bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart Shockwave Responsive Titania-Based Nanoparticles for Cancer Treatment
Authors: Vighetto Veronica , Racca Luisa , Canta Marta , Matos Joana C. , Dumontel Bianca , Gonçalves Maria Clara , Cauda Valentina
Published: September 2021

Nanomedicine is an emerging treatment approach for many cancers, characterized by having high sensitivity and selectivity for tumor cells and minimal toxic effects induced by the conventional chemotherapeutics. In these context, smart nanoparticles (NPs) are getting increasingly relevant in the development of new therapies. NPs with specific chemical composition and/or structure and being stimuli-responsive to magnetic, light or ultrasound waves are new promising tools. In the present work, amorphous-titania propyl-amine functionalized (a-TiO2-NH2) NPs, coated with bovine serum albumin (BSA), are stimulated with high energy shock waves to induce cytotoxic effects in cancer cells. First, a new method to coat a-TiO2-NH2 NPs with BSA (a-TiO2-NH2/BSA) was proposed, allowing for a high dispersion and colloidal stability in a cell culture media. The a-TiO2-NH2/BSA NPs showed no cancer cell cytotoxicity. In a second step, the use of shock waves to stimulate a-TiO2-NH2/BSA NPs, was evaluated and optimized. A systematic study was performed in in vitro cell culture aiming to impair the cancer cell viability: NP concentrations, time steps and single versus multiple shock waves treatments were studied. The obtained results highlighted the relevance of NPs design and administration time point with respect to the shock wave treatment and allow to hypothesize mechanical damages to cells.
Whey Proteins–Zinc Oxide Bionanocomposite as Antibacterial Films
Authors: Pino Paolo , Ronchetti Silvia , Mollea Chiara , Sangermano Marco , Onida Barbara , Bosco Francesca
Published: September 2021

The use of toxic crosslinking agents and reagents in the fabrication of hydrogels is a frequent issue which is particularly concerning for biomedical or food packaging applications. In this study, novel antibacterial bionanocomposite films were obtained through a simple solvent casting technique without using any crosslinking substance. Films were made from a flexible and transparent whey protein matrix containing zinc oxide nanoparticles synthesised via a wet chemical precipitation route. The physicochemical and functional properties of the ZnO nanoparticles and of the composite films were characterised, and their antibacterial activity was tested against S. epidermidis and E. coli. The synthesised ZnO nanoparticles had an average size of about 30 nm and a specific surface area of 49.5 m2/g. The swelling ratio of the bionanocomposite films increased at basic pH, which is an appealing feature in relation to the absorption of chronic wound exudate. A n-ZnO concentration-dependent antibacterial effect was observed for composite films. In particular, marked antibacterial activity was observed against S. epidermidis. Overall, these findings suggest that this novel material can be a promising and sustainable alternative in the design of advanced solutions for wound dressing or food packaging.
Therapeutic Targeting of the Anaplastic Lymphoma Kinase (ALK) in Neuroblastoma—A Comprehensive Update
Authors: Brenner Annette K. , Gunnes Maria W.
Published: September 2021

Neuroblastoma (NBL) is an embryonic malignancy of the sympathetic nervous system and mostly affects children under the age of five. NBL is highly heterogeneous and ranges from spontaneously regressing to highly aggressive disease. One of the risk factors for poor prognosis are aberrations in the receptor tyrosine kinase anaplastic lymphoma kinase (ALK), which is involved in the normal development and function of the nervous system. ALK mutations lead to constitutive activation of ALK and its downstream signalling pathways, thus driving tumorigenesis. A wide range of steric ALK inhibitors has been synthesized, and several of these inhibitors are already in clinical use. Major challenges are acquired drug resistance to steric inhibitors and pathway evasion strategies of cancer cells upon targeted therapy. This review will give a comprehensive overview on ALK inhibitors in clinical use in high-risk NBL and on the potential and limitations of novel inhibitors. Because combinatory treatment regimens are probably less likely to induce drug resistance, a special focus will be on the combination of ALK inhibitors with drugs that either target downstream signalling pathways or that affect the survival and proliferation of cancer cells in general.
Intragenomic Conflict between Knob Heterochromatin and B Chromosomes Is the Key to Understand Genome Size Variation along Altitudinal Clines in Maize
Authors: González Graciela Esther , Poggio Lidia
Published: September 2021

