bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Moringa oleifera Leaf Powder on Postprandial Blood Glucose Response: In Vivo Study on Saharawi People Living in Refugee Camps
Authors: Leone Alessandro , Bertoli Simona , Di Lello Sara , Bassoli Angela , Ravasenghi Stefano , Borgonovo Gigliola , Forlani Fabio , Battezzati Alberto
Published: October 2018

The hypoglycemic effect in humans of Moringa oleifera (MO) leaf powder has, to date, been poorly investigated. We assessed the chemical composition of MO leaf powder produced at Saharawi refugee camps, its in vitro ability to inhibit α-amylase activity, and its sensory acceptability in food. We then evaluated its effect on postprandial glucose response by randomly administering, on 2 different days, a traditional meal supplemented with 20 g of MO leaf powder (MOR20), or not (control meal, CNT), to 17 Saharawi diabetics and 10 healthy subjects. Capillary glycaemia was measured immediately before the meal and then at 30 min intervals for 3 h. In the diabetic subjects the postprandial glucose response peaked earlier with MOR20 compared to CNT and with lower increments at 90, 120, and 150 min. The mean glycemic meal response with MOR20 was lower than with CNT. The healthy subjects showed no differences. Thus, MO leaf powder could be a hypoglycemic herbal drug. However, given the poor taste acceptability of the 20 g MO meal, lower doses should be evaluated. Moreover, the hypoglycemic effects of MO leaf powder should also be demonstrated by trials evaluating its long-term effects on glycaemia.
Chronic Intake of Micrograms of Abscisic Acid Improves Glycemia and Lipidemia in a Human Study and in High-Glucose Fed Mice
Authors: Magnone Mirko , Leoncini Giovanna , Vigliarolo Tiziana , Emionite Laura , Sturla Laura , Zocchi Elena , Murialdo Giovanni
Published: October 2018

We tested the effect of chronic low-dose abscisic acid (ABA), a phytohormone-regulating human glucose tolerance, on the metabolic parameters that are dysregulated in prediabetes and metabolic syndrome (MS).Ten healthy subjects received 1 µg ABA/Kg body weight (BW)/day as an ABA-rich food supplement: (i) the glycemia profile after a carbohydrate-rich meal, with or without supplement, was compared; (ii) fasting blood glucose (FBG), glycated hemoglobin (HbA1c), total cholesterol (TC), and body mass index (BMI) after 75 days of daily supplementation of a habitual Mediterranean diet were compared with starting values.CD1 mice were fed a high-glucose diet with or without synthetic ABA (1 µg/Kg BW) for 4 months and the same parameters investigated in the human study were compared. The food supplement significantly reduced the area under the curve of glycemia after a carbohydrate-rich meal and FBG, HbA1c, TC, and BMI after chronic treatment. ABA-treated mice showed a significant reduction of HbA1c, TC, and body weight gain compared with untreated controls. The combined results from the human and murine studies allow us to conclude that the observed improvement of the metabolic parameters can be attributed to ABA and to advocate the use of ABA-containing food supplements in prediabetes and/or MS.
Obeticholic Acid: A New Era in the Treatment of Nonalcoholic Fatty Liver Disease
Authors: Abenavoli Ludovico , Falalyeyeva Tetyana , Boccuto Luigi , Tsyryuk Olena , Kobyliak Nazarii
Published: October 2018

The main treatments for patients with nonalcoholic fatty liver disease (NAFLD) are currently based on lifestyle changes, including ponderal decrease and dietary management. However, a subgroup of patients with nonalcoholic steatohepatitis (NASH), who are unable to modify their lifestyle successfully, may benefit from pharmaceutical support. Several drugs targeting pathogenic mechanisms of NAFLD have been evaluated in clinical trials for the treatment of NASH. Farnesoid X receptor (FXR) is a nuclear key regulator controlling several processes of the hepatic metabolism. NAFLD has been proven to be associated with abnormal FXR activity. Obeticholic acid (OCA) is a first-in-class selective FXR agonist with anticholestatic and hepato-protective properties. Currently, OCA is registered for the treatment of primary biliary cholangitis. However, promising effects of OCA on NASH and its metabolic features have been reported in several studies.
Deprescribing—A Few Steps Further
Authors: Sadowski Cheryl A.
Published: October 2018

n/a
Pharmacy Technicians’ Willingness to Perform Emerging Tasks in Community Practice
Authors: Doucette William R. , Schommer Jon C.
Published: October 2018

New tasks are being developed for pharmacy technicians in community practice. The objectives of this study were to (1) assess the willingness of community pharmacy technicians to perform new tasks, and (2) to identify factors affecting technicians in assuming new tasks in community pharmacy practice. An online survey asked about the respondent characteristics, involvement in pharmacy technician tasks, willingness to perform emerging pharmacy technician tasks, and influences on pharmacy technicians’ performance of emerging tasks. Descriptive statistics were calculated for all items. A total of 639 usable surveys from community pharmacy technicians were used in the analyses. The respondents reported a mean of 11.5 years working as a pharmacy technician, with 79.2% working full time. Technicians reported high willingness to perform four emerging tasks, moderate willingness for six tasks, and low willingness to perform two tasks. The low willingness tasks were administering a vaccination and drawing a blood sample with a finger stick. Four workplace influences on willingness to perform emerging tasks were insufficient staffing, insufficient time to complete additional tasks, employers not classifying technicians based on specialized skills, and usually feeling stress at work. It appears likely that pharmacy technicians will be willing to perform the new tasks needed to support the emerging patient care services in community pharmacies.
New Generation Wearable Antenna Based on Multimaterial Fiber for Wireless Communication and Real-Time Breath Detection
Authors: Roudjane Mourad , Khalil Mazen , Miled Amine , Messaddeq Younés
Published: October 2018

