-scale data. Finally, a multi-scale fusion strategy was introduced to combine band information and angle information simultaneously. Overall, in the experiments undertaken in this paper, the proposed method achieved a pixel accuracy of 92.66% and a category pixel accuracy of 92.51%. For cloud detection, the proposed method achieved a recall of 97.76% and an F1 of 95.06%. The intersection over union (IoU) of the proposed method was 89.63%. Both in terms of quantitative results and visual effects, the deep learning model we propose is superior to the existing semantic segmentation methods.
Viticultural Suitability Analysis Based on Multi-Source Data Highlights Climate-Change-Induced Decrease in Potential Suitable Areas: A Case Analysis in Ningxia, China
Authors: Bai Huiqing , Sun Zhongxiang , Yao Xuenan , Kong Junhua , Wang Yongjian , Zhang Xiaoyu , Chen Weiping , Fan Peige , Li Shaohua , Liang Zhenchang , Dai Zhanwu
Published: August 2022

As a perennial plant with long productive span of 30–50 years, grapevine may experience cross-lifespan climate change, which can modify wine quality and challenge viticultural sustainability. Therefore, it is essential to evaluate the viticultural suitability by considering both current and future climate conditions. To this end, a maximum entropy model was proposed to delimitate potentially suitable areas for viticulture based on multi-source data in a novel wine region, Ningxia, China, considering both current and future climate conditions. Firstly, we combined traditional data of climate, soil, and topography with remote sensing data to screen predictors that best characterize current geographical distribution of vineyards. Then, we used those predictors to assess current suitability (2001–2020) in Ningxia. The results indicated altitude, aridity index during April–September (K0409), precipitation during July–September (P0709), normalized difference vegetation index during July–September (NDVI0709), soil organic carbon (SOC), and precipitation in September (P09) were key predictors to assess potential suitability for viticulture, and their threshold values ranged from 1075 m to 1648 m, 2.93 to 4.83, 103.1 mm to 164.1 mm, 0.1 to 0.89, 0.07 g/kg to 11 g/kg and 28.4 mm to 45.0 mm, respectively. Suitability maps revealed a total suitable area of 12029 km2, among which the highly and moderately suitable areas accounted for 6.1% and 23.1%, respectively. Finally, the alteration in proportion of potential suitable areas due to changing climate was estimated. The potential suitable areas varied from 8742 km2 to 10623 km2 over the next 40 years (2022–2060) and decreased to 8826–9184 km2 under a short-term sustainability (suitable only during current–2040). To further consider long-term and sustainable development of the wine industry (current–2060), total suitable areas dropped by 26.7–29.2% under different climate scenarios compared with current suitable areas (2001–2020). The conclusions provide indispensable guidance for vineyard zoning considering long-term climate change.
Two-Decade GNSS Observation Processing and Analysis with the New IGS Repro3 Criteria: Implications for the Refinement of Velocity Field and Deformation Field in Continental China
Authors: Wang Hu , Ren Yingying , Wang Ahao , Wang Jiexian , Cheng Yingyan , Fang Shushan , Yang Qiang
Published: August 2022

Extensive observation collection, unified and rigorous data processing, and accurate construction of the station motion model are the three essential elements for the accuracy and reliability of the Global Navigation Satellite System (GNSS) velocity field. GNSS data reprocessing not only can weaken the influence of untrue nonlinear site signals caused by imperfect models but also can eliminate the displacement offset caused by frame transformation, solution strategy, and model change. Based on the new repro3 criteria of the International GNSS Service (IGS), we process rigorously GNSS observations of continental China from the period 2000 to 2020 to refine GNSS station secular velocities and analyze the present-day crustal deformation in continental China. The main contributions of this work included the followings. Firstly, the repro3 algorithm and model are used to uniformly and rigorously process the two-decade GNSS historical observations to obtain more reliable GNSS coordinate time series with mm-level precision. Combined with the historical records of major earthquakes in continental China, we build a GNSS time series model considering nonlinear factors (velocity, offset, period, co-seismic/post-seismic deformation) to extract GNSS horizontal velocity field whose root mean square (RMS) mean is 0.1 mm/a. Secondly, the GNSS horizontal grid velocity field in continental China is interpolated using the gpsgridder method (the minimum radius is set to 16, and the Poisson’s ratio is set to 0.5). Estimation and analysis of the crustal strain rate solution lead to the conclusion that the strain degree in West China (the high strain region is mainly located in the Qinghai Tibet Plateau and Tianshan Mountains) is much more intense than that in the east (the main strain rate is less than 5 nstrain/year). In addition, most strong earthquakes in the Chinese mainland occurred on active blocks and their boundary faults with large changes in the GNSS velocity field and strain field. Then, an improved K-means++ clustering analysis method is proposed to divide active blocks using GNSS horizontal velocity field. Furthermore, different relative motion models of different blocks are constructed using the block division results. Among them, the Eurasian block has the lowest accuracy (the RMS of residual velocity in the east and north directions are 5.60 and 9.65 mm/a, respectively), and the China block 7 has the highest accuracy (the RMS mean of relative velocity in the east and north directions are 2.60 and 2.65 mm/a, respectively). More observations (2260+ sites), longer time (20 years), and updated criteria (Repro3) are to finely obtain the GNSS velocity field in continental China, and depict crustal deformation and active block with the gpsgridder and improved K-means++ methods.
Mapping Paddy Rice in Complex Landscapes with Landsat Time Series Data and Superpixel-Based Deep Learning Method
Authors: Zhang Hongguo , He Binbin , Xing Jin
Published: August 2022

