bluuebunny/crossref_metadata_2025 huggingface dataset:
STRATEGI PELAYANAN PRIMA BAGI PELANGGAN VILLA AIR BALI BOUTIQUE RESORT AND SPA
Authors: Dewi Anak Agung Sasmita , Susanto Budi , Budiarta I Putu
Published: June 2019

Penelitian ini dilatarbelakangi oleh rasa ingin tahu penulis terhadap respon pelanggan Villa Air Bali Boutique Resort and Spa dari segi loyalitas pelanggan. Hal ini dikarenakan Villa Air Bali Boutique Resort and Spa memiliki pelanggan yang loyal terhadap pelayanan yang diberikan meskipun di Bali khususnya daerah Seminyak juga banyak terdapat villa resort yang menawarkan pelayanan baik dengan harga lebih murah. Tujuan penelitian ini adalah untuk mengetahui strategi pelayanan prima terhadap loyalitas pelanggan. Teknik pengambilan sampel menggunakan non probability sampling dengan jenis purposive sampling. Responden dalam penelitian ini berjumlah 100 responden. Analisis yang digunakan dalam penelitian adalah analisis kuantitatif dengan menggunakan software SPSS versi 17.0 for Windows, di mana sebelumnya dilakukan uji validitas, reliabilitas, analisis regresi berganda, uji t, uji F, dan koefisien determinasi berganda terlebih dahulu. Hasil penelitian ini menunjukkan bahwa pelayanan prima (X1) dan harga (X2) secara parsial maupun simultan bisa meningkatkan loyalitas pelanggan (Y).
Comparison of The Sleep Status and Nutrition Habits of the Students in The First and Second Education of Trakya University Faculty of Economics and Administrative Sciences
Authors: Duran Sedef , Durmuşçelebi Ezgi , Yalçın Merve , Karmil Gülşah , Radonciq Asja
Published: June 2019

Aim: Sleep duration and quality affect the food consumption and weight gain; also food consumption affects the sleep. It was found that the university students have very serious problems in terms of nutrition and sleep patterns. The aim of this study is to investigate the sleep status and eating habits of the students in the first and secondary education of university.

Methods: This cross-sectional study was carried out with 130 students from first and 108 students from secondary education of the university. Height, weight, waist and hip measurements of each participant were taken. Demographic characteristics, habits, dietary behaviors and sleep patterns of the participants were evaluated.

Results: It was determined that the students in the secondary education had a significantly higher rate of eating more at nights and skipped meals during the day. When all the participants were considered, there was a opposite and weak opposite correlation in the between the Pittsburgh Sleep Quality Index and Mediterranean Diet Quality Index scores. According to the Mediterranean Diet Quality Index, the ratio of those with very low dietary quality was 51.5% for the students in the first education and 61.1% for the students in the second education.

Conclusion: It was found that, secondary education students eat more at night than first education students; they skip meals during the day and had a very low diet quality according to Mediterranean Diet Quality Index. In order to prevent these problems, regular sleep and nutrition training should be given to the students of secondary education.
Are European Part-Time MBA Programs Designed to Foster Entrepreneurial Minds? An Exploratory Study
Authors: Entrialgo Montserrat , Iglesias Víctor , Müller Frank
Published: June 2019

Are the MBA programs really designed to foster entrepreneurial minds? Answering this question is the main objective of our work. After a literature review we identified several programs’ characteristics that promote entrepreneurship. Using a sample of 99 executive or part-time MBA programs, we found that the diversity in this sector is high. Not all the programs have been designed to foster entrepreneurship behavior; moreover, most of them do not even have an entrepreneurship subject in their curriculum. Nevertheless, other dimensions that favor this type of behavior, like internationality, are widespread in the European MBA market.
Optimal Strategy to Select Load Identification Features by Using a Particle Resampling Algorithm
Authors: He Hengjing , Lin Xiaohong , Xiao Yong , Qian Bin , Zhou Hong
Published: June 2019

This paper proposes a robust strategy to select the load identification features, which is based on particle resampling to promote the performance for the successive load identification. Firstly, the sliding window incorporated with the bilateral cumulative sum control chart (CUSUM) method is utilized to obtain the load event. Then, the minimum inner-class variance, using the time-serial data, is introduced to judge the happened time as precise as possible, thus marking the changing point of the state of load for the following feature extraction. Due to the fluctuating data of current and voltage sampled by the monitoring device, the particle resampling method, containing the importance principle, is applied to find the steady and effectiveness point, ensuring that the obtained features have the desired fit with its actual features. The fitness measurement is then carried out by using the 2-D fuzzy theory. Finally, the proposed method was tested on the real household measurements in the labs. The result demonstrates an improvement in obtaining the desired load features when applied to the real household for the following load identification.
Formation of a Double-Layer Ultrafine Crystal Structure for High-Current Pulsed Electron Beam-Treated Al–20Si–5Mg Alloy
Authors: Gao Bo , Li Kui , Xing Pengfei
Published: June 2019

