bluuebunny/crossref_metadata_2025 huggingface dataset:
Lost in explanation: Lessons learned from audio-recordings and surveys of the antenatal consultation
Authors: Studer E.M. , Marc-Aurele K.L.
Published: November 2016

OBJECTIVE: Determine content of antenatal prematurity consultations and identify factors associated with satisfaction.

DESIGN: This is an observational study of consultations for possible preterm delivery. Consultations were audio-recorded and analyzed. Parents and physicians were surveyed post-consultation.

RESULTS: We analyzed 17 audio-recordings. Mean gestation was 28 weeks. Frequency of topics discussed were: antenatal steroids 82%, intubation 82%, breast milk 76%, time in NICU 65%, development 59%, and survival 53%. Parents frequently asked about length of hospitalization stay, feeding, and separation concerns. Parents’ greatest fears were developmental problems, survival, separation from baby, infant health, and length of hospitalization. The parent satisfaction score was 8.9, and physician satisfaction score was 4.8 on a ten-point scale. No factors were found to be associated with satisfaction. Physicians felt 82% of consultations could be improved.

CONCLUSIONS: In consultations for possible preterm delivery, physicians discussed resuscitation details and initial neonatal care. Parental greatest fears involved more global issues. Despite content variability, parents were highly satisfied. No specific factors (such as topics discussed or length of consultation) were found to be statistically associated with parent satisfaction. Physicians were less satisfied. Providing too much/too little information was a repeated physician concern.
Good Science, Good Sense and Good Sensibilities: The Three Ss of Carol Newton
Authors: Smith Adrian , Hawkins Penny
Published: November 2016

The Three Rs principle of Replacement, Reduction and Refinement developed by William M. S. Russell and Rex L. Burch in the 1950s has achieved worldwide recognition as a means of reducing the impact of science on animals and improving their welfare. However, application of the Three Rs is still far from universal, and evidence-based methods to implement the Three Rs are still lacking in many areas of laboratory animal science. The purpose of this paper is to create interest in a less well-known but equally useful principle that complements the Three Rs, which was proposed by the American biomathematician Carol M. Newton in the 1970s: the Three Ss—Good Science, Good Sense and Good Sensibilities.
The Effect of Freezing Drizzle, Sleet and Snow on Microphysical Characteristics of Supercooled Fog during the Icing Process in a Mountainous Area
Authors: Zhou Yue , Niu Shengjie , Lü Jingjing , Zhou Yuehua
Published: November 2016

Both the similar and different effects of freezing drizzle, sleet and snow on microphysical properties of supercooled fog were analyzed for fourteen events during a comprehensive wire icing, fog, and precipitation observation experiment conducted at Enshi radar station (30°17′N, 109°16′E; 1722 m a.s.l.) on a hilltop in Shibanling, Hubei, China. Liquid precipitation is in a relatively stable form in mountainous areas. Short-term precipitation (1–3 h) is dominant with temperature below 0 °C. The wet scavenging effect of freezing drizzle on small fog droplets with a size range less than 6–12 μm is weak but is stronger for fog droplets with a larger size, which is opposite to the effects of solid precipitation, broadening the fog droplet spectra significantly. As the fog droplet diameter increases, the distributions of droplet spectra change from leptokurtosis to platykurtosis and from positive skewness to negative skewness. Occurrence of freezing drizzle would improve the positive correlation of N-r in dissipation and oscillation periods, resulting in the N-r relationship having a weak negative correlation in the maturity period, and resulting in the transition of the N-L and N-r relationships into positive correlations in the development period. Meanwhile, the emergence of solid precipitation particles would result in negative values for the correlation coefficients of N-L and N-r. The change in relationships among the microphysical properties was caused by the occurrence of different phase precipitation, showing the influence on the main microphysical mechanisms of supercooled fog.
Rectification and Non-Gaussian Diffusion in Heterogeneous Media
Authors: Malgaretti Paolo , Pagonabarraga Ignacio , Rubi J.
Published: November 2016

We show that when Brownian motion takes place in a heterogeneous medium, the presence of local forces and transport coefficients leads to deviations from a Gaussian probability distribution that make that the ratio between forward and backward probabilities depend on the nature of the host medium, on local forces, and also on time. We have applied our results to two situations: diffusion in a disordered medium, and diffusion in a confined system. For such scenarios, we have shown that our theoretical predictions are in very good agreement with numerical results. Moreover, we have shown that the deviations from the Gaussian solution lead to the onset of rectification. Our predictions could be used to detect the presence of local forces and to characterize the intrinsic short-scale properties of the host medium—a problem of current interest in the study of micro- and nano-systems.
Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission
Authors: Liang Yi , Niu Dongxiao , Cao Ye , Hong Wei-Chiang
Published: November 2016

