bluuebunny/crossref_metadata_2025 huggingface dataset:
Essential Oil and Major Non-Volatile Secondary Metabolites from the Leaves of Amazonian Piper subscutatum
Authors: Ramírez Jorge , Andrade María Daniela , Vidari Giovanni , Gilardoni Gianluca
Published: June 2021

The essential oil and the major non-volatile secondary metabolites from the leaves of Piper subscutatum (Miq.) C. DC. (Family Piperaceae), collected in the Ecuadorian Amazon, were analyzed for the first time in the present study. The essential oil was submitted to chemical and enantioselective analyses by GC-MS and GC-FID. (E)-β-caryophyllene (25.3–25.2%), β-chamigrene (10.3–7.8%), (E)-nerolidol (8.1–7.7%), β-selinene (7.2–7.7%), δ-cadinene (2.7–3.9%), bicyclogermacrene (3.7–2.4%), and β-pinene (2.6–3.4%) were the major components. The enantioselective analysis, carried out on a β-cyclodextrin-based column, showed four scalemic mixtures in which (1R,5R)-(+)-α-pinene, (1S,5S)-(−)-β-pinene, (S)-(−)-limonene, and (1R,2S,6S,7S,8S)-(−)-α-copaene were the major enantiomers, with enantiomeric excesses of 28.8%, 77.8%, 18.4%, and 6.0%, respectively. The study was complemented with the chemical analysis of the organic fraction dissolved in the hydrolate, whose major components were 6-methyl-5-hepten-2-one (63.7–64.4%) and linalool (6.5–6.0%). Concerning the non-volatile fraction, five lignans were the major components. (–)-Beilshminol B, (–)-grandisin, (–)-3′,4′-methylenedioxy-3,4,5-trimethoxy-7,7′-epoxylignan, (–)-3′,4′-methylenedioxy-3,4,5,5′-tetramethoxy-7,7′-epoxylignan, and (–)-3,4,3′,4′-dimethylenedioxy-5,5′-dimethoxy-7,7′-epoxylignan were identified by means of NMR spectroscopy, mass spectrometry and X-ray crystallography. The absolute configuration 7S,8S,7′S,8′S was tentatively assigned to all of them.
Three β-Glucuronosyltransferase Genes Involved in Arabinogalactan Biosynthesis Function in Arabidopsis Growth and Development
Authors: Ajayi Oyeyemi O. , Held Michael A. , Showalter Allan M.
Published: June 2021

Arabinogalactan proteins (AGPs) contain arabinogalactan (AG) polysaccharides that are biologically relevant to plant growth processes. Here, the biochemical and physiological roles of three Golgi localized β-glucuronosyltransferase genes (GLCAT14A, GLCAT14B and GLCAT14C) in Arabidopsis thaliana, responsible for the addition of glucuronic acid to AG chains, were further investigated using single, double and triple glcat14 mutant plants. These proteins were localized to the Golgi apparatus when transiently expressed in Nicotiana benthamiana. Sugar analysis of AGP extracts from Arabidopsis stem, leaf and siliques showed a consistent reduction in glucuronic acid in glcat14 mutants relative to wild type, with concomitant effects resulting in tissue-specific alterations, especially in arabinose and galactose sugars. Although we observed defects in trichome branching in glca14a/b and glca14a/b/c mutants, scanning electron microscope analysis/energy dispersive microanalysis (SEM/EDX) showed no difference in the calcium content of trichomes in these mutants relative to wild type. Immunoblot analyses of the stem and leaf showed a reduction in AGPs as detected with the LM2 antibody in glcat14a/b and glcat14a/b/c mutants relative to wild type. The current work exemplifies the possibility of conducting structure-function assessment of cell wall biosynthetic genes to identify their physiological roles in plant growth and development.
Pre-Harvest Supplemental Blue Light Enhanced Antioxidant Activity of Flower Stalk in Chinese Kale during Storage
Authors: Jiang Haozhao , Li Xia , Tian Jialing , Liu Houcheng
Published: June 2021

For 10 days before harvest, supplemental 50 μmol m−2 s−1 blue light (430 nm) was applied in greenhouse conditions in order to evaluate the influences of pre-harvest supplemental blue light on both antioxidants and nutrition of the flower stalk of Chinese kale during storage. The weight loss of the flower stalk of Chinese kale treated with supplemental blue light was generally lower than control during storage. Higher antioxidant activity was maintained during storage by supplemental blue light. Meanwhile, supplemental blue light derived higher contents of vitamin C, soluble protein, free amino acids, and chlorophyll at harvest. The samples exposed to supplemental blue light possessed both higher nutrition and antioxidant values. Thus, pre-harvest supplemental blue light treatment might be a promising strategy to enhance the antioxidant activity and nutritional values and extend the shelf-life of the flower stalk of Chinese kale.
Divergent Leaf Morpho-Physiological and Anatomical Adaptations of Four Lettuce Cultivars in Response to Different Greenhouse Irradiance Levels in Early Summer Season
Authors: Formisano Luigi , Ciriello Michele , Cirillo Valerio , Pannico Antonio , El-Nakhel Christophe , Cristofano Francesco , Duri Luigi Giuseppe , Giordano Maria , Rouphael Youssef , De Pascale Stefania
Published: June 2021