The spatial pattern and temporal variation in paddy rice areas captured by remote sensing imagery provide an effective way of performing crop management and developing suitable agricultural policies. However, fragmented and scattered rice paddies due to undulating and varied topography, and the availability and quality of remote sensing images (e.g., frequent cloud coverage) pose significant challenges to accurate long-term rice mapping, especially for traditional pixel and phenological methods in subtropical monsoon regions. This study proposed a superpixel and deep-learning-based time series method to analyze Landsat time series data for paddy rice classification in complex landscape regions. First, a superpixel segmentation map was generated using a dynamic-time-warping-based simple non-iterative clustering algorithm with preprocessed spectral indices (SIs) time series data. Second, the SI images were overlaid onto the superpixel map to construct mean SIs time series for each superpixel. Third, a multivariate long short-term memory full convolution neural network (MLSTM-FCN) classifier was employed to learn time series features of rice paddies to produce accurate paddy rice maps. The method was evaluated using Landsat imagery from 2000 to 2020 in Cengong County, Guizhou Province, China. Results indicate that the superpixel MLSTM-FCN achieved a high performance with an overall accuracy varying from 0.9547 to 0.9721, which presents an 0.17–1.23% improvement compared to the random forest method. This study showed that combining spectral, spatial, and temporal features with deep learning methods can generate accurate paddy rice maps in complex landscape regions.
Monitoring Land Subsidence Using PS-InSAR Technique in Rawalpindi and Islamabad, Pakistan
Authors: Khan Junaid , Ren Xingwei , Hussain Muhammad Afaq , Jan M. Qasim
Published: August 2022

Land subsidence is a major concern in vastly growing metropolitans worldwide. The most serious risks in this scenario are linked to groundwater extraction and urban development. Pakistan’s fourth-largest city, Rawalpindi, and its twin Islamabad, located at the northern edge of the Potwar Plateau, are witnessing extensive urban expansion. Groundwater (tube-wells) is residents’ primary daily water supply in these metropolitan areas. Unnecessarily pumping and the local inhabitant’s excessive demand for groundwater disturb the sub-surface’s viability. The Persistent Scatterer Interferometry Synthetic Aperture Radar (PS-InSAR) approach, along with Sentinel-1 Synthetic Aperture Radar (SAR) imagery, were used to track land subsidence in Rawalpindi-Islamabad. The SARPROZ application was used to study a set of Sentinel-1 imagery obtained from January 2019 to June 2021 along descending and ascending orbits to estimate ground subsidence in the Rawalpindi-Islamabad area. The results show a significant increase (−25 to −30 mm/yr) in subsidence from −69 mm/yr in 2019 to −98 mm/yr in 2020. The suggested approach effectively maps, detects, and monitors subsidence-prone terrains and will enable better planning, surface infrastructure building designs, and risk management related to subsidence.
Optimization of Magnetoplasmonic ε-Near-Zero Nanostructures Using a Genetic Algorithm
Authors: de Figueiredo Felipe A. P. , Moncada-Villa Edwin , Mejía-Salazar Jorge Ricardo
Published: August 2022

Magnetoplasmonic permittivity-near-zero (ε-near-zero) nanostructures hold promise for novel highly integrated (bio)sensing devices. These platforms merge the high-resolution sensing from the magnetoplasmonic approach with the ε-near-zero-based light-to-plasmon coupling (instead of conventional gratings or bulky prism couplers), providing a way for sensing devices with higher miniaturization levels. However, the applications are mostly hindered by tedious and time-consuming numerical analyses, due to the lack of an analytical relation for the phase-matching condition. There is, therefore, a need to develop mechanisms that enable the exploitation of magnetoplasmonic ε-near-zero nanostructures’ capabilities. In this work, we developed a genetic algorithm (GA) for the rapid design (in a few minutes) of magnetoplasmonic nanostructures with optimized TMOKE (transverse magneto-optical Kerr effect) signals and magnetoplasmonic sensing. Importantly, to illustrate the power and simplicity of our approach, we designed a magnetoplasmonic ε-near-zero sensing platform with a sensitivity higher than 56∘/RIU and a figure of merit in the order of 102. These last results, higher than any previous magnetoplasmonic ε-near-zero sensing approach, were obtained by the GA intelligent program in times ranging from 2 to 5 min (using a simple inexpensive dual-core CPU computer).
Influence of Temporal and Spatial Fluctuations of the Shallow Sea Acoustic Field on Underwater Acoustic Communication
Authors: Lv Zhichao , Du Libin , Li Huming , Wang Lei , Qin Jixing , Yang Min , Ren Chao
Published: August 2022

