bluuebunny/crossref_metadata_2025 huggingface dataset:
Third-Order Nonlinear Spectrum of GaN under Femtosecond-Pulse Excitation from the Visible to the Near Infrared
Authors: Almeida Gustavo F. B. , Santos Sabrina N. C. , Siqueira Jonathas P. , Dipold Jessica , Voss Tobias , Mendonça Cleber R.
Published: June 2019

Gallium nitride (GaN) has been established as a promising candidate for integrated electro-optic and photonic devices, aiming at applications from optical switching to signal processing. Studies of its optical nonlinearities, however, lack spectral coverage, especially in the telecommunications range. In this study, we measured the two-photon absorption coefficient (β) and the nonlinear index of refraction (n2) of GaN from the visible to the near-infrared by using femtosecond laser pulses. We observed an increase of β from (1.0 ± 0.2) to (2.9 ± 0.6) ×10−11 m/W as the photon energy approached the band gap from 1.77 up to 2.25 eV (700–550 nm), while n2 varied from (90 ± 30) ×10−20 up to (265 ± 80) ×10−20 m2/W within a broad spectral range, from 0.80 up to 2.25 eV (1550–550 nm). The results were modeled by applying a theory based on the second-order perturbation theory and the Kramers-Kronig relationship for direct-gap semiconductors, which are important for the development of GaN-based nonlinear photonic devices.
Design of Controlled Release System for Paracetamol Based on Modified Lignin
Authors: Pishnamazi Mahboubeh , Hafizi Hamid , Shirazian Saeed , Culebras Mario , Walker Gavin , Collins Maurice
Published: June 2019

The influence of lignin modification on drug release and pH-dependent releasing behavior of oral solid dosage forms was investigated using three different formulations. The first formulation contains microcrystalline cellulose (MCC 101) as the excipient and paracetamol as the active pharmaceutical ingredient (API). The second formulation includes Alcell lignin and MCC 101 as the excipient and paracetamol, and the third formulation consists of carboxylated Alcell lignin, MCC 101 and paracetamol. Direct compaction was carried out in order to prepare the tablets. Lignin can be readily chemically modified due to the existence of different functional groups in its structure. The focus of this investigation is on lignin carboxylation and its influence on paracetamol control release behavior at varying pH. Results suggest that carboxylated lignin tablets had the highest drug release, which is linked to their faster disintegration and lower tablet hardness.
Selectively Biodegradable Polyesters: Nature-Inspired Construction Materials for Future Biomedical Applications
Authors: Urbánek Tomáš , Jäger Eliézer , Jäger Alessandro , Hrubý Martin
Published: June 2019

In the last half-century, the development of biodegradable polyesters for biomedical applications has advanced significantly. Biodegradable polyester materials containing external stimuli-sensitive linkages are favored in the development of therapeutic devices for pharmacological applications such as delivery vehicles for controlled/sustained drug release. These selectively biodegradable polyesters degrade after particular external stimulus (e.g., pH or redox potential change or the presence of certain enzymes). This review outlines the current development of biodegradable synthetic polyesters materials able to undergo hydrolytic or enzymatic degradation for various biomedical applications, including tissue engineering, temporary implants, wound healing and drug delivery.
Synthesis of a Novel Phosphorous-Nitrogen Based Charring Agent and Its Application in Flame-retardant HDPE/IFR Composites
Authors: Chen Junlei , Wang Jihui , Ni Aiqing , Chen Hongda , Shen Penglong
Published: June 2019

In this work, a novel phosphorous–nitrogen based charring agent named poly(1,3-diaminopropane-1,3,5-triazine-o-bicyclic pentaerythritol phosphate) (PDTBP) was synthesized and used to improve the flame retardancy of high-density polyethylene (HDPE) together with ammonium polyphosphate (APP). The results of Fourier transform infrared spectroscopy (FTIR) and 13C solid-state nuclear magnetic resonance (NMR) showed that PDTBP was successfully synthesized. Compared with the traditional intumescent flame retardant (IFR) system contained APP and pentaerythritol (PER), the novel IFR system (APP/PDTBP, weight ratio of 2:1) could significantly promote the flame retardancy, water resistance, and thermal stability of HDPE. The HDPE/APP/PDTBP composites (PE3) could achieve a UL-94 V-0 rating with LOI value of 30.8%, and had a lower migration percentage (2.2%). However, the HDPE/APP/PER composites (PE5) had the highest migration percentage (4.7%), lower LOI value of 23.9%, and could only achieve a UL-94 V-1 rating. Besides, the peak of heat release rate (PHRR), total heat release (THR), and fire hazard value of PE3 were markedly decreased compared to PE5. PE3 had higher tensile strength and flexural strength of 16.27 ± 0.42 MPa and 32.03 ± 0.59 MPa, respectively. Furthermore, the possible flame-retardant mechanism of the APP/PDTBP IFR system indicated that compact and continuous intumescent char layer would be formed during burning, thus inhibiting the degradation of substrate material and improving the thermal stability of HDPE.
A Novel Technology for Separating Copper, Lead and Zinc in Flotation Concentrate by Oxidizing Roasting and Leaching
Authors: Zhang Qian , Feng Qicheng , Wen Shuming , Cui Chuanfa , Liu Junbo
Published: June 2019

