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Persistent overuse of water supplies from the Colorado River during recent decades has substantially depleted large storage reservoirs and triggered mandatory cutbacks in water use. The river holds critical importance to more than 40 million people and more than two million hectares of cropland. Therefore, a full accounting of where the river’s water goes en route to its delta is necessary. Detailed knowledge of how and where the river’s water is used can aid design of strategies and plans for bringing water use into balance with available supplies. Here we apply authoritative primary data sources and modeled crop and riparian/wetland evapotranspiration estimates to compile a water budget based on average consumptive water use during 2000–2019. Overall water consumption includes both direct human uses in the municipal, commercial, industrial, and agricultural sectors, as well as indirect water losses to reservoir evaporation and water consumed through riparian/wetland evapotranspiration. Irrigated agriculture is responsible for 74% of direct human uses and 52% of overall water consumption. Water consumed for agriculture amounts to three times all other direct uses combined. Cattle feed crops including alfalfa and other grass hays account for 46% of all direct water consumption.

Tasks such as semantic search and clustering on crisis-related social media texts enhance our comprehension of crisis discourse, aiding decision-making and targeted interventions. Pre-trained language models have advanced performance in crisis informatics, but their contextual embeddings lack semantic meaningfulness. Although the CrisisTransformers family includes a sentence encoder to address the semanticity issue, it remains monolingual, processing only English texts. Furthermore, employing separate models for different languages leads to embeddings in distinct vector spaces, introducing challenges when comparing semantic similarities between multi-lingual texts. Therefore, we propose multi-lingual sentence encoders (CT-XLMR-SE and CT-mBERT-SE) that embed crisis-related social media texts for over 50 languages, such that texts with similar meanings are in close proximity within the same vector space, irrespective of language diversity. Results in sentence encoding and sentence matching tasks are promising, suggesting these models could serve as robust baselines when embedding multi-lingual crisis-related social media texts. The models are publicly available at: https://huggingface.co/crisistransformers., Comment: Accepted to ISCRAM 2024

COVID-19 pandemic has brought unprecedented challenges to the world, and vaccination has been a key strategy to combat the disease. Since Twitter is one of the most widely used public microblogging platforms, researchers have analysed COVID-19 vaccines and vaccination Twitter discourse to explore the conversational dynamics around the topic. While contributing to the crisis informatics literature, we curate a large-scale geotagged Twitter dataset, GeoCovaxTweets Extended, and explore the discourse through multiple spatiotemporal analyses. This dataset covers a longer time span of 38 months, from the announcement of the first vaccine to the availability of booster doses. Results show that 43.4% of the collected tweets, although containing phrases and keywords related to vaccines and vaccinations, were unrelated to the COVID-19 context. In total, 23.1% of the discussions on vaccines and vaccinations were classified as Pro, 16% as Hesitant, 11.4% as Anti, and 6.1% as Informative. The trend shifted towards Pro and Informative tweets globally as vaccination programs progressed, indicating a change in the public's perception of COVID-19 vaccines and vaccination. Furthermore, we explored the discourse based on account attributes, i.e., followers counts and tweet counts. Results show a significant pattern of discourse differences. Our findings highlight the potential of harnessing a large-scale geotagged Twitter dataset to understand global public health communication and to inform targeted interventions aimed at addressing vaccine hesitancy.

Persistent overuse of water supplies from the Colorado River during recent decades has substantially depleted large storage reservoirs and triggered mandatory cutbacks in water use. The river holds critical importance to more than 40 million people and more than two million hectares of cropland. Therefore, a full accounting of where the river’s water goes en route to its delta is necessary. Detailed knowledge of how and where the river’s water is used can aid design of strategies and plans for bringing water use into balance with available supplies. Here we apply authoritative primary data sources and modeled crop and riparian/wetland evapotranspiration estimates to compile a water budget based on average consumptive water use during 2000–2019. Overall water consumption includes both direct human uses in the municipal, commercial, industrial, and agricultural sectors, as well as indirect water losses to reservoir evaporation and water consumed through riparian/wetland evapotranspiration. Irrigated agriculture is responsible for 74% of direct human uses and 52% of overall water consumption. Water consumed for agriculture amounts to three times all other direct uses combined. Cattle feed crops including alfalfa and other grass hays account for 46% of all direct water consumption.

During times of crisis, social media platforms play a vital role in facilitating communication and coordinating resources. Amidst chaos and uncertainty, communities often rely on these platforms to share urgent pleas for help, extend support, and organize relief efforts. However, the sheer volume of conversations during such periods, which can escalate to unprecedented levels, necessitates the automated identification and matching of requests and offers to streamline relief operations. This study addresses the challenge of efficiently identifying and matching assistance requests and offers on social media platforms during emergencies. We propose CReMa (Crisis Response Matcher), a systematic approach that integrates textual, temporal, and spatial features for multi-lingual request-offer matching. By leveraging CrisisTransformers, a set of pre-trained models specific to crises, and a cross-lingual embedding space, our methodology enhances the identification and matching tasks while outperforming strong baselines such as RoBERTa, MPNet, and BERTweet, in classification tasks, and Universal Sentence Encoder, Sentence Transformers in crisis embeddings generation tasks. We introduce a novel multi-lingual dataset that simulates scenarios of help-seeking and offering assistance on social media across the 16 most commonly used languages in Australia. We conduct comprehensive cross-lingual experiments across these 16 languages, also while examining trade-offs between multiple vector search strategies and accuracy. Additionally, we analyze a million-scale geotagged global dataset to comprehend patterns in relation to seeking help and offering assistance on social media. Overall, these contributions advance the field of crisis informatics and provide benchmarks for future research in the area., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Hermetic storage systems are used around the world to reduce stored product losses. Scavenging residual oxygen in hermetic containers can further enhance their effectiveness in minimizing stored commodity losses. Our objective was to assess the effectiveness of germinating seeds of soybeans, rice, cowpeas, and corn in scavenging oxygen. There were six germination stages: seeds soaked for 24 h and allowed to grow for 1, 2, 3, 4, 5, or 6 days (T1 to T6). Oxygen consumption was monitored for 30 h. Root length, the weight of mobilized seed reserve, and visual fungal growth were also assessed. The results showed that cowpeas in their fourth (T4), fifth (T5), and sixth (T6) germination stages were the most effective in scavenging oxygen to below 5% after only 12 h. Corn in its fifth (T5) germination stage took twice the time (24 h) of cowpeas (T4–T6) to reach 5%. Hypoxia affected the growth of radicle length and seed reserve mobilization in all crops except soybeans. Very minimal fungal growth was observed on germinating cowpea seeds under hermetic conditions. The fourth stage (T4) of germinating cowpeas has more potential as an oxygen scavenger because it requires less time to grow, and the seeds are easy to handle. Further research is needed to understand the role of seed weight and sizes, crop varieties, and genetic mechanisms that govern rapid oxygen consumption by germinating seeds among crops. Harnessing seeds as oxygen scavengers to reduce storage losses holds the promise of advancing the sustainable utilization of resources on smallholder farms.