In underwater acoustic communication (UAC) systems, the channel characteristics are mainly affected by spatiotemporal changes, which are specifically manifested by two factors: the effects of refraction and scattering caused by seawater layered media on the sound field and the random fluctuations from the sea floor and surface. Due to the time-varying and space-varying characteristics of a channel, the communication signals have significant variations in time and space. Furthermore, the signal shows frequency-selective fading in the frequency domain and signal waveform distortion in the time domain, which seriously affect the performance of a UAC system. Techniques such as error correction coding or space diversity are usually adopted by UAC systems to neutralize or eliminate the effects of deep fading and signal distortion, which results in a significant waste of limited communication resources. From the perspective of the sound field, this study used experimental data to analyze the spatiotemporal fluctuation characteristics of the signal and noise fields and then summarized the temporal and spatial variation rules. The influence of the system then guided the parameter configuration and network protocol optimization of the underwater acoustic communication system by reasonably selecting the communication signal parameters, such as frequency, bandwidth, equipment deployment depth, and horizontal distance.
A Universal Calibration Device for an Air Flow Sensor of the VAV Terminal Unit
Authors: Zhang Heng , Cai Hui , Zhang Xin , Cai Wenjian , Yin Zhaoqin
Published: August 2022

In this paper, a new calibration device for an air flow sensor of the VAV terminal unit is designed. Multi-aperture air outlets are designed to meet the calibration requirements of the air flow sensor in a variety of measurement range. The device can calibrate the air flow sensors of different types of VAV terminal unit by a movable flow rectifier without repeating the design of a different calibration pipeline. The Raspberry PI is used to design the high-performance GUI interface and controlling algorithm to achieve a one-button intelligent calibration. The air flow sensors in three different types of VAV terminal units are used to calibrate the experiment. After testing, the differential pressure value measured by the air flow sensor can accurately measure the air flow within the accuracy of 5% after the formula conversion. The conversion from differential pressure values to air flow values requires precise calibration in order to establish an accurate air flow equation, and here the calibration device plays a key role. The negative effect caused by the distance between the flow rectifiers and the VAV terminal unit is discovered. In other words, the distance between the inlet flow rectifier and the air inlet of VAV terminal unit should be kept as close as possible, or within a range of 2~3 cm. Moreover, the distance between the air outlet of VAV terminal unit and the middle-flow rectifier should be kept as close as possible; otherwise, any slight gap will cause a huge error in the calibration result. The research contributes to the further study of airflow sensing technology through the conversion and calibration of differential pressure measurements to accurate air flow values.
Urban Plants Classification Using Deep-Learning Methodology: A Case Study on a New Dataset
Authors: Litvak Marina , Divekar Sarit , Rabaev Irina
Published: August 2022

Plant classification requires the eye of an expert in botanics when the subtle differences in stem or petals differentiate between different species. Hence, an accurate automatic plant classification might be of great assistance to a person who studies agriculture, travels, or explores rare species. This paper focuses on a specific task of urban plants classification. The possible practical application of this work is a tool which assists people, growing plants at home, to recognize new species and to provide the relevant caring instructions. Because urban species are barely covered by the benchmark datasets, these species cannot be accurately recognized by the state-of-the-art pre-trained classification models. This paper introduces a new dataset, Urban Planter, for plant species classification with 1500 images categorized into 15 categories. The dataset contains 15 urban species, which can be grown at home in any climate (mostly desert) and are barely covered by existing datasets. We performed an extensive analysis of this dataset, aimed at answering the following research questions: (1) Does the Urban Planter dataset provide enough information to train accurate deep learning models? (2) Can pre-trained classification models be successfully applied on Urban Planter, and is the pre-training on ImageNet beneficial in comparison to the pre-training on a much smaller but more relevant dataset? (3) Does two-step transfer learning further improve the classification accuracy? We report the results of experiments designed to answer these questions. In addition, we provide the link to the installation code of the alpha version and the demo video of the web app for urban plants classification based on the best evaluated model. To conclude, our contribution is three-fold: (1) We introduce a new dataset of urban plant images; (2) We report the results of an extensive case study with several state-of-the-art deep networks and different configurations for transfer learning; (3) We provide a web application based on the best evaluated model. In addition, we believe that, by extending our dataset in the future to eatable plants and assisting people to grow food at home, our research contributes to achieve the United Nations’ 2030 Agenda for Sustainable Development.
Development of Sustainable Inhibitors for Corrosion Control
Authors: Khan Muhammad Azhar Ali , Irfan Osama Mohamed , Djavanroodi Faramarz , Asad Muhammad
Published: August 2022