In this work, oxidizing roasting was combined with leaching to separate copper, lead, and zinc from a concentrate obtained by bulk flotation of a low-grade ore sourced from the Jiama mining area of Tibet. The flotation concentrate contained 7.79% Cu, 22.00% Pb, 4.81% Zn, 8.24% S, and 12.15% CaO; copper sulfide accounted for 76.97% of the copper, lead sulfide for 25.55% of the lead, and zinc sulfide for 67.66% of the zinc. After oxidizing roasting of the flotation concentrate, the S content in the roasting slag decreased to 0.22%, indicating that most sulfide in the concentrate was transformed to oxide, which was beneficial to leaching. The calcine was subjected to sulfuric acid leaching for separation of copper, lead, and zinc; i.e., copper and zinc were leached, and lead was retained in the residue. The optimum parameters of the leaching process were: a leaching temperature of 55 °C; sulfuric acid added at 828 kg/t calcine; a liquid:solid ratio of 3:1; and a leaching time of 1.5 h. Under these conditions, the extents of leaching of copper and zinc were 87.43% and 64.38%, respectively. Copper and zinc in the leaching solution could be further separated by electrowinning. The effects of leaching parameters on the extents of leaching of copper and zinc were further revealed by X-ray diffraction and scanning electron microscopy analysis.
Dynamic Modelling of Phosphorolytic Cleavage Catalyzed by Pyrimidine-Nucleoside Phosphorylase
Authors: Giessmann Robert T. , Krausch Niels , Kaspar Felix , Cruz Bournazou Mariano Nicolas , Wagner Anke , Neubauer Peter , Gimpel Matthias
Published: June 2019

Pyrimidine-nucleoside phosphorylases (Py-NPases) have a significant potential to contribute to the economic and ecological production of modified nucleosides. These can be produced via pentose-1-phosphates, an interesting but mostly labile and expensive precursor. Thus far, no dynamic model exists for the production process of pentose-1-phosphates, which involves the equilibrium state of the Py-NPase catalyzed reversible reaction. Previously developed enzymological models are based on the understanding of the structural principles of the enzyme and focus on the description of initial rates only. The model generation is further complicated, as Py-NPases accept two substrates which they convert to two products. To create a well-balanced model from accurate experimental data, we utilized an improved high-throughput spectroscopic assay to monitor reactions over the whole time course until equilibrium was reached. We examined the conversion of deoxythymidine and phosphate to deoxyribose-1-phosphate and thymine by a thermophilic Py-NPase from Geobacillus thermoglucosidasius. The developed process model described the reactant concentrations in excellent agreement with the experimental data. Our model is built from ordinary differential equations and structured in such a way that integration with other models is possible in the future. These could be the kinetics of other enzymes for enzymatic cascade reactions or reactor descriptions to generate integrated process models.
Natural Science and Supernatural Thought Experiments
Authors: Brown James Robert
Published: June 2019

Religious notions have long played a role in epistemology. Theological thought experiments, in particular, have been effective in a wide range of situations in the sciences. Some of these are merely picturesque, others have been heuristically important, and still others, as I will argue, have played a role that could be called essential. I will illustrate the difference between heuristic and essential with two examples. One of these stems from the Newton–Leibniz debate over the nature of space and time; the other is a thought experiment of my own constructed with the aim of making a case for a more liberal view of evidence in mathematics.
Development of an Industrial Environmental Index to Assess the Sustainability of Industrial Solvent-Based Processes
Authors: Fadel Chris , Tarabieh Khaled
Published: June 2019

In light of the constant increase in global temperatures, increasing risks associated with climate change, and stricter environmental policies, societies are at a crossroad where sound environmental decisions need to be taken. This is particularly applicable to the chemical industry where the sustainability of processes is all the more relevant to decision-making. This article supports the development of a holistic industrial environmental index (IEI) to assess the sustainability of industrial solvent-based processes. Several metrics are reviewed to individually assess particular aspects of the process in terms of materials, equipment, energy, environmental health and safety (EHS) considerations, and the product’s entire life cycle. The metrics are later used to support the development of an aggregate and holistic IEI using a composite indicator method. The developed methodology and framework can pave the way for environmentally sound decision-making in industries and spark the development of dedicated assessment indices similar to IEI that can be applied to a wide array of other industries.
Inverse Kinematics with a Geometrical Approximation for Multi-Segment Flexible Curvilinear Robots
Authors: Kim Sehun , Xu Wenjun , Ren Hongliang
Published: June 2019

