bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Consumption Patterns and Load Forecasting with Profiled CNN-LSTM Networks
Authors: Al-Saudi Kareem , Degeler Viktoriya , Medema Michel
Published: October 2021

By virtue of the steady societal shift to the use of smart technologies built on the increasingly popular smart grid framework, we have noticed an increase in the need to analyze household electricity consumption at the individual level. In order to work efficiently, these technologies rely on load forecasting to optimize operations that are related to energy consumption (such as household appliance scheduling). This paper proposes a novel load forecasting method that utilizes a clustering step prior to the forecasting step to group together days that exhibit similar energy consumption patterns. Following that, we attempt to classify new days into pre-generated clusters by making use of the available context information (day of the week, month, predicted weather). Finally, using available historical data (with regard to energy consumption) alongside meteorological and temporal variables, we train a CNN-LSTM model on a per-cluster basis that specializes in forecasting based on the energy profiles present within each cluster. This method leads to improvements in forecasting performance (upwards of a 10% increase in mean absolute percentage error scores) and provides us with the added benefit of being able to easily highlight and extract information that allows us to identify which external variables have an effect on the energy consumption of any individual household.
Contemporary Business Practices of the Ru (Confucian) Ethic of “Three Guides and Five Constant Virtues (三綱五常)” in Asia and Beyond
Authors: Song Bin
Published: October 2021

What can remain unchanged while the Ru tradition (Confucianism) is continually passed down generationally and passed on geographically to non-Chinese Asian countries and beyond? Does the answer to this question hinted by the tradition itself, viz., the ethic of Three Guides and Five Constant Virtues, still work in contemporary society? As intrigued by these fundamental questions on Ruism, scholars have debated on the nature of the ethic and its adaptability to the contemporary world. One side of scholars condemned it as an outdated, premodern ethic of power which urges unconditional obedience to hierarchy, while another side championed it as a modern ethic which aims to strengthen the autonomy of each individual in reciprocal relationships. While presenting two cases of Ru business practice, viz., Shibusawa Eiichi in Meiji Japan and Peter Drucker in the contemporary U.S., the article treats the controversial ethic as a hypothesis, and assesses it using an empirical method to reinforce views of scholars who have furnished a favorable interpretation of the ethic.
Incorporating Folk Belief into National Heritage: The Interaction between Ritual Practice and Theatrical Performance in Xiud Yax Lus Qim (Yalu wang) of the Miao (Hmong) Ethnic Group
Authors: Guo Chao , Hua Huijuan , Geng Xiwen
Published: October 2021

Xiud Yax Lus Qim or Yalu wang 亞魯王 (Ode to the King Yalu) is a type of oral performance inherited verbally and transmitted orally by dongb langf (donglang 東郎, chanters of Yalu wang) at funerals and festive occasions. As one of the most representative cultural sets of the Miao (Hmong) ethnic group located in southern China, Yalu wang is embedded in Miao sorcery beliefs and practices, and serves as a vehicle to unite the community and maintain the identity of the ethnic group. However, since Yalu wang was “discovered” as a heroic epic by scholars in 2009 and entered the government’s “List of National Intangible Cultural Heritage” two years later, different agencies have been vying to appropriate its cultural resources. Not only do local government authorities use it as a tourist attraction, stage performances have also produced various versions of Yalu wang to portray an emblem of what are presumed to be “authentic Miao cultures”. This article explores the interactive relationship between Miao sorcery and folk traditions in the oral performance of Yalu wang and their enactment and re-enactment in theatrical performances under the aegis of a state-endorsed tourism policy. In so doing, the discussion sheds new light on the bidirectional dynamics that not only remold the style of performing culture, but also facilitate religious synthesis.
Contribution of Soil Type to Quantity and Nutritional Value of Grass Species on the South African Highveld
Authors: Mokgakane Thabile Joyce , Mlambo Victor , Ravhuhali Khuliso Emmanuel , Magoro Norman
Published: October 2021

The biggest threat to cattle production in most South African communal areas is poor management of grazing, which negatively affects vegetation and soil structures. This study was conducted to assess the spatial variation of grass species density, production potential and quality in Breyten (Hutton soil type), Davel (Avalon soil type), and Wesselton (Clovelly soil type) communal rangelands in the highveld region of Mpumalanga province. Three 100 m transects per grazing area, placed at 50 m intervals (0, 50, and 100 m) were used to collect soil samples at 200 mm depth. A 100 m permanent line point method, replicated three times (50 m apart) per site, was used to identify and collect grass species samples. Grass species were classified according to life form, palatability, ecological status, and abundance. Grasses species were also harvested for chemical composition and in vitro ruminal dry matter degradability determination. Soils from the study areas had an acidic pH range (3.5–4.5). Hutton soil had the highest (p < 0.05) nitrate (N-NO3) concentration (0.770 mg/kg) compared to Clovelly (0.030 mg/kg) and Avalon (0.533 mg/kg) soil types. Thirty-one grass species composed of 28 turf perennials, two weak perennials and one perennial creeping grass were identified across the study areas. About 16% of identified grass species were classified as highly palatable, 39% as moderately palatable, and 32% as unpalatable. Across all the soil types, Digitaria eriantha had the highest (p < 0.05) crude protein (CP) (106.5 g/kg DM) content when compared to other grass species. In the Avalon soil type, D. eriantha had the lowest (p < 0.05) neutral detergent fiber (NDF) (696.4 g/kg DM). Across all soils, D. eriantha, Aristida congesta, Eragrostis curvula, Eragrostis gummiflua, and Eragrostis plana grasses had the same (p > 0.05) 48-h in vitro ruminal dry matter degradability Hutton soil had a higher proportion of common and dominant grass species as well as more palatable species with higher crude protein content than Avalon and Clovelly soils. However, for all three rangelands, there is a need for supplementary feeding to enhance the production efficiency of livestock given that the nutritive value of grasses was low.
Regulation of InsurTech: Is the Principle of Proportionality an Answer?
Authors: Ostrowska Marta
Published: October 2021

