bluuebunny/crossref_metadata_2025 huggingface dataset:
Shape-Stabilized Phase Change Materials for Solar Energy Storage: MgO and Mg(OH)2 Mixed with Polyethylene Glycol
Authors: Zahir Md. Hasan , Rahman Mohammad Mizanur , Irshad Kashif , Rahman Mohammad Mominur
Published: December 2019

Heat energy storage systems were fabricated with the impregnation method using MgO and Mg(OH)2 as supporting materials and polyethylene glycol (PEG-6000) as the functional phase. MgO and Mg(OH)2 were synthesized from the salt Mg(NO3)·6H2O by performing hydrothermal reactions with various precipitating agents. The precipitating agents were NaOH, KOH, NH3, NH3 with pamoic acid (PA), or (NH4)2CO3. The result shows that the selection of the precipitating agent has a significant impact on the crystallite structure, size, and shape of the final products. Of the precipitating agents tested, only NaOH and NH3 with PA produce single-phase Mg(OH)2 as the as-synthesized product. Pore size distribution analyses revealed that the surfaces of the as-synthesized MgO have a slit-like pore structure with a broad-type pore size distribution, whereas the as-synthesized Mg(OH)2 has a mesoporous structure with a narrow pore size distribution. This structure enhances the latent heat of the phase change material (PCM) as well as super cooling mitigation. The PEG/Mg(OH)2 PCM also exhibits reproducible behavior over a large number of thermal cycles. Both MgO and Mg(OH)2 matrices prevent the leakage of liquid PEG during the phase transition in phase change materials (PCMs). However, MgO/PEG has a low impregnation ratio and efficiency, with a low thermal storage capability. This is due to the large pore diameter, which does not allow MgO to retain a larger amount of PEG. The latent heat values of PEG-1000/PEG-6000 blends with MgO and Mg(OH)2 were also determined with a view to extending the application of the PCMs to energy storage over wider temperature ranges.
Variability of Water-Soluble Forms of Choline Concentrations in Human Milk during Storage, after Pasteurization, and among Women
Authors: Moukarzel Sara , Wiedeman Alejandra M. , Soberanes Lynda S. , Dyer Roger A. , Innis Sheila M. , Lamers Yvonne
Published: December 2019

Choline is critical for infant development and mother’s milk is the sole source of choline for fully breastfed infants until six months of age. Human milk choline consists to 85% of water-soluble forms of choline including free choline (FC), phosphocholine (PhosC), and glycerophosphocholine (GPC). Donor milk requires safe handling procedures such as cold storage and pasteurization. However, the stability of water-soluble forms of choline during these processes is not known. The objectives of this research were to determine the effect of storage and pasteurization on milk choline concentration, and the diurnal intra- and inter-individual variability of water-soluble choline forms. Milk samples were collected from healthy women who were fully breastfeeding a full-term, singleton infant <6 months. Milk total water-soluble forms of choline, PhosC, and GPC concentrations did not change during storage at room temperature for up to 4 h. Individual and total water-soluble forms of choline concentrations did not change after storage for 24 h in the refrigerator or for up to one week in the household freezer. Holder pasteurization decreased PhosC and GPC, and thereby total water-soluble choline form concentrations by <5%. We did not observe diurnal variations in PhosC and total water-soluble forms of choline concentrations, but significant differences in FC and GPC concentrations across five sampling time points throughout one day. In conclusion, these outcomes contribute new knowledge for the derivation of evidence-informed guidelines for the handling and storage of expressed human milk as well as the development of optimized milk collection and storage protocols for research studies.
Why Do Children in Slums Suffer from Anemia, Iron, Zinc, and Vitamin A Deficiency? Results from a Birth Cohort Study in Dhaka
Authors: Mahfuz Mustafa , Murray-Kolb Laura E. , Hasan S. M. Tafsir , Das Subhasish , Fahim Shah Mohammad , Alam Mohammed Ashraful , Caulfield Laura , Ahmed Tahmeed
Published: December 2019

Considering the high burden of micronutrient deficiencies in Bangladeshi children, this analysis aimed to identify the factors associated with micronutrient deficiencies and association of plasma micronutrient concentration trajectories from 7 to 24 months with the concentrations at 60 months of age. Plasma samples were collected at 7, 15, 24, and 60 months of age, and hemoglobin, ferritin, zinc, and retinol concentrations of 155, 153, 154, and 155 children were measured, respectively. A generalized estimating equation was used to identify the factors associated with micronutrient deficiencies, while latent class growth modeling identified the trajectories of plasma micronutrients from 7 to 24 months and its association with the concentrations of micronutrients at 60 months was examined using multiple linear regression modeling. Early (AOR = 2.21, p < 0.05) and late convalescence (AOR = 1.65, p < 0.05) stage of an infection, low ferritin (AOR = 3.04, p < 0.05), and low retinol (AOR = 2.07, p < 0.05) were associated with increased anemia prevalence. Wasting at enrollment was associated with zinc deficiency (AOR = 1.8, p < 0.05) and birth weight was associated with ferritin deficiency (AOR = 0.58, p < 0.05). Treatment of drinking water was found protective against vitamin A deficiency (AOR = 0.57, p < 0.05). Higher trajectories for ferritin and retinol during 7–24 months were positively associated with plasma ferritin (β = 13.72, p < 0.05) and plasma retinol (β = 3.99, p < 0.05) at 60 months.
Exploring the Benefit of 2-Methylbutyric Acid in Patients Undergoing Hemodialysis Using a Cardiovascular Proteomics Approach
Authors: Wu Ping-Hsun , Chiu Yi-Wen , Zou Hsin-Bai , Hsu Cheng-Chih , Lee Su-Chu , Lin Yi-Ting , Tsai Yi-Chun , Kuo Mei-Chuan , Hwang Shang-Jyh
Published: December 2019