Ixodes ricinus ticks are Scandinavia's main vector for tick-borne encephalitis virus (TBEV), which infects many people annually. The aims of the present study were (i) to obtain information on the TBEV prevalence in host-seeking I. ricinus collected within the Øresund-Kattegat-Skagerrak (ØKS) region, which lies in southern Norway, southern Sweden and Denmark; (ii) to analyse whether there are potential spatial patterns in the TBEV prevalence; and (iii) to understand the relationship between TBEV prevalence and meteorological factors in southern Scandinavia. Tick nymphs were collected in 2016, in southern Scandinavia, and screened for TBEV, using pools of 10 nymphs, with RT real-time PCR, and positive samples were confirmed with pyrosequencing. Spatial autocorrelation and cluster analysis was performed with Global Moran's I and SatScan to test for spatial patterns and potential local clusters of the TBEV pool prevalence at each of the 50 sites. A climatic analysis was made to correlate parameters such as minimum, mean and maximum temperature, relative humidity and saturation deficit with TBEV pool prevalence. The climatic data were acquired from the nearest meteorological stations for 2015 and 2016. This study confirms the presence of TBEV in 12 out of 30 locations in Denmark, where six were from Jutland, three from Zealand and two from Bornholm and Falster counties. In total, five out of nine sites were positive from southern Sweden. TBEV prevalence of 0.7%, 0.5% and 0.5%, in nymphs, was found at three sites along the Oslofjord (two sites) and northern Skåne region (one site), indicating a potential concern for public health. We report an overall estimated TBEV prevalence of 0.1% in questing I. ricinus nymphs in southern Scandinavia with a region-specific prevalence of 0.1% in Denmark, 0.2% in southern Sweden and 0.1% in southeastern Norway. No evidence of a spatial pattern or local clusters was found in the study region. We found a strong correlation between TBE

Irrigated agriculture dominates freshwater consumption globally, but crop production and farm revenues suffer when water supplies are insufficient to meet irrigation needs. In the United States, the mismatch between irrigation demand and freshwater availability has been exacerbated in recent decades due to recurrent droughts, climate change and over extraction that dries rivers and depletes aquifers. Yet, there has been no spatially detailed assessment of the potential for shifting to new crop mixes to reduce crop water demands and alleviate water shortage risks. In this study, we combined modelled crop water requirements and detailed agricultural statistics within a national hydrological model to quantify sub-basin-level river depletion, finding high-to-severe levels of irrigation scarcity in 30% of sub-basins in the western United States, with cattle-feed crops—alfalfa and other hay—being the largest water consumers in 57% of the region’s sub-basins. We also assessed recent trends in irrigation water consumption, crop production and revenue generation in six high-profile farming areas and found that in recent decades, water consumption has decreased in four of our study areas—a result of a reduction in the irrigated area and shifts in the production of the most water-consumptive crops—even while farm revenues increased. To examine the opportunities for crop shifting and fallowing to realize further reductions in water consumption, we performed optimizations on realistic scenarios for modifying crop mixes while sustaining or improving net farm profits, finding that additional water savings of 28–57% are possible across our study areas. These findings demonstrate strong opportunities for economic, food security and environmental co-benefits in irrigated agriculture and provide both hope and direction to regions struggling with water scarcity around the world.

Postharvest processing is a significant contributor to losses in the value chain, dramatically reducing income potential and food security for farmers in Ethiopia. This report seeks to evaluate the challenges and opportunities for improved postharvest processing across a range of selected priority crops in Ethiopia.

Ixodes ricinus ticks are Scandinavia's main vector for tick-borne encephalitis virus (TBEV), which infects many people annually. The aims of the present study were (i) to obtain information on the TBEV prevalence in host-seeking I. ricinus collected within the Øresund-Kattegat-Skagerrak (ØKS) region, which lies in southern Norway, southern Sweden and Denmark; (ii) to analyse whether there are potential spatial patterns in the TBEV prevalence; and (iii) to understand the relationship between TBEV prevalence and meteorological factors in southern Scandinavia. Tick nymphs were collected in 2016, in southern Scandinavia, and screened for TBEV, using pools of 10 nymphs, with RT real-time PCR, and positive samples were confirmed with pyrosequencing. Spatial autocorrelation and cluster analysis was performed with Global Moran's I and SatScan to test for spatial patterns and potential local clusters of the TBEV pool prevalence at each of the 50 sites. A climatic analysis was made to correlate parameters such as minimum, mean and maximum temperature, relative humidity and saturation deficit with TBEV pool prevalence. The climatic data were acquired from the nearest meteorological stations for 2015 and 2016. This study confirms the presence of TBEV in 12 out of 30 locations in Denmark, where six were from Jutland, three from Zealand and two from Bornholm and Falster counties. In total, five out of nine sites were positive from southern Sweden. TBEV prevalence of 0.7%, 0.5% and 0.5%, in nymphs, was found at three sites along the Oslofjord (two sites) and northern Skåne region (one site), indicating a potential concern for public health. We report an overall estimated TBEV prevalence of 0.1% in questing I. ricinus nymphs in southern Scandinavia with a region-specific prevalence of 0.1% in Denmark, 0.2% in southern Sweden and 0.1% in southeastern Norway. No evidence of a spatial pattern or local clusters was found in the study region. We found a strong correlation between TBE