In the view of the current discussion on how to regulate the emerging InsurTech companies, if at all, the author attempts to demonstrate that rather than automatically introducing new regulation, the principle of proportionality can, in most cases, help to adapt application of the existing rules and policy approaches to the InsurTech business models without incurring major regulatory changes. An example of peer-to-peer platforms is used to show how the specificity of each InsurTech company can be grasped by the three key criteria of proportionality: nature, scale and complexity.
Exploring Fuzzy Local Spatial Information Algorithms for Remote Sensing Image Classification
Authors: Madhu Anjali , Kumar Anil , Jia Peng
Published: October 2021

Fuzzy c-means (FCM) and possibilistic c-means (PCM) are two commonly used fuzzy clustering algorithms for extracting land use land cover (LULC) information from satellite images. However, these algorithms use only spectral or grey-level information of pixels for clustering and ignore their spatial correlation. Different variants of the FCM algorithm have emerged recently that utilize local spatial information in addition to spectral information for clustering. Such algorithms are seen to generate clustering outputs that are more enhanced than the classical spectral-based FCM algorithm. Nonetheless, the scope of integrating spatial contextual information with the conventional PCM algorithm, which has several advantages over the FCM algorithm for supervised classification, has not been explored much. This study proposed integrating local spatial information with the PCM algorithm using simpler but proven approaches from available FCM-based local spatial information algorithms. The three new PCM-based local spatial information algorithms: Possibilistic c-means with spatial constraints (PCM-S), possibilistic local information c-means (PLICM), and adaptive possibilistic local information c-means (ADPLICM) algorithms, were developed corresponding to the available fuzzy c-means with spatial constraints (FCM-S), fuzzy local information c-means (FLICM), and adaptive fuzzy local information c-means (ADFLICM) algorithms. Experiments were conducted to analyze and compare the FCM and PCM classifier variants for supervised LULC classifications in soft (fuzzy) mode. The quantitative assessment of the soft classification results from fuzzy error matrix (FERM) and root mean square error (RMSE) suggested that the new PCM-based local spatial information classifiers produced higher accuracies than the PCM, FCM, or its local spatial variants, in the presence of untrained classes and noise. The promising results from PCM-based local spatial information classifiers suggest that the PCM algorithm, which is known to be naturally robust to noise, when integrated with local spatial information, has the potential to result in more efficient classifiers capable of better handling ambiguities caused by spectral confusions in landscapes.
CryoSat-2 Significant Wave Height in Polar Oceans Derived Using a Semi-Analytical Model of Synthetic Aperture Radar 2011–2019
Authors: Heorton Harold , Tsamados Michel , Armitage Thomas , Ridout Andy , Landy Jack
Published: October 2021

This paper documents the retrieval of significant ocean surface wave heights in the Arctic Ocean from CryoSat-2 data. We use a semi-analytical model for an idealised synthetic aperture satellite radar or pulse-limited radar altimeter echo power. We develop a processing methodology that specifically considers both the Synthetic Aperture and Pulse Limited modes of the radar that change close to the sea ice edge within the Arctic Ocean. All CryoSat-2 echoes to date were matched by our idealised echo revealing wave heights over the period 2011–2019. Our retrieved data were contrasted to existing processing of CryoSat-2 data and wave model data, showing the improved fidelity and accuracy of the semi-analytical echo power model and the newly developed processing methods. We contrasted our data to in situ wave buoy measurements, showing improved data retrievals in seasonal sea ice covered seas. We have shown the importance of directly considering the correct satellite mode of operation in the Arctic Ocean where SAR is the dominant operating mode. Our new data are of specific use for wave model validation close to the sea ice edge and is available at the link in the data availability statement.
Spatiotemporal Analysis of Sea Ice Leads in the Arctic Ocean Retrieved from IceBridge Laxon Line Data 2012–2018
Authors: Sha Dexuan , Koo Younghyun , Miao Xin , Srirenganathan Anusha , Lan Hai , Biswas Shorojit , Liu Qian , Mestas-Nuñez Alberto M. , Xie Hongjie , Yang Chaowei
Published: October 2021

