bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-Pixel MEMS Imaging Systems
Authors: Zhou Guangcan , Lim Zi Heng , Qi Yi , Zhou Guangya
Published: February 2020

Single-pixel imaging technology is an attractive technology considering the increasing demand of imagers that can operate in wavelengths where traditional cameras have limited efficiency. Meanwhile, the miniaturization of imaging systems is also desired to build affordable and portable devices for field applications. Therefore, single-pixel imaging systems based on microelectromechanical systems (MEMS) is an effective solution to develop truly miniaturized imagers, owing to their ability to integrate multiple functionalities within a small device. MEMS-based single-pixel imaging systems have mainly been explored in two research directions, namely the encoding-based approach and the scanning-based approach. The scanning method utilizes a variety of MEMS scanners to scan the target scenery and has potential applications in the biological imaging field. The encoding-based system typically employs MEMS modulators and a single-pixel detector to encode the light intensities of the scenery, and the images are constructed by harvesting the power of computational technology. This has the capability to capture non-visible images and 3D images. Thus, this review discusses the two approaches in detail, and their applications are also reviewed to evaluate the efficiency and advantages in various fields.
Gallium Nitride (GaN) High-Electron-Mobility Transistors with Thick Copper Metallization Featuring a Power Density of 8.2 W/mm for Ka-Band Applications
Authors: Lin Y. C. , Chen S. H. , Lee P. H. , Lai K. H. , Huang T. J. , Chang Edward Y. , Hsu Heng-Tung
Published: February 2020

Copper-metallized gallium nitride (GaN) high-electron-mobility transistors (HEMTs) using a Ti/Pt/Ti diffusion barrier layer are fabricated and characterized for Ka-band applications. With a thick copper metallization layer of 6.8 μm adopted, the device exhibited a high output power density of 8.2 W/mm and a power-added efficiency (PAE) of 26% at 38 GHz. Such superior performance is mainly attributed to the substantial reduction of the source and drain resistance of the device. In addition to improvement in the Radio Frequency (RF) performance, the successful integration of the thick copper metallization in the device technology further reduces the manufacturing cost, making it extremely promising for future fifth-generation mobile communication system applications at millimeter-wave frequencies.
A Simulation Study of a Gate-All-Around Nanowire Transistor with a Core–Insulator
Authors: Zhang Yannan , Han Ke , Li and Jiawei
Published: February 2020

Ultra-low power and high-performance logical devices have been the driving force for the continued scaling of complementary metal oxide semiconductor field effect transistors which greatly enable electronic devices such as smart phones to be energy-efficient and portable. In the pursuit of smaller and faster devices, researchers and scientists have worked out a number of ways to further lower the leaking current of MOSFETs (Metal oxide semiconductor field effect transistor). Nanowire structure is now regarded as a promising candidate of future generation of logical devices due to its ultra-low off-state leaking current compares to FinFET. However, the potential of nanowire in terms of off-state current has not been fully discovered. In this article, a novel Core–Insulator Gate-All-Around (CIGAA) nanowire has been proposed, investigated, and simulated comprehensively and systematically based on 3D numerical simulation. Comparisons are carried out between GAA and CIGAA. The new CIGAA structure exhibits low off-state current compares to that of GAA, making it a suitable candidate of future low-power and energy-efficient devices.
Colistin-Resistant Acinetobacter Baumannii Bacteremia: A Serious Threat for Critically Ill Patients
Authors: Papathanakos Georgios , Andrianopoulos Ioannis , Papathanasiou Athanasios , Priavali Efthalia , Koulenti Despoina , Koulouras Vasilios
Published: February 2020

The prevalence of acinetobacter baumannii (AB) as a cause of hospital infections has been rising. Unfortunately, emerging colistin resistance limits therapeutic options and affects the outcome. The aim of the study was to confirm our clinically-driven hypothesis that intensive care unit (ICU) patients with AB resistant-to-colistin (ABCoR) bloodstream infection (BSI) develop fulminant septic shock and die. We conducted a 28-month retrospective observational study including all patients developing AB infection on ICU admission or during ICU stay. From 622 screened patients, 31 patients with BSI sepsis were identified. Thirteen (41.9%) patients had ABCoR BSI and 18/31 (58.1%) had colistin-susceptible (ABCoS) BSI. All ABCoR BSI patients died; of them, 69% (9/13) presented with fulminant septic shock and died within the first 3 days from its onset. ABCoR BSI patients compared to ABCoS BSI patients had higher mortality (100% vs. 50%, respectively (p = 0.001)), died sooner (p = 0.006), had lower pH (p = 0.004) and higher lactate on ICU admission (p = 0.0001), and had higher APACHE II (p = 0.01) and Charlson Comorbidity Index scores (p = 0.044). In conclusion, we documented that critically ill patients with ABCoR BSI exhibit fulminant septic shock with excessive mortality. Our results highlight the emerging clinical problem of AB colistin resistance among ICU patients.
U–Pb Dating of Zircon and Zirconolite Inclusions in Marble-Hosted Gem-Quality Ruby and Spinel from Mogok, Myanmar
Authors: Phyo Myint Myat , Wang Hao A.O. , Guillong Marcel , Berger Alfons , Franz Leander , Balmer Walter A. , Krzemnicki Michael S.
Published: February 2020

