bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Nitrogen Supply Ameliorates the Performance of Wheat Seedlings under Osmotic Stress in Genotype-Specific Manner
Authors: Kartseva Tania , Dobrikova Anelia , Kocheva Konstantina , Alexandrov Vladimir , Georgiev Georgi , Brestič Marián , Misheva Svetlana
Published: March 2021

Strategies and coping mechanisms for stress tolerance under sub-optimal nutrition conditions could provide important guidelines for developing selection criteria in sustainable agriculture. Nitrogen (N) is one of the major nutrients limiting the growth and yield of crop plants, among which wheat is probably the most substantial to human diet worldwide. Physiological status and photosynthetic capacity of two contrasting wheat genotypes (old Slomer and modern semi-dwarf Enola) were evaluated at the seedling stage to assess how N supply affected osmotic stress tolerance and capacity of plants to survive drought periods. It was evident that higher N input in both varieties contributed to better performance under dehydration. The combination of lower N supply and water deprivation (osmotic stress induced by polyethylene glycol treatment) led to greater damage of the photosynthetic efficiency and a higher degree of oxidative stress than the individually applied stresses. The old wheat variety had better N assimilation efficiency, and it was also the one with better performance under N deficiency. However, when both N and water were deficient, the modern variety demonstrated better photosynthetic performance. It was concluded that different strategies for overcoming osmotic stress alone or in combination with low N could be attributed to differences in the genetic background. Better performance of the modern variety conceivably indicated that semi-dwarfing (Rht) alleles might have a beneficial effect in arid regions and N deficiency conditions.
Structure–Property Relationships in Bionanocomposites for Pipe Extrusion Applications
Authors: Botta Luigi , La Mantia Francesco Paolo , Mistretta Maria Chiara , Oliveri Antonino , Arrigo Rossella , Malucelli Giulio
Published: March 2021

In this work, bionanocomposites based on different biodegradable polymers and two types of nanofillers, namely a nanosized calcium carbonate and an organomodified nanoclay, were produced through melt extrusion, with the aim to evaluate the possible applications of these materials as a potential alternative to traditional fossil fuel-derived polyolefins, for the production of irrigation pipes. The rheological behavior of the formulated systems was thoroughly evaluated by exploiting different flow regimes, and the obtained results indicated a remarkable effect of the introduced nanofillers on the low-frequency rheological response, especially in nanoclay-based bionanocomposites. Conversely, the shear viscosity at a high shear rate was almost unaffected by the presence of both types of nanofillers, as well as the rheological response under nonisothermal elongational flow. In addition, the analysis of the mechanical properties of the formulated materials indicated that the embedded nanofillers increased the elastic modulus when compared to the unfilled counterparts, notwithstanding a slight decrease of the material ductility. Finally, the processing behavior of unfilled biopolymers and bionanocomposites was evaluated, allowing for selecting the most suitable material and thus fulfilling the processability requirements for pipe extrusion applications.
Oligoether/Zwitterion Diblock Copolymers: Synthesis and Application as Cathode-Coating Material for Li Batteries
Authors: Yoshizawa-Fujita Masahiro , Ishii Jun , Takeoka Yuko , Rikukawa Masahiro
Published: March 2021

Poly (ethylene oxide) (PEO) has been investigated as an ion-conductive matrix for several decades due to its excellent properties. However, further improvements are needed to enable a PEO-based ion-conductive matrix for practical applications. In order to develop novel solid polymer electrolytes based on zwitterions, we synthesized diblock copolymers (PPEGMA-b-SPBs) with oligoether and zwitterionic side-chains and evaluated their physico-chemical properties. PPEGMA-b-SPBs with various unit ratios were synthesized by RAFT polymerization. PPEGMA-b-SPBs with/without LiTFSA exhibited two distinct glass transition temperatures regardless of the unit ratio of PEGMA and SPB. AFM observations clearly revealed phase-separated structures. The ionic conductivity of PPEGMA-b-SPBs increased even at a high salt concentrations such as [EO]:[Li] = 6:1 and was over 10−5 S cm−1 at 25 °C. This tendency is unusual in a PEO matrix. The oxidation stability of PPEGMA-b-SPBs was about 5.0 V vs. Li/Li+, which is a higher value than that of PEO. The improvement of the electrochemical properties is attributed to the introduction of the SPB block into the block copolymers. PPEGMA-b-SPBs were evaluated as cathode-coating materials for Li batteries. The discharge capacity and coulombic efficiency of the cells employing the cathode (LiNi1/3Mn1/3Co1/3O2 (NMC)) coated with the block copolymers were much higher than those of the cell employing the pristine cathode at the 50th cycle in the cut-off voltage range of 3.0–4.6 V.
Ultraviolet-C as a Viable Reprocessing Method for Disposable Masks and Filtering Facepiece Respirators
Authors: Nicolau Talita , Filho Núbio Gomes , Zille Andrea
Published: March 2021

