bluuebunny/crossref_metadata_2025 huggingface dataset:
Improvement of Enzymatic Saccharification of Cellulose-Containing Raw Materials Using Aspergillus niger
Authors: Budenkova Ekaterina , Sukhikh Stanislav , Ivanova Svetlana , Babich Olga , Dolganyuk Vyacheslav , Michaud Philippe , Kriger Olga
Published: August 2021

Enzymatic hydrolysis of cellulose-containing raw materials, using Aspergillus niger, were studied. Filter paper, secondary cellulose-containing or starch-containing raw materials, miscanthus cellulose after alkaline or acid pretreatment, and wood chip cellulose, were used as substrates. The study focused on a wild A. niger strain, treated, or not (control), by ultraviolet (UV) irradiations for 45, 60, or 120 min (UV45, UV60, or UV120), or by UV irradiation for 120 min followed by a chemical treatment with NaN3 + ItBr for 30 min or 80 min (UV120 + CH30 or UV120 + CH80). A mixture of all the A. niger strains (MIX) was also tested. A citrate buffer, at 50 mM, wasthe most suitable for enzymatic hydrolysis. As the UV exposure time increased to 2 h, the cellulase activity of the surviving culturewas increased (r = 0.706; p < 0.05). The enzymatic activities of the obtained strains, towards miscanthus cellulose, wood chips, and filter paper, were inferior to those obtained with commercial enzymes (8.6 versus 9.1 IU), in some cases. Under stationary hydrolysis at 37 °C, pH = 4.7, the enzymatic activity of A. niger UV120 + CH30 was 24.9 IU. The enzymatic hydrolysis of secondary raw materials, using treated A. niger strains, was themost effective at 37 °C. Similarly, the most effective treatment of miscanthus cellulose and wood chips occurred at 50 °C. The maximum conversion of cellulose to glucose was observed using miscanthus cellulose (with alkaline pretreatment), and the minimum conversion was observed when using wood chips. The greatest value of cellulase activity was evidenced in the starch-containing raw materials, indicating that A. niger can ferment not only through cellulase activity, but also via an amylolytic one.
Concept and Case Study for a Generic Simulation as a Digital Shadow to Be Used for Production Optimisation
Authors: Kassen Stefan , Tammen Holger , Zarte Maximilian , Pechmann Agnes
Published: August 2021

Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production systems are in line with the call of Industry 4.0 for substantial and frequent changes. Creating simulation models for those systems requires high effort and in-depth knowledge of production processes. In the current literature, digital twins promise several advantages for production optimisation and can be used to simulate production systems, which reduce necessary physical test runs and related costs. While most companies are not able to create digital twins yet, companies using enterprise resource planning (ERP) systems have the general capability to create digital shadows. This paper presents a concept and a case study for a generic simulation of production systems in AnyLogic™ to create digital shadows as the first step towards a full digital twin. The generic simulation visualises production systems automatically and displays key performance indicators (KPIs) for the planned production program, using representational state transfer (REST) interfaces to extract product and production data from an ERP system. The case study has been applied in a learning factory of the University of Applied Life Sciences Emden/Leer. The results prove the presented concept of the generic simulation and show the limits and challenges of working with generic simulation models.
Properties of Extruded Snacks Prepared from Corn and Carrot Powder with Ascorbic Acid Addition
Authors: Obradović Valentina , Babić Jurislav , Dragović-Uzelac Verica , Jozinović Antun , Ačkar Đurđica , Šubarić Drago
Published: August 2021

The objective of this research was to investigate the potentiality of carrot powder (CP) utilization at levels 4, 6, or 8% as ingredient of corn snacks and evaluation of the extrusion influence on functionally important ingredients such as carotenoids (color), polyphenols, fiber, fat, and antioxidant activity. The influence of ascorbic acid (AA) as an external source at levels 0.5 and 1% on this particular extrusion was also investigated. A single-screw extruder at two temperature regimes (135/170/170 °C (E1) and 100/150/150 °C (E2)) carried out extrusion. The E1 temperature regime acted favorably on total polyphenol content and crude fiber, but fat preferred the E2 regime. Extrusion, especially the E1 temperature regime, increased the extractability of carotenoids. Ascorbic acid degraded during extrusion, but it still provided protection to carotenoids and color attributes of extrudates. Snacks with increased nutritional and functional value due to carrot powder addition were successfully produced, which is a starting point for production of a new type of extruded snacks.
CSF Proteomic Alzheimer’s Disease-Predictive Subtypes in Cognitively Intact Amyloid Negative Individuals
Authors: Tijms Betty , Gobom Johan , Teunissen Charlotte , Dobricic Valerija , Tsolaki Magda , Verhey Frans , Popp Julius , Martinez-Lage Pablo , Vandenberghe Rik , Lleó Alberto , Molinuévo José , Engelborghs Sebastiaan , Freund-Levi Yvonne , Froelich Lutz , Bertram Lars , Lovestone Simon , Streffer Johannes , Vos Stephanie , ADNI  , Blennow Kaj , Scheltens Philip , Zetterberg Henrik , Visser Pieter
Published: August 2021

