bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential of Silicon Amendment for Improved Wheat Production
Authors: Walsh Olga , Shafian Sanaz , McClintick-Chess Jordan , Belmont Kelli , Blanscet Steven
Published: March 2018

Many studies throughout the world have shown positive responses of various crops to silicon (Si) application in terms of plant health, nutrient uptake, yield, and quality. Although not considered an essential element for plant growth, Si has been recently recognized as a “beneficial substance” or “quasi-essential” due to its important role in plant nutrition, especially notable under stressed conditions. The goal of this study was to evaluate the effect of Si on wheat plant height, grain yield (GY), and grain protein content (GP). The experiment was conducted during two consecutive growing seasons in Idaho. A split-plot experimental design was used with three Si fertilization rates (140, 280, and 560 kg Si ha−1) corresponding to 100, 50, and 25% of manufacturer-recommended rates and two application times—at planting and tillering (Feekes 5). MontanaGrowTM (0-0-5) by MontanaGrow Inc. (Bonner, MT, USA) used in this study is a Si product sourced from a high-energy amorphous (non-crystalized) volcanic tuff. There was no significant effect of Si rate and application time on plant height, nutrient uptake, GY, or GP of irrigated winter wheat grown in non-stressed conditions. These results could be directly related to the Si fertilizer source used in the study. We are planning to further evaluate Si’s effect on growth and grain production of wheat grown in non-stressed vs. stressed conditions utilizing several different Si sources and application methods.
Identification of Leaf Promoters for Use in Transgenic Wheat
Authors: Alotaibi Saqer , Sparks Caroline , Parry Martin , Simkin Andrew , Raines Christine
Published: March 2018

Wheat yields have plateaued in recent years and given the growing global population there is a pressing need to develop higher yielding varieties to meet future demand. Genetic manipulation of photosynthesis in elite wheat varieties offers the opportunity to significantly increase yields. However, the absence of a well-defined molecular tool-box of promoters to manipulate leaf processes in wheat hinders advancements in this area. Two promoters, one driving the expression of sedoheptulose-1,7-bisphosphatase (SBPase) and the other fructose-1,6-bisphosphate aldolase (FBPA) from Brachypodium distachyon were identified and cloned into a vector in front of the GUS reporter gene. Both promoters were shown to be functionally active in wheat in both transient assays and in stably transformed wheat plants. Analysis of the stable transformants of wheat (cv. Cadenza) showed that both promoters controlled gus expression throughout leaf development as well as in other green tissues. The availability of these promoters provides new tools for the expression of genes in transgenic wheat leaves and also paves the way for multigene manipulation of photosynthesis to improve yields.
Internal and External Reinforcement of Concrete Members by Use of Shape Memory Alloy and Fiber Reinforced Polymers under Cyclic Loading—A Review
Authors: Parvin Azadeh , Raad Janet
Published: March 2018

This paper presents a review of recent studies on reinforced concrete (RC) structural components, such as beam-column joints (BCJs). These members are internally or externally reinforced with corrosion free shape memory alloy (SMA), fiber reinforced polymers (FRP), or a combination of the two materials. Bonded FRP sheets or near surface mounted (NSM) FRP bars are used in external strengthening cases. The use of FRP and SMA materials in RC structures can offer great potential benefits including lifetime cost saving, durability, safety, and post-earthquake serviceability for RC structures. Although FRP materials are well known for their corrosion resistance, high strength-to-weight ratios, ease of application, and constructability; SMA materials as reinforcement allow the structures to regain their original shape after the termination of the load without any permanent large residual deformation. In summary, the presented literature review provides an insight into the ongoing research on the use of these materials for retrofitting or strengthening of RC structural components and the trends for future research in this area. The cost and durability are also discussed.
Polymerization-Driven Immobilization of dc-APGD Synthesized Gold Nanoparticles into a Quaternary Ammonium-Based Hydrogel Resulting in a Polymeric Nanocomposite with Heat-Transfer Applications
Authors: Cyganowski Piotr , Dzimitrowicz Anna , Jamroz Piotr , Jermakowicz-Bartkowiak Dorota , Pohl Pawel
Published: March 2018

A new method for the production of nanocomposites, composed of gold nanoparticles (AuNPs) and (vinylbenzyl)trimethylammonium chloride-co-N,N-methylene bisacrylamide (VBTAC-co-MBA) hydrogel, is described. Raw-AuNPs of defined optical and granulometric properties were synthesized using direct current atmospheric pressure glow discharge (dc-APGD) generated in contact with a solution of HAuCl4. Different approaches to the polymerization-driven synthesis of Au/VBTAC-co-MBA nanocomposites were tested. It was established that homogenous dispersion of AuNPs in this new nanomaterial with was achieved in the presence of NaOH in the reaction mixture. The new nanocomposite was found to have excellent heat-transfer properties.
‘Better as a Buddhist’: An Interpretative Phenomenological Analysis of the Reflections on the Religious Beliefs of Buddhist Men Serving a Prison Sentence for a Sexual Offence
Authors: Bell Katie , Winder Belinda , Blagden Nicholas
Published: March 2018