In this paper, the effect of high-current pulsed electron beam (HCPEB) on the microstructure refinement of an Al–20Si–5Mg alloy in the cross-section modified zone was studied, and a double-layer ultrafine crystal structure of the Al–20Si–5Mg alloy was formed. It was found that the cross-section modified zone was divided into three zones, namely, the remelted layer, the heat-affected zone, and the thermal stress wave-affected zone after HCPEB treatment. For the remelted layer, metastable structures were formed due to the rapid heating and cooling rates. For the heat-affected zone, the grain of the aluminum phase was refined due to the cooperative effects of shock wave (formed during an eruption event of the brittle phase), thermal-stress wave (formed during thermal expansion of the alloy surface), and quasi-static thermal stress (formed as a result of an unevenly distributed temperature gradient in the inner material) at high temperatures. For the thermal stress wave-affected zone, the grain refinement was not obvious due to the decreasing energy of the shock wave and the thermal-stress wave at low temperatures. In addition, firm evidence for the tracing of shock waves in the heat-affected zone was demonstrated for the first time and verified for the founding of the broken acicular eutectic silicon. Through this experiment, the mechanical properties of Al–20Si–5Mg alloy materials in both the remelted layer and heat-affected zone were significantly improved after HCPEB treatment.
Database for Research Projects to Solve the Inverse Heat Conduction Problem
Authors: Szénási Sándor , Felde Imre
Published: June 2019

To achieve the optimal performance of an object to be heat treated, it is necessary to know the value of the Heat Transfer Coefficient (HTC) describing the amount of heat exchange between the work piece and the cooling medium. The prediction of the HTC is a typical Inverse Heat Transfer Problem (IHCP), which cannot be solved by direct numerical methods. Numerous techniques are used to solve the IHCP based on heuristic search algorithms having very high computational demand. As another approach, it would be possible to use machine-learning methods for the same purpose, which are capable of giving prompt estimations about the main characteristics of the HTC function. As known, a key requirement for all successful machine-learning projects is the availability of high quality training data. In this case, the amount of real-world measurements is far from satisfactory because of the high cost of these tests. As an alternative, it is possible to generate the necessary databases using simulations. This paper presents a novel model for random HTC function generation based on control points and additional parameters defining the shape of curve segments. As an additional step, a GPU accelerated finite-element method was used to simulate the cooling process resulting in the required temporary data records. These datasets make it possible for researchers to develop and test their IHCP solver algorithms.
Spherical Fuzzy Logarithmic Aggregation Operators Based on Entropy and Their Application in Decision Support Systems
Authors: Jin Yun , Ashraf Shahzaib , Abdullah Saleem
Published: June 2019

Keeping in view the importance of new defined and well growing spherical fuzzy sets, in this study, we proposed a novel method to handle the spherical fuzzy multi-criteria group decision-making (MCGDM) problems. Firstly, we presented some novel logarithmic operations of spherical fuzzy sets (SFSs). Then, we proposed series of novel logarithmic operators, namely spherical fuzzy weighted average operators and spherical fuzzy weighted geometric operators. We proposed the spherical fuzzy entropy to find the unknown weights information of the criteria. We study some of its desirable properties such as idempotency, boundary and monotonicity in detail. Finally, the detailed steps for the spherical fuzzy decision-making problems were developed, and a practical case was given to check the created approach and to illustrate its validity and superiority. Besides this, a systematic comparison analysis with other existent methods is conducted to reveal the advantages of our proposed method. Results indicate that the proposed method is suitable and effective for the decision process to evaluate their best alternative.
Holistic Type Extension for Classical Logic via Toffoli Quantum Gate
Authors: Freytes Hector , Giuntini Roberto , Sergioli Giuseppe
Published: June 2019

A holistic extension of classical propositional logic is introduced via Toffoli quantum gate. This extension is based on the framework of the so-called “quantum computation with mixed states”, where also irreversible transformations are taken into account. Formal aspects of this new logical system are detailed: in particular, the concepts of tautology and contradiction are investigated in this extension. These concepts turn out to receive substantial changes due to the non-separability of some quantum states; as an example, Werner states emerge as particular cases of “holistic” contradiction.
An Entropy Formulation Based on the Generalized Liouville Fractional Derivative
Authors: Ferreira Rui A. C. , Tenreiro Machado J.
Published: June 2019

This paper presents a new formula for the entropy of a distribution, that is conceived having in mind the Liouville fractional derivative. For illustrating the new concept, the proposed definition is applied to the Dow Jones Industrial Average. Moreover, the Jensen-Shannon divergence is also generalized and its variation with the fractional order is tested for the time series.
A Deep-Sea Pipeline Skin Effect Electric Heat Tracing System
Authors: Ding Li , Zhang Jiasheng , Lin Aiguo
Published: June 2019