The power industry is the main battlefield of CO2 emission reduction, which plays an important role in the implementation and development of the low carbon economy. The forecasting of electricity demand can provide a scientific basis for the country to formulate a power industry development strategy and further promote the sustained, healthy and rapid development of the national economy. Under the goal of low-carbon economy, medium and long term electricity demand forecasting will have very important practical significance. In this paper, a new hybrid electricity demand model framework is characterized as follows: firstly, integration of grey relation degree (GRD) with induced ordered weighted harmonic averaging operator (IOWHA) to propose a new weight determination method of hybrid forecasting model on basis of forecasting accuracy as induced variables is presented; secondly, utilization of the proposed weight determination method to construct the optimal hybrid forecasting model based on extreme learning machine (ELM) forecasting model and multiple regression (MR) model; thirdly, three scenarios in line with the level of realization of various carbon emission targets and dynamic simulation of effect of low-carbon economy on future electricity demand are discussed. The resulting findings show that, the proposed model outperformed and concentrated some monomial forecasting models, especially in boosting the overall instability dramatically. In addition, the development of a low-carbon economy will increase the demand for electricity, and have an impact on the adjustment of the electricity demand structure.
Simple Design Approach for Low Torque Ripple and High Output Torque Synchronous Reluctance Motors
Authors: Ibrahim Mohamed , Sergeant Peter , Rashad Essam
Published: November 2016

The rotor design of Synchronous Reluctance Motors (SynRMs) has a large effect on their efficiency, torque density and torque ripple. In order to achieve a good compromise between these three goals, an optimized rotor geometry is necessary. A finite element method (FEM) is a good tool for the optimization. However, the computation time is an obstacle as there are many geometrical parameters to be optimized. The flux-barrier widths and angles are the two most crucial parameters for the SynRM output torque and torque ripple. This paper proposes an easy-to-use set of parametrized equations to select appropriate values for these two rotor parameters. With these equations, the reader can design a SynRM of distributed windings with a low torque ripple and with a better average torque. The methodology is valid for a wide range of SynRMs. To check the validity of the proposed equations, the sensitivity analysis for the variation of these two parameters on the SynRM torque and torque ripple is carried out. In addition, the analysis in this paper gives insight into the behavior of the machine as a function of these two parameters. Furthermore, the torque and torque ripple of SynRMs having a rotor with three, four and five flux-barriers are compared with three literature approaches. The comparison shows that the proposed equations are effective in choosing the flux-barrier angles and widths for low torque ripple and better average torque. Experimental results have been obtained to confirm the FEM results and to validate the methodology for choosing the rotor parameters.
Conventional P-ω/Q-V Droop Control in Highly Resistive Line of Low-Voltage Converter-Based AC Microgrid
Authors: Hou Xiaochao , Sun Yao , Yuan Wenbin , Han Hua , Zhong Chaolu , Guerrero Josep
Published: November 2016

In low-voltage converter-based alternating current (AC) microgrids with resistive distribution lines, the P-V droop with Q-f boost (VPD/FQB) is the most common method for load sharing. However, it cannot achieve the active power sharing proportionally. To overcome this drawback, the conventional P-ω/Q-V droop control is adopted in the low-voltage AC microgrid. As a result, the active power sharing among the distributed generators (DGs) is easily obtained without communication. More importantly, this study clears up the previous misunderstanding that conventional P-ω/Q-V droop control is only applicable to microgrids with highly inductive lines, and lays a foundation for the application of conventional droop control under different line impedances. Moreover, in order to guarantee the accurate reactive power sharing, a guide for designing Q-V droop gains is given, and virtual resistance is adopted to shape the desired output impedance. Finally, the effects of power sharing and transient response are verified through simulations and experiments in converter-based AC Microgrid.
A Novel Multi-Focus Image Fusion Method Based on Stochastic Coordinate Coding and Local Density Peaks Clustering
Authors: Zhu Zhiqin , Qi Guanqiu , Chai Yi , Chen Yinong
Published: November 2016

The multi-focus image fusion method is used in image processing to generate all-focus images that have large depth of field (DOF) based on original multi-focus images. Different approaches have been used in the spatial and transform domain to fuse multi-focus images. As one of the most popular image processing methods, dictionary-learning-based spare representation achieves great performance in multi-focus image fusion. Most of the existing dictionary-learning-based multi-focus image fusion methods directly use the whole source images for dictionary learning. However, it incurs a high error rate and high computation cost in dictionary learning process by using the whole source images. This paper proposes a novel stochastic coordinate coding-based image fusion framework integrated with local density peaks. The proposed multi-focus image fusion method consists of three steps. First, source images are split into small image patches, then the split image patches are classified into a few groups by local density peaks clustering. Next, the grouped image patches are used for sub-dictionary learning by stochastic coordinate coding. The trained sub-dictionaries are combined into a dictionary for sparse representation. Finally, the simultaneous orthogonal matching pursuit (SOMP) algorithm is used to carry out sparse representation. After the three steps, the obtained sparse coefficients are fused following the max L1-norm rule. The fused coefficients are inversely transformed to an image by using the learned dictionary. The results and analyses of comparison experiments demonstrate that fused images of the proposed method have higher qualities than existing state-of-the-art methods.
Blood Pressure Control in Smokers with Arterial Hypertension Who Switched to Electronic Cigarettes
Authors: Polosa Riccardo , Morjaria Jaymin , Caponnetto Pasquale , Battaglia Eliana , Russo Cristina , Ciampi Claudio , Adams George , Bruno Cosimo
Published: November 2016