This paper presents a qualitative analysis of the accounts offered by individuals (n = 7) convicted of a sexual offense who describe themselves as Buddhists. Data were collected through semi-structured interviews within a custodial environment and analyzed using interpretative phenomenological analysis (IPA). This paper presents the two superordinate themes that emerged from the data: (i) Better as a Buddhist and (ii) Ebb and Flow. Reflections and analysis from the Buddhist prison chaplain are integrated within the analysis of prisoner-participant data. Implications of the analysis are discussed with reference to interventions that use Buddhist principles, factors that underpin factors that help reduce reoffending and those that fit with the formation of a desistance narrative for religious individuals who have committed sexual offenses
TU1208 Open Database of Radargrams: The Dataset of the IFSTTAR Geophysical Test Site
Authors: Dérobert Xavier , Pajewski Lara
Published: March 2018

This paper aims to present a wide dataset of ground penetrating radar (GPR) profiles recorded on a full-size geophysical test site, in Nantes (France). The geophysical test site was conceived to reproduce objects and obstacles commonly met in the urban subsurface, in a completely controlled environment; since the design phase, the site was especially adapted to the context of radar-based techniques. After a detailed description of the test site and its building process, the GPR profiles included in the dataset are presented and commented on. Overall, 67 profiles were recorded along eleven parallel lines crossing the test site in the transverse direction; three pulsed radar systems were used to perform the measurements, manufactured by different producers and equipped with various antennas having central frequencies from 200 MHz to 900 MHz. An archive containing all profiles (raw data) is enclosed to this paper as supplementary material. This dataset is the core part of the Open Database of Radargrams initiative of COST (European Cooperation in Science and Technology) Action TU1208 “Civil engineering applications of Ground Penetrating Radar”. The idea beyond such initiative is to share with the scientific community a selection of interesting and reliable GPR responses, to enable an effective benchmark for direct and inverse electromagnetic approaches, imaging methods and signal processing algorithms. We hope that the dataset presented in this paper will be enriched by the contributions of further users in the future, who will visit the test site and acquire new data with their GPR systems. Moreover, we hope that the dataset will be made alive by researchers who will perform advanced analyses of the profiles, measure the electromagnetic characteristics of the host materials, contribute with synthetic radargrams obtained by modeling the site with electromagnetic simulators, and more in general share results achieved by applying their techniques on the available profiles.
PSPICE Hybrid Modeling and Simulation of Capacitive Micro-Gyroscopes
Authors: Su Yan , Tong Xin , Liu Nan , Han Guowei , Si Chaowei , Ning Jin , Li Zhaofeng , Yang Fuhua
Published: March 2018

With an aim to reduce the cost of prototype development, this paper establishes a PSPICE hybrid model for the simulation of capacitive microelectromechanical systems (MEMS) gyroscopes. This is achieved by modeling gyroscopes in different modules, then connecting them in accordance with the corresponding principle diagram. Systematic simulations of this model are implemented along with a consideration of details of MEMS gyroscopes, including a capacitance model without approximation, mechanical thermal noise, and the effect of ambient temperature. The temperature compensation scheme and optimization of interface circuits are achieved based on the hybrid closed-loop simulation of MEMS gyroscopes. The simulation results show that the final output voltage is proportional to the angular rate input, which verifies the validity of this model.
A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication
Authors: Yang Ching-Han , Chang Chin-Chun , Liang Deron
Published: March 2018

All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication—an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment—confirm the feasibility of this approach.
Alpha Particle Detection Using Alpha-Induced Air Radioluminescence: A Review and Future Prospects for Preliminary Radiological Characterisation for Nuclear Facilities Decommissioning
Authors: Crompton Anita , Gamage Kelum , Jenkins Alex , Taylor Charles
Published: March 2018

The United Kingdom (UK) has a significant legacy of nuclear installations to be decommissioned over the next 100 years and a thorough characterisation is required prior to the development of a detailed decommissioning plan. Alpha radiation detection is notoriously time consuming and difficult to carry out due to the short range of alpha particles in air. Long-range detection of alpha particles is therefore highly desirable and this has been attempted through the detection of secondary effects from alpha radiation, most notably the air-radioluminescence caused by ionisation. This paper evaluates alpha induced air radioluminescence detectors developed to date and looks at their potential to develop a stand-off, alpha radiation detector which can be used in the nuclear decommissioning field in daylight conditions to detect alpha contaminated materials.
Diagnosing a Strong-Fault Model by Conflict and Consistency
Authors: Zhang Wenfeng , Zhao Qi , Zhao Hongbo , Zhou Gan , Feng Wenquan
Published: March 2018

