bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Effect of Zn Ferrite Nanoparticles on the Thermomechanical, Dielectric and Magnetic Properties of Polymer Nanocomposites
Authors: Sanida Aikaterini , Stavropoulos Sotirios G. , Speliotis Thanassis , Psarras Georgios C.
Published: September 2019

In this study nanocomposites consisting of an epoxy resin and ceramic zinc ferrite nanoparticles have been successfully developed and investigated morphologically and structurally by means of scanning electron microscopy (SEM) images and X-ray diffraction (XRD) spectra. The thermal properties of the nanocomposites were studied via differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The thermomechanical characterization of the fabricated nanocomposites was studied via dynamic mechanical analysis (DMA) and the magneto-dielectric response was assessed by means of a broadband dielectric spectroscopy (BDS) and by employing a superconducting quantum interference device (SQUID) magnetometer. Data analysis demonstrates that the incorporation of nanoinclusions into the matrix improves both the thermomechanical and the dielectric properties of the systems, as indicated by the increase of the storage modulus, the real part of dielectric permittivity and conductivity values with filler content, while at the same time induces magnetic properties into the matrix. Zinc ferrite nanoparticles and their respective nanocomposites exhibit superparamagnetic behavior at room temperature. Three relaxations were recorded in the dielectric spectra of all systems; originating from the filler and the polymer matrix, namely interfacial polarization, glass to rubber transition of the polymer matrix and the reorientation of small polar side groups of the polymer chain.
A Dual-Band Terahertz Absorber with Two Passbands Based on Periodic Patterned Graphene
Authors: Zhang Ximeng , Wu Weiwei , Li Chenxin , Wang Chang , Ma Yuhong , Yang Zhangbiao , Sun Guang , Yuan Naichang
Published: September 2019

In this paper, a dual-band terahertz absorber with two passbands is proposed. The absorber is composed of periodic patterned graphene arrays on the top of a SiO 2 substrate and a frequency selective surface (FSS) on the bottom of the substrate. The simulated results indicate that there are two absorption bands (absorption greater than 90%) ranging from 0.54 to 0.84 THz and 2.13 to 2.29 THz. It is almost transparent to incident waves (transmission greater than 50%) below 0.19 THz and between 1.3 and 1.67 THz with a center frequency of 1.49 THz. The absorber has a good tolerance to the transverse electric (TE) and transverse magnetic (TM) polarized wave oblique incidence, and the transmission rate of the passbands remains greater than 50% within 70 degrees. Moreover, the absorption rate of the absorber can be tuned by the chemical potential of graphene. The structure with absorption and transmission properties has potential applications in filtering, sensing, detecting and antenna stealth.
Numerical Integral Transform Methods for Random Hyperbolic Models with a Finite Degree of Randomness
Authors: Casabán M. Consuelo , Company Rafael , Jódar Lucas
Published: September 2019

This paper deals with the construction of numerical solutions of random hyperbolic models with a finite degree of randomness that make manageable the computation of its expectation and variance. The approach is based on the combination of the random Fourier transforms, the random Gaussian quadratures and the Monte Carlo method. The recovery of the solution of the original random partial differential problem throughout the inverse integral transform allows its numerical approximation using Gaussian quadratures involving the evaluation of the solution of the random ordinary differential problem at certain concrete values, which are approximated using Monte Carlo method. Numerical experiments illustrating the numerical convergence of the method are included.
Optimal Sliced Latin Hypercube Designs with Slices of Arbitrary Run Sizes
Authors: Zhang Jing , Xu Jin , Jia Kai , Yin Yimin , Wang Zhengming
Published: September 2019

Sliced Latin hypercube designs (SLHDs) are widely used in computer experiments with both quantitative and qualitative factors and in batches. Optimal SLHDs achieve better space-filling property on the whole experimental region. However, most existing methods for constructing optimal SLHDs have restriction on the run sizes. In this paper, we propose a new method for constructing SLHDs with arbitrary run sizes, and a new combined space-filling measurement describing the space-filling property for both the whole design and its slices. Furthermore, we develop general algorithms to search for the optimal SLHD with arbitrary run sizes under the proposed measurement. Examples are presented to illustrate that effectiveness of the proposed methods.
Modelling of Mass and Thermal Balance and Simulation of Iron Sintering Process with Biomass
Authors: Legemza Jaroslav , Fröhlichová Mária , Findorák Róbert , Džupková Martina
Published: September 2019

