bluuebunny/crossref_metadata_2025 huggingface dataset:
Lovage (Levisticum officinale W.D.J. Koch) Roots: A Source of Bioactive Compounds towards a Circular Economy
Authors: Spréa Rafael Mascoloti , Fernandes Ângela , Finimundy Tiane C. , Pereira Carla , Alves Maria José , Calhelha Ricardo C. , Canan Cristiane , Barros Lillian , Amaral Joana S. , Ferreira Isabel C. F. R.
Published: June 2020

Lovage (Levisticum officinale W.D.J. Koch) is an aromatic plant from the Apiaceae (Umbelliferae) family used as a condiment in several regions of Europe and also described to have medicinal properties. While the aerial parts are used as foods, the roots are generally discarded. In the past, lovage roots were used in folk medicine for their diuretic, carminative, and spasmolytic properties. Therefore, the exploitation of this undervalued part of the plant can be a source of valuable bioactive compounds for food and/or pharmaceutical industries. Thus, in this study, extracts of different polarity were prepared and studied regarding their chemical composition and bioactive properties. To the best of our knowledge, the composition in phenolic compounds and the volatile profile of the n-hexane extract are reported for the first time. A total of 24 compounds were identified by GC-MS in the n-hexane extract, evidencing a high relative abundance of phthalides. A total of eight phenolic compounds were identified in lovage root extracts (decoction and hydroethanolic extract), with vanillic acid being the major compound. Regarding antioxidant activity, also reported for the first time, decoction and hydroethanolic extract exhibited a high antioxidant capacity in thiobarbituric acid reactive substances (TBARS) (179 ± 11 μg/mL) and in oxidative hemolysis (OxHLIA) assays (510 ± 6 μg/mL), respectively. n-Hexane extract showed relevant anti-proliferative activity against all tumor cell lines tested (GI50, 48–69 μg/mL), despite inhibiting also the growth of a non-tumoral hepatocyte cell line, however, presenting a significantly higher GI50 value (147 μg/mL). This study revealed that lovage root, an agri-food residue, can be a source of valuable bioactive compounds also presenting biological properties that deserve being explored, which could lead to a circular economy for food and/or the pharmaceutical industry.
Change Detection Based on the Coefficient of Variation in SAR Time-Series of Urban Areas
Authors: Colin Koeniguer Elise , Nicolas Jean-Marie
Published: June 2020

This paper discusses change detection in SAR time-series. First, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Subsequently, several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Furthermore, several criteria that are based on ratios of coefficients of variations are proposed to detect long events, such as construction test sites, or point-event, such as vehicles. These detection methods are first evaluated on theoretical statistical simulations to determine the scenarios where they can deliver the best results. The simulations demonstrate the greater sensitivity of the coefficient of variation to speckle mixtures, as in the case of agricultural plots. Conversely, they also demonstrate the greater specificity of the other criteria for the cases addressed: very short event or longer-term changes. Subsequently, detection performance is assessed on real data for different types of scenes and sensors (Sentinel-1, UAVSAR). In particular, a quantitative evaluation is performed with a comparison of our solutions with baseline methods. The proposed criteria achieve the best performance, with reduced computational complexity. On Sentinel-1 images containing mainly construction test sites, our best criterion reaches a probability of change detection of 90% for a false alarm rate that is equal to 5%. On UAVSAR images containing boats, the criteria proposed for short events achieve a probability of detection equal to 90% of all pixels belonging to the boats, for a false alarm rate that is equal to 2%.
Variability and Uncertainty of Satellite Sea Surface Salinity in the Subpolar North Atlantic (2010–2019)
Authors: Yu Lisan
Published: June 2020

Satellite remote sensing of sea surface salinity (SSS) in the recent decade (2010–2019) has proven the capability of L-band (1.4 GHz) measurements to resolve SSS spatiotemporal variability in the tropical and subtropical oceans. However, the fidelity of SSS retrievals in cold waters at mid-high latitudes has yet to be established. Here, four SSS products derived from two satellite missions were evaluated in the subpolar North Atlantic Ocean in reference to two in situ gridded products. Harmonic analysis of annual and semiannual cycles in in situ products revealed that seasonal variations of SSS are dominated by an annual cycle, with a maximum in March and a minimum in September. The annual amplitudes are larger (>0.3 practical salinity scale (pss)) in the western basin where surface waters are colder and fresher, and weaker (~0.06 pss) in the eastern basin where surface waters are warmer and saltier. Satellite SSS products have difficulty producing the right annual cycle, particularly in the Labrador/Irminger seas where the SSS seasonality is dictated by the influx of Arctic low-salinity waters along the boundary currents. The study also found that there are basin-scale, time-varying drifts in the decade-long SMOS data records, which need to be corrected before the datasets can be used for studying climate variability of SSS.
Falling Mixed-Phase Ice Virga and their Liquid Parent Cloud Layers as Observed by Ground-Based Lidars
Authors: Cheng Chong , Yi Fan
Published: June 2020

