bluuebunny/crossref_metadata_2025 huggingface dataset:
About Validation-Comparison of Burned Area Products
Authors: Valencia Germán M. , Anaya Jesús A. , Velásquez Éver A. , Ramo Rubén , Caro-Lopera Francisco J.
Published: December 2020

This paper proposes a validation-comparison method for burned area (BA) products. The technique considers: (1) bootstrapping of scenes for validation-comparison and (2) permutation tests for validation. The research focuses on the tropical regions of Northern Hemisphere South America and Northern Hemisphere Africa and studies the accuracy of the BA products: MCD45, MCD64C5.1, MCD64C6, Fire CCI C4.1, and Fire CCI C5.0. The first and second parts consider methods based on random matrix theory for zone differentiation and multiple ancillary variables such as BA, the number of burned fragments, ecosystem type, land cover, and burned biomass. The first method studies the zone effect using bootstrapping of Riemannian, full Procrustes, and partial Procrustes distances. The second method explores the validation by using distance permutation tests under uncertainty. The results refer to Fire CCI 5.0 with the best BA description, followed by MCD64C6, MCD64C5.1, MCD45, and Fire CCI 4.1. It was also found that biomass, total BA, and the number of fragments affect the BA product accuracy.
An Assessment of the Hydrological Trends Using Synergistic Approaches of Remote Sensing and Model Evaluations over Global Arid and Semi-Arid Regions
Authors: Li Wenzhao , El-Askary Hesham , Thomas Rejoice , Tiwari Surya Prakash , Manikandan Karuppasamy P. , Piechota Thomas , Struppa Daniele
Published: December 2020

Drylands cover about 40% of the world’s land area and support two billion people, most of them living in developing countries that are at risk due to land degradation. Over the last few decades, there has been warming, with an escalation of drought and rapid population growth. This will further intensify the risk of desertification, which will seriously affect the local ecological environment, food security and people’s lives. The goal of this research is to analyze the hydrological and land cover characteristics and variability over global arid and semi-arid regions over the last decade (2010–2019) using an integrative approach of remotely sensed and physical process-based numerical modeling (e.g., Global Land Data Assimilation System (GLDAS) and Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) models) data. Interaction between hydrological and ecological indicators including precipitation, evapotranspiration, surface soil moisture and vegetation indices are presented in the global four types of arid and semi-arid areas. The trends followed by precipitation, evapotranspiration and surface soil moisture over the decade are also mapped using harmonic analysis. This study also shows that some hotspots in these global drylands, which exhibit different processes of land cover change, demonstrate strong coherency with noted groundwater variations. Various types of statistical measures are computed using the satellite and model derived values over global arid and semi-arid regions. Comparisons between satellite- (NASA-USDA Surface Soil Moisture and MODIS Evapotranspiration data) and model (FLDAS and GLDAS)-derived values over arid regions (BSh, BSk, BWh and BWk) have shown the over and underestimation with low accuracy. Moreover, general consistency is apparent in most of the regions between GLDAS and FLDAS model, while a strong discrepancy is also observed in some regions, especially appearing in the Nile Basin downstream hyper-arid region. Data-driven modelling approaches are thus used to enhance the models’ performance in this region, which shows improved results in multiple statistical measures ((RMSE), bias (ψ), the mean absolute percentage difference (|ψ|)) and the linear regression coefficients (i.e., slope, intercept, and coefficient of determination (R2)).
Surface Motion Prediction and Mapping for Road Infrastructures Management by PS-InSAR Measurements and Machine Learning Algorithms
Authors: Fiorentini Nicholas , Maboudi Mehdi , Leandri Pietro , Losa Massimo , Gerke Markus
Published: December 2020

This paper introduces a methodology for predicting and mapping surface motion beneath road pavement structures caused by environmental factors. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) measurements, geospatial analyses, and Machine Learning Algorithms (MLAs) are employed for achieving the purpose. Two single learners, i.e., Regression Tree (RT) and Support Vector Machine (SVM), and two ensemble learners, i.e., Boosted Regression Trees (BRT) and Random Forest (RF) are utilized for estimating the surface motion ratio in terms of mm/year over the Province of Pistoia (Tuscany Region, central Italy, 964 km2), in which strong subsidence phenomena have occurred. The interferometric process of 210 Sentinel-1 images from 2014 to 2019 allows exploiting the average displacements of 52,257 Persistent Scatterers as output targets to predict. A set of 29 environmental-related factors are preprocessed by SAGA-GIS, version 2.3.2, and ESRI ArcGIS, version 10.5, and employed as input features. Once the dataset has been prepared, three wrapper feature selection approaches (backward, forward, and bi-directional) are used for recognizing the set of most relevant features to be used in the modeling. A random splitting of the dataset in 70% and 30% is implemented to identify the training and test set. Through a Bayesian Optimization Algorithm (BOA) and a 10-Fold Cross-Validation (CV), the algorithms are trained and validated. Therefore, the Predictive Performance of MLAs is evaluated and compared by plotting the Taylor Diagram. Outcomes show that SVM and BRT are the most suitable algorithms; in the test phase, BRT has the highest Correlation Coefficient (0.96) and the lowest Root Mean Square Error (0.44 mm/year), while the SVM has the lowest difference between the standard deviation of its predictions (2.05 mm/year) and that of the reference samples (2.09 mm/year). Finally, algorithms are used for mapping surface motion over the study area. We propose three case studies on critical stretches of two-lane rural roads for evaluating the reliability of the procedure. Road authorities could consider the proposed methodology for their monitoring, management, and planning activities.
Analytical Model for Blood Glucose Detection Using Electrical Impedance Spectroscopy
Authors: Pedro Bruna , Marcôndes David , Bertemes-Filho Pedro
Published: December 2020

