bluuebunny/crossref_metadata_2025 huggingface dataset:
Growth Assessment in Preterm Children from Birth to Preschool Age
Authors: Ceratto Simone , Savino Francesco , Vannelli Silvia , De Sanctis Luisa , Giuliani Francesca
Published: June 2020

Preterm infant growth is a major health indicator and needs to be monitored with an appropriate growth curve to achieve the best developmental and growth potential while avoiding excessive caloric intake that is linked to metabolic syndrome and hypertension later in life. New international standards for size at birth and postnatal growth for preterm infants are available and need implementation in clinical practice. A prospective, single center observational study was conducted to evaluate the in-hospital and long-term growth of 80 preterm infants with a mean gestational age of 33.3 ± 2.2 weeks, 57% males. Size at birth and at discharge were assessed using the INTERGROWTH-21ST standards, at preschool age with World Health Organization (WHO) child growth standards. The employment of INTERGROWTH-21ST Preterm Postnatal longitudinal standards during the in-hospital follow-up significantly reduced the diagnosis of short term extrauterine growth restriction when compared to commonly used cross sectional neonatal charts, with significant lower loss of percentiles between birth and term corrected age (p < 0.0001). The implementation of a package of standards at birth, preterm postnatal growth standards and WHO child growth standards proved to be consistent, with correlation between centile at birth and at follow-up, and therefore effective in monitoring growth in a moderate and late preterm infant cohort without chronic or major morbidities. Infants identified as small for gestational age at birth showed significantly more frequently a need for auxological referral.
Chenopodium Quinoa and Salvia Hispanica Provide Immunonutritional Agonists to Ameliorate Hepatocarcinoma Severity under a High-Fat Diet
Authors: Laparra Llopis Jose Moisés , Brown Daniel , Saiz Blanca
Published: June 2020

Complex interactions between immunonutritional agonist and high fat intake (HFD), the immune system and finally gut microbiota are important determinants of hepatocarcinoma (HCC) severity. The ability of immunonutritional agonists to modulate major aspects such as liver innate immunity and inflammation and alterations in major lipids profile as well as gut microbiota during HCC development is poorly understood. 1H NMR has been employed to assess imbalances in saturated fatty acids, MUFA and PUFA, which were associated to variations in iron homeostasis. These effects were dependent on the botanical nature (Chenopodium quinoa vs. Salvia hispanica L.) of the compounds. The results showed that immunonutritional agonists’ promoted resistance to hepatocarcinogenesis under pro-tumorigenic inflammation reflected, at a different extent, in increased proportions of F4/80+ cells in injured livers as well as positive trends of accumulated immune mediators (CD68/CD206 ratio) in intestinal tissue. Administration of all immunonutritional agonists caused similar variations of fecal microbiota, towards a lower obesity-inducing potential than animals only fed a HFD. Modulation of Firmicutes to Bacteroidetes contents restored the induction of microbial metabolites to improve epithelial barrier function, showing an association with liver saturated fatty acids and the MUFA and PUFA fractions. Collectively, these data provide novel findings supporting beneficial immunometabolic effects targeting hepatocarcinogenesis, influencing innate immunity within the gut-liver axis, and providing novel insights into their immunomodulatory activity.
Effects of Dietary Fibres on Acute Indomethacin-Induced Intestinal Hyperpermeability in the Elderly: A Randomised Placebo Controlled Parallel Clinical Trial
Authors: Ganda Mall John-Peter , Fart Frida , Sabet Julia A. , Lindqvist Carl Mårten , Nestestog Ragnhild , Hegge Finn Terje , Keita Åsa V. , Brummer Robert J. , Schoultz Ida
Published: June 2020

The effect of dietary fibres on intestinal barrier function has not been well studied, especially in the elderly. We aimed to investigate the potential of the dietary fibres oat β-glucan and wheat arabinoxylan to strengthen the intestinal barrier function and counteract acute non-steroid anti-inflammatory drug (indomethacin)-induced hyperpermeability in the elderly. A general population of elderly subjects (≥65 years, n = 49) was randomised to a daily supplementation (12g/day) of oat β-glucan, arabinoxylan or placebo (maltodextrin) for six weeks. The primary outcome was change in acute indomethacin-induced intestinal permeability from baseline, assessed by an in vivo multi-sugar permeability test. Secondary outcomes were changes from baseline in: gut microbiota composition, systemic inflammatory status and self-reported health. Despite a majority of the study population (85%) showing a habitual fibre intake below the recommendation, no significant effects on acute indomethacin-induced intestinal hyperpermeability in vivo or gut microbiota composition were observed after six weeks intervention with either dietary fibre, compared to placebo.
Inhibition of UVB-Induced Inflammation by Laminaria japonica Extract via Regulation of nc886-PKR Pathway
Authors: Lee Kwang-Soo , Cho Eunae , Weon Jin Bae , Park Deokhoon , Fréchet Mathilde , Chajra Hanane , Jung Eunsun
Published: June 2020

