bluuebunny/crossref_metadata_2025 huggingface dataset:
Testing the Cow’s Milk-Related Symptom Score (CoMiSSTM) for the Response to a Cow’s Milk-Free Diet in Infants: A Prospective Study
Authors: Salvatore Silvia , Bertoni Elisabetta , Bogni Federica , Bonaita Valentina , Armano Chiara , Moretti Alex , Baù Mario , Luini Chiara , D’Auria Enza , Marinoni Maddalena , Zuccotti GianVincenzo , Agosti Massimo
Published: October 2019

The diagnosis of cow’s milk allergy (CMA) is particularly challenging in infants, especially with non-Immunoglobulin E (IgE)-mediated manifestations, and inaccurate diagnosis may lead to unnecessary dietary restrictions. The aim of this study was to assess the accuracy of the cow’s milk-related symptom score (CoMiSSTM) in response to a cow’s milk-free diet (CMFD). We prospectively recruited 47 infants (median age three months) who had been placed on a CMFD due to persisting unexplained gastrointestinal symptoms. We compared data with 94 healthy controls (median age three months). The CoMiSSTM score was completed at recruitment and while on the exclusion diet. In 19/47 (40%) cases a response to the diet occurred. At recruitment CoMiSSTM was significantly higher in cases compared to controls (median score 8 vs. 3; p-value: <0.05), 9 cases had a score ≥12 and 8/9 normalized on CMFD. An oral milk challenge was performed in all 19 responders and six of these had a positive reaction to cow’s milk (CM). In eight infants IgE allergy tests were positive. The receiver operation characteristic (ROC) curve identified a CoMISSTM score of 9 to be the best cut-off value (84% sensitivity, 85% specificity, 80% positive (PPV) and 88% negative predictive value (NPV)) for the response to CMFD. We found CoMiSSTM to be a useful tool to help identify infants with persisting gastrointestinal symptoms and suspected CMA that would benefit from CMFD.
The Effect of the Yingyangbao Complementary Food Supplement on the Nutritional Status of Infants and Children: A Systematic Review and Meta-Analysis
Authors: Li Zhihui , Li Xinyi , Sudfeld Christopher R. , Liu Yuning , Tang Kun , Huang Yangmu , Fawzi Wafaie
Published: October 2019

Yingyangbao (YYB) is a nutrient-dense complementary food supplement for infants and young children in China. There has been considerable interest and research on the potential effects of YYB on hematological and anthropometric outcomes in China, but limited effort has been made to consolidate and synthesize the evidence to inform the research and policy agendas. Eight English databases and three Chinese databases were searched from January 2001 to June 2019 to identify YYB intervention studies. A total of 32 quasi-experimental, post-only, concurrent-control studies or pre-post studies were identified, and 26 were included in the meta-analyses. A pooled analysis of post-only studies with concurrent-control determined that YYB was associated with an increase of 4.43 g/L (95% confidence interval (CI) 1.55, 7.30) hemoglobin concentration, 2.46 cm (CI 0.96, 3.97) in height, and 0.79 kg (CI 0.25, 1.32) weight in infants and young children. YYB was also associated with reductions in the prevalence of anemia (risk ratio (RR) = 0.55; 95% CI: 0.45, 0.67), stunting (RR = 0.60; 95% CI: 0.44, 0.81), and underweight (RR = 0.51; 95% CI: 0.39, 0.65). Overall, YYB was found to be associated with improved hematological and anthropometric indicators among infants and young children in China; however, randomized trials are needed to causally assess the efficacy of YYB due to the inherent risk of bias in existing quasi-experimental studies; rigorous implementation and cost-effectiveness evaluations are also needed.
Metabolic Trajectories Following Contrasting Prudent and Western Diets from Food Provisions: Identifying Robust Biomarkers of Short-Term Changes in Habitual Diet
Authors: Wellington Nadine , Shanmuganathan Meera , de Souza Russell J. , Zulyniak Michael A. , Azab Sandi , Bloomfield Jonathon , Mell Alicia , Ly Ritchie , Desai Dipika , Anand Sonia S. , Britz-McKibbin Philip
Published: October 2019