In order to ensure deep-water flowline safety, this paper combined the axial temperature distribution model of the submarine pipeline and the distributed parameter circuit model of the skin effect electric heat tracing system; such work is conducive to proving that the heating effect of the skin effect electric heat tracing system depends on the distributed circuit parameters and power frequency of the system. Due to the complexity of the power supply device, the frequency cannot be increased indefinitely. Therefore, for the case that the input of the skin electric heat tracing system is constrained, a generalized predictive control algorithm introducing the input softening factor is proposed, and the constrained generalized predictive control strategy is applied to the electric heating temperature control system of the submarine oil pipeline. Simulation results demonstrated that the control quantity of the skin effect electric heat tracing system is effectively controlled within a constraint range, and also the values of heating power and power frequency are obtained by theoretical calculations rather than empirical estimations. Moreover, compared with the conventional control algorithm, the proposed constrained generalized predictive algorithm unfolds more significant dynamic response and better adaptive adjustment ability, which verifies the feasibility of the proposed control strategy.
Cooperation Intensity for Effective Policy Development and Implementation: A Case Study of Thailand’s Alternative Energy Development Plan
Authors: Chenboonthai Haruthai , Watanabe Tsunemi
Published: June 2019

This research examined cooperation among core Thai government organizations involved in achieving the energy-from-waste (EFW) targets stipulated in the country’s 2015 Alternative Energy Development Plan (AEDP). To this end, we used the institutional analysis and development (IAD) framework to illuminate the intricacies of such collaboration, which reflects interactions that flow logically from the decisions and measures taken by actors as they deliberate over relevant situations. Data were obtained mainly from government documents and in-depth interviews with employees of the collaborators that are directly involved in the development and implementation of AEDP 2015. The concept of cooperation intensity was used to inquire into the cooperative interactions of the aforementioned government organizations and analyze the factors and conditions that influence these actors’ decision to work with one another. We focused on the effects of institutions on cooperation under the AEDP policy process. To strengthen the novelty of this work, we categorized cooperation intensity into five levels, which can serve as guidance in the evaluation and improvement of collaborative endeavors. These levels are reflected in collaboration through (1) the pursuit of common goals and mutual benefits, (2) the pooling of resources, (3) the sharing of responsibilities, (4) the synchronization of activities, and (5) the monitoring of partners. Using the proposed cooperation intensity levels, we identified the following causes of ineffective cooperation: Differences in perceptions of problems related to municipal solid waste (MSW) and the prioritization of solutions put forward by the individual actors; the actors’ commitment to different solutions; the inconsistency among responsibilities, actions, and control over the expected outcomes of the actors; the failure of the actors to clarify and synchronize related and duplicate policy activities; and the unwillingness of the actors to undergo checking and monitoring. Overcoming these problems necessitates the enhancement of communication, which would reinforce cooperation given that effective communication leads to perfect information and an improved understanding of other actors.
Evolutionary Multi-Objective Cost and Privacy Driven Load Morphing in Smart Electricity Grid Partition
Authors: Alamaniotis Miltiadis , Gatsis Nikolaos
Published: June 2019

Utilization of digital connectivity tools is the driving force behind the transformation of the power distribution system into a smart grid. This paper places itself in the smart grid domain where consumers exploit digital connectivity to form partitions within the grid. Every partition, which is independent but connected to the grid, has a set of goals associated with the consumption of electric energy. In this work, we consider that each partition aims at morphing the initial anticipated partition consumption in order to concurrently minimize the cost of consumption and ensure the privacy of its consumers. These goals are formulated as two objectives functions, i.e., a single objective for each goal, and subsequently determining a multi-objective problem. The solution to the problem is sought via an evolutionary algorithm, and more specifically, the non-dominated sorting genetic algorithm-II (NSGA-II). NSGA-II is able to locate an optimal solution by utilizing the Pareto optimality theory. The proposed load morphing methodology is tested on a set of real-world smart meter data put together to comprise partitions of various numbers of consumers. Results demonstrate the efficiency of the proposed morphing methodology as a mechanism to attain low cost and privacy for the overall grid partition.
Integrated Wind Farm Power Curve and Power Curve Distribution Function Considering the Wake Effect and Terrain Gradient
Authors: Tao Siyu , Xu Qingshan , Feijóo Andrés , Kuenzel Stefanie , Bokde Neeraj
Published: June 2019

This work presents a computational method for the simulation of wind speeds and for the calculation of the statistical distributions of wind farm (WF) power curves, where the wake effects and terrain features are taken into consideration. A three-parameter (3-P) logistic function is used to represent the wind turbine (WT) power curve. Wake effects are simulated by means of the Jensen’s wake model. Wind shear effect is used to simulate the influence of the terrain on the WTs located at different altitudes. An analytical method is employed for deriving the probability density function (PDF) of the WF power output, based on the Weibull distribution for describing the cumulative wind speed behavior. The WF power curves for four types of terrain slopes are analyzed. Finally, simulations applying the Monte Carlo method on different sample sizes are provided to validate the proposed model. The simulation results indicate that this approximated formulation is a possible substitute for WF output power estimation, especially for the scenario where WTs are built on a terrain with gradient.
Control Oriented Prediction of Driver Brake Intention and Intensity Using a Composite Machine Learning Approach
Authors: Zhou Jianhao , Sun Jing , He Longqiang , Ding Yi , Cao Hanzhang , Zhao Wanzhong
Published: June 2019

