bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Seawater Ageing on Fracture of Carbon Fiber Reinforced Epoxy Composites for Ocean Engineering
Authors: Le Guen-Geffroy Antoine , Davies Peter , Le Gac Pierre-Yves , Habert Bertrand
Published: September 2020

Carbon fiber reinforced composite materials are finding new applications in highly loaded marine structures such as tidal turbine blades and marine propellers. Such applications require long-term damage resistance while being subjected to continuous seawater immersion. However, few data exist on which to base material selection and design. This paper provides a set of results from interlaminar fracture tests on specimens before and after seawater ageing. The focus is on delamination as this is the main failure mechanism for laminated composites under out-of-plane loading. Results show that there are two contributions to changes in fracture toughness during an accelerated wet ageing program: effects due to water and effects due to physical ageing. These are identified and it is shown that this composite retains over 70% of its initial fracture properties even for the worst case examined.
Explanation of Photon Navigation in the Mach-Zehnder Interferometer
Authors: Pons Dirk J.
Published: September 2020

Photons in interferometers manifest the functional ability to simultaneously navigate both paths through the device, but eventually appear at only one outlet. How this relates to the physical behaviour of the particle is still ambiguous, even though mathematical representation of the problem is adequate. This paper applies a non-local hidden-variable (NLHV) solution, in the form of the Cordus theory, to explain photon path dilemmas in the Mach–Zehnder (MZ) interferometer. The findings suggest that the partial mirrors direct the two reactive ends of the Cordus photon structures to different legs of the apparatus, depending on the energisation state of the photon. Explanations are provided for a single photon in the interferometer in the default, open-path, and sample modes. The apparent intelligence in the system is not because the photon knows which path to take, but rather because the MZ interferometer is a finely-tuned photon-sorting device that auto-corrects for randomness in the frequency phase to direct the photon to a specific detector. The principles also explain other tunnelling phenomena involving barriers. Thus, navigation dilemmas in the MZ interferometer may be explained in terms of physical realism after all.
The Development and Proof of Principle Test of TRIAGE: A Practical Question Set to Identify and Discuss Medication-Related Problems in Community Pharmacy
Authors: Vervloet Marcia , Zwikker Hanneke E. , Linn Annemiek J. , Koster Ellen S. , Gipmans Suzan G. H. , van Aarle Maaike C. W. , van Dijk Liset
Published: September 2020

The pharmacy counter is a good place to identify and discuss medication-related problems. However, there is a lack of practical communication tools to support pharmacy technicians (PTs) in initiating a conversation with patients. This study aimed to develop and test a practical set of questions for PTs, called TRIAGE, to identify problems during encounters. TRIAGE was developed based on insight from the literature, focus groups with PTs and pharmacists, and input from patients and experts. In 10 community pharmacies, 17 PTs used TRIAGE during encounters with patients who collected their cardiovascular medication. For each encounter, PTs registered the identified problems and suggested solutions. A total of 105 TRIAGE conversations were held, 66 for first refill and 39 for follow-up refill prescriptions. In 15 (23%) first refill prescription encounters, a problem was identified. These problems concerned forgetting to take the medication, a complex medication regime or (fear of) side effects. In three (8%) follow-up refill prescription encounters, a problem was identified. Most of the problems were solved on the spot. Pharmacy technicians indicated that they identified medication-related problems with TRIAGE that otherwise would be left unnoticed. They appreciated TRIAGE as a useful instrument for starting the conversation with patients about medication use.
Teaching Research Ethics to Pharmacists: The Practice of Participatory Learning
Authors: Ogura Miku , Takehira Rieko , Arita Etsuko
Published: September 2020

The research history of community pharmacists in Japan is short, and ethical responses may not be mature. Therefore, the Japan Pharmaceutical Association and universities are working on research ethics education to help pharmacists make appropriate ethical responses. In this study, we evaluated whether an educational program using participatory learning was effective in research ethics education for pharmacists. Regarding the educational effects of our workshop, the score for motivation to learn about research ethics was high, and that for judgment and applied skills related to research ethics was low. Overall, participants’ assessment of the program contents was extremely favorable, indicating their satisfaction. Participatory learning was widely accepted and suggested to be effective in improving learning motivation. Additionally, to be able to apply the knowledge of research ethics to own research, it was considered necessary to continue learning through participatory learning. This will help pharmacists gain judgment and applied skills related to research ethics.
Mitochondrial Genome of Fagus sylvatica L. as a Source for Taxonomic Marker Development in the Fagales
Authors: Mader Malte , Schroeder Hilke , Schott Thomas , Schöning-Stierand Katrin , Leite Montalvão Ana Paula , Liesebach Heike , Liesebach Mirko , Fussi Barbara , Kersten Birgit
Published: September 2020