Metal degradation due to corrosion is a major challenge in most industries, and its control and prevention has to maintain a balance between efficiency and cost-effectiveness. The rising concern over environmental damage has greatly influenced this domain, as corrosion prevention should comply with the waste regulations of different regions. In this respect, a fundamental question is which modern synthetic materials are more viable from the point of view of their effectiveness. Therefore, this paper is aims to provide an advanced and holistic review of corrosion prevention and control methods. Corrosion prevention techniques have become extensive; however, the literature indicates that polymer coatings, nano-composite coatings, and encapsulation techniques consistently provide the most efficient and feasible outcomes. Therefore, this review article examined the phenomenon of corrosion inhibition mainly from the perspective of these three techniques. Moreover, this research utilized secondary qualitative methods to obtain data and information on comparative techniques. It is found that due to the rapid development of novel materials, corrosion inhibition techniques need to be developed on scales that are more general, so that they could be applied to varying environments. The self-healing coatings are generally based on epoxy-resins incorporated with synthetic compounds such as inhibitor ions, amino-acids, or carboxylic acids. These coatings have become more widespread, especially due to bans on several traditional prevention materials such as compounds of chromium (VI). However, self-healing coatings are comparatively more costly than other techniques because of their method of synthesis and long-term durability. Therefore, although self-healing nanomaterial-based coatings are viable options for limited usage, their utilization in large and complex facilities is limited due to the costs involved. Amino acids and other biological macro-molecules provide another option to attain environmental sustainability and long durability, especially due to their origins being most of naturally occurring compounds such as lignin, cellulose, and proteins.
Study on Urban Thermal Environment in Beijing Based on Local Climate Zone Method
Authors: Han Fei , Zheng Xinqi , Li Jiayang , Zhao Yuwei , Zheng Minrui
Published: August 2022

In recent years, with the introduction of the concept of a local climate zone (LCZ), researchers have proved that adding an LCZ to the Weather Research and Forecasting (WRF) Model can improve the simulation effect. However, many existing studies cannot explain whether the improvement of accuracy in the model results is the effect of the refined zone or the effect of urban area correction, so they cannot explain the advantages of LCZ data. Therefore, this paper uses remote sensing images to generate two kinds of land use data sets and introduces them into the Weather Research and Forecasting Model coupled with the building energy model (WRF-BEM). In this paper, the two factors of urban area expansion and fine classification are considered, and three numerical examples are set up to simulate high-temperature weather in August 2019. The research shows that the simulated 2 m temperature of the scheme of correcting only urban area is the closest to the observed data. Although the RMSE in the 2 m temperature simulated by the LCZ scheme is 0.43 °C higher than that of the scheme of correcting only the urban area, it can well reproduce the spatial variation characteristics of 2 m temperature. In addition, different urban morphologies affect the spatial distribution of the surface urban heat islands in Beijing. High surface urban heat island effect zones mainly appear in the compact low-rise, compact mid-rise, and large low-rise types.
New Paradigm of Sustainable Urban Mobility: Electric and Autonomous Vehicles—A Review and Bibliometric Analysis
Authors: Kovačić Matija , Mutavdžija Maja , Buntak Krešimir
Published: August 2022

The growing relevance of sustainability, as well as the necessity to replace traditional forms of transportation with sustainable ones, has made sustainable urban mobility an imperative. In order to respond to the ever-increasing need to develop sustainable modes of transport, the importance of electric, autonomous, and electric autonomous vehicles is increasingly emphasized. In addition, as trends of growth and development in electric autonomous vehicle technology are increasing, one of the questions that has appeared is whether autonomous electric vehicles represent one of the mechanisms that will be used to increase the sustainability of urban mobility. With this in mind, the results of a systematic analysis of existing research in the WOS and Scopus databases using the keywords “urban mobility”, “electric vehicles”, and “autonomous vehicles” was carried out to identify research trends in the use of autonomous electric vehicles in urban areas. The research showed that authors focus on the advantages and disadvantages of autonomous electric vehicles and their usage in the urban mobility system, but an insufficient number of authors consider and define the need to plan the transition towards incorporating autonomous electric vehicles into the urban system. The results of this research also indicate an insufficient number of papers that research and describe the application of autonomous electric vehicles in distribution logistics. This paper provides an overview of existing research related to autonomous electric vehicles and the challenges of transition in the context of infrastructure and the development of a culture of sustainability among urban residents.
Decentralized Cooperative Active Power Control for Small-Scale Grids with High Renewable Penetration through VSC-HVDC
Authors: So Jihun , Shin Hyun , Tran Thai Nguyen , Choi Yeong-Jun
Published: August 2022

Rising renewable penetration has accelerated the volatility and instability of the power grid. A small-scale grid is especially vulnerable. Therefore, flexibility and stability enhancement are required for small-scale grids. The interconnection with the large-scale grid through the voltage sourced converter-high voltage direct current (VSC-HVDC) can be a solution to the aforementioned problems. VSC-HVDC can deliver power bidirectionally and change the direction in a short time. Hereby, the cooperative operation of distributed generations (DG) and a large-scale grid through the VSC-HVDC system is proposed in this paper. The VSC-HVDC will take the role of the main source of the small-scale grid. It determines the grid frequency based on its output power. DGs adjust their output power according to the grid frequency, and then the balance between the demand and the supply is maintained. To verify it, a PSCAD/EMTDC simulation was conducted using actual data from Jeju Island, including transmission lines, loads, and climate. Consequently, by the proposed method, the RE share was improved and the grid was operated stably even though the fault situations.
Bibliometric Analysis on the Influencing Factors of International Courses’ Effectiveness from the Perspective of Sustainable Development Education
Authors: Jiang Wei , Wu Zonghao , Su Huiyuan , Zhou Xiangping , Cui Xiaoyuan
Published: August 2022