The ocean and atmosphere exert stresses on sea ice that create elongated cracks and leads which dominate the vertical exchange of energy, especially in cold seasons, despite covering only a small fraction of the surface. Motivated by the need of a spatiotemporal analysis of sea ice lead distribution, a practical workflow was developed to classify the high spatial resolution aerial images DMS (Digital Mapping System) along the Laxon Line in the NASA IceBridge Mission. Four sea ice types (thick ice, thin ice, open water, and shadow) were identified, and relevant sea ice lead parameters were derived for the period of 2012–2018. The spatiotemporal variations of lead fraction along the Laxon Line were verified by ATM (Airborne Topographic Mapper) surface height data and correlated with coarse spatial resolution sea ice motion, air temperature, and wind data through multiple regression models. We found that the freeboard data derived from sea ice leads were compatible with other products. The temperature and ice motion vorticity were the leading factors of the formation of sea ice leads, followed by wind vorticity and kinetic moments of ice motion.
STC-Det: A Slender Target Detector Combining Shadow and Target Information in Optical Satellite Images
Authors: Huang Zhaoyang , Wang Feng , You Hongjian , Hu Yuxin
Published: October 2021

Object detection has made great progress. However, due to the unique imaging method of optical satellite remote sensing, the detection of slender targets is still insufficient. Specifically, the perspective of optical satellites is small, and the characteristics of slender targets are severely lost during imaging, resulting in insufficient detection task information; at the same time, the appearance of slender targets in the image is greatly affected by the satellite perspective, which is likely to cause insufficient generalization capabilities of conventional detection models. In response to these two points, we have made some improvements. First, in this paper, we introduce the shadow as auxiliary information to complement the trunk features of the target lost in imaging. Second, to reduce the impact of satellite perspective on imaging, in this paper, we use the characteristic that shadow information is not affected by satellite perspective to design STC-Det. STC-Det treats the shadow and the target as two different types of targets and uses the shadow information to assist the detection, reducing the impact of the satellite perspective on detection. Among them, in order to improve the performance of STC-Det, we propose an automatic matching method (AMM) of shadow and target and a feature fusion method (FFM). Finally, this paper proposes a new method to calculate the heatmaps of detectors, which verifies the effectiveness of the proposed network in a visual way. Experiments show that when the satellite perspective is variable, the precision of STC-Det is increased by 1.7%, and when the satellite perspective is small, the precision of STC-Det is increased by 5.2%.
Are the Latest GSMaP Satellite Precipitation Products Feasible for Daily and Hourly Discharge Simulations in the Yellow River Source Region?
Authors: Shi Jiayong , Wang Bing , Wang Guoqing , Yuan Fei , Shi Chunxiang , Zhou Xiong , Zhang Limin , Zhao Chongxu
Published: October 2021

Global Satellite Mapping of Precipitation (GSMaP) products, as important satellite-based precipitation products (SPPs) of Global Precipitation Measurement (GPM) mission, have provided hydrologists with critical precipitation data sources for hydrological applications in gauge-sparse or ungauged basins. This study statistically and hydrologically evaluated the latest GPM-era GSMaP SPPs in real-, near-real- and post-real-time versions at daily and hourly temporal scales in the sparsely gauged Yellow River source region (YRSR) in China. It includes the five latest GSMaP SPPs, namely, gauge-adjusted product (GSMaP-Gauge), microwave-infrared reanalyzed product (GSMaP-MVK), near-real-time product (GSMaP-NRT), near-real-time product with gauge-based adjustment (GSMaP-NRT-Gauge), and real-time product (GSMaP-Now). The statistical assessment showed that among all five GSMaP SPPs, GSMaP-Gauge presented the best overall performance in daily and hourly precipitation detections in YRSR, followed by GSMaP-Now. GSMaP-NRT-Gauge was ranked the third, whereas GSMaP-MVK and GSMaP-NRT had relatively inferior performance. Given that GSMaP-Gauge demonstrated the best quality among all evaluated GSMaP SPPs, GSMaP-Gauge displayed the best hydrological feasibility in daily streamflow simulation. Both GSMaP-MVK and GSMaP-NRT presented inferior hydrological capability, with a considerable overestimation of the total streamflow. In contrast, GSMaP-Now and GSMaP-NRT-Gauge displayed basically acceptable hydrological performance in daily discharge simulations. In terms of hourly flood simulations, the performance of GSMaP-Gauge slightly worsened but was comparable to the rain-gauge-based precipitation data set. Following GSMaP-Gauge, GSMaP-Now and GSMaP-NRT-Gauge obtained certain predictability of flood events. In general, GSMaP-MVK and GSMaP-NRT barely had hydrological utility for flood-event simulations.
SGA-Net: Self-Constructing Graph Attention Neural Network for Semantic Segmentation of Remote Sensing Images
Authors: Zi Wenjie , Xiong Wei , Chen Hao , Li Jun , Jing Ning
Published: October 2021