Electronic cigarettes (ECs) are battery-operated devices designed to vaporise nicotine, which may help smokers with quitting or reducing their tobacco consumption. No data is available regarding the health effects of ECs use among smokers with arterial hypertension and whether regular use results in blood pressure (BP) changes. We investigated long-term changes in resting BP and level of BP control in hypertensive smokers who quit or reduced substantially their tobacco consumption by switching to ECs. A medical records review of patients with hypertension was conducted to identify patients reporting regular daily use of ECs on at least two consecutive follow-up visits. Regularly smoking hypertensive patients were included as a reference group. A marked reduction in cigarette consumption was observed in ECs users (n = 43) though consumption remained unchanged in the control group (n = 46). Compared to baseline, at 12 months (follow-up visit 2) decline in cigarette consumption was associated with significant reductions in median (25th-, 75th-centile) systolic BP (140 (134.5, 144) to 130 (123.5, 138.5) mmHg; p < 0.001) and diastolic BP (86 (78, 90) to 80 (74.5, 90) mmHg; p = 0.006). No significant changes were observed in the control group. As expected, decline in cigarette consumption in the ECs users was also associated with improved BP control. The study concludes that regular ECs use may aid smokers with arterial hypertension reduce or abstain from cigarette smoking, with only trivial post-cessation weight gain. This resulted in improvements in systolic and diastolic BP as well as better BP control.
Correction: Wang, J.-J., et al. Psychological Correlates of Self-Reported and Objectively Measured Physical Activity among Chinese Children—Psychological Correlates of PA. Int. J. Environ. Res. Public Health 2016, 13, 1006
Authors: Wang Jing-Jing , Baranowski Tom , Lau Patrick , Chen Tzu-An , Zhang Shu-Ge
Published: November 2016

The authors wish to make the following correction to their paper [1]. [...]
Spatial Analysis of Severe Fever with Thrombocytopenia Syndrome Virus in China Using a Geographically Weighted Logistic Regression Model
Authors: Wu Liang , Deng Fei , Xie Zhong , Hu Sheng , Shen Shu , Shi Junming , Liu Dan
Published: November 2016

Severe fever with thrombocytopenia syndrome (SFTS) is caused by severe fever with thrombocytopenia syndrome virus (SFTSV), which has had a serious impact on public health in parts of Asia. There is no specific antiviral drug or vaccine for SFTSV and, therefore, it is important to determine the factors that influence the occurrence of SFTSV infections. This study aimed to explore the spatial associations between SFTSV infections and several potential determinants, and to predict the high-risk areas in mainland China. The analysis was carried out at the level of provinces in mainland China. The potential explanatory variables that were investigated consisted of meteorological factors (average temperature, average monthly precipitation and average relative humidity), the average proportion of rural population and the average proportion of primary industries over three years (2010–2012). We constructed a geographically weighted logistic regression (GWLR) model in order to explore the associations between the selected variables and confirmed cases of SFTSV. The study showed that: (1) meteorological factors have a strong influence on the SFTSV cover; (2) a GWLR model is suitable for exploring SFTSV cover in mainland China; (3) our findings can be used for predicting high-risk areas and highlighting when meteorological factors pose a risk in order to aid in the implementation of public health strategies.
Drug Dependence Treatment Awareness among Japanese Female Stimulant Drug Offenders
Authors: Yatsugi Shinzo , Fujita Koji , Kashima Saori , Eboshida Akira
Published: November 2016

Few stimulant drug users receive adequate treatment. This cross-sectional study describes the characteristics of female drug offenders that use stimulants and clarifies the factors related to the awareness of treatment for drug dependencies. We included 80 females imprisoned due to stimulant control law violations from 2012 to 2015. The characteristics of the female prisoners were stratified according to various treatment awareness levels, and associations between each characteristic and treatment awareness were evaluated using logistic regression models. The average period of stimulant drug use was 17.7 years. Participants imprisoned for the second time were significantly more likely to consider treatment compared to those imprisoned only once: odds ratio (OR) = 3.2 (95% confidence interval (CI): 1.0–10.7). This elevated OR was diluted in repeat offenders. Participants who had experienced multiple aftereffects (≥7) or serious depressive symptoms were also more likely to consider treatment: OR = 6.1 (95% CI: 1.8–20.8) and OR = 2.5 (95% CI: 1.0–6.2), respectively. Second-time stimulant offenders or offenders who had experienced health problems were more likely to consider it important to receive drug dependence treatment. To overcome relapses of stimulant use, it is recommended that stimulant use offenders are encouraged to accept adequate treatment.
Response Surface Methodology Modelling of an Aqueous Two-Phase System for Purification of Protease from Penicillium candidum (PCA 1/TT031) under Solid State Fermentation and Its Biochemical Characterization
Authors: Alhelli Amaal , Abdul Manap Mohd , Mohammed Abdulkarim , Mirhosseini Hamed , Suliman Eilaf , Shad Zahra , Mohammed Nameer , Meor Hussin Anis
Published: November 2016

