bluuebunny/crossref_metadata_2025 huggingface dataset:
Acute Effects of Three Cooked Non-Cereal Starchy Foods on Postprandial Glycemic Responses and in Vitro Carbohydrate Digestion in Comparison with Whole Grains: A Randomized Trial
Authors: Zhu Ruixin , Fan Zhihong , Han Yue , Li Shuang , Li Guojing , Wang Linlin , Ye Ting , Zhao Wenqi
Published: March 2019

Plant origin, processing, and domestic preparation may affect the postprandial glycemic response (PGR) of starchy foods. The objective of this study was to examine the possibility of integrating domestically cooked non-cereal starchy foods commonly consumed in Northeast Asia into glycemic management diet, and compare their glycemic characteristics with those of waxy and non-waxy whole grains and starchy beans. In a randomized crossover trial, ten healthy subjects consumed dried lily bulb (LB), lotus seed (LS), adlay (AD), waxy black rice (BR), millet (MI), and adzuki bean (AB), pre-soaked and each cooked for two time durations. Acute PGR tests and in vitro carbohydrate digestion were carried out for each test food. Both the LS and AB meals achieved low glycemic index (GI 21–51), while the other starchy foods failed to show significant difference with rice (GI 83–109). The hydrolysis indexes of LS and AB were 37.7%–61.1%, significantly lower than other test foods. The in vitro tests indicated that pre-soaking resulted in high rapidly digestible starch (RDS) and low resistant starch (RS). Careful choice of whole grain materials, minimized pre-soaking, and moderate cooking may be critical factors for successful postprandial glycemic management for diabetic and pre-diabetic.
The Effect of Inulin on Lifespan, Related Gene Expression and Gut Microbiota in InRp5545/TM3 Mutant Drosophila melanogaster: A Preliminary Study
Authors: Dong Yuling , Sun Hao , Yang Weichao , Ma Shuang , Du Beibei , Xu Hui
Published: March 2019

Inulin is considered an efficient prebiotic and is beneficial for metabolic diseases via promoting intestinal probiotic enrichment and the metabolites of short-chain fatty acids (SCFAs). However, the effect of inulin on patients with InR deficiencies has seldom been reported. In this study, the lifespan, related gene expression, and gut microbiota of InRp5545/TM3 (insulin receptor mutant) Drosophila melanogaster under inulin treatment were investigated. The results showed that the lifespan was extended in only males and not in females. Furthermore, distinctly different patterns of gene expression were found between males and females, especially in the insulin/insulin-like growth factor (IGF)-like signalling (IIS) and target of rapamycin (TOR) pathways. Additionally, as a link between inulin and lifespan responses, the gut microbiota was distinctly separated by gender in both the standard diet group and the inulin treatment group, and the relationship between lifespan and the gut microbiota community was stronger in male flies than in females. This study provides preliminary evidence for the gender-dependent lifespan responses to inulin in insulin signalling-deficient Drosophila. However, controls such as wild-type and TM3 flies, and more InR mutant strains with different genetic backgrounds need to be further investigated to elucidate the mechanisms underlying the phenomenon.
Key Genes of Lipid Metabolism and WNT-Signaling Are Downregulated in Subcutaneous Adipose Tissue with Moderate Weight Loss
Authors: Schübel Ruth , Sookthai Disorn , Greimel Judith , Johnson Theron S. , Grafetstätter Mirja E. , Kirsten Romy , Kratz Mario , Ulrich Cornelia M. , Kaaks Rudolf , Kühn Tilman
Published: March 2019

Smaller cross-sectional studies and bariatric surgery trials suggest that weight loss may change the expression of genes in adipose tissue that have been implicated in the development of metabolic diseases, but well-powered intervention trials are lacking. In post hoc analyses of data from a 12-week dietary intervention trial initially designed to compare metabolic effects of intermittent vs. continuous calorie restriction, we analyzed the effects of overall weight loss on the subcutaneous adipose tissue (SAT) transcriptome. Changes in the transcriptome were measured by microarray using SAT samples of 138 overweight or obese individuals (age range: 35–65 years, BMI range: 25–40, non-smokers, non-diabetics). Participants were grouped post hoc according to the degree of their weight loss by quartiles (average weight loss in quartiles 1 to 4: 0%, −3.2%, −5.9%, and −10.7%). Candidate genes showing differential expression with weight loss according to microarray analyses were validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR), and fold changes (FCs) were calculated to quantify differences in gene expression. A comparison of individuals in the highest vs. the lowest weight loss quartile revealed 681 genes to be differentially expressed (corrected p < 0.05), with 40 showing FCs of at least 0.4. Out of these, expression changes in secreted frizzled-related protein 2 (SFRP2, FC = 0.65, p = 0.006), stearoyl-CoA desaturase (SCD, FC = −1.00, p < 0.001), and hypoxia inducible lipid droplet-associated (HILPDA, FC = −0.45, p = 0.001) with weight loss were confirmed by RT-qPCR. Dietary weight loss induces significant changes in the expression of genes implicated in lipid metabolism (SCD and HILPDA) and WNT-signaling (SFRP2) in SAT.
Supplementation with Hydroxytyrosol and Punicalagin Improves Early Atherosclerosis Markers Involved in the Asymptomatic Phase of Atherosclerosis in the Adult Population: A Randomized, Placebo-Controlled, Crossover Trial
Authors: Quirós-Fernández Rebeca , López-Plaza Bricia , Bermejo Laura M. , Palma-Milla Samara , Gómez-Candela Carmen
Published: March 2019