The Mogok area in Myanmar (Burma) is known since historic times as a source for some of the finest rubies and spinels in the world. In this study, we focus on in-situ U–Pb geochronological analyses of zircon and zirconolite, either present as inclusions in gem-quality ruby and spinel or as accessory minerals in ruby- and spinel-bearing marble and adjacent granulite facies gneisses. The age determination was carried out using both laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) and sector-field mass spectrometry (LA-ICP-SF-MS). In addition, we present multi-element data (REE) of zircon and zirconolite collected with LA-ICP-TOF-MS to further characterize these inclusions. Most of the studied zircon grains display growth zoning (core/rim) regardless if as inclusion in gemstones, or as accessory mineral in host rock samples. U–Pb dating was conducted on both core and rim of zircon grains and revealed most ages ranging from ~200 Ma in the core to ~17 Ma in the rim. The youngest U–Pb ages determined from the rim of zircon inclusions in gem-quality ruby and spinel are 22.26 ± 0.36 Ma and 22.88 ± 0.72 Ma, respectively. This agreement in U–Pb ages is interpreted to indicate a simultaneous formation of ruby and spinel in the Mogok area. In ruby- and spinel-bearing marble from Bawlongyi, the youngest zircon age was determined as 17.11 ± 0.22 Ma. Furthermore, U–Pb age measured on the rim of zircon grains in a biotite-garnet gneiss reveals a Late Oligocene age (26.13 ± 1.24 Ma), however older ages up to Precambrian age were also recorded in the cores of zircon as accessory minerals from this gneiss. These old ages point to a detrital origin of the analysed zircon cores. Although non-matrix matched standard was applied, zirconolite U–Pb age results are narrower in distribution from ~35 Ma to ~17 Ma, falling within the range of zircon ages. Based on results which are well in accordance with previous geochronological data from the Mogok Metamorphic Belt (MMB), we deduce that gem-quality ruby and spinel from Mogok probably formed during a granulite-facies regional metamorphic event in Oligocene to Early Miocene, related to post collision tectonics of the Eurasian and Indian plates. Our data not only provide key information to understand the formation of gem-quality ruby and spinel in the so-called Mogok Stone Tract, but also provide assisting evidence when determining the country of origin of gemstones in gemmological laboratories.
Nanomedicines to Deliver mRNA: State of the Art and Future Perspectives
Authors: Gómez-Aguado Itziar , Rodríguez-Castejón Julen , Vicente-Pascual Mónica , Rodríguez-Gascón Alicia , Solinís María Ángeles , del Pozo-Rodríguez Ana
Published: February 2020

The use of messenger RNA (mRNA) in gene therapy is increasing in recent years, due to its unique features compared to plasmid DNA: Transient expression, no need to enter into the nucleus and no risk of insertional mutagenesis. Nevertheless, the clinical application of mRNA as a therapeutic tool is limited by its instability and ability to activate immune responses; hence, mRNA chemical modifications together with the design of suitable vehicles result essential. This manuscript includes a revision of the strategies employed to enhance in vitro transcribed (IVT) mRNA functionality and efficacy, including the optimization of its stability and translational efficiency, as well as the regulation of its immunostimulatory properties. An overview of the nanosystems designed to protect the mRNA and to overcome the intra and extracellular barriers for successful delivery is also included. Finally, the present and future applications of mRNA nanomedicines for immunization against infectious diseases and cancer, protein replacement, gene editing, and regenerative medicine are highlighted.
Synergistic Antibacterial Activity of Silver-Loaded Graphene Oxide towards Staphylococcus Aureus and Escherichia Coli
Authors: Vi Truong , Kumar Selvaraj , Pang Jong-Hwei , Liu Yu-Kuo , Chen Dave , Lue Shingjiang
Published: February 2020

In this study, the physicochemical and surface properties of the GO–Ag composite promote a synergistic antibacterial effect towards both Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. Aureus) bacteria. GO–Ag NPs have a better bactericidal effect on E. coli (73%) and S. Aureus (98.5%) than pristine samples (pure Ag or GO). Transmission electron microscopy (TEM) confirms that the GO layers folded entire bacteria by attaching to the membrane through functional groups, while the Ag NPs penetrated the inner cell, thus damaging the cell membrane and leading to cell death. Cyclic voltammetry (CV) tests showed significant redox activity in GO–Ag NPs, enabling good catalytic performance towards H2O2 reduction. Strong reactive oxygen species (ROS) in GO–Ag NPs suggests that ROS might be associated with bactericidal activity. Therefore, the synergy between the physicochemical effect and ROS production of this material is proposed as the mechanism of its antibacterial activity.
Graphene Oxide–Silver Nanoparticle Nanohybrids: Synthesis, Characterization, and Antimicrobial Properties
Authors: Cobos Mónica , De-La-Pinta Iker , Quindós Guillermo , Fernández M. Jesús , Fernández M. Dolores
Published: February 2020

