bluuebunny/crossref_metadata_2025 huggingface dataset:
Gut Microbiome in Children from Indigenous and Urban Communities in México: Different Subsistence Models, Different Microbiomes
Authors: Sánchez-Quinto Andrés , Cerqueda-García Daniel , Falcón Luisa I. , Gaona Osiris , Martínez-Correa Santiago , Nieto Javier , G-Santoyo Isaac
Published: October 2020

The human gut microbiome is an important component that defines host health. Childhood is a particularly important period for the establishment and development of gut microbiota (GM). We sequenced the 16S rRNA gene from fecal samples of children between 5 and 10 years old, in two Mexican communities with contrasting lifestyles, i.e., “Westernized” (México City, n = 13) and “non-Westernized” (Me’phaa indigenous group, n = 29), in order to characterize and compare their GM. The main differences between these two communities were in bacteria associated with different types of diets (high animal protein and refined sugars vs. high fiber food, respectively). In addition, the GM of Me’phaa children showed higher total diversity and the presence of exclusive phyla, such as Deinococcus-Thermus, Chloroflexi, Elusimicrobia, Acidobacteria, and Fibrobacteres. In contrast, the children from México City showed less diversity and the presence of Saccharibacteria phylum, which was associated with the degradation of sugar compounds and was not present in the samples from Me’phaa children. This comparison provided further knowledge of the selective pressures affecting microbial ecosystemic composition over the course of human evolution and the potential consequences of pathophysiological states correlated with Westernization lifestyles.
First Detection of GES-5-Producing Escherichia coli from Livestock—An Increasing Diversity of Carbapenemases Recognized from German Pig Production
Authors: Irrgang Alexandra , Tausch Simon H. , Pauly Natalie , Grobbel Mirjam , Kaesbohrer Annemarie , Hammerl Jens A.
Published: October 2020

Resistance to carbapenems due to carbapenemase-producing Enterobacteriaceae (CPE) is an increasing threat to human health worldwide. In recent years, CPE could be found only sporadically from livestock, but concern rose that livestock might become a reservoir for CPE. In 2019, the first GES carbapenemase-producing Escherichia coli from livestock was detected within the German national monitoring on antimicrobial resistance. The isolate was obtained from pig feces and was phenotypically resistant to meropenem and ertapenem. The isolate harbored three successive blaGES genes encoding for GES-1, GES-5 and GES-5B in an incomplete class-I integron on a 12 kb plasmid (pEC19-AB02908; Acc. No. MT955355). The strain further encoded for virulence-associated genes typical for uropathogenic E. coli, which might hint at an increased pathogenic potential. The isolate produced the third carbapenemase detected from German livestock. The finding underlines the importance CPE monitoring and detailed characterization of new isolates.
American Crows as Carriers of Extra Intestinal Pathogenic E. coli and Avian Pathogenic-Like E. coli and Their Potential Impact on a Constructed Wetland
Authors: Sen Keya , Shepherd Vaughn , Berglund Tanner , Quintana Alexa , Puim Shnia , Tadmori Rama , J. Turner Robert , Khalil Laura , Soares Marilia A.
Published: October 2020

The study examines whether crows are carriers of extraintestinal pathogenic E. coli (ExPEC) and avian pathogenic E. coli (APEC)-like strains, and if wetland roost areas contribute to their spread. A total of 10 crow feces (n = 71) and 15 water E. coli isolates (n = 134) from a wetland area could be characterized as potentially ExPEC based on the presence of ≥2 of the five cardinal genes iutA, kpsMT2, papEF, pap A/C, papG, sfa/foc, and afa/dra, while six fecal and 14 water isolates could be characterized as potentially APEC-like based on the presence of plasmid associated genes: iutA, episomal iss, ompT, hlyF and iroN. A total of 32 fecal and 27 water isolates tested carried plasmids based on incompatibility typing. Plasmids from 34 of 38 isolates tested could be transferred to another E. coli strain by conjugation with the antibiotic resistance (AR) profile being transferred, indicating their potential to be transferred to indigenous and non-pathogenic strains in the wetland. APEC-like plasmids could be transferred in six of eight isolates tested. Pathogenic E. coli of importance to the medical community and poultry industry may be detected in high levels in surface water due to corvid activity. Regardless of their role in health or disease, water in wetlands and streams can serve as a media for the dissemination of AR and virulence traits of bacteria, with corvids acting as potential vectors for farther dissemination.
Isolation and Identification of Potentially Pathogenic Microorganisms Associated with Dental Caries in Human Teeth Biofilms
Authors: Chen Xiuqin , Daliri Eric Banan-Mwine , Chelliah Ramachandran , Oh Deog-Hwan
Published: October 2020