Short-chain fatty acids (SCFAs) can reduce pro-inflammatory parameters and oxidative stress, providing potential cardiovascular (CV) benefits. Although some evidence links SCFAs with host metabolic health via several biological mechanisms, the role of SCFA on CV disease in patients with kidney disease remains unclear. Herein, we investigate the association between a SCFA, 2-methylbutyric acid, and target CV proteomics to explore the potential pathophysiology of SCFA-related CV benefit in patients with kidney disease. Circulating 2-methylbutyric acid was quantified by high-performance liquid chromatography and 181 CV proteins by a proximity extension assay in 163 patients undergoing hemodialysis (HD). The associations between 2-methylbutyric acid and CV proteins were evaluated using linear regression analysis with age and gender, and multiple testing adjustment. The selected CV protein in the discovery phase was further confirmed in multivariable-adjusted models and evaluated by continuous scale association. The mean value of circulating 2-methylbutyric acid was 0.22 ± 0.02 µM, which was negatively associated with bone morphogenetic protein 6 (BMP-6) according to the false discovery rate (FDR) multiple testing adjustment method. The 2-methylbutyric acid level remained negatively associated with BMP-6 (β coefficient −1.00, 95% confidence interval −1.45 to −0.55, p < 0.001) after controlling for other CV risk factors in multivariable models. The cubic spline curve demonstrated a linear relationship. In conclusion, circulating 2-methylbutyric acid level was negatively associated with BMP-6, suggesting that this pathway maybe involved in vascular health in patients undergoing HD. However, further in vitro work is still needed to validate the translation of the mechanistic pathways.
Eating Disorders and Gastrointestinal Diseases
Authors: Santonicola Antonella , Gagliardi Mario , Guarino Michele Pier Luca , Siniscalchi Monica , Ciacci Carolina , Iovino Paola
Published: December 2019

Eating disorders (ED) are frequently associated with a wide range of psychiatric or somatic comorbidities. The most relevant ED are anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorders (BED). Patients with ED exhibit both upper and lower gastrointestinal (GI) symptoms. Evidence of alterations throughout the GI tract in ED will be analyzed given the role of the GI tract in food intake and its regulation. It remains a matter of debate whether GI disorders are inherent manifestations of ED or the results of malnutrition occurring from ED. Moreover, recent clinical studies have highlighted the growing role of intestinal microbiota in the pathogenesis of ED, making it possible to hypothesize a modulation of intestinal microbiota as a co-adjuvant to standard therapy. The aim of this review is to analyze the link between ED and GI diseases and to present, where known, the potential key factors underlying these conditions. Conclusions: The presence of GI disorders should be investigated in patients with ED. Screening for ED should also be encouraged in individuals seeking treatment for unexplained GI complaints to better address therapeutic issues that surround these difficult medical conditions.
Polyaniline Nanotubes/Carbon Cloth Composite Electrode by Thermal Acid Doping for High-Performance Supercapacitors
Authors: Hui Jia , Wei Daoxin , Chen Jing , Yang Zhou
Published: December 2019

Carbon materials have been widely used in designing supercapacitors (SCs) but the capacitance is not ideal. Herein, we synthesize polyaniline (PANI) nanotubes on the basis of a carbon cloth (CC) through a one-step self-degradation template method, and fabricate a CC@PANI NTs-H (CC@PANI nanotubes doping at high temperature) composite electrode by thermal acid doping. The CC@PANI NTs-H electrode obviously exhibits better electrochemical performance with a gravimetric capacitance of 438 F g−1 and maintains 86.8% after 10,000 cycles than the CC@PANI NTs-R (CC@PANI nanotubes doping at room temperature) electrode. Furthermore, we assemble a flexible solid state supercapacitor (FSSC) device with the as-prepared CC@PANI NTs-H composite electrodes, showing good flexibility and outstanding electrochemical performances with a high gravimetric capacitance of 247 F g−1, a large energy density of 21.9 Wh kg−1, and a capacitance retention of 85.4% after 10,000 charge and discharge cycles. Our work proposes a novel and easy pathway to fabricate low-cost FSSCs for the development of energy storage devices.
Enhancement of Solvent Resistance of Polyimide Electrospun Mat via the UV-Assisted Electrospinning and Photosensitive Varnish
Authors: Qi Lin , Guo Chen-Yu , Huang Fu Meng-Ge , Zhang Yan , Yin Lu-meng , Wu Lin , Liu Jin-gang , Zhang Xiu-min
Published: December 2019