This paper specifies the mathematical and physical modelling of the iron sintering process in laboratory conditions. The aim is to get the simplest approach (using thermodynamic software “HSC Chemistry”, version 9, Outokumpu Research Oy, Pori, Finland) that allows one to predict the output parameters based on the initial composition analysis. As a part of the application of mathematical modelling, a mass and thermal balance of combustion of carbonaceous fuels (including biomass) and a mass and thermal balance of high-temperature sintering of an agglomeration charge were determined. The objective of the paper was to point out the advantages of modelling using thermodynamic software and apply the results into a simulation of the sintering process. The outcome of mathematical modelling correlates to the outcome of physical modelling for fuel combustion and the agglomerate production in a laboratory sintering pan. The energy required to reach the desired sintering temperatures and acquire the standard quality of agglomerate was calculated using 4.97% of coke breeze. In a real experiment with the laboratory sintering pan, 4.35% of coke was used. When a biomass fuel with a lower calorific value (lignin) is used in the agglomeration charge, the amount of fuel has to be increased to 5.52% (with 20% substitution of coke). This paper also aimed at predicting methodological tools and defining thermodynamic conditions for creating an interactive simulation. In addition, kinetics should be considered to improve the predicting capabilities of the current model and therefore in further research it will be required to optimise the computational program pursuant to the results of the kinetics experiments.
The Microstructure, Mechanical Properties, and Corrosion Resistance of UNS S32707 Hyper-Duplex Stainless Steel Processed by Selective Laser Melting
Authors: Shang Feng , Chen Xiaoqiu , Wang Zhiyong , Ji Zuchun , Ming Fei , Ren Shubin , Qu Xuanhui
Published: September 2019

UNS S32707 hyper-duplex stainless steel (HDSS) parts with complex shapes for ocean engineering were prepared by selective laser melting (SLM) process. In the process of SLM, the balance between austenite and ferrite was undermined due to the high melting temperature and rapid cooling rate, resulting in poor ductility and toughness. The solution annealing was carried out with various temperatures (1050–1200 °C) for one hour at a time. The evolution of microstructures, mechanical properties, and corrosion resistance of UNS S32707 samples prepared by SLM was comprehensively investigated. The results indicate that a decrease in nitrogen content during the SLM process reduced the content of austenite, and a nearly balanced microstructure was obtained after appropriate solution annealing. The ratio between ferrite and austenite was approximately 59.5:40.5. The samples with solution treated at 1150 °C and 1100 °C exhibited better comprehensive mechanical properties and pitting resistance, respectively.
An Integrated Portable Multiplex Microchip Device for Fingerprinting Chemical Warfare Agents
Authors: Petkovic Karolina , Swallow Anthony , Stewart Robert , Gao Yuan , Li Sheng , Glenn Fiona , Gotama Januar , Dell’Olio Mel , Best Michael , Doward Justin , Ovendon Simon , Zhu Yonggang
Published: September 2019

The rapid and reliable detection of chemical and biological agents in the field is important for many applications such as national security, environmental monitoring, infectious diseases screening, and so on. Current commercially available devices may suffer from low field deployability, specificity, and reproducibility, as well as a high false alarm rate. This paper reports the development of a portable lab-on-a-chip device that could address these issues. The device integrates a polymer multiplexed microchip system, a contactless conductivity detector, a data acquisition and signal processing system, and a graphic/user interface. The samples are pre-treated by an on-chip capillary electrophoresis system. The separated analytes are detected by conductivity-based microsensors. Extensive studies are carried out to achieve satisfactory reproducibility of the microchip system. Chemical warfare agents soman (GD), sarin (GB), O-ethyl S-[2-diisoproylaminoethyl] methylphsophonothioate (VX), and their degradation products have been tested on the device. It was demonstrated that the device can fingerprint the tested chemical warfare agents. In addition, the detection of ricin and metal ions in water samples was demonstrated. Such a device could be used for the rapid and sensitive on-site detection of both chemical and biological agents in the future.
Identification of Microbial Profiles in Heavy-Metal-Contaminated Soil from Full-Length 16S rRNA Reads Sequenced by a PacBio System
Authors: Hur Moonsuk , Park Soo-Je
Published: September 2019

Heavy metal pollution is a serious environmental problem as it adversely affects crop production and human activity. In addition, the microbial community structure and composition are altered in heavy-metal-contaminated soils. In this study, using full-length 16S rRNA gene sequences obtained by a PacBio RS II system, we determined the microbial diversity and community structure in heavy-metal-contaminated soil. Furthermore, we investigated the microbial distribution, inferred their putative functional traits, and analyzed the environmental effects on the microbial compositions. The soil samples selected in this study were heavily and continuously contaminated with various heavy metals due to closed mines. We found that certain microorganisms (e.g., sulfur or iron oxidizers) play an important role in the biogeochemical cycle. Using phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) analysis, we predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) functional categories from abundances of microbial communities and revealed a high proportion belonging to transport, energy metabolism, and xenobiotic degradation in the studied sites. In addition, through full-length analysis, Conexibacter-like sequences, commonly identified by environmental metagenomics among the rare biosphere, were detected. In addition to microbial composition, we confirmed that environmental factors, including heavy metals, affect the microbial communities. Unexpectedly, among these environmental parameters, electrical conductivity (EC) might have more importance than other factors in a community description analysis.
A Discovery of Relevant Hepatoprotective Effects and Underlying Mechanisms of Dietary Clostridium butyricum Against Corticosterone-Induced Liver Injury in Pekin Ducks
Authors: Liu Yanhan , Liu Cun , Huang Liqing , Xia Zhaofei
Published: September 2019

