bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Phytochemical Composition of Pomegranate Fruit Juices, Peels and Kernels: A Comparative Study on Four Cultivars Grown in Southern Italy
Authors: Montefusco Anna , Durante Miriana , Migoni Danilo , De Caroli Monica , Ilahy Riadh , Pék Zoltán , Helyes Lajos , Fanizzi Francesco Paolo , Mita Giovanni , Piro Gabriella , Lenucci Marcello Salvatore
Published: November 2021

The increasing popularity of pomegranate (Punica granatum L.), driven by the awareness of its nutraceutical properties and excellent environmental adaptability, is promoting a global expansion of its production area. This investigation reports the variability in the weight, moisture, pH, total soluble solids, carbohydrates, organic acids, phenolic compounds, fatty acids, antioxidant activities, and element composition of different fruit parts (juices, peels, and kernels) from four (Ako, Emek, Kamel, and Wonderful One) of the most widely cultivated Israeli pomegranate varieties in Salento (South Italy). To the best of our knowledge, this is the first systematic characterization of different fruit parts from pomegranate cultivars grown simultaneously in the same orchard and subjected to identical agronomic and environmental conditions. Significant genotype-dependent variability was observed for many of the investigated parameters, though without any correlation among fruit parts. The levels of phenols, flavonoids, anthocyanins, and ascorbic and dehydroascorbic acids of all samples were higher than the literature-reported data, as was the antioxidant activity. This is likely due to positive interactions among genotypes, the environment, and good agricultural practices. This study also confirms that pomegranate kernels and peels are, respectively, rich sources of punicic acid and phenols together, with several other bioactive molecules. However, the variability in their levels emphasizes the need for further research to better exploit their agro-industrial potential and thereby increase juice-production chain sustainability. This study will help to assist breeders and growers to respond to consumer and industrial preferences and encourage the development of biorefinery strategies for the utilization of pomegranate by-products as nutraceuticals or value-added ingredients for custom-tailored supplemented foods.
Valorization of Fig (Ficus carica L.) Waste Leaves: HPLC-QTOF-MS/MS-DPPH System for Online Screening and Identification of Antioxidant Compounds
Authors: Li Chunying , Yu Meiting , Li Shen , Yang Xue , Qiao Bin , Shi Sen , Zhao Chunjian , Fu Yujie
Published: November 2021

Fig (Ficus carica L.) leaves are produced each year and often disposed, resulting in a waste of resources. Fig waste leaves are rich in flavonoids, which have strong antioxidant activity; however, the variety and chemical structure of antioxidants in fig leaves have not been reported in detail. To take full advantage of fig waste leaves, antioxidant capacity of different extracts (petroleum ether, ethyl acetate, and water) was evaluated by 1, 1-diphenyl-2-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic) acid (ABTS), and ferric-ion-reducing antioxidant power (FRAP) methods. The results showed that flavonoids in ethyl acetate extraction had the highest content (83.92 ± 0.01 mg/g), maximum DPPH scavenging activity (IC50 0.54 mg/mL), highest ABTS scavenging rate (80.28%), and FRAP (3.46 mmol/g). Furthermore, an HPLC-QTOF-MS/MS-DPPH method was developed to identify 11 flavonoids in fig waste leaves. This rapid and efficient method can not only be used for screening the antioxidant components in fig waste leaves, but also can be combined with mass spectrometry to identify the compounds with antioxidant capacity. There are three flavonoids with significant antioxidant capacity, which are 3-O-(rhamnopyranosyl-glucopyranosyl)-7-O-(glucopyranosyl)-quercetin, isoschaftoside, and rutin. The results confirmed that fig waste leaves contain a variety of antioxidant components, which contributed to increase the value of fig waste leaves as antioxidants.
Screening of the Chemical Composition and Identification of Hyaluronic Acid in Food Supplements by Fractionation and Fourier-Transform Infrared Spectroscopy
Authors: Mirzayeva Tamilla , Čopíková Jana , Kvasnička František , Bleha Roman , Synytsya Andriy
Published: November 2021

Hyaluronic acid, together with collagen, vitamins or plant extracts, is a part of many cosmetic and food preparations. For example, this polysaccharide is used in formulation of many food supplements due to its protective effects on human health. In this work, the screening of the chemical composition of three chosen dietary supplements (powder, tablets and capsules) containing hyaluronic acid was carried out using Fourier-transform infrared spectroscopy. Because of the low amount of analyte in all these samples, it was isolated or concentrated prior to the analysis using a suitable sequential fractionation protocol. Individual isolation procedures were established for each sample based on their declared composition. Firstly, the major components such as collagen or vitamins were removed to obtain polysaccharide fractions by the enzymatic treatment and/or washing out with the appropriate solvents. In some cases, the water insoluble part was removed from the rest dissolved in water. Then, hyaluronic acid was precipitated with copper(II) cations and thus separated from the other polysaccharides. Finally, the analyte was identified in the enriched fractions by the characteristic vibrational bands. The amount of hyaluronic acid in the purified fractions was determined in three ways: gravimetrically, spectrophotometrically, and using isotachophoresis. The combination of the appropriate preparative and analytical steps led to the successful evaluation of chemical composition, finding and quantification of hyaluronic acid in all the studied samples.
Fabrication of High-Performance CNT Reinforced Polymer Composite for Additive Manufacturing by Phase Inversion Technique
Authors: Parnian Pooyan , D’Amore Alberto
Published: November 2021