Continuous exposure to ultraviolet B (UVB) can cause photodamage of the skin. This photodamage can be inhibited by the overexpression of the non-coding RNA, nc886, via the protein kinase RNA-activated (PKR) pathway. The study aims to identify how UVB inhibits nc886 expression, and it also seeks to determine whether substances that can control nc886 expression can influence UV-induced inflammation, and the mechanisms involved. The results suggest that UVB irradiation accelerates the methylation of the nc886 gene, therefore, reducing its expression. This induces the activation of the PKR, which accelerates the expression of metalloproteinase-9 (MMP-9) and cyclooxygenase (COX-2), and the production of MMP-9, prostaglandin-endoperoxide synthase (PGE2), and certain pro-inflammatory cytokines, specifically interleukin-8 (IL-8), and tumor necrosis factor-α (TNF-α). Conversely, in a model of nc886 overexpression, the expression and production of those inflammatory factors are inhibited. In addition, Laminaria japonica extract (LJE) protect the levels of nc886 against UVB irradiation then subsequently inhibit the production of UV-induced inflammatory factors through the PKR pathway.
Development of Lipid–Polymer Hybrid Nanoparticles for Improving Oral Absorption of Enoxaparin
Authors: Tang Bo , Qian Yu , Fang Guihua
Published: June 2020

Enoxaparin, an anticoagulant that helps prevent the formation of blood clots, is administered parenterally. Here, we report the development and evaluation of lipid–polymer hybrid nanoparticles (LPHNs) for the oral delivery of enoxaparin. The polymer poloxamer 407 (P407) was incorporated into lipid nanoparticles to form gel cores and ensure high encapsulation efficiency and the controlled release of enoxaparin. In vitro results indicated that 30% of P407 incorporation offered higher encapsulation efficiency and sustained the release of enoxaparin. Laser confocal scanning microscopy (LCSM) images showed that LPHNs could not only significantly improve the accumulation of enoxaparin in intestinal villi but also facilitate enoxaparin transport into the underlayer of intestinal epithelial cells. In vivo pharmacokinetic study results indicated that the oral bioavailability of enoxaparin was markedly increased about 6.8-fold by LPHNs. In addition, its therapeutic efficacy against pulmonary thromboembolism was improved 2.99-fold by LPHNs. Moreover, LPHNs exhibited excellent biocompatibility in the intestine. Overall, the LPHN is a promising delivery carrier to boost the oral absorption of enoxaparin.
Dual Network Hydrogels Incorporated with Bone Morphogenic Protein-7-Loaded Hyaluronic Acid Complex Nanoparticles for Inducing Chondrogenic Differentiation of Synovium-Derived Mesenchymal Stem Cells
Authors: Min Qing , Liu Jiaoyan , Zhang Yuchen , Yang Bin , Wan Ying , Wu Jiliang
Published: June 2020

Alginate-poloxamer (ALG-POL) copolymer with optimal POL content was synthesized, and it was combined with silk fibroin (SF) for building ALG-POL/SF dual network hydrogels. Hyaluronic acid(HA)/chitosan-poly(dioxanone)(CH-PDO) complex nanoparticles (NPs) with optimized composition and high encapsulation efficiency were employed as a vehicle for loading bone morphogenic protein-7 (BMP-7). BMP-7-loaded HA/CH-PDO NPs were incorporated into ALG-POL/SF hydrogel for constructing composite gels to achieve controlled release of BMP-7. These gels showed thermosensitive sol-gel transitions near physiological temperature and pH; and they were tested to be elastic, tough and strong. Some gels exhibited abilities to administer the BMP-7 release in nearly linear manners for a few weeks. Synovium-derived mesenchymal stem cells (SMSCs) were seeded into optimally fabricated gels for assessing their chondrogenic differentiation potency. Real-time PCR analyses showed that the blank ALG-POL/SF gels were not able to induce the chondrogenic differentiation of SMSCs, whereas SMSCs were detected to significantly express cartilage-related genes once they were seeded in the BMP-7-loaded ALG-POL/SF gel for two weeks. The synthesis of cartilaginous matrix components further confirmed that SMSCs seeded in the BMP-7-loaded ALG-POL/SF gel differentiated toward chondrogenesis. Results suggest that BMP-7-loaded ALG-POL/SF composite gels can function as a promising biomaterial for cartilage tissue engineering applications.
Supermolecular Structure of Poly(Butylene Terephthalate) Fibers Formed with the Addition of Reduced Graphene Oxide
Authors: Ślusarczyk Czesław , Sieradzka Marta , Fabia Janusz , Fryczkowski Ryszard
Published: June 2020

Nanocomposite fibers based on poly(butylene terephthalate) (PBT) and reduced graphene oxide (rGO) were prepared using a method able to disperse graphene in one step into a polymer matrix. The studies were performed for fibers containing four different concentrations of rGO at different take-up velocities. The supermolecular structures of the fibers at the crystallographic and lamellar levels were examined by means of calorimetric and X-ray scattering methods (DSC, WAXS, and SAXS). It was found that the fiber structure is mainly influenced by the take-up velocity. Fibers spun at low and medium take-up velocities contained a crystalline α-form, whereas the fibers spun at a high take-up velocity contained a smectic mesophase. During annealing, the smectic phase transformed into its α-form. The degree of transformation depended on the rGO content. Reduced graphene mainly hindered the crystallization of PBT by introducing steric obstacles confining the ordering of the macromolecules of PBT.
Multi-Modal Contractive Forces of Wools as Actuator
Authors: Zhu Shanshan , Hu Jinlian
Published: June 2020