Despite research related to flexible or continuum curvilinear robots, there lacks a common simulation tool for continuum robots, which are unlike rigid robots. Thus, in this paper, a robotics toolbox is utilized to model a wire-driven flexible manipulator as one of the continuum robots. Constant curvature property can enable the robotics toolbox to represent the flexible manipulator and validate its kinematics. Moreover, because the closed-form inverse kinematics methods developed previously for real-time control conceded limitations in modeling some continuum robots, we hereby develop an inverse kinematics method for the wire-driven flexible manipulator which can provide fast and reliable inverse results. Experimental results showed that geometrical information offered a stable starting point for the proposed inverse kinematics algorithm. Moreover, the first and second derivatives of a fitness function further contributed to a fast-converging solution within a few microseconds. Lastly, for the potential feasibility of an active compliance controller without physical force/torque sensors, a reaction torque observer was investigated for a flexible manipulator with direct drive mechanisms.
Crop NDVI Monitoring Based on Sentinel 1
Authors: Filgueiras Roberto , Mantovani Everardo Chartuni , Althoff Daniel , Fernandes Filho Elpídio Inácio , Cunha Fernando França da
Published: June 2019

Monitoring agricultural crops is necessary for decision-making in the field. However, it is known that in some regions and periods, cloud cover makes this activity difficult to carry out in a systematic way throughout the phenological cycle of crops. This circumstance opens up opportunities for techniques involving radar sensors, resulting in images that are free of cloud effects. In this context, the objective of this work was to obtain a normalized different vegetation index (NDVI) cloudless product (NDVInc) by modeling Sentinel 2 NDVI using different regression techniques and the Sentinel 1 radar backscatter as input. To do this, we used four pairs of Sentinel 2 and Sentinel 1 images on coincident days, aiming to achieve the greatest range of NDVI values for agricultural crops (soybean and maize). These coincident pairs were the only ones in which the percentage of clouds was not equal to 100% for 33 central pivot areas in western Bahia, Brazil. The dataset used for NDVInc modeling was divided into two subsets: training and validation. The training and validation datasets were from the period from 24 June 2017 to 19 July 2018 (four pairs of images). The best performing model was used in a temporal analysis from 02 October 2017 to 08 August 2018, totaling 55 Sentinel 2 images and 25 Sentinel 1 images. The selection of the best regression algorithm was based on two validation methodologies: K-fold cross-validation (k = 10) and holdout. We tested four modeling approaches with eight regression algorithms. The random forest was the algorithm that presented the best statistical metrics, regardless of the validation methodology and the approach used. Therefore, this model was applied to a time series of Sentinel 1 images in order to demonstrate the robustness and applicability of the model created. We observed that the data derived from Sentinel 1 allowed us to model, with great reliability, the NDVI of agricultural crops throughout the phenological cycle, making the methodology developed in this work a relevant solution for the monitoring of various regions, regardless of cloud cover.
Unmanned Aerial Vehicle for Remote Sensing Applications—A Review
Authors: Yao Huang , Qin Rongjun , Chen Xiaoyu
Published: June 2019

The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in almost every application (e.g., agriculture, forestry, and mining) that needs observed information from the top or oblique views. While they intend to be a general remote sensing (RS) tool, the relevant RS data processing and analysis methods are still largely ad-hoc to applications. Although the obvious advantages of UAV data are their high spatial resolution and flexibility in acquisition and sensor integration, there is in general a lack of systematic analysis on how these characteristics alter solutions for typical RS tasks such as land-cover classification, change detection, and thematic mapping. For instance, the ultra-high-resolution data (less than 10 cm of Ground Sampling Distance (GSD)) bring more unwanted classes of objects (e.g., pedestrian and cars) in land-cover classification; the often available 3D data generated from photogrammetric images call for more advanced techniques for geometric and spectral analysis. In this paper, we perform a critical review on RS tasks that involve UAV data and their derived products as their main sources including raw perspective images, digital surface models, and orthophotos. In particular, we focus on solutions that address the “new” aspects of the UAV data including (1) ultra-high resolution; (2) availability of coherent geometric and spectral data; and (3) capability of simultaneously using multi-sensor data for fusion. Based on these solutions, we provide a brief summary of existing examples of UAV-based RS in agricultural, environmental, urban, and hazards assessment applications, etc., and by discussing their practical potentials, we share our views in their future research directions and draw conclusive remarks.
Newly Built Construction Detection in SAR Images Using Deep Learning
Authors: Jaturapitpornchai Raveerat , Matsuoka Masashi , Kanemoto Naruo , Kuzuoka Shigeki , Ito Riho , Nakamura Ryosuke
Published: June 2019

Remote sensing data can be utilized to help developing countries monitor the use of land. However, the problem of constant cloud coverage prevents us from taking full advantage of satellite optical images. Therefore, we instead opt to use data from synthetic-aperture radar (SAR), which can capture images of the Earth’s surface regardless of the weather conditions. In this study, we use SAR data to identify newly built constructions. Most studies on change detection tend to detect all of the changes that have a similar temporal change characteristic occurring on two occasions, while we want to identify only the constructions and avoid detecting other changes such as the seasonal change of vegetation. To do so, we study various deep learning network techniques and have decided to propose the fully convolutional network with a skip connection. We train this network with pairs of SAR data acquired on two different occasions from Bangkok and the ground truth, which we manually create from optical images available from Google Earth for all of the SAR pairs. Experiments to assign the most suitable patch size, loss weighting, and epoch number to the network are discussed in this paper. The trained model can be used to generate a binary map that indicates the position of these newly built constructions precisely with the Bangkok dataset, as well as with the Hanoi and Xiamen datasets with acceptable results. The proposed model can even be used with SAR images of the same specific satellite from another orbit direction and still give promising results.
Changes in Forest Net Primary Productivity in the Yangtze River Basin and Its Relationship with Climate Change and Human Activities
Authors: Zhang Fengying , Zhang Zengxin , Kong Rui , Chang Juan , Tian Jiaxi , Zhu Bin , Jiang Shanshan , Chen Xi , Xu Chong-Yu
Published: June 2019