European beech, Fagus sylvatica L., is one of the most important and widespread deciduous tree species in Central Europe and is widely managed for its hard wood. The complete DNA sequence of the mitochondrial genome of Fagus sylvatica L. was assembled and annotated based on Illumina MiSeq reads and validated using long reads from nanopore MinION sequencing. The genome assembled into a single DNA sequence of 504,715 bp in length containing 58 genes with predicted function, including 35 protein-coding, 20 tRNA and three rRNA genes. Additionally, 23 putative protein-coding genes were predicted supported by RNA-Seq data. Aiming at the development of taxon-specific mitochondrial genetic markers, the tool SNPtax was developed and applied to select genic SNPs potentially specific for different taxa within the Fagales. Further validation of a small SNP set resulted in the development of four CAPS markers specific for Fagus, Fagaceae, or Fagales, respectively, when considering over 100 individuals from a total of 69 species of deciduous trees and conifers from up to 15 families included in the marker validation. The CAPS marker set is suitable to identify the genus Fagus in DNA samples from tree tissues or wood products, including wood composite products.
Model-Free Extremum Seeking Control of Bioprocesses: A Review with a Worked Example
Authors: Dewasme Laurent , Vande Wouwer Alain
Published: September 2020

Uncertainty is a common feature of biological systems, and model-free extremum-seeking control has proved a relevant approach to avoid the typical problems related to model-based optimization, e.g., time- and resource-consuming derivation and identification of dynamic models, and lack of robustness of optimal control. In this article, a review of the past and current trends in model-free extremum seeking is proposed with an emphasis on finding optimal operating conditions of bioprocesses. This review is illustrated with a simple simulation case study which allows a comparative evaluation of a few selected methods. Finally, some experimental case studies are discussed. As usual, practice lags behind theory, but recent developments confirm the applicability of the approach at the laboratory scale and are encouraging a transfer to industrial scale.
New Insights on Protein Recovery from Olive Oil Mill Wastewater through Bioconversion with Edible Filamentous Fungi
Authors: Sar Taner , Ozturk Murat , Taherzadeh Mohammad J. , Ferreira Jorge A.
Published: September 2020

Olive oil mills represent an important sector in the Mediterranean Sea Basin but also an environmental hazard due to untreated wastewater. Recovery of nutrients from olive oil mill wastewater (OMWW) as protein-rich microbial biomass can produce novel feed and reduce its chemical oxygen demand; however, low-protein containing products have been reported. New strategies leading to higher protein-containing fungal biomass could renew the research interest on bioconversion for pollution mitigation of OMWW. In this work, through cultivation of edible filamentous fungi (Aspergillus oryzae, Neurospora intermedia, and Rhizopus delemar), a link between the protein content in the originated fungal biomass, and the addition of nitrogen and medium dilution was established. Addition of nitrogen in the form of NaNO3 reduced the cultivation time from 96 h to 48 h while achieving a similar biomass mass concentration of 8.43 g/L and increased biomass protein content, from w = 15.9% to w = 29.5%. Nitrogen addition and dilution of OMWW, and consequent reduction of suspended solids, led to an increase in the protein content to up to w = 44.9%. To the best of our knowledge, the protein contents achieved are the highest reported to date and can open new research avenues towards bioconversion of OMWW using edible filamentous fungi.
Thermal Assessment of a Micro Fibrous Fischer Tropsch Fixed Bed Reactor Using Computational Fluid Dynamics
Authors: Abusrafa Aya E. , Challiwala Mohamed S. , Wilhite Benjamin A. , Elbashir Nimir O.
Published: September 2020

A two-dimensional (2D) Computational Fluid Dynamics (CFD) scale-up model of the Fischer Tropsch reactor was developed to thermally compare the Microfibrous-Entrapped-Cobalt-Catalyst (MFECC) and the conventional Packed Bed Reactor (PBR). The model implements an advanced predictive detailed kinetic model to study the effect of a thermal runaway on C5+ hydrocarbon product selectivity. Results demonstrate the superior capability of the MFECC bed in mitigating hotspot formation due to its ultra-high thermal conductivity. Furthermore, a process intensification study for radial scale-up of the reactor bed from 15 mm internal diameter (ID) to 102 mm ID demonstrated that large tube diameters in PBR lead to temperature runaway >200 K corresponding to >90% CO conversion at 100% methane selectivity, which is highly undesirable. While the MFECC bed hotspot temperature corresponded to <10 K at >30% CO conversion, attributing to significantly high thermal conductivity of the MFECC bed. Moreover, a noticeable improvement in C5+ hydrocarbon selectivity >70% was observed in the MFECC bed in contrast to a significantly low number for the PBR (<5%).
Cyclostationary Analysis towards Fault Diagnosis of Rotating Machinery
Authors: Tang Shengnan , Yuan Shouqi , Zhu Yong
Published: September 2020

In the light of the significance of the rotating machinery and the possible severe losses resulted from its unexpected defects, it is vital and meaningful to exploit the effective and feasible diagnostic methods of its faults. Among them, the emphasis of the analysis approaches for fault type and severity is on the extraction of useful components in the fault features. On account of the common cyclostationarity of vibration signal under faulty states, fault diagnosis methods based on cyclostationary analysis play an essential role in the rotatory machine. Based on it, the fundamental definition and classification of cyclostationarity are introduced briefly. The mathematical principles of the essential cyclic spectral analysis are outlined. The significant applications of cyclostationary theory are highlighted in the fault diagnosis of the main rotating machinery, involving bearing, gear, and pump. Finally, the widely-used methods on the basis of cyclostationary theory are concluded, and the potential research directions are prospected.
First Experiment of Spin Contrast Variation Small-Angle Neutron Scattering on the iMATERIA Instrument at J-PARC
Authors: Noda Yohei , Maeda Tomoki , Oku Takayuki , Koizumi Satoshi , Masui Tomomi , Kishimoto Hiroyuki
Published: September 2020