Pathogens and adulterants in human feeding consumables can be readily identified according to their electrical properties. Electrical bioimpedance analysis (BIA) has been widely used for body contents characterization, such as blood, urine, lactate, and sweat. If the concentration of glucose in blood alters the electrical properties of the blood medium, then the impedance spectrum obtained by BIA can be used to measure glycemia. For some applications, artificial neural networks allow the correlation of these parameters both impedance and concentration of glucose by means of symbolic and statistical rules. According to our literature review, there is not any physical model that allows the interpretation of the relationship between blood’s electrical properties from impedance spectra and the concentration of glucose in blood plasma. This article proposes a simplified physical model for blood electrical conductivity as a function of concentration of glucose, based on Bruggeman’s effective medium theory. The equations of this model were obtained considering an insulating phase distribution diffused in a conductive matrix, in which red blood cells are represented by macroscopic insulating nuclei and glucose molecules by microscopic insulating particles. The impedance spectrum for different glucose concentrations (4.0 to 6.8 mmol/L) in a blood sample, published by Kamat Bagul (2014), were compared to the proposed model. The results showed a significant correlation with the experimental data, showing a maximum error of 5.2%. The proposed model might be useful in the design of noninvasive blood glucose monitoring systems.
Local Water-Filling Algorithm for Shadow Detection and Removal of Document Images
Authors: Wang Bingshu , Chen C. L. Philip
Published: December 2020

Shadow detection and removal is an important task for digitized document applications. It is hard for many methods to distinguish shadow from printed text due to the high darkness similarity. In this paper, we propose a local water-filling method to remove shadows by mapping a document image into a structure of topographic surface. Firstly, we design a local water-filling approach including a flooding and effusing process to estimate the shading map, which can be used to detect umbra and penumbra. Then, the umbra is enhanced using Retinex Theory. For penumbra, we propose a binarized water-filling strategy to correct illumination distortions. Moreover, we build up a dataset called optical shadow removal (OSR dataset), which includes hundreds of shadow images. Experiments performed on OSR dataset show that our method achieves an average ErrorRatio of 0.685 with a computation time of 0.265 s to process an image size of 960×544 pixels on a desktop. The proposed method can remove the shading artifacts and outperform some state-of-the-art methods, especially for the removal of shadow boundaries.
Precision Angle Measurement Systems on the Basis of Ring Laser Gyro
Authors: Filatov Yuri V. , Pavlov Petr A. , Velikoseltsev Alexander A. , Schreiber K. Ulrich
Published: December 2020

The main application of a ring laser gyroscope is navigation. It is currently the most widely used device for strapdown inertial navigation systems. However, it is also applicable for high-precision angle metrology systems. This paper discusses the properties of a laser dynamic goniometer (LDG) based on the ring laser gyroscope and designed for the calibration of optical polygons and digital angle converters, and for the measurement of angles between external mirrors (theodolite operating mode). We consider the main sources of uncertainty, such as the ring laser gyro bias due to an external magnetic field and the instability caused by the velocity of rotation along with applicable methods of their compensation. The reversal method providing separation of uncertainties of the LDG and the calibrated angle converter is analyzed in detail. The simplified cross-calibration method is also considered. The results of calibration of optical encoders of various designs—with and without their own rotors (on-axis and off-axis in Euramet terminology)—are presented. Some results of the dynamic goniometer for the measurement of angles between external mirrors are presented. It is shown that the LDG in this mode of operation demonstrates better accuracy than modern theodolites and total stations.
Using Convolutional Neural Networks with Multiple Thermal Sensors for Unobtrusive Pose Recognition
Authors: Burns Matthew , Cruciani Federico , Morrow Philip , Nugent Chris , McClean Sally
Published: December 2020

