bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermal Treatment and High-Intensity Ultrasound Processing to Evaluate the Chemical Profile and Antioxidant Activity of Amazon Fig Juices
Authors: Cruz Josias M. dos A. , Ramos Andrezza S. , Corrêa Renilto F. , Sanches Edgar A. , Campelo Pedro H. , Kinupp Valdely F. , Bezerra Jaqueline de A.
Published: January 2023

The present paper evaluated the influence of heat treatment (HT) and high-intensity ultrasound (HIUS) on the chemical profile of the Amazon fig (Ficus subapiculata, Moraceae) juices. Antioxidant activity, quantification of carotenoids, total phenolic compounds (TPC), pH, titratable acidity, soluble solids, color and chemical profile (NMR) were evaluated. Treatments did not change the pH (3.4–3.5), titratable acidity (0.044–0.048%) and soluble solids (2.3–2.4 °Brix). The highest antioxidant activity (DPPH, ABTS) and TPC were presented by the HT-treated juice, which was equivalent to 1235 ± 11 µM TE, 1440 ± 13 µM TE and 312 ± 5 mg GAE mL−1, respectively. The treatments influenced the color luminosity according to the L* and a* parameters, while the b* parameter showed no significant change. The L* parameter was elevated in all treated samples compared to the control sample. Analyzing the parameter a* f, it was verified that the sample with thermal treatment (HT) was different from the control sample, but presented similarity with the samples of the HIUS processes. The 1H NMR spectra of the juices showed similar chemical profiles in all treatments. The compounds α-glucose, β-glucose, fructose, citric, malic, quinic, and p-hydroxybenzoic acids were identified. The HT treatment presented higher efficiency to extract the antioxidant compounds from fig juices. The HIUS treatments with constant energy density also improved the tolerance of the antioxidant compounds, especially in conditions of higher potency and reduced time. Future studies will be devoted to carry out microbiological analysis and evaluate the stability of treated juices.
Alkali Etching Hydrochar-Based Adsorbent Preparation Using Chinese Medicine Industry Waste and Its Application in Efficient Removal of Multiple Pollutants
Authors: Zhang Xinyan , Liu Shanshan , Qin Qingyu , Chen Guifang , Wang Wenlong
Published: January 2023

The annual discharge (6–7 million tons per year) of Chinese medicine industry waste (CMIW) is large and harmful. CMIW with a high moisture content can be effectively treated by hydrothermal carbonization (HTC) technology. Compared with CMIW, the volume and number of pores of the prepared hydrochar increased significantly after alkali etching (AE), and they had abundant oxygen-containing functional groups. These properties provide physical and chemical adsorption sites, improving the adsorbent activity of the alkaline etching of Chinese medicine industry waste hydrochar (AE-CMIW hydrochar). However, few studies have investigated the adsorption of organic dyes and heavy metals in mixed solutions. This study proposed a method of coupling HTC with AE to treat CMIW and explored the potential of AE-CMIW hydrochar to remove metal ions and organic dyes from mixed solution. We analyzed the removal rates of metal ions and organic dyes by the adsorbents and investigated their differences. The results showed that the lead ion, cadmium ion, and methylene blue could be efficiently removed by AE-CMIW hydrochar in a mixed solution, with removal rates of more than 98%, 20–57%, and 60–80%, respectively. The removal rates were different mainly due to the various electrostatic interactions, physical adsorption, differences in the hydrating ion radius of the metal ions, and functional group interactions between the AE-CMIW hydrochar and the lead ion, cadmium ion, and methylene blue. This study provides a technical method for preparing multi-pollutant adsorbents from CMIW, which enables efficient utilization of organic solid waste and achieves the purpose of treating waste with waste.
Mechanical Properties and Water Resistance of Magnesium Oxychloride Cement–Solidified Residual Sludge
Authors: Ma Haiqiang , Liang Jiling , Wang Lu , He Han , Wang Wenwu , Han Tingting , Xu Ziting , Han Jie
Published: January 2023

As a solid waste, the amount of residual sludge produced by the municipal wastewater treatment process is escalating. How to dispose it properly is attracting much attention in society. Herein, solidifying residual sludge using magnesium oxychloride cement (MOC) is promising for converting it into building materials. Various factors of mass ratio (RW/S) of liquid to solid, molar ratio (Rn) of MgO to MgCl2 in MOC, mass ratio (Rm) of residual sludge to MOC, the mass concentration of Na2SiO3 (DNa2SiO3), and dosage of fly ash (DF) influenced the unconfined compression strength (RC) of the as–obtained MOC–solidified residual sludge, and it was characterized using SEM and XRD analysis. The results show that the value of RC for MOC–residual sludge solidified blocks increased initially and then decreased as Rn and Rm increased, respectively, for 60–day curing. At 10–day curing, equilibrium RC was reached at all RW/S values except 1.38, and at 60–day curing, RC decreased with RW/S increasing. The maximum RC of 60 days of 20.90 MPa was obtained at RW/S = 0.90, Rn = 5.0, and Rm = 1.00. Furthermore, adding Na2SiO3 or fly ash in the solidifying process could improve RC. The water resistance test showed that SM13 and NF5 samples exhibited good alkaline resistance after immersion for 7 and 14 days in an aqueous solution with pH = 7.0–11.0. The water resistance of MOC–residual sludge solidified blocks decreased with increase in immersion duration in aqueous solutions. The fly ash could also help improve water resistance of MOC–solidified residual sludge in neutral and basic aqueous solutions. This work provides an important theoretical basis and possibility for the efficient disposal and comprehensive utilization of residual sludge through solidification/stabilization technology using MOC from the perspective of mechanics and water resistance.
Design and Parametric Optimization of the Injection Molding Process Using Statistical Analysis and Numerical Simulation
Authors: Chen Jinping , Cui Yanmei , Liu Yuanpeng , Cui Jianfeng
Published: January 2023

