bluuebunny/crossref_metadata_2025 huggingface dataset:
Starchy Carbohydrates in a Healthy Diet: The Role of the Humble Potato
Authors: Robertson Tracey M. , Alzaabi Abdulrahman Z. , Robertson M. Denise , Fielding Barbara A.
Published: November 2018

Potatoes have been an affordable, staple part of the diet for many hundreds of years. Recently however, there has been a decline in consumption, perhaps influenced by erroneous reports of being an unhealthy food. This review provides an overview of the nutritional value of potatoes and examines the evidence for associations between potato consumption and non-communicable diseases. Potatoes are an important source of micronutrients, such as vitamin C, vitamin B6, potassium, folate, and iron and contribute a significant amount of fibre to the diet. However, nutrient content is affected by cooking method; boiling causes leaching of water-soluble nutrients, whereas frying can increase the resistant starch content of the cooked potato. Epidemiological studies have reported associations between potato intake and obesity, type 2 diabetes and cardiovascular disease. However, results are contradictory and confounded by lack of detail on cooking methods. Indeed, potatoes have been reported to be more satiating than other starchy carbohydrates, such as pasta and rice, which may aid weight maintenance. Future research should consider cooking methods in the study design in order to reduce confounding factors and further explore the health impact of this food.
The Primary Tumor and Regional Lymph Node Clinical Status of Distant Metastasis in Nasopharyngeal Carcinoma
Authors: Indrasari Sagung Rai , Sudarman Kartono , Fedriani Jessica
Published: November 2018

Background: Nasopharyngeal carcinoma (NPC) is a squamous cell carcinoma derived from nasopharyngeal epithelium. NPC characteristic is highly invasive and can metastasize rapidly. The presence of distant metastasis is a major factor in determining the patient’s management and prognosis. The magnitude of radiologic and molecular costs encouraging the need to know the clinical variables associated with distant metastasis of NPC. Methods: Cross-sectional analytical retrospective studies of undifferentiated NPC (WHO type III) patients at initial diagnosis in the ORL-HNS Department of Dr. Sardjito Hospital Yogyakarta from January 2014 to December 2016. Results: At 276 NPC patients with the ratio of 197 men (71.4%) and 79 women (28.6%) was 2.5:1, mean age 48.5 years, distant metastasis was found in 37 patients (13.4%). There was no significant difference in the frequency of sex (p = 0.346), age (p = 0.784), and primary tumor clinical status (p = 0.297) between NPC with distant metastasis and without distant metastasis. There was significant difference in the frequency of regional lymph node clinical status between NPC with distant metastasis and without distant metastasis (p = 0.004; PR = 3.866). Conclusions: There is no statistically significant difference of primary tumor clinical status between NPC with and without distant metastasis. There is statistically significant difference of lymph node clinical status between NPC with and without distant metastasis.
Hsp90 Interacts with the Bacterial Effector NleH1
Authors: Wu Miaomiao , Hardwidge Philip
Published: November 2018

Enterohemorrhagic Escherichia coli (EHEC) utilizes a type III secretion system (T3SS) to inject effector proteins into host cells. The EHEC NleH1 effector inhibits the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway by reducing the nuclear translocation of the ribosomal protein S3 (RPS3). NleH1 prevents RPS3 phosphorylation by the IκB kinase-β (IKKβ). IKKβ is a central kinase in the NF-κB pathway, yet NleH1 only restricts the phosphorylation of a subset of the IKKβ substrates. We hypothesized that a protein cofactor might dictate this inhibitory specificity. We determined that heat shock protein 90 (Hsp90) interacts with both IKKβ and NleH1 and that inhibiting Hsp90 activity reduces RPS3 nuclear translocation.
Developmental Stage and Shape of Embryo Determine the Efficacy of Embryo Rescue in Introgressing Orange/Yellow Color and Anthocyanin Genes of Brassica Species
Authors: Pen Sreyvatey , Nath Ujjal Kumar , Song Samnang , Goswami Gayatri , Lee Ji-Hee , Jung Hee-Jeong , Kim Hoy-Taek , Park Jong-In , Nou Ill-Sup
Published: November 2018

Vegetables in Brassica are some of the world’s most commonly cultivated plants and have a wide range of consumable plant organs. Improvement of this group of vegetables is limited at the species level due to limited genetic variability. Interspecies hybridization could be a powerful alternate tool for broadening the genetic variability of target traits. Embryo rescue technique is necessarily practiced in interspecies hybridization for protecting embryos from premature abortion. However, its success depends on the age of ovaries, shape of embryos, and the effect of female genotype. In this study, we carried out a wide range of interspecies crossing for introgressing target traits (orange/yellow color in cabbage and anthocyanin in Chinese cabbage) and optimizing the appropriate age of ovaries, the shape of embryo, and the suitable genotypes of such crosses. We observed that 15 DAP (days after pollination) was the best for embryo rescue in the diploid-diploid (Brassica rapa × B. oleracea) crosses, while 20 DAP was optimum for amphidiploid-diploid (B. napus/B. juncea × B. rapa) crosses. Cotyledonary shape of embryos and genotypes of amphidiploid species were the best for successful plant regeneration in interspecies crosses. We successfully selected plants with desired orange/yellow inner leaves for cabbage and higher anthocyanin in Chinese cabbage. The results of this study have the potential to be applied for the efficient production of interspecific hybrids and to develop Brassica vegetables with new traits, which could have potential for the enrichment of the human diet.
Bubble Melt Electrospinning for Production of Polymer Microfibers
Authors: Li Ye-Ming , Wang Xiao-Xiong , Yu Shu-Xin , Zhao Ying-Tao , Yan Xu , Zheng Jie , Yu Miao , Yan Shi-Ying , Long Yun-Ze
Published: November 2018