Drug resistance of pathogenic microorganisms has become a global public health problem, which has prompted the development of new materials with antimicrobial properties. In this context, antimicrobial nanohybrids are an alternative due to their synergistic properties. In this study, we used an environmentally friendly one-step approach to synthesize graphene oxide (GO) decorated with silver nanoparticles (GO–AgNPs). By this process, spherical AgNPs of average size less than 4 nm homogeneously distributed on the surface of the partially reduced GO can be generated in the absence of any stabilizing agent, only with ascorbic acid (L-AA) as a reducing agent and AgNO3 as a metal precursor. The size of the AgNPs can be controlled by the AgNO3 concentration and temperature. Smaller AgNPs are obtained at lower concentrations of the silver precursor and lower temperatures. The antimicrobial properties of nanohybrids against Gram-negative bacteria Escherichia coli and Pseudomonas aeruginosa, Gram-positive Staphylococcus aureus, and the yeast Candida albicans were found to be concentration- and time-dependent. C. albicans and S. aureus showed the highest susceptibility to GO–AgNPs. These nanohybrids can be used as nanofillers in polymer nanocomposites to develop materials with antimicrobial activity for applications in different areas, and another potential application could be cancer therapeutic agents.
Calcium Oxalate Nephrolithiasis and Gut Microbiota: Not just a Gut-Kidney Axis. A Nutritional Perspective
Authors: Ticinesi Andrea , Nouvenne Antonio , Chiussi Giulia , Castaldo Giampiero , Guerra Angela , Meschi Tiziana
Published: February 2020

Recent studies have shown that patients with kidney stone disease, and particularly calcium oxalate nephrolithiasis, exhibit dysbiosis in their fecal and urinary microbiota compared with controls. The alterations of microbiota go far beyond the simple presence and representation of Oxalobacter formigenes, a well-known symbiont exhibiting a marked capacity of degrading dietary oxalate and stimulating oxalate secretion by the gut mucosa. Thus, alterations of the intestinal microbiota may be involved in the pathophysiology of calcium kidney stones. However, the role of nutrition in this gut-kidney axis is still unknown, even if nutritional imbalances, such as poor hydration, high salt, and animal protein intake and reduced fruit and vegetable intake, are well-known risk factors for kidney stones. In this narrative review, we provide an overview of the gut-kidney axis in nephrolithiasis from a nutritional perspective, summarizing the evidence supporting the role of nutrition in the modulation of microbiota composition, and their relevance for the modulation of lithogenic risk.
Dietary Patterns of Breakfast Consumption Among Chilean University Students
Authors: Díaz-Torrente Ximena , Quintiliano-Scarpelli Daiana
Published: February 2020

Breakfast is one of the most important meals of the day. A good quality breakfast must include dairy products, cereals, and fruits. The aim of this study is to determine breakfast dietary patterns and their nutritional quality among Chilean university students. A cross-sectional non-probabilistic study was conducted in 200 university students between 18 and 27 years in Santiago, Chile. To identify dietary patterns and breakfast quality, a breakfast food survey was conducted. Patterns were identified by factor analysis. Most of the subjects (53%) ate breakfast daily, with a higher prevalence among females (60.2% vs. 43.7%, p < 0.05); 68% did not consume fruits and 17.5% had good breakfast quality, with no differences by sex. Four breakfast dietary patterns were identified: “dairy & cereals”, “healthy”, “traditional salty” and “traditional sweet” that together explained 35.6% of the total variance. There was no sex difference in predominant dietary patterns. The “dairy & cereals” and “traditional sweet” patterns were associated with regularly eating breakfast (β: −0.47, p = 0.001; β: −0.32, p = 0.020) and the “healthy” pattern with BMI ≥25 kg/m2 (β: 0.35, p = 0.024). In conclusion, breakfast quality was inadequate due to low fruit consumption and energy intake. The four identified patterns included cereals, bread, dairy, fats and sugars. Results may be usual in the planning of future interventions aimed at improving breakfast consumption and quality in university students.
Possible Involvement of Vitamin C in Periodontal Disease-Diabetes Mellitus Association
Authors: Bogdan Maria , Meca Andreea Daniela , Boldeanu Mihail Virgil , Gheorghe Dorin Nicolae , Turcu-Stiolica Adina , Subtirelu Mihaela-Simona , Boldeanu Lidia , Blaj Mihaela , Botnariu Gina Eosefina , Vlad Cristiana Elena , Foia Liliana Georgeta , Surlin Petra
Published: February 2020

