bluuebunny/crossref_metadata_2025 huggingface dataset:
The Scrap Collection per Industry Sector and the Circulation Times of Steel in the U.S. between 1900 and 2016, Calculated Based on the Volume Correlation Model
Authors: Gauffin Alicia , Pistorius Petrus Christiaan
Published: May 2018

On the basis of the Volume Correlation Model (VCM) as well as data on steel consumption and scrap collection per industry sector (construction, automotive, industrial goods, and consumer goods), it was possible to estimate service lifetimes of steel in the United States between 1900 and 2016. Input data on scrap collection per industry sector was based on a scrap survey conducted by the World Steel Association for a static year in 2014 in the United States. The lifetimes of steel calculated with the VCM method were within the range of previously reported measured lifetimes of products and applications for all industry sectors. Scrapped (and apparent) lifetimes of steel compared with measured lifetimes were calculated to be as follows: a scrapped lifetime of 29 years for the construction sector (apparent lifetime: 52 years) compared with 44 years measured in 2014. Industrial goods: 16 (27) years compared with 19 years measured in 2010. Consumer goods: 12 (14) years compared with 13 years measured in 2014. Automotive sector: 14 (19) years compared with 17 years measured in 2011. Results show that the VCM can estimate reasonable values of scrap collection and availability per industry sector over time.
Effect of Microstructures on Working Properties of Nickel-Manganese-Copper Cast Iron
Authors: Medyński Daniel , Janus Andrzej , Samociuk Bartłomiej , Chęcmanowski Jacek
Published: May 2018

In the paper, the effects, on basic usable properties (abrasive wear and corrosion resistance), of solidification (acc. to the stable and non-stable equilibrium system) and transformations occurring in the matrix during the cooling of castings of Ni-Mn-Cu cast iron were determined. Abrasive wear resistance was mainly determined by the types and arrangements of high-carbon phases (indicated by eutectic saturation degree), and the kinds of matrices (indicated by the nickel equivalent value, calculated from chemical composition). The highest abrasive wear resistance was found for white cast iron, with the highest degree of austenite to martensite transformation occurring in its matrix. Irrespective of solidification, a decrease of the equivalent value below a limit value resulted in increased austenite transformation, and thus, to a significant rise in hardness and abrasive wear resistance for the castings. At the same time, corrosion resistance of the alloy was slightly reduced. The examinations showed that corrosion resistance of Ni-Mn-Cu cast iron is, too a much lesser degree, decided by the means of solidification of the castings, rather than transformations occurring in the matrix, as controlled by nickel equivalent value (especially elements with high electrochemical potential).
A Microfluidic Platform for Investigating Transmembrane Pressure-Induced Glomerular Leakage
Authors: Chen Ting-Hsuan , Chen Jie-Sheng , Ko Yi-Ching , Chen Jyun-Wei , Chu Hsueh-Yao , Lu Chih-Shuan , Chu Chiao-Wen , Hsu Hsiang-Hao , Tseng Fan-Gang
Published: May 2018

Transmembrane pressure across the glomerular filter barrier may underlie renal failure. However, studies of renal failure have been difficult owing to a lack of in vitro models to capture the transmembrane pressure in a controlled approach. Here we report a microfluidic platform of podocyte culture to investigate transmembrane pressure induced glomerular leakage. Podocytes, the glomerular epithelial cells essential for filtration function, were cultivated on a porous membrane supplied with transmembrane pressure ΔP. An anodic aluminum oxide membrane with collagen coating was used as the porous membrane, and the filtration function was evaluated using dextrans of different sizes. The results show that dextran in 20 kDa and 70 kDa can penetrate the podocyte membrane, whereas dextran in 500 kDa was blocked until ΔP ≥ 60 mmHg, which resembles the filtration function when ΔP was in the range of a healthy kidney (ΔP < 60 mmHg) as well as the hypertension-induced glomerular leakage (ΔP ≥ 60 mmHg). Additionally, analysis showed that synaptopodin and actin were also downregulated when ΔP > 30 mmHg, indicating that the dysfunction of renal filtration is correlated with the reduction of synaptopodin expression and disorganized actin cytoskeleton. Taking together, our microfluidic platform enables the investigation of transmembrane pressure in glomerular filter membrane, with potential implications for drug development in the future.
Classical Polarizable Force Field to Study Hydrated Hectorite: Optimization on DFT Calculations and Validation against XRD Data
Authors: Hånde Ragnhild , Ramothe Vivien , Tesson Stéphane , Dazas Baptiste , Ferrage Eric , Lanson Bruno , Salanne Mathieu , Rotenberg Benjamin , Marry Virginie
Published: May 2018

Following our previous works on dioctahedral clays, we extend the classical Polarizable Ion Model (PIM) to trioctahedral clays, by considering dry Na-, Cs-, Ca- and Sr-hectorites as well as hydrated Na-hectorite. The parameters of the force field are determined by optimizing the atomic forces and dipoles on density functional theory calculations. The simulation results are validated by comparison with experimental X-ray diffraction (XRD) data. The XRD patterns calculated from classical molecular dynamics simulations performed with the PIM force field are in very good agreement with experimental results. In the bihydrated state, the less structured electronic density profile obtained with PIM compared to the one from the state-of-the-art non-polarizable force field clayFF explains the slightly better agreement between the PIM results and experiments.
Towards an Asymmetric Organocatalytic α-Azidation of β-Ketoesters
Authors: Tiffner Maximilian , Stockhammer Lotte , Schörgenhumer Johannes , Röser Katharina , Waser Mario
Published: May 2018