Nitrogen oxides (NOx ≡ NO + NO2) are of central importance for air quality, climate forcing, and nitrogen deposition to ecosystems. The Geostationary Environment Monitoring Spectrometer (GEMS) is now providing hourly NO2 satellite observations over East Asia, offering the first direct measurements of NO2 diurnal variation from space to guide understanding of NOx emissions and chemistry. The NO2 retrieval requires independent vertical profile information from a chemical transport model (CTM) to compute the air mass factor (AMF) that relates the NO2 column measured along the line of sight to the NO2 vertical column. Here, we use aircraft observations from the Korea-United States Air Quality (KORUS-AQ) campaign over the Seoul metropolitan area (SMA) and around the Korean Peninsula in May-June 2016 to better understand the factors controlling the NO2 vertical profile, its diurnal variation, the implications for the AMFs, and the ability of the GEOS-Chem CTM to compute the NO2 vertical profiles used for AMFs. Proper representation of oxidant chemistry is critical for the CTM simulation of NO2 vertical profiles and is achieved in GEOS-Chem through new model developments, including aerosol nitrate photolysis, reduced uptake of hydroperoxy (HO2) radicals by aerosols, and accounting for atmospheric oxidation of volatile chemical products (VCPs). We find that the tropospheric NO2 columns measured from space in the SMA are mainly contributed by the planetary boundary layer (PBL) below 2 km altitude, reflecting the highly polluted conditions. Repeated measurements of NO2 vertical profiles over the SMA at different times of day show that diurnal change in mixing depth affecting the NO2 vertical profile induces a diurnal variation in AMFs of comparable magnitude to the diurnal variation in the NO2 column. GEOS-Chem captures this diurnal variation in AMFs and more generally the variability in the AMFs for the KORUS-AQ NO2 vertical profiles (2.7 % mean bias, 7.6 % precision), with

Social media platforms contain abundant data that can provide comprehensive knowledge of historical and real-time events. During crisis events, the use of social media peaks, as people discuss what they have seen, heard, or felt. Previous studies confirm the usefulness of such socially generated discussions for the public, first responders, and decision-makers to gain a better understanding of events as they unfold at the ground level. This study performs an extensive analysis of COVID-19-related Twitter discussions generated in Australia between January 2020, and October 2022. We explore the Australian Twitterverse by employing state-of-the-art approaches from both supervised and unsupervised domains to perform network analysis, topic modeling, sentiment analysis, and causality analysis. As the presented results provide a comprehensive understanding of the Australian Twitterverse during the COVID-19 pandemic, this study aims to explore the discussion dynamics to aid the development of future automated information systems for epidemic/pandemic management., Comment: Accepted to ISCRAM 2023

The COVID-19 pandemic introduced new norms such as social distancing, face masks, quarantine, lockdowns, travel restrictions, work/study from home, and business closures, to name a few. The pandemic's seriousness made people vocal on social media, especially on microblogs such as Twitter. Researchers have been collecting and sharing large-scale datasets of COVID-19 tweets since the early days of the outbreak. Sharing raw Twitter data with third parties is restricted; users need to hydrate tweet identifiers in a public dataset to re-create the dataset locally. Large-scale datasets that include original tweets, retweets, quotes, and replies have tweets in billions which takes months to hydrate. The existing datasets carry issues related to proportion and redundancy. We report that more than 500 million tweet identifiers point to deleted or protected tweets. In order to address these issues, this paper introduces an enriched global billion-scale English-language COVID-19 tweets dataset, BillionCOV, that contains 1.4 billion tweets originating from 240 countries and territories between October 2019 and April 2022. Importantly, BillionCOV facilitates researchers to filter tweet identifiers for efficient hydration. This paper discusses associated methods to fetch raw Twitter data for a set of tweet identifiers, presents multiple tweets' distributions to provide an overview of BillionCOV, and finally, reviews the dataset's potential use cases.

Social media platforms provide actionable information during crises and pandemic outbreaks. The COVID-19 pandemic has imposed a chronic public health crisis worldwide, with experts considering vaccines as the ultimate prevention to achieve herd immunity against the virus. A proportion of people may turn to social media platforms to oppose vaccines and vaccination, hindering government efforts to eradicate the virus. This paper presents the COVID-19 vaccines and vaccination-specific global geotagged tweets dataset, GeoCovaxTweets, that contains more than 1.8 million tweets, with location information and longer temporal coverage, originating from 233 countries and territories between January 2020 and November 2022. The paper discusses the dataset's curation method and how it can be re-created locally, and later explores the dataset through multiple tweets distributions and briefly discusses its potential use cases. We anticipate that the dataset will assist the researchers in the crisis computing domain to explore the conversational dynamics of COVID-19 vaccines and vaccination Twitter discourse through numerous spatial and temporal dimensions concerning trends, shifts in opinions, misinformation, and anti-vaccination campaigns.