Falling mixed-phase virga from a thin supercooled liquid layer cloud base were observed on 20 occasions at altitudes of 2.3–9.4 km with ground-based lidars at Wuhan (30.5 °N, 114.4 °E), China. Polarization lidar profile (3.75-m) analysis reveals some ubiquitous features of both falling mixed-phase virga and their liquid parent cloud layers. Each liquid parent cloud had a well-defined base height where the backscatter ratio R was ~7.0 and the R profile had a clear inflection point. At an altitude of ~34 m above the base height, the depolarization ratio reached its minimum value (~0.04), indicating a liquid-only level therein. The thin parent cloud layers tended to form on the top of a broad preexisting aerosol/liquid water layer. The falling virga below the base height showed firstly a significant depolarization ratio increase, suggesting that most supercooled liquid drops in the virga were rapidly frozen into ice crystals (via contact freezing). After reaching a local maximum value of the depolarization ratio, both the values of the backscatter ratio and depolarization ratio for the virga exhibited an overall decrease with decreasing height, indicating sublimated ice crystals. The diameters of the ice crystals in the virga were estimated based on an ice particle sublimation model along with the lidar and radiosonde observations. It was found that the ice crystal particles in these virga cases tended to have smaller mean diameters and narrower size distributions with increasing altitude. The mean diameter value is 350 ± 111 µm at altitudes of 4–8.5 km.
Comparison of Different Cropland Classification Methods under Diversified Agroecological Conditions in the Zambezi River Basin
Authors: Bofana José , Zhang Miao , Nabil Mohsen , Wu Bingfang , Tian Fuyou , Liu Wenjun , Zeng Hongwei , Zhang Ning , Nangombe Shingirai S. , Cipriano Sueco A. , Phiri Elijah , Mushore Terence Darlington , Kaluba Peter , Mashonjowa Emmanuel , Moyo Chrispin
Published: June 2020

Having updated knowledge of cropland extent is essential for crop monitoring and food security early warning. Previous research has proposed different methods and adopted various datasets for mapping cropland areas at regional to global scales. However, most approaches did not consider the characteristics of farming systems and apply the same classification method in different agroecological zones (AEZs). Furthermore, the acquisition of in situ samples for classification training remains challenging. To address these knowledge gaps and challenges, this study applied a zone-specific classification by comparing four classifiers (random forest, the support vector machine (SVM), the classification and regression tree (CART) and minimum distance) for cropland mapping over four different AEZs in the Zambezi River basin (ZRB). Landsat-8 and Sentinel-2 data and derived indices were used and synthesized to generate thirty-five layers for classification on the Google Earth Engine platform. Training samples were derived from three existing landcover datasets to minimize the cost of sample acquisitions over the large area. The final cropland map was generated at a 10 m resolution. The performance of the four classifiers and the viability of training samples were analysed. All classifiers presented higher accuracy in cool AEZs than in warm AEZs, which may be attributed to field size and lower confusion between cropland and grassland classes. This indicates that agricultural landscape may impact classification results regardless of the classifiers. Random forest was found to be the most stable and accurate classifier across different agricultural systems, with an overall accuracy of 84% and a kappa coefficient of 0.67. Samples extracted over the full agreement areas among existing datasets reduced uncertainty and provided reliable calibration sets as a replacement of costly in situ measurements. The methodology proposed by this study can be used to generate periodical high-resolution cropland maps in ZRB, which is helpful for the analysis of cropland extension and abandonment as well as intensity changes in response to the escalating population and food insecurity.
Satellite-Based Drought Impact Assessment on Rice Yield in Thailand with SIMRIW−RS
Authors: Raksapatcharawong Mongkol , Veerakachen Watcharee , Homma Koki , Maki Masayasu , Oki Kazuo
Published: June 2020

Advances in remote sensing technologies have enabled effective drought monitoring globally, even in data-limited areas. However, the negative impact of drought on crop yields still necessitates stakeholders to make informed decisions according to its severity. This research proposes an algorithm to combine a drought monitoring model, based on rainfall, land surface temperature (LST), and normalized difference vegetation index/leaf area index (NDVI/LAI) satellite products, with a crop simulation model to assess drought impact on rice yields in Thailand. Typical crop simulation models can provide yield information, but the requirement for a complicated set of inputs prohibits their potential due to insufficient data. This work utilizes a rice crop simulation model called the Simulation Model for Use with Remote Sensing (SIMRIW–RS), whose inputs can mostly be satisfied by such satellite products. Based on experimental data collected during the 2018/19 crop seasons, this approach can successfully provide a drought monitoring function as well as effectively estimate the rice yield with mean absolute percentage error (MAPE) around 5%. In addition, we show that SIMRIW–RS can reasonably predict the rice yield when historical weather data is available. In effect, this research contributes a methodology to assess the drought impact on rice yields on a farm to regional scale, relevant to crop insurance and adaptation schemes to mitigate climate change.
Performance Analysis of Cooperative and Non-Cooperative Relaying over VLC Channels
Authors: Gheth Waled , Rabie Khaled M. , Adebisi Bamidele , Ijaz Muhammad , Harris Georgina
Published: June 2020