Net Primary Productivity (NPP) is a basis of material and energy flows in terrestrial ecosystems, and it is also an important component in the research on carbon cycle and carbon budget. This paper evaluated the spatial distribution pattern and temporal change trends for forest NPP simulated by the LPJ (Lund-Potsdam-Jena) model and NDVI (normalized difference vegetation index) in the Yangtze River basin from 1982 to 2013. The results revealed that: (1) the spatial distribution of the forest NPP and NDVI in the Yangtze River basin has gradually decreased from the southeast coast to the northwest. The forest NPP and NDVI in the mid-lower Yangtze were higher than that of the upper Yangtze; (2) the forest NPP and NDVI in most areas of the Yangtze River basin were positively correlated with the temperature and precipitation. Moreover, the correlations among the temperature with the forest NPP and NDVI were stronger than that of correlations among precipitation with forest NPP and NDVI. Moreover, the extreme drought event in the year of 2004–2005 led the NPP to decrease in the middle and lower Yangtze River basin; (3) human activity such as major ecological projects would have a certain impact on the NPP and NDVI. The increase in forest areas from 2000 to 2010 was larger than that from 1990 to 2000. Moreover, the increasing rate for the NDVI was higher than that of NPP, especially after the year 2000, which indicates that the major ecological projects might have great impacts on the vegetation dynamics. Moreover, more attention should be paid on the joint impacts of human activity and climate change on terrestrial NPP and NDVI.
A Novel Framework of Detecting Convective Initiation Combining Automated Sampling, Machine Learning, and Repeated Model Tuning from Geostationary Satellite Data
Authors: Han Daehyeon , Lee Juhyun , Im Jungho , Sim Seongmun , Lee Sanggyun , Han Hyangsun
Published: June 2019

This paper proposes a complete framework of a machine learning-based model that detects convective initiation (CI) from geostationary meteorological satellite data. The suggested framework consists of three main processes: (1) An automated sampling tool; (2) machine learning-based CI detection modelling; (3) repeated model tuning through validation. In this study, the automated sampling tool was able to track the CI objects iteratively, even without ancillary data such as an atmospheric motion vector (AMV). The collected samples were used to train the machine learning model for CI detection. Random forest (RF) was used to classify the CI and non-CI. To enhance the advantages of the machine learning approach, we adopted model tuning to iteratively update the training dataset from each validation result by adding hits and misses to the CI samples, and false alarms and correct negatives to the non-CI samples. Using 12 interest fields from the Himawari-8 Advanced Himawari Imager (AHI) over the Korean Peninsula, this simple and intuitive tuning process increased the overall probability of detection (POD) from 0.79 to 0.82 and decreased the overall false alarm rate (FAR) from 0.46 to 0.37 with around 40 min of the lead-time. Amongst the 12 interest fields, T b (11.2) µm was identified as the most significant predictor in the RF model, followed by T b (8.6—11.2) µm, and T b (6.2–7.3) µm. The effect of model tuning on the CI detection performance was also analyzed using spatiotemporal validation maps. By automatically collecting and updating the machine learning training dataset, the suggested framework is expected to help the maintenance of the CI detection model from an operational perspective.
Remote Sensing of Snow Cover Using Spaceborne SAR: A Review
Authors: Tsai Ya-Lun S. , Dietz Andreas , Oppelt Natascha , Kuenzer Claudia
Published: June 2019

The importance of snow cover extent (SCE) has been proven to strongly link with various natural phenomenon and human activities; consequently, monitoring snow cover is one the most critical topics in studying and understanding the cryosphere. As snow cover can vary significantly within short time spans and often extends over vast areas, spaceborne remote sensing constitutes an efficient observation technique to track it continuously. However, as optical imagery is limited by cloud cover and polar darkness, synthetic aperture radar (SAR) attracted more attention for its ability to sense day-and-night under any cloud and weather condition. In addition to widely applied backscattering-based method, thanks to the advancements of spaceborne SAR sensors and image processing techniques, many new approaches based on interferometric SAR (InSAR) and polarimetric SAR (PolSAR) have been developed since the launch of ERS-1 in 1991 to monitor snow cover under both dry and wet snow conditions. Critical auxiliary data including DEM, land cover information, and local meteorological data have also been explored to aid the snow cover analysis. This review presents an overview of existing studies and discusses the advantages, constraints, and trajectories of the current developments.
Kinematic GPR-TPS Model for Infrastructure Asset Identification with High 3D Georeference Accuracy Developed in a Real Urban Test Field
Authors: Šarlah Nikolaj , Podobnikar Tomaž , Mongus Domen , Ambrožič Tomaž , Mušič Branko
Published: June 2019