Recently, we have developed a novel dynamic nuclear polarization (DNP) apparatus with a magnetic field of 7 T and a sample temperature of 1 K. High proton spin polarizations from −84% to 76%, for TEMPO doped polystyrene samples, have been demonstrated. This DNP apparatus satisfies the simultaneous requirement for quick and easy sample exchange and high DNP performance. On the iMATERIA (BL20) instrument at J-PARC, the first beam experiment using this DNP apparatus has been performed. For this experiment, the beamline was equipped with a supermirror polarizer. The stray magnetic field due to the superconducting magnet for DNP was also evaluated. The stray magnetic field plays an important role for in maintaining the neutron polarization during the transportation from the polarizer to the sample. The small-angle neutron scattering (SANS) profiles of silica-filled rubber under dynamically polarized conditions are presented. By applying our new analytical approach for SANS coherent scattering intensity, neutron polarization (PN) as a function of neutron wavelength was determined. Consequently, for the neutron wavelength, range from 4 Å to 10 Å, |PN| was sufficient for DNP-SANS studies.
“Glory to the Righteous One” (Tzvi la-tzaddik) (Isa. 24:16): The Use of Biblical Quotations in the Polemic against the Sabbatean Movement
Authors: Breier Idan
Published: September 2020

Promoted by Nathan of Gaza—a reputable figure—Sabbatai Tzvi was hailed as the messiah across the Jewish communities of the medieval world, thousands flocking to his side. One of his prominent detractors was R. Jacob Sasportas, who wrote numerous letters to his peers—rabbis of the western Sephardi diaspora—in order to dissuade them from giving Sabbatai their support and prove Nathan to be a false prophet. Much of Tzitzat novel Tzvi consists of his extensive correspondence on the subject, together with the responses he received. The rich language in which it is couched reflects the biblical citations on which all the parties drew in order to clarify their position and substantiate their arguments. Herein, I examine this significant but relatively neglected phenomenon, focusing primarily on Sasportas’ exegesis of Scripture and the peculiar meanings the biblical text assumed within the context of the polemic.
A Generative Adversarial Network Approach to Calibration of Local Stochastic Volatility Models
Authors: Cuchiero Christa , Khosrawi Wahid , Teichmann Josef
Published: September 2020

We propose a fully data-driven approach to calibrate local stochastic volatility (LSV) models, circumventing in particular the ad hoc interpolation of the volatility surface. To achieve this, we parametrize the leverage function by a family of feed-forward neural networks and learn their parameters directly from the available market option prices. This should be seen in the context of neural SDEs and (causal) generative adversarial networks: we generate volatility surfaces by specific neural SDEs, whose quality is assessed by quantifying, possibly in an adversarial manner, distances to market prices. The minimization of the calibration functional relies strongly on a variance reduction technique based on hedging and deep hedging, which is interesting in its own right: it allows the calculation of model prices and model implied volatilities in an accurate way using only small sets of sample paths. For numerical illustration we implement a SABR-type LSV model and conduct a thorough statistical performance analysis on many samples of implied volatility smiles, showing the accuracy and stability of the method.
Detection of Longhorned Borer Attack and Assessment in Eucalyptus Plantations Using UAV Imagery
Authors: Duarte André , Acevedo-Muñoz Luis , Gonçalves Catarina I. , Mota Luís , Sarmento Alexandre , Silva Margarida , Fabres Sérgio , Borralho Nuno , Valente Carlos
Published: September 2020

Eucalyptus Longhorned Borers (ELB) are some of the most destructive pests in regions with Mediterranean climate. Low rainfall and extended dry summers cause stress in eucalyptus trees and facilitate ELB infestation. Due to the difficulty of monitoring the stands by traditional methods, remote sensing arises as an invaluable tool. The main goal of this study was to demonstrate the accuracy of unmanned aerial vehicle (UAV) multispectral imagery for detection and quantification of ELB damages in eucalyptus stands. To detect spatial damage, Otsu thresholding analysis was conducted with five imagery-derived vegetation indices (VIs) and classification accuracy was assessed. Treetops were calculated using the local maxima filter of a sliding window algorithm. Subsequently, large-scale mean-shift segmentation was performed to extract the crowns, and these were classified with random forest (RF). Forest density maps were produced with data obtained from RF classification. The normalized difference vegetation index (NDVI) presented the highest overall accuracy at 98.2% and 0.96 Kappa value. Random forest classification resulted in 98.5% accuracy and 0.94 Kappa value. The Otsu thresholding and random forest classification can be used by forest managers to assess the infestation. The aggregation of data offered by forest density maps can be a simple tool for supporting pest management.
Development of a Machine Learning-Based Radiometric Bias Correction for NOAA’s Microwave Integrated Retrieval System (MiRS)
Authors: Zhou Yan , Grassotti Christopher
Published: September 2020