Hydroxytyrosol (HT) and Punicalagin (PC) exert cardioprotective and anti-atherosclerotic effects. This study evaluates the effect of oral supplementation with HT and PC (SAx) on early atherosclerosis markers in middle-aged, seemingly healthy adults. A randomized, double-blinded, placebo-controlled, crossover trial was performed for 20 weeks. There were two treatment sequences (Placebo/SAx, n = 41; SAx/Placebo, n = 43) for which the intervention periods (Placebo and SAx) were 8 weeks long, followed by a 4-week wash out period. The supplement was composed of 9.9 mg of HT and 195 mg of PC, and the placebo was composed of maltodextrin. SAx increased endothelial function (Flow-mediated dilatation [FMD]: 2.36%; p < 0.001) in the endothelial dysfunction subgroup compared to the placebo (2.36 ± 3.9 vs. 0.76 ± 3.5%, p < 0.05). SAx also reduced oxLDL by −28.74 ng/mL (p < 0.05) in subjects with higher levels of oxLDL, which was an improvement compared with the placebo (−28.74 ± 40.2 vs. 25.64 ± 93.8 ng/mL, p < 0.001). The prehypertension and hypertension subgroups exhibited decreased systolic (−15.75 ± 9.9 mmHg; p < 0.001) and diastolic (−6.36 ± 8.7 mmHg; p < 0.001) blood pressure after SAx consumption. Moreover, the systolic prehypertension and hypertension subgroups presented significant differences in systolic blood pressure compared to the placebo (−15.75 ± 9.9 vs. −2.67 ± 12.0 mmHg, p < 0.05). In conclusion, the supplement exerted anti-atherosclerotic effects by improving endothelial function, blood pressure, and levels of circulating oxLDL, especially for persons in whom these parameters were altered.
Cyanidin Increases the Expression of Mg2+ Transport Carriers Mediated by the Activation of PPARα in Colonic Epithelial MCE301 Cells
Authors: Takashina Yui , Manabe Aya , Tabuchi Yoshiaki , Ikari Akira
Published: March 2019

Mg2+ deficiency may be involved in lifestyle-related diseases, including hypertension, cardiovascular diseases, and diabetes mellitus. Dietary Mg2+ is absorbed in the intestine mediated through transcellular and paracellular pathways. However, there is little research into what factors upregulate Mg2+ absorption. We searched for food constituents that can increase the expression levels of Mg2+ transport carriers using mouse colonic epithelial MCE301 cells. Cyanidin, an anthocyanidin found in black beans and berries, increased the mRNA levels of Mg2+ transport carriers including transient receptor potential melastatin 6 (TRPM6) channel and cyclin M4 (CNNM4). The cyanidin-induced elevation of Mg2+ transport carriers was blocked by GW6471, a peroxisome proliferator-activated receptor α (PPARα) inhibitor, but not by PPARγ, PPARδ, and protein kinase A inhibitors. Cyanidin-3-glucoside showed similar results to cyanidin. Cyanidin increased the protein levels of TRPM6 and CNNM4, which were distributed in the apical and lateral membranes, respectively. The nuclear localization of PPARα and reporter activities of Mg2+ transport carriers were increased by cyanidin, which were inhibited by GW6471. The cyanidin-induced elevation of reporter activity was suppressed by a mutation in a PPAR-response element. Fluorescence measurements using KMG-20, an Mg2+ indicator, showed that Mg2+ influx and efflux from the cells were enhanced by cyanidin, and which were inhibited by GW6471. Furthermore, cyanidin increased paracellular Mg2+ flux without affecting transepithelial electrical resistance. We suggest that cyanidin increases intestinal Mg2+ absorption mediated by the elevation of TRPM6 and CNNM4 expression, and may constitute a phytochemical that can improve Mg2+ deficiency.
Maternal Fatty Fish Intake Prior to and during Pregnancy and Risks of Adverse Birth Outcomes: Findings from a British Cohort
Authors: Nykjaer Camilla , Higgs Charlotte , Greenwood Darren C. , Simpson Nigel A.B. , Cade Janet E. , Alwan Nisreen A.
Published: March 2019

Fish is an important source of the essential fatty acids contributing to foetal growth and development, but the evidence linking maternal fatty fish consumption with birth outcomes is inconsistent. In the UK, pregnant women are recommended to consume no more than two 140 g portions of fatty fish per week. This study aimed to investigate the association between fatty fish consumption before and during pregnancy with preterm birth and size at birth in a prospective birth cohort. Dietary intake data were acquired from a cohort of 1208 pregnant women in Leeds, UK (CARE Study) to assess preconception and trimester-specific fatty fish consumption using questionnaires. Multiple 24-h recalls during pregnancy were used to estimate an average fatty fish portion size. Intake was classified as ≤2, >2 portions/week and no fish categories. Following the exclusion of women taking cod liver oil and/or omega-3 supplements, the associations between fatty fish intake with size at birth and preterm delivery (<37 weeks gestation) were examined in multivariable regression models adjusting for confounders including salivary cotinine as a biomarker of smoking status.. The proportion of women reporting any fatty fish intake decreased throughout pregnancy, with the lowest proportion observed in trimester 3 (43%). Mean intakes amongst consumers were considerably lower than that recommended, with the lowest intake amongst consumers observed in the 1st trimester (106 g/week, 95% CI: 99, 113). This was partly due to small portion sizes when consumed, with the mean portion size of fatty fish being 101 g. After adjusting for confounders, no association was observed between fatty fish intake before or during pregnancy with size at birth and preterm delivery.
Non-Nutritive Sweeteners and Their Implications on the Development of Metabolic Syndrome
Authors: Liauchonak Iryna , Qorri Bessi , Dawoud Fady , Riat Yatin , Szewczuk Myron R.
Published: March 2019