This paper describes in detail the development of a ground-penetrating radar (GPR) model for the acquisition, processing and visualisation of underground utility infrastructure (UUI) in a controlled environment. The initiative was to simulate a subsurface urban environment through the construction of regional road, local road and pedestrian pavement in real urban field/testing pools (RUTPs). The RUTPs represented a controlled environment in which the most commonly used utilities were installed. The accuracy of the proposed kinematic GPR-TPS (terrestrial positioning system) model was analysed using all the available data about the materials, whilst taking into account the thickness of the pavement as well as the materials, dimensions and 3D position of the UUI as given reference values. To determine the reference 3D position of the UUI, a terrestrial geodetic surveying method based on the established positional and height geodetic network was used. In the first phase of the model, the geodetic network was used as a starting point for determining the 3D position of the GPR antenna with the efficient kinematic GPR surveying setup using a GPR and self-tracking (robotic) TPS. In the second phase, GPR-TPS system latency was quantified by matching radargram pairs with a set of fidelity measures based on a correlation coefficient and mean squared error. This was followed by the most important phase, where, by combining sets of “standard” processing routines of GPR signals with the support of advanced algorithms for signal processing, UUI were interpreted and visualised semi-automatically. As demonstrated by the results, the proposed GPR model with a kinematic GPR-TPS surveying setup for data acquisition is capable of achieving an accuracy of less than ten centimetres.
A Fault Detection System for a Geothermal Heat Exchanger Sensor Based on Intelligent Techniques
Authors: Aláiz-Moretón Héctor , Castejón-Limas Manuel , Casteleiro-Roca José-Luis , Jove Esteban , Fernández Robles Laura , Calvo-Rolle José Luis
Published: June 2019

This paper proposes a methodology for dealing with an issue of crucial practical importance in real engineering systems such as fault detection and recovery of a sensor. The main goal is to define a strategy to identify a malfunctioning sensor and to establish the correct measurement value in those cases. As study case, we use the data collected from a geothermal heat exchanger installed as part of the heat pump installation in a bioclimatic house. The sensor behaviour is modeled by using six different machine learning techniques: Random decision forests, gradient boosting, extremely randomized trees, adaptive boosting, k-nearest neighbors, and shallow neural networks. The achieved results suggest that this methodology is a very satisfactory solution for this kind of systems.
Modeling Flaw Pulse-Echo Signals in Cylindrical Components Using an Ultrasonic Line-Focused Transducer with Consideration of Wave Mode Conversion
Authors: Wang Weixin , Liu Xiling , Li Xiongbing , Xu Gang , Zhang Shuzeng
Published: June 2019

Investigations on flaw responses can benefit the nondestructive testing of cylinders using line-focused transducers. In this work, the system function, the wave beam model, and a flaw scattering model are combined to develop an ultrasonic measurement model for line-focused transducers to predict flaw responses in cylindrical components. The system function is characterized using reference signals by developing an acoustic transfer function for line-focused transducers, which works at different distances for both planar and curved surfaces. The wave beams in cylindrical components are modeled using a multi-Gaussian beam model, where the effects of wave mode conversion and curvatures of cylinders are considered. Simulation results of wave beams are provided to analyze their propagation behaviors. The proposed ultrasonic measurement model is certified from good agreement between the experimental and predicted signals of side-drilled holes. This work provides guidance for evaluating the detection ability of line-focused transducers in cylindrical component testing applications.
Immunoassays Based on Hot Electron-Induced Electrochemiluminescence at Disposable Cell Chips with Printed Electrodes
Authors: Grönroos Päivi , Nur-E-Habiba  , Salminen Kalle , Nissinen Marja , Tuomaala Tomi , Miikki Kim , Zhang Qiang , Wei Nan , Kauppinen Esko , Eskola Jarkko , Härmä Harri , Kulmala Sakari
Published: June 2019

Novel hot electron-emitting working electrodes and conventional counter electrodes were created by screen printing. Thus, low-cost disposable electrode chips for bioaffinity assays were produced to replace our older expensive electrode chips manufactured by manufacturing techniques of electronics from silicon or on glass chips. The present chips were created by printing as follows: (i) silver lines provided the electronic contacts, counter electrode and the bottom of the working electrode and counter electrode, (ii) the composite layer was printed on appropriate parts of the silver layer, and (iii) finally a hydrophobic ring was added to produce the electrochemical cell boundaries. The applicability of these electrode chips in bioaffinity assays was demonstrated by an immunoassay of human C-reactive protein (i) using Tb(III) chelate label displaying long-lived hot electron-induced electrochemiluminescence (HECL) and (ii) now for the first time fluorescein isothiocyanate (FITC) was utilized as an a low-cost organic label displaying a short-lived HECL in a real-world bioaffinity assay.
The Use of Social Digital Networks by NGDO from a Social Marketing Perspective
Authors: Galiano-Coronil Araceli , MierTerán-Franco Juan José
Published: June 2019