The line-of-sight (LoS) channel is one of the requirements for efficient data transmission in visible-light communications (VLC), but this cannot always be guaranteed in indoor applications for a variety of reasons, such as moving objects and the layout of rooms. The relay-assisted VLC system is one of the techniques that can be used to address this issue and ensures seamless connectivity. This paper investigates the performance of half-duplex (HD) conventional DF relay system and cooperative systems (i.e., selective DF (SDF) and incremental DF (IDF)) over VLC channels in terms of outage probability and energy consumption. Analytical expressions for both outage probability and the minimum energy-per-bit performance of the aforementioned relaying systems are derived. Furthermore, Monte Carlo simulations are provided throughout the paper to validate the derived expressions. The results show that exploiting SDF and IDF relaying schemes can achieve approximately 25% and 15% outage probability enhancement compared to single-hop and DF protocols, respectively. The results also demonstrate that the performance of the single-hop VLC system deteriorates when the end-to-end distances become larger. For example, when the vertical distance is 3.5m, the single-hop approach consumes 20%, 40% and 45% more energy in comparison to the DF, SDF, and IDF approaches, respectively.
Fault Detection, Isolation, Identification and Recovery (FDIIR) Methods for Automotive Perception Sensors Including a Detailed Literature Survey for Lidar
Authors: Goelles Thomas , Schlager Birgit , Muckenhuber Stefan
Published: June 2020

Perception sensors such as camera, radar, and lidar have gained considerable popularity in the automotive industry in recent years. In order to reach the next step towards automated driving it is necessary to implement fault diagnosis systems together with suitable mitigation solutions in automotive perception sensors. This is a crucial prerequisite, since the quality of an automated driving function strongly depends on the reliability of the perception data, especially under adverse conditions. This publication presents a systematic review on faults and suitable detection and recovery methods for automotive perception sensors and suggests a corresponding classification schema. A systematic literature analysis has been performed with focus on lidar in order to review the state-of-the-art and identify promising research opportunities. Faults related to adverse weather conditions have been studied the most, but often without providing suitable recovery methods. Issues related to sensor attachment and mechanical damage of the sensor cover were studied very little and provide opportunities for future research. Algorithms, which use the data stream of a single sensor, proofed to be a viable solution for both fault detection and recovery.
Long-Term Tracking of Group-Housed Livestock Using Keypoint Detection and MAP Estimation for Individual Animal Identification
Authors: T. Psota Eric , Schmidt Ty , Mote Benny , C. Pérez Lance
Published: June 2020

Tracking individual animals in a group setting is a exigent task for computer vision and animal science researchers. When the objective is months of uninterrupted tracking and the targeted animals lack discernible differences in their physical characteristics, this task introduces significant challenges. To address these challenges, a probabilistic tracking-by-detection method is proposed. The tracking method uses, as input, visible keypoints of individual animals provided by a fully-convolutional detector. Individual animals are also equipped with ear tags that are used by a classification network to assign unique identification to instances. The fixed cardinality of the targets is leveraged to create a continuous set of tracks and the forward-backward algorithm is used to assign ear-tag identification probabilities to each detected instance. Tracking achieves real-time performance on consumer-grade hardware, in part because it does not rely on complex, costly, graph-based optimizations. A publicly available, human-annotated dataset is introduced to evaluate tracking performance. This dataset contains 15 half-hour long videos of pigs with various ages/sizes, facility environments, and activity levels. Results demonstrate that the proposed method achieves an average precision and recall greater than 95% across the entire dataset. Analysis of the error events reveals environmental conditions and social interactions that are most likely to cause errors in real-world deployments.
Three Dimensional Upper Limb Joint Kinetics of a Golf Swing with Measured Internal Grip Force
Authors: Choi Hyeob , Park Sukyung
Published: June 2020