Wool has a long history of use in textiles throughout human civilization. Many smart functions such as reversible shape changes to various stimuli have been demonstrated in the last few years. However, the force-related characteristics are still imperfectly recognized, although they are expected to be used as actuators due to their biological origins and broad applications. Herein, we investigated the feasibility of wools in performing actuating ability through its intrinsic structures and fabrication methods. The diverse modes of contractive forces were obtained in wool materials including platform-like, double-peak, and slope-like shapes, where a molecular model was also presented to trace the origins of stress evolution. After that, a polymeric blend was created to modify the wool materials and a dissimilar performance of stress production was achieved, a square stress mode with stable manner and maintenance, for broad applications in a more efficient way. It is believed that these actuating properties extracted from natural hairs have a large potential in current smart applications and lay down new inspiration in designing actuators.
Design and Preparation of New Multifunctional Hydrogels Based on Chitosan/Acrylic Polymers for Drug Delivery and Wound Dressing Applications
Authors: Duceac Ioana A. , Verestiuc Liliana , Dimitriu Cristina D. , Maier Vasilica , Coseri Sergiu
Published: June 2020

The dynamic evolution of materials with medical applications, particularly for drug delivery and wound dressing applications, gives impetus to design new proposed materials, among which, hydrogels represent a promising, powerful tool. In this context, multifunctional hydrogels have been obtained from chemically modified chitosan and acrylic polymers as cross-linkers, followed by subsequent conjugation with arginine. The hydrogels were finely tuned considering the variation of the synthetic monomer and the preparation conditions. The advantage of using both natural and synthetic polymers allowed porous networks with superabsorbent behavior, associated with a non-Fickian swelling mechanism. The in vitro release profiles for ibuprofen and the corresponding kinetics were studied, and the results revealed a swelling-controlled release. The biodegradability studies in the presence of lysozyme, along with the hemostatic evaluation and the induced fibroblast and stem cell proliferation, have shown that the prepared hydrogels exhibit characteristics that make them suitable for local drug delivery and wound dressing.
Thermal and Fluid Dynamic Performance Comparison of Three Nanofluids in Microchannels Using Analytical and Computational Models
Authors: Ray Dustin R. , Strandberg Roy , Das Debendra K.
Published: June 2020

The fluid dynamic and thermal performance of three nanofluids containing aluminum oxide, copper oxide, and silicon dioxide nanoparticles dispersed in 60:40 ethylene glycol and water base fluid as a coolant in a microchannel heatsink are compared here by two methods. The first is a simple analytical analysis, which is acceptable for very low nanoparticle volumetric concentration (1–2%). The second method is a rigorous three-dimensional finite volume conjugate heat transfer and fluid dynamic model based upon a constant heat flux boundary condition, which is applicable for cooling electronic chips. The fluids’ thermophysical properties employed in the modeling are based on empirically derived, temperature dependent correlations from the literature. The analytical and computational results for pressure drop and Nusselt number were in good agreement with the nanofluids showing a maximum difference of 4.1% and 2.9%, respectively. Computations cover the practical range of Reynolds number from 20 to 200 in the laminar regime. Based on equal Reynolds number, all of the nanofluids examined generate a higher convective heat transfer coefficient in the microchannel than the base fluid, while copper oxide provided the most significant increase by 21%. Based on the analyses performed for this study, nanofluids can enhance the cooling performance of the heatsink by requiring a lower pumping power to maintain the same maximum wall temperature. Aluminum oxide and copper oxide nanofluids of 2% concentration reduce the pumping power by 23% and 22%, respectively, while maintaining the same maximum wall temperature as the base fluid.
Conversion as Negotiation. Converts as Actors of Civil Society
Authors: Langewiesche Katrin
Published: June 2020

This article focuses on the religious movement of the Ahmadiyya and its civil society organization, Humanity First, in West-Africa and in Europe. Particular attention is paid to the place of converts within these two institutions. Conversions to an Islamic minority and the actions of this minority are studied through the prism of social commitment. I examine the intersections between religious values, the ideas of solidarity in the societies under scrutiny and, the kaleidoscopic range of Muslim charities. The paper investigates conversion as negotiation in regard to gender, social mobility, and power. Conversion is approached here as a matter of social relations and not personal belief. I argue that converts have to use various strategies of recognition, either as individuals or as a group, which places them in a permanent state of negotiation with their entourage.
The Funerary Rites of Won Buddhism in Korea
Authors: Park Kwangsoo
Published: June 2020