Additive Manufacturing (AM) of polymer composites has enabled the fabrication of highly customized parts with notably mechanical properties, thermal and electrical conductivity compared to un-reinforced polymers. Employing the reinforcements was a key factor in improving the properties of polymers after being 3D printed. However, almost all the existing 3D printing methods could make the most of disparate fiber reinforcement techniques, the fused filament fabrication (FFF) method is reviewed in this study to better understand its flexibility to employ for the proposed novel method. Carbon nanotubes (CNTs) as a desirable reinforcement have a great potential to improve the mechanical, thermal, and electrical properties of 3D printed polymers. Several functionalization approaches for the preparation of CNT reinforced composites are discussed in this study. However, due to the non-uniform distribution and direction of reinforcements, the properties of the resulted specimen do not change as theoretically expected. Based on the phase inversion method, this paper proposes a novel technique to produce CNT-reinforced filaments to simultaneously increase the mechanical, thermal, and electrical properties. A homogeneous CNT dispersion in a dilute polymer solution is first obtained by sonication techniques. Then, the CNT/polymer filaments with the desired CNT content can be obtained by extracting the polymer’s solvent. Furthermore, optimizing the filament draw ratio can result in a reasonable CNT orientation along the filament stretching direction.
Insights on the Molecular Behavior of Polypropylene in the Process of Ultrasonic Injection Molding
Authors: Iturbe-Ek Jackeline , Sustaita Alan O. , Aguilar-Viches Diego , Mata-Padilla José Manuel , Ávila-Orta Carlos A. , Elizalde Luis E. , Elías-Zúñiga Alex , Lozano Luis Marcelo
Published: November 2021

Product miniaturization is a constant trend in industries that demand ever-smaller products that can be mass produced while maintaining high precision dimensions in the final pieces. Ultrasonic micro injection molding (UMIM) technology has emerged as a polymer processing technique capable of achieving the mass production of polymeric parts with micro-features, while still assuring replicability, repeatability, and high precision, contrary to the capabilities of conventional processing technologies of polymers. In this study, it is shown that the variation of parameters during the UMIM process, such as the amplitude of the ultrasound waves and the processing time, lead to significant modification on the molecular structure of the polymer. The variation of both the amplitude and processing time contribute to chain scission; however, the processing time is a more relevant factor for this effect as it is capable of achieving a greater chain scission in different areas of the same specimen. Further, the presence of polymorphism within the samples produced by UMIM is demonstrated. Similarly to conventional processes, the UMIM technique leads to some degree of chain orientation, despite the fact that it is carried out in a relatively small time and space. The results presented here aim to contribute to the optimization of the use of the UMIM process for the manufacture of polymeric micro parts.
Development of Oil and Gas Stimulation Fluids Based on Polymers and Recycled Produced Water
Authors: AlKhowaildi Mustafa , Tawabini Bassam , Kamal Muhammad , Mahmoud Mohamed , Aljawad Murtada , Bataweel Mohammed
Published: November 2021

Freshwater scarcity is a highly pressing and accelerating issue facing our planet. Therefore, there is a great incentive to develop sustainable solutions by reusing wastewater or produced water (PW), especially in places where it is generated abundantly. PW represents the water produced as a by-product during oil and gas extraction operations in the petroleum industry. It is the largest wastewater stream within the industry, with hundreds of millions of produced water barrels per day worldwide. This research investigates a reuse opportunity for PW to replace freshwater utilization in well stimulation applications. Introducing an environmentally friendly chelating agent (GLDA) allowed formulating a PW-based fluid system that has similar rheological properties in fresh water. This work aims at evaluating the rheological properties of the developed stimulation fluid. The thickening profile of the fluid was controlled by chelation chemistry and varying different design parameters. The experiments were carried out using a high-pressure, high-temperature (HPHT) viscometer. Variables such as polymer concentration and pH have a great impact on the viscosity, while temperature and concentration of the chelating agents are shown to control the thickening profile, as well as its stability and breakage behaviors. Furthermore, 50 pptg of carboxymethyl hydroxypropyl guar (CMHPG) polymer in 20 wt.% chelating solution was shown to sustain 172 cP viscosity for nearly 2.5 h at 150 °F and 100 S−1 shear rate. The newly developed fluid system, solely based on polymer, chelating agent, and PW, showed great rheological capabilities to replace the conventional stimulation fluids based on fresh water. The newly developed fluid can also have economic value realization due to fewer additives, compared with conventional fluids.
Optimization of Chitosan Properties with the Aim of a Water Resistant Adhesive Development
Authors: Silvestre Jeanne , Delattre Cédric , Michaud Philippe , de Baynast Hélène
Published: November 2021