Individuals widely use non-nutritive sweeteners (NNS) in attempts to lower their overall daily caloric intake, lose weight, and sustain a healthy diet. There are insufficient scientific data that support the safety of consuming NNS. However, recent studies have suggested that NNS consumption can induce gut microbiota dysbiosis and promote glucose intolerance in healthy individuals that may result in the development of type 2 diabetes mellitus (T2DM). This sequence of events may result in changes in the gut microbiota composition through microRNA (miRNA)-mediated changes. The mechanism(s) by which miRNAs alter gene expression of different bacterial species provides a link between the consumption of NNS and the development of metabolic changes. Another potential mechanism that connects NNS to metabolic changes is the molecular crosstalk between the insulin receptor (IR) and G protein-coupled receptors (GPCRs). Here, we aim to highlight the role of NNS in obesity and discuss IR-GPCR crosstalk and miRNA-mediated changes, in the manipulation of the gut microbiota composition and T2DM pathogenesis.
Mediterranean Diet and Cardiodiabesity: A Systematic Review through Evidence-Based Answers to Key Clinical Questions
Authors: Franquesa Marcella , Pujol-Busquets Georgina , García-Fernández Elena , Rico Laura , Shamirian-Pulido Laia , Aguilar-Martínez Alicia , Medina Francesc Xavier , Serra-Majem Lluís , Bach-Faig Anna
Published: March 2019

The Mediterranean Diet (MedDiet) has been promoted as a means of preventing and treating cardiodiabesity. The aim of this study was to answer a number of key clinical questions (CQs) about the role of the MedDiet in cardiodiabesity in order to provide a framework for the development of clinical practice guidelines. A systematic review was conducted to answer five CQs formulated using the Patient, Intervention, Comparison, and Outcome (PICO) criteria. Twenty articles published between September 2013 and July 2016 were included, adding to the 37 articles from the previous review. There is a high level of evidence showing that MedDiet adherence plays a role in the primary and secondary prevention of cardiovascular disease (CVD) and improves health in overweight and obese patients. There is moderate-to-high evidence that the MedDiet prevents increases in weight and waist circumference in non-obese individuals, and improves metabolic syndrome (MetS) and reduces its incidence. Finally, there is moderate evidence that the MedDiet plays primary and secondary roles in the prevention of type 2 diabetes mellitus (T2DM). The MedDiet is effective in preventing obesity and MetS in healthy and at-risk individuals, in reducing mortality risk in overweight or obese individuals, in decreasing the incidence of T2DM and CVD in healthy individuals, and in reducing symptom severity in individuals with T2DM or CVD.
Bentonite Modified by Allylamine Polymer for Adsorption of Amido Black 10B
Authors: Guo Wenjuan , Xia Tingcheng , Pei Meishan , Du Yankai , Wang Luyan
Published: March 2019

The main object of this work is to remove Amido black 10B using a new type of bentonite-based adsorbent with cationic groups by the modification of polyallyl amines between the interlayers of bentonite. Fourier transform infrared, X-ray diffraction, thermogravimetric analysis, and scanning electron microscopy were used to characterize the functionalized bentonite. A series of batch adsorption experiments were performed. The maximum adsorption amount was 144.08 mg g−1 when the pH was 2 and the contact time was 120 min. In addition, the equilibrium isotherm data were analyzed using Langmuir and Freundlich isotherm models, while only the Langmuir model could provide a high correlation. Therefore, this study provided a new functionalized bentonite as a low-cost adsorbent for dye removal from water.
In-Situ Polymerization of High-Molecular Weight Nylon 66 Modified Clay Nanocomposites with Low Apparent Viscosity
Authors: Duan Xiaochao , Wu Yanpeng , Chen Zhao , Yang Tonghui , Cheng Yongchang , Yu Hao , Huang Tao
Published: March 2019

High-molecular weight nylon 66/modified clay (Mclay) nanocomposites with a low apparent viscosity were prepared by in-situ polymerization and post solid-state polycondensation. Thermogravimetric analysis and X-ray diffraction patterns of the Mclay revealed that cetyltrimethyl ammonium bromide successfully inserted into the interlayers of the clay. Scanning electron microscope images of the cross sections showed that the Mclay was well-dispersed in the nylon 66 matrix. The effects of clay on the mechanical, rheological, and thermal properties of the nanocomposites were investigated using an Instron 5969 machine, a capillary rheometer, and a differential scanning calorimeter. The results indicated that the incorporation of a very small amount of Mclay considerably decreased the shear viscosity of the nanocomposites and increased the melt index, acting as a viscosity reducer. More importantly, the mechanical properties and spinnability of the nylon 66/Mclay nanocomposites were not affected by the viscosity reducer.
Ashura in Italy: The Reshaping of Shi’a Rituals
Authors: Mirshahvalad Minoo
Published: March 2019