Satellite-based retrievals of tropospheric NO2 columns are widely used to infer NOx (gNOg+gNO2) emissions. These retrievals rely on model information for the vertical distribution of NO2. The free tropospheric background above 2gkm is particularly important because the sensitivity of the retrievals increases with altitude. Free tropospheric NOx also has a strong effect on tropospheric OH and ozone concentrations. Here we use observations from three aircraft campaigns (SEAC4RS, DC3, and ATom) and four atmospheric chemistry models (GEOS-Chem, GMI, TM5, and CAMS) to evaluate the model capabilities for simulating NOx in the free troposphere and attribute it to sources. NO2 measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry (DC3) campaigns over the southeastern U.S. in summer show increasing concentrations in the upper troposphere above 10gkm, which are not replicated by the GEOS-Chem, although the model is consistent with the NO measurements. Using concurrent NO, NO2, and ozone observations from a DC3 flight in a thunderstorm outflow, we show that the NO2 measurements in the upper troposphere are biased high, plausibly due to interference from thermally labile NO2 reservoirs such as peroxynitric acid (HNO4) and methyl peroxy nitrate (MPN). We find that NO2 concentrations calculated from the NO measurements and NO-NO2 photochemical steady state (PSS) are more reliable to evaluate the vertical profiles of NO2 in models. GEOS-Chem reproduces the shape of the PSS-inferred NO2 profiles throughout the troposphere for SEAC4RS and DC3 but overestimates NO2 concentrations by about a factor of 2. The model underestimates MPN and alkyl nitrate concentrations, suggesting missing organic NOx chemistry. On the other hand, the standard GEOS-Chem model underestimates NO observations from the Atmospheric Tomography Mission (ATom) campaigns over the Pacific and Atlan

Werner Syndrome is a rare autosomal recessive condition characterized by premature aging and increased risk of malignancies due to gene mutations associated with DNA stability. We present the first case report of a 29-year-old Hispanic female with WS diagnosed with breast cancer. Diagnostic mammography and ultrasound, breast MRI and PET examinations revealed two lesions biopsy proven as invasive ductal carcinoma. The patient underwent neoadjuvant chemotherapy and radical mastectomy. Recurrence occurred 10 months postoperatively with molecular analysis demonstrating TP53 mutations. The multifactorial assessment of breast cancer in this case study is crucial towards optimizing screening, diagnosis and management of this disease in patients with WS.

Ixodes ricinus ticks are Scandinavia's main vector for tick-borne encephalitis virus (TBEV), which infects many people annually. The aims of the present study were (i) to obtain information on the TBEV prevalence in host-seeking I. ricinus collected within the Øresund-Kattegat-Skagerrak (ØKS) region, which lies in southern Norway, southern Sweden and Denmark; (ii) to analyse whether there are potential spatial patterns in the TBEV prevalence; and (iii) to understand the relationship between TBEV prevalence and meteorological factors in southern Scandinavia. Tick nymphs were collected in 2016, in southern Scandinavia, and screened for TBEV, using pools of 10 nymphs, with RT real-time PCR, and positive samples were confirmed with pyrosequencing. Spatial autocorrelation and cluster analysis was performed with Global Moran's I and SatScan to test for spatial patterns and potential local clusters of the TBEV pool prevalence at each of the 50 sites. A climatic analysis was made to correlate parameters such as minimum, mean and maximum temperature, relative humidity and saturation deficit with TBEV pool prevalence. The climatic data were acquired from the nearest meteorological stations for 2015 and 2016. This study confirms the presence of TBEV in 12 out of 30 locations in Denmark, where six were from Jutland, three from Zealand and two from Bornholm and Falster counties. In total, five out of nine sites were positive from southern Sweden. TBEV prevalence of 0.7%, 0.5% and 0.5%, in nymphs, was found at three sites along the Oslofjord (two sites) and northern Skåne region (one site), indicating a potential concern for public health. We report an overall estimated TBEV prevalence of 0.1% in questing I. ricinus nymphs in southern Scandinavia with a region-specific prevalence of 0.1% in Denmark, 0.2% in southern Sweden and 0.1% in southeastern Norway. No evidence of a spatial pattern or local clusters was found in the study region. We found a strong correlation between TBE

Social media platforms play an essential role in crisis communication, but analyzing crisis-related social media texts is challenging due to their informal nature. Transformer-based pre-trained models like BERT and RoBERTa have shown success in various NLP tasks, but they are not tailored for crisis-related texts. Furthermore, general-purpose sentence encoders are used to generate sentence embeddings, regardless of the textual complexities in crisis-related texts. Advances in applications like text classification, semantic search, and clustering contribute to the effective processing of crisis-related texts, which is essential for emergency responders to gain a comprehensive view of a crisis event, whether historical or real-time. To address these gaps in crisis informatics literature, this study introduces CrisisTransformers, an ensemble of pre-trained language models and sentence encoders trained on an extensive corpus of over 15 billion word tokens from tweets associated with more than 30 crisis events, including disease outbreaks, natural disasters, conflicts, and other critical incidents. We evaluate existing models and CrisisTransformers on 18 crisis-specific public datasets. Our pre-trained models outperform strong baselines across all datasets in classification tasks, and our best-performing sentence encoder improves the state-of-the-art by 17.43% in sentence encoding tasks. Additionally, we investigate the impact of model initialization on convergence and evaluate the significance of domain-specific models in generating semantically meaningful sentence embeddings. The models are publicly available at: https://huggingface.co/crisistransformers

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health1–9. A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-1910–20. Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates., Atmospheric Remote Sensing