Chitosan is a bio-sourced polysaccharide widely used in different fields from health to wastewater treatment through food supplements. Another important use of this polymer is adhesion. Indeed, the current demand to replace non-natural and hazardous polymers by greener ones is well present in the adhesive field and open good opportunities for chitosan and its derivatives. However, chitosan is water soluble and exhibits a poor water-resistance in the field of adhesion which reduces the possibilities of its utilization within the paste field. This review focuses on exploration of different ways available to modify the chitosan and transform it into a water-resistant adhesive. The first part concerns the chitosan itself and gives important information from the discovery of chitin to the pure chitosan ready to use. The second part reviews the background information relative to adhesion theories, ideal properties of adhesives and the characteristics of chitosan as an adhesive. The last part focuses on exploration of the possible modification of chitosan to make it a water-resistant chemical adhesive.
Effects of Albedo and Thermal Inertia on Pavement Surface Temperatures with Convective Boundary Conditions—A CFD Study
Authors: Acharya Tathagata , Riehl Brooke , Fuchs Alan
Published: November 2021

The urban heat island (UHI) effect increases the ambient temperatures in cities and alters the energy budget of building materials. Urban surfaces such as pavements and roofs absorb solar heat and re-emit it back into the atmosphere, contributing towards the UHI effect. Over the past few decades, researchers have identified albedo and thermal inertia as two of the most significant thermal properties that influence pavement surface temperatures under a given solar load. However, published data for comparisons of albedo and thermal inertia are currently inadequate. This work focuses on asphalt and concrete as two important materials used in the construction of pavements. Computational fluid dynamics (CFD) analyses are performed on asphalt and concrete pavements with the same dimensions and under the same ambient conditions. Under given conditions, the pavement top surface temperature is evaluated with varying albedo and thermal inertia values. The results show that the asphalt surface temperatures are consistently higher than the concrete surface temperatures. Surface temperatures under solar load reduce with increasing albedo and thermal inertia values for both asphalt and concrete pavements. The CFD results show that increasing the albedo is more effective in reducing pavement surface temperatures than increasing the thermal inertia.
Inspiration and Revelation of the Qur’an and Its Relation to the Bible
Authors: Galadari Abdulla
Published: November 2021

The Qur’an often compares its own inspiration and revelation with previous scriptures to its audience. However, the Jews and Christians in Late Antiquity had manifold understandings of the inspiration and revelation of scripture. The rabbinic tradition posits various degrees of inspiration behind canonical scriptures: the Torah was dictated by God to Moses, while other prophets had lesser degrees of divine inspiration. Many Christian churches typically held a dual authorship concept, where the human author wrote under the inspiration of a divine author. Many Muslim traditions held various understandings of the agency, or lack thereof, of Muḥammad in the utterances of the Qur’an. Nonetheless, the Qur’an claims that its own inspiration is no different from some biblical books. Since the rabbinic and Christian views differ, it is imperative to understand the Qur’anic concept of itself on inspiration and revelation (waḥy and tanzīl), especially since it compares itself with other scriptures. Additionally, it is argued that the Qur’an’s self-referentiality as a “kitāb” that descends does not necessarily denote a “book” (neither heavenly nor earthly), but an order or commandment, which is more loyal to the root definition.
GIS-Based Groundwater Potential Assessment in Varied Topographic Areas of Mianyang City, Southwestern China, Using AHP
Authors: Zhang Qing , Zhang Shuangxi , Zhang Yu , Li Mengkui , Wei Yu , Chen Meng , Zhang Zeyi , Dai Zhouqing
Published: November 2021

Mianyang City is located in the varied topographic areas of Sichuan Province in southwestern China and is characterized by a complex geological background. This area is prone to disasters and its varied topography is inconvenient for emergency water storage and supply. Groundwater is essential for alleviating the demand for water and post-disaster emergency water supply in this area. This study applied AHP to integrate remote sensing, geological and hydrological data into GIS for the assessment of groundwater potential, providing a plan for the rational exploitation of groundwater and post-disaster emergency water supply in the area. Nine factors, including the spring calibration related to groundwater, were integrated by AHP after multicollinear checks. As a result, the geology-controlled groundwater potential map was classified into five levels with equal intervals. All the results were validated using borehole data, indicating the following: the areas with yield rates of <1t/d·m, 1–20 t/d·m, and 20–400 t/d·m accounted for 2.66%, 36.1%, and 39.62%, respectively, whereas the areas with yield rates of 400–4000 t/d·m and >4000t/d·m accounted for only 20.88% and 0.75% of the overall area. The flexibility of this quick and efficient method enables its application in other regions with a similar geological background.
Investigating the Effects of k and Area Size on Variance Estimation of Multiple Pixel Areas Using a k-NN Technique for Forest Parameters
Authors: Walshe Dylan , McInerney Daniel , Paulo Pereira João , Byrne Kenneth A.
Published: November 2021