This essay explores the impacts of Italy’s socio-religious tendencies on the Shi’a rituals of Muḥarram and Ṣafar. Ethnography and semi-structured interviews were the main methods adopted for the performance of this research. The implications of commemorating the Karbala tragedy in Italy were studied from four viewpoints. This article demonstrates that the presence of Shi’as in Italy not only exerts an effect on the core meaning of these rituals, namely paying tribute to Ḥusayn’s courageous stand against injustice, but also on the structure of Shi’a communities in terms of gender relations and power hierarchy.
Life-Cycle Assessment of Adsorbents for Biohydrogen Production
Authors: Seo Yuna , Suzuki Masaya , Takagi Tetsuichi , Dowaki Kiyoshi
Published: March 2019

Adsorbents are used to remove impurities such as carbon monoxide, carbon dioxide, methane, and hydrogen sulfide in the pressure swing adsorption process of biohydrogen production. These impurities are present in the produced gas along with hydrogen and often cause voltage reduction in fuel cells and shorten the lifespan of catalysts. Zeolite A is a typical adsorbent, and more recently, hydroxyl aluminum silicate clay (Has-Clay) and Kanuma clay have been suggested as alternatives. We conducted a life-cycle assessment (LCA) of zeolite A, Has-Clay, and Kanuma clay, and evaluated their environmental impact based on the ReCiPe midpoint method. Kanuma clay had the least impact in all of the environmental categories. The largest contributions for zeolite A and Has-Clay were in the categories of climate change and fossil depletion. In the climate change category, production of 1 kg of Has-Clay and zeolite A was estimated to emit 17.142 kg CO2 eq and 2.352 kg CO2 eq, respectively. In the fossil depletion category, the values were estimated to be 3.999 kg oil eq and 1.039 kg oil eq, respectively. These LCA results will be useful in designing and using adsorbents in pressure swing adsorption processes to meet environmental challenges associated with sustainable biohydrogen production.
Major Orientation Estimation-Based Rock Surface Extraction for 3D Rock-Mass Point Clouds
Authors: Liu Lupeng , Xiao Jun , Wang Ying
Published: March 2019

In the fields of 3D modeling, analysis of discontinuities and engineering calculation, surface extraction is of great importance. The rapid development of photogrammetry and Light Detection and Ranging (LiDAR) technology facilitates the study of surface extraction. Automatic extraction of rock surfaces from 3D rock-mass point clouds also becomes the basis of 3D modeling and engineering calculation of rock mass. This paper presents an automated and effective method for extracting rock surfaces from unorganized rock-mass point clouds. This method consists of three stages: (i) clustering based on voxels; (ii) estimating major orientations based on Gaussian Kernel and (iii) rock surface extraction. Firstly, the two-level spatial grid is used for fast voxelization and segmenting the point cloud into three types of voxels, including coplanar, non-coplanar and sparse voxels. Secondly, the coplanar voxels, rather than the scattered points, are employed to estimate major orientations by using a bivariate Gaussian Kernel. Finally, the seed voxels are selected on the basis of major orientations and the region growing method based on voxels is applied to extract rock surfaces, resulting in sets of surface clusters. The sub-surfaces of each cluster are coplanar or parallel. In this paper, artificial icosahedron point cloud and natural rock-mass point clouds are used for testing the proposed method, respectively. The experimental results show that, the proposed method can effectively and accurately extract rock surfaces in unorganized rock-mass point clouds.
Geographically Weighted Regression Effects on Soil Zinc Content Hyperspectral Modeling by Applying the Fractional-Order Differential
Authors: Lin Xue , Su Yung-Chih , Shang Jiali , Sha Jinming , Li Xiaomei , Sun Yang-Yi , Ji Jianwan , Jin Biao
Published: March 2019

With the development of remote sensing techniques and the increasing need for soil contamination monitoring, we estimated soil heavy metal zinc (Zn) content using hyperspectral imaging. Geographically weighted regression (GWR), an extension of the ordinary least squares (OLS) regression framework, was proposed. By estimating a set of parameters for any number of locations in a study area, GWR can probe the spatial heterogeneity in data relationships, whereas the regression parameters of an OLS model are global and aspatially-varied. The objectives of this study were: (1) To find the possible relationships between hyperspectral data and soil Zn content, and (2) to investigate the existence of their spatial heterogeneity. In this study, 67 soil samples collected from Pingtan Island, Fujian Province, China, were used to conduct laboratory hyperspectral modeling for soil Zn content estimation. Four transformations of square root, logarithm, reciprocal of logarithm, and reciprocal, as well as the fractional-order differential operations were applied to increase the amount of reflectance data in which the effective variables for modeling might be involved, and to enhance the spectral characteristics of soil Zn content. To find sensitive variables and to remove redundancy and multicollinearity in the spectra, a data sifting process was applied by selecting wavelengths with local maximum in the absolute values of the correlation coefficients with Zn content in one type of spectral data and by employing Variance Inflation Factors. Since a modeling sample size of 46 is insufficient to construct the appropriate OLS and GWR models, four methods are proposed using all 67 samples to choose explanatory variables. A random process to select 57 samples for modeling and 10 samples for validation was applied to assess model performance, in which the mean verification R2 (Rv2) was used as an indicator. The results show that GWR stepwise regression is the most effective method to select better variables. As the mean Rv2 converges toward the OLS value when the bandwidth of the GWR model increases, the four variables selected by the GWR stepwise regression were used to establish the representative OLS and GWR models. The representative OLS model has the best mean verification effect among all studied models, which had a mean Rv2 value that is 44.6% higher than the OLS model constructed using OLS stepwise regression.
Developing an Advanced PM2.5 Exposure Model in Lima, Peru
Authors: Vu Bryan N. , Sánchez Odón , Bi Jianzhao , Xiao Qingyang , Hansel Nadia N. , Checkley William , Gonzales Gustavo F. , Steenland Kyle , Liu Yang
Published: March 2019