The biomechanics of a golf swing have been of interest to golfers, instructors, and biomechanists. In addition to the complexity of the three-dimensional (3D) dynamics of multi-segments of body, the closed-chain body posture as a result of both hands holding a club together makes it difficult to fully analyze the 3D kinetics of a golf swing. To identify the hand-grip joint force and torque applied by each hand, we directly measured the 3D internal grip force of nine registered professional golfers using an instrumented grip. A six-axis force-torque sensor was connected to a custom-made axially separated grip, which was then connected to a driver shaft using a manufactured screw thread. Subjects participated in two sessions of data collection featuring five driver swings with both a regular and customized sensor-embedded grip, respectively. Internal grip force measurement and upper limb kinematics were used to calculate the joint force and torque of the nine-linkage closed-chain of the upper limb and club using 3D inverse dynamics. Direct measurement of internal grip forces revealed a threefold greater right-hand torque application compared to the left hand, and counterforce by both hands was also found. The joint force and torque of the left arm tended to precede that of the right arm, the majority of which had peaks around the impact and showed a larger magnitude than that of the left arm. Due to the practical challenge of measuring internal force, heuristic estimation methods based on club kinematics showed fair approximation. Our results suggest that measuring the internal forces of the closed-chain posture could identify redundant joint kinetics and further propose a heuristic approximation.
Robust ℋ∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations
Authors: Ahmad Nur
Published: June 2020

Motion control involving DC motors requires a closed-loop system with a suitable compensator if tracking performance with high precision is desired. In the case where structural model errors of the motors are more dominating than the effects from noise disturbances, accurate system modelling will be a considerable aid in synthesizing the compensator. The focus of this paper is on enhancing the tracking performance of a wheeled mobile robot (WMR), which is driven by two DC motors that are subject to model parametric uncertainties and uncertain deadzones. For the system at hand, the uncertain nonlinear perturbations are greatly induced by the time-varying power supply, followed by behaviour of motion and speed. In this work, the system is firstly modelled, where correlations between the model parameters and different input datasets as well as voltage supply are obtained via polynomial regressions. A robust H ∞ -fuzzy logic approach is then proposed to treat the issues due to the aforementioned perturbations. Via the proposed strategy, the H ∞ controller and the fuzzy logic (FL) compensator work in tandem to ensure the control law is robust against the model uncertainties. The proposed technique was validated via several real-time experiments, which showed that the speed and path tracking performance can be considerably enhanced when compared with the results via the H ∞ controller alone, and the H ∞ with the FL compensator, but without the presence of the robust control law.
Assessment of Gold Bio-Functionalization for Wide-Interface Biosensing Platforms
Authors: Sarcina Lucia , Torsi Luisa , Picca Rosaria Anna , Manoli Kyriaki , Macchia Eleonora
Published: June 2020

The continuous improvement of the technical potential of bioelectronic devices for biosensing applications will provide clinicians with a reliable tool for biomarker quantification down to the single molecule. Eventually, physicians will be able to identify the very moment at which the illness state begins, with a terrific impact on the quality of life along with a reduction of health care expenses. However, in clinical practice, to gather enough information to formulate a diagnosis, multiple biomarkers are normally quantified from the same biological sample simultaneously. Therefore, it is critically important to translate lab-based bioelectronic devices based on electrolyte gated thin-film transistor technology into a cost-effective portable multiplexing array prototype. In this perspective, the assessment of cost-effective manufacturability represents a crucial step, with specific regard to the optimization of the bio-functionalization protocol of the transistor gate module. Hence, we have assessed, using surface plasmon resonance technique, a sustainable and reliable cost-effective process to successfully bio-functionalize a gold surface, suitable as gate electrode for wide-field bioelectronic sensors. The bio-functionalization process herein investigated allows to reduce the biorecognition element concentration to one-tenth, drastically impacting the manufacturing costs while retaining high analytical performance.
Vulnerability of European Union Economies in Agro Trade
Authors: Civín Lubomír , Smutka Luboš
Published: June 2020

The European Union (EU) is characterized by a high level of openness to trade, consequently increasing its member countries’ vulnerability to external shocks coming from the rapidly changing global environment. The paper’s objective was to compare and evaluate the factors of the EU agribusiness, its vulnerability and its measurement tools, and consequently to create subgroupings within EU member countries with different levels of vulnerability to exogenous shocks. The study hypothesized that the EU is not a homogenous unit regarding its trade sensitivity and vulnerability. It analyzed this phenomenon using data of recognized international institutions. Its method was a multi-criteria analysis with summative scaling. The assessment of the analysis was provided by the linear aggregation of 19 relevant vulnerability-influencing parameters, including climate change risk and political stability. The study results confirmed the hypothesis of the EU heterogeneity and identified four groups of member countries with different levels of the vulnerability to global shocks. It can improve an understanding of the agrarian sector position within the EU economy and a more precise re-formulation of its Common Agricultural Policy (CAP) priorities under the new conditions requiring the comprehensive resilience of the sector.
Spatiotemporal Variation of Vegetation Coverage and Its Response to Climate Factors and Human Activities in Arid and Semi-Arid Areas: Case Study of the Otindag Sandy Land in China
Authors: Wang Hao , Yao Fei , Zhu Huasheng , Zhao Yuanyuan
Published: June 2020