Combining auxiliary variables and field inventory data of forest parameters using the model-based approach is frequently used to produce synthetic estimates for small areas. These small areas arise when it may not be financially feasible to take ground measurements or when such areas are inaccessible. Until recently, these estimates have been calculated without providing a measure of the variance when aggregating multiple pixel areas. This paper uses a Random Forest algorithm to produce estimates of quadratic mean diameter at breast height (QMDBH) (cm), basal area (m2 ha−1), stem density (n/ha−1), and volume (m3 ha−1), and subsequently estimates the variance of multiple pixel areas using a k-NN technique. The area of interest (AOI) is the state owned commercial forests in the Slieve Bloom mountains in the Republic of Ireland, where the main species are Sitka spruce (Picea sitchensis (Bong.) Carr.) and Lodgepole pine (Pinus contorta Dougl.). Field plots were measured in summer 2018 during which a lidar campaign was flown and Sentinel 2 satellite imagery captured, both of which were used as auxiliary variables. Root mean squared error (RMSE%) and R2 values for the modelled estimates of QMDBH, basal area, stem density, and volume were 19% (0.70), 22% (0.67), 28% (0.62), and 26% (0.77), respectively. An independent dataset of pre-harvest forest stands was used to validate the modelled estimates. A comparison of measured values versus modelled estimates was carried out for a range of area sizes with results showing that estimated values in areas less than 10–15 ha in size exhibit greater uncertainty. However, as the size of the area increased, the estimated values became increasingly analogous to the measured values for all parameters. The results of the variance estimation highlighted: (i) a greater value of k was needed for small areas compared to larger areas in order to obtain a similar relative standard deviation (RSD) and (ii) as the area increased in size, the RSD decreased, albeit not indefinitely. These results will allow forest managers to better understand how aspects of this variance estimation technique affect the accuracy of the uncertainty associated with parameter estimates. Utilising this information can provide forest managers with inventories of greater accuracy, therefore ensuring a more informed management decision. These results also add further weight to the applicability of the k-NN variance estimation technique in a range of forests landscapes.
Quantitative Evaluation of the Soil Signal Effect on the Correlation between Sentinel-1 Cross Ratio and Snow Depth
Authors: Feng Tianwen , Hao Xiaohua , Wang Jian , Li Hongyi , Zhang Juan
Published: November 2021

High-resolution Synthetic Aperture Radar (SAR), as an efficient Earth observation technology, can be used as a complementary means of observation for snow depth (SD) and can address the spatial heterogeneity of mountain snow. However, there is still uncertainty in the SD retrieval algorithm based on SAR data, due to soil surface scattering. The aim of this study is to quantify the impact of soil signals on the SD retrieval method based on the cross-ratio (CR) of high-spatial resolution SAR images. Utilizing ascending Sentinel-1 observation data during the period from November 2016 to March 2020 and a CR method based on VH- and VV-polarization, we quantitatively analyzed the CR variability characteristics of rock and soil areas within typical thick snow study areas in the Northern Hemisphere from temporal and spatial perspectives. The correlation analysis demonstrated that the CR signal in rock areas at a daily timescale shows a strong correlation (mean value > 0.60) with snow depth. Furthermore, the soil areas are more influenced by freeze-thaw cycles, such that the monthly CR changes showed no or negative trend during the snow accumulation period. This study highlights the complexity of the physical mechanisms of snow scattering during winter processes and the influencing factors that cause uncertainty in the SD retrieval, which help to promote the development of high-spatial resolution C-band data for snow characterization applications.
Monitoring the Spring Flood in Lena Delta with Hydrodynamic Modeling Based on SAR Satellite Products
Authors: Pertiwi Avi Putri , Roth Achim , Schaffhauser Timo , Bhola Punit Kumar , Reuß Felix , Stettner Samuel , Kuenzer Claudia , Disse Markus
Published: November 2021

Due to the remote location and the extreme climate, monitoring stations in Arctic rivers such as Lena in Siberia have been decreasing through time. Every year, after a long harsh winter, the accumulated snow on the Lena watershed melts, leading to the major annual spring flood event causing heavy transport of sediments, organic carbon, and trace metals, both into as well as within the delta. This study aims to analyze the hydrodynamic processes of the spring flood taking place every year in the Lena Delta. Thus, a combination of remote sensing techniques and hydrodynamic modeling methodologies is used to overcome limitations caused by missing ground-truth data. As a test site for this feasibility study, the outlet of the Lena River to its delta was selected. Lena Delta is an extensive wetland spanning from northeast Siberia into the Arctic Ocean. Spaceborne Synthetic Aperture Radar (SAR) data of the TerraSAR-X/TanDEM-X satellite mission served as input for the hydrodynamic modeling software HEC-RAS. The model resulted in inundation areas, flood depths, and flow velocities. The model accuracy assessed by comparing the multi-temporal modeled inundation areas with the satellite-derived inundation areas ranged between 65 and 95%, with kappa coefficients ranging between 0.78 and 0.97, showing moderate to almost perfect levels of agreement between the two inundation boundaries. Modeling results of high flow discharges show a better agreement with the satellite-derived inundation areas compared to that of lower flow discharges. Overall, the remote-sensing-based hydrodynamic modeling succeeded in indicating the increase and decrease in the inundation areas, flood depths, and flow velocities during the annual flood events.
Proximal-Sensing-Powered Modelling of Energy-Water Fluxes in a Vineyard: A Spatial Resolution Analysis
Authors: Paciolla Nicola , Corbari Chiara , Maltese Antonino , Ciraolo Giuseppe , Mancini Marco
Published: November 2021