Leaf biochemical traits indicating early symptoms of plant stress can be assessed using imaging spectroscopy combined with radiative transfer modelling (RTM). In this study, we assessed the potential applicability of the leaf radiative transfer model Fluspect-Cx to simulate optical properties and estimate leaf biochemical traits through inversion of two native Australian eucalypt species: Eucalyptus dalrympleana and E. delegetensis. The comparison of measured and simulated optical properties revealed the necessity to recalibrate the refractive index and specific absorption coefficients of the eucalypt leaves’ biochemical constituents. Subsequent validation of the modified Fluspect-Cx showed a closer agreement with the spectral measurements. The average root mean square error (RMSE) of reflectance, transmittance and absorptance values within the wavelength interval of 450–1600 nm was smaller than 1%. We compared the performance of both the original and recalibrated Fluspect-Cx versions through inversions aiming to simultaneously retrieve all model inputs from leaf optical properties with and without prior information. The inversion of recalibrated Fluspect-Cx constrained by laboratory-based measurements produced a superior accuracy in estimations of leaf water content (RMSE = 0.0013 cm, NRMSE = 6.55%) and dry matter content (RMSE = 0.0036 g·cm−2, NRMSE = 21.28%). The estimation accuracies of chlorophyll content (RMSE = 8.46 µg·cm−2, NRMSE = 24.73%), carotenoid content (RMSE = 3.83 µg·cm−2, NRMSE = 30.82%) and anthocyanin content (RMSE = 1.69 µg·cm−2, NRMSE = 37.12%) were only marginally better than for the inversion without any constraints. Additionally, we investigated the possibility to substitute the prior information derived in the laboratory by non-destructive reflectance-based spectral indices sensitive to the retrieved biochemical traits, resulting in the most accurate estimation of carotenoid content (RMSE = 3.65 µg·cm−2, NRMSE = 29%). Future coupling of the

Floods pose significant risk to riparian buildings as evidenced during many historical events. Although structural resilience to tsunami flooding is well studied in the literature, high-velocity and debris-laden floods in steep terrains are not considered adequately so far. Historical floods in steep terrains necessitate the need for flood vulnerability analysis of buildings. To this end, we report vulnerability of riparian-reinforced concrete buildings using forensic damage interpretations and empirical/analytical vulnerability analyses. Furthermore, we propose the concept and implications of functionality loss due to flooding in residential reinforced concrete (RC) buildings using empirical data. Fragility functions using inundation depth and momentum flux are presented for RC buildings considering a recent flooding event in Nepal. The results show that flow velocity and sediment load, rather than hydrostatic load, govern the damages in riparian RC buildings. However, at larger inundation depth, hydrostatic force alone may collapse some of the RC buildings.

Floods pose significant risk to riparian buildings as evidenced during many historical events. Although structural resilience to tsunami flooding is well studied in the literature, high-velocity and debris-laden floods in steep terrains are not considered adequately so far. Historical floods in steep terrains necessitate the need for flood vulnerability analysis of buildings. To this end, we report vulnerability of riparian-reinforced concrete buildings using forensic damage interpretations and empirical/analytical vulnerability analyses. Furthermore, we propose the concept and implications of functionality loss due to flooding in residential reinforced concrete (RC) buildings using empirical data. Fragility functions using inundation depth and momentum flux are presented for RC buildings considering a recent flooding event in Nepal. The results show that flow velocity and sediment load, rather than hydrostatic load, govern the damages in riparian RC buildings. However, at larger inundation depth, hydrostatic force alone may collapse some of the RC buildings.

Public conversations on Twitter comprise many pertinent topics including disasters, protests, politics, propaganda, sports, climate change, epidemics/pandemic outbreaks, etc., that can have both regional and global aspects. Spatial discourse analysis rely on geographical data. However, today less than 1% of tweets are geotagged; in both cases--point location or bounding place information. A major issue with tweets is that Twitter users can be at location A and exchange conversations specific to location B, which we call the Location A/B problem. The problem is considered solved if location entities can be classified as either origin locations (Location As) or non-origin locations (Location Bs). In this work, we propose a simple yet effective framework--the True Origin Model--to address the problem that uses machine-level natural language understanding to identify tweets that conceivably contain their origin location information. The model achieves promising accuracy at country (80%), state (67%), city (58%), county (56%) and district (64%) levels with support from a Location Extraction Model as basic as the CoNLL-2003-based RoBERTa. We employ a tweet contexualizer (locBERT) which is one of the core components of the proposed model, to investigate multiple tweets' distributions for understanding Twitter users' tweeting behavior in terms of mentioning origin and non-origin locations. We also highlight a major concern with the currently regarded gold standard test set (ground truth) methodology, introduce a new data set, and identify further research avenues for advancing the area., Comment: To appear in Proceedings of the IEEE Big Data Conference 2022

The rise of social media platforms provides an unbounded, infinitely rich source of aggregate knowledge of the world around us, both historic and real-time, from a human perspective. The greatest challenge we face is how to process and understand this raw and unstructured data, go beyond individual observations and see the "big picture"--the domain of Situation Awareness. We provide an extensive survey of Artificial Intelligence research, focusing on microblog social media data with applications to Situation Awareness, that gives the seminal work and state-of-the-art approaches across six thematic areas: Crime, Disasters, Finance, Physical Environment, Politics, and Health and Population. We provide a novel, unified methodological perspective, identify key results and challenges, and present ongoing research directions., Comment: Accepted to ACM Computing Surveys (CSUR) 2022

Ranju Pokharel,1 Sudha Agrawal,1 Prajwal Pandey,1 Madhab Lamsal2 1Department of Dermatology and Venereology, B.P Koirala Institute of Health Sciences, Dharan, Nepal; 2Department of Biochemistry, B.P Koirala Institute of Health Sciences, Dharan, NepalCorrespondence: Ranju Pokharel, Junior Resident, Department of Dermatology and Venereology, B.P. Koirala Institute of Health Sciences, Dharan, Nepal, Tel +9779860660852, Email ranjupokharel.rp@gmail.comBackground: Chronic plaque psoriasis is a chronic inflammatory skin disorder. Vitamin D has been shown to have effects on keratinocyte differentiation as well as immune regulation in the skin.Objective: The main objective of this study was to assess the 25hydroxyvitamin D [25 (OH) D] level in patients with psoriasis in comparison with healthy control subjects.Materials and Methods: This case–control study included 180 persons (120 cases and 60 age- and sex-matched control subjects) from outpatient department of BPKIHS, a tertiary care hospital in eastern Nepal. Severity of psoriatic skin lesions was assessed using psoriasis area severity index (PASI) scoring. Serum vitamin D level was assessed by chemiluminescent immunoassay.Results: The mean serum 25(OH) D levels in psoriatic patients and controls were 19.57 ± 6.85 ng/mL and 23.63 ± 6.40 ng/mL, respectively. The difference was statistically significant even after adjusting for confounding factors in a multivariate analysis (aOR 2.929, 95% CI 1.376– 6.230). Low serum 25(OH) D levels were negatively associated with the severity of disease (r= − 0.628, P= 0.01).Conclusion: Serum 25(OH) D levels are significantly lower in psoriatic patients than in healthy control subjects. Deficiency of serum 25(OH) D was associated with severity of disease with an inverse relationship with PASI score.Keywords: psoriasis, psoriasis area severity index, 25hydroxyvitamin vitamin D

