bluuebunny/crossref_metadata_2025 huggingface dataset:
The Combined Effect of Promoting the Mediterranean Diet and Physical Activity on Metabolic Risk Factors in Adults: A Systematic Review and Meta-Analysis of Randomised Controlled Trials
Authors: Malakou Evangelia , Linardakis Manolis , Armstrong Miranda Elaine Glynis , Zannidi Dimitra , Foster Charlie , Johnson Laura , Papadaki Angeliki
Published: October 2018

Adhering to the Mediterranean diet (MD) and physical activity (PA) public health guidelines have independently been linked to health benefits in adults. These behaviours form essential components of the traditional Mediterranean lifestyle. However, their combined effect on metabolic risk has not been systematically assessed. This systematic review with meta-analysis (PROSPERO; CRD42017073958) aimed to examine, for the first time, the combined effect of promoting the MD and PA compared with no treatment, treatment with MD or PA alone, or a different dietary and/or PA treatment, and estimate its magnitude on metabolic risk factors. Medline, Embase, CINAHL and Web of Science were systematically searched until March 2018 for English language controlled interventions reporting the combined effects of the MD and PA on one or multiple metabolic risk factors in adults. Two researchers independently conducted data extraction and risk of bias assessment using a rigorous methodology. Reporting followed PRISMA guidelines. Quality of reporting and risk of bias were assessed using the CONSORT guidelines and the Cochrane Collaboration’s tool, respectively. Data from 12 articles reporting 11 randomised controlled trials (n = 1684) were included in the qualitative synthesis; across them, risk of bias was considered low, unclear and high for 42%, 25% and 33% of domains, respectively. Between-study heterogeneity ranged from 44% (triglycerides) to 98% (insulin and high density lipoprotein cholesterol (HDL)-cholesterol). Compared to a control condition, there was strong evidence (p < 0.001) of a beneficial effect of promoting the MD and PA on body weight (−3.68 kg, 95% CI (confidence intervals) −5.48, −1.89), body mass index (−0.64 kg/m2, 95% CI −1.10, −0.18), waist circumference (−1.62 cm, 95% CI −2.58, −0.66), systolic (−0.83 mmHg, 95% CI −1.57, −0.09) and diastolic blood pressure (−1.96 mmHg, 95% CI −2.57, −1.35), HOMA-IR index (−0.90, 95% CI −1.22, −0.58), blood glucose (−7.32 mg/dL, 95% CI −9.82, −4.82), triglycerides (−18.47 mg/dL, 95% CI −20.13, −16.80), total cholesterol (−6.30 mg/dL, 95% CI −9.59, −3.02) and HDL-cholesterol (+3.99 mg/dL, 95% CI 1.22, 6.77). There was no evidence of an effect on insulin concentrations. The data presented here provide systematically identified evidence that concurrently promoting the MD and PA is likely to provide an opportunity for metabolic risk reduction. However, due to the high degree of heterogeneity, most likely due to the variation in control group treatment, and the small number of included studies, findings from the pooled analysis should be interpreted with caution. These findings also highlight the need for high quality randomised controlled trials examining the combined effect of the MD and PA on metabolic risk.
Nutritional 1C Imbalance, B12 Tissue Accumulation, and Pregnancy Outcomes: An Experimental Study in Rats
Authors: Nymark Ole , Nexo Ebba , Greibe Eva
Published: October 2018

Vitamin B12 deficiency during pregnancy has been associated with poor fetal outcome. Here we investigate the influence of a one-carbon (1C) imbalanced diet (low B12, high folate, high methionine) on maternal B12 status, fetal outcome, B12 distribution, and on the 24-h distribution of synthetic cyano-B12 (CN-B12) and natural hydroxo-B12 (HO-B12). Female Wistar rats were mated while on a 1C balanced (n = 12) or imbalanced diet starting two weeks (n = 10) or four weeks (n = 9) prior to pregnancy and continuing throughout pregnancy. At gestation day 18 (out of 21), all rats received an oral dose of labeled CN-B12 or HO-B12. After 24 h, the rats were sacrificed. Fetuses were inspected, and maternal tissues and fetuses were measured for endogenous and labeled B12. Pregnancy caused a redistribution of B12 from the kidneys to the liver and fetal compartment (uterus, placenta, fetuses). The 1C imbalanced diet reduced maternal kidney B12 and gave rise to lower-weight fetuses with visual malformations. In contrast, fetal B12 did not reflect fetal outcome. This suggests that maternal B12 is more important for fetal outcome than fetal B12. The 24-h distribution of labeled B12 in the rats on the 1C imbalanced diet showed a higher fetal accumulation of CN-B12 than HO-B12, while the opposite was seen in the maternal tissues.
Reply: On the Reporting of Odds Ratios and Risk Ratios, Nutrients 2018, 10, 10
Authors: Ricci Elena , Noli Stefania , Cipriani Sonia , La Vecchia Irene , Chiaffarino Francesca , Ferrari Stefania , Mauri Paola , Reschini Marco , Fedele Luigi , Parazzini Fabio
Published: October 2018