Spatial resolution is a key parameter in energy–water surface flux modelling. In this research, scale effects are analyzed on fluxes modelled with the FEST-EWB model, by upscaling both its inputs and outputs separately. The main questions are: (a) if high-resolution remote sensing images are necessary to accurately model a heterogeneous area; and (b) whether and to what extent low-resolution modelling provides worse/better results than the upscaled results of high-resolution modelling. The study area is an experimental vineyard field where proximal sensing images were obtained by an airborne platform and verification fluxes were measured via a flux tower. Modelled fluxes are in line with those from alternative energy-balance models, and quite accurate (NSE = 0.78) with respect to those measured in situ. Field-scale evapotranspiration has resulted in both the tested upscaling approaches (with relative error within ±30%), although fewer pixels available for low-resolution calibration may produce some differences. When working at low resolutions, the model has produced higher relative errors (20% on average), but is still within acceptable bounds. This means that the model can produce high-quality results, partially compensating for the loss in spatial heterogeneity associated with low-resolution images.
Building Polygon Extraction from Aerial Images and Digital Surface Models with a Frame Field Learning Framework
Authors: Sun Xiaoyu , Zhao Wufan , Maretto Raian V. , Persello Claudio
Published: November 2021

Deep learning-based models for building delineation from remotely sensed images face the challenge of producing precise and regular building outlines. This study investigates the combination of normalized digital surface models (nDSMs) with aerial images to optimize the extraction of building polygons using the frame field learning method. Results are evaluated at pixel, object, and polygon levels. In addition, an analysis is performed to assess the statistical deviations in the number of vertices of building polygons compared with the reference. The comparison of the number of vertices focuses on finding the output polygons that are the easiest to edit by human analysts in operational applications. It can serve as guidance to reduce the post-processing workload for obtaining high-accuracy building footprints. Experiments conducted in Enschede, the Netherlands, demonstrate that by introducing nDSM, the method could reduce the number of false positives and prevent missing the real buildings on the ground. The positional accuracy and shape similarity was improved, resulting in better-aligned building polygons. The method achieved a mean intersection over union (IoU) of 0.80 with the fused data (RGB + nDSM) against an IoU of 0.57 with the baseline (using RGB only) in the same area. A qualitative analysis of the results shows that the investigated model predicts more precise and regular polygons for large and complex structures.
Phase Shift Migration with Modified Coherent Factor Algorithm for MIMO-SAR 3D Imaging in THz Band
Authors: Yang Guan , Li Chao , Wu Shiyou , Zheng Shen , Liu Xiaojun , Fang Guangyou
Published: November 2021

In multiple-input-multiple-output synthetic aperture radar (MIMO-SAR) systems, sparse arrays are usually applied, resulting in increased sidelobes of the point spread function. In this paper, a phase shift migration (PSM) imaging algorithm based on the explosion reflection model with modified coherent factor was proposed for sidelobe suppression in MIMO-SAR three-dimensional (3D) imaging application. By defining the virtual difference wavenumber, reconstructing the raw echo by data rearrangement in wavenumber domain, the original coherent factor algorithm operating in spatial domain can be achieved by the PSM algorithm frame in the wavenumber domain, which means two orders of magnitude increase in computational efficiency. The correctness of the theory is verified by simulation. Finally, a bistatic prototype imaging system in the 0.3 THz band was designed for the proof-of-principle experiments. The experimental results show that the proposed algorithm has a 0.948 structural similarity value to the original coherent factor back-projection algorithm (CF-BPA) which means comparable image quality with much superior efficiency.
Crop Water Stress Index as a Proxy of Phenotyping Maize Performance under Combined Water and Salt Stress
Authors: Gu Shujie , Liao Qi , Gao Shaoyu , Kang Shaozhong , Du Taisheng , Ding Risheng
Published: November 2021

The crop water stress index (CWSI), based on canopy temperature (Tc), has been widely used in evaluating plant water status and planning irrigation scheduling, but whether CWSI can diagnose the stress status of crops and predict the physiological traits and growth under combined water and salt stress remains to be further studied. Here, a model of CWSI was established based on the continuous measurements of Tc for two maize genotypes (ZD958 and XY335) under two water and salt conditions, combined with growth stage-specific non-water-stressed baselines (NWSB). The relationships between physiology, growth, and yield of maize with CWSI were analyzed. There were significant differences in NWSB between the two maize genotypes at the same and different growth stages; thus, growth stage-specific NWSBs were used. The difference in NWSB was due to the difference and change in effective leaf width. CWSI was closely related to leaf water potential, stomatal conductance, and net photosynthetic rate under different water and salt stress, and also explained the variations in leaf area index, biomass, water use, and yield. Collectively, CWSI can be used as a proxy indicator of high-throughput phenotyping maize performance under combined water and salt stress, which will be valuable for predicting yield and improving water use efficiency.
A Two-Stage Multistep-Ahead Electricity Load Forecasting
Scheme Based on LightGBM and Attention-BiLSTM
Authors: Park Jinwoong , Hwang Eenjun
Published: November 2021

