bluuebunny/crossref_metadata_2025 huggingface dataset:
Combined Longitudinal Effect of Physical Activity and Screen Time on Food and Beverage Consumption in European Preschool Children: The ToyBox-Study
Authors: Miguel-Berges María , Santaliestra-Pasias Alba , Mouratidou Theodora , De Miguel-Etayo Pilar , Androutsos Odysseas , De Craemer Marieke , Galcheva Sonya , Koletzko Berthold , Kulaga Zbigniew , Manios Yannis , Moreno Luis , group on behalf of the ToyBox-study
Published: May 2019

Lifestyle behavioral habits such as excess screen time (ST), a lack of physical activity (PA), and high energy-dense food consumption are associated with an increased risk of children being overweight or obese. This study aimed to (1) track longitudinal adherence to PA and ST recommendations at baseline (T0) and follow-up (T1) and (2) assess the association between changes in adherence to PA and ST recommendations and food and beverage consumption at follow-up. The present study included 2321 preschool children (3.5 to 6) participating in the multicenter ToyBox-study. A lineal mixed effects model was used to examine the association between different types of food and beverages and their relationship with changes in adherence to PA and ST recommendations. Approximately half of the children (50.4%) did not meet the PA and ST recommendations at both baseline and follow-up. However, only 0.6% of the sample met both PA and ST recommendations. Preschool children who met both recommendations consumed fewer fizzy drinks, juices, sweets, desserts, and salty snacks and consumed more water, fruits and vegetables, and dairy products than did those not meeting both recommendations. In conclusion, the proportion of European preschool children adhering to both PA and ST recommendations was very low and was associated with a low consumption of energy-dense foods.
A Scoring System for Identifying Patients Likely to Be Diagnosed with Low-Grade Coeliac Enteropathy
Authors: Fernández-Bañares Fernando , Carrasco Anna , Rosinach Mercè , Arau Beatriz , García-Puig Roger , González Clarisa , Tristán Eva , Zabana Yamile , Esteve Maria
Published: May 2019

Background & Aims: Determining whether patients with lymphocytic enteritis (LE) have coeliac disease is a challenge. We analysed the variables associated with a low-grade coeliac enteropathy diagnosis in patients with suspected coeliac disease but without villous atrophy, and developed a scoring system to identify them. Methods: We collected data from 2010 through to 2016 on patients with lymphocytic enteritis and persistent symptoms compatible with the clinical spectrum of coeliac disease. One hundred and four patients starting on a gluten-free diet (GFD) were included. Duodenal biopsies were collected before the GFD and analysed for numbers of CD3+ T-cell receptor gamma delta+ (TCRγδ+), and CD3− intraepithelial lymphocytes. We performed a logistic regression analysis to identify factors associated with a low-grade coeliac enteropathy diagnosis. Results: Sixty-two patients achieved clinical remission after the GFD. Fifty of these 62 patients were diagnosed with low-grade coeliac enteropathy. Multivariate analysis identified the presence of >25% intraepithelial lymphocytosis, HLA-DQ2.5, positive serology, and increased numbers of TCRγδ+ cells with a low-grade coeliac enteropathy diagnosis. We developed a scoring system that identified patients with an area under the ROC curve (AUC) of 0.91. Scores of >10 had 86% sensitivity and 85% specificity. Conclusion: We developed a scoring system that identifies patients likely to be diagnosed with low-grade coeliac enteropathy with an AUC value of 0.91.
Dietary Patterns Are Related to Clinical Characteristics in Memory Clinic Patients with Subjective Cognitive Decline: The SCIENCe Project
Authors: Wesselman Linda M. P. , Doorduijn Astrid S. , de Leeuw Francisca A. , Verfaillie Sander C. J. , van Leeuwenstijn-Koopman Mardou , Slot Rosalinde E. R. , Kester Maartje I. , Prins Niels D. , van de Rest Ondine , de van der Schueren Marian A. E. , Scheltens Philip , Sikkes Sietske A. M. , van der Flier Wiesje M.
Published: May 2019

As nutrition is one of the modifiable risk factors for cognitive decline, we studied the relationship between dietary quality and clinical characteristics in cognitively normal individuals with subjective cognitive decline (SCD). We included 165 SCD subjects (age: 64 ± 8 years; 45% female) from the SCIENCe project, a prospective memory clinic based cohort study on SCD. The Dutch Healthy Diet Food Frequency Questionnaire (DHD-FFQ) was used to assess adherence to Dutch guidelines on vegetable, fruit, fibers, fish, saturated fat, trans fatty acids, salt and alcohol intake (item score 0–10, higher score indicating better adherence). We measured global cognition (Mini Mental State Examination), cognitive complaints (Cognitive Change Index self-report; CCI) and depressive symptoms (Center for Epidemiologic Studies Depression Scale; CES-D). Using principal component analysis, we identified dietary components and investigated their relation to clinical characteristics using linear regression models adjusted for age, sex and education. We identified three dietary patterns: (i) “low-Fat-low-Salt”, (ii) “high-Veggy”, and (iii) “low-Alcohol-low-Fish”. Individuals with lower adherence on “low-Fat-low-Salt” had more depressive symptoms (β −0.18 (−2.27–−0.16)). Higher adherence to “high-Veggy” was associated with higher MMSE scores (β 0.30 (0.21–0.64)). No associations were found with the low-Alcohol-low-Fish component. We showed that in SCD subjects, dietary quality was related to clinically relevant outcomes. These findings could be useful to identify individuals that might benefit most from nutritional prevention strategies to optimize brain health.
Influence of Vitamin D Deficiency on Inflammatory Markers and Clinical Disease Activity in IBD Patients
Authors: López-Muñoz Pedro , Beltrán Belén , Sáez-González Esteban , Alba Amparo , Nos Pilar , Iborra Marisa
Published: May 2019