Lettuce (Lactuca sativa L.) is a winter-spring leafy vegetable, but the high demand for fresh products available year-round requires off-season production. However, the warm climate of the Mediterranean areas can impair the summer production of lettuce, thus requiring the adoption of genotypes tolerant to high irradiance as well as useful agronomic strategies like shading net installations. The aim of our research was to assess the leaf morpho-physiological and anatomical changes, in addition to productive responses, of four lettuce cultivars (‘Ballerina’, ‘Maravilla De Verano Canasta’, ‘Opalix’, and ‘Integral’) grown under shading and non-shading conditions to unveil the adaptive mechanisms of this crop in response to sub-optimal microclimate (high irradiance and temperature) in a protected environment. Growth and yield parameters, leaf gas exchanges, chlorophyll fluorescence and morpho-anatomical leaf traits (i.e., leaf mass area, stomatal density and epidermal cell density) were determined. Under shading conditions, the fresh yields of the cultivars ‘Ballerina’, ‘Opalix’ (‘Oak leaf’) and ‘Integral’ (‘Romaine’) increased by 16.0%, 26.9% and 13.2% respectively, compared to non-shading conditions while both abaxial and adaxial stomatal density decreased. In contrast, ‘Canasta’ under non-shading conditions increased fresh yield, dry biomass and instantaneous water use efficiency by 9.6%, 18.0% and 15.7%, respectively, while reduced abaxial stomatal density by 30.4%, compared to shading conditions. Regardless of cultivar, the unshaded treatment increased the leaf mass area by 19.5%. Even though high light intensity and high temperature are critical limiting factors for summer lettuce cultivation in a protected environment, ‘Canasta’ showed the most effective adaptive mechanisms and had the best production performance under sub-optimal microclimatic conditions. However, greenhouse coverage with a white shading net (49% screening) proved to be a suitable agricultural practice that ensured an adequate microclimate for the off-season growth of more sensitive cultivars ‘Ballerina’, ‘Oak leaf’ and ‘Romaine’.
Dietary Fiber-Tethered Gold Nanoparticles: An Innovative Analytical Tool for Probing Interactions
Authors: Lupo Cristina , Boulos Samy , Delle Vedove Chiara , Gramm Fabian , Nyström Laura
Published: June 2021

Epidemiological studies have recognized that daily consumption of dietary fiber-containing foods reduces the incidence of developing many chronic diseases, for example, by interacting with nutritionally relevant compounds. The low affinity nature that some of these interactions can have make the development of an analytical detection system for their study particularly difficult. Therefore, the mechanism of action of binding compounds, by which a dietary fiber exerts its potential health benefits, remains largely unknown. Here, a novel method based on glyco-nanotechnology is proposed for studying the interaction between galactomannan and target molecules. Starting from a bottom-up approach, gold nanoparticles and thiolated galactomannans of two different sizes were synthesized separately, and then mixed for auto-assembly of the two glyconanoparticle materials. In addition, a preliminary interaction study between the prepared glyconanoparticles and Concanavalin A was carried out using transmission electron microscopy (TEM) from which it could be deduced that the molecular weight and ligand density on the gold core play an important role in the interaction. Therefore, dietary fiber-tethered gold nanoparticles are a valuable tool to elucidate key parameters underlying dietary fiber interactions.
Study of Air Pressure and Velocity for Solution Blow Spinning of Polyvinylidene Fluoride Nanofibres
Authors: Atif Rasheed , Combrinck Madeleine , Khaliq Jibran , Martin James , Hassanin Ahmed H. , Shehata Nader , Elnabawy Eman , Shyha Islam
Published: June 2021

Solution blow spinning (SBS) is gaining popularity for producing fibres for smart textiles and energy harvesting due to its operational simplicity and high throughput. The whole SBS process is significantly dependent on the characteristics of the attenuation force, i.e., compressed air. Although variation in the fibre morphology with varying air input pressure has been widely investigated, there is no available literature on the experimentally determined flow characteristics. Here, we have experimentally measured and calculated airflow parameters, namely, output air pressure and velocity in the nozzle wake at 12 different pressure values between 1 and 6 bar and 11 different positions (retracted 5 mm to 30 mm) along the centreline. The results obtained in this work will answer many critical questions about optimum protrusion length for the polymer solution syringe and approximate mean fibre diameter for polyvinylidene fluoride (PVDF) at given output air pressure and velocity. The highest output air pressure and velocity were achieved at a distance of 3–5 mm away from the nozzle wake and should be an ideal location for the apex of the polymer solution syringe. We achieved 250 nm PVDF fibres when output air pressure and velocity were 123 kPa and 387 m/s, respectively.
Integral Sliding Mode Control for Maximum Power Point Tracking in DFIG Based Floating Offshore Wind Turbine and Power to Gas
Authors: Pan Lin , Zhu Ze , Xiong Yong , Shao Jingkai
Published: June 2021