A large body of evidence has linked unhealthy eating patterns with an alarming increase in obesity and chronic disease worldwide. However, existing methods of assessing dietary intake in nutritional epidemiology rely on food frequency questionnaires or dietary records that are prone to bias and selective reporting. Herein, metabolic phenotyping was performed on 42 healthy participants from the Diet and Gene Intervention (DIGEST) pilot study, a parallel two-arm randomized clinical trial that provided complete diets to all participants. Matching single-spot urine and fasting plasma specimens were collected at baseline, and then following two weeks of either a Prudent or Western diet with a weight-maintaining menu plan designed by a dietician. Targeted and nontargeted metabolite profiling was conducted using three complementary analytical platforms, where 80 plasma metabolites and 84 creatinine-normalized urinary metabolites were reliably measured (CV < 30%) in the majority of participants (>75%) after implementing a rigorous data workflow for metabolite authentication with stringent quality control. We classified a panel of metabolites with distinctive trajectories following two weeks of food provisions when using complementary univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high-resolution MS/MS, as well as co-elution after spiking with authentic standards if available. Overall, 3-methylhistidine and proline betaine concentrations increased in both plasma and urine samples after participants were assigned a Prudent diet (q < 0.05) with a corresponding decrease in the Western diet group. Similarly, creatinine-normalized urinary imidazole propionate, hydroxypipecolic acid, dihydroxybenzoic acid, and enterolactone glucuronide, as well as plasma ketoleucine and ketovaline increased with a Prudent diet (p < 0.05) after adjustments for age, sex, and BMI. In contrast, plasma myristic acid, linoelaidic acid, linoleic acid, α-linoleic acid, pentadecanoic acid, alanine, proline, carnitine, and deoxycarnitine, as well as urinary acesulfame K increased among participants following a Western diet. Most metabolites were also correlated (r > ± 0.30, p < 0.05) to changes in the average intake of specific nutrients from self-reported diet records reflecting good adherence to assigned food provisions. Our study revealed robust biomarkers sensitive to short-term changes in habitual diet, which is needed for accurate monitoring of healthy eating patterns in free-living populations, and evidence-based public health policies for chronic disease prevention.
Sex-Specific Glucose Homeostasis and Anthropometric Responses to Sleeve Gastrectomy in Obese Patients
Authors: Taylor Mark A. , Szczerbinski Lukasz , Citko Anna , Niemira Magdalena , Gorska Maria , Hady Hady Razak , Kretowski Adam
Published: October 2019

Bariatric surgery rapidly and effectively treats obesity and its comorbidities like dysregulated glucose homeostasis. Despite the sex-balanced incidence of obesity in most human populations, women have sought this intervention more frequently than men. However, as the number of bariatric surgeries rapidly rises, it is increasingly urgent to understand how sex-specific differences may emerge in metabolic and anthropometric parameters. Hundred fifty-four obese patients (47% men and 53% women) from the Bialystok Bariatric Surgery Study underwent sleeve gastrectomy and were measured for 25 parameters at baseline (immediately prior to surgery) and at four follow-up visits over one year. We used generalized linear mixed models to detect sex-specific differences in the time series of responses parameters. Unlike most previous studies with older cross-sections of men than women, our cohort was age-matched, and men were less healthy at baseline. Of parameters that showed a significant cohort-wide (across-sex) response, 14 (56%) also showed sex-specific responses with men improving more than women. In particular, men remitted in diabetes symptoms more strongly, rapidly, and durably than women. Taken together, our results indicate that men may benefit more from sleeve gastrectomy and that this difference in improvement may be related to more progressed morbidity prior to surgery independent of age.
Hypnotic Effects of Lactobacillus fermentum PS150TM on Pentobarbital-Induced Sleep in Mice
Authors: Lin Alexander , Shih Ching-Ting , Huang Chin-Lin , Wu Chien-Chen , Lin Ching-Ting , Tsai Ying-Chieh
Published: October 2019

The bidirectional communication between the gastrointestinal tract and the central nervous system appears to be functionally linked to the intestinal microbiome, namely the microbiome–gut–brain axis (MGBA). Probiotics with health benefits on psychiatric or neurological illnesses are generally called psychobiotics, and some of them may also be able to improve sleep by targeting the MGBA. This study aimed to investigate the effects of a psychobiotic strain, Lactobacillus fermentum PS150TM (PS150TM), on sleep improvement by using a pentobarbital-induced sleep mouse model. Compared with the vehicle control group, the oral administration of PS150TM, but not the other L. fermentum strains, significantly decreased the sleep latency and increased the sleep duration of mice, suggesting strain-specific sleep-improving effects of PS150TM. Moreover, the ingestion of diphenhydramine, an antihistamine used to treat insomnia, as a drug control group, only increased the sleep duration of mice. We also found that the sleep-improving effects of PS150TM are time- and dose-dependent. Furthermore, the oral administration of PS150TM could attenuate a caffeine-induced sleep disturbance in mice, and PS150TM appeared to increase the expression of the gene encoding the adenosine 1 receptor in the hypothalamus of mice, as assessed by quantitative real-time polymerase chain reaction. Taken together, our results present a potential application of PS150TM as a dietary supplement for sleep improvement.
Precision Nutrition and Metabolic Syndrome Management
Authors: González-Muniesa Pedro , Martínez J. Alfredo
Published: October 2019

The journal NUTRIENTS published some time ago a special issue about “Precision Nutrition and Metabolic Syndrome Management”, which included a series of articles about the role of bioactive compounds, amino acids/proteins and fatty acids for personalized nutritional applications [...]
The Pharmacokinetics of Vitamin C
Authors: Lykkesfeldt Jens , Tveden-Nyborg Pernille
Published: October 2019

The pharmacokinetics of vitamin C (vitC) is indeed complex. Regulated primarily by a family of saturable sodium dependent vitC transporters (SVCTs), the absorption and elimination are highly dose-dependent. Moreover, the tissue specific expression levels and subtypes of these SVCTs result in a compartmentalized distribution pattern with a diverse range of organ concentrations of vitC at homeostasis ranging from about 0.2 mM in the muscle and heart, and up to 10 mM in the brain and adrenal gland. The homeostasis of vitC is influenced by several factors, including genetic polymorphisms and environmental and lifestyle factors such as smoking and diet, as well as diseases. Going from physiological to pharmacological doses, vitC pharmacokinetics change from zero to first order, rendering the precise calculation of dosing regimens in, for example, cancer and sepsis treatment possible. Unfortunately, the complex pharmacokinetics of vitC has often been overlooked in the design of intervention studies, giving rise to misinterpretations and erroneous conclusions. The present review outlines the diverse aspects of vitC pharmacokinetics and examines how they affect vitC homeostasis under a variety of conditions.
Optimization of Taste-Masked (–)-Oleocanthal Effervescent Formulation with Potent Breast Cancer Progression and Recurrence Suppressive Activities
Authors: Tajmim Afsana , Siddique Abu Bakar , El Sayed Khalid
Published: October 2019