Vitamin D has recently been discovered to be a potential immune modulator. Low serum vitamin D levels have been associated with risk of relapse and exacerbation of clinical outcomes in Crohn’s disease (CD) and ulcerative colitis (UC). A retrospective, longitudinal study was conducted to determine the association between vitamin D levels and inflammatory markers and clinical disease activity in inflammatory bowel disease (IBD). In addition, circulating 25(OH)D3 progression was evaluated according to vitamin D supplementation. Participants were separated into three groups according to their vitamin D level: severe deficiency (SD), moderate deficiency (MD) and sufficiency (S). Serum 25(OH)D3 was inversely correlated with faecal calprotectin (FC) for CD and UC but was only correlated with C-reactive protein (CRP) for UC patients. In the multivariate analysis of FC, CRP and fibrinogen (FBG), we predicted the presence of a patient in the SD group with 80% accuracy. A deficiency of 25(OH)D3 was associated with increased hospitalisations, flare-ups, the use of steroids and escalating treatment. Supplemental doses of vitamin D were likely to be insufficient to reach adequate serum levels of 25(OH)D3. Vitamin D intervention studies are warranted to determine whether giving higher doses of vitamin D in IBD might reduce intestinal inflammation or disease activity.
Clotrimazole-Loaded Mediterranean Essential Oils NLC: A Synergic Treatment of Candida Skin Infections
Authors: Carbone Claudia , Teixeira Maria do Céu , Sousa Maria do Céu , Martins-Gomes Carlos , Silva Amelia M. , Souto Eliana Maria Barbosa , Musumeci Teresa
Published: May 2019

The increasing development of resistance of Candida species to traditional drugs represents a great challenge to the medical field for the treatment of skin infections. Essential oils were recently proposed to increase drug effectiveness. Herein, we developed and optimized (23 full factorial design) Mediterranean essential oil (Rosmarinus officinalis, Lavandula x intermedia “Sumian”, Origanum vulgare subsp. hirtum) lipid nanoparticles for clotrimazole delivery, exploring the potential synergistic effects against Candida spp. Small sized nanoparticles (<100 nm) with a very broad size distribution (PDI < 0.15) and long-term stability were successfully prepared. Results of the in vitro biosafety on HaCaT (normal cell line) and A431 (tumoral cell line), allowed us to select Lavandula and Rosmarinus as anti-proliferative agents with the potential to be used as co-adjuvants in the treatment of non-tumoral proliferative dermal diseases. Results of calorimetric studies on biomembrane models, confirmed the potential antimicrobial activity of the selected oils due to their interaction with membrane permeabilization. Nanoparticles provided a prolonged in vitro release of clotrimazole. In vitro studies against Candida albicans, Candida krusei and Candida parapsilosis, showed an increase of the antifungal activity of clotrimazole-loaded nanoparticles prepared with Lavandula or Rosmarinus, thus confirming nanostructured lipid carriers (NLC) containing Mediterranean essential oils represent a promising strategy to improve drug effectiveness against topical candidiasis.
Characterization and Formulation of Isoniazid for High-Dose Dry Powder Inhalation
Authors: Sibum Imco , Hagedoorn Paul , Frijlink Henderik W. , Grasmeijer Floris
Published: May 2019

Tuberculosis is a major health problem and remains one of the main causes of mortality. In recent years, there has been an increased interest in the pulmonary delivery of antibiotics to treat tuberculosis. Isoniazid is one of these antibiotics. In this study, we aimed to characterize isoniazid and formulate it into a dry powder for pulmonary administration with little or no excipient, and for use in the disposable Twincer® inhaler. Isoniazid was jet milled and spray dried with and without the excipient l-leucine. Physiochemical characterization showed that isoniazid has a low Tg of −3.99 ± 0.18 °C and starts to sublimate around 80 °C. Milling isoniazid with and without excipients did not result in a suitable formulation, as it resulted in a low and highly variable fine particle fraction. Spray drying pure isoniazid resulted in particles too large for pulmonary administration. The addition of 5% l-leucine resulted in a fraction <5 µm = 89.61% ± 1.77% from spray drying, which dispersed well from the Twincer®. However, storage stability was poor at higher relative humidity, which likely results from dissolution-crystallization. Therefore, follow up research is needed to further optimize this spray dried formulation.
Analysis of Disposed Unused Medications at a Village Community Pharmacy
Authors: Vella Valerie , West Lorna-Marie
Published: May 2019