This paper proposes a current decoupling controller for a Doubly-fed Induction Generator (DFIG) based on floating offshore wind turbine and power to gas. The proposed controller realizes Maximum Power Point Tracking (MPPT) through integral sliding mode compensation. By using the internal model control strategy, an open-loop controller is designed to ensure that the system has good dynamic performance. Furthermore, using the integral Sliding Mode Control (SMC) strategy, a compensator is designed to eliminate the parameter perturbation and external disturbance of the open-loop control. The parameters of the designed controller are designed through Grey Wolf Optimization (GWO). Simulation results show that the proposed control strategy has better response speed and smaller steady-state error than the traditional control strategy. This research is expected to be applied to the field of hydrogen production by floating offshore wind power.
Naturally Inspired Highly Stable Salt-Resisting Material for Solar Water Desalination
Authors: Samo Imran Ahmed , Mughal Waqas , Samo Kamran Ahmed , Zhong Yang , Cheng Congtian , Zhao Yajun , Siyal Asif Ali , Tian Benqiang
Published: June 2021

Solar desalination is a promising method for producing drinkable water, but salt accumulation on the evaporator surface leads to reduced light absorption. This study presents a nature-inspired self-driven salt-resistant material (NI-SRM) for a salt-free solar desalination system. The introduced material has great porosity to generate desirable capillary force to lift up water to the evaporator surface, which can function as water pumping channels. The concentration of salt solution in the absorber could not achieve saturation and produce salt via solar evaporation during the experiment. The NI-SRM had an evaporation rate of 3.02 kg-m−2 h−1 under 1 sun irradiation and outstanding long-term stability for the desalination of high-salinity brine with no apparent salt deposition. An 80% efficiency was achieved for 24 h under 1 sun (10 kW-m−2). Through control experiments, the multifunctional NI-SRM was found to play a critical role in preventing salt accumulation over the surface under 1 sun. The newly developed NI-SRM had a higher evaporation rate with higher stability in a high-salinity brine solution. The developed material is environmentally friendly and cost-effective.
Evaluation of Orbital Drift Effect on Proba-V Surface Reflectances Time Series
Authors: Niro Fabrizio
Published: June 2021

Multi-temporal consistency of space-borne observations is an essential requirement for studying inter-annual changes and trends of satellite-derived biophysical products. The Proba-V mission, launched in 2013, was designed to ensure the continuity of the SPOT-VEGETATION long-term data record of global daily observations for land applications. The suitability of Proba-V to provide a temporally consistent data record is, however, potentially jeopardized by the orbital drift effect, which is known to induce spurious trends in time series. The aim of this paper is therefore to evaluate, for the first time, the orbital drift effect on Proba-V surface reflectance time series at 1 km resolution. In order to reliably identify such an effect, a two-fold approach is adopted. A simulation study is first defined to predict the temporal anomalies induced by the drifting illumination conditions. The numerical simulations are used as a benchmark to predict the impact of the drift for a range of sun-viewing angles. Real observations are then analyzed over a large set of land sites, globally spread and spanning a wide range of surface and environmental conditions. The surface anisotropy is characterized using the Ross-Thick Li-Sparse Reciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model. Both the simulation and the analysis of real observations consistently show that the orbital drift induces distinct and opposite trends in the two sides of the sensor across-track swath. Particularly, a positive drift is estimated in backward and a negative one in the forward scattering direction. When observations from all angular conditions are retained, these opposite trends largely compensate, with no remaining statistically significant drifts in time series of surface reflectances or Normalized Difference Vegetation Index (NDVI). As such, the Proba-V archive at 1 km resolution can be reliably used for inter-annual vegetation studies.
Fengyun-3D/MERSI-II Cloud Thermodynamic Phase Determination Using a Machine-Learning Approach
Authors: Zhao Dexin , Zhu Lin , Sun Hongfu , Li Jun , Wang Weishi
Published: June 2021

Global cloud thermodynamic phase (CP) is normally derived from polar-orbiting satellite imaging data with high spatial resolution. However, constraining conditions and empirical thresholds used in the MODIS (Moderate Resolution Imaging Spectroradiometer) CP algorithm are closely associated with spectral properties of the MODIS infrared (IR) spectral bands, with obvious deviations and incompatibility induced when the algorithm is applied to data from other similar space-based sensors. To reduce the algorithm dependence on spectral properties and empirical thresholds for CP retrieval, a machine learning (ML)-based methodology was developed for retrieving CP data from China’s new-generation polar-orbiting satellite, FY-3D/MERSI-II (Fengyun-3D/Moderate Resolution Spectral Imager-II). Five machine learning algorithms were used, namely, k-nearest-neighbor (KNN), support vector machine (SVM), random forest (RF), Stacking and gradient boosting decision tree (GBDT). The RF algorithm gave the best performance. One year of EOS (Earth Observation System) MODIS CP products (July 2018 to June 2019) were used as reference labels to train the relationship between MODIS CP (MYD06 IR) and six IR bands of MERSI-II. CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), MODIS, and FY-3D/MERSI-II CP products were used together for cross-validation. Results indicate strong spatial consistency between ML-based MERSI-II and MODIS CP products. The hit rate (HR) of random forest (RF) CP product could reach 0.85 compared with MYD06 IR CP products. In addition, when compared with the operational FY-3D/MERSI CP product, the RF-based CP product had higher HRs. Using the CALIOP cloud product as an independent reference, the liquid-phase accuracy of the RF CP product was higher than that of operational FY-3D/MERSI-II and MYD06 IR CP products. This study aimed to establish a robust algorithm for deriving FY-3D/MERSI-II CP climate data record (CDR) for research and applications.
Real-Time Path Planning Based on Harmonic Functions under a Proper Generalized Decomposition-Based Framework
Authors: Montés Nicolas , Chinesta Francisco , Mora Marta C. , Falcó Antonio , Hilario Lucia , Rosillo Nuria , Nadal Enrique
Published: June 2021

