bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of a Novel Immersive Virtual Reality Technology Associated with Serious Games in Parkinson’s Disease Patients on Upper Limb Rehabilitation: A Mixed Methods Intervention Study
Authors: Sánchez-Herrera-Baeza Patricia , Cano-de-la-Cuerda Roberto , Oña-Simbaña Edwin Daniel , Palacios-Ceña Domingo , Pérez-Corrales Jorge , Cuenca-Zaldivar Juan Nicolas , Gueita-Rodriguez Javier , Balaguer-Bernaldo de Quirós Carlos , Jardón-Huete Alberto , Cuesta-Gomez Alicia
Published: April 2020

Background: Parkinson’s disease is a neurodegenerative disorder that causes impaired motor functions. Virtual reality technology may be recommended to optimize motor learning in a safe environment. The objective of this paper was to evaluate the effects of a novel immersive virtual reality technology used for serious games (Oculus Rift 2 plus leap motion controller—OR2-LMC) for upper limb outcomes (muscle strength, coordination, speed of movements, fine and gross dexterity). Another objective was to obtain qualitative data for participants’ experiences related to the intervention. Methods: A mixed methods intervention (embedded) study was used, with a qualitative design after a technology intervention (quantitative design). The intervention and qualitative design followed international guidelines and were integrated into the method and reporting subheadings. Results: Significant improvements were observed in strength (p = 0.028), fine (p = 0.026 to 0.028) and gross coordination dexterity, and speed movements (p = 0.039) in the affected side, with excellent compliance (100%) and a high level of satisfaction (3.66 ± 0.18 points out of the maximum of 4). No adverse side effects were observed. Qualitative findings described patients’ perspectives regarding OR2-LMC treatment, facilitators and barriers for adherence, OR2-LMC applications, and treatment improvements. Conclusions: The intervention showed positive results for the upper limbs, with elements of discordance, expansion, and confirmation between qualitative and quantitative results.
Multi-Modality Medical Image Fusion Using Convolutional Neural Network and Contrast Pyramid
Authors: Wang Kunpeng , Zheng Mingyao , Wei Hongyan , Qi Guanqiu , Li Yuanyuan
Published: April 2020

Medical image fusion techniques can fuse medical images from different morphologies to make the medical diagnosis more reliable and accurate, which play an increasingly important role in many clinical applications. To obtain a fused image with high visual quality and clear structure details, this paper proposes a convolutional neural network (CNN) based medical image fusion algorithm. The proposed algorithm uses the trained Siamese convolutional network to fuse the pixel activity information of source images to realize the generation of weight map. Meanwhile, a contrast pyramid is implemented to decompose the source image. According to different spatial frequency bands and a weighted fusion operator, source images are integrated. The results of comparative experiments show that the proposed fusion algorithm can effectively preserve the detailed structure information of source images and achieve good human visual effects.
A Rescue-Assistance Navigation Method by Using the Underground Location of WSN after Disasters
Authors: Li Shuo , Guo Tiancheng , Mo Ran , Zhao Xiaoshuai , Zhou Feng , Liu Weirong , Peng Jun
Published: April 2020

A challenging rescue task for the underground disaster is to guide survivors in getting away from the dangerous area quickly. To address the issue, an escape guidance path developing method is proposed based on anisotropic underground wireless sensor networks under the condition of sparse anchor nodes. Firstly, a hybrid channel model was constructed to reflect the relationship between distance and receiving signal strength, which incorporates the underground complex communication characteristics, including the analytical ray wave guide model, the Shadowing effect, the tunnel size, and the penetration effect of obstacles. Secondly, a trustable anchor node selection algorithm with node movement detection is proposed, which solves the problem of high-precision node location in anisotropic networks with sparse anchor nodes after the disaster. Consequently, according to the node location and the obstacles, the optimal guidance path is developed by using the modified minimum spanning tree algorithm. Finally, the simulations in the 3D scene are conducted to verify the performance of the proposed method on the localization accuracy, guidance path effectiveness, and scalability.
Feasibility Study on Shear Horizontal Surface Acoustic Wave Sensors for Engine Oil Evaluation
Authors: Kobayashi Saya , Kondoh Jun
Published: April 2020

On site monitoring of engine oil is required. The features of a shear horizontal surface acoustic wave (SH-SAW) sensor include simultaneous detection of mechanical and electrical properties of liquids (such as viscosity, relative permittivity, and conductivity) and loaded mass on the sensor surface. In this paper, the used engine oil extracted from a motorbike was measured using the SH-SAW sensor. The degradation factors of the used engine oil were experimentally discussed. Especially, the influences of the particles in the engine oil, heating effect, and water contained in the engine oil were considered by comparing the differences between new and used engine oils. The results indicate that the influence of the water contained in the engine oil is the primary cause of the degradation of the used engine oil.
Wearable Inertial Sensor System towards Daily Human Kinematic Gait Analysis: Benchmarking Analysis to MVN BIOMECH
Authors: Figueiredo Joana , Carvalho Simão P. , Vilas-Boas João Paulo , Gonçalves Luís M. , Moreno Juan C. , Santos Cristina P.
Published: April 2020

