bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural Network-Based Modeling of Electric Vehicle Energy Demand and All Electric Range
Authors: Topić Jakov , Škugor Branimir , Deur Joško
Published: April 2019

A deep neural network-based approach of energy demand modeling of electric vehicles (EV) is proposed in this paper. The model-based prediction of energy demand is based on driving cycle time series used as a model input, which is properly preprocessed and transformed into 1D or 2D static maps to serve as a static input to the neural network. Several deep feedforward neural network architectures are considered for this application along with different model input formats. Two energy demand models are derived, where the first one predicts the battery state-of-charge and fuel consumption at destination for an extended range electric vehicle, and the second one predicts the vehicle all-electric range. The models are validated based on a separate test dataset when compared to the one used in neural network training, and they are compared with the traditional response surface approach to illustrate effectiveness of the method proposed.
3D Imaging of Geothermal Faults from a Vertical DAS Fiber at Brady Hot Spring, NV USA
Authors: Trainor-Guitton Whitney , Guitton Antoine , Jreij Samir , Powers Hayden , Sullivan Bane
Published: April 2019

In March 2016, arguably the most ambitious 4D (3D space + over time) active-source seismic survey for geothermal exploration in the U.S. was acquired at Brady Natural Laboratory, outside Fernley, Nevada. The four-week experiment included 191 vibroseis source locations, and approximately 130 m of distributed acoustic sensing (DAS) in a vertical well, located at the southern end of the survey area. The imaging of the geothermal faults is done with reverse time migration of the DAS data for both P-P and P-S events in order to generate 3D models of reflectivity, which can identify subsurface fault locations. Three scenarios of receiver data are explored to investigate the reliability of the reflectivity models obtained: (1) Migration of synthetic P-P and P-S DAS data, (2) migration of the observed field DAS data and (3) migration of pure random noise to better assess the validity of our results. The comparisons of the 3D reflectivity models from these three scenarios confirm that sections of three known faults at Brady produce reflected energy observed by the DAS. Two faults that are imaged are ~1 km away from the DAS well; one of these faults (middle west-dipping) is well-constructed for over 400 m along the fault’s strike, and 300 m in depth. These results confirm that the DAS data, together with an imaging engine such as reverse time migration, can be used to position important geothermal features such as faults.
Shales Leaching Modelling for Prediction of Flowback Fluid Composition
Authors: Rogala Andrzej , Kucharska Karolina , Hupka Jan
Published: April 2019

The object of the paper is the prediction of flowback fluid composition at a laboratory scale, for which a new approach is described. The authors define leaching as a flowback fluid generation related to the shale processing. In the first step shale rock was characterized using X-ray fluorescence spectroscopy, X-ray diffractometry and laboratory analysis. It was proven that shale rock samples taken from the selected sections of horizontal well are heterogeneous. Therefore, the need to carry a wide range of investigations for highly diversified samples occurred. A series of leaching tests have been conducted. The extracts were analyzed after leaching to determine Total Organic Carbon and selected elements. For the results analysis significant parameters were chosen, and regression equations describing the influence of rocks and fracturing fluid parameters on the flowback fluid composition were proposed. Obtained models are described by high values of determination coefficients with confidence coefficients above 0.99 and a relatively low standard deviation. It was proven that the proposed approach regarding shale leaching can be properly described using shale models at a laboratory scale, however scaling up requires further investigations.
Accuracy and Reliability of Switching Transients Measurement with Open-Air Capacitive Sensors
Authors: Barakou Fani , Steennis Fred , Wouters Peter
Published: April 2019

Contactless capacitive (open-air) sensors are applied to monitor overvoltages near overhead line terminations at a substation or at the transition from underground cables to overhead lines. It is shown that these sensors, applied in a differentiating/integrating measuring concept, can result in excellent characteristics in terms of electromagnetic compatibility. The inherent cross-coupling from open-air sensors to other phases is dealt with. The paper describes a method to calibrate the sensor to line coupling matrix based on assumed 50 Hz symmetric phase voltages and in particular focuses on uncertainty analysis of assumptions made. Network simulation shows that predicted maximum overvoltages agree within typically 7% compared to reconstructed values from measurement, also with significant cross-coupling. Transient voltages from energization of an (extra-)high voltage connection can cause large and steep rising ground currents near the line terminations. Comparison with results obtained by a capacitive divider confirms the intrinsic capability in interference rejection by the differentiating/integrating measurement methodology.
A Study on Ceiling Temperature Distribution and Critical Exhaust Volumetric Flow Rate in a Long-Distance Subway Tunnel Fire with a Two-Point Extraction Ventilation System
Authors: Zhao Peng , Yuan Zhongyuan , Yuan Yanping , Yu Nanyang , Yu Tao
Published: April 2019