This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main property of the proposed technique is that the computational cost is negligible in real-time, even if the robot is disturbed or the goal is changed. The main idea of the method is the off-line generation, for a given environment, of the whole set of paths from any start and goal configurations of a mobile robot, namely the computational vademecum, derived from a harmonic potential field in order to use it on-line for decision-making purposes. Up until now, the resolution of the Laplace or Poisson equations has been based on traditional numerical techniques unfeasible for real-time calculation. This drawback has prevented the extensive use of harmonic functions in autonomous navigation, despite their powerful properties. The numerical technique that reverses this situation is the Proper Generalized Decomposition. To demonstrate and validate the properties of the PGD-vademecum in a potential-guided path planning framework, both real and simulated implementations have been developed. Simulated scenarios, such as an L-Shaped corridor and a benchmark bug trap, are used, and a real navigation of a LEGO®MINDSTORMS robot running in static environments with variable start and goal configurations is shown. This device has been selected due to its computational and memory-restricted capabilities, and it is a good example of how its properties could help the development of social robots.
Enhancing Formaldehyde Selectivity of SnO2 Gas Sensors with the ZSM-5 Modified Layers
Authors: Wang Wei , Zhang Qinyi , Lv Ruonan , Wu Dong , Zhang Shunping
Published: June 2021

High performance formaldehyde gas sensors are widely needed for indoor air quality monitoring. A modified layer of zeolite on the surface of metal oxide semiconductors results in selectivity improvement to formaldehyde as gas sensors. However, there is insufficient knowledge on how the thickness of the zeolite layer affects the gas sensing properties. In this paper, ZSM-5 zeolite films were coated on the surface of the SnO2 gas sensors by the screen printing method. The thickness of ZSM-5 zeolite films was controlled by adjusting the numbers of screen printing layers. The influence of ZSM-5 film thickness on the performance of ZSM-5/SnO2 gas sensors was studied. The results showed that the ZSM-5/SnO2 gas sensors with a thickness of 19.5 μm greatly improved the selectivity to formaldehyde, and reduced the response to ethanol, acetone and benzene at 350 °C. The mechanism of the selectivity improvement to formaldehyde of the sensors was discussed.
Design and Characterization of an Asynchronous Fixed Priority Tree Arbiter for SPAD Array Readout
Authors: Aguénounon Enagnon , Razavinejad Safa , Schell Jean-Baptiste , Dolatpoor Lakeh Mohammadreza , Khaddour Wassim , Dadouche Foudil , Kammerer Jean-Baptiste , Fesquet Laurent , Uhring Wilfried
Published: June 2021

The usage of single-photon avalanche diode arrays is becoming increasingly common in various domains such as medical imaging, automotive vision systems, and optical communications. Nowadays, thanks to the development of microelectronics technologies, the SPAD arrays designed for these applications has been drastically well-facilitated, allowing for the manufacturing of large matrices. However, there are growing challenges for the design of readout circuits with the needs of reducing their energy consumption (linked to the usage cost) and data rate. Indeed, the design of the readout circuit for the SPAD array is generally based on synchronous logic; the latter requires synchronization that may increase the dead time of the SPADs and clock trees management that are known to increase power consumption. With these limitations, the long-neglected asynchronous (clockless) logic proved to be a better alternative because of its ability to operate without a clock. In this paper, we presented the design of a 16-to-1 fixed-priority tree arbiter readout circuit for a SPAD array based on asynchronous logic principles. The design of this circuit was explained in detail and supported by simulation results. The manufactured chip was tested, and the experimental results showed that it is possible to record up to 333 million events per second; no reading errors were detected during the data extraction test.
Multi-Sensor and Decision-Level Fusion-Based Structural Damage Detection Using a One-Dimensional Convolutional Neural Network
Authors: Teng Shuai , Chen Gongfa , Liu Zongchao , Cheng Li , Sun Xiaoli
Published: June 2021

This paper presents a novel approach to substantially improve the detection accuracy of structural damage via a one-dimensional convolutional neural network (1-D CNN) and a decision-level fusion strategy. As structural damage usually induces changes in the dynamic responses of a structure, a CNN can effectively extract structural damage information from the vibration signals and classify them into the corresponding damage categories. However, it is difficult to build a large-scale sensor system in practical engineering; the collected vibration signals are usually non-synchronous and contain incomplete structure information, resulting in some evident errors in the decision stage of the CNN. In this study, the acceleration signals of multiple acquisition points were obtained, and the signals of each acquisition point were used to train a 1-D CNN, and their performances were evaluated by using the corresponding testing samples. Subsequently, the prediction results of all CNNs were fused (decision-level fusion) to obtain the integrated detection results. This method was validated using both numerical and experimental models and compared with a control experiment (data-level fusion) in which all the acceleration signals were used to train a CNN. The results confirmed that: by fusing the prediction results of multiple CNN models, the detection accuracy was significantly improved; for the numerical and experimental models, the detection accuracy was 10% and 16–30%, respectively, higher than that of the control experiment. It was demonstrated that: training a CNN using the acceleration signals of each acquisition point and making its own decision (the CNN output) and then fusing these decisions could effectively improve the accuracy of damage detection of the CNN.
Evaluation of the Effects of Mobile Smart Object to Boost IoT Network Synchronization
Authors: Lamonaca Francesco , Carnì Domenico Luca
Published: June 2021