The diagnosis method for a weak-fault model with only normal behaviors of each component has evolved over decades. However, many systems now demand a strong-fault models, the fault modes of which have specific behaviors as well. It is difficult to diagnose a strong-fault model due to its non-monotonicity. Currently, diagnosis methods usually employ conflicts to isolate possible fault and the process can be expedited when some observed output is consistent with the model’s prediction where the consistency indicates probably normal components. This paper solves the problem of efficiently diagnosing a strong-fault model by proposing a novel Logic-based Truth Maintenance System (LTMS) with two search approaches based on conflict and consistency. At the beginning, the original a strong-fault model is encoded by Boolean variables and converted into Conjunctive Normal Form (CNF). Then the proposed LTMS is employed to reason over CNF and find multiple minimal conflicts and maximal consistencies when there exists fault. The search approaches offer the best candidate efficiency based on the reasoning result until the diagnosis results are obtained. The completeness, coverage, correctness and complexity of the proposals are analyzed theoretically to show their strength and weakness. Finally, the proposed approaches are demonstrated by applying them to a real-world domain—the heat control unit of a spacecraft—where the proposed methods are significantly better than best first and conflict directly with A* search methods.
Semi-Automated Air-Coupled Impact-Echo Method for Large-Scale Parkade Structure
Authors: Epp Tyler , Svecova Dagmar , Cha Young-Jin
Published: March 2018

Structural Health Monitoring (SHM) has moved to data-dense systems, utilizing numerous sensor types to monitor infrastructure, such as bridges and dams, more regularly. One of the issues faced in this endeavour is the scale of the inspected structures and the time it takes to carry out testing. Installing automated systems that can provide measurements in a timely manner is one way of overcoming these obstacles. This study proposes an Artificial Neural Network (ANN) application that determines intact and damaged locations from a small training sample of impact-echo data, using air-coupled microphones from a reinforced concrete beam in lab conditions and data collected from a field experiment in a parking garage. The impact-echo testing in the field is carried out in a semi-autonomous manner to expedite the front end of the in situ damage detection testing. The use of an ANN removes the need for a user-defined cutoff value for the classification of intact and damaged locations when a least-square distance approach is used. It is postulated that this may contribute significantly to testing time reduction when monitoring large-scale civil Reinforced Concrete (RC) structures.
A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique
Authors: Ardila-Rey Jorge , Montaña Johny , De Castro Bruno , Schurch Roger , Covolan Ulson José , Muhammad-Sukki Firdaus , Bani Nurul
Published: March 2018

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.
Statistical Platform for Individualized Behavioral Analyses Using Biophysical Micro-Movement Spikes
Authors: Torres Elizabeth , Vero Joe , Rai Richa
Published: March 2018

Wearable biosensors, such as those embedded in smart phones, can provide data to assess neuro-motor control in mobile settings, at homes, schools, workplaces and clinics. However, because most machine learning algorithms currently used to analyze such data require several steps that depend on human heuristics, the analyses become computationally expensive and rather subjective. Further, there is no standardized scale or set of tasks amenable to take advantage of such technology in ways that permit broad dissemination and reproducibility of results. Indeed, there is a critical need for fully objective automated analytical methods that easily handle the deluge of data these sensors output, while providing standardized scales amenable to apply across large sections of the population, to help promote personalized-mobile medicine. Here we use an open-access data set from Kaggle.com to illustrate the use of a new statistical platform and standardized data types applied to smart phone accelerometer and gyroscope data from 30 participants, performing six different activities. We report full distinction without confusion of the activities from the Kaggle set using a single parameter (linear acceleration or angular speed). We further extend the use of our platform to characterize data from commercially available smart shoes, using gait patterns within a set of experiments that probe nervous systems functioning and levels of motor control.
Tunable Nanosensor Based on Fano Resonances Created by Changing the Deviation Angle of the Metal Core in a Plasmonic Cavity
Authors: Wang Qiong , Ouyang Zhengbiao , Sun Yiling , Lin Mi , Liu Qiang , Zheng Guoliang , Fan Junxing
Published: March 2018