This paper presents a cost- and time-effective wearable inertial sensor system, the InertialLAB. It includes gyroscopes and accelerometers for the real-time monitoring of 3D-angular velocity and 3D-acceleration of up to six lower limbs and trunk segment and sagittal joint angle up to six joints. InertialLAB followed an open architecture with a low computational load to be executed by wearable processing units up to 200 Hz for fostering kinematic gait data to third-party systems, advancing similar commercial systems. For joint angle estimation, we developed a trigonometric method based on the segments’ orientation previously computed by fusion-based methods. The validation covered healthy gait patterns in varying speed and terrain (flat, ramp, and stairs) and including turns, extending the experiments approached in the literature. The benchmarking analysis to MVN BIOMECH reported that InertialLAB provides more reliable measures in stairs than in flat terrain and ramp. The joint angle time-series of InertialLAB showed good waveform similarity (>0.898) with MVN BIOMECH, resulting in high reliability and excellent validity. User-independent neural network regression models successfully minimized the drift errors observed in InertialLAB’s joint angles (NRMSE < 0.092). Further, users ranked InertialLAB as good in terms of usability. InertialLAB shows promise for daily kinematic gait analysis and real-time kinematic feedback for wearable third-party systems.
A Reliability-Based Multisensor Data Fusion with Application in Target Classification
Authors: Awogbami Gabriel , Homaifar Abdollah
Published: April 2020

The theory of belief functions has been extensively utilized in many practical applications involving decision making. One such application is the classification of target based on the pieces of information extracted from the individual attributes describing the target. Each piece of information is usually modeled as the basic probability assignment (BPA), also known as the mass function. The determination of the BPA has remained an open problem. Although fuzzy membership functions such as triangular and Gaussian functions have been widely used to model the likelihood estimation function based on the historical data, it has been observed that less emphasis has been placed on the impact of the spread of the membership function on the decision accuracy of the reasoning process. Conflict in the combination of BPAs may arise due to poor characterization of fuzzy membership functions to induce belief mass. In this work, we propose a multisensor data fusion within the framework of belief theory for target classification where shape/spread of the membership function is adjusted during the training/modeling stage to improve on the classification accuracy while removing the need for the computation of the credibility. To further enhance the performance of the proposed method, the reliability factor is deployed not only to effectively manage the possible conflict among participating bodies of evidence for better decision accuracy but also to reduce the number of sources for improved efficiency. The effectiveness of the proposed method was evaluated using both the real-world and the artificial datasets.
Near-Infrared Spectroscopy for Monitoring Sternocleidomastoid Muscular Oxygenation during Isometric Flexion for Patients with Mild Nonspecific Neck Pain: A Pilot Study
Authors: Yang Chia-Chi , Yang Po-Ching , Chen Jia-Jin J. , Lai Yi-Horng , Hu Chia-Han , Chang Yung , Tu Shihfan Jack , Guo Lan-Yuen
Published: April 2020

Since there is merit in noninvasive monitoring of muscular oxidative metabolism for near-infrared spectroscopy in a wide range of clinical scenarios, the present study attempted to evaluate the clinical usability for featuring the modulatory strategies of sternocleidomastoid muscular oxygenation using near-infrared spectroscopy in mild nonspecific neck pain patients. The muscular oxygenation variables of the dominant or affected sternocleidomastoid muscles of interest were extracted at 25% of the maximum voluntary isometric contraction from ten patients (5 males and 5 females, 23.6 ± 4.2 years) and asymptomatic individuals (6 males and 4 females, 24.0 ± 5.1 years) using near-infrared spectroscopy. Only a shorter half-deoxygenation time of oxygen saturation during a sternocleidomastoid isometric contraction was noted in patients compared to asymptomatic individuals (10.43 ± 1.79 s vs. 13.82 ± 1.42 s, p < 0.001). Even though the lack of statically significant differences in most of the muscular oxygenation variables failed to refine the definite pathogenic mechanisms underlying nonspecific neck pain, the findings of modulatory strategies of faster deoxygenation implied that near-infrared spectroscopy appears to have practical potential to provide relevant physiological information regarding muscular oxidative metabolism and constituted convincing preliminary evidences of the adaptive manipulations rather than pathological responses of oxidative metabolism capacity of sternocleidomastoid muscles in nonspecific neck patients with mild disability.
An Optically Tunable THz Modulator Based on Nanostructures of Silicon Substrates
Authors: Mo Chen , Liu Jingbo , Wei Dongshan , Wu Honglei , Wen Qiye , Ling Dongxiong
Published: April 2020