Quality control is considered a critical aspect of plastic materials in the injection molding process. Two types of deformations occur during the injection molding process, namely, volumetric shrinkage and warpage. This study aims to optimize the warpage of the polyethylene terephthalate preform (PET) used for the packing of carbonated drinks. PET warpage results in an uneven distribution of material over the wall surface of the preform and causes variation in wall thickness. During the filling operation of carbonated drinks, the preforms are subjected to high pressure at the points where the wall thickness is at a minimum, which induces a high-stress concentration. Under high pressure, the preforms are ruptured at the points where the warpage is at a maximum (stress concentration area), causing wastage of the beverage as well as the preform. In this study, the Taguchi method and analysis of variance (ANOVA) are used to determine the most significant parameters to induce warpage during the molding process. Then, we optimize the process parameters in order to reduce warpage through a numerical approach using SolidWorks Plastics. The result shows that the ambient temperature and melting temperature are the most critical parameters that contribute to the warpage, yielding 42.115% and 41.278%, respectively. Among the 6 parameters considered for this study, the pressure holding time contributes a minimum of 0.5961% to the yielding of the warpage. Overall, by optimizing the process parameters, warpage of the PET preform is minimized by 7.7202%, which helps to reduce wastage of the carbonated drink as well as the rejection rate of the preform during the filling operation. In a nutshell, the quality of the preform is improved.
Healthcare Provider Reports on Social Determinants of Health in Opioid Treatment
Authors: Cambron Christopher , Gouripeddi Ramkiran , Facelli Julio C.
Published: January 2023

Opioid overdose and death from overdose continue to present a pressing problem in the United States. It is well-established that a range of social and economic factors, often referred to as social determinants of health (SDOH), are associated with increased opioid overdose and death. Few studies have examined healthcare provider reports on social and economic barriers to opioid treatment. Healthcare providers (N = 161) participating in opioid Project ECHO (Extension for Community Healthcare Outcomes) programs were surveyed on the portion of their patients experiencing 15 different SDOH. Results indicated that multiple determinants were experienced by the majority of their patients, with poverty as the most commonly experienced social determinant (72%). Regression analyses indicated that physicians generally reported a lower portion of patients experiencing SDOH compared with social workers, nurse practitioners, and other healthcare providers. Results suggest that SDOH are widely experienced by patients seeking opioid treatment and that professional backgrounds may be related to reports of SDOH at the point of care. Multi-disciplinary teams involving social workers, nurse practitioners, and other healthcare providers may improve the identification of social and economic barriers to opioid treatment.
America’s Mosque: The Islamic Center of Washington, Protestant Inclusivism, and the Cold War Genesis of “Multireligious America”
Authors: Strasburg James D.
Published: January 2023

This article examines the contested nature of American efforts to expand America’s twentieth century notion of tri-faith idealism—the unity of the three monotheistic faiths of Protestantism, Catholicism, and Judaism—to include Muslims both at home and abroad. It does so through a contextual, historical study of the construction and dedication of the Islamic Center of Washington. The construction of the Islamic Center ultimately proved a lightning rod that electrified competing wings of Protestant Christian nationalism within in the United States—namely “inclusivist ecumenists” and “exclusivist populists.”
The Power of Example: Following Jesus on the Path of Spirituality in Luke-Acts
Authors: Wright Catherine
Published: January 2023

Luke sets up Jesus as an example of spirituality in Luke-Acts. In Luke, Jesus does not simply tell his disciples to adopt spiritual practices; he models them, inviting readers to imitate him as well. The first century world was familiar with the power of example. Leaders in Luke’s literary world were often idealized because they taught or legislated not just through words, but through the virtuous example of their lives. In the Gospel of Luke, Jesus invites his followers to follow him on the pathway to prayer and simplicity in a similar manner. Like the Lukan Jesus, Numa and Lycurgus, Plutarch’s legendary kings, legislate piety and simplicity through their own lifestyles during their lifetimes. Plutarch devotes significant attention to the issue of their influence after their deaths. Luke’s authorial audience also might have wondered how the powerful effect of Jesus’ exemplary instruction might be sustained after his crucifixion and ascension. In Acts, we see that Jesus’ followers have internalized his instruction and example of prayer and simplicity through the power of the Holy Spirit, adopting Jesus’ spiritual patterns as their own. Early receptions of Lukan texts on prayer and simplicity in Luke-Acts show that the early church continues to follow this practice, looking to Jesus as a model of spirituality for their own lives and the lives of their communities.
A Spatial Study of the Relics of Chinese Tomb Murals
Authors: Shi Yizhen , Wang Xiaoyang
Published: January 2023