Background: The aim of this study was to determine the type, quantity, and cost of medications being disposed of by clients in a specifically-set pharmaceutical disposal bin at a village community pharmacy. Methods: Medicines placed in a medication disposal bin by clients were examined during a nine-month period from April to December 2018. The data recorded included the active ingredient, trade name, dose, dosage form, disposed quantity, and the actual expiry date on the pack. The medications were classified according to ATC (Anatomical Therapeutic Chemical Classification System) code, and the cost of the amount wasted was calculated using the pharmacy’s price list. Descriptive statistics were used to analyze the data. Results: A total of 411 medications were collected, amounting to a total cost of approximately €2600. The largest group of medications belonged to the alimentary group, and this also represented the group with the highest monetary value. The number of months that medicinal products were retained by patients beyond the expiry date ranged from 1 to 232. Conclusion: This small study provides a glimpse of what clients dispose of in a medication bin when this is readily available in their community pharmacy, a simple measure which, if adopted on a national level, could aid in ensuring the appropriate disposal of wasted medication.
Efficient Hydrophobic Modification of Old Newspaper and Its Application in Paper Fiber Reinforced Composites
Authors: Zhang Weiwei , Gu Jin , Tu Dengyun , Guan Litao , Hu Chuanshuang
Published: May 2019

Paper fibers have gained broad attention in natural fiber reinforced composites in recent years. The specific problem in preparing paper fiber reinforced composites is that paper fibers easily become flocculent after pulverization, which increases difficulties during melt-compounding with polymer matrix and results in non-uniform dispersion of paper fibers in the matrix. In this study, old newspaper (ONP) was treated with a low dosage of gaseous methyltrichlorosilane (MTCS) to solve the flocculation. The modified ONP fibers were characterized by Scanning Electron Microscope (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and Thermogravimetric Analysis (TG). Then the modified ONP fibers and high-density polyethylene (HDPE) were extruded and pelletized to prepare ONP/HDPE composites via injection molding. Maleic anhydride-grafted polyethylene (MAPE) was added to enhance the interfacial bonding performance with the ultimate purpose of improving the mechanical strength of the composites. The mechanical properties such as tensile, flexural, and impact strength and the water absorption properties of the composite were tested. The results showed that the formation of hydrogen bonding between ONP fibers was effectively prevented after MTCS treatment due to the reduction of exposed –OH groups at the fiber surface. Excessive dosage of MTCS led to severe fiber degradation and dramatically reduced the aspect ratio of ONP fibers. Composites prepared with ONP fibers modified with 4% (v/w) MTCS showed the best mechanical properties due to reduced polarity between the fibers and the matrix, and the relatively long aspect ratio of treated ONP fibers. The composite with or without MAPE showed satisfactory water resistance properties. MTCS was proven to be a cheap and efficient way to pretreat old newspaper for preparing paper fiber reinforced composites.
Facile Preparation of EVOH-Based Amphoteric Ion Exchange Membrane Using Radiation Grafting Technique: A Preliminary Investigation on Its Application for Vanadium Redox Flow Battery
Authors: Xie Kangjun , Dong Zhen , Wang Yicheng , Qi Wei , Zhai Maolin , Zhao Long
Published: May 2019

A novel amphoteric ion exchange membrane (AIEM) was successfully prepared by one-step radiation grafting of sodium styrene sulfonate (SSS) and dimethylaminoethyl methacrylate (DMAEMA) onto ethylene-vinylalcohol copolymer (EVOH) powder and sequent transferring into film by casting method. Fourier transform infrared spectrometry (FT-IR), thermal gravimetric analyzer (TGA) and elemental analysis testified SSS and DMAEMA were successfully grafted onto EVOH. The ion exchange capacity, water uptake and proton conductivity of the resulting AIEM increased with grafting yield (GY). At the GY of 40.9%, the permeability of vanadium ions of AIEM was 3.98 × 10−7 cm2 min−1, which was better than Nafion117 membrane. Furthermore, the cost of this AIEM is much lower than that of Nafion117 membrane. This work provided a low cost and simple method for fabrication of the ion exchange membrane for vanadium redox flow battery (VRFB). Meanwhile, it also provided a new direction for the application of EVOH.
Comparative Analysis of Fluorinated Anions for Polypyrrole Linear Actuator Electrolytes
Authors: Khuyen Nguyen Quang , Zondaka Zane , Harjo Madis , Torop Janno , Tamm Tarmo , Kiefer Rudolf
Published: May 2019

Either as salts or room temperature ionic liquids, fluorinated anion-based electrolytes have been a common choice for ionic electroactive polymer actuators, both linear and bending. In the present work, propylene carbonate solutions of four electrolytes of the three hugely popular anions—triflouromethanesulfonate, bis(trifluoromethane)sulfonimide, and hexafluorophosphate were compared and evaluated in polypyrrole linear actuators. The actuation direction, the characteristics—performance relations influence the behavior of the actuators. Isotonic Electro-chemo-mechanical deformation (ECMD) measurements were performed to study the response of the PPy/DBS samples. The highest strain for pristine PPy/DBS linear actuators was found in range of 21% for LiTFSI, while TBAPF6 had the least cation involvement, suggesting the potential for application in durable and controllable actuators. Interesting cation effects on the actuation of the same anions (CF3SO3−) were also observed.
Quantitative Evaluation of Ultrasound-Assisted Extraction of 1,3-β-glucans from Dictyophora indusiata Using an Improved Fluorometric Assay
Authors: Fu Yuan , Lin Shang , Lu Min , Wei Si-Yu , Zhou Jia , Zhao Li , Zhang Qing , Lin De-Rong , Liu Yun-Tao , Chen Hong , Qin Wen , Wu Ding-Tao
Published: May 2019