Smart textiles and wearable antennas along with broadband mobile technologies have empowered the wearable sensors for significant impact on the future of digital health care. Despite the recent development in this field, challenges related to lack of accuracy, reliability, user’s comfort, rigid form and challenges in data analysis and interpretation have limited their wide-scale application. Therefore, the necessity of developing a new reliable and user friendly approach to face these problems is more than urgent. In this paper, a new generation of wearable antenna is presented, and its potential use as a contactless and non-invasive sensor for human breath detection is demonstrated. The antenna is made from multimaterial fiber designed for short-range wireless network applications at 2.4 GHz frequency. The used composite metal-glass-polymer fibers permits their integration into a textile without compromising comfort or restricting movement of the user due to their high flexibility, and shield efficiently the antenna from the environmental perturbation. The multimaterial fiber approach provided a good radio-frequency emissive properties, while preserving the mechanical and cosmetic properties of the garments. With a smart textile featuring a spiral shape fiber antenna placed on a human chest, a significant shift of the operating frequency of the antenna was observed during the breathing process. The frequency shift is caused by the deformation of the antenna geometry due to the chest expansion, and to the modification of the dielectric properties of the chest during the breath. We demonstrate experimentally that the standard wireless networks, which measure the received signal strength indicator (RSSI) via standard Bluetooth protocol, can be used to reliably detect human breathing and estimate the breathing rate in real time. The mobile platform takes the form of a wearable stretching T-shirt featuring a sensor and a detection base station. The sensor is formed by a spiral-shaped antenna connected to a compact Bluetooth transmitter. Breathing patterns were recorded in the case of female and male volunteers. Although the chest anatomy of females and males is different compared, the sensor’s flexibility allowed recording successfully a breathing rate of 0.3 Hz for the female and 0.5 Hz for the male, which corresponds to a breathing rate of 21 breaths per minutes (bpm) and 30 bpm, respectively.
Hairy Polydopamine Particles as Platforms for Photonic and Magnetic Materials
Authors: Kohri Michinari , Uradokoro Kanako , Nannichi Yuri , Kawamura Ayaka , Taniguchi Tatsuo , Kishikawa Keiki
Published: October 2018

By selecting the core materials and grafted-hair polymers, hairy particles with polymer brushes can create various types of functional materials. In recent years, polydopamine (PDA) particles that are obtained by polymerizing dopamine, which is an amino acid derivative, have attracted attention for various applications. Herein, we present a novel approach for creating photonic and magnetic materials from hairy PDA particles. By grafting a hydrophilic hair polymer, we have succeeded in producing photonic materials capable of structural color changes. Furthermore, we have demonstrated the preparation of magnetic materials by immobilizing holmium, which is one of the lanthanide elements, by electrostatic interactions onto a cationic hair polymer. These results demonstrate the possibility of hairy PDA particles for a wide range of applications, such as for photonic and magnetic materials.
Cinnamic Acid Inhibited Growth of Faba Bean and Promoted the Incidence of Fusarium Wilt
Authors: Zhao Qian , Chen Ling , Dong Kun , Dong Yan , Xiao Jingxiu
Published: October 2018

To ascertain the role and mechanism of cinnamic acid in the process of soil-borne Fusarium wilt infection with fava bean, we studied the effect of cinnamic acid on the faba bean and Fusarium oxysporum f. fabae (FOF). Our results showed that cinnamic acid treatment affected the physiological resistance of faba bean to FOF after inoculation with the pathogen and enhanced the pathogenicity of the pathogen, which may have led to aggravation of infection by the pathogen and increases in the incidence rates of Fusarium wilt and disease.
Novel Photocatalytic PVDF/Nano-TiO2 Hollow Fibers for Environmental Remediation
Authors: Galiano Francesco , Song Xue , Marino Tiziana , Boerrigter Marcel , Saoncella Omar , Simone Silvia , Faccini Mirko , Chaumette Christiane , Drioli Enrico , Figoli Alberto
Published: October 2018

Polyvinylidene difluoride (PVDF) mixed matrix membranes loaded with inorganic TiO2 nanoparticles have received increasing attention in the last few years as self-cleaning membranes for possible application in wastewater treatment and seawater filtration. These novel membranes show increased hydrophilicity, stability and catalytic activity under UV-A irradiation. In this work, PVDF-TiO2 hollow fibers were prepared by employing new strategies for enhancing the stability of the TiO2 dispersion, reducing particle agglomeration and improving their distribution. The spinning conditions for producing ultrafiltration hollow fiber membranes from PVDF material and nano-TiO2 were investigated. Finally, the optimized fibers have been characterized and tested for methylene blue (MB) degradation in water and salty seawater, revealing good permeability, long-term stability under UV-A irradiation, and photo-catalytic activity in both test solutions.
Optimization of Mechanical and Thermal Properties of iPP and LMPP Blend Fibres by Surface Response Methodology
Authors: Yasin Sohail , Sun Danmei , Memon Hafeezullah , Zhu Feichao , Jian Han , Bin Yu , Mingbo Ma , Hussain Munir
Published: October 2018