China has numerous relics from tomb murals. Over 70 years (1949–2019), 1495 relic sites were excavated. Distributed across more than two-thirds of China’s provincial administrative regions, the relics of tomb murals span from the Han Dynasty (206 BC–220 AD) to the Qing Dynasty (1644–1911). In previous studies, scholars focused on the qualitative analysis of tomb murals. In this paper, we applied GIS tools to visualize these relics and analyze their density values for the first time. In terms of academic standards, we propose the material distribution index, the regional distribution index, and the temporal distribution index for relics. The academic innovation of this paper is threefold. First, with regard to the distribution of relic sites, this paper draws a distribution map of the relic sites of Chinese tomb murals and explores the preliminary significance of these relic sites in the culture of the Yellow River basin and its ancient political center. Second, in terms of synchronic viewpoints, this paper designs a material distribution map and a kernel density distribution map based on the distribution map of relic sites. Third, from a diachronic viewpoint, this paper sketches the secondary-level distribution map of six historical periods for the overall kernel density distribution map of relic materials in nine provinces, whereby it outlines the general trend of the development of Chinese tomb murals and the contributions of nine provinces. In brief, with the use of the GIS tool, this paper obtains information on the distribution of relics and reveals the characteristics of tomb murals in terms of their regional and temporal distributions through the ranking of various density values. This paper aims to construct a frame of reference for testing traditional theoretical achievements from the two perspectives of information acquisition and theoretical analysis.
Kinship and Leadership in 1 Timothy: A Study of Filial Framework and Model for Christian Communities in Asia Minor
Authors: Darko Daniel K.
Published: January 2023

This essay examines the kinship framework and lexemes in the directives for leadership in 1 Timothy, aiming to curb the influence of false teachers and to bolster internal cohesion in the communities. It explores the author’s appeal to household conduct, natural and fictive kinship, and group dynamics couched in filial parlance vis-à-vis the undisputed Pauline letters. The study sheds light on the authorial framework, and suggests that the notion of a departure from ‘love-patriarchalism’ or egalitarian Paul developing later into hierarchical kinship framework in 1 Timothy may be misleading. It becomes apparent that the letter’s kinship lexemes are consistent with what we find in the undisputed letters. Thus, the pseudonymous author, an associate of Paul, does not appeal to or use kinship lexemes any differently from the undisputed letters or elsewhere in Greco-Roman discourse. This does not establish Pauline authorship, but suggest that the notion that the kinship lexemes reflect an elevated hierarchical institutional development in a post-Pauline era, that is uncharacteristic of Paul in the authorship debate, may need to be reconsidered if not revised.
Insights into the Effect of Urban Morphology and Land Cover on Land Surface and Air Temperatures in the Metropolitan City of Milan (Italy) Using Satellite Imagery and In Situ Measurements
Authors: Puche Mathilde , Vavassori Alberto , Brovelli Maria Antonia
Published: January 2023

With a concentration of people, activities, and infrastructures, urban areas are particularly vulnerable to the negative effects of climate change. Among others, the intensification of the Urban Heat Island (UHI) effect is leading to an increased impact on citizen health and the urban ecosystem. In this context, this study aims to investigate the effect of urban morphology and land cover composition—which are established by exploiting the Local Climate Zone (LCZ) classification system—on two urban climate indicators, i.e., Land Surface Temperature (LST) and air temperature. The study area is the Metropolitan City of Milan (northern Italy). LCZ and LST maps are derived by leveraging satellite imagery and building height datasets. Both authoritative and crowdsourced in situ measurements are used for the analysis of air temperature. Several experiments are run to investigate the mutual relation between LCZ, LST, and air temperature by measuring LST and air temperature patterns in different LCZs and periods. Besides a strong temporal correlation between LST and air temperature, results point out vegetation and natural areas as major mitigating factors of both variables. On the other hand, higher buildings turn out to increase local air temperature while buffering LST values. A way lower influence of building density is measured, with compact building areas experiencing slightly higher air temperature yet no significant differences in terms of LST. These outcomes provide valuable tools to urban planners and stakeholders for implementing evidence-based UHI mitigation strategies.
Dominant Contribution of South Asia Monsoon to External Moisture for Extreme Precipitation Events in Northern Tibetan Plateau
Authors: Wang Yan , Yang Kun , Huang Wenyu , Qiu Tianpei , Wang Binbin
Published: January 2023