This paper deals with the synchronization of Mobile Smart Objects (MSOs). Today, this scenario is becoming typical in Industrial IoT applications due to the plethora of MSOs available as robots, drones and wearables, equipped by sensors making them measurement instruments cooperating in distributed measurement systems. In this context, the synchronization accuracy is directly tied with the accuracy of the performed measurements. In hierarchical synchronization approaches, the presence of an MSO makes the network topology time varying, and this could prevent the synchronization of the whole network. Peer to peer approaches do not need node hierarchy to synchronize but could not converge to a common sense of time. To overcome these challenges, this paper proposes a consensus-based approach for which the convergence to a common sense of time is here demonstrated. The proposal deploys the MSO to bring the common sense of time from an SO to another, establishing new paths among SOs. The new paths are temporary and depend on the MSO’s route. In the paper, the influence of the MSO’s route on the synchronization accuracy σ and the time interval to synchronize all the SOs ∆TIS is investigated, also. The mathematical proof, the simulations and the experimental tests confirm that the MSO can reduce both the values of σ and ∆TIS, because the new connections introduced by the MSO can boost the exchange of information among SOs. Consequently, the criteria to a priori select the route ameliorating σ and ∆TIS values are proposed.
Calibration Method for Particulate Matter Low-Cost Sensors Used in Ambient Air Quality Monitoring and Research
Authors: Venkatraman Jagatha Janani , Klausnitzer André , Chacón-Mateos Miriam , Laquai Bernd , Nieuwkoop Evert , van der Mark Peter , Vogt Ulrich , Schneider Christoph
Published: June 2021

Over the last decade, manufacturers have come forth with cost-effective sensors for measuring ambient and indoor particulate matter concentration. What these sensors make up for in cost efficiency, they lack in reliability of the measured data due to their sensitivities to temperature and relative humidity. These weaknesses are especially evident when it comes to portable or mobile measurement setups. In recent years many studies have been conducted to assess the possibilities and limitations of these sensors, however mostly restricted to stationary measurements. This study reviews the published literature until 2020 on cost-effective sensors, summarizes the recommendations of experts in the field based on their experiences, and outlines the quantile-mapping methodology to calibrate low-cost sensors in mobile applications. Compared to the commonly used linear regression method, quantile mapping retains the spatial characteristics of the measurements, although a common correction factor cannot be determined. We conclude that quantile mapping can be a useful calibration methodology for mobile measurements given a well-elaborated measurement plan assures providing the necessary data.
Interference Analysis for mmWave Automotive Radar Considering Blockage Effect
Authors: Kui Liping , Huang Sai , Feng Zhiyong
Published: June 2021

Due to the increasing number of vehicles equipped with millimeter wave (mmWave) radars, interference among automotive radars is becoming a major issue. This paper explores the automotive radar interference in both two-lane and multi-lane scenarios using stochastic geometry. We derive closed-form expressions for mean and variance of interference power considering directional antenna with constant and Gaussian decaying gains. In view of the sensitivity of mmWave radar signals to the blockages, we propose a blockage model including partially and completely blocking, and then calculate the effective number of the interferers. By means of modeling randomness for interferers and blockages as Poisson point process, we characterize the statistics of radar interference under different conditions. We further utilize the interference characterization to estimate the successful ranging probability of automotive radars. These theoretical analyses are verified by using Monte Carlo simulations. The results show that the increasing interfering density and ranging distance largely degrade the radar detection performance, whereas the interference levels decrease as blockage intensity increases.
Smart City Data Sensing during COVID-19: Public Reaction to Accelerating Digital Transformation
Authors: Kharlamov Alexander A. , Raskhodchikov Aleksei N. , Pilgun Maria
Published: June 2021

The article presents the results of the analysis of the adaptation of metropolis IT technologies to solve operational problems in extreme conditions during the COVID-19 pandemic. The material for the study was Russian-language data from social networks, microblogging, blogs, instant messengers, forums, reviews, video hosting services, thematic portals, online media, print media and TV related to the first wave of the COVID-19 pandemic in Russia. The data were collected between 1 March 2020 and 1 June 2020. The database size includes 85,493,717 characters. To analyze the content of social media, a multimodal approach was used involving neural network technologies, text analysis, sentiment-analysis and analysis of lexical associations. The transformation of old digital services and applications, as well as the emergence of new ones were analyzed in terms of the perception of digital communications by actors.
Acousto-Optic Comb Interrogation System for Random Fiber Grating Sensors with Sub-nm Resolution
Authors: Poiana Dragos A. , Garcia-Souto Jose A. , Bao Xiaoyi
Published: June 2021