Vegetation coverage is a key variable in terrestrial ecosystem monitoring and climate change research and is closely related to soil erosion and land desertification. In this article, we aimed to resolve two key scientific issues: (1) quantifying the spatial-temporal vegetation dynamics in the Otindag Sandy Land (OSL); and (2) identifying the relative importance of climate factors and human activities in impacting vegetation dynamics. Based on correlation analysis, simple regression analysis, and the partial derivative formula method, we examined the spatiotemporal variation of vegetation coverage in the OSL, belonging to the arid and semiarid region of northern China, and their interaction with climate-human factors. The results showed that the vegetation coverage of the area showed a downward trend with a rate of −0.0006/a during 2001–2017, and gradually decreased from east to west. Precipitation was the main climate factor controlling the overall distribution pattern of vegetation coverage, while the human factors had a more severe impact on the vegetation coverage than the climate factors in such a short period, and the overall impact was negative. Among the human factors, population pressure, urbanization, industrialization, pastoral production activities, and residents’ lifestyles had a negative impact. However, ecological restoration polices alleviated the contradiction between human development and vegetation deterioration. The results of this article provide a scientific basis for restoring grassland systems in arid and semi-arid areas
Power Assessment in Road Cycling: A Narrative Review
Authors: Sitko Sebastian , Cirer-Sastre Rafel , Corbi Francisco , López-Laval Isaac
Published: June 2020

Nowadays, the evaluation of physiological characteristics and training load quantification in road cycling is frequently performed through power meter data analyses, but the scientific evidence behind this tool is scarce and often contradictory. The aim of this paper is to review the literature related to power profiling, functional threshold testing, and performance assessment based on power meter data. A literature search was conducted following preferred reporting items for review statement (PRISMA) on the topic of {“cyclist” OR “cycling” AND “functional threshold” OR “power meter”}. The reviewed evidence provided important insights regarding power meter-based training: (a) functional threshold testing is closely related to laboratory markers of steady state; (b) the 20-min protocol represents the most researched option for functional threshold testing, although shorter durations may be used if verified on an individual basis; (c) power profiling obtained through the recovery of recorded power outputs allows the categorization and assessment of the cyclist’s fitness level; and (d) power meters represent an alternative to laboratory tests for the assessment of the relationship between power output and cadence. This review elucidates the increasing amount of studies related to power profiling, functional threshold testing, and performance assessment based on power meter data, highlighting the opportunity for the expanding knowledge that power meters have brought in the road cycling field.
The Mediating Role of Intellectual Capital in Open Innovation in the Service Industries
Authors: Lo Chihcheng , Wang Chunhsien , Chen Yi-Chun
Published: June 2020

The paper intends to examine the mediating role of intellectual capital in the relation between the openness of service companies’ search strategies and thr innovation performance. It models the relationship between external search strategies of open innovation and proposes how intellectual capital matters for openness strategies in the service industries. Moreover, the paper intends to expand the field of open innovation through exploring the mediating effect of intellectual capital. This paper fulfills an identified need to study how intellectual capital can be enabled in the open innovation of the service industries. Both Hierarchical Multiple Regression and the Structural Equation Model were employed to test the innovation model by the panel data of the second Taiwan Innovation Survey including 948 service firms. Empirical insights enable us to have a better understanding in terms of how service companies learn from external knowledge sources. This paper suggests that the impact of openness strategies on innovation performance becomes indirect through the partial mediator of intellectual capital so that innovation performance in service industry benefits from simultaneously incorporating intellectual capital with the efficient openness strategies. Finally, the paper includes implications for more insights into how service companies improve their innovative activities with external searching strategies and practices in terms of intellectual capital.
Effects of CSR and CR on Business Confidence in an Emerging Country
Authors: del Brío Jesús , Bolaños Edmundo Lizarzaburu
Published: June 2020

Corporate social responsibility has been one of the main pillars of development for companies in developed countries and studies are being conducted for developed countries and the productive sector of the economy. Therefore, the main objective of this paper is to analyze the relationship between corporate social responsibility (CSR), corporate reputation (CR), and business confidence in the context of the banking sector in an emerging country (Peru). To test the hypotheses presented in this paper, we sent a survey to 1745 banking executive officers of the branch offices in Peru. These key individuals were selected as the target population of the study because the authors sought to study the management’s perception of CSR and business confidence. From the data obtained from the survey, it has been determined that the strategic consideration of CSR in Peruvian banks directly influences the perception of business confidence. Secondly, it has been demonstrated that the strategic consideration of CSR in Peruvian banks positively influences corporate reputation and, finally, the perception of the importance of the corporate reputation of Peruvian banks and significantly influences the perception of business confidence by the managers. The main contribution of this paper is that it analyzes empirically how business confidence is perceived by managers, who are the main agents involved in implementing CSR actions, based on their opinion of the strategic consideration of CSR and the perception of CR in a context barely investigated, an emerging country.
Diversity Management as a Tool for Sustainable Development of Health Care Facilities
Authors: Jankelová Nadežda , Joniaková Zuzana , Procházková Katarína , Blštáková Jana
Published: June 2020