Optimization of the mechanical and thermal properties of isotactic polypropylene (iPP) homopolymer blended with relatively new low molecular low modulus polypropylene (LMPP) at different blend ratios was carried out via surface response methodology (RSM). Regression equations for the prediction of optimal conditions were achieved considering eight individual parameters: naming, elongation at break, tensile strength and elastic modulus, crystallization temperature (TC), first melting temperatures (TM1), heat fusion (Hf), crystallinity, and melt flow rate (MFR), which were measured as responses for the design of experiment (DOE). The adjusted and predicted correlation coefficient (R2) shows good agreement between the actual and the predicted values. To confirm the optimal values from the response model, supplementary experiments as a performance evaluation were conducted, posing better operational conditions. It has been confirmed that the RSM model was adequate to reflect the predicted optimization. The results suggest that the addition of LMPP into iPP could effectively enhance the functionality and processability of blend fibres if correctly proportioned.
Development of a Semiglobal Reaction Mechanism for the Thermal Decomposition of a Polymer Containing Reactive Flame Retardants: Application to Glass-Fiber-Reinforced Polybutylene Terephthalate Blended with Aluminum Diethyl Phosphinate and Melamine Polyphosphate
Authors: Ding Yan , Stoliarov Stanislav , Kraemer Roland
Published: October 2018

This work details a methodology for parameterization of the kinetics and thermodynamics of the thermal decomposition of polymers blended with reactive additives. This methodology employs Thermogravimetric Analysis, Differential Scanning Calorimetry, Microscale Combustion Calorimetry, and inverse numerical modeling of these experiments. Blends of glass-fiber-reinforced polybutylene terephthalate (PBT) with aluminum diethyl phosphinate and melamine polyphosphate were used to demonstrate this methodology. These additives represent a potent solution for imparting flame retardancy to PBT. The resulting lumped-species reaction model consisted of a set of first- and second-order (two-component) reactions that defined the rate of gaseous pyrolyzate production. The heats of reaction, heat capacities of the condensed-phase reactants and products, and heats of combustion of the gaseous products were also determined. The model was shown to reproduce all aforementioned experiments with a high degree of detail. The model also captured changes in the material behavior with changes in the additive concentrations. Second-order reactions between the material constituents were found to be necessary to reproduce these changes successfully. The development of such models is an essential milestone toward the intelligent design of flame retardant materials and solid fuels.
Thermo-Mechanical Characterisations of Flax Fibre and Thermoplastic Resin Composites during Manufacturing
Authors: Xiao Shenglei , Wang Peng , Soulat Damien , Gao Hang
Published: October 2018

The flax fibre reinforced composites with advanced structure, which can be regarded as recyclable parts, are potential and promising materials in the automobile industry. During their manufacturing, the reinforcements or prepregs should be performed to the desired shape beforehand. Mechanical behaviours accordingly play an important role during this process. However, this preforming process is usually under high temperatures, thus, the mechanical behaviours could be modified under this state. Especially for reinforcements produced by flax yarns, has barely been studied. To fill this gap, in this paper the thermos-mechanical characterization of Flax/Polyamide12 (PA12) commingled yarn and prepreg woven fabric is analysed using tensile and in-plane shearing tests under different temperatures and tensile speeds. The results conclusively show that strength can be improved by increasing the temperature below the PA12 melting value on woven fabrics, which is inverse tendency for single yarn. Moreover, increasing tensile speed could increase the strength of the single yarn and fabric. This reveals that the PA12 fluidity has great influence on tensile behaviour. The characterisation results would be employed as prescriptive recommendations in the process of manufacturing flax fibre-reinforced composite parts.
π-Stacked Polymer Consisting of a Pseudo–meta–[2.2]Paracyclophane Skeleton
Authors: Maeda Hazuki , Kameda Mayu , Hatakeyama Takuji , Morisaki Yasuhiro
Published: October 2018

A novel π-stacked polymer based on a pseudo–meta–linked [2.2]paracyclophane moieties was synthesized by Sonogashira-Hagihara coupling. The UV-vis absorption spectra of the synthesized polymer and model compounds revealed an extension of the conjugation length owing to the through-space conjugation. The optical properties of the π-stacked dimer with the pseudo–meta–linked [2.2]paracyclophane unit were compared with those of the corresponding dimers with the pseudo–ortho– and pseudo–para–linked [2.2]paracyclophane units.
Perceptions of Spirituality and Spiritual Care of Health Professionals Working in a State Hospital
Authors: Toker Kerem , Çınar Fadime
Published: October 2018