The broad-frequency response and nanometer-range displacements of ultrasound detection are essential for the characterization of small cracks, structural health monitoring and non-destructive evaluation. Those perturbations are generated at sub-nano-strain to nano-strain levels. This corresponds to the sub-nm level and, therefore, to about 0.1% of wavelength change at 1550 nm, making it difficult to detect them by conventional interferometric techniques. In this paper, we propose a demodulation system to read the random fiber grating spectrum using a self-heterodyne acousto-optic frequency comb. The system uses a self-heterodyne approach to extract phase and amplitude modulated signals to detect surface acoustic waves with sub-nanometer amplitudes in the frequency domain. The method can detect acoustic frequencies of 1 MHz and the associated displacement. The system is calibrated via phase detection with a heterodyne interferometer, which has a limited frequency response of up to 200 kHz. The goal is to achieve sub-nanometer strain detection at MHz frequency with random fiber gratings.
A Flexible Integrated Bending Strain and Pressure Sensor System for Motion Monitoring
Authors: Feng Rou , Mu Yifeng , Zeng Xiangwen , Jia Weijie , Liu Yuxuan , Jiang Xijun , Gong Qibei , Hu Youfan
Published: June 2021

Flexible sensors have attracted increasing research interest due to their broad application potential in the fields of human–computer interaction, medical care, sports monitoring, etc. Constructing an integrated sensor system with high performance and being capable of discriminating different stimuli remains a challenge. Here, we proposed a flexible integrated sensor system for motion monitoring that can measure bending strain and pressure independently with a low-cost and simple fabrication process. The resistive bending strain sensor in the system is fabricated by sintering polyimide (PI), demonstrating a gauge factor of 9.54 and good mechanical stability, while the resistive pressure sensor is constructed based on a composite structure of silver nanowires (AgNWs) and polydimethylsiloxane (PDMS)-expandable microspheres with a tunable sensitivity and working range. Action recognition is demonstrated by attaching the flexible integrated sensor system on the wrist with independent strain and pressure information recorded from corresponding sensors. It shows a great application potential in motion monitoring and intelligent human–machine interfaces.
Measurement Compensation for Time-Delay Seeker and Three-Dimensional Adaptive Guidance Law Design
Authors: Liu Yukuan , He Guanglin , Qiao Zenghui , Guo Zhaoxuan , Wang Zehu
Published: June 2021

The time delay of seekers has grown to be a serious issue for tactical missile guidance with the development of flight vehicle technologies. To address the problem, a measurement compensation system for the seeker, with lags and delays based on predictive active disturbance rejection control, is proposed. In addition, to eliminate the effects of target maneuvers to the tactical missile guidance, an adaptive finite-time convergent sliding mode guidance law, based on super-twisting algorithm, is proposed in three-dimensional missile-target engagement kinematics. Specifically, the compensation system consists of a predictive tracking structure and an active disturbance rejection control system, which could follow a virtual measurement without lags and delays. The compensation system has advantages in disturbance rejection and model inaccuracy addressing, compared with existing compensation methods for seeker measurement. As for the sliding mode guidance law design, the proposed approach is based on an improved super-twisting algorithm with fast convergent adaptive gains, which has advantages in addressing unknown but bounded target maneuvers and avoiding chattering of the classical sliding mode control. As a result, the measurement compensation system and the adaptive sliding mode guidance law is verified robust and effective under the proposed constraints by the simulation examples.
Podiatrist-Delivered Health Coaching to Facilitate the Use of a Smart Insole to Support Foot Health Monitoring in People with Diabetes-Related Peripheral Neuropathy
Authors: Macdonald Emma M. , Perrin Byron M. , Cleeland Leanne , Kingsley Michael I. C.
Published: June 2021

This trial evaluated the feasibility of podiatrist-led health coaching (HC) to facilitate smart-insole adoption and foot monitoring in adults with diabetes-related neuropathy. Adults aged 69.9 ± 5.6 years with diabetes for 13.7 ± 10.3 years participated in this 4-week explanatory sequential mixed-methods intervention. An HC training package was delivered to podiatrists, who used HC to issue a smart insole to support foot monitoring. Insole usage data monitored adoption. Changes in participant understanding of neuropathy, foot care behaviours, and intention to adopt the smart insole were measured. Focus group and in-depth interviews explored quantitative data. Initial HC appointments took a mean of 43.8 ± 8.8 min. HC fidelity was strong for empathy/rapport and knowledge provision but weak for assessing motivational elements. Mean smart-insole wear was 12.53 ± 3.46 h/day with 71.2 ± 13.9% alerts not effectively off-loaded, with no significant effect for time on usage F(3,6) = 1.194 (p = 0.389) or alert responses F(3,6) = 0.272 (p = 0.843). Improvements in post-trial questionnaire mean scores and focus group responses indicate podiatrist-led HC improved participants’ understanding of neuropathy and implementation of footcare practices. Podiatrist-led HC is feasible, supporting smart-insole adoption and foot monitoring as evidenced by wear time, and improvements in self-reported footcare practices. However, podiatrists require additional feedback to better consolidate some unfamiliar health coaching skills. ACTRN12618002053202.
Rapid and Sensitive Detection of miRNA Based on AC Electrokinetic Capacitive Sensing for Point-of-Care Applications
Authors: Wan Nan , Jiang Yu , Huang Jiamei , Oueslati Rania , Eda Shigetoshi , Wu Jayne , Lin Xiaogang
Published: June 2021