In maize, we studied the causes of genome size variation and their correlates with cultivation altitude that suggests the existence of adaptive clines. To discuss the biological role of the genome size variation, we focused on Bolivian maize landraces growing along a broad altitudinal range. These were analyzed together with previously studied populations from altitudinal clines of Northwestern Argentina (NWA). Bolivian populations exhibited numerical polymorphism for B chromosomes (Bs) (from 1 to 5), with frequencies varying from 16.6 to 81.8 and being positively correlated with cultivation altitude. The 2C values of individuals 0B (A-DNA) ranged between 4.73 and 7.71 pg, with 58.33% of variation. The heterochromatic knobs, detected by DAPI staining, were more numerous and larger in individuals 0B than in those with higher doses of Bs. Bolivian and NWA landraces exhibited the same pattern of A-DNA downsizing and fewer and smaller knobs with increasing cultivation altitude, suggesting a mechanistic link among heterochromatin, genome size and phenology. The negative association between the two types of supernumerary DNA (knob heterochromatin and Bs), mainly responsible for the genome size variation, may be considered as an example of intragenomic conflict. It could be postulated that the optimal nucleotype is the result of such conflict, where genome adjustment may lead to an appropriate length of the vegetative cycle for maize landraces growing across altitudinal clines.
Safety and Efficacy of Kartigen® in Treating Cartilage Defects: A Randomized, Controlled, Phase I Trial
Authors: Liu Yen-Liang , Yen Chun-Che , Liu Tzu-Shang Thomas , Chang Chih-Hung , Shih Tiffany Ting-Fang , Wang Jyh-Horng , Yang Ming-Chia , Lin Feng-Huei , Liu Hwa-Chang
Published: September 2021

Here, we aimed to investigate the safety and preliminary efficacy of Kartigen®, a matrix with autologous bone marrow mesenchymal stem cell-derived chondrocyte precursors embedded in atelocollagen. As a surgical graft, Kartigen® was implanted onto the cartilage defects at the weight-bearing site of the medial femoral condyle of the knee. Fifteen patients were enrolled and stratified into two groups, undergoing either Kartigen® implantation (n = 10) or microfracture (control group, n = 5). The primary endpoint was to evaluate the safety of Kartigen® by monitoring the occurrence of adverse events through physician queries, physical examinations, laboratory tests, and radiological analyses for 2 years. There were no infections, inflammations, adhesions, loose body, or tumor formations in the Kartigen®-implanted knees. The preliminary efficacy was assessed using the International Knee Documentation Committee (IKDC) score, visual analog scale, and second-look arthroscopy. The postoperative IKDC scores of the Kartigen® group significantly improved in the 16th week (IKDC = 62.1 ± 12.8, p = 0.025), kept increasing in the first year (IKDC = 78.2 ± 15.4, p < 0.005), and remained satisfactory in the second year (IKDC = 73.6 ± 13.8, p < 0.005), compared to the preoperative condition (IKDC = 47.1 ± 17.0), while the postoperative IKDC scores of the control group also achieved significant improvement in the 28th week (IKDC = 68.5 ± 6.1, p = 0.032) versus preoperative state (IKDC = 54.0 ± 9.1). However, the IKDC scores decreased in the first year (IKDC = 63.5 ± 11.6) as well as in the second year (IKDC = 52.6 ± 16.4). Thirteen patients underwent second-look arthroscopy and biopsy one year after the operation. The Kartigen® group exhibited integration between Kartigen® and host tissue with a smooth appearance at the recipient site, whereas the microfracture group showed fibrillated surfaces. The histological and immunohistochemical analyses of biopsy specimens demonstrated the columnar structure of articular cartilage and existence of collagen type II and glycosaminoglycan mimic hyaline cartilage. This study indicates that Kartigen® is safe and effective in treating cartilage defects.
Extraction of Microcrystalline Cellulose from Washingtonia Fibre and Its Characterization
Authors: Azum Naved , Jawaid Mohammad , Kian Lau Kia , Khan Anish , Alotaibi Maha Moteb
Published: September 2021

Washingtonia is a desert plant with great sustainability and renewability in nature and is abundantly cultivated across global urban regions. Its fibre biomass comprises cellulose as the major structural part, and this is why it can be potentially utilized as an alternative biomaterial for manufacturing microcrystalline cellulose (MCC) products that can be widely applied in industrial fields. In the present study, NaOH-treated Washingtonia fibre (WAKL), NaClO2-treated Washingtonia fibre (WBLH), and Washingtonia microcrystalline cellulose (WMCC) were extracted through combined treatments of alkalization, bleaching, and acidic hydrolysis, respectively. The obtained chemically treated fibre samples were subjected to characterization to investigate their morphology, physico-chemistry, and thermal stability. In a morphological examination, the large bunch WAKL fibre reduced into small size WMCC fibrils, evidencing that the lignin and hemicellulose components were greatly eliminated through chemical dissolution. The elemental composition revealed that almost all impurities of anions and cations had been removed, particularly for the WMCC sample, showing its high purity of cellulose content. Additionally, the WMCC sample could attain at 25% yield, giving it the advantage for feasible economic production. Furthermore, the physicochemical analysis, Fourier Transform Infrared-ray (FTIR), indicated the presence of a crystalline cellulose region within the WMCC structure, which had promoted it with high crystallinity of 72.6% as examined by X-ray diffraction (XRD). As for thermal analysis, WMCC showed greater thermal stability comparing to WAKL and WBLC samples at high temperature. Therefore, Washingtonia fibre can be a reliable biosubstituent to replace other plant material for MCC production in the future.
Aging Mechanisms and Non-Destructive Aging Indicators of XLPE/CSPE Unshielded LV Nuclear Power Cables Subjected to Simultaneous Radiation-Mechanical Aging
Authors: Afia Ramy S. A. , Mustafa Ehtasham , Tamus Zoltán Ádám
Published: September 2021