The desire to remain living in one’s own home rather than a care home by those in need of 24/7 care is one that requires a level of understanding for the actions of an environment’s inhabitants. This can potentially be accomplished with the ability to recognise Activities of Daily Living (ADLs); however, this research focuses first on producing an unobtrusive solution for pose recognition where the preservation of privacy is a primary aim. With an accurate manner of predicting an inhabitant’s poses, their interactions with objects within the environment and, therefore, the activities they are performing, can begin to be understood. This research implements a Convolutional Neural Network (CNN), which has been designed with an original architecture derived from the popular AlexNet, to predict poses from thermal imagery that have been captured using thermopile infrared sensors (TISs). Five TISs have been deployed within the smart kitchen in Ulster University where each provides input to a corresponding trained CNN. The approach is evaluated using an original dataset and an F1-score of 0.9920 was achieved with all five TISs. The limitations of utilising a ceiling-based TIS are investigated and each possible permutation of corner-based TISs is evaluated to satisfy a trade-off between the number of TISs, the total sensor cost and the performances. These tests are also promising as F1-scores of 0.9266, 0.9149 and 0.8468 were achieved with the isolated use of four, three, and two corner TISs, respectively.
Real-Time Prediction of Joint Forces by Motion Capture and Machine Learning
Authors: Giarmatzis Georgios , Zacharaki Evangelia I. , Moustakas Konstantinos
Published: December 2020

Conventional biomechanical modelling approaches involve the solution of large systems of equations that encode the complex mathematical representation of human motion and skeletal structure. To improve stability and computational speed, being a common bottleneck in current approaches, we apply machine learning to train surrogate models and to predict in near real-time, previously calculated medial and lateral knee contact forces (KCFs) of 54 young and elderly participants during treadmill walking in a speed range of 3 to 7 km/h. Predictions are obtained by fusing optical motion capture and musculoskeletal modeling-derived kinematic and force variables, into regression models using artificial neural networks (ANNs) and support vector regression (SVR). Training schemes included either data from all subjects (LeaveTrialsOut) or only from a portion of them (LeaveSubjectsOut), in combination with inclusion of ground reaction forces (GRFs) in the dataset or not. Results identify ANNs as the best-performing predictor of KCFs, both in terms of Pearson R (0.89–0.98 for LeaveTrialsOut and 0.45–0.85 for LeaveSubjectsOut) and percentage normalized root mean square error (0.67–2.35 for LeaveTrialsOut and 1.6–5.39 for LeaveSubjectsOut). When GRFs were omitted from the dataset, no substantial decrease in prediction power of both models was observed. Our findings showcase the strength of ANNs to predict simultaneously multi-component KCF during walking at different speeds—even in the absence of GRFs—particularly applicable in real-time applications that make use of knee loading conditions to guide and treat patients.
An Improved HMM-Based Approach for Planning Individual Routes Using Crowd Sourcing Spatiotemporal Data
Authors: Wu Tao , Zeng Zhixuan , Qin Jianxin , Xiang Longgang , Wan Yiliang
Published: December 2020

With the rapid development of LBSs (location-based services) in recent years, researchers have increasingly taken an interest in trying to make travel routes more practicable and individualized. Despite the fact that many studies have been conducted on routes using LBS data, the specific routes are deficient in dynamic scalability and the correlations between environmental constraints and personal choices have not been investigated. This paper proposes an improved HMM-based (hidden Markov model) method for planning personalized routes with crowd sourcing spatiotemporal data. It tries to integrate the dynamic public preferences, the individual interests and the physical road network space in the same spatiotemporal framework, ensuring that reasonable routes will be generated. A novel dual-layer mapping structure has been proposed to bridge the gap from brief individual preferences to specific entries of POIs (points-of-interest) inside realistic road networks. A case study on Changsha city has proven that the proposed method can not only flexibly plan people’s travel routes under different spatiotemporal backgrounds but also is close to people’s natural selection by the perception of the group.
Analysis and Synthesis of Traffic Scenes from Road Image Sequences
Authors: Yuan Sheng , Chen Yuting , Huo Huihui , Zhu Li
Published: December 2020

Traffic scene construction and simulation has been a hot topic in the community of intelligent transportation systems. In this paper, we propose a novel framework for the analysis and synthesis of traffic elements from road image sequences. The proposed framework is composed of three stages: traffic elements detection, road scene inpainting, and road scene reconstruction. First, a new bidirectional single shot multi-box detector (BiSSD) method is designed with a global context attention mechanism for traffic elements detection. After the detection of traffic elements, an unsupervised CycleGAN is applied to inpaint the occlusion regions with optical flow. The high-quality inpainting images are then obtained by the proposed image inpainting algorithm. Finally, a traffic scene simulation method is developed by integrating the foreground and background elements of traffic scenes. The extensive experiments and comparisons demonstrate the effectiveness of the proposed framework.
Feature Extraction for Dimensionality Reduction in Cellular Networks Performance Analysis
Authors: de-la-Bandera Isabel , Palacios David , Mendoza Jessica , Barco Raquel
Published: December 2020

Next-generation mobile communications networks will have to cope with an extraordinary amount and variety of network performance indicators, causing an increase in the storage needs of the network databases and the degradation of the management functions due to the high-dimensionality of every network observation. In this paper, different techniques for feature extraction are described and proposed as a means for reducing this high dimensionality, to be integrated as an intermediate stage between the monitoring of the network performance indicators and their usage in mobile networks’ management functions. Results using a dataset gathered from a live cellular network show the benefits of this approach, in terms both of storage savings and subsequent management function improvements.
Moving Towards Intelligent Transportation via Artificial Intelligence and Internet-of-Things
Authors: Lytras Miltiadis D. , Chui Kwok Tai , Liu Ryan Wen
Published: December 2020