It is well recognized that exposure to fine particulate matter (PM2.5) affects health adversely, yet few studies from South America have documented such associations due to the sparsity of PM2.5 measurements. Lima’s topography and aging vehicular fleet results in severe air pollution with limited amounts of monitors to effectively quantify PM2.5 levels for epidemiologic studies. We developed an advanced machine learning model to estimate daily PM2.5 concentrations at a 1 km2 spatial resolution in Lima, Peru from 2010 to 2016. We combined aerosol optical depth (AOD), meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF), parameters from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and land use variables to fit a random forest model against ground measurements from 16 monitoring stations. Overall cross-validation R2 (and root mean square prediction error, RMSE) for the random forest model was 0.70 (5.97 μg/m3). Mean PM2.5 for ground measurements was 24.7 μg/m3 while mean estimated PM2.5 was 24.9 μg/m3 in the cross-validation dataset. The mean difference between ground and predicted measurements was −0.09 μg/m3 (Std.Dev. = 5.97 μg/m3), with 94.5% of observations falling within 2 standard deviations of the difference indicating good agreement between ground measurements and predicted estimates. Surface downwards solar radiation, temperature, relative humidity, and AOD were the most important predictors, while percent urbanization, albedo, and cloud fraction were the least important predictors. Comparison of monthly mean measurements between ground and predicted PM2.5 shows good precision and accuracy from our model. Furthermore, mean annual maps of PM2.5 show consistent lower concentrations in the coast and higher concentrations in the mountains, resulting from prevailing coastal winds blown from the Pacific Ocean in the west. Our model allows for construction of long-term historical daily PM2.5 measurements at 1 km2 spatial resolution to support future epidemiological studies.
A Mapping Framework to Characterize Land Use in the Sudan-Sahel Region from Dense Stacks of Landsat Data
Authors: Sedano Fernando , Molini Vasco , Azad M. Abul Kalam
Published: March 2019

We developed a land cover and land use mapping framework specifically designed for agricultural systems of the Sudan-Sahel region. The mapping approach extracts information from inter- and intra-annual vegetation dynamics from dense stacks of Landsat 8 images. We applied this framework to create a 30 m spatial resolution land use map with a focus on agricultural landscapes of northern Nigeria for 2015. This map provides up-to-date information with a higher level of spatial and thematic detail resulting in a more precise characterization of agriculture in the region. The map reveals that agriculture is the main land use in the region. Arable land represents on average 52.5% of the area, higher than the reported national average for Nigeria (38.4%). Irrigated agriculture covers nearly 2.2% of the total area, reaching nearly 20% of the cultivated land when traditional floodplain agriculture systems are included, above the reported national average (0.63%). There is significant variability in land use within the region. Cultivated land in the northern section can reach values higher than 75%, most land suitable for agriculture is already under cultivation and there is limited land for future agricultural expansion. Marginal lands, not suitable for permanent agriculture, can reach 30% of the land at lower altitudes in the northeast and northwest. In contrast, the southern section presents lower land use intensity that results in a complex landscape that intertwines areas farms and larger patches of natural vegetation. This map improves the spatial detail of existing sources of LCLU information for the region and provides updated information of the current status of its agricultural landscapes. This study demonstrates the feasibility of multi temporal medium resolution remote sensing data to provide detailed and up-to-date information about agricultural systems in arid and sub arid landscapes of the Sahel region.
A Novel Tri-Training Technique for the Semi-Supervised Classification of Hyperspectral Images Based on Regularized Local Discriminant Embedding Feature Extraction
Authors: Ou Depin , Tan Kun , Du Qian , Zhu Jishuai , Wang Xue , Chen Yu
Published: March 2019

This paper introduces a novel semi-supervised tri-training classification algorithm based on regularized local discriminant embedding (RLDE) for hyperspectral imagery. In this algorithm, the RLDE method is used for optimal feature information extraction, to solve the problems of singular values and over-fitting, which are the main problems in the local discriminant embedding (LDE) and local Fisher discriminant analysis (LFDA) methods. An active learning method is then used to select the most useful and informative samples from the candidate set. In the experiments undertaken in this study, the three base classifiers were multinomial logistic regression (MLR), k-nearest neighbor (KNN), and random forest (RF). To confirm the effectiveness of the proposed RLDE method, experiments were conducted on two real hyperspectral datasets (Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Reflective Optics System Imaging Spectrometer (ROSIS)), and the proposed RLDE tri-training algorithm was compared with its counterparts of tri-training alone, LDE, and LFDA. The experiments confirmed that the proposed approach can effectively improve the classification accuracy for hyperspectral imagery.
Support Vector Machine Accuracy Assessment for Extracting Green Urban Areas in Towns
Authors: Kranjčić Nikola , Medak Damir , Župan Robert , Rezo Milan
Published: March 2019