Ascorbic acid (vitamin C) is an important water-soluble vitamin found in many fruits and vegetables. It has well-documented beneficial effects on the human body and is used as a supplement, alone or in combination with other vitamins and minerals. Over recent years, research has focused on possible new therapeutic actions in chronic conditions including periodontal disease (PD). We conducted a systematic review on clinical trials from four databases (PubMed, Clinical Trials, Cochrane, Web of Science) which measured plasmatic/salivary levels of ascorbic acid in PD–diabetes mellitus (DM) association. Six studies were included in our review, three of them analyzing patients with different grades of PD and DM who received vitamin C as a treatment (500 mg vitamin C/day for 2 months and 450 mg/day for 2 weeks) or as part of their alimentation (guava fruits), in combination with standard therapies and procedures. Decreased levels of vitamin C were observed in PD patients with DM but data about efficacy of vitamin C administration are inconclusive. Given the important bidirectional relationship between PD and DM, there is a strong need for more research to assess the positive effects of ascorbic acid supplementation in individuals suffering from both diseases and also its proper regimen for these patients.
Increased Colonic Permeability and Lifestyles as Contributing Factors to Obesity and Liver Steatosis
Authors: Di Palo Domenica Maria , Garruti Gabriella , Di Ciaula Agostino , Molina-Molina Emilio , Shanmugam Harshitha , De Angelis Maria , Portincasa Piero
Published: February 2020

Intestinal permeability (IP) is essential in maintaining gut-metabolic functions in health. An unequivocal evaluation of IP, as marker of intestinal barrier integrity, however, is missing in health and in several diseases. We aimed to assess IP in the whole gastrointestinal tract according to body mass index (BMI) and liver steatosis. In 120 patients (61F:59M; mean age 45 ± SEM 1.2 years, range: 18–75), IP was distinctively studied by urine recovery of orally administered sucrose (SO, stomach), lactulose/mannitol ratio (LA/MA, small intestine), and sucralose (SA, colon). By triple quadrupole mass-spectrometry and high-performance liquid chromatography, we measured urinary recovery of saccharide probes. Subjects were stratified according to BMI as normal weight, overweight, and obesity, and answered questionnaires regarding dietary habits and adherence to the Mediterranean Diet. Liver steatosis was assessed by ultrasonography. IP at every gastrointestinal tract was similar in both sexes and decreased with age. Stomach and small intestinal permeability did not differ according to BMI. Colonic permeability increased with BMI, waist, neck, and hip circumferences and was significantly higher in obese than in lean subjects. As determined by logistic regression, the odds ratio (OR) of BMI increment was significantly higher in subjects in the highest tertile of sucralose excretion, also after adjusting for age and consumption of junk food. The presence of liver steatosis was associated with increased colonic permeability. Patients with lower score of adherence to Mediterranean diet had a higher score of ‘junk food’. Intestinal permeability tended to increase in subjects with a lower adherence to Mediterranean diet. In conclusion, colonic (but not stomach and small intestinal) permeability seems to be linked to obesity and liver steatosis independently from dietary habits, age, and physical activity. The exact role of these last factors, however, requires specific studies focusing on intestinal permeability. Results should pave the way to both primary prevention measures and new therapeutic strategies in metabolic and liver diseases.
Prescriber-Initiated Engagement of Pharmacists for Information and Intervention in Programs of All-Inclusive Care for the Elderly
Authors: Bankes David L. , Schamp Richard O. , Knowlton Calvin H. , Bain Kevin T.
Published: February 2020

Little is known about the types of drug information inquiries (DIIs) prescribers caring for older adults ask pharmacists during routine practice. The objective of this research was to analyze the types of DIIs prescribing clinicians of Programs of All-Inclusive Care for the Elderly (PACE) made to clinical pharmacists during routine patient care. This was a retrospective analysis of documented pharmacists’ encounters with PACE prescribers between March through December, 2018. DIIs were classified using a developed taxonomy that describes prescribers’ motivations for consulting with pharmacists and their drug information needs. Prescribers made 414 DIIs during the study period. Medication safety concerns motivated the majority of prescribers’ inquiries (223, 53.9%). Inquiries received frequently involved modifying drug therapy (94, 22.7%), identifying or resolving adverse drug events (75, 18.1%), selecting or adjusting doses (61, 14.7%), selecting new drug therapies (57, 13.8%), and identifying or resolving drug interactions (52, 12.6%). Central nervous system medications (e.g., antidepressants and opioids), were involved in 38.6% (n = 160) of all DIIs. When answering DIIs, pharmacists made 389 recommendations. Start alternative medications (18.0%), start new medications (16.7%), and change doses (12.1%) were the most frequent recommendations rendered. Prescribers implemented at least 79.3% (n = 268) of recommendations based on pharmacy records (n = 338 verifiable recommendations). During clinical practice, PACE prescribers commonly ask pharmacists a variety of DIIs, largely related to medication safety concerns. In response to these DIIs, pharmacists provide medication management recommendations, which are largely implemented by prescribers.
Quantum Theory of Multisubband Plasmon– Phonon Coupling
Authors: Ribeiro Sofia , Vasanelli Angela , Todorov Yanko , Sirtori Carlo
Published: February 2020

We present a theoretical description of the coupling between longitudinal optical phonons and collective excitations of a two-dimensional electron gas. By diagonalizing the Hamiltonian of the system, including Coulomb electron–electron and Fröhlich interactions, we observe the formation of multisubband polarons, mixed states partially phonon and partially multisubband plasmon, characterized by a coupling energy which is a significant fraction, up to ∼ 40 % , of the phonon energy. We demonstrate that multisubband plasmons and longitudinal optical phonons are in the ultra-strong coupling regime in several III–V and II–VI material systems.
Confession and Hope: Ekklesia’s Task in the Global Emergency
Authors: Gorringe Timothy
Published: February 2020