In this paper, we report an interesting bubble melt electrospinning (e-spinning) to produce polymer microfibers. Usually, melt e-spinning for fabricating ultrafine fibers needs “Taylor cone”, which is formed on the tip of the spinneret. The spinneret is also the bottleneck for mass production in melt e-spinning. In this work, a metal needle-free method was tried in the melt e-spinning process. The “Taylor cone” was formed on the surface of the broken polymer melt bubble, which was produced by an airflow. With the applied voltage ranging from 18 to 25 kV, the heating temperature was about 210–250 °C, and polyurethane (TPU) and polylactic acid (PLA) microfibers were successfully fabricated by this new melt e-spinning technique. During the melt e-spinning process, polymer melt jets ejected from the burst bubbles could be observed with a high-speed camera. Then, polymer microfibers could be obtained on the grounded collector. The fiber diameter ranged from 45 down to 5 μm. The results indicate that bubble melt e-spinning may be a promising method for needleless production in melt e-spinning.
Starch-Based Flexible Coating for Food Packaging Paper with Exceptional Hydrophobicity and Antimicrobial Activity
Authors: Ni Shuzhen , Zhang Hui , Dai Hongqi , Xiao Huining
Published: November 2018

Herein, we fabricated a starch-based flexible coating for food packaging papers with excellent hydrophobicity and antimicrobial properties. FTIR (Fourier transform infrared) and XRD (X-ray diffraction) spectra revealed the homogeneous dispersion of the ZnO nanoparticles (NPs) in the composite film within 5% ZnO NP dosage. SEM (scanning electron microscope) and AFM (atomic force microscope) micrographs confirmed the increased roughness on the composite film with the increased dosages of ZnO NPs. Hydrophobic characteristics showed that dramatic enhancement was obtained in the values and stabilities of DCAs (dynamic contact angles) in the resultant film and coated paper. TG (thermogravimetry) results demonstrated the increased thermal stabilities of the composite films. Significantly, a decreased water vapor transmission rate was observed in the coated paper. When 20% guanidine-based starch and 2% CMC (carboxy methyl cellulose) was added, a flexible coating with excellent antimicrobial activity towards Escherichia coli can be obtained. Furthermore, the migration of ZnO NPs into the food simulants was well below the overall migration legislative limit. The resultant starch-based flexible composite film and coated paper established an effective approach to develop a green-based material for food packaging applications.
Biosynthesis and Characteristics of Aromatic Polyhydroxyalkanoates
Authors: Ishii-Hyakutake Manami , Mizuno Shoji , Tsuge Takeharu
Published: November 2018

Polyhydroxyalkanoates (PHAs) are polyesters synthesized by bacteria as a carbon and energy storage material. PHAs are characterized by thermoplasticity, biodegradability, and biocompatibility, and thus have attracted considerable attention for use in medical, agricultural, and marine applications. The properties of PHAs depend on the monomer composition and many types of PHA monomers have been reported. This review focuses on biosynthesized PHAs bearing aromatic groups as side chains. Aromatic PHAs show characteristics different from those of aliphatic PHAs. This review summarizes the types of aromatic PHAs and their characteristics, including their thermal and mechanical properties and degradation behavior. Furthermore, the effect of the introduction of an aromatic monomer on the glass transition temperature (Tg) of PHAs is discussed. The introduction of aromatic monomers into PHA chains is a promising method for improving the properties of PHAs, as the characteristics of aromatic PHAs differ from those of aliphatic PHAs.
Calculation Model and Rapid Estimation Method for Coal Seam Gas Content
Authors: Wang Fakai , Zhao Xusheng , Liang Yunpei , Li Xuelong , Chen Yulong
Published: November 2018

Coalbed gas content is the most important parameter for forecasting and preventing the occurrence of coal and gas outburst. However, existing methods have difficulty obtaining the coalbed gas content accurately. In this study, a numerical calculation model for the rapid estimation of coal seam gas content was established based on the characteristic values of gas desorption at specific exposure times. Combined with technical verification, a new method which avoids the calculation of gas loss for the rapid estimation of gas content in the coal seam was investigated. Study results show that the balanced adsorption gas pressure and coal gas desorption characteristic coefficient (Kt) satisfy the exponential equation, and the gas content and Kt are linear equations. The correlation coefficient of the fitting equation gradually decreases as the exposure time of the coal sample increases. Using the new method to measure and calculate the gas content of coal samples at two different working faces of the Lubanshan North mine (LBS), the deviation of the calculated coal sample gas content ranged from 0.32% to 8.84%, with an average of only 4.49%. Therefore, the new method meets the needs of field engineering technology.
Deep Profiling of the Aggregated Proteome in Alzheimer’s Disease: From Pathology to Disease Mechanisms
Authors: Lutz Brianna M. , Peng Junmin
Published: November 2018