Nanostructures can induce light multireflection, enabling strong light absorption and efficient photocarrier generation. In this work, silicon nanostructures, including nanocylinders, nanotips, and nanoholes, were proposed as all-optical broadband THz modulators. The modulation properties of these modulators were simulated and compared with finite element method calculations. It is interesting to note that the light reflectance values from all nanostructure were greatly suppressed, showing values of 26.22%, 21.04%, and 0.63% for nanocylinder, nanohole, and nanotip structures, respectively, at 2 THz. The calculated results show that under 808 nm illumination light, the best modulation performance is achieved in the nanotip modulator, which displays a modulation depth of 91.63% with a pumping power of 60 mW/mm2 at 2 THz. However, under shorter illumination wavelengths, such as 532 nm, the modulation performance for all modulators deteriorates and the best performance is found with the nanohole-based modulator rather than the nanotip-based one. To further clarify the effects of the nanostructure and wavelength on the THz modulation, a graded index layer model was established and the simulation results were explained. This work may provide a further theoretical guide for the design of optically tunable broadband THz modulators.
Research on Turning Motion Targets and Velocity Estimation in High Resolution Spaceborne SAR
Authors: Wen Xuejiao , Qiu Xiaolan
Published: April 2020

The development of high resolution SAR makes the influence of moving target more prominent, which results in defocusing and other unexplained phenomena. This paper focuses on the research of imaging signatures and velocity estimation of turning motion targets. In this paper, the turning motion is regarded as the straight line motion of continuous change of moving direction. Through the analysis of the straight line motion with constant velocity and the geometric modeling of the turning motion in spaceborne SAR, the imaging signatures of the turning motion target are obtained, such as the broken line phenomenon at the curve. Furthermore, a method for estimating the turning velocity is proposed here. The radial velocity is calculated by the azimuth offset of the turning motion target and the azimuth velocity is calculated by the phase error compensated in the refocusing process. The amplitude and direction of the velocity can be obtained by using both of them. The results of simulation and GF-3 data prove the accuracy of the analysis of turning motion imaging signatures, and they also show the accuracy and validity of the velocity estimation method in this paper.
The TACL Model: A Framework for Safeguarding Children with a Disability in Sport
Authors: Rhind Daniel J. A. , McDermott Jamie
Published: April 2020

This study represents the first investigation of how children with a disability can be safeguarded in Rugby Union. In study 1, a questionnaire containing quantitative questions was completed by 389 safeguarding volunteers regarding their experiences of working with a child with a disability in their role. Descriptive statistics revealed that 76% of this sample had worked with a child with a disability in Rugby Union and that 28% continue to do so on a weekly basis. In study 2, a qualitative survey was completed by 329 safeguarding volunteers and interviews were conducted with a geographically representative sample of 14 Safeguarding Officers. This study focused on developing a model of promising practice with respect to safeguarding children with a disability in Rugby Union. Based on an inductive thematic analysis of the qualitative survey and interview data, the TACL model was developed: Trigger (creating a system that sensitively identifies children with a disability), Action Plan (creating an individualized approach such that the child is effectively included and protected), Communicate (ensuring that all key stakeholders are informed about the plan) and Learn (ensuring that cases of good practice are identified and disseminated). The name TACL (pronounced tackle) was chosen to promote proactive strategies and to provide a label relevant to the language of Rugby Union. These strategies are proposed as the basis for the safeguarding of children with a disability.
Reputation Cues as Signals in the Sharing Economy
Authors: Rosenthal Sonny , Tan Jean Yi Colette , Poh Ting Fang
Published: April 2020

Reputation cues, like star ratings, signal qualities of service providers in the sharing economy and may affect user behavior. Guided by concepts from signaling theory and using a repeated measures experiment (N = 221), this study manipulated the level of star ratings of ride sharing drivers. Intuitive findings are perceived service quality and willingness to use the service provider are higher when the star rating is high versus low. Extending prior work, perceived service quality mediates the effect of reputation on willingness, explaining 83% of the total effect. Also, the direct effect of reputation cues on perceived service quality depends, albeit weakly (η2p = 0.02), on how much users say they pay attention to them. These novel findings clarify the kinds of mental processing that occur when users of shared services evaluate reputation cues. We discuss findings in terms of costly signaling and consider practical implications for users and providers.
Irrigation and Greenhouse Gas Emissions: A Review of Field-Based Studies
Authors: Sapkota Anish , Haghverdi Amir , Avila Claudia C. E. , Ying Samantha C.
Published: April 2020