The most commonly used model for analyzing satellite imagery is the Support Vector Machine (SVM). Since there are a large number of possible variables for use in SVM, this paper will provide a combination of parameters that fit best for extracting green urban areas from Copernicus mission satellite images. This paper aims to provide a combination of parameters to extract green urban areas with the highest degree of accuracy, in order to speed up urban planning and ultimately improve town environments. Two different towns in Croatia were investigated, and the results provide an optimal combination of parameters for green urban areas extraction with an overall kappa index of 0.87 and 0.89, which demonstrates a very high classification accuracy.
Design and Evaluation of a Surface Electromyography-Controlled Steering Assistance Interface
Authors: Nacpil Edric John Cruz , Wang Zheng , Zheng Rencheng , Kaizuka Tsutomu , Nakano Kimihiko
Published: March 2019

Millions of drivers could experience shoulder muscle overload when rapidly rotating steering wheels and reduced steering ability at increased steering wheel angles. In order to address these issues for drivers with disability, surface electromyography (sEMG) sensors measuring biceps brachii muscle activity were incorporated into a steering assistance system for remote steering wheel rotation. The path-following accuracy of the sEMG interface with respect to a game steering wheel was evaluated through driving simulator trials. Human participants executed U-turns with differing radii of curvature. For a radius of curvature equal to the minimum vehicle turning radius of 3.6 m, the sEMG interface had significantly greater accuracy than the game steering wheel, with intertrial median lateral errors of 0.5 m and 1.2 m, respectively. For a U-turn with a radius of 7.2 m, the sEMG interface and game steering wheel were comparable in accuracy, with respective intertrial median lateral errors of 1.6 m and 1.4 m. The findings of this study could be utilized to realize accurate sEMG-controlled automobile steering for persons with disability.
Online Monitoring and Prediction of Thermo-Mechanics of AFP Based Thermoplastic Composites
Authors: Oromiehie Ebrahim , Chakladar Nilanjan Das , Rajan Ginu , Prusty B. Gangadhara
Published: March 2019

Precision sensing in the characterization of complex additive manufacturing processes such as the Automated Fibre Placement (AFP) technique is important since the process involves a significant level of uncertainty in terms of quality and integrity of the manufactured product. These uncertainties can be monitored by embedding optical fibre Bragg grating (FBGs) sensors which provide accurate and simultaneous measurement of strain and temperature during the AFP process. The embedded sensors have been shown to remain resilient in continuous health monitoring after manufacturing. The thermal history obtained from the FBG sensors demonstrates a reduction of temperature on the bottom ply by up to 25% when the plies are laid one above the other. A numerical tool is developed to identify the physical parameters which may be responsible for the rise/fall of the temperature during ply layup. The numerical findings agree well with the sensor data and is extended to capture a breadth of parametric studies through the layup simulation. The model provides a comprehensive insight to the characteristics of the laid and the laying ply from a thermo-mechanics perspective.
A Novel Multiband Spectrum Sensing Method Based on Wavelets and the Higuchi Fractal Dimension
Authors: Molina-Tenorio Yanqueleth , Prieto-Guerrero Alfonso , Aguilar-Gonzalez Rafael
Published: March 2019

In this work, two novel methodologies for the multiband spectrum sensing in cognitive radios are implemented. Methods are based on the continuous wavelet transform (CWT) and the multiresolution analysis (MRA) to detect the edges of available holes in the considered wideband spectrum. Besides, MRA is also combined with the Higuchi fractal dimension (a non-linear measure) to establish the decision rule permitting the detection of the absence or presence of one or multiple primary users in the studied wideband spectrum. Methods were tested on simulated and real signals showing a good performance. The results present these two methods as effective options for detecting primary user activity on the multiband spectrum. The first methodology works for 95% of cases, while the second one presents 98% of effectivity under simulated signals of signal-to-noise ratios (SNR) higher than 0 dB.
Implementation and Validation of a Two-Stage Energy Extraction Circuit for a Self Sustained Asset-Tracking System
Authors: Dorsch Philipp , Bartsch Toni , Hubert Florian , Milosiu Heinrich , Rupitsch Stefan J.
Published: March 2019

We present a two-stage energy extraction circuit for a piezoelectric energy harvester, powering an asset-tracking system. Exploiting accelerations generated by many logistic transport devices, e.g., pushcarts, forklifts, assembly belts or cars, we are able to harvest sufficient electrical energy to transmit radio signals, which will allow to track an object when it is moving. Accelerations in logistic applications are non-sinusoidal and lead to high open-circuit voltages, which demand a special adaption of the energy extraction network. We evaluate the performance of several state-of-the-art energy extraction networks and compare those to the performance of our two-stage approach under various excitation conditions. By using the proposed energy extraction circuit, the transmission rate could be increased from four to six transmissions per second for sinusoidal excitations with an open-circuit-voltage of 60 V . In the practical use-case, the two-stage energy extraction network performs more than two times better compared to the one-stage and synchronized switching harvesting with inductor approach.
A Deep Neural Network Based Model for a Kind of Magnetorheological Dampers
Authors: Duchanoy Carlos A. , Moreno-Armendáriz Marco A. , Moreno-Torres Juan C. , Cruz-Villar Carlos A.
Published: March 2019

In this paper, a deep neural network based model for a set of small-scale magnetorheological dampers (MRD) is developed where relevant parameters that have a physical meaning are inputs to the model. An experimental platform and a 3D-printing rapid prototyping facility provided a set of different conditions including MRD filled with two different MR fluids, which were used to train a Deep Neural Network (DNN), which is the core of the proposed model. Testing results indicate the model could forecast the hysteretic response of magnetorheological dampers for different load conditions and various physical configurations.
A Hybrid System for Distinguishing between Brain Death and Coma Using Diverse EEG Features
Authors: Zhu Li , Cui Gaochao , Cao Jianting , Cichocki Andrzej , Zhang Jianhai , Zhou Changle
Published: March 2019