Low-voltage cable systems in nuclear power plants are key components that have a crucial role in the safe operation of nuclear facilities. Thus, the aging management of cable systems is of utmost importance as they cannot easily or economically be replaced or upgraded. Therefore, there is a continuous need to develop reliable non-destructive condition monitoring techniques, mostly based on the measurement of the dielectric properties of cable insulation. This paper introduces the changing of dielectric and mechanical properties of XLPE insulated and CSPE jacketed unshielded low-voltage nuclear power plant power cable in case of simultaneous mechanical and radiation aging. The cable samples were bent and exposed to 400 kGy gamma irradiation with a 0.5 kGy/hr dose rate. Dielectric response (real and imaginary permittivity) in the 0.1 Hz−1 kHz frequency range, extended voltage response (EVR), and the Shore D hardness test techniques were measured to track aging. The electrical and mechanical parameters have increased monotonically with aging, except the imaginary permittivity, which increased only at frequencies higher than 10 Hz. Furthermore, different quantities were deducted based on the frequency and permittivity data. The electrical parameters and deducted quantities correlation with aging and mechanical parameters were investigated. Since the deducted quantities and the electrical parameters are strongly correlated with absorbed dose and mechanical properties, the electrical measurements can be applied as a non-destructive aging indicator for XLPE/CSPE unshielded low-voltage nuclear power cables.
A Review on Synthesis, Properties, and Applications of Polylactic Acid/Silica Composites
Authors: Kaseem Mosab , Ur Rehman Zeeshan , Hossain Shakhawat , Singh Ashish Kumar , Dikici Burak
Published: September 2021

Polylactic acid (PLA)/silica composites as multifunctional high-performance materials have been extensively examined in the past few years by virtue of their outstanding properties relative to neat PLA. The fabrication methods, such as melt-mixing, sol–gel, and in situ polymerization, as well as the surface functionalization of silica, used to improve the dispersion of silica in the polymer matrix are outlined. The rheological, thermal, mechanical, and biodegradation properties of PLA/silica nanocomposites are highlighted. The potential applications arising from the addition of silica nanoparticles into the PLA matrix are also described. Finally, we believe that a better understanding of the role of silica additive with current improvement strategies in the dispersion of this additive in the polymer matrix is the key for successful utilization of PLA/silica nanocomposites and to maximize their fit with industrial applications needs.
Feasibility of Processing Hot-Melt Pressure-Sensitive Adhesive (HMPSA) with Solvent in the Lab
Authors: Xue Jing , Wang Jing , Huang Haofei , Wang Ming , Zhang Yali , Zhang Lijuan
Published: September 2021

Hot-melt pressure-sensitive adhesive (HMPSA) is an environmentally benign adhesive which is typically processed without solvent in industries. However, casting solution method is commonly used for experimental purposes in the lab for convenience. Therefore, seven types of solvent with different polarities, including toluene as the most commonly used solvent, were investigated in this work to study the feasibilities. Quick bond strength and holding power were tested with different types of solvents and different adhesive weight percent in the prepared solutions. Through viscosity measurement, thermal analysis, and compositional analysis, the correlation between the chosen solvents and adhesive performance was further explored. It was found that the differences in the obtained bond strength of HMPSA treated with a variety of solvents were due to physical reasons instead of chemical reactions, and a solvent with similar polarity to toluene (e.g., tetrachloride, octane) should be considered as an option because a similar polymer chain relaxation could be maintained as the original HMPSA without solvent treatment. In this study, the mechanism of choosing toluene as common solvent for HMPSA testing was analyzed, and the feasibility of optional solvents was discussed.
Thermal Analysis Technologies for Biomass Feedstocks: A State-of-the-Art Review
Authors: Teh Jun Sheng , Teoh Yew Heng , How Heoy Geok , Sher Farooq
Published: September 2021

An effective analytical technique for biomass characterisation is inevitable for biomass utilisation in energy production. To improve biomass processing, various thermal conversion methods such as torrefaction, pyrolysis, combustion, hydrothermal liquefaction, and gasification have been widely used to improve biomass processing. Thermogravimetric analysers (TG) and gas chromatography (GC) are among the most fundamental analytical techniques utilised in biomass thermal analysis. Thus, GC and TG, in combination with MS, FTIR, or two-dimensional analysis, were used to examine the key parameters of biomass feedstock and increase the productivity of energy crops. We can also determine the optimal ratio for combining two separate biomass or coals during co-pyrolysis and co-gasification to achieve the best synergetic relationship. This review discusses thermochemical conversion processes such as torrefaction, combustion, hydrothermal liquefaction, pyrolysis, and gasification. Then, the thermochemical conversion of biomass using TG and GC is discussed in detail. The usual emphasis on the various applications of biomass or bacteria is also discussed in the comparison of the TG and GC. Finally, this study investigates the application of technologies for analysing the composition and developed gas from the thermochemical processing of biomass feedstocks.
An Investigation of Ultrasonic-Assisted Electrochemical Machining of Micro-Hole Array
Authors: Shen Zhe-Yong , Tsui Hai-Ping
Published: September 2021