Penicillium candidum (PCA 1/TT031) synthesizes different types of extracellular proteases. The objective of this study is to optimize polyethylene glycol (PEG)/citrate based on an aqueous two-phase system (ATPS) and Response Surface Methodology (RSM) to purify protease from Penicillium candidum (PCA 1/TT031). The effects of different PEG molecular weights (1500–10,000 g/mol), PEG concentration (9%–20%), concentrations of NaCl (0%–10%) and the citrate buffer (8%–16%) on protease were also studied. The best protease purification could be achieved under the conditions of 9.0% (w/w) PEG 8000, 5.2% NaCl, and 15.9% sodium citrate concentration, which resulted in a one-sided protease partitioning for the bottom phase with a partition coefficient of 0.2, a 6.8-fold protease purification factor, and a yield of 93%. The response surface models displayed a significant (p ≤ 0.05) response which was fit for the variables that were studied as well as a high coefficient of determination (R2). Similarly, the predicted and observed values displayed no significant (p > 0.05) differences. In addition, our enzyme characterization study revealed that Penicillium candidum (PCA 1/TT031) produced a slight neutral protease with a molecular weight between 100 and 140 kDa. The optimal activity of the purified enzyme occurred at a pH of 6.0 and at a temperature of 50 °C. The stability between different pH and temperature ranges along with the effect of chemical metal ions and inhibitors were also studied. Our results reveal that the purified enzyme could be used in the dairy industry such as in accelerated cheese ripening.
Influence of Sintering Temperature on the Microstructure and Mechanical Properties of In Situ Reinforced Titanium Composites by Inductive Hot Pressing
Authors: Arévalo Cristina , Montealegre-Meléndez Isabel , Ariza Enrique , Kitzmantel Michael , Rubio-Escudero Cristina , Neubauer Erich
Published: November 2016

This research is focused on the influence of processing temperature on titanium matrix composites reinforced through Ti, Al, and B4C reactions. In order to investigate the effect of Ti-Al based intermetallic compounds on the properties of the composites, aluminum powder was incorporated into the starting materials. In this way, in situ TixAly were expected to form as well as TiB and TiC. The specimens were fabricated by the powder metallurgy technique known as inductive hot pressing (iHP), using a temperature range between 900 °C and 1400 °C, at 40 MPa for 5 min. Raising the inductive hot pressing temperature may affect the microstructure and properties of the composites. Consequently, the variations of the reinforcing phases were investigated. X-ray diffraction, microstructural analysis, and mechanical properties (Young’s modulus and hardness) of the specimens were carried out to evaluate and determine the significant influence of the processing temperature on the behavior of the composites.
A Modular Synthetic Approach to Isosteric Sulfonic Acid Analogues of the Anticoagulant Pentasaccharide Idraparinux
Authors: Mező Erika , Eszenyi Dániel , Varga Eszter , Herczeg Mihály , Borbás Anikó
Published: November 2016

Heparin-based anticoagulants are drugs of choice in the therapy and prophylaxis of thromboembolic diseases. Idraparinux is a synthetic anticoagulant pentasaccharide based on the heparin antithrombin-binding domain. In the frame of our ongoing research aimed at the synthesis of sulfonic acid-containing heparinoid anticoagulants, we elaborated a modular pathway to obtain a series of idraparinux-analogue pentasaccharides bearing one or two primary sulfonic acid moieties. Five protected pentasaccharides with different C-sulfonation patterns were prepared by two subsequent glycosylation reactions, respectively, using two monosaccharide and four disaccharide building blocks. Transformation of the protected derivatives into the fully O-sulfated, O-methylated sulfonic acid end-products was also studied.
Tropane and Granatane Alkaloid Biosynthesis: A Systematic Analysis
Authors: Kim Neill , Estrada Olga , Chavez Benjamin , Stewart Charles , D’Auria John
Published: November 2016

The tropane and granatane alkaloids belong to the larger pyrroline and piperidine classes of plant alkaloids, respectively. Their core structures share common moieties and their scattered distribution among angiosperms suggest that their biosynthesis may share common ancestry in some orders, while they may be independently derived in others. Tropane and granatane alkaloid diversity arises from the myriad modifications occurring to their core ring structures. Throughout much of human history, humans have cultivated tropane- and granatane-producing plants for their medicinal properties. This manuscript will discuss the diversity of their biological and ecological roles as well as what is known about the structural genes and enzymes responsible for their biosynthesis. In addition, modern approaches to producing some pharmaceutically important tropanes via metabolic engineering endeavors are discussed.
Influenza Neuraminidase Inhibitors: Synthetic Approaches, Derivatives and Biological Activity
Authors: Laborda Pedro , Wang Su-Yan , Voglmeir Josef
Published: November 2016