Detailed investigations concerning the organocatalytic (asymmetric) α-azidation of prochiral β-ketoesters were carried out. It was shown that the racemic version of such a reaction can either be carried out under oxidative conditions using TMSN3 as the azide-source with quaternary ammonium iodides as the catalysts, or by using hypervalent iodine-based electrophilic azide-transfer reagents with different organocatalysts. In addition, the latter strategy could also be carried out with modest enantioselectivities when using simple cinchona alkaloid catalysts, albeit with relatively low yields.
Network Medicine for Alzheimer’s Disease and Traditional Chinese Medicine
Authors: Jarrell Juliet T. , Gao Li , Cohen David S. , Huang Xudong
Published: May 2018

Alzheimer’s Disease (AD) is a neurodegenerative condition that currently has no known cure. The principles of the expanding field of network medicine (NM) have recently been applied to AD research. The main principle of NM proposes that diseases are much more complicated than one mutation in one gene, and incorporate different genes, connections between genes, and pathways that may include multiple diseases to create full scale disease networks. AD research findings as a result of the application of NM principles have suggested that functional network connectivity, myelination, myeloid cells, and genes and pathways may play an integral role in AD progression, and may be integral to the search for a cure. Different aspects of the AD pathology could be potential targets for drug therapy to slow down or stop the disease from advancing, but more research is needed to reach definitive conclusions. Additionally, the holistic approaches of network pharmacology in traditional Chinese medicine (TCM) research may be viable options for the AD treatment, and may lead to an effective cure for AD in the future.
Tetrel Bonding as a Vehicle for Strong and Selective Anion Binding
Authors: Scheiner Steve
Published: May 2018

Tetrel atoms T (T = Si, Ge, Sn, and Pb) can engage in very strong noncovalent interactions with nucleophiles, which are commonly referred to as tetrel bonds. The ability of such bonds to bind various anions is assessed with a goal of designing an optimal receptor. The Sn atom seems to form the strongest bonds within the tetrel family. It is most effective in the context of a -SnF3 group and a further enhancement is observed when a positive charge is placed on the receptor. Connection of the -SnF3 group to either an imidazolium or triazolium provides a strong halide receptor, which can be improved if its point of attachment is changed from the C to an N atom of either ring. Aromaticity of the ring offers no advantage nor is a cyclic system superior to a simple alkyl amine of any chain length. Placing a pair of -SnF3 groups on a single molecule to form a bipodal dicationic receptor with two tetrel bonds enhances the binding, but falls short of a simple doubling. These two tetrel groups can be placed on opposite ends of an alkyl diamine chain of any length although SnF3+NH2(CH2)nNH2SnF3+ with n between 2 and 4 seems to offer the strongest halide binding. Of the various anions tested, OH− binds most strongly: OH− > F− > Cl− > Br− > I−. The binding energy of the larger NO3− and HCO3− anions is more dependent upon the charge of the receptor. This pattern translates into very strong selectivity of binding one anion over another. The tetrel-bonding receptors bind far more strongly to each anion than an equivalent number of K+ counterions, which leads to equilibrium ratios in favor of the former of many orders of magnitude.
Silver Nanoparticles: Synthetic Routes, In Vitro Toxicity and Theranostic Applications for Cancer Disease
Authors: De Matteis Valeria , Cascione Mariafrancesca , Toma Chiara Cristina , Leporatti Stefano
Published: May 2018

The large use of nanomaterials in many fields of application and commercial products highlights their potential toxicity on living organisms and the environment, despite their physico-chemical properties. Among these, silver nanoparticles (Ag NPs) are involved in biomedical applications such as antibacterial agents, drug delivery vectors and theranostics agents. In this review, we explain the common synthesis routes of Ag NPs using physical, chemical, and biological methods, following their toxicity mechanism in cells. In particular, we analyzed the physiological cellular pathway perturbations in terms of oxidative stress induction, mitochondrial membrane potential alteration, cell death, apoptosis, DNA damage and cytokines secretion after Ag NPs exposure. In addition, their potential anti-cancer activity and theranostic applications are discussed.
The Relative Validity of the Menzies Remote Short-Item Dietary Assessment Tool (MRSDAT) in Aboriginal Australian Children Aged 6–36 Months
Authors: Tonkin Emma , Kennedy Dani , Golley Rebecca , Byrne Rebecca , Rohit Athira , Kearns Therese , Hanieh Sarah , Biggs Beverley-Ann , Brimblecombe Julie
Published: May 2018