Semantic segmentation of remote sensing images is always a critical and challenging task. Graph neural networks, which can capture global contextual representations, can exploit long-range pixel dependency, thereby improving semantic segmentation performance. In this paper, a novel self-constructing graph attention neural network is proposed for such a purpose. Firstly, ResNet50 was employed as backbone of a feature extraction network to acquire feature maps of remote sensing images. Secondly, pixel-wise dependency graphs were constructed from the feature maps of images, and a graph attention network is designed to extract the correlations of pixels of the remote sensing images. Thirdly, the channel linear attention mechanism obtained the channel dependency of images, further improving the prediction of semantic segmentation. Lastly, we conducted comprehensive experiments and found that the proposed model consistently outperformed state-of-the-art methods on two widely used remote sensing image datasets.
SAR Target Detection Based on Domain Adaptive Faster R-CNN with Small Training Data Size
Authors: Guo Yuchen , Du Lan , Lyu Guoxin
Published: October 2021

It is expensive and time-consuming to obtain a large number of labeled synthetic aperture radar (SAR) images. In the task of small training data size, the results of target detection on SAR images using deep network approaches are usually not ideal. In this study, considering that optical remote sensing images are much easier to be labeled than SAR images, we assume to have a large number of labeled optical remote sensing images and a small number of labeled SAR images with the similar scenes, propose to transfer knowledge from optical remote sensing images to SAR images, and develop a domain adaptive Faster R-CNN for SAR target detection with small training data size. In the proposed method, in order to make full use of the label information and realize more accurate domain adaptation knowledge transfer, an instance level domain adaptation constraint is used rather than feature level domain adaptation constraint. Specifically, generative adversarial network (GAN) constraint is applied as the domain adaptation constraint in the adaptation module after the proposals of Faster R-CNN to achieve instance level domain adaptation and learn the transferable features. The experimental results on the measured SAR image dataset show that the proposed method has higher detection accuracy in the task of SAR target detection with small training data size than the traditional Faster R-CNN.
GRACE-FO Antenna Phase Center Modeling and Precise Orbit Determination with Single Receiver Ambiguity Resolution
Authors: Jin Biao , Li Yuqiang , Jiang Kecai , Li Zhulian , Chen Shanshan
Published: October 2021

Precise knowledge of the phase center location of the global navigation satellite system (GNSS) antenna is a prerequisite for precise orbit determination (POD) of the low Earth orbit (LEO) satellite. The phase center offset (PCO) and phase center variation (PCV) values for the LEO antenna obtained from ground calibration cannot reflect the error sources encountered in the actual spacecraft environment. PCV corrections are estimated by ionosphere free (IF) carrier phase post-fit residuals of reduced dynamic orbit determination. Ambiguity resolution (AR) plays a crucial role in achieving the best orbit accuracy. The single receiver AR concept is realized using wide-lane (WL) and narrow-lane (NL) bias products. Single difference (SD) observations between satellites are applied to remove the receiver dependent phase bias. SD AR and traditional double difference (DD) AR methods are applied to fix the ambiguities. The recovered SD and DD IF ambiguities are taken as pseudo-observations to constrain the undifferenced IF ambiguity parameters in the POD process. The LEO orbits based on float ambiguity (FA), SD, AR, and DD AR are investigated. One year’s data collected by the Gravity Recovery And Climate Experiment Follow-On (GRACE-FO) mission and GPS precise products provided by the Center for Orbit Determination in Europe (CODE) were analyzed. Precise orbit generated by the Jet Propulsion Laboratory (JPL), independent satellite laser ranging (SLR), and K-band ranging (KBR) measurements were utilized to assess the orbit accuracy. More than 98% of SD WL and 95% of SD NL ambiguities are fixed, which confirms the good quality of the bias products and correctness of the SD AR method. With PCV corrections, the average phase residuals of DD and SD AR solutions are 0.13 and 0.41 mm, which indicates improved consistency between applied models and observations. Compared with JPL’s orbit, the SD AR orbits achieve the accuracy of 6.0, 6.2, and 5.1 mm in along-track, cross-track, and radial directions. The SD AR solutions show an average improvement of 18.3% related to the FA orbits while 6.3% is gained by the DD AR approach. The root mean squares (RMSs) of SLR residuals for FA, DD AR, and SD AR solutions are 11.5, 10.2, and 9.6 mm, which validate the positive effect of AR on POD. Standard deviation (STD) of KBR residuals for SD AR orbits is 1.8 mm while 0.9 mm is achieved by the DD AR method. The explanation is that the phase bias products used for SD AR are not free of errors and the errors may degrade the KBR validation. In-flight PCV calibration and ambiguity resolution improve the LEO orbit accuracy effectively.
BiFA-YOLO: A Novel YOLO-Based Method for Arbitrary-Oriented Ship Detection in High-Resolution SAR Images
Authors: Sun Zhongzhen , Leng Xiangguang , Lei Yu , Xiong Boli , Ji Kefeng , Kuang Gangyao
Published: October 2021