Despite being a common viral disease, influenza has very negative consequences, causing the death of around half a million people each year. A neuraminidase located on the surface of the virus plays an important role in viral reproduction by contributing to the release of viruses from infected host cells. The treatment of influenza is mainly based on the administration of neuraminidase inhibitors. The neuraminidase inhibitors zanamivir, laninamivir, oseltamivir and peramivir have been commercialized and have been demonstrated to be potent influenza viral neuraminidase inhibitors against most influenza strains. In order to create more potent neuraminidase inhibitors and fight against the surge in resistance resulting from naturally-occurring mutations, these anti-influenza drugs have been used as templates for the development of new neuraminidase inhibitors through structure-activity relationship studies. Here, we review the synthetic routes to these commercial drugs, the modifications which have been performed on these structures and the effects of these modifications on their inhibitory activity.
Kinetic Spectrophotometric Method for the 1,4-Diionic Organophosphorus Formation in the Presence of Meldrum′s Acid: Stopped-Flow Approach
Authors: Ghodsi Fatemeh , Habibi-Khorassani Sayyed , Shahraki Mehdi
Published: November 2016

The kinetics of the reaction between triphenylphosphine (TPP) and dimethyl acetylenedicarboxylate (DMAD) in the presence of Meldrum’s acid (MA) for the generation of the 1,4-diionic organophosphorus compound has been investigated using the stopped-flow and UV-VIS spectrophotometry techniques. The first step of the reaction between TPP and DMAD for the generation of (I1) in ethanol was followed by the stopped-flow apparatus. This step was recognized as a fast step. The reaction between the intermediate (I1) and MA showed first-order kinetics, and it was followed by the UV-VIS spectrophotometry technique. The activation parameters for the slow step of the proposed mechanism were determined using two linearized forms of the Eyring equation. From the temperature, concentration and solvent studies, the activation energy (Ea = 20.16 kJ·mol−1) and the related activation parameters (ΔG‡ = 71.17 ± 0.015 kJ·mol−1, ΔS‡ = −185.49 ± 0.026 J·mol−1 and ΔH‡ =17.72 ± 0.007 kJ·mol−1) were calculated. The experimental data indicated that the reaction was zero-order in MA and second-order overall. The proposed mechanism was confirmed with the observed kinetic data obtained from the UV-VIS and stopped-flow techniques.
CST, an Herbal Formula, Exerts Anti-Obesity Effects through Brain-Gut-Adipose Tissue Axis Modulation in High-Fat Diet Fed Mice
Authors: Ansari AbuZar , Bose Shambhunath , Yadav Mukesh , Wang Jing-Hua , Song Yun-Kyung , Ko Seong-Gyu , Kim Hojun
Published: November 2016

The brain, gut, and adipose tissue interact to control metabolic pathways, and impairment in the brain-gut-adipose axis can lead to metabolic disorders, including obesity. Chowiseungcheng-tang (CST), a herbal formulation, is frequently used to treat metabolic disorders. Here, we investigated the anti-obesity effect of CST and its link with brain-gut-adipose axis using C57BL/6J mice as a model. The animals were provided with a normal research diet (NRD) or high-fat diet (HFD) in absence or presence of CST or orlistat (ORL) for 12 weeks. CST had a significant anti-obesity effect on a number of vital metabolic and obesity-related parameters in HFD-fed mice. CST significantly decreased the expression levels of genes encoding obesity-promoting neuropeptides (agouti-related peptide, neuropeptide Y), and increased the mRNA levels of obesity-suppressing neuropeptides (proopiomelanocortin, cocaine-and amphetamine-regulated transcript) in the hypothalamus. CST also effectively decreased the expression level of gene encoding obesity-promoting adipokine (retinol-binding protein-4) and increased the mRNA level of obesity-suppressing adipokine (adiponectin) in visceral adipose tissue (VAT). Additionally, CST altered the gut microbial composition in HFD groups, a phenomenon strongly associated with key metabolic parameters, neuropeptides, and adipokines. Our findings reveal that the anti-obesity impact of CST is mediated through modulation of metabolism-related neuropeptides, adipokines, and gut microbial composition.
Oral Toxicity and Intestinal Transport Mechanism of Colloidal Gold Nanoparticle-Treated Red Ginseng
Authors: Bae Song-Hwa , Yu Jin , Go Mi-Ran , Kim Hyun-Jin , Hwang Yun-Gu , Choi Soo-Jin
Published: November 2016