As of writing this paper, COVID-19 (Coronavirus disease 2019) has spread to more than 220 countries and territories. Following the outbreak, the pandemic's seriousness has made people more active on social media, especially on the microblogging platforms such as Twitter and Weibo. The pandemic-specific discourse has remained on-trend on these platforms for months now. Previous studies have confirmed the contributions of such socially generated conversations towards situational awareness of crisis events. The early forecasts of cases are essential to authorities to estimate the requirements of resources needed to cope with the outgrowths of the virus. Therefore, this study attempts to incorporate the public discourse in the design of forecasting models particularly targeted for the steep-hill region of an ongoing wave. We propose a sentiment-involved topic-based latent variables search methodology for designing forecasting models from publicly available Twitter conversations. As a use case, we implement the proposed methodology on Australian COVID-19 daily cases and Twitter conversations generated within the country. Experimental results: (i) show the presence of latent social media variables that Granger-cause the daily COVID-19 confirmed cases, and (ii) confirm that those variables offer additional prediction capability to forecasting models. Further, the results show that the inclusion of social media variables introduces 48.83--51.38% improvements on RMSE over the baseline models. We also release the large-scale COVID-19 specific geotagged global tweets dataset, MegaGeoCOV, to the public anticipating that the geotagged data of this scale would aid in understanding the conversational dynamics of the pandemic through other spatial and temporal contexts., Comment: Accepted to Applied Soft Computing

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health1–9. A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-1910–20. Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates., Atmospheric Remote Sensing

Tick-borne encephalitis virus (TBEV) is a medically important arbovirus, widespread in Europe and Asia. The virus is primarily transmitted to humans and animals by bites from ticks and, in rare cases, by consumption of unpasteurized dairy products. The aim of this study was to sequence and characterize two TBEV strains with amplicon sequencing by designing overlapping primers. The amplicon sequencing, via Illumina MiSeq, covering nearly the entire TBEV genome, was successful: We retrieved and characterized the complete polyprotein sequence of two TBEV strains, Hochosterwitz and 1993/783 from Austria and Sweden, respectively. In this study the previous phylogenetic analysis of both strains was confirmed to be of the European subtypes of TBEV (TBEV-Eu) by whole genome sequencing. The Hochosterwitz strain clustered with the two strains KrM 93 and KrM 213 from South Korea, and the 1993/783 strain clustered together with the NL/UH strain from the Netherlands. Our study confirms the suitability and rapidness of the high-throughput sequencing method used to produce complete TBEV genomes from TBEV samples of high viral load giving high-molecular-weight cDNA with large overlapping amplicons.

The field of Augmented Reality (AR) and Virtual Reality (VR) has seen massive growth in recent years. Numerous degree programs have started to redesign their curricula to meet the high market demand of such job positions. In this paper, we performed a content analysis of online job postings hosted on Indeed.com and provided a skill classification framework for AR/VR job positions. Furthermore, we present a ranking of the relevant skills for the job position. Overall, we noticed that technical skills like UI/UX design, software design, asset design and graphics rendering are highly desirable for AR/VR positions. Our findings regarding prominent skill categories could be beneficial for the human resource departments as well as enhancing existing course curricula to tailor to the high market demand., Comment: Preprint submitted to Sage

There has been considerable debate about the comparative advantages of marketing education emphasizing theoretical knowledge and applied skills. The current study investigated the skills necessary for entry-level marketing positions, specifically that of Social Media Manager (SMMgr) and Social Media Marketer (SMMkt). Data was collected from Indeed.com using a web crawler to extract job postings for SMMgr and SMMkt. A total of 766 and 654 entry-level jobs for SMMgr and SMMkt, respectively, across the entire United States, was collected. Independent raters separately analyzed the data for keywords and categories. Findings suggest that the most desired skills are occupational digital marketing skills. Other relevant skill categories included communication, employee attributes, problem-solving, and information technology skills. This study extends the current literature by highlighting the desired skills prevalent across the social media industry. The findings also have relevance in designing the marketing education curriculum, specifically in isolating core skills that could be integrated into the marketing courses., Comment: This is the authors original manuscript (preprint) of an article that has been accepted for publication in a future issue of The Journal of Social Media in Society. Content may change prior to final publication

Nitrogen oxides (NOx=NO+NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment - 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36 and 4ĝ€¯km resolutions are in reasonably good agreement with the regional mean temporospatial NO2 observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO2 (O3) surface concentrations during nighttime, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4ĝ€¯km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NOx emissions in the model when the model spatial resolution is increased from 36 to 4ĝ€¯km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4ĝ€¯km model simulations, likely reflecting

The tick-borne encephalitis virus (TBEV), a zoonotic flaviviral infection, is endemic in large parts of Norway and Eurasia. Humans are mainly infected with TBEV via bites from infected ticks. In Norway, the main geographical distribution of ticks is along the Norwegian coastline from southeast (similar to 59 degrees N) and up to the southern parts of Nordland County (similar to 65 degrees N). In this study, we collected ticks by flagging along the coast from ostfold County to Nordland County. By whole-genome sequencing of the mitochondrial genome of Ixodes ricinus, the phylogenetic tree suggests that there is limited phylogeographic structure both in Norway and in Europe. The overall TBEV prevalence is 0.3% for nymphs and 4.3% for adults. The highest estimated TBEV prevalence in adult ticks was detected in Rogaland and Vestfold County, while for nymphs it is highest in Vestfold, Vest-Agder and Rogaland. The present work is one of the largest studies on distribution and prevalence of TBEV in ticks in Scandinavia, showing that the virus is wider distributed in Norway than previously anticipated.