We present the development of a dynamic over-ocean radiometric bias correction for the Microwave Integrated Retrieval System (MiRS) which accounts for spatial, temporal, spectral, and angular dependence of the systematic differences between observed and forward model-simulated radiances. The dynamic bias correction, which utilizes a deep neural network approach, is designed to incorporate dependence on the atmospheric and surface conditions that impact forward model biases. The approach utilizes collocations of observed Suomi National Polar-orbiting Partnership/Advanced Technology Microwave Sounder (SNPP/ATMS) radiances and European Centre for Medium-Range Weather Forecasts (ECMWF) model analyses which are used as input to the Community Radiative Transfer Model (CRTM) forward model to develop training data of radiometric biases. Analysis of the neural network performance indicates that in many channels, the dynamic bias is able to reproduce realistically both the spatial patterns of the original bias and its probability distribution function. Furthermore, retrieval impact experiments on independent data show that, compared with the baseline static bias correction, using the dynamic bias correction can improve temperature and water vapor profile retrievals, particularly in regions with higher Cloud Liquid Water (CLW) amounts. Ocean surface emissivity retrievals are also improved, for example at 23.8 GHz, showing an increase in correlation from 0.59 to 0.67 and a reduction of standard deviation from 0.035 to 0.026.
An Airport Knowledge-Based Method for Accurate Change Analysis of Airport Runways in VHR Remote Sensing Images
Authors: Ding Wei , Wu Jidong
Published: September 2020

Due to the complexity of airport background and runway structure, the performances of most runway extraction methods are limited. Furthermore, at present, the military fields attach greater importance to semantic changes of some objects in the airport, but few studies have been done on this subject. To address these issues, this paper proposes an accurate runway change analysis method, which comprises two stages: airport runway extraction and runway change analysis. For the former stage, some airport knowledge, such as chevron markings and runway edge markings, are first applied in combination with multiple features of runways to improve the accuracy. In addition, the proposed method can accomplish airport runway extraction automatically. For the latter, semantic information and vector results of runway changes can be obtained simultaneously by comparing bi-temporal runway extraction results. In six test images with about 0.5-m spatial resolution, the average completeness of runway extraction is nearly 100%, and the average quality is nearly 89%. In addition, the final experiment using two sets of bi-temporal very high-resolution (VHR) images of runway changes demonstrated that semantic results obtained by our method are consistent with the real situation and the final accuracy is over 80%. Overall, the airport knowledge, especially chevron markings for runways and runway edge markings, are critical to runway recognition/detection, and multiple features of runways, such as shape and parallel line features, can further improve the completeness and accuracy of runway extraction. Finally, a small step has been taken in the study of runway semantic changes, which cannot be accomplished by change detection alone.
How Do Urban Parks Provide Bird Habitats and Birdwatching Service? Evidence from Beijing, China
Authors: Zhang Zhengkai , Huang Ganlin
Published: September 2020

Parks are an important green infrastructure. Besides other benefits for human and animals, parks provide important bird habitats and accommodate most human-bird interactions in cities. Understanding the complex dynamics among park characteristics, bird habitats and park attractiveness to birdwatchers will inform park designers and managers. However, previous studies often examined factors influencing bird habitats and birdwatching activities separately. To fill this gap, we aim to study the whole picture of “parks, birds and birdwatchers” in Beijing, China for its spatial patterns and possible factors which influence bird habitat areas and birdwatching services. We conducted a three-month bird census in at 159 sites and mapped bird habitat areas in parks of Beijing through the maximum entropy method based on results of the bird survey as well as high-resolution remote sensing data. We derived the number of birdwatching records to describe birdwatching activities from the China Birdwatching Record Center website. We used correlation analysis, regression and analysis of variance to investigate factors that may influence areas of bird habitats and the number of birdwatching records for each park. Our results showed that among the 102 parks, 61 provide habitats to breeding birds with an average of 17 ha, and 26 parks generated a total of 330 birdwatching records. Park size, age, proportion of pavement, landscape connectedness, pavement largest patch index and woodland patch density explained 95% of the variation in habitat areas altogether. Bird habitat area alone explained 65% of the variation in the number of birdwatching records. Furthermore, parks with birdwatching records are significantly larger, older, closer to the city center and more accessible than those have no reported birdwatching. These findings have important implications for park management. While park size or age cannot be easily changed, modifying landscape patterns can increase bird habitats in parks, and improving accessibility may attract more birdwatchers to parks that already have considerable bird habitats.
Early Fire Detection Based on Aerial 360-Degree Sensors, Deep Convolution Neural Networks and Exploitation of Fire Dynamic Textures
Authors: Barmpoutis Panagiotis , Stathaki Tania , Dimitropoulos Kosmas , Grammalidis Nikos
Published: September 2020