An efficient energy operation strategy for the smart grid requires accurate day-ahead electricity load forecasts with high time resolutions, such as 15 or 30 min. Most high-time resolution electricity load prediction techniques deal with a single output prediction, so their ability to cope with sudden load changes is limited. Multistep-ahead forecasting addresses this problem, but conventional multistep-ahead prediction models suffer from deterioration in prediction performance as the prediction range is expanded. In this paper, we propose a novel two-stage multistep-ahead forecasting model that combines a single-output forecasting model and a multistep-ahead forecasting model to solve the aforementioned problem. In the first stage, we perform a single-output prediction based on recent electricity load data using a light gradient boosting machine with time-series cross-validation, and feed it to the second stage. In the second stage, we construct a multistep-ahead forecasting model that applies an attention mechanism to sequence-to-sequence bidirectional long short-term memory (S2S ATT-BiLSTM). Compared to the single S2S ATT-BiLSTM model, our proposed model achieved improvements of 3.23% and 4.92% in mean absolute percentage error and normalized root mean square error, respectively.
Development and Piezoelectric Properties of a Stack Units-Based Piezoelectric Device for Roadway Application
Authors: Li Chenchen , Yang Fan , Liu Pengfei , Fu Chaoliang , Liu Quan , Zhao Hongduo , Lin Peng
Published: November 2021

To improve the energy harvesting efficiency of the piezoelectric device, a stack units-based structure was developed and verified. Factors such as stress distribution, load resistance, loads, and loading times influencing the piezoelectric properties were investigated using theoretical analysis and experimental tests. The results show that the unit number has a negative relationship with the generated energy and the stress distribution has no influence on the power generation of the piezoelectric unit array. However, with a small stress difference, units in a parallel connection can obtain high energy conversion efficiency. Additionally, loaded with the matched impedance of 275.0 kΩ at 10.0 kN and 10.0 Hz, the proposed device reached a maximum output power of 84.3 mW, which is enough to supply the low-power sensors. Moreover, the indoor load test illustrates that the electrical performance of the piezoelectric device was positively correlated with the simulated loads when loaded with matched resistance. Furthermore, the electrical property remained stable after the fatigue test of 100,000 cyclic loads. Subsequently, the field study confirmed that the developed piezoelectric device had novel piezoelectric properties with an open-circuit voltage of 190 V under an actual tire load, and the traffic parameters can be extracted from the voltage waveform.
CP Antenna with 2 × 4 Hybrid Coupler for Wireless Sensing and Hybrid RF Solar Energy Harvesting
Authors: Mujahidin Irfan , Kitagawa Akio
Published: November 2021

The main challenge faced by RF energy harvesting systems is to supply relatively small electrical power to wireless sensor devices using microwaves. The solution is to implement a new device in a circularly polarized rectenna with circular polarization sensitivity integrated with a thin-film solar cell. Its dual-feed antennas are connected to a 2 × 4 asymmetric hybrid coupler and a multi-stage voltage doubler rectifier circuit. This configuration has a 2 × 4 asymmetric hybrid coupler used to produce 4 outputs with a 90-degree waveform phase difference. The two ports can independently be connected to the wireless sensor circuit: radiofrequency harvesting of hybrid energy solar and information equipment can be carried out with these two antennas. The Dual-Feed circular patch antenna has a two-port bandwidth of 137 MHz below −15 dB and an axial ratio of less than 3 dB, with a center frequency of 2.4 GHz with directional radiation and a high gain of 8.23 dB. It can be sensitive to arbitrary polarization of the input voltage multiplier waveform to overcome uncertainty in empirical communication environments. A parallel structure is arranged with a thin film solar cell integration from the transmitter with an output voltage of 1.3297 V with a compact composition and RF energy. The importance of adopting a wireless sensor strategy with circular polarization sensitivity and integrated RF solar energy harvesting rather than a single source method makes this research a significant novelty by optimizing the analysis of multiple wireless sensor signal access.
KOSMOS: An Open Source Underwater Video Lander for Monitoring Coastal Fishes and Habitats
Authors: Pelletier Dominique , Rouxel Justin , Fauvarque Olivier , Hanon David , Gestalin Jean-Paul , Lebot Morgann , Dreano Paul , Furet Enora , Tardivel Morgan , Le Bras Yvan , Royaux Coline , Leguen Guillaume
Published: November 2021

Background: Monitoring the ecological status of coastal ecosystems is essential to track the consequences of anthropogenic pressures and assess conservation actions. Monitoring requires periodic measurements collected in situ, replicated over large areas and able to capture their spatial distribution over time. This means developing tools and protocols that are cost-effective and provide consistent and high-quality data, which is a major challenge. A new tool and protocol with these capabilities for non-extractively assessing the status of fishes and benthic habitats is presented here: the KOSMOS 3.0 underwater video system. Methods: The KOSMOS 3.0 was conceived based on the pre-existing and successful STAVIRO lander, and developed within a digital fabrication laboratory where collective intelligence was contributed mostly voluntarily within a managed project. Our suite of mechanical, electrical, and software engineering skills were combined with ecological knowledge and field work experience. Results: Pool and aquarium tests of the KOSMOS 3.0 satisfied all the required technical specifications and operational testing. The prototype demonstrated high optical performance and high consistency with image data from the STAVIRO. The project’s outcomes are shared under a Creative Commons Attribution CC-BY-SA license. The low cost of a KOSMOS unit (~1400 €) makes multiple units affordable to modest research or monitoring budgets.
Over-Actuated Underwater Robots: Configuration Matrix Design and Perspectives
Authors: Dang Tho , Lapierre Lionel , Zapata Rene , Ropars Benoit , Lepinay Pascal
Published: November 2021

