bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel Random Copolymers of Poly(butylene 1,4-cyclohexane dicarboxylate) with Outstanding Barrier Properties for Green and Sustainable Packaging: Content and Length of Aliphatic Side Chains as Efficient Tools to Tailor the Material’s Final Performance
Authors: Guidotti Giulia , Soccio Michelina , Siracusa Valentina , Gazzano Massimo , Munari Andrea , Lotti Nadia
Published: August 2018

The present paper describes the synthesis of novel bio-based poly(butylene 1,4-cyclohexane dicarboxylate)-containing random copolymers for sustainable and flexible packaging applications. On one side, the linear butylene moiety has been substituted by glycol subunits with alkyl pendant groups of different length. On the other side, copolymers with different cis/trans isomer ratio of cyclohexane rings have been synthesized. The prepared samples were subjected to molecular, thermal, diffractometric, and mechanical characterization. The barrier performances to O2, CO2, and N2 gases were also evaluated. The presence of side alkyl groups did not alter the thermal stability, whereas it significantly influences the formation of ordered phases that deeply affect the functional properties, mainly in terms of mechanical response and barrier performance. In particular, the final materials present higher flexibility and significantly improved barrier properties with respect to the homopolymer and most polymers widely employed for flexible packaging. The improvement due to copolymerization was more pronounced in the case of higher co-unit-containing copolymers and for the samples with cyclohexane rings in the trans conformation.
Maleic Anhydride-Grafted Isotactic Polybutene-1 and Modified Polyamide 6
Authors: Zhao Yongxian , Ma Chen , Cheng Shijie , Xu Wei , Du Yuejuan , Bao Yansong , Xiao Zuojie
Published: August 2018

Maleic anhydride (MAH)–divinyl benzene (DVB) multi-monomer melt-grafting onto isotactic polybutene-1 (iPB-1) was carried out in a torque rheometer. The effects of dicumyl peroxide (DCP), MAH, and DVB concentrations, and temperature, on the reaction, were investigated. The optimized conditions were 170 °C, DVB/MAH = 4:6 (mass ratio). DVB as a comonomer enhanced the grafting degree (Gd) and grafting efficiency (Ge) of iPB-g-MAH better than styrene. The initiator DCP had little effect on Gd as its concentration over 0.2 phr, but the grafts’ melt flow rate (MFR) increased significantly, and relative molecular weight decreased remarkably with increased DCP concentration. With increasing Gd, the contact angle of grafts with water decreased, and there was a larger crystallization rate. The study of iPB-1 and iPB-g-MAH (Gd = 1.5%)-modified polyamide 6 (PA6) showed that iPB-g-MAH had an obviously toughening effect on PA6. With increasing iPB-g-MAH concentration, the blends of impact strength and elongation at break increased obviously, tensile strength decreased slightly, and MFR decreased prominently, which greatly slowed the processing degradation of PA6. The properties of iPB-1/PA6 blends deteriorated. Both DSC curves and SEM micrographs confirmed that PA6/iPB-g-MAH blends had much better compatibility than PA6/iPB. The reason was that the anhydride group in iPB-g-MAH reacted with amide group in PA6 to improve the compatibility between two phases, and iPB-g-MAH is an excellent modifier for PA6.
Synthesis of High Molar Mass Poly(phenylene methylene) Catalyzed by Tungsten(II) Compounds
Authors: Braendle Andreas , Vidovič Carina , Mösch-Zanetti Nadia C. , Niederberger Markus , Caseri Walter
Published: August 2018

Poly(phenylene methylene)s (PPMs) with high molar masses were isolated by polymerization of benzyl chloride catalyzed with tungsten(II) compounds and subsequent fractionation. Four different tungsten(II) catalysts were successfully exploited for the polymerization, for which a strict temperature profile was developed. The PPMs possessed roughly a trimodal molar mass distribution. Simple fractionation by phase separation of 2-butanone solutions allowed to effectively segregate the products primarily into PPM of low molar mass (Mn = 1600 g mol−1) and high molar mass (Mn = 167,900 g mol−1); the latter can be obtained in large quantities up to 50 g. The evolution of the trimodal distribution and the monomer conversion was monitored by gel permeation chromatography (GPC) and 1H NMR spectroscopy, respectively, over the course of the polymerization. The results revealed that polymerization proceeded via a chain-growth mechanism. This study illustrates a new approach to synthesize PPM with hitherto unknown high molar masses which opens the possibility to explore new applications, e.g., for temperature-resistant coatings, fluorescent coatings, barrier materials or optical materials.
Liberation through Seeing: Screening The Tibetan Book of the Dead
Authors: Donnelly Paul B.
Published: August 2018

