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Objectives: During the COVID-19 pandemic, the NHS delivered a community-based remote home monitoring service for COVID-19 patients. The service came in two models characterised based on the referral method: home-based care to ensure the right people were admitted at hospital at the right time (named COVID Oximetry @ home (CO@h)) and facilitation of patients' transition when discharged home (named Covid-19 Virtual Ward (CVW)). Patients were provided with pulse oximeters and asked to regularly record and submit oxygen levels and other symptoms to a team of administrators and clinicians via digital means (tech-enable and analogue mode) and/or over the phone (analogue). Our aim was to evaluate the costs of implementing these services in England during wave 2 of the pandemic (October 2020-April 2021). Method(s): We used a top-down approach to describe the costs of setting-up and running the service. 26 sites reported the number of patients and staff members involved in the service, and other used resources. Descriptive statistics and multivariate regression analysis were used appropriately. Result(s): The mean cost per patient monitored was lower in the CO@h service compared to the CVW (527.5 vs. 599.1). The corresponding cost was lower for sites using tech-enabled and analogue data submission mode compared to sites using analogue-only mode for both CO@h (515 vs. 561) and CVW (584 vs. 612) services. The number of patients enrolled in the service and the service type significantly affected the mean cost per patient (b=0.62, p= 0.001;b=-457.99, p=0.05 correspondingly). Conclusion(s): Our analysis offers a model for future research since it covers sites of various sizes and raises questions about different practices within the overall remote monitoring services.Copyright © 2023
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Objectives: Insulin optimisation requires review of glucose monitoring;Covid-19 posed challenges to this. We evaluated DBm -a remote monitoring platform utilising a glucometer and smartphone app. Method(s): Evaluation was from January to November 2021. Inclusion criteria was insulin treated diabetes with HbA1c greater than 68mmol/mol. HbA1c, demographics, frequency of CBG uploads and interactions with clinicians were collected. Result(s): 97 patients were offered DBm. 48.5% used the app. There were no statistically significant differences in gender (p = 0.05), age (p = 0.36), type of diabetes (p = 0.13) or deprivation index (p = 0.96) between users and non-users. Patients of white ethnicity were less likely to use the platform (p = 0.01). Amongst users, 70% had a reduction of HbA1c of at least 5mmol/mol over six months, with a mean reduction of 25.6mmol/mol (p = 0.01). There was no difference in age (p = 0.64), gender (p = 0.4), and type of diabetes (p = 0.23) between responders and non-responders. There was also no difference in number of call back requests generated by patients (p = 0.32) or number of CBG uploads (p = 0.899) between responders and non-responders. Conclusion(s): Uptake of the remote monitoring solution was just under 50%, with no evidence of digital exclusion, although the finding that white ethnicity patients were less likely to use the system needs further exploration. Most users had improved glucose control, but there was no association with numbers of tests or call back requests. This study demonstrates that insulin optimisation can effectively be delivered using a remote glucose monitoring system. Future work will explore patient experience and patient satisfaction.
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A hybrid workstyle is becoming more common post-COVID-19, and longer occupancy hours at home are increasing household electricity consumption. Small homes are regarded as a potential for improving energy efficiency in the residential sector, and a home consists of mixed-function spaces with dynamic occupancy behaviors. These underpin the opportunity to optimize presence sensing lighting in small homes for energy efficiency and user-behavioral needs. A comprehensive overview of presence sensing approaches, comparing four types of non-wearable sensors connected to home lighting is made. A bibliometric mapping of the reviewed literature visually reinforces a significant research gap that presence sensing studies were not connected to home lighting but inclined toward the commercial and institutional context. Next, a non-exhaustive example of commercially available presence sensing products applicable to residential lighting for small homes is analyzed, and their general characteristics and technologies are synthesized. The literature and product overview identified five significant product knowledge gaps. Incorporating the gathered information leads to the proposal of a conceptual flexible radar-based sensor (prototype design), addressing a wish list with three important criteria to optimize future presence sensing lighting in a mixed-function small home. Future radar sensing studies are expected to develop an anticipatory lighting system that processes real-time multi-user vital signals for smarter localized and personalized lighting options for (small) living environments.