Electroencephalography (EEG) signals may provide abundant information reflecting the developmental changes in brain status. It usually takes a long time to finally judge whether a brain is dead, so an effective pre-test of brain states method is needed. In this paper, we present a hybrid processing pipeline to differentiate brain death and coma patients based on canonical correlation analysis (CCA) of power spectral density, complexity features, and feature fusion for group analysis. In addition, time-varying power spectrum and complexity were observed based on the analysis of individual patients, which can be used to monitor the change of brain status over time. Results showed three major differences between brain death and coma groups of EEG signal: slowing, increased complexity, and the improvement on classification accuracy with feature fusion. To the best of our knowledge, this is the first scheme for joint general analysis and time-varying state monitoring. Delta-band relative power spectrum density and permutation entropy could effectively be regarded as potential features of discrimination analysis on brain death and coma patients.
Smart Camera Aware Crowd Counting via Multiple Task Fractional Stride Deep Learning
Authors: Tong Minglei , Fan Lyuyuan , Nan Hao , Zhao Yan
Published: March 2019

Estimating the number of people in highly clustered crowd scenes is an extremely challenging task on account of serious occlusion and non-uniformity distribution in one crowd image. Traditional works on crowd counting take advantage of different CNN like networks to regress crowd density map, and further predict the count. In contrast, we investigate a simple but valid deep learning model that concentrates on accurately predicting the density map and simultaneously training a density level classifier to relax parameters of the network to prevent dangerous stampede with a smart camera. First, a combination of atrous and fractional stride convolutional neural network (CAFN) is proposed to deliver larger receptive fields and reduce the loss of details during down-sampling by using dilated kernels. Second, the expanded architecture is offered to not only precisely regress the density map, but also classify the density level of the crowd in the meantime (MTCAFN, multiple tasks CAFN for both regression and classification). Third, experimental results demonstrated on four datasets (Shanghai Tech A (MAE = 88.1) and B (MAE = 18.8), WorldExpo’10(average MAE = 8.2), NS UCF_CC_50(MAE = 303.2) prove our proposed method can deliver effective performance.
Optimization and Technical Validation of the AIDE-MOI Fall Detection Algorithm in a Real-Life Setting with Older Adults
Authors: Scheurer Simon , Koch Janina , Kucera Martin , Bryn Hȧkon , Bärtschi Marcel , Meerstetter Tobias , Nef Tobias , Urwyler Prabitha
Published: March 2019

Falls are the primary contributors of accidents in elderly people. An important factor of fall severity is the amount of time that people lie on the ground. To minimize consequences through a short reaction time, the motion sensor “AIDE-MOI” was developed. “AIDE-MOI” senses acceleration data and analyzes if an event is a fall. The threshold-based fall detection algorithm was developed using motion data of young subjects collected in a lab setup. The aim of this study was to improve and validate the existing fall detection algorithm. In the two-phase study, twenty subjects (age 86.25 ± 6.66 years) with a high risk of fall (Morse > 65 points) were recruited to record motion data in real-time using the AIDE-MOI sensor. The data collected in the first phase (59 days) was used to optimize the existing algorithm. The optimized second-generation algorithm was evaluated in a second phase (66 days). The data collected in the two phases, which recorded 31 real falls, was split-up into one-minute chunks for labelling as “fall” or “non-fall”. The sensitivity and specificity of the threshold-based algorithm improved significantly from 27.3% to 80.0% and 99.9957% (0.43) to 99.9978% (0.17 false alarms per week and subject), respectively.
A Patch/Dipole Hybrid-Mode Antenna for Sub-6GHz Communication
Authors: Huang Bei , Lin Weifeng , Huang Jialu , Zhang Jun , Zhang Gary , Wu Fugen
Published: March 2019

A low-profile antenna with a high gain and broad bandwidth is proposed for Sub-6GHz communication in this paper. A narrow-band patch mode and a narrow-band dipole mode are shared in one radiator and simultaneously excited to broaden the bandwidth. A compact prototype with a projection size of 0.90 λ0 × 0.78 λ0 and a profile of 0.13 λ0 (λ0 is the wavelength in the free space at the center of the operating frequency) is fabricated and measured. The measurement demonstrates an impedance bandwidth of 67.50%, covering the frequency range from 2.75 GHz to 5.45 GHz and an average gain of 8.4 dBi in the operating band of 3.0–5.0 GHz.
Precision Medicine and Exercise Therapy in Duchenne Muscular Dystrophy
Authors: Kostek Matthew
Published: March 2019

Precision medicine is being discussed and incorporated at all levels of health care and disease prevention, management, and treatment. Key components include new taxonomies of disease classification, the measurement and incorporation of genetics and “omics” data, biomarkers, and health care professionals who can optimize this information for a precision approach to treatment. The study and treatment of Duchenne Muscular Dystrophy is making rapid advances in these areas in addition to rapid advances in new gene and cell-based therapies. New therapies will increase the variability in disease severity, furthering a need for a precision-based approach. An area of therapy that is rarely considered in this approach is how the physiology of muscle contractions will interact with these therapies and a precision approach. As muscle pathology improves, physical activity levels will increase, which will likely be very beneficial to some patients but likely not to all. Physical activity is likely to synergistically improve these therapies and can be used to enhance muscle health and quality of life after these therapies are delivered using the tools of precision medicine.
Effect of New Zealand Blackcurrant Extract on Cycling Performance and Substrate Oxidation in Normobaric Hypoxia in Trained Cyclists
Authors: Willems Mark , Şahin Mehmet , Berendsen Tim , Cook Matthew
Published: March 2019