We recently discovered three distinct pathophysiological subtypes in Alzheimer’s disease (AD) using cerebrospinal fluid (CSF) proteomics: one with neuronal hyperplasticity, a second with innate immune system activation, and a third subtype with blood–brain barrier dysfunction. It remains unclear whether AD proteomic subtype profiles are a consequence of amyloid aggregation, or might exist upstream from aggregated amyloid. We studied this question in 127 older individuals with intact cognition and normal AD biomarkers in two independent cohorts (EMIF-AD MBD and ADNI). We clustered 705 proteins measured in CSF that were previously related to AD. We identified in these cognitively intact individuals without AD pathology three subtypes: two subtypes were seen in both cohorts (n = 49 with neuronal hyperplasticity and n = 44 with blood–brain barrier dysfunction), and one only in ADNI (n = 12 with innate immune activation). The proteins specific for these subtypes strongly overlapped with AD subtype protein profiles (overlap coefficients 92%–71%). Longitudinal p181-tau and amyloid β 1–42 (Aβ42) CSF analysis showed that in the hyperplasticity subtype p181-tau increased (β = 2.6 pg/mL per year, p = 0.01) and Aβ42 decreased over time (β = −4.4 pg/mL per year, p = 0.03), in the innate immune activation subtype p181-tau increased (β = 3.1 pg/mL per year, p = 0.01) while in the blood–brain barrier dysfunction subtype Aβ42 decreased (β = −3.7 pg/mL per year, p = 0.009). These findings suggest that AD proteomic subtypes might already manifest in cognitively normal individuals and may predispose for AD before amyloid has reached abnormal levels.
A Randomised Controlled CBT Intervention for Maladaptive Perfectionism: Outcome and Predictors
Authors: Zikopoulou Olga , Nisyraiou Anna , Simos Gregoris
Published: August 2021

Maladaptive perfectionism has been associated with certain mental health problems. Moreover, studies suggest that the development of perfectionism can be attributed to childhood experiences and, more specifically, to parenting styles. (1) Background: The aims of the present study were first to examine the relationship of perfectionism to perceived parenting and current symptoms of depression and anxiety and, secondly, to study the effectiveness of a group CBT intervention program for high perfectionism; (2) Methods: Participants were 81 young Greek adults with relatively high scores in perfectionism. They were randomly allocated to two conditions: either the intervention group (IG; n = 40) or a non-active control group (CG; n = 41). The intervention group received a CBT intervention of 10 weekly sessions, while assessments were made in two time points for both groups; (3) Results: There was significant correlation of perfectionism with perceived parental indifference, abuse, and overcontrol as well as measures of anxiety and depression. Results showed significant decrease in perfectionism and other symptoms in the IG. Although perceived paternal indifference and abuse could predict perfectionism at pre-intervention, no pre-intervention variable could predict the perfectionism intervention outcome; (4) Conclusions: Overall, the study suggests that maladaptive perfectionism is associated with perceived negative parenting and current anxiety and depression and that a group CBT intervention can address specific dimensions of maladaptive perfectionism.
Association between Self-Restraint Behavior, Stigma and Depressive Tendency in Office Workers during the COVID-19 Pandemic in Japan—Self-Restraint Behavior and Depression during the COVID-19
Authors: Katsuki Ryoko , Kubo Hiroaki , Yamakawa Itsuki , Shinfuku Naotaka , Sartorius Norman , Sakamoto Shinji , Kato Takahiro A.
Published: August 2021

Background: The COVID-19 pandemic has forced people to change their lifestyles, especially with respect to restrictions on going out. Forced quarantine (i.e., lockdown) and self-restraint behavior (SRB), including self-quarantine, are suggested to induce potential negative impacts on public mental health. SRB seems to be related to governmental policies, each individual’s social background and mental condition; however, no empirical studies have been conducted. Methods: 1053 participants (mainly office workers) from epidemic areas and non-epidemic areas in Japan voluntarily conducted an online survey in June 2020. We assessed COVID-19-related aspects such as the degree of SRB, motivation for SRB, stigma, anxiety and depressive feelings due to COVID-19 by original questionnaires) and general mental health status (social anxiety by MINI-SPIN, depressive tendency by PHQ-9, depression-related personality traits by TACS-22 and resilience by TRS). Results: Regional comparison showed significant differences in SRB and social anxiety. People in epidemic areas tend to refrain from going out. Conversely, people in non-epidemic areas tend to shun the public eye. Regardless of epidemic status, proactive SRB was associated with higher motivation for SRB, higher social anxiety, higher depressive tendency, stronger COVID-19-related psychological factors and lower resilience. Moreover, people with proactive SRB in non-epidemic areas had the highest depressive tendency. Discussion: The present cross-sectional survey among office workers in Japan showed that people with proactive SRB have stronger COVID-19-related anxiety and depressive feelings, regardless of where they live. Our key finding is that people with proactive SRB in non-epidemic areas have the highest depressive tendency. Based on the present finding, we herein propose the following hypothesis: Higher levels of depressive tendency may enhance proactive SRB, which may be partly associated with higher levels of stigma, anxiety and depressive feelings related to COVID-19. Limitations: The general tendencies to avoid danger and stigma were not evaluated. Conclusions: Depressive tendency is suggested to be associated with proactive SRB against COVID-19. Intervention for depressive tendency in non-clinical settings (e.g., workplaces) may help citizens understand the infectious situation appropriately and to behave effectively during the pandemic. Further investigations should be conducted to clarify the present findings.
From the Ivory Tower to the Grass Roots: Ending Orthodox Oppression of Evangelicals, and Beginning Grassroots Fellowship
Authors: Hancock-Stefan George , Stefan SaraGrace
Published: August 2021