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This work utilizes Sentinel-2A L1C remote sensing photographs from the years 2018, 2020, and 2022 to identify the different land use categories in the study area using the support vector machine (SVM) technique. The accuracy of categorization is greater than 90%. This research explores four factors of the dynamic change in land use in Hongta District from 2018 to 2022: the proportion of various types of land;the extent of something like the changing land usage;land use transfer;and the dynamic degree of the change in land use. According to the study's results, the proportion of cultivated and grassland land grew, while the quantity of barren and construction land fell by 1.90 percent, 0.03 percent, and 0.69 percent, respectively. The water system land portion of total area increased by 2.58 percent and 0.13 percent, respectively. After comparing the two research periods, the entire dynamic degree of the second stage is determined to be 3.5 percent lower than that of the first stage, and the pace of land use change is quite sluggish, which may be associated with the worldwide COVID-19 outbreak in 2020. The outcomes of the research may give the natural resources department the knowledge it needs to manage land resources properly. © 2023 SPIE.
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Aims: A proof-of- concept pilot investigating the profile of person who engaged with remote testing for their annual diabetes review, and service user (SU) and primary care practice acceptability for completing annual diabetes review tests remotely (blood pressure, finger-stick blood test and urine test). Method(s): A mixed methods evaluation based on SU surveys sent to all 144 pilot participants, semi-structured SU and staff interviews, and demographic and clinical data extraction from primary care electronic patient record system. Result(s): Profile: The pathway was considered suitable for people who were working, digitally capable, younger, had household support to complete the tests, had non-complex diabetes, or a combination of these attributes. It was deemed less suitable for the very elderly, the less digitally capable, those with complex health needs or socially isolated. SU Acceptability: Interviewees and survey respondents overall deemed the remote tests acceptable for use. Convenience and reduced exposure to Covid-19 were motivating factors for participation. Preference for face-to- face care or concerns around using digital technologies were key reasons for decline. Staff Acceptability: The pathway was deemed acceptable and was successfully implemented at both practices. Support from a designated pathway co-ordinator and project manager were key factors linked to acceptability and success. The remote pathway was seen as an opportunity to reduce primary care pressures on in-person care. Conclusion(s): It is possible to successfully conduct annual diabetes reviews remotely. Although not appropriate nor desirable to everyone, remote testing provides a viable alternative to in-person testing for certain individuals.
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Adding to the already polarizing 2020 general election was the COVID-19 pandemic. One way in which this pandemic greatly affected the election was through an increased participation in by-mail, or mail-in, ballots. The state of North Carolina experienced a 316 percent increase in by-mail votes between 2016 and 2020, when approximately 977,186 votes were cast by mail. It is no surprise that this increase was due to the COVID-19 pandemic;however, these by-mail voting patterns are spatial in nature and vary across the state. This research measures to what degree COVID-19 rates affected by-mail voting rates. Using geographic information systems data developed from robust tabular files provided by the North Carolina State Board of Elections, by-mail votes were calculated and mapped at ZIP code scale and compared to COVID-19 rates measured at different dates. By-mail rates taken from final absentee tallies for the highest and lowest COVID-19 ZIP codes saw no significant differences across multiple dates (30 September 2020 and 31 October 2020) when COVID-19 data were collected. COVID-19 hot spots (high COVID-19 rates surrounded by other high COVID-19 rates) were extracted using geostatistical techniques and compared to COVID-19 cold spots (low COVID-19 rates surrounded by other low COVID-19 rates). It was found the lowest by-mail rates actually occurred in these COVID-19 hot spots across both dates, as well a metric that expressed percentage change in COVID-19 rates in the month before the 2020 election.Alternate :COVID-19使得已经两极分化的2020年美国大选, 变得更加雪上加霜。COVID-19影响选举的一种方式是邮寄选票的增加。2016年至2020年, 北卡罗来纳州的邮寄选票增加了316%, 共约977,186张。毫无疑问, COVID-19导致了邮寄选票的增加。然而, 邮寄选票在本质上是空间性的, 并且在北卡罗来纳州的各个地方具有差异性。本研究计算了COVID-19发病率对邮寄选票比例的影响程度。利用北卡罗来纳州选举委员会提供的准确的表格文件, 本文制作了地理信息系统数据, 在邮政编码尺度上对邮寄选票进行计算和制图, 并将这些邮寄选票与不同时间的COVID-19发病率进行了比较。在拥有最高和最低COVID-19发病率的邮政编码和不同时间（2020年9月30日和2020年10月31日）, 从缺失人数统计中得到的邮寄选票比例没有显著差异。利用地学统计方法提取COVID-19热点（COVID-19高发病率在空间上被其它高发病率所包围）, 并与COVID-19冷点（COVID-19低发病率在空间上被其它低发病率所包围）进行比较。结果发现, 在这两个时间内, 最低邮寄选票比例出现在COVID-19热点地区。本文还制定了一个指标, 可以表示2020年大选前一个月的COVID-19发病率百分比的变化。