In response to the letter of Pace and Multani, in general, we cannot disagree with their considerations about the use of odds ratios, risk ratios, and rate ratios. [...]
Selected Medicines Used in Iontophoresis
Authors: Karpiński Tomasz M.
Published: October 2018

Iontophoresis is a non-invasive method of systemic and local drug delivery using an electric field. Iontophoresis enables diffusion of the selected drug via skin, mucosa, enamel, dentin, and other tissues. The amount of delivered therapeutic molecules is about 10–2000 times greater than conventional forms of delivery. Among other fields, this method is used in dentistry, ophthalmology, otorhinolaryngology, and dermatology. According to related literature, the most important drugs studied or administered by iontophoresis are: Local anesthetics, opioids, steroids, non-steroidal anti-inflammatory drugs, antibacterial drugs, antifungal drugs, antiviral drugs, anticancer drugs, fluorides, and vitamins. The present review covers current available data regarding the selected medicines used in iontophoresis. Furthermore, indications and conditions of iontophoresis application are reviewed.
The Role of Combined Penetration Enhancers in Nasal Microspheres on In Vivo Drug Bioavailability
Authors: Rassu Giovanna , Ferraro Luca , Pavan Barbara , Giunchedi Paolo , Gavini Elisabetta , Dalpiaz Alessandro
Published: October 2018

Microspheres based on both methyl-β-cyclodextrins and chitosan were prepared by spray-drying as nasal formulations of a model polar drug to analyze, firstly, how the composition of the carrier affects drug permeation across synthetic membranes and, secondly, how it induces systemic or brain delivery of the drug. Microparticles with different weight ratios of the two penetration enhancers (10–90, 50–50, 90–10) were characterized with respect to morphology, size, structural composition, water uptake, and the in vitro drug permeation profile. The leader formulation (weight ratio of 50–50) was then nasally administered to rats; systemic and cerebrospinal fluid (CSF) drug concentrations were analyzed by high performance liquid chromatography (HPLC) over time. Microspheres obtained with a single enhancer, methyl-β-cyclodextrins or chitosan, were administered in vivo as a comparison. The in vitro properties of combined microspheres appeared modified with regard to the polymeric matrix ratio. In vivo results suggest that the optimal drug distribution between CSF and bloodstream can be easily obtained by varying the amount of these two penetration enhancers studied in the matrix of nasal microspheres.
Bioreactor Operating Strategies for Improved Polyhydroxyalkanoate (PHA) Productivity
Authors: Blunt Warren , Levin David B. , Cicek Nazim
Published: October 2018

Microbial polyhydroxyalkanoates (PHAs) are promising biodegradable polymers that may alleviate some of the environmental burden of petroleum-derived polymers. The requirements for carbon substrates and energy for bioreactor operations are major factors contributing to the high production costs and environmental impact of PHAs. Improving the process productivity is an important aspect of cost reduction, which has been attempted using a variety of fed-batch, continuous, and semi-continuous bioreactor systems, with variable results. The purpose of this review is to summarize the bioreactor operations targeting high PHA productivity using pure cultures. The highest volumetric PHA productivity was reported more than 20 years ago for poly(3-hydroxybutryate) (PHB) production from sucrose (5.1 g L−1 h−1). In the time since, similar results have not been achieved on a scale of more than 100 L. More recently, a number fed-batch and semi-continuous (cyclic) bioreactor operation strategies have reported reasonably high productivities (1 g L−1 h−1 to 2 g L−1 h−1) under more realistic conditions for pilot or industrial-scale production, including the utilization of lower-cost waste carbon substrates and atmospheric air as the aeration medium, as well as cultivation under non-sterile conditions. Little development has occurred in the area of fully continuously fed bioreactor systems over the last eight years.
High-Throughput Phenotyping of Crop Water Use Efficiency via Multispectral Drone Imagery and a Daily Soil Water Balance Model
Authors: Thorp Kelly R. , Thompson Alison L. , Harders Sara J. , French Andrew N. , Ward Richard W.
Published: October 2018

Improvement of crop water use efficiency (CWUE), defined as crop yield per volume of water used, is an important goal for both crop management and breeding. While many technologies have been developed for measuring crop water use in crop management studies, rarely have these techniques been applied at the scale of breeding plots. The objective was to develop a high-throughput methodology for quantifying water use in a cotton breeding trial at Maricopa, AZ, USA in 2016 and 2017, using evapotranspiration (ET) measurements from a co-located irrigation management trial to evaluate the approach. Approximately weekly overflights with an unmanned aerial system provided multispectral imagery from which plot-level fractional vegetation cover ( f c ) was computed. The f c data were used to drive a daily ET-based soil water balance model for seasonal crop water use quantification. A mixed model statistical analysis demonstrated that differences in ET and CWUE could be discriminated among eight cotton varieties ( p < 0 . 05 ), which were sown at two planting dates and managed with four irrigation levels. The results permitted breeders to identify cotton varieties with more favorable water use characteristics and higher CWUE, indicating that the methodology could become a useful tool for breeding selection.
Derivation of Three-Dimensional Displacement Vectors from Multi-Temporal Long-Range Terrestrial Laser Scanning at the Reissenschuh Landslide (Tyrol, Austria)
Authors: Pfeiffer Jan , Zieher Thomas , Bremer Magnus , Wichmann Volker , Rutzinger Martin
Published: October 2018