Clostridium butyricum (C. butyricum) can attenuate oxidative stress, inflammation, and hepatic fatty deposition in poultry, however, the underlying mechanisms for this in Pekin ducks remain unclear. This study evaluated these hepatoprotective effects and the underlying mechanisms in a corticosterone (CORT)-induced liver injury model in Pekin ducks fed a C. butyricum intervention diet. A total of 500 Pekin ducks were randomly divided into five groups: one group (CON group) was only provided with a basal diet, three groups were provided a basal diet with 200 mg/kg (LCB group), 400 mg/kg (MCB group), or 600 mg/kg (HCB group) C. butyricum, respectively, and one group was provided a basal diet with 150 mg/kg aureomycin (ANT group) for 42 d. At 37 days-old, all ducks received daily intraperitoneal injections of CORT for five days to establish a liver injury model. C. butyricum intervention alleviated liver injury by decreasing the liver organ indices, hepatic steatosis and hepatocyte necrosis, and improving liver function, antioxidant capacity, and inflammatory factors. Hepatic RNA-seq revealed 365 differentially expressed genes (DEGs) between the MCB and CON groups, with 229 up- and 136 down-regulated DEGs in the MCB group. Between the MCB and ANT groups, 407 DEGs were identified, including 299 up- and 108 down-regulated genes in MCB group. Some DEGs in the MCB group related to oxidative stress and inflammatory responses such as Sod3, Tlr2a/b, and Il10, which were up-regulated, while Apoa1, Cyp7a1, Acsl1/5, Fasn, Ppar-γ, and Scd, which are involved in lipid metabolism, were down-regulated, indicating that these genes were responsive to dietary C. butyricum for the alleviation of corticosterone-induced hepatic injury. Toll-like receptor signaling, PI3K-Akt signaling pathway, cytokine-cytokine receptor interaction, peroxisome proliferator-activated receptor (PPAR) signaling pathway, adipocytokine and glycerophospholipid metabolism signaling pathway were significantly enriched in the MCB group. These findings indicate that C. butyricum intervention can protect Pekin ducks from corticosterone-induced liver injury by the modulation of immunoregulatory- and lipid metabolism-related genes and pathways.
MicroRNAs in Ocular Infection
Authors: Xu Shunbin , Hazlett Linda D.
Published: September 2019

MicroRNAs (miRNAs) are small, non-coding, regulatory RNA molecules and constitute a newly recognized, important layer of gene-expression regulation at post-transcriptional levels. miRNAs quantitatively fine tune the expression of their downstream genes in a cell type- and developmental stage-specific fashion. miRNAs have been proven to play important roles in the normal development and function as well as in the pathogenesis of diseases in all tissues and organ systems. miRNAs have emerged as new therapeutic targets and biomarkers for treatment and diagnosis of various diseases. Although miRNA research in ocular infection remains in its early stages, a handful of pioneering studies have provided insight into the roles of miRNAs in the pathogenesis of parasitic, fungal, bacterial, and viral ocular infections. Here, we review the current status of research in miRNAs in several major ocular infectious diseases. We predict that the field of miRNAs in ocular infection will greatly expand with the discovery of novel miRNA-involved molecular mechanisms that will inform development of new therapies and identify novel diagnostic biomarkers.
A Systematic Review and Meta-Analysis of B Vitamin Supplementation on Depressive Symptoms, Anxiety, and Stress: Effects on Healthy and ‘At-Risk’ Individuals
Authors: Young Lauren M , Pipingas Andrew , White David J , Gauci Sarah , Scholey Andrew
Published: September 2019

A systematic review and meta-analysis was undertaken to examine and quantify the effects of B vitamin supplementation on mood in both healthy and ‘at-risk’ populations. A systematic search identified all available randomised controlled trials (RCTs) of daily supplementation with ≥3 B group vitamins with an intervention period of at least four weeks. Random effects models for a standardized mean difference were used to test for overall effect. Heterogeneity was tested using the I2 statistic. Eighteen articles (16 trials, 2015 participants) were included, of which 12 were eligible for meta-analysis. Eleven of the 18 articles reported a positive effect for B vitamins over a placebo for overall mood or a facet of mood. Of the eight studies in ‘at-risk’ cohorts, five found a significant benefit to mood. Regarding individual facets of mood, B vitamin supplementation benefited stress (n = 958, SMD = 0.23, 95% CI = 0.02, 0.45, p = 0.03). A benefit to depressive symptoms did not reach significance (n = 568, SMD = 0.15, 95% CI = −0.01, 0.32, p = 0.07), and there was no effect on anxiety (n = 562, SMD = 0.03, 95% CI = −0.13, 0.20, p = 0.71). The review provides evidence for the benefit of B vitamin supplementation in healthy and at-risk populations for stress, but not for depressive symptoms or anxiety. B vitamin supplementation may particularly benefit populations who are at risk due to (1) poor nutrient status or (2) poor mood status.
Animal Models of Undernutrition and Enteropathy as Tools for Assessment of Nutritional Intervention
Authors: Salameh Emmeline , Morel Fanny B. , Zeilani Mamane , Déchelotte Pierre , Marion-Letellier Rachel
Published: September 2019