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The results of a preliminary analysis of the relationship between the short-term impact of air pollution exposure on hospitalizations associated with COVID-19 in Tomsk, Russia are presented. The statistical data on air pollution and COVID-19 associated hospitalization were collected and analyzed for the period from March 16, 2022 to April 14, 2022. This period corresponds to a flat plateau of confirmed COVID-19 cases after the main pandemic wave in 2022 in Tomsk and the Tomsk region which were associated with omicron strain of SARS-CoV-2. It was found that all representative peaks in a graph of daily hospitalizations coincide with the peaks in graphs of measured levels of air pollution. The increase in hospitalizations occurred on the same days when air pollution levels increased, or with a slight lag of 1-2 days. This allows us to tentatively conclude that air pollution has a quick effect on infected persons and may provoke an increase in symptoms and severity of the disease. Further detailed research is required. © 2022 SPIE.
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Non-grain production (NGP) on cultivated land has become a common phenomenon due to the prosperity of the rural economy and the optimisation of the agricultural structure. However, the excessive use of cultivating land for NGP has threatened food production and the sustainable use of cultivated land. To halt this trend and to ensure food security, the authors of this paper applied a novel non-grain index to measure NGP, which could reflect multiple NGP activities;designated Hubei Province as its object of research;and revealed NGP's spatio-temporal patterns of the past 30 years. We then assessed the characteristics of NGP based on spatial autocorrelation analysis, the Theil index, and geographically weighted regression. The results showed that the value of the non-grain index grew from 0.497 to 1.113 as NGP increased significantly in Hubei Province. The number of high-NGP counties increased, spatial agglomeration became obvious, and the eastern and western sides of Hubei Province witnessed an observable growth in NGP. As a result, the NGP in the eastern and western regions overtook production in the central region. Despite a series of historical subsidy policies and agricultural modernisation initiatives that promoted the planting of grain crops, the policy of "grain on valuable cultivated land” could be better implemented. We conclude by making some suggestions for reducing NGP and protecting cultivated land.
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Annotation. The aim of this study was to investigate the learning styles of prospective biology teachers in Islamic universities (PBTs-IU) in Indonesia during the COVID-19 pandemic. 195 PBTs-IU were surveyed by using the Felder-Silverman Learning Style instruments. The results show that in online learning PBTs-IU practice and like dimensions of learning styles, such as in active – social oriented learning, in sensing – existing ways, concrete material, careful with details, in visual – pictures, and in sequential – sequential progress. © 2023, Vilnius Pedagogical University. All rights reserved.
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Nowadays, spatial geographic data analysis and GIS related software are more and more applied to the planning of urban public facilities. Under the COVID-19, people pay more attention to the protection of medical facilities for people's health, and a reasonable distribution of hospital facilities is conducive to people's health. Taking Haikou City as an example, this research will optimize the location of hospital space layout according to the existing third-level first-class general hospitals in Haikou City by using GIS software, road analysis, spatial analysis, and other methods. The results show that the existing hospitals in Haikou are too concentrated in the central urban area, the overall distribution of medical facilities is lack of balance, and there is a serious lack of medical facilities in new urban development areas and suburbs. According to the comparison between population density analysis and traffic analysis and the service scope of existing hospitals, the author finds out the scope of hospitals that need to be supplemented, and then calculates the scope of service area after taking several random points within the scope, and finally finds the one with the largest service scope is the optimal location. The results obtained by optimizing the site selection can provide a scientific reference for the rational layout of medical facilities in Haikou City in the future. © 2023 SPIE.