Humanity is currently faced with deadly dangers that could bring about the breakdown of civilization, and even the end of human life on earth in short order. The Marxist and Green thinker Rudolf Bahro spoke of a ‘logic of salvation’, which involved a return to the idea of God. Ekklesia arose as a witness to such a logic of salvation. It can be understood as a social movement, that sketches out a prefigurative politics that can then be realised. The contemporary church needs to recover this understanding, adopting climate change as a confessional issue that defines its common life. This could be part of a practical logic of salvation.
Agricultural Expansion in Mato Grosso from 1986–2000: A Bayesian Time Series Approach to Tracking Past Land Cover Change
Authors: Lee Jacky , Cardille Jeffrey A. , Coe Michael T.
Published: February 2020

Landsat 5 has produced imagery for decades that can now be viewed and manipulated in Google Earth Engine, but a general, automated way of producing a coherent time series from these images—particularly over cloudy areas in the distant past—is elusive. Here, we create a land use and land cover (LULC) time series for part of tropical Mato Grosso, Brazil, using the Bayesian Updating of Land Cover: Unsupervised (BULC-U) technique. The algorithm built backward in time from the GlobCover 2009 data set, a multi-category global LULC data set at 300 m resolution for the year 2009, combining it with Landsat time series imagery to create a land cover time series for the period 1986–2000. Despite the substantial LULC differences between the 1990s and 2009 in this area, much of the landscape remained the same: we asked whether we could harness those similarities and differences to recreate an accurate version of the earlier LULC. The GlobCover basis and the Landsat-5 images shared neither a common spatial resolution nor time frame, But BULC-U successfully combined the labels from the coarser classification with the spatial detail of Landsat. The result was an accurate fine-scale time series that quantified the expansion of deforestation in the study area, which more than doubled in size during this time. Earth Engine directly enabled the fusion of these different data sets held in its catalog: its flexible treatment of spatial resolution, rapid prototyping, and overall processing speed permitted the development and testing of this study. Many would-be users of remote sensing data are currently limited by the need to have highly specialized knowledge to create classifications of older data. The approach shown here presents fewer obstacles to participation and allows a wide audience to create their own time series of past decades. By leveraging both the varied data catalog and the processing speed of Earth Engine, this research can contribute to the rapid advances underway in multi-temporal image classification techniques. Given Earth Engine’s power and deep catalog, this research further opens up remote sensing to a rapidly growing community of researchers and managers who need to understand the long-term dynamics of terrestrial systems.
Remote Sensing-Based Research for Monitoring Progress towards SDG 15 in Bangladesh: A Review
Authors: Ishtiaque Asif , Masrur Arif , Rabby Yasin Wahid , Jerin Tasnuba , Dewan Ashraf
Published: February 2020

The Sustainable Development Goals (SDGs) have been in effect since 2015 to continue the progress of the Millennium Development Goals. Some of the SDGs are expected to be achieved by 2020, while others by 2030. Among the 17 SDGs, SDG 15 is particularly dedicated to environmental resources (e.g., forest, wetland, land). These resources are gravely threatened by human-induced climate change and intense anthropogenic activities. In Bangladesh, one of the most climate-vulnerable countries, climate change and human interventions are taking a heavy toll on environmental resources. Ensuring the sustainability of these resources requires regular monitoring and evaluation to identify challenges, concerns, and progress of environmental management. Remote sensing has been used as an effective tool to monitor and evaluate these resources. As such, many studies on Bangladesh used various remote-sensing approaches to conduct research on the issues related to SDG 15, particularly on forest, wetland, erosion, and landslides. However, we lack a comprehensive view of the progress, challenges, concerns, and future outlook of the goal and its targets. In this study, we sought to systematically review the remote-sensing studies related to SDG 15 (targets 15.1–15.3) to present developments, analyze trends and limitations, and provide future directions to ensure sustainability. We developed several search keywords and finally selected 53 articles for review. We discussed the topical and methodological trends of current remote-sensing works. In addition, limitations were identified and future research directions were provided.
A High-Resolution Global Map of Giant Kelp (Macrocystis pyrifera) Forests and Intertidal Green Algae (Ulvophyceae) with Sentinel-2 Imagery
Authors: Mora-Soto Alejandra , Palacios Mauricio , Macaya Erasmo , Gómez Iván , Huovinen Pirjo , Pérez-Matus Alejandro , Young Mary , Golding Neil , Toro Martin , Yaqub Mohammad , Macias-Fauria Marc
Published: February 2020