Dental caries is attributed to the predominance of cariogenic microorganisms. Cariogenic microorganisms are pathological factors leading to acidification of the oral microenvironment, which is related to the initiation and progression of caries. The accepted cariogenic microorganism is Streptococcus mutans (S. mutans). However, studies have found that caries could occur in the absence of S. mutans. This study aimed to assess the presence of potentially cariogenic microorganisms in human teeth biofilm. The microorganisms were isolated from human mouth and freshly extracted human maxillary incisors extracted for reasons of caries. The isolates were sorted based on their acidogenic and aciduric properties, and the S. mutans was used as the reference strain. Four potentially cariogenic strains were selected. The selected strains were identified as Streptococcus salivarius (S. salivarius), Streptococcus anginosus (S. anginosus), Leuconostoc mesenteroides (L. mesenteroides), and Lactobacillus sakei (L. sakei) through morphological analysis followed by 16S rRNA gene sequence analysis. The cariogenicity of isolates was analyzed. We show, for the first time, an association between L. sakei (present in fermented food) and dental caries. The data provide useful information on the role of lactic acid bacteria from fermented foods and oral commensal streptococci in dental caries.
Study on the Liberation of Organic Macerals in Coal by Liquid Nitrogen Quenching Pretreatment
Authors: Fan Jinwen , Du Meili , Liu Lei
Published: October 2020

In order to study the liberation characteristics of different macerals in coal, one must improve the liberation degree of macerals in coal and promote the utilization of macerals based on their properties. Based on the idea of quick cooling to change the brittleness and toughness of different macerals, the characteristics of macerals in coal are studied here by liquid nitrogen quenching pretreatment. In particular, coarse-grained samples (with a particle size of 1–3 mm) were. For this study, coal samples were sourced from the Yan’an Formation (J2y), a middle Jurassic coal formation in the Huangling no. 1 coal mine, located in northern Shaanxi Province, China. Firstly, we analyzed the coal properties and coal petrographic characteristics by the Chinese national standard method. Secondly, the distribution characteristics of macerals in different particle sizes (>0.9, 0.5–0.9, 0.1–0.5, and <0.1) were studied. Then, the samples with different particle sizes were quenched with or without liquid nitrogen to obtain the experimental group and blank group products. Finally, the differences in the liberation characteristics between the experimental group and the blank group products were studied via analyzing the micromorphology, specific surface area, pore volume, pore size and liberation degree. Our results for the particles size and liberation degree analysis indicate that inertinite and vitrinite were enriched in the coarse particles (>0.5 mm) and fine particles (<0.1 mm) here, respectively. Moreover, quenching pretreatment could contribute to the liberation of different macerals from coal, mainly because of the different effects of stress on the different components when they suddenly encounter cold, and this kind of liberation is mainly arc-shaped liberation between different macerals. In addition, along with the above results, this paper presents an optimized model for the liberation of macerals based on a combination of screening, liquid nitrogen quenching pretreatment and re-crushing.
Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data
Authors: Papadiamantis Anastasios G. , Klaessig Frederick C. , Exner Thomas E. , Hofer Sabine , Hofstaetter Norbert , Himly Martin , Williams Marc A. , Doganis Philip , Hoover Mark D. , Afantitis Antreas , Melagraki Georgia , Nolan Tracy S. , Rumble John , Maier Dieter , Lynch Iseult
Published: October 2020

The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it. Here, we demonstrate, using specific worked case studies, how to organise the nano-community efforts to define metadata schemas, by organising the data management cycle as a joint effort of all players (data creators, analysts, curators, managers, and customers) supervised by the newly defined role of data shepherd. We propose that once researchers understand their tasks and responsibilities, they will naturally apply the available tools. Two case studies are presented (modelling of particle agglomeration for dose metrics, and consensus for NM dissolution), along with a survey of the currently implemented metadata schema in existing nanosafety databases. We conclude by offering recommendations on the steps forward and the needed workflows for metadata capture to ensure FAIR nanosafety data.
Tunable Electronic Properties of Type-II SiS2/WSe2 Hetero-Bilayers
Authors: Guan Yue , Li Xiaodan , Niu Ruixia , Zhang Ningxia , Hu Taotao , Zhang Liyao
Published: October 2020

First-principle calculations based on the density functional theory (DFT) are implemented to study the structural and electronic properties of the SiS2/WSe2 hetero-bilayers. It is found that the AB-2 stacking model is most stable among all the six SiS2/WSe2 heterostructures considered in this work. The AB-2 stacking SiS2/WSe2 hetero-bilayer possesses a type-II band alignment with a narrow indirect band gap (0.154 eV and 0.738 eV obtained by GGA-PBE and HSE06, respectively), which can effectively separate the photogenerated electron–hole pairs and prevent the recombination of the electron–hole pairs. Our results revealed that the band gap can be tuned effectively within the range of elastic deformation (biaxial strain range from −7% to 7%) while maintaining the type-II band alignment. Furthermore, due to the effective regulation of interlayer charge transfer, the band gap along with the band offset of the SiS2/WSe2 heterostructure can also be modulated effectively by applying a vertical external electric field. Our results offer interesting alternatives for the engineering of two-dimensional material-based optoelectronic nanodevices.
Precarity at the Margins of Malaria Control in the Chittagong Hill Tracts in Bangladesh: A Mixed-Methods Study
Authors: Matin Mohammad Abdul , Sarkar Nandini D. P. , Phru Ching Swe , Ley Benedikt , Thriemer Kamala , Price Ric N. , Peeters Grietens Koen , Ali Khan Wasif , Alam Mohammad Shafiul , Gryseels Charlotte
Published: October 2020