Undernutrition is a major public health problem leading to 1 in 5 of all deaths in children under 5 years. Undernutrition leads to growth stunting and/or wasting and is often associated with environmental enteric dysfunction (EED). EED mechanisms leading to growth failure include intestinal hyperpermeability, villus blunting, malabsorption and gut inflammation. As non-invasive methods for investigating gut function in undernourished children are limited, pre-clinical models are relevant to elucidating the pathophysiological processes involved in undernutrition and EED, and to identifying novel therapeutic strategies. In many published models, undernutrition was induced using protein or micronutrient deficient diets, but these experimental models were not associated with EED. Enteropathy models mainly used gastrointestinal injury triggers. These models are presented in this review. We found only a few studies investigating the combination of undernutrition and enteropathy. This highlights the need for further developments to establish an experimental model reproducing the impact of undernutrition and enteropathy on growth, intestinal hyperpermeability and inflammation, that could be suitable for preclinical evaluation of innovative therapeutic intervention.
Appetite-Suppressing and Satiety-Increasing Bioactive Phytochemicals: A Systematic Review
Authors: Stuby Johann , Gravestock Isaac , Wolfram Evelyn , Pichierri Giuseppe , Steurer Johann , Burgstaller Jakob M.
Published: September 2019

The prevalence of obesity is increasing worldwide. Bioactive phytochemicals in food supplements are a trending approach to facilitate dieting and to improve patients’ adherence to reducing food and caloric intake. The aim of this systematic review was to assess efficacy and safety of the most commonly used bioactive phytochemicals with appetite/hunger-suppressing and/or satiety/fullness-increasing properties. To be eligible, studies needed to have included at least 10 patients per group aged 18 years or older with no serious health problems except for overweight or obesity. Of those studies, 32 met the inclusion criteria, in which 27 different plants were tested alone or as a combination, regarding their efficacy in suppressing appetite/hunger and/or increasing satiety/fullness. The plant extracts most tested were derived from Camellia sinensis (green tea), Capsicum annuum, and Coffea species. None of the plant extracts tested in several trials showed a consistent positive treatment effect. Furthermore, only a few adverse events were reported, but none serious. The findings revealed mostly inconclusive evidence that the tested bioactive phytochemicals are effective in suppressing appetite/hunger and/or increasing satiety/fullness. More systematic and high quality clinical studies are necessary to determine the benefits and safety of phytochemical complementary remedies for dampening the feeling of hunger during dieting.
Genetic Profiling of Aggregatibacter actinomycetemcomitans Serotype B Isolated from Periodontitis Patients Living in Sweden
Authors: Johansson Anders , Claesson Rolf , Höglund Åberg Carola , Haubek Dorte , Lindholm Mark , Jasim Sarah , Oscarsson Jan
Published: September 2019

The bacterium Aggregatibacter actinomycetemcomitans is associated with aggressive forms of periodontitis and with systemic diseases, such as endocarditis. By assessing a Ghanaian longitudinal adolescent cohort, we earlier recognized the cagE gene as a possible diagnostic marker for a subgroup of JP2 and non-JP2 genotype serotype b A. actinomycetemcomitans strains, associated with high leukotoxicity as determined in a semi-quantitative cell assay. This group of A. actinomycetemcomitans is associated with the progression of attachment loss. In the present work, we used conventional polymerase chain reaction (PCR) and quantitative PCR to perform the cagE genotyping of our collection of 116 selected serotype b A. actinomycetemcomitans strains, collected over a period of 15 years from periodontitis patients living in Sweden. The A. actinomycetemcomitans strains carrying cagE (referred to as cagE+; n = 49) were compared to the cagE-negative strains (n = 67), present at larger proportions in the subgingival plaque samples, and were also much more prevalent in the young (≤35 years) compared to in the old (>35 years) group of patients. Our present results underline the potential use of cagE genotyping in the risk assessment of the development of periodontal attachment loss in Swedish adolescents.
The Efficacy of Iron Chelators for Removing Iron from Specific Brain Regions and the Pituitary—Ironing out the Brain
Authors: Crichton Robert R. , Ward Roberta J. , Hider Robert C.
Published: September 2019

Iron chelation therapy, either subcutaneous or orally administered, has been used successfully in various clinical conditions. The removal of excess iron from various tissues, e.g., the liver spleen, heart, and the pituitary, in beta thalassemia patients, has become an essential therapy to prolong life. More recently, the use of deferiprone to chelate iron from various brain regions in Parkinson’s Disease and Friederich’s Ataxia has yielded encouraging results, although the side effects, in <2% of Parkinson’s Disease(PD) patients, have limited its long-term use. A new class of hydroxpyridinones has recently been synthesised, which showed no adverse effects in preliminary trials. A vital question remaining is whether inflammation may influence chelation efficacy, with a recent study suggesting that high levels of inflammation may diminish the ability of the chelator to bind the excess iron.
Boron Removal from Aqueous Solutions by Using a Novel Alginate-Based Sorbent: Comparison with Al2O3 Particles
Authors: Demey Hary , Barron-Zambrano Jesus , Mhadhbi Takoua , Miloudi Hafida , Yang Zhen , Ruiz Montserrat , Sastre Ana Maria
Published: September 2019