The text known in English as The Tibetan Book of the Dead is arguably the principle source for popular understandings of Tibetan Buddhist conceptions of death. First translated into English in 1927, subsequent translations have read it according to a number of interpretive frameworks. This paper examines two recent films that take The Tibetan Book of the Dead as their inspiration: Bruce Joel Rubin’s Jacob’s Ladder (1990) and Gaspar Noé’s Enter the Void (2009). Neither of these films overtly claim to be depicting The Tibetan Book of the Dead, but the directors of both have acknowledged that the text was an influence on their films, and both are undeniably about the moment of death and what follows. The analysis begins with the question of how, and to what degree, each of the films departs from the meaning and purpose of The Tibetan Book of the Dead, before moving on to examine the reasons, both practical and ideological, for these changes. Buddhist writer Bruce Joel Rubin wrote a film that sought to depict the death experience from a Tibetan Buddhist perspective, but ultimately audience expectation and studio pressure transformed the film into a story at odds with Tibetan Buddhism. Gaspar Noé wrote and directed a film that is based on a secular worldview, yet can be seen to be largely consistent with a Tibetan Buddhist reading. Finally, I consider if, and to what extent, these films function to express or cultivate an experiential engagement with Tibetan Buddhist truths and realization, concluding that Jacob’s Ladder does not, while Enter the Void largely succeeds, despite the intention of its creator.
Towards Global-Scale Seagrass Mapping and Monitoring Using Sentinel-2 on Google Earth Engine: The Case Study of the Aegean and Ionian Seas
Authors: Traganos Dimosthenis , Aggarwal Bharat , Poursanidis Dimitris , Topouzelis Konstantinos , Chrysoulakis Nektarios , Reinartz Peter
Published: August 2018

Seagrasses are traversing the epoch of intense anthropogenic impacts that significantly decrease their coverage and invaluable ecosystem services, necessitating accurate and adaptable, global-scale mapping and monitoring solutions. Here, we combine the cloud computing power of Google Earth Engine with the freely available Copernicus Sentinel-2 multispectral image archive, image composition, and machine learning approaches to develop a methodological workflow for large-scale, high spatiotemporal mapping and monitoring of seagrass habitats. The present workflow can be easily tuned to space, time and data input; here, we show its potential, mapping 2510.1 km2 of P. oceanica seagrasses in an area of 40,951 km2 between 0 and 40 m of depth in the Aegean and Ionian Seas (Greek territorial waters) after applying support vector machines to a composite of 1045 Sentinel-2 tiles at 10-m resolution. The overall accuracy of P. oceanica seagrass habitats features an overall accuracy of 72% following validation by an independent field data set to reduce bias. We envision that the introduced flexible, time- and cost-efficient cloud-based chain will provide the crucial seasonal to interannual baseline mapping and monitoring of seagrass ecosystems in global scale, resolving gain and loss trends and assisting coastal conservation, management planning, and ultimately climate change mitigation.
Assisting Flood Disaster Response with Earth Observation Data and Products: A Critical Assessment
Authors: Schumann Guy , Brakenridge G. , Kettner Albert , Kashif Rashid , Niebuhr Emily
Published: August 2018

Floods are among the top-ranking natural disasters in terms of annual cost in insured and uninsured losses. Since high-impact events often cover spatial scales that are beyond traditional regional monitoring operations, remote sensing, in particular from satellites, presents an attractive approach. Since the 1970s, there have been many studies in the scientific literature about mapping and monitoring of floods using data from various sensors onboard different satellites. The field has now matured and hence there is a general consensus among space agencies, numerous organizations, scientists, and end-users to strengthen the support that satellite missions can offer, particularly in assisting flood disaster response activities. This has stimulated more research in this area, and significant progress has been achieved in recent years in fostering our understanding of the ways in which remote sensing can support flood monitoring and assist emergency response activities. This paper reviews the products and services that currently exist to deliver actionable information about an ongoing flood disaster to emergency response operations. It also critically discusses requirements, challenges and perspectives for improving operational assistance during flood disaster using satellite remote sensing products.
HOMPC: A Local Feature Descriptor Based on the Combination of Magnitude and Phase Congruency Information for Multi-Sensor Remote Sensing Images
Authors: Fu Zhitao , Qin Qianqing , Luo Bin , Sun Hong , Wu Chun
Published: August 2018

Local region description of multi-sensor images remains a challenging task in remote sensing image analysis and applications due to the non-linear radiation variations between images. This paper presents a novel descriptor based on the combination of the magnitude and phase congruency information of local regions to capture the common features of images with non-linear radiation changes. We first propose oriented phase congruency maps (PCMs) and oriented magnitude binary maps (MBMs) using the multi-oriented phase congruency and magnitude information of log-Gabor filters. The two feature vectors are then quickly constructed based on the convolved PCMs and MBMs. Finally, a dense descriptor named the histograms of oriented magnitude and phase congruency (HOMPC) is developed by combining the histograms of oriented phase congruency (HPC) and the histograms of oriented magnitude (HOM) to capture the structure and shape properties of local regions. HOMPC was evaluated with three datasets composed of multi-sensor remote sensing images obtained from unmanned ground vehicle, unmanned aerial vehicle, and satellite platforms. The descriptor performance was evaluated by recall, precision, F1-measure, and area under the precision-recall curve. The experimental results showed the advantages of the HOM and HPC combination and confirmed that HOMPC is far superior to the current state-of-the-art local feature descriptors.
Monitoring of an Indonesian Tropical Wetland by Machine Learning-Based Data Fusion of Passive and Active Microwave Sensors
Authors: Mizuochi Hiroki , Nishiyama Chikako , Ridwansyah Iwan , Nishida Nasahara Kenlo
Published: August 2018