The environmental challenges the world faces have never been greater or more complex. Global areas that are covered by forests and urban woodlands are threatened by large-scale forest fires that have increased dramatically during the last decades in Europe and worldwide, in terms of both frequency and magnitude. To this end, rapid advances in remote sensing systems including ground-based, unmanned aerial vehicle-based and satellite-based systems have been adopted for effective forest fire surveillance. In this paper, the recently introduced 360-degree sensor cameras are proposed for early fire detection, making it possible to obtain unlimited field of view captures which reduce the number of required sensors and the computational cost and make the systems more efficient. More specifically, once optical 360-degree raw data are obtained using an RGB 360-degree camera mounted on an unmanned aerial vehicle, we convert the equirectangular projection format images to stereographic images. Then, two DeepLab V3+ networks are applied to perform flame and smoke segmentation, respectively. Subsequently, a novel post-validation adaptive method is proposed exploiting the environmental appearance of each test image and reducing the false-positive rates. For evaluating the performance of the proposed system, a dataset, namely the “Fire detection 360-degree dataset”, consisting of 150 unlimited field of view images that contain both synthetic and real fire, was created. Experimental results demonstrate the great potential of the proposed system, which has achieved an F-score fire detection rate equal to 94.6%, hence reducing the number of required sensors. This indicates that the proposed method could significantly contribute to early fire detection.
GPS/BDS RTK Positioning Based on Equivalence Principle Using Multiple Reference Stations
Authors: Wang Jian , Xu Tianhe , Nie Wenfeng , Xu Guochang
Published: September 2020

Reliable real-time kinematic (RTK) is crucially important for emerging global navigation satellite systems (GNSSs) applications, such as drones and unmanned vehicles. The performance of conventional single baseline RTK (SBRTK) with one reference station degrades greatly in dense, urban environments, due to signal blockage and multipath error. The increasing use of multiple reference stations for kinematic positioning can improve RTK positioning accuracy and availability in urban areas. This paper proposes a new algorithm for multi-baseline RTK (MBRTK) positioning based on the equivalence principle. The advantages of the solution are to keep observation independent and increase the redundancy to estimate the unknown parameters. The equivalent double-differenced (DD) observation equations for multiple reference stations are firstly developed through the equivalent transform. A modified Kalman filter with parameter constraints is proposed, as well as a partial ambiguity resolution (PAR) strategy is developed to determine an ambiguity subset. Finally, the static and kinematic experiments are carried out to validate the proposed algorithm. The results demonstrate that, compared with single global positioning system (GPS) and Beidou navigation system (BDS) RTK positioning, the GPS/BDS positioning for MBRTK can enhance the positioning accuracy with improvement by approximately (45%, 35%, and 27%) and (12%, 6%, and 19%) in the North (N), East (E), and Up (U) components, as well as the availability with improvement by about 33% and 10%, respectively. Moreover, the MBRTK model with two and three reference receivers can significantly increase the redundancy and provide smaller ambiguity dilution of precision (ADOP) values. Compared with the scheme-one and scheme-two for SBRTK, the MBRTK with multiple reference receivers have a positioning accuracy improvement by about (9%, 0%, and 6%) and (9%, 16%, and 16%) in N, E, and U components, as well as the availability improvement by approximately 10%. Therefore, compared with the conventional SBRTK, the MBRTK can enhance the strength of the kinematic positioning model as well as improve the positioning accuracy and availability.
Development of Fog Detection Algorithm Using GK2A/AMI and Ground Data
Authors: Han Ji-Hye , Suh Myoung-Seok , Yu Ha-Yeong , Roh Na-Young
Published: September 2020

Fog affects transportation due to low visibility and also aggravates air pollutants. Thus, accurate detection and forecasting of fog are important for the safety of transportation. In this study, we developed a decision tree type fog detection algorithm (hereinafter GK2A_FDA) using the GK2A/AMI and auxiliary data. Because of the responses of the various channels depending on the time of day and the underlying surface characteristics, several versions of the algorithm were created to account for these differences according to the solar zenith angle (day/dawn/night) and location (land/sea/coast). Numerical model data were used to distinguish the fog from low clouds. To test the detection skill of GK2A_FDA, we selected 23 fog cases that occurred in South Korea and used them to determine the threshold values (12 cases) and validate GK2A_FDA (11 cases). Fog detection results were validated using the visibility data from 280 stations in South Korea. For quantitative validation, statistical indices, such as the probability of detection (POD), false alarm ratio (FAR), bias ratio (Bias), and equitable threat score (ETS), were used. The total average POD, FAR, Bias, and ETS for training cases (validation cases) were 0.80 (0.82), 0.37 (0.29), 1.28 (1.16), and 0.52 (0.59), respectively. In general, validation results showed that GK2A_FDA effectively detected the fog irrespective of time and geographic location, in terms of accuracy and stability. However, its detection skill and stability were slightly dependent on geographic location and time. In general, the detection skill and stability of GK2A_FDA were found to be better on land than on coast at all times, and at night than day at any location.
Light-Weight Student LSTM for Real-Time Wildfire Smoke Detection
Authors: Jeong Mira , Park MinJi , Nam Jaeyeal , Ko Byoung Chul
Published: September 2020