Numerous previous studies have pointed out that the South Asia monsoon (SAM) contributes most moisture to the southern Tibetan Plateau, whilst the moisture over the Northern Tibetan Plateau (NTP) is supplied by the westerlies, but the moisture sources for extreme precipitation events remain unclear. In this study, the tracking of external moisture sources was performed on ten extreme precipitation events over each of six target subregions of the NTP during the summer of 2010–2018. We found that the SAM provided most of the external moisture for extreme precipitation events in the NTP, except for the largest contribution from East Asia to extreme precipitation in the easternmost subregion. The moisture carried by westerly winds is the second foreign source over the western NTP. In addition, more than 40% of the NTP extreme precipitation events occurred under the synergy of weak westerlies and enhanced SAM, and these events have a longer duration than others. Thus, SAM plays a key role in moisture transport for the extreme precipitation events over the NTP, even though its contribution to the climatological moisture is not significant.
Isostatic Anomaly and Isostatic Additional Force Analysis by Multiple Geodetic Observations in Qinling Area
Authors: Yuan Huaqing , Wu Yunlong , Zhang Yi , Shi Xuguo , Bian Shaofeng
Published: January 2023

Determination of the isostatic anomaly and the isostatic additional force plays a key role in understanding the deep tectonic features and dynamics in the Qinling area. At present, high-accuracy observation gravity data are one of the important means to obtain the isostatic anomaly and the isostatic additional force. Firstly, we calculate the free-air gravity anomalies and the Bouguer gravity anomalies by using hybrid gravity and GPS observation data. Then, we invert the isostatic anomaly and the isostatic additional force. The results show that the isostatic depth calculated by Airy isostatic theory is 40–49 km, and the Moho depth is 39–48 km. The Weihe Basin is in a non-isostatic state with an upward isostatic additional force that reached about 20 MPa. The isostatic anomaly and the isostatic additional force are approximately zero in the northern Sichuan Basin, which indicates that the crust is in isostatic state. The negative isostatic anomaly and isostatic additional force in Liupanshan Mountains, the southwest margin of the Ordos Basin, and the local areas of the Qinling Orogen and Dabashan indicate the existence of crustal movement. By combining the measurement of InSAR, we obtain the surface deformation information of the Weihe Basin, as well as an upward trend, which proves that the result is highly consistent with the gravity observation.
Strong-Scattering Multiparameter Reconstruction Based on Elastic Direct Envelope Inversion and Full-Waveform Inversion with Anisotropic Total Variation Constraint
Authors: Zhang Pan , Wu Ru-Shan , Han Liguo , Zhou Yixiu
Published: January 2023

Strong-scattering medium can usually form a good sealing medium for oil and gas resources. However, conventional elastic full-waveform inversion (EFWI) methods are difficult to build reliable velocity models under the condition of lacking low-frequency information. The elastic direct envelope inversion (EDEI) method has been proven to be able to model large-scale Vp and Vs structures of strong-scattering media. The successive use of EDEI and EFWI can obtain fine structures of the strong scatterers and their shielding areas. However, the inversion effects of inner velocity and bottom boundaries of strong scatterers by the existing methods need to be improved. In this paper, we propose the elastic direct envelope inversion with anisotropic total variation constraint (EDEI-ATV). The anisotropic total variation (ATV) constraint has the advantage of making the velocity more uniform inside the layer and sharper on boundaries, which can be used to improve the inversion results of EDEI. During the iterations, the ATV constraint is directly applied to the update of Vp and Vs, and the alternately iterative algorithm can achieve good results. After obtaining reliable large-scale Vp and Vs structures, the EFWI with anisotropic total variation constraint (EFWI-ATV) is performed to obtain high-precision Vp and Vs structures. Numerical examples verify the effectiveness of the proposed method.
Urban Tree Canopy Mapping Based on Double-Branch Convolutional Neural Network and Multi-Temporal High Spatial Resolution Satellite Imagery
Authors: Chen Shuaiqiang , Chen Meng , Zhao Bingyu , Mao Ting , Wu Jianjun , Bao Wenxuan
Published: January 2023

Accurate knowledge of urban forest patterns contributes to well-managed urbanization, but accurate urban tree canopy mapping is still a challenging task because of the complexity of the urban structure. In this paper, a new method that combines double-branch U-NET with multi-temporal satellite images containing phenological information is introduced to accurately map urban tree canopies. Based on the constructed GF-2 image dataset, we developed a double-branch U-NET based on the feature fusion strategy using multi-temporal images to obtain an accuracy improvement with an IOU (intersection over union) of 2.3% and an F1-Score of 1.3% at the pixel level compared to the U-NET using mono-temporal images which performs best in existing studies for urban tree canopy mapping. We also found that the double-branch U-NET based on the feature fusion strategy has better accuracy than the early fusion strategy and decision fusion strategy in processing multi-temporal images for urban tree canopy mapping. We compared the impact of image combinations of different seasons on the urban tree canopy mapping task and found that the combination of summer and autumn images had the highest accuracy in the study area. Our research not only provides a high-precision urban tree canopy mapping method but also provides a direction to improve the accuracy both from the model structure and data potential when using deep learning for urban tree canopy mapping.
Using Pre-Fire High Point Cloud Density LiDAR Data to Predict Fire Severity in Central Portugal
Authors: Fernández-Guisuraga José Manuel , Fernandes Paulo M.
Published: January 2023