Won Buddhism, established in 1916 by Founding Master Sot’aesan (少太山, 1891–1943), is one of the most active new religious movements in South Korea. When Korean society experienced a revolution in terms of values together with a swift transformation at the societal and national levels during the late 19th century, many novel religious movements emerged. Among these movements, Won Buddhism developed as one of Korea’s influential religions with an expanding role in society, both in performing the National funeral rites for deceased presidents and in the military religious affairs alongside Buddhism, Catholicism, and Protestantism. Unique interpretations of death underlie differences in rituals performed to pay homage to the dead. In this paper, I focus on the funerary rites of Won Buddhism. First, I will provide an introduction to Won Buddhism and subsequently give a brief overview of procedures involved in the death rituals of the religion. Finally, I will elaborate on the symbolism of the Won Buddhist funerary customs and discuss the deliverance service (K. ch’ŏndojae 薦度齋) as a practical demonstration of Won Buddhism’s teachings on birth and death.
Developing a Remote Sensing-Based Combined Drought Indicator Approach for Agricultural Drought Monitoring over Marathwada, India
Authors: Kulkarni Sneha S. , Wardlow Brian D. , Bayissa Yared A. , Tadesse Tsegaye , Svoboda Mark D. , Gedam Shirishkumar S.
Published: June 2020

The increasing drought severities and consequent devastating impacts on society over the Indian semi-arid regions demand better drought monitoring and early warning systems. Operational agricultural drought assessment methods in India mainly depend on a single input parameter such as precipitation and are based on a sparsely located in-situ measurements, which limits monitoring precision. The overarching objective of this study is to address this need through the development of an integrated agro-climatological drought monitoring approach, i.e., combined drought indicator for Marathwada (CDI_M), situated in the central part of Maharashtra, India. In this study, satellite and model-based input parameters (i.e., standardized precipitation index (SPI-3), land surface temperature (LST), soil moisture (SM), and normalized difference vegetation index (NDVI)) were analyzed at a monthly scale from 2001 to 2018. Two quantitative methods were tested to combine the input parameters for developing the CDI_M. These methods included an expert judgment-based weight of each parameter (Method-I) and principle component analysis (PCA)-based weighting approach (Method-II). Secondary data for major types of crop yields in Marathwada were utilized to assess the CDI_M results for the study period. CDI_M maps depict moderate to extreme drought cases in the historic drought years of 2002, 2009, and 2015–2016. This study found a significant increase in drought intensities (p ≤ 0.05) and drought frequency over the years 2001–2018, especially in the Latur, Jalna, and Parbhani districts. In comparison to Method-I (r ≥ 0.4), PCA-based (Method-II) CDI_M showed a higher correlation (r ≥ 0.60) with crop yields in both harvesting seasons (Kharif and Rabi). In particular, crop yields during the drier years showed a greater association (r > 6.5) with CDI_M over Marathwada. Hence, the present study illustrated the effectiveness of CDI_M to monitor agricultural drought in India and provide improved information to support agricultural drought management practices.
Cirrus Cloud Identification from Airborne Far-Infrared and Mid-Infrared Spectra
Authors: Magurno Davide , Cossich William , Maestri Tiziano , Bantges Richard , Brindley Helen , Fox Stuart , Harlow Chawn , Murray Jonathan , Pickering Juliet , Warwick Laura , Oetjen Hilke
Published: June 2020

Airborne interferometric data, obtained from the Cirrus Coupled Cloud-Radiation Experiment (CIRCCREX) and from the PiknMix-F field campaign, are used to test the ability of a machine learning cloud identification and classification algorithm (CIC). Data comprise a set of spectral radiances measured by the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS) and the Airborne Research Interferometer Evaluation System (ARIES). Co-located measurements of the two sensors allow observations of the upwelling radiance for clear and cloudy conditions across the far- and mid-infrared part of the spectrum. Theoretical sensitivity studies show that the performance of the CIC algorithm improves with cloud altitude. These tests also suggest that, for conditions encompassing those sampled by the flight campaigns, the additional information contained within the far-infrared improves the algorithm’s performance compared to using mid-infrared data only. When the CIC is applied to the airborne radiance measurements, the classification performance of the algorithm is very high. However, in this case, the limited temporal and spatial variability in the measured spectra results in a less obvious advantage being apparent when using both mid- and far-infrared radiances compared to using mid-infrared information only. These results suggest that the CIC algorithm will be a useful addition to existing cloud classification tools but that further analyses of nadir radiance observations spanning the infrared and sampling a wider range of atmospheric and cloud conditions are required to fully probe its capabilities. This will be realised with the launch of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission, ESA’s 9th Earth Explorer.
A Classified Adversarial Network for Multi-Spectral Remote Sensing Image Change Detection
Authors: Wu Yue , Bai Zhuangfei , Miao Qiguang , Ma Wenping , Yang Yuelei , Gong Maoguo
Published: June 2020