Background: The determination and fulfillment of the spiritual needs of the individual in times of crisis can be realized by the health care professionals having the knowledge and skills to provide individual-specific care. This research was conducted to determine the perceptions of health professionals about spirituality and spiritual care. Methods: The study of 197 health professionals working in a state hospital was performed. This study is a descriptive study which was conducted between December 2017 and January 2018. Data in the form of an “Introductory Information Form” and “Spirituality and Spiritual Care Grading Scale” was collected. In the analysis of the data, the Mann–Whitney U test, Kruskal–Wallis tests, frequency as percentage, and scale scores as mean and standard deviation were used. Results: It was determined that 45.7% of the health professionals were trained in spiritual care, but that they were unable to meet their patients’ spiritual care needs due to the intensive work environment and personnel insufficiency. The total score averaged by the health professionals on the spirituality and spiritual care grading scales was 52.13 ± 10.13. Conclusions: The findings of the research show that health professionals are inadequate in spiritual care initiatives and that their knowledge levels are not at the desired level. With in-service trainings and efforts to address these deficiencies, spiritual care initiatives can be made part of the recovery process.
Risk of Bankruptcy, Its Determinants and Models
Authors: Horváthová Jarmila , Mokrišová Martina
Published: October 2018

In this paper, the following research problem was addressed: Is DEA (Data Envelopment Analysis) method a suitable alternative to Altman model in predicting the risk of bankruptcy? Based on the above-mentioned research problem, we formulated the aim of the paper: To apply DEA method for predicting the risk of bankruptcy and to compare its results with the results of Altman model. The research problem and the aim of the paper follow the research of authors aimed at the application of methods which are appropriate for measuring business financial health, performance and competitiveness as well as for predicting the risk of bankruptcy. To address the problem, the following methods were applied: financial ratios, Altman model for private non-manufacturing firms and DEA method. When applying DEA method, we formulated input-oriented DEA CCR model. We found that DEA method is an appropriate alternative to Altman model in predicting the risk of possible business bankruptcy. The important conclusion is that DEA allows us to apply not only outputs but also inputs. Since prediction models do not include these indicators, DEA method appears to be the right choice. We recommend, especially for Slovak companies, to apply cost ratio when calculating risk of bankruptcy.
Leaf Area Estimation of Reconstructed Maize Plants Using a Time-of-Flight Camera Based on Different Scan Directions
Authors: Vázquez-Arellano Manuel , Reiser David , Paraforos Dimitrios S. , Garrido-Izard Miguel , Griepentrog Hans W.
Published: October 2018

The leaf area is an important plant parameter for plant status and crop yield. In this paper, a low-cost time-of-flight camera, the Kinect v2, was mounted on a robotic platform to acquire 3-D data of maize plants in a greenhouse. The robotic platform drove through the maize rows and acquired 3-D images that were later registered and stitched. Three different maize row reconstruction approaches were compared: reconstruct a crop row by merging point clouds generated from both sides of the row in both directions, merging point clouds scanned just from one side, and merging point clouds scanned from opposite directions of the row. The resulted point cloud was subsampled and rasterized, the normals were computed and re-oriented with a Fast Marching algorithm. The Poisson surface reconstruction was applied to the point cloud, and new vertices and faces generated by the algorithm were removed. The results showed that the approach of aligning and merging four point clouds per row and two point clouds scanned from the same side generated very similar average mean absolute percentage error of 8.8% and 7.8%, respectively. The worst error resulted from the two point clouds scanned from both sides in opposite directions with 32.3%.
Two New Polarimetric Feature Parameters for the Recognition of the Different Kinds of Buildings in Earthquake-Stricken Areas Based on Entropy and Eigenvalues of PolSAR Decomposition
Authors: Zhai Wei , Huang Chunlin , Pei Wansheng
Published: October 2018

Rapidly and accurately obtaining collapsed building information for earthquake-stricken areas can help to effectively guide the implementation of the emergency response and can reduce disaster losses and casualties. This work is focused on rapid building earthquake damage detection in urban areas using a single post-earthquake polarimetric synthetic aperture radar (PolSAR) image. In an earthquake-stricken area, the buildings include both damaged buildings and undamaged buildings. The undamaged buildings are made up of both parallel buildings, whose array direction is parallel to the flight direction, and oriented buildings, whose array direction is not parallel to the flight direction. The damaged buildings after an earthquake are made up of completely collapsed buildings and residual damaged parallel walls and oriented walls of the damaged buildings. Therefore, we divide the buildings in earthquake-stricken areas into five kinds: intact parallel buildings, damaged parallel walls, collapsed buildings, intact oriented buildings, and damaged oriented walls. The two new polarimetric feature parameters of λ_H and H_λ are proposed to recognize the five kinds of buildings, and the Wishart supervised classification method is employed to further improve the extraction accuracy of the damaged buildings and undamaged buildings.
Desertification Information Extraction Based on Feature Space Combinations on the Mongolian Plateau
Authors: Wei Haishuo , Wang Juanle , Cheng Kai , Li Ge , Ochir Altansukh , Davaasuren Davaadorj , Chonokhuu Sonomdagva
Published: October 2018