Organizations providing health services are often criticized because of inadequate and unsuitable management processes or procedures. Today’s challenge is focused on effective management and leadership skills in the area of health care. The aim of the research is to describe, analyze, and evaluate the current state of diversity management in details in the context of human resources management in the selected healthcare facilities. The source of the information was a questionnaire survey. The sample consists of 181 managers from various health care and health service organizations. The method of analysis of variance (ANOVA) was used for data processing. The results were processed in SPSS and Excel programs. Pearson’s coefficient was used to evaluate the cross-correlation of the variables. The level of significance was 5% on both sides. Basic awareness of diversity management in the healthcare facilities is low. Some tools of diversity management are used, but only in isolation, non-conceptually, and unsystematically. The acknowledgment of diversity concept is poor and chaotic. The basic models of this concept defining its goals, activities, programs, responsibilities, and measurements are not known. One of the strong areas of the diversity management in the healthcare facilities is the diversity of working teams. On other hand, the weak side is the diversity as part of the organization culture and diversity as a part of human resource management. The summarizing index Attitudes towards Diversity received a higher average value than the Diversity Management Implementation index. Significant variables influencing the level of aggregate indices were identified: Ownership, size of the organization in terms of number of employees, patients’ satisfaction, and employees’ satisfaction.
Understanding Peer-to-Peer, Two-Sided Digital Marketplaces: Pricing Lessons from Airbnb in Barcelona
Authors: Lladós-Masllorens Josep , Meseguer-Artola Antoni , Rodríguez-Ardura Inma
Published: June 2020

Peer-to-peer, two-sided digital marketplaces are reshaping the way in which consumers exchange products and interact with brand value propositions, particularly in the travel and tourism industry. Within the dynamics of these marketplaces, pricing approaches are of the utmost importance; yet, in contrast to conventional digital marketplaces, prices are set by non-professional vendors who are also consumers. We contribute to research on the topic by examining pricing within a single peer-to-peer, two-sided marketing platform: Airbnb. We use a large dataset covering accommodation listed by non-professional hosts in Barcelona, Spain. We identify a range of intrinsic and extrinsic attributes of the value propositions of Airbnb peer-to-peer accommodation, which enables us to explain differences in price levels. The paper offers evidence that higher accommodation prices are best explained by guests’ preference for the intrinsic functional qualities of the value proposition; and that the systematic interaction of valence and volume of online reviews can produce a crucial impact on pricing.
Consumers’ Preferences for and Perception of CSR Initiatives in the Wine Sector
Authors: Stanco Marcello , Lerro Marco
Published: June 2020

This study explores consumers’ preferences for corporate social responsibility (CSR) initiatives implemented in the wine sector. Moreover, it investigates consumers’ perception and price premium for four wine certifications related to corporate social responsibility (i.e., SQNPI Sustainable Quality; V.I.V.A. Sustainable Wine; Organic, and Equalitas—Sustainable Wine). Overall 251 regular Italian wine consumers participated in an online survey. Their preferences for 11 CSR initiatives implemented in the wine sector were assessed through a best–worst scaling analysis. The study findings show that the most important CSR initiatives for consumers are “health and food safety”, “sustainable agricultural practices”, and “air pollution”. By contrast, those least important for consumers are “energy consumption”, “sustainable packaging”, and “fair trade”. Consumers expressed a positive perception in terms of CSR performance for all the certifications investigated, while their price premium was higher for wine with Organic certification. The study offers several implications for wineries. Specifically, it suggests the CSR initiatives that wineries may implement to fully meet consumers’ preferences.
Framework for Risk Identification of Renewable Energy Projects Using Fuzzy Case-Based Reasoning
Authors: Somi Sahand , Gerami Seresht Nima , Fayek Aminah Robinson
Published: June 2020

Construction projects are highly risk-prone due to both internal factors (e.g., organizational, contractual, project, etc.) and external factors (e.g., environmental, economic, political, etc.). Construction risks can thus have a direct or indirect impact on project objectives, such as cost, time, safety, and quality. Identification of these risks is crucial in order to fulfill project objectives. Many tools and techniques have been proposed for risk identification, including literature review, questionnaire surveys, and expert interviews. However, the majority of these approaches are highly reliant on expert knowledge or prior knowledge of the project. Therefore, the application of such tools and techniques in risk identification for renewable energy projects (e.g., wind farm and solar power plant projects) is challenging due to their novelty and the limited availability of historical data or literature. This paper addresses these challenges by introducing a new risk identification framework for renewable energy projects, which combines case-based reasoning (CBR) with fuzzy logic. CBR helps to solve problems related to novel projects (e.g., renewable energy projects) based on their similarities to existing, well-studied projects (e.g., conventional energy projects). CBR addresses the issue of data scarcity by comparing novel types of construction projects to other well-studied project types and using the similarities between these two sets of projects to solve the different problems associated with novel types of construction projects, such as risk identification of renewable energy projects. Moreover, the integration of fuzzy logic with CBR, to develop fuzzy case-based reasoning (FCBR), increases the applicability of CBR in construction by capturing the subjective uncertainty that exists in construction-related problems. The applicability of the proposed framework was tested on a case study of an onshore wind farm project. The objectives of this paper are to introduce a novel framework for risk identification of renewable energy projects and to identify the risks associated with the construction of onshore wind farm projects at the work package level. The results of this paper will help to improve the risk management of renewable energy projects during the construction phase.
Analysis of the Possibility of Transport Mode Switch: A Case Study for Joinville Students
Authors: Schubert Thamires Ferreira , Henning Elisa , Lopes Simone Becker
Published: June 2020