Boron removal was evaluated in the present work by using calcium alginate beads (CA) and a novel composite based on alginate–alumina (CAAl) as sorbents in a batch system. The effects of different parameters such as pH, temperature, contact time, and composition of alginate (at different concentrations of guluronic and mannuronic acids) on boron sorption were investigated. The results confirm that calcium alginate beads (CA) exhibited a better adsorption capacity in a slightly basic medium, and the composite alginate–alumina (CAAl) exhibited improved boron removal at neutral pH. Sorption isotherm studies were performed and the Langmuir isotherm model was found to fit the experimental data. The maximum sorption capacities were 4.5 mmol g−1 and 5.2 mmol g−1, using CA and CAAl, respectively. Thermodynamic parameters such as change in free energy (ΔG0), enthalpy (ΔH0), and entropy (ΔS0) were also determined. The pseudo-first-order and pseudo-second-order rate equations (PFORE and PSORE, respectively) were tested to fit the kinetic data; the experimental results can be better described with PSORE. The regeneration of the loaded sorbents was demonstrated by using dilute HCl solution (distilled water at pH 3) as eluent for metal recovery.
Preparation of Ag Doped Keratin/PA6 Nanofiber Membrane with Enhanced Air Filtration and Antimicrobial Properties
Authors: Shen Baolei , Zhang Dongyu , Wei Yujuan , Zhao Zihua , Ma Xiaofei , Zhao Xiaodan , Wang Shuo , Yang Wenxiu
Published: September 2019

Coarse wool is a kind of goat wool that is difficult to further process in the textile industry due to its large diameter, dispersion, better strength, and less bending. Therefore, coarse wool is often discarded as waste or made into low-cost products. In this work, keratin was extracted from coarse wool by a high-efficiency method, and then, an Ag-doped keratin/PA6 composite nanofiber membrane with enhanced filtration and antibacterial performance was prepared using HCOOH as solvent and reductant. HAADF-STEM (high-angle annular dark field-scanning transmission electron microscopy) shows that AgNPs are uniformly distributed in keratin/PA6 (30/70) nanofibers. TGA (Thermogravimetric Analysis) and DSC (Differential Scanning Calorimetry) were employed to investigate the thermal stability of composite membranes with different keratin and AgNP contents. The present keratin as a dopant with polyamide-6 (PA6) was found not only to improve air filtration efficiency but also to enhance water–vapour transmission (WVT). The addition of the Ag nanoparticles (AgNPs) gave a strong antibacterial activity to the composite membrane against Staphylococcus aureus (99.62%) and Escherichia coli (99.10%). Bacterial filtration efficiency (BFE) of the composite membrane against S. aureus and E. coli were up to 96.8% and 95.6%, respectively. All of the results suggested a great potential for coarse wool extraction and application in the air filtration field.
Medial Cortical Structures Mediate Implicit Trustworthiness Judgments about Kin Faces, but Not Familiar Faces: A Brief Report
Authors: Platek Steven M. , Hendry Judson C.
Published: September 2019

Human kin recognition activates substrates of the extended facial processing network, notably the right-hemisphere structures involved in self-face recognition and posterior medial cortical substrates. To understand the mechanisms underlying prosociality toward kin faces in comparison to other familiar faces, we investigated the neural correlates of implicit trustworthiness ratings to faces of actual kin and personal friends, controlling for activation to distracter faces. When controlling for activation associated with unknown faces, trustworthiness ratings of faces of kin, compared to friends, were associated with increased activation in the dorsal anterior cingulate cortex, posterior cingulate, and precuneous. On the other hand, trustworthiness ratings of friend faces, relative to kin faces, were associated with the lateral occipital gyrus and insular cortex. Trustworthiness ratings for unknown faces were only associated with activation in the fusiform gyrus. These findings suggest that we should employ medial cortical substrates known to be part of the self-other network when making implicit social judgements about kin, but not other classes of facial stimuli.
DeepTriangle: A Deep Learning Approach to Loss Reserving
Authors: Kuo Kevin
Published: September 2019

We propose a novel approach for loss reserving based on deep neural networks. The approach allows for joint modeling of paid losses and claims outstanding, and incorporation of heterogeneous inputs. We validate the models on loss reserving data across lines of business, and show that they improve on the predictive accuracy of existing stochastic methods. The models require minimal feature engineering and expert input, and can be automated to produce forecasts more frequently than manual workflows.
Orientation- and Scale-Invariant Multi-Vehicle Detection and Tracking from Unmanned Aerial Videos
Authors: Wang Jie , Simeonova Sandra , Shahbazi Mozhdeh
Published: September 2019