In normal conditions, discarding single-use personal protective equipment after use is the rule for its users due to the possibility of being infected, particularly for masks and filtering facepiece respirators. When the demand for these protective tools is not satisfied by the companies supplying them, a scenario of shortages occurs, and new strategies must arise. One possible approach regards the disinfection of these pieces of equipment, but there are multiple methods. Analyzing these methods, Ultraviolet-C (UV-C) becomes an exciting option, given its germicidal capability. This paper aims to describe the state-of-the-art for UV-C sterilization in masks and filtering facepiece respirators. To achieve this goal, we adopted a systematic literature review in multiple databases added to a snowball method to make our sample as robust as possible and encompass a more significant number of studies. We found that UV-C’s germicidal capability is just as good as other sterilization methods. Combining this characteristic with other advantages makes UV-C sterilization desirable compared to other methods, despite its possible disadvantages.
Pilgrimage and Religion: Pilgrim Religiosity on the Ways of St. James
Authors: Heiser Patrick
Published: March 2021

Pilgrimages on the Ways of St. James are becoming increasingly popular, so the number of pilgrims registered in Santiago de Compostela has been rising continuously for several decades. The large number of pilgrims is accompanied by a variety of motives for a contemporary pilgrimage, whereby religion is only rarely mentioned explicitly. While pilgrimage was originally a purely religious practice, the connection between pilgrimage and religion is less clear nowadays. Therefore, this paper examines whether and in which way religion shows itself in the context of contemporary pilgrimages on the Ways of St. James. For this purpose, 30 in-depth biographical interviews with pilgrims are analyzed from a sociological perspective on religion by using a qualitative content analysis. This analysis reveals that religion is manifested in many ways in the context of contemporary pilgrimages, whereby seven forms of pilgrim religiosity can be distinguished. They have in common that pilgrims shape their pilgrim religiosity individually and self-determined, but in doing so they rely on traditional and institutional forms of religion. Today’s pilgrim religiosity can therefore be understood as an extra-ordinary form of lived religion, whose popularity may be explained by a specific interrelation of individual shaping and institutional assurance of evidence.
Estimating Global Gross Primary Production from Sun-Induced Chlorophyll Fluorescence Data and Auxiliary Information Using Machine Learning Methods
Authors: Bai Yu , Liang Shunlin , Yuan Wenping
Published: March 2021

The gross primary production (GPP) is important for regulating the global carbon cycle and climate change. Recent studies have shown that sun-induced chlorophyll fluorescence (SIF) is highly advantageous regarding GPP monitoring. However, using SIF to estimate GPP on a global scale is limited by the lack of a stable SIF-GPP relationship. Here, we estimated global monthly GPP at 0.05° spatial resolution for the period 2001–2017, using the global OCO-2-based SIF product (GOSIF) and other auxiliary data. Large amounts of flux tower data are not available to the public and the available data is not evenly distributed globally and has a smaller measured footprint than the GOSIF data. This makes it difficult to use the flux tower GPP directly as an input to the model. Our strategy is to scale in situ measurements using two moderate-resolution satellite GPP products (MODIS and GLASS). Specifically, these two satellite GPP products were calibrated and eventually integrated by in situ measurements (FLUXNET2015 dataset, 83 sites), which was then used to train a machine learning model (GBRT) that performed the best among five evaluated models. The GPP estimates from GOSIF were highly accurate coefficient of determination (R2) = 0.58, root mean square error (RMSE) = 2.74 g C·m−2, bias = –0.34 g C·m−2) as validated by in situ measurements, and exhibited reasonable spatial and seasonal variations on a global scale. Our method requires fewer input variables and has higher computational efficiency than other satellite GPP estimation methods. Satellite-based SIF data provide a unique opportunity for more accurate, near real-time GPP mapping in the future.
The Spatial Different Order Derivative Method of Gravity and Magnetic Anomalies for Source Distribution Inversion
Authors: Ming Yanbo , Ma Guoqing , Li Lili , Han Jiangtao , Wang Taihan
Published: March 2021

Gravity and magnetic measurements are common remote sensing strategies to obtain the property change of observed targets. Nowadays, the characteristic value of the derivatives of gravity and magnetic anomalies is commonly used to detect the source horizontal edge. We found that the horizontal coordinates of the characteristic value of different-order derivatives are not directly corresponding to the edge of the source, which varies with the depth and size of the source. The spatial different-order derivative (SDD) method of gravity and magnetic anomalies was developed, and we proved that the spatial intersection of different-order derivatives is corresponding to the location of the source, and used this feature to obtain horizontal location and depth of the source simultaneously. The model tests proved that the SDD method has high accuracy and strong anti-noisy. According to the corresponding relationship between the potential field data and lithology, we used the SDD method to delineate the potential metalorganic area in the survey region, which provides the basis for subsequent exploration.
Estimation of Surface NO2 Concentrations over Germany from TROPOMI Satellite Observations Using a Machine Learning Method
Authors: Chan Ka Lok , Khorsandi Ehsan , Liu Song , Baier Frank , Valks Pieter
Published: March 2021