One of the key smart city visions is to bring smarter transport networks, specifically intelligent/smart transportation [...]
Sparse Blind Deconvolution with Nonconvex Optimization for Ultrasonic NDT Application
Authors: Gao Xuyang , Shi Yibing , Du Kai , Zhu Qi , Zhang Wei
Published: December 2020

In the field of ultrasonic nondestructive testing (NDT), robust and accurate detection of defects is a challenging task because of the attenuation and noising of the ultrasonic wave from the structure. For determining the reflection characteristics representing the position and amplitude of ultrasonic detection signals, sparse blind deconvolution methods have been implemented to separate overlapping echoes when the ultrasonic transducer impulse response is unknown. This letter introduces the ℓ1/ℓ2 ratio regularization function to model the deconvolution as a nonconvex optimization problem. The initialization influences the accuracy of estimation and, for this purpose, the alternating direction method of multipliers (ADMM) combined with blind gain calibration is used to find the initial approximation to the real solution, given multiple observations in a joint sparsity case. The proximal alternating linearized minimization (PALM) algorithm is embedded in the iterate solution, in which the majorize-minimize (MM) approach accelerates convergence. Compared with conventional blind deconvolution algorithms, the proposed methods demonstrate the robustness and capability of separating overlapping echoes in the context of synthetic experiments.
BACE1 Inhibitor, Neuroprotective, and Neuritogenic Activities of Melatonin Derivatives
Authors: Panyatip Panyada , Tadtong Sarin , Sousa Emília , Puthongking Ploenthip
Published: December 2020

Alzheimer’s disease (AD) is a common chronic neurodegenerative disorders. Melatonin (MLT) has been reported to be neuroprotective agent, and its modified structures exhibit potent antioxidant and anti-inflammation activities. Therefore, the activity of MLT and its derivatives against AD was investigated. Herein, the targeted enzymes, such as β-secretase (BACE1) and acetylcholinesterase (AChE), as well as the neuroprotective and neuritogenic effects on P19-derived neurons were evaluated. All the derivatives (1–5), including MLT, displayed potent inhibitory activity for BACE1, with inhibition values of more than 75% at 5 µM. A molecular docking study predicted that MLT, 5-MT, and 5 bound with BACE1 at catalytic amino acids Asp32 and the flap region, whereas 1–4 interacted with allosteric residue Thr232 and the flap region. The additional π-π interactions between 2, 3, and 5 with Tyr71 promoted ligand-enzyme binding. In addition, MLT, 1, 3, and 5 significantly protected neuron cells from oxidative stress by increasing the cell viability to 97.95, 74.29, 70.80, and 69.50% at 1 nM, respectively. Moreover, these derivatives significantly induced neurite outgrowth by increasing the neurite length and number. The derivatives 1, 3, and 5 should be thoroughly studied as potential AD treatment and neuroprotective agents.
Relation between College Students’ Conservatism and Negative Stereotypes about Social Groups
Authors: Beyer Sylvia
Published: December 2020

This study examined the interrelations among political attitudes and negative stereotypes in U.S. undergraduates. Participants answered questions measuring conservatism, social dominance orientation, Global Belief in a Just World, and religiosity. This research employed two measures of stereotypes: modern sexism and feelings about 15 social groups. It was hypothesized that conservatives would show more evidence of negative stereotypes than liberals would. The study revealed that indeed conservatives show stronger evidence of negative stereotypes, but that liberals also harbor some biases. Importantly, the social groups against whom conservatives and liberals are stereotyped differed greatly. Conservatives showed considerably more negative stereotypes against racial and religious minorities, and particularly against those who do not identify with the cis-gender, heterosexual norm. Thus, the targets of conservatives’ stereotypes were groups that have traditionally been subject to discrimination. Liberals held stronger stereotypes against groups that are more politically powerful, such as Caucasians and Christians.
Exploring Environmental Supply Chain Innovation in M&A
Authors: Manocha Pavan , Srai Jagjit Singh
Published: December 2020

Organisations are challenged with executing innovation for sustainable development within the context of their operations and value networks—networks which are increasingly fuelled by mergers and acquisitions (M&As), and which accounted for USD 4 trillion in global deal value in 2019. While outcomes from M&As may produce mixed results, merger synergies fundamentally change the environmental, social and governance (ESG) footprint of an organisation and its product-supply chain. These compounding challenges of innovation for sustainability and ESG product-supply chain due diligence are not adequately explored in the operations management literature or practically considered during M&As. In this article, we consider those factors that determine “how innovative is the deal?” and explore how environmental supply chain innovation for sustainability might inform M&As. A case study approach is adopted, drawing upon an exemplar deal within the global food product-supply chain for ingredient production, where high M&A deal-interest and ESG sustainability considerations exist. The theoretical lens is the resource-based view (RBV) of the firm. A deal analysis framework, integrating key concepts from strategic environmental supply chain management and the M&A process literature, is defined. These findings suggest that product design and technology selection factors represent sources of M&A value creation when exploring an innovation for sustainability deal thesis. The implication for firms with ambitious environmental agendas or motives is that the M&A process needs to be reconfigured, such that product design and technology selection, currently secondary factors, are considered primary drivers. Together, these drivers form substantive strategic considerations and new merger motives of both theoretical and practical relevance, informing a new perspective of operations sustainability targeted M&A.
Sustainability vs. Circular Economy from a Disposition Decision Perspective: A Proposal of a Methodology and an Applied Example in SMEs
Authors: Alarcón Faustino , Cortés-Pellicer Pascual , Pérez-Perales David , Sanchis Raquel
Published: December 2020