In this paper, a type of tunable plasmonic refractive index nanosensor based on Fano resonance is proposed and investigated. The sensor comprises a metal-insulator-metal (MIM) nanocavity with a center-deviated metal core and two side-coupled waveguides. By carefully adjusting the deviation angle and distance of the metal core in the cavity, Fano resonances can be obtained and modulated. The Fano resonances can be considered as results induced by the symmetry-breaking or geometric effect that affects the field distribution intensity at the coupling region between the right waveguide and the cavity. Such a field-distribution pattern change can be regarded as being caused by the interference between the waveguide modes and the cavity modes. The investigations demonstrate that the spectral positions and modulation depths of Fano resonances are highly sensitive to the deviation parameters. Furthermore, the figure of merit (FOM) value is calculated for different deviation angle. The result shows that this kind of tunable sensor has compact structure, high transmission, sharp Fano lineshape, and high sensitivity to the change in background refractive index. This work provides an effective method for flexibly tuning Fano resonance, which has wide applications in designing on-chip plasmonic nanosensors or other relevant devices, such as information modulators, optical filters, and ultra-fast switches.
Quantifying the Accuracy of Digital Hemispherical Photography for Leaf Area Index Estimates on Broad-Leaved Tree Species
Authors: Gilardelli Carlo , Orlando Francesca , Movedi Ermes , Confalonieri Roberto
Published: March 2018

Digital hemispherical photography (DHP) has been widely used to estimate leaf area index (LAI) in forestry. Despite the advancement in the processing of hemispherical images with dedicated tools, several steps are still manual and thus easily affected by user’s experience and sensibility. The purpose of this study was to quantify the impact of user’s subjectivity on DHP LAI estimates for broad-leaved woody canopies using the software Can-Eye. Following the ISO 5725 protocol, we quantified the repeatability and reproducibility of the method, thus defining its precision for a wide range of broad-leaved canopies markedly differing for their structure. To get a complete evaluation of the method accuracy, we also quantified its trueness using artificial canopy images with known canopy cover. Moreover, the effect of the segmentation method was analysed. The best results for precision (restrained limits of repeatability and reproducibility) were obtained for high LAI values (>5) with limits corresponding to a variation of 22% in the estimated LAI values. Poorer results were obtained for medium and low LAI values, with a variation of the estimated LAI values that exceeded the 40%. Regardless of the LAI range explored, satisfactory results were achieved for trees in row-structured plantations (limits almost equal to the 30% of the estimated LAI). Satisfactory results were achieved for trueness, regardless of the canopy structure. The paired t-test revealed that the effect of the segmentation method on LAI estimates was significant. Despite a non-negligible user effect, the accuracy metrics for DHP are consistent with those determined for other indirect methods for LAI estimates, confirming the overall reliability of DHP in broad-leaved woody canopies.
A Novel Model to Simulate Flexural Complements in Compliant Sensor Systems
Authors: Tang Hongyan , Zhang Dan , Guo Sheng , Qu Haibo
Published: March 2018

The main challenge in analyzing compliant sensor systems is how to calculate the large deformation of flexural complements. Our study proposes a new model that is called the spline pseudo-rigid-body model (spline PRBM). It combines dynamic spline and the pseudo-rigid-body model (PRBM) to simulate the flexural complements. The axial deformations of flexural complements are modeled by using dynamic spline. This makes it possible to consider the nonlinear compliance of the system using four control points. Three rigid rods connected by two revolute (R) pins with two torsion springs replace the three lines connecting the four control points. The kinematic behavior of the system is described using Lagrange equations. Both the optimization and the numerical fitting methods are used for resolving the characteristic parameters of the new model. An example is given of a compliant mechanism to modify the accuracy of the model. The spline PRBM is important in expanding the applications of the PRBM to the design and simulation of flexural force sensors.
Optimally Distributed Kalman Filtering with Data-Driven Communication
Authors: Dormann Katharina , Noack Benjamin , Hanebeck Uwe
Published: March 2018

For multisensor data fusion, distributed state estimation techniques that enable a local processing of sensor data are the means of choice in order to minimize storage and communication costs. In particular, a distributed implementation of the optimal Kalman filter has recently been developed. A significant disadvantage of this algorithm is that the fusion center needs access to each node so as to compute a consistent state estimate, which requires full communication each time an estimate is requested. In this article, different extensions of the optimally distributed Kalman filter are proposed that employ data-driven transmission schemes in order to reduce communication expenses. As a first relaxation of the full-rate communication scheme, it can be shown that each node only has to transmit every second time step without endangering consistency of the fusion result. Also, two data-driven algorithms are introduced that even allow for lower transmission rates, and bounds are derived to guarantee consistent fusion results. Simulations demonstrate that the data-driven distributed filtering schemes can outperform a centralized Kalman filter that requires each measurement to be sent to the center node.
Vehicle Mode and Driving Activity Detection Based on Analyzing Sensor Data of Smartphones
Authors: Lu Dang-Nhac , Nguyen Duc-Nhan , Nguyen Thi-Hau , Nguyen Ha-Nam
Published: March 2018