Due to its great application value in the military and civilian fields, ship detection in synthetic aperture radar (SAR) images has always attracted much attention. However, ship targets in High-Resolution (HR) SAR images show the significant characteristics of multi-scale, arbitrary directions and dense arrangement, posing enormous challenges to detect ships quickly and accurately. To address these issues above, a novel YOLO-based arbitrary-oriented SAR ship detector using bi-directional feature fusion and angular classification (BiFA-YOLO) is proposed in this article. First of all, a novel bi-directional feature fusion module (Bi-DFFM) tailored to SAR ship detection is applied to the YOLO framework. This module can efficiently aggregate multi-scale features through bi-directional (top-down and bottom-up) information interaction, which is helpful for detecting multi-scale ships. Secondly, to effectively detect arbitrary-oriented and densely arranged ships in HR SAR images, we add an angular classification structure to the head network. This structure is conducive to accurately obtaining ships’ angle information without the problem of boundary discontinuity and complicated parameter regression. Meanwhile, in BiFA-YOLO, a random rotation mosaic data augmentation method is employed to suppress the impact of angle imbalance. Compared with other conventional data augmentation methods, the proposed method can better improve detection performance of arbitrary-oriented ships. Finally, we conduct extensive experiments on the SAR ship detection dataset (SSDD) and large-scene HR SAR images from GF-3 satellite to verify our method. The proposed method can reach the detection performance with precision = 94.85%, recall = 93.97%, average precision = 93.90%, and F1-score = 0.9441 on SSDD. The detection speed of our method is approximately 13.3 ms per 512 × 512 image. In addition, comparison experiments with other deep learning-based methods and verification experiments on large-scene HR SAR images demonstrate that our method shows strong robustness and adaptability.
The Perinatal Journey of a Refugee Woman in Greece: A Qualitative Study in the Context of the ORAMMA Project to Elucidate Current Challenges and Future Perspectives
Authors: Papadakaki Maria , Iliadou Maria , Sioti Eirini , Petelos Elena , Vivilaki Victoria
Published: October 2021

Migrant and refugee women face specific health risks and challenges during the perinatal period, presenting with complex physical, psychological, and mental health issues. Compassionate antenatal and postnatal care is urgently required across Europe given how outcomes during this period determine the health wellbeing throughout a person’s life. The current study aimed to describe the perinatal health care provided to refugee and migrant women in Greece, as well as to identify the barriers to delivering quality health care to these population groups. Data were gathered via qualitative research, and via document analysis, including grey literature research. Two focus groups were convened; one with five midwives in Athens (representing NGOs in refugee camps and public maternity hospitals) and another in Crete with twenty-six representatives of key stakeholder groups involved in the perinatal care of refugees and migrant women. Desk research was conducted with in a stepwise manner comprising two steps: (a) a mapping exercise to identify organizations/institutes of relevance across Greece, i.e., entities involved in perinatal healthcare provision for refugees and migrants; (b) an electronic search across institutional websites and the World Wide Web, for key documents on the perinatal care of refugee and migrant women that were published during the 10-year period prior to the research being conducted and referring to Greece. Analysis of the desk research followed the principles of content analysis, and the analysis of the focus group data followed the principles of an inductive thematic analysis utilizing the actual data to drive the structure analysis. Key findings of the current study indicate that the socioeconomic status, living and working conditions, the legal status in the host country, as well as providers’ cultural competence, attitudes and beliefs and communication challenges, all currently represent major barriers to the efficient and culturally appropriate provision of perinatal care. The low capacity of the healthcare system to meet the needs of women in these population groups in the context of maternal care in a country that has suffered years of austerity has been amply recorded and adds further contextual constraints. Policy reform is urgently required to achieve cultural competence, to improve transcultural care provision across maternity care settings, and to ensure improved maternal and children’s outcomes.
Diversity Barometer 2020: Attitudes towards Immigration and Ethnic Diversity in Sweden
Authors: Munobwa Jimmy Stephen , Ahmadi Fereshteh , Darvishpour Mehrdad
Published: October 2021

Migration is topical in many counties, and attitudes towards immigration and ethnic diversity are volatile. In our longitudinal “Diversity Barometer”, we have studied changes in Swedes’ attitudes towards immigration and ethnic diversity in Sweden since 2005, using a postal questionnaire sent to a random sample of the Swedish population aged 18–75. In this article, we analyzed data from 2020 (n = 1035) in comparison with previous Diversity Barometer surveys from 2005 to 2018. The findings showed that Swedes had increased contact with immigrants from the Middle East, Asia and Africa. The majority had good experiences of studying or working with people with foreign background, although those with bad experiences had also increased. Attitudes towards immigration and ethnic diversity were more positive in 2020, thereby stopping a negative trend that started with the refugee influx in 2015. Positive attitudes were more established among women, younger people, those with higher education, people living in larger cities and those with more contact with people with foreign background. Sympathizers of political parties closer to the left wing were more positive towards immigration and ethnic diversity. We used political correctness, contact theory, strain theory and theory about group conflict/threats to provide hypothetical explanations for the observed changes in attitudes.
Putative Role of MCT1 rs1049434 Polymorphism in High-Intensity Endurance Performance: Concept and Basis to Understand Possible Individualization Stimulus
Authors: Ramírez de la Piscina-Viúdez Xavier , Álvarez-Herms Jesús , Bonilla Diego A. , Castañeda-Babarro Arkaitz , Larruskain Jon , Díaz-Ramírez Julen , Ahmetov Ildus I. , Martínez-Ascensión Alex , Kreider Richard B. , Odriozola-Martínez Adrián
Published: October 2021