The Mongolian plateau is a hotspot of global desertification because it is heavily affected by climate change, and has a large diversity of vegetation cover across various regions and seasons. Within this arid region, it is difficult to distinguish desertified land from other land cover types using low-quality vegetation information. To address this, we analyze both the effects and the applicability of different feature space models for the extraction of desertification information with the goal of finding appropriate approaches to extract desertification data on the Mongolian plateau. First, we used Landsat 8 remote sensing images to invert NDVI (normalized difference vegetation index), MSAVI (modified soil adjusted vegetation index), TGSI (topsoil grain size index), and albedo (land surface albedo) data. Then, we constructed the feature space models of Albedo-NDVI, Albedo-MSAVI, and Albedo-TGSI, and compared their extraction accuracies. Our results show that the overall classification accuracies of the three models were 84.53%, 85.60%, and 88.27%, respectively, indicating that the three feature space models are feasible for extracting information relating to desertification on the Mongolian plateau. Further analysis indicates that the Albedo-NDVI model is suitable for areas with a high vegetation cover or a high forest ratio, whilst the Albedo-MSAVI model is suitable for areas with relatively low vegetation cover, and the Albedo-TGSI model is suitable for areas with extremely low vegetation cover, including the widely distributed Gobi Desert and other barren areas. This study provides a technical selection reference for the investigation of desertification of different zones on the Mongolian plateau.
A National Assessment of Wetland Status and Trends for Canada’s Forested Ecosystems Using 33 Years of Earth Observation Satellite Data
Authors: Wulder Michael A. , Li Zhan , Campbell Elizabeth M. , White Joanne C. , Hobart Geordie , Hermosilla Txomin , Coops Nicholas C.
Published: October 2018

Wetlands are important globally for supplying clean water and unique habitat, and for storing vast amounts of carbon and nutrients. The geographic extent and state of wetlands vary over time and represent a dynamic land condition rather than a permanent land cover state. Herein, we combined a time series of land cover maps derived from Landsat data at 30-m resolution to inform on spatial and temporal changes to non-treed and treed wetland extents over Canada’s forested ecosystems (>650 million ha) from 1984 to 2016. Overall, for the period, 1984 to 2016, we found the extent of wetlands (non-treed and treed combined) in Canada’s forested ecosystems to be stable, with some regional variability, often resulting from offsetting decreases and increases within a given ecozone. Notwithstanding difficulties in using optical satellite data for mapping a land condition, by accumulating wetland evidence via earth observations consistently through multiple decades, our results capture the trends in wetland cover over a previously unmapped, national extent at a level of spatial detail and temporal reach suitable for further focused interpretations of wetlands and drivers and projections of wetland dynamics.
A Volume Measurement Method for Lunar Soil Collection Based on a Single Monitoring Camera
Authors: Ding Shaowen , Zhang Xiaohu , Yu Qifeng , Li Lichun , Wang Jie
Published: October 2018

In the task of lunar soil collection, estimating the volume of the collected soil is an important part of the sampling control of the lander. Due to the design constraints of the lander, there is no additional installation position for volume measurement equipment. To fully use the sensors already installed, a collected soil volume measurement method is designed in this paper based only on a single monitoring camera. This method uses a sequence of images of the collection area captured by the camera mounted on the acquisition arm to accurately reconstruct the terrain of the collection area surface before and after soil acquisition. Additionally, bi-temporal dense point clouds are reconstructed. Based on the area of change associated with soil collection, the constructed dense point clouds are compared according to the topographic characteristics of the area to estimate the volume of soil collected. Experiments show that the method is stable and reliable and can meet the requirements of actual measurement tasks.
Effects of an Integrated Neurofeedback System with Dry Electrodes: EEG Acquisition and Cognition Assessment
Authors: Pei Guangying , Wu Jinglong , Chen Duanduan , Guo Guoxin , Liu Shuozhen , Hong Mingxuan , Yan Tianyi
Published: October 2018

Electroencephalogram (EEG) neurofeedback improves cognitive capacity and behaviors by regulating brain activity, which can lead to cognitive enhancement in healthy people and better rehabilitation in patients. The increased use of EEG neurofeedback highlights the urgent need to reduce the discomfort and preparation time and increase the stability and simplicity of the system’s operation. Based on brain-computer interface technology and a multithreading design, we describe a neurofeedback system with an integrated design that incorporates wearable, multichannel, dry electrode EEG acquisition equipment and cognitive function assessment. Then, we evaluated the effectiveness of the system in a single-blind control experiment in healthy people, who increased the alpha frequency band power in a neurofeedback protocol. We found that upregulation of the alpha power density improved working memory following short-term training (only five training sessions in a week), while the attention network regulation may be related to other frequency band activities, such as theta and beta. Our integrated system will be an effective neurofeedback training and cognitive function assessment system for personal and clinical use.
A Combinatorial Solution to Point Symbol Recognition
Authors: Quan Yining , Shi Yuanyuan , Miao Qiguang , Qi Yutao
Published: October 2018

Recent work has shown that recognizing point symbols is an essential task in the field of map digitization. For the identification of symbols, it is generally necessary to compare the symbols with a specific criterion and find the most similar one with each known symbol one by one. Most of the works can only identify a single symbol, a small number of works are to deal with multiple symbols simultaneously with a low recognition accuracy. Given the two deficiencies, this paper proposes a deep transfer learning architecture, where the task is to learn a symbol classifier with AlexNet. For the insufficient dataset, we develop a method for transfer learning that uses a MNIST dataset to pretrain the model, which makes up for the problem of small training dataset and enhances the generalization of the model. Before the recognition process, preprocessing the point symbols in the map to coarse screening out the areas suspected of point symbols. We show a significant improvement over using point symbol images to keep a high performance in being able to deal with many more categories of symbols simultaneously.
An On-Line Low-Cost Irradiance Monitoring Network with Sub-Second Sampling Adapted to Small-Scale PV Systems
Authors: Espinosa-Gavira Manuel Jesús , Agüera-Pérez Agustín , González de la Rosa Juan José , Palomares-Salas José Carlos , Sierra-Fernández José María
Published: October 2018