The Menzies Remote Short-item Dietary Assessment Tool (MRSDAT) can be used to derive a dietary index score, which measures the degree of compliance with the Australian Dietary Guidelines. This study aimed to determine the relative validity of a dietary index score for children aged 6–24 months, living in a Remote Aboriginal Community (RAC), derived using MRSDAT. This validation study compared dietary index scores derived using MRSDAT with those derived from the average of three 24-h recalls. Participants were aged 6–36 months at the first dietary assessment and were living in a RAC. The level of agreement between the two methods was explored using Lin’s concordance correlation coefficient (CCC), Bland-Altman plots, weighted Cohen’s kappa, and Fischer’s exact and paired t-tests. Forty participants were recruited. The CCC was poor between methods (R = 0.35, 95% CI 0.06, 0.58), with MRSDAT estimating higher dietary intake scores for all food groups except fruit, and higher dietary quality scores by an average of 4.78 points/100. Community-based Aboriginal researchers were central to this validation study. MRSDAT was within the performance range of other short-item dietary assessment tools developed for young children, and shows promise for use with very young children in RACs.
The Quaker Sanctuary Tradition †
Authors: Rabben Linda
Published: May 2018

In the beginning of the Religious Society of Friends, in the seventeenth century, Quakers sought sanctuary from persecution in England and its American colonies. Later they provided sanctuary to people fleeing persecution, slavery, and war in many countries. They base their humanitarian efforts on five Testimonies and their core beliefs in the inner light of God in every person and the primacy of individual conscience. Often their sanctuary activities have led them into conflict with repressive governments and religious authorities. Their relief work with refugees, asylum seekers, and other migrants, sometimes under dangerous conditions, earned them the Nobel Peace Prize in 1947. Despite their small numbers, Quakers have continued to play leadership roles in humanitarian initiatives up to the present day. Their sanctuary tradition has now flourished for more than 350 years.
Exploration of Planetary Hyperspectral Images with Unsupervised Spectral Unmixing: A Case Study of Planet Mars
Authors: Liu Jun , Luo Bin , Douté Sylvain , Chanussot Jocelyn
Published: May 2018

We propose to replace traditional spectral index methods by unsupervised spectral unmixing methods for the exploration of large datasets of planetary hyperspectral images. The main goal of this article is to test the ability of these analysis techniques to automatically extract the spectral signatures of the species present on the surface and to map their abundances accurately and with an acceptable processing time. We consider observations of the surface of Mars acquired by the imaging spectrometer OMEGA aboard MEX as a case study. The moderate spatial resolution (≈300 m/pixel at best) of this instrument implies the systematic existence of geographical mixtures possibly conjugated with non-linear (e.g., intimate) mixtures. We examine the sensitivity of a series of state-of-the-art methods of unmixing to the intrinsic spectral variability of the species in the image and to intimate assemblages of compounds. This study is made possible thanks to the use of well-controlled synthetic data and a real OMEGA image, for which the present icy species (water and carbon dioxide ices) and their characteristic spectra are widely known by the planetary community. Furthermore, reference maps of component abundances are built by the inversion of a more realistic physical model (simulating the propagation of solar light through the atmosphere and reflected back to the sensor) in order to validate the methods with the real image by comparison with the maps extracted by unmixing. The results produced by the processing pipeline of the eigenvalue likelihood maximization (ELM), vertex component analysis (VCA) and non-negativity condition least squares error estimators (NNLS) are the most robust to non-linear effects, highly-mixed pixels and different types of mixtures. Despite this fact, the produced results are not always the best because the VCA method assumes the existence of pure pixels in the image, that is pixels completely occupied by a single species. However, this pipeline is very fast and provides endmember spectra that are always interpretable. Finally, it produces more accurate distribution maps than the spectral index methods. More generally, the potential benefits of unsupervised spectral unmixing methods in planetary exploration is emphasized.
A Hierarchical Sparsity Unmixing Method to Address Endmember Variability in Hyperspectral Image
Authors: Zou Jinlin , Lan Jinhui , Shao Yang
Published: May 2018

With a low spectral resolution hyperspectral sensor, the signal recorded from a given pixel against the complex background is a mixture of spectral contents. To improve the accuracy of classification and subpixel object detection, hyperspectral unmixing (HU) is under research in the field of remote sensing. Two factors affect the accuracy of unmixing results including the search of global rather than local optimum in the HU procedure and the spectral variability. With that in mind, this paper proposes a hierarchical weighted sparsity unmixing (HWSU) method to improve the separation of similar interclass endmembers. The hierarchical strategy with abundance sparsity representation in each layer aims to obtain the global optimal solution. In addition, considering the significance of different bands, a weighted matrix of spectra is used to decrease the variability of intra-class endmembers. Both simulations and experiments with real hyperspectral data show that the proposed method can correctly obtain distinct signatures, accurate abundance estimation, and outperforms previous methods. Additionally, the test data shows that the mean spectral angle distance is less than 0.12 and the root mean square error is superior to 0.01.
Geostationary Sensor Based Forest Fire Detection and Monitoring: An Improved Version of the SFIDE Algorithm
Authors: Di Biase Valeria , Laneve Giovanni
Published: May 2018