Smoke control is a crucial issue in a long-distance subway tunnel fire, and a two-point extraction ventilation system is an effective way to solve this problem, due to the characteristics of controlling the smoke in a limited area and removing high-temperature and toxic smoke in time. In this study, the ceiling temperature distribution and the critical exhaust volumetric flow rate to control the smoke in the zone between two extraction vents were investigated in a long-distance subway tunnel fire with a two-point extraction ventilation system. Experiments were carried out in a 1/20 reduced-scale tunnel model based on Froude modeling. Factors, including the heat release rate (HRR), the extraction vent length, the internal distance between two extraction vents and exhaust volumetric flow rate, were studied. Smoke temperature below the ceiling, exhaust volumetric flow rate and smoke spreading configurations were measured. The ceiling temperature distribution was analyzed. Meanwhile, an empirical equation was developed to predict the critical exhaust volumetric flow rate based on the one-dimensional theory, experimental phenomenon and the analysis of forces acting at the smoke underneath the extraction vent. The coefficients in the empirical equation were determined by experimental data. Compared with the experimental results, the developed empirical equation can predict the critical exhaust volumetric flow rate well. Research outcomes in this study will be beneficial to the design and application of two-point extraction ventilation system for a long-distance subway tunnel fire.
Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer
Authors: Choi Kyunghwan , Kim Kyung-Soo , Kim Seok-Kyoon
Published: April 2019

This study seeks an advanced sensor fault diagnosis algorithm for DC/DC boost converters governed by nonlinear dynamics with parameter and load uncertainties. The proposed algorithm is designed with a combination of proportional-type state observer and disturbance observer (DOB) without integral actions. The convergence, performance recovery and offset-free properties of the proposed algorithm are derived by analyzing the estimation error dynamics. An optimization process to assign the optimal feedback gain for the state observer is also provided. Finally, a fault diagnosis criteria is introduced to identify the location and type of sensor faults online using normalized residuals. The experimental results verify the effectiveness of the suggested technique under variable operating conditions and three types of sensor faults using a prototype 3 kW DC/DC boost converter.
Internal Combustion Engine Analysis of Energy Ecological Parameters by Neutrosophic MULTIMOORA and SWARA Methods
Authors: Zavadskas Edmundas Kazimieras , Čereška Audrius , Matijošius Jonas , Rimkus Alfredas , Bausys Romualdas
Published: April 2019

The investigation for new innovative solutions to reduce transport pollution is a priority for the European Union (EU). This study includes energy and a sustainable environment, as well as transport, logistics, and information and communication technologies. Energy ecological parameters of internal combustion depend on many factors: fuel, the fuel injection time, engine torque, etc. The engine’s energy ecological parameters were studied by changing engine torques, using different fuels, and changing the start of the fuel injection time. The selection of the optimum parameters is a complex problem. Multicriteria decision-making methods (MCDM) present powerful and flexible techniques for the solution of many sustainability problems. The article presents a new way of tackling transport pollution. The analysis of the energy ecological parameters of the experimental internal combustion engine is performed using the neutrosophic multi-objective optimization by a ratio analysis plus the full multiplicative form (MULTIMOORA) and step-wise weight assessment ratio analysis (SWARA) methods. The application of MCDM methods provides us with the opportunity to establish the best alternatives which reflect the best energy ecological parameters of the internal combustion engine.
Forecasting Daily Solar Radiation Using CEEMDAN Decomposition-Based MARS Model Trained by Crow Search Algorithm
Authors: Rezaie-Balf Mohammad , Maleki Niloofar , Kim Sungwon , Ashrafian Ali , Babaie-Miri Fatemeh , Kim Nam Won , Chung Il-Moon , Alaghmand Sina
Published: April 2019

The precise forecasting of daily solar radiation (DSR) is receiving prominent attention among thriving solar energy studies. In this study, three standalone models, including gene expression programing (GEP), multivariate adaptive regression splines (MARS), and self-adaptive MARS (SaMARS), were evaluated to forecast DSR. A SaMARS model was classified as MARS model when using the crow search algorithm (CSA). In addition, to overcome the limitations of the standalone models, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was employed to enhance the accuracy of DSR forecasting. Therefore, three hybrid models including CEEMDAN-GEP, CEEMDAN-MARS, and CEEMDAN-SaMARS were proposed to forecast DSR in Busan and Incheon stations in South Korea. The performance of proposed models were evaluated and affirmed that the accuracy of the CEEMDAN-SaMARS model (NSE = 0.878–0.883) outperformed CEEMDAN-MARS (NSE = 0.819–0.818), CEEMDAN-GEP (NSE = 0.873–0.789), SaMARS (NSE = 0.846–0.769), MARS (NSE = 0.819–0.758), and GEP (NSE = 0.814–0.755) models at both stations. Therefore, it can be concluded that the optimized CEEMDAN-SaMARS model significantly enhanced the accuracy of DSR forecasting compared to that of standalone models.
A SGAM-Based Test Platform to Develop a Scheme for Wide Area Measurement-Free Monitoring of Smart Grids under High PV Penetration
Authors: Estebsari Abouzar , Barbierato Luca , Bahmanyar Alireza , Bottaccioli Lorenzo , Macii Enrico , Patti Edoardo
Published: April 2019