In the present study, an improved fluorometric assay based on aniline blue dye for the specific, accurate, and rapid quantification of 1,3-β-glucans in edible mushrooms was developed and fully validated. Furthermore, the improved method was successfully applied for the quantitative evaluation of water soluble 1,3-β-glucans extracted from Dictyophora indusiata by ultrasound-assisted extraction (UAE) with response surface methodology. Results showed that the improved method exhibited high specificity, accuracy, precision, repeatability, and stability, as well as a wide calibration range of 10–600 µg/mL (R2 > 99.9%). The maximum extraction yields of water soluble 1,3-β-glucans (1.20%) and total polysaccharides (5.41%) were achieved at the optimized extraction parameters as follows: ultrasound amplitude (56%), ultrasound extraction time (15 min), and ratio of liquid to raw material (22 mL/g). The results suggest that the improved fluorometric assay has great potential to be used as a routine method for the quantitative evaluation of 1,3-β-glucans in edible mushrooms and that the UAE method is effective for the extraction of 1,3-β-glucans from edible mushrooms.
Surface Modification of Cellulose Nanocrystals with Succinic Anhydride
Authors: Leszczyńska Agnieszka , Radzik Paulina , Szefer Ewa , Mičušík Matej , Omastová Mária , Pielichowski Krzysztof
Published: May 2019

The surface modification of cellulose nanocrystals (CNC) is a key intermediate step in the development of new functionalities and the tailoring of nanomaterial properties for specific applications. In the area of polymeric nanocomposites, apart from good interfacial adhesion, the high thermal stability of cellulose nanomaterial is vitally required for the stable processing and improvement of material properties. In this respect, the heterogeneous esterification of CNC with succinic anhydride was investigated in this work in order to obtain CNC with optimised surface and thermal properties. The influence of reaction parameters, such as time, temperature, and molar ratio of reagents, on the structure, morphology and thermal properties, were systematically studied over a wide range of values by DLS, FTIR, XPS, WAXD, SEM and TGA methods. It was found that the degree of surface substitution of CNC increased with the molar ratio of succinic anhydride to cellulose hydroxyl groups (SA:OH), as well as the reaction time, whilst the temperature of reaction showed a moderate effect on the degree of esterification in the range of 70–110 °C. The studies on the thermal stability of modified nanoparticles indicated that there is a critical extent of surface esterification below which only a slight decrease of the initial temperature of degradation was observed in pyrolytic and oxidative atmospheres. A significant reduction of CNC thermal stability was observed only for the longest reaction time (240 min) and the highest molar ratio of SA:OH. This illustrates the possibility of manufacturing thermally stable, succinylated, CNC by controlling the reaction conditions and the degree of esterification.
Co3O4/g-C3N4 Hybrids for Gas-Phase Hg0 Removal at Low Temperature
Authors: Zhang Zhen , Wu Jiang , Liu Dongjing
Published: May 2019

The Co3O4/g-C3N4 hybrids are constructed via the incipient wetness impregnation method by depositing Co3O4 onto the exterior of g-C3N4, and then employed for Hg0 capture within 60–240 °C. The results show that the Co3O4/g-C3N4 hybrid with a Co3O4 content of 12 wt% performs optimally with the highest Hg0 removal efficiency of ~100% at or above 120 °C. The high performances of the Co3O4/g-C3N4 hybrids are probably attributed to the tight interfacial contact between Co3O4 and g-C3N4, with its improved electron transfer, inferring that cobalt oxide and g-C3N4 display a cooperative effect towards Hg0 removal. NO and SO2 shows a significant suppressive influence on the mercury capture performance, plausibly owing to the competing adsorption and side reactions.
Cross-Sectorial Semantic Model for Support of Data Analytics in Process Industries
Authors: Sarnovsky Martin , Bednar Peter , Smatana Miroslav
Published: May 2019

The process industries rely on various software systems and use a wide range of technologies. Predictive modeling techniques are often applied to data obtained from these systems to build the predictive functions used to optimize the production processes. Therefore, there is a need to provide a proper representation of knowledge and data and to improve the communication between the data scientists who develop the predictive functions and domain experts who possess the expert knowledge of the domain. This can be achieved by developing a semantic model that focuses on cross-sectorial aspects rather than concepts for specific industries, and that specifies the meta-classes for the formal description of these specific concepts. This model should cover the most important areas including modeling the production processes, data analysis methods, and evaluation using the performance indicators. In this paper, our primary objective was to introduce the specifications of the Cross-sectorial domain model and to present a set of tools that support data analysts and domain experts in the creation of process models and predictive functions. The model and the tools were used to design a knowledge base that could support the development of predictive functions in the green anode production in the aluminum production domain.
Standardizing Innovation Management: An Opportunity for SMEs in the Aerospace Industry
Authors: Cerezo-Narváez Alberto , García-Jurado Daniel , González-Cruz María Carmen , Pastor-Fernández Andrés , Otero-Mateo Manuel , Ballesteros-Pérez Pablo
Published: May 2019