Bangladesh has achieved significant progress towards malaria elimination, although health service delivery for malaria remains challenging in remote forested areas such as the Chittagong Hill Tracts (CHT). The aim of this study was to investigate perceptions of malaria and its treatment among the local population to inform contextualized strategies for rolling out radical cure for P. vivax in Bangladesh. The study comprised two sequential strands whereby the preliminary results of a qualitative strand informed the development of a structured survey questionnaire used in the quantitative strand. Results show that ethnic minority populations in the CHT live in precarious socio-economic conditions which increase their exposure to infectious diseases, and that febrile patients often self-treat, including home remedies and pharmaceuticals, before attending a healthcare facility. Perceived low quality of care and lack of communication between Bengali health providers and ethnic minority patients also affects access to public healthcare. Malaria is viewed as a condition that affects vulnerable people weakened by agricultural work and taking away blood is perceived to increase such vulnerability. Healthcare providers that initiate and sustain a dialogue about these issues with ethnic minority patients may foster the trust that is needed for local malaria elimination efforts.
Diverse Epidemiology of Leptospira Serovars Notified in New Zealand, 1999–2017
Authors: Nisa Shahista , Wilkinson David , Angelin-Bonnet Olivia , Paine Shevaun , Cullen Karen , Wright Jackie , Baker Michael , Benschop Jackie
Published: October 2020

Leptospirosis in New Zealand has been strongly associated with animal-contact occupations and with serovars Hardjo and Pomona. However, recent data suggest changes in these patterns, hence, serovar-specific epidemiology of leptospirosis from 1999 to 2017 was investigated. The 19-year average annual incidence is 2.01/100,000. Early (1999–2007) and late (2008–2017) study period comparisons showed a significant increase in notifications with serovar Ballum (IRR: 1.59, 95% CI: 1.22–2.09) in all cases and serovar Tarassovi (IRR: 1.75, 95% CI: 1.13–2.78) in Europeans and a decrease in notifications with serovars Hardjo and Pomona in all cases. Incidences of Ballum peaked in winter, Hardjo peaked in spring and Tarassovi peaked in summer. Incidence was highest in Māori (2.24/100,000) with dominant serovars being Hardjo and Pomona. Stratification by occupation showed meat workers had the highest incidence of Hardjo (57.29/100,000) and Pomona (45.32/100,000), farmers had the highest incidence of Ballum (11.09/100,000) and dairy farmers had the highest incidence of Tarassovi (12.59/100,000). Spatial analysis showed predominance of Hardjo and Pomona in Hawke’s Bay, Ballum in West Coast and Northland and Tarassovi in Waikato, Taranaki and Northland. This study highlights the serovar-specific heterogeneity of human leptospirosis in New Zealand that should be considered when developing control and prevention strategies.
Establishment of an In Vitro Model of Persistent Chicken Anemia Virus Infection
Authors: Van Dong Hieu , Tran Giang Thi Huong , Trinh Dai Quang , Takeda Yohei , Ogawa Haruko , Imai Kunitoshi
Published: October 2020

Persistent infection of chicken anemia virus (CAV) in chickens has been suspected to result in immunosuppression and exogenous virus contamination within vaccine production. However, no direct evidence for persistent CAV infection has thus far been obtained. In this study, we aimed to establish an in vitro model of persistent CAV infection. CAV-infected MDCC-MSB1 (MSB1) cells, a Marek’s disease virus-transformed continuous cell line, were cultured in the presence of both CAV and CAV neutralizing antibody (NA). Cell viability, expression of viral antigens, viral DNA, and recovery of CAV were examined by acridine orange/propidium iodide staining, immunofluorescence measurement, real-time PCR, and viral isolation, respectively. The results indicated that CAV was maintained and possibly replicated in CAV-infected cells cultured in the presence of NA, without affecting host cell viability. It was also shown that persistently infectious CAV induced cell death again after removing NA. The persistent infection of CAV in MSB1 cells was not related to viral gene mutation. In summary, we have herein established a novel model of persistent CAV infection in MSB1 cells cultured in the presence of NA.
Sepsis, Phages, and COVID-19
Authors: Górski Andrzej , Borysowski Jan , Międzybrodzki Ryszard
Published: October 2020

Phage therapy has emerged as a potential novel treatment of sepsis for which no decisive progress has been achieved thus far. Obviously, phages can help eradicate local bacterial infection and bacteremia that may occur in a syndrome. For example, phages may be helpful in correcting excessive inflammatory responses and aberrant immunity that occur in sepsis. Data from animal studies strongly suggest that phages may indeed be an efficient means of therapy for experimentally induced sepsis. In recent years, a number of reports have appeared describing the successful treatment of patients with sepsis. Moreover, novel data on the anti-viral potential of phages may be interpreted as suggesting that phages could be used as an adjunct therapy in severe COVID-19. Thus, clinical trials assessing the value of phage therapy in sepsis, including viral sepsis, are urgently needed.
Expression of Hypoxia-Inducible Factors in Different Stages of Pancreatic Tumor Progression
Authors: Jung Jung Hwa , Sosnowska Danuta , Weaver Jessica , Parson Henri K. , Casellini Carolina M. , Vinik Aaron I.
Published: October 2020