Disposition Decision (DD) consists of deciding how to treat a recovered product, and it is one of the most important decisions in reverse logistics. Any of the selected disposition alternatives will have a significant impact on the enterprise sustainability. However, the most sustainable alternative may not be an alternative to make circular economy (CE) possible. In these cases, if the company wishes to adopt a CE strategy, it will have to switch from the most sustainable alternative to a less sustainable one that CE allows. Then, how much should be sacrificed for each sustainability dimension to make CE possible? This paper proposes a methodology for quantitatively comparing the most sustainable disposition alternative and the most sustainable CE alternative. This comparison allows small and medium enterprises (SMEs) to know how exactly all dimensions increase or decrease when selecting the most sustainable CE disposition alternative and to, therefore, assess the interest of adopting a CE policy. The proposed methodology is applied to a used tire recovery company. The results of this example show that the CE alternative offers a better environmental result but presents worst economic and social results. This example can be used as a guide for future applications other SMEs.
Assessing Young Consumers’ Responses to Sustainable Labels: Insights from a Factorial Experiment in Italy
Authors: Rossi Carla , Rivetti Francesca
Published: December 2020

This study provides insights into young consumers’ responses to sustainable labels. Drawing on signaling theory, the article studies how third-party labels (TPLs) act and interact with company-level claims, trying to better understand their impact on young consumers’ perceptions and willingness to buy (pay for) a chocolate bar. A between-subjects factorial experiment—conducted by manipulating third-party sustainable labels (presence/absence of the labels) and self-declared claims (absence of the claim, formal claim, and friendly claim)—was used to test: (a) the effect of TPLs and self-declared claims on consumers’ perceptions, purchase intention, and willingness to pay, (b) whether this effect was mediated through the perceived credibility of the sustainability message, and (c) what kind of tone-of-voice adopted in the company’s claim was more effective. Data were collected via an online survey among a sample of 315 consumers (age range: 18–39 years) in South Italy. We found that third-party labels, “alone” were not effective in influencing consumers’ perceptions and willingness to buy/pay, while a self-declared claim, especially if characterized by a formal tone of voice, had a much more relevant impact. The combination of TPLs and self-declaration affected most consumers’ willingness to pay when the copy claim was informal. The perceived credibility of the sustainability message mediated the relationships between self-declared claims and the majority of the dependent variables, while, with reference to the relationship between TPLs and dependent variables, it did not act as a mediator.
Assessing the Rationality and Walkability of Campus Layouts
Authors: Zhang Zhehao , Fisher Thomas , Feng Gang
Published: December 2020

Walking has become an indispensable and sustainable way of travel for college students in their daily lives and improving the walkability of the college campus will increase the convenience of student life. This paper develops a new campus walkability assessment tool, which optimizes the Walk Score method based on the frequency, variety, and distance of students’ walking to and from public facilities. The campus Walk Score is the product of four components. A preliminary score is calculated through 13 types of facility weight and 3 types of cure of time-decay, and the final score also factors in intersection density and block length. We examine the old and new campuses of Tianjin University to test the tool’s application and evaluate the rationality of facility layout and walkability, and to give suggestions for improvement. The results show that the old campus’ multi-center layout has a high degree of walkability, while the centralized layout of the new campus results in lower walkability. In addition, the diversified distribution of facilities surrounding the old campus promotes the walkability of peripheral places. This assessment tool can help urban planners and campus designers make decisions about how to adjust the facility layout of existing campuses in different regions or to evaluate the campus schemes based on the results of their walkability assessment.
Estimating Changes in Habitat Quality through Land-Use Predictions: Case Study of Roe Deer (Capreolus pygargus tianschanicus) in Jeju Island
Authors: Lee Dong-jin , Jeon Seong Woo
Published: December 2020