The wall-to-wall prediction of fuel structural characteristics conducive to high fire severity is essential to provide integrated insights for implementing pre-fire management strategies designed to mitigate the most harmful ecological effects of fire in fire-prone plant communities. Here, we evaluate the potential of high point cloud density LiDAR data from the Portuguese áGiLTerFoRus project to characterize pre-fire surface and canopy fuel structure and predict wildfire severity. The study area corresponds to a pilot LiDAR flight area of around 21,000 ha in central Portugal intersected by a mixed-severity wildfire that occurred one month after the LiDAR survey. Fire severity was assessed through the differenced Normalized Burn Ratio (dNBR) index computed from pre- and post-fire Sentinel-2A Level 2A scenes. In addition to continuous data, fire severity was also categorized (low or high) using appropriate dNBR thresholds for the plant communities in the study area. We computed several metrics related to the pre-fire distribution of surface and canopy fuels strata with a point cloud mean density of 10.9 m−2. The Random Forest (RF) algorithm was used to evaluate the capacity of the set of pre-fire LiDAR metrics to predict continuous and categorized fire severity. The accuracy of RF regression and classification model for continuous and categorized fire severity data, respectively, was remarkably high (pseudo-R2 = 0.57 and overall accuracy = 81%) considering that we only focused on variables related to fuel structure and loading. The pre-fire fuel metrics with the highest contribution to RF models were proxies for horizontal fuel continuity (fractional cover metric) and the distribution of fuel loads and canopy openness up to a 10 m height (density metrics), indicating increased fire severity with higher surface fuel load and higher horizontal and vertical fuel continuity. Results evidence that the technical specifications of LiDAR acquisitions framed within the áGiLTerFoRus project enable accurate fire severity predictions through point cloud data with high density.
Vicarious CAL/VAL Approach for Orbital Hyperspectral Sensors Using Multiple Sites
Authors: Pearlshtien Daniela Heller , Pignatti Stefano , Ben-Dor Eyal
Published: January 2023

The hyperspectral (HSR) sensors Earth Surface Mineral Dust Source Investigation (EMIT) of the National Aeronautics and Space Administration (NASA) and Environmental Mapping and Analysis Program (EnMAP) of the German Aerospace Center (DLR) were recently launched. These state-of-the-art sensors have joined the already operational HSR sensors DESIS (DLR), PRISMA (Italian Space Agency), and HISUI (developed by the Japanese Ministry of Economy, Trade, and Industry METI and Japan Aerospace Exploration Agency JAXA). The launching of more HSR sensors is being planned for the near future (e.g., SBG of NASA, and CHIME of the European Space Agency), and the challenge of monitoring and maintaining their calibration accuracy is becoming more relevant. We proposed two test sites: Amiaz Plain (AP) and Makhtesh Ramon (MR) for spectral, radiometric, and geometric calibration/validation (CAL/VAL). The sites are situated in the arid environment of southern Israel and are in the same overpass coverage. Both test sites have already demonstrated favorable results in assessing an HSR sensor’s performance and were chosen to participate in the EMIT and EnMAP validation stage. We first evaluated the feasibility of using AP and MR as CAL/VAL test sites with extensive datasets and sensors, such as the multispectral sensor Landsat (Landsat5 TM and Landsat8 OLI), the airborne HSR sensor AisaFENIX 1K, and the spaceborne HSR sensors DESIS and PRISMA. Field measurements were taken over time. The suggested methodology integrates reflectance and radiometric CAL/VAL test sites into one operational protocol. The method can highlight degradation in the spectral domain early on, help maintain quantitative applications, adjust the sensor’s radiometric calibration during its mission lifetime, and minimize uncertainties of calibration parameters. A PRISMA sensor case study demonstrates the complete operational protocol, i.e., performance evaluation, quality assessment, and cross-calibration between HSR sensors. These CAL/VAL sites are ready to serve as operational sites for other HSR sensors.
Coherent Multi-Dwell Processing of Un-Synchronized Dwells for High Velocity Estimation and Super-Resolution in Radar
Authors: Levy Benzion , Maman Lior , Shvartzman Shlomi , Pinhasi Yosef
Published: January 2023

This paper describes a coherent multi-dwell processing (CMDP) method for high velocity estimation and super-resolution in search and track, while search (TWS) radar modes use an un-conventional signal processing algorithm that exploits multi-dwell transmissions. The existence of the multi-dwell waveform is necessary for visibility needs by un-folding the target’s velocity and range ambiguity and is proposed to be utilized for high velocity estimation and super-resolution. In this paper, the proposed scheme is shown to result in improved velocity estimation and doppler resolution performance for un-ambiguous targets in comparison to classical radar processing. The processing concept uses the same transmitted waveform (WF) and time duration without the need to increase the time on target (TOT) through sophisticated coherent concatenation of the received dwells with velocity compensation between the dwells. The phase compensation in receive mode is implemented for each target according to its characteristics, which means that target velocities are estimated in each dwell separately. The notable result of the CMDP is the linear doppler resolution improvement obtained with the given search resources and without knowing the target characteristics in advance or the dwell delay time. Other possible benefits of this process are the ability to achieve larger detection ranges and high-angle measurement precisions in search mode due to the higher signal-to-noise ratio (SNR) of the extended dwell and the ability to track more targets due to efficient time and resource management. An outstanding opportunity to exploit the CMDP is by combining missions in phased array (PA) radars, meeting the multi-objective needs of both high spatial scan rates for illuminating the target and high doppler estimation and resolution performance.
Real-Time Precise Point Positioning during Outages of the PPP-B2b Service
Authors: Chen Yufei , Wang Xiaoming , Zhou Kai , Zhang Jinglei , Qiu Cong , Li Haobo , Xin Shiji
Published: January 2023