Background: Early diagnosis in pancreatic cancer is key for improving prognosis. Hypoxia plays a critical role in tumor progression. Thus, an evaluation of associations between pancreatic tumor progression and markers of hypoxia is needed. Methods: We assessed the expression of hypoxia-inducible factors (HIF-1α and HIF-2α) by immuno-histochemical staining from 29 subjects with the following: pancreatic intraepithelial neoplasia (PanIN), intraductal papillary mucinous neoplasm (IPMN), neuroendocrine tumor (NET), and pancreatic ductal adenocarcinoma (PDAC) and compared it to the expression in non-tumor samples. Results: Expression of HIF-1α increased significantly from PanIN (3.01 ± 0.17) to IPMN (7.63 ± 0.18), NET (9.10 ± 0.23) and PDAC samples (11.06 ± 0.15, p < 0.0001). Similar findings were observed for HIF-2α (p < 0.0001)}. A strong correlation between HIF-1α and HIF-2α expression was demonstrated (R2 = 0.8408, p < 0.0001). Conclusions: This data suggest that HIF-1α and HIF-2α may play a role in the progression from PanIN through PDAC. Further studies are necessary to confirm these findings and determine the effect of HIFs abrogation on tumor progression that can lead to novel therapies.
Improved Method to Suppress Azimuth Ambiguity for Current Velocity Measurement in Coastal Waters Based on ATI-SAR Systems
Authors: Yi Na , He Yijun , Liu Baochang
Published: October 2020

Measurements of ocean surface currents in coastal waters are crucial for improving our understanding of tidal atlases, as well as for ecosystem and water pollution monitoring. This paper proposes an improved method for estimating the baseline-to-platform speed ratio (BPSR) for improving the current line-of-sight (LOS) velocity measurement accuracy in coastal waters with along-track interferometric synthetic aperture radar (ATI-SAR) based on eigenvalue spectrum entropy (EVSE) analysis. The estimation of BPSR utilizes the spaceborne along-track interferometry and considers the effects of a satellite orbit and an inaccurate baseline responsible for azimuth ambiguity in coastal waters. Unlike the existing methods, which often assume idealized rather than actual operating environments, the proposed approach considers the accuracy of BPSR, which is its key advantage applicable to many, even poorly designed, ATI-SAR systems. This is achieved through an alternate algorithm for the suppression of azimuth ambiguity and BPSR estimation based on an improved analysis of the eigenvalue spectrum entropy, which is an important parameter representing the mixability of unambiguous and ambiguous signals. The improvements include the consideration of a measurement of the heterogeneity of the scene, the corrections of coherence-inferred phase fluctuation (CPF), and the interferogram-derived phase variability (IPV); the last two variables are closely related to the determination of the EVSE threshold. Besides, the BPSR estimation also represents an improvement that has not been achieved in previous work of EVSE analysis. When the improved method is used on the simulated ocean-surface current LOS velocity data obtained from a coastal area, the root-mean-square error is less than 0.05 m/s. The other strengths of the proposed algorithm are adaptability, robustness, and a limited user input requirement. Most importantly, the method can be adopted for practical applications.
Magnetospheric–Ionospheric–Lithospheric Coupling Model. 1: Observations during the 5 August 2018 Bayan Earthquake
Authors: Piersanti Mirko , Materassi Massimo , Battiston Roberto , Carbone Vincenzo , Cicone Antonio , D’Angelo Giulia , Diego Piero , Ubertini Pietro
Published: October 2020

The short-term prediction of earthquakes is an essential issue connected with human life protection and related social and economic matters. Recent papers have provided some evidence of the link between the lithosphere, lower atmosphere, and ionosphere, even though with marginal statistical evidence. The basic coupling is hypothesized as being via the atmospheric gravity wave (AGW)/acoustic wave (AW) channel. In this paper we analyze a scenario of the low latitude earthquake (Mw = 6.9) which occurred in Indonesia on 5 August 2018, through a multi-instrumental approach, using ground and satellites high quality data. As a result, we derive a new analytical lithospheric–atmospheric–ionospheric–magnetospheric coupling model with the aim to provide quantitative indicators to interpret the observations around 6 h before and at the moment of the earthquake occurrence.
Estimating Terrain Slope from ICESat-2 Data in Forest Environments
Authors: Zhu Xiaoxiao , Nie Sheng , Wang Cheng , Xi Xiaohuan , Li Dong , Li Guoyuan , Wang Pu , Cao Di , Yang Xuebo
Published: October 2020