When considering the relationship between the Eastern Orthodox Church and the Evangelical Church, can we both celebrate progress towards unity, while acknowledging where growth must still occur? Dr. George Hancock-Stefan, who fled the oppressive communist regime of Yugoslavia with the rest of his Baptist family, now frequently returns to Eastern Europe to explore topics of modern theology. During these travels, he has recognized a concerning trend: the religious unity and interfaith fellowship celebrated in Western academia does not reach the Eastern European local level. This is primarily due to the fact that Orthodoxy is a top to bottom institution, and nothing happens at the local level unless approved by the top. This lack of religious unity and cooperation at the local level is also due to the fact that the Eastern Orthodox Church claims a national Christian monopoly and the presence of Evangelicals is considered an invasion. In this article, Dr. Hancock-Stefan unpacks the history of the spiritual revivals that took place in various Eastern Orthodox Churches in the 19th–20th centuries, as well as the policies established by the national patriarchs after the fall of communism that are now jeopardizing the relationship between Orthodox and Evangelicals. By addressing this friction with candor and Christian love, this article pleads for the Orthodox Church to relinquish its monopoly and hopes that both Orthodox and Evangelicals will start considering each other to be brothers and sisters in Christ.
Spiritual and Philosophical Practices: Together for Community Using the Counseling
Authors: Hațegan Vasile-Petru
Published: August 2021

The paper presents characteristics of practices in the humanities that can be manifested through specific forms of counseling, namely spiritual or pastoral counseling and philosophical counseling. Through the comparative analysis of the two practices, interdisciplinary links are identified, reflected at the conceptual and applied level, with both their similarities and differences being highlighted, in order to emphasize the originality and the capacity to adapt to the requirements of the field from which they come. The paper supports the new trend of involvement in communities of specific counseling practices by expanding their application potential from person to group and community, with the help of an adaptation process necessary to achieve the goal in order to bring the practice of counseling to as many persons and to community or society in general.
Understanding the Role of the Exodus in the Institutionalization and Dismantling of Apartheid: Considering the Paradox of Justice and Injustice in the Exodus
Authors: Gunda Masiiwa Ragies
Published: August 2021

The Exodus played an explicit and implicit role in sustaining the policy and practice of apartheid in South Africa and in various other places that went through the pains of colonization. Interestingly, the same Exodus also played a central part in the resistance to and the subsequent dismantling of the apartheid policy and practice in South Africa. That readers on both sides of the divide found solace in the Exodus was put down to the common assumption that guided both parties. The assumption of historicity caused the Exodus to be read as if it were a photographic record of what happened and the experience of oppression and discrimination by the readers assigned the Exodus a historical status for speaking to a historical situation. The assumption of historicity was central in the destructive uses of the Exodus thereby creating a cycle of oppressed–oppressors across the African continent, as groups took turns to seek out their own advantage. An assumption of justice was proposed as an alternative guiding principle through which justice for all, in line with pivotal events of the Old Testament, can be realized in the world.
Management of Distribution Risks and Digital Transformation of Insurance Distribution—A Regulatory Gap in the IDD
Authors: Marano Pierpaolo
Published: August 2021

The Insurance Distribution Directive (IDD) aims to regulate insurance distribution in the EU regardless of distribution channels and means. Although new technologies affect insurance distribution, the IDD does not explicitly regulate this digital transformation. Insurers and intermediaries must comply with detailed business conduct rules that aim to counteract distribution risks. However, the IDD exempts ancillary insurance intermediaries from its scope when they meet certain conditions. The article highlights the regulatory framework on insurance, requiring insurers and intermediaries to address distribution risks, and analyses how this exemption affects the management of distribution risks in online distribution from a legal perspective. The focus on online distribution depends on the scale such distribution can achieve. The consideration of the scale allows for challenging the political choice behind the exemption of ancillary insurance intermediaries, which consists of the principle of proportionality. A regulatory proposal to counteract these adverse effects is to remove the exemption from the IDD rules for ancillary intermediaries in online distribution. Such a proposal is compliant with the principle of technological neutrality and is in line with the new legislative proposals in the Digital Services Act and Digital Markets Act.
The Potential of Mapping Grassland Plant Diversity with the Links among Spectral Diversity, Functional Trait Diversity, and Species Diversity
Authors: Zhao Yujin , Sun Yihan , Chen Wenhe , Zhao Yanping , Liu Xiaoliang , Bai Yongfei
Published: August 2021

