Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge and Attitudes of Ajman University Dentists towards the Coronavirus (COVID-19)

Background: in December, 2019 corona virus discovered in Wuhan, china as a new viral infection affect respiratory system. It is then distributed throughout the whole word causing death and sickness for huge number of people in most of the countries. This study evaluate Ajman university dental professionals' knowledge and attitudes towards corona virus and the applied strategies for its prevention and treatment. Material and methods: The study done by online questionnaire which distributed to the participants through emails. The questionnaire consists of three parts (demographic, knowledge, and attitudes) towards corona virus which was filled by 297 dentists. Data analyzed by (SPSS, 22V) to revealed study results. Results: study showed that (100%) know the main rout of virus transmission through close contact with the patient and sharing things with patients. However, there is a loss of information towards other way of virus transmission. (78%) of the participants do not know about any medication for corona virus nor a vaccination for it. (76%) they are willing to treat patients with corona however they prefer to do it in hospitals or specialized centers. (95%) of the participants ask for more precautions and preventive measures for dental treatment of corona virus patients. The majority of dental professionals had anxiety towards dental treatment of corona virus. Conclusions: study findings revealed that dental professionals showed good knowledge towards virus transmission, however there are missing information of other ways of transmission. This finding indicates that providing information strategies by health institutions should be updated to enhance information needed for the medical staff. Study showed that infection control should be applied in all dental clinics and high quality of dental materials and instruments for preventive measures should be provided. To avoid dental staff anxiety towards dental treatment of corona virus patients' high standard staff preparation should be provided during dental treatment.
Tailored Algorithms for the Detection of the Atmospheric Boundary Layer Height from Common Automatic Lidars and Ceilometers (ALC)

A detailed understanding of atmospheric boundary layer (ABL) processes is key to improve forecasting of pollution dispersion and cloud dynamics in the context of future climate scenarios. International networks of automatic lidars and ceilometers (ALC) are gathering valuable data that allow for the height of the ABL and its sublayers to be derived in near real time. A new generation of advanced methods to automatically detect the ABL heights now exist. However, diversity in ALC models means these algorithms need to be tailored to instrument-specific capabilities. Here, the advanced algorithm STRATfinder is presented for application to high signal-to-noise ratio (SNR) ALC observations, and results are compared to an automatic algorithm designed for low-SNR measurements (CABAM). The two algorithms are evaluated for application in an operational network setting. Results indicate that the ABL heights derived from low-SNR ALC have increased uncertainty during daytime deep convection, while high-SNR observations can have slightly reduced capabilities in detecting shallow nocturnal layers. Agreement between the ALC-based methods is similar when either is compared to the ABL heights derived from temperature profile data. The two independent methods describe very similar average diurnal and seasonal variations. Hence, high-quality products of ABL heights may soon become possible at national and continental scales.
Two new fish specie of the genus Schistura McClelland (Cypriniformes: Balitoridae) from Western Ghats, India

Schistura nagodiensis an S.sharavathiensis are the new fish species described from Sharavathi river, central Western Ghats. These species are distinct from their closest congeners in Schistura, which are evident from variations in combination of characters such as processus dentiformis, barbels, bars on body, extent of lateral line with pores, marks on lower lip, ray counts, shape of caudal fin, caudal bar, adipose crest, etc. Distinct clusters of Principal Components based on morphometric variables (PCA) further substantiate that these are significantly different from their closest congeners.
How Do Urban Parks Provide Bird Habitats and Birdwatching Service? Evidence from Beijing, China