The global digital elevation measurement (DEM) products such as SRTM DEM and GDEM have been widely used for terrain slope retrieval in forests. However, the slope estimation accuracy is generally limited due to the DEMs’ low vertical accuracy over complex forest environments. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission shows excellent potential for slope estimation because of the high elevation accuracy and unique design of beam pairs. This study aimed to explore the possibility of ICESat-2 data for terrain slope retrieval in the United States forests. First, raw ICESat-2 data were processed to obtain accurate ground surfaces. Second, two different methods based on beam pairs were proposed to derive terrain slopes from the ground surfaces. Third, the estimated slopes were validated by airborne LiDAR-derived slopes and compared with SRTM-derived slopes and GDEM-derived slopes. Finally, we further explored the influence of surface topography and ground elevation error on slope estimation from ICESat-2 data. The results show that the ground surface can be accurately extracted from all scenarios of ICESat-2 data, even weak beams in the daytime, which provides the basis for terrain slope retrieval from ICESat-2 beam pairs. The estimated slope has a strong correlation with airborne LiDAR-derived slopes regardless of slope estimation methods, which demonstrates that the ICESat-2 data are appropriate for terrain slope estimation in complex forest environments. Compared with the method based on along- and across-track analysis (method 1), the method based on plane fitting of beam pairs (method 2) has a high estimation accuracy of terrain slopes, which indicates that method 2 is more suitable for slope estimation because it takes full advantage of more ground surface information. Additionally, the results also indicate that ICESat-2 performs much better than SRTM DEMs and GDEMs in estimating terrain slopes. Both ground elevation error and surface topography have a significant impact on terrain slope retrieval from ICESat-2 data, and ground surface extraction should be improved to ensure the accuracy of terrain slope retrieval over extremely complex environments. This study demonstrates for the first time that ICESat-2 has a strong capability in terrain slope retrieval. Additionally, this paper also provides effective solutions to accurately estimate terrain slopes from ICESat-2 data. The ICESat-2 slopes have many potential applications, including the generation of global slope products, the improvement of terrain slopes derived from the existing global DEM products, and the correction of vegetation biophysical parameters retrieved from space-borne LiDAR waveform data.
Potential and Limitations of Satellite Altimetry Constellations for Monitoring Surface Water Storage Changes—A Case Study in the Mississippi Basin
Authors: Dettmering Denise , Ellenbeck Laura , Scherer Daniel , Schwatke Christian , Niemann Christoph
Published: October 2020

Remote sensing data are essential for monitoring the Earth’s surface waters, especially since the amount of publicly available in-situ data is declining. Satellite altimetry provides valuable information on the water levels and variations of lakes, reservoirs and rivers. In combination with satellite imagery, the derived time series allow the monitoring of lake storage changes and river discharge. However, satellite altimetry is limited in terms of its spatial resolution due to its measurement geometry, only providing information in the nadir direction beneath the satellite’s orbit. In a case study in the Mississippi River Basin (MRB), this study investigates the potential and limitations of past and current satellite missions for the monitoring of basin-wide storage changes. For that purpose, an automated target detection is developed and the extracted lake surfaces are merged with the satellites’ tracks. This reveals that the current altimeter configuration misses about 80% of all lakes larger than 0.1 km2 in the MRB and 20% of lakes larger than 10 km2, corresponding to 30% and 7% of the total water area, respectively. Past altimetry configurations perform even more poorly. From the larger water bodies represented by a global hydrology model, at least 91% of targets and 98% of storage changes are captured by the current altimeter configuration. This will improve significantly with the launch of the planned Surface Water and Ocean Topography (SWOT) mission.
Application of UAV Imagery to Detect and Quantify Submerged Filamentous Algae and Rooted Macrophytes in a Non-Wadeable River
Authors: Kislik Chippie , Genzoli Laurel , Lyons Andy , Kelly Maggi
Published: October 2020

Imagery from unoccupied aerial vehicles (UAVs) is useful for mapping floating and emerged primary producers, as well as single taxa of submerged primary producers in shallow, clear lakes and streams. However, there is little research on the effectiveness of UAV imagery-based detection and quantification of submerged filamentous algae and rooted macrophytes in deeper rivers using a standard red-green-blue (RGB) camera. This study provides a novel application of UAV imagery analysis for monitoring a non-wadeable river, the Klamath River in northern California, USA. River depth and solar angle during flight were analyzed to understand their effects on benthic primary producer detection. A supervised, pixel-based Random Trees classifier was utilized as a detection mechanism to estimate the percent cover of submerged filamentous algae and rooted macrophytes from aerial photos within 32 sites along the river in June and July 2019. In-situ surveys conducted via wading and snorkeling were used to validate these data. Overall accuracy was 82% for all sites and the highest overall accuracy of classified UAV images was associated with solar angles between 47.5 and 58.72° (10:04 a.m. to 11:21 a.m.). Benthic algae were detected at depths of 1.9 m underwater and submerged macrophytes were detected down to 1.2 m (river depth) via the UAV imagery in this relatively clear river (Secchi depth > 2 m). Percent cover reached a maximum of 31% for rooted macrophytes and 39% for filamentous algae within all sites. Macrophytes dominated the upstream reaches, while filamentous algae dominated the downstream reaches closer to the Pacific Ocean. In upcoming years, four proposed dam removals are expected to alter the species composition and abundance of benthic filamentous algae and rooted macrophytes, and aerial imagery provides an effective method to monitor these changes.
RETRACTED: He et al. The Exploration of Urban Material Anabolism Based on RS and GIS Methods: Case Study in Jinchang, China. Remote Sens. 2020, 12, 370
Authors:   Remote Sensing Editorial Office
Published: October 2020

The Remote Sensing Editorial Office has been made aware that the published paper [...]
Improving Spatial Agreement in Machine Learning-Based Landslide Susceptibility Mapping
Authors: Adnan Mohammed Sarfaraz Gani , Rahman Md Salman , Ahmed Nahian , Ahmed Bayes , Rabbi Md. Fazleh , Rahman Rashedur M.
Published: October 2020