Irrigation practices can greatly influence greenhouse gas (GHG) emissions because of their control on soil microbial activity and substrate supply. However, the effects of different irrigation management practices, such as flood irrigations versus reduced volume methods, including drip and sprinkler irrigation, on GHG emissions are still poorly understood. Therefore, this review was performed to investigate the effects of different irrigation management strategies on the emission of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) by synthesizing existing research that either directly or indirectly examined the effects of at least two irrigation rates on GHG emissions within a single field-based study. Out of thirty-two articles selected for review, reduced irrigation was found to be effective in lowering the rate of CH4 emissions, while flood irrigation had the highest CH4 emission. The rate of CO2 emission increased mostly under low irrigation, and the effect of irrigation strategies on N2O emissions were inconsistent, though a majority of studies reported low N2O emissions in continuously flooded field treatments. The global warming potential (GWP) demonstrated that reduced or water-saving irrigation strategies have the potential to decrease the effect of GHG emissions. In general, GWP was higher for the field that was continuously flooded. The major finding from this review is that optimizing irrigation may help to reduce CH4 emissions and net GWP. However, more field research assessing the effect of varying rates of irrigation on the emission of GHGs from the agricultural field is warranted.
The Federated Practice of Soccer Influences Hamstring Flexibility in Healthy Adolescents: Role of Age and Weight Status
Authors: Ponce-González Jesús Gustavo , Gutiérrez-Manzanedo José V. , De Castro-Maqueda Guillermo , Fernández-Torres Victor Jose , Fernández-Santos Jorge R.
Published: April 2020

The aim of this study was to compare the hamstring flexibility between federated soccer and non-federated adolescents, and also to evaluate the effect of age and weight status on hamstring flexibility. The participants were 234 students (11–18 years old) divided into: (i) G1: non-federated (n = 127), and (ii) G2: federated in soccer (n = 107). The deep flexion of the trunk (DF) test and the sit and reach test (SRT) were performed. G2 showed higher values for the DF and SRT compared to G1 (p < 0.05). Both flexibility tests correlated positively (r = 0.4, p < 0.001). Body mass index (BMI) was negatively correlated with the DF test (r = −0.3, p < 0.001), but not with the SRT. Divided by BMI, the underweight and normal weight groups had higher scores in the DF test compared with the overweight and obese groups (p < 0.001). BMI was negatively correlated with hamstring flexibility. Federated soccer students present higher scores of hamstring flexibility.
Mobile Personalized Recommendation Model based on Privacy Concerns and Context Analysis for the Sustainable Development of M-commerce
Authors: Xiao Liang , Lu Qibei , Guo Feipeng
Published: April 2020

A mobile personalized recommendation service satisfies the needs of users and stimulates them to continue to adopt mobile commerce applications. Therefore, how to precisely provide mobile personalized recommendation service is very important for the sustainable development of mobile commerce. However, privacy concerns regarding mobile commerce affect users’ consumption intentions, and also reduce the quality of mobile personalized recommendation services. In order to address this issue and the existing recommendation method problem in the mobile personalized recommendation service, this paper introduces six dimensions of privacy concerns and the relevant contextual information to propose a novel mobile personalized recommendation service based on privacy concerns and context analysis. First, this paper puts forward an intensity measurement method to measure the factors that influence privacy concerns, and then realizes a user-based collaborative filtering recommendation integrated with the intensity of privacy concerns. Second, a context similarity algorithm based on a context ontology-tree is proposed, after which this study realizes a user-based collaborative filtering recommendation integrated with context similarity. Finally, the research produces a hybrid collaborative filtering recommendation integrated with privacy concerns and context information. After experimental verification, the results show that this model can effectively solve the problems of data sparseness and cold starts. More importantly, it can reduce the influence of users’ privacy concerns on the adoption of mobile personalized recommendation services, and promote the sustainable development of mobile commerce.
Land Access in the Development of Horticultural Crops in East Africa. A Case Study of Passion Fruit in Burundi, Kenya, and Rwanda
Authors: Bashangwa Mpozi Bosco , Mizero Mireille , Egesa Andrew Ogolla , Nguezet Paul M. Dontsop , Vanlauwe Bernard , Ndimanya Patrice , Lebailly Philippe
Published: April 2020