Monocarboxylate transporters (MCTs) have been proposed as important mediators of the exchange between lactate (La−) producer and La− recipient (consumer) cells. Previous studies have suggested that the MCT1 A1470T genotype could be related to different physical performance phenotypes. This study followed the guidelines for Strengthening the Reporting of Genetic Association Studies (STREGA) and aimed to evaluate the distribution of the MCT1 polymorphism rs1049434 in endurance-trained athletes compared to the untrained population. Moreover, this study explored the potential influence of the polymorphism alleles phenotypes on high-intensity exercise performance. In a cross-sectional study fashion, a total of 85 triathletes from northern Spain were genotyped for MCT1 rs1049434 and compared to a control group of 107 healthy male participants (1000 Genomes Research Study for Iberian Populations in Spain). All athletes performed a 30 s Wingate all-out test (WAnT) on a cycle ergometer. Peak and mean power (absolute and relative) were measured. After verification of the Hardy–Weinberg equilibrium, the findings indicated that the MCT1 TT genotype was overrepresented in triathletes in comparison to the genotypic frequency of the general Spanish population. No significant associations were found between any MCT1 genotype and peak or mean power performance in the WAnT. Further studies are required to understand the relationship among MCT1 A1470T polymorphism, endurance-trained athletes, and high-intensity performance.
Articulating Spatial Statistics and Spatial Optimization Relationships: Expanding the Relevance of Statistics
Authors: Griffith Daniel A.
Published: October 2021

Both historically and in terms of practiced academic organization, the anticipation should be that a flourishing synergistic interface exists between statistics and operations research in general, and between spatial statistics/econometrics and spatial optimization in particular. Unfortunately, for the most part, this expectation is false. The purpose of this paper is to address this existential missing link by focusing on the beneficial contributions of spatial statistics to spatial optimization, via spatial autocorrelation (i.e., dis/similar attribute values tend to cluster together on a map), in order to encourage considerably more future collaboration and interaction between contributors to their two parent bodies of knowledge. The key basic statistical concept in this pursuit is the median in its bivariate form, with special reference to the global and to sets of regional spatial medians. One-dimensional examples illustrate situations that the narrative then extends to two-dimensional illustrations, which, in turn, connects these treatments to the spatial statistics centrography theme. Because of computational time constraints (reported results include some for timing experiments), the summarized analysis restricts attention to problems involving one global and two or three regional spatial medians. The fundamental and foundational spatial, statistical, conceptual tool employed here is spatial autocorrelation: geographically informed sampling designs—which acknowledge a non-random mixture of geographic demand weight values that manifests itself as local, homogeneous, spatial clusters of these values—can help spatial optimization techniques determine the spatial optima, at least for location-allocation problems. A valuable discovery by this study is that existing but ignored spatial autocorrelation latent in georeferenced demand point weights undermines spatial optimization algorithms. All in all, this paper should help initiate a dissipation of the existing isolation between statistics and operations research, hopefully inspiring substantially more collaborative work by their professionals in the future.
Measuring Citizens-Centric Smart City: Development and Validation of Ex-Post Evaluation Framework
Authors: Oh Jooseok , Seo Minho
Published: October 2021

This research aims to present a standardized evaluation system to review and further enhance users’ levels of satisfaction with technologies, facilities, and services of a modern smart city at a time when the smart city paradigm has shifted from the focus of its infrastructural features to citizens. The study also seeks to verify the standardized system, so as to explore the possibility of its future application. For the goals, this research established the Structural Equation Model (SEM) based upon the basic structure of the Customer Satisfaction Index, which is a widely used ex-post assessment model, and upon implications of related studies. To verify the SEM, this study chose two cities, which are located far away from one another and employ different business methods, and conducted a survey of 212 and 197 residents, respectively, with the results being applied to the model for analysis to ascertain if the SEM is reliable and adequate. The analysis results showed that the model secures explanatory power in statistical terms, partially proving that it can be developed into a post-evaluation system for a citizens-centric smart city down the road. However, as meaningful differences were spotted in accordance with characteristics of each urban project, this study tried to come up with the background information of and reasons for such variations, to present implications for urban planning.
Challenges and Prospects of Advancing Groundwater Research in Ethiopian Aquifers: A Review
Authors: Mengistu Tarekegn Dejen , Chung Il-Moon , Chang Sun Woo , Yifru Bisrat Ayalew , Kim Min-Gyu , Lee Jeongwoo , Ware Hiyaw Hatiya , Kim Il-Hwan
Published: October 2021