Giant kelp (Macrocystis pyrifera) is the most widely distributed kelp species on the planet, constituting one of the richest and most productive ecosystems on Earth, but detailed information on its distribution is entirely missing in some marine ecoregions, especially in the high latitudes of the Southern Hemisphere. Here, we present an algorithm based on a series of filter thresholds to detect giant kelp employing Sentinel-2 imagery. Given the overlap between the reflectances of giant kelp and intertidal green algae (Ulvophyceae), the latter are also detected on shallow rocky intertidal areas. The kelp filter algorithm was applied separately to vegetation indices, the Floating Algae Index (FAI), the Normalised Difference Vegetation Index (NDVI), and a novel formula (the Kelp Difference, KD). Training data from previously surveyed kelp forests and other coastal and ocean features were used to identify reflectance threshold values. This procedure was validated with independent field data collected with UAV imagery at a high spatial resolution and point-georeferenced sites at a low spatial resolution. When comparing UAV with Sentinel data (high-resolution validation), an average overall accuracy ≥ 0.88 and Cohen’s kappa ≥ 0.64 coefficients were found in all three indices for canopies reaching the surface with extensions greater than 1 hectare, with the KD showing the highest average kappa score (0.66). Measurements between previously surveyed georeferenced points and remotely-sensed kelp grid cells (low-resolution validation) showed that 66% of the georeferenced points had grid cells indicating kelp presence within a linear distance of 300 m. We employed the KD in our kelp filter algorithm to estimate the global extent of giant kelp and intertidal green algae per marine ecoregion and province, producing a high-resolution global map of giant kelp and intertidal green algae, powered by Google Earth Engine.
A Novel Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions Using a Two-Stream Convolutional Neural Network
Authors: Jia Duo , Song Changqing , Cheng Changxiu , Shen Shi , Ning Lixin , Hui Chun
Published: February 2020

Spatiotemporal fusion is considered a feasible and cost-effective way to solve the trade-off between the spatial and temporal resolution of satellite sensors. Recently proposed learning-based spatiotemporal fusion methods can address the prediction of both phenological and land-cover change. In this paper, we propose a novel deep learning-based spatiotemporal data fusion method that uses a two-stream convolutional neural network. The method combines both forward and backward prediction to generate a target fine image, where temporal change-based and a spatial information-based mapping are simultaneously formed, addressing the prediction of both phenological and land-cover changes with better generalization ability and robustness. Comparative experimental results for the test datasets with phenological and land-cover changes verified the effectiveness of our method. Compared to existing learning-based spatiotemporal fusion methods, our method is more effective in predicting phenological change and directly reconstructing the prediction with complete spatial details without the need for auxiliary modulation.
Uncertainty Analysis for Topographic Correction of Hyperspectral Remote Sensing Images
Authors: Ma Zhaoning , Jia Guorui , Schaepman Michael E. , Zhao Huijie
Published: February 2020

Quantitative uncertainty analysis is generally taken as an indispensable step in the calibration of a remote sensor. A full uncertainty propagation chain has not been established to set up the metrological traceability for surface reflectance inversed from remotely sensed images. As a step toward this goal, we proposed an uncertainty analysis method for the two typical semi-empirical topographic correction models, i.e., C and Minnaert, according to the ‘Guide to the Expression of Uncertainty in Measurement (GUM)’. We studied the data link and analyzed the uncertainty propagation chain from the digital elevation model (DEM) and at-sensor radiance data to the topographic corrected radiance. We obtained spectral uncertainty characteristics of the topographic corrected radiance as well as its uncertainty components associated with all of the input quantities by using a set of Earth Observation-1 (EO-1) Hyperion data acquired over a rugged soil surface partly covered with snow. Firstly, the relative uncertainty of cover types with lower radiance values was larger for both C and Minnaert corrections. Secondly, the trend of at-sensor radiance contributed to a spectral feature, where the uncertainty of the topographic corrected radiance was poor in bands below 1400 nm. Thirdly, the uncertainty components associated with at-sensor radiance, slope, and aspect dominated the total combined uncertainty of corrected radiance. It was meaningful to reduce the uncertainties of at-sensor radiance, slope, and aspect for reducing the uncertainty of corrected radiance and improving the data quality. We also gave some suggestions to reduce the uncertainty of slope and aspect data.
A New Model for Transfer Learning-Based Mapping of Burn Severity
Authors: Zheng Zhong , Wang Jinfei , Shan Bo , He Yongjun , Liao Chunhua , Gao Yanghua , Yang Shiqi
Published: February 2020

In recent years, global forest fires have occurred more frequently, seriously destroying the structural functions of forest ecosystem. Mapping the burn severity after forest fires is of great significance for quantifying fire’s effects on landscapes and establishing restoration measures. Generally, intensive field surveys across burned areas are required for the effective application of traditional methods. Unfortunately, this requirement could not be satisfied in most cases, since the field work demands a lot of personnel and funding. For mapping severity levels across burned areas without field survey data, a semi-supervised transfer component analysis-based support vector regression model (SSTCA-SVR) was proposed in this study to transfer knowledge trained from other burned areas with field survey data. Its performance was further evaluated in various eco-type regions of southwestern United States. Results show that SSTCA-SVR which was trained on source domain areas could effectively be transferred to a target domain area. Meanwhile, the SSTCA-SVR could maintain as much spectral information as possible to map burn severity. Its mapped results are more accurate (RMSE values were between 0.4833 and 0.6659) and finer, compared to those mapped by ∆NDVI-, ∆LST-, ∆NBR- (RMSE values ranged from 0.7362 to 1.1187) and SVR-based models (RMSE values varied from 1.7658 to 2.0055). This study has introduced a potentially efficient mechanism to map burn severity, which will speed up the response of post-fire management.
Understanding Intra-Annual Dynamics of Ecosystem Services Using Satellite Image Time Series
Authors: del Río-Mena Trinidad , Willemen Louise , Vrieling Anton , Nelson Andy
Published: February 2020