Deep-seated gravitational slope deformations (DSGSDs) endanger settlements and infrastructure in mountain areas all over the world. To prevent disastrous events, their activity needs to be continuously monitored. In this paper, the movement of the Reissenschuh DSGSD in the Schmirn valley (Tyrol, Austria) is quantified based on point clouds acquired with a Riegl VZ®-6000 long-range laser scanner in 2016 and 2017. Geomorphological features (e.g., block edges, terrain ridges, scarps) travelling on top of the landslide are extracted from the acquired point clouds using morphometric attributes based on locally computed eigenvectors and -values. The corresponding representations of the extracted features in the multi-temporal data are exploited to derive 3D displacement vectors based on a workflow exploiting the iterative closest point (ICP) algorithm. The subsequent analysis reveals spatial patterns of landslide movement with mean displacements in the order of 0.62 ma − 1 , corresponding well with measurements at characteristic points using a differential global navigation satellite system (DGNSS). The results are also compared to those derived from a modified version of the well-known image correlation (IMCORR) method using shaded reliefs of the derived digital terrain models. The applied extended ICP algorithm outperforms the raster-based method particularly in areas with predominantly vertical movement.
Identifying Collapsed Buildings Using Post-Earthquake Satellite Imagery and Convolutional Neural Networks: A Case Study of the 2010 Haiti Earthquake
Authors: Ji Min , Liu Lanfa , Buchroithner Manfred
Published: October 2018

Earthquake is one of the most devastating natural disasters that threaten human life. It is vital to retrieve the building damage status for planning rescue and reconstruction after an earthquake. In cases when the number of completely collapsed buildings is far less than intact or less-affected buildings (e.g., the 2010 Haiti earthquake), it is difficult for the classifier to learn the minority class samples, due to the imbalance learning problem. In this study, the convolutional neural network (CNN) was utilized to identify collapsed buildings from post-event satellite imagery with the proposed workflow. Producer accuracy (PA), user accuracy (UA), overall accuracy (OA), and Kappa were used as evaluation metrics. To overcome the imbalance problem, random over-sampling, random under-sampling, and cost-sensitive methods were tested on selected test A and test B regions. The results demonstrated that the building collapsed information can be retrieved by using post-event imagery. SqueezeNet performed well in classifying collapsed and non-collapsed buildings, and achieved an average OA of 78.6% for the two test regions. After balancing steps, the average Kappa value was improved from 41.6% to 44.8% with the cost-sensitive approach. Moreover, the cost-sensitive method showed a better performance on discriminating collapsed buildings, with a PA value of 51.2% for test A and 61.1% for test B. Therefore, a suitable balancing method should be considered when facing imbalance dataset to retrieve the distribution of collapsed buildings.
Application and Validation of a Model for Terrain Slope Estimation Using Space-Borne LiDAR Waveform Data
Authors: Yang Xuebo , Wang Cheng , Nie Sheng , Xi Xiaohuan , Hu Zhenyue , Qin Haiming
Published: October 2018

The terrain slope is one of the most important surface characteristics for quantifying the Earth surface processes. Space-borne LiDAR sensors have produced high-accuracy and large-area terrain measurement within the footprint. However, rigorous procedures are required to accurately estimate the terrain slope especially within the large footprint since the estimated slope is likely affected by footprint size, shape, orientation, and terrain aspect. Therefore, based on multiple available datasets, we explored the performance of a proposed terrain slope estimation model over several study sites and various footprint shapes. The terrain slopes were derived from the ICESAT/GLAS waveform data by the proposed method and five other methods in this study. Compared with five other methods, the proposed method considered the influence of footprint shape, orientation, and terrain aspect on the terrain slope estimation. Validation against the airborne LiDAR measurements showed that the proposed method performed better than five other methods (R2 = 0.829, increased by ~0.07, RMSE = 3.596°, reduced by ~0.6°, n = 858). In addition, more statistics indicated that the proposed method significantly improved the terrain slope estimation accuracy in high-relief region (RMSE = 5.180°, reduced by ~1.8°, n = 218) or in the footprint with a great eccentricity (RMSE = 3.421°, reduced by ~1.1°, n = 313). Therefore, from these experiments, we concluded that this terrain slope estimation approach was beneficial for different terrains and various footprint shapes in practice and the improvement of estimated accuracy was distinctly related with the terrain slope and footprint eccentricity.
More Than Meets the Eye: Using Sentinel-2 to Map Small Plantations in Complex Forest Landscapes
Authors: Nomura Keiko , Mitchard Edward T. A.
Published: October 2018