In order to systematically shift existing control and management paradigms in distribution systems to new interoperable communication supported schemes in smart grids, we need to map newly developed use cases to standard reference models like Smart Grid Architecture Model (SGAM). From the other side, any new use cases should be tested and validated ex-ante before being deployed in the real-world system. Considering various types of actors in smart grids, use cases are usually tested using co-simulation platforms. Currently, there is no efficient co-simulation platform which supports interoperability analysis based on SGAM. In this paper, we present our developed test platform which offers a support to design new use cases based on SGAM. We used this platform to develop a new scheme for wide area monitoring of existing distribution systems under growing penetration of Photovoltaic production. Off-the-shelf solutions of state estimation for wide area monitoring are either used for passive distribution grids or applied to the active networks with wide measurement of distributed generators. Our proposed distribution state estimation algorithm does not require wide area measurements and relies on the data provided by a PV simulator we developed. This practical scheme is tested experimentally on a realistic urban distribution grid. The monitoring results shows a very low error rate of about 1 % by using our PV simulator under high penetration of PV with about 30 % error of load forecast. Using our SGAM-based platform, we could propose and examine an Internet-of-Things-based infrastructure to deploy the use case.
A Conceptual Model for Forest Naturalness Assessment and Application in Quebec’s Boreal Forest
Authors: Côté Sylvie , Bélanger Louis , Beauregard Robert , Thiffault Évelyne , Margni Manuele
Published: April 2019

Research Highlights: To inform eco-designers in green building conception, we propose a conceptual model for the assessment of the impact of using wood on the quality of ecosystems. Background and Objectives: The proposed model allows the assessment of the quality of ecosystems at the landscape level based on the condition of the forest and the proportion of different practices to characterize precisely the forest management strategy. The evaluation provides a numerical index, which corresponds to a suitable format to inform decision-making support tools, such as life cycle analysis. Materials and Methods: Based on the concept of naturalness, the methodology considers five naturalness characteristics (landscape context, forest composition, structure, dead wood, and regeneration process) and relies on forest inventory maps and data. An area within the boreal black spruce-feathermoss ecological domain of Quebec (Canada) was used as a case study for the development of the methodology, designed to be easily exportable. Results: In 2012, the test area had a near-natural class (naturalness index NI = 0.717). Simulation of different management strategies over 70 years shows that, considering 17.9% of strict protected areas, the naturalness index would have lost one to two classes of naturalness (out of five classes), depending on the strategy applied for the regeneration (0.206 ≤ ΔNI ≤ 0.413). Without the preservation of the protected areas, the management strategies would have further reduced the naturalness (0.274 ≤ ΔNI ≤ 0.492). Apart from exotic species plantation, the most sensitive variables are the percentage of area in irregular, old, and closed forests at time zero and the percentage of area in closed forests, late successional species groups, and modified wetlands after 70 years. Conclusions: Despite the necessity of further model and parameter validation, the use of the index makes it possible to combine the effects of different forestry management strategies and practices into one alteration gradient.
Identification of Key Genes in the Synthesis Pathway of Volatile Terpenoids in Fruit of Zanthoxylum bungeanum Maxim
Authors: Shi Jingwei , Fei Xitong , Hu Yang , Liu Yulin , Wei Anzhi
Published: April 2019

Zanthoxylum bungeanum Maxim. (Z. bungeanum), a plant that belongs to the Rutaceae family, is widely planted in China. Its outstanding feature is its rich aroma. The main component that creates this aroma is the volatile terpenoids. In this study, we aimed to understand the molecular mechanism related to aroma synthesis in Z. bungeanum and provide new ideas for breeding. Headspace solid phase micro extraction-gas chromatography mass spectrometry (HS-SPME-GC-MS), RT-qPCR and bioinformatics were used to study the changes in volatile terpenoids and identify key genes in the pathway of terpenoids in fruits of Z. bungeanum. The results show that the trend of volatile terpenoids is consistent among the two varieties. As the fruit matures, the terpenoids gradually accumulate and peak in the third period (mid-development) before gradually decreasing. Among these terpenoids, there is the highest content of α-pinene. In Z. bungeanum cv. ‘Hanchengdahongpao’ (Hanchengdahongpao) and Z. bungeanum cv. ‘Fuguhuajiao’ (Fuguhuajiao), this reached 24.74% and 20.78% respectively. In general, for the content of volatile terpenoids, Hanchengdahongpao is 62% and Fuguhuajiao is 41%. The results of RT-qPCR showed that most gene expression in this study was upregulated. Among them, ZbDXS has the highest relative level of expression in itself, which is the key rate-limiting enzymein the MEP pathway. These results explore the synthetic route of terpenoids during the ripening process of Z. bungeanum, which provides a reference for cultivar and improving good traits.
N Isotope Fractionation in Tree Tissues During N Reabsorption and Remobilization in Fagus crenata Blume
Authors: Seidel Felix , Lopez C. M. Larry , Celi Luisella , Bonifacio Eleonora , Oikawa Akira , Yamanaka Toshiro
Published: April 2019