A new methodology for enhancing the solvent resistance of electrospun polyimide (PI) ultrafine fibrous mat (UFM) was investigated in the current work. For this purpose, a negative intrinsically photosensitive polyimide (PSPI) resin was prepared by the one-step high- temperature polycondensation procedure from 3,3’,4,4’-benzophenonetetracarboxylic dianhydride (BTDA) and α,α-bis(4-amino-3,5-dimethylphenyl)phenylmethane (PTMDA). The PI varnish, by dissolving the derived PI (BTDA-PTMDA) resin in N,N-dimethylacetamide (DMAc) at a solid of 20 wt %, was used as the starting material for the standard electrospinning (ES) and ultraviolet-assisted ES (UVAES) fabrications, respectively. The 365 nm wavelength of the high-pressure mercury lamp ultraviolet (UV) irradiation induced the photocrosslinking reaction in the PSPI mat. Solubility tests indicated that the PI UFM fabricated by standard ES procedure showed poor DMAc resistance, while the one by UVAES (PI-UV) exhibited excellent resistance to DMAc.
Polymer-Based Systems for Controlled Release and Targeting of Drugs
Authors: Giammona Gaetano , Craparo Emanuela Fabiola
Published: December 2019

The current need to find new advanced approaches to carry biologically active substances (conventional organic drugs, peptides, proteins (such as antibodies), and nucleic acid-based drugs (NABDs such as siRNA and miRNA)) in the body fluids, to realize targeted therapies and even personalized ones, goes hand in hand with research on the performance of new materials to better realize appropriate drug vectors [...]
Characterization of Poly(Ethylene Oxide) Nanofibers—Mutual Relations between Mean Diameter of Electrospun Nanofibers and Solution Characteristics
Authors: Filip Petr , Peer Petra
Published: December 2019

The quality of electrospun poly(ethylene oxide) (PEO) nanofibrous mats are subject to a variety of input parameters. In this study, three parameters were chosen: molecular weight of PEO (100, 300, 600, and 1000 kg/mol), PEO concentration (in distilled water), and shear viscosity of PEO solution. Two relations free of any adjustable parameters were derived. The first, describing the initial stage of an electrospinning process expressing shear viscosity using PEO molecular weight and concentration. The second, expressing mean nanofiber diameter using concentration and PEO molecular weight. Based on these simple mathematical relations, it is possible to control the mean nanofiber diameter during an electrospinning process.
A Comprehensive Review and Technical Guideline for Optimal Design and Operations of Fuel Cell-Based Cogeneration Systems
Authors: Ramadhani Farah , Hussain Mohd Azlan , Mokhlis Hazlie
Published: December 2019

The need for energy is increasing from year to year and has to be fulfilled by developing innovations in energy generation systems. Cogeneration is one of the matured technologies in energy generation, which has been implemented since the last decade. Cogeneration is defined as energy generation unit that simultaneously produced electricity and heat from a single primary fuel source. Currently, the implementation of this system has been spread over the world for stationary and mobile power generation in residential, industrial and transportation uses. On the other hand, fuel cells as an emerging energy conversion device are potential prime movers for this cogeneration system due to its high heat production and flexibility in its fuel usage. Even though the fuel cell-based cogeneration system has been popularly implemented in research and commercialization sectors, the review regarding this technology is still limited. Focusing on the optimal design of the fuel cell-based cogeneration system, this study attempts to provide a comprehensive review, guideline and future prospects of this technology. With an up-to-date literature list, this review study becomes an important source for researchers who are interested in developing this system for future implementation.
Assessment of Green Infrastructure in Riparian Zones Using Copernicus Programme
Authors: Piedelobo Laura , Taramelli Andrea , Schiavon Emma , Valentini Emiliana , Molina José-Luis , Nguyen Xuan Alessandra , González-Aguilera Diego
Published: December 2019

This article presents an approach to identify Green Infrastructure (GI), its benefits and condition. This information enables environmental agencies to prioritise conservation, management and restoration strategies accordingly. The study focuses on riparian areas due to their potential to supply Ecosystem Services (ES), such as water quality, biodiversity, soil protection and flood or drought risk reduction. Natural Water Retention Measures (NWRM) related to agriculture and forestry are the type of GI considered specifically within these riparian areas. The approach is based on ES condition indicators, defined by the European Environment Agency (EEA) to support the policy targets of the 2020 Biodiversity Strategy. Indicators that can be assessed through remote sensing techniques are used, namely: capacity to provide ecosystem services, proximity to protected areas, greening response and water stress. Specifically, the approach uses and evaluates the potential of freely available products from the Copernicus Land Monitoring Service (CLMS) to monitor GI. Moreover, vegetation and water indices are calculated using data from the Sentinel-2 MSI Level-2A scenes and integrated in the analysis. The approach has been tested in the Italian Po river basin in 2018. Firstly, agriculture and forest NWRM were identified in the riparian areas of the river network. Secondly, the Riparian Zones products from the CLMS local component and the satellite-based indices were linked to the aforementioned ES condition indicators. This led to the development of a pixel-based model that evaluates the identified GI according to: (i) its disposition to provide riparian regulative ES and (ii) its condition in the analysed year. Finally, the model was used to prioritise GI for conservation or restoration initiatives, based on its potential to deliver ES and current condition.
Building Extraction from Very High Resolution Aerial Imagery Using Joint Attention Deep Neural Network
Authors: Ye Ziran , Fu Yongyong , Gan Muye , Deng Jinsong , Comber Alexis , Wang Ke
Published: December 2019