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Data collection and large-scale urban audits are challenging and can be time consuming processes. Geographic information systems can extract and combine relevant data that can be used as input to calculation tools that provide results and quantify indicators with sufficient spatial analysis to facilitate the local decision-making process for building renovations and sustainability assessment. This work presents an open-access tool that offers an automated process that can be used to audit an urban area in order to extract relevant information about the characteristics of the built environment, analyze the building characteristics to evaluate energy performance, assess the potential for the installation of photovoltaics on available building rooftops, and quantify ground permeability. A case study is also presented to demonstrate data collection and processing for an urban city block, and the relevant results are elaborated upon. The method is easily replicable and is based on open data and non-commercial tools.
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Wearable sensor technologies have improved people's daily lives through their applications in almost every field. Sensor technologies of inventive kinds are used in an extensive variety of applications in lifestyle, healthcare, fitness, manufacturing, etc. There have also been crucial issues in making significant improvements to the actual mechanical, electrical, and optical sensing methods mainly in upgrading the precision of identification of wearable sensors to various stimuli. With an extensive study of the basic demands in wearable device technology as of now, the road map becomes clearer for creating greater innovations in the future. This is a review that gives an outline of types of wearable sensors by the score that is utilized in daily life. © 2023 IEEE.
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The title of the ConferenceXXII Conference of PhD Students and Young Scientists "Interdisciplinary topics in mining and geology”The location and the date of the conferencevirtual event – online conference, June 29th to July 1st, 2022 in Wrocław, PolandXXIInd Conference of PhD Students and Young Scientists "Interdisciplinary topics in mining and geology” continues a series of events that started in 2000 at Wrocław University of Science and Technology. Scientific programme of the Conference focuses on four thematic panels:1. Mining Engineering: sustainable development, digitalisation in mining, problems of securing, protecting and using remnants of old mining works, underground mining, opencast mining, mineral processing, waste management, mining machinery, mine transport, economics in mining, mining aeronautics, ventilation and air conditioning in mines,2. Earth and Space Sciences: geology, hydrogeology, environmental protection, extraterrestrial resources, groundwater and medicinal waters, engineering and environmental protection, geotourism,3. Geoengineering: environmental protection, applied geotechnics, rock and soil mechanics, geohazards,4. Geoinformation: mining geodesy, GIS, photogrammetry and remote sensing, geodata modeling and analysis.The XXII Conference of PhD Students and Young Scientists was held as a virtual event, that is as a virtual, online conference in real-time. The reason why the Organizing Committee decided to change the traditional formula of the event to online formula was related to the concern for the health of the participants due to the COVID-19 epidemic.The XXII Conference of PhD Students and Young Scientists took place from June 29th to July 1st, 2022 in Wroclaw, Poland. That is the organizers worked and managed the event from the Wrocław University of Science and Technology Geocentre building. Because the conference focused on four thematic panels, four different special opening lectures were delivered by wellknown scientists- Professor Jan Zalasiewicz (University of Leicester, England)- Associate Professor Artur Krawczyk (AGH University of Science and Technology, Poland)- Professor Biljana Kovacević-Zelić (University of Zagreb, Croatia)- Assistant Professor Eduard Kan (Tashkent Institute of Irrigation and Agricultural Mechanizations Engineers, Uzbekistan).The Conference was divided into 8 oral sessions (with 33 presentations) and 1 poster session (with 33 posters). The amount of time provided to one presentation was 15 minutes, after presentation there was 5 minutes available for discussion. The poster session was available throughout the event, and the posters were available for online viewing on the Conference's website with the possibility of make discussion and ask questions in real time via zoom meeting application as well. Every day of the Conference one "virtual coffee break” was devoted for discussion between participants and question and answer session for the Organizers.There were 96 registered participants from 13 countries. The online XXII Conference of PhD Students and Young Scientists was conducted using the Zoom meeting platform with commemorative screen shots taken. By tradition two competitions, for the best oral presentation and for the best poster were held. The award for the best oral presentation was given ex aequo to Julia Tiganj (TH Georg Agricola University of Applied Sciences, Germany) for the presentation entitled Post-mining goes international: hurdles to climate neutrality using the example of China and Oksana Khomiak, Jörg Benndorf (TU Bergakademie Freiberg, Germany) for the presentation entitled Spectral analysis of ore hyperspectral images at different stages of the mining value chain, whereas the best poster was awarded to Adam Wróblewski, Jacek Wodecki, Paweł Trybała, Radosław Zimroz (Wrocław University of Science and technology, Poland) for the poster entitled Large underground structures geometry evaluation based on point cloud data analysis.List of Scientific Committee, Organizing Committee, Editorial Team are available i this pdf.