In this paper, we present the estimation of surface NO2 concentrations over Germany using a machine learning approach. TROPOMI satellite observations of tropospheric NO2 vertical column densities (VCDs) and several meteorological parameters are used to train the neural network model for the prediction of surface NO2 concentrations. The neural network model is validated against ground-based in situ air quality monitoring network measurements and regional chemical transport model (CTM) simulations. Neural network estimation of surface NO2 concentrations show good agreement with in situ monitor data with Pearson correlation coefficient (R) of 0.80. The results also show that the machine learning approach is performing better than regional CTM simulations in predicting surface NO2 concentrations. We also performed a sensitivity analysis for each input parameter of the neural network model. The validated neural network model is then used to estimate surface NO2 concentrations over Germany from 2018 to 2020. Estimated surface NO2 concentrations are used to investigate the spatio-temporal characteristics, such as seasonal and weekly variations of NO2 in Germany. The estimated surface NO2 concentrations provide comprehensive information of NO2 spatial distribution which is very useful for exposure estimation. We estimated the annual average NO2 exposure for 2018, 2019 and 2020 is 15.53, 15.24 and 13.27 µµg/m3, respectively. While the annual average NO2 concentration of 2018, 2019 and 2020 is only 12.79, 12.60 and 11.15 µµg/m3. In addition, we used the surface NO2 data set to investigate the impacts of the coronavirus disease 2019 (COVID-19) pandemic on ambient NO2 levels in Germany. In general, 10–30% lower surface NO2 concentrations are observed in 2020 compared to 2018 and 2019, indicating the significant impacts of a series of restriction measures to reduce the spread of the virus.
Mapping Forest Types in China with 10 m Resolution Based on Spectral–Spatial–Temporal Features
Authors: Cheng Kai , Wang Juanle , Yan Xinrong
Published: March 2021

The comprehensive application of spectral, spatial, and temporal (SST) features derived from remote sensing images is a significant technique for classifying and mapping forest types. Facing limitations in the availability of detailed forest type identification processes for large regions, a forest type classification framework based on SST features was developed in this study. The advantages of Sentinel-2 and Landsat series imagery were used to extract SST forest type classification features, using red-edge bands, a gray-level co-occurrence matrix, and harmonic analysis, with the assistance of the Google Earth Engine platform. Considering four representative Chinese geographic regions—middle and high latitudes, complex mountainous areas, cloudy and rainy areas, and the N–S climate transition zone—our method was proven to be effective, with overall classification accuracies > 85%. The scheme to assess the importance of SST features for forest classification in various regions was designed using the Gini criterion in the random forest algorithm and revealed that spectral features were more effective in classifying forest types with complex compositions. Temporal features were found to be favorable for identifying forest types with obvious evergreen and deciduous growth patterns, while spatial features produced better classification results for forest types with different spatial structures, such as needle- or broad-leaved forests. The findings of this study can provide a reference for feature selection in remote sensing forest type classification processes, and identifying forest types in this way could provide support for the accurate and sustainable management of forest resources.
Identifying Spatiotemporal Patterns in Land Use and Cover Samples from Satellite Image Time Series
Authors: Santos Lorena Alves , Ferreira Karine , Picoli Michelle , Camara Gilberto , Zurita-Milla Raul , Augustijn Ellen-Wien
Published: March 2021

The use of satellite image time series analysis and machine learning methods brings new opportunities and challenges for land use and cover changes (LUCC) mapping over large areas. One of these challenges is the need for samples that properly represent the high variability of land used and cover classes over large areas to train supervised machine learning methods and to produce accurate LUCC maps. This paper addresses this challenge and presents a method to identify spatiotemporal patterns in land use and cover samples to infer subclasses through the phenological and spectral information provided by satellite image time series. The proposed method uses self-organizing maps (SOMs) to reduce the data dimensionality creating primary clusters. From these primary clusters, it uses hierarchical clustering to create subclusters that recognize intra-class variability intrinsic to different regions and periods, mainly in large areas and multiple years. To show how the method works, we use MODIS image time series associated to samples of cropland and pasture classes over the Cerrado biome in Brazil. The results prove that the proposed method is suitable for identifying spatiotemporal patterns in land use and cover samples that can be used to infer subclasses, mainly for crop-types.
ABOships—An Inshore and Offshore Maritime Vessel Detection Dataset with Precise Annotations
Authors: Iancu Bogdan , Soloviev Valentin , Zelioli Luca , Lilius Johan
Published: March 2021

Availability of domain-specific datasets is an essential problem in object detection. Datasets of inshore and offshore maritime vessels are no exception, with a limited number of studies addressing maritime vessel detection on such datasets. For that reason, we collected a dataset consisting of images of maritime vessels taking into account different factors: background variation, atmospheric conditions, illumination, visible proportion, occlusion and scale variation. Vessel instances (including nine types of vessels), seamarks and miscellaneous floaters were precisely annotated: we employed a first round of labelling and we subsequently used the CSRT tracker to trace inconsistencies and relabel inadequate label instances. Moreover, we evaluated the out-of-the-box performance of four prevalent object detection algorithms (Faster R-CNN, R-FCN, SSD and EfficientDet). The algorithms were previously trained on the Microsoft COCO dataset. We compared their accuracy based on feature extractor and object size. Our experiments showed that Faster R-CNN with Inception-Resnet v2 outperforms the other algorithms, except in the large object category where EfficientDet surpasses the latter.
Improved Mekong Basin Runoff Estimate and Its Error Characteristics Using Pure Remotely Sensed Data Products
Authors: Fok Hok Sum , Chen Yutong , Wang Lei , Tenzer Robert , He Qing
Published: March 2021