In this study, a novel data fusion approach was used to monitor the water-body extent in a tropical wetland (Lake Sentarum, Indonesia). Monitoring is required in the region to support the conservation of water resources and biodiversity. The developed approach, random forest database unmixing (RFDBUX), makes use of pixel-based random forest regression to overcome the limitations of the existing lookup-table-based approach (DBUX). The RFDBUX approach with passive microwave data (AMSR2) and active microwave data (PALSAR-2) was used from 2012 to 2017 in order to obtain PALSAR-2-like images with a 100 m spatial resolution and three-day temporal resolution. In addition, a thresholding approach for the obtained PALSAR-2-like backscatter coefficient images provided water body extent maps. The validation revealed that the spatial patterns of the images predicted by RFDBUX are consistent with the original PALSAR-2 backscatter coefficient images (r = 0.94, RMSE = 1.04 in average), and that the temporal pattern of the predicted water body extent can track the wetland dynamics. The PALSAR-2-like images should be a useful basis for further investigation of the hydrological/climatological features of the site, and the proposed approach appears to have the potential for application in other tropical regions worldwide.
Detection of Methane Plumes Using Airborne Midwave Infrared (3–5 µm) Hyperspectral Data
Authors: Scafutto Rebecca Del’ Papa Moreira , De Souza Filho Carlos Roberto
Published: August 2018

Methane (CH4) display spectral features in several regions of the infrared range (0.75–14 µm), which can be used for the remote mapping of emission sources through the detection of CH4 plumes from natural seeps and leaks. Applications of hyperspectral remote sensing techniques for the detection of CH4 in the near and shortwave infrared (NIR-SWIR: 0.75–3 µm) and longwave infrared (LWIR: 7–14 µm) have been demonstrated in the literature with multiple sensors and scenarios. However, the acquisition and processing of hyperspectral data in the midwave infrared (MWIR: 3–5 µm) for this application is rather scarce. Here, a controlled field experiment was used to evaluate the potential for CH4 plume detection in the MWIR based on hyperspectral data acquired with the SEBASS airborne sensor. For comparison purposes, LWIR data were also acquired simultaneously with the same instrument. The experiment included surface and undersurface emission sources (ground stations), with flow rates ranging between 0.6–40 m3/h. The data collected in both ranges were sequentially processed using the same methodology. The CH4 plume was detected, variably, in both datasets. The gas plume was detected in all LWIR images acquired over nine gas leakage stations. In the MWIR range, the plume was detected in only four stations, wherein 18 m3/h was the lowest flux sensed. We demonstrate that the interference of target reflectance, the low contrast between plume and background and a low signal of the CH4 feature in the MWIR at ambient conditions possibly explain the inferior results observed for this range when compared to LWIR. Furthermore, we show that the acquisition time and weather conditions, including specific limits of temperature, humidity, and wind speed, proved critical for plume detection using daytime MWIR hyperspectral data.
Multiparametric Monitoring in Equatorian Tomato Greenhouses (III): Environmental Measurement Dynamics
Authors: Erazo-Rodas Mayra , Sandoval-Moreno Mary , Muñoz-Romero Sergio , Huerta Mónica , Rivas-Lalaleo David , Rojo-Álvarez José Luis
Published: August 2018

World population growth currently brings unequal access to food, whereas crop yields are not increasing at a similar rate, so that future food demand could be unmet. Many recent research works address the use of optimization techniques and technological resources on precision agriculture, especially in large demand crops, including climatic variables monitoring using wireless sensor networks (WSNs). However, few studies have focused on analyzing the dynamics of the environmental measurement properties in greenhouses. In the two companion papers, we describe the design and implementation of three WSNs with different technologies and topologies further scrutinizing their comparative performance, and a detailed analysis of their energy consumption dynamics is also presented, both considering tomato greenhouses in the Andean region of Ecuador. The three WSNs use ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The present study provides a systematic and detailed analysis of the environmental measurement dynamics from multiparametric monitoring in Ecuadorian tomato greenhouses. A set of monitored variables (including CO2, air temperature, and wind direction, among others) are first analyzed in terms of their intrinsic variability and their short-term (circadian) rhythmometric behavior. Then, their cross-information is scrutinized in terms of scatter representations and mutual information analysis. Based on Bland–Altman diagrams, good quality rhythmometric models were obtained at high-rate sampling signals during four days when using moderate regularization and preprocessing filtering with 100-coefficient order. Accordingly, and especially for the adjustment of fast transition variables, it is appropriate to use high sampling rates and then to filter the signal to discriminate against false peaks and noise. In addition, for variables with similar behavior, a longer period of data acquisition is required for the adequate processing, which makes more precise the long-term modeling of the environmental signals.
An X-band Bi-Directional Transmit/Receive Module for a Phased Array System in 65-nm CMOS
Authors: Nguyen Van-Viet , Nam Hyohyun , Choe Young Joe , Lee Bok-Hyung , Park Jung-Dong
Published: August 2018