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Land surface temperature (LST) is an important variable in urban microclimate research. At the end of 2019, the emergence of Covid-19 pandemic has changed the world in a manner that forced many countries to impose restrictions in human activities. As a measure to prevent the expansion of Covid-19 infections, most of the major cities have entered a prolonged lockdown period and reduction in human activities between the early 2020 and the late 2021. These restrictions were strict in most of the cities in Southeast Asia, particularly in Vietnam. The present study investigated the variations in LST and NDVI observed in three rapidly growing urban areas, namely Da Nang, Hue and Vinh, in Vietnam using Landsat-8 imagery acquired between 2017 and 2022. There has been a slight reduction in LST in the study sites, particularly in Da Nang City, during the lockdown period but not as high as observed in recently conducted studies from big metropolitan cities, including in Vietnam. It is also observed that LST estimated from built-up areas and other impervious surfaces remained relatively stable during the study period which is similar to the results from recent studies.
Subject(s)
COVID-19 , Urbanization , Humans , Cities , Temperature , Hot Temperature , Vietnam/epidemiology , Pandemics , Environmental Monitoring/methods , COVID-19/epidemiology , Communicable Disease ControlABSTRACT
Field-effect transistor (FET) is regarded as the most promising candidate for the next-generation biosensor, benefiting from the advantages of label-free, easy operation, low cost, easy integration, and direct detection of biomarkers in liquid environments. With the burgeoning advances in nanotechnology and biotechnology, researchers are trying to improve the sensitivity of FET biosensors and broaden their application scenarios from multiple strategies. In order to enable researchers to understand and apply FET biosensors deeply, focusing on the multidisciplinary technical details, the iteration and evolution of FET biosensors are reviewed from exploring the sensing mechanism in detecting biomolecules (research direction 1), the response signal type (research direction 2), the sensing performance optimization (research direction 3), and the integration strategy (research direction 4). Aiming at each research direction, forward perspectives and dialectical evaluations are summarized to enlighten rewarding investigations.
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Biosensing Techniques , Transistors, Electronic , Nanotechnology , Biosensing Techniques/methodsABSTRACT
The ability to estimate the current mood states of web users has considerable potential for realizing user-centric opportune services in pervasive computing. However, it is difficult to determine the data type used for such estimation and collect the ground truth of such mood states. Therefore, we built a model to estimate the mood states from search-query data in an easy-to-collect and non-invasive manner. Then, we built a model to estimate mood states from mobile sensor data as another estimation model and supplemented its output to the ground-truth label of the model estimated from search queries. This novel two-step model building contributed to boosting the performance of estimating the mood states of web users. Our system was also deployed in the commercial stack, and large-scale data analysis with >11 million users was conducted. We proposed a nationwide mood score, which bundles the mood values of users across the country. It shows the daily and weekly rhythm of people's moods and explains the ups and downs of moods during the COVID-19 pandemic, which is inversely synchronized to the number of new COVID-19 cases. It detects big news that simultaneously affects the mood states of many users, even under fine-grained time resolution, such as the order of hours. In addition, we identified a certain class of advertisements that indicated a clear tendency in the mood of the users who clicked such advertisements.
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Smartphone use provides a significant amount of screen-time for youth, and there have been growing concerns regarding its impact on their mental health. While time spent in a passive manner on the device is frequently considered deleterious, more active engagement with the phone might be protective for mental health. Recent developments in mobile sensing technology provide a unique opportunity to examine behaviour in a naturalistic manner. The present study sought to investigate, in a sample of 451 individuals (mean age 20.97 years old, 83% female), whether the amount of time spent on the device, an indicator of passive smartphone use, would be associated with worse mental health in youth and whether an active form of smartphone use, namely frequent checking of the device, would be associated with better outcomes. The findings highlight that overall time spent on the smartphone was associated with more pronounced internalizing and externalizing symptoms in youth, while the number of unlocks was associated with fewer internalizing symptoms. For externalizing symptoms, there was also a significant interaction between the two types of smartphone use observed. Using objective measures, our results suggest interventions targeting passive smartphone use may contribute to improving the mental health of youth.