Many tropical forest landscapes are now complex mosaics of intact forests, recovering forests, tree crops, agroforestry, pasture, and crops. The small patch size of each land cover type contributes to making them difficult to separate using satellite remote sensing data. We used Sentinel-2 data to conduct supervised classifications covering seven classes, including oil palm, rubber, and betel nut plantations in Southern Myanmar, based on an extensive training dataset derived from expert interpretation of WorldView-3 and UAV data. We used a Random Forest classifier with all 13 Sentinel-2 bands, as well as vegetation and texture indices, over an area of 13,330 ha. The median overall accuracy of 1000 iterations was >95% (95.5%–96.0%) against independent test data, even though the tree crop classes appear visually very similar at a 20 m resolution. We conclude that the Sentinel-2 data, which are freely available with very frequent (five day) revisits, are able to differentiate these similar tree crop types. We suspect that this is due to the large number of spectral bands in Sentinel-2 data, indicating great potential for the wider application of Sentinel-2 data for the classification of small land parcels without needing to resort to object-based classification of higher resolution data.
Development of Sensor Registry System-Based Predictive Information Service Using a Grid
Authors: Jung Hyunjun , Jeong Dongwon , Lee Sukhoon
Published: October 2018

A sensor registry system (SRS) registers sensor metadata and provides them for a seamless semantic process. Recently, network coverage information-based SRS (NC-SRS) was developed to provide sensor information filtering by combining path prediction and network coverage checks. However, the NC-SRS has problems caused by issues such as termination of OpenSignal service and pre-building road segments. Therefore, this paper proposes a sensor registry system-based predictive information service (SRS-PIS) using a grid. SRS-PIS predicts a path based on the grid, checks the network coverage, and filters the sensor. This paper presents a grid-based real-time path prediction algorithm and an algorithm for grouping network service-disabled areas. To obtain network coverage information, we constructed and implemented a grid-based coverage map through experiment to measure the signal strength. As an evaluation, we compared features among SRS-based systems and SRS-PIS, and compared advantages and disadvantages between segment-based and grid-based methods.
Integration of Autonomous Wireless Sensor Networks in Academic School Gardens
Authors: Lopez-Iturri Peio , Celaya-Echarri Mikel , Azpilicueta Leyre , Aguirre Erik , Astrain José J. , Villadangos Jesús , Falcone Francisco
Published: October 2018

In this work, the combination of capabilities provided by Wireless Sensor Networks (WSN) with parameter observation in a school garden is employed in order to provide an environment for school garden integration as a complementary educational activity in primary schools. Wireless transceivers with energy harvesting capabilities are employed in order to provide autonomous system operation, combined with an ad-hoc implemented application called MySchoolGardenApp, based on a modular software architecture. The system enables direct parameter observation, data analysis and processing capabilities, which can be employed by students in a cloud based platform. Providing remote data access allows the adaptation of content to specific classroom/homework needs. The proposed monitoring WSN has been deployed in an orchard located in the schoolyard of a primary school, which has been built with EnOcean’s energy harvesting modules, providing an optimized node device as well network layout. For the assessment of the wireless link quality and the deployment of the modules, especially the central module which needs to receive directly the signals of all the sensor modules, simulation results obtained by an in-house developed 3D Ray Launching deterministic method have been used, providing coverage/capacity estimations applicable to the specific school environment case. Preliminary trials with MySchoolGardenApp have been performed, showing the feasibility of the proposed platform as an educational resource in schools, with application in specific natural science course content, development of technological skills and the extension of monitoring capabilities to new context-aware applications.
Leaf Segmentation on Dense Plant Point Clouds with Facet Region Growing
Authors: Li Dawei , Cao Yan , Tang Xue-song , Yan Siyuan , Cai Xin
Published: October 2018

Leaves account for the largest proportion of all organ areas for most kinds of plants, and are comprise the main part of the photosynthetically active material in a plant. Observation of individual leaves can help to recognize their growth status and measure complex phenotypic traits. Current image-based leaf segmentation methods have problems due to highly restricted species and vulnerability toward canopy occlusion. In this work, we propose an individual leaf segmentation approach for dense plant point clouds using facet over-segmentation and facet region growing. The approach can be divided into three steps: (1) point cloud pre-processing, (2) facet over-segmentation, and (3) facet region growing for individual leaf segmentation. The experimental results show that the proposed method is effective and efficient in segmenting individual leaves from 3D point clouds of greenhouse ornamentals such as Epipremnum aureum, Monstera deliciosa, and Calathea makoyana, and the average precision and recall are both above 90%. The results also reveal the wide applicability of the proposed methodology for point clouds scanned from different kinds of 3D imaging systems, such as stereo vision and Kinect v2. Moreover, our method is potentially applicable in a broad range of applications that aim at segmenting regular surfaces and objects from a point cloud.
Towards Human Activity Recognition: A Hierarchical Feature Selection Framework
Authors: Wang Aiguo , Chen Guilin , Wu Xi , Liu Li , An Ning , Chang Chih-Yung
Published: October 2018