This work mainly aims to identify and understand the factors influencing the switching of transportation modes among higher-education students in Joinville, Brazil, when traveling to universities. An online questionnaire was prepared for data collection which obtained 511 responses from six higher education institutions. The revealed preference survey identified the bus as the most used by students today, while the stated preference survey assessed the possibility of changing modes. Employing a multinomial logit model, the results indicate that students would be interested in switching from individual motor vehicles to other options. The scenarios for switching to buses presented the highest switching probability. Bus cost was the most important factor for switching. Despite the small number, the students showed interest in switching from the car to active modes. This may indicate the lack of current infrastructure and the need for investments so these modes can be seen as quality options for users. Finally, a transport mode switch would occur only if alternative modes to the car or their infrastructure are improved; otherwise, students maintain their usual choices. This knowledge can assist in the development of public policies aimed at urban management seeking to increase the supply and the quality of more sustainable modes of transport.
Circularity in Waste Electrical and Electronic Equipment (WEEE) Directive. Comparison of a Manufacturer’s Danish and Norwegian Operations
Authors: Andersen Terje , Jæger Bjørn , Mishra Alok
Published: June 2020

Waste electrical and electronic equipment (WEEE) as a reverse supply chain (RSC) has a low degree of circularity, mainly focusing on recovering or recycling. Targets to increase the circularity have recently been introduced in the EU WEEE directive. In this case study, we have investigated how WEEE is handled within an electric and electronic (EE) equipment manufacturer. The case study includes findings from two different Nordic countries, Norway and Denmark, with interviews of six stakeholders. The case study shows that there are significant differences in how the case company fulfills its extended producer responsibility (EPR), especially related to reporting. The study also found that there is a mismatch between the ambitions in the WEEE directive and a company’s approach related to circularity in the end-of-life phase of an EE product. Based on the results of this case study and from the literature we propose recommendations on alignment with other directives and on a common information regime within the WEEE RSC.
Soil-Based Vegetation Productivity Model for Coryell County, Texas
Authors: Wen Bin , Burley Jon Bryan
Published: June 2020

Managers, scientists, planners and designers of landscapes are interested in systematic investigations, to predict the reconstruction of disturbed soil resources for optimum vegetation productivity. In this study, a predictive equation for estimating neo-soil plant growth in Coryell County, Texas was developed. The equation predicts the vegetation growth for wheat (Triticum aestivum L.), oats [Avena sativa L. (1753)], sorghum [Sorghum bicolor (L.) Moench], cotton lint (Gossypium hirsutum L.), Bermuda grass [Cynodon dactylon (L.) Pers.], and rangeland production in general. The results suggest that an all-vegetation predictive model was highly significant (p ≤ 0.0001), explaining over 80% of the variance. The equation employed hydraulic conductivity as a main-effect variable; bulk density and hydraulic conductivity as squared terms; and percent clay times bulk density, bulk density times soil reaction, hydraulic conductivity times available water holding capacity, and hydraulic conductivity times soil reactions as first order interaction terms, with each predicting variable containing a p-value equal to or less than 0.05. The results suggest that an annual crop equation and a plant-specific cotton lint equation also have merit.
Assessment of Formal Credit and Climate Change Impact on Agricultural Production in Pakistan: A Time Series ARDL Modeling Approach
Authors: Chandio Abbas Ali , Jiang Yuansheng , Rauf Abdul , Ahmad Fayyaz , Amin Waqas , Shehzad Khurram
Published: June 2020