Parks are an important green infrastructure. Besides other benefits for human and animals, parks provide important bird habitats and accommodate most human-bird interactions in cities. Understanding the complex dynamics among park characteristics, bird habitats and park attractiveness to birdwatchers will inform park designers and managers. However, previous studies often examined factors influencing bird habitats and birdwatching activities separately. To fill this gap, we aim to study the whole picture of “parks, birds and birdwatchers” in Beijing, China for its spatial patterns and possible factors which influence bird habitat areas and birdwatching services. We conducted a three-month bird census in at 159 sites and mapped bird habitat areas in parks of Beijing through the maximum entropy method based on results of the bird survey as well as high-resolution remote sensing data. We derived the number of birdwatching records to describe birdwatching activities from the China Birdwatching Record Center website. We used correlation analysis, regression and analysis of variance to investigate factors that may influence areas of bird habitats and the number of birdwatching records for each park. Our results showed that among the 102 parks, 61 provide habitats to breeding birds with an average of 17 ha, and 26 parks generated a total of 330 birdwatching records. Park size, age, proportion of pavement, landscape connectedness, pavement largest patch index and woodland patch density explained 95% of the variation in habitat areas altogether. Bird habitat area alone explained 65% of the variation in the number of birdwatching records. Furthermore, parks with birdwatching records are significantly larger, older, closer to the city center and more accessible than those have no reported birdwatching. These findings have important implications for park management. While park size or age cannot be easily changed, modifying landscape patterns can increase bird habitats in parks, and improving accessibility may attract more birdwatchers to parks that already have considerable bird habitats.
Psychological Effect of the COVID 19 Pandemic on Hospital Health Personnel based on Impact Scales

Faced with pandemic events, health personnel on the front line of care for seriously ill patients with COVID-19 infection, turns out to be vulnerable to mental health problems. Objective: The objective of this review study is to identify the psychological effects of the Coronavirus pandemic on hospital health personnel and the different scales used to assess the psychological impact. Methodology: A systematic literature review was carried out on five search platforms such as PubMed, Elsevier, The Lancet, Google academic and Scielo. Then, apply selection criteria and methodological quality checklists, take 16 articles for data extraction and analysis. Results: All the recognized studies recognize the development of symptoms related to the mental health of the workers who are facing the care of patients with COVID-19, highlighting depression, anxiety and post traumatic stress as effects of greater impact. On the other hand, a diversity of scales used in the articles analyzed was found, the Post-Traumatic Test and the Revised Event Impact Scale standing out. Conclusion: The pandemic caused by COVID-19 is having a negative impact on the mental health of health personnel and there are a variety of validated scales to measure the psychological effect.
Classification of Ice in Lützow-Holm Bay, East Antarctica, Using Data from ASCAT and AMSR2

This paper presents an ice classification algorithm based on combined active and passive microwave radiometer data in Lützow-Holm Bay (LHB), East Antarctica. The ice classification algorithm is developed based on the threshold values of an advanced scatterometer (ASCAT) and advanced microwave scanning radiometer 2 (here, AMSR2). These values are calculated via the features of various ice types, including open ice, first-year (FY) ice, multi-year (MY) ice, MY ice including icebergs (MY IB), ice shelves, coastal ice sheets, and inland ice sheets. To verify the validity of the ice classification algorithm, the algorithm results are compared with visual observation data and satellite imagery. Except for the flaw polynya and area with surface melting, the FY ice, MY ice, and the ice shelf areas estimated here using the proposed ice classification algorithm match those discernible from the verification data. Inter-annual changes in the areal extents of FY ice, MY ice, and the ice shelves are investigated here using the proposed ice classification algorithm. Investigation of MY ice and ice shelf areas revealed that the breakup of MY ice induced a breakup of an ice shelf. A comparison of the FY ice and MY ice areas showed the replacement of these ice types. The proposed ice classification algorithm can detect ice breakup events as quantitative changes in the distribution and ice type. In future work, we plan to classify sea ice in other sea ice areas, applying the proposed algorithm throughout the Antarctic region.
Testing Urban Flood Mapping Approaches from Satellite and In-Situ Data Collected during 2017 and 2019 Events in Eastern Canada