S-(–)-Oleocanthal (OC), a naturally occurring phenolic secoiridoid exclusively found in extra-virgin olive oil (EVOO), is a potential nutraceutical therapeutic for inflammation, neurodegenerative diseases, and many malignancies, especially breast cancer (BC). The oral delivery of OC is challenging because of its irritative, bitter, and pungent taste and exceptional chemistry, including two reactive aldehydes, phenolic, and ester groups. OC irritation did not correlate with CO2-induced irritation, and hence, OC was not exerting generalized acid-sensing irritation. The objective of this study was to develop an effervescent formulation of OC with an effective CO2-induced masked taste maintaining the efficacy against the estrogen receptor (ER) and HER2 positive BC. Several ratios of acid and carbonate sources were screened, and five effervescent formulations EF1-EF5 were selected and prepared based on their pH and effervescence time. OC formulations were characterized using differential scanning calorimetry, FT-IR spectroscopy, and scanning electron microscopy analyses. OC formulations exhibited acceptable flowability and effervescence time. Based on physical characteristics and improved OC release, formulation EF-2 was selected for subsequent studies. EF-2 showed effective OC taste masking, as suggested by electronic artificial tongue and mouse preference tests. EF-2 suppressed more than 70% of the hormone and HER2-positive BT-474 BC cell growth in a nude mouse xenograft model. Furthermore, EF-2 demonstrated significant inhibition of BT-474 tumor cell locoregional recurrence after primary tumor surgical excision. EF-2-treated mouse sera had significantly reduced CA 15-3 levels, the human BC recurrence marker, compared to the placebo control group at the end of the study. These results highlight the potential of the OC formulation EF-2 as a prospective nutraceutical for the control and prevention of ER+/HER+ BC progression and locoregional recurrence.
Evaluation of Different Techniques for Size Determination of Drug Nanocrystals: A Case Study of Celecoxib Nanocrystalline Solid Dispersion
Authors: Kaur Amanpreet , Parmar Prashantkumar Khodabhai , Bansal Arvind Kumar
Published: October 2019

Celecoxib (CEL) Nanocrystalline Solid Dispersion (CEL_NCSD) was generated by spray drying CEL, mannitol (MAN) and sodium lauryl sulfate (SLS) from a solvent mixture of methanol, acetone and water. The purpose of the work was to determine the size of CEL nanocrystals, investigate agglomeration and inspect dissolution of CEL_NCSD. Size determination was challenging as CEL nanocrystals are embedded in the matrix of MAN. Firstly, neat CEL_NCSD was analyzed using Scherrer equation. Secondly, MAN was dissolved in an aqueous stabilizer medium to selectively measure the size of CEL nanocrystals. Raman Spectra captured in Morphologi G3-ID confirmed the presence of CEL-only particles in the media. This dispersion gave D90 values of 882 ± 170.34 nm in Zetasizer. Discriminatory dissolution studies confirmed total release of 34.61 ± 1.59%, 47.42 ± 0.24%, and 44.61 ± 1.11% at 120 min from a microsuspension (size 3 µm), a nanosuspension (media milled; size 660 nm) and CEL_NCSD, respectively. The dissolution profile of CEL_NCSD was similar to that of a nanosuspension (f2 72.24) instead of a coarse microsuspension. Thus, the present study revealed that optimized sample preparation is critical for the size determination of embedded drug nanocrystals in NCSD. Further, a discriminatory dissolution study substantiated that the size of CEL nanocrystals in CEL_NCSD is well below 1000 nm, thus showing a size-dependent improved dissolution profile.
Improved Understanding of the High Shear Wet Granulation Process under the Paradigm of Quality by Design Using Salvia miltiorrhiza Granules
Authors: Zhang Yi , Cheng Brian Chi-Yan , Zhou Wenjuan , Xu Bing , Gao Xiaoyan , Qiao Yanjiang , Luo Gan
Published: October 2019