In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS), that is capable of detecting either the current vehicle mode or the current driving activity of travelers. Our proposed system is designed to be lightweight in computation and very fast in response to the changes of travelers’ vehicle modes or driving events. The vehicle mode detection module is responsible for recognizing both motorized vehicles, such as cars, buses, and motorbikes, and non-motorized ones, for instance, walking, and bikes. It relies only on accelerometer data in order to minimize the energy consumption of smartphones. By contrast, the driving activity detection module uses the data collected from the accelerometer, gyroscope, and magnetometer of a smartphone to detect various driving activities, i.e., stopping, going straight, turning left, and turning right. Furthermore, we propose a method to compute the optimized data window size and the optimized overlapping ratio for each vehicle mode and each driving event from the training datasets. The experimental results show that this strategy significantly increases the overall prediction accuracy. Additionally, numerous experiments are carried out to compare the impact of different feature sets (time domain features, frequency domain features, Hjorth features) as well as the impact of various classification algorithms (Random Forest, Naïve Bayes, Decision tree J48, K Nearest Neighbor, Support Vector Machine) contributing to the prediction accuracy. Our system achieves an average accuracy of 98.33% in detecting the vehicle modes and an average accuracy of 98.95% in recognizing the driving events of motorcyclists when using the Random Forest classifier and a feature set containing time domain features, frequency domain features, and Hjorth features. Moreover, on a public dataset of HTC company in New Taipei, Taiwan, our framework obtains the overall accuracy of 97.33% that is considerably higher than that of the state-of the art.
The Influence of Cross-Cultural Awareness and Tourist Experience on Authenticity, Tourist Satisfaction and Acculturation in World Cultural Heritage Sites of Korea
Authors: Zhang Hao , Cho Taeyoung , Wang Huanjiong , Ge Quansheng
Published: March 2018

This study aimed to identify the relationship among the following factors: cross-cultural awareness, tourist experience, authenticity, tourist satisfaction, and acculturation. It also sought to determine what role that tourist activities play in acculturation. Furthermore, this study looked to provide a feasibility plan for the effective management, protection, and sustainable development of World Cultural Heritage Sites. We chose Chinese in Korea (immigrants, workers, and international students) who visited the historic villages of Korea (Hahoe and Yangdong) as the research object, and used 430 questionnaires for analysis. The confirmatory factor analysis and structural equation model were used to verify proposed hypotheses. The results showed that (1) Chinese in Korea, who have higher cultural awareness, had more interests in objective authenticity (e.g., historical traditions, cultural heritage, and architecture) of world heritage sites; (2) Chinese in Korea could feel and appreciate the true value of traditional culture through tourist experience; (3) The objective authenticity and existential authenticity have a positive effect on tourist satisfaction; and, (4) Higher tourist satisfaction could effectively promote cultural integration and assimilation, and prevent cultural separation and marginalization.
Business Area Changes and Entrepreneurial Persistence in Ecology- and Food-Related Industries: Knowledge Heterogeneity and Emotion Perspectives
Authors: Chen Hongmin , Tsai Fu-Sheng , Ling Han-Chang
Published: March 2018

Entrepreneurs’ changes to different business areas can be viewed as shifts in entrepreneurial knowledge domains (e.g., from restaurant to food waste processing firm as an ecological helping business). From a sample of 73 representative entrepreneurs, we present a study of the impact of such area changes on the persistence of entrepreneurship (i.e., the degree an entrepreneur remains in entrepreneurial activities). Furthermore, two mediators, managerial experience and insecurity, and two moderators, positive and negative affect, were proposed and examined to make a more comprehensive theoretical inference of the relationship between area difference and persistence. The results revealed that, counter-intuitively, area difference was significantly and positively associated with entrepreneurial persistence. The mediation effects of managerial experience and psychological insecurity were also confirmed. However, only the moderation of positive affect was effective. Based on the knowledge heterogeneity and entrepreneurial emotion perspectives, academic and practical implications for inter-temporal dynamics of entrepreneurship are discussed.
Spatial Distribution Characteristics of Agritourism Consumption
Authors: Jiang Youxue , Wang Shujin
Published: March 2018