Basin runoff is a quantity of river discharge per unit basin area monitored close to an estuary mouth, essential for providing information on the flooding and drought conditions of an entire river basin. Owing to a decreasing number of in situ monitoring stations since the late 1970s, basin runoff estimates using remote sensing have been advocated. Previous runoff estimates of the entire Mekong Basin calculated from the water balance equation were achieved through the hybrid use of remotely sensed and model-predicted data products. Nonetheless, these basin runoff estimates revealed a weak consistency with the in situ ones. To address this issue, we provide a newly improved estimate of the monthly Mekong Basin runoff by using the terrestrial water balance equation, purely based on remotely sensed water balance component data products. The remotely sensed water balance component data products used in this study included the satellite precipitation from the Tropical Rainfall Measuring Mission (TRMM), the satellite evapotranspiration from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the inferred terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE). A comparison of our new estimate and previously published result against the in situ runoff indicated a marked improvement in terms of the Pearson’s correlation coefficient (PCC), reaching 0.836 (the new estimate) instead of 0.621 (the previously published result). When a three-month moving-average process was applied to each data product, our new estimate further reached a PCC of 0.932, along with the consistent improvement revealed from other evaluation metrics. Conducting an error analysis of the estimated mean monthly runoff for the entire data timespan, we found that the usage of different evapotranspiration data products had a substantial influence on the estimated runoff. This indicates that the choice of evapotranspiration data product is critical in the remotely sensed runoff estimation.
A New Approach to Social Entrepreneurship: A Systematic Review and Meta-Analysis
Authors: García-Jurado Alejandro , Pérez-Barea José Javier , Nova Rodrigo J.
Published: March 2021

All social entrepreneurship experts state that the issue of definition is the main problem affecting research in this field. Although there is no single definition, this is clearly a new domain in the field of research on entrepreneurship. The main objective of this study is to further knowledge in this area by means of a systematic review of scientific literature to determine the conceptual development of social entrepreneurship and to identify the most interesting research trends. This study uses a research method, known as latent semantic analysis (LSA), which has been applied to a database of keywords collected from a rigorous selection of academic articles. The results show that this phenomenon has emerged from two parallel currents within the organization management field; on the one hand, the non-governmental organization (NGO) and voluntary tradition and, on the other, the world of business ethics and corporate social responsibility (CSR). The main lines of future research highlighted in the analysis include the measurement of social impact, venture philanthropy, and hybrid organizations.
Evaluation of GHG Emission Measures Based on Shipping and Shipbuilding Market Forecasting
Authors: Wada Yujiro , Yamamura Tatsumi , Hamada Kunihiro , Wanaka Shinnosuke
Published: March 2021

Greenhouse gas (GHG) emissions from the global shipping sector have been increasing due to global economic growth. The International Maritime Organization (IMO) has set a goal of halving GHG emissions from the global shipping sector by 2050 as compared with 2008 levels, and has responded by introducing several international regulations to reduce the GHG emissions of maritime transportation. The impact of GHG emissions’ regulation and measures to curb them have been evaluated in the IMO’s GHG studies. However, the long-term influence of these GHG emission measures has not yet been assessed. Additionally, the impact of various GHG reduction measures on the shipping and shipbuilding markets has not been considered; accordingly, there is room for improvement in the estimation of GHG emissions. Therefore, in this study, a model to consider GHG emission scenarios for the maritime transportation sector was developed using system dynamics and was integrated into a shipping and shipbuilding market model. The developed model was validated based on actual results and estimation results taken from a previous study. Subsequently, simulations were conducted, allowing us to evaluate the impact and effectiveness of GHG emission-curbing measures using the proposed model. Concretely, we conducted an evaluation of the effects of current and future measures, especially ship speed reduction, transition to liquid natural gas (LNG) fuel, promotion of energy efficiency design index (EEDI) regulation, and introduction of zero-emission ships, for GHG emission reduction. Additionally, we conducted an evaluation of the combination of current and future measures. The results showed that it is difficult to achieve the IMO goals for 2050 by combining only current measures and that the introduction of zero-emission ships is necessary to achieve the goals. Moreover, the limits of ship speed reduction were discussed quantitatively in relation to the maritime market aspect, and it was found that the feasible limit of ship speed reduction from a maritime market perspective was approximately 50%.
A Cultural Heritage Low Entropy Enhancement Approach: An Ex Post Evaluation of Creative Practices
Authors: Cerreta Maria , Daldanise Gaia , Giovene di Girasole Eleonora , Torre Carmelo Maria
Published: March 2021