Background: High shear wet granulation (HSWG) is a shaping process for granulation that has been enhanced for application in the pharmaceutical industry. However, study of HSWG is complex and challenging due to the relatively poor understanding of HSWG, especially for sticky powder-like herbal extracts. Aim: In this study, we used Salvia miltiorrhiza granules to investigate the HSWG process across different scales using quality by design (QbD) approaches. Methods: A Plackett–Burman experimental design was used to screen nine granulation factors in the HSWG process. Moreover, a quadratic polynomial regression model was established based on a Box–Behnken experimental design to optimize the granulation factors. In addition, the scale-up of HSWG was implemented based on a nucleation regime map approach. Results: According to the Plackett–Burman experimental design, it was found that three granulation factors, including salvia ratio, binder amount, and chopper speed, significantly affected the granule size (D50) of S. miltiorrhiza in HSWG. Furthermore, the results of the Box–Behnken experimental design and validation experiment showed that the model successfully captured the quadratic polynomial relationship between granule size and the two granulation factors of salvia ratio and binder amount. At the same experiment points, granules at all scales had similar size distribution, surface morphology, and flow properties. Conclusions: These results demonstrated that rational design, screening, optimization, and scale-up of HSWG are feasible using QbD approaches. This study provides a better understanding of HSWG process under the paradigm of QbD using S. miltiorrhiza granules.
Simulation of Phosphorus Chemistry, Uptake and Utilisation by Winter Wheat
Authors: Wu Lianhai , Blackwell Martin , Dunham Sarah , Hernández-Allica Javier , McGrath Steve P.
Published: October 2019

The phosphorus (P) supply from soils is crucial to crop production. Given the complexity involved in P-cycling, a model that can simulate the major P-cycling processes and link with other nutrients and environmental factors, e.g., soil temperature and moisture, would be a useful tool. The aim of this study was to describe a process-based P module added to the SPACSYS (Soil Plant and Atmosphere Continuum System) model and to evaluate its predictive capability on the dynamics of P content in crops and the impact of soil P status on crop growth. A P-cycling module was developed and linked to other modules included in the SPACSYS model. We used a winter wheat (Triticum aestivum, cv Xi-19) field experiment at Rothamsted Research in Harpenden to calibrate and validate the model. Model performance statistics show that the model simulated aboveground dry matter, P accumulation and soil moisture dynamics reasonably well. Simulated dynamics of soil nitrate and ammonium were close to the observed data when P fertiliser was applied. However, there are large discrepancies in fields without P fertiliser. This study demonstrated that the SPACSYS model was able to investigate the interactions between carbon, nitrogen, P and water in a single process-based model after the tested P module was implemented.
Stabilization of Electrospun Nanofiber Mats Used for Filters by 3D Printing
Authors: Kozior Tomasz , Trabelsi Marah , Mamun Al , Sabantina Lilia , Ehrmann Andrea
Published: October 2019

Electrospinning is a well-known technology used to create nanofiber mats from diverse polymers and other materials. Due to their large surface-to-volume ratio, such nanofiber mats are often applied as air or water filters. Especially the latter, however, have to be mechanically highly stable, which is challenging for common nanofiber mats. One of the approaches to overcome this problem is gluing them on top of more rigid objects, integrating them in composites, or reinforcing them using other technologies to avoid damage due to the water pressure. Here, we suggest another solution. While direct 3D printing with the fused deposition modeling (FDM) technique on macroscopic textile fabrics has been under examination by several research groups for years, here we report on direct FDM printing on nanofiber mats for the first time. We show that by choosing the proper height of the printing nozzle above the nanofiber mat, printing is possible for raw polyacrylonitrile (PAN) nanofiber mats, as well as for stabilized and even more brittle carbonized material. Under these conditions, the adhesion between both parts of the composite is high enough to prevent the nanofiber mat from being peeled off the 3D printed polymer. Abrasion tests emphasize the significantly increased mechanical properties, while contact angle examinations reveal a hydrophilicity between the original values of the electrospun and the 3D printed materials.
Sustainable Synthesis Processes for Carbon Dots through Response Surface Methodology and Artificial Neural Network
Authors: Yahaya Pudza Musa , Zainal Abidin Zurina , Abdul Rashid Suraya , Md Yasin Faizah , Noor Ahmad Shukri Muhammad , Issa Mohammed A.
Published: October 2019

Nowadays, to ensure sustainability of smart materials, it is imperative to eliminate or reduce carbon footprint related to nano material production. The concept of design of experiment to provide an optimal synthesis process, with a desired yield, is indispensable. It is the researcher’s goal to get optimum value for experiments that requires multiple runs and multiple inputs. Herein, is a reliable approach of utilizing design of experiment (DOE) for response surface methodology (RSM). Thus, to optimize a facile and effective synthesis process for fluorescent carbon dots (CDs) derived from tapioca that is in line with green chemistry principles for sustainable synthesis. The predictions for fluorescent CDs synthesis from RSM were in excellent agreement with the artificial neural network (ANN) model prediction by the Levenberg–Marquardt back propagation (LMBP) algorithm. Considering R2, root mean square error (RMSE) and mean absolute error (MAE) have all revealed a positive hidden layer size. The best hidden layer of neurons were discovered at point 4-8, to confirm the validity of carbon dots, characterization of surface morphology and particles sizes of CDs were conducted with favorable confirmations of the unique characteristics and attributes of synthesized CDs by hydrothermal route.
Thermochemical Conversion of Napier Grass for Production of Renewable Syngas
Authors: Md Said Mohamad Syazarudin , Wan Abdul Karim Ghani Wan Azlina , Hong Boon Tan , Hussain Siti Aslina , Ng Denny Kok Sum
Published: October 2019