Rapid population growth in fertile agricultural lands of East Africa creates land scarcity, which has become a major hindrance to land access for the introduction of new horticultural crops. But their introduction in these areas is increasing, because of their high market price, which improves farmers’ income. As such, this research evaluated land access dynamics (availability, acquisition, and use changes) on the introduction of passion fruits in East Africa. The study used purposeful sampling to collect information from 171 passion fruit farmers from Burundi (60), Kenya (51), and Rwanda (60) through interviews during field surveys. Among the respondents from all three countries, inheritance and land purchase were the predominant modes of land access (>50% and >21%, respectively). Furthermore, the substitution of other crops by passion fruits was high (>60%) among Kenyan and Rwandan farmers, but low (18%) among Burundian farmers. Our findings indicate that land access influences the patterns of adoption of new crops, since, when limited in supply, it may require the acquisition of new land space, abandonment of other crops, or opting for mixed farming. As such, land access should be a consideration in the promotion of new crops for sustainable agricultural ventures.
Evaluation of MSW Compost and Digestate Mixtures for a Circular Economy Application
Authors: Pecorini Isabella , Peruzzi Eleonora , Albini Elena , Doni Serena , Macci Cristina , Masciandaro Grazia , Iannelli Renato
Published: April 2020

In order to obtain a product with agronomic characteristics and biological stability consistent with the EU fertilizer decree for the market of EU fertilising products three different mixtures obtained from sludge digestate from municipal wastewater treatment plant, fresh compost and mature compost have been studied and characterized. For the experimental activity, the raw samples and three mixing ones were collected for the analytical characterization. The biological stability was then assessed for all samples using different stability criteria such as Specific Oxygen Uptake Rate, Rottegrad self-heating factor, Residual biogas potential. Specific enzymatic tests provided information about the status of nutrient cycles (C, P and S) and to overall microbial activity. Physical (bulk density, particle density, air capacity and water content), nutritional (C, N, P, K, Mg, and Ca) and toxicological properties (seedling growth tests on Lepidum sativum L., Cucumis sativus L., Lolium perenne L.) were also evaluated in order to assess the feasibility of agronomic use of the digestate-based mixtures. All the digestate-based mixtures responded to the main characteristics of compost quality requirements proposed in national and international regulations. The evidence found in this study highlighted that the strategy of mixing of sludge digestates with the composts allowed to mitigate the environmental risk posed by each starting material and to valorize their nutrient content.
Hybrid Genetic Algorithm-Based Approach for Estimating Flood Losses on Structures of Buildings
Authors: Hanák Tomáš , Tuscher Martin , Přibyl Oto
Published: April 2020

Occurrence of extreme natural events raises the need for a quick and accurate estimation of losses on the insured residential property in order to support timely recovery of the area. Although various models are now available to estimate the amount of loss on buildings, there is a lack of models providing a sufficient level of detail and accuracy that can be used for insurance purposes. In this study, a hybrid genetic algorithm-based model for flood loss estimation on the structures of buildings is presented. The proposed model combines the ordinary least squares method, a genetic algorithm, and the bill of costs method, which offers a good balance of maximum simplicity on the one hand and the accuracy of calculation on the other hand. The model considers the geometric characteristics (dimensions and shape) of rooms and is enabled to work with various types of materials and structures, as well as a variable depth of flooding. The results achieved show that in quick loss estimation, the model provides highly accurate results which meet the requirements for its use for the purposes of settlement of real insurance claims by insurance companies. The article outlines the potential automated connection of the model to insurance companies’ information system in order to create a simple building information model (BIM) of the insured property (building’s structures).
Hyperspectral Reflectance as a Basis to Discriminate Olive Varieties—A Tool for Sustainable Crop Management
Authors: Gomes Luis , Nobre Tânia , Sousa Adélia , Rei Fernando , Guiomar Nuno
Published: April 2020

Worldwide sustainable development is threatened by current agricultural land change trends, particularly by the increasing rural farmland abandonment and agricultural intensification phenomena. In Mediterranean countries, these processes are affecting especially traditional olive groves with enormous socio-economic costs to rural areas, endangering environmental sustainability and biodiversity. Traditional olive groves abandonment and intensification are clearly related to the reduction of olive oil production income, leading to reduced economic viability. Most promising strategies to boost traditional groves competitiveness—such as olive oil differentiation through adoption of protected denomination of origin labels and development of value-added olive products—rely on knowledge of the olive varieties and its specific properties that confer their uniqueness and authenticity. Given the lack of information about olive varieties on traditional groves, a feasible and inexpensive method of variety identification is required. We analyzed leaf spectral information of ten Portuguese olive varieties with a powerful data-mining approach in order to verify the ability of satellite’s hyperspectral sensors to provide an accurate olive variety identification. Our results show that these olive varieties are distinguishable by leaf reflectance information and suggest that even satellite open-source data could be used to map them. Additional advantages of olive varieties mapping were further discussed.
Competitive Structure of Accommodations in a Traditional Japanese Hot Springs Tourism Area
Authors: Kurata Shohei , Ohe Yasuo
Published: April 2020