Automated methods to extract buildings from very high resolution (VHR) remote sensing data have many applications in a wide range of fields. Many convolutional neural network (CNN) based methods have been proposed and have achieved significant advances in the building extraction task. In order to refine predictions, a lot of recent approaches fuse features from earlier layers of CNNs to introduce abundant spatial information, which is known as skip connection. However, this strategy of reusing earlier features directly without processing could reduce the performance of the network. To address this problem, we propose a novel fully convolutional network (FCN) that adopts attention based re-weighting to extract buildings from aerial imagery. Specifically, we consider the semantic gap between features from different stages and leverage the attention mechanism to bridge the gap prior to the fusion of features. The inferred attention weights along spatial and channel-wise dimensions make the low level feature maps adaptive to high level feature maps in a target-oriented manner. Experimental results on three publicly available aerial imagery datasets show that the proposed model (RFA-UNet) achieves comparable and improved performance compared to other state-of-the-art models for building extraction.
Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter
Authors: Kowalewska-Kalkowska Halina , Kowalewski Marek
Published: December 2019

Coastal upwelling involves an upward movement of deeper, usually colder, water to the surface. Satellite sea surface temperature (SST) observations and simulations with a hydrodynamic model show, however, that the coastal upwelling in the Baltic Sea in winter can bring warmer water to the surface. In this study, the satellite SST data collected by the advanced very high resolution radiometer (AVHRR) and the moderate-resolution imaging spectroradiometer (MODIS), as well as simulations with the Parallel Model 3D (PM3D) were used to identify upwelling events in the southern Baltic Sea during the 2010–2017 winter seasons. The PM3D is a three-dimensional hydrodynamic model of the Baltic Sea developed at the Institute of Oceanography, University of Gdańsk, Poland, in which parallel calculations enable high-resolution modelling. A validation of the model results with in situ observations and satellite-derived SST data showed the PM3D to adequately represent thermal conditions in upwelling areas in winter (91.5% agreement). Analysis of the frequency of warm upwellings in 12 areas of the southern Baltic Sea showed a high variability in January and February. In those months, the upwelling was most frequent, both in satellite imagery and in model results, off the Hel Peninsula (38% and 43% frequency, respectively). Upwelling was also frequent off the Vistula Spit, west of the Island of Rügen, and off the eastern coast of Skåne, where the upwelling frequency estimated from satellite images exceeded 26%. As determined by the PM3D, the upwelling frequency off VS and R was at least 25%, while off the eastern coast of Skåne, it reached 17%. The faithful simulation of SST variability in the winters of 2010–2017 by the high-resolution model used was shown to be a reliable tool with which to identify warm upwellings in the southern Baltic Sea.
High-Resolution and Accurate Topography Reconstruction of Mount Etna from Pleiades Satellite Data
Authors: Palaseanu-Lovejoy Monica , Bisson Marina , Spinetti Claudia , Buongiorno Maria Fabrizia , Alexandrov Oleg , Cecere Thomas
Published: December 2019

The areas characterized by dynamic and rapid morphological changes need accurate topography information with frequent updates, especially if these are populated and involve infrastructures. This is particularly true in active volcanic areas such as Mount (Mt.) Etna, located in the northeastern portion of Sicily, Italy. The Mt. Etna volcano is periodically characterized by explosive and effusive eruptions and represents a potential hazard for several thousands of local people and hundreds of tourists present on the volcano itself. In this work, a high-resolution, high vertical accuracy digital surface model (DSM) of Mt. Etna was derived from Pleiades satellite data using the National Aeronautics and Space Administration (NASA) Ames Stereo Pipeline (ASP) tool set. We believe that this is the first time that the ASP using Pleiades imagery has been applied to Mt. Etna with sub-meter vertical root mean square error (RMSE) results. The model covers an area of about 400 km2 with a spatial resolution of 2 m and centers on the summit portion of the volcano. The model was validated by using a set of reference ground control points (GCP) obtaining a vertical RMSE of 0.78 m. The described procedure provides an avenue to obtain DSMs at high spatial resolution and elevation accuracy in a relatively short amount of processing time, making the procedure itself suitable to reproduce topographies often indispensable during the emergency management case of volcanic eruptions.
First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI
Authors: Li Shuang , Wang Weile , Hashimoto Hirofumi , Xiong Jun , Vandal Thomas , Yao Jing , Qian Lexiang , Ichii Kazuhito , Lyapustin Alexei , Wang Yujie , Nemani Ramakrishna
Published: December 2019