Landscape processes fluctuate over time, influencing the intra-annual dynamics of ecosystem services. However, current ecosystem service assessments generally do not account for such changes. This study argues that information on the dynamics of ecosystem services is essential for understanding and monitoring the impact of land management. We studied two regulating ecosystem services (i. erosion prevention, ii. regulation of water flows) and two provisioning services (iii. provision of forage, iv. biomass for essential oil production) in thicket vegetation and agricultural fields in the Baviaanskloof, South Africa. Using models based on Sentinel-2 data, calibrated with field measurements, we estimated the monthly supply of ecosystem services and assessed their intra-annual variability within vegetation cover types. We illustrated how the dynamic supply of ecosystem services related to temporal variations in their demand. We also found large spatial variability of the ecosystem service supply within a single vegetation cover type. In contrast to thicket vegetation, agricultural land showed larger temporal and spatial variability in the ecosystem service supply due to the effect of more intensive management. Knowledge of intra-annual dynamics is essential to jointly assess the temporal variation of supply and demand throughout the year to evaluate if the provision of ecosystem services occurs when most needed.
Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors
Authors: Karlsson Karl-Göran , Johansson Erik , Håkansson Nina , Sedlar Joseph , Eliasson Salomon
Published: February 2020

Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generation, cloud screening must be balanced, so both false cloud-free and false cloudy retrievals are minimized. Many methods used in recent CDRs show signs of clear-conservative cloud screening leading to overestimated cloudiness. This study presents a new cloud screening approach for Advanced Very-High-Resolution Radiometer (AVHRR) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery based on the Bayesian discrimination theory. The method is trained on high-quality cloud observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The method delivers results designed for optimally balanced cloud screening expressed as cloud probabilities together with information on for which clouds (minimum cloud optical thickness) the probabilities are valid. Cloud screening characteristics over 28 different Earth surface categories were estimated. Using independent CALIOP observations (including all observed clouds) in 2010 for validation, the total global hit rates for AVHRR data and the SEVIRI full disk were 82% and 85%, respectively. High-latitude oceans had the best performance, with a hit rate of approximately 93%. The results were compared to the CM SAF cLoud, Albedo, and surface RAdiation dataset from AVHRR data–second edition (CLARA-A2) CDR and showed general improvements over most global regions. Notably, the Kuipers’ Skill Score improved, verifying a more balanced cloud screening. The new method will be used to prepare the new CLARA-A3 and CLAAS-3 (CLoud property dAtAset using SEVIRI, Edition 3) CDRs in the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project.
Operational Monitoring and Damage Assessment of Riverine Flood-2014 in the Lower Chenab Plain, Punjab, Pakistan, Using Remote Sensing and GIS Techniques
Authors: Sajjad Asif , Lu Jianzhong , Chen Xiaoling , Chisenga Chikondi , Saleem Nayyer , Hassan Hammad
Published: February 2020

In flood-prone areas, the delineation of the spatial pattern of historical flood extents, damage assessment, and flood durations allow planners to anticipate potential threats from floods and to formulate strategies to mitigate or abate these events. The Chenab plain in the Punjab region of Pakistan is particularly prone to flooding but is understudied. It experienced its worst riverine flood in recorded history in September 2014. The present study applies Remote Sensing (RS) and Geographical Information System (GIS) techniques to estimate the riverine flood extent and duration and assess the resulting damage using Landsat-8 data. The Landsat-8 images were acquired for the pre-flooding, co-flooding, and post-flooding periods for the comprehensive analysis and delineation of flood extent, damage assessment, and duration. We used supervised classification to determine land use/cover changes, and the satellite-derived modified normalized difference water index (MNDWI) to detect flooded areas and duration. The analysis permitted us to calculate flood inundation, damages to built-up areas, and agriculture, as well as the flood duration and recession. The results also reveal that the floodwaters remained in the study area for almost two months, which further affected cultivation and increased the financial cost. Our study provides an empirical basis for flood response assessment and rehabilitation efforts in future events. Thus, the integrated RS and GIS techniques with supporting datasets make substantial contributions to flood monitoring and damage assessment in Pakistan.
Recognition of Water Colour Anomaly by Using Hue Angle and Sentinel 2 Image
Authors: Zhao Yelong , Shen Qian , Wang Qian , Yang Fan , Wang Shenglei , Li Junsheng , Zhang Fangfang , Yao Yue
Published: February 2020