Mapping biodiversity is essential for assessing conservation and ecosystem services in global terrestrial ecosystems. Compared with remotely sensed mapping of forest biodiversity, that of grassland plant diversity has been less studied, because of the small size of individual grass species and the inherent difficulty in identifying these species. The technological advances in unmanned aerial vehicle (UAV)-based or proximal imaging spectroscopy with high spatial resolution provide new approaches for mapping and assessing grassland plant diversity based on spectral diversity and functional trait diversity. However, relatively few studies have explored the relationships among spectral diversity, remote-sensing-estimated functional trait diversity, and species diversity in grassland ecosystems. In this study, we examined the links among spectral diversity, functional trait diversity, and species diversity in a semi-arid grassland monoculture experimental site. The results showed that (1) different grassland plant species harbored different functional traits or trait combinations (functional trait diversity), leading to different spectral patterns (spectral diversity). (2) The spectral diversity of grassland plant species increased gradually from the visible (VIR, 400–700 nm) to the near-infrared (NIR, 700–1100 nm) region, and to the short-wave infrared (SWIR, 1100–2400 nm) region. (3) As the species richness increased, the functional traits and spectral diversity increased in a nonlinear manner, finally tending to saturate. (4) Grassland plant species diversity could be accurately predicted using hyperspectral data (R2 = 0.73, p < 0.001) and remotely sensed functional traits (R2 = 0.66, p < 0.001) using cluster algorithms. This will enhance our understanding of the effect of biodiversity on ecosystem functions and support regional grassland biodiversity conservation.
A Method for Quantifying Understory Leaf Area Index in a Temperate Forest through Combining Small Footprint Full-Waveform and Point Cloud LiDAR Data
Authors: Song Jinling , Zhu Xiao , Qi Jianbo , Pang Yong , Yang Lei , Yu Lihong
Published: August 2021

Understory vegetation plays an important role in the structure and function of forest ecosystems. Light detection and ranging (LiDAR) can provide understory information in the form of either point cloud or full-waveform data. Point cloud data have a remarkable ability to represent the three-dimensional structures of vegetation, while full-waveform data contain more detailed information on the interactions between laser pulses and vegetation; both types have been widely used to estimate various forest canopy structural parameters, including leaf area index (LAI). Here, we present a new method for quantifying understory LAI in a temperate forest by combining the advantages of both types of LiDAR data. To achieve this, we first estimated the vertical distribution of the gap probability using point cloud data to automatically determine the height boundary between overstory and understory vegetation at the plot level. We then deconvolved the full-waveform data to remove the blurring effect caused by the system pulse to restore the vertical resolution of the LiDAR system. Subsequently, we decomposed the deconvolved data and integrated the plot-level boundary height to differentiate the waveform components returned from the overstory, understory, and soil layers. Finally, we modified the basic LiDAR equations introducing understory leaf spectral information to quantify the understory LAI. Our results, which were validated against ground-based measurements, show that the new method produced a good estimation of the understory LAI with an R2 of 0.54 and a root-mean-square error (RMSE) of 0.21. Our study demonstrates that the understory LAI can be successfully quantified through the combined use of point cloud and full-waveform LiDAR data.
A Waveform-Encoded SAR Implementation Using a Limited Number of Cyclically Shifted Chirps
Authors: Jeon Se-Yeon , Glatz Fabian , Villano Michelangelo
Published: August 2021

Synthetic aperture radar (SAR) provides high-resolution images of the Earth’s surface irrespective of sunlight and weather conditions. In conventional spaceborne SAR, nadir echoes caused by the pulsed operation of SAR may significantly affect the SAR image quality. Therefore, the pulse repetition frequency (PRF) is constrained within the SAR system design to avoid the appearance of nadir echoes in the SAR image. As an alternative, the waveform-encoded SAR concept using a pulse-to-pulse variation of the transmitted waveform and dual-focus postprocessing can be exploited for nadir echo removal and to alleviate the PRF constraints. In particular, cyclically shifted chirps have been proposed as a possible waveform variation scheme. However, a large number of distinct waveforms is required to enable the simple implementation of the concept. This work proposes a technique based on the Eulerian circuit for generating a waveform sequence starting from a reduced number of distinct cyclically shifted chirps that can be effectively exploited for waveform-encoded SAR. The nadir echo suppression performance of the proposed scheme is analyzed through simulations using real TerraSAR-X data and a realistic nadir echo model that shows how the number of distinct waveforms and therefore the system complexity can be reduced without significant performance loss. These developments reduce the calibration burden and make the concept viable for implementation in future SAR systems.
Use of TanDEM-X and SRTM-C Data for Detection of Deforestation Caused by Bark Beetle in Central European Mountains
Authors: Gdulová Kateřina , Marešová Jana , Barták Vojtěch , Szostak Marta , Červenka Jaroslav , Moudrý Vítězslav
Published: August 2021