Fuel resource diversification is a global effort to deviate from non-renewable fossil fuels. Biomass has been identified as an alternative solid biofuel source due to its desirable properties and carbon neutrality. As reported in the literature, biomass can positively contribute towards combating climate change while providing alleviation for energy security issue. As part of efforts to diversify biomass resources, this work intends to explore the potential of Napier grass, one type of energy crop, for the production of renewable syngas via gasification. This energy crop is originally from Africa, which is highly productive with low cost (40 tonnes per year per hectare). Limited studies were conducted to analyze the potential of such an energy crop as a fuel source, which is the subject of this work. In order to analyze the full potential of such energy crop, the physical and chemical characteristics of this biomass was first analyzed. To determine the productivity of syngas from this biomass, fluidized bed gasifier was used in this work. The effects of gasification process parameters (i.e., equivalence ratio and temperature) on product yield and producer gas compositions were examined. Besides, the effects of equivalence ratio towards higher heating value of syngas and carbon conversion efficiency were analyzed. Based on the ultimate analysis results, the molecular formula of Napier gas was CH1.56O0.81N0.0043. Meanwhile, the higher heating value of such biomass was determined as 16.73 MJ/kg, which was comparable to other biomasses. It is noted that in this work, the volatile matter was determined as 85.52% and this promoted gasification process remarkably. The dynamics of the reactions involved were observed as a significant variation in product yield and biogas components were recorded at varying equivalence ratio and gasifier operating temperature.
MODIS and PROBA-V NDVI Products Differ when Compared with Observations from Phenological Towers at Four Tropical Dry Forests in the Americas
Authors: Guzmán Q. J. Antonio , Sanchez-Azofeifa G. Arturo , Espírito-Santo Mário M.
Published: October 2019

The Normalized Difference Vegetation Index (NDVI) is widely used to monitor vegetation phenology and productivity around the world. Over the last few decades, phenology monitoring at large scales has been possible due to the information and metrics derived from satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Project for On-Board Autonomy–Vegetation (PROBA-V). However, due to their temporal and spatial resolution, adequate ground comparison is lacking. In this paper, we analyze how NDVI products from MODIS (Aqua and Terra) and PROBA-V predict vegetation phenology when compared with near-surface observations. We conduct this comparison at four tropical dry forests (TDFs) in the Americas. We undertake this study by comparing the following: (i) Dissimilarities of the standardized NDVI (NDVIS) using dynamic time warping, (ii) the differences of daily NDVIS between seasons and ENSO months using generalized linear models, and (iii) phenometrics derived from NDVI time series. Overall, our results suggest that NDVIS from satellite observations present DTW distances (dissimilarities) between 2.98 and 46.57 (18.91 ± 12.31) when compared with near-surface observations. Furthermore, NDVIS comparisons reveal that overall differences between satellite and near-surface observations are close to zero, but this tends to differ between seasons or when El Nino Southern Oscillation (ENSO) is present. Phenometrics comparisons show that metrics derived from satellite observations such as green-up, maturity, and start and end of the wet season strongly correlate with those from near-surface observations. In contrast, phenometrics that describe the day of the highest or lowest NDVI tend to be inconsistent with those from near-surface observations. All findings were observed independently of the NDVI source. Our results suggest that satellite-based NDVI products tend to be inconsistent descriptors of vegetation events on tropical deciduous forests in comparison with near-surface observations. These results reinforce the idea that satellite-based NDVI products should be used and interpreted with great caution and only in ecosystems with well-established knowledge of their vegetation phenology.
Drawback in the Change Detection Approach: False Detection during the 2018 Western Japan Floods
Authors: Moya Luis , Endo Yukio , Okada Genki , Koshimura Shunichi , Mas Erick
Published: October 2019

Synthetic aperture radar (SAR) images have been used to map flooded areas with great success. Flooded areas are often identified by detecting changes between a pair of images recorded before and after a certain flood. During the 2018 Western Japan Floods, the change detection method generated significant misclassifications for agricultural targets. To evaluate whether such a situation could be repeated in future events, this paper examines and identifies the causes of the misclassifications. We concluded that the errors occurred because of the following. (i) The use of only a single pair of SAR images from before and after the floods. (ii) The unawareness of the dynamics of the backscattering intensity through time in agricultural areas. (iii) The effect of the wavelength on agricultural targets. Furthermore, it is highly probable that such conditions might occur in future events. Our conclusions are supported by a field survey of 35 paddy fields located within the misclassified area and the analysis of Sentinel-1 time series data. In addition, in this paper, we propose a new parameter, which we named “conditional coherence”, that can be of help to overcome the referred issue. The new parameter is based on the physical mechanism of the backscattering on flooded and non-flooded agricultural targets. The performance of the conditional coherence as an input of discriminant functions to identify flooded and non-flooded agricultural targets is reported as well.
On C-Band Quad-Polarized Synthetic Aperture Radar Properties of Ocean Surface Currents
Authors: Fan Shengren , Kudryavtsev Vladimir , Zhang Biao , Perrie William , Chapron Bertrand , Mouche Alexis
Published: October 2019