We present an X-band bi-directional transmit/receive module (TRM) for a phased array system utilized in radar-based sensor systems. The proposed module, comprising a 6-bit phase shifter, a 6-bit digital step attenuator, and bi-directional gain amplifiers, is fabricated using 65-nm CMOS technology. By constructing passive networks in the phase-shifter and the variable attenuator, the implemented TRM provides amplitude and phase control with 360° phase coverage and 5.625° as the minimum step size while the attenuation range varies from 0 to 31.5 dB with a step size of 0.5 dB. The fabricated T/R module in all of the phase shift states had RMS phase errors of less than 4° and an RMS amplitude error of less than 0.93 dB at 9–11 GHz. The output 1dB gain compression point (OP1dB) of the chip was 5.13 dBm at 10 GHz. The circuit occupies 3.92 × 2.44 mm2 of the chip area and consumes 170 mW of DC power.
Evaluation of Water Indices for Surface Water Extraction in a Landsat 8 Scene of Nepal
Authors: Acharya Tri Dev , Subedi Anoj , Lee Dong Ha
Published: August 2018

Accurate and frequent updates of surface water have been made possible by remote sensing technology. Index methods are mostly used for surface water estimation which separates the water from the background based on a threshold value. Generally, the threshold is a fixed value, but can be challenging in the case of environmental noise, such as shadow, forest, built-up areas, snow, and clouds. One such challenging scene can be found in Nepal where no such evaluation has been done. Taking that in consideration, this study evaluates the performance of the most widely used water indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and Automated Water Extraction Index (AWEI) in a Landsat 8 scene of Nepal. The scene, ranging from 60 m to 8848 m, contains various types of water bodies found in Nepal with different forms of environmental noise. The evaluation was conducted based on measures from a confusion matrix derived using validation points. Comparing visually and quantitatively, not a single method was able to extract surface water in the entire scene with better accuracy. Upon selecting optimum thresholds, the overall accuracy (OA) and kappa coefficient (kappa) was improved, but not satisfactory. NDVI and NDWI showed better results for only pure water pixels, whereas MNDWI and AWEI were unable to reject snow cover and shadows. Combining NDVI with NDWI and AWEI with shadow improved the accuracy but inherited the NDWI and AWEI characteristics. Segmenting the test scene with elevations above and below 665 m, and using NDVI and NDWI for detecting water, resulted in an OA of 0.9638 and kappa of 0.8979. The accuracy can be further improved with a smaller interval of categorical characteristics in one or multiple scenes.
Fabric Phase Sorptive Extraction: Current State of the Art and Future Perspectives
Authors: Zilfidou Eirini , Kabir Abuzar , Furton Kenneth G. , Samanidou Victoria
Published: August 2018

Fabric phase sorptive extraction (FPSE) is a novel and green sample preparation technique introduced in 2014. FPSE utilizes a natural or synthetic permeable and flexible fabric substrate chemically coated with a sol-gel organic-inorganic hybrid sorbent in the form of ultra-thin coating, which leads to a fast and sensitive micro-extraction device. The flexible FPSE requires no modification of samples and allows direct extraction of analytes. Sol-gel sorbent-coated FPSE media possesses high chemical, solvent, and thermal stability due to the strong covalent bonding between the substrate and the sol-gel sorbent. Therefore, any elution solvent can be used in a small volume, which achieves a high pre-concentration factor without requiring any solvent evaporation and sample reconstitution step. Taking into consideration the complexity of the samples and the need of further minimization and automation, some new, alternative modes of the FPSE have also been developed. Therefore, FPSE has attracted the interest of the scientific community that deals with sample pre-treatment and has been successfully applied for the extraction and determination of many analytes in environmental samples as well as in food and biological samples. The objective of the current review is to present and classify the applications of FPSE according to different sample categories and to briefly show the progress, advantages, and the main principles of the proposed technique.
Banking Expansion and Income Growth in India
Authors: Anwar Mohd , Shaikh Imlak
Published: August 2018