Adversarial training has demonstrated advanced capabilities for generating image models. In this paper, we propose a deep neural network, named a classified adversarial network (CAN), for multi-spectral image change detection. This network is based on generative adversarial networks (GANs). The generator captures the distribution of the bitemporal multi-spectral image data and transforms it into change detection results, and these change detection results (as the fake data) are input into the discriminator to train the discriminator. The results obtained by pre-classification are also input into the discriminator as the real data. The adversarial training can facilitate the generator learning the transformation from a bitemporal image to a change map. When the generator is trained well, the generator has the ability to generate the final result. The bitemporal multi-spectral images are input into the generator, and then the final change detection results are obtained from the generator. The proposed method is completely unsupervised, and we only need to input the preprocessed data that were obtained from the pre-classification and training sample selection. Through adversarial training, the generator can better learn the relationship between the bitemporal multi-spectral image data and the corresponding labels. Finally, the well-trained generator can be applied to process the raw bitemporal multi-spectral images to obtain the final change map (CM). The effectiveness and robustness of the proposed method were verified by the experimental results on the real high-resolution multi-spectral image data sets.
Paving the Way to Eco-Friendly IoT Antennas: Tencel-Based Ultra-Thin Compact Monopole and Its Applications to ZigBee
Authors: de Cos Gómez María Elena , Fernández Álvarez Humberto , Flórez Berdasco Alicia , Las-Heras Andrés Fernando
Published: June 2020

An ultrathin, compact ecofriendly antenna suitable for IoT applications around 2.45 GHz is achieved as a result of exploring the use of Tencel fabric for the antenna’s design. The botanical ecofriendly Tencel is electromagnetically characterized, in terms of relative dielectric permittivity and loss tangent, in the target IoT frequency band. To explore the suitability of the Tencel, a comparison is conducted with conventionally used RO3003, with similar relative dielectric permittivity, regarding the antenna dimensions and performance. In addition, the antenna robustness under bent conditions is also analyzed by measurement. To assess the relevance of this contribution, the ultrathin ecofriendly Tencel-based antenna is compared with recently published antennas for IoT in the same band and also, with commercial half-wave dipole by performing a range test on a ZigBee-based IoT testbed.
An Integrated Strategy for Autonomous Exploration of Spatial Processes in Unknown Environments
Authors: Karolj Valentina , Viseras Alberto , Merino Luis , Shutin Dmitriy
Published: June 2020

Exploration of spatial processes, such as radioactivity or temperature is a fundamental task in many robotic applications. In the literature, robotic exploration is mainly carried out for applications where the environment is a priori known. However, for most real life applications this assumption often does not hold, specifically for disaster scenarios. In this paper, we propose a novel integrated strategy that allows a robot to explore a spatial process of interest in an unknown environment. To this end, we build upon two major blocks. First, we propose the use of GP to model the spatial process of interest, and process entropy to drive the exploration. Second, we employ registration algorithms for robot mapping and localization, and frontier-based exploration to explore the environment. However, map and process exploration can be conflicting goals. Our integrated strategy fuses the two aforementioned blocks through a trade-off between process and map exploration. We carry out extensive evaluations of our algorithm in simulated environments with respect to different baselines and environment setups using simulated GP data as a process at hand. Additionally, we perform experimental verification with a mobile holonomic robot exploring a simulated process in an unknown labyrinth environment. Demonstrated results show that our integrated strategy outperforms both frontier-based and GP entropy-driven exploration strategies.
Learning Reward Function with Matching Network for Mapless Navigation
Authors: Zhang Qichen , Zhu Meiqiang , Zou Liang , Li Ming , Zhang Yong
Published: June 2020

Deep reinforcement learning (DRL) has been successfully applied in mapless navigation. An important issue in DRL is to design a reward function for evaluating actions of agents. However, designing a robust and suitable reward function greatly depends on the designer’s experience and intuition. To address this concern, we consider employing reward shaping from trajectories on similar navigation tasks without human supervision, and propose a general reward function based on matching network (MN). The MN-based reward function is able to gain the experience by pre-training through trajectories on different navigation tasks and accelerate the training speed of DRL in new tasks. The proposed reward function keeps the optimal strategy of DRL unchanged. The simulation results on two static maps show that the DRL converge with less iterations via the learned reward function than the state-of-the-art mapless navigation methods. The proposed method performs well in dynamic maps with partially moving obstacles. Even when test maps are different from training maps, the proposed strategy is able to complete the navigation tasks without additional training.
Effects of Artificial Texture Insoles and Foot Arches on Improving Arch Collapse in Flat Feet
Authors: Wang Yao-Te , Chen Jong-Chen , Lin Ying-Sheng
Published: June 2020