The inherent complexity of human physical activities makes it difficult to accurately recognize activities with wearable sensors. To this end, this paper proposes a hierarchical activity recognition framework and two different feature selection methods to improve the recognition performance. Specifically, according to the characteristics of human activities, predefined activities of interest are organized into a hierarchical tree structure, where each internal node represents different groups of activities and each leaf node represents a specific activity label. Then, the proposed feature selection methods are appropriately integrated to optimize the feature space of each node. Finally, we train corresponding classifiers to distinguish different activity groups and to classify a new unseen sample into one of the leaf-nodes in a top-down fashion to predict its activity label. To evaluate the performance of the proposed framework and feature selection methods, we conduct extensive comparative experiments on publicly available datasets and analyze the model complexity. Experimental results show that the proposed method reduces the dimensionality of original feature space and contributes to enhancement of the overall recognition accuracy. In addition, for feature selection, returning multiple activity-specific feature subsets generally outperforms the case of returning a common subset of features for all activities.
Optical Fibre-Based Pulse Oximetry Sensor with Contact Force Detection
Authors: Liu Chong , Correia Ricardo , Ballaji Hattan , Korposh Serhiy , Hayes-Gill Barrie , Morgan Stephen
Published: October 2018

A novel optical sensor probe combining monitoring of blood oxygen saturation (SpO2) with contact pressure is presented. This is beneficial as contact pressure is known to affect SpO2 measurement. The sensor consists of three plastic optical fibres (POF) used to deliver and collect light for pulse oximetry, and a fibre Bragg grating (FBG) sensor to measure contact pressure. All optical fibres are housed in a biocompatible epoxy patch which serves two purposes: (i) to reduce motion artefacts in the photoplethysmogram (PPG), and (ii) to transduce transverse loading into an axial strain in the FBG. Test results show that using a combination of pressure measuring FBG with a reference FBG, reliable results are possible with low hysteresis which are relatively immune to the effects of temperature. The sensor is used to measure the SpO2 of ten volunteers under different contact pressures with perfusion and skewness indices applied to assess the quality of the PPG. The study revealed that the contact force ranging from 5 to 15 kPa provides errors of <2%. The combined probe has the potential to improve the reliability of reflectance oximeters. In particular, in wearable technology, the probe should find use in optimising the fitting of garments incorporating this technology.
Passive Harmonic RFID System for Buried Assets Localization
Authors: Abdelnour Abanob , Lazaro Antonio , Villarino Ramón , Kaddour Darine , Tedjini Smail , Girbau David
Published: October 2018

A passive harmonic tag for buried assets localization is presented for utility localization. The tag design is based on a dual-polarized patch antenna at Ultra High Frequency (UHF) band. One of its feeders is connected to a frequency doubler based on a Schottky diode that generates the second harmonic, which is transmitted using a linear-polarized patch tuned at this frequency. The power received at the other feeder of the dual-polarized antenna is harvested by an RF to DC converter based on a five-stage voltage multiplier whose energy is used to bias a low-power quartz oscillator that modulates the output of the doubler. The different parts of the system are presented, and the theoretical read range is estimated as a function of the soil composition and the water content. A low-cost reader based on a software defined radio is also presented. Finally, experiments with a prototype of the tag are performed for different soil conditions.
A Mathematical Model of a Piezo-Resistive Eight-Beam Three-Axis Accelerometer with Simulation and Experimental Validation
Authors: Song Jinlong , He Changde , Wang Renxin , Xue Chenyang , Zhang Wendong
Published: October 2018

A mathematical model of a sensor is vital to deeply comprehend its working principle and implement its optimal design. However, mathematical models of piezo-resistive eight-beam three-axis accelerometers have rarely been reported. Furthermore, those works are largely focused on the analysis of sensing acceleration in the normal direction, rather than in three directions. Therefore, a complete mathematical model of a piezo-resistive eight-beam three-axis accelerometer is developed in this paper. The validity of the mathematical model is proved by a Finite Element Method (FEM) simulation. Furthermore, the accelerometer is fabricated and tested. The prime sensitivities of X, Y and Z axes are 0.209 mV/g, 0.212 mV/g and 1.247 mV/g at 160 Hz, respectively, which is in accord with the values obtained by the model. The reason why the prime sensitivity SZZ is bigger than SXX and SYY is explained. Besides, it is also demonstrated why the cross-sensitivities SXZ and SYZ exceed SZX and SZY. Compared with the FEM model, the developed model could be helpful in evaluating the performance of three-axis accelerometers in an accurate and rapid way.
Explaining the Diffusion of Renewable Electricity Technologies in Canadian Remote Indigenous Communities through the Technological Innovation System Approach
Authors: Karanasios Konstantinos , Parker Paul
Published: October 2018