Very short-term solar forecasts are gaining interest for their application on real-time control of photovoltaic systems. These forecasts are intimately related to the cloud motion that produce variations of the irradiance field on scales of seconds and meters, thus particularly impacting in small photovoltaic systems. Very short-term forecast models must be supported by updated information of the local irradiance field, and solar sensor networks are positioning as the more direct way to obtain these data. The development of solar sensor networks adapted to small-scale systems as microgrids is subject to specific requirements: high updating frequency, high density of measurement points and low investment. This paper proposes a wireless sensor network able to provide snapshots of the irradiance field with an updating frequency of 2 Hz. The network comprised 16 motes regularly distributed over an area of 15 m × 15 m (4 motes × 4 motes, minimum intersensor distance of 5 m). The irradiance values were estimated from illuminance measurements acquired by lux-meters in the network motes. The estimated irradiances were validated with measurements of a secondary standard pyranometer obtaining a mean absolute error of 24.4 W/m 2 and a standard deviation of 36.1 W/m 2 . The network was able to capture the cloud motion and the main features of the irradiance field even with the reduced dimensions of the monitoring area. These results and the low-cost of the measurement devices indicate that this concept of solar sensor networks would be appropriate not only for photovoltaic plants in the range of MW, but also for smaller systems such as the ones installed in microgrids.
Dynamic Neural Network Modelling of Soil Moisture Content for Predictive Irrigation Scheduling
Authors: Adeyemi Olutobi , Grove Ivan , Peets Sven , Domun Yuvraj , Norton Tomas
Published: October 2018

Sustainable freshwater management is underpinned by technologies which improve the efficiency of agricultural irrigation systems. Irrigation scheduling has the potential to incorporate real-time feedback from soil moisture and climatic sensors. However, for robust closed-loop decision support, models of the soil moisture dynamics are essential in order to predict crop water needs while adapting to external perturbation and disturbances. This paper presents a Dynamic Neural Network approach for modelling of the temporal soil moisture fluxes. The models are trained to generate a one-day-ahead prediction of the volumetric soil moisture content based on past soil moisture, precipitation, and climatic measurements. Using field data from three sites, a R 2 value above 0.94 was obtained during model evaluation in all sites. The models were also able to generate robust soil moisture predictions for independent sites which were not used in training the models. The application of the Dynamic Neural Network models in a predictive irrigation scheduling system was demonstrated using AQUACROP simulations of the potato-growing season. The predictive irrigation scheduling system was evaluated against a rule-based system that applies irrigation based on predefined thresholds. Results indicate that the predictive system achieves a water saving ranging between 20 and 46% while realizing a yield and water use efficiency similar to that of the rule-based system.
A Service-Constrained Positioning Strategy for an Autonomous Fleet of Airborne Base Stations
Authors: José-Torra Ferran , Pascual-Iserte Antonio , Vidal Josep
Published: October 2018

This paper proposes a positioning strategy for a fleet of unmanned aerial vehicles (UAVs) airlifting wireless base stations driven by communication constraints. First, two schedulers that model the distribution of resources among users within a single cell are analyzed. Then, an UAV autonomous positioning strategy is developed, based on a fair distribution of the radio resources among all the users of all the cells in a given scenario, in such a way that the user bitrate is the same regardless the users’ distribution and spatial density. Moreover, two realistic constraints are added related to capacity of the backhaul link among the UAVs and the ground station: the bitrate delivered per UAV and the total backhaul bandwidth shared among all the UAVs. Additionally, an energy consumption model is considered to evaluate the efficiency and viability of the proposed strategy. Finally, numerical results in different scenarios are provided to assess both the schedulers performance and the proposed coordinated positioning strategy for the UAVs.
Ultrafast and Energy-saving Synthesis of Nitrogen and Chlorine Co-doped Carbon Nanodots via Neutralization Heat for Selective Detection of Cr(VI) in Aqueous Phase
Authors: Hu Qin , Li Tao , Gao Lu , Gong Xiaojuan , Rao Shengqi , Fang Weiming , Gu Ruixia , Yang Zhenquan
Published: October 2018