As the need for wildfire detection increases, research on wildfire smoke detection combining low-cost cameras and deep learning technology is increasing. Camera-based wildfire smoke detection is inexpensive, allowing for a quick detection, and allows a smoke to be checked by the naked eye. However, because a surveillance system must rely only on visual characteristics, it often erroneously detects fog and clouds as smoke. In this study, a combination of a You-Only-Look-Once detector and a long short-term memory (LSTM) classifier is applied to improve the performance of wildfire smoke detection by reflecting on the spatial and temporal characteristics of wildfire smoke. However, because it is necessary to lighten the heavy LSTM model for real-time smoke detection, in this paper, we propose a new method for applying the teacher–student framework to deep LSTM. Through this method, a shallow student LSTM is designed to reduce the number of layers and cells constituting the LSTM model while maintaining the original deep LSTM performance. As the experimental results indicate, our proposed method achieves up to an 8.4-fold decrease in the number of parameters and a faster processing time than the teacher LSTM while maintaining a similar detection performance as deep LSTM using several state-of-the-art methods on a wildfire benchmark dataset.
A Novel Weighted Clustering Algorithm Supported by a Distributed Architecture for D2D Enabled Content-Centric Networks
Authors: Aslam Saad , Alam Fakhrul , Hasan Syed Faraz , Rashid Mohammad
Published: September 2020

Next generation cellular systems need efficient content-distribution schemes. Content-sharing via Device-to-Device (D2D) clustered networks has emerged as a popular approach for alleviating the burden on the cellular network. In this article, we utilize Content-Centric Networking and Network Virtualization to propose a distributed architecture, that supports efficient content delivery. We propose to use clustering at the user level for content-distribution. A weighted multifactor clustering algorithm is proposed for grouping the D2D User Equipment (DUEs) sharing a common interest. The proposed algorithm is evaluated in terms of energy efficiency, area spectral efficiency, and throughput. The effect of the number of clusters on these performance parameters is also discussed. The proposed algorithm has been further modified to allow for a tradeoff between fairness and other performance parameters. A comprehensive simulation study demonstrates that the proposed clustering algorithm is more flexible and outperforms several classical and state-of-the-art algorithms.
Raman Microscopy: Progress in Research on Cancer Cell Sensing
Authors: Elumalai Satheeshkumar , Managó Stefano , De Luca Anna Chiara
Published: September 2020

In the last decade, Raman Spectroscopy (RS) was demonstrated to be a label-free, non-invasive and non-destructive optical spectroscopy allowing the improvement in diagnostic accuracy in cancer and analytical assessment for cell sensing. This review discusses how Raman spectra can lead to a deeper molecular understanding of the biochemical changes in cancer cells in comparison to non-cancer cells, analyzing two key examples, leukemia and breast cancer. The reported Raman results provide information on cancer progression and allow the identification, classification, and follow-up after chemotherapy treatments of the cancer cells from the liquid biopsy. The key obstacles for RS applications in cancer cell diagnosis, including quality, objectivity, number of cells and velocity of the analysis, are considered. The use of multivariant analysis, such as principal component analysis (PCA) and linear discriminate analysis (LDA), for an automatic and objective assessment without any specialized knowledge of spectroscopy is presented. Raman imaging for cancer cell mapping is shown and its advantages for routine clinical pathology practice and live cell imaging, compared to single-point spectral analysis, are debated. Additionally, the combination of RS with microfluidic devices and high-throughput screening for improving the velocity and the number of cells analyzed are also discussed. Finally, the combination of the Raman microscopy (RM) with other imaging modalities, for complete visualization and characterization of the cells, is described.
Measurement of the Flow Field Generated by Multicopter Propellers
Authors: Czyż Zbigniew , Karpiński Paweł , Stryczniewicz Wit
Published: September 2020

This paper presents the results of research on the airflow around a multirotor aircraft. The research consisted of the analysis of the velocity field using particle image velocimetry. Based on the tests carried out in a wind tunnel, the distribution of the velocity and its components in the vertical plane passing through the propeller axis were determined for several values of the angle of attack of the tested object for two values of airflow velocity inside the tunnel, i.e., vwt = 0 m/s and vwt = 12.5 m/s. Determining the velocity value as a function of the coordinates of the adopted reference system allowed for defining the range of impact of the horizontal propellers and the fuselage of the research object itself. The tests allowed for quantitative and qualitative analyses of the airflow through the horizontal rotor. Particular attention was paid to the impact of the airflow and the angle of attack on the obtained velocity field distributions.
Monitoring Transepidermal Water Loss and Skin Wettedness Factor with Battery-Free NFC Sensor
Authors: Ali Syed Muhammad , Chung Wan-Young
Published: September 2020