This paper applies the Technological Innovation System (TIS) approach for the first time in the context of remote indigenous communities in Northwest Territories (NWT) and Ontario, Canada, to explain the diffusion of Renewable Energy Technologies (RETs). These communities need reliable and sustainable electricity to address social, environmental and economic development issues. The study examines the diffusion of RETs during the 2000–2016 period, identifies the systemic and transformational failures responsible for the functional performance of the TISs, and generates insights about factors that have the potential to sustain the development of RET projects. Findings suggest that the TIS-proposed causal mechanisms were present and performed as expected. Since the accumulation of TIS functions influences the rate of deployment of renewable technologies, policy intervention to improve local learning and networking could lead to accelerated diffusion of RETs to the benefit of remote communities and other stakeholders.
The Influences of CSR’s Multi-Dimensional Characteristics on Firm Value Determination by a Fusion Approach
Authors: Hu Kuang-Hua , Lin Sin-Jin , Liu Jau-Yang , Chen Fu-Hsiang , Chen Shih-Han
Published: October 2018

Corporate social responsibility (CSR) implementation has been widely acknowledged as playing a key part in enhancing firm value as well as achieving sustainable development. However, up to now the extant works in the literature have yielded non-conclusive results regarding the relationships between CSR and firm value. One of the possible reasons is that the studies ignore the multi-dimensional characteristics of CSR—that is, they merely utilize a singular synthesized indicator as a proxy to represent the corporate’s CSR performance as being unreliable and problematic. Thus, this study breaks down CSR into numerous dimensions and further examines each dimension’s impact on firm value. By doing so, managers can allocate their firm’s valuable resources to suitable areas so as to increase its reputation and value. In addition, this research sets up an artificial intelligence (AI)-based fusion model, grounded by fusion learning theory that aims at complementing the error made by a singular model, to examine the relationship between CSR’s multidimensional characteristics and firm value. Through different combinations of adopted strategies, users can realize the most representative features from an over-abundant database.
Engineering Properties of Concrete with Waste Recycled Plastic: A Review
Authors: Babafemi Adewumi John , Šavija Branko , Paul Suvash Chandra , Anggraini Vivi
Published: October 2018

The abundance of waste plastic is a major issue for the sustainability of the environment as plastic pollutes rivers, land, and oceans. However, the versatile behavior of plastic (it is lightweight, flexible, strong, moisture-resistant, and cheap) can make it a replacement for or alternative to many existing composite materials like concrete. Over the past few decades, many researchers have used waste plastic as a replacement for aggregates in concrete. This paper presents a comprehensive review of the engineering properties of waste recycled plastic. It is divided into three sections, along with an introduction and conclusion. The influence of recycled waste plastics on the fresh properties of concrete is discussed first, followed by its influence on the mechanical and durability properties of concrete. Current experimental results have shown that the mechanical and durability properties of concrete are altered due to the inclusion of plastic. However, such concrete still fulfills the requirements of many engineering applications. This review also advocates further study of possible pre-treatment of waste plastic properties for the modification of its surface, shape, and size in order to improve the quality of the composite product and make its use more widespread.
Advancements in Passenger Processes at Airports from Aircraft Perspective
Authors: Schultz Michael , Schmidt Michael
Published: October 2018

We provide an overview about the research done in the field of airport and airline operations with a specific focus on a fast, reliable and sustainable passenger boarding. The reliable prediction operational processes along the aircraft air-ground trajectory demands a comprehensive consideration of economic, environmental, and handling constraints of airlines and airports. In particular, the critical process of passenger boarding is driven by passengers’ ability to follow the proposed boarding procedures and is not controlled by operational experts. In this paper we implement and compare two individual-based approaches which cover both specific passenger behavior during boarding and operational airline constraints. Both models used similar input values, but exhibit different magnitudes in the benefit evaluation. Furthermore, we demonstrate that there are still unused potentials to further improve boarding progress by using innovative infrastructural adaptations inside the aircraft cabin.
Experimental Investigation on Establishing the HCCI Process Fueled by N-Heptane in a Direct Injection Diesel Engine at Different Compression Ratios
Authors: Anh Tuan Le , Duy Vinh Nguyen , Thi Ha Khuong , Xa Hoi Nguyen
Published: October 2018

Establishing the homogeneous charge compression ignition (HCCI) process in a diesel engine, in order to improve exhaust emission quality while extending the HCCI regime, is one of the challenges in applying HCCI in worldwide applications. This can be done by decreasing the compression ratio, and controlling the exhaust gas recirculation (EGR) rate and charging temperature. In this paper, an original single cylinder diesel engine was converted to n-heptane-fueled HCCI with the fuel injected into the intake manifold. At the designed compression ratio of 20:1, the HCCI engine could operate stably at low speed (from 1600 rpm to 2000 rpm) and low load (10% to 20% load). In addition, reducing the compression ratio from 20:1 to 14.87:1 by changing the thickness of the cylinder head gasket and with no EGR applied extended the operating range to 50% load and 3200 rpm speed.
Fatty Acid Compositions of Selected Polish Pork Hams and Sausages as Influenced by Their Traditionality
Authors: Halagarda Michał , Kędzior Władysław , Pyrzyńska Ewa , Kudełka Wanda
Published: October 2018