The increasing frequency of flooding worldwide has driven research to improve near real-time flood mapping from remote-sensing data. Improved automation and processing speed to map both open water and vegetated area flooding have resulted from these research efforts. Despite these achievements, flood mapping in urban areas where a significant number of overall impacts are felt remains a challenge. Near real-time data availability, shadowing caused by manmade infrastructure, spatial resolution, and cloud cover inhibiting optical transmission, are all factors that complicate detailed urban flood mapping needed to inform response efforts. This paper uses numerous data sources collected during two major flood events that impacted the same region of Eastern Canada in 2017 and 2019 to test different urban flood mapping approaches presented as case studies in three separate urban boroughs. Cloud-free high-resolution 3 m PlanetLab optical data acquired near peak-flood in 2019 were used to generate a maximum flood extent product for that year. Approaches using new Lidar Digital Elevation Models (DEM)s and water height estimated from nineteen RADARSAT-2 flood maps, point-based flood perimeter observations from citizen geographic information, and simulated traffic camera or other urban sensor network data were tested and verified using independent data. Coherent change detection (CCD) using multi-temporal Interferometric Wide (IW) Sentinel-1 data was also tested. Results indicate that while clear-sky high-resolution optical imagery represents the current gold standard, its availability is not guaranteed due to timely coverage and cloud cover. Water height estimated from 8 to 12.5 m resolution RADARSAT-2 flood perimeters were not sufficiently accurate to flood adjacent urban areas using a Lidar DEM in near real-time, but all nineteen scenes combined captured boroughs that flooded at least once in both flood years. CCD identified flooded boroughs and roughly captured their flood extents, but lacked timeliness and sufficient detail to inform street-level decision-making in near real-time. Point-based flood perimeter observation, whether from in-situ sensors or high-resolution optical satellites combined with Lidar DEMs, can generate accurate full flood extents under certain conditions. Observed point-based flood perimeters on manmade features with low topographic variation produced the most accurate flood extents due to reliable water height estimation from these points.
Potential Lidar Height, Intensity, and Ratio Parameters for Plot Dominant Species Discrimination and Volume Estimation

Precise stand species classification and volume estimation are key research topics for automated forest inventory. This study aims to explore the feasibility of light detection and ranging (lidar) height, intensity, and ratio parameters for discriminating dominant species (Pinus densiflora, Larix kaempferi, and Quercus spp.) and estimating volume at plot scale. To achieve these objectives, multiple linear discriminant and regression analyses were utilized after a separate selection of explanatory variables from extracted 38 lidar height, intensity, and ratio parameters. A kappa accuracy of 0.75 was achieved in discriminating the plot-dominant species from three different species by adopting a combination of nine selected explanatory variables. Further investigation found that dispersion and mean of lidar intensity within a plot are key classifiers of identifying three species. Species-specific optimal plot volume models for Pinus densiflora, Larix kaempferi, and Quercus spp. were evaluated by coefficients of determination of 0.71, 0.74, and 0.56, respectively. Compared to species classification, height-related lidar variables play a key role in modeling forest plot volume. Several explanatory variables for each modeling practice were correlated to canopy vertical and horizontal structures and were enough to represent species-specific characteristics in both approaches for species classification and plot volume estimation. Additionally, observed different variable combinations for two important applications imply that future studies should use proper variable combinations for each purpose.
Leveraging Very-High Spatial Resolution Hyperspectral and Thermal UAV Imageries for Characterizing Diurnal Indicators of Grapevine Physiology