In this article, we examine the impact of banking expansion on income growth in India. The banking expansion indices have been calculated across the region and states/Union Territories, providing the insight that all the regions, excluding the western region, are exhibiting banking expansion indices in the low range. The state-wise analysis indicates that all states exhibit a low-range index, excluding the state of Maharashtra and the UTs of Delhi and Chandigarh. Further, for the examination of the linkage between banking expansion and income growth, a panel data set was prepared for the 23 states/UTs over the period from 1990 to 2015. The panel data regression analysis approach was applied for the estimation of the regression model. It is apparent from the results that the banking expansion has significant and positive effects on credit disbursement. The results indicate that a one crore increase in deposit mobility causes 0.81 crores of increase in credit disbursement. Moreover, credit disbursement and deposit mobilization have a substantial and positive effect on the Net State Domestic Product. Moreover, a 1 percent increase in credit causes a 0.46 percent increase in NSDP, and a 1 percent increase in deposits causes a 0.57 percent increase in NSDP. Further, Net State Domestic Product has a significant and positive effect on the income of individuals. It is evident that a 1 percent increase in NSDP causes a 0.54 percent increase in per capita NSDP, while a 1 percent increase in capital expenditure causes a 0.13 percent increase in per capita NSDP.
The Sustainability of Romanian SMEs and Their Involvement in the Circular Economy
Authors: Oncioiu Ionica , Căpuşneanu Sorinel , Türkeș Mirela Cătălina , Topor Dan Ioan , Constantin Dana-Maria Oprea , Marin-Pantelescu Andreea , Ștefan Hint Mihaela
Published: August 2018

Sustainability involves extending the relational framework of SMEs outside the sphere of economic activity by justifying and legitimizing actions with a social impact on the environment. Links with the circular economy are achieved through the economic and environmental dimensions and through corporate social responsibility as a component of sustainable development. The main purpose of the paper was to determine the level of involvement of Romanian SMEs in activities related to the circular economy. The sample survey conducted among SME managers offered the advantage of collecting a large amount of direct information on the activities undertaken, the size of the investments and the nature of the funding sources used over the last five years. In this descriptive research, the process of setting up a representative sample of 384 enterprises was carried out by random sampling. The major contributions of the research project are to outline the contribution of Romanian SMEs to the development of a sustainable economy through their involvement in specific activities, the size of the investments made, and the level of participation of representatives of the enterprises in courses in order to identify new sources of financing and positive solutions in order to implement the principles of the circular economy.
Evaluating Greenhouse Tomato and Pepper Input Efficiency Use in Kosovo
Authors: Frangu Blend , Popp Jennie Sheerin , Thomsen Michael , Musliu Arben
Published: August 2018

Determinants of vegetable production input efficiency affect a Kosovar farmer’s decision to contribute to the agricultural sector. This study evaluates the input efficiency of greenhouse tomato and pepper farms in Kosovo. Using data collected from farm surveys, we conducted an input-oriented data envelopment analysis (DEA) to empirically assess input efficiency. Second, linear regression analysis was used to investigate what farm variables predict greenhouse tomato and pepper technical efficiency (TE). The DEA results indicated that, among the seven regions in Kosovo, Prizren emerged as the most efficient greenhouse tomato-producing region with a mean efficiency of 0.83 (on a scale of 0 to 1.00). Prishtina followed with a mean efficiency of 0.80. In the production of greenhouse peppers, Prishtina was the most efficient region with a mean efficiency of 0.99. Ferizaj followed with a mean efficiency of 0.93. Conclusions about farm characteristics that explain differences in efficiency were sensitive to model specification. Nevertheless, depending on the structural and operational characteristics of the greenhouse tomato and pepper farms, there is an opportunity for the technically inefficient farms and regions to improve their use of inputs.
Environmental Risk Management Strategies and the Moderating Role of Corporate Social Responsibility in Project Financing Decisions
Authors: Sarfraz Muddassar , Qun Wang , Hui Li , Abdullah Muhammad
Published: August 2018

The purpose of this study is to examine the moderating role of corporate social responsibility (CSR) in project financing decisions. CSR has gained growing prominence in today’s business era. This study investigates four environmental strategies and the credit risk assessment, stakeholder assessment and corporate social responsibility assessment impact on project financing decision. It explores three main issues related to environmental responsibility (planet), economic responsibility (profit) and social responsibility (people). The study is explanatory and quantitative, and both domestic and foreign banks participated in the data collection process. The sample size for the study is 491 participants. Data was collected through a simple random sampling technique and was analyzed by applying simple linear regression, confirmatory factor analysis (CFA) and structural equation modeling analysis (SEM) through the Statistical Package for the Social Sciences (SPSS). The study shows that the Pakistani banking sector is implementing environmental management policies. Foreign banks are more motivated towards corporate social responsibility practices. Cultural differences can influence a manager’s attitude towards implementation of environmental risk-management policies. The result shows that corporate social responsibility has a moderating role in project financing decisions and environmental risk management, stakeholder and credit risk assessment. All hypotheses has significant values.
Estimates of Daily PM2.5 Exposure in Beijing Using Spatio-Temporal Kriging Model
Authors: Lin Jinhuang , Zhang An , Chen Wenhui , Lin Mingshui
Published: August 2018