In this work, it is presented for the first time that nitrogen and chlorine co-doped carbon nanodots (N,Cl-CDs) were synthesized by simply mixing glucose, concentrated hydrochloric acid (HCl), and 1,2-ethylenediamine (EDA). No external heat was employed; the neutralization reaction served as the heat source. The glucose served as the carbon source while EDA and HCl were the N and Cl dopants, respectively. The fluorescence of N,Cl-CDs was adequately quenched by hexavalent chromium Cr(VI) based on a combination of dynamic quenching and inner filter effect (IFE). Accordingly, an efficient N,Cl-CDs-based fluorescence probe was established for sensitive and selective detection of Cr(VI). The proposed fluorescence sensor provides a linear recognition range for Cr(VI) determination from 3 to 40 µM with a limit of detection (LOD) of 0.28 µM (14.6 µg/L). The proposed fluorescence method was successfully utilized to detect Cr(VI) in different water samples with satisfactory results. The spike recoveries vary from 97.01% to 103.89% with relative standard deviations (RSDs) of less than 0.82%. This work highlights the development of a simple, ultrafast, and energy-saving one-step synthetic route to fabricate N,Cl-CDs for highly selective and sensitive detection of Cr(VI) in real water samples. It is anticipated that the proposed fluorescence method could be further explored and widely used for Cr(VI) detection in the environmental industry.
Fast Signals of Opportunity Fingerprint Database Maintenance with Autonomous Unmanned Ground Vehicle for Indoor Positioning
Authors: Peng Yitang , Niu Xiaoji , Tang Jian , Mao Dazhi , Qian Chuang
Published: October 2018

Indoor positioning technology based on Received Signal Strength Indicator (RSSI) fingerprints is a potential navigation solution, which has the advantages of simple implementation, low cost and high precision. However, as the radio frequency signals can be easily affected by the environmental change during its transmission, it is quite necessary to build location fingerprint database in advance and update it frequently, thereby guaranteeing the positioning accuracy. At present, the fingerprint database building methods mainly include point collection and line acquisition, both of which are usually labor-intensive and time consuming, especially in a large map area. This paper proposes a fast and efficient location fingerprint database construction and updating method based on a self-developed Unmanned Ground Vehicle (UGV) platform NAVIS, called Automatic Robot Line Collection. A smartphone was installed on NAVIS for collecting indoor Received Signal Strength Indicator (RSSI) fingerprints of Signals of Opportunity (SOP), such as Bluetooth and Wi-Fi. Meanwhile, indoor map was created by 2D LiDAR-based Simultaneous Localization and Mapping (SLAM) technology. The UGV automatically traverse the unknown indoor environment due to a pre-designed full-coverage path planning algorithm. Then, SOP sensors collect location fingerprints and generates grid map during the process of environment-traversing. Finally, location fingerprint database is built or updated by Kriging interpolation. Field tests were carried out to verify the effectiveness and efficiency of our proposed method. The results showed that, compared with the traditional point collection and line collection schemes, the root mean square error of the fingerprinting-based positioning results were reduced by 35.9% and 25.0% in static tests and 30.0% and 21.3% respectively in dynamic tests. Moreover, our UGV can traverse the indoor environment autonomously without human-labor on data acquisition, the efficiency of the automatic robot line collection scheme is 2.65 times and 1.72 times that of the traditional point collection and the traditional line acquisition, respectively.
Using the Pulse Contour Method to Measure the Changes in Stroke Volume during a Passive Leg Raising Test
Authors: Su Chun-Hung , Liu Shing-Hong , Tan Tan-Hsu , Lo Chien-Hsien
Published: October 2018

The pulse contour method is often used with the Windkessel model to measure stroke volume. We used a digital pressure and flow sensors to detect the parameters of the Windkessel model from the pulse waveform. The objective of this study was to assess the stability and accuracy of this method by making use of the passive leg raising test. We studied 24 healthy subjects (40 ± 9.3 years), and used the Medis® CS 1000, an impedance cardiography, as the comparing reference. The pulse contour method measured the waveform of the brachial artery by using a cuff. The compliance and resistance of the peripheral artery was detected from the cuff characteristics and the blood pressure waveform. Then, according to the method proposed by Romano et al., the stroke volume could be measured. This method was implemented in our designed blood pressure monitor. A passive leg raising test, which could immediately change the preloading of the heart, was done to certify the performance of our method. The pulse contour method and impedance cardiography simultaneously measured the stroke volume. The measurement of the changes in stroke volume using the pulse contour method had a very high correlation with the Medis® CS 1000 measurement, the correlation coefficient of the changed ratio and changed differences in stroke volume were r2 = 0.712 and r2 = 0.709, respectively. It was shown that the stroke volume measured by using the pulse contour method was not accurate enough. But, the changes in the stroke volume could be accurately measured with this pulse contour method. Changes in stroke volume are often used to understand the conditions of cardiac preloading in the clinical field. Moreover, the operation of the pulse contour method is easier than using impedance cardiography and echocardiography. Thus, this method is suitable to use in different healthcare fields.
Clutter Elimination and Random-Noise Denoising of GPR Signals Using an SVD Method Based on the Hankel Matrix in the Local Frequency Domain
Authors: Bi Wenda , Zhao Yonghui , An Cong , Hu Shufan
Published: October 2018

Ground-penetrating radar (GPR) is a kind of high-frequency electromagnetic detection technology. It is mainly used to locate targets and interfaces in underground structures. In addition to the effective signals reflected from the subsurface objects or interfaces, the GPR signals in field work also include noise and different clutters, such as antenna-coupled waves, ground clutters, and radio-frequency interference, which have similar wavelet spectral characteristics with the target signals. Clutter and noise seriously interfere with the target’s response signal. The singular value decomposition (SVD) filtering method can select appropriate singular values and characteristic components corresponding to the effective signals for signal reconstruction to filter the GPR data. However, the conventional time-domain SVD method introduces fake signals when eliminating direct waves, and does not have good suppression of random noise around non-horizontal phase axes. Here, an SVD method based on the Hankel matrix in the local frequency domain of GPR data is proposed. Different numerical models and real field GPR data were handled using the proposed method. Based on the power of fake signals introduced via different processes, qualitative and quantitative analyses were carried out. The comparison shows that the newly proposed method could improve efforts to suppress random noise around non-horizontal phase reflection events and weaken the horizontal fake signals introduced by eliminating clutter such as ground waves.
HCV Detection, Discrimination, and Genotyping Technologies
Authors: Warkad Shrikant Dashrath , Nimse Satish Balasaheb , Song Keum-Soo , Kim Taisun
Published: October 2018