A provisional surface reflectance (SR) product from the Advanced Himawari Imager (AHI) on-board the new generation geostationary satellite (Himawari-8) covering the period between July 2015 and December 2018 is made available to the scientific community. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is used in conjunction with time series Himawari-8 AHI observations to generate 1-km gridded and tiled land SR every 10 minutes during day time. This Himawari-8 AHI SR product includes retrieved atmospheric properties (e.g., aerosol optical depth at 0.47µm and 0.51µm), spectral surface reflectance (AHI bands 1–6), parameters of the RTLS BRDF model, and quality assurance flags. Product evaluation shows that Himawari-8 AHI data on average yielded 35% more cloud-free, valid pixels in a single day when compared to available data from the low earth orbit (LEO) satellites Terra/Aqua with MODIS sensor. Comparisons of Himawari-8 AHI SR against corresponding MODIS SR products (MCD19A1) over a variety of land cover types with the similar viewing geometry show high consistency between them, with correlation coefficients (r) being 0.94 and 0.99 for red and NIR bands, respectively. The high-frequency geostationary data are expected to facilitate studies of ecosystems on daily to diurnal time scales, complementing observations from networks such as the FLUXNET.
Change of Objectively-Measured Physical Activity during Geriatric Rehabilitation
Authors: Klenk Jochen , Wekenmann Sebastian , Schwickert Lars , Lindemann Ulrich , Becker Clemens , Rapp Kilian
Published: December 2019

This prospective study investigated feasibility and sensitivity of sensor-based physical activity (PA) measures to monitor changes in PA during geriatric rehabilitation and its relation to clinical parameters at admission. PA was routinely measured at day 2 and day 15 after admission in 647 patients (70.2% women, mean age = 82.0 (SD = 7.19) years) of a German geriatric hospital using a thigh-worn accelerometer. Clinical records were used to include age, Barthel Index, diagnosis, mobility, orientation and cognition. Mean values and 95% confidence intervals (95%-CI) of walking duration, walking bout duration and number of sit-to-stand transfers were calculated to quantify different domains of PA. All observed PA parameters improved during rehabilitation, regardless of age, diagnosis or physical and cognitive function at admission. Walking duration increased by 12.1 (95%-CI: 10.3; 13.8) min, walking bout duration by 2.39 (95%-CI: 1.77; 3.00) s, and number of sit-to-stand transfers by 7 (95%-CI: 5; 8). Floor and ceiling effects were not observed. Walking duration at day 2 as well as day 15 was continuously associated with Barthel Index and statistically significant improved for all levels of Barthel Index. In summary, this study showed that sensor-based PA monitoring is feasible to assess the individual progress in geriatric rehabilitation patients.
A Portable, Single-Use, Paper-Based Microbial Fuel Cell Sensor for Rapid, On-Site Water Quality Monitoring
Authors: Cho Jong Hyun , Gao Yang , Choi Seokheun
Published: December 2019

Human access to safe water has become a major problem in many parts of the world as increasing human activities continue to spill contaminants into our water systems. To guarantee the protection of the public as well as the environment, a rapid and sensitive way to detect contaminants is required. In this work, a paper-based microbial fuel cell was developed to act as a portable, single-use, on-site water quality sensor. The sensor was fabricated by combining two layers of paper for a simple, low-cost, and disposable design. To facilitate the use of the sensor for on-site applications, the bacterial cells were pre-inoculated onto the device by air-drying. To eliminate any variations, the voltage generated by the microorganism before and after the air-drying process was measured and calculated as an inhibition ratio. Upon the addition of different formaldehyde concentrations (0%, 0.001%, 0.005%, and 0.02%), the inhibition ratios obtained were 5.9 ± 0.7%, 6.9 ± 0.7%, 8.2 ± 0.6%, and 10.6 ± 0.2%, respectively. The inhibition ratio showed a good linearity with the formaldehyde concentrations at R2 = 0.931. Our new sensor holds great promise in monitoring water quality as a portable, low-cost, and on-site sensor.
Integrator Drift Compensation of Magnetic Flux Transducers by Feed-Forward Correction
Authors: Amodeo Maria , Arpaia Pasquale , Buzio Marco
Published: December 2019

Integrator drift is a problem strongly felt in different measurement fields, often detrimental even for short-term applications. An analytical method for modelling and feed-forward correcting drift in magnetic flux measurements was developed analytically and tested experimentally. A case study is reported on the proof of principle as a novel kind of quasi-DC field marker of the 5-ppm Nuclear Magnetic Resonance (NMR) transducer Metrolab PT2026, applied to the Extra Low ENergy Antiproton (ELENA) ring and the Proton Synchrotron Booster (PSB) at CERN. In some particle accelerators, such as in ELENA, the resulting feed-forward correction guarantees 1

μ

T field stability over 120-s long magnetic cycle on a plateau of 50 mT, reducing by three orders of magnitude the field error caused by the integrator drift with respect to the state of the art.
Longest-Range UHF RFID Sensor Tag Antenna for IoT Applied for Metal and Non-Metal Objects
Authors: Byondi Franck Kimetya , Chung Youchung
Published: December 2019