Excessive exposure to ambient (outdoor) air pollution may greatly increase the incidences of respiratory and cardiovascular diseases. Accurate reports of the spatial-temporal distribution characteristics of daily PM2.5 exposure can effectively prevent and reduce the harm caused to humans. Based on the daily average concentration data of PM2.5 in Beijing in May 2014 and the spatio-temporal kriging (STK) theory, we selected the optimal STK fitting model and compared the spatial-temporal prediction accuracy of PM2.5 using the STK method and ordinary kriging (OK) method. We also reveal the spatial-temporal distribution characteristics of the daily PM2.5 exposure in Beijing. The results show the following: (1) The fitting error of the Bilonick model (BM) model which is the smallest (0.00648), and the fitting effect of the prediction model of STK is the best for daily PM2.5 exposure. (2) The cross-examination results show that the STK model (RMSE = 8.90) has significantly lower fitting errors than the OK model (RMSE = 10.70), so its simulation prediction accuracy is higher. (3) According to the interpolation of the STK model, the daily exposure of PM2.5 in Beijing in May 2014 has good continuity in both time and space. The overall air quality is good, and overall the spatial distribution is low in the north and high in the south, with the highest concentration in the southwestern region. (4) There is a certain degree of spatial heterogeneity in the cumulative duration at the good, moderate, and polluted grades of China National Standard. The areas with the longest cumulative duration at the good, moderate and polluted grades are in the north, southeast, and southwest of the study area, respectively.
Exploring the Research Trend of Smart Factory with Topic Modeling
Authors: Yang Hyun-Lim , Chang Tai-Woo , Choi Yerim
Published: August 2018

Growing competition among manufacturing businesses and the advent of the Fourth Industrial Revolution has meant that many countries are conducting various research projects to understand how to introduce and populate smart factories. Smart factories are expected to provide a way of solving the manufacturing industries’ complex problems, to take a role in breakthroughs in factories and to carry on a sustainable business. Smart factories are currently in the introduction stage, so we should follow up on the majorities and check their tendencies. However, smart-factory research is an interdisciplinary field that should be studied by researchers with diverse backgrounds in various domains. Thus, studying the past and present overall research trends of smart factory studies is required for their successful introduction and sustainable research. In this study, we explored the research trends of smart factories in both international and specifically Korean research, as an example of a nation case, to determine the major research directions. We determined trends using latent semantic analysis, which is a known topic-modeling technique, and analyzed the trends with regression-based methods. As a result, we could read the clear trends by analyzing existing studies related to smart factories. In addition, it is possible to compare research trends in Korea and international research trends for the commonly appeared topics, such as ‘ICT’ (Information and Communications Technology) and ‘R&D (Research and Development)/Technology Innovation’. We expect that the quantitative analysis results and suggestions presented in this study can be used to formulate strategies for the future diffusion of smart factories.
How Does Project Supervisor Maintain Sustainability of Project Members? A Study from Leadership Perspective
Authors: Lei Han-Sheng , Lai Chuan-Fu , Chen Chih-Chang
Published: August 2018

Project members’ innovative behavior is crucial to their sustainability and successful implementation of the project. This research develops a conceptual model to explore the effect of project supervisor leadership skills on member’s innovative behavior. The model is examined by a sample of 437 project members in Taiwan. The results show that project supervisors’ emotional healing positively influences members’ innovative behavior through affect-based trust in their supervisor and supervisor conceptual skill has an inverted-U impact on members’ innovative behavior through cognition-based trust in their supervisor. This paper further discusses implications of these conclusions for additional research on the association between leadership skills and innovative behavior.
Structural Relationship and Influence between Open Innovation Capacities and Performances
Authors: Shin Kwangsoo , Kim Eungdo , Jeong EuiSeob
Published: August 2018

Previous studies related to open innovation have presented piecewise implications in relation to various knowledge management capacities. The study published by Lichtenthaler and Lichtenthaler in 2009 presented a model that combines the various open innovation capacities of firms in view of a mix of knowledge management, dynamic capability and absorptive capacity. Despite these efforts, there have been few empirical studies on the relationships among capacities, or between capacities and performance from an integrated perspective. Therefore, this study seeks to clarify the relationships among knowledge capacities and between knowledge capacities, technological innovation and financial performance at the firm level. Our findings are that the transformative, connective, inventive and absorptive capacities both directly and indirectly affects technological innovation performance; and innovative and desorptive capacities are the key factors connecting technological innovation to financial performance. This study provides managerial implications for the balanced development of the various knowledge capacities and the improvement of technological innovation and financial performance for firm knowledge managers.
Aspects Regarding the Pharmaceutical Waste Management in Romania
Authors: Bungau Simona , Tit Delia , Fodor Katalin , Cioca Gabriela , Agop Maricel , Iovan Ciprian , Cseppento Delia , Bumbu Adrian , Bustea Cristiana
Published: August 2018