As polluted water bodies are often small in area and widely distributed, performing artificial field screening is difficult; however, remote-sensing-based screening has the advantages of being rapid, large-scale, and dynamic. Polluted water bodies often show anomalous water colours, such as black, grey, and red. Therefore, the large-scale recognition of suspected polluted water bodies through high-resolution remote-sensing images and water colour can improve the screening efficiency and narrow the screening scope. However, few studies have been conducted on such kinds of water bodies. The hue angle of a water body is a parameter used to describe colour in the International Commission on Illumination (CIE) colour space. Based on the measured data, the water body with a hue angle greater than 230.958° is defined as a water colour anomaly, which is recognised based on the Sentinel-2 image through the threshold set in this study. The results showed that the hue angle of the water body was extracted from the Sentinel-2 image, and the accuracy of the hue angle calculated by the in situ remote-sensing reflectance Rrs (λ) was evaluated, where the root mean square error (RMSE) and mean relative error (MRE) were 4.397° and 1.744%, respectively, proving that this method is feasible. The hue angle was calculated for a water colour anomaly and a general water body in Qiqihar. The water body was regarded as a water colour anomaly when the hue angle was >230.958° and as a general water body when the hue angle was ≤230.958°. High-quality Sentinel-2 images of Qiqihar taken from May 2016 to August 2019 were chosen, and the position of the water body remained unchanged; there was no error or omission, and the hue angle of the water colour anomaly changed obviously, indicating that this method had good stability. Additionally, the method proposed is only suitable for optical deep water, not for optical shallow water. When this method was applied to Xiong’an New Area, the results showed good recognition accuracy, demonstrating good universality of this method. In this study, taking Qiqihar as an example, a surface survey experiment was conducted from October 14 to 15, 2018, and the measured data of six general and four anomalous water sample points were obtained, including water quality terms such as Rrs (λ), transparency, water colour, water temperature, and turbidity.
Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China
Authors: He Zhonghua , Lei Liping , Zeng Zhao-Cheng , Sheng Mengya , Welp Lisa R.
Published: February 2020

Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO2 concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO2 dry air mole fraction (XCO2) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO2 changes during growing season for 13 years. We derived a relationship between XCO2 and surface net CO2 fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO2 flux enhancement based on satellite observed XCO2 changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO2 emissions, we estimated an enhanced XCO2 drawdown during the GP of −0.070 to −0.084 ppm yr−1. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO2 to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord.
Novel Secure Group Data Exchange Protocol in Smart Home with Physical Layer Network Coding
Authors: Liu Qiao , Zhang Wenjing , Ding Sheng , Li Hui , Wang Yong
Published: February 2020

Smart homes have been shown to be one of the most important applications of Internet of Things (IoT); however, security issues are still the main drawback to be improved, especially facing the problem of terminal power constraint and distributed network architecture. In this paper, we propose a novel secure group data exchange protocol in smart homes with physical layer approaches which retains the benefit of key sharing needless and lightweight computation. As the core technique, nested lattice physical layer network coding is conduct in each sensor node to form a summed data at a home router. With such summed data, the untrusted home router attack and external eavesdropper attack can be resistant. Performance has been analyzed for the proposed protocol in terms of time slot cost, security resistance, and secrecy capacity. Finally, simulations have been conducted to demonstrate the theoretical analysis.
Standing-Posture Recognition in Human–Robot Collaboration Based on Deep Learning and the Dempster–Shafer Evidence Theory
Authors: Li Guan , Liu Zhifeng , Cai Ligang , Yan Jun
Published: February 2020

During human–robot collaborations (HRC), robot systems must accurately perceive the actions and intentions of humans. The present study proposes the classification of standing postures from standing-pressure images, by which a robot system can predict the intended actions of human workers in an HRC environment. To this end, it explores deep learning based on standing-posture recognition and a multi-recognition algorithm fusion method for HRC. To acquire the pressure-distribution data, ten experimental participants stood on a pressure-sensing floor embedded with thin-film pressure sensors. The pressure data of nine standing postures were obtained from each participant. The human standing postures were discriminated by seven classification algorithms. The results of the best three algorithms were fused using the Dempster–Shafer evidence theory to improve the accuracy and robustness. In a cross-validation test, the best method achieved an average accuracy of 99.96%. The convolutional neural network classifier and data-fusion algorithm can feasibly classify the standing postures of human workers.
Cost-Effective Implementation of a Temperature Traceability System Based on Smart RFID Tags and IoT Services
Authors: Urbano Oscar , Perles Angel , Pedraza Cesar , Rubio-Arraez Susana , Castelló María Luisa , Ortola María Dolores , Mercado Ricardo
Published: February 2020

This paper presents the design and validation of a traceability system, based on radio frequency identification (RFID) technology and Internet of Things (IoT) services, intended to address the interconnection and cost-implementation problems typical in traceability systems. The RFID layer integrates temperature sensors into RFID tags, to track and trace food conditions during transportation. The IoT paradigm makes it possible to connect multiple systems to the same platform, addressing interconnection problems between different technology providers. The cost-implementation issues are addressed following the Data as a Service (DaaS) billing scheme, where users pay for the data they consume and not the installed equipment, avoiding the big initial investment that these high-tech solutions commonly require. The developed system is validated in two case scenarios, one carried out in controlled laboratory conditions, monitoring chopped pumpkin. Another case, carried out in a real scenario, monitors oranges sent from Valencia, Spain to Cork, Ireland.