In a globalized marketplace, the competition in the aerospace industry has increased significantly. Producers can choose between many suppliers. These suppliers have to comply with more requirements and technical specifications, as well as take on greater responsibilities that originally fell on producers. In this context, business opportunities for small and medium-sized enterprises (SMEs) are limited, but still suppliers must try to leverage the maximum strategic advantage of the few that present. Adopting research, development and innovation (R+D+i) practices has proven to bring great benefits to companies and allows them to gain significant competitive advantages. However, the process of designing, implementing and testing R+D+i-related processes is not straightforward, nor it has been addressed in the recent research on SMEs. In this paper, a case study of a Spanish innovative small company providing industrial metrology and quality services is analyzed. Thanks to an internal decision-making process, an R+D+i management system based on the UNE 166.002:2014 standard is eventually adopted. A pilot project is closely followed up to test the robustness of the system implementation. The R+D+i management system has allowed the company to streamline its innovation activities, establish objectives to better allocate essential resources, organize high performing innovation units within the organization structure, increase the clients’ confidence, improve the company’s competitiveness, carry out technological surveillance, and get more patented technology, among many others. Adoption steps taken by this SME are generalizable to other SMEs from other industries and show how an R+D+i management system can be chosen, designed, implemented and tested in the context of Industry 4.0 (I4.0).
In Defence of Plant Personhood
Authors: Hall Matthew
Published: May 2019

The philosopher Michael Marder has asserted that animist engagement with plants involves a projection of human purposes and goals leading to veneration. He has also argued that an extension of a categorical concept of personhood underpins my previous work on plant personhood. This paper draws on the growing scholarship of animist traditions following the work of Hallowell to reject Marder’s characterization of a naïve animist approach to plants. It draws on these insights from animist traditions to outline a relational plant personhood, which is fully realized only in grounded, situated relationships of care that seek to enable the flourishing of plants.
Starring Dante
Authors: Ascoli Albert Russell
Published: May 2019

This essay offers an example of a guiding thread in my own research on and teaching of Dante’s Commedia. Specifically, I will follow a strand that leads us from Dante’s encounter with the “bella scola” of classical poets in Inferno Canto 4, through a key scene in the Purgatorio where Dante and his guide Virgil meet the late classical poet Statius, to the remarkable six-canto suite in the Heaven of the Stars, sign of Gemini, in which Dante-poet has Dante-character undergo a series doctrinal tests on the theological virtues. His successful response to the challenges posed by the apostles Peter, James, and Paul doubly authorizes him as poet and as Christian teacher of the highest order. These unique experiences as Dante is successively introduced to and made part of a rising series of elite groups, highlights his double role as humble student and prospective teacher of others. Among the various aims of this essay is to give a sample of a way in which teachers of the Commedia may address the perennial pedagogical problem of how to account for the extraordinary spectacle of a first-person epic that at once expresses deep piety with profound “charitas” (spiritual love) and appears as the absolute height of a self-aggrandizement seemingly inconsistent with Christian humility. Another is to suggest one possible strategy for teaching the Comedy as a whole, and especially the final canticle, the Paradiso, which even Dante himself notoriously thinks is “not for everyone”.
Concretizing Green Growth and Sustainable Business Models in the Water Sector of Jordan
Authors: Engelmann Jan , Al-Saidi Mohammad , Hamhaber Johannes
Published: May 2019

The green growth paradigm has gained much attention from various governments worldwide as a guiding strategy for national and sectoral growth strategies. There is, however, little knowledge on how to integrate green growth into key natural resource sectors, such as water. This paper explains the origins and underlying concepts of green growth, and assesses its potential in the Jordanian water sector. Using a green growth diagnostic model, we analyze six key industries in the Jordanian water sector that can be an engine for green growth and the achievement of key sector-related Sustainable Development Goals (SDGs). In addition, four innovative business models are presented which exemplify the best practices and future directions of the water sector in Jordan. The results and recommendations support the strategic decision-making process of linking economic growth and sustainability, and encouraging private investments.
Deep Learning Based Fossil-Fuel Power Plant Monitoring in High Resolution Remote Sensing Images: A Comparative Study
Authors: Zhang Haopeng , Deng Qin
Published: May 2019

The frequent hazy weather with air pollution in North China has aroused wide attention in the past few years. One of the most important pollution resource is the anthropogenic emission by fossil-fuel power plants. To relieve the pollution and assist urban environment monitoring, it is necessary to continuously monitor the working status of power plants. Satellite or airborne remote sensing provides high quality data for such tasks. In this paper, we design a power plant monitoring framework based on deep learning to automatically detect the power plants and determine their working status in high resolution remote sensing images (RSIs). To this end, we collected a dataset named BUAA-FFPP60 containing RSIs of over 60 fossil-fuel power plants in the Beijing-Tianjin-Hebei region in North China, which covers about 123 km 2 of an urban area. We compared eight state-of-the-art deep learning models and comprehensively analyzed their performance on accuracy, speed, and hardware cost. Experimental results illustrate that our deep learning based framework can effectively detect the fossil-fuel power plants and determine their working status with mean average precision up to 0.8273, showing good potential for urban environment monitoring.
Improving Jujube Fruit Tree Yield Estimation at the Field Scale by Assimilating a Single Landsat Remotely-Sensed LAI into the WOFOST Model
Authors: Bai Tiecheng , Zhang Nannan , Mercatoris Benoit , Chen Youqi
Published: May 2019