According to the current European and Italian scenario related to urban regeneration, cultural and landscape heritage valorization is being enhanced by the activation of innovative processes and new emerging approaches. These involve the development of methodologies and tools that can address decision-making processes based on creative practices consistent with a concept named “low-entropy economy” in this paper. The low-entropy economy represents an economic approach based on the minimization of physical urban transformation and the enhancement of the existing heritage. In this perspective, the research aims to develop the Cultural Heritage Low Entropy Enhancement (CHLEE) approach by exploring how some frugal experiences have promoted cultural heritage enhancement and related complex values through a program of temporary uses and activities able to produce new values, where the human experience is essential. A crucial role is represented by the heterogeneity of creative practices that contribute to identifying and implementing innovative management and governance models. The analysis of creative practices, based upon the ex post evaluation of some Italian case studies across the PROMETHEE-GAIA multicriteria method, is able to show how these experiences build innovation ecosystems and improve the ex ante evaluation for new strategies and policies, underlining strengths, weaknesses, and milestones that shape creative experiences as drivers of urban competitiveness.
Selection of Suitable Potato Genotypes for Late-Sown Heat Stress Conditions Based on Field Performance and Stress Tolerance Indices
Authors: Al Mahmud Abdullah , Alam M. Jahangir , Kundu Bimal Chandra , Skalicky Milan , Rahman M. Matiar , Rahaman E. H. M. Shofiur , Sultana Mousumi , Molla M. Samim Hossain , Hossain Akbar , El-Shehawi Ahmed M. , Brestic Marian , Sabagh Ayman EL
Published: March 2021

International Potato Center (CIP), -bred potato genotypes produce various yields under heat stress conditions due to being sown late. To explore options for achieving this, a replicated experiment was conducted at the field of Tuber Crops Research Sub-Centre, Bangladesh Agricultural Research Institute, Bogura, Bangladesh to evaluate the performance of fourteen CIP-bred potato genotypes with two controls (Asterix and Granola). The experiment was laid out in a split-plot design with three replications. Several indices were applied to find out the suitable genotypes under heat stress. The plant height increased by 34.61% under heat stress, which was common in all the potato genotypes. Similarly, other yield-participating characters like stem per hill, canopy coverage (%), plant vigor, and tuber number per plant were also increased under heat stress conditions. However, the tuber yield was decreased by 6.30% and 11.41%, respectively when harvested at 70 and 90 days after plantation. Moreover, “CIP-203” yielded the highest (40.66 t ha−1) in non-stressed whereas, “CIP-118” yielded the highest (32.89 t/ha) in stressed conditions. Likewise, the bred “CIP-218” and “CIP-118” performed better under both growing conditions and yielded >35.00 t ha−1. According to a rank-sum test, among the fourteen potato genotypes, “CIP-218”, “LB-7”, “CIP-118”, “CIP-232”, and “CIP-112” were selected as heat-tolerant potatoes and can grow in both growing conditions with higher yield potential.
A New User-Based Incentive Strategy for Improving Bike Sharing Systems’ Performance
Authors: El Sibai Rayane , Challita Khalil , Bou Abdo Jacques , Demerjian Jacques
Published: March 2021

The benefits of having a Bike Sharing System (BSS) in a city are numerous. Among other advantages, it promotes a cleaner environment with less traffic and pollution. One major problem the users of such services encounter is that of full or empty stations, causing user dissatisfaction. The objective of this work is to propose a new user-based incentive method to enhance BSS performance. The proposed method relies on a spatial outlier detection algorithm. It consists of adapting the departure and arrival stations of the users to the BSS state by stimulating the users to change their journeys in view of minimizing the number of full and empty stations. Experiments are carried out to compare our proposed method to some existing methods for enhancing the resource availability of BSSs, and they are performed on a real dataset issued from a well-known BSS called Velib. The results show that the proposed strategy improves the availability of BSS resources, even when the collaboration of users is partial.
Burnout among Direct-Care Workers in Nursing Homes during the COVID-19 Pandemic in Spain: A Preventive and Educational Focus for Sustainable Workplaces
Authors: Martínez-López José Ángel , Lázaro-Pérez Cristina , Gómez-Galán José
Published: March 2021

Due to their continuous contact with pain and death, healthcare workers have one of the most stressful professions. Pain and death are more common in nursing homes. During the health crisis associated with COVID-19, these work centers have been characterized as spaces of high vulnerability to infection for the elderly, with a high mortality rate. This research aims to determine how the health crisis associated with COVID-19 has influenced healthcare professionals working in nursing homes for the elderly. Using a quantitative and cross-sectional method, the research was developed in residential centers in the Region of Murcia (Spain) during the second wave of the pandemic. A survey design based mainly on the Maslach Burnout Inventory (MBI) was employed. MBI measures three subscales: emotional burnout, depersonalization, and self-fulfillment. The results show that 6.4% of the respondents were burned out, 53.8% of the participants were emotionally exhausted, 35.1% were found to suffer from depersonalization, and in the case of personal development, the respondents showed a low level of 15.6%. This study shows the need to consider the establishment, in the academic environment, of training programs for health professionals related to coping with, managing, and identifying stress, especially in adverse circumstances. Similarly, in the professional field, it is necessary to develop strategies to prevent stress and anxiety in the workplace. The development of training programs for this purpose is essential for achieving a sustainable work context.
COVID-19 Inspired a STEM-Based Virtual Learning Model for Middle Schools—A Case Study of Qatar
Authors: Abouhashem Azza , Abdou Rana Magdy , Bhadra Jolly , Siby Nitha , Ahmad Zubair , Al-Thani Noora Jabor
Published: March 2021