This paper uses an ultrasonic vibration-integrated array electrode for 301 stainless steel micro-hole drilling. The influence of machining parameters such as ultrasonic vibration amplitude, working voltage, pulse-off time and electrode feed rate on different processing characteristics are discussed. The experimental results show that the ultrasonic-assisted electrode array vibrating generates a periodic pressure difference for the electrolyte. The periodic pressure difference forms a pumping effect and a cavitation effect. The two effects can effectively renew the electrolyte in the machining gap and discharge the reaction product, gas and reaction heat from the gap. Machining speed can be increased by over 500% when the ultrasonic amplitude increases from 0.94 μm to 2.87 μm. Micro-hole drilling with the optimum experimental parameter combination of ultrasonic amplitude 2.87 μm, working voltage 11 V, pulse-off time 50 μs and electrode feed rate 5 μm/s can result in a minimum average diagonal length and a smaller amount of variation in diagonal length. It also improves the inlet and outlet taper angle of micro-holes.
Economic Policy Uncertainty and Cryptocurrency Market as a Risk Management Avenue: A Systematic Review
Authors: Haq Inzamam Ul , Maneengam Apichit , Chupradit Supat , Suksatan Wanich , Huo Chunhui
Published: September 2021

Cryptocurrency literature is increasing rapidly nowadays. Particularly, the role of the cryptocurrency market as a risk management avenue has got the attention of researchers. However, it is an immature asset class and requires gaps in current literature for future research directions. This research provides a systematic review of the vast range empirical literature based on the cryptocurrency market as a risk management avenue against economic policy uncertainty (EPU). The review discovers that cryptocurrencies have mixed connectedness patterns with all national EPU therefore, the risk mitigation ability varies from country to country. The review finds that heterogeneous correlation patterns are due to the dependence of EPU on the policies and decisions usually taken by regulatory authorities of a particular country. Additionally, heterogeneous EPU requires heterogeneous solutions to deal with stock market volatility and economic policy uncertainty in different economies. Likewise, the divergent protocol and administration of currencies in the crypto market consequently vicissitudes the hedging and diversification performance against each economy. Many research lines can benefit investors, policymakers, fund managers, or portfolio managers. Therefore, the authors suggested future research avenues in terms of topics, data frequency, and methodologies.
Data Processing and Analysis of Eight-Beam Wind Profile Coherent Wind Measurement Lidar
Authors: Zhao Yuefeng , Zhang Xiaojie , Zhang Yurong , Ding Jinxin , Wang Kun , Gao Yuhou , Su Runsong , Fang Jing
Published: September 2021

Real-time measurement of atmospheric wind field parameters plays an important role in weather analysis and forecasting, including improving the efficiency of wind energy, particle tracking, boundary layer measurements, and airport security. In this study, a wind profile coherent wind Light Detection and Ranging (Lidar) measurement with a wavelength of 1.55 µm was developed and demonstrated based on the principle of eight-beam velocimetry. The wind speed information was retrieved, and vertical and horizontal profiles were calculated via power spectrum estimation of sampled echo signals through the measurement of the atmospheric wind field in Hefei for several consecutive days. The experimental results show that the wind profiles produced using different techniques are quite consistent and the standard error is less than 0.42 m/s compared with three-beam and five-beam wind measurements.
Effect of Atmospheric Corrections on NDVI: Intercomparability of Landsat 8, Sentinel-2, and UAV Sensors
Authors: Moravec David , Komárek Jan , López-Cuervo Medina Serafín , Molina Iñigo
Published: September 2021

Sentinel-2 and Landsat 8 satellites constitute an unprecedented source of freely accessible satellite imagery. To produce precise outputs from the satellite data, however, proper use of atmospheric correction methods is crucial. In this work, we tested the performance of six different atmospheric correction methods (QUAC, FLAASH, DOS, ACOLITE, 6S, and Sen2Cor), together with atmospheric correction given by providers, non-corrected image, and images acquired using an unmanned aerial vehicle while working with the normalised difference vegetation index (NDVI) as the most widely used index. We tested their performance across urban, rural, and vegetated land cover types. Our results show a substantial impact from the choice of the atmospheric correction method on the resulting NDVI. Moreover, we demonstrate that proper use of atmospheric correction methods can increase the intercomparability between data from Landsat 8 and Sentinel-2 satellite imagery.
Accuracy of Global Ionosphere Maps in Relation to Their Time Interval
Authors: Milanowska Beata , Wielgosz Paweł , Krypiak-Gregorczyk Anna , Jarmołowski Wojciech
Published: September 2021