The paper aims to present the results obtained in the development of a system allowing for the detection and monitoring of forest fires and the continuous comparison of their intensity when several events occur simultaneously—a common occurrence in European Mediterranean countries during the summer season. The system, called SFIDE (Satellite FIre DEtection), exploits a geostationary satellite sensor (SEVIRI, Spinning Enhanced Visible and InfraRed Imager, on board of MSG, Meteosat Second Generation, satellite series). The algorithm was developed several years ago in the framework of a project (SIGRI) funded by the Italian Space Agency (ASI). This algorithm has been completely reviewed in order to enhance its efficiency by reducing false alarms rate preserving a high sensitivity. Due to the very low spatial resolution of SEVIRI images (4 × 4 km2 at Mediterranean latitude) the sensitivity of the algorithm should be very high to detect even small fires. The improvement of the algorithm has been obtained by: introducing the sun elevation angle in the computation of the preliminary thresholds to identify potential thermal anomalies (hot spots), introducing a contextual analysis in the detection of clouds and in the detection of night-time fires. The results of the algorithm have been validated in the Sardinia region by using ground true data provided by the regional Corpo Forestale e di Vigilanza Ambientale (CFVA). A significant reduction of the commission error (less than 10%) has been obtained with respect to the previous version of the algorithm and also with respect to fire-detection algorithms based on low earth orbit satellites.
Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks
Authors: Shah Shashi , Kittipiyakul Somsak , Lim Yuto , Tan Yasuo
Published: May 2018

The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.
IrisDenseNet: Robust Iris Segmentation Using Densely Connected Fully Convolutional Networks in the Images by Visible Light and Near-Infrared Light Camera Sensors
Authors: Arsalan Muhammad , Naqvi Rizwan Ali , Kim Dong Seop , Nguyen Phong Ha , Owais Muhammad , Park Kang Ryoung
Published: May 2018

The recent advancements in computer vision have opened new horizons for deploying biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition is now much needed in unconstraint scenarios with accuracy. These environments make the acquired iris image exhibit occlusion, low resolution, blur, unusual glint, ghost effect, and off-angles. The prevailing segmentation algorithms cannot cope with these constraints. In addition, owing to the unavailability of near-infrared (NIR) light, iris recognition in visible light environment makes the iris segmentation challenging with the noise of visible light. Deep learning with convolutional neural networks (CNN) has brought a considerable breakthrough in various applications. To address the iris segmentation issues in challenging situations by visible light and near-infrared light camera sensors, this paper proposes a densely connected fully convolutional network (IrisDenseNet), which can determine the true iris boundary even with inferior-quality images by using better information gradient flow between the dense blocks. In the experiments conducted, five datasets of visible light and NIR environments were used. For visible light environment, noisy iris challenge evaluation part-II (NICE-II selected from UBIRIS.v2 database) and mobile iris challenge evaluation (MICHE-I) datasets were used. For NIR environment, the institute of automation, Chinese academy of sciences (CASIA) v4.0 interval, CASIA v4.0 distance, and IIT Delhi v1.0 iris datasets were used. Experimental results showed the optimal segmentation of the proposed IrisDenseNet and its excellent performance over existing algorithms for all five datasets.
Quantitative Determining of Ultra-Trace Aluminum Ion in Environmental Samples by Liquid Phase Microextraction Assisted Anodic Stripping Voltammetry
Authors: Zhang Liuyang , Luo Jinju , Shen Xinyu , Li Chunya , Wang Xian , Nie Bei , Fang Huaifang
Published: May 2018

Direct detecting of trace amount Al(III) in aqueous solution by stripping voltammetry is often frustrated by its irreversible reduction, resided at −1.75 V (vs. Ag/AgCl reference), which is in a proximal potential of proton reduction. Here, we described an electroanalytical approach, combined with liquid phase microextraction (LPME) using ionic liquid (IL), to quantitatively assess trace amount aluminum in environmental samples. The Al(III) was caged by 8-hydroxyquinoline, forming a superb hydrophobic metal–chelate, which sequentially transfers and concentrates in the bottom layer of IL-phase during LPME. The preconcentrated Al(III) was further analyzed by a square-wave anodic stripping voltammetry (SW-ASV). The resulting Al-deposited electrodes were characterized by scanning electron microscopy and powder X-ray diffraction, showing the intriguing amorphous nanostructures. The method developed provides a linear calibration ranging from 0.1 to 1.2 ng L−1 with a correlation coefficient of 0.9978. The LOD attains as low as 1 pmol L−1, which reaches the lowest report for Al(III) detection using electroanalytical techniques. The applicable methodology was implemented for monitoring Al(III) in commercial distilled water.
Unifying Terrain Awareness for the Visually Impaired through Real-Time Semantic Segmentation
Authors: Yang Kailun , Wang Kaiwei , Bergasa Luis M. , Romera Eduardo , Hu Weijian , Sun Dongming , Sun Junwei , Cheng Ruiqi , Chen Tianxue , López Elena
Published: May 2018