Sausages and hams are perceived as important components of culinary heritage for many regions all over the world. Consumers believe that traditional foods are characterized by unique sensory properties and high quality. However, the fats found in all pork meat products are generally not associated with favorable dietary patterns. The aim of this study was to verify the possible differences regarding the composition of fatty acids between traditional Polish pork hams and wiejska sausages, and their conventional equivalents. For this purpose, the fat content and fatty acid profiles were determined. The research material consisted of 2 varieties of traditional hams and 5 varieties of sausages, as well as 4 varieties of both conventional hams and sausages. The results of this study demonstrated that traditional hams contained significantly higher percentage of C 20:3 (cis-11,14,17) acid than their conventional equivalents. Traditional sausages were characterized by lower shares of C 18:2 (cis-9,12) and Polyunsaturated Fatty Acids (PUFA), whereas higher content of C 18:1 (cis-9), C 18:3 (cis-9,12,15), C 20:0 and Monounsaturated Fatty Acids (MUFA). This resulted in significantly higher amounts of n-3 and lower of n-6 acids than in conventional sausages. All of the tested meat products were also characterized by an unfavorable n-6/n-3 ratio.
Chicken Raising in a Diverse Finnish Classroom: Multidimensional Sustainability Learning
Authors: Wolff Lili-Ann , Vuorenpää Sari , Sjöblom Pia
Published: October 2018

Social change requires new educational planning and sustainable teaching methods. Shaping an environment of care with animals as a part of the daily school life may produce such a change. In this article, we present a transdisciplinary study with the aim of exploring whether raising chickens in a classroom could promote learning, especially sustainability learning, and how. The study employs an ethnographic approach and we have analyzed the data according to interaction analysis. We collected the data in a culturally-diverse Finnish primary school class during May 2018. The data comprise field notes, videos and photographs from indoor and outdoor school activities; interviews and discussions with teachers and students; and, texts and artifacts that were made by students. The results show that having chickens in the classroom not only improved the students’ learning of biology, but also enhanced many other activities. The chicken project became part of a complex learning culture that met several of the aims of the curriculum and in many ways reached beyond the aim of merely learning science. The project became a natural part of sustainability education and promoted the acquisition of knowledge and skills in relation to the ecological and social dimensions of sustainability.
Factors Determining Desirability of Entrepreneurship in Romania
Authors: Păunescu Carmen , Popescu Mihaela Cornelia , Duennweber Matthias
Published: October 2018

Studies in entrepreneurship have identified that a positive entrepreneurial attitude and willingness to start a business influence future entrepreneurial intention. In the study of entrepreneurial intention, there is a growing interest in understanding the factors that determine desirability of entrepreneurship. Earlier studies have identified that there is a significant correlation between individuals’ perceived desirability of entrepreneurship and their entrepreneurial intention. This study addressed the question of what factors determine the desirability of entrepreneurship and how these different factors affect the desire to become an entrepreneur. We discussed the key determinants of the desirability of entrepreneurship in Romania. Using the Amway Global Entrepreneurship Report (AGER) dataset for 2016, we examined the desirability of entrepreneurship among Romanian respondents by considering multiple factors indicated by the theory as being significant predictors of entrepreneurship: feasibility, social stability, and comfort with acquiring customers, as well as socio-demographic factors such as age, gender, education, income level and working status. The results of our regression analysis demonstrate that social stability and feasibility have the most impact on the desirability of entrepreneurship. In addition, we document that comfort with acquiring customers is perceived as an important factor in increasing the desirability of entrepreneurship. These results suggest that a good understanding of individuals’ social environment and their need for skills and capabilities may lead to greater entrepreneurial efficacy, which is fundamental to sustaining economic growth. Future research should be grounded on testing if level of education, working status and income influence desirability of entrepreneurship as our existing data did not prove that it did.
Pro-Environmental Intentions among Food Festival Attendees: An Application of the Value-Belief-Norm Model
Authors: Kim Woo-Hyuk , Kim Kyung-Sook
Published: October 2018

Although festival organizers have significantly increased their adoption of green practices, there has been relatively little research on the pro-environmental decision-making process in festival settings. Drawing from the value-belief-norm-theory, the purpose of this study is to investigate the pro-environmental decision-making processes of attendees of eco-friendly food festivals. A structural analysis of responses collected from 601 surveys revealed that affective triggers and personal norms played critical roles in the development of respondents’ pro-environmental intentions in festival settings. This study provides discussions and implications for research and practices related to green festivals.
Public Capital and the Labor Income Share
Authors: Bom Pedro R. D. , Goti Aitor
Published: October 2018