Efficient and accurate methods to monitor crop physiological responses help growers better understand crop physiology and improve crop productivity. In recent years, developments in unmanned aerial vehicles (UAV) and sensor technology have enabled image acquisition at very-high spectral, spatial, and temporal resolutions. However, potential applications and limitations of very-high-resolution (VHR) hyperspectral and thermal UAV imaging for characterization of plant diurnal physiology remain largely unknown, due to issues related to shadow and canopy heterogeneity. In this study, we propose a canopy zone-weighting (CZW) method to leverage the potential of VHR (≤9 cm) hyperspectral and thermal UAV imageries in estimating physiological indicators, such as stomatal conductance (Gs) and steady-state fluorescence (Fs). Diurnal flights and concurrent in-situ measurements were conducted during grapevine growing seasons in 2017 and 2018 in a vineyard in Missouri, USA. We used neural net classifier and the Canny edge detection method to extract pure vine canopy from the hyperspectral and thermal images, respectively. Then, the vine canopy was segmented into three canopy zones (sunlit, nadir, and shaded) using K-means clustering based on the canopy shadow fraction and canopy temperature. Common reflectance-based spectral indices, sun-induced chlorophyll fluorescence (SIF), and simplified canopy water stress index (siCWSI) were computed as image retrievals. Using the coefficient of determination (R2) established between the image retrievals from three canopy zones and the in-situ measurements as a weight factor, weighted image retrievals were calculated and their correlation with in-situ measurements was explored. The results showed that the most frequent and the highest correlations were found for Gs and Fs, with CZW-based Photochemical reflectance index (PRI), SIF, and siCWSI (PRICZW, SIFCZW, and siCWSICZW), respectively. When all flights combined for the given field campaign date, PRICZW, SIFCZW, and siCWSICZW significantly improved the relationship with Gs and Fs. The proposed approach takes full advantage of VHR hyperspectral and thermal UAV imageries, and suggests that the CZW method is simple yet effective in estimating Gs and Fs.
Terrestrial Water Storage Change Retrieved by GRACE and Its Implication in the Tibetan Plateau: Estimating Areal Precipitation in Ungauged Region

The Tibetan Plateau (TP) is referred to as the water tower of Asia, where water storage and precipitation have huge impacts on most major Asian rivers. Based on gravity recovery and climate experiment data, this study analyzed the terrestrial water storage (TWS) changes and estimated areal precipitation based on the water balance equation in four different basins, namely, the upper Yellow River (UYE), the upper Yangtze River (UYA), the Yarlung Zangbo River (YZ), and the Qiangtang Plateau (QT). The results show that the TWS change exhibits different patterns in the four basins and varies from −13 to 2 mm/year from 2003 to 2017. The estimated mean annual precipitation was 260 ± 19 mm/year (QT), 697 ± 26 mm/year (UYA), 541 ± 36 mm/year (UYE), and 1160 ± 39 mm/year (YZ) which performed better than other precipitation products in the TP. It indicates a potential method for estimating basin-scale precipitation through integrating basin average precipitation from the water balance equation in the poorly gauged and ungauged regions.
Reactions of hybrid and parabiontic pseudo-hybrid mice to inoculations of tumor C198.

The following paragraphs report further studies of a transferable hepatic neoplasm (CI98) which was first described in i939 ( i ) . This tumor, which originated spontaneously in an old breeding female of the leaden strain of mice, was first seen in I936 and has been under observation up to the present time. As previously reported, C~98 grows readily in mice of the C57 leaden strain in which it originated but not in mice of other inbred strains. Certain additional experiments, which followed this work and which will be discussed later, frequently altered the natural response of inbred mice of the C57 black strain to injections of tumor CI98. In this way normally resistant mice were made susceptible to the growth of the tumor. As this changed response bore a resemblance to the susceptibility seen in F1 hybrids between the leaden strain and mice of the other strains, we have employed the term "pseudohybrid" to describe such an animal showing an altered response. Previously we used "pseudo-hybrid" in describing the increased susceptibility of descendants of transferred-ova mice 1 to implants of tumors originating in the same strain that was employed as the ova-recipient foster mother strain (2). A pseudo-hybrid could be defined as an inbred animal whose prenatal or postnatal environment has so altered its physiological response (or responses) that a change has occurred to give it some of the characteristics of a hybrid. This change is measurable, at least in part, through the use of transplantable spontaneous tumors to determine the susceptibility of the inbred strain, the pseudo-hybrid, and the true hybrid groups.
A Major Ecosystem Shift in Coastal East African Waters During the 1997/98 Super El Niño as Detected Using Remote Sensing Data