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Rapid, easy-to-use, and low-cost systems for biological sample testing are important for point-of-care diagnostics and various other health applications. The recent pandemic of Coronavirus Disease 2019 (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) showed an urgent need to rapidly and accurately identify the genetic material of SARS-CoV-2, an enveloped ribonucleic acid (RNA) virus, in upper respiratory specimens from people. In general, sensitive testing methods require genetic material extraction from the specimen. Unfortunately, current commercially available extraction kits are expensive and involve time-consuming and laborious extraction procedures. To overcome the difficulties associated with common extraction methods, we propose a simple enzymatic assay for the nucleic acid extraction step using heat mediation to improve the polymerase chain reaction (PCR) reaction sensitivity. Our protocol was tested on Human Coronavirus 229E (HCoV-229E) as an example, which comes from the large coronaviridae family of viruses that affect birds, amphibians, and mammals, of which SARS-CoV-2 is a member. The proposed assay was performed using a low-cost, custom-made, real-time PCR system that incorporates thermal cycling and fluorescence detection. It had fully customizable reaction settings to allow versatile biological sample testing for various applications, including point-of-care medical diagnosis, food and water quality testing, and emergency health situations. Our results show that heat-mediated RNA extraction is a viable extraction method when compared to commercial extraction kits. Further, our study showed that extraction has a direct impact on purified laboratory samples of HCoV-229E, but no direct impact on infected human cells. This is clinically relevant, as it allows us to circumvent the extraction step on clinical samples when using PCR.
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COVID-19 , Nucleic Acids , Animals , Humans , Real-Time Polymerase Chain Reaction , RNA , COVID-19/diagnosis , SARS-CoV-2/genetics , Mammals , COVID-19 TestingABSTRACT
Carbon dots (CDs) or carbon quantum dots (CQDs) have emerged as rising stars in the carbon family due to their diverse applications in various fields. CDs are spherical particles with a well-distributed size of less than 10 nm. Functional CDs are promising nanomaterials with low toxicity, low cost, and enormous applications in the field of bioimaging, optoelectronics, photocatalysis, and sensing. Plastic is non-biodegradable and hazardous to the environment, however extremely durable and used in abundance. During the COVID-19 pandemic, the use of plastic waste, particularly masks, goggles, face shields, and shoe cover, has increased tremendously. It needs to be recycled in a productive way as plastic wastes take hundreds or thousands of years to degrade naturally. The conversion of plastic waste into magnificent CDs has been reported as one of the key alternatives for environmental sustainability and socio-economic benefits. In this review, synthetic routes for the conversion of plastic wastes into CDs utilizing hydrothermal, solvothermal, pyrolysis, flash joule heating, and characterization of these CDs using different techniques, such as Fourier-transform infrared spectroscopy, Raman spectroscopy, X-ray diffraction, and transmission electron microscope, have been discussed. Furthermore, potential applications of these plastic-derived CDs in sensing, catalysis, agronomics, and LED lights are summarized herein.
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Open source Geographic Information System (GIS) have been fostering spatial data research such as Earth observation and environmental monitoring for more than 30 years. More recently, globally available geospatial information combined with web technologies are providing new environments and tools for data handling. Thus, binding the mapping and processing capabilities of traditional GIS to the accessibility and reliability of web-based data providers can bring new opportunities for research. In this paper, we built a QGIS plugin to explore the integration of different public data providers in Brazil along with field data produced by the BONDS project. The biOdiversity conservatioN with Development in Amazon wetlandS project (BONDS) proposes to develop biodiversity scenarios for the Amazonian floodplains aiming to support solutions to preserve biodiversity and ecosystem services. The use of web services enabled dynamic and fast access to several products ranging from remote sensing images, land use and land cover, territorial cartography, water quality, to COVID-19 health data, and more. © 2022 National Institute for Space Research, INPE. All rights reserved.