Few studies were focused on yield estimation of perennial fruit tree crops by integrating remotely-sensed information into crop models. This study presented an attempt to assimilate a single leaf area index (LAI) near to maximum vegetative development stages derived from Landsat satellite data into a calibrated WOFOST model to predict yields for jujube fruit trees at the field scale. Field experiments were conducted in three growth seasons to calibrate input parameters for WOFOST model, with a validated phenology error of −2, −3, and −3 days for emergence, flowering, and maturity, as well as an R2 of 0.986 and RMSE of 0.624 t ha−1 for total aboveground biomass (TAGP), R2 of 0.95 and RMSE of 0.19 m2 m−2 for LAI, respectively. Normalized Difference Vegetation Index (NDVI) showed better performance for LAI estimation than a Soil-adjusted Vegetation Index (SAVI), with a better agreement (R2 = 0.79) and prediction accuracy (RMSE = 0.17 m2 m−2). The assimilation after forcing LAI improved the yield prediction accuracy compared with unassimilated simulation and remotely sensed NDVI regression method, showing a R2 of 0.62 and RMSE of 0.74 t ha−1 for 2016, and R2 of 0.59 and RMSE of 0.87 t ha−1 for 2017. This research would provide a strategy to employ remotely sensed state variables and a crop growth model to improve field-scale yield estimates for fruit tree crops.
Quality Assessment and Glaciological Applications of Digital Elevation Models Derived from Space-Borne and Aerial Images over Two Tidewater Glaciers of Southern Spitsbergen
Authors: Błaszczyk Małgorzata , Ignatiuk Dariusz , Grabiec Mariusz , Kolondra Leszek , Laska Michał , Decaux Leo , Jania Jacek , Berthier Etienne , Luks Bartłomiej , Barzycka Barbara , Czapla Mateusz
Published: May 2019

In this study, we assess the accuracy and precision of digital elevation models (DEM) retrieved from aerial photographs taken in 2011 and from Very High Resolution satellite images (WorldView-2 and Pléiades) from the period 2012–2017. Additionally, the accuracy of the freely available Strip product of ArcticDEM was verified. We use the DEMs to characterize geometry changes over Hansbreen and Hornbreen, two tidewater glaciers in southern Spitsbergen, Svalbard. The satellite-based DEMs from WorldView-2 and Pléiades stereo pairs were processed using the Rational Function Model (RFM) without and with one ground control point. The elevation quality of the DEMs over glacierized areas was validated with in situ data: static differential GPS survey of mass balance stakes and GPS kinematic data acquired during ground penetrating radar survey. Results demonstrate the usefulness of the analyzed sources of DEMs for estimation of the total geodetic mass balance of the Svalbard glaciers. DEM accuracy is sufficient to investigate glacier surface elevation changes above 1 m. Strips from the ArcticDEM are generally precise, but some of them showed gross errors and need to be handled with caution. The surface of Hansbreen and Hornbreen has been lowering in recent years. The average annual elevation changes for Hansbreen were more negative in the period 2015–2017 (−2.4 m a−1) than in the period 2011–2015 (−1.7 m a−1). The average annual elevation changes over the studied area of Hornbreen for the period 2012–2017 amounted to −1.6 m a−1. The geodetic mass balance for Hansbreen was more negative than the climatic mass balance estimated using the mass budget method, probably due to underestimation of the ice discharge. From 2011 to 2017, Hansbreen lost on average over 1% of its volume each year. Such a high rate of relative loss illustrates how fast these glaciers are responding to climate change.
DisCountNet: Discriminating and Counting Network for Real-Time Counting and Localization of Sparse Objects in High-Resolution UAV Imagery
Authors: Rahnemoonfar Maryam , Dobbs Dugan , Yari Masoud , Starek Michael J.
Published: May 2019

Recent deep-learning counting techniques revolve around two distinct features of data—sparse data, which favors detection networks, or dense data where density map networks are used. Both techniques fail to address a third scenario, where dense objects are sparsely located. Raw aerial images represent sparse distributions of data in most situations. To address this issue, we propose a novel and exceedingly portable end-to-end model, DisCountNet, and an example dataset to test it on. DisCountNet is a two-stage network that uses theories from both detection and heat-map networks to provide a simple yet powerful design. The first stage, DiscNet, operates on the theory of coarse detection, but does so by converting a rich and high-resolution image into a sparse representation where only important information is encoded. Following this, CountNet operates on the dense regions of the sparse matrix to generate a density map, which provides fine locations and count predictions on densities of objects. Comparing the proposed network to current state-of-the-art networks, we find that we can maintain competitive performance while using a fraction of the computational complexity, resulting in a real-time solution.
Satellite-based Cloudiness and Solar Energy Potential in Texas and Surrounding Regions
Authors: Xia Shuang , Mestas-Nuñez Alberto M. , Xie Hongjie , Vega Rolando
Published: May 2019