The social marketing paradigm has been changing due to the use of digital social networks. This causes Non-Governmental Development Organizations’ efforts to focus on achieving a greater reaction from the public in these communication channels. We propose that the way forward is to analyze aspects of messages that give rise to a greater response from the audience. In this regard, we have analyzed 3608 Facebook and Twitter publications with the combination of content analysis and correlation analysis. We have considered three aspects: purpose, theme, and quality of the message. We have also listed a breakdown of quality and purpose parameters in order to become more fully acquainted with these aspects. The objectives of this research are firstly to carry out the communication profiles of the NGDOs studied from the points of view of the organizations and the public. Secondly, to analyze the reaction from the public (interactions) measured by the sum of likes plus the number of shares for each post, on Facebook and Twitter, according the parameters considered. The results showed that the most published messages from the organizations do not usually coincide with those that have the most impact on the public. Another proven aspect is that Twitter posts about behavior have more effectiveness than informative messages. Likewise, quality aspects, such as hashtags, mentions, or links, are not succeeding in generating public reaction.
Correction: Bountagkidis, G.; et al. EU Development Aid towards Sub-Saharan Africa: Exploring the Normative Principle. Soc. Sci. 2015, 4, 85–116
Authors: Bountagkidis Georgios K. , Fragkos Konstantinos C. , Frangos Christos C.
Published: June 2019

The authors wish to make the following change to their paper (Bountagkidis et al [...]
Governance Discourses Reflecting Tensions in a Multifunctional Land Use System in Decay; Tradition Versus Modernity in the Portuguese Montado
Authors: Pinto-Correia Teresa , Muñoz-Rojas José , Thorsøe Martin Hvarregaard , Noe Egon Bjørnshave
Published: June 2019

The montado is a silvo pastoral system, and the dominant land-use in the region of Alentejo (Portugal). It bears high nature, socio-economic, and landscape values, shaping the strong cultural identity of the region. Despite these values, it has been under decay over the last decades, indicating the inefficiency of current governance strategies. In this paper, we argue how three main discourses can be found that underpin different governance strategies in the montado: The heritage discourse, the modern production discourse, and the land stewardship discourse. These discourses frame farmers’ decisions, though not always explicitly. The discourse analysis is grounded on an analysis of the relevant literature and research results from diverse projects, including an analysis of media representation of the montado since the 1990s, participatory observations, and 30 in-depth interviews with key stakeholders. Each of the three discourses identified are characterized in terms of key farming developments and defining elements, their time-scopes, the ways in which they are perceived by society, their measures of success, and underpinning institutions and power mechanisms. We argue that these discourses co-exist today, and this is a cause of increased tensions in montado governance strategies, hindering more effective and sustainable potential alternatives for the system.
Does What Goes Around Really Comes Around? The Mediating Effect of CSR on the Relationship between Transformational Leadership and Employee’s Job Performance in Law Firms
Authors: Hongdao Qian , Bibi Sughra , Khan Asif , Ardito Lorenzo , Nurunnabi Mohammad
Published: June 2019

Leadership is essential for the success of every organization, as people believe in the ability of their leaders to guide change and achieve success. Today’s law firms are operating in a complex business environment and facing huge competition from both clients and talent. Tough competition, business alliances, corporate social responsibleness, and market conditions demand a huge transformation in the law industry. This study was designed to investigate the relationships between transformational leadership (TL), employee’s job performance (JP), and corporate social responsibility (CSR), as well the mediating mechanism of CSR among TL and JP. The data has been collected from 200 employees working in law firms of Pakistan by using a cross sectional research method. The study hypothesized that TL is significantly related to JP and CSR; in addition, CSR mediates the relationship between TL and JP. Results confirm our conjectures, hence allowing us to contribute to the scant literature of TL, CSR, and JP in the law industry. Our study provides important information to the decision makers who are involved in policymaking; that the adoption of TL practices and involvement in CSR activities can improve JP. Moreover, theoretical and practical implementations are provided for generalization.
Social Factors as a Basic Driver of the Digitalization of the Business Models of Railway Companies
Authors: Jabłoński Marek , Jabłoński Adam
Published: June 2019

The aim of the paper is to present the results of research into the assessment of social factors resulting from the digitalization of railway companies’ business models and building, by means of the AHP method, a ranking of the significance of these criteria in the process of their digital transformation. The results focused on identifying the components of the business models of railway companies that are most affected by social factors and the creation of such factors. Railway companies do not operate within the business environment alone. In the context of processes, they form one common technical and service ecosystem. Digitalization should increase opportunities to create positive social effects which influence the quality of services provided and the safety of rail traffic as well as the increased efficiency of business models.
Degradation Characteristics of Soil-Quality-Related Physical and Chemical Properties Affected by Collapsing Gully: The Case of Subtropical Hilly Region, China
Authors: Feng Shuyue , Wen Hui , Ni Shimin , Wang Junguang , Cai Chongfa
Published: June 2019