Despite yielding considerable degrees of accuracy in landslide predictions, the outcomes of different landslide susceptibility models are prone to spatial disagreement; and therefore, uncertainties. Uncertainties in the results of various landslide susceptibility models create challenges in selecting the most suitable method to manage this complex natural phenomenon. This study aimed to propose an approach to reduce uncertainties in landslide prediction, diagnosing spatial agreement in machine learning-based landslide susceptibility maps. It first developed landslide susceptibility maps of Cox’s Bazar district of Bangladesh, applying four machine learning algorithms: K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM), featuring hyperparameter optimization of 12 landslide conditioning factors. The results of all the four models yielded very high prediction accuracy, with the area under the curve (AUC) values range between 0.93 to 0.96. The assessment of spatial agreement of landslide predictions showed that the pixel-wise correlation coefficients of landslide probability between various models range from 0.69 to 0.85, indicating the uncertainty in predicted landslides by various models, despite their considerable prediction accuracy. The uncertainty was addressed by establishing a Logistic Regression (LR) model, incorporating the binary landslide inventory data as the dependent variable and the results of the four landslide susceptibility models as independent variables. The outcomes indicated that the RF model had the highest influence in predicting the observed landslide locations, followed by the MLP, SVM, and KNN models. Finally, a combined landslide susceptibility map was developed by integrating the results of the four machine learning-based landslide predictions. The combined map resulted in better spatial agreement (correlation coefficients range between 0.88 and 0.92) and greater prediction accuracy (0.97) compared to the individual models. The modelling approach followed in this study would be useful in minimizing uncertainties of various methods and improving landslide predictions.
Approaches of Satellite Remote Sensing for the Assessment of Above-Ground Biomass across Tropical Forests: Pan-tropical to National Scales
Authors: Abbas Sawaid , Wong Man Sing , Wu Jin , Shahzad Naeem , Muhammad Irteza Syed
Published: October 2020

Tropical forests are acknowledged for providing important ecosystem services and are renowned as “the lungs of the planet Earth” due to their role in the exchange of gasses—particularly inhaling CO2 and breathing out O2—within the atmosphere. Overall, the forests provide 50% of the total plant biomass of the Earth, which accounts for 450–650 PgC globally. Understanding and accurate estimates of tropical forest biomass stocks are imperative in ascertaining the contribution of the tropical forests in global carbon dynamics. This article provides a review of remote-sensing-based approaches for the assessment of above-ground biomass (AGB) across the tropical forests (global to national scales), summarizes the current estimate of pan-tropical AGB, and discusses major advancements in remote-sensing-based approaches for AGB mapping. The review is based on the journal papers, books and internet resources during the 1980s to 2020. Over the past 10 years, a myriad of research has been carried out to develop methods of estimating AGB by integrating different remote sensing datasets at varying spatial scales. Relationships of biomass with canopy height and other structural attributes have developed a new paradigm of pan-tropical or global AGB estimation from space-borne satellite remote sensing. Uncertainties in mapping tropical forest cover and/or forest cover change are related to spatial resolution; definition adapted for ‘forest’ classification; the frequency of available images; cloud covers; time steps used to map forest cover change and post-deforestation land cover land use (LCLU)-type mapping. The integration of products derived from recent Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LiDAR) satellite missions with conventional optical satellite images has strong potential to overcome most of these uncertainties for recent or future biomass estimates. However, it will remain a challenging task to map reference biomass stock in the 1980s and 1990s and consequently to accurately quantify the loss or gain in forest cover over the periods. Aside from these limitations, the estimation of biomass and carbon balance can be enhanced by taking account of post-deforestation forest recovery and LCLU type; land-use history; diversity of forest being recovered; variations in physical attributes of plants (e.g., tree height; diameter; and canopy spread); environmental constraints; abundance and mortalities of trees; and the age of secondary forests. New methods should consider peak carbon sink time while developing carbon sequestration models for intact or old-growth tropical forests as well as the carbon sequestration capacity of recovering forest with varying levels of floristic diversity.
Simulation of the Dynamic Water Storage and Its Gravitational Effect in the Head Region of Three Gorges Reservoir Using Imageries of Gaofen-1
Authors: Ma Xian , Wang Linsong , Chen Chao , Du Jinsong , Sun Shida
Published: October 2020

The construction of a high-resolution dynamic water storage model, driven by the mass load of the huge water storage of the Three Gorges Reservoir (TGR), is the necessary basic data for accurately simulating changes in the geophysical field, e.g., gravity, crustal deformation, and stress. However, previously established models cannot meet the needs of accurately simulating the impoundment effects of TGR, because these models were simplified and approximated and did not consider the variation of river boundaries caused by water level changes. In this study, we combined high-resolution Gaofen-1 (GF-1) satellite imageries and real-time water level in front of the dam and extracted 31 river boundaries of the head region of TGR between the lowest (145 m) and the highest (175 m) impoundment stages based on the Normalized Differential Water Index (NDWI) and threshold segmentation from Otsu method. Developed dynamic water storage model based on higher-resolution GF-1 data can show the true river boundary changes more exactly, especially in local areas. Compared to the previous approximate models, the model that we constructed accurately depicts the boundary distribution information of the different impoundment stages. Moreover, we simulated TGR-induced gravitational effects based on the high-precision forward modeling of the dynamic water storage model (i.e., considering changes of dynamic water area and water level). The theoretical modelled results are consistent with in situ gravity measurements with the difference mainly within 10 μGal. Our results indicate that water storage variations of TGR mainly affect the gravity field response within 1000 m of the reservoir bank with its maximum amplitude up to several hundred μGal. The dynamic water storage and its simulation results of gravitational effects can effectively eliminate the impact of surface water load driven by the TGR under human control and greatly improve the signal-to-noise ratio of regional gravity observational data. Thus, this work will be beneficial in the application of geophysical and geodetic monitoring aimed to comprehensively track the local and regional geological structural stability, e.g., artificial reservoir induced earthquake and landslide.
A Refinement Method of Real-Time Ionospheric Model for China
Authors: Wang Yang , Yao Yibin , Zhang Liang , Fang Mingshan
Published: October 2020