<p>Under the impact of natural and anthropogenic climate variability, upwelling systems are known to change their properties leading to associated regime shifts in marine ecosystems. These often impact commercial fisheries and societies dependent on them. In a region where in situ hydrographic and biological marine data are scarce, this study uses a combination of remote sensing and ocean modelling to show how a stable seasonal upwelling off the Kenyan coast shifted into the territorial waters of neighboring Tanzania under the influence of the unique 1997/ 98 El Ni&#241;o and positive Indian Ocean Dipole event. The formation of an anticyclonic gyre adjacent to the Kenyan/ Tanzanian coast led to a reorganization of the surface currents and caused the southward migration of the Somali&#8211;Zanzibar confluence zone and is attributed to anomalous wind stress curl over the central Indian Ocean. This caused the lowest observed chlorophyll-a over the North Kenya banks (Kenya), while it reached its historical maximum off Dar Es Salaam (Tanzanian waters). We demonstrate that this situation is specific to the 1997/ 98 El Ni&#241;o when compared with other the super El-Ni&#241;o events of 1972,73, 1982&#8211;83 and 2015&#8211;16. Despite the lack of available fishery data in the region, the local ecosystem changes that the shift of this upwelling may have caused are discussed based on the literature. The likely negative impacts on local fish stocks in Kenya, affecting fishers&#8217; livelihoods and food security, and the temporary increase in pelagic fishery species&#8217; productivity in Tanzania are highlighted. Finally, we discuss how satellite observations may assist fisheries management bodies to anticipate low productivity periods, and mitigate their potentially negative economic impacts. </p>
Effect of Different Clipping Treatments on the Yield and Vigor of Prairie Grass Vegetation

Clipping vegetation at different heights and frequencies to imitate various methods of grazing has been rather commonly used to supplement actual grazing experiments. The clipping tests have been especially valuable in determining the effect of the treatments on the yield, succession, and vigor of the vegetation. They may also be used to determine the quality of the vegetation obtained under the different treatments. Where these tests are conducted with actual grazing experiments it is often possible to interpret better, and to evaluate more closely, the results secured from the grazing investigations.
Sentinel-1 SAR Time Series-Based Assessment of the Impact of Severe Salinity Intrusion Events on Spatiotemporal Changes in Distribution of Rice Planting Areas in Coastal Provinces of the Mekong Delta, Vietnam

Food security has become a key global issue due to rapid population growth, extensive conversion of arable lands, and declining overall productivity in some areas because of the effects of floods, water shortage, salinity intrusion, and plant diseases. In this study, we analyzed the relationship between the pattern of salinity intrusion and the spatiotemporal distribution of rice cultivation in the winter–spring crops of 2015, 2016, 2019 and 2020 in coastal provinces of the Vietnamese Mekong Delta. Sentinel-1 (S-1) data were used to extract the spatial distribution information of six rice growth stages based on a rice age algorithm. The classification accuracy of rice crop growth stages was found to have an overall accuracy of 85% and a Kappa coefficient of 0.80 (n = 373). For evaluating salinity intrusion effects, salinity isolines (4 g/L) were used to determine the percentage of rice areas affected. Results show that in the years observed to have severe salinity intrusion such as 2016 and 2020, a strong shift in planting calendar was identified to avoid salinity intrusion, with some areas being sown or transplanted 10–30 days earlier than normal planting. In addition, the lack of irrigation water and salinity intrusion limits rice cultivation in the dry season of coastal areas. Further analysis from the S-1 data confirms that the spatiotemporal distribution of rice cultivation is related to the change in government policy/recommendation affected by salinity intrusion. These findings demonstrate the potential and feasibility of using S-1 data to develop an operational rice crop adaptation framework on the delta scale.