In general, for the configuration designs of underwater robots, the positions and directions of actuators (i.e., thrusters) are given and installed in conventional ways (known points, vertically, horizontally). This yields limitations for the capability of robots and does not optimize the robot’s resources such as energy, reactivity, and versatility, especially when the robots operate in confined environments. In order to optimize the configuration designs in the underwater robot field focusing on over-actuated systems, in the paper, performance indices (manipulability, energetic, reactive, and robustness indices) are introduced. The multi-objective optimization problem was formulated and analyzed. To deal with different objectives with different units, the goal-attainment method, which can avoid the difficulty of choosing a weighting vector to obtain a good balance among these objectives, was selected to solve the problem. A solution design procedure is proposed and discussed. The efficiency of the proposed method was proven by simulations and experimental results.
Fiber Optic Load Cells with Enhanced Sensitivity by Optical Vernier Effect
Authors: Paixão Tiago , Ferreira Ricardo , Domingues M. Fátima , Antunes Paulo
Published: November 2021

Developing technologies capable of constantly assessing and optimizing day-to-day activities has been a research priority for several years. A key factor in such technologies is the use of highly sensitive sensors to monitor in real-time numerous parameters, such as temperature and load. Due to their unique features, optical fiber sensors became one of the most interesting and viable solutions for applications dependent on those parameters. In this work, we present an optical fiber load sensor, called load cell, based on Fabry–Pérot hollow cavities embedded in a polymeric material. By using the load cells in a parallel configuration with a non-embedded hollow cavity, the optical Vernier effect was generated, allowing maximum sensitivity values of 0.433 nm N−1 and 0.66 nm °C−1 to be attained for vertical load and temperature, respectively. The proposed sensor’s performance, allied with the proposed configuration, makes it a viable and suitable device for a wide range of applications, namely those requiring high thermal and load sensitivities.
The Staircase Drive—A Novel Actuator Design Optimised for Daisy-Chaining and Minimum Stress Load Coupling
Authors: Hoffmann Falk-Martin , Holland Keith R. , Harris Nick R. , White Neil M. , Fazi Filippo Maria
Published: November 2021

This work presents a novel type of actuator that improves over the standard cantilever by permitting daisy-chaining while minimising stress to the joint connecting to the load. A detailed structural and functional comparison of the proposed device against the cantilever actuator as a baseline is given, led by a brief revision of the cantilever actuator as the state-of-the-art that highlights its limitations with respect to daisy-chaining and the stress it inherently creates within the joint connecting to the load when attempting out-of-plane displacement without rotation. Simulations of both devices’ performance confirm that the newly proposed device yields the targeted displacement profile that both enables the daisy-chaining of such a device into a higher-order actuator for increased displacement and reduce stress in the joint with the load. This comes at the cost of reduced maximum displacement compared to the cantilever, which can be overcome by daisy-chaining. The proposed device’s performance is further evaluated on the basis of manufactured prototypes measured by means of a laser scanning vibrometer. The prototype was manufactured on a 150 μm alumina substrate, and both electrodes and piezoelectric layer were deposited in a thick-film printing process.
New Results on Small and Dim Infrared Target Detection
Authors: Wang Hao , Zhao Zehao , Kwan Chiman , Zhou Geqiang , Chen Yaohong
Published: November 2021

Real-time small infrared (IR) target detection is critical to the performance of the situational awareness system in high-altitude aircraft. However, current IR target detection systems are generally hardware-unfriendly and have difficulty in achieving a robust performance in datasets with clouds occupying a large proportion of the image background. In this paper, we present new results by using an efficient method that extracts the candidate targets in the pre-processing stage and fuses the local scale, blob-based contrast map and gradient map in the detection stage. We also developed mid-wave infrared (MWIR) and long-wave infrared (LWIR) cameras for data collection experiments and algorithm evaluations. Experimental results using both publicly available datasets and image sequences acquired by our cameras clearly demonstrated that the proposed method achieves high detection accuracy with the mean AUC being at least 22.3% higher than comparable methods, and the computational cost beating the other methods by a large margin.
NanoMIP-Based Solid Phase Extraction of Fluoroquinolones from Human Urine: A Proof-of-Concept Study
Authors: Chiarello Matteo , Anfossi Laura , Cavalera Simone , Di Nardo Fabio , Serra Thea , Baggiani Claudio
Published: November 2021