Global ionosphere maps (GIMs) representing ionospheric total electron content (TEC) are applicable in many scientific and engineering applications. However, the GIMs provided by seven Ionosphere Associated Analysis Centers (IAACs) are generated with different temporal resolutions and using different modeling techniques. In this study, we focused on the influence of map time interval on the empirical accuracy of these ionospheric products. We investigated performance of the high-resolution GIMs during high (2014) and low (2018) solar activity periods as well as under geomagnetic storms (19 February 2014 and 17 March 2015). In each of the analyzed periods, GIMs were also assessed over different geomagnetic latitudes. For the evaluation, we used direct comparison of GIM-derived slant TEC (STEC) with dual-frequency GNSS observations obtained from 18 globally distributed stations. In order to perform a comprehensive study, we also evaluated GIMs with respect to altimetry-derived vertical TEC (VTEC) obtained from the Jason-2 and Jason-3 satellites. The study confirmed the influence of GIMs time interval on the provided TEC accuracy, which was particularly evident during high solar activity, geomagnetic storms, and also at low latitudes. The results show that 120-min interval contributes significantly to the accuracy degradation, whereas 60-min one is sufficient to maintain TEC accuracy.
Wearable Near-Infrared Spectroscopy as a Physiological Monitoring Tool for Seals under Anaesthesia
Authors: Bønnelycke Eva-Maria , Hastie Gordon , Bennett Kimberley , Kainerstorfer Jana , Milne Ryan , Moss Simon , Ruesch Alexander , Wu Jingyi , McKnight J. Chris
Published: September 2021

Chemical immobilisation of pinnipeds is a routine procedure in research and veterinary practice. Yet, there are inevitable risks associated with chemical immobilisation, and the physiological response to anaesthetic agents in pinnipeds remains poorly understood. The current study used wearable continuous-wave near-infrared spectroscopy (NIRS) data from 10 trials of prolonged anaesthesia (0.5 to 1.4 h) induced through ketamine and midazolam in five grey seals (Halichoerus grypus) involved in other procedures. The aim of this study was to (1) analyse the effect of each compound on heart rate, arterial oxygen saturation (SpO2), and relative concentration changes in oxygenated [ΔO2Hb] and deoxygenated haemoglobin [ΔHHb] in cerebral tissue and (2) to investigate the use of NIRS as a real-time physiological monitoring tool during chemical immobilisation. Average group responses of ketamine (n = 27) and midazolam (n = 11) administrations were modelled using generalised additive mixed models (GAMM) for each dependent variable. Following ketamine and midazolam administration, [ΔHHb] increased and [ΔO2Hb] remained relatively stable, which was indicative of apnoea. Periods of apnoea were confirmed from respiratory band data, which were simultaneously collected during drugging trials. Given that SpO2 remained at 97% during apnoea, we hypothesized that increasing cerebral [ΔHHb] was a result of venous congestion as opposed to decreased oxygen delivery. Changes in heart rate were limited and appeared to be driven by the individual pharmacological actions of each drug. Future research could include simultaneous measures of metabolic rate, such as the relative change in concentration of cytochrome-c-oxidase, to guide operators in determining when apnoea should be considered prolonged if changes in [ΔHHb] and [ΔO2Hb] occur beyond the limits recorded in this study. Our findings support the use of NIRS as real-time physiological monitoring tool during pinniped chemical immobilisation, which could assist veterinarians and researchers in performing safe anaesthetic procedures.
Encoding Spectral-Spatial Features for Hyperspectral Image Classification in the Satellite Internet of Things System
Authors: Lv Ning , Han Zhen , Chen Chen , Feng Yijia , Su Tao , Goudos Sotirios , Wan Shaohua
Published: September 2021

Hyperspectral image classification is essential for satellite Internet of Things (IoT) to build a large scale land-cover surveillance system. After acquiring real-time land-cover information, the edge of the network transmits all the hyperspectral images by satellites with low-latency and high-efficiency to the cloud computing center, which are provided by satellite IoT. A gigantic amount of remote sensing data bring challenges to the storage and processing capacity of traditional satellite systems. When hyperspectral images are used in annotation of land-cover application, data dimension reduction for classifier efficiency often leads to the decrease of classifier accuracy, especially the region to be annotated consists of natural landform and artificial structure. This paper proposes encoding spectral-spatial features for hyperspectral image classification in the satellite Internet of Things system to extract features effectively, namely attribute profile stacked autoencoder (AP-SAE). Firstly, extended morphology attribute profiles EMAP is used to obtain spatial features of different attribute scales. Secondly, AP-SAE is used to extract spectral features with similar spatial attributes. In this stage the program can learn feature mappings, on which the pixels from the same land-cover class are mapped as closely as possible and the pixels from different land-cover categories are separated by a large margin. Finally, the program trains an effective classifier by using the network of the AP-SAE. Experimental results on three widely-used hyperspectral image (HSI) datasets and comprehensive comparisons with existing methods demonstrate that our proposed method can be used effectively in hyperspectral image classification.
Quality Analysis of Direct Georeferencing in Aspects of Absolute Accuracy and Precision for a UAV-Based Laser Scanning System
Authors: Dreier Ansgar , Janßen Jannik , Kuhlmann Heiner , Klingbeil Lasse
Published: September 2021