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011-2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed

Nepal has a concentrated epidemic of HIV, and 29,944 people were estimated to be living with HIV in 2018. This descriptive study assesses the relationship between antiretroviral therapy adherence and the selected factors among the people living with HIV using Visual Analogue Scale. Data were collected using structure questionnaires from 183 people living with HIV recruited by systematic random sampling. Approximately 27% of the respondents perceived they had received low social support. Similarly, 55.7% of the respondents perceived their adherence to be less than 95% (suboptimal adherence), whereas 44.3% of the respondents perceived their adherence to be more than 95% (optimal adherence). Age, income, alcohol use, drug use, ART pills per day, taking pills for other diseases and frequency of taking pills were found to be significantly associated with ART adherence. The antiretroviral therapy program in Nepal should be focused on the use of drug regimen with fewer side effects along with fixed-dose combination.

China's policy interventions to reduce the spread of the coronavirus disease 2019 have environmental and economic impacts. Tropospheric nitrogen dioxide indicates economic activities, as nitrogen dioxide is primarily emitted from fossil fuel consumption. Satellite measurements show a 48% drop in tropospheric nitrogen dioxide vertical column densities from the 20 days averaged before the 2020 Lunar New Year to the 20 days averaged after. This decline is 21±5% larger than that from 2015 to 2019. We relate this reduction to two of the government's actions: the announcement of the first report in each province and the date of a province's lockdown. Both actions are associated with nearly the same magnitude of reductions. Our analysis offers insights into the unintended environmental and economic consequences through reduced economic activities., Atmospheric Remote Sensing

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011-2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed

China's policy interventions to reduce the spread of the coronavirus disease 2019 have environmental and economic impacts. Tropospheric nitrogen dioxide indicates economic activities, as nitrogen dioxide is primarily emitted from fossil fuel consumption. Satellite measurements show a 48% drop in tropospheric nitrogen dioxide vertical column densities from the 20 days averaged before the 2020 Lunar New Year to the 20 days averaged after. This decline is 21±5% larger than that from 2015 to 2019. We relate this reduction to two of the government's actions: the announcement of the first report in each province and the date of a province's lockdown. Both actions are associated with nearly the same magnitude of reductions. Our analysis offers insights into the unintended environmental and economic consequences through reduced economic activities., Atmospheric Remote Sensing

Nearly one-sixth of U.S. river basins are unable to consistently meet societal water demands while also providing sufficient water for the environment. Water scarcity is expected to intensify and spread as populations increase, new water demands emerge, and climate changes. Improving water productivity by meeting realistic benchmarks for all water users could allow U.S. communities to expand economic activity and improve environmental flows. Here we utilize a spatially detailed database of water productivity to set realistic benchmarks for over 400 industries and products. We assess unrealized water savings achievable by each industry in each river basin within the conterminous U.S. by bringing all water users up to industry- and region-specific water productivity benchmarks. Some of the most water stressed areas throughout the U.S. West and South have the greatest potential for water savings, with around half of these water savings obtained by improving water productivity in the production of corn, cotton, and alfalfa. By incorporating benchmark-meeting water savings within a national hydrological model (WaSSI), we demonstrate that depletion of river flows across Western U.S. regions can be reduced on average by 6.2-23.2%, without reducing economic production. Lastly, we employ an environmentally extended input-output model to identify the U.S. industries and locations that can make the biggest impact by working with their suppliers to reduce water use 'upstream' in their supply chain. The agriculture and manufacturing sectors have the largest indirect water footprint due to their reliance on water-intensive inputs but these sectors also show the greatest capacity to reduce water consumption throughout their supply chains.

Utsav Acharya, Ritesh Lamsal Department of Anaesthesiology, Tribhuvan University Teaching Hospital, Institute of Medicine, Tribhuvan University, Kathmandu, NepalCorrespondence: Utsav AcharyaDepartment of Anaesthesiology, Tribhuvan University Teaching Hospital, Institute of Medicine, Tribhuvan University, Kathmandu 44600, NepalTel +977 9843613683Fax +977 14473059Email utsav.ach@gmail.comAbstract: Acute subdural hematoma (aSDH) is commonly encountered in the emergency department in patients with traumatic injuries. If the hematoma is small, non-expanding and asymptomatic, it is managed conservatively. However, other injuries sustained during trauma may warrant surgical intervention, during which anesthetic management becomes challenging. There have been reports of rebleeding in patients with aSDH after undergoing surgery under either general or spinal anesthesia. Here we present a case where ankle surgery for tri-malleolar fracture was successfully performed in a patient with traumatic aSDH under combined lumbar plexus and proximal (para-sacral) sciatic nerve block.Keywords: intracranial hemorrhage, regional anesthesia, traumatic brain injury, ultrasound

Nearly one-sixth of U.S. river basins are unable to consistently meet societal water demands while also providing sufficient water for the environment. Water scarcity is expected to intensify and spread as populations increase, new water demands emerge, and climate changes. Improving water productivity by meeting realistic benchmarks for all water users could allow U.S. communities to expand economic activity and improve environmental flows. Here we utilize a spatially detailed database of water productivity to set realistic benchmarks for over 400 industries and products. We assess unrealized water savings achievable by each industry in each river basin within the conterminous U.S. by bringing all water users up to industry- and region-specific water productivity benchmarks. Some of the most water stressed areas throughout the U.S. West and South have the greatest potential for water savings, with around half of these water savings obtained by improving water productivity in the production of corn, cotton, and alfalfa. By incorporating benchmark-meeting water savings within a national hydrological model (WaSSI), we demonstrate that depletion of river flows across Western U.S. regions can be reduced on average by 6.2-23.2%, without reducing economic production. Lastly, we employ an environmentally extended input-output model to identify the U.S. industries and locations that can make the biggest impact by working with their suppliers to reduce water use 'upstream' in their supply chain. The agriculture and manufacturing sectors have the largest indirect water footprint due to their reliance on water-intensive inputs but these sectors also show the greatest capacity to reduce water consumption throughout their supply chains.