This paper presents a passive cavity type Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tag antenna having the longest read-range, and compares it with existing long-range UHF RFID tag antenna. The study also demonstrates mathematically and experimentally that our proposed longest-range UHF RFID cavity type tag antenna has a longer read-range than existing passive tag antennas. Our tag antenna was designed with 140 × 60 × 10 mm3 size, and reached 26 m measured read-range and 36.3 m mathematically calculated read-range. This UHF tag antenna can be applied to metal and non-metal objects. By adding a further sensing capability, it can have a great benefit for the Internet of Things (IoT) and wireless sensor networks (WSN).
Object-Based Image Analysis Applied to Low Altitude Aerial Imagery for Potato Plant Trait Retrieval and Pathogen Detection
Authors: Siebring Jasper , Valente João , Domingues Franceschini Marston Heracles , Kamp Jan , Kooistra Lammert
Published: December 2019

There is a growing demand in both food quality and quantity, but as of now, one-third of all food produced for human consumption is lost due to pests and other pathogens accounting for roughly 40% of pre-harvest loss in potatoes. Pathogens in potato plants, like the Erwinia bacteria and the PVYNTN virus for example, exhibit symptoms of varying severity that are not easily captured by pixel-based classes (as these ignore shape, texture, and context in general). The aim of this research is to develop an object-based image analysis (OBIA) method for trait retrieval of individual potato plants that maximizes information output from Unmanned Aerial Vehicle (UAV) RGB very high resolution (VHR) imagery and its derivatives, to be used for disease detection of the Solanum tuberosum. The approach proposed can be split in two steps: (1) object-based mapping of potato plants using an optimized implementation of large scale mean-shift segmentation (LSMSS), and (2) classification of disease using a random forest (RF) model for a set of morphological traits computed from their associative objects. The approach was proven viable as the associative RF model detected presence of Erwinia and PVY pathogens with a maximum F1 score of 0.75 and an average Matthews Correlation Coefficient (MCC) score of 0.47. It also shows that low-altitude imagery acquired with a commercial UAV is a viable off-the-shelf tool for precision farming, and potato pathogen detection.
AI Radar Sensor: Creating Radar Depth Sounder Images Based on Generative Adversarial Network
Authors: Rahnemoonfar Maryam , Johnson Jimmy , Paden John
Published: December 2019

Significant resources have been spent in collecting and storing large and heterogeneous radar datasets during expensive Arctic and Antarctic fieldwork. The vast majority of data available is unlabeled, and the labeling process is both time-consuming and expensive. One possible alternative to the labeling process is the use of synthetically generated data with artificial intelligence. Instead of labeling real images, we can generate synthetic data based on arbitrary labels. In this way, training data can be quickly augmented with additional images. In this research, we evaluated the performance of synthetically generated radar images based on modified cycle-consistent adversarial networks. We conducted several experiments to test the quality of the generated radar imagery. We also tested the quality of a state-of-the-art contour detection algorithm on synthetic data and different combinations of real and synthetic data. Our experiments show that synthetic radar images generated by generative adversarial network (GAN) can be used in combination with real images for data augmentation and training of deep neural networks. However, the synthetic images generated by GANs cannot be used solely for training a neural network (training on synthetic and testing on real) as they cannot simulate all of the radar characteristics such as noise or Doppler effects. To the best of our knowledge, this is the first work in creating radar sounder imagery based on generative adversarial network.
Corporate Social Responsibility Activity Combinations for Sustainability: A Fuzzy Set Analysis of Korean Firms
Authors: Kim Jinhwan , Kim Hyeob , Kwon HyukJun
Published: December 2019

We examine how combinations of corporate social responsibility (CSR) activities yield high performance in Korean companies by addressing two related questions to expand our limited knowledge. First, what combinations of CSR activities yield high performance? Second, how do CSR activities form an interdependent system based on different corporate contexts? We draw the 2012–2018 data from the Korean Economic Justice Institute index for a fuzzy set qualitative comparative analysis. The results reveal several effective CSR activity factor combinations under the given strategies and management environments. Companies with a high performance exhibit complementarity between social contribution, environmental management, fairness, and employee satisfaction. By contrast, companies with a low corporate performance show no complementarity between relatively unrelated activity factors. For companies with a low financial performance from CSR activities, most of the causal pathways focus only on activities at the primary stakeholder level, with weak diversity of CSR activities’ combinations at the primary and secondary stakeholder levels. These results indicate not only the appropriateness of CSR activity factor combinations for companies’ strategy and management environment contexts, but also their effectiveness, and are expected to provide companies with significant implications for CSR activities.
Repeat Consumer Behavior on Smart P2P Tourism Platforms
Authors: Talón-Ballestero Pilar , García-Muiña Fernando E. , Rienda-Gómez Juan José , González-Serrano Lydia
Published: December 2019