Navigational assistance aims to help visually-impaired people to ambulate the environment safely and independently. This topic becomes challenging as it requires detecting a wide variety of scenes to provide higher level assistive awareness. Vision-based technologies with monocular detectors or depth sensors have sprung up within several years of research. These separate approaches have achieved remarkable results with relatively low processing time and have improved the mobility of impaired people to a large extent. However, running all detectors jointly increases the latency and burdens the computational resources. In this paper, we put forward seizing pixel-wise semantic segmentation to cover navigation-related perception needs in a unified way. This is critical not only for the terrain awareness regarding traversable areas, sidewalks, stairs and water hazards, but also for the avoidance of short-range obstacles, fast-approaching pedestrians and vehicles. The core of our unification proposal is a deep architecture, aimed at attaining efficient semantic understanding. We have integrated the approach in a wearable navigation system by incorporating robust depth segmentation. A comprehensive set of experiments prove the qualified accuracy over state-of-the-art methods while maintaining real-time speed. We also present a closed-loop field test involving real visually-impaired users, demonstrating the effectivity and versatility of the assistive framework.
An Adaption Broadcast Radius-Based Code Dissemination Scheme for Low Energy Wireless Sensor Networks
Authors: Yu Shidi , Liu Xiao , Liu Anfeng , Xiong Naixue , Cai Zhiping , Wang Tian
Published: May 2018

Due to the Software Defined Network (SDN) technology, Wireless Sensor Networks (WSNs) are getting wider application prospects for sensor nodes that can get new functions after updating program codes. The issue of disseminating program codes to every node in the network with minimum delay and energy consumption have been formulated and investigated in the literature. The minimum-transmission broadcast (MTB) problem, which aims to reduce broadcast redundancy, has been well studied in WSNs where the broadcast radius is assumed to be fixed in the whole network. In this paper, an Adaption Broadcast Radius-based Code Dissemination (ABRCD) scheme is proposed to reduce delay and improve energy efficiency in duty cycle-based WSNs. In the ABCRD scheme, a larger broadcast radius is set in areas with more energy left, generating more optimized performance than previous schemes. Thus: (1) with a larger broadcast radius, program codes can reach the edge of network from the source in fewer hops, decreasing the number of broadcasts and at the same time, delay. (2) As the ABRCD scheme adopts a larger broadcast radius for some nodes, program codes can be transmitted to more nodes in one broadcast transmission, diminishing the number of broadcasts. (3) The larger radius in the ABRCD scheme causes more energy consumption of some transmitting nodes, but radius enlarging is only conducted in areas with an energy surplus, and energy consumption in the hot-spots can be reduced instead due to some nodes transmitting data directly to sink without forwarding by nodes in the original hot-spot, thus energy consumption can almost reach a balance and network lifetime can be prolonged. The proposed ABRCD scheme first assigns a broadcast radius, which doesn’t affect the network lifetime, to nodes having different distance to the code source, then provides an algorithm to construct a broadcast backbone. In the end, a comprehensive performance analysis and simulation result shows that the proposed ABRCD scheme shows better performance in different broadcast situations. Compared to previous schemes, the transmission delay is reduced by 41.11~78.42%, the number of broadcasts is reduced by 36.18~94.27% and the energy utilization ratio is improved up to 583.42%, while the network lifetime can be prolonged up to 274.99%.
Experiments and Analysis of Close-Shot Identification of On-Branch Citrus Fruit with RealSense
Authors: Liu Jizhan , Yuan Yan , Zhou Yao , Zhu Xinxin , Syed Tabinda Naz
Published: May 2018

Fruit recognition based on depth information has been a hot topic due to its advantages. However, the present equipment and methods cannot meet the requirements of rapid and reliable recognition and location of fruits in close shot for robot harvesting. To solve this problem, we propose a recognition algorithm for citrus fruit based on RealSense. This method effectively utilizes depth-point cloud data in a close-shot range of 160 mm and different geometric features of the fruit and leaf to recognize fruits with a intersection curve cut by the depth-sphere. Experiments with close-shot recognition of six varieties of fruit under different conditions were carried out. The detection rates of little occlusion and adhesion were from 80–100%. However, severe occlusion and adhesion still have a great influence on the overall success rate of on-branch fruits recognition, the rate being 63.8%. The size of the fruit has a more noticeable impact on the success rate of detection. Moreover, due to close-shot near-infrared detection, there was no obvious difference in recognition between bright and dark conditions. The advantages of close-shot limited target detection with RealSense, fast foreground and background removal and the simplicity of the algorithm with high precision may contribute to high real-time vision-servo operations of harvesting robots.
The Effects of Sleep Extension on Sleep, Performance, Immunity and Physical Stress in Rugby Players
Authors: Swinbourne Richard , Miller Joanna , Smart Daniel , Dulson Deborah , Gill Nicholas
Published: May 2018