This study predicts future land-use changes and the resulting changes in habitat quality, suggesting a method for establishing land-use management to ensure sustainable wildlife habitats. The conservation effects were verified in terms of wild animal habitat quality according to the designation of protected areas. Land-use change until 2050 was predicted using the Dyna-Conversion of Land Use Change and its effects (Dyna-CLUE) model for Jeju Island, Korea, and the change in the quality of roe deer habitats was predicted using the Integrated Valuation and Environmental Services and Tradeoffs (InVEST) model. Results indicate that, compared to 2030, urbanized area increased by 42.55 km2, farmland decreased by 81.36 km2, and natural area increased by 38.82 km2 by 2050. The average habitat quality on Jeju Island was predicted to decrease from 0.306 in 2030 to 0.303 in 2050. The average habitat quality ranged from 0.477 in 2030 to 0.476 in 2050 in protected areas and 0.281 in 2030 to 0.278 in 2050 outside protected areas. Habitat quality in protected areas was relatively high, and its reduction was limited. Areas with lower habitat quality need approaches such as expanding greenery and improving its quality. By establishing appropriate land-use plans by predicting habitat quality, wildlife habitats can be better maintained and protected, which is a primary goal of green infrastructure.
Using a DEA–AutoML Approach to Track SDG Achievements
Authors: Singpai Bodin , Wu Desheng
Published: December 2020

Each country needs to monitor progress on their Sustainable Development Goals (SDGs) to develop strategies that meet the expectations of the United Nations. Data envelope analysis (DEA) can help identify best practices for SDGs by setting goals to compete against. Automated machine learning (AutoML) simplifies machine learning for researchers who need less time and manpower to predict future situations. This work introduces an integrative method that integrates DEA and AutoML to assess and predict performance in SDGs. There are two experiments with different data properties in their interval and correlation to demonstrate the approach. Three prediction targets are set to measure performance in the regression, classification, and multi-target regression algorithms. The back-propagation neural network (BPNN) is used to validate the outputs of the AutoML. As a result, AutoML can outperform BPNN for regression and classification prediction problems. Low standard deviation (SD) data result in poor prediction performance for the BPNN, but does not have a significant impact on AutoML. Highly correlated data result in a higher accuracy, but does not significantly affect the R-squared values between the actual and predicted values. This integrative approach can accurately predict the projected outputs, which can be used as national goals to transform an inefficient country into an efficient country.
Optimization of the Weighted Linear Combination Method for Agricultural Land Suitability Evaluation Considering Current Land Use and Regional Differences
Authors: Yin Shouqiang , Li Jing , Liang Jiaxin , Jia Kejing , Yang Zhen , Wang Yuan
Published: December 2020

This study was aimed at optimizing the weighted linear combination method (WLC) for agricultural land suitability evaluation (ALSE) through indicator selection, weight determination, and classification of overall suitability scores in Handan, China. Handan is a representative research area with distinct agricultural advantages and regional differences in land use, where the expansion of construction land has led to a rapid decrease of agricultural land in recent years. Natural factors (topography, climate, soil conditions, and vegetation cover) and socioeconomic factors (land use and spatial accessibility) were selected to establish a more comprehensive evaluation system. The index weight was calculated by the mutual information between index suitability and current land use. The consistency index was used to identify the boundary value dividing the overall suitability score into a suitable category and unsuitable category in each sub-region. The results demonstrated that the optimized WLC-ALSE model outperformed the comparison models using conventional methods in terms of the consistency between the evaluation results and current land use. Owing to the increasing limitations of topography, soil conditions, spatial accessibility, and land use, the proportions of suitable land in Zone 1, Zone 2, and Zone 3 were 77.4%, 67.5%, and 30.9%, respectively. The agricultural land unsuitable for agriculture (14.5%) was less than non-agricultural land suitable for agriculture (7.4%), indicating that agricultural land had low growth potential in Handan. Finally, specific recommendations were made to improve agricultural land suitability, alleviate land use conflicts, and further optimize the model. The results can provide effective guidance for WLC-ALSE and land use decision-making for sustainable agriculture.
Business Management Teaching-Learning Processes in Times of Pandemic: Flipped Classroom at A Distance
Authors: Izagirre-Olaizola Julen , Morandeira-Arca Jon
Published: December 2020

The main objective of this study is to present a teaching-learning experience carried out before the appearance of the COVID-19 pandemic and to analyze its usefulness in times of social and academic restrictions, as well as its fit into an online teaching format. In recent years, much research has been done on the development and application of new teaching methodologies, but the current health emergency situation means that it is necessary to assess how these methodologies are useful in a context of social distancing. Managing teaching-learning processes following the closure of educational centers due to the pandemic caused by COVID-19 presents a significant challenge, not just in Business Management, but across all subjects. In the context of a pandemic, active methodologies take on greater importance as a way of adapting to new, socially distanced educational needs. This article presents a study carried out among students of Business Management at the University of the Basque Country (Spain). The study focuses on the context of the flipped classroom methodology, with students being asked to rate the effectiveness of this methodology, before and after the pandemic. Following the appearance of the pandemic, opinions have been strengthened in favor of the inverted classroom methodology, which is shown to be a powerful methodological alternative compatible with online teaching. Educational authorities must strengthen the technological tools as well as the teacher skills needed to develop capacities related to the rapid response to current and future teaching challenges.
Eco-Anxiety and Environmental Education
Authors: Pihkala Panu
Published: December 2020