(1) Background: Application of nanotechnology or nanomaterials in agricultural food crops has attracted increasing attention with regard to improving crop production, quality, and nutrient utilization. Gold nanoparticles (Au-NPs) have been reported to enhance seed yield, germination rate, and anti-oxidant potential in food crops, raising concerns about their toxicity potential. In this study, we evaluated the oral toxicity of red ginseng exposed to colloidal Au-NPs during cultivation (G-red ginseng) in rats and their intestinal transport mechanism. (2) Methods: 14-day repeated oral administration of G-red ginseng extract to rats was performed, and body weight, hematological, serum biochemical, and histopathological values were analyzed. An in vitro model of human intestinal follicle-associated epithelium (FAE) and an intestinal epithelial monolayer system were used for intestinal transport mechanistic study. (3) Results: No remarkable oral toxicity of G-red ginseng extract in rats was found, and Au-NPs did not accumulate in any organ, although Au-NP transfer to G-red ginseng and some increased saponin levels were confirmed. Au-NPs were transcytozed by microfold (M) cells, but not by a paracellular pathway in the intestinal epithelium. (4) Conclusion: These findings suggest great potential of Au-NPs for agricultural food crops at safe levels. Further study is required to elucidate the functional effects of Au-NPs on ginseng and long-term toxicity.
What Do People Know and Believe about Vitamin D?
Authors: Deschasaux Mélanie , Souberbielle Jean-Claude , Partula Valentin , Lécuyer Lucie , Gonzalez Rebeca , Srour Bernard , Guinot Christiane , Malvy Denis , Latino-Martel Paule , Druesne-Pecollo Nathalie , Galan Pilar , Hercberg Serge , Kesse-Guyot Emmanuelle , Fassier Philippine , Ezzedine Khaled , Touvier Mathilde
Published: November 2016

People have been exposed to a lot of information regarding vitamin D, with evidence suggesting that vitamin D may be involved in numerous health conditions, subsequently creating concerns about vitamin D insufficiency. As a result, what do people really know or believe about this topic? In this cross-sectional study, we assessed vitamin D-related knowledge and beliefs in 59,273 French adults (NutriNet-Santé cohort) using a specific questionnaire. Answers to this questionnaire were weighted according to the French sociodemographic distribution and compared across individual characteristics, using χ2-tests. Physicians and media were identified as key information providers. Participants did not always accurately cite vitamin D sources (e.g., 72% only for sun exposure, fatty fish: 61%) or established health effects (e.g., bone health: 62%–78%). Conversely, they mentioned incorrect sources and health effects for which there is no consensus yet (e.g., skin cancer). These findings were modulated by age/generational and socioeconomic factors. A strong inconsistency was also observed between participants’ true vitamin D status (plasma 25-hydroxyvitamin D concentration) and their opinion about it. This study, the first in Europe with such a large sample, stresses the need for simple and up-to-date supports of communication for the public and healthcare professionals regarding sources and health effects of vitamin D.
Investigating the Cellular and Metabolic Responses of World-Class Canoeists Training: A Sportomics Approach
Authors: Coelho Wagner , Viveiros de Castro Luis , Deane Elizabeth , Magno-França Alexandre , Bassini Adriana , Cameron Luiz-Claudio
Published: November 2016

(1) Background: We have been using the Sportomics approach to evaluate biochemical and hematological changes in response to exercise. The aim of this study was to evaluate the metabolic and hematologic responses of world-class canoeists during a training session; (2) Methods: Blood samples were taken at different points and analyzed for their hematological properties, activities of selected enzymes, hormones, and metabolites; (3) Results: Muscle stress biomarkers were elevated in response to exercise which correlated with modifications in the profile of white blood cells, where a leukocyte rise was observed after the canoe session. These results were accompanied by an increase in other exercise intensity parameters such as lactatemia and ammonemia. Adrenocorticotropic hormone and cortisol increased during the exercise sessions. The acute rise in both erythrocytes and white blood profile were probably due to muscle cell damage, rather than hepatocyte integrity impairment; (4) Conclusion: The cellular and metabolic responses found here, together with effective nutrition support, are crucial to understanding the effects of exercise in order to assist in the creation of new training and recovery planning. Also we show that Sportomics is a primal tool for training management and performance improvement, as well as to the understanding of metabolic response to exercise.
Novel Approaches to Investigate One-Carbon Metabolism and Related B-Vitamins in Blood Pressure
Authors: McMahon Amy , McNulty Helene , Hughes Catherine , Strain J. , Ward Mary
Published: November 2016

Hypertension, a major risk factor for heart disease and stroke, is the world’s leading cause of preventable, premature death. A common polymorphism (677C→T) in the gene encoding the folate metabolizing enzyme methylenetetrahydrofolate reductase (MTHFR) is associated with increased blood pressure, and there is accumulating evidence demonstrating that this phenotype can be modulated, specifically in individuals with the MTHFR 677TT genotype, by the B-vitamin riboflavin, an essential co-factor for MTHFR. The underlying mechanism that links this polymorphism, and the related gene-nutrient interaction, with hypertension is currently unknown. Previous research has shown that 5-methyltetrahydrofolate, the product of the reaction catalysed by MTHFR, appears to be a positive allosteric modulator of endothelial nitric oxide synthase (eNOS) and may thus increase the production of nitric oxide, a potent vasodilator. Blood pressure follows a circadian pattern, peaking shortly after wakening and falling during the night, a phenomenon known as ‘dipping’. Any deviation from this pattern, which can only be identified using ambulatory blood pressure monitoring (ABPM), has been associated with increased cardiovascular disease (CVD) risk. This review will consider the evidence linking this polymorphism and novel gene-nutrient interaction with hypertension and the potential mechanisms that might be involved. The role of ABPM in B-vitamin research and in nutrition research generally will also be reviewed.
Data Service Platform for Sentinel-2 Surface Reflectance and Value-Added Products: System Use and Examples
Authors: Vuolo Francesco , Żółtak Mateusz , Pipitone Claudia , Zappa Luca , Wenng Hannah , Immitzer Markus , Weiss Marie , Baret Frederic , Atzberger Clement
Published: November 2016