The issue of drug disposal, as well as the development and implementation of efficient collection strategies, represents an important concern at the highest European level. This research looks into the factors that could have an impact on the efficiency of pharmacies in collecting and disposing the medicinal waste of the population. There were 521 pharmacists from all over the country who filled in a questionnaire on their opinion/attitude related to the system of collecting and disposing the pharmaceutical waste of the population. Of the surveyed pharmacists, 16% work in pharmacies that do not collect unused/expired drugs from the population, and nearly 33% of those investigated have refused, at least once, to take the unused medicines from the people. Pharmacists’ most important reasons for refusing to collect the pharmaceutical waste were the lack of procedure, incomplete legislation, exceeding the amount contracted with the operators, and high costs. Results show that pharmacies in Romania face several deficiencies in the pharmaceutical waste collection services. The lack of implemented programs has contributed considerably to lower standards of pharmaceutical waste management in Romania. This study is the first research on this topic in Romania, a country where the management of drug-based waste generated by the population is at the beginning. The results shown in this survey can provide a reference point for competent authorities in developing and implementing a take-back program for waste medicine whose efficiency is superior to the existing ones.
Enhanced Cooperation among Stakeholders in PPP Mega-Infrastructure Projects: A China Study
Authors: Li Long , Li Zhongfu , Jiang Lei , Wu Guangdong , Cheng Daojin
Published: August 2018

Despite the consensus that enhanced cooperation among stakeholders is critical to the successful delivery of public-private partnership (PPP) mega-infrastructure projects, there has been a limited utilization of the quantitative approach to explore the cooperation mechanism. Drawing on research and the actual practice of PPP projects in China, a quantitative mathematical model using evolutionary game theory is constructed to explore the internal cooperation mechanism. Numerical simulation is implemented to investigate the impact of the punitive mechanism and allocation mechanism on the enhanced cooperation. The simulation result indicates that reasonable benefit allocation and a strong punitive mechanism are crucial to enhanced cooperation. Action research supported by a case study in Dalian was conducted to verify the scientific practicalities of the simulation method. An enhanced cooperation framework was proposed. The role conversion of the government and the private sectors makes the enhanced cooperation feasible. This evolution model and cooperation framework can facilitate enhanced cooperation in PPP mega-infrastructure projects.
The Causal Nexus between Oil Prices, Interest Rates, and Unemployment in Norway Using Wavelet Methods
Authors: Kim Karlsson Hyunjoo , Li Yushu , Shukur Ghazi
Published: August 2018

This paper applies wavelet multi-resolution analysis (MRA), combined with two types of causality tests, to investigate causal relationships between three variables: real oil price, real interest rate, and unemployment in Norway. Impulse response functions were also utilised to examine effects of innovation in one variable on the other variables. We found that causal relations between the variables tend to be stronger as the wavelet time scale increases; specifically, there were no causal relationships between the variables at the lowest time scales of one to three months. A causal relationship between unemployment rate and interest rate was observed during the period of two quarters to two years, during which time a feedback mechanism was also detected between unemployment and interest rate. Causal relationships between oil price and both interest rate and unemployment were observed at the longest time scale of eight quarters. In conjunction with Granger causality analysis, impulse response functions showed that unemployment rates in Norway respond negatively to oil price shocks around two years after the shocks occur. As an oil exporting country, increases (or decreases) in oil prices reduce (or increase) unemployment in Norway under a time horizon of about two years; previous studies focused on oil importing economies have generally found the inverse to be true. Unlike most studies in this field, we decomposed the implicit aggregation for all time scales by applying MRA with a focus on the Norwegian economy. Thus, one main contribution of this paper is that we unveil and systematically distinguish the nature of the time-scale dependent relationship between real oil price, real interest rate, and unemployment using wavelet decomposition.
Hydropower Potential in the Periglacial Environment of Switzerland under Climate Change
Authors: Ehrbar Daniel , Schmocker Lukas , Vetsch David F. , Boes Robert M.
Published: August 2018

Hydropower is the most important domestic source of renewable energy in Switzerland. Many reservoirs are located in the periglacial environment of the Swiss Alps. Climate change and the changeover to a new energy system will challenge the existing infrastructure, but will also provide perspectives for new hydropower plants (HPPs). This study presents a framework for the systematic analysis of the hydropower potential of the periglacial Swiss Alps. The results are referenced to the Swiss Energy Strategy and other potential courses of action, such as upgrade of existing infrastructure. An evaluation matrix with 16 economical, environmental and social criteria for the consistent rating of all feasible sites is proposed. All criteria and their ratings are explained. It is demonstrated that the chosen methodology leads to a relatively stable ranking even for significantly different weighting models. Although being affected by uncertainties and remaining challenges, the methodology and results are sufficiently detailed for decision-making. Therefore, recommendations for future hydropower investments can be given. The results are strongly linked to Swiss boundary conditions, but the methodology itself is generally applicable for all glaciers worldwide, if the required input data are available.
A Definition and Theoretical Review of the Circular Economy, Value Creation, and Sustainable Business Models: Where Are We Now and Where Should Research Move in the Future?
Authors: Lahti Tom , Wincent Joakim , Parida Vinit
Published: August 2018