This paper investigates the competitive structure of prices in a traditional hot springs resort area in Japan from a spatial econometric perspective. This perspective has not been addressed in hot springs—or “onsen” in Japanese—tourism areas, which have been gradually losing momentum due to the ageing of operators and diversification of leisure activities. The study area is one of the three oldest hot springs in Japan, the Dogo Onsen area in Matsuyama, where hotels and ryokans are clustered. First, we present a conceptual framework that characterizes two strategies, namely, differentiation and partnership strategies. Then, spatial error models are employed to test the hypothesis that spatial closeness intensifies price competition, while social closeness mitigates price competition. The estimation results reveal that our hypothesis was verified, in that the social network which has been nurtured for generations in the study hot spring area mitigates price competition, in comparison with the non-hot spring area in Matsuyama. Thus, good partnerships among local operators based on social networks should be more closely scrutinized for the revitalization of traditional hot springs areas.
Decision Support Simulation Method for Process Improvement of Electronic Product Testing Systems
Authors: Tamás Péter , Tollár Sándor , Illés Béla , Bányai Tamás , Tóth Ágota Bányai , Skapinyecz Róbert
Published: April 2020

Spread of the Jidoka concept can be phrased as a trend at the production of electronic products. In most of the cases, with the application of this concept, the development of testing procedures (for quality assurance purposes) of the finished products can be avoided. In those cases, when the production process of the appropriate quality product cannot be implemented safely for the establishment of the product testing process (following the production process), changing the number of variety products, change of requirements concerning the electronic products (e.g., instructions related to energy consumption, noise level) and the variation of the required testing capacity make the modification of the established testing process necessary. The implementation of related plans often leads to problems (e.g., not the appropriate storage area, material flow process or material handling equipment having been chosen). The method of process configuration affects the sustainability, since the poorly established process can lead to additional usage of non-renewable natural resources and unjustified environmental impact. For one of the tools of Industry 4.0, we developed such a state-of-the-art testing method with the use of simulation modelling by which the change of testing process can be effectively examined and evaluated, thus we can prevent the unnecessary planning failures. The application of the developed method is also shown through a case study.
Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †
Authors: Huynh Tai , Nguyen Hien , Zelinka Ivan , Dinh Dac , Pham Xuan Hau
Published: April 2020

Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user’s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results.
Reliability of Creative Composite Indicators with Territorial Specification in the EU
Authors: Boal-San Miguel Iván , Herrero-Prieto Luis César
Published: April 2020

There is wide consensus regarding the capacity of the creative economy as a factor in economic development and sustainability in regions in the medium term, and it is an issue that has aroused interest in measuring the creative potential of areas by estimating composite indicators. Most works posit indicators by countries or cities and normally employ a single aggregation method. This work proposes the construction of a synthetic indicator of creativity with regional disaggregation for a wide sample of European countries, comparing different aggregation methods under the hypothesis of the benefit of the doubt (BoD). We use Eurostat data and also analyse spatial dependence processes. Findings point to an inequality in the regional distribution of creativity in Europe and this reveals creative gap models in areas, suggesting that creativity triggers greater spatial disparities wherever it is found. The principal creative clusters are located in regions in central and northern Europe, particularly in regions with national capitals. The regional distribution of the indicator evidences positive spatial dependence, thereby revealing the existence of spatial externalities that provide feedback for the concentration process and, therefore, a widening of the disparities.
Carbon Footprint of Lamb and Wool Production at Farm Gate and the Regional Scale in Southern Patagonia
Authors: Peri Pablo L. , Rosas Yamina M. , Ladd Brenton , Díaz-Delgado Ricardo , Martínez Pastur Guillermo
Published: April 2020

Natural steppe grasslands are the principal food resource for sheep in the Patagonia region, reared for meat and wool. However, there is currently a concern about the relationship between ruminant livestock and climate change due to its contribution to anthropogenic greenhouse gas (GHG) emissions. The objective of this study was to determine the carbon footprints (CF) of sheep meat (lamb) and wool on a range of farms using empirical data collected on farm and then upscaled to the regional scale using models that use topographic, climatic, and vegetation indices as independent variables. At the regional level, the total CF of lamb and wool (the combination of emissions produced on farm, via transport, and via industrial processing) varied from 10.64 to 41.32 kg CO2-eq/kg for lamb meat (carcass) and from 7.83 to 18.70 kg CO2-eq/kg for fine-grade wool. For both, the predominant contribution was from primary production on-farm (75–90%), followed by industrial processing (2–15%), and transportation. We used multiple regression models to produce maps of lamb and wool CF at farm gate across Santa Cruz province. The model for variation of lamb CF explained 95% of the variance on the data and the most significant predictor variables were temperature seasonality and normalized difference vegetation index (NDVI, dimensionless). The most important variables for the model of CF of greasy wool production at farm gate were isothermality, temperature seasonality, and NDVI explained 98%. The lowest CF values of both products (lamb and wool) were located in more productive grasslands. The successful management of livestock GHG emissions becomes an important challenge to the scientific, commercial, and policy communities. The results of CF for lamb and wool production found in the present work assist in characterizing the greenhouse gas emissions profile of livestock products in Southern Patagonia by providing a baseline against which mitigation actions can be planned and progress monitored.
Social Networking Information and Pre-Employment Background Checks: The Mediating Role of Sustainable Organizational Reputation
Authors: Hosain Md Sajjad , Hossin Md Altab , Xiaohua Yin , Aktaruzzaman Md , Mustafi Mohitul Ameen Ahmed
Published: April 2020