The availability of global digital elevation models (DEMs) from multiple time points allows their combination for analysing vegetation changes. The combination of models (e.g., SRTM and TanDEM-X) can contain errors, which can, due to their synergistic effects, yield incorrect results. We used a high-resolution LiDAR-derived digital surface model (DSM) to evaluate the accuracy of canopy height estimates of the aforementioned global DEMs. In addition, we subtracted SRTM and TanDEM-X data at 90 and 30 m resolutions, respectively, to detect deforestation caused by bark beetle disturbance and evaluated the associations of their difference with terrain characteristics. The study areas covered three Central European mountain ranges and their surrounding areas: Bohemian Forest, Erzgebirge, and Giant Mountains. We found that vertical bias of SRTM and TanDEM-X, relative to the canopy height, is similar with negative values of up to −2.5 m and LE90s below 7.8 m in non-forest areas. In forests, the vertical bias of SRTM and TanDEM-X ranged from −0.5 to 4.1 m and LE90s from 7.2 to 11.0 m, respectively. The height differences between SRTM and TanDEM-X show moderate dependence on the slope and its orientation. LE90s for TDX-SRTM differences tended to be smaller for east-facing than for west-facing slopes, and varied, with aspect, by up to 1.5 m in non-forest areas and 3 m in forests, respectively. Finally, subtracting SRTM and NASA DEMs from TanDEM-X and Copernicus DEMs, respectively, successfully identified large areas of deforestation caused by hurricane Kyril in 2007 and a subsequent bark beetle disturbance in the Bohemian Forest. However, local errors in TanDEM-X, associated mainly with forest-covered west-facing slopes, resulted in erroneous identification of deforestation. Therefore, caution is needed when combining SRTM and TanDEM-X data in multitemporal studies in a mountain environment. Still, we can conclude that SRTM and TanDEM-X data represent suitable near global sources for the identification of deforestation in the period between the time points of their acquisition.
A Cross-Direction and Progressive Network for Pan-Sharpening
Authors: Xu Han , Le Zhuliang , Huang Jun , Ma Jiayi
Published: August 2021

In this paper, we propose a cross-direction and progressive network, termed CPNet, to solve the pan-sharpening problem. The full processing of information is the main characteristic of our model, which is reflected as follows: on the one hand, we process the source images in a cross-direction manner to obtain the source images of different scales as the input of the fusion modules at different stages, which maximizes the usage of multi-scale information in the source images; on the other hand, the progressive reconstruction loss is designed to boost the training of our network and avoid partial inactivation, while maintaining the consistency of the fused result with the ground truth. Since the extraction of the information from the source images and the reconstruction of the fused image is based on the entire image rather than a single type of information, there is little loss of partial spatial or spectral information due to insufficient information processing. Extensive experiments, including qualitative and quantitative comparisons demonstrate that our model can maintain more spatial and spectral information compared to the state-of-the-art pan-sharpening methods.
A Robust SAR Speckle Tracking Workflow for Measuring and Interpreting the 3D Surface Displacement of Landslides
Authors: Donati Davide , Rabus Bernhard , Engelbrecht Jeanine , Stead Doug , Clague John , Francioni Mirko
Published: August 2021

We present a workflow for investigating large, slow-moving landslides which combines the synthetic aperture radar (SAR) technique, GIS post-processing, and airborne laser scanning (ALS), and apply it to Fels landslide in Alaska, US. First, we exploit a speckle tracking (ST) approach to derive the easting, northing, and vertical components of the displacement vectors across the rock slope for two five-year windows, 2010–2015 and 2015–2020. Then, we perform post-processing in a GIS environment to derive displacement magnitude, trend, and plunge maps of the landslide area. Finally, we compare the ST-derived displacement data with structural lineament maps and profiles extracted from the ALS dataset. Relying on remotely sensed data, we estimate that the thickness of the slide mass is more than 100 m and displacements occur through a combination of slumping at the toe and planar sliding in the central and upper slope. Our approach provides information and interpretations that can assist in optimizing and planning fieldwork activities and site investigations at landslides in remote locations.
Study of the Spatiotemporal Characteristics of the Equatorial Ionization Anomaly Using Shipborne Multi-GNSS Data: A Case Analysis (120–150°E, Western Pacific Ocean, 2014–2015)
Authors: Luo Xiaowen , Wang Di , Wang Jinling , Wu Ziyin , Gao Jinyao , Zhang Tao , Yang Chunguo , Qin Xiaoming , Chen Xiaolun
Published: August 2021