Global horizontal irradiance (i.e., shortwave downward solar radiation received by a horizontal surface on the ground) is an important geophysical variable for climate and energy research. Since solar radiation is attenuated by clouds, its variability is intimately associated with the variability of cloud properties. The spatial distribution of clouds and the daily, monthly, seasonal, and annual solar energy potential (i.e., the solar energy available to be converted into electricity) derived from satellite estimates of global horizontal irradiance are explored over the state of Texas, USA and surrounding regions, including northern Mexico and the western Gulf of Mexico. The maximum (minimum) monthly solar energy potential in the study area is 151–247 kWhm−2 (43–145 kWhm−2) in July (December). The maximum (minimum) seasonal solar energy potential is 457–706 kWhm−2 (167–481 kWhm−2) in summer (winter). The available annual solar energy in 2015 was 1295–2324 kWhm−2. The solar energy potential is significantly higher over the Gulf of Mexico than over land despite the ocean waters having typically more cloudy skies. Cirrus is the dominant cloud type over the Gulf which attenuates less solar irradiance compared to other cloud types. As expected from our previous work, there is good agreement between satellite and ground estimates of solar energy potential in San Antonio, Texas, and we assume this agreement applies to the surrounding larger region discussed in this paper. The study underscores the relevance of geostationary satellites for cloud/solar energy mapping and provides useful estimates on solar energy in Texas and surrounding regions that could potentially be harnessed and incorporated into the electrical grid.
Same Viewpoint Different Perspectives—A Comparison of Expert Ratings with a TLS Derived Forest Stand Structural Complexity Index
Authors: Frey Julian , Joa Bettina , Schraml Ulrich , Koch Barbara
Published: May 2019

Forests are one of the most important terrestrial ecosystems for the protection of biodiversity, but at the same time they are under heavy production pressures. In many cases, management optimized for timber production leads to a simplification of forest structures, which is associated with species loss. In recent decades, the concept of retention forestry has been implemented in many parts of the world to mitigate this loss, by increasing structure in managed stands. Although this concept is widely adapted, our understanding what forest structure is and how to reliably measure and quantify it is still lacking. Thus, more insights into the assessment of biodiversity-relevant structures are needed, when aiming to implement retention practices in forest management to reach ambitious conservation goals. In this study we compare expert ratings on forest structural richness with a modern light detection and ranging (LiDAR) -based index, based on 52 research sites, where terrestrial laser scanning (TLS) data and 360° photos have been taken. Using an online survey (n = 444) with interactive 360° panoramic image viewers, we sought to investigate expert opinions on forest structure and learn to what degree measures of structure from terrestrial laser scans mirror experts’ estimates. We found that the experts’ ratings have large standard deviance and therefore little agreement. Nevertheless, when averaging the large number of participants, they distinguish stands according to their structural richness significantly. The stand structural complexity index (SSCI) was computed for each site from the LiDAR scan data, and this was shown to reflect some of the variation of expert ratings (p = 0.02). Together with covariates describing participants’ personal background, image properties and terrain variables, we reached a conditional R2 of 0.44 using a linear mixed effect model. The education of the participants had no influence on their ratings, but practical experience showed a clear effect. Because the SSCI and expert opinion align to a significant degree, we conclude that the SSCI is a valuable tool to support forest managers in the selection of retention patches.
Smartphone Sensors for Health Monitoring and Diagnosis
Authors: Majumder Sumit , Deen M. Jamal
Published: May 2019

Over the past few decades, we have witnessed a dramatic rise in life expectancy owing to significant advances in medical science and technology, medicine as well as increased awareness about nutrition, education, and environmental and personal hygiene. Consequently, the elderly population in many countries are expected to rise rapidly in the coming years. A rapidly rising elderly demographics is expected to adversely affect the socioeconomic systems of many nations in terms of costs associated with their healthcare and wellbeing. In addition, diseases related to the cardiovascular system, eye, respiratory system, skin and mental health are widespread globally. However, most of these diseases can be avoided and/or properly managed through continuous monitoring. In order to enable continuous health monitoring as well as to serve growing healthcare needs; affordable, non-invasive and easy-to-use healthcare solutions are critical. The ever-increasing penetration of smartphones, coupled with embedded sensors and modern communication technologies, make it an attractive technology for enabling continuous and remote monitoring of an individual’s health and wellbeing with negligible additional costs. In this paper, we present a comprehensive review of the state-of-the-art research and developments in smartphone-sensor based healthcare technologies. A discussion on regulatory policies for medical devices and their implications in smartphone-based healthcare systems is presented. Finally, some future research perspectives and concerns regarding smartphone-based healthcare systems are described.
Flying Small Target Detection for Anti-UAV Based on a Gaussian Mixture Model in a Compressive Sensing Domain
Authors: Wang Chuanyun , Wang Tian , Wang Ershen , Sun Enyan , Luo Zhen
Published: May 2019

Addressing the problems of visual surveillance for anti-UAV, a new flying small target detection method is proposed based on Gaussian mixture background modeling in a compressive sensing domain and low-rank and sparse matrix decomposition of local image. First of all, images captured by stationary visual sensors are broken into patches and the candidate patches which perhaps contain targets are identified by using a Gaussian mixture background model in a compressive sensing domain. Subsequently, the candidate patches within a finite time period are separated into background images and target images by low-rank and sparse matrix decomposition. Finally, flying small target detection is achieved over separated target images by threshold segmentation. The experiment results using visible and infrared image sequences of flying UAV demonstrate that the proposed methods have effective detection performance and outperform the baseline methods in precision and recall evaluation.
Dry Electrode-Based Body Fat Estimation System with Anthropometric Data for Use in a Wearable Device
Authors: Shin Seung-Chul , Lee Jinkyu , Choe Soyeon , Yang Hyuk In , Min Jihee , Ahn Ki-Yong , Jeon Justin Y. , Kang Hong-Goo
Published: May 2019