A sensitive and efficient method for microRNAs (miRNAs) detection is strongly desired by clinicians and, in recent years, the search for such a method has drawn much attention. There has been significant interest in using miRNA as biomarkers for multiple diseases and conditions in clinical diagnostics. Presently, most miRNA detection methods suffer from drawbacks, e.g., low sensitivity, long assay time, expensive equipment, trained personnel, or unsuitability for point-of-care. New methodologies are needed to overcome these limitations to allow rapid, sensitive, low-cost, easy-to-use, and portable methods for miRNA detection at the point of care. In this work, to overcome these shortcomings, we integrated capacitive sensing and alternating current electrokinetic effects to detect specific miRNA-16b molecules, as a model, with the limit of detection reaching 1.0 femto molar (fM) levels. The specificity of the sensor was verified by testing miRNA-25, which has the same length as miRNA-16b. The sensor we developed demonstrated significant improvements in sensitivity, response time and cost over other miRNA detection methods, and has application potential at point-of-care.
Modeling Stratum Corneum Swelling for the Optimization of Electrode-Based Skin Hydration Sensors
Authors: Malnati Claudio , Fehr Daniel , Spano Fabrizio , Bonmarin Mathias
Published: June 2021

We present a novel computational model of the human skin designed to investigate dielectric spectroscopy electrodes for stratum corneum hydration monitoring. The multilayer skin model allows for the swelling of the stratum corneum, as well as the variations of the dielectric properties under several hydration levels. According to the results, the stratum corneum thickness variations should not be neglected. For high hydration levels, swelling reduces the skin capacitance in comparison to a fixed stratum corneum thickness model. In addition, different fringing-field electrodes are evaluated in terms of sensitivity to the stratum corneum hydration level. As expected, both conductance and capacitance types of electrodes are influenced by the electrode geometry and dimension. However, the sensitivity of the conductance electrodes is more affected by dimension changes than the capacitance electrode leading to potential design optimization.
Camera-LiDAR Multi-Level Sensor Fusion for Target Detection at the Network Edge
Authors: Mendez Javier , Molina Miguel , Rodriguez Noel , Cuellar Manuel P. , Morales Diego P.
Published: June 2021

There have been significant advances regarding target detection in the autonomous vehicle context. To develop more robust systems that can overcome weather hazards as well as sensor problems, the sensor fusion approach is taking the lead in this context. Laser Imaging Detection and Ranging (LiDAR) and camera sensors are two of the most used sensors for this task since they can accurately provide important features such as target´s depth and shape. However, most of the current state-of-the-art target detection algorithms for autonomous cars do not take into consideration the hardware limitations of the vehicle such as the reduced computing power in comparison with Cloud servers as well as the reduced latency. In this work, we propose Edge Computing Tensor Processing Unit (TPU) devices as hardware support due to their computing capabilities for machine learning algorithms as well as their reduced power consumption. We developed an accurate and small target detection model for these devices. Our proposed Multi-Level Sensor Fusion model has been optimized for the network edge, specifically for the Google Coral TPU. As a result, high accuracy results are obtained while reducing the memory consumption as well as the latency of the system using the challenging KITTI dataset.
Semi-Supervised Anomaly Detection in Video-Surveillance Scenes in the Wild
Authors: Sarker Mohammad Ibrahim , Losada-Gutiérrez Cristina , Marrón-Romera Marta , Fuentes-Jiménez David , Luengo-Sánchez Sara
Published: June 2021

Surveillance cameras are being installed in many primary daily living places to maintain public safety. In this video-surveillance context, anomalies occur only for a very short time, and very occasionally. Hence, manual monitoring of such anomalies may be exhaustive and monotonous, resulting in a decrease in reliability and speed in emergency situations due to monitor tiredness. Within this framework, the importance of automatic detection of anomalies is clear, and, therefore, an important amount of research works have been made lately in this topic. According to these earlier studies, supervised approaches perform better than unsupervised ones. However, supervised approaches demand manual annotation, making dependent the system reliability of the different situations used in the training (something difficult to set in anomaly context). In this work, it is proposed an approach for anomaly detection in video-surveillance scenes based on a weakly supervised learning algorithm. Spatio-temporal features are extracted from each surveillance video using a temporal convolutional 3D neural network (T-C3D). Then, a novel ranking loss function increases the distance between the classification scores of anomalous and normal videos, reducing the number of false negatives. The proposal has been evaluated and compared against state-of-art approaches, obtaining competitive performance without fine-tuning, which also validates its generalization capability. In this paper, the proposal design and reliability is presented and analyzed, as well as the aforementioned quantitative and qualitative evaluation in-the-wild scenarios, demonstrating its high sensitivity in anomaly detection in all of them.
Privacy-Enhancing k-Nearest Neighbors Search over Mobile Social Networks
Authors: Li Yuxi , Zhou Fucai , Ge Yue , Xu Zifeng
Published: June 2021