Ionospheric delay is a crucial error source and determines the source of single-frequency precise point positioning (SF-PPP) accuracy. To meet the demands of real-time SF-PPP (RT-SF-PPP), several international global navigation satellite systems (GNSS) service (IGS) analysis centers provide real-time global ionospheric vertical total electron content (VTEC) products. However, the accuracy distribution of VTEC products is nonuniform. Proposing a refinement method is a convenient means to obtain a more accuracy and consistent VTEC product. In this study, we proposed a refinement method of a real-time ionospheric VTEC model for China and carried out experiments to validate the model effectiveness. First, based on the refinement method and the Centre National d’Études Spatiales (CNES) VTEC products, three refined real-time global ionospheric models (RRTGIMs) with one, three, and six stations in China were built via GNSS observations. Second, the slant total electron content (STEC) and Jason-3 VTEC were used as references to evaluate VTEC accuracy. Third, RT-SF-PPP was used to evaluate the accuracy in the positioning domain. Results showed that even if using only one station to refine the global ionospheric model, the refined model achieved a better performance than CNES and the Center for Orbit Determination in Europe (CODE). The refinement model with six stations was found to be the best of the three refinement models.
Performance Analysis of the Korean Positioning System Using Observation Simulation
Authors: Choi Byung-Kyu , Roh Kyoung-Min , Ge Haibo , Ge Maorong , Joo Jung-Min , Heo Moon Beom
Published: October 2020

The Korean government has a plan to build a new regional satellite navigation system called the Korean Positioning System (KPS). The initial KPS constellation is designed to consist of seven satellites, which include three geostationary Earth orbit (GEO) satellites and four inclined geosynchronous orbit (IGSO) satellites. KPS will provide an independent positioning, navigation, and timing (PNT) service in the Asia-Oceania region and can also be compatible with GPS. In the simulation for KPS, we employ 24 GPS as designed initially and 7 KPS satellites. Compared to the true orbit that we simulated, the averaged root mean square (RMS) values of orbit-only signal-in-space ranging errors (SISRE) are approximately 4.3 and 3.9 cm for KPS GEO and IGSO. Two different positioning solutions are analyzed to demonstrate the KPS performance. KPS standard point positioning (SPP) errors in the service area are about 4.7, 3.9, and 7.1 m for east (E), north (N), and up (U) components, respectively. The combined KPS+GPS SPP accuracy can be improved by 25.0%, 31.8%, and 35.0% compared to GPS in E, N, and U components. The averaged position errors for KPS kinematic precise point positioning (KPPP) are less than 10 cm. In the fringe of the KPS service area, however, the position RMS errors can reach about 40 cm. Unlike KPS, GPS solutions show high positioning accuracy in the KPS service area. The combined KPS+GPS can be improved by 28.7%, 27.1%, and 30.5% compared to GPS in E, N, and U components, respectively. It is noted that KPS can provide better performance with GPS in the Asia-Oceania region.
Skin Sea-Surface Temperature from VIIRS on Suomi-NPP—NASA Continuity Retrievals
Authors: Minnett Peter J. , Kilpatrick Katherine A. , Podestá Guillermo P. , Evans Robert H. , Szczodrak Malgorzata D. , Izaguirre Miguel Angel , Williams Elizabeth J. , Walsh Susan , Reynolds R. Michael , Bailey Sean W. , Armstrong Edward M. , Vazquez-Cuervo Jorge
Published: October 2020

Retrievals of skin Sea-Surface Temperature (SSTskin) from the measurements of the Visible Infrared Imaging Radiometer Suite on the Suomi-National Polar-orbiting Partnership satellite are presented and discussed. The algorithms used to derive the SSTskin from the radiometric measurements are given in detail. A number of approaches to assess the accuracy and stability of the Visible Infrared Imaging Radiometer Suite (VIIRS) SSTskin retrievals are reported, and factors including latitude and season, and physical processes in the atmosphere and at the surface are discussed. We conclude that the Suomi National Polar-orbiting Partnership (S-NPP) VIIRS is capable of matching and improving upon the accuracies of SSTskin from the MODISs on Terra and Aqua, and that the VIIRS SSTskin fields have the potential to contribute to the extension of the satellite-derived Climate Data Records of SST into the future.
Data Downlink System in the Vast IOT Node Condition Assisted by UAV, Large Intelligent Surface, and Power and Data Beacon
Authors: Zhang Zhibo , Chang Qing , Zhao Na , Li Chen , Li Tianrun
Published: October 2020