This study was aimed at identifying the role of social networking information (SNI) on pre-employment background checks (PBCs) of job applicants involving a single mediating variable, sustainable organizational reputation (SOR). In addition to that, we conducted a multi-group analysis to examine whether the direct and mediating effects were stronger in terms of gender difference. For investigation, a structured questionnaire was utilized to collect data from 1138 respondents working as hiring professionals in Bangladesh applying purposive sampling. Finally, 798 valid samples were considered. Structural equation modeling was applied using AMOS 24 to test the hypothesized relationships. The results indicated that SNI is positively and significantly related to PBCs. Additionally, it was revealed that SOR can partially mediate the direct relationship between SNI and PBCs. Furthermore, the study did not reveal any noteworthy gender differences influencing these relationships. The paper is expected to assist academicians involved in investigating pre-selection background checks and hiring professionals looking for further academic references to formulate a proper social media background policy.
Analyzing Determining Factors of Young Graduates’ Decision to Stay in Lagged Regions
Authors: Woo Youngjin , Kim Euijune
Published: April 2020

This study identifies what factors have effects on college graduates’ decisions to stay for jobs in lagged regions using a bivariate probit model with sample selection. The results show that strong preferences for a home village and a university region contribute to the decision about job location concerning the regions. In addition, low living costs have much significant impact on spatial choice compared with economic factors, such as the levels of wage and job security. The long-term economic growth of lagged regions could be affected by a preference of high-school graduates to attend local universities.
Learning Science in Primary Education with STEM Workshops: Analysis of Teaching Effectiveness from a Cognitive and Emotional Perspective
Authors: Mateos-Núñez Milagros , Martínez-Borreguero Guadalupe , Naranjo-Correa Francisco Luis
Published: April 2020

Several international institutions emphasize the need to develop a comprehensive education in STEM areas (Science, Technology, Engineering, Mathematics) to improve learning, competences and student perception of these subjects. The general objective of this study was to analyze the teaching effectiveness, from a cognitive and emotional perspective, of a STEM workshop versus an academic-expositional methodology in the science classroom in primary education. The research design was quasi-experimental with a control group, an experimental group, a pre-test and two post-tests. By means of a randomized probabilistic sampling, 256 students between 10 and 12 years old participated. Cognitive, emotional, attitudinal and gender variables were analyzed according to two teaching methodologies, an expository academic methodology for the control group and an active methodology based on the development of a practical STEM workshop for the experimental group. The results reveal that both methodologies are equally effective in short-term learning, but statistically significant differences are found in long-term learning, in favor of STEM workshops. Likewise, the STEM workshop mainly generates positive emotions and attitudes in the students compared to the transmission-reception methodology applied with the control group.
Proposing a Paradigm Shift in Rural Electrification Investments in Sub-Saharan Africa through Agriculture
Authors: Kyriakarakos George , Balafoutis Athanasios T. , Bochtis Dionysis
Published: April 2020

Almost one billion people in the world still do not have access to electricity. Most of them live in rural areas of the developing world. Access to electricity in the rural areas of Sub-Saharan Africa is only 28%, roughly 600 million people. The financing of rural electrification is challenging and, in order to accomplish higher private sector investments, new innovative business models have to be developed. In this paper, a new approach in the financing of microgrid electrification activities is proposed and investigated. In this approach, agriculture related businesses take the lead in the electrification activities of the surrounding communities. It is shown that the high cost of rural electrification can be met through the increased value of locally produced products, and cross-subsidization can take place in order to decrease the cost of household electrification. The approach is implemented in a case study in Rwanda, through which the possibility of local agricultural cooperatives leading electrification activities is demonstrated.
How Knowledge Assets Affect the Learning-by-Exporting Effect: Evidence Using Panel Data for Manufacturing Firms
Authors: Kim Hyun-Jee , Sung Bongsuk
Published: April 2020