Groundwater is a strategic resource in all climatic regions of Ethiopia, contributing about 80% of the domestic supply of urban and rural populations. However, little research has been available compared with extensive geographical coverage and increasing population growth rates. Hence, the present study aimed to review published groundwater research of Ethiopian aquifers to realize potential research challenges and suggest future research directions. We focused on groundwater potential, recharge process, and qualities. The total potential groundwater of the country ranges from 2.5 to 47 billion cubic meters. The study depicted that the mean annual recharge estimate varies from 24.9 mm to 457 mm at catchments scales. However, the overall country was about 39.1 mm. The study found a need for a detailed investigation of different factors susceptible to groundwater pollution, as some of the evaluations indicated exceeding acceptable standards. This study observed that the main challenge was the lack of data and convergence research trends. Henceforth, future research in different climate regions should focus on multifaceted technical and stakeholder settings. This study gives the insight to integrate palatable research findings with the national policy and decision-making process to enhance the sustainability of groundwater resources significantly.
Techno-Economic Optimization of a Solar–Wind Hybrid System to Power a Large-Scale Reverse Osmosis Desalination Plant
Authors: Soliman A. M. , Alharbi Abdullah G. , Sharaf Eldean Mohamed A.
Published: October 2021

Solar-wind hybrid systems have grown to become a pivotal option for powering membrane desalination processes, especially because they have zero harmful emissions. In this work, solar photovoltaic (PV) and horizontal wind turbine (HWT) systems were used to drive a reverse osmosis (RO) desalination process to produce large-capacity fresh water. Moreover, an investigation into a hybrid PV–HWT system combined with RO was also conducted. The proposed systems are compared technically and economically with the solar organic Rankine cycle (SORC) for RO. Technical and analytical optimization methods were performed to minimize the unit product cost (USD/m3). The results revealed that photovoltaic-powered RO is recommended over wind energy operations. However, for large capacities, both thermal and wind farms dominate.
The Effect of Corporate Social Responsibility and the Executive Compensation on Implicit Cost of Equity: Evidence from French ESG Data
Authors: Chouaibi Yamina , Rossi Matteo , Zouari Ghazi
Published: October 2021

This research aimed to evaluate the effect of corporate social responsibility (CSR) and executive incentive compensation based on the achievement of sustainability goals on the implicit cost of equity. To test the study’s hypotheses, the authors applied linear regressions on panel data using the Thomson Reuters ASSET4 and Thompson Institutional Brokers Earnings Services (I/B/E/S) database of a sample of 154 French ESG firms over the 2015–2020 period. Our results show that CSR activities lower the cost of equity capital; hence, these activities are important to shareholders’ investment and financing decisions. The results have practical implications for investors and other partners interested in the business. Thus, using the implicit cost of equity is a better estimate of shareholder requirements in the context of socially responsible businesses. The results of this work could attract the attention of socially responsible investors and, especially, corporate citizens.
Endocrine Disruption, Cytotoxicity and Genotoxicity of an Organophosphorus Insecticide
Authors: Belaid Afifa , Methneni Nosra , Nasri Emna , Bchir Sarra , Anthonissen Roel , Verschaeve Luc , Le Tilly Véronique , Lo Turco Vincenzo , Di Bella Giuseppa , Ben Mansour Hedi , Khdary Nezar
Published: October 2021

In the present study, a battery of biological tests undertaken in vitro and in vivo was used to evaluate the toxic potential of an organophosphorus insecticide, namely Fenitrothion. The cytotoxic effect of pesticide was evaluated with the MTT assay against two human cancer cell lines: Hep-2 and MDA-MB-231. Genotoxicity was also studied using the bacterial VITOTOX® assay. The estrogenic effect was tested using the recombinant yeasts (YES) assay. Likewise, bioluminescence assays using V. fischeri and D. magna immobilization were performed. The results showed that Fenitrothion exhibits a variable cytotoxic effect depending on the dose as well as the studied cell lines, and no genotoxicity was observed in the tested sample. However, an estrogenic effect was recorded when investigating Fenitrothion using the recombinant yeasts (YES) assay. Analogously, acute toxicity was observed for both organisms and at all tested concentrations of Fenitrothion. Overall, these results underline the crucial importance of in vitro and in vivo bioassays in monitoring toxicity of pesticides.
Decision-Making Behavior Analysis and Empirical Study under Information Intervention in a Cold Environment
Authors: Huang Wenbo , Chen Yanyan , Chai Shushan
Published: October 2021