Background and Motivation: Nitrogen content in tissues of Fagus crenata Blume is key for flowering and seed production. However, there is a lack of information on seasonal intra-plant nitrogen partitioning in this representative tree species typical of heavy snowfall regions in Japan. Therefore, the objective of this study was to elucidate Fagus crenata intra-plant nitrogen movement by means of nitrogen content, nitrogen isotope analysis, and amino acids temporal variability. Materials and Methods: Nitrogen content, isotope ratio, and free amino acids content were measured in coarse roots, sapwood, leaves, and litter in four phenological stages in nine adult Fagus crenata trees and upscaled to the whole-tree level. Results: Nitrogen was reabsorbed to and stored in coarse roots during the pre-abscission stage, as was revealed by the depletion of the δ15N ratio of coarse roots, which coincided with an enrichment of 15N found in leaves. During the post-abscission stage, N was stored in the sapwood, where an enrichment in 15N was found coinciding with the depletion of the δ15N ratio in leaves. It seemed that 15N-enriched nitrogen was initially reabsorbed from leaves to coarse roots during the pre-abscission period, followed by the reabsorption of 15N-enriched nitrogen from leaves to sapwood shortly before leaf abscission. Free amino acids content and their dynamics could mostly explain seasonal δ15N fractionation in leaves, coarse roots, and partially in sapwood. At the whole-tree level, N content stored in coarse roots and sapwood was similar. Furthermore, reabsorbed leaf N accounted for 32% of all nitrogen stored during leaf senescence. Conclusion: We found three phases of nitrogen storage revealed by δ15N fractionation during leaf senescence: (1) reabsorption of leaf 15N-depleted nitrogen to coarse roots, followed by (2) reabsorption of leaf 15N-enriched nitrogen to sapwood and (3) soil 15N-depleted nitrogen uptake to coarse roots. Further, changes in free amino acids, which are the result of enzyme activities involved in amino acids synthesis, partially explained δ15N fractionation in plant tissues.
Industrial Ultrasound Applications in the Extra-Virgin Olive Oil Extraction Process: History, Approaches, and Key Questions
Authors: Clodoveo Maria Lisa
Published: April 2019

Taking an idea from a basic concept to a commercially available product is highly rewarding, but it can be a very long, complex, and difficult journey. Recognizing and understanding the stages of the process and using the right support to help you navigate through it can mean all the difference between success and failure. The road from concept to market is marred with obstacles, and many businesses fail to pass beyond the development stage. A better understanding of the innovation process is essential from the outset if the pioneers of innovation are to overcome the dangers that they are likely to face along the way and maximize their opportunities for success. In the olive oil sector, the most recent radical innovation is the introduction of ultrasound into the industrial extraction process. Many efforts have been made in order to overcome the Valley of Death. The strategy of designing, implementing, and testing an innovative system that combines the mechanical energy of ultrasound with the possibility of modulating the thermal exchange of olive paste (heating or cooling) has enabled the following: (1) Eliminating malaxation by realizing a real continuous process; (2) raising extraction yields by recovering a further quota of extra-virgin olive oil that is usually lost in the pomace; (3) improving the content of antioxidant molecules simultaneously with yields; and (4) offering a sustainable plant solution that can guarantee the right income for producers.
Complexity and Politics of Naming in Yoruba Tradition: A Dramatic Exploration of Once Upon an Elephant
Authors: Balogun Lekan , Fasanu Sesan
Published: April 2019

This paper examines the connection between naming and oral tradition, specifically àló and ìtàn, by discussing Bosede Ademilua-Afolayan’s Once Upon an Elephant (2015), and demonstrates the ways in which contemporary Nigerian playwrights appropriate the same to engage their political realities. The Yoruba are aware that names are not mere signs but the material nodes of the social network, hence the rites associated with naming underscore the people’s belief in birth, life, and living, as well as the totality of existence. The paper is in three parts: a background to the analysis, a discussion of Yoruba belief about naming that is linked with a discussion of oral tradition, and an analysis of the play with materials that are drawn from the previous discussion in order to show how the playwright has used the strategy of naming to engage a broader socio-political reality of her society.
Commensal and Pathogenic Members of the Dental Calculus Microbiome of Badia Pozzeveri Individuals from the 11th to 19th Centuries
Authors: Santiago-Rodriguez Tasha M. , Fornaciari Antonio , Fornaciari Gino , Luciani Stefania , Marota Isolina , Vercellotti Giuseppe , Toranzos Gary A. , Giuffra Valentina , Cano Raul J.
Published: April 2019

The concept of the human oral microbiome was applied to understand health and disease, lifestyles, and dietary habits throughout part of human history. In the present study, we augment the understanding of ancient oral microbiomes by characterizing human dental calculus samples recovered from the ancient Abbey of Badia Pozzeveri (central Italy), with differences in socioeconomic status, time period, burial type, and sex. Samples dating from the Middle Ages (11th century) to the Industrial Revolution era (19th century) were characterized using high-throughput sequencing of the 16S ribosomal RNA (rRNA) gene V4 region. Consistent with previous studies, individuals from Badia Pozzeveri possessed commensal oral bacteria that resembled modern oral microbiomes. These results suggest that members of the oral microbiome are ubiquitous despite differences in geographical regions, time period, sex, and socioeconomic status. The presence of fecal bacteria could be in agreement with poor hygiene practices, consistent with the time period. Respiratory tract, nosocomial, and other rare pathogens detected in the dental calculus samples are intriguing and could suggest subject-specific comorbidities that could be reflected in the oral microbiome.
Time-Lapse 3D Electric Tomography for Short-time Monitoring of an Experimental Heat Storage System
Authors: Comina Cesare , Giordano Nicolò , Ghidone Giulia , Fischanger Federico
Published: April 2019