Using panel data from Korean manufacturing firms, this study empirically investigates how knowledge assets impact the relationship between exports and productivity. We consider a scenario in which firms are situated in a globally competitive, knowledge-based environment. We establish a dynamic panel vector autoregressive model by considering the outcomes of various panel framework tests. A generalized method of moments estimator is employed to test the dynamic relationships among the variables, and a post-estimation test, Granger causality test, and impulse response test are performed. Our findings indicate the existence of a learning-by-exporting effect on the enhancement of total factor productivity (TFP). The result show that TFP can be improved by interacting with exports and knowledge assets, and that firms’ knowledge assets significantly and positively affect their exports. However, industry competition, as an external force, does not contribute to boosting firms’ productivity. We highlight the importance of continuously upgrading productivity, exports, knowledge assets, and industry competition by demonstrating that the present levels of these elements serve as the main source of their own future values. Finally, the implications of our results are outlined.
Citizenship and Pluriculturalism Approaches of Teachers in the Hispanic and Japanese Contexts: Higher Education Research
Authors: Delgado-Algarra Emilio José , Aguaded Ignacio , Bernal-Bravo César , Lorca-Marín Antonio Alejandro
Published: April 2020

Current higher education policies include several challenges, such as the academic internationalization of universities, mobility, and cultural plurality. Beyond the official curriculum, university educators have conceptions of citizenship and pluricultural competence. To understand the conceptions of educators on both topics in the Hispanic and Japanese contexts of higher education, this article presents a quantitative study involving a collaboration between a sample of education and social sciences teaching staff from universities in Spain and Japan. The CYASPS® (Citizenship and Plurilingual Social Actors in Higher Education) instrument and a categories system were designed for data collection and analysis with the support of SPSS (Statistical Package for the Social Sciences) software. Using a comparative approach, this study investigated the teaching staffs’ conceptions about citizenship and pluricultural teaching–learning environments, which focused on their views regarding different kinds of citizenship, citizens’ participation, and sources for the development of pluricultural competences. Based on a descriptive and factorial analysis, there were significant correlations between citizenship and pluricultural competence, with relevant connections between key aspects of pluricultural competence, including awareness of the rights from the liberal citizenship model, civic commitment of the republican citizenship model, and several elements of cosmopolitan and radical citizenship.
A Land Evaluation Framework for Agricultural Diversification
Authors: Jahanshiri Ebrahim , Mohd Nizar Nur Marahaini , Tengku Mohd Suhairi Tengku Adhwa Syaherah , Gregory Peter J. , Mohamed Ayman Salama , Wimalasiri Eranga M. , Azam-Ali Sayed N.
Published: April 2020

Shortlisting ecologically adaptable plant species can be a starting point for agricultural diversification projects. We propose a rapid assessment framework based on an ecological model that can accelerate the evaluation of options for sustainable crop diversification. To test the new model, expert-defined and widely available crop requirement data were combined with more than 100,000 occurrence data for 40 crops of different types (cereals, legumes, vegetables, fruits, and tubers/roots). Soil pH, texture, and depth to bedrock data were obtained and harmonised based on the optimal rooting depths of each crop. Global baseline temperature and rainfall data were used to extract averages at each location. To evaluate the ability of the method to capture intraspecies variation, a test was performed using more than 1000 accession records of bambara groundnut (Vigna subterranea (L.) Verdc.) as an exemplar underutilised crop. Results showed that a suitability index based on soil pH and an index that combines the thermal suitability moderated by the soil pH, texture, and depth suitability have the potential to predict crop adaptability. We show that the proposed method can be combined with traditional land use and crop models to evaluate diversification options for sustainable land and agrobiodiversity resources management.
An Evaluation of the Ceiling Depth’s Impact on Skylight Energy Performance Predictions Through a Building Simulation
Authors: Irakoze Amina , Lee Young-A , Kim Kee Han
Published: April 2020

This study evaluated the impact of including a building ceiling depth into a simulation model on skylight efficiency under two climatic conditions (Ulsan and Seoul, South Korea). Using Radiance and EnergyPlus simulation tools integrated in OpenStudio program by National Renewable Energy Laboratory, Golden, Colorado, USA, daylighting and building energy consumption were computed and assessed to evaluate the energy performance and optimization of skylights. Skylight-to-roof ratios from 1% to 25% were analyzed with ceiling depths of 1.5 m to 3 m. The results showed that the range for efficient skylight ratios became smaller with an increase of ceiling depth; in addition, small apertures were more affected by the ceiling depth than were large apertures. Under Ulsan’s climatic conditions, the optimal skylight-to-roof ratios were 8%, 9%, 10%, and 11% for ceiling depths of 1.5 m, 2 m, 2.5 m, and 3 m, respectively. In Seoul, 8% and 9% were the optimum skylight-to-roof ratios for ceiling depths of 1.5 m and 2 m, respectively; no skylight was energy efficient for a ceiling deeper than 2 m. This study indicates that ceiling depth is a critical factor in the evaluation of skylight performance; thus, it should not be excluded from a simulation model, as is often done to simplify simulation modeling.