The decline of the labor share of income over the last few decades has been documented for many developed economies. A declining labor share is associated with rising income inequality, which raises obvious economic and social concerns. Although several explanations for this fact have been provided in the literature, they usually rely on elastic substitution between private capital and labor, which is generally not supported by the empirical literature. We argue in this paper that the fall in the labor share is potentially associated with the decline in public investment ratios, which have also been observed in most developed economies in the last few decades. We use a calibrated small-scale macroeconomic model to show how a negative public investment shock can have a sizeable negative effect on the labor share. Two assumptions are key in this result: that public capital directly augments private capital in production and that the elasticity of substitution between private capital and labor is smaller than one. We argue that both assumptions are plausible in practice. Our results suggest that, to promote long-run sustainable and inclusive growth, governments should increase the fraction of output devoted to public investment.
Comprehensive Evaluation of Regional Sustainable Development Based on Data Envelopment Analysis
Authors: Li Zhijiang , Tang Decai , Han Mang , Bethel Brandon J.
Published: October 2018

In the light of the shortcomings of the analytic hierarchy process and other common regional sustainable development evaluation methods, this paper proposes the use of a combination of subjective and objective weights to generate input/output indicators using the Data Envelopment Analysis (DEA) method. Using this methodology, we construct a comprehensive evaluation index which is useful in expanding the application of Data Envelopment Analysis (DEA) in the comprehensive evaluation of sustainable development. Moreover, this paper addresses the shortfalls of the traditional DEA evaluation model and uses the Super-Slack Based Measure (SBM)-Undesirable and DEA-Malmquist evaluation models, which are based on traditional DEA model optimization, to analyze the spatio-temporal characteristics of sustainable development on regional scales. Using China’s Yangzte River Economic Belt as an example, an empirical analysis is carried out. We show that analysis results are virtually identical to the extant situation and can objectively reflect the status and abilities of sustainable development in each subregion. Additionally, from the angles of input, output and technological progress, this paper uses the DEA evaluation method to analyze the reasons behind the slow development in several provinces and municipalities along the Yangzte River Economic Belt (YERB). The regional characteristics of each province and city within our study are combined to explore the optimal mechanisms for sustainable development.
Spatio-Temporal Patterns and Determinants of Inter-Provincial Migration in China 1995–2015
Authors: Wu Rongwei , Yang Degang , Zhang Lu , Huo Jinwei
Published: October 2018

Inter-provincial migration causes dramatic changes in the population, as well as in the development of the social economy at both origin and destination, which is related to sustainable development in any country. Using inter-provincial migration data during the periods covering 1995–2000, 2000–2005, 2005–2010, and 2010–2015, we analyze the migration volume, intensity and flow, as well as its changes over time. We also examine the determinants associated with migration by applying Poisson pseudo-maximum-likelihood (PPML) estimation techniques. The results show that migrants move mainly from inland to coastal areas; however, since 2010, the number of migrants moving from coastal to inland areas has shown a continuous increase. This inter-provincial migration was driven largely by the influence of economic factors, such as high urban income per capita. A better model for the period of 2010–2015 is established by adopting an extended set of variables. New variables that represent regional disparities and industrial upgrades have a positive impact on inter-provincial migration, which shows that regional economic disparities and economic restructuring have played an important role in migration in recent years.
Construction Process Technical Impact Factors on Degradation of the External Thermal Insulation Composite System
Authors: Sulakatko Virgo , Vogdt Frank U.
Published: October 2018

The European climate strategy has encouraged the usage of the External Thermal Insulation Composite System (ETICS) to increase the energy efficiency of external building envelopes. This externally and relatively easily applicable façade solution must meet various technical requirements. This paper develops a technical severity evaluation model of on-site construction activities of ETICS to prioritize the risks of the construction process. The model can be used independently by any stakeholder of the construction process. The relevance of the activities is assessed with the Failure Mode Effects Analysis method. The model weights the impact of the essential technical requirements and simulates an integrated weighted technical severity value, which is derived from the analysis of experts’ judgments validated with the non-parametric Friedman’s test. The data collection for probability of occurrence and difficulty of detectability follows the Delphi technique to quantify the opinions of a group. The simulation, conducted on 103 degradation factors, shows that the on-site construction activities of ETICS strongly influence the decrease in the technical resilience of long-term durability, mechanical resistance, and stability, as well as the ability to bypass tensions. The highest risk is detected by the shortcomings in the layers of substrate, reinforcement, adhesive, and additional details.
Sustainable Financing for Sustainable Development: Understanding the Interrelations between Public Investment and Sovereign Debt
Authors: Ari Ibrahim , Koc Muammer
Published: October 2018

This study investigates the causal relationship between public investment and sovereign debt (i.e., external and domestic public debt) with respect to the limits of public-debt sustainability for four countries with the highest GDP (i.e., the United States, China, Japan, Germany) during the period of 2000–2015. In summary, this study establishes quantitative evidence based on empirical findings to support the claim that sovereign debt is harmful to the financing of public infrastructure if it breaches certain thresholds, as proposed in this study, and according to the literature. By this approach, the findings enable us to make recommendations about the need for mobilizing domestic resources and innovating new financial models to promote sustainable development within the limits of sustainable public debt. In short, this paper concludes that performing a project for sustainable development by implementing unsustainable financing models will always end up with unsustainable economic outcomes.