Along with the advancement of light-weight sensing and processing technologies, unmanned aerial vehicles (UAVs) have recently become popular platforms for intelligent traffic monitoring and control. UAV-mounted cameras can capture traffic-flow videos from various perspectives providing a comprehensive insight into road conditions. To analyze the traffic flow from remotely captured videos, a reliable and accurate vehicle detection-and-tracking approach is required. In this paper, we propose a deep-learning framework for vehicle detection and tracking from UAV videos for monitoring traffic flow in complex road structures. This approach is designed to be invariant to significant orientation and scale variations in the videos. The detection procedure is performed by fine-tuning a state-of-the-art object detector, You Only Look Once (YOLOv3), using several custom-labeled traffic datasets. Vehicle tracking is conducted following a tracking-by-detection paradigm, where deep appearance features are used for vehicle re-identification, and Kalman filtering is used for motion estimation. The proposed methodology is tested on a variety of real videos collected by UAVs under various conditions, e.g., in late afternoons with long vehicle shadows, in dawn with vehicles lights being on, over roundabouts and interchange roads where vehicle directions change considerably, and from various viewpoints where vehicles’ appearance undergo substantial perspective distortions. The proposed tracking-by-detection approach performs efficiently at 11 frames per second on color videos of 2720p resolution. Experiments demonstrated that high detection accuracy could be achieved with an average F1-score of 92.1%. Besides, the tracking technique performs accurately, with an average multiple-object tracking accuracy (MOTA) of 81.3%. The proposed approach also addressed the shortcomings of the state-of-the-art in multi-object tracking regarding frequent identity switching, resulting in a total of only one identity switch over every 305 tracked vehicles.
A High-Resolution Airborne Color-Infrared Camera Water Mask for the NASA ABoVE Campaign
Authors: Kyzivat Ethan D. , Smith Laurence C. , Pitcher Lincoln H. , Fayne Jessica V. , Cooley Sarah W. , Cooper Matthew G. , Topp Simon N. , Langhorst Theodore , Harlan Merritt E. , Horvat Christopher , Gleason Colin J. , Pavelsky Tamlin M.
Published: September 2019

The airborne AirSWOT instrument suite, consisting of an interferometric Ka-band synthetic aperture radar and color-infrared (CIR) camera, was deployed to northern North America in July and August 2017 as part of the NASA Arctic-Boreal Vulnerability Experiment (ABoVE). We present validated, open (i.e., vegetation-free) surface water masks produced from high-resolution (1 m), co-registered AirSWOT CIR imagery using a semi-automated, object-based water classification. The imagery and resulting high-resolution water masks are available as open-access datasets and support interpretation of AirSWOT radar and other coincident ABoVE image products, including LVIS, UAVSAR, AIRMOSS, AVIRIS-NG, and CFIS. These synergies offer promising potential for multi-sensor analysis of Arctic-Boreal surface water bodies. In total, 3167 km2 of open surface water were mapped from 23,380 km2 of flight lines spanning 23 degrees of latitude and broad environmental gradients. Detected water body sizes range from 0.00004 km2 (40 m2) to 15 km2. Power-law extrapolations are commonly used to estimate the abundance of small lakes from coarser resolution imagery, and our mapped water bodies followed power-law distributions, but only for water bodies greater than 0.34 (±0.13) km2 in area. For water bodies exceeding this size threshold, the coefficients of power-law fits vary for different Arctic-Boreal physiographic terrains (wetland, prairie pothole, lowland river valley, thermokarst, and Canadian Shield). Thus, direct mapping using high-resolution imagery remains the most accurate way to estimate the abundance of small surface water bodies. We conclude that empirical scaling relationships, useful for estimating total trace gas exchange and aquatic habitats on Arctic-Boreal landscapes, are uniquely enabled by high-resolution AirSWOT-like mappings and automated detection methods such as those developed here.
Partial Linear NMF-Based Unmixing Methods for Detection and Area Estimation of Photovoltaic Panels in Urban Hyperspectral Remote Sensing Data
Authors: Karoui Moussa , Benhalouche Fatima , Deville Yannick , Djerriri Khelifa , Briottet Xavier , Houet Thomas , Le Bris Arnaud , Weber Christiane
Published: September 2019

High-spectral-resolution hyperspectral data are acquired by sensors that gather images from hundreds of narrow and contiguous bands of the electromagnetic spectrum. These data offer unique opportunities for characterization and precise land surface recognition in urban areas. So far, few studies have been conducted with these data to automatically detect and estimate areas of photovoltaic panels, which currently constitute an important part of renewable energy systems in urban areas of developed countries. In this paper, two hyperspectral-unmixing-based methods are proposed to detect and to estimate surfaces of photovoltaic panels. These approaches, related to linear spectral unmixing (LSU) techniques, are based on new nonnegative matrix factorization (NMF) algorithms that exploit known panel spectra, which makes them partial NMF methods. The first approach, called Grd-Part-NMF, is a gradient-based method, whereas the second one, called Multi-Part-NMF, uses multiplicative update rules. To evaluate the performance of these approaches, experiments are conducted on realistic synthetic and real airborne hyperspectral data acquired over an urban region. For the synthetic data, obtained results show that the proposed methods yield much better overall performance than NMF-unmixing-based methods from the literature. For the real data, the obtained detection and area estimation results are first confirmed by using very high-spatial-resolution ortho-images of the same regions. These results are also compared with those obtained by standard NMF-unmixing-based methods and by a one-class-classification-based approach. This comparison shows that the proposed approaches are superior to those considered from the literature.
Multidimensional Vibration Suppression Method with Piezoelectric Control for Wind Tunnel Models
Authors: Zhou Mengde , Liu Wei , Tang Linlin , Yao Zhuang , Wen Zhengquan , Liang Bing , Jia Zhenyuan
Published: September 2019