In the subtropical hilly areas of China, a collapsing gully, a particular type of permanent gully, poses a great threat to the productivity and sustainability of the local ecological and agricultural systems. However, few studies have been performed regarding the effects of collapsing gully erosion on soil degradation. The aim of this study was to evaluate the effects of collapsing gully erosion on soil-quality-related physical and chemical properties. The collapsing gullies that were severely affected by erosion processes were considered at three stages (initial, active and stable stages) and corresponding soil samples were collected to analyze the spatial variation of the soil physical and chemical quality at each stage. The changes in the properties were assumed to be considerable in the regions affected by the erosion process compared with those unaffected by this process. Soil physical properties were more susceptible than soil nutrients to collapsing gully erosion in different spatial locations. The soil quality index (SQI) system consists of total nitrogen (TN), total phosphorus (TP), pH, capillary porosity (CP), sand content (SA), soil cohesion (SC) and root density (RD). Collapsing gully erosion was found to affect the soil physical and chemical properties by progressively reducing the SQI. The mean SQI value was the lowest in the active stage of the collapsing gully, with a higher soil degradation. For the different spatial positions in the collapsing gullies, the scour channel showed the lowest SQI value. The limiting indicators varied in the different stages or spatial sites in the collapsing gullies.
Is Corporate Social Responsibility Used to Mask Corporate Speculation? Evidence from Emerging China
Authors: Sui Wenjuan , Yang Chunwei , Zhang Huiyu
Published: June 2019

Why do rational, profit-orientated firms generously engage in corporate social responsibility (CSR)? Our study explores the real motives of speculative firms for CSR engagement and the hidden causality behind it. Using national survey data of privately owned firms in China, we find that corporate speculation positively influences firms’ engagement in CSR, revealing that CSR is instrumental and that firms use it as a tool to mask their speculative activities by building their reputations and buying ‘leniency insurance’ against potential penalties. Further, the relationship between speculation and CSR is less pronounced in firms with political involvement, revealing that the effect of political involvement as an informal institution somewhat protects speculators from potential sanctions without a CSR premium. We also discovered that the relationship between corporate speculation and CSR—as well as the moderating role of political involvement—is less pronounced among developed regions, revealing that the development of formal institutions can restrict the instrumentality of CSR and the effect of political involvement. Such findings have important implications for CSR in emerging economies.
Anatomizing the Institutional Arrangements of Urban Village Redevelopment: Case Studies in Guangzhou, China
Authors: Yuan Dinghuan , Yau Yung , Bao Haijun , Liu Yongshen , Liu Ting
Published: June 2019

Given the increasing scarcity of urban land, the Chinese government has been initiating large-scale redevelopment of urban villages that are commonly regarded problematic for their low land use efficiencies and negative externalities. During this process, the emerging neo-urbanism in China demonstrates the heterogeneity of institutional arrangements, with different levels of transaction costs incurred. To explore the transaction costs incurred in different institutional arrangements of urban village redevelopment projects, this study anatomizes three projects in Guangzhou from the perspective of neo-institutional economics. The project duration and level of conflict are taken as two key variables to evaluate the efficiency and equality of the projects. With this research design, this study illustrates that institutional arrangements significantly affect the project outcomes. The conclusion suggests that the local and central governments alter the existing institutions with a view to lowering the transaction costs.
Investigating the Drivers of Farm Diversification Among U.S. Fruit and Vegetable Operations
Authors: Lancaster Nicholas A. , Torres Ariana P.
Published: June 2019

Diversification of an agricultural operation’s crop mix is considered an environmental and financial management strategy. Environmentally, crop diversification can stabilize the ecosystem via the introduction of biodiversity, allowing for more rapid response to physical and social changes. Economically, crop mix diversification can mitigate risk. Though there are environmental and economic benefits of crop diversification, little economic work has been conducted on crop diversification outside of the row crop industry. This study estimated how internal and external factors affect crop diversification among fruit and vegetable (FV) operations. External factors included access to markets and land; internal factors included farmer beliefs and access to information from extension and network sources. An OLS regression was conducted using data from 1532 farmers across 16 states in the United States. Endogeneity was addressed using an instrumental variable approach and a score endogeneity test indicated that endogeneity was not an issue. OLS results indicate that selling locally increases diversification, while reliance on other farmers for information decreases diversification. A conditional quantile analysis was conducted to reveal factors’ effects across different degrees of diversification. Quantile results indicate that selling locally, season extension technologies, and use of organic practices positively influence crop diversification across all levels of diversification. Receiving information from farmers negatively influences diversification for specialized farms, but positively influences diversification for highly diversified operations.
Fusion of Remote Sensing and Internet Data to Calculate Urban Floor Area Ratio
Authors: Zhang Xiaoyong , Chen Zhengchao , Yue Yuemin , Qi Xiangkun , Zhang Charlie H.
Published: June 2019