An unprecedented turn in educational pedagogies due to the COVID-19 pandemic has significantly affected the students’ learning process worldwide. This article describes developing a STEM-based online course during the schools’ closure in the COVID-19 epidemic to combat the virtual science classroom’s limitations that could promise an active STEM learning environment. This learning model of the online STEM-based course successfully developed and exercised on 38 primary–preparatory students helped them to overcome the decline in their learning productivity. Various digital learning resources, including PowerPoint presentations, videos, online simulations, interactive quizzes, and innovative games, were implemented as instructional tools to achieve the respective content objectives. A feedback mechanism methodology was executed to improve online instructional delivery and project learners’ role in a student-centered approach, thereby aiding in the course content’s qualitative assessment. The students’ learning behavior provided concrete insights into the program’s positive outcomes, witnessing minimal student withdrawals and maximum completed assignments. Conclusions had been drawn from the course assessment (by incorporating both synchronous and asynchronous means), student feedback, and SWOT analysis to evaluate the course’s effectiveness.
3D Variables Requirements for Property Valuation Modeling Based on the Integration of BIM and CIM
Authors: El Yamani Siham , Hajji Rafika , Nys Gilles-Antoine , Ettarid Mohamed , Billen Roland
Published: March 2021

The growing rate of urbanization and vertical urban development has aroused the significance of geo-related variables for property units disposed vertically within the same building. Among these, 3D indoor physical and outdoor environmental variables are impacting the property value for each building unit. However, in the literature, the identified 3D variables, by using hedonic pricing models (HPM) for property valuation, are mainly restricted to 3D visualization. Their use in 3D simulation for an accurate evaluation of the property value is still limited. Furthermore, their value is often defined for a specific valuation purpose (e.g., taxation). This paper aims to investigate 3D variables with a significant impact on property value, to combine them with 3D technical requirements and to be integrated in a future valuation model. Moreover, their 3D spatial and non-spatial elements are analyzed to identify which variables can be provided from 3D city models and building scale elements. To accomplish this, the potential of 3D building information modeling (BIM) and city information modeling (CIM) in property valuation is examined. From indoors; BIM/IFC (Industry Foundation Classes) models are the main data sources for structural and living quality variables. While from outdoors, environmental variables and the surrounding building’s information are provided from 3D city models (CityGML).
Highly Efficient Deacidification Process for Camelina sativa Crude Oil by Molecular Distillation
Authors: Ştefan Nicoleta Gabriela , Iancu Petrica , Pleșu Valentin , Călinescu Ioan , Ignat Nicoleta Daniela
Published: March 2021

Recovery and reuse of high-acidity vegetable oil waste (higher content of free fatty acids) is a major concern for reducing their effect on the environment. Moreover, the conventional deacidification processes are known to show drawbacks, such as oil losses or higher costs of wastewater treatment, for which it requires great attention, especially at the industrial scale. This work presents the design of a highly efficient and sustainable process for Camelina sativa oil deacidification by using an ecofriendly method, namely molecular distillation. Experimental studies were performed to identify operating conditions for removing of free fatty acids (FFA) by molecular distillation which involves the oil evaporation in high vacuum conditions. The experimental studies were supported by statistical analysis and technical-economic analysis. Response surface methodology (RSM) was employed to formulate and validate second-order models to predict deacidification efficiency, FFA concentration, and triacylglyceride (TAG) concentration in deodorized oil based on three parameters effects, validated by statistical p-value < 0.05. For a desirability function value of 0.9826, the optimal parameters of evaporator temperature at 173.5 °C, wiper speed at 350 rpm, and feed flowrate at 2 mL/min were selected. The results for process design at optimal conditions (using conventional and molecular distillation methods) showed an efficiency over 92%, a significant reduction in FFA (up to 1%), and an increase in TAG (up to 93%) in refined oil for both methods. From an economical point of view, the deacidification by molecular distillation of Camelina sativa oil is a sustainable process: no wastewater generation, no solvents and water consumption, and lower production costs, obtaining a valuable by-product (FFA).
The Debate If Agents Matter vs. the System Matters in Sustainability Transitions—A Review of the Literature
Authors: Koistinen Katariina , Teerikangas Satu
Published: March 2021

Transition studies is a growing discipline for addressing sustainability challenges. Traditionally, its focus has been at the system level. However, addressing sustainability challenges also requires attending to the role of agents in sustainability transitions. This is the focus adopted in this paper. We review the literature on agency in sustainability transitions, based on 77 journal articles on sustainability transitions listed in Scopus from 2014 to 2018. We find that agency is increasingly explored in the sustainability transitions literature. Despite this growing interest, this body of knowledge remains scattered in regard to typologies or theoretical framings. Our review leads us to identify three recurring themes. One theme drew our attention in particular: the transition research community is divided into those who argue that agency is sufficiently embedded in the transition literature and those who oppose this argument. Going forward, the dynamics of individual-level agency, including behaviors and motivation, deserve further attention.
Energy Storage for Energy Security and Reliability through Renewable Energy Technologies: A New Paradigm for Energy Policies in Turkey and Pakistan
Authors: Uddin Riaz , Raza Khan Hashim , Arfeen Asad , Shirazi Muhammad Ayaz , Rashid Athar , Shahbaz Khan Umar
Published: March 2021