Ground-based GNSS (Global Navigation Satellite System) reference stations lack the capacity to provide data for ocean regions with sufficient spatial-temporal resolution, limiting the detailed study of the equatorial ionization anomaly (EIA). Thus, this study collected kinematic multi-GNSS data on the ionospheric Total Electron Content (TEC) during two research cruises across the equator in the Western Pacific Ocean in 2014 (31 October–8 November) and 2015 (29 March–6 April). The purpose of the study was to use sufficient spatial–temporal resolution data to conduct a detailed analysis of the diurnal variation of the equatorial ionization anomaly in different seasons. The two-year data collected were used to draw the following conclusions. During the test in 2014, the EIA phenomenon in the Northern and Southern Hemispheres was relatively obvious. The maximum values occurred at local time (LT) 15:00 (~136TECu) and LT22:00 (~107TECu) in the Northern Hemisphere and at LT14:00 (100TECu) and LT22:00 (80TECu) in the Southern Hemisphere. During the test in 2015, the EIA in the Southern Hemisphere reached its maximum level at LT14:00 (~115TECu) and LT20:00 (~85TECu). However, the EIA phenomenon in the Northern Hemisphere was weakened, and a maximum value occurred only at LT 15:00 (~85TECu). The intensity contrast was reversed. The EIA phenomenon manifests a strong hemisphere asymmetry in this region.
LEO Constellation-Augmented Multi-GNSS for 3D Water Vapor Tomography
Authors: Xiong Si , Ma Fujian , Ren Xiaodong , Chen Jun , Zhang Xiaohong
Published: August 2021

Global navigation satellite systems (GNSS) water vapor tomography is an important technique to obtain the three-dimensional distribution of atmospheric water vapor. The rapid development of low Earth orbit (LEO) constellations has led to a richer set of observations, which brings new expectations for water vapor tomography. This paper analyzes the influence of LEO constellation-augmented multi-GNSS(LCAMG)on the tomography, in terms of ray distribution, tomography accuracy, and horizontal resolution, by simulating LEO constellation data. The results show that after adding 288 LEO satellites to GNSS, the 30-min ray distribution effect of GNSS can be achieved in 10 min, which can effectively shorten the observation time by 66.7%. In the 10-min observation time, the non-repetitive effective observation value of LCAMG is 2.38 times that of GNSS, and the accuracy is 1.27% higher than that of GNSS. Compared with GNSS and the global positioning system (GPS), at a horizontal resolution of 13 × 14, the proportion of empty voxels in LCAMG reduces by 5.22% and 22.53%, respectively.
Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery
Authors: Valerio Aline de M. , Kampel Milton , Vantrepotte Vincent , Ward Nicholas D. , Richey Jeffrey E.
Published: August 2021

Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The k-means classification was applied to the in situ normalized reflectance spectra (rn(λ)), allowing the identification of four OWTs. An optical index method was also applied to the rn(λ) defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (aCDOM) and particulate matter (ap), chlorophyll-a and suspended particulate matter (SPM) concentrations, and aCDOM/ap ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of ap to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region.
Error Characteristics and Scale Dependence of Current Satellite Precipitation Estimates Products in Hydrological Modeling
Authors: Zhang Yuhang , Ye Aizhong , Nguyen Phu , Analui Bita , Sorooshian Soroosh , Hsu Kuolin
Published: August 2021

Satellite precipitation estimates (SPEs) are promising alternatives to gauge observations for hydrological applications (e.g., streamflow simulation), especially in remote areas with sparse observation networks. However, the existing SPEs products are still biased due to imperfections in retrieval algorithms, data sources and post-processing, which makes the effective use of SPEs a challenge, especially at different spatial and temporal scales. In this study, we used a distributed hydrological model to evaluate the simulated discharge from eight quasi-global SPEs at different spatial scales and explored their potential scale effects of SPEs on a cascade of basins ranging from approximately 100 to 130,000 km2. The results indicate that, regardless of the difference in the accuracy of various SPEs, there is indeed a scale effect in their application in discharge simulation. Specifically, when the catchment area is larger than 20,000 km2, the overall performance of discharge simulation emerges an ascending trend with the increase of catchment area due to the river routing and spatial averaging. Whereas below 20,000 km2, the discharge simulation capability of the SPEs is more randomized and relies heavily on local precipitation accuracy. Our study also highlights the need to evaluate SPEs or other precipitation products (e.g., merge product or reanalysis data) not only at the limited station scale, but also at a finer scale depending on the practical application requirements. Here we have verified that the existing SPEs are scale-dependent in hydrological simulation, and they are not enough to be directly used in very fine scale distributed hydrological simulations (e.g., flash flood). More advanced retrieval algorithms, data sources and bias correction methods are needed to further improve the overall quality of SPEs.
Understanding the Influence of Building Loads on Surface Settlement: A Case Study in the Central Business District of Beijing Combining Multi-Source Data
Authors: Li Fengkai , Gong Huili , Chen Beibei , Gao Mingliang , Zhou Chaofan , Guo Lin
Published: August 2021