This paper contains a theory review of value creation and the implementation of next-generation sustainable business models to profit in the circular economy. While previous research has pointed to the influence of society and regulatory policy on companies’ ability to address larger sustainability concerns and to change their ways of working, the field suffers from little theoretical guidance outlining how undertake circular business mode transformation in practice. By reviewing the field’s main theories, we illustrate significant implications for how future research can study profitability and competitiveness in the circular economy. This paper introduces the central components of circular business models and discusses links to contingency theory, transaction cost theory, resource-based theory, theory on networks and industrial economics, and agency theory. Understanding the circular economy and the ways companies can compete in the circular economy based on these theories is important for establishing important new research directions for scholars of sustainable business and circular business models.
Development of a Magnetic Nanoparticles-Based Screen-Printed Electrodes (MNPs-SPEs) Biosensor for the Quantification of Ochratoxin A in Cereal and Feed Samples
Authors: Zhang Xian , Wang Zuohuan , Xie Hui , Sun Renjie , Cao Tong , Paudyal Narayan , Fang Weihuan , Song Houhui
Published: August 2018

A rapid and sensitive electrochemical biosensor based on magnetic nanoparticles and screen-printed electrodes (MNPs-SPEs sensor) was developed for the detection of ochratoxin A (OTA) in cereal and feed samples. Different types of magnetic nanoparticles-based ELISA (MNPs-ELISA) were optimized, and the signal detection, as well as sensitivity, was enhanced by the combined use of screen-printed electrodes (SPEs). Under the optimized conditions, the calibration curve of the MNPs-SPEs sensor was y = 0.3372x + 0.8324 (R2 = 0.9805). The linear range of detection and the detection limit were 0.01–0.82 ng/mL and 0.007 ng/mL, respectively. In addition, 50% inhibition (IC50) was detectable at 0.10 ng/mL. The limit of detection (LOD) of this MNPs-SPEs sensor in cereal and feed samples was 0.28 μg/kg. The recovery rates in spiked samples were between 78.7% and 113.5%, and the relative standard deviations (RSDs) were 3.6–9.8%, with the coefficient of variation lower than 15%. Parallel analysis of commercial samples (corn, wheat, and feedstuff) showed a good correlation between MNPs-SPEs sensor and liquid chromatography tandem mass spectrometry (LC/MS-MS). This new method provides a rapid, highly sensitive, and less time-consuming method to determine levels of ochratoxin A in cereal and feedstuff samples.
Biological Activities of Cationicity-Enhanced and Hydrophobicity-Optimized Analogues of an Antimicrobial Peptide, Dermaseptin-PS3, from the Skin Secretion of Phyllomedusa sauvagii
Authors: Tan Yining , Chen Xiaoling , Ma Chengbang , Xi Xinping , Wang Lei , Zhou Mei , Burrows James F. , Kwok Hang Fai , Chen Tianbao
Published: August 2018

The skin secretions of the subfamily Phyllomedusinae have long been known to contain a number of compounds with antimicrobial potential. Herein, a biosynthetic dermaseptin-precursor cDNA was obtained from a Phyllomedusa sauvagii skin secretion-derived cDNA library, and thereafter, the presence of the mature peptide, namely dermaseptin-PS3 (DPS3), was confirmed by LC–MS/MS. Moreover, this naturally occurring peptide was utilized to design two analogues, K5, 17-DPS3 (introducing two lysine residues at positions 5 and 17 to replace acidic amino acids) and L10, 11-DPS3 (replacing two neutral amino acids with the hydrophobic amino acid, leucine), improving its cationicity on the polar/unipolar face and hydrophobicity in a highly conserved sequence motif, respectively. The results in regard to the two analogues show that either increasing cationicity, or hydrophobicity, enhance the antimicrobial activity. Also, the latter analogue had an enhanced anticancer activity, with pretreatment of H157 cells with 1 µM L10, 11-DPS3 decreasing viability by approximately 78%, even though this concentration of peptide exhibited no haemolytic effect. However, it must be noted that in comparison to the initial peptide, both analogues demonstrate higher membrane-rupturing capacity towards mammalian red blood cells.
Towards a Better Understanding of Public Transportation Traffic: A Case Study of the Washington, DC Metro
Authors: Truong Robert , Gkountouna Olga , Pfoser Dieter , Züfle Andreas
Published: August 2018

The problem of traffic prediction is paramount in a plethora of applications, ranging from individual trip planning to urban planning. Existing work mainly focuses on traffic prediction on road networks. Yet, public transportation contributes a significant portion to overall human mobility and passenger volume. For example, the Washington, DC metro has on average 600,000 passengers on a weekday. In this work, we address the problem of modeling, classifying and predicting such passenger volume in public transportation systems. We study the case of the Washington, DC metro exploring fare card data, and specifically passenger in- and outflow at stations. To reduce dimensionality of the data, we apply principal component analysis to extract latent features for different stations and for different calendar days. Our unsupervised clustering results demonstrate that these latent features are highly discriminative. They allow us to derive different station types (residential, commercial, and mixed) and to effectively classify and identify the passenger flow of “unknown” stations. Finally, we also show that this classification can be applied to predict the passenger volume at stations. By learning latent features of stations for some time, we are able to predict the flow for the following hours. Extensive experimentation using a baseline neural network and two naïve periodicity approaches shows the considerable accuracy improvement when using the latent feature based approach.