Anxiety and distress about the ecological crisis seems to be a rapidly growing phenomenon. This article analyzes the challenges and possibilities posed by such “eco-anxiety” for environmental education. Variations of eco-anxiety are analyzed, and it is argued that educators should be aware of the multiple forms that the phenomenon has. Eco-anxiety is found to be closely connected with many difficult emotions, such as grief, guilt, anger, and despair. However, anxiety also has an adaptive dimension, which can be called “practical anxiety”. Anxiety is connected with expectation, motivation, and hopes. Previous research about eco-anxiety and ecological emotions in various disciplines is discussed, and related studies from various fields of education are brought together. Based on this extensive literature review, theoretical analyses are made, using a philosophical method. It is argued that environmental educators need organizational and peer support both in relation to their own difficult emotions and in order to develop emotional skills in their work. Educators should first practice self-reflection about eco-anxiety, after which they have many possibilities to help their audiences to develop emotional resilience. Potential practical activities related to eco-anxiety are discussed, drawing from various fields of education. These include validation of eco-anxiety and ecological emotions, providing safe spaces to discuss them, and, if possible, providing embodied and creative activities to more fully deliberate on them.
Shopping Centres, Cycling Accessibility and Planning—The Case of Nova Lund in Sweden
Authors: Koglin Till , Glasare Lucas
Published: December 2020

This paper evaluates the history and cycling accessibility of Nova, a shopping centre established in Lund, Sweden, in 2002. The current situation was also analysed through observation and a literature review. Moreover, the study conducted a closer analysis of the history and role of the municipality based on further literature study and interviews with officials. The conclusion of the analysis indicates poor and unsafe bikeways caused by conflicts of interest between politicians, officials, landowners and the general public. It also depicts a situation in which the municipality’s master plan has been ignored, and, in contrast to the local goals, cycling accessibility at Nova has seen no significant improvement since the shopping centre was first established. The reasons for this, arguably, are a relatively low budget for bikeway improvements in the municipality, as well as a situation in which decision-makers have stopped approaching the subject, as a result of the long and often boisterous conflicts it has created in the past. Lastly, it must be noted that it is easy to regard the whole process of Nova, from its establishment to the current situation, as being symptomatic of the power structures between drivers and cyclists that still affect decision-makers at all levels.
BCG as a Vector for Novel Recombinant Vaccines against Infectious Diseases and Cancers
Authors: Mustafa Abu Salim
Published: December 2020

Bacillus Calmette–Guérin (BCG) has been widely used globally as a prophylactic vaccine to protect against tuberculosis (TB) for about a century [...]
DNA Vaccine Development at Pre- and Post-Operation Warp Speed
Authors: Ljungberg Karl , Isaguliants Maria
Published: December 2020

DNA is a rapidly developing vaccine platform for combatting cancer, infectious and noninfectious diseases [...]
Meningococcal Vaccines: Challenges and Prospects
Authors: Bagwe Priyal , Bajaj Lotika , Gala Rikhav , Zughaier Susu M. , Uddin Mohammad N. , D’Souza Martin J.
Published: December 2020

Neisseria meningitidis is a gram-negative bacterium that causes a severe acute infection, called the meningococcal disease [...]
Trends in diabetes medication use in Australia, Canada, England, and Scotland: a repeated cross-sectional analysis in primary care
Authors: Greiver Michelle , Havard Alys , Bowles Juliana KF , Kalia Sumeet , Chen Tao , Aliarzadeh Babak , Moineddin Rahim , Sherlock Julian , Hinton William , Sullivan Frank , O’Neill Braden , Pow Conrad , Bhatt Aashka , Rahman Fahurrozi , Meza-Torres Bernardo , Litchfield Melisa , de Lusignan Simon
Published: December 2020

Background

Several new classes of glucose-lowering medications have been introduced in the past two decades. Some, such as sodium-glucose cotransporter 2 inhibitors (SGLT2s), have evidence of improved cardiovascular outcomes, while others, such as dipeptidyl peptidase-4 inhibitors (DPP4s), do not. It is therefore important to identify their uptake in order to find ways to support the use of more effective treatments.

Aim

To analyse the uptake of these new classes among patients with type 2 diabetes.

Design and setting

This was a retrospective repeated cross-sectional analysis in primary care. Rates of medication uptake in Australia, Canada, England, and Scotland were compared.

Method

Primary care Electronic Medical Data on prescriptions (Canada, UK) and dispensing data (Australia) from 2012 to 2017 were used. Individuals aged ≥40 years on at least one glucose-lowering drug class in each year of interest were included, excluding those on insulin only. Proportions of patients in each nation, for each year, on each class of medication, and on combinations of classes were determined.

Results

Data from 238 619 patients were included in 2017. The proportion of patients on sulfonylureas (SUs) decreased in three out of four nations, while metformin decreased in Canada. Use of combinations of metformin and new drug classes increased in all nations, replacing combinations involving SUs. In 2017, more patients were on DPP4s (between 19.1% and 27.6%) than on SGLT2s (between 10.1% and 15.3%).