We present new results for ocean surface current signatures in dual co- and cross-polarized synthetic aperture radar (SAR) images. C-band RADARSAT-2 quad-polarized SAR ocean scenes are decomposed into resonant Bragg scattering from regular (non-breaking) surface waves and scattering from breaking waves. Surface current signatures in dual co- and cross-polarized SAR images are confirmed to be governed by the modulations due to wave breaking. Due to their small relaxation scale, short Bragg waves are almost insensitive to surface currents. Remarkably, the contrast in sensitivity of the non-polarized contribution to dual co-polarized signals is found to largely exceed, by a factor of about 3, the contrast in sensitivity of the corresponding cross-polarized signals. A possible reason for this result is the co- and cross-polarized distinct scattering mechanisms from breaking waves: for the former, quasi-specular radar returns are dominant, whereas for the latter, quasi-resonant scattering from the rough breaking crests governs the backscatter intensity. Thus, the differing sensitivity can be related to distinct spectral intervals of breaking waves contributing to co- and cross-polarized scattering in the presence of surface currents. Accordingly, routinely observed current signatures in quad-polarized SAR images essentially originate from wave breaking modulations, and polarized contrasts can therefore help quantitatively retrieve the strength of surface current gradients.
Deriving a Forest Cover Map in Kyrgyzstan Using a Hybrid Fusion Strategy
Authors: Jia Tao , Li Yuqian , Shi Wenzhong , Zhu Ling
Published: October 2019

Forests have potential economic value and play a significant role in maintaining ecological balance. Considering its outdated and incomplete forest statistics, the Kyrgyzstan Republic urgently needs a forest cover map for assessing its current forest resources and assisting national policies on improving rural livelihood and sustainability. This study adopted a hybrid fusion strategy to develop a forest cover map for the Kyrgyzstan Republic with improved accuracy. The fusion strategy uses the merits of the GlobeLand30 in 2010 and the USGS TreeCover2010, the benefits of auxiliary geographic information, and the advantages of the stacking learning method in classification. Additionally, we explored the influence of different forest definitions, based on the tree cover percentage value in the USGS TreeCover2010, on the accuracy of forest cover. Results suggested that the accuracy of our model can be improved significantly by including auxiliary geographic features and feeding the optimal size of training samples. Thereafter, using our model, forest cover maps were derived at different tree cover threshold values in the USGS TreeCover2010. Importantly, the forest cover map at the tree cover threshold value of 40% was determined as the most accurate one with the kappa value of 0.89, whose spatial extent constitutes about 2.4% of the entire territory. This estimated forest cover percentage suggests a low estimation of forest resources based on rigorous definition, which can be valuable for reviewing and amending the current national forest policies.
Unmanned Aerial Vehicles (UAVs) for Monitoring Macroalgal Biodiversity: Comparison of RGB and Multispectral Imaging Sensors for Biodiversity Assessments
Authors: Tait Leigh , Bind Jochen , Charan-Dixon Hannah , Hawes Ian , Pirker John , Schiel David
Published: October 2019

Developments in the capabilities and affordability of unmanned aerial vehicles (UAVs) have led to an explosion in their use for a range of ecological and agricultural remote sensing applications. However, the ubiquity of visible light cameras aboard readily available UAVs may be limiting the application of these devices for fine-scale, high taxonomic resolution monitoring. Here we compare the use of RGB and multispectral cameras deployed aboard UAVs for assessing intertidal and shallow subtidal marine macroalgae to a high taxonomic resolution. Our results show that the diverse spectral profiles of marine macroalgae naturally lend themselves to remote sensing and habitat classification. Furthermore, we show that biodiversity assessments, particularly in shallow subtidal habitats, are enhanced using six-band discrete wavelength multispectral sensors (81% accuracy, Cohen’s Kappa) compared to three-band broad channel RGB sensors (79% accuracy, Cohen’s Kappa) for 10 habitat classes. Combining broad band RGB signals and narrow band multispectral sensing further improved the accuracy of classification with a combined accuracy of 90% (Cohen’s Kappa). Despite notable improvements in accuracy with multispectral imaging, RGB sensors were highly capable of broad habitat classification and rivaled multispectral sensors for classifying intertidal habitats. High spatial scale monitoring of turbid exposed rocky reefs presents a unique set of challenges, but the limitations of more traditional methods can be overcome by targeting ideal conditions with UAVs.
Using Landsat and Sentinel-2 Data for the Generation of Continuously Updated Forest Type Information Layers in a Cross-Border Region
Authors: Nink Sascha , Hill Joachim , Stoffels Johannes , Buddenbaum Henning , Frantz David , Langshausen Joachim
Published: October 2019

From global monitoring to regional forest management there is an increasing demand for information about forest ecosystems. For border regions that are closely connected ecologically and economically, a key factor is the cross-border availability and consistency of up-to-date information such as the forest type. The combination of existing forest information with Earth observation data is a rational method and can provide valuable contribution to serve the increased information demand on a transnational level. We present an approach for the remote sensing-based generation of a transnational and temporally consistent forest type information layer for the German federal states of Rhineland-Palatinate and Saarland, and the Grand Duchy of Luxembourg. Existing forest information data from different countries were merged and combined with suitable vegetation indices derived from Landsat 8 and Sentinel-2 imagery acquired in early spring. An automated bootstrap-based approximation of the optimum threshold for the distinction of “broadleaved” and “coniferous” forest was applied. The spatially explicit forest type information layer is updated annually depending on image availability. Overall accuracies between 79 and 96 percent were obtained. Every spot in the region will be updated successively within a period of expectably three years. The presented approach can be integrated in fully automated processing chains to generate basic forest type information layers on a regular basis.
A New Submersion Detection Sensor Using Two Resistance Temperature Detectors Operating on the Thermal Equilibrium Principle
Authors: Lee Youngjun , Lee Young Sam
Published: October 2019