The use of UAV-based laser scanning systems is increasing due to the rapid development in sensor technology, especially in applications such as topographic surveys or forestry. One advantage of these multi-sensor systems is the possibility of direct georeferencing of the derived 3D point clouds in a global reference frame without additional information from Ground Control Points (GCPs). This paper addresses the quality analysis of direct georeferencing of a UAV-based laser scanning system focusing on the absolute accuracy and precision of the system. The system investigated is based on the RIEGL miniVUX-SYS and the evaluation uses the estimated point clouds compared to a reference point cloud from Terrestrial Laser Scanning (TLS) for two different study areas. The precision is estimated by multiple repetitions of the same measurement and the use of artificial objects, such as targets and tables, resulting in a standard deviation of <1.2 cm for the horizontal and vertical directions. The absolute accuracy is determined using a point-based evaluation, which results in the RMSE being <2 cm for the horizontal direction and <4 cm for the vertical direction, compared to the TLS reference. The results are consistent for the two different study areas with similar evaluation approaches but different flight planning and processing. In addition, the influence of different Global Navigation Satellite System (GNSS) master stations is investigated and no significant difference was found between Virtual Reference Stations (VRS) and a dedicated master station. Furthermore, to control the orientation of the point cloud, a parameter-based analysis using planes in object space was performed, which showed a good agreement with the reference within the noise level of the point cloud. The calculated quality parameters are all smaller than the manufacturer’s specifications and can be transferred to other multi-sensor systems.
Comparing Three Remotely Sensed Approaches for Simulating Gross Primary Productivity over Mountainous Watersheds: A Case Study in the Wanglang National Nature Reserve, China
Authors: Xie Xinyao , Li Ainong , Jin Huaan , Bian Jinhu , Zhang Zhengjian , Nan Xi
Published: September 2021

Light Use Efficiency (LUE), Vegetation Index (VI)-based, and process-based models are the main approaches for spatially continuous gross primary productivity (GPP) estimation. However, most current GPP models overlook the effects of topography on the vegetation photosynthesis process. Based on the structures of a two-leaf LUE model (TL-LUE), a VI-based model (temperature and greenness, TG), and a process-based model (Boreal Ecosystem Productivity Simulator, BEPS), three models, named mountain TL-LUE (MTL-LUE), mountain TG (MTG), and BEPS-TerrainLab, have been proposed to improve GPP estimation over mountainous areas. The GPP estimates from the three mountain models have been proven to align more closely with tower-based GPP than those from the original models at the site scale, but their abilities to characterize the spatial variation of GPP at the watershed scale are not yet known. In this work, the GPP estimates from three LUE models (i.e., MOD17, TL-LUE, and MTL-LUE), two VI-based models (i.e., TG and MTG), and two process-based models (i.e., BEPS and BEPS-TerrainLab) were compared for a mountainous watershed. At the watershed scale, the annual GPP estimates from MTL-LUE, MTG, and BTL were found to have a higher spatial variation than those from the original models (increasing the spatial coefficient of variation by 6%, 8%, and 22%), highlighting that incorporating topographic information into GPP models might improve understanding of the high spatial heterogeneity of the vegetation photosynthesis process over mountainous areas. Obvious discrepancies were also observed in the GPP estimates from MTL-LUE, MTG, and BTL, with determination coefficients ranging from 0.02–0.29 and root mean square errors ranging from 399–821 gC m−2yr−1. These GPP discrepancies mainly stem from the different (1) structures of original LUE, VI, and process models, (2) assumptions associated with the effects of topography on photosynthesis, (3) input data, and (4) values of sensitive parameters. Our study highlights the importance of considering surface topography when modeling GPP over mountainous areas, and suggests that more attention should be given to the discrepancy of GPP estimates from different models.
Effect of Dust Deposition on Chlorophyll Concentration Estimation in Urban Plants from Reflectance and Vegetation Indexes
Authors: Lin Wenpeng , Yu Xumiao , Xu Di , Sun Tengteng , Sun Yue
Published: September 2021

Using reflectance spectroscopy to monitor vegetation pigments is a crucial method to know the nutritional status, environmental stress, and phenological phase of vegetation. Defining cities as targeted areas and common greening plants as research objects, the pigment concentrations and dust deposition amounts of the urban plants were classified to explore the spectral difference, respectively. Furthermore, according to different dust deposition levels, this study compared and discussed the prediction models of chlorophyll concentration by correlation analysis and linear regression analysis. The results showed: (1) Dust deposition had interference effects on pigment concentration, leaf reflectance, and their correlations. Dust was an essential factor that must be considered. (2) The influence of dust deposition on chlorophyll—a concentration estimation was related to the selected vegetation indexes. Different modeling indicators had different sensitivity to dust. The SR705 and CIrededge vegetation indexes based on the red edge band were more suitable for establishing chlorophyll-a prediction models. (3) The leaf chlorophyll concentration prediction can be achieved by using reflectance spectroscopy data. The effect of the chlorophyll estimation model under the levels of “Medium dust” and “Heavy dust” was worse than that of “Less dust”, which meant the accumulation of dust had interference to the estimation of chlorophyll concentration. The quantitative analysis of vegetation spectrum by reflectance spectroscopy shows excellent advantages in the research and application of vegetation remote sensing, which provides an important theoretical basis and technical support for the practical application of plant chlorophyll content prediction.
A Closed-Form Solution to Linear Feature-Based Registration of LiDAR Point Clouds
Authors: Wang Yongbo , Zheng Nanshan , Bian Zhengfu , Zhang Hua
Published: September 2021