Driver perception, decision, and control behaviors are easily affected by traffic conditions and driving style, showing the tendency of randomness and personalization. Brake intention and intensity are integrated and control-oriented parameters that are crucial to the development of an intelligent braking system. In this paper, a composite machine learning approach was proposed to predict driver brake intention and intensity with a proper prediction horizon. Various driving data were collected from Controller Area Network (CAN) bus under a real driving condition, which mainly contained urban and rural road types. ReliefF and RReliefF (they don’t have abbreviations) algorithms were employed as feature subset selection methods and applied in a prepossessing step before the training. The rank importance of selected predictors exhibited different trends or even negative trends when predicting brake intention and intensity. A soft clustering algorithm, Fuzzy C-means, was adopted to label the brake intention into categories, namely slight, medium, intensive, and emergency braking. Data sets with misplaced labels were used for training of an ensemble machine learning method, random forest. It was validated that brake intention could be accurately predicted 0.5 s ahead. An open-loop nonlinear autoregressive with external input (NARX) network was capable of learning the long-term dependencies in comparison to the static neural network and was suggested for online recognition and prediction of brake intensity 1 s in advance. As system redundancy and fault tolerance, a close-loop NARX network could be adopted for brake intensity prediction in the case of possible sensor failure and loss of CAN message.
Coordinated Defense of Distributed Denial of Service Attacks against the Multi-Area Load Frequency Control Services
Authors: Wang Qi , Tai Wei , Tang Yi , Zhu Hong , Zhang Ming , Zhou Dongxu
Published: June 2019

With the application of information and communication technology (ICT), the modern power system has gradually been updated to a typical cyber physical power system (CPPS). The deployment of distributed measurement devices enriches the application range of power communication services. However, due to the easy accessibility of distributed devices, it also creates favorable conditions for distributed denial-of-service (DDoS) attacks. In this paper, we focus on the security performance and defense strategies of the CPPS against DDoS attacks. In order to construct a coordinated defense in the power and information space, the cyber-attack process with a complete data flow of the CPPS needs to be described precisely. Therefore, a co-simulation technology-based platform is utilized to coordinate various layers in the CPPS and provide a unified research tool for the attack-defense test. On this basis, OPNET is used to replicate DDoS attacks in the information layer. Then, through the load frequency control (LFC) service of a multi-area interconnected power system, the influence of delays resulting from attacks on the control effect of the power layer is analyzed. Finally, to cope with the attack effects in both layers, detection measures of information and recovery measures of power quality are coordinated to eliminate attack consequences. Therefore, the stable operation of power services can be enabled.
Optimal Economic Dispatch for Integrated Power and Heating Systems Considering Transmission Losses
Authors: Huang Bonan , Zheng Chaoming , Sun Qiuye , Hu Ruixue
Published: June 2019

To address the problem of the supply–demand imbalance caused by network transmission losses in integrated power and heating systems (IPHS), this paper presents an optimal economic dispatch strategy to minimize system operation cost and realize coordination and optimization between power and heat. Firstly, an innovative economic dispatch model considering transmission losses is developed, where both power and heat transmission losses models are established with good precision together. In addition, the coordination equation is derived from the formulated nonlinear, multi-constrained coupling optimization problem, where the coordination relationship of units’ outputs is clearly analyzed in an analytic way. Then, a double- λ -iteration algorithm is proposed, which can not only effectively solve the nonlinear coupling optimization problem but also decrease computation burden with faster convergence rate. Finally, simulations performed on five case studies illustrate the satisfying performance of the presented strategy.
Analysing the Utilisation Effectiveness of Mining Machines Using Independent Data Acquisition Systems: A Case Study
Authors: Brodny Jarosław , Tutak Magdalena
Published: June 2019

Growing competition in the market for energy raw materials needed for power generation has led to an increasing number of measures being undertaken in the mining sector to reduce the unit costs of mining production. One of the areas that offer considerable savings in this regard is the utilisation of the technical resources owned by mines. This article is therefore focussed on analysing the utilisation effectiveness of these machines, based on the data recorded by industrial automation systems, as well as on measurements from independent surveying and chemical analysis of the excavated material’s quality. For this purpose, a methodology was developed to use the data about the operational parameters of the machines in order to analyse the effectiveness of their utilisation. It was assumed that the reliability of this assessment would depend mainly on the quality of the data used to conduct it. It was also assumed that using independent data sources for the analysis would provide objective and reliable information on the operation of the machines, devoid of any subjective feelings of the personnel or other factors. The developed methodology, based on a modified Overall Equipment Effectiveness (OEE) model, was used to analyse four machines that comprise the automated longwall system. Values were determined for each machine, including their availability, performance and product quality. This, in turn, made it possible to determine a total effectiveness indicator, based on a modified Overall Equipment Effectiveness (OEE) model, for the particular machines and the entire technical systems they form. The obtained results were used to assess the effectiveness of their utilisation and recommend corrective measures aimed at improving this metric. Moreover, the analysis results made it possible to assess the utilisation status of the machines in question. They also served as the basis for determining further lines of research, the purpose of which is to improve the effectiveness of the mining sector. The obtained results indicated that this process requires the wide application of IT tools, especially for data archiving and analysis. These tools, along with the developed model and methodology based on the analysis of large volumes of digital data, are in accord with the activities related to the implementation of Industry 4.0 idea in mining. It is the authors’ opinion that the material at hand should find a wide range of practical applications in supporting the management of technical resources within the mining sector.
Geophysical Equatorial Edge Wave with Underlying Currents in the f-Plane Approximation
Authors: Hsu Hung-Chu
Published: June 2019