The transepidermal water loss (TEWL) and the skin wettedness factor (SWF) are considered parts of a key perspective related to skincare. The former is used to determine the loss of water content from the stratum corneum (SC), while the latter is used to determine the human skin comfort level. Herein, we developed two novel approaches: (1) determination of the TEWL and the SWF based on a battery-free humidity sensor, and (2) the design of a battery-free smart skincare sensor device tag that can harvest energy from a near field communication (NFC)-enabled smartphone, making it a battery-free design approach. The designed skincare device tag has a diameter of 2.6 cm and could harvest energy (~3 V) from the NFC-enabled smartphone. A series of experimental tests involving the participation of eight and six subjects were conducted in vivo for the indoor and outdoor environments, respectively. During the experimental analysis, the skin moisture content level was measured at different times of the day using an android smartphone. The TEWL and SWF values were calculated based on these sensor readings. For the TEWL case: if the skin moisture is high, the TEWL is high, and if the skin moisture is low, the TEWL is low, ensuring that the skin moisture and the TEWL follow the same trend. Our smart skincare device is enclosed in a 3D flexible design print, and it is battery-free with an android application interface that is more convenient to carry outside than other commercially available battery-based devices.
One-Shot Learning for Partial Discharge Diagnosis Using Ultra-High-Frequency Sensor in Gas-Insulated Switchgear
Authors: Tuyet-Doan Vo-Nguyen , Do The-Duong , Tran-Thi Ngoc-Diem , Youn Young-Woo , Kim Yong-Hwa
Published: September 2020

In recent years, deep learning has been successfully used in order to classify partial discharges (PDs) for assessing the condition of insulation systems in different electrical equipment. However, fault diagnosis using deep learning is still challenging, as it requires a large amount of training data, which is difficult and expensive to obtain in the real world. This paper proposes a novel one-shot learning method for fault diagnosis using a small dataset of phase-resolved PDs (PRPDs) in a gas-insulated switchgear (GIS). The proposed method is based on a Siamese network framework, which employs a distance metric function for predicting sample pairs from the same PRPD class or different PRPD classes. Experimental results over the small PRPD dataset that was obtained from an ultra-high-frequency sensor in the GIS show that the proposed method achieves outstanding performance for PRPD fault diagnosis as compared with the previous methods.
An Evaluation of the Impact of Ecological Compensation on the Cross-Section Efficiency Using SFA and DEA: A Case Study of Xin’an River Basin
Authors: Dong Junran , Wu Desheng
Published: September 2020

This paper aims to address the issue of evaluating watershed environmental efficiency with ecological compensation. One of the main objectives is the dynamic assessment of cross-section efficiency. The first transboundary watershed ecological compensation pilot of Xin’an river basin serves as the case study, and stochastic frontier analysis (SFA) is adopted as the main evaluation method. Furthermore, the efficiency is estimated by the data envelopment analysis (DEA) approach. The results validate that SFA can be used as an effective method on such issues by comparing it with the benchmark and the result of DEA, which proves the feasibility of our research methodology. The other purpose is to investigate the factors affecting environmental efficiency. This paper explores the relationship between environmental efficiency with 21 pollutant emission factors as well as the correlation between environmental efficiency and five macro factors of economic development, industrial structure, population density, degree of environmental protection, and natural environment. Finally, suggestions are provided for future improvement. This paper therefore presents a comprehensive reference analysis that contributes to facilitating balanced regional development and environmental conservation in the future.
Mechanism and Effect of Shantytown Reconstruction under Balanced and Full Development: A Case Study of Nanjing, China
Authors: Yuan Yaqi , Song Weixuan
Published: September 2020

Shantytown is a type of urban residential space with a long history in populated areas; it is a negative and stark space with a gradual decline in function and poverty. It is also a concentrated reflection of an unbalanced and inadequate development of the urban social space, which restricts the development of a high-quality and sustainable social economy. Taking shantytown reconstruction in Nanjing as an example, based on the information of 434 shantytown plots dating from 2008 to 2020, it combines the two typical cases of state-owned land: Xijie and collective land—Nanhe, and the questionnaire data regarding the removal and resettlement of residents, the driving mechanism and the effect of social space reconstruction of shantytown. Reconstruction is mainly discussed based on the overall understanding of the space–time characteristics of shantytown reconstruction in Nanjing. It is found that the top-down policy which transfer from the central government to the local government, the value orientation of urban growth alliance in pursuit of asset appreciation, and the interest demands and game attitude of shantytown residents from the bottom up are all important forces to promote shantytown reconstruction. Shantytown reconstruction plays a key role in improving the housing conditions of residents; it fully taps on the potential land value, thus enhancing the urban function and quality. However, the gentrification reconstruction of the original shantytown space, and the centralized resettlement of the poor groups in the urban fringes, have led to an unbalanced development of the new urban social space, with an insufficient guarantee for the removal and resettlement groups. In view of the social space problems caused by the poor people living in the outer suburbs, this paper puts forward some recommendations on policy optimization and plan adjustment of shantytown reconstruction.
Entrepreneurship in an Increasingly Digital and Global World. Evaluating the Role of Digital Capabilities on International Entrepreneurial Intention
Authors: von Arnim Laura , Mrozewski Matthias
Published: September 2020