Due to the high complexity of geo-spatial entities and the limited field of view of LiDAR equipment, pairwise registration is a necessary step for integrating point clouds from neighbouring LiDAR stations. Considering that accurate extraction of point features is often difficult without the use of man-made reflectors, and the initial approximate values for the unknown transformation parameters must be estimated in advance to ensure the correct operation of those iterative methods, a closed-form solution to linear feature-based registration of point clouds is proposed in this study. Plücker coordinates are used to represent the linear features in three-dimensional space, whereas dual quaternions are employed to represent the spatial transformation. Based on the theory of least squares, an error norm (objective function) is first constructed by assuming that each pair of corresponding linear features is equivalent after registration. Then, by applying the extreme value analysis to the objective function, detailed derivations of the closed-form solution to the proposed linear feature-based registration method are given step by step. Finally, experimental tests are conducted on a real dataset. The derived experimental result demonstrates the feasibility of the proposed solution: By using eigenvalue decomposition to replace the linearization of the objective function, the proposed solution does not require any initial estimates of the unknown transformation parameters, which assures the stability of the registration method.
A Comparative Evaluation of Inertial Sensors for Gait and Jump Analysis
Authors: Andrenacci Isaia , Boccaccini Riccardo , Bolzoni Alice , Colavolpe Giulio , Costantino Cosimo , Federico Michelangelo , Ugolini Alessandro , Vannucci Armando
Published: September 2021

Gait and jump anomalies are often used as indicators to identify the presence and state of disorders that involve motor symptoms. Physical tests are often performed in specialized laboratories, which offer reliable and accurate results, but require long and costly analyses performed by specialized personnel. The use of inertial sensors for gait and jump evaluation offers an easy-to-use low-cost alternative, potentially applicable by the patients themselves at home. In this paper, we compared three inertial measurement units that are available on the market by means of well-known standardized tests for the evaluation of gait and jump behavior. The aim of the study was to highlight the strengths and weaknesses of each of the tested sensors, considered in different tests, by comparing data collected on two healthy subjects. Data were processed to identify the phases of the movement and the possible inaccuracies of each sensor. The analysis showed that some of the considered inertial units could be reliably used to identify the gait and jump phases and could be employed to detect anomalies, potentially suggesting the presence of disorders.
Immunomagnetic Separation Improves the Detection of Mycobacteria by Paper-Based Lateral and Vertical Flow Immunochromatographic Assays
Authors: Ben Aissa Alejandra , Araújo Barbara , Julián Esther , Boldrin Zanoni Maria Valnice , Pividori María Isabel
Published: September 2021

This work addresses a method that combines immunomagnetic separation (IMS) and paper-based nucleic acid immunochromatographic assay for the sensitive detection of Mycolicibacterium fortuitum (basonym Mycobacterium fortuitum) In particular, the preconcentration of the bacteria was achieved by using magnetic particles modified with an antibody specific towards mycobacteria. Following the IMS, the bacteria were lysed, and the genome was amplified by double-tagging PCR, using a set of primers specific for the 16S rRNA gene for Mycobacterium. During the amplification, the amplicons were labeled with biotin and digoxigenin tags. Moreover, a comparative study of paper-based immunochromatographic platforms, relying on vertical and lateral flow and on the use of streptavidin gold nanoparticles as a signal generating system, was also performed. The visual readout was achieved when the gold-modified amplicons were captured by the anti-DIG antibody in the test line. The analytical performance of both methods, nucleic acid vertical flow (NAVF) and nucleic acid lateral flow (NALF), is also discussed. Although NALF showed lower limit of detections (LODs), both NALF and NAVF combined with IMS were able to detect the required LOD in hemodialysis water, becoming two promising and useful techniques for the rapid screening of water supplies in hemodialysis centers, to prevent the exposure of immunosuppressed patients to contaminated sources.
Home-Based Sleep Sensor Measurements in an Older Australian Population: Before and during a Pandemic
Authors: Kholghi Mahnoosh , Ellender Claire M. , Zhang Qing , Gao Yang , Higgins Liesel , Karunanithi Mohanraj
Published: September 2021

Older adults are susceptible to poor night-time sleep, characterized by short sleep duration and high sleep disruptions (i.e., more frequent and longer awakenings). This study aimed to longitudinally and objectively assess the changes in sleep patterns of older Australians during the 2020 pandemic lockdown. A non-invasive mattress-based device, known as the EMFIT QS, was used to continuously monitor sleep in 31 older adults with an average age of 84 years old before (November 2019–February 2020) and during (March–May 2020) the COVID-19, a disease caused by a form of coronavirus, lockdown. Total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, time to bed, and time out of bed were measured across these two periods. Overall, there was no significant change in total sleep time; however, women had a significant increase in total sleep time (36 min), with a more than 30-min earlier bedtime. There was also no increase in wake after sleep onset and sleep onset latency. Sleep efficiency remained stable across the pandemic time course between 84–85%. While this sample size is small, these data provide reassurance that objective sleep measurement did not deteriorate through the pandemic in older community-dwelling Australians.
Smart Prognostics and Health Management (SPHM) in Smart Manufacturing: An Interoperable Framework
Authors: Sundaram Sarvesh , Zeid Abe
Published: September 2021