In this study, a new submersion detection sensor with improved reliability and stability is proposed. The new sensor uses two Resistance Temperature Detectors (RTDs) and operates on the thermal equilibrium principle. The submersion detection sensor controls two RTDs that maintain a constant temperature difference between them in the surrounding environment. The first RTD is used as a reference sensor to measure ambient temperature and the second RTD is supplied with higher current than the reference sensor for self-heating. When submerged, because the thermal conductivity and convective heat transfer coefficient of water are higher than that of air, the temperature difference between the two RTDs is lower in water than in air based on the thermal equilibrium principle. Under these conditions, a submersion detector with a signal conditioning circuit detects these temperature differences. The static performance of the proposed sensor was evaluated by checking whether malfunctions occurred at varying ambient temperatures, differing humidities, and when there was rainfall. In addition, the dynamic performance was evaluated using the response time at varying ambient air temperatures before submersion and with changing water temperatures after submersion, as a metric. The proposed submersion detection sensor is expected to find useful application in aircrafts, ships, and various other industrial fields.
M-Bonacci Zone Plates for Ultrasound Focusing
Authors: Pérez-López Sergio , Fuster José Miguel , Candelas Pilar
Published: October 2019

In this work, we present a thorough analysis on M-bonacci zone plates for ultrasound focusing applications. These planar lenses are capable of providing bifocal focusing profiles with equal intensity in both foci and become very appealing for a wide range of scenarios including medical and industrial applications. We show that in high-wavelength domains, such as acoustics or microwaves, the separation between both foci can be finely adjusted at the expense of slightly increasing the distortion of the focusing profile, and we introduce a design parameter to deal with this issue and simplify the design process of these lenses. Experimental measurements are in good agreement with numerical simulations and demonstrate the potential of M-bonacci lenses in ultrasound focusing applications.
An Adaptive, Discrete Space Oriented Wolf Pack Optimization Algorithm for a Movable Wireless Sensor Network
Authors: Wang Dongxing , Wang Huibo , Ban Xiaojuan , Qian Xu , Ni Jingxiu
Published: October 2019

Recently, many related algorithms have been proposed to find an efficient wireless sensor network with good sustainability, a stable connection, and a high covering rate. To further improve the coverage rate of movable wireless sensor networks under the condition of guaranteed connectivity, this paper proposes an adaptive, discrete space oriented wolf pack optimization algorithm for a movable wireless sensor network (DSO-WPOA). Firstly, a strategy of adaptive expansion based on a minimum overlapping full-coverage model is designed to achieve minimum overlap and no-gap coverage for the monitoring area. Moreover, the adaptive shrinking grid search wolf pack optimization algorithm (ASGS-CWOA) is improved to optimize the movable wireless sensor network, which is a discrete space oriented problem. This improvement includes the usage of a target–node probability matrix and the design of an adaptive step size method, both of which work together to enhance the convergence speed and global optimization ability of the algorithm. Theoretical research and experimental results indicate that compared with the coverage algorithm based on particle swarm optimization (PSO-WSN) and classical virtual force algorithm, the newly proposed algorithm possesses the best coverage rate, better stability, acceptable performance in terms of time, advantages in energy savings, and no gaps.
Double-Drum Test Bench for Variable Load Transfer Simulation by Electromechanical Inertia Compensation
Authors: Xing Zhichao , Wang Guoye , Gong Zhangpeng , Zhang Shudong , Xu Dongxin , Peng Sijie
Published: October 2019

To improve the accuracy and actual road equivalence of vehicle performance testing using test benches, a double-drum test bench that meets the test requirements of vehicle control system prototypes and in-use vehicles was designed. Dynamic models of the single-wheel test bench and the vehicle test bench were established, and mechanisms were theoretically analyzed for single-wheel variable adhesion and vehicle load transfer for equivalent testing using the variable placement angle. The mechanism of electromechanical inertia compensation was studied to realize stepless simulation of vehicle inertia and simulate dynamic load while braking. The simulation model of the vehicle test bench system was established based on MATLAB/Simulink. Simulations were carried out to verify the anti-lock braking system (ABS) performance test functionality of the test bench under high adhesion, bisectional, and low adhesion conditions. Referring to the simulation conditions, ABS tests under actual test bench and road conditions were carried out. Results demonstrated that the mechanism of variable load transfer simulation by electromechanical inertia compensation improves the equivalent accuracy compared to that of its road test equivalent, verifying the feasibility of the simulation mechanism. This study could help further improve the accuracy and reduce the cost of vehicle performance testing, thus greatly benefitting the vehicle development and testing industry.
Arbitrary Microphone Array Optimization Method Based on TDOA for Specific Localization Scenarios
Authors: Liu Haitao , Kirubarajan Thia , Xiao Qian
Published: October 2019