NanoMIPs that are prepared by solid phase synthesis have proven to be very versatile, but to date only limited attention has been paid to their use in solid phase extraction. Thus, since nanoMIPs show close similarities, in terms of binding behavior, to antibodies, it seems relevant to verify if it is possible to use them as mimics of the natural antibodies that are used in immunoextraction methods. As a proof-of-concept, we considered prepared nanoMIPs against fluoroquinolone ciprofloxacin. Several nanoMIPs were prepared in water with polymerization mixtures of different compositions. The polymer with the highest affinity towards ciprofloxacin was then grafted onto a solid support and used to set up a solid phase extraction–HPLC method with fluorescence detection, for the determination of fluoroquinolones in human urine. The method resulted in successful selection for the fluoroquinolone antibiotics, such that the nanoMIPs were suitable for direct extraction of the antibiotics from the urine samples at the µg mL−1 level. They required no preliminary treatment, except for a 1 + 9 (v/v) dilution with a buffer of pH 4.5 and they had good analyte recovery rates; up to 85% with precision in the range of 3 to 4.5%, without interference from the matrix. These experimental results demonstrate, for the first time, the feasibility of the use of nanoMIPs to develop solid phase extraction methods.
Willingness to Take the COVID-19 Vaccine as Reported Nine Months after the Pandemic Outbreak: A Cross-National Study
Authors: Price Daicia , Bonsaksen Tore , Ruffolo Mary , Leung Janni , Thygesen Hilde , Schoultz Mariyana , Geirdal Amy Ostertun
Published: November 2021

Although vaccination has been identified as an effective measure of reducing the spread of COVID-19, hesitancy to obtain a vaccine for COVID-19 has been shared. The aim of this cross-national study was to examine (i) the willingness in the general population to take the COVID-19 vaccine nine months after the pandemic outbreak and (ii) the willingness to take the vaccine in relation to sociodemographic variables, whether one has experienced COVID-19 infection, concerns about health and family, and trust in the authorities’ information about the pandemic. A cross-sectional survey design was used to collect data online in Norway, the UK, the USA, and Australia. Chi-Square tests or Fisher’s Exact test were used to analyze the data. Logistic regression analysis was used to assess direct associations between the independent variables and the outcome. Within the total sample (n = 3474), living in a city, having a college education, being concerned about your own health and the health of next of kin, and trusting information provided by authorities increased the likelihood of reporting willingness to take the COVID-19 vaccine. Across all countries, participants who reported trust in the authorities’ information about COVID-19 demonstrated a significantly higher plausibility of taking the COVID-19 vaccine.
The Incentive Mechanism of Knowledge Sharing in Cross-Border Business Models Based on Digital Technologies
Authors: Wang Yan , Yang Lifan , Russo Enzo , Graziano Domenico
Published: November 2021

This paper aims to solve the time-constrained problems of knowledge sharing caused by geographical distance and cultural differences in cross-border business models by proposing a novel knowledge sharing model based on principal–agent theory. Given that digital technologies (DTs) can solve the information asymmetry issue, this paper analyses and compares the contract parameters given by the principal, the efforts of the agent, and the changes in the expected profits of both parties before and after the application of DTs and therefore discusses the influence of various relevant factors in incentive contracts; the relationship between the expected profit of both parties and the various relevant factors is analyzed through numerical simulations. The results show that, in cross-border business models considering the time value of knowledge, the principal is affected not only by “information rent” and “channel loss” but also by the “time cost”. The application of DTs can effectively reduce all three of these costs. More importantly, the principal’s incentive coefficient and the agent’s effort are related to this time constraint and the application of DTs.
Does Corporate Social Responsibility Vary by Real Estate Asset Types? Evidence from Real Estate Investment Trusts
Authors: Liang Jian , Jain Ameeta , Wu Hao
Published: November 2021

This paper investigates how real estate investment trusts’ corporate social responsibility (CSR) (REITs) varies by two intrinsic firm factors: real estate asset types and REITs’ financial aspirations. We develop a conceptual model to demonstrate the theoretical role of these intrinsic firm factors in moderating CSR. Using a database containing the Morgan Stanley Capital International CSR rating index, we test REITs from 19 countries for variations of their CSR performance across each of the three pillars of CSR: environment, social, and governance (ES&G) by real estate asset types from 2009 to 2016. The results show that REITs focusing on less market-transparent real assets relying heavily on intensive human-based services and physical capital in property management like hotels and hospitals exhibit a poorer performance in environmental responsibility, social responsibility, and overall CSR score. We found no significant difference between the REITs in their governance responsibility with respect to the real estate asset types. We found that moderation by financial aspiration in establishing their CSR strategies varies by the types of real estate asset that REITs focus on, with the maximum positive impact on REITS with hotel holdings and negative impact on REITs with office and retail assets.
Barriers to Electric Vehicle Adoption in Thailand
Authors: Kongklaew Chanwit , Phoungthong Khamphe , Prabpayak Chanwit , Chowdhury Md. Shahariar , Khan Imran , Yuangyai Nuttaya , Yuangyai Chumpol , Techato Kuaanan
Published: November 2021

Electric vehicles (EVs) are considered to be a solution for sustainable transportation. EVs can reduce fossil fuel consumption, greenhouse gas emissions, and the negative impacts of climate change and global warming, as well as help improve air quality. However, EV adoption in Thailand is quite low. Against this backdrop, this study investigates barriers and motivators for EV adoption and their public perception in Thailand. A total of 454 responses were collected through an online questionnaire. The results indicate that the top three concerns of respondents about EVs are public infrastructure and vehicle performance in terms of charge range and battery life. Respondents with more than five years of driving experience in the age range of 26–35 years old could be key targets for early EV adoption.