The future development of communication systems will create a great demand for the internet of things (IOT), where the overall control of all IOT nodes will become an important problem. Considering the essential issues of miniaturization and energy conservation, in this study, a new data downlink system is designed in which all IOT nodes harvest energy first and then receive data. To avoid the unsolvable problem of pre-locating all positions of vast IOT nodes, a device called the power and data beacon (PDB) is proposed. This acts as a relay station for energy and data. In addition, we model future scenes in which a communication system is assisted by unmanned aerial vehicles (UAVs), large intelligent surfaces (LISs), and PDBs. In this paper, we propose and solve the problem of determining the optimal flight trajectory to reach the minimum energy consumption or minimum time consumption. Four future feasible scenes are analyzed and then the optimization problems are solved based on numerical algorithms. Simulation results show that there are significant performance improvements in energy/time with the deployment of LISs and reasonable UAV trajectory planning.
Adaptive Weighted Graph Fusion Incomplete Multi-View Subspace Clustering
Authors: Zhang Pei , Wang Siwei , Hu Jingtao , Cheng Zhen , Guo Xifeng , Zhu En , Cai Zhiping
Published: October 2020

With the enormous amount of multi-source data produced by various sensors and feature extraction approaches, multi-view clustering (MVC) has attracted developing research attention and is widely exploited in data analysis. Most of the existing multi-view clustering methods hold on the assumption that all of the views are complete. However, in many real scenarios, multi-view data are often incomplete for many reasons, e.g., hardware failure or incomplete data collection. In this paper, we propose an adaptive weighted graph fusion incomplete multi-view subspace clustering (AWGF-IMSC) method to solve the incomplete multi-view clustering problem. Firstly, to eliminate the noise existing in the original space, we transform complete original data into latent representations which contribute to better graph construction for each view. Then, we incorporate feature extraction and incomplete graph fusion into a unified framework, whereas two processes can negotiate with each other, serving for graph learning tasks. A sparse regularization is imposed on the complete graph to make it more robust to the view-inconsistency. Besides, the importance of different views is automatically learned, further guiding the construction of the complete graph. An effective iterative algorithm is proposed to solve the resulting optimization problem with convergence. Compared with the existing state-of-the-art methods, the experiment results on several real-world datasets demonstrate the effectiveness and advancement of our proposed method.
UnetDVH-Linear: Linear Feature Segmentation by Dilated Convolution with Vertical and Horizontal Kernels
Authors: Liao Jiacai , Cao Libo , Li Wei , Luo Xiaole , Feng Xiexing
Published: October 2020

Linear feature extraction is crucial for special objects in semantic segmentation networks, such as slot marking and lanes. The objects with linear characteristics have global contextual information dependency. It is very difficult to capture the complete information of these objects in semantic segmentation tasks. To improve the linear feature extraction ability of the semantic segmentation network, we propose introducing the dilated convolution with vertical and horizontal kernels (DVH) into the task of feature extraction in semantic segmentation networks. Meanwhile, we figure out the outcome if we put the different vertical and horizontal kernels on different places in the semantic segmentation networks. Our networks are trained on the basis of the SS dataset, the TuSimple lane dataset and the Massachusetts Roads dataset. These datasets consist of slot marking, lanes, and road images. The research results show that our method improves the accuracy of the slot marking segmentation of the SS dataset by 2%. Compared with other state-of-the-art methods, our UnetDVH-Linear (v1) obtains better accuracy on the TuSimple Benchmark Lane Detection Challenge with a value of 97.53%. To prove the generalization of our models, road segmentation experiments were performed on aerial images. Without data argumentation, the segmentation accuracy of our model on the Massachusetts roads dataset is 95.3%. Moreover, our models perform better than other models when training with the same loss function and experimental settings. The experiment result shows that the dilated convolution with vertical and horizontal kernels will enhance the neural network on linear feature extraction.
An Acoustic Sensor Based on Active Fiber Fabry–Pérot Microcavities
Authors: Gao Xin-Xia , Cui Jin-Ming , Ai Ming-Zhong , Huang Yun-Feng , Li Chuan-Feng , Guo Guang-Can
Published: October 2020

We demonstrate an active acoustic sensor based on a high-finesse fiber Fabry–Pérot micro-cavity with a gain medium. The sensor is a compacted device lasing around 1535 nm by external optical pumping. The acoustic pressure acting on the sensor disturbs the emitted laser frequency, which is subsequently transformed to beat signals through a delay-arm interferometer, and directly detected by a photo-detector. In this configuration, the sensing device exhibits a high sensitivity of 2.6 V/Pa and a noise equivalent acoustic signal level of 230 μPa/Hz1/2 at a frequency of 4 kHz. Experimental results provide a wide frequency response from 100 Hz to 18 kHz. As the sensor works at communication wavelength and the output laser can be electrically tuned in the 10 nm range, a multi-sensor network can be easily constructed with the dense wavelength division multiplexing devices. Extra lasers or demodulators are unnecessary thus the proposed sensor is low cost and easy fabrication. The proposed sensor shows broad applications prospect in remote oil and gas leakage exploration, photo-acoustic spectrum detection, and sound source location.