Various microphone array geometries (e.g., linear, circular, square, cubic, spherical, etc.) have been used to improve the positioning accuracy of sound source localization. However, whether these array structures are optimal for various specific localization scenarios is still a subject of debate. This paper addresses a microphone array optimization method for sound source localization based on TDOA (time difference of arrival). The geometric structure of the microphone array is established in parametric form. A triangulation method with TDOA was used to build the spatial sound source location model, which consists of a group of nonlinear multivariate equations. Through reasonable transformation, the nonlinear multivariate equations can be converted to a group of linear equations that can be approximately solved by the weighted least square method. Then, an optimization model based on particle swarm optimization (PSO) algorithm was constructed to optimize the geometric parameters of the microphone array under different localization scenarios combined with the spatial sound source localization model. In the optimization model, a reasonable fitness evaluation function is established which can comprehensively consider the positioning accuracy and robustness of the microphone array. In order to verify the array optimization method, two specific localization scenarios and two array optimization strategies for each localization scenario were constructed. The optimal array structure parameters were obtained through numerical iteration simulation. The localization performance of the optimal array structures obtained by the method proposed in this paper was compared with the optimal structures proposed in the literature as well as with random array structures. The simulation results show that the optimized array structure gave better positioning accuracy and robustness under both specific localization scenarios. The optimization model proposed could solve the problem of array geometric structure design based on TDOA and could achieve the customization of microphone array structures under different specific localization scenarios.
Spatial Aggregation Net: Point Cloud Semantic Segmentation Based on Multi-Directional Convolution
Authors: Cai Guorong , Jiang Zuning , Wang Zongyue , Huang Shangfeng , Chen Kai , Ge Xuyang , Wu Yundong
Published: October 2019

Semantic segmentation of 3D point clouds plays a vital role in autonomous driving, 3D maps, and smart cities, etc. Recent work such as PointSIFT shows that spatial structure information can improve the performance of semantic segmentation. Motivated by this phenomenon, we propose Spatial Aggregation Net (SAN) for point cloud semantic segmentation. SAN is based on multi-directional convolution scheme that utilizes the spatial structure information of point cloud. Firstly, Octant-Search is employed to capture the neighboring points around each sampled point. Secondly, we use multi-directional convolution to extract information from different directions of sampled points. Finally, max-pooling is used to aggregate information from different directions. The experimental results conducted on ScanNet database show that the proposed SAN has comparable results with state-of-the-art algorithms such as PointNet, PointNet++, and PointSIFT, etc. In particular, our method has better performance on flat, small objects, and the edge areas that connect objects. Moreover, our model has good trade-off in segmentation accuracy and time complexity.
Improving the GRACE Kinematic Precise Orbit Determination Through Modified Clock Estimating
Authors: Zhou Xingyu , Jiang Weiping , Chen Hua , Li Zhao , Liu Xuexi
Published: October 2019

Utilizing global positioning system (GPS) to determine the precise kinematic orbits for the twin satellites of the Gravity Recovery and Climate Experiment (GRACE) plays a very important role in the earth’s gravitational and other scientific fields. However, the orbit quality is highly depended on the geometry of observed GPS satellites. In this study, we propose a kinematic orbit determination method for improving the GRACE orbit quality especially when the geometry of observed GPS satellites is weak, where an appropriate random walk clock constraint between adjacent epochs is recommended according to the stability of on-board GPS receiver clocks. GRACE data over one month were adopted in the experimental validation. Results show that the proposed method could improve the root mean square (RMS) by 20–40% in radial component and 5–20% in along and cross components. For those epochs with position dilution of precision (PDOP) larger than 4, the orbits were improved by 50–70% in radial component and 17–50% in along and cross components. Meanwhile, the Allan deviation of clock estimates in the proposed method was much closer to the reported Allan deviation of GRACE on-board oscillator. All the results confirmed the improvement of the proposed method.
INSPEX: Optimize Range Sensors for Environment Perception as a Portable System
Authors: Foucault Julie , Lesecq Suzanne , Dudnik Gabriela , Correvon Marc , O’Keeffe Rosemary , Di Palma Vincenza , Passoni Marco , Quaglia Fabio , Ouvry Laurent , Buckley Steven , Herveg Jean , di Matteo Andrea , Rakotovao Tiana , Debicki Olivier , Mareau Nicolas , Barrett John , Rea Susan , McGibney Alan , Birot François , de Chaumont Hugues , Banach Richard , Razavi Joseph , Ó’Murchú Cian
Published: October 2019

Environment perception is crucial for the safe navigation of vehicles and robots to detect obstacles in their surroundings. It is also of paramount interest for navigation of human beings in reduced visibility conditions. Obstacle avoidance systems typically combine multiple sensing technologies (i.e., LiDAR, radar, ultrasound and visual) to detect various types of obstacles under different lighting and weather conditions, with the drawbacks of a given technology being offset by others. These systems require powerful computational capability to fuse the mass of data, which limits their use to high-end vehicles and robots. INSPEX delivers a low-power, small-size and lightweight environment perception system that is compatible with portable and/or wearable applications. This requires miniaturizing and optimizing existing range sensors of different technologies to meet the user’s requirements in terms of obstacle detection capabilities. These sensors consist of a LiDAR, a time-of-flight sensor, an ultrasound and an ultra-wideband radar with measurement ranges respectively of 10 m, 4 m, 2 m and 10 m. Integration of a data fusion technique is also required to build a model of the user’s surroundings and provide feedback about the localization of harmful obstacles. As primary demonstrator, the INSPEX device will be fixed on a white cane.