The bioelectrical impedance analysis (BIA) method is widely used to predict percent body fat (PBF). However, it requires four to eight electrodes, and it takes a few minutes to accurately obtain the measurement results. In this study, we propose a faster and more accurate method that utilizes a small dry electrode-based wearable device, which predicts whole-body impedance using only upper-body impedance values. Such a small electrode-based device typically needs a long measurement time due to increased parasitic resistance, and its accuracy varies by measurement posture. To minimize these variations, we designed a sensing system that only utilizes contact with the wrist and index fingers. The measurement time was also reduced to five seconds by an effective parameter calibration network. Finally, we implemented a deep neural network-based algorithm to predict the PBF value by the measurement of the upper-body impedance and lower-body anthropometric data as auxiliary input features. The experiments were performed with 163 amateur athletes who exercised regularly. The performance of the proposed system was compared with those of two commercial systems that were designed to measure body composition using either a whole-body or upper-body impedance value. The results showed that the correlation coefficient ( r 2 ) value was improved by about 9%, and the standard error of estimate (SEE) was reduced by 28%.
An Inverse Approach of Damage Identification Using Lamb Wave Tomography
Authors: Liu Yaolu , Zhou Shijie , Ning Huiming , Yan Cheng , Hu Ning
Published: May 2019

A pulse laser combined LWT technique with a two-stage reconstruction algorithm was proposed to realize rapid damage location, or even the evaluation of damage size for plate-like structures. Since the amplitude of Lamb waves in propagation is highly sensitive to damage, including inside damage, the change of the attenuation coefficient of Lamb waves in the inspection region was used as a damage index to reconstruct damage images. In stage one, the rough area of the damage was identified by a comparison of the amplitude of the testing signal data and reference data (undamaged state). In stage two, the damage image was reconstructed using an inverse approach based on the least-square method. In order to verify the effectiveness of the proposed rapid approach, experiments on an aluminum plate with a non-penetrating notch and a carbon fiber-reinforced plastic laminated plate with internal delamination induced by a low-velocity impact were carried out. The results show that the notch can be detected with accurate location, and the delamination image can be reconstructed successfully.
Active Hyperspectral Sensor Based on MEMS Fabry-Pérot Interferometer
Authors: Kääriäinen Teemu , Jaanson Priit , Vaigu Aigar , Mannila Rami , Manninen Albert
Published: May 2019

An active hyperspectral sensor (AHS) was developed for target detection and classification applications. AHS measures light scattered from a target, illuminated by a broadband near-infrared supercontinuum (SC) light source. Spectral discrimination is based on a voltage-tunable MEMS Fabry-Pérot Interferometer (FPI). The broadband light is filtered by the FPI prior to transmitting, allowing for a high spectral-power density within the eye-safety limits. The approach also allows for a cost-efficient correction of the SC instability, employing a non-dispersive reference detector. A precision of 0.1% and long-term stability better than 0.5% were demonstrated in laboratory tests. The prototype was mounted on a car for field measurements. Several road types and objects were distinguished based on the spectral response of the sensor targeted in front of the car.
An Evaluation of Gearbox Condition Monitoring Using Infrared Thermal Images Applied with Convolutional Neural Networks
Authors: Li Yongbo , Gu James Xi , Zhen Dong , Xu Minqiang , Ball Andrew
Published: May 2019

As an important machine component, the gearbox is widely used in industry for power transmission. Condition monitoring (CM) of a gearbox is critical to provide timely information for undertaking necessary maintenance actions. Massive research efforts have been made in the last two decades to develop vibration-based techniques. However, vibration-based methods usually include several inherent shortages including contact measurement, localized information, noise contamination, and high computation costs, making it difficult to be a cost-effective CM technique. In this paper, infrared thermal (IRT) images, which can contain information covering a large area and acquired remotely, are based on developing a cost-effective CM method. Moreover, a convolutional neural network (CNN) is employed to automatically process the raw IRT images for attaining more comprehensive feature parameters, which avoids the deficiency of incomplete information caused by various feature-extraction methods in vibration analysis. Thus, an IRT–CNN method is developed to achieve online remote monitoring of a gearbox. The performance evaluation based on a bevel gearbox shows that the proposed method can achieve nearly 100% correctness in identifying several common gear faults such as tooth pitting, cracks, and breakages and their compounds. It is also especially robust to ambient temperature changes. In addition, IRT also significantly outperforms its vibration-based counterparts.
Optimal Design of Angular Displacement Sensor with Shared Magnetic Field Based on the Magnetic Equivalent Loop Method
Authors: Luo Pinggui , Tang Qifu , Jing Huan
Published: May 2019

Angular displacement sensor with shared magnetic field has strong environmental adaptability and high measurement accuracy. However, its 3-D structure is multi-pole double-layer structure, using time stepping finite element method (TSFEM) to optimize the structure is time-consuming and uneconomical. Therefore, a magnetic equivalent loop method (MELM) is proposed to simplify the optimal design of sensors. By reasonably setting the node position, the mechanical structure parameters, winding coefficients and input voltage of the sensor are integrated into a mathematical model to calculate of the induced voltage. The calculation results are compared with the simulation results, and a sensor prototype is made to test the optimized effect of the MELM.