The floor area ratio is a comprehensive index that plays an important role in urban planning and sustainable development. Remote sensing data are widely used in floor area ratio calculations because they can produce both two-dimensional planar and three-dimensional stereo information on buildings. However, remote sensing is not adequate for calculating the number of floors in a building. In this paper, a simple and practical pixel-level model is established through defining a quantitative relationship among the floor area ratio, building density, and average number of floors (ANF). The floor area ratios are calculated by combining remote sensing data with publicly available Internet data. It incorporates supplemental map data and street-level views from Internet maps to confirm building types and the number of floors, thereby enabling more-accurate floor area ratio calculations. The proposed method is tested in the Tiantongyuan neighborhood, Changping District, Beijing, and the results show that it can accurately approximate the number of floors in buildings. Inaccuracies in the value of the floor area ratio were found to be primarily due to the uncertainties in building density calculations. After performing systematic error correction, the building density (BD) and floor area ratio were each calculated with the relative accuracy exceeding 90%. Moreover, the experiments verified that the fusion of internet map data with remote sensing data has innate advantages for floor area ratio calculations.
Strengthening of RC Structures by Using Engineered Cementitious Composites: A Review
Authors: Shang Xing-yan , Yu Jiang-tao , Li Ling-zhi , Lu Zhou-dao
Published: June 2019

This paper presents a review of the recent work assessing the performance of building structures strengthened with engineered cementitious composite (ECC). ECC characterizes tensile strain hardening and multiple cracking properties, as well as strong interfacial bonding performance with substrate concrete, which makes it a promising retrofitting material. A lot of researches have been conducted on reinforced concrete (RC) structures, including beams, columns, beam–column joints, and fire-damaged slabs, strengthened with ECC material, and an extensive collection of valuable conclusions were obtained. These strengthening systems usually combine ECC with FRP textiles or steel bars to form a composite strengthening layer. The review demonstrates that ECC strengthening can greatly improve the performance of RC structures.
Destination Image Analytics Through Traveller-Generated Content
Authors: Marine-Roig Estela
Published: June 2019

The explosion of content generated by users, in parallel with the spectacular growth of social media and the proliferation of mobile devices, is causing a paradigm shift in research. Surveys or interviews are no longer necessary to obtain users’ opinions, because researchers can get this information freely on social media. In the field of tourism, online travel reviews (OTRs) hosted on travel-related websites stand out. The objective of this article is to demonstrate the usefulness of OTRs to analyse the image of a tourist destination. For this, a theoretical and methodological framework is defined, as well as metrics that allow for measuring different aspects (designative, appraisive and prescriptive) of the tourist image. The model is applied to the region of Attica (Greece) through a random sample of 300,000 TripAdvisor OTRs about attractions, activities, restaurants and hotels written in English between 2013 and 2018. The results show trends, preferences, assessments, and opinions from the demand side, which can be useful for destination managers in optimising the distribution of available resources and promoting sustainability.
Structural Properties of Vicsek-like Deterministic Multifractals
Authors: Anitas Eugen Mircea , Marcelli Giorgia , Szakacs Zsolt , Todoran Radu , Todoran Daniela
Published: June 2019

Deterministic nano-fractal structures have recently emerged, displaying huge potential for the fabrication of complex materials with predefined physical properties and functionalities. Exploiting the structural properties of fractals, such as symmetry and self-similarity, could greatly extend the applicability of such materials. Analyses of small-angle scattering (SAS) curves from deterministic fractal models with a single scaling factor have allowed the obtaining of valuable fractal properties but they are insufficient to describe non-uniform structures with rich scaling properties such as fractals with multiple scaling factors. To extract additional information about this class of fractal structures we performed an analysis of multifractal spectra and SAS intensity of a representative fractal model with two scaling factors—termed Vicsek-like fractal. We observed that the box-counting fractal dimension in multifractal spectra coincide with the scattering exponent of SAS curves in mass-fractal regions. Our analyses further revealed transitions from heterogeneous to homogeneous structures accompanied by changes from short to long-range mass-fractal regions. These transitions are explained in terms of the relative values of the scaling factors.
Intuitionistic Type-2 Fuzzy Set and Its Properties
Authors: Dan Surajit , Kar Mohuya B. , Majumder Saibal , Roy Bikashkoli , Kar Samarjit , Pamucar Dragan
Published: June 2019

Decision making under uncertainty describes situations that consider a profound lack of knowledge, where the functional form is completely unknown, and often, the relevant input and output variables are unknown as well. Data, being the vital input of decision making, contain a dissimilar level of imprecision that necessitates different approaches for making a proper and legitimate decision. In this article, we propose the concept of the intuitionistic type-2 fuzzy set (IT2FS). Several arithmetic operations on IT2FS such as union, intersection, complement, containment, etc., are defined, and the related algebraic properties of IT2FS are also studied. Subsequently, we define two new operators, namely the necessity operator and the possibility operator, to convert an IT2FS into an ordinary T2FS, and then discuss some of their basic properties. Moreover, in this study, two distance measures, the Hamming distance and Euclidian distance of IT2FS, are proposed, and their applications are illustrated with an example.