Agritourism is a newly developed type of tourism, which is significant in promoting the sustainable development of rural economies and ecological environments. The spatial distribution of agritourism consumption is an important basis on which to formulate an agritourism development plan. This paper introduces the concept of agritourism consumption, which is applied to develop a theoretical model of spatial distribution based on the analogy that the attraction to agritourism by urban residents is similar to the attraction among charges in physics. With this model, the spatial distribution characteristics of agritourism consumption are investigated under the superposition of multifield sources arising from metropolitan regions. The results indicate that the field strength of agritourism consumption is gradually attenuated with spatial distance. The trend that field strength under multifield sources varies with distance is generally similar to that under a single field source, but the decay rate under multifield sources tends to slow down slightly in different directions. Due to the superposition of multifield sources, the spatial distribution of field strength is no longer in a pattern of concentric circles, but an uneven distribution of contour lines. In addition, there is a positive correlation between field strength distribution and the consumption demand of agritourism.
Consumer Attitudes toward Sustainable Development and Risk to Brand Loyalty
Authors: Kuchinka Daniel , Balazs Szilvia , Gavriletea Marius , Djokic Borivoje-Boris
Published: March 2018

The present study reveals the importance of understanding how business decisions focused on sustainability can impact companies, due to the risks associated with brand loyalty. The relationship between brand loyalty and consumers’ environmental viewpoint is investigated, including how consumers’ brand loyalty would be impacted after environmental-based expansion decisions are announced. College students from the USA and Romania (N = 92) were asked to voluntarily participate in a survey. The Brand Loyalty Scale (BLS) is used to assess brand loyalty before and after a fictitious expansion announcement was made and the New Ecological Paradigm (NEP) scale is utilized to assess attitudes toward sustainability. A paired samples t-test analysis reveals a significant positive correlation between NEP scores (attitudes toward sustainability) and brand loyalty. No significant differences are found in attitudes toward sustainability regarding region (Romania and USA) or gender. These results indicate that individuals who generally show concern towards the environment will stay loyal to their favorite companies after sustainability is introduced. Results also indicate that the gap regarding region and gender is slowly closing in attitudes toward sustainability; individuals in developing countries are also showing a major concern toward environmental issues. Males indicate just as much concern toward the environment as females, which is confirmed by other findings in previous literature.
From Cascade to Bottom-Up Ecosystem Services Model: How Does Social Cohesion Emerge from Urban Agriculture?
Authors: Petit-Boix Anna , Apul Defne
Published: March 2018

Given the expansion of urban agriculture (UA), we need to understand how this system provides ecosystem services, including foundational societal needs such as social cohesion, i.e., people’s willingness to cooperate with one another. Although social cohesion in UA has been documented, there is no framework for its emergence and how it can be modeled within a sustainability framework. In this study, we address this literature gap by showing how the popular cascade ecosystem services model can be modified to include social structures. We then transform the cascade model into a bottom-up causal framework for UA. In this bottom-up framework, basic biophysical (e.g., land availability) and social (e.g., leadership) ecosystem structures and processes lead to human activities (e.g., learning) that can foster specific human attitudes and feelings (e.g., trust). These attitudes and feelings, when aggregated (e.g., social network), generate an ecosystem value of social cohesion. These cause-effect relationships can support the development of causality pathways in social life cycle assessment (S-LCA) and further our understanding of the mechanisms behind social impacts and benefits. The framework also supports UA studies by showing the sustainability of UA as an emergent food supplier in cities.
A Supervised Event-Based Non-Intrusive Load Monitoring for Non-Linear Appliances
Authors: Zheng Zhuang , Chen Hainan , Luo Xiaowei
Published: March 2018

Smart meters generate a massive volume of energy consumption data which can be analyzed to recover some interesting and beneficial information. Non-intrusive load monitoring (NILM) is one important application fostered by the mass deployment of smart meters. This paper presents a supervised event-based NILM approach for non-linear appliance activities identification. Firstly, the additive properties (stating that, when a certain amount of specific appliances’ feature is added to their belonging network, an equal amount of change in the network’s feature can be observed) of three features (harmonic feature, voltage–current trajectory feature, and active–reactive–distortion (PQD) power curve features) were investigated through experiments. The results verify the good additive property for the harmonic features and Voltage–Current (U-I) trajectory features. In contrast, PQD power curve features have a poor additive property. Secondly, based on the verified additive property of harmonic current features and the representation of waveforms, a harmonic current features based approach is proposed for NILM, which includes two main processes: event detection and event classification. For event detection, a novel model is proposed based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. Compared to other event detectors, the proposed event detector not only can detect both event timestamp and two adjacent steady states but also shows high detection accuracy over public dataset with F1-score up to 98.99%. Multi-layer perceptron (MLP) classifiers are then built for multi-class event classification using the harmonic current features and are trained using the data collected from the laboratory and the public dataset. The results show that the MLP classifiers have a good performance in classifying non-linear loads. Finally, the proposed harmonic current features based approach is tested in the laboratory through experiments, in which multiple on–off events of multiple appliances occur. The research indicates that clustering-based event detection algorithms are promising for future works in event-based NILM. Harmonic current features have perfect additive property, and MLP classifier using harmonic current features can accurately identify typical non-linear and resistive loads, which could be integrated with other approaches in the future.
Influence of Steel Plate Roughness on the Frictional Properties of Cereal Kernels
Authors: Kaliniewicz Zdzisław , Żuk Zbigniew , Krzysiak Zbigniew
Published: March 2018