The precise point positioning service on B2b signal (PPP-B2b) is a real-time decimeter-level positioning service provided by the BeiDou-3 Global Navigation Satellite System (BDS-3). The service provides users with high-precision orbit and clock corrections through geostationary orbit (GEO) satellites, which means that the PPP-B2b service would be unusable if GEO satellites were blocked. In this study, the performance of PPP-B2b corrections and real-time positioning results during outages of the PPP-B2b service are comprehensively investigated. The results showed that PPP can achieve satisfactory accuracy during outages of the PPP-B2b service by extending the nominal validity of the received PPP-B2b corrections. After extending the PPP-B2b corrections for 10 min, for BDS-3 medium earth orbit (MEO) satellites, the mean root-mean-square error (RMSE) values of the extended orbit were 0.16 m, 0.26 m, and 0.23 m in the radial, along-, and cross-track directions, respectively. The accuracy of the BDS-3 inclined geostationary orbit (IGSO) satellites was slightly worse than that of the BDS-3 MEO satellites; for Global Positioning System (GPS) satellites, the mean RMSE values of the extended orbit were 0.11 m, 0.45 m, and 0.33 m in the radial, along-, and cross-track directions, respectively. In terms of the extended clock, the mean standard deviation (STD) reached 0.17 ns, 0.20 ns, and 0.22 ns after 10 min for the BDS-3 MEO, BDS-3 IGSO, and GPS satellites, respectively. The positioning performance maintained with the extended corrections during the PPP-B2b service outage was evaluated based on five stations in and around China. Our experiments showed that, as long as the interruption time does not exceed 10 min, the real-time positioning with extended PPP-B2b corrections can achieve a comparable accuracy with that obtained following PPP-B2b correction.
Evaluation of Linear Kernel-Driven BRDF Models over Snow-Free Rugged Terrain
Authors: Zhu Wenzhe , You Dongqin , Wen Jianguang , Tang Yong , Gong Baochang , Han Yuan
Published: January 2023

Semi-empirical kernel-driven models have been widely used to characterize anisotropic reflectance due to their simple form and physically meaningful approximation. Recently, several kernel-driven models have been coupled with topographic effects to improve the fitting of bidirectional reflectance over rugged terrains. However, extensive evaluations of the various models’ performances are required before their subsequent application in remote sensing. Three typical kernel-driven BRDF models over snow-free rugged terrains such as the RTLSR, TCKD, and the KDST-adjusted TCKD (KDST-TCKD) were investigated in this paper using simulated and observed BRFs. Against simulated data, the fitting error (NIR/Red RMSE) of the RTLSR gradually increases from 0.0358/0.0342 to 0.0471/0.0516 with mean slopes (α) increases from 9.13° to 33.40°. However, the TCKD and KDST-TCKD models perform an overall better fitting accuracy: the fitting errors of TCKD gradually decreased from 0.0366/0.0337 to 0.0252/0.0292, and the best fit from the KDST-TCDK model with NIR/Red RMSE decreased from 0.0192/0.0269 to 0.0169/0.0180. When compared to the sandbox data (α from 8.4° to 30.36°), the NIR/Red RMSE of the RTLSR model ranges from 0.0147/0.0085 to 0.0346/0.0165, for the TCKD model from 0.0144/0.0086 to 0.0298/0.0154, and for the KDST-TCKD model from 0.0137/0.0082 to 0.0234/0.0149. Using MODIS data, the TCKD and KDST-TCKD models show more significant improvements compared to the RTLSR model in rugged terrains. Their RMSE differences are within 0.003 over a relatively flat terrain (α < 10°). When α is large (20°–30° and >30°), the RMSE of the TCKD model has a decrease of around 0.01 compared to that of the RTLSR; for KDST-TCKD, it is approximately 0.02, and can even reach 0.0334 in the savannas. Therefore, the TCKD and KDST-TCKD models have an overall better performance than the RTLSR model in rugged terrains, especially in the case of large mean slopes. Among them, the KDST-TCKD model performs the best due to its consideration of topographic effects, geotropic growth, and component spectra.
Effect of Equipment on the Accuracy of Accelerometer-Based Human Activity Recognition in Extreme Environments
Authors: Ward Stephen , Hu Sijung , Zecca Massimiliano
Published: January 2023