This technical note presents the first Sentinel-2 data service platform for obtaining atmospherically-corrected images and generating the corresponding value-added products for any land surface on Earth. Using the European Space Agency’s (ESA) Sen2Cor algorithm, the platform processes ESA’s Level-1C top-of-atmosphere reflectance to atmospherically-corrected bottom-of-atmosphere (BoA) reflectance (Level-2A). The processing runs on-demand, with a global coverage, on the Earth Observation Data Centre (EODC), which is a public-private collaborative IT infrastructure in Vienna (Austria) for archiving, processing, and distributing Earth observation (EO) data. Using the data service platform, users can submit processing requests and access the results via a user-friendly web page or using a dedicated application programming interface (API). Building on the processed Level-2A data, the platform also creates value-added products with a particular focus on agricultural vegetation monitoring, such as leaf area index (LAI) and broadband hemispherical-directional reflectance factor (HDRF). An analysis of the performance of the data service platform, along with processing capacity, is presented. Some preliminary consistency checks of the algorithm implementation are included to demonstrate the expected product quality. In particular, Sentinel-2 data were compared to atmospherically-corrected Landsat-8 data for six test sites achieving a R2 = 0.90 and Root Mean Square Error (RMSE) = 0.031. LAI was validated for one test site using ground estimations. Results show a very good agreement (R2 = 0.83) and a RMSE of 0.32 m2/m2 (12% of mean value).
Water Constituents and Water Depth Retrieval from Sentinel-2A—A First Evaluation in an Oligotrophic Lake
Authors: Dörnhöfer Katja , Göritz Anna , Gege Peter , Pflug Bringfried , Oppelt Natascha
Published: November 2016

Satellite remote sensing may assist in meeting the needs of lake monitoring. In this study, we aim to evaluate the potential of Sentinel-2 to assess and monitor water constituents and bottom characteristics of lakes at spatio-temporal synoptic scales. In a field campaign at Lake Starnberg, Germany, we collected validation data concurrently to a Sentinel-2A (S2-A) overpass. We compared the results of three different atmospheric corrections, i.e., Sen2Cor, ACOLITE and MIP, with in situ reflectance measurements, whereof MIP performed best (r = 0.987, RMSE = 0.002 sr−1). Using the bio-optical modelling tool WASI-2D, we retrieved absorption by coloured dissolved organic matter (aCDOM(440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and aCDOM(440) were modelled in optically shallow water. In deep water, SPM and aCDOM(440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m−1) showed an underestimation of S2-A derived aCDOM(440) (mean: 0.14 m−1); S2-A backscattering of SPM was slightly higher than backscattering from in situ data (mean: 0.027 m−1 vs. 0.019 m−1). Chlorophyll-a concentrations (~1 mg·m−3) of the lake were too low for a retrieval. In shallow water, retrieved water depths exhibited a high correlation with echo sounding data (r = 0.95, residual standard deviation = 0.12 m) up to 2.5 m (Secchi disk depth: 4.2 m), though water depths were slightly underestimated (RMSE = 0.56 m). In deeper water, Sentinel-2A bands were incapable of allowing a WASI-2D based separation of macrophytes and sediment which led to erroneous water depths. Overall, the results encourage further research on lakes with varying optical properties and trophic states with Sentinel-2A.
A Novel Approach for Retrieving Tree Leaf Area from Ground-Based LiDAR
Authors: Yun Ting , An Feng , Li Weizheng , Sun Yuan , Cao Lin , Xue Lianfeng
Published: November 2016