A borehole thermal energy storage living lab was built nearby Torino (Northern Italy). The aim of this living lab is to test the ability of the alluvial deposits of the north-western Po Plain to store the thermal energy collected by solar panels. Monitoring the temperature distribution induced in the underground and the effectiveness of the heat storage in this climatic context is not an easy task. For this purpose, different temperature evolution strategies are compared in this paper: Local temperature measurements, numerical simulations and geophysical surveys. These different approaches were compared during a single day of operation of the living lab. The results of this comparison allowed to underline the effectiveness of time-lapse 3D electric resistivity tomography as a non-invasive and cost-effective qualitative heat monitoring tool. This was obtained even in a test site with unfavorable thermo-hydrogeological conditions and high-level anthropic noise. Moreover, the present study demonstrated that, if properly calibrated with local temperature values, time-lapse 3D electric resistivity tomography also provides a quantitative estimation of the underground temperature.
Bayesian Variable Selection for Pareto Regression Models with Latent Multivariate Log Gamma Process with Applications to Earthquake Magnitudes
Authors: Yang Hou-Cheng , Hu Guanyu , Chen Ming-Hui
Published: April 2019

Generalized linear models are routinely used in many environment statistics problems such as earthquake magnitudes prediction. Hu et al. proposed Pareto regression with spatial random effects for earthquake magnitudes. In this paper, we propose Bayesian spatial variable selection for Pareto regression based on Bradley et al. and Hu et al. to tackle variable selection issue in generalized linear regression models with spatial random effects. A Bayesian hierarchical latent multivariate log gamma model framework is applied to account for spatial random effects to capture spatial dependence. We use two Bayesian model assessment criteria for variable selection including Conditional Predictive Ordinate (CPO) and Deviance Information Criterion (DIC). Furthermore, we show that these two Bayesian criteria have analytic connections with conditional AIC under the linear mixed model setting. We examine empirical performance of the proposed method via a simulation study and further demonstrate the applicability of the proposed method in an analysis of the earthquake data obtained from the United States Geological Survey (USGS).
Productive Remembering of Childhood: Child–Adult Memory-Work with the School Literary Canon
Authors: Deszcz-Tryhubczak Justyna , Marecki Mateusz , Chawar Ewa , Kaczkowska Magdalena , Kowalska Katarzyna , Kulawik Aleksandra , Ożlańska Maja , Palczyńska Milena , Parcheniak Natalia , Pszczołowski Eryk
Published: April 2019

This essay, co-written by adult and child researchers, marks an important shift in the field of children’s literature studies because it promotes an academic practice in which children are actively involved in decision-making. In our polyphonic account of the collaboration, we draw on the ideas of productive remembering, re-memorying, and child-led research to advance a new pedagogical approach to the current, adult-centered literary school canon in Poland, which was compiled in 2017 by a panel of politically appointed experts. We exemplify our proposal by discussing “Staś and Nel in the 21st Century”: Do Long-established School Readings Connect Generations?”, a participatory research project conducted at a primary school in Wrocław, Poland, in spring 2018. As we argue, selected texts from the canon may catalyze memories of childhood from older readers that can be shared with younger readers to develop their own connections with these texts. Such an exchange may open new individual and collective remembering spaces linking intragenerational perspectives with intergenerational meanings and resulting in a school canon that promotes both national cohesion and openness to other cultures. Seen thus, our approach can be adopted in school and other settings to engage children and adults as co-creators of particular memory-work methods. In broader terms, it can promote a critical and action-oriented understanding of the heritage of childhood in Poland and elsewhere.
Impact of Outpatient Rehabilitation Service in Preventing the Deterioration of the Care-Needs Level Among Japanese Older Adults Availing Long-Term Care Insurance: A Propensity Score Matched Retrospective Study
Authors: Maruta Michio , Tabira Takayuki , Makizako Hyuma , Sagari Akira , Miyata Hironori , Yoshimitsu Koji , Han Gwanghee , Yoshiura Kazuhiro , Kawagoe Masahiro
Published: April 2019

Outpatient rehabilitation (OR) and outpatient day long-term care (ODLC) services are frequently used by older adult patients in Japan. However, there is a need to clarify that OR service, which has more rehabilitation professionals than ODLC, has the role of providing rehabilitation. This retrospective study examined the impact of OR services by comparing the two services based on City A data from the care-needs certification survey conducted between 2015 to 2017. We performed a propensity score matched analysis to compare the changes in the care level and function of OR and ODLC users after two years. The results showed that OR users showed a lower deterioration in care levels and less decline in the activities of daily living (ADL) in dementia and adaptation to social life. In the analysis of older adults requiring support, OR users had a lower deterioration in care levels and less decline in the ADL in dementia and behavioral and psychological symptoms than ODLC users did. There was no difference between the two services with respect to older adults requiring long-term care. The OR service has had an increasingly preventive effect on the deterioration of care levels compared to the ODLC service, which was particularly evident in older adults requiring support.
Strength Decrease, Perceived Physical Exertion and Endurance Time for Backpacking Tasks
Authors: Li Kai Way , Chu Jenn Chun , Chen Ching Chung
Published: April 2019