In metropolitan areas, the static load of high-rise buildings may result in uneven settlement, which seriously threatens residents’ living safety. Studying the response relationship between the additional stress of high-rise buildings and foundation settlement plays an important role in ensuring the safe development of metropolitan cities. Firstly, based on Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology, we used 68 descending TerraSAR-X images to obtain the surface settlement in the study area from April 2010 to October 2018, which were validated with leveling benchmark monitoring results. Secondly, we calculated the additional stress of the building loads to quantify its effect on the uneven settlement in the Central Business District (CBD) of Beijing. Finally, two sets of characteristic points were selected to analyze the response relationships between foundation settlement and additional stress generated by building loads. The findings show: (1) The surface settlement rate varied from −145.2 to 24 mm/year in the Beijing Plain. The InSAR results agree well with the monitoring results derived from the leveling benchmark; the Pearson correlation coefficients were 0.98 and 0.95 in 2011–2013 and 2015–2016, respectively. (2) The stress results show that the depth of the influence of the static load of high-rise buildings was 74.9 m underground in the CBD. (3) The spatial distribution pattern of the additional stress is consistent with the foundation settlement. A characteristic point with greater additional stress in the same group has a higher foundation settlement rate. This relationship has also been found between the uneven foundation settlement and additional stress gradients. These findings provide scientific support for mitigating economic losses due to foundation settlement caused by additional stresses derived from building loads.
A Method of Increasing the Accuracy of Radar Distance Measurement in VTS Systems for Vessels with Very Large Dimensions
Authors: Czaplewski Krzysztof , Świerczyński Sławomir
Published: August 2021

The navigation information about a vessel’s position in the waters covered by the vessel traffic system operation is obtained through supervisory services, mainly from coastal navigation radars. Although today it is possible to simultaneously acquire data from many independent radars, the obtained radar image is inconsistent and consists of several echoes next to each other. This makes it difficult to establish which echo represents the monitored unit. Another problem is the method of determining radar distances, which significantly affect the quality of determining the observation position. Errors in radar distance may occur when determining the radar echoes from large vessels, where the position of the unit is not the same as the edge of the radar echo to which the observation is made. In this article, the authors present a method of improving the measured radar distance. The presented proposal was verified in navigation and maneuvering simulation conditions. It could support the process of determining the ship position in vessel traffic service (VTS) systems with increased accuracy.
Forecasting of Typhoon-Induced Wind-Wave by Using Convolutional Deep Learning on Fused Data of Remote Sensing and Ground Measurements
Authors: Wei Chih-Chiang , Chang Hao-Chun
Published: August 2021

Taiwan is an island, and its economic activities are primarily dependent on maritime transport and international trade. However, Taiwan is also located in the region of typhoon development in the Northwestern Pacific Basin. Thus, it frequently receives strong winds and large waves brought by typhoons, which pose a considerable threat to port operations. To determine the real-time status of winds and waves brought by typhoons near the coasts of major ports in Taiwan, this study developed models for predicting the wind speed and wave height near the coasts of ports during typhoon periods. The forecasting horizons range from 1 to 6 h. In this study, the gated recurrent unit (GRU) neural networks and convolutional neural networks (CNNs) were combined and adopted to formulate the typhoon-induced wind and wave height prediction models. This work designed two wind speed prediction models (WIND-1 and WIND-2) and four wave height prediction models (WAVE-1 to WAVE-4), which are based on the WIND-1 and WIND-2 model outcomes. The Longdong and Liuqiu Buoys were the experiment locations. The observatory data from the ground stations and buoys, as well as radar reflectivity images, were adopted. The results indicated that, first, WIND-2 has a superior wind speed prediction performance to WIND-1, where WIND-2 can be used to identify the temporal and spatial changes in wind speeds using ground station data and reflectivity images. Second, WAVE-4 has the optimal wave height prediction performance, followed by WAVE-3, WAVE-2, and WAVE-1. The results of WAVE-4 revealed using the designed models with in-situ and reflectivity data directly yielded optimal predictions of the wind-based wave heights. Overall, the results indicated that the presented combination models were able to extract the spatial image features using multiple convolutional and pooling layers and provide useful information from time-series data using the GRU memory cell units. Overall, the presented models could exhibit promising results.
A Deep-Learning Based Posture Detection System for Preventing Telework-Related Musculoskeletal Disorders
Authors: Piñero-Fuentes Enrique , Canas-Moreno Salvador , Rios-Navarro Antonio , Domínguez-Morales Manuel , Sevillano José Luis , Linares-Barranco Alejandro
Published: August 2021

The change from face-to-face work to teleworking caused by the pandemic has induced multiple workers to spend more time than usual in front of a computer; in addition, the sudden installation of workstations in homes means that not all of them meet the necessary characteristics for the worker to be able to position himself/herself comfortably with the correct posture in front of their computer. Furthermore, from the point of view of the medical personnel in charge of occupational risk prevention, an automated tool able to quantify the degree of incorrectness of a postural habit in a worker is needed. For this purpose, in this work, a system based on the postural detection of the worker is designed, implemented and tested, using a specialized hardware system that processes video in real time through convolutional neural networks. This system is capable of detecting the posture of the neck, shoulders and arms, providing recommendations to the worker in order to prevent possible health problems, due to poor posture. The results of the proposed system show that this video processing can be carried out in real time (up to 25 processed frames/sec) with a low power consumption (less than 10 watts) using specialized hardware, obtaining an accuracy of over 80% in terms of the pattern detected.
The Information Geometry of Sensor Configuration
Authors: Williams Simon , Suvorov Arthur George , Wang Zengfu , Moran Bill
Published: August 2021