Despite the key role played by frequent consumers interacting on smart P2P (peer to peer) tourism platforms, there are hardly any studies on the explanatory variables of their frequency of use. This paper aims to understand the motivational and sociodemographic factors that bring about repeat consumers in collaborative accommodation and transport services. In order to test various assumptions, a set of logistic regressions were made where the dependent variable is the frequency of use and the independent variables are sociodemographic and motivational factors. The results suggest that many consumer attributes recognized as being typical of collaborative platforms, such as young people traveling with friends for leisure who are interested in low prices, have changed. We found that, due to the consolidation of these smart business models, the frequency of use increases with age and for those who travel for work reasons. In addition, it is worth noting the existence of a positive relationship between consumers who provide reviews on these platforms and their frequency of use.
Soil Properties Spatial Variability and Delineation of Site-Specific Management Zones Based on Soil Fertility Using Fuzzy Clustering in a Hilly Field in Jianyang, Sichuan, China
Authors: Metwally Mohamed S. , Shaddad Sameh M. , Liu Manqiang , Yao Rong-Jiang , Abdo Ahmed I. , Li Peng , Jiao Jiaoguo , Chen Xiaoyun
Published: December 2019

Avoiding soil degradation and improving crop productivity could be achieved by performing sustainable soil nutrient management with an appropriate understanding of soil properties’ spatial variability. The present fertilizer recommendations for the region where the study area is located are typically symmetric for large regions. This leads to the under-application of fertilizers in zones with low nutrient contents and over-application in zones with high nutrient contents. Therefore, this study was conducted to assess soil management zones (MZs) in the study area for effective soil nutrient management and to evaluate soil properties’ spatial variability. A total of 100 geo-referenced soil samples were collected at a depth of 0–20 cm, processed and analyzed for pH, available nitrogen (AN), available phosphorus (AP), available potassium (AK), soil organic carbon (SOC), total nitrogen (TN) and total phosphorous (TP), while C:N, C:P and N:P ratios were calculated. Soil properties’ coefficients of variation (CVs) widely varied from low (1.132%) to moderate (45.748%). Ordinary kriging and semi-variogram analysis showed differed spatial variability patterns for the studied soil properties with spatial dependence ranged from weak to strong. MZs were delineated by performing principal component analysis (PCA) and fuzzy K-means clustering. Four PCs with eigen values more than 1 dominated 84.44% of the total variance, so they were retained for clustering analysis. Three MZs were delineated based on the two criteria modified partition entropy (MPE) and fuzzy performance index (FPI). The studied soil properties differed significantly among MZs. Thus, the methodology used for MZ delineation could be used effectively for soil site-specific nutrient management for avoiding soil degradation concurrently with maximizing crop production in the study area.
Mapping Bioenergy Supply and Demand in Selected Least Developed Countries (LDCs): Exploratory Assessment of Modern Bioenergy’s Contribution to SDG7
Authors: Khatiwada Dilip , Purohit Pallav , Ackom Emmanuel Kofi
Published: December 2019

Bioenergy can play an important role in achieving the agreed United Nations Sustainable Development Goals (SDGs) and implementing the Paris Agreement on Climate Change, thereby advancing climate goals, food security, better land use, and sustainable energy for all. In this study, we assess the surplus agricultural residues availability for bioelectricity in six least developed countries (LDCs) in Asia and Africa, namely Bangladesh, Lao-PDR, and Nepal in Asia; and Ethiopia, Malawi, and Zambia in Africa, respectively. The surplus agricultural residues have been estimated using residue-to-product ratio (RPR), agricultural residues lost in the collection, transportation and storage, and their alternative applications. We use a linear regression model to project the economic potential of bioelectricity. The contribution of bioelectricity for meeting the LDCs’ electricity requirements is estimated in a time frame between 2017 and 2030. Our results reveal that the surplus biomass feedstock available from the agriculture sector could provide the total current electricity demand in Malawi alone, followed by Nepal (45%), Bangladesh (29%), Lao People’s Democratic Republic (Lao-PDR) (29%), Ethiopia (27%), and Zambia (13%). This study also explores the complementarity and synergies of bioelectricity, SDG7, and their interlinkages with other SDGs. Findings from the study show that providing access to sustainable energy in the LDCs to meet the SDG7 by 2030 might be a challenge due to limited access to technology, infrastructure, and finance. Site-specific investigations on how much agricultural residues could be extracted in an environmentally benign manner for bioelectricity and increased investment in the bioenergy sector are key potential solutions in a myriad of options required to harness the full energy potential in the LDCs.
The Potential of Industrial Symbiosis: Case Analysis and Main Drivers and Barriers to Its Implementation
Authors: Neves Angela , Godina Radu , G. Azevedo Susana , Pimentel Carina , C.O. Matias João
Published: December 2019

Industrial symbiosis, which is characterised mainly by the reuse of waste from one company as raw material by another, has been applied worldwide with recognised environmental, economic, and social benefits. However, the potential for industrial symbiosis is not exhausted in existing cases, and there is still a wide range of opportunities for its application. Through a comprehensive literature review, this article aims to compile and analyse studies that focus on potential industrial symbiosis in real contexts, to highlight the margin of optimisation that is not being used. The cases reported in the publications identified here were characterised and analysed according to geographic location, type of economic activity, waste/by-products, main benefits, and the methods employed in the studies. From this analysis, we conclude that there is great potential for applications involving industrial symbiosis throughout the world, and especially in Europe, corresponding to 53% of the total cases analysed. Manufacturing stood out as the sector with the highest potential for establishing symbiosis relationships, and the most common types of waste streams in potential networks were organic, plastic and rubber, wood, and metallic materials. This article also discusses the main drivers and barriers to realising the potential of industrial symbiosis. The diversity of industries, geographical proximity, facilitating entities and legislation, plans, and policies are shown to be the main drivers.
Optimal Generation Scheduling with Dynamic Profiles for the Sustainable Development of Electricity Grids
Authors: Roldán-Blay Carlos , Miranda Vladimiro , Carvalho Leonel , Roldán-Porta Carlos
Published: December 2019