Hallmarks of Alzheimer’s disease (AD), a progressive neurodegenerative disease causing dementia, include protein aggregates such as amyloid beta plaques and tau neurofibrillary tangles in a patient’s brain. Understanding the complete composition and structure of protein aggregates in AD can shed light on the as-yet unidentified underlying mechanisms of AD development and progression. Biochemical isolation of aggregates coupled with mass spectrometry (MS) provides a comprehensive proteomic analysis of aggregates in AD. Dissection of these AD-specific aggregate components, such as U1 small nuclear ribonucleoprotein complex (U1 snRNP), provides novel insights into the deregulation of RNA splicing in the disease. In this review, we summarize the methodologies of laser capture microdissection (LCM) and differential extraction to analyze the aggregated proteomes in AD samples, and discuss the derived novel insights that may contribute to AD pathogenesis.
Solovyov’s Metaphysics between Gnosis and Theurgy
Authors: Gaisin Aleksandr
Published: November 2018

This article provides a reading of Vladimir Solovyov’s philosophy as expressed in his ‘Lectures on Divine Humanity’ and ‘The Meaning of Love’. It seeks to unpack his eclectic thought in order to answer the question of whether there is a Jewish Kabbalistic influence on the Russian thinker amidst his usual platonic, gnostic, and Schellengian tropes. Interested as a young man in Jewish Mysticism, Solovyov fluctuates in his ‘Lectures on Divine Humanity’ between a platonic reading of Schellengian Gnosticism and some elements of Kabbalistic origin. In ‘The Meaning of Love’, he develops a notion of love that puts him very close to what Moshe Idel calls ‘theosophic-theurgical Kabbalah’. Showing how ‘The Meaning of Love’ completes the narrative of ‘Lectures’, we can affirm that there is a certain Christian Kabbalistic line in Solovyov’s thought that culminates in his theurgical understanding of love. In this sense, Solovyov might be called a philosophical Marrano as he is certainly a heterodox theosopher that fluctuates between Christian Gnosis and Christian Kabbalah, never assuming a solid identity.
Nation as a Neo-Idol: Muslim Political Theology and the Critique of Secular Nationalism in Modern South Asia
Authors: Rehman Mohammad Adnan
Published: November 2018

Modern perspectives on nationalism tend to privilege structuralist readings which approach nationalism as entailing economic and political restructuring, thereby overlooking the necessary role of human factors in the functioning of nationalism. Religious opposition to secular nationalism is then condemned as backward, reactionary, fundamentalist, or ideological. However, a different understanding of nationalism is uncovered when the role of human factors in nationalism are scrutinized. Toward discerning the role of human factors in nationalism and its relation to religion in general, I turn to Liah Greenfeld’s analysis of social psychology of nationalism as a secular ideology. In exploring the effects of nationalist ideology on religion, I return to the earliest Muslim debates on nationalism in South Asia between two critics of nationalism, Muhammad Iqbal and Abu’l A’laa Mawdudi, and their opponents, Abul Kalam Azad and Husayn Ahmad Madani.
A Methodology for Multi-Camera Surface-Shape Estimation of Deformable Unknown Objects
Authors: Nuger Evgeny , Benhabib Beno
Published: November 2018

A novel methodology is proposed herein to estimate the three-dimensional (3D) surface shape of unknown, markerless deforming objects through a modular multi-camera vision system. The methodology is a generalized formal approach to shape estimation for a priori unknown objects. Accurate shape estimation is accomplished through a robust, adaptive particle filtering process. The estimation process yields a set of surface meshes representing the expected deformation of the target object. The methodology is based on the use of a multi-camera system, with a variable number of cameras, and range of object motions. The numerous simulations and experiments presented herein demonstrate the proposed methodology’s ability to accurately estimate the surface deformation of unknown objects, as well as its robustness to object loss under self-occlusion, and varying motion dynamics.
A Persistent Scatterer Interferometry Procedure Based on Stable Areas to Filter the Atmospheric Component
Authors: Crosetto Michele , Devanthéry Núria , Monserrat Oriol , Barra Anna , Cuevas-González María , Mróz Marek , Botey-Bassols Joan , Vázquez-Suñé Enric , Crippa Bruno
Published: November 2018

This paper describes a Persistent Scatterer Interferometry (PSI) procedure to monitor the land deformation in an urban area induced by aquifer dewatering and the consequent drawdown of the water table. The procedure, based on Sentinel-1 data, is illustrated considering the construction works of Glories Square, Barcelona (Spain). The study covers a period from March 2015 to November 2017, which includes a dewatering event in spring 2017. This paper describes the proposed procedure, whose most original part includes the estimation of the atmospheric phase component using stable areas located in the vicinity of the monitoring area. The performances of the procedure are analysed, characterising the original atmospheric phase component and the residual one that remains after modelling the atmospheric contribution. This procedure can work with any type of deformation phenomena, provided that its spatial extension is sufficiently small. The quality of the obtained time series is illustrated discussing different deformation results, including a validation result using piezometric data and a thermal expansion case.
Developing a Quality Index Associated with Rain for Hurricane Winds from SAR
Authors: Shen Hui , Seitz Chana , Perrie William , He Yijun , Powell Mark
Published: November 2018

Differences in synthetic aperture radar (SAR)-retrieved hurricane wind speeds from co-polarization and cross-polarization measurements are found to be correlated with rain rate. A quality index is proposed for the SAR-retrieved wind speed product to recognize heavy rain- affected areas by taking account of the different imaging mechanisms of the radar backscattering from the ocean surface via cross-polarization and co-polarization observations. A procedure is proposed to rectify wind retrievals in the rain-contaminated areas within the hurricane core, based on the theoretical physical profile for hurricanes. The effectiveness of the proposed methodology for heavy rain area recognition and wind speed reconstruction in the rain-affected areas is validated against step frequency microwave radiometer measurements from hurricane reconnaissance missions and the hurricane surface wind analysis product (HWIND). The quality flags provide confidence levels of hurricane surface winds from SAR, which together with the proposed method to correct wind retrievals in rain-contaminated areas, can contribute to improved operational applications of SAR-derived winds under hurricane conditions.
Does Sea Surface Temperature Contribute to Determining Range Limits and Expansion of Mangroves in Eastern South America (Brazil)?
Authors: Ximenes Arimatéa C. , Ponsoni Leandro , Lira Catarina F. , Koedam Nico , Dahdouh-Guebas Farid
Published: November 2018

Low Sea Surface Temperature (SST) is a climate barrier because it may inhibit and reduce seedling growth of mangrove propagules upon dispersal through seawater. Our objective is to analyze the spatio-temporal series of daily SST data from the Multi-scale Ultra-high Resolution (MUR)-SST in order to identify the occurrence of chilling events for mangrove plants at the Eastern South America mangrove limit and beyond. We focus our study on three key sites: (i) the Rhizophora mangle L. distribution limit (Praia do Sonho: 27°53′S), (ii) the Eastern South America mangrove limit (Laguna: 28°30′S) and (iii) one beyond mangrove areas, in Araranguá (28°55′S). Our results show that, in Araranguá, chilling events are more intense and occur more frequently than in the other two sites that have a mangrove cover. We conclude that, the chilling events of SST may play a role in restricting mangroves within their actual limits. In this sense, higher occurrences of chilling events of SST could be an explanation for the absence of R. mangle in Laguna. However, Laguncularia racemosa (L.) C.F. Gaertn. was reported to be tolerant to low temperatures, and yet it is absent from the southernmost study site. This may be an indication of the role of other factors than SST in determining a mangrove range expansion, such as dispersal constraints.
Comparison of Aerosol Reflectance Correction Schemes Using Two Near-Infrared Wavelengths for Ocean Color Data Processing
Authors: Ahn Jae-Hyun , Park Young-Je , Fukushima Hajime
Published: November 2018

This paper reanalyzes the aerosol reflectance correction schemes employed by major ocean color missions. The utilization of two near-infrared (NIR) bands to estimate aerosol reflectance in visible wavelengths has been widely adopted, for example by SeaWiFS/MODIS/VIIRS (GW1994), OCTS/GLI/SGLI (F1998), MERIS/OLCI (AM1999), and GOCI/GOCI-II (A2016). The F1998, AM1999, and A2016 schemes were developed based on GW1994; however, they are implemented differently in terms of aerosol model selection and weighting factor computation. The F1998 scheme determines the contribution of the most appropriate aerosol models in the aerosol optical thickness domain, whereas the GW1994 scheme focuses on single-scattering reflectance. The AM1999 and A2016 schemes both directly resolve the multiple scattering domain contribution. However, A2016 also considers the spectrally dependent weighting factor, whereas AM1999 calculates the spectrally invariant weighting factor. Additionally, ocean color measurements on a geostationary platform, such as GOCI, require more accurate aerosol correction schemes because the measurements are made over a large range of solar zenith angles which causes diurnal instabilities in the atmospheric correction. Herein, the four correction schemes were tested with simulated top-of-atmosphere radiances generated by radiative transfer simulations for three aerosol models. For comparison, look-up tables and test data were generated using the same radiative transfer simulation code. All schemes showed acceptable accuracy, with less than 10% median error in water reflectance retrieval at 443 nm. Notably, the accuracy of the A2016 scheme was similar among different aerosol models, whereas the other schemes tended to provide better accuracy with coarse aerosol models than the fine aerosol models.
Tree Species Classification with Multi-Temporal Sentinel-2 Data
Authors: Persson Magnus , Lindberg Eva , Reese Heather
Published: November 2018

The Sentinel-2 program provides the opportunity to monitor terrestrial ecosystems with a high temporal and spectral resolution. In this study, a multi-temporal Sentinel-2 data set was used to classify common tree species over a mature forest in central Sweden. The tree species to be classified were Norway spruce (Picea abies), Scots pine (Pinus silvestris), Hybrid larch (Larix × marschlinsii), Birch (Betula sp.) and Pedunculate oak (Quercus robur). Four Sentinel-2 images from spring (7 April and 27 May), summer (9 July) and fall (19 October) of 2017 were used along with the Random Forest (RF) classifier. A variable selection approach was implemented to find fewer and uncorrelated bands resulting in the best model for tree species identification. The final model resulting in the highest overall accuracy (88.2%) came from using all bands from the four image dates. The single image that gave the most accurate classification result (80.5%) was the late spring image (27 May); the 27 May image was always included in subsequent image combinations that gave the highest overall accuracy. The five tree species were classified with a user’s accuracy ranging from 70.9% to 95.6%. Thirteen of the 40 bands were selected in a variable selection procedure and resulted in a model with only slightly lower accuracy (86.3%) than that using all bands. Among the highest ranked bands were the red edge bands 2 and 3 as well as the narrow NIR (near-infrared) band 8a, all from the 27 May image, and SWIR (short-wave infrared) bands from all four image dates. This study shows that the red-edge bands and SWIR bands from Sentinel-2 are of importance, and confirms that spring and/or fall images capturing phenological differences between the species are most useful to tree species classification.
Long-Term Arctic Snow/Ice Interface Temperature from Special Sensor for Microwave Imager Measurements
Authors: Lee Sang-Moo , Sohn Byung-Ju , Kummerow Christian D.
Published: November 2018