Forecasting the microeconomics of electricity will turn into a challenging process when electricity is produced through renewable energy technologies (RET). These technologies are mainly sunlight-based photovoltaic (PV), wind power, and tidal resources, which vigorously rely upon ecological conditions. For a reliable and livable energy supply to the electricity grid from renewable means, electrical energy storage technologies can play an important role while considering the weather effects in order to provide immaculate, safe, and continuous energy throughout the generation period. Energy storage technologies (ESTs) charge themselves during the low power demand period and discharge when the demand of electricity increases in such a way that they act as a catalyst to provide energy boost to the power grid. In this paper, we presented and discussed the renewable ESTs for each type with respect to their operational mechanism. In this regard, the renewable energy scenarios of Pakistan and Turkey are first discussed in detail by analyzing the actual potential of each renewable energy resource in both the countries. Then, policy for the EST utilization for both the countries is recommended in order to secure sustainable and reliable energy provision.
Omnichannel Customer Experience and Management: An Integrative Review and Research Agenda
Authors: Gerea Carmen , Gonzalez-Lopez Fernanda , Herskovic Valeria
Published: March 2021

In a highly competitive landscape, adopting an omnichannel approach might lead to a market advantage in terms of acquiring and retaining customers, as well as a means to ensure business sustainability. Omnichannel organizations situate the customer at the core of their interaction. However, research on omnichannel customer experience (CX) is still fragmented. In this paper, by adopting an integrative approach, we aim to articulate the empirical evidence around omnichannel CX and its management. Moreover, we show how research around omnichannel CX emerged from different theoretical perspectives and disciplines such as marketing, sociology and computer science. Towards this goal, we conducted a systematic literature review—with in depth analysis of 50 papers—and identified that omnichannel CX literature has engaged a number of research streams from various theoretical perspectives. Based on the research gaps, we propose an agenda for future research including topics such as (1) understanding the customer lifecycle in an omnichannel context; (2) integrating new touchpoints and channels; (3) predicting the omnichannel customer behavior; and (4) approaching omnichannel CX in service-based organizations. We conclude that adopting an omnichannel CX management approach requires the entire organization to be customer-centric while articulating interdisciplinary teams. Available studies on omnichannel CX provide the foundations for extending the knowledge on this topic and developing tools for practitioners to use in the omnichannel management assessment, operationalization, and measurement.
Research on Residents’ Willingness to Pay for Promoting the Green Development of Resource-Based Cities: A Case Study in Chifeng
Authors: Zhao Meng , Zhang Xueqi , Wang Chenxing , Zhao Yu , Wu Gang
Published: March 2021

Resource-based cities have made significant contributions to the development of human beings but have also accumulated various unsustainable ills. For this reason, China put forward the strategy of green development. This study used questionnaires to explore the extent of residents’ understanding of regional green development in Chifeng City and their willingness to support local green development, and further analyzed the differences in the residents’ attitudes and willingness to pay (WTP) with different socioeconomic characteristics. The results showed that most of the respondents supported the green development strategy and demonstrated a strong willingness to participate in regional green development investment. According to calculations, the per capita WTP for green development in Chifeng is 45.05 yuan/a (about 7 dollars/a, 5.7 euros/a). Urban residents, government employees, and well-educated respondents were more inclined to support regional green development and showed a greater WTP. Elderly and female respondents agreed more with the government’s green development promotion, while the young and middle-aged populations and men tended to have higher green development expenditures. The respondents’ annual income difference was reflected in the amounts of residents’ WTP. This study also offered scientific support and policy assistance to promote the environmental protection work from government-led to public participation.
Zearalenone Induces Endothelial Cell Apoptosis through Activation of a Cytosolic Ca2+/ERK1/2/p53/Caspase 3 Signaling Pathway
Authors: Lee Hyeon-Ju , Oh Se-Young , Jo Inho
Published: March 2021