(1) Background: The purpose of the present study was to examine the efficacy of sleep extension in professional rugby players. The aims were to: (i) characterise sleep quantity in elite rugby players and determine changes in immune function and stress hormone secretion during a pre-season training programme; (ii) evaluate the efficacy of a sleep extension intervention in improving sleep, markers of physical stress, immune function and performance. (2) Methods: Twenty five highly trained athletes from a professional rugby team (age (mean ± SD) 25 ± 2.7 years; height 1.87 ± 0.07 m; weight 105 ± 12.1 kg) participated in a six week pre-post control-trial intervention study. Variables of sleep, immune function, sympathetic nervous activity, physiological stress and reaction times were measured. (3) Results: Sleep extension resulted in a moderate improvement in sleep quality scores ([mean; ± 90% confidence limits] −24.8%; ± 54.1%) and small to moderate increases in total sleep time (6.3%; ± 6.3%) and time in bed (7.3%; ± 3.6%). In addition, a small decrease in cortisol (−18.7%; ± 26.4%) and mean reaction times (−4.3%; ± 3.1%) was observed following the intervention, compared to the control. (4) Conclusions: Professional rugby players are at risk of poor sleep during pre-season training, with concomitant rises in physical stress. Implementing a sleep extension programme among professional athletes is recommended to improve sleep, with beneficial changes in stress hormone expression and reaction time performance.
Climate Change Communication in an Online Q&A Community: A Case Study of Quora
Authors: Jiang Hanchen , Qiang Maoshan , Zhang Dongcheng , Wen Qi , Xia Bingqing , An Nan
Published: May 2018

An emerging research trend in climate change studies is to use user-generated-data collected from social media to investigate the public opinion and science communication of climate change issues. This study collected data from the social Q&A website Quora to explore the key factors influencing the public preferences in climate change knowledge and opinions. Using web crawler, topic modeling, and count data regression modeling, this study quantitatively analyzed the effects of an answer’s textual and auxiliary features on the number of up-votes received by the answer. Compared with previous studies based on open-ended surveys of citizens, the topic modeling result indicates that Quora users are more likely to talk about the energy, human and societal issues, and scientific research rather than the natural phenomena of climate change. The regression modeling results show that: (i) answers with more emphasis on specific subjects, but not popular knowledge, about climate change can get significantly more up-votes; (ii) answers with more terms of daily dialogue will get significantly fewer up-votes; and (iii) answers written by an author with more followers, with a longer text, with more images, or belonging to a question with more followers, can get significantly more up-votes.
The Collaborative Networks and Thematic Trends of Research on Purchasing and Supply Management for Environmental Sustainability: A Bibliometric Review
Authors: Zhu Wenwen , Wang Zhiqiang
Published: May 2018

Improving environmental sustainability through purchasing and supply management (PSM) has gained increasing attention from both industry and academia. However, few attempts have been made to summarize the research development of this field. This study aims to identify the major author collaborative networks and thematic trends of this field by conducting a bibliometric review based on 371 peer-reviewed articles published between 1998 and 2017 using CiteSpace. The results show that this field is an emergent and fast-growing field which has been recognized by multiple disciplines. In terms of authors, the top ten influential authors represented by Sarkis, J., Zhu, Q.H., Vachon, S., and Klassen, R.D. were identified. Further, the four largest collaborative networks with varying research topics such as green supplier selection/evaluation and sustainable sub-supplier management were found. As for the research themes, the six largest research themes were abstracted: green supplier assessment, sustainable supplier/supply chain management, green supplier management, green supplier selection, environmental purchasing, and green supply chain management (GSCM). Further, the research thread over time was summarized as four stages: infancy stage, grow-up stage, surging stage, and deep-going stage. Finally, future research directions were given. To the best of the authors’ knowledge, this is the first systematic review of this field using bibliometric analysis, comprehensively acknowledging the current research status of this field and that of the future.
Estimation and Forecasts for the Share of Renewable Energy Consumption in Final Energy Consumption by 2020 in the European Union
Authors: Mehedintu Anca , Sterpu Mihaela , Soava Georgeta
Published: May 2018

European Union Directive 2009/28/EC established that the share of renewable energy in the final energy consumption should reach a target of 20% by 2020 in European Union (EU) countries. This study analyses the tendency of this share using data for EU 28, taken from the Eurostat database for the period 1995–2016. First, after a brief statistical and economic analysis of the three macroeconomic indicators at EU level, five regression models (polynomial, ARIMA) were used to estimate the evolution of the share of renewable energy consumption into the final energy consumption, all of them showing an increasing trend for this indicator. The positive impact of the EU Directive in increasing this share was proved by means of a perturbed regression model. Forecasts of this share for the 2020 horizon were obtained, all showing that the EU target is yet to be reached. Secondly, four groups of EU-countries were considered, according to the final energy consumption. Empirical estimations of renewable energy share into the final energy consumption showed increasing trend for all groups, while providing forecasts quite different from the EU ones. Also, economic interpretations of the results are performed.
Comparative Analysis of Public Attitudes toward Nuclear Power Energy across 27 European Countries by Applying the Multilevel Model
Authors: Wang Jaesun , Kim Seoyong
Published: May 2018

Despite its potential risks, nuclear power energy offers some economic benefits including cheap electricity. This benefit clarifies part of the reason why people support nuclear energy. Our research examined whether there was a difference in the acceptance of nuclear energy across 27 European countries in 2009, before the Fukushima accident. In particular, we analyzed how each factor at the individual and contextual level influences the acceptance. To answer this question, we set up the acceptance of nuclear energy as a dependent variable, and 5 perception variables at the individual level and 11 structural ones at the contextual level as independent variables. We executed multilevel modeling by using a Eurobarometer survey, which covered 27 European countries. The analysis results showed that at the individual level, the perceived benefit explained the largest variance of the acceptance, followed by perceived risk and trust. At the contextual level, the share of the energy supply by nuclear power, environmentalism and ideology influenced the acceptance of nuclear energy. This study shows that individuals’ acceptance of nuclear energy is based on individual beliefs and perceptions, but it is also influenced by the institutional and socio-cultural context which each country faces.
Novel Botulinum Neurotoxins: Exploring Underneath the Iceberg Tip
Authors: Azarnia Tehran Domenico , Pirazzini Marco
Published: May 2018