A little explored area of human activity recognition (HAR) is in people operating in relation to extreme environments, e.g., mountaineers. In these contexts, the ability to accurately identify activities, alongside other data streams, has the potential to prevent death and serious negative health events to the operators. This study aimed to address this user group and investigate factors associated with the placement, number, and combination of accelerometer sensors. Eight participants (age = 25.0 ± 7 years) wore 17 accelerometers simultaneously during lab-based simulated mountaineering activities, under a range of equipment and loading conditions. Initially, a selection of machine learning techniques was tested. Secondly, a comprehensive analysis of all possible combinations of the 17 accelerometers was performed to identify the optimum number of sensors, and their respective body locations. Finally, the impact of activity-specific equipment on the classifier accuracy was explored. The results demonstrated that the support vector machine (SVM) provided the most accurate classifications of the five machine learning algorithms tested. It was found that two sensors provided the optimum balance between complexity, performance, and user compliance. Sensors located on the hip and right tibia produced the most accurate classification of the simulated activities (96.29%). A significant effect associated with the use of mountaineering boots and a 12 kg rucksack was established.
Tire Slip H∞ Control for Optimal Braking Depending on Road Condition
Authors: Meléndez-Useros Miguel , Jiménez-Salas Manuel , Viadero-Monasterio Fernando , Boada Beatriz López
Published: January 2023

Tire slip control is one of the most critical topics in vehicle dynamics control, being the basis of systems such the Anti-lock Braking System (ABS), Traction Control System (TCS) or Electronic Stability Program (ESP). The highly nonlinear behavior of tire–road contact makes it challenging to design robust controllers able to find a dynamic stable solution in different working conditions. Furthermore, road conditions greatly affect the braking performance of vehicles, being lower on slippery roads than on roads with a high tire friction coefficient. For this reason, by knowing the value of this coefficient, it is possible to change the slip ratio tracking reference of the tires in order to obtain the optimal braking performance. In this paper, an H∞ controller is proposed to deal with the tire slip control problem and maximize the braking forces depending on the road condition. Simulations are carried out in the vehicular dynamics simulator software CarSim. The proposed controller is able to make the tire slip follow a given reference based on the friction coefficient for the different tested road conditions, resulting in a small reference error and good transient response.
A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue
Authors: Mou Tian , Liang Jianwen , Vu Trung Nghia , Tian Mu , Gao Yi
Published: January 2023

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.
Outlier Vehicle Trajectory Detection Using Deep Autoencoders in Santiago, Chile
Authors: Peralta Billy , Soria Richard , Nicolis Orietta , Ruggeri Fabrizio , Caro Luis , Bronfman Andrés
Published: January 2023

In the last decade, a large amount of data from vehicle location sensors has been generated due to the massification of GPS systems to track them. This is because these sensors usually include multiple variables such as position, speed, angular position of the vehicle, etc., and, furthermore, they are also usually recorded in very short time intervals. On the other hand, routes are often generated so that they do not correspond to reality, due to artifacts such as buildings, bridges, or sensor failures and where, due to the large amount of data, visual analysis of human expert is unable to detect genuinely anomalous routes. The presence of such abnormalities can lead to faulty sensors being detected which may allow sensor replacement to reliably track the vehicle. However, given the reliability of the available sensors, there are very few examples of such anomalies, which can make it difficult to apply supervised learning techniques. In this work we propose the use of unsupervised deep neural network models based on stacked autoencoders to detect anomalous routes in vehicles within Santiago de Chile. The results show that the proposed model is capable of effectively detecting anomalous paths in real data considering validation given by an expert user, reaching a performance of 82.1% on average. As future work, we propose to incorporate the use of Long Short-Term Memory (LSTM) and attention-based networks in order to improve the detection of anomalous trajectories.
Improvement of Hexacopter UAVs Attitude Parameters Employing Control and Decision Support Systems
Authors: Stamate Mihai-Alin , Pupăză Cristina , Nicolescu Florin-Adrian , Moldoveanu Cristian-Emil
Published: January 2023

Today, there is a conspicuous upward trend for the development of unmanned aerial vehicles (UAVs), especially in the field of multirotor drones. Their advantages over fixed-wing aircrafts are that they can hover, which allows their usage in a wide range of remote surveillance applications: industrial, strategic, governmental, public and homeland security. Moreover, because the component market for this type of vehicles is in continuous growth, new concepts have emerged to improve the stability and reliability of the multicopters, but efficient solutions with reduced costs are still expected. This work is focused on hexacopter UAV tests carried out on an original platform both within laboratory and on unrestricted open areas during the start–stop manoeuvres of the motors to verify the operational parameters, hover flight, the drone stability and reliability, as well as the aerodynamics and robustness at different wind speeds. The flight parameters extracted from the sensor systems’ comprising accelerometers, gyroscopes, magnetometers, barometers, GPS antenna and EO/IR cameras were analysed, and adjustments were performed accordingly, when needed. An FEM simulation approach allowed an additional decision support platform that expanded the experiments in the virtual environment. Finally, practical conclusions were drawn to enhance the hexacopter UAV stability, reliability and manoeuvrability.
A Differential Confocal Sensor for Simultaneous Position and Slope Acquisitions Based on a Zero-Crossing Prediction Algorithm
Authors: Wang Tingyu , Wang Zhiyi , Yang Yongqiang , Mi Xiaotao , Ti Yunzan , Wang Jianli
Published: January 2023