Manual material handling (MMH) tasks create a burden for workers which could result in musculoskeletal injuries. Assessments of the decrease of muscular strength and the maximum endurance time (MET) for MMH tasks are essential in studying the ergonomic risk of MMH tasks. A backpacking experiment was conducted for measuring the MET for MMH tasks. Human participants carried a load on their back and walked on a treadmill under various load, walking speed, and ramp angle conditions until they coud no longer do so. It was found that the participants were able to walk for approximately 15 min to two hours before they needed to have a pause. Their back and leg strengths declined moderately due to performing the tasks. These tasks resulted in an increase in heart rate and elevated perceived physical exertion. The rating of perceived exertion (RPE)/heart rate ratio in our backpacking tasks was 31% higher than that in the literature, implying the calibration of the RPE may be required for such tasks. A MET model incorporating the fMVC_back, body weight, walking speed, and ramp angle was established. This model may be used to determine the work/rest allowance for backpacking tasks under conditions similar to this study.
Geochemical Characteristics and Toxic Elements in Alumina Refining Wastes and Leachates from Management Facilities
Authors: Sun Chunwei , Chen Jiannan , Tian Kuo , Peng Daoping , Liao Xin , Wu Xiyong
Published: April 2019

A nationwide investigation was carried out to evaluate the geochemical characteristics and environmental impacts of red mud and leachates from the major alumina plants in China. The chemical and mineralogical compositions of red mud were investigated, and major, minor, and trace elements in the leachates were analyzed. The mineral and chemical compositions of red mud vary over refining processes (i.e., Bayer, sintering, and combined methods) and parental bauxites. The main minerals in the red mud are quartz, calcite, dolomite, hematite, hibschite, sodalite, anhydrite, cancrinite, and gibbsite. The major chemical compositions of red mud are Al, Fe, Si, Ca, Ti, and hydroxides. The associated red mud leachate is hyperalkaline (pH > 12), which can be toxic to aquatic life. The concentrations of Al, Cl−, F−, Na, NO32−, and SO42− in the leachate exceed the recommended groundwater quality standard of China by up to 6637 times. These ions are likely to increase the salinization of the soil and groundwater. The minor elements in red mud leachate include As, B, Ba, Cr, Cu, Fe, Ni, Mn, Mo, Ti, V, and Zn, and the trace elements in red mud leachate include Ag, Be, Cd, Co, Hg, Li, Pb, Sb, Se, Sr, and Tl. Some of these elements have the concentration up to 272 times higher than those of the groundwater quality standard and are toxic to the environment and human health. Therefore, scientific guidance is needed for red mud management, especially for the design of the containment system of the facilities.
When Do Service Employees Suffer More from Job Insecurity? The Moderating Role of Coworker and Customer Incivility
Authors: Shin Yuhyung , Hur Won-Moo
Published: April 2019

The present study examines the effect of service employees’ job insecurity on job performance through emotional exhaustion. We identified workplace incivility (i.e., coworker and customer incivility) as a boundary condition that strengthens the positive relationship between job insecurity and emotional exhaustion. To test this moderating effect, we collected online panel surveys from 264 Korean service employees at two time points three months apart. As predicted, the positive relationship between job insecurity and job performance was partially mediated by emotional exhaustion. Of the two forms of workplace incivility, only coworker incivility exerted a significant moderating effect on the job insecurity–emotional exhaustion relationship, such that this relationship was more pronounced when service employees experienced a high level of coworker incivility than when coworker incivility was low. Coworker incivility further moderated the indirect effect of job insecurity on job performance through emotional exhaustion. These findings have theoretical implications for job insecurity research and managerial implications for practitioners.
Negative Impacts of Self-Stigma on the Quality of Life of Patients in Methadone Maintenance Treatment: The Mediated Roles of Psychological Distress and Social Functioning
Authors: Cheng Ching-Ming , Chang Chih-Cheng , Wang Jung-Der , Chang Kun-Chia , Ting Shuo-Yen , Lin Chung-Ying
Published: April 2019