Botulinum neurotoxins (BoNTs), the etiological agents of botulism, are the deadliest toxins known to humans. Yet, thanks to their biological and toxicological features, BoNTs have become sophisticated tools to study neuronal physiology and valuable therapeutics for an increasing number of human disorders. BoNTs are produced by multiple bacteria of the genus Clostridium and, on the basis of their different immunological properties, were classified as seven distinct types of toxin. BoNT classification remained stagnant for the last 50 years until, via bioinformatics and high-throughput sequencing techniques, dozens of BoNT variants, novel serotypes as well as BoNT-like toxins within non-clostridial species have been discovered. Here, we discuss how the now “booming field” of botulinum neurotoxin may shed light on their evolutionary origin and open exciting avenues for future therapeutic applications.
Single Viruses on the Fluorescence Microscope: Imaging Molecular Mobility, Interactions and Structure Sheds New Light on Viral Replication
Authors: Parveen Nagma , Borrenberghs Doortje , Rocha Susana , Hendrix Jelle
Published: May 2018

Viruses are simple agents exhibiting complex reproductive mechanisms. Decades of research have provided crucial basic insights, antiviral medication and moderately successful gene therapy trials. The most infectious viral particle is, however, not always the most abundant one in a population, questioning the utility of classic ensemble-averaging virology. Indeed, viral replication is often not particularly efficient, prone to errors or containing parallel routes. Here, we review different single-molecule sensitive fluorescence methods that we employ routinely to investigate viruses. We provide a brief overview of the microscopy hardware needed and discuss the different methods and their application. In particular, we review how we applied (i) single-molecule Förster resonance energy transfer (smFRET) to probe the subviral human immunodeficiency virus (HIV-1) integrase (IN) quaternary structure; (ii) single particle tracking to study interactions of the simian virus 40 with membranes; (iii) 3D confocal microscopy and smFRET to quantify the HIV-1 pre-integration complex content and quaternary structure; (iv) image correlation spectroscopy to quantify the cytosolic HIV-1 Gag assembly, and finally; (v) super-resolution microscopy to characterize the interaction of HIV-1 with tetherin during assembly. We hope this review is an incentive for setting up and applying similar single-virus imaging studies in daily virology practice.
Indirect Damage of Urban Flooding: Investigation of Flood-Induced Traffic Congestion Using Dynamic Modeling
Authors: Zhu Jingxuan , Dai Qiang , Deng Yinghui , Zhang Aorui , Zhang Yingzhe , Zhang Shuliang
Published: May 2018

In many countries, industrialization has led to rapid urbanization. Increased frequency of urban flooding is one consequence of the expansion of urban areas which can seriously affect the productivity and livelihoods of urban residents. Therefore, it is of vital importance to study the effects of rainfall and urban flooding on traffic congestion and driver behavior. In this study, a comprehensive method to analyze the influence of urban flooding on traffic congestion was developed. First, a flood simulation was conducted to predict the spatiotemporal distribution of flooding based on Storm Water Management Model (SWMM) and TELAMAC-2D. Second, an agent-based model (ABM) was used to simulate driver behavior during a period of urban flooding, and a car-following model was established. Finally, in order to study the mechanisms behind how urban flooding affects traffic congestion, the impact of flooding on urban traffic was investigated based on a case study of the urban area of Lishui, China, covering an area of 4.4 km2. It was found that for most events, two-hour rainfall has a certain impact on traffic congestion over a five-hour period, with the greatest impact during the hour following the cessation of the rain. Furthermore, the effects of rainfall with 10- and 20-year return periods were found to be similar and small, whereas the effects with a 50-year return period were obvious. Based on a combined analysis of hydrology and transportation, the proposed methods and conclusions could help to reduce traffic congestion during flood seasons, to facilitate early warning and risk management of urban flooding, and to assist users in making informed decisions regarding travel.
Soft-Link Control for Electric Light Vehicle
Authors: Omae Manabu , Ogitsu Takeki , Shimizu Hiroshi
Published: May 2018

This study developed a soft-link control system for electric light vehicles. The meaning of the soft-link control is that a vehicle automatically follows the preceding vehicle with a very short inter-vehicle distance as if the both vehicles were mechanically connected. The soft-link control is expected to stretch the limitation of the light vehicles, because small capacity of the light vehicle is timely enlarged, resulting in giving a potential to apply them to more various purposes. In this study, the experimental vehicles are developed based on small electric vehicles and control algorithms are designed. Stability and reliability of control and accurate tracking are realized by using information of the preceding vehicle sent via wireless LAN communication. The experimental results show that the controlled vehicle can follow the preceding vehicle with an inter-vehicle distance of less than 1[m].
Peak Power based Fuel Cell Hybrid Propulsion System
Authors: VAN MIERLO Joeri , Timmermans Jean-Marc , MAGGETTO Gaston , VAN DEN BOSSCHE Peter
Published: May 2018