Conclusion

New drugs are displacing SUs. However, despite evidence of better outcomes, the adoption of SGLT2s lagged behind DPP4s.
Інституціональні процеси державного управління у сфері зайнятості: проблеми реалізації
Authors: Серьогіна Н. О.
Published: December 2020

Розглянуто співвідношення понять “інституціоналізація” та “інституалізація”.Зроблено висновок, що ці поняття є тотожними. Доведено, що у контексті глобалізації, цифровізації, демографічних змін, міграції тощо проблема державного управління у сфері зайнятості населення упродовж останніх років суттєво актуалізується, що сильно впливає на стан світового і національного ринків праці. Наголошено, що значення інститутів ринку праці є критичним для подолання розбалансованості у секторі зайнятості. Досліджено інституціональні основи діяльності Державної служби зайнятості. Визначено, що інституціональне середовище зайнятості та ринку праці є недосконалим: існує велика кількість колізій у нормативно-правовому забезпеченні, відсутня чітко окреслена стратегія розвитку
Eurointegration aspects of public housing policy in forming public health strategies in Ukraine
Authors: Demikhov O. I. , Dehtyarova І. O.
Published: December 2020

In article the domestic legislative and regulatory documents, materials of bodies of public authority, non-governmental organizations, materials of specialized sites are considered. The article used both basic interdisciplinary and systematic approaches, methods of analysis and synthesis, modeling. The purpose of article is to develop complexes of tools to stimulate citizens’ participation in formation and realization of the public housing policy and public health policy according to different levels of their housing self-sufficiency. The study proved that the categorical apparatus is being improved in the field of science “Public Administration” in the context of defining the concept of “residential self-sufficiency of the population”. This is the ability of citizens, depending on their material wealth, social situation, cultural and aesthetic preference, local traditions to satisfy their basic needs for the use or possession of secure housing and land on a temporary or permanent basis. The importance of connection of public housing policy with the public health system based on the selfsufficiency of the local community has also been proven. The complexes of tools for stimulating the participation of the population in the formation and implementation of the state housing policy for groups of the population are defined, depending on the level of their housing self-sufficiency. Establishing a link between social policies for vulnerable groups of the population, the state of health of citizens and the level of their housing self-sufficiency will allow developing transversal approaches to housing construction and public health policy in general. Establishing the relationship between the state of health of citizens and the level of their living self-sufficiency will allow developing approaches to public housing policy and public health policy.
Стратегічні напрями вдосконалення стимулюючого механізму публічного управління у сфері поводження з твердими побутовими відходами
Authors: Зюзь О. С.
Published: December 2020

Актуалізовано питання вдосконалення стимулюючого механізму публічного управління в сфері поводження з твердими побутовими відходами (далі – ТПВ). Обґрунтовано неефективність існуючих механізмів і запропоновано мобілізаційні заходи щодо покращення публічного управління в цьому напрямку. Встановлено, що функціональна спрямованість стимулюючого механізму полягає у досягненні мети публічного управління в сфері поводження із ТПВ, вихованні культури поводження з відходами та консолідації діяльності суб’єктів у напрямку охорони навколишнього природного середовища.
Епоха турбулентності і суспільні метаморфози як фактори ризиків державного управління
Authors: Панченко О. А.
Published: December 2020

Розкрито сутність причино-наслідкового зв’язку між турбулентністю іметаморфозами суспільства. Наголошено, що головною метаморфозою сучасного суспільства є перетворення його в турбулентний стан, де основною ознакою є потокова реальність, і в силу цього суспільство пронизане хаотичними, неконтрольованими процесами. Зазначено, що нестабільне середовище продукує як високі ризики, так і високі шанси для держави не втратити управлінські функції. Зауважено, що важливим завданням є розуміння нових реалій і вироблення відповідної політики. Вказано, що варіантом вирішення проблеми може стати симбіоз делегування широких повноважень на локальний рівень при належному контролі центру і “культури безпеки” як форми реалізації турботи про себе.
Особливості етикету публічного службовця в сучасних умовах реформування публічної служби
Authors: Сорокіна Н. Г.
Published: December 2020

Досліджено особливості етикету публічного службовця. Проаналізовано основніпринципи сучасного етикету, такі як: гуманізм, доцільність дій, зовнішній вигляд, повага до традицій своєї країни та інших країн, субординація та культура мови. Акцентовано увагу, що професіоналізм публічного службовця повинен визначатися не тільки рівнем його освіченості, а й дотриманням норм етикету та морально-етичних принципів законності, справедливості, гуманності, відповідальності та неупередженості.
Вплив функціонування агломерацій на діяльність суб’єктів господарювання
Authors: Матвіїшин Є. Г. , Горпинюк З. С.
Published: December 2020

Проаналізовано вітчизняний і зарубіжний досвід формування та функціонуванняагломерацій та їх вплив на національну економіку. Виявлено, що загалом чинник входження міст до агломерацій позитивно впливає на діяльність суб’єктів господарювання, середню заробітну плату, обсяги податків на доходи фізичних осіб, що припадають на одного жителя. Проте показник кількості зареєстрованих у містах суб’єктів господарювання не може бути використаний для оцінювання впливу функціонування агломерацій на економіку, особливо якщо виключити з аналізу дані про обласні центри, які в Україні є центрами агломерацій.