I present an exact and explicit solution to the nonlinear governing equations in the equatorial f-plane, describing geophysical edge waves propagating over a plane-sloping beach, in the presence of underlying uniform currents. I also derive the analytical expressions of geophysical edge wave dynamics and the mass transport velocity.
The Complete Mitochondrial Genome of Platysternon megacephalum peguense and Molecular Phylogenetic Analysis
Authors: Luo Hongdi , Li Haijun , Huang An , Ni Qingyong , Yao Yongfang , Xu Huailiang , Zeng Bo , Li Ying , Wei Zhimin , Yu Guohua , Zhang Mingwang
Published: June 2019

Platysternon megacephalum is the only living representative species of Platysternidae and only three subspecies remain: P. m. megalorcephalum, P. m. shiui, and P. m. peguense. However, previous reports implied that P. m. peguense has distinct morphological and molecular features. The characterization of the mitogenome has been accepted as an efficient means of phylogenetic and evolutionary analysis. Hence, this study first determined the complete mitogenome of P. m. peguense with the aim to identify the structure and variability of the P. m. peguense mitogenome through comparative analysis. Furthermore, the phylogenetic relationship of the three subspecies was tested. Based on different tRNA gene loss and degeneration of these three subspecies, their rearrangement pathways have been inferred. Phylogenetic analysis showed that P. m. peguense is a sister group to (P. m. megalorcephalum and P. m. shiui). Furthermore, the divergence time estimation of these three subspecies coincided with the uplift of the Tibetan Plateau. This study shows that the genetic distances between P. m. peguense and the other two subspecies are comparable to interspecific genetic distances, for example within Mauremys. In general, this study provides new and meaningful insights into the evolution of the three Platysternidae subspecies.
Spatial-Temporal Pattern of Human-Induced Land Degradation in Northern China in the Past 3 Decades—RESTREND Approach
Authors: Zhuge Wenyi , Yue Yaojie , Shang Yanrui
Published: June 2019

Land degradation is one of the world’s most serious environmental issues. Human activities play an important role in it. Therefore, human-induced land degradation monitoring is of crucial scientific significance in revealing the evolution of land degradation and guiding its governance. Based on the residual trend (RESTREND) approach and using Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) 3g and monthly precipitation as data sources, a quantitative evaluation is conducted on the conditions of human-induced land degradation during 1982–2012 in northern China. The results indicate that (1) the “optimal cumulative precipitation-NDVImax” regression model constructed herein can improve the capability of recognizing human-induced land degradation of arid and semiarid areas in the RESTREND approach. Moreover, long time-series NDVI and precipitation data may reduce the uncertainty of quantifying human-induced land degradation. (2) In the past 3 decades, northern China has experienced three stages of human-induced land degradation, i.e., rapid development, overall reversal with local development, and continuous reversion. Human-induced land degradation in the agro-pastoral ecotone of northern China has shown a rapid restoration trend since the 1990s. (3) It is believed that the dominant factor of land degradation has a significant spatial-temporal scale effect and spatial heterogeneity. Therefore, concrete issues should be specifically analyzed to improve our understanding of land degradation development and reversal, the spatial-temporal pattern and the driving forces of land degradation in the past 3 decades in northern China. Climate change may be the main driving force of land degradation. However, the influence of human activities on the development and reversal of land degradation in small areas and in a short time is more remarkable.
Selection of Level-Dependent Hearing Protectors for Use in An Indoor Shooting Range
Authors: Mlynski Rafal , Kozlowski Emil
Published: June 2019

The high sound pressure level generated by impulse noise produced in an indoor shooting range makes it necessary to protect the hearing of the people it affects. Due to the need for verbal communication during training at a shooting range, level-dependent hearing protectors are useful. The objective of this study was to answer the question of whether it is possible to properly protect the hearing of a shooting instructor using level-dependent hearing protectors. The noise parameters were measured in the places where the instructor was present at the shooting range. The division of a specific group of trained shooters into subgroups consisting of three or six simultaneously shooting individuals did not significantly affect the exposure of the shooting instructor to the noise. An assessment of noise reduction was carried out for eight models of earmuffs and two variants of earplugs, using computational methods for the selection of hearing protectors. Among the noise parameters, both the A-weighted equivalent sound pressure level and the C-weighted peak sound pressure level were taken into account. Depending on the assessment criterion adopted, a sufficient reduction in impulse noise was provided by either four or six out of the 10 hearing protectors included in the study.
Cognitive Biases of Consumers’ Risk Perception of Foodborne Diseases in China: Examining Anchoring Effect
Authors: Shan Lijie , Wang Shusai , Wu Linhai , Tsai Fu-Sheng
Published: June 2019