Hybrid electric propulsion systems are interesting solutions to increase the energy efficiency of the road transportation technology. In this paper, several series hybrid propulsion system topologies are analysed in the Vehicle Simulation Programme (VSP). Especially the use of a DC/DC converter connected between the DC-bus and a energy source like a battery or the fuel cell stack, the supercapacitor or both are investigated together with its control algorithms in the validated VSP model. Both the advantages and drawbacks of the different topologies are presented. On the basis of experimental results, the proposed power management control strategy is also validated, which can ensure the main power supply (e.g. fuel cell) only providing the moving average power.
Development of an EV Drive Torque Control System for Improving Vehicle Handling Performance Through Steering Improvements
Authors: Shiozawa Yuuki , Kobayashi Yosuke , Ohta Mitsunori , Murata Toshiyuki , Kageyama Yusuke , Nakamura Yohei , Misawa Hideaki
Published: May 2018

At Nissan we have developed many different environmental technologies to date and launched sales of an electric vehicle (EV) in December 2010 that achieves zero carbon dioxide and zero exhaust emissions. Besides its outstanding environmental performance, this zero-emission EV also embodies new potentialities not found in conventional gasoline-engine vehicles. The responsiveness and controllability of the electrified powertrain (EV drive motor) combine to provide an unprecedented driving experience that transforms conventional thinking about automobiles.This paper presents an EV drive torque control system that takes advantage of this EV-unique performance to provide handling capabilities for driving ease that anyone can enjoy.
Predicting the strain-mediated topological phase transition in 3D cubic ThTaN3
Authors: Zhang Chunmei , Du Aijun
Published: May 2018

The cubic ThTaN3 compound has long been known as a semiconductor with a band gap of approximately 1 eV, but its electronic properties remain largely unexplored. By using density functional theory, we find that the band gap of ThTaN3 is very sensitive to the hydrostatic pressure/strain. A Dirac cone can emerge around the Γ point with an ultrahigh Fermi velocity at a compressive strain of 8%. Interestingly, the effect of spin–orbital coupling (SOC) is significant, leading to a band gap reduction of 0.26 eV in the ThTaN3 compound. Moreover, the strong SOC can turn ThTaN3 into a topological insulator with a large inverted gap up to 0.25 eV, which can be primarily attributed to the inversion between the d-orbital of the heavy element Ta and the p-orbital of N. Our results highlight a new 3D topological insulator with strain-mediated topological transition for potential applications in future spintronics.
Toward the ICRF3: Astrometric Comparison of the USNO 2016A VLBI Solution with ICRF2 and Gaia DR1
Authors: Frouard Julien , Johnson Megan C. , Fey Alan , Makarov Valeri V. , Dorland Bryan N.
Published: May 2018

The VLBI USNO 2016A (U16A) solution is part of a work-in-progress effort by USNO toward the preparation of the ICRF3. Most of the astrometric improvement with respect to the ICRF2 is due to the re-observation of the VCS sources. Our objective in this paper is to assess U16A’s astrometry. A comparison with ICRF2 shows statistically significant offsets of size 0.1 mas between the two solutions. While Gaia DR1 positions are not precise enough to resolve these offsets, they are found to be significantly closer to U16A than ICRF2. In particular, the trend for typically larger errors for southern sources in VLBI solutions is decreased in U16A. Overall, the VLBI-Gaia offsets are reduced by 21%. The U16A list includes 718 sources not previously included in ICRF2. Twenty of those new sources have statistically significant radio-optical offsets. In two-thirds of the cases, these offsets can be explained from PanSTARRS images.
A Search for Molecular Gas in the Host Galaxy of FRB 121102
Authors: Bower Geoffrey C. , Rao Ramprasad , Krips Melanie , Maddox Natasha , Bassa Cees , Adams Elizabeth A. K. , Law C. J. , Tendulkar Shriharsh P. , Langevelde Huib Jan van , Paragi Zsolt , Butler Bryan J. , Chatterjee Shami
Published: May 2018

We present Submillimeter Array and Northern Extended Millimeter Array observations of the host galaxy of FRB 121102 in the CO 3–2 and 1–0 transitions, respectively. We do not detect emission from either transition. We set 3σ upper limits to the CO luminosity L
CO < 2.5 × 107 K km s−1 pc−2 for CO 3–2 and L
CO < 2.3 × 109 K km s−1 pc−2 for CO 1–0. For Milky Way–like star formation properties, we set a 3σ upper limit on the H2 mass of 2.5 × 108
M
⊙, slightly less than the predictions for the H2 mass based on the star formation rate. The true constraint on the H2 mass may be significantly higher, however, because of the reduction in CO luminosity that is common for low-metallicity dwarf galaxies like the FRB host galaxy. These results demonstrate the challenge of identifying the nature of FRB progenitors through study of the host galaxy molecular gas. We also place a limit of 42 μJy (3σ) on the continuum flux density of the persistent radio source at 97 GHz, consistent with a power-law extrapolation of the low-frequency spectrum, which may arise from an active galactic nucleus or other nonthermal source.