Advances in the manufacturing industry have led to modern approaches such as Industry 4.0, Cyber-Physical Systems, Smart Manufacturing (SM) and Digital Twins. The traditional manufacturing architecture that consisted of hierarchical layers has evolved into a hierarchy-free network in which all the areas of a manufacturing enterprise are interconnected. The field devices on the shop floor generate large amounts of data that can be useful for maintenance planning. Prognostics and Health Management (PHM) approaches use this data and help us in fault detection and Remaining Useful Life (RUL) estimation. Although there is a significant amount of research primarily focused on tool wear prediction and Condition-Based Monitoring (CBM), there is not much importance given to the multiple facets of PHM. This paper conducts a review of PHM approaches, the current research trends and proposes a three-phased interoperable framework to implement Smart Prognostics and Health Management (SPHM). The uniqueness of SPHM lies in its framework, which makes it applicable to any manufacturing operation across the industry. The framework consists of three phases: Phase 1 consists of the shopfloor setup and data acquisition steps, Phase 2 describes steps to prepare and analyze the data and Phase 3 consists of modeling, predictions and deployment. The first two phases of SPHM are addressed in detail and an overview is provided for the third phase, which is a part of ongoing research. As a use-case, the first two phases of the SPHM framework are applied to data from a milling machine operation.
Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning
Authors: Hsu Chen-Ming , Hsu Chien-Chang , Hsu Zhe-Ming , Shih Feng-Yu , Chang Meng-Lin , Chen Tsung-Hsing
Published: September 2021

Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of colorectal cancer (CRC). The adenoma detection rate and accuracy of diagnosis of colorectal polyp which vary in different experienced endoscopists have impact on the colonoscopy protection effect of CRC. The work proposed a colorectal polyp image detection and classification system through grayscale images and deep learning. The system collected the data of CVC-Clinic and 1000 colorectal polyp images of Linkou Chang Gung Medical Hospital. The red-green-blue (RGB) images were transformed to 0 to 255 grayscale images. Polyp detection and classification were performed by convolutional neural network (CNN) model. Data for polyp detection was divided into five groups and tested by 5-fold validation. The accuracy of polyp detection was 95.1% for grayscale images which is higher than 94.1% for RGB and narrow-band images. The diagnostic accuracy, precision and recall rates were 82.8%, 82.5% and 95.2% for narrow-band images, respectively. The experimental results show that grayscale images achieve an equivalent or even higher accuracy of polyp detection than RGB images for lightweight computation. It is also found that the accuracy of polyp detection and classification is dramatically decrease when the size of polyp images small than 1600 pixels. It is recommended that clinicians could adjust the distance between the lens and polyps appropriately to enhance the system performance when conducting computer-assisted colorectal polyp analysis.
A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical Exercise
Authors: Badiola-Bengoa Aritz , Mendez-Zorrilla Amaia
Published: September 2021

Human Pose Estimation (HPE) has received considerable attention during the past years, improving its performance thanks to the use of Deep Learning, and introducing new interesting uses, such as its application in Sport and Physical Exercise (SPE). The aim of this systematic review is to analyze the literature related to the application of HPE in SPE, the available data, methods, performance, opportunities, and challenges. One reviewer applied different inclusion and exclusion criteria, as well as quality metrics, to perform the paper filtering through the paper databases. The Association for Computing Machinery Digital Library, Web of Science, and dblp included more than 500 related papers after the initial filtering, finally resulting in 20. In addition, research was carried out regarding the publicly available data related to this topic. It can be concluded that even if related public data can be found, much more data is needed to be able to obtain good performance in different contexts. In relation with the methods of the authors, the use of general purpose systems as base, such as Openpose, combined with other methods and adaptations to the specific use case can be found. Finally, the limitations, opportunities, and challenges are presented.
Impact of Accurate Detection of Freeway Traffic Conditions on the Dynamic Pricing: A Case Study of I-95 Express Lanes
Authors: Alshayeb Suhaib , Stevanovic Aleksandar , Mitrovic Nikola , Dimitrijevic Branislav
Published: September 2021

Express lanes (ELs) implementation is a proven strategy to deal with freeway traffic congestion. Dynamic toll pricing schemes effectively achieve reliable travel time on ELs. The primary inputs for the typical dynamic pricing algorithms are vehicular volumes and speeds derived from the data collected by sensors installed along the ELs. Thus, the operation of dynamic pricing critically depends on the accuracy of data collected by such traffic sensors. However, no previous research has been conducted to explicitly investigate the impact of sensor failures and erroneous sensors’ data on toll computations. This research fills this gap by examining the effects of sensor failure and faulty detection scenarios on ELs tolls calculated by a dynamic pricing algorithm. The paper’s methodology relies on applying the dynamic toll pricing algorithm implemented in the field and utilizing the fundamental speed-volume relationship to ‘simulate’ the sensors’ reported data. We implemented the methodology in a case study of ELs on Interstate-95 in Southeast Florida. The results have shown that the tolls increase when sensors erroneously report higher than actual traffic demand. Moreover, it has been found that the accuracy of individual sensors and the number of sensors utilized to estimate traffic conditions are critical for accurate toll calculations.