Consumer cognitive biases arise from judgment and decision-making due to their limitations in information processing. As one of the important cognitive biases, the anchoring effect plays a significant role in interfering with consumers’ risk perception. With a stratified random approach, we collected survey data from 375 consumers in Wuxi, Jiangsu Province, China. Based on these data, this study attempted to analyze the anchoring effect in consumers’ risk perception of foodborne diseases (FBDs) and the differences in their perception before and after intervention in a contrast experiment using the anchoring index and the Wilcoxon signed-rank test. The results confirm the existence of the proposed anchoring effect. Moreover, the experimenter-provided anchor value, a history of FBD, and familiarity with FBD were found to be important factors influencing this anchoring effect. Therefore, improving consumers’ risk perception of FBD is critical to the long-term prevention of FBD risks by the government and consumers. The government should strengthen active monitoring, publicity, and education about FBD.
A Systematic Review to Evaluate the Association between Clean Cooking Technologies and Time Use in Low- and Middle-Income Countries
Authors: Simkovich Suzanne M. , Williams Kendra N. , Pollard Suzanne , Dowdy David , Sinharoy Sheela , Clasen Thomas F. , Puzzolo Elisa , Checkley William
Published: June 2019

Interventions implementing clean fuels to mitigate household air pollution in low- and middle-income countries have focused on environmental and health outcomes, but few have evaluated time savings. We performed a systematic review, searching for studies of clean fuel interventions that measured time use. A total of 868 manuscripts were identified that met the search criteria, but only 2 met the inclusion criteria. Both were cross-sectional and were conducted in rural India. The first surveyed the female head of household (141 using biogas and 58 using biomass) and reported 1.2 h saved per day collecting fuel and 0.7 h saved cooking, resulting in a combined 28.9 days saved over an entire year. The second surveyed the head of household (37 using biogas and 68 using biomass, 13% female) and reported 1.5 h saved per day collecting fuel, or 22.8 days saved over a year. Based on these time savings, we estimated that clean fuel use could result in a 3.8% or 4.7% increase in daily income, respectively, not including time or costs for fuel procurement. Clean fuel interventions could save users time and money. Few studies have evaluated this potential benefit, suggesting that prospective studies or randomized controlled trials are needed to adequately measure gains.
Employees’ Environmental Protection and Charitable Donation and Ethical Leadership: An Empirical Study
Authors: Zhang Qian , Liu Yun
Published: June 2019

The sustainable development of the environment and society depends not only on firms’ social responsibility initiatives, but also on employees’ socially responsible behavior during their daily work life. Hence, it is important to study why and how employees go about the socially responsible behaviors (SRB), such as environmental protection and charitable donations. Although research has been done on the antecedents of employees’ SRB from personal, contextual and leadership perspectives, little is known about the mechanism through which they affect these behaviors. Moreover, compared with the other two perspectives, research from the leadership perspective is relatively scarce. In this paper, we aim to fill these research gaps. Based on 936 respondents from 109 corporations, we empirically test the cross-level direct effect of ethical leadership on employees’ SRB and the cross-level mediating effect of perceived organizational virtuousness. In our empirical analyses, we adopt statistical methodologies such as hierarchical linear modeling and multilevel mediation analysis. Our results show that perceived organizational virtuousness partly mediates the influence of ethical leadership on employees’ environmental protection and charitable donation. In other words, ethical leadership enables employees to form the perception of organizational virtuousness, and therefore employees are more engaged in environmental protection and charitable donations. This research provides important insights for firms and their employees to become more socially and environmentally responsible.
Death-Associated Protein Kinase 1 Phosphorylation in Neuronal Cell Death and Neurodegenerative Disease
Authors: Kim Nami , Chen Dongmei , Zhou Xiao Zhen , Lee Tae Ho
Published: June 2019

Regulated neuronal cell death plays an essential role in biological processes in normal physiology, including the development of the nervous system. However, the deregulation of neuronal apoptosis by various factors leads to neurodegenerative diseases such as ischemic stroke and Alzheimer’s disease (AD). Death-associated protein kinase 1 (DAPK1) is a calcium/calmodulin (Ca2+/CaM)-dependent serine/threonine (Ser/Thr) protein kinase that activates death signaling and regulates apoptotic neuronal cell death. Although DAPK1 is tightly regulated under physiological conditions, DAPK1 deregulation in the brain contributes to the development of neurological disorders. In this review, we describe the molecular mechanisms of DAPK1 regulation in neurons under various stresses. We also discuss the role of DAPK1 signaling in the phosphorylation-dependent and phosphorylation-independent regulation of its downstream targets in neuronal cell death. Moreover, we focus on the major impact of DAPK1 deregulation on the progression of neurodegenerative diseases and the development of drugs targeting DAPK1 for the treatment of diseases. Therefore, this review summarizes the DAPK1 phosphorylation signaling pathways in various neurodegenerative diseases.
Characterization of Maize miRNAs in Response to Synergistic Infection of Maize Chlorotic Mottle Virus and Sugarcane Mosaic Virus
Authors: Xia Zihao , Zhao Zhenxing , Gao Xinran , Jiao Zhiyuan , Wu Yuanhua , Zhou Tao , Fan Zaifeng
Published: June 2019