New Zealand blackcurrant (NZBC) extract enhanced exercise-induced fat oxidation and 16.1 km cycling time trial (TT) in normobaric normoxia. The effect of NZBC extract on physiological and metabolic responses was examined during steady state cycling and a 16.1 km TT in normobaric hypoxia. This study used a randomized, double-blind, crossover design. Eleven healthy male cyclists (age: 38 ± 11 y, height: 179 ± 4 cm, body mass: 76 ± 8 kg, V ˙ O2max: 47 ± 5 mL·kg−1·min−1, mean ± SD) ingested NZBC extract (600 mg·day−1 CurraNZ® containing 210 mg anthocyanins) or a placebo (600 mg microcrystalline cellulose M102) for seven days (washout 14 days) and performed a steady state cycling test (3 × 10 min at 45%, 55% and 65% V ˙ O2max) followed by a 16.1 km TT at a simulated altitude of ~2500 meters (~15% of O2). Indirect calorimetry was used to measure substrate oxidation during steady state cycling. Intake of NZBC extract had no effect on blood glucose and lactate, heart rate, substrate oxidation, and respiratory exchange ratio during steady state cycling at 45%, 55% and 65% V ˙ O2max, and on 16.1 km TT performance (placebo: 1685 ± 92 s, NZBC extract: 1685 ± 99 s, P = 0.97). Seven days intake of New Zealand blackcurrant extract does not change exercise-induced metabolic responses and 16.1 km cycling time trial performance for moderately endurance-trained men in normobaric hypoxia.
Effects of Low-Moderate Load High-Velocity Resistance Training on Physical Performance of Under-20 Futsal Players
Authors: Marques Diogo Luís , Travassos Bruno , Sousa António Carlos , Gil Maria Helena , Ribeiro João Nuno , Marques Mário Cardoso
Published: March 2019

Resistance training (RT) is an effective methodology to improve physical performance of athletes. However, up to now, no studies have addressed the RT benefits in under-20 futsal players. The purpose of this study was to evaluate the effects of six weeks of RT with high-velocity movements, low-to-moderate loads, and low volume on physical performance of under-20 futsal players. A total of 21 players were divided into two groups: A control group (CG, n = 10) and a RT group (RTG, n = 11). The RTG performed two weekly training sessions constituted by leg-press, jumps, and sprints, along with three futsal training sessions, while the CG only performed the futsal training. Before and after the intervention, the sprint time in 0–10 m (T10), 10–20 m (T10–20), and 0–20 m (T20), the countermovement jump (CMJ) height, the T-Test time, the kicking ball speed (KBS), and the maximum dynamic strength in the leg-press, were assessed. In post-test, significant improvements in CMJ, T-Test, KBS, and leg-press were found for the RTG, whilst a significant decrease in T10–20 was evidenced in the CG. The present results suggested that RT based on high velocity movements, low-to-moderate loads, and low volume produce positive effects on physical performance of under-20 futsal players.
Research Topics in Accounting Fraud in the 21st Century: A State of the Art
Authors: Ramos Montesdeoca Monica , Sánchez Medina Agustín J. , Blázquez Santana Felix
Published: March 2019

Companies play a role in society that clearly goes beyond mere economic interest. Their contribution to social development and to the sustainability of the territory where they are located seems unquestionable. However, after the great financial scandals of companies such as ENRON, WorldCom or AHOLD, interest groups require accurate and transparent financial information. The development of more demanding financial reporting standards seems, however, not to have been up to scratch, since accounting fraud continues to be detected all over the world. The search, therefore, for possible causes that may induce companies to act unethically was the main motivation behind this research. To do this, a review of the literature in high-impact journals that has dealt with accounting fraud, covering the main lines of research, was carried out. The findings of the literature review highlight the importance of responsible corporate governance and good accounting practices, as well as the importance of certain psychological characteristics of managers and employees as enhancers of the lack of ethics. It is clear that the social cost of accounting fraud should be minimized, and governments should develop specific policies that combine responsible corporate governance in companies with the sustainability of their environment.
“Everybody I Know Is Always Hungry…But Nobody Asks Why”: University Students, Food Insecurity and Mental Health
Authors: Hattangadi Nayantara , Vogel Ellen , Carroll Linda J , Côté Pierre
Published: March 2019

Food insecurity is a substantial problem in Canadian university students. Multiple cross-sectional studies suggest that nearly a third of university students across Canada report food insecurity. Yet, little is understood about the experiences of food-insecure students and the impact of their experiences on their mental health. To address this, a multi-method study was conducted using quantitative and qualitative approaches to describe the prevalence, association and experience of food insecurity and mental health in undergraduate students. The current paper reports on the qualitative component, which described the lived experiences of food-insecure students, captured through face-to-face focus group interviews with participants (n = 6). The themes included (1) contributing factors to food insecurity; (2) consequences of food insecurity; and (3) students’ responses/attempts to cope with food insecurity. The findings illuminated student voices, added depth to quantitative results, and made the experience of food insecurity more visible at the undergraduate level. Additional research is needed to understand students’ diverse experiences across the university community and to inform programs to support students.