The arches of the foot play a vital role in cushioning the impact and pressure generated from ground reaction forces due to body weight. Owing to a lack of normal human arch structure, people diagnosed as having flat feet often have discomfort in the soles of their feet. The results may not only cause inappropriate foot pressure distribution on the sole but also further cause foot injuries. This study heavily relies on a homemade foot pressure sensing device equipped with textured insoles of different heights and artificial arches. This was to explore the extent to which the pressure distribution of the foot in people with flat feet could be improved. A further comparison was made of the effects of using the textured insoles with different heights on two different groups of people diagnosed with flat and normal feet respectively. Sixty-five undergraduate and postgraduate volunteers were invited to receive the ink footprint test for measuring their degrees of arch index. Nine of these 65 had 2 flat feet, 3 had a left flat foot, 5 had a right flat foot, and 48 had 2 normal feet. To ensure the same number of subjects in both the control and the experimental groups, 9 of the 48 subjects who had normal feet were randomly selected. In total, 26 subjects (Male: 25, Female: 1; Age: 22 ± 1 years; height: 173.6 ± 2.5 cm; body mass: 68.3 ± 5.4 kg; BMI: 22.6 ± 1.2) were invited to participate in this foot pressure sensing insoles study. The experimental results showed that the use of textured insoles designed with different heights could not effectively improve the plantar pressure distribution and body stability in subjects with flat feet. Conversely, the use of an artificial arch effectively improved the excessive peak in pressure and poor body stability, and alleviated the problem of plantar collapse for patients with flat feet, especially in the inner part of their hallux and forefoot.
Photothermal Sensing of Nano-Devices Made of Graphene Materials
Authors: Lu Xiwen , Yang Lijun , Yang Zhan
Published: June 2020

Graphene is widely used as the basic materials of nano optical devices and sensors on account of its special structures and excellent photoelectric properties. Graphene is considered as an ideal material for photodetectors because of its ultra-wide absorption spectrum from the ultraviolet to the terahertz band, ultrahigh carrier mobility and ultrafast photoreaction speed. In this study, a photothermal nano-device was made using graphene that was transferred to an electrode using an all-dry viscoelastic stamping method. The nano-device has the advantages of simplicity, high efficiency and instant measurement. This nano-device was used to measure the light absorption of graphene, and the calculated light absorption rate of graphene is basically consistent with previous research results. Experiments on irradiation at different wavelengths and thermal heating at different temperatures show that the nano-device has an excellent response to near-infrared and mid-infrared light. The conclusions provide an experimental basis for the research, design and fabrication of nano-devices, and this device can provide an effective method for detecting light and temperature in areas such as electronic components and solar cells.
Fuzzy-Based Approach Using IoT Devices for Smart Home to Assist Blind People for Navigation
Authors: Tayyaba Shahzadi , Ashraf Muhammad Waseem , Alquthami Thamer , Ahmad Zubair , Manzoor Saher
Published: June 2020

The demand of devices for safe mobility of blind people is increasing with advancement in wireless communication. Artificial intelligent devices with multiple input and output methods are used for reliable data estimation based on maximum probability. A model of a smart home for safe and robust mobility of blind people has been proposed. Fuzzy logic has been used for simulation. Outputs from the internet of things (IoT) devices comprising sensors and bluetooth are taken as input of the fuzzy controller. Rules have been developed based on the conditions and requirements of the blind person to generate decisions as output. These outputs are communicated through IoT devices to assist the blind person or user for safe movement. The proposed system provides the user with easy navigation and obstacle avoidance.
Road Profile Estimation Using a 3D Sensor and Intelligent Vehicle
Authors: Ni Tao , Li Wenhang , Zhao Dingxuan , Kong Zhifei
Published: June 2020

Autonomous vehicles can achieve accurate localization and real-time road information perception using sensors such as global navigation satellite systems (GNSSs), light detection and ranging (LiDAR), and inertial measurement units (IMUs). With road information, vehicles can navigate autonomously to a given position without traffic accidents. However, most of the research on autonomous vehicles has paid little attention to road profile information, which is a significant reference for vehicles driving on uneven terrain. Most vehicles experience violent vibrations when driving on uneven terrain, which reduce the accuracy and stability of data obtained by LiDAR and IMUs. Vehicles with an active suspension system, on the other hand, can maintain stability on uneven roads, which further guarantees sensor accuracy. In this paper, we propose a novel method for road profile estimation using LiDAR and vehicles with an active suspension system. In the former, 3D laser scanners, IMU, and GPS were used to obtain accurate pose information and real-time cloud data points, which were added to an elevation map. In the latter, the elevation map was further processed by a Kalman filter algorithm to fuse multiple cloud data points at the same cell of the map. The model predictive control (MPC) method is proposed to control the active suspension system to maintain vehicle stability, thus further reducing drifts of LiDAR and IMU data. The proposed method was carried out in outdoor environments, and the experiment results demonstrated its accuracy and effectiveness.
Average Consensus over Mobile Wireless Sensor Networks: Weight Matrix Guaranteeing Convergence without Reconfiguration of Edge Weights
Authors: Kenyeres Martin , Kenyeres Jozef
Published: June 2020

Efficient data aggregation is crucial for mobile wireless sensor networks, as their resources are significantly constrained. Over recent years, the average consensus algorithm has found a wide application in this technology. In this paper, we present a weight matrix simplifying the average consensus algorithm over mobile wireless sensor networks, thereby prolonging the network lifetime as well as ensuring the proper operation of the algorithm. Our contribution results from the theorem stating how the Laplacian spectrum of an undirected simple finite graph changes in the case of adding an arbitrary edge into this graph. We identify that the mixing parameter of Best Constant weights of a complete finite graph with an arbitrary order ensures the convergence in time-varying topologies without any reconfiguration of the edge weights. The presented theorems and lemmas are verified over evolving graphs with various parameters, whereby it is demonstrated that our approach ensures the convergence of the average consensus algorithm over mobile wireless sensor networks in spite of no edge reconfiguration.
Improved Active Disturbance Rejection Control for Trajectory Tracking Control of Lower Limb Robotic Rehabilitation Exoskeleton
Authors: Aole Sumit , Elamvazuthi Irraivan , Waghmare Laxman , Patre Balasaheb , Meriaudeau Fabrice
Published: June 2020

Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging affect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the quality of treatment. Amongst recent control strategies used for rehabilitation robots, active disturbance rejection control (ADRC) strategy is a systematic way out from a robust control paradox with possibilities and promises. In this modern era, we always try to find the solution in order to have minimum resources and maximum output, and in robotics-control, to approach the same condition observer-based control strategies is an added advantage where it uses a state estimation method which reduces the requirement of sensors that is used for measuring every state. This paper introduces improved active disturbance rejection control (I-ADRC) controllers as a combination of linear extended state observer (LESO), tracking differentiator (TD), and nonlinear state error feedback (NLSEF). The proposed controllers were evaluated through simulation by investigating the sagittal plane gait trajectory tracking performance of two degrees of freedom, Lower Limb Robotic Rehabilitation Exoskeleton (LLRRE). This multiple input multiple output (MIMO) LLRRE has two joints, one at the hip and other at the knee. In the simulation study, the proposed controllers show reduced trajectory tracking error, elimination of random, constant, and harmonic disturbances, robustness against parameter variations, and under the influence of noise, with improvement in performance indices, indicates its enhanced tracking performance. These promising simulation results would be validated experimentally in the next phase of research.
Efficient Star Identification Using a Neural Network
Authors: Rijlaarsdam David , Yous Hamza , Byrne Jonathan , Oddenino Davide , Furano Gianluca , Moloney David
Published: June 2020

The required precision for attitude determination in spacecraft is increasing, providing a need for more accurate attitude determination sensors. The star sensor or star tracker provides unmatched arc-second precision and with the rise of micro satellites these sensors are becoming smaller, faster and more efficient. The most critical component in the star sensor system is the lost-in-space star identification algorithm which identifies stars in a scene without a priori attitude information. In this paper, we present an efficient lost-in-space star identification algorithm using a neural network and a robust and novel feature extraction method. Since a neural network implicitly stores the patterns associated with a guide star, a database lookup is eliminated from the matching process. The search time is therefore not influenced by the number of patterns stored in the network, making it constant (O(1)). This search time is unrivalled by other star identification algorithms. The presented algorithm provides excellent performance in a simple and lightweight design, making neural networks the preferred choice for star identification algorithms.
Natural Recovery and Liming Effects in Acidified Forest Soils in SW-Germany
Authors: Jansone Lelde , von Wilpert Klaus , Hartmann Peter
Published: June 2020

In the state of Baden-Wuerttemberg, Southwest-Germany, a large-scale forest liming trial was government-funded in 1983 and a lime treatment was carried out in autumn 1983 until early winter 1984. Repeated liming was applied in 2003. The limed sites and adjacent control plots were surveyed repeatedly: in 2003 before the second lime application and again in 2010 and 2015. Research of this scope presents a rare opportunity to evaluate firstly the long-term development of acidified soils with their potential for natural recovery on established control plots, and secondly the long-term effects of repeated lime application—at a collective of study sites of various growth regions and soil properties. A natural recovery in soil pH was observed since 2003, on average limited to an increase of 0.2–0.4 pH units in the forest floor and 0.1–0.3 pH units in the mineral soil until 2015. The majority of the organic layers still show very strong or extreme acidity with a pH value 3.9 on average and in the mineral soil with pH values between 3.8 and 4.6 on average. The exchangeable cations calcium and magnesium slightly increased also, although the base saturation remained <20% by 2015. The exchangeable acid cation concentrations indicated no significant changes and thus no recovery. The lime treatment greatly accelerated the rise in pH by 1.2–1.3 units and base saturation by 40–70% in the organic layer, as well as 0.3–1.2 pH units and base saturation by 7–50% in mineral soil. These effects were decreasing (yet still significant) with depth in the measured soil profile as well as with time since last treatment. Changes in soil cation exchange capacity after liming were significant in 0–5 cm mineral soil, below that they were negligible as the significant increase in base cations were accompanied by decreasing acid cations aluminum and iron (III) especially in the upper soil profile. Additionally, a decrease of forest floor and an enrichment of organic carbon and nitrogen in the mineral topsoil tended to follow liming at some sites. Overall the liming effects had a high variability among the study sites, and were more pronounced in the more acidic and coarser textured sites. Liming of acidified forest soils significantly adds to natural recovery and therefore helps to establish greater buffering capacities and stabilize forest nutrition for the future.
Sustainable Sport Entrepreneurship and Innovation: A Bibliometric Analysis of This Emerging Field of Research
Authors: González-Serrano María Huertas , Añó Sanz Vicente , González-García Rómulo Jacobo
Published: June 2020