According to the World Health Organization (WHO), 71 million people were living with Hepatitis C virus (HCV) infection worldwide in 2015. Each year, about 399,000 HCV-infected people succumb to cirrhosis, hepatocellular carcinoma, and liver failure. Therefore, screening of HCV infection with simple, rapid, but highly sensitive and specific methods can help to curb the global burden on HCV healthcare. Apart from the determination of viral load/viral clearance, the identification of specific HCV genotype is also critical for successful treatment of hepatitis C. This critical review focuses on the technologies used for the detection, discrimination, and genotyping of HCV in clinical samples. This article also focuses on advantages and disadvantages of the reported methods used for HCV detection, quantification, and genotyping.
Acetone Sensing Properties and Mechanism of SnO2 Thick-Films
Authors: Chen Yanping , Qin Hongwei , Cao Yue , Zhang Heng , Hu Jifan
Published: October 2018

In the present work, we investigated the acetone sensing characteristics and mechanism of SnO2 thick-films through experiments and DFT calculations. SnO2 thick film annealed at 600 °C could sensitively detect acetone vapors. At the optimum operating temperature of 180 °C, the responses of the SnO2 sensor were 3.33, 3.94, 5.04, and 7.27 for 1, 3, 5, and 10 ppm acetone, respectively. The DFT calculation results show that the acetone molecule can be adsorbed on the five-fold-coordinated Sn and oxygen vacancy (VO) sites with O-down, with electrons transferring from acetone to the SnO2 (110) surface. The acetone molecule acts as a donor in these modes, which can explain why the resistance of SnO2 or n-type metal oxides decreased after the acetone molecules were introduced into the system. Molecular dynamics calculations show that acetone does not convert to other products during the simulation.
Discrimination of Malus Taxa with Different Scent Intensities Using Electronic Nose and Gas Chromatography–Mass Spectrometry
Authors: Fan Junjun , Zhang Wangxiang , Zhou Ting , Zhang Dandan , Zhang Donglin , Zhang Long , Wang Guibin , Cao Fuliang
Published: October 2018

Floral scent is important in plant reproduction and also has aesthetic implications. However, the accurate determination of aroma is presently limited by the available collection and analysis tools. In this study, the floral scents of four crabapple taxa exhibiting faint, weak, clear, and strong scent intensities were comparatively analyzed by electronic nose (E-nose) and gas chromatography–mass spectrometry (GC–MS). The E-nose was able to effectively group the different taxa in the principal component analysis in correspondence with scent intensity. GC–MS analysis identified a total of 60 volatile compounds. The content of nitrogen-containing compounds and aliphatics and the number of unique components of the more aromatic taxa was significantly higher than the less aromatic taxa. α-Cedrene, β-cedrene, 5-methyl-1,3-dihydro-2H-benzimidazol-2-one, benzyl alcohol, linalool, and 4-pyrrolidinopyridine contributed significantly to taxon separation. The pattern recognition results confirmed that the E-nose results corroborated the GC–MS results. Furthermore, partial least squares regression analysis between the aromatic constituents and sensors indicated that particular sensors were highly sensitive to N-containing compounds, aliphatics, and terpenes. In conclusion, the E-nose is capable of discriminating crabapple taxa of different scent intensities in both a qualitative and quantitative respect, presenting a rapid and accurate reference approach for future applications.
The Improved Image Scrambling Algorithm for the Wireless Image Transmission Systems of UAVs
Authors: Dong Jie , Wu Guowei , Yang Tingting , Li Yangyang
Published: October 2018

With the deepening of modern military reforms, information has become the key to winning modern warfare. The use of unmanned aerial vehicle (UAV) to capture image information has become an important means of reconnaissance in modern warfare and plays an irreplaceable role. The image information usually uses a wireless image transmission system, since image information is intercepted or stolen easily during the information transmission, encrypting an image is a common method for ensuring image security. However, traditional encryption algorithms have some deficiencies in terms of efficiency and security. In order to overcome these shortcomings, a new algorithm is proposed in this paper-an improved image scrambling encryption algorithm based on Fibonacci-p coding. The first new idea of the algorithm is to separate the positive and negative signs and data of the scrambled DCT coefficients, then form the symbol matrix and the data matrix respectively, perform the scrambling encryption operation on the symbol matrix. The second new idea is to encrypt the color RGB image by converting the R, G, and B colors into Y, Cb, and Cr, and converting the normal image operation into operations on Y, Cb, and Cr, thereby implementing the encryption operation. The comprehensive performance of the algorithm is optimal with different image information. Experiments results validate the favorable performance of the proposed improved encryption algorithm.