A sample of heroin users (n = 250) in methadone maintenance treatment (MMT) was used in this cross-sectional study to clarify the mechanisms of the effects of stigma on quality of life (QoL) through psychological distress and social functioning. All the participants had their self-stigma, psychological distress, social functioning, and QoL measured. Psychological distress and social functioning were proposed to be mediators between self-stigma and QoL. Several linear models using structural equation modeling were conducted to examine the mediated effects. The negative effects of self-stigma on QoL were significantly mediated by psychological distress, as self-stigma directly and significantly influenced psychological distress, but not social functioning. This study demonstrated a linear model describing the effects of self-stigma on QoL for opioid-dependent individuals; psychological distress was also an important mediator between self-stigma and their QoL. Clinicians were able to notice the importance of reducing self-stigma for opioid-dependent individuals according to the following results: higher levels of self-stigma were associated with high psychological distress, decreased social functioning, and impaired QoL. Our mediation findings suggest that treating psychological distress is better than treating social functioning if we want to eliminate the effects of self-stigma on QoL for heroin users.
Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration
Authors: Hsu Chin-Yu , Wu Jhao-Yi , Chen Yu-Cheng , Chen Nai-Tzu , Chen Mu-Jean , Pan Wen-Chi , Lung Shih-Chun Candice , Guo Yue Leon , Wu Chih-Da
Published: April 2019

This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O3 concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency’s (EPA) data of O3 concentrations from 2000 and 2013 were used to develop this model, while observations from 2014 were used as the external data verification to assess model reliability. The distribution of temples, cemeteries, and crematoriums was included for a potential predictor as an Asian culturally specific source for incense and joss money burning. We used stepwise regression for the LUR model development, and applied 10-fold cross-validation and external data for the verification of model reliability. With the overall model R2 of 0.74 and a 10-fold cross-validated R2 of 0.70, this model presented a mid-high prediction performance level. Moreover, during the stepwise selection procedures, the number of temples, cemeteries, and crematoriums was selected as an important predictor. By using the long-term monitoring data to establish an LUR model with culture specific predictors, this model can better depict O3 concentration variation in Asian areas.
Application of Artificial Neural Networks to Identify Alzheimer’s Disease Using Cerebral Perfusion SPECT Data
Authors: Świetlik Dariusz , Białowąs Jacek
Published: April 2019

The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer disease diagnosis (AD) using data of brain single photon emission computed tomography (SPECT). The results were compared with discriminant analysis. The study population consisted of 132 clinically diagnosed patients. There were 72 subjects with AD and 60 belonging to the normal control group. The artificial neural network used 36 numerical values being the count numbers obtained for each area of brain SPECT. These numbers determined the set of input data for the artificial neural network. The sensitivity of Alzheimer disease diagnosis detection by artificial neural network and discriminant analysis were 93.8% and 86.1%, respectively, and the corresponding specificity was 100% and 95%. We also used receiver operating characteristic curve (ROC) analysis and areas under receiver operating characteristics curves were correspondingly 0.97 (p < 0.0001) for the artificial neural networks (ANN) and 0.96 (p < 0.0001) for discriminant analysis. In conclusion, artificial neural networks and conventional statistics methods (discriminant analysis) are a useful tool in Alzheimer disease diagnosis.
Surface Body Temperature of Full-Term Healthy Newborns Immediately after Birth—Pilot Study
Authors: Lubkowska Anna , Szymański Sławomir , Chudecka Monika
Published: April 2019

The aim of the study was to perform an evaluation of chosen body surface temperatures in neonates immediately after birth, and to seek a relationship between those temperatures and the factors related both to the mother and newborn. The study included 74 healthy newborns. Maternal age, body weight, body mass index before pregnancy and on delivery day, birth and pregnancy order, newborn sex, birth weight, body length, pregnancy week on delivery, as well as newborn gasometric test results were collected. The highest temperature values were observed in the chest of the newborn. Significant relationships between the temperature of the evaluated areas were found. The parameters that correlated positively with the temperature of the back region were maternal body weight (both before pregnancy and on delivery day) as well as weight gain during pregnancy. The core and surface temperatures of the body are one of the most important elements of neonatal homeostasis and any changes constitute a risk to the newborn’s health. It seemed that according to the surface temperature, the most important area that must be evaluated is the neonate’s back, as it is most affected by appropriate weight gain during pregnancy.
Social Determinants of Health-Related Quality of Life among Residents in Zhejiang and Qinghai, China
Authors: Gu Yuxuan , Zhang Hao , Ali Shahmir H. , Huang Minzhuo , Wei Jingming , Gu Shuyan , Zhen Xuemei , Hu Xiaoqian , Sun Xueshan , Dong Hengjin
Published: April 2019

Social determinants are closely related to health and play a significant role in shaping the quality of life of a population. This study aimed to explore the differences in HRQoL (health-related quality of life) scores of residents in the eastern province of Zhejiang and the western province of Qinghai and probe factors affecting the HRQoL among the two populations. A sample of 4210 residents from a cross-sectional survey was included in the analysis. The EQ-5D-3L instrument was used to measure the HRQoL of residents. A Chi-square test and a t-test were used to examine the differences between different variables and analysis of variance (ANOVA) with interaction effects was used to analyze factors associated with the HRQoL between the two provinces. Residents’ EQ-5D index score (EQ VAS score) was 0.963 (82.71) and 0.962 (81.51), respectively, in Zhejiang and Qinghai. Generally, residents in Qinghai displayed significantly worse HRQoL scores than those in Zhejiang. The differences between the two regions lay on mobility, pain/discomfort, and anxiety/depressions. In both regions, an increased education level and being employed were most strongly associated with a positive HRQoL; increased age and presence of chronic diseases were most strongly associated with a negative HRQoL. When formulating health policies, the significant health disparities between western and eastern provinces must be given greater consideration. The health of vulnerable groups should be particularly focused on to improve the observed health disparities.
Effects of Social Support on the Stress-Health Relationship: Gender Comparison among Military Personnel
Authors: Hsieh Chi-Ming , Tsai Bi-Kun
Published: April 2019