Some mega-sport events such as the Winter Olympics are usually held in areas accompanied by cold environment, which has a great risk of frostbite and safety for pedestrians. Releasing guidance information have become a good way for managers to reduce freezing time, improve travel efficiency and prevent safety accidents. In this article, the 2022 Winter Olympics were taken as an example to discuss influence of information intervention on TDMB (travel decision-making behavior). The mechanism of the TDMB was explored, and a survey of pedestrian behavior was carried out in the area. In particular, the influence of the subjective perception and objective factors on the RDMB (route decision-making behavior) was analyzed based on the SEM-logit model. The results show that information, congestion and the cold have an impact on the decision-making behavior. The path coefficient values of the pedestrians’ perception of information, congestion and the cold were 0.557, 0.216 and 0.324, respectively, which indicates that guidance information has the most serious impact on the pedestrians’ comprehensive perception. The objective factors including outdoor walking time, information intervention frequency, distance to a heated space had a significant impact on the RDMB. Indeed, when information intervention frequency is 2, the compliance rate of pedestrians to the information can be effectively increased. If the manager wants to alleviate traffic congestion, setting up heated spaces within a radius of 1 km is a good way to divert pedestrians. This study can provide a scientific reference for the sustainable development of mega-sport events, long-term construction of service facilities and the passenger flow management in a cold environment.
Education as a Critical Factor of Sustainability: Case Study in Qatar from the Teachers’ Development Perspective
Authors: Al-Thani Wadha A , Ari Ibrahim , Koç Muammer
Published: October 2021

Education is considered the primary driver of sustainable development. Teachers play a critical role in the conjunction of ideal, designed, and actual teaching and learning experience delivery. Successful education plays a crucial role in accomplishing the UN Sustainable Development goals (SDGs). Therefore, this research focused on the better preparation of teachers to deliver high-quality education for achieving SDGs in Qatar. To this end, this study investigated teachers’ development needs, including their professional preparation, empowerment, and assessment, by employing semi-structured interviews in selected schools. In summary, the findings show a lack of professional development (PD) opportunities, and the current PD approaches have no direction, purpose, or progress. The results also demonstrate that objective and customized assessment methods, a clear and robust career roadmap, and career promotions accordingly would increase teachers’ motivation for their, and thus students’, development. In addition, only a few teachers are aware of the SDGs and their connections with education. Therefore, there is a need to raise their level of understanding and motivation by preparing them with the right set of skills and tools and paying attention to the teachers’ development as a whole at school, society, and policy levels.
How Do Different Households Respond to Public Education Spending?
Authors: Yu Shuang , Zhao Xiaojun
Published: October 2021

Using data from the China Family Panel Studies (CFPS), we developed an educational production function to examine how households with different income levels and parental human capital respond to changes in public spending. Our results suggest that there is a significant complementary effect between household inputs of time and money and public investments in the educational process. However, the results are heterogeneous in terms of different income levels. Rich families have more incentives to invest in their children, suggesting a crowd-in effect of public resources. In contrast, public spending crowds out private inputs for poor families, who care more about their own well-being. Moreover, we show that educational investments in parents have spill-over effects on their children, but the degrees of influence are different for the poor and the rich.
Applying Spatial Analysis to Create Modern Rich Pictures for Grassland Health Analysis
Authors: Pereira Fabiellen C. , Smith Carol M. S. , Maxwell Thomas M. R. , Charters Stuart M. , Logan Chris M. , Donovan Mitchell , Jayathunga Sadeepa , Gregorini Pablo
Published: October 2021

Grasslands are complex and heterogeneous ecosystems, and their health can be defined by the cumulative ability of their components to evolve, adapt, and maintain their integrity in the presence of stress/disturbance and provide ecosystem services. Herein, a design approach is used to generate alternative and multifunctional pastoral livestock production systems that enhance grassland health. As a way of understanding the complexity of grasslands and initiating the design process using systems thinking, rich pictures emerge as a useful method. As rich pictures are subjective views, geographic information systems (GIS) could be applied to improve the veracity of their outcomes, as both techniques are forms of an analytical process. This paper reports the application of GIS to a case study of a high-country farm to generate and combine different thematic maps to create a modern rich picture. The rich picture is a combination of remote sensing data (altitude, slope, aspects, and the Normalized Difference Vegetation Index (NDVI)), and on-the-ground data (plant species distribution and diversity and soil chemical, biological, and physical parameters). Layers were combined using a multi-criteria evaluation (MCE) based on the analytical hierarchy process (AHP) to create a final rich picture. The results highlight dissimilarities in perceptions of what underpins ‘grassland health’ between researchers in different fields and with different perspectives. The use of GIS produced a modern rich picture that enhanced the understanding of grassland health and allowed for the identification of gaps, values, and possibilities for future research work.
The Mediating Role of the Social Identity on Agritourism Business
Authors: Khazami Nesrine , Lakner Zoltan
Published: October 2021

There is a significant relationship between social capital, functional competences and social identity which forms the environment of rural tourism. This complexity was studied using the PLS-SEM approach, applying the initial corrected bias method based on direct questionnaire surveys among rural tourism entrepreneurs in Tunisia. The results of the bias-corrected primer model revealed that the entrepreneur’s social identity mediated the link between social capital and functional competencies. Managerially, social capital supports rural lodge entrepreneurs in the process of defining their marketing strategy and optimizing the different components of their marketing mix, focusing on the differentiation of their products and services. A strong link within the entrepreneur’s social capital network will encourage them to strengthen their social identity, leading to the enhancement of their different functional competencies.