In wind tunnel tests, the low-frequency and large-amplitude vibration of the cantilever sting result in poor test data in pitch plane and yaw plane, more seriously, even threatens the safety of wind tunnel tests. To ensure the test data quality, a multidimensional vibration suppression method is proposed to withstand the vibration from any direction, which is based on a system with stackable piezoelectric actuators and velocity feedback employing accelerometers. Firstly, the motion equation of the cantilever sting system is obtained by Hamilton’s principle with the assumed mode method. Then, the multidimensional active control mechanism is qualitatively analyzed and a negative velocity feedback control algorithm combined with a root mean square (RMS) evaluation method is introduced to realize active mass and active damping effect, meanwhile, a weight modification method is performed to determine the sequence number of the stacked piezoelectric actuators and the weight of control voltages in real time. Finally, a multidimensional vibration suppression system was established and verification experiments were carried out in lab and a transonic wind tunnel. The results of lab experiments indicate that the damping ratio of the system is improved more than 4.3 times and the spectrum analyses show reductions of more than 23 dB. In addition, wind tunnel test results have shown that for the working conditions (α = −4~10° with γ = 0° or α = −4~10° with γ = 45°) respectively at 0.6 Ma and 0.7 Ma, the remainder vibration is less than 1.53 g, which proves that the multidimensional vibration suppression method has the ability to resist vibration from any direction to ensure the smooth process of wind tunnel tests.
Method for Detecting Abnormal Activity in a Group of Mobile Robots
Authors: Basan Elena , Basan Alexandr , Nekrasov Alexey
Published: September 2019

The range of attacks implemented on wireless networks is quite wide. To avoid or reduce the likelihood of an attack, it is necessary to use various defense mechanisms. Existing protection mechanisms are not always suitable for robotic systems and may not fully provide the necessary level of security. Thus, it is necessary to develop new ways of protection, which would be specific to groups of mobile robots. In this study, we propose an analysis of the following cyber parameters: the power consumption and the residual energy, as well as an in-depth traffic analysis to evaluate the effectiveness of the attack and identify abnormal network. We realized an analysis of the behavior of robotic systems under normal conditions and determined that, by their nature, robotic systems have a static and uniform behavior. We developed an experimental stand, and also conducted a theoretical analysis to confirm our assumptions. We found that some indicators of the components of the robotic system change statically; that is, there was a little deviation from the mean. Thus, we identified a set of metrics that allow us to determine how static the operation of the robotic system and its components is. Metrics allow us to evaluate parameters such as power consumption, and incoming/outgoing/redirected/dropped network packets. The results obtained are important for creating an integrated system for detecting anomalies in robotic systems. At the same time, the robotic node can analyze these parameters independently and make calculations that do not greatly affect performance. The main idea of this paper is to define a set of metrics characterizing the static behavior of a robotic system for the further development of an anomaly detection system.
Pleurotus spp. Cultivation on Different Agri-Food By-Products: Example of Biotechnological Application
Authors: Ritota Mena , Manzi Pamela
Published: September 2019

Agri-food industry generally produces huge volumes of wastes all over the world, and their disposal is a threat to the environment and public health. The chemical composition of most of these wastes make them be defined as lignocellulosic materials, so they could be a suitable substrate for solid-state fermentation process operated by mushrooms. White-rot fungi are well known for their degradation ability of lignocellulosic material, and many scientific works reported the use of different substrates for their production. Biotechnological treatments of agri-food wastes by mushrooms could be considered an eco-friendly solution to reuse and valorize them, besides to reduce their environmental impact. In this way, wastes would be transformed into new resources to produce added-value food products, besides representing an economic return for the same industries. The aim of this review is to provide an overview of the recent literature concerning the use of different agri-food residues as growth substrates for Pleurotus spp. cultivation, with attention to their effects on the growth and chemical composition of the cultivated mushrooms.
Social Acceptability of Flood Management Strategies under Climate Change Using Contingent Valuation Method (CVM)
Authors: Maghsood Fatemeh Fadia , Moradi Hamidreza , Berndtsson Ronny , Panahi Mostafa , Daneshi Alireza , Hashemi Hossein , Bavani Ali Reza Massah
Published: September 2019

Floods are natural hazards with serious impact on many aspects of human life. The Intergovernmental Panel on Climate Change (IPCC) reported that climate change already has significant impact on magnitude and frequency of flood events worldwide. Thus, it is suggested to adopt strategies to manage damage impacts of climate change. For this, involving the local community in the decision-making process, as well as experts and decision-makers, is essential. We focused on assessing the social acceptability of flood management strategies under climate change through a socio-hydrological approach using the Contingent Valuation Method (CVM). For this purpose as well, hydro-climate modelling and the Analytical Network Process (ANP) were used. Among twelve investigated flood management strategies, “river restoration”, “agricultural management and planning”, and “watershed management” were the publicly most accepted strategies. Assessment of the social acceptability of these three strategies was carried out by use of the CVM and Willingness to Pay (WTP) methodology. Generally, 50%, 38%, and 18% were willing to pay and 44%, 48%, and 52% were willing to contribute flood management strategy in zones 1, 2, and 3, respectively. Overall, peoples’ WTP for flood management strategies decreased with increasing distance from the river. Among different investigated dependent variables, household income had the highest influence on WTP.
The Digital Divide? Analyzing Regional Differences of Tablet PC Use in Korean Middle Schools for Sustainable Development
Authors: Lim Keol , Kim Yujin , Kim Minyoung , Jang Yoonho , Joo Min-Ho
Published: September 2019