Sustainable development education is a dynamic and developing process. In recent years, the rapid development of international courses has made great contributions to sustainable development education. The effectiveness of international courses is influenced by many factors. To promote the sustainable development of education and to improve the effectiveness of international courses, this paper studied the influencing factors on international courses by using literature analysis, system dynamics analysis, questionnaire survey, and correlation analysis methods. First, based on the literature analysis, 27 factors affecting course effectiveness were initially obtained. Second, using system dynamics to study the relationship between each factor, five additional factors were added, namely, learning motivation, social focus, lesson planning, class time, and class location. A total of 32 factors influencing course effectiveness were obtained and classified into three categories, namely, students, teachers, and external factors, and a relationship model of the 32 factors influencing course effectiveness was constructed. Finally, a questionnaire survey was conducted to quantify the 32 influencing factors, and a correlation analysis was performed on all undergraduates majoring in safety engineering enrolled in 2018 and 2019 in a university in 2019 and 2020. The results show that among the 32 influencing factors in the three categories of students, teachers, and external factors proposed, there were 7 strong correlations, 22 moderate correlations, and 3 weak correlations. All of the strong correlations belonged to the student dimension, thereby indicating that the effectiveness of international online courses is mainly influenced by student factors. In addition, these influencing factors can not only impact course effectiveness directly, but also indirectly through the interaction between factors. The relationship model of the influencing factors can provide a reference for improving the effectiveness of international programs and realizing the sustainable development research for international courses.
Impact Assessment of Seed Village Programme by Using Difference in Difference (DiD) Approach in Telangana, India
Authors: Bhavani Gottemukkula , Sreenivasulu Middhe , Naik Ravinder V. , Reddy M. Jagan Mohan , Darekar Ashwini S. , Reddy Anugu Amarender
Published: August 2022

Seed village programmes are becoming popular in developing countries due to their potential to supply of affordable seed to farmers in a timely manner. Under the programme, the profitability of seed growing farmers is important as it incentivizes them to grow more seed for distribution of seed to other farmers. This paper tried to analyze the impact of the seed village programme on profitability of seed growing farmers of paddy crop by using Difference-in-Difference approach. The study was conducted during the year 2020 in India. A significant increase in profitability of seed growing farmers compared to non-seed farmers was noticed due to the SVP scheme. It was observed that after the introduction of SVP, there was about 69.01% increase in profits of seed-farmers compared to only 5.63% among non-seed-farmers. Age, education, acreage under seed production and farming experience contributed 71.6% of the total variation in the higher profits through SVP in paddy crop, leaving the rest to extraneous factors. The difference-in-difference regression results showed that, with the introduction of the SVP in India, there was an increase in the profits of seed growing farmers by INR 13,032/acre (186 USD). These results show that most of the seed growing farmers are in favor of the growing seed under SVP and benefited from this programme.
Impact of Suspended Sediment Diffusion from the Implementation of Arresting Facilities on Cross-Sea Bridges
Authors: Chen Peng , Li Yuting , Wu Jiaxing , Li Ruijie , Song Zhiyao , Dai Lu
Published: August 2022

In order to ensure the safety of bridges and ships, non-navigable channel arresting facilities for ships have become an important part of cross-sea bridges, and the diffusion of suspended sediment caused by their implementation has an impact on seawater quality. Taking the Jintang bridge as an example, a two-dimensional tidal current and sediment numerical model was applied to predict the distribution of suspended sediment diffusion caused by the implementation of arresting facilities, in order to analyze seawater quality. We adopted a new formula for the equivalent roughness method, to generalize the bridge piers, and obtained good results. The results showed that the zone where the SSC (suspended sediment concentration) reached 10 mg/L was concentrated in the area from 4.5 km north to 6.5 km south of the arresting facility, when it was implemented near the western channel. The sea area by the main channel was concentrated within 500 m of the arresting facility. The impact of the implementation of the arresting facility on seawater quality was relatively limited. Only the protected marine area in the Zhenhai Section of the Hangzhou Bay Estuary Coastal Wetland was affected by the suspended sediment from the construction of the western channel.
Competence-Based Assessment in Higher Education during COVID-19 Lockdown: The Demise of Sustainability Competence
Authors: Cano García Elena , Lluch Molins Laia
Published: August 2022