The purpose of this study was to investigate how the role of workplace social support and gender affect the relationship between work stress and the physical and mental health of military personnel in Taiwan. The analysis results reveal that military personnel expressed significantly high perceptions of work-related stress. Social support from supervisors and colleagues is a crucial factor in buffering the effect of work-related stress on perceived health, and increasing the physical and mental health among military personnel. This study shows that male personnel who perceived higher stress and gained more social support from supervisors and colleagues than female personnel were less likely to have physical and mental issues than female personnel. Managerial implications and suggestions could serve as references in managing work-related stress, enhancing social support occurring in the military workplace, and reducing job dissatisfaction, which in turn improves the health and well-being of military personnel in Taiwan.
Health of Refugees and Migrants—Where Do We Stand and What Directions Should We Take?
Authors: Keidar Osnat , Srivastava David S. , Pikoulis Emmanouil , Exadaktylos Aristomenis K.
Published: April 2019

International migration, particularly to Europe, has increased in the last few decades, making research on aspects of this phenomenon, including numbers, challenges, and successes, particularly vital [...]
Effects of Long Noncoding RNA H19 Polymorphisms on Urothelial Cell Carcinoma Development
Authors: Yang Po-Jen , Hsieh Ming-Ju , Hung Tung-Wei , Wang Shian-Shiang , Chen Shiuan-Chih , Lee Meng-Chih , Yang Shun-Fa , Chou Ying-Erh
Published: April 2019

Urothelial cell carcinoma (UCC) is one of the major malignancies of the genitourinary tract, and it is induced by carcinogenic epidemiological risk factors. H19 is one of the most crucial long noncoding RNAs (lncRNAs) and is involved in various types of bladder cancer. In this study, we examined H19 single-nucleotide polymorphisms (SNPs) to investigate UCC susceptibility and clinicopathological characteristics. Using real-time polymerase chain reaction, we analyzed five SNPs of H19 in 431 UCC patients and 431 controls without cancer. The results showed that patients with UCC carrying the H19 rs217727 CT + TT and rs2107425 CT + TT genetic variants had a high risk of developing muscle invasive tumors (pT2–T4) (p = 0.030; p = 0.025, respectively). With a median follow up of 39 months, CT+TT polymorphisms of rs2107425 were associated with worse disease-specific survival (adjusted hard ratio (AHR) = 2.043, 95% confidence interval (CI) = 1.029-4.059) in UCC patients aged older than 65 years. In conclusion, our results indicate that patients with UCC carrying the H19 rs217727 CT + TT and rs2107425 CT + TT genetic variants have a high risk of developing muscle invasive tumors. Thus, H19 polymorphisms may be applied as a marker or therapeutic target in UCC treatment.
Association between Dipeptidyl Peptidase-4 Inhibitors and Allergic Rhinitis in Asian Patients with Diabetes
Authors: Chen Hsin-Hung , Li Shang-Yi , Chen Weishan , Kao Chia-Hung
Published: April 2019

In this retrospective study, we attempted to evaluate the association between dipeptidyl peptidase-4 (DPP-4) inhibitors and allergic rhinitis in patients with diabetes. We analyzed the Longitudinal Health Insurance Database 2000 subdatabase. Our study population included patients with type 2 diabetes (ICD-9-CM 250) between 2009 and 2012, and the study groups were DPP-4 inhibitor users and nonusers. Propensity scores were estimated in a multivariable logistic regression model for the analysis of allergic rhinitis (ICD-9-CM 477.9). Each group consisted of 6204 patients. DPP-4 inhibitor users had a reduced risk of allergic rhinitis (aHR = 0.74, 95% confidence interval (CI) = 0.61–0.90) in all stratifications. Among women, DPP-4 inhibitor users had a lower risk of allergic rhinitis (aHR = 0.67, 95% CI = 0.50–0.90). Among patients aged older than 40 years, DPP-4 inhibitor users had a decreased risk of allergic rhinitis (those aged 40–59: aHR = 0.75, 95% CI = 0.56–0.99; those aged ≧60: aHR = 0.73, 95% CI = 0.54–0.97). Among patients with comorbidities, the risk of allergic rhinitis for DPP-4 inhibitor users was 0.73 (95% CI = 0.60–0.90). High-dose (cumulative defined daily dose ≧648mg) DPP-4 inhibitor users had a decreased risk of allergic rhinitis (aHR = 0.23, 95% CI = 0.15–0.35). Our study revealed that Asian patients with diabetes who used DPP-4 inhibitors had decreased risk of allergic rhinitis, especially for DPP-4 inhibitor treatment in patients who were women, were older than 40 years, had higher diabetes severity scores, were taking higher doses of DPP-4 inhibitors, and had diabetes with comorbidities.