The synergistic infection of maize chlorotic mottle virus (MCMV) and sugarcane mosaic virus (SCMV) causes maize lethal necrosis, with considerable losses to global maize production. microRNAs (miRNAs) are conserved non-coding small RNAs that play essential regulatory roles in plant development and environmental stress responses, including virus infection. However, the characterization of maize miRNAs in response to synergistic infection of MCMV and SCMV remains largely unknown. In this study, the profiles of small RNAs from MCMV and SCMV single- and co-infected (S + M) maize plants were obtained by high-throughput sequencing. A total of 173 known miRNAs, belonging to 26 miRNA families, and 49 novel miRNAs were profiled. The expression patterns of most miRNAs in S + M-infected maize plants were similar to that in SCMV-infected maize plants, probably due to the existence of RNA silencing suppressor HC-Pro. Northern blotting and quantitative real-time PCR were performed to validate the accumulation of miRNAs and their targets in different experimental treatments, respectively. The down-regulation of miR159, miR393, and miR394 might be involved in antiviral defense to synergistic infection. These results provide novel insights into the regulatory networks of miRNAs in maize plants in response to the synergistic infection of MCMV and SCMV.
The Role of SIRT1 on DNA Damage Response and Epigenetic Alterations in Cancer
Authors: Alves-Fernandes Débora Kristina , Jasiulionis Miriam Galvonas
Published: June 2019

Sirtuin-1 (SIRT1) is a class-III histone deacetylase (HDAC), an NAD+-dependent enzyme deeply involved in gene regulation, genome stability maintenance, apoptosis, autophagy, senescence, proliferation, aging, and tumorigenesis. It also has a key role in the epigenetic regulation of tissue homeostasis and many diseases by deacetylating both histone and non-histone targets. Different studies have shown ambiguous implications of SIRT1 as both a tumor suppressor and tumor promoter. However, this contradictory role seems to be determined by the cell type and SIRT1 localization. SIRT1 upregulation has already been demonstrated in some cancer cells, such as acute myeloid leukemia (AML) and primary colon, prostate, melanoma, and non-melanoma skin cancers, while SIRT1 downregulation was described in breast cancer and hepatic cell carcinomas. Even though new functions of SIRT1 have been characterized, the underlying mechanisms that define its precise role on DNA damage and repair and their contribution to cancer development remains underexplored. Here, we discuss the recent findings on the interplay among SIRT1, oxidative stress, and DNA repair machinery and its impact on normal and cancer cells.
GPathFinder: Identification of Ligand-Binding Pathways by a Multi-Objective Genetic Algorithm
Authors: Sánchez-Aparicio José-Emilio , Sciortino Giuseppe , Herrmannsdoerfer Daniel Viladrich , Chueca Pablo Orenes , Pedregal Jaime Rodríguez-Guerra , Maréchal Jean-Didier
Published: June 2019

Protein–ligand docking is a widely used method to generate solutions for the binding of a small molecule with its target in a short amount of time. However, these methods provide identification of physically sound protein–ligand complexes without a complete view of the binding process dynamics, which has been recognized to be a major discriminant in binding affinity and ligand selectivity. In this paper, a novel piece of open-source software to approach this problem is presented, called GPathFinder. It is built as an extension of the modular GaudiMM platform and is able to simulate ligand diffusion pathways at atomistic level. The method has been benchmarked on a set of 20 systems whose ligand-binding routes were studied by other computational tools or suggested from experimental “snapshots”. In all of this set, GPathFinder identifies those channels that were already reported in the literature. Interestingly, the low-energy pathways in some cases indicate novel possible binding routes. To show the usefulness of GPathFinder, the analysis of three case systems is reported. We believe that GPathFinder is a software solution with a good balance between accuracy and computational cost, and represents a step forward in extending protein–ligand docking capacities, with implications in several fields such as drug or enzyme design.
Aristolochic Acid and Immunotherapy for Urothelial Carcinoma: Directions for unmet Needs
Authors: Yang Huang-Yu , Yang Chih-Chao , Wu Chao-Yi , Wang Li-Jen , Lu Kun-Lin
Published: June 2019