Given the growing role of entrepreneurial companies in international markets, recent research endeavors direct their attention towards understanding the role of digital technologies for the internationalization efforts of new ventures. Thereby, existing research is mostly focused on explaining the enabling role of digital technologies as a contextual frame, but widely neglects the role of the individual and his/her capabilities to make use of those technologies. This paper aims at closing the above research gap by focusing on digital capabilities and investigating their effect on the intention to engage in international entrepreneurship. With the help of structural equation modeling, we integrate the concept of digital capabilities into the Theory of Planned Behavior (TPB) and empirically analyze the complex relationship between digital capabilities, the three TPB dimensions, and international entrepreneurial intention (IEI). Using a student sample from a major German university (n = 198), we find evidence for the significant role of digital capabilities for IEI through its positive effects on an individual’s attitude towards international entrepreneurship and perceived behavioral control.
Potential Pathways to the German Bioeconomy: A Media Discourse Analysis of Public Perceptions
Authors: Dieken Sophia , Venghaus Sandra
Published: September 2020

The bioeconomy has emerged as a popular, but ambiguous vision for a sustainable future. Its implementation depends not only on novel products and production processes, but also on balancing diverse interests, values, and interpretations of the concept. The German government’s plan to develop a sustainable bioeconomy in response to structural change in the lignite mining regions provides a unique opportunity to investigate what pathways towards the bioeconomy are supported by society. In order to characterize bioeconomy visions prevalent in public perception, we conducted a computer-assisted, mixed-methods discourse analysis of German-language newspaper articles published between 2010 and 2019. Results show that a techno-economic vision is dominant over ecological and social aspects, suggesting only one clear pathway to the German bioeconomy, which is increasingly criticized in the public debate.
Sensitivity Analysis as a Tool in Environmental Policy for Sustainability: The Case of Waste Recycling Projects in the Republic of Serbia
Authors: Denčić-Mihajlov Ksenija , Krstić Mladen , Spasić Dejan
Published: September 2020

Modern consumer society uses an increasing number of products to meet its needs, which become waste after use, thus posing a serious problem that threatens sustainable development. Investment in waste recycling, due to a high level of non-financial benefits, is considered sustainable, especially in the End-of-life Vehicles (ELV) and Waste Electrical and Electronic Equipment (WEEE) recycling areas. The research objective of this paper is to test the sensitivity of the model for sustainable management of recycling projects by applying a cost-benefit analysis (CBA) to investment projects of car and refrigerator recycling in the Republic of Serbia. By testing the key risk factors of the above investment projects within the sensitivity analysis, the main aim is to determine the critical value of these variables in terms of the financial and social acceptability of these investment alternatives. The results obtained indicate that state subsidies have the greatest influence on defining the model of sustainable investment, especially in the field of e-waste recycling. The impact of other factors, the price of secondary raw materials and the social cost of CO2 emissions, is significantly smaller, but should certainly be taken into account when defining the optimal model of sustainable investment.
Performance Analysis of a New Electricity and Freshwater Production System Based on an Integrated Gasification Combined Cycle and Multi-Effect Desalination
Authors: Hamrang Farzad , Shokri Afshar , Mahmoudi S. M. Seyed , Ehghaghi Biuk , Rosen Marc A.
Published: September 2020

Integrated biomass gasification combined cycles can be advantageous for providing multiple products simultaneously. A new electricity and freshwater generation system is proposed based on the integrated gasification and gas turbine cycle as the main system, and a steam Rankine cycle and multi-effect desalination system as the waste heat recovery units. To evaluate the performance of the system, energy, exergy, and economic analyses were performed. Also, a parametric analysis was performed to assess the effects of various parameters on the system’s performance criteria. The economic feasibility of the plant was analyzed in terms of net present value. For the base case, the performance metrics are evaluated as W.net=8.347 MW, ε=46.22%, SUCP=14.07 $/GJ, and m.fw=11.7 kg/s. Among all components of the system, the combustion chamber is the greatest contributor to the exergy destruction rate, at 3250 kW. It is shown with the parametric analysis that raising the combustion temperature leads to higher electricity and freshwater production capacity. For a fuel cost of 2 $/GJ and an electricity price of 0.07 $/kWh, the total net present value at the end of plant’s lifespan is 6.547×106 $, and the payback period is 6.75 years. Thus, the plant is feasible from an economic perspective.
Corporate Sustainability in Bangladeshi Banks: Proactive or Reactive Ethical Behavior?
Authors: Weber Olaf , Chowdury Rezaul Karim
Published: September 2020

The purpose of this study is to analyze the connection between the sustainability performance and financial performance of Bangladeshi banks to explore the impact of the Bangladesh Environmental Risk Management Guideline. We analyzed all 56 scheduled commercial banks that are currently operating in Bangladesh under the guidelines of the Central Bank of Bangladesh. Data for the sample has been collected from publicly available reports such as annual, sustainability, and corporate social responsibility (CSR) reports, disclosed sustainability and financial information on the banks’ websites, including all bank branches, and data published from the Central Bank. Data has been analyzed using panel regression. Our results indicate that higher sustainability performance creates a higher financial performance, and that bigger banks perform better with regard to sustainability than smaller banks. The analysis did not find, however, that higher financial performance influences the sustainability performance of the banks positively. Consequently, this research contributes to the research on legitimacy-driven behavior of Bangladeshi banks. This behavior rather leads to a reactive adoption of sustainability activities instead of proactive behavior.