The purpose of this study was to investigate the effects of digital learning environments using tablet Personal Computers (PCs) in Korean metropolitan and rural middle schools. After 12 weeks of professional development for six teachers to enhance ICT and instructional design competency, 48 metropolitan and 63 rural students participated in learning with tablet PCs in English, science, and social studies subjects for 12 weeks. As a result, teachers’ various experiences of changes and challenges in digital learning environments were qualitatively analyzed and described. Also, quantitative measurements of students’ self-regulated learning abilities, collaborative learning disposition, and learning satisfaction were conducted and findings indicated that rural students showed significant differences compared to urban students in all three variables. Based on the results, educational implications and suggestions are discussed.
A Heterogeneous MCDM Framework for Sustainable Supplier Evaluation and Selection Based on the IVIF-TODIM Method
Authors: Mao Ren-Jie , You Jian-Xin , Duan Chun-Yan , Shao Lu-Ning
Published: September 2019

The third-party platform named ECO system is used by many transnational companies to monitor the sustainability performance of their global suppliers because of its easiness and shareability. Nonetheless, methods used in this platform for evaluating and calculating the sustainability performance of the alternative suppliers are criticized for their lack of accuracy. In response to these problems, this paper presents a heterogeneous multi-criteria decision-making (MCDM) method based on interval-valued intuitionistic fuzzy--an acronym in Portuguese for interactive multi-criteria decision making (IVIF--TODIM) to improve the efficiency of the evaluation model. Considering the varying features of evaluation criteria, i.e., either quantitative or qualitative, the evaluation values under different criteria are expressed in their appropriate information types. In this paper, a general method based on the relative closeness to the technique for order preference by similarity to ideal solution (TOPSIS) method is applied for aggregating the heterogeneous assessment information, including crisp numbers, interval numbers, and triangular fuzzy numbers (TFNs), into interval-valued intuitionistic fuzzy numbers (IVIFNs). Then, the TODIM (an acronym in Portuguese for interactive multi-criteria decision making) is extended and employed to prioritize the alternative suppliers. Finally, the applicability and effectiveness of the proposed method is verified by a practical example of polymer manufacturing company and a comparison analysis with existing methods.
Optimal Alignments for Designing Urban Transport Systems: Application to Seville
Authors: Marseglia Guido , Medaglia Carlo Maria , Ortega Francisco A. , Mesa Juan A.
Published: September 2019

The achievement of some of the Sustainable Development Goals (SDGs) from the recent 2030 Agenda for Sustainable Development has drawn the attention of many countries towards urban transport networks. Mathematical modeling constitutes an analytical tool for the formal description of a transportation system whereby it facilitates the introduction of variables and the definition of objectives to be optimized. One of the stages of the methodology followed in the design of urban transit systems starts with the determination of corridors to optimize the population covered by the system whilst taking into account the mobility patterns of potential users and the time saved when the public network is used instead of private means of transport. Since the capture of users occurs at stations, it seems reasonable to consider an extensive and homogeneous set of candidate sites evaluated according to the parameters considered (such as pedestrian population captured and destination preferences) and to select subsets of stations so that alignments can take place. The application of optimization procedures that decide the sequence of nodes composing the alignment can produce zigzagging corridors, which are less appropriate for the design of a single line. The main aim of this work is to include a new criterion to avoid the zigzag effect when the alignment is about to be determined. For this purpose, a curvature concept for polygonal lines is introduced, and its performance is analyzed when criteria of maximizing coverage and minimizing curvature are combined in the same design algorithm. The results show the application of the mathematical model presented for a real case in the city of Seville in Spain.
Multi-Scale Assessment of Relationships between Fragmentation of Riparian Forests and Biological Conditions in Streams
Authors: Yirigui Yirigui , Lee Sang-Woo , Nejadhashemi A. Pouyan
Published: September 2019

Due to anthropogenic activities within watersheds and riparian areas, stream water quality and ecological communities have been significantly affected by degradation of watershed and stream environments. One critical indicator of anthropogenic activities within watersheds and riparian areas is forest fragmentation, which has been directly linked to poor water quality and ecosystem health in streams. However, the true nature of the relationship between forest fragmentation and stream ecosystem health has not been fully elucidated due to its complex underlying mechanism. The purpose of this study was to examine the relationships of riparian fragmented forest with biological indicators including diatoms, macroinvertebrates, and fish. In addition, we investigated variations in these relationships over multiple riparian scales. Fragmentation metrics, including the number of forest patches (NP), proportion of riparian forest (PLAND), largest riparian forest patch ratio (LPI), and spatial proximity of riparian forest patches (DIVISION), were used to quantify the degree of fragmentation of riparian forests, and the trophic diatom index (TDI), benthic macroinvertebrates index (BMI), and fish assessment index (FAI) were used to represent the biological condition of diatoms, macroinvertebrates, and fish in streams. PLAND and LPI showed positive relationships with TDI, BMI, and FAI, whereas NP and DIVISION were negatively associated with biological indicators at multiple scales. Biological conditions in streams were clearly better when riparian forests were less fragmented. The relationships of NP and PLAND with biological indicators were stronger at a larger riparian scale, whereas relationships of LPI and DIVISION with biological indicators were weaker at a large scale. These results suggest that a much larger spatial range of riparian forests should be considered in forest management and restoration to enhance the biological condition of streams.