The aim of this study was to determine the correlation between the external friction angle of cereal kernels and the roughness of a steel friction plate. The experiment was performed on the kernels of five principal cereals: wheat, rye, barley, oats, and triticale. Flat seed units composed of three spaced kernels joined by adhesive tape were analyzed in each experimental variant. The external friction angle of flat seed units was determined on nine steel friction plates with different roughness. Measurements were performed in three replications with a photosensor device which registered the external friction angle of cereal kernels. On friction plates with surface roughness Ra = 0.36 to Ra = 6.72, the average values of the angle of external friction ranged from 17.56° in rye kernels to 34.01° in oat kernels. The greatest similarities in the angle of external friction were observed between wheat and triticale kernels, whereas the greatest differences were noted between barley and oat kernels and between barley and triticale kernels. Friction plates made of ST3S steel should be characterized by the lowest surface roughness to minimize energy consumption during grain processing. The optimal surface roughness of steel friction plates was determined at Ra = 0.9.
Depopulation and the Aging Population: The Relationship in Italian Municipalities
Authors: Reynaud Cecilia , Miccoli Sara
Published: March 2018

In European countries, many territories have experienced and are still experiencing a depopulation, caused by a deficit of births relative to deaths, a negative net migration, or both. At the same time, many of these territories are also facing the population aging process, caused by a decrease in births and prolonged rise in longevity. Depopulation and the population aging processes are strongly connected. The aim of this work is to study the relationship between depopulation and the aging population and the sustainability of the two phenomena. We studied these phenomena in the Italian territories in the period of 1951–2011. The study was conducted by using the census data of the Italian municipalities. The correlation coefficient between depopulation and aging population indicators was calculated in order to investigate the relationship between the two phenomena. A regression model was applied in order to understand if population aging is linked to population variation. Finally, the municipalities, which experienced continuing depopulation, are examined in depth. Our results show that a strong depopulation trend contributed to subsequent levels of population aging, but recent population aging has also contributed to ongoing depopulation, creating a vicious circle. Long-term depopulation and continuing population aging does not seem to be sustainable in the near future.
Policies, Politics, and Paradigms: Healthy Planning in Australian Local Government
Authors: McCosker Anthony , Matan Anne , Marinova Dora
Published: March 2018

Local government in Australia is critically positioned to provide built environment initiatives that respond to the increasing prevalence of non-communicable diseases (NCD), climate change, and various other human and ecological health considerations. However, action on the ground has not been as widespread as might be expected, particularly in improving community health. This research explores the barriers to and enablers of the implementation of healthy planning and active living initiatives through in-depth interviews with healthy planning and active living advocates. Advocates are seen to promote healthy planning in relatively weak policy settings, where politicised, largely reactive decisions by individual politicians or practitioners are the main determinants of project success. The most important factor affecting project uptake and implementation is how the ‘problem’ of healthy planning, or what might be considered a healthy planning paradigm, is presented. Such a paradigm includes a strong reliance on the co-benefits of projects; it is also subject to the way that healthy planning is communicated and framed. Potential problems around such a setting are subsequently examined, identifying the potential reasons for the slow delivery of healthy planning.
Evolution of Rural Livelihood Strategies in a Remote Sino-Mongolian Border Area: A Cross-Country Analysis
Authors: Tsvegemed Munkhnasan , Shabier Alimu , Schlecht Eva , Jordan Greta , Wiehle Martin
Published: March 2018

Ecologically sound natural resources management is still the backbone of rural livelihoods in many regions of the world. The Altai-Dzungarian region between China and Mongolia constitutes an ideal site to study how political, economic, infrastructural, and cultural differences affect rural livelihoods. Structured semi-quantitative interviews were conducted with 483 households on both sides to characterise their current livelihood strategies and assess the importance of the various activities for the households’ current socio-economic situation by means of the categorical principal component and two-step cluster analysis. In total, four livelihood clusters were identified across both regions, whereby one cluster was only present in Mongolia. In general, all clusters mirrored the transition from almost pure pastoralist to agro-pastoralist livelihood strategies. While animal husbandry was more common in Mongolia and crop farming more common in China, most households in both countries pursued a rather mixed approach. The composition of the herds, as well as the richness and diversity of the livestock species, differed significantly between the countries and was generally higher in Mongolia. Supplementary feedstuff and pesticide and fertiliser use were higher in China, along with diversification of produces. Our analysis indicates that until very recently the livelihood strategies on both sides of the border were the same, manifesting in the fact that we can define three identical clusters across countries (environment factor) even though there are slight differences in land, livestock and asset endowment.
Multimedia System for Real-Time Photorealistic Nonground Modeling of 3D Dynamic Environment for Remote Control System
Authors: Chu Phuong , Cho Seoungjae , Sim Sungdae , Kwak Kiho , Cho Kyungeun
Published: March 2018