Sustainability competence is understood as the interlinked set of knowledge, skills, attitudes, and values that effectively enable embodied action in the world concerning real-world sustainability problems, challenges, and opportunities, according to the context. Higher education institutions should promote this competence in their graduates due to its importance, which has been stressed during the period of COVID-19. However, it seems to be becoming forgotten, in the syllabus as well as in the voices of teachers and students. A study carried out at the University of Barcelona (UB) with n = 265 students and n = 129 professors on the importance and frequency of assessing this competence in times of pandemic is presented. Quantitative data was supplemented with n = 31 interviews. The data show a scarce use of assessment strategies to evaluate this competence (9.7% of the students and 15.2% of the teachers indicate some type of assessment) as well as a very low consideration of the usefulness of the assessment processes of this competence. Interviews prove that this is a missing competence. However, 14% of the students associate it with productive assessment tasks, and 19.4% of the teachers think it is related to well-aligned assessment tasks. Therefore, it seems that the future challenge is in the design of learning and assessment tasks which should consider sustainability in teaching plans and ask students to apply, solve or make decisions considering environmental, social or economic sustainability.
A Comparative Study of Three Mathematical Models for the Interaction between the Human Immune System and a Virus
Authors: Munteanu Florian
Published: August 2022

In this paper, we will consider three deterministic models for the study of the interaction between the human immune system and a virus: the logistic model, the Gompertz model, and the generalized logistic model (or Richards model). A qualitative analysis of these three models based on dynamical systems theory will be performed by studying the local behavior of the equilibrium points and obtaining the local dynamics properties from the linear stability point of view. Additionally, we will compare these models in order to understand which is more appropriate to model the interaction between the human immune system and a virus. Some natural medical interpretations will be obtained, which are available for all three models and can be useful to the medical community.
A Generalization of Szász–Mirakyan Operators Based on α Non-Negative Parameter
Authors: Ansari Khursheed J. , Usta Fuat
Published: August 2022

The main purpose of this paper is to define a new family of Szász–Mirakyan operators that depends on a non-negative parameter, say α. This new family of Szász–Mirakyan operators is crucial in that it includes both the existing Szász–Mirakyan operator and allows the construction of new operators for different values of α. Then, the convergence properties of the new operators with the aid of the Popoviciu–Bohman–Korovkin theorem-type property are presented. The Voronovskaja-type theorem and rate of convergence are provided in a detailed proof. Furthermore, with the help of the classical modulus of continuity, we deduce an upper bound for the error of the new operator. In addition to these, in order to show that the convex or monotonic functions produced convex or monotonic operators, we obtain shape-preserving properties of the new family of Szász–Mirakyan operators. The symmetry of the properties of the classical Szász–Mirakyan operator and of the properties of the new sequence is investigated. Moreover, we compare this operator with its classical correspondence to show that the new one has superior properties. Finally, some numerical illustrative examples are presented to strengthen our theoretical results.
AdS Black Holes in the Framework of Nonlinear Electrodynamics, Thermodynamics, and Joule–Thomson Expansion
Authors: Kruglov Sergey Il’ich
Published: August 2022

The thermodynamics and phase transitions of magnetic Anti-de Sitter black holes were studied. We considered extended-phase-space thermodynamics, with the cosmological constant being a thermodynamic pressure and the black hole mass being treated as a chemical enthalpy. The extended-phase-space thermodynamics of black holes mimic the behavior of a Van der Waals liquid. Quantities conjugated to the coupling of nonlinear electrodynamics (NED) and a magnetic charge are obtained. Thermodynamic critical points of phase transitions are investigated. It was demonstrated that the first law of black hole thermodynamics and the generalized Smarr relation hold. The Joule–Thomson adiabatic expansion of NED-AdS black holes is studied. The dependence of inversion temperature on pressure and the minimum of the inversion temperature are found.
Classes of Multivalent Spirallike Functions Associated with Symmetric Regions
Authors: Cotîrlǎ Luminiţa-Ioana , Karthikeyan Kadhavoor R.
Published: August 2022

We define a function to unify the well-known class of Janowski functions with a class of spirallike functions of reciprocal order. We focus on the impact of defined function on various conic regions which are symmetric with respect to the real axis. Further, we have defined a new subclass of multivalent functions of complex order subordinate to the extended Janowski function. This work bridges the studies of various subclasses of spirallike functions and extends well-known results. Interesting properties have been obtained for the defined function class. Several consequences of our main results have been pointed out.
Preparation of Monoclonal Antibody against Deoxynivalenol and Development of Immunoassays
Authors: Mokhtar Hoyda Elsir , Xu Aidi , Xu Yang , Fadlalla Mohamed Hassan , Wang Shihua
Published: August 2022