This study attempts to investigate the short-run and long-run impact of formal credit (CR) and climate change (CC, via CO2 emissions) on agricultural production (AP) in Pakistan. In addition, other imperative control variables included in this study comprise technology factors (tractors (TRs) and tube wells (TWs), energy consumption (EC), and labor force (LF). This study used annual data covering the period 1983–2016. The autoregressive distributed lag (ARDL) approach is applied to explore the cointegration between the underlying variables and used the granger causality test under the vector error correction model (VECM) context to determine the direction of causality among the variables. The findings of the ARDL bounds-testing approach suggest that there is a long-term relationship among formal credit, climate change (CO2 emissions), technology factors (tractors and tube wells), energy consumption, labor force, and agricultural production. The empirical results reveal that formal credit, technology use (tractors), and labor force have a positive and significant impact on agricultural production in both the short-run and long-run. CO2 emissions have a positive impact on agricultural production but are not significant in either case. Finally, a unidirectional relationship is established from formal credit to agricultural production; labor force to agricultural production; and electricity consumption and technology factors (tractors and tube wells) to CO2 emissions. The recent study claims that formal institutions should guarantee the redeployment of their services/amenities to those who call for them acutely, with the purpose of boosting their approach to monetary credit facilities and empower farmers to further the resilience that will capitalize on post-fruitage enrichments. Finally, considering that climatic change is a widespread fact with regional community trajectories, perhaps the global community may provide reassurance for loaning to smallholder agriculturalists through central and commercial banks by protecting the moneys that banks lend to the agriculturalists towards supporting climatic change espousal strategies.
Students’ Conceptions of Sustainable Nutrition
Authors: Dornhoff Maximilian , Hörnschemeyer Annelie , Fiebelkorn Florian
Published: June 2020

In Education for Sustainable Development, the topic of sustainable nutrition offers an excellent learning topic as it combines the five dimensions of health, environment, economy, society, and culture, unlike most topics with a regional-global scope. The identification of existing students’ conceptions of this topic is important for the development of effective teaching and learning arrangements. This study aimed to understand students’ conceptions of sustainable nutrition and the relevance that students attribute to the five dimensions. For this purpose, we conducted semi-structured individual interviews with 10th-grade students at secondary schools in Germany (n = 46; female = 47.8%; MAge = 15.59, SD = 0.78). We found that the health dimension prevailed in students’ conceptions of sustainable nutrition; however, the more dimensions the students considered, the less importance was attached to the health dimension. The ecological dimension, in turn, became more prominent as the students’ conceptions became more elaborate. Many students neglected the social, economic, and especially the cultural dimensions. Furthermore, alternative conceptions of the terminology of sustainable nutrition, which did not correspond to the scientific concept, were identified. Students had difficulties linking the ecological, social, economic, and cultural dimensions to sustainable nutrition due to a predominant egocentric perspective on nutrition, which primarily entails focusing on one’s own body.
Design of a Lightweight Rear Crash Management System in a Sustainable Perspective
Authors: Del Pero Francesco , Delogu Massimo , Kerschbaum Martin
Published: June 2020

The paper presents an innovative lightweight design solution for the rear crash management system of a C-class car, developed within the AffordabLe LIghtweight Automobiles AlliaNCE (ALLIANCE) EU research project. The innovation provides that the reference version of the module, based on conventional steel components, is revolutionized through the introduction of extruded 6000/7000 series aluminum alloys. The two competing alternatives are described and compared in relation to design and technological solutions, including also a sustainability analysis which assesses the entire Life Cycle (LC) of the system on the basis of a wide range of environmental indicators. The lightweight solution allows achieving a large mass reduction (almost 40%), while providing improvements in terms of strength, production efficiency and design freedom. On the other hand, the introduction of new materials and manufacturing technologies entails contrasting sustainability effects depending on impact category, thus not allowing to affirm that the novel alternative is unequivocally preferable under the environmental point of view. However, the comprehensive evaluation of all sustainability aspects through a multi-criteria decision analysis (TOPSIS method) reveals that the environmental profile of the innovative design is slightly preferable with respect to the conventional one.
Applications of Nonconventional Green Extraction Technologies in Process Industries: Challenges, Limitations and Perspectives
Authors: Fomo Gertrude , Madzimbamuto Tafirenyika Nyamayaro , Ojumu Tunde Victor
Published: June 2020

This study reviewed five different nonconventional technologies which are aligned with green concepts of product recovery from raw materials on industrial scale, with minimal energy consumption and chemical use. Namely, this study reviewed supercritical fluid extraction (SCFE), pressurized liquid extraction (PLE), microwave-assisted extraction (MAE), ultrasound extraction (UAE) and pulsed electric fields extraction (PEFE). This paper provides an overview of relevant innovative work done in process industries on different plant matrices for functional value-added compounds and byproduct production. A comparison of the five extraction methods showed the supercritical CO2 (SC-CO2) process to be more reliable despite some limitations and challenges in terms of extraction yield and solubility of some bioactive compounds when applied in processing industries. However, these challenges can be solved by using ionic liquids as a trainer or cosolvent to supercritical CO2 during the extraction process. The choice of ionic liquid over organic solvents used to enhance extraction yield and solubility is based on properties such as hydrophobicity, polarity and selectivity in addition to a safe environment.