Focusing on the diversified demands of location privacy in mobile social networks (MSNs), we propose a privacy-enhancing k-nearest neighbors search scheme over MSNs. First, we construct a dual-server architecture that incorporates location privacy and fine-grained access control. Under the above architecture, we design a lightweight location encryption algorithm to achieve a minimal cost to the user. We also propose a location re-encryption protocol and an encrypted location search protocol based on secure multi-party computation and homomorphic encryption mechanism, which achieve accurate and secure k-nearest friends retrieval. Moreover, to satisfy fine-grained access control requirements, we propose a dynamic friends management mechanism based on public-key broadcast encryption. It enables users to grant/revoke others’ search right without updating their friends’ keys, realizing constant-time authentication. Security analysis shows that the proposed scheme satisfies adaptive L-semantic security and revocation security under a random oracle model. In terms of performance, compared with the related works with single server architecture, the proposed scheme reduces the leakage of the location information, search pattern and the user–server communication cost. Our results show that a decentralized and end-to-end encrypted k-nearest neighbors search over MSNs is not only possible in theory, but also feasible in real-world MSNs collaboration deployment with resource-constrained mobile devices and highly iterative location update demands.
Dynamic Functional Principal Components for Testing Causality
Authors: Saumard Matthieu , Hadjadji Bilal
Published: June 2021

In this paper, we investigate the causality in the sense of Granger for functional time series. The concept of causality for functional time series is defined, and a statistical procedure of testing the hypothesis of non-causality is proposed. The procedure is based on projections on dynamic functional principal components and the use of a multivariate Granger test. A comparative study with existing procedures shows the good results of our test. An illustration on a real dataset is provided to attest the performance of the proposed procedure.
Construction and Characterization of Representations of SU(7) for GUT Model Builders
Authors: Jones Daniel , Secrest Jeffery A.
Published: June 2021

The natural extension to the SU(5) Georgi-Glashow grand unification model is to enlarge the gauge symmetry group. In this work, the SU(7) symmetry group is examined. The Cartan subalgebra is determined along with their commutation relations. The associated roots and weights of the SU(7) algebra are derived and discussed. The raising and lowering operators are explicitly constructed and presented. Higher dimensional representations are developed by graphical as well as tensorial methods. Applications of the SU(7) Lie group to supersymmetric grand unification as well as applications are discussed.
Food Contaminants Effects on an In Vitro Model of Human Intestinal Epithelium
Authors: Guibourdenche Marion , Haug Johanna , Chevalier Noëllie , Spatz Madeleine , Barbezier Nicolas , Gay-Quéheillard Jérôme , Anton Pauline
Published: June 2021

Pesticide residues represent an important category of food contaminants. Furthermore, during food processing, some advanced glycation end-products resulting from the Maillard reaction can be formed. They may have adverse health effects, in particular on the digestive tract function, alone and combined. We sought to validate an in vitro model of the human intestinal barrier to mimic the effects of these food contaminants on the epithelium. A co-culture of Caco-2/TC7 cells and HT29-MTX was stimulated for 6 h with chlorpyrifos (300 μM), acrylamide (5 mM), Nε-Carboxymethyllysine (300 μM) alone or in cocktail with a mix of pro-inflammatory cytokines. The effects of those contaminants on the integrity of the gut barrier and the inflammatory response were analyzed. Since the co-culture responded to inflammatory stimulation, we investigated whether this model could be used to evaluate the effects of food contaminants on the human intestinal epithelium. CPF alone affected tight junctions’ gene expression, without inducing any inflammation or alteration of intestinal permeability. CML and acrylamide decreased mucins gene expression in the intestinal mucosa, but did not affect paracellular intestinal permeability. CML exposure activated the gene expression of MAPK pathways. The co-culture response was stable over time. This cocktail of food contaminants may thus alter the gut barrier function.
Cancer Vaccines for Genitourinary Tumors: Recent Progresses and Future Possibilities
Authors: Maiorano Brigida Anna , Schinzari Giovanni , Ciardiello Davide , Rodriquenz Maria Grazia , Cisternino Antonio , Tortora Giampaolo , Maiello Evaristo
Published: June 2021

Background: In the last years, many new treatment options have widened the therapeutic scenario of genitourinary malignancies. Immunotherapy has shown efficacy, especially in the urothelial and renal cell carcinomas, with no particular relevance in prostate cancer. However, despite the use of immune checkpoint inhibitors, there is still high morbidity and mortality among these neoplasms. Cancer vaccines represent another way to activate the immune system. We sought to summarize the most recent advances in vaccine therapy for genitourinary malignancies with this review. Methods: We searched PubMed, Embase and Cochrane Database for clinical trials conducted in the last ten years, focusing on cancer vaccines in the prostate, urothelial and renal cancer. Results: Various therapeutic vaccines, including DNA-based, RNA-based, peptide-based, dendritic cells, viral vectors and modified tumor cells, have been demonstrated to induce specific immune responses in a variable percentage of patients. However, these responses rarely corresponded to significant survival improvements. Conclusions: Further preclinical and clinical studies will improve the knowledge about cancer vaccines in genitourinary malignancies to optimize dosage, select targets with a driver role for tumor development and growth, and finally overcome resistance mechanisms. Combination strategies represent possibly more effective and long-lasting treatments.