Nowadays, unmanned ground vehicles (UGVs) are widely used for many applications. UGVs have sensors including multi-channel laser sensors, two-dimensional (2D) cameras, Global Positioning System receivers, and inertial measurement units (GPS–IMU). Multi-channel laser sensors and 2D cameras are installed to collect information regarding the environment surrounding the vehicle. Moreover, the GPS–IMU system is used to determine the position, acceleration, and velocity of the vehicle. This paper proposes a fast and effective method for modeling nonground scenes using multiple types of sensor data captured through a remote-controlled robot. The multi-channel laser sensor returns a point cloud in each frame. We separated the point clouds into ground and nonground areas before modeling the three-dimensional (3D) scenes. The ground part was used to create a dynamic triangular mesh based on the height map and vehicle position. The modeling of nonground parts in dynamic environments including moving objects is more challenging than modeling of ground parts. In the first step, we applied our object segmentation algorithm to divide nonground points into separate objects. Next, an object tracking algorithm was implemented to detect dynamic objects. Subsequently, nonground objects other than large dynamic ones, such as cars, were separated into two groups: surface objects and non-surface objects. We employed colored particles to model the non-surface objects. To model the surface and large dynamic objects, we used two dynamic projection panels to generate 3D meshes. In addition, we applied two processes to optimize the modeling result. First, we removed any trace of the moving objects, and collected the points on the dynamic objects in previous frames. Next, these points were merged with the nonground points in the current frame. We also applied slide window and near point projection techniques to fill the holes in the meshes. Finally, we applied texture mapping using 2D images captured using three cameras installed in the front of the robot. The results of the experiments prove that our nonground modeling method can be used to model photorealistic and real-time 3D scenes around a remote-controlled robot.
Generalized Interval Neutrosophic Choquet Aggregation Operators and Their Applications
Authors: Li Xin , Zhang Xiaohong , Park Choonkil
Published: March 2018

The interval neutrosophic set (INS) is a subclass of the neutrosophic set (NS) and a generalization of the interval-valued intuitionistic fuzzy set (IVIFS), which can be used in real engineering and scientific applications. This paper aims at developing new generalized Choquet aggregation operators for INSs, including the generalized interval neutrosophic Choquet ordered averaging (G-INCOA) operator and generalized interval neutrosophic Choquet ordered geometric (G-INCOG) operator. The main advantages of the proposed operators can be described as follows: (i) during decision-making or analyzing process, the positive interaction, negative interaction or non-interaction among attributes can be considered by the G-INCOA and G-INCOG operators; (ii) each generalized Choquet aggregation operator presents a unique comprehensive framework for INSs, which comprises a bunch of existing interval neutrosophic aggregation operators; (iii) new multi-attribute decision making (MADM) approaches for INSs are established based on these operators, and decision makers may determine the value of λ by different MADM problems or their preferences, which makes the decision-making process more flexible; (iv) a new clustering algorithm for INSs are introduced based on the G-INCOA and G-INCOG operators, which proves that they have the potential to be applied to many new fields in the future.
1st German Phage Symposium—Conference Report
Authors: Huber Irene , Potapova Katerina , Kuhn Andreas , Schmidt Herbert , Hinrichs Jörg , Rohde Christine , Beyer Wolfgang
Published: March 2018

In Germany, phage research and application can be traced back to the beginning of the 20th century. However, with the triumphal march of antibiotics around the world, the significance of bacteriophages faded in most countries, and respective research mainly focused on fundamental questions and niche applications. After a century, we pay tribute to the overuse of antibiotics that led to multidrug resistance and calls for new strategies to combat pathogenic microbes. Against this background, bacteriophages came into the spotlight of researchers and practitioners again resulting in a fast growing “phage community”. In October 2017, part of this community met at the 1st German Phage Symposium to share their knowledge and experiences. The participants discussed open questions and challenges related to phage therapy and the application of phages in general. This report summarizes the presentations given, highlights the main points of the round table discussion and concludes with an outlook for the different aspects of phage application.