The output power of wind and photovoltaic (PV) systems contain fluctuations due to the intermittent nature of solar irradiance and wind speed. It is required to smooth the fluctuated power before supplying it to the grid. Here, a fuzzy-based discrete Kalman filter approach is proposed for smoothing output power fluctuations of the wind and PV generation systems using a battery energy storage system. The proposed approach incorporates the state of health of the battery as a feedback to not only obtain smooth output power but also improve the battery health by adaptively regulating the battery power. The effectiveness of the proposed approach is verified by evaluating the power fluctuation rates and performance indices.

Wind and photovoltaic generation systems possess fluctuating output power due to intermittency in wind speed and solar irradiance which needs to be smoothed before supplying power to the grid for a proper operation. Several power smoothing methods are developed in recent years for wind and photovoltaic systems. This paper presents an extensive review of the output power smoothing methods considering the use of the energy storage system (ESS). In general, the smoothing of fluctuating power is carried out with an ESS such as a battery energy storage system, fuel cell/electrolyzer, superconducting magnetic energy storage, flywheel energy storage system, energy capacitor system as well as without any energy storage system. As the installation and maintenance cost of ESS-based smoothing methods are high, the existing approaches of power smoothing can be broadly categorized into with and without ESS. This paper discusses the merits and demerits of the existing research in power smoothing approaches and proposes key future directions. Moreover, a comparative study of some well-known smoothing techniques is presented for a simple power system with wind, Photovoltaics and batteries.

Higher penetration of intermittent renewable sources such as wind and photovoltaic systems requires an efficient way to manage the fluctuated power before injecting it into the grid. This paper proposes a fuzzy‐based smoothing of the output power of wind and photovoltaic generators in a hybrid power system with batteries. The state of charge of the battery system, as well as the pitch angle of wind turbines, is used to limit the fluctuations of the injected power. A first‐order filter is adaptively adjusted by incorporating changes in the battery power, state of charge, and pitch angle through the use of fuzzy logic. The proposed method is verified for different levels of state of charges, and the simulation results show that the proposed approach produces a better smoothing as compared to other methods.

TROPOspheric Monitoring Instrument (TROPOMI), on-board the Sentinel-5 Precurser satellite, is a nadir-viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near-infrared, and shortwave infrared. From these spectra several important air quality and climate-related atmospheric constituents are retrieved, including nitrogen dioxide (NO2) at unprecedented spatial resolution from a satellite platform. We present the first retrievals of TROPOMI NO2 over the Canadian Oil Sands, contrasting them with observations from the Ozone Monitoring Instrument satellite instrument, and demonstrate TROPOMI's ability to resolve individual plumes and highlight its potential for deriving emissions from individual mining facilities. Further, the first TROPOMI NO2 validation is presented, consisting of aircraft and surface in situ NO2 observations, and ground-based remote-sensing measurements between March and May 2018. Our comparisons show that the TROPOMI NO2 vertical column densities are highly correlated with the aircraft and surface in situ NO2 observations, and the ground-based remote-sensing measurements with a low bias (15–30 %); this bias can be reduced by improved air mass factors.

In this study, a discrete Kalman filter-based approach is presented for minimising the output power fluctuations of wind and photovoltaic systems. The control strategy is based on the change in power fluctuation which is determined by the weighted average of the highest and lowest values of the power fluctuation for each interval of time. A genetic algorithm optimisation approach is utilised to determine the optimal value of weighted average such that the power fluctuation rate is minimum. This study also gives the optimum battery power and its state of charge to achieve smoothing determined by the optimal weighted average. On the basis of this optimum battery power, the specification and configuration of the battery energy storage system are also determined.

The battery energy storage system (BESS) is a popularly used source to smooth the power fluctuation caused by variation of wind speed and solar irradiance. The forecasted data of wind and solar irradiance may contain bias error and does not provide the true power available from wind and photovoltaic generating systems. This study proposes a method based on discrete Kalman filter (DKF) to eliminate the bias error present in the forecasted data so that true power of wind and photovoltaic systems could be predicted. A DKF-based state-space approach is utilised to predict the true power obtained through wind and photovoltaic generating systems. The proposed approach also attenuates the power fluctuation of wind and PVGSs considering the desired power dispatched to the load as well as evaluates the BESS power needed for this purpose.

This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain., Atmospheric Remote Sensing

This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain., Atmospheric Remote Sensing

Exactly how do forest bureaucracies manoeuvre to regain power and maximise benefits in the bewildering legal, financial, and administrative field of forest decentralisation? Based on a review of thirty management plans, stakeholder consultations, intensive interactions with six forest user groups, forest officials, and donor project employees in Nepal, we document the mechanisms of legal-sounding re-centralisation. The central tenet is that bureaucratically established procedures, which are not required by law but treated as if they were, are used to impose regular revisions of community forest management plans. Meagre government or more generous donor budgets financed the revisions. Forest bureaucrats and/or consultants did the work and benefitted financially. None of the approaches, however, lived up to technical, scientific standards or followed stipulated participatory processes. The revised plans were almost identical to their previous versions and differences mostly a result of mere desk exercises to fulfil donor requirements and government orders, at least on paper. While legitimised by a perceived promotion of rational, technical sound, and equitable forest governance, the main function of plan revisions appears to be strengthening or re-establishing the forest bureaucracy's control over community forest resources which allows forest bureaucrats to tap into donor project and forest product value chains.