Fusarium toxins are the largest group of mycotoxins, which contain more than 140 known secondary metabolites of fungi. Deoxynivalenol (DON) is one of the most important compounds of this class due to its high toxicity and its potential to harm mankind and animals and a widespread contaminant of agricultural commodities, such as wheat, corn, barley, oats, bread, and biscuits. Herein, a hybridoma cell 8G2 secreting mAb against DON was produced by fusing the splenocytes with a tumor cell line Sp2/0. The obtained mAb had a high affinity (2.39 × 109 L/mol) to DON. An indirect competitive Enzyme-Linked Immunosorbent Assay (ic-ELISA) showed that the linear range for DON detection was 3.125–25 μg/mL, and the minimum inhibitory concentration (IC50) was 18.125 μg/mL with a limit of detection (LOD) of 7.875 μg/mL. A colloidal gold nanoparticle (AuNP) with 20 nm in diameter was synthesized for on-site detection of DON within 10 min with vLOD of 20 μg/mL. To improve the limit of detection, the gold nanoflower (AuNF) with a larger size (75 nm) was used to develop the AuNF-based strip with vLOD of 6.67 μg/mL. Compared to the vLOD of a convectional AuNP-based strip, the AuNF-based strip was three times lower. Herein, three immunoassay methods (ic-ELISA and AuNP/AuNF-based strips) were successfully developed, and these methods could be applied for the DON detection in agricultural products.
Synergistically Improved Catalytic Ozonation Process Using Iron-Loaded Activated Carbons for the Removal of Arsenic in Drinking Water
Authors: Qazi Umair Yaqub , Javaid Rahat , Ikhlaq Amir , Al-Sodani Khaled A. Alawi , Rizvi Osama Shaheen , Alazmi Amira , Asiri Abdullah Mohamed , Ibn Shamsah Sami M.
Published: August 2022

This research attempts to find a new approach for the removal of arsenic (As) from drinking water by developing a novel solution. To the author’s knowledge, iron-loaded activated carbons (Fe-AC) have not been previously applied for the removal of As in a synergistic process using ozonation and catalytic ozonation processes. The As was investigated using drinking water samples in different areas of Lahore, Pakistan, and the As removal was compared with and without using catalysts. The results also suggested that the catalytic ozonation process significantly removes As as compared with single ozonation and adsorption processes. Moreover, a feed ozone of 1.0 mg/min and catalyst dose of 10 g was found to maintain a maximum removal efficiency of 98.6% within 30 min. The results of the catalyst dose–effect suggested that the removal of As tends to increase with the increase in catalysts amount. Hence, it is concluded that the Fe-AC/O3 process efficiently removes As in water. Moreover, it was established that the Fe-AC/O3 process might be regarded as an effective method for removing As from drinking water compared to the single ozonation and adsorption processes.
Analysis of Socio-Economic Factors That Influence Loss of Life in Sediment-Related Disasters
Authors: Chiba Miki , Furuido Hiromichi , Shibasaki Shigemitsu , Haga Kazuki
Published: August 2022

Non-structural measures, including relocation from a hazard zone, land development regulations, and evacuation, are important sediment-related countermeasures. Such measures depend on the behaviour of residents and are affected by socio-economic conditions. In Japan, the declining birth rate and ageing population are expected to result in rapid changes in socio-economic conditions; accordingly, there is a need to evaluate the impact of such changes. However, there is no established methodology for the establishment of non-structural measures that considers the socio-economic conditions of all areas. Therefore, this study analysed the regional characteristics of disaster-affected areas with high numbers of casualties to elucidate the impact of socio-economic conditions. The results imply that severe losses occurred under various topographical and socio-economic conditions, such as in urban areas with high population densities and in mountainous areas with increasing depopulation. More data are needed, especially regarding socio-economic conditions. Importantly, the community-based analytical method used in this study enables a comparative analysis of disasters in different regions at different times.
THE EFFECT OF BENEFITS AND CONVENIENCE ON INTEREST IN USING E-WALLET ON MILLENNIAL GENERATION IN TUAH MADANI DISTRICT, PEKANBARU CITY
Authors: Yolanda Helga , Kartikowati Rr Sri , Hendripides Hendripides
Published: August 2022

Payment instruments continue to develop in a more practical and modern direction following human needs and technological developments, one of which is electronic money which is very helpful and makes daily transactions easier. However, in reality the public's interest in using electronic money is still relatively low. This study aims to determine the effect of benefits and convenience on interest in using e-wallet in the millennial generation in Tuah Madani District, Pekanbaru City, both simultaneously and partially. This type of research is a descriptive quantitative research. The population in this study is the millennial generation with an age range of 21 to 41 years in 2021 in the Tuah Madani District, Pekanbaru City who owns and uses e-wallet, especially GoPay. The sample of this study amounted to 110 people who were obtained using snowball sampling techniques. While the data of this study were obtained from the results of distributing online questionnaires which were measured using a Likert scale. The collected data was then processed and analyzed using multiple linear regression analysis with the help of the SPSS computer program. The results obtained indicate that the benefits and convenience variables simultaneously influence the interest in using e-wallet in the millennial generation in Tuah Madani District, Pekanbaru City. However, if an analysis is carried out on each variable, it is known that the benefit variable can have a significant influence on interest in using e-wallet. Meanwhile, the convenience variable does not have a significant effect on interest in using e-wallet.
A Comparison of the Expression of Cyclin D1 in OSCC and CSCC
Authors: Modabbernia Shirin , Mousapour Hadise , Rahimirad Parisa , Daryoush Shima
Published: August 2022