In problems of parameter estimation from sensor data, the Fisher information provides a measure of the performance of the sensor; effectively, in an infinitesimal sense, how much information about the parameters can be obtained from the measurements. From the geometric viewpoint, it is a Riemannian metric on the manifold of parameters of the observed system. In this paper, we consider the case of parameterized sensors and answer the question, “How best to reconfigure a sensor (vary the parameters of the sensor) to optimize the information collected?” A change in the sensor parameters results in a corresponding change to the metric. We show that the change in information due to reconfiguration exactly corresponds to the natural metric on the infinite-dimensional space of Riemannian metrics on the parameter manifold, restricted to finite-dimensional sub-manifold determined by the sensor parameters. The distance measure on this configuration manifold is shown to provide optimal, dynamic sensor reconfiguration based on an information criterion. Geodesics on the configuration manifold are shown to optimize the information gain but only if the change is made at a certain rate. An example of configuring two bearings-only sensors to optimally locate a target is developed in detail to illustrate the mathematical machinery, with Fast Marching methods employed to efficiently calculate the geodesics and illustrate the practicality of using this approach.
A Fast Firefly Algorithm for Function Optimization: Application to the Control of BLDC Motor
Authors: Bazi Smail , Benzid Redha , Bazi Yakoub , Rahhal Mohamd Mahmoud Al
Published: August 2021

Firefly Algorithm (FA) is a recent swarm intelligence first introduced by X.S. Yang in 2008. It has been widely used to solve several optimization problems. Since then, many research works were elaborated presenting modified versions intending to improve performances of the standard one. Consequently, this article aims to present an accelerated variant compared to the original Algorithm. Through the resolving of some benchmark functions to reach optimal solution, obtained results demonstrate the superiority of the suggested alternative, so-called Fast Firefly Algorithm (FFA), when faced with those of the standard FA in term of convergence fastness to the global solution according to an almost similar precision. Additionally, a successful application for the control of a brushless direct current electric motor (BLDC) motor by optimization of the Proportional Integral (PI) regulator parameters is given. These parameters are optimized by the FFA, FA, GA, PSO and ABC algorithms using the IAE, ISE, ITAE and ISTE performance criteria.
Daily Human Activity Recognition Using Non-Intrusive Sensors
Authors: Ramos Raúl Gómez , Domingo Jaime Duque , Zalama Eduardo , Gómez-García-Bermejo Jaime
Published: August 2021

In recent years, Artificial Intelligence Technologies (AIT) have been developed to improve the quality of life of the elderly and their safety in the home. This work focuses on developing a system capable of recognising the most usual activities in the daily life of an elderly person in real-time to enable a specialist to monitor the habits of this person, such as taking medication or eating the correct meals of the day. To this end, a prediction model has been developed based on recurrent neural networks, specifically on bidirectional LSTM networks, to obtain in real-time the activity being carried out by the individuals in their homes, based on the information provided by a set of different sensors installed at each person’s home. The prediction model developed in this paper provides a 95.42% accuracy rate, improving the results of similar models currently in use. In order to obtain a reliable model with a high accuracy rate, a series of processing and filtering processes have been carried out on the data, such as a method based on a sliding window or a stacking and re-ordering algorithm, that are subsequently used to train the neural network, obtained from the public database CASAS.
EEMD and Multiscale PCA-Based Signal Denoising Method and Its Application to Seismic P-Phase Arrival Picking
Authors: Peng Kang , Guo Hongyang , Shang Xueyi
Published: August 2021

Signal denoising is one of the most important issues in signal processing, and various techniques have been proposed to address this issue. A combined method involving wavelet decomposition and multiscale principal component analysis (MSPCA) has been proposed and exhibits a strong signal denoising performance. This technique takes advantage of several signals that have similar noises to conduct denoising; however, noises are usually quite different between signals, and wavelet decomposition has limited adaptive decomposition abilities for complex signals. To address this issue, we propose a signal denoising method based on ensemble empirical mode decomposition (EEMD) and MSPCA. The proposed method can conduct MSPCA-based denoising for a single signal compared with the former MSPCA-based denoising methods. The main steps of the proposed denoising method are as follows: First, EEMD is used for adaptive decomposition of a signal, and the variance contribution rate is selected to remove components with high-frequency noises. Subsequently, the Hankel matrix is constructed on each component to obtain a higher order matrix, and the main score and load vectors of the PCA are adopted to denoise the Hankel matrix. Next, the PCA-denoised component is denoised using soft thresholding. Finally, the stacking of PCA- and soft thresholding-denoised components is treated as the final denoised signal. Synthetic tests demonstrate that the EEMD-MSPCA-based method can provide good signal denoising results and is superior to the low-pass filter, wavelet reconstruction, EEMD reconstruction, Hankel–SVD, EEMD-Hankel–SVD, and wavelet-MSPCA-based denoising methods. Moreover, the proposed method in combination with the AIC picking method shows good prospects for processing microseismic waves.