A new sensor type is proposed to accurately detect the surface profiles of three-dimensional (3D) free-form surfaces. This sensor is based on the single-exposure, zero-crossing method and is used to measure position and angle simultaneously. First, the field intensity distribution in the posterior focal plane of the confocal microscope’s objective was modeled accurately. Second, because the camera needs to trigger acquisition when the surface (to be measured) reaches the focal position of the sensor, a zero-crossing prediction method based on a sliding window was proposed. Third, a fast, spatially convergent, peak-extraction algorithm was proposed to improve the accuracy and efficiency of peak extraction. This scheme reduces system installation and adjustment difficulties, and the single-exposure, zero-crossing method achieves high-speed, real-time image acquisitions. The experimental results indicate that the average error of the zero-crossing prediction system was 17.63 nm, the average error of the tilt degree measurement was 0.011° in the range of 0–8°, and the prediction error of the tilt direction measurement was 0.089° in the range of 0–360°. The sensor can measure the slope and can be potentially used for 3D surface precision detection.
Application of Feedforward and Recurrent Neural Networks for Fusion of Data from Radar and Depth Sensors Applied for Healthcare-Oriented Characterisation of Persons’ Gait
Authors: Mazurek Paweł
Published: January 2023

In this paper, the useability of feedforward and recurrent neural networks for fusion of data from impulse-radar sensors and depth sensors, in the context of healthcare-oriented monitoring of elderly persons, is investigated. Two methods of data fusion are considered, viz., one based on a multilayer perceptron and one based on a nonlinear autoregressive network with exogenous inputs. These two methods are compared with a reference method with respect to their capacity for decreasing the uncertainty of estimation of a monitored person’s position and uncertainty of estimation of several parameters enabling medical personnel to make useful inferences on the health condition of that person, viz., the number of turns made during walking, the travelled distance, and the mean walking speed. Both artificial neural networks were trained on the synthetic data. The numerical experiments show the superiority of the method based on a nonlinear autoregressive network with exogenous inputs. This may be explained by the fact that for this type of network, the prediction of the person’s position at each time instant is based on the position of that person at the previous time instants.
Gas Sensor Based on Lossy Mode Resonances by Means of Thin Graphene Oxide Films Fabricated onto Planar Coverslips
Authors: Vitoria Ignacio , Gallego Elieser E. , Melendi-Espina Sonia , Hernaez Miguel , Ruiz Zamarreño Carlos , Matías Ignacio R.
Published: January 2023

The use of planar waveguides has recently shown great success in the field of optical sensors based on the Lossy Mode Resonance (LMR) phenomenon. The properties of Graphene Oxide (GO) have been widely exploited in various sectors of science and technology, with promising results for gas sensing applications. This work combines both, the LMR-based sensing technology on planar waveguides and the use of a GO thin film as a sensitive coating, to monitor ethanol, water, and acetone. Experimental results on the fabrication and performance of the sensor are presented. The obtained results showed a sensitivity of 3.1, 2.0, and 0.6 pm/ppm for ethanol, water, and acetone respectively, with a linearity factor R2 > 0.95 in all cases.
Air-GR: An Over-the-Air Handwritten Character Recognition System Based on Coordinate Correction YOLOv5 Algorithm and LGR-CNN
Authors: Zhang Yajun , Li Zijian , Yang Zhixiong , Yuan Bo , Liu Xu
Published: January 2023

Traditional human-computer interaction technology relies heavily on input devices such as mice and keyboards, which limit the speed and naturalness of interaction and can no longer meet the more advanced interaction needs of users. With the development of computer vision (CV) technology, research on contactless gesture recognition has become a new research hotspot. However, current CV-based gesture recognition technology has the limitation of a limited number of gesture recognition and cannot achieve fast and accurate text input operations. To solve this problem, this paper proposes an over-the-air handwritten character recognition system based on the coordinate correction YOLOv5 algorithm and a lightweight convolutional neural network (LGR-CNN), referred to as Air-GR. Unlike the direct recognition of captured gesture pictures, the system uses the trajectory points of gesture actions to generate images for gesture recognition. Firstly, by combining YOLOv5 with the gesture coordinate correction algorithm proposed in this paper, the system can effectively improve gesture detection accuracy. Secondly, considering that the captured gesture coordinates may contain multiple gestures, this paper proposes a time-window-based algorithm for segmenting the gesture coordinates. Finally, the system recognizes user gestures by plotting the segmented gesture coordinates in a two-dimensional coordinate system and feeding them into the constructed lightweight convolutional neural network, LGR-CNN. For the gesture trajectory image classification task, the accuracy of LGR-CNN is 13.2%, 12.2%, and 4.5% higher than that of the mainstream networks VGG16, ResNet, and GoogLeNet, respectively. The experimental results show that Air-GR can quickly and effectively recognize any combination of 26 English letters and numbers, and its recognition accuracy reaches 95.24%.