Urothelial carcinoma of the bladder (UCB) and upper tracts (UTUC) used to share management with similar principles. However, their genetic and epigenetic differences along with different responses to immunotherapy were recently identified, which are reminiscent of their distinct etiologies. Different from the variety of environmental factors relating to UCB, UTUC is best known for its close relationship with exposure to aristolochic acid (AA). AA is believed to cause its carcinogenicity through forming DNA adducts of deoxyadenosine-aristolactam, as well as A:T → T:A transversions in the TP53 tumor suppressor gene. Since recent findings suggested that cancers with higher somatic mutations are associated with better treatment responses upon immune checkpoint blockade, UTUC and AA-related biomarkers reasonably serve as good candidates, as well as a potential prognostic predictor for the flourishing immunotherapy. This review covers the current state of the literature on the clinical response of UTUC and UCB receiving immunotherapy and points out directions for refinement regarding patient selection.
Phase I Clinical Trial Using Autologous Ex Vivo Expanded NK Cells and Cytotoxic T Lymphocytes for Cancer Treatment in Vietnam
Authors: Liem Nguyen Thanh , Van Phong Nguyen , Kien Nguyen Trung , Anh Bui Viet , Huyen Truong Linh , Thao Chu Thi , Tu Nguyen Dac , Hiep Doan Trung , Hoai Thu Do Thi , Nhung Hoang Thi My
Published: June 2019

(1) Background: Immune cell therapy recently attracted enormous attention among scientists as a cancer treatment, but, so far, it has been poorly studied and applied in Vietnam. The aim of this study was to assess the safety of autologous immune cell therapy for treating lung, liver, and colon cancers—three prevalent cancers in Vietnam. (2) Method: This was an open-label, single-group clinical trial that included 10 patients with confirmed diagnosis of colon, liver, or lung cancer, conducted between March 2016 and December 2017. (3) Results: After 20–21 days of culture, the average number of cytotoxic T lymphocytes (CTLs) increased 488.5-fold and the average cell viability was 96.3%. The average number of natural killer cells (NKs) increased 542.5-fold, with an average viability of 95%. Most patients exhibited improved quality of life, with the majority of patients presenting a score of 1 to 2 in the Eastern Cooperative Oncology Group (ECOG) performance status (ECOG/PS) scale, a decrease in symptoms on fatigue scales, and an increase in the mean survival time to 18.7 months at the end of the study. (4) Conclusion: This method of immune cell expansion met the requirements for clinical applications in cancer treatment and demonstrated the safety of this therapy for the cancer patients in Vietnam.
ATP Binding Cassette Transporter A1 is Involved in Extracellular Secretion of Acetylated APE1/Ref-1
Authors: Lee Yu , Joo Hee , Lee Eun , Cho Hyun , Choi Sunga , Kim Cuk-Seong , Jeon Byeong
Published: June 2019

Acetylation of nuclear apurinic/apyrimidinic endonuclease-1/redox factor-1 (APE1/Ref-1) is associated with its extracellular secretion, despite the lack of an N-terminal protein secretion signal. In this study, we investigated plasma membrane targeting and translocation of APE1/Ref-1 in HEK293T cells with enhanced acetylation. While APE1/Ref-1 targeting was not affected by inhibition of the endoplasmic reticulum/Golgi-dependent secretion, its secretion was reduced by inhibitors of ATP-binding cassette (ABC) transporters, and siRNA-mediated down-regulation of ABC transporter A1. The association between APE1/Ref-1 and ABCA1 transporter was confirmed by proximal ligation assay and immunoprecipitation experiments. An APE1/Ref-1 construct with mutated acetylation sites (K6/K7R) showed reduced co-localization with ABC transporter A1. Exposure of trichostatin A (TSA) induced the acetylation of APE1/Ref-1, which translocated into membrane fraction. Taken together, acetylation of APE1/Ref-1 is considered to be necessary for its extracellular targeting via non-classical secretory pathway using the ABCA1 transporter.
Towards a Comprehensive Framework for Climate Change Multi-Risk Assessment in the Mining Industry
Authors: Mavrommatis Evangelos , Damigos Dimitris , Mirasgedis Sevastianos
Published: June 2019

Changing climate conditions affect mining operations all over the world, but so far, the mining sector has focused primarily on mitigation actions. Nowadays, there exists increasing recognition of the need for planned adaptation actions. To this end, the development of a practical tool for the assessment of climate change-related risks to support the mining community is deemed necessary. In this study, a comprehensive framework is proposed for climate change multi-risk assessment at the local level customized for the needs of the mining industry. The framework estimates the climate change risks in economic terms by modeling the main activities that a mining company performs, in a probabilistic model, using Bayes’ theorem. The model permits incorporating inherent uncertainty via fuzzy logic and is implemented in two versatile ways: as a discrete Bayesian network or as a conditional linear Gaussian network. This innovative quantitative methodology produces probabilistic outcomes in monetary values estimated either as percentage of annual loss revenue or net loss/gains value. Finally, the proposed framework is the first multi-risk methodology in the mining context that considers all the relevant hazards caused by climate change extreme weather events, which offers a tool for selecting the most cost-effective action among various adaptation strategies.