The integration of renewable generation in electricity networks is one of the most widespread strategies to improve sustainability and to deal with the energy supply problem. Typically, the reinforcement of the generation fleet of an existing network requires the assessment and minimization of the installation and operating costs of all the energy resources in the network. Such analyses are usually conducted using peak demand and generation data. This paper proposes a method to optimize the location and size of different types of generation resources in a network, taking into account the typical evolution of demand and generation. The importance of considering this evolution is analyzed and the methodology is applied to two standard networks, namely the Institute of Electrical and Electronics Engineers (IEEE) 30-bus and the IEEE 118-bus. The proposed algorithm is based on the use of particle swarm optimization (PSO). In addition, the use of an initialization process based on the cross entropy (CE) method to accelerate convergence in problems of high computational cost is explored. The results of the case studies highlight the importance of considering dynamic demand and generation profiles to reach an effective integration of renewable resources (RRs) towards a sustainable development of electric systems.
Solar Energy Production for a Decarbonization Scenario in Spain
Authors: Sánchez-Durán Rafael , Barbancho Julio , Luque Joaquín
Published: December 2019

Solar energy is one of the most promising sources of energy that could be used to address distributed supply problems. Global warming and decarbonization are significant global concerns, particularly for countries that are not fossil fuel providers. This paper presents a study focused on Spain, a country with a favorable location with respect to horizontal irradiance. The study addresses the future energy demand forecast and how photovoltaic energy could supply an important part of electricity needs. Our approach focuses on two analyses. First, several traditional statistical techniques are discussed in order to obtain a model that best suits Spanish energy demand forecasts for the future years. Different algorithms are compared in order to determine which is the most appropriate for the considered purpose. Second, the evolution of solar photovoltaic technology in Spain is analyzed. The latitude of Spanish cities makes them suitable for utilizing this kind of technology. In this sense, seasonal and monthly trends are identified with high levels of detail, considering a large historical dataset. The increase of the capacity of electricity generation based on this procedure is evaluated. Finally, a discussion about matching electricity demand forecasts and photovoltaic production is offered. Considering the selected model for the photovoltaic power of Spain, from 5 to 42 GW in 2030, the Spanish production is determined as 81 TWh. The obtained results suggest that a possible energy transition is feasible. However, some challenges have to be considered, such us the design of an effective strategy to store excess energy produced when generation is higher than electricity demand. In this way, the electrical distribution system could be fed by the stored energy when solar energy production is deficient.
Predicting and Explaining the Acceptance of Social Video Platforms for Learning: The Case of Brazilian YouTube Users
Authors: Ramírez-Correa Patricio , Mariano-Melo Ari , Alfaro-Pérez Jorge
Published: December 2019

This study aims to predict and explain the acceptance of social video platforms for learning. A research model is proposed that explains that the intention of using these platforms is based on the perception of performance, social influence, and hedonic motivation. To validate the model, 568 Brazilian YouTube users were surveyed. The data were analyzed with partial least squares structural equations modeling (PLS-SEM). In particular, the predictive power of the model was assessed using the PLSpredict procedure. The results of this study can help to understand and forecast the use of these platforms for learning in developing countries.
Comparative Investigation of the Effect of Recycled Fine Aggregate from New and Old Construction Wastes in C-25 Concrete in Ethiopia
Authors: Nigussie Lucy Feleke , Darwish Muge Mukaddes , Ghebrab Tewodros
Published: December 2019

Wherever there are construction activities, there is waste generation. In Ethiopia, the popular material for wall construction is a hollow concrete block that can be broken on the production site or the construction site during loading and unloading and is also found abundantly in demolished buildings. This research aimed at searching for alternative construction materials through recycling and examined the properties of recycled fine aggregate from demolished (old) and construction (new) hollow concrete block (HCB) wastes. The study examined the effect of the recycled HCB on fresh and hardened C-25 concrete properties and the possible replacement percentage of river sand by those recycled fine aggregates. The research also examined the comparative properties of the two recycled fine aggregates. The replacement percentage was in steps of 25%, starting from 25% up to 100%, and 0% represented the reference mix. In general, the recycled fine aggregate exhibited relatively lower physical properties than natural river sand but satisfied the American Society for Testing and Materials (ASTM) standard requirements. The demolished recycled fine aggregate (DRFA) had slightly lower physical properties than the construction recycled fine aggregate (CRFA). The properties of fresh and hardened concrete were decreased as percentage replacement of DRFA and CRFA increased. The optimum percentage replacement of river sand by recycled fine aggregate was between 50% to 75% but was much closer to 75% for that of recycled from construction (new) and closer to 50% for that of recycled from demolished (old) HCB. Recycling wastes can reduce environmental impact due to sand mining and waste disposal as well as partially conserve the natural resource depletion.