Background: There are several types of carcinoma which may cause serious diseases in humans and lead to their death. Neoplasia in squamous cells is a subtype of carcinoma which can cause squamous cell carcinoma (SCC). SCC can occur in several areas in the oral cavity (oral squamous cell carcinoma, OSCC) and cutaneous tissues (cutaneous squamous cell carcinoma, CSCC) such as skin. This study aims to investigate the expression level of cyclin D1 and its relevance to different prognoses of OSCC and CSCC. The present study investigates the expression of cyclin D1 and its relevance to different prognoses of OSCC and CSCC. Indexes such as lesion site, gender, and age have been checked. Methods: In this cross-sectional descriptive-analytical study, 23 cases of OSCC and 23 cases of CSCC were evaluated. The immunohistochemistry (IHC) staining method was employed to study the correlation of cyclin D1 and the above-mentioned SCCs. The data were analyzed using KAI2, Fisher’s exact test, Mann-Whitney U test, and dependent t tests in SPSS version 22.0. Statistical significance was set at P<0.05. Results: The results showed that staining status was not significantly correlated with lesion site (P=0.999). According to the results, there was no significant relationship between staining pattern and lesion site (P=0.749). There was a significant relationship between the severity of staining and lesion site (P=0.040). In addition, those with skin lesions showed higher staining intensity. The staining status of gender or age groups was not affected by the adjustment of lesion site. By moderating the effect of lesion site and age group, gender was found to affect staining pattern (P=0.036). The odds ratio of having a diffuse pattern was 4.90 times higher in men than in women. Regardless of the independent variables in the model of people with color intensity 2, their likelihood of going to color 4 was significantly higher (P<0.001). People in intensity 0 were significantly less likely to go to 4 (P=0.001). People in intensity 1 had no significant relationship with those in intensity 4 (P=0.405). Men were less likely to go higher than women. Furthermore, people aged 72 and under were less likely to go higher. Individuals with skin lesions were more likely to go to higher intensity, even though none of the independent variables was significant. Conclusions: The staining intensity was higher in CSCC than in OSCC. A lot of factors are associated with the prognosis of SCCs, and cyclin D1 may be used as a prognostic marker.
Kleine-Levin Syndrome in a Young Woman Triggered in Travel: A Case Report From Iran in COVID-19 Arena
Authors: Bidaki Reza , Amirifard Hamed , Fazli Parisa , Asadi Mohadeseh , Babaeian Bahabadi Samira
Published: August 2022

Introduction: Kleine-Levin syndrome (KLS) is a rare disorder often associated with recurrent hypersomnia, first described by Klein in 1925 but named in 1942 by Critchley and Hoffman. KLS is more common in adolescence and is also more common in men than women. It must be distinguished from repetitive depressive disorder, or psychotic disorder. Case Presentation: In this report, we present a 27-year-old woman with KLS who showed symptoms such as overeating and mood changes, unwillingness to talk to anyone, and a sedentary lifestyle. Meanwhile, during these periods, other symptoms such as lack of speech, decreased energy, lethargy, and slowness of mental and mood movements were observed in the patient. Eventually, with lithium consumption, her symptoms improve significantly. However, the exact cause of this syndrome and its definitive treatment is still unknown and will require further reports and studies. Conclusion: According to the reported case, KLS may be triggered by travel and migration, and in such a situation, may respond well to lithium.
Hematological Parameters Variations Among Patients With Uncomplicated Plasmodium falciparum Infection in Cambodia
Authors: Bun Rathvicheth , My Anh Bui Thi , Ko Kyaw Ko , Chan Oo May , Tun Kyaw Zarni , Thu Soe Myat , Aung Pyae Linn
Published: August 2022

Introduction: The prevalence of anemia among patients with malaria is very common from subsequent erythrocytes destruction and should be managed most appropriately. This study aimed to explore the changes in hematological parameters and their underlying influence among people with uncomplicated Plasmodium falciparum infection. Methods: A cross-sectional study was conducted among uncomplicated malaria patients infected by P. falciparum on community-based active screening days in one of the highest malaria hot-spot areas of northwestern Cambodia. Descriptive statistics, and student t-tests were used to analyze the data. Results: Among 103 malaria blood samples, the results showed that most participants had thrombocytopenia (84.5%). More than onehalf of the participants presented normal levels of the following hematological parameters: red blood cells, hemoglobin, hematocrit, mean corpuscular volume (MCV) and red cell distribution width (RDW). A significant correlation was noted between parasite counts and three body mass index (BMI) groups (P=0.047). Next, a strong association was also seen between parasite counts and body temperature (P = 0.03). Statistically significant differences in parasite count were observed across three levels of neutrophil (P=0.005), lymphocyte (P=0.001), eosinophil (P<0.001), absolute lymphocyte (P=0.001) and absolute eosinophil (P<0.001) counts. Conclusion: The results of this study revealed the significant role of hematological parameters in predicting the presence of malaria infection, parasite density, and forecasting adverse consequences of malaria, together with the underlying risk factors.