Zearalenone (ZEN) is a mycotoxin that has been reported to damage various types of cells/tissues, yet its effects on endothelial cells (ECs) have never been investigated. Therefore, this study investigates the potential effects of ZEN using bovine aortic ECs (BAECs). In this study, we found that ZEN induced apoptosis of BAECs through increased cleavage of caspase 3 and poly ADP-ribose polymerase (PARP). ZEN also increased phosphorylation of ERK1/2 and p53, and treatment with the ERK1/2 or p53 inhibitor reversed ZEN-induced EC apoptosis. Transfection of BAECs with small interfering RNA against ERK1/2 or p53 revealed ERK1/2 as an upstream target of p53 in ZEN-stimulated apoptosis. ZEN increased the production of reactive oxygen species (ROS), yet treatment with the antioxidant did not prevent EC apoptosis. Similarly, blocking of estrogen receptors by specific inhibitors also did not prevent ZEN-induced apoptosis. Finally, chelation of cytosolic calcium (Ca2+) using BAPTA-AM or inhibition of endoplasmic reticulum (ER) Ca2+ channel using 2-APB reversed ZEN-induced EC apoptosis, but not by inhibiting ER stress using 4-PBA. Together, our findings demonstrate that ZEN induces EC apoptosis through an ERK1/2/p53/caspase 3 signaling pathway activated by Ca2+ release from the ER, and this pathway is independent of ROS production and estrogen receptor activation.
A Novel High Throughput, Parallel Infection Assay for Determining the Replication Capacities of 346 Primary HIV-1 Isolates of the Zurich Primary HIV-1 Infection Study in Primary Cells
Authors: Rindler Audrey E. , Kuster Herbert , Neumann Kathrin , Leemann Christine , Braun Dominique L. , Metzner Karin J. , Günthard Huldrych F.
Published: March 2021

HIV-1 replication capacity is an important characteristic to understand the replication competence of single variants or virus populations. It can further aid in the understanding of HIV-1 pathogenicity, disease progression, and drug resistance mutations. To effectively study RC, many assays have been established. However, there is still demand for a high throughput replication capacity assay using primary cells which is robust and reproducible. In this study, we established such an assay and validated it using 346 primary HIV-1 isolates from patients enrolled in the Zurich Primary HIV Infection study (ZPHI) and two control viruses, HIV-1 JR-CSFWT and HIV-1 JR-CSFK65R_M184V. Replication capacity was determined by measuring the viral growth on PBMCs over 10 days by longitudinally transferring cell culture supernatant to TZM-bl reporter cells. By utilizing the TZM-bl luciferase reporter assay, we determined replication capacity by measuring viral infectivity. The simplicity of the experimental setup allowed for all 346 primary HIV-1 isolates to be replicated at one time. Although the infectious input dose for each virus was normalized, a broad range of replication capacity values over 4 logs was observed. The approach was confirmed by two repeated experiments and we demonstrated that the reproducibility of the replication capacity values is statistically comparable between the two separate experiments. In summary, these results endorse our high throughput replication capacity assay as reproducible and robust and can be utilized for large scale HIV-1 replication capacity experiments in primary cells.
SARS-CoV-2 Survival on Surfaces and the Effect of UV-C Light
Authors: Gidari Anna , Sabbatini Samuele , Bastianelli Sabrina , Pierucci Sara , Busti Chiara , Bartolini Desirée , Stabile Anna Maria , Monari Claudia , Galli Francesco , Rende Mario , Cruciani Gabriele , Francisci Daniela
Published: March 2021

The aim of this study was to establish the persistence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on inanimate surfaces such as plastic, stainless steel, and glass during UV-C irradiation which is a physical means commonly utilized in sanitization procedures. The viral inactivation rate, virus half-life, and percentage of titer reduction after UV-C irradiation were assessed. Infectivity was maintained on plastic and glass until 120 h and on stainless steel until 72 h. The virus half-life was 5.3, 4.4, and 4.2 h on plastic, stainless steel, and glass, respectively. In all cases, titer decay was >99% after drop drying. UV-C irradiation efficiently reduced virus titer (99.99%), with doses ranging from 10.25 to 23.71 mJ/cm2. Plastic and stainless steel needed higher doses to achieve target reduction. The total inactivation of SARS-CoV-2 on glass was obtained with the lower dose applied. SARS-CoV-2 survival can be long lasting on inanimate surfaces. It is worth recommending efficient disinfection protocols as a measure of prevention of viral spread. UV-C can provide rapid, efficient and sustainable sanitization procedures of different materials and surfaces. The dosages and mode of irradiation are important parameters to consider in their implementation as an important means to fight the SARS-CoV-2 pandemic.
Pharmacogenetics Approach for the Improvement of COVID-19 Treatment
Authors: Fricke-Galindo Ingrid , Falfán-Valencia Ramcés
Published: March 2021

The treatment of coronavirus disease 2019 (COVID-19) has been a challenge. The efficacy of several drugs has been evaluated and variability in drug response has been observed. Pharmacogenetics could explain this variation and improve patients’ outcomes with this complex disease; nevertheless, several disease-related issues must be carefully reviewed in the pharmacogenetic study of COVID-19 treatment. We aimed to describe the pharmacogenetic variants reported for drugs used for COVID-19 treatment (remdesivir, oseltamivir, lopinavir, ritonavir, azithromycin, chloroquine, hydroxychloroquine, ivermectin, and dexamethasone). In addition, other factors relevant to the design of pharmacogenetic studies were mentioned. Variants in CYP3A4, CYP3A5, CYP2C8, CY2D6, ABCB1, ABCC2, and SLCO1B1, among other variants, could be included in pharmacogenetic studies of COVID-19 treatment. Besides, nongenetic factors such as drug–drug interactions and inflammation should be considered in the search for personalized therapy of COVID-19.