The Arctic sea ice region is the most visible area experiencing global warming-induced climate change. However, long-term measurements of climate-related variables have been limited to a small number of variables such as the sea ice concentration, extent, and area. In this study, we attempt to produce a long-term temperature record for the Arctic sea ice region using Special Sensor for Microwave Imager (SSM/I) Fundamental Climate Data Record (FCDR) data. For that, we developed an algorithm to retrieve the wintertime snow/ice interface temperature (SIIT) over the Arctic Ocean by counting the effect of the snow/ice volume scattering and ice surface roughness on the apparent emissivity (the total effect is referred to as the correction factor). A regression equation was devised to predict the correction factor from SSM/I brightness temperatures (TBs) only and then applied to SSM/I 19.4 GHz TB to estimate the SIIT. The obtained temperatures were validated against collocated Cold Regions Research and Engineering Laboratory (CRREL) ice mass balance (IMB) drifting buoy-measured temperatures at zero ice depth. It is shown that the SSM/I retrievals are in good agreement with the drifting buoy measurements, with a correlation coefficient of 0.95, bias of 0.1 K, and root-mean-square error of 1.48 K on a daily time scale. By applying the algorithm to 24-year (1988–2011) SSM/I FCDR data, we were able to produce the winter-time temperature at the sea ice surface for the 24-year period.
Multi-Variable Classification Approach for the Detection of Lightning Activity Using a Low-Cost and Portable X Band Radar
Authors: Capozzi Vincenzo , Montopoli Mario , Mazzarella Vincenzo , Marra Anna Cinzia , Roberto Nicoletta , Panegrossi Giulia , Dietrich Stefano , Budillon Giorgio
Published: November 2018

This work proposes a multi-parameter method for the detection of cloud-to-ground stroke rate (SRCG) associated to convective cells, based on the measurements of a low-cost single-polarization X-band weather radar. To train and test our procedure, we built up a multi-year dataset, collecting 1575 radar reflectivity volumes that were acquired in the pilot study area of Naples metropolitan environment matched with the LIghtning NETwork (LINET) strokes and meteorological in-situ data. Three radar-based variables are extracted simultaneously for each rain cell and properly merged together, using “ad hoc” classification methods, to produce an estimation of the expected lightning activity for each rain cell. These variables, proxies of mixed-phase particles and ice amount into a convective cell, are combined into a single label to cluster the SRCG into two categories: SRCG = 0 (no production of strokes) or SRCG > 0 (stroke production), respectively. Overall, the main results are comparable with those that were obtained from more advanced radar systems, showing a Critical Success Index of 0.53, an Equitable Threat Score of 0.34, a Frequency Bias Index of 1.00, a Heidke Skill Score of 0.42, a Hanssen-Kuiper Skill Score of 0.42, and an area under the curve of probability of detection as a function of false alarm rate (usually referred as ROC curve) equal to 0.78. The developed technique, although with some limitations, outperforms those based on the use of single stroke proxy parameters.
How Far Can Consumer-Grade UAV RGB Imagery Describe Crop Production? A 3D and Multitemporal Modeling Approach Applied to Zea mays
Authors: Michez Adrien , Bauwens Sébastien , Brostaux Yves , Hiel Marie-Pierre , Garré Sarah , Lejeune Philippe , Dumont Benjamin
Published: November 2018

In recent decades, remote sensing has increasingly been used to estimate the spatio-temporal evolution of crop biophysical parameters such as the above-ground biomass (AGB). On a local scale, the advent of unmanned aerial vehicles (UAVs) seems to be a promising trade-off between satellite/airborne and terrestrial remote sensing. This study aims to evaluate the potential of a low-cost UAV RGB solution to predict the final AGB of Zea mays. Besides evaluating the interest of 3D data and multitemporality, our study aims to answer operational questions such as when one should plan a combination of two UAV flights for AGB modeling. In this case, study, final AGB prediction model performance reached 0.55 (R-square) using only UAV information and 0.8 (R-square) when combining UAV information from a single flight with a single-field AGB measurement. The adding of UAV height information to the model improves the quality of the AGB prediction. Performing two flights provides almost systematically an improvement in AGB prediction ability in comparison to most single flights. Our study provides clear insight about how we can counter the low spectral resolution of consumer-grade RGB cameras using height information and multitemporality. Our results highlight the importance of the height information which can be derived from UAV data on one hand, and on the other hand, the lower relative importance of RGB spectral information.
A Situation-Aware Indoor Localization (SAIL) System Using a LF and RF Hybrid Approach
Authors: Park Jung Kwang , Kim Jeeyoung , Kang Soon Ju
Published: November 2018

Recently, studies focusing on identifying user’s current location for use in a wide variety of differentiated location-based and localization services have steadily increased. In particular, location awareness using wireless communication is gaining attention in indoor environments composed of many obstacles, where GPS signals cannot reach. Previously, studies have focused mostly on location precision, which resulted in using many beacon nodes, not considering the initial installation and maintenance costs, communication robustness, or power consumption. This makes it difficult to apply existing methods to various fields, especially in mobile nodes (i.e., wearable devices, mobile tags, etc.) with limited battery capacity. In this paper, we propose a hybrid situation-aware indoor localization (SAIL) system for real-time indoor localization using a combination of low frequency (LF) and Bluetooth Low Energy (BLE) 4.0. This approach allows us to work with limited battery capacity mobile devices, and identify tagged mobile nodes and their current location in relevance to the anchor node. In our experiment, we attached one anchor node at the entrance to indoor areas such as office or factory settings. Using our hybrid SAIL system, we were able to detect the passing of a mobile node through the entrance and recognize whether the node is entering or exiting the room by calculating the direction of movement as well as the distance from the entrance. This allowed us to distinguish the precise position in an indoor environment with the margin of error being 0.5 m. The signal attenuation due to obstacles is overcome by using LF communication in the 125-kHz band. This approach enables us to reduce the number of initially installed anchor nodes as well as the power consumption of the mobile node. We propose an indoor position recognition system, namely, the hybrid SAIL system, that can be applied to mobile nodes with limited battery capacity by reducing the system complexity and power consumption.
Deep CNNs with Robust LBP Guiding Pooling for Face Recognition
Authors: Ma Zhongjian , Ding Yuanyuan , Li Baoqing , Yuan Xiaobing
Published: November 2018

Pooling layer in Convolutional Neural Networks (CNNs) is designed to reduce dimensions and computational complexity. Unfortunately, CNN is easily disturbed by noise in images when extracting features from input images. The traditional pooling layer directly samples the input feature maps without considering whether they are affected by noise, which brings about accumulated noise in the subsequent feature maps as well as undesirable network outputs. To address this issue, a robust Local Binary Pattern (LBP) Guiding Pooling (G-RLBP) mechanism is proposed in this paper to down sample the input feature maps and lower the noise impact simultaneously. The proposed G-RLBP method calculates the weighted average of all pixels in the sliding window of this pooling layer as the final results based on their corresponding probabilities of being affected by noise, thus lowers the noise impact from input images at the first several layers of the CNNs. The experimental results show that the carefully designed G-RLBP layer can successfully lower the noise impact and improve the recognition rates of the CNN models over the traditional pooling layer. The performance gain of the G-RLBP is quite remarkable when the images are severely affected by noise.
Emotion Recognition Based on Multichannel Physiological Signals with Comprehensive Nonlinear Processing
Authors: Zhang Xingxing , Xu Chao , Xue Wanli , Hu Jing , He Yongchuan , Gao Mengxin
Published: November 2018

Multichannel physiological datasets are usually nonlinear and separable in the field of emotion recognition. Many researchers have applied linear or partial nonlinear processing in feature reduction and classification, but these applications did not work well. Therefore, this paper proposed a comprehensive nonlinear method to solve this problem. On the one hand, as traditional feature reduction may cause the loss of significant amounts of feature information, Kernel Principal Component Analysis (KPCA) based on radial basis function (RBF) was introduced to map the data into a high-dimensional space, extract the nonlinear information of the features, and then reduce the dimension. This method can provide many features carrying information about the structure in the physiological dataset. On the other hand, considering its advantages of predictive power and feature selection from a large number of features, Gradient Boosting Decision Tree (GBDT) was used as a nonlinear ensemble classifier to improve the recognition accuracy. The comprehensive nonlinear processing method had a great performance on our physiological dataset. Classification accuracy of four emotions in 29 participants achieved 93.42%.
On the Performance of an Aerosol Electrometer with Enhanced Detection Limit
Authors: Yang Yixin , Yu Tongzhu , Zhang Jiaoshi , Wang Jian , Wang Wenyu , Gui Huaqiao , Liu Jianguo
Published: November 2018

An aerosol electrometer with enhanced detection limit was developed for measuring the collected particles electrical current ranging from −50 pA to 50 pA with no range switching necessary. The detection limit was enhanced by suppressing the electric current measurement noise and improving the detection efficiency. A theoretical model for the aerosol electrometer has been established to investigate the noise effect factors and verified experimentally. The model showed that the noise was a function of ambient temperature, and it was affected by the characteristics of feedback resistor and operational amplifier simultaneously. The Faraday cup structure of the aerosol electrometer was optimized by adopting a newly designed cup-shaped metal filter which increased the surface area of the cup; thus the particle interception efficiency was improved. The aerosol electrometer performance-linearity, noise and the particle detection efficiency, were evaluated experimentally. When compared with TSI-3068B, a 99.4% ( R 2 ) statistical correlation was achieved. The results also showed that the root mean square noise and the peak-to-peak noise were 0.31 fA and 1.55 fA, respectively. The particle detection efficiency was greater than 99.3% when measuring particle diameter larger than 7.0 nm.
Comparative Study on Conductive Knitted Fabric Electrodes for Long-Term Electrocardiography Monitoring: Silver-Plated and PEDOT:PSS Coated Fabrics
Authors: Ankhili Amale , Tao Xuyuan , Cochrane Cédric , Koncar Vladan , Coulon David , Tarlet Jean-Michel
Published: November 2018

Long-term monitoring of the electrical activity of the heart helps to detect the presence of potential dysfunctions, enabling the diagnosis of a wide range of cardiac pathologies. However, standard electrodes used for electrocardiogram (ECG) acquisition are not fully integrated into garments, and generally need to be used with a gel to improve contact resistance. This article is focused on the development of washable screen-printed cotton, with and without Lycra, textile electrodes providing a medical quality ECG signal to be used for long-term electrocardiography measurements. Several samples with different Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) concentrations were investigated. Silver-plated knitted fabric electrodes were also used for comparison, within the same process of ECG signal recording. The acquisition of ECG signals carried out by a portable medical device and a low-coast Arduino-based device on one female subject in a sitting position. Three textile electrodes were placed on the right and left forearms and a ground electrode was placed on the right ankle of a healthy female subject. Plastic clamps were applied to maintain electrodes on the skin. The results obtained with PEDOT:PSS used for electrodes fabrication have been presented, considering the optimal concentration required for medical ECG quality and capacity to sustain up to 50 washing cycles. All the ECG signals acquired and recorded, using PEDOT:PSS and silver-plated electrodes, have been reviewed by a cardiologist in order to validate their quality required for accurate diagnosis.
Electrical Characteristics and pH Response of a Parylene-H Sensing Membrane in a Si-Nanonet Ion-Sensitive Field-Effect Transistor
Authors: Jin Bo , Lee Ga-Yeon , Park ChanOh , Kim Donghoon , Choi Wonyeong , Yoo Jae-Woo , Pyun Jae-Chul , Lee Jeong-Soo
Published: November 2018

We report the electrical characteristics and pH responses of a Si-nanonet ion-sensitive field-effect transistor with ultra-thin parylene-H as a gate sensing membrane. The fabricated device shows excellent DC characteristics: a low subthreshold swing of 85 mV/dec, a high current on/off ratio of ~107 and a low gate leakage current of ~10−10 A. The low interface trap density of 1.04 × 1012 cm−2 and high field-effect mobility of 510 cm2V−1s−1 were obtained. The pH responses of the devices were evaluated in various pH buffer solutions. A high pH sensitivity of 48.1 ± 0.5 mV/pH with a device-to-device variation of ~6.1% was achieved. From the low-frequency noise characterization, the signal-to-noise ratio was extracted as high as ~3400 A/A with the lowest noise equivalent pH value of ~0.002 pH. These excellent intrinsic electrical and pH sensing performances suggest that parylene-H can be promising as a sensing membrane in an ISFET-based biosensor platform.
Iss2Image: A Novel Signal-Encoding Technique for CNN-Based Human Activity Recognition
Authors: Hur Taeho , Bang Jaehun , Huynh-The Thien , Lee Jongwon , Kim Jee-In , Lee Sungyoung
Published: November 2018

The most significant barrier to success in human activity recognition is extracting and selecting the right features. In traditional methods, the features are chosen by humans, which requires the user to have expert knowledge or to do a large amount of empirical study. Newly developed deep learning technology can automatically extract and select features. Among the various deep learning methods, convolutional neural networks (CNNs) have the advantages of local dependency and scale invariance and are suitable for temporal data such as accelerometer (ACC) signals. In this paper, we propose an efficient human activity recognition method, namely Iss2Image (Inertial sensor signal to Image), a novel encoding technique for transforming an inertial sensor signal into an image with minimum distortion and a CNN model for image-based activity classification. Iss2Image converts real number values from the X, Y, and Z axes into three color channels to precisely infer correlations among successive sensor signal values in three different dimensions. We experimentally evaluated our method using several well-known datasets and our own dataset collected from a smartphone and smartwatch. The proposed method shows higher accuracy than other state-of-the-art approaches on the tested datasets.
Robust Iterative Distributed Minimum Total MSE Algorithm for Secure Communications in the Internet of Things Using Relays
Authors: Kong Zhengmin , Wang Die , Li Yunjuan , Wang Chao
Published: November 2018

In this article, we first investigate secure communications for a two-hop interference channel relay system with imperfect channel estimation in the wireless Internet of Things (IoT), where K source-destination pairs communicate simultaneously when an eavesdropper exists. We jointly conceive source, relay and destination matrices upon minimizing total mean-squared error (MSE) of all legitimate destinations while keeping the MSE at eavesdropper above a given threshold. We illuminate that the design of the source, relay and destination matrices is subject to both transmit power constraints and secrecy requirements. More specifically, we propose an efficient robust iterative distributed algorithm to simplify the process of the joint design for optimal source, relay and destination matrices. Furthermore, the convergence of the iterative distributed algorithm is described. Additionally, the performances of our proposed algorithm, such as its secrecy rate and MSE, are characterized in the form of simulation results. The simulation results reveal that the proposed algorithm is superior to the traditional approach. As a benefit, secure communications can be ensured by using the proposed algorithm for the multiple input multiple output (MIMO) interference relay IoT network in the presence of an eavesdropper.
Predicting the Health Status of an Unmanned Aerial Vehicles Data-Link System Based on a Bayesian Network
Authors: Wang Xiaohong , Guo Hongzhou , Wang Jingbin , Wang Lizhi
Published: November 2018

Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations. The performance of a UAV data-link system is affected by the health status of both the hardware and UAV data-links. This paper proposes a method for predicting the health state of a UAV data-link system based on a Bayesian network fusion of information about potential hardware device failures and link failures. Our model employs the Bayesian network to describe the information and uncertainty associated with a complex multi-level system. To predict the health status of the UAV data-link, we use the health status information about the root node equipment with various life characteristics along with the health status of the links as affected by the bit error rate. In order to test the validity of the model, we tested its prediction of the health of a multi-level solar-powered unmanned aerial vehicle data-link system and the result shows that the method can quantitatively predict the health status of the solar-powered UAV data-link system. The results can provide guidance for improving the reliability of UAV data-link system and lay a foundation for predicting the health status of a UAV data-link system accurately.
Automatic Extraction and Detection of Characteristic Movement Patterns in Children with ADHD Based on a Convolutional Neural Network (CNN) and Acceleration Images
Authors: Muñoz-Organero Mario , Powell Lauren , Heller Ben , Harpin Val , Parker Jack
Published: November 2018

Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental disorder, which is characterized by inattention, hyperactivity and impulsive behaviors. In particular, children have difficulty keeping still exhibiting increased fine and gross motor activity. This paper focuses on analyzing the data obtained from two tri-axial accelerometers (one on the wrist of the dominant arm and the other on the ankle of the dominant leg) worn during school hours by a group of 22 children (11 children with ADHD and 11 paired controls). Five of the 11 ADHD diagnosed children were not on medication during the study. The children were not explicitly instructed to perform any particular activity but followed a normal session at school alternating classes of little or moderate physical activity with intermediate breaks of more prominent physical activity. The tri-axial acceleration signals were converted into 2D acceleration images and a Convolutional Neural Network (CNN) was trained to recognize the differences between non-medicated ADHD children and their paired controls. The results show that there were statistically significant differences in the way the two groups moved for the wrist accelerometer (t-test p-value <0.05). For the ankle accelerometer statistical significance was only achieved between data from the non-medicated children in the experimental group and the control group. Using a Convolutional Neural Network (CNN) to automatically extract embedded acceleration patterns and provide an objective measure to help in the diagnosis of ADHD, an accuracy of 0.875 for the wrist sensor and an accuracy of 0.9375 for the ankle sensor was achieved.
Sandwich Electrochemical Immunosensor for Early Detection of Tuberculosis Based on Graphene/Polyaniline-Modified Screen-Printed Gold Electrode
Authors: Mohd Azmi Umi Zulaikha , Yusof Nor Azah , Kusnin Norzila , Abdullah Jaafar , Suraiya Siti , Ong Poh Shing , Ahmad Raston Nurul Hanun , Abd Rahman Siti Fatimah , Mohamad Fathil Mohamad Faris
Published: November 2018

A rapid and sensitive sandwich electrochemical immunosensor was developed based on the fabrication of the graphene/polyaniline (GP/PANI) nanocomposite onto screen-printed gold electrode (SPGE) for detection of tuberculosis biomarker 10-kDa culture filtrate protein (CFP10). The prepared GP/PANI nanocomposite was characterized using Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM). The chemical bonding and morphology of GP/PANI-modified SPGE were studied by Raman spectroscopy and FESEM coupled with energy dispersive X-ray spectroscopy, respectively. From both studies, it clearly showed that GP/PANI was successfully coated onto SPGE through drop cast technique. Cyclic voltammetry was used to study the electrochemical properties of the modified electrode. The effective surface area for GP/PANI-modified SPGE was enhanced about five times compared with bare SPGE. Differential pulse voltammetry was used to detect the CFP10 antigen. The GP/PANI-modified SPGE that was fortified with sandwich type immunosensor exhibited a wide linear range (20–100 ng/mL) with a low detection limit of 15 ng/mL. This proposed electrochemical immunosensor is sensitive, low sample volume, rapid and disposable, which is suitable for tuberculosis detection in real samples.
Influence of Oxygen Vacancy Behaviors in Cooling Process on Semiconductor Gas Sensors: A Numerical Analysis
Authors: Liu Jianqiao , Wang Wanqiu , Zhai Zhaoxia , Jin Guohua , Chen Yuzhen , Hong Wusong , Wu Liting , Gao Fengjiao
Published: November 2018

The influence of oxygen vacancy behaviors during a cooling process in semiconductor gas sensors is discussed by the numerical analysis method based on the gradient-distributed oxygen vacancy model. A diffusion equation is established to describe the behaviors of oxygen vacancies, which follows the effects of diffusion and exclusion in the cooling process. Numerical analysis is introduced to find the accurate solutions of the diffusion equation. The solutions illustrate the oxygen vacancy distribution profiles, which are dependent on the cooling rate as well as the temperature interval of the cooling process. The gas-sensing characteristics of reduced resistance and response are calculated. Both of them, together with oxygen vacancy distribution, show the grain size effects and the re-annealing effect. It is found that the properties of gas sensors can be controlled or adjusted by the designed cooling process. The proposed model provides a possibility for sensor characteristics simulations, which may be beneficial for the design of gas sensors. A quantitative interpretation on the gas-sensing mechanism of semiconductors has been contributed.