In the sports sector, entrepreneurship, innovation, and social corporative responsible are generating growing interest during the last years. Due to that situation, sustainable entrepreneurship and innovation in sport have emerged in this sector, receiving individual attention from academics and practitioners. However, little is known about the evolution of this new field of research. Thus, the main aim of this paper is to analyze the documents published in the Web of Science about sport sustainable entrepreneurship and innovation. The bibliometric analysis allows us to discover the current state of a research field, identify the principal authors, articles, and topics, and propose future research lines to develop it further. The articles published between 2000 and 2019 were analyzed quantitatively, and by word and author co-occurrence. Later, through the bibliographic coupling, the articles were grouped in different clusters. Seven central thematics were found, being the sports mega-events and the sustainability the most development sub-area or research, followed by the sport innovation for fostering inclusion. Moreover, for the development of this field of research, studies focused on “tourism” and “entrepreneurship” with “environment”, “sport”, “sustainability and knowledge” and “innovation” focus, are necessary. Thus, sustainable entrepreneurship and innovation in sport are an undeveloped but promising field for the future of the sports industry.
The Effects of Perceived Risk, Brand Credibility and Past Experience on Purchase Intention in the Airbnb Context
Authors: Jun Soo-Hyun
Published: June 2020

This study investigated the main effects of perceived risks, brand credibility and past experience on intention to stay at Airbnb places and the interaction effects of past experience with perceived risks and brand credibility on intention to stay. A survey research method was utilized in South Korea. Our study is the first study to have applied and supported Jacoby and Kaplan’s six constructs in explaining consumers’ risk perceptions in the Airbnb context. One of the primary findings of this study was that past experience played a significant moderating role in the Airbnb context. Social risk and psychological risk had negative effects and performance risk had a positive effect on Airbnb users’ intention to stay. With regard to non-users, psychological risk had a negative effect on intention to stay. These findings indicate that Airbnb users consider more specific risks based on their prior experiences of Airbnb use. This study also revealed that brand credibility had the strongest influence on both Airbnb users’ and non-users’ intention to stay. Consistent with previous research, this finding indicates that brand credibility is a critical variable in consumer decision-making for the intangible and heterogeneous products like accommodation. Based on these findings, theoretical and managerial implications were provided, and limitations and future research were discussed.
Outward FDI and Entrepreneurship: The Case of China
Authors: Shen Li , Koveos Peter , Zhu Xiaodong , Wen Fei , Liao Jiaxian
Published: June 2020

Outward foreign direct investment (OFDI) from developing countries, like China, has been growing significantly so far. However, there is surprisingly little research on the effects of OFDI on the home county’s entrepreneurship. In this paper, we initially examine the characteristics of China’s OFDI during the country’s economic reform and opening up. We subsequently test for the hypothesis that Chinese OFDI, along with the Chinese entrepreneurial institutional environment and inward FDI, impacted entrepreneurial activities from the year of 2004 to 2015. We find that OFDI has an inverted “U” effect on entrepreneurial activities, and that the impacts of inward FDI as well as the foreign trade are different in the coastal and non-coastal cities. We conclude by discussing the implications of our findings for researchers and policymakers as well as the limitations of our data.
A Harris Hawks Optimization Based Single- and Multi-Objective Optimal Power Flow Considering Environmental Emission
Authors: Islam Mohammad Zohrul , Wahab Noor Izzri Abdul , Veerasamy Veerapandiyan , Hizam Hashim , Mailah Nashiren Farzilah , Guerrero Josep M. , Mohd Nasir Mohamad Nasrun
Published: June 2020

The electric sector is majorly concerned about the greenhouse and non-greenhouse gas emissions generated from both conventional and renewable energy sources, as this is becoming a major issue globally. Thus, the utilities must adhere to certain environmental guidelines for sustainable power generation. Therefore, this paper presents a novel nature-inspired and population-based Harris Hawks Optimization (HHO) methodology for controlling the emissions from thermal generating sources by solving single and multi-objective Optimal Power Flow (OPF) problems. The OPF is a non-linear, non-convex, constrained optimization problem that primarily aims to minimize the fitness function by satisfying the equality and inequality constraints of the system. The cooperative behavior and dynamic chasing patterns of hawks to pounce on escaping prey is modeled mathematically to minimize the objective function. In this paper, fuel cost, real power loss and environment emissions are regarded as single and multi-objective functions for optimal adjustments of power system control variables. The different conflicting framed multi-objective functions have been solved using weighted sums using a no-preference method. The presented method is coded using MATLAB software and an IEEE (Institute of Electrical and Electronics Engineers) 30-bus. The system was used to demonstrate the effectiveness of selective objectives. The obtained results are compared with the other Artificial Intelligence (AI) techniques such as the Whale Optimization Algorithm (WOA), the Salp Swarm Algorithm (SSA), Moth Flame (MF) and Glow Warm Optimization (GWO). Additionally, the study on placement of Distributed Generation (DG) reveals that the system losses and emissions are reduced by an amount of 9.8355% and 26.2%, respectively.