Leaf area is an important plant canopy structure parameter with important ecological significance. Light detection and ranging technology (LiDAR) with the application of a terrestrial laser scanner (TLS) is an appealing method for accurately estimating leaf area; however, the actual utility of this scanner depends largely on the efficacy of point cloud data (PCD) analysis. In this paper, we present a novel method for quantifying total leaf area within each tree canopy from PCD. Firstly, the shape, normal vector distribution and structure tensor of PCD features were combined with the semi-supervised support vector machine (SVM) method to separate various tree organs, i.e., branches and leaves. In addition, the moving least squares (MLS) method was adopted to remove ghost points caused by the shaking of leaves in the wind during the scanning process. Secondly, each target tree was scanned using two patterns, i.e., one scan and three scans around the canopy, to reduce the occlusion effect. Specific layer subdivision strategies according to the acquisition ranges of the scanners were designed to separate the canopy into several layers. Thirdly, 10% of the PCD was randomly chosen as an analytic dataset (ADS). For the ADS, an innovative triangulation algorithm with an assembly threshold was designed to transform these discrete scanning points into leaf surfaces and estimate the fractions of each foliage surface covered by the laser pulses. Then, a novel ratio of the point number to leaf area in each layer was defined and combined with the total number of scanned points to retrieve the total area of the leaves in the canopy. The quantified total leaf area of each tree was validated using laborious measurements with a LAI-2200 Plant Canopy Analyser and an LI-3000C Portable Area Meter. The results showed that the individual tree leaf area was accurately reproduced using our method from three registered scans, with a relative deviation of less than 10%. Nevertheless, estimations from only one scan resulted in a deviation of >25% in the retrieved individual tree leaf area due to the occlusion effect. Indeed, this study provides a novel connection between leaf area estimates and scanning sensor configuration and supplies an interesting method for estimating leaf area based on PCD.
Tip-Clearance Measurement in the First Stage of the Compressor of an Aircraft Engine
Authors: García Iker , Przysowa Radosław , Amorebieta Josu , Zubia Joseba
Published: November 2016

In this article, we report the design of a reflective intensity-modulated optical fiber sensor for blade tip-clearance measurement, and the experimental results for the first stage of a compressor of an aircraft engine operating in real conditions. The tests were performed in a ground test cell, where the engine completed four cycles from idling state to takeoff and back to idling state. During these tests, the rotational speed of the compressor ranged between 7000 and 15,600 rpm. The main component of the sensor is a tetrafurcated bundle of optical fibers, with which the resulting precision of the experimental measurements was 12 µm for a measurement range from 2 to 4 mm. To get this precision the effect of temperature on the optoelectronic components of the sensor was compensated by calibrating the sensor in a climate chamber. A custom-designed MATLAB program was employed to simulate the behavior of the sensor prior to its manufacture.
Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting
Authors: Husen Mohd , Lee Sukhan
Published: November 2016

A method of location fingerprinting based on the Wi-Fi received signal strength (RSS) in an indoor environment is presented. The method aims to overcome the RSS instability due to varying channel disturbances in time by introducing the concept of invariant RSS statistics. The invariant RSS statistics represent here the RSS distributions collected at individual calibration locations under minimal random spatiotemporal disturbances in time. The invariant RSS statistics thus collected serve as the reference pattern classes for fingerprinting. Fingerprinting is carried out at an unknown location by identifying the reference pattern class that maximally supports the spontaneous RSS sensed from individual Wi-Fi sources. A design guideline is also presented as a rule of thumb for estimating the number of Wi-Fi signal sources required to be available for any given number of calibration locations under a certain level of random spatiotemporal disturbances. Experimental results show that the proposed method not only provides 17% higher success rate than conventional ones but also removes the need for recalibration. Furthermore, the resolution is shown finer by 40% with the execution time more than an order of magnitude faster than the conventional methods. These results are also backed up by theoretical analysis.
Tunnel Magnetoresistance Sensors with Magnetostrictive Electrodes: Strain Sensors
Authors: Tavassolizadeh Ali , Rott Karsten , Meier Tobias , Quandt Eckhard , Hölscher Hendrik , Reiss Günter , Meyners Dirk
Published: November 2016

Magnetostrictive tunnel magnetoresistance (TMR) sensors pose a bright perspective in micro- and nano-scale strain sensing technology. The behavior of TMR sensors under mechanical stress as well as their sensitivity to the applied stress depends on the magnetization configuration of magnetic tunnel junctions (MTJ)s with respect to the stress axis. Here, we propose a configuration resulting in an inverse effect on the tunnel resistance by tensile and compressive stresses. Numerical simulations, based on a modified Stoner–Wohlfarth (SW) model, are performed in order to understand the magnetization reversal of the sense layer and to find out the optimum bias magnetic field required for high strain sensitivity. At a bias field of −3.2 kA/m under a 0.2 × 10 - 3 strain, gauge factors of 2294 and −311 are calculated under tensile and compressive stresses, respectively. Modeling results are investigated experimentally on a round junction with a diameter of 30 ± 0.2 μ m using a four-point bending apparatus. The measured field and strain loops exhibit nearly the same trends as the calculated ones. Also, the gauge factors are in the same range. The junction exhibits gauge factors of 2150 ± 30 and −260 for tensile and compressive stresses, respectively, under a −3.2 kA/m bias magnetic field. The agreement of the experimental and modeling results approves the proposed configuration for high sensitivity and ability to detect both tensile and compressive stresses by a single TMR sensor.
Advanced Pedestrian Positioning System to Smartphones and Smartwatches
Authors: Correa Alejandro , Munoz Diaz Estefania , Bousdar Ahmed Dina , Morell Antoni , Lopez Vicario Jose
Published: November 2016

In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user’s position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m 2 .
DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field
Authors: Christiansen Peter , Nielsen Lars , Steen Kim , Jørgensen Rasmus , Karstoft Henrik
Published: November 2016

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m) than RCNN. RCNN has a similar performance at a short range (0–30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit).