Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration

Background Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualization of 3D histology data, creating a novel interface for digital pathology to aid cancer research. Methods Our contribution includes 3D modeling of a whole organ and embedded objects of interest, fusing the models with associated quantitative features and full resolution serial section patches, and implementing the virtual reality application. Our VR application is multi-scale in nature, covering two object levels representing different ranges of detail, namely organ level and sub-organ level. In addition, the application includes several data layers, including the measured histology image layer and multiple representations of quantitative features computed from the histology. Results In our interactive VR application, the user can set visualization properties, select different samples and features, and interact with various objects, which is not possible in the traditional 2D-image view used in digital pathology. In this work, we used whole mouse prostates (organ level) with prostate cancer tumors (sub-organ objects of interest) as example cases, and included quantitative histological features relevant for tumor biology in the VR model. Conclusions Our application enables a novel way for exploration of high-resolution, multidimensional data for biomedical research purposes, and can also be used in teaching and researcher training. Due to automated processing of the histology data, our application can be easily adopted to visualize other organs and pathologies from various origins.

Knowledge Extraction in Digit Recognition Using MNIST Dataset

In handwriting recognition, traditional systems have relied heavily on handcrafted features and a massive amount of prior data and knowledge. Deep learning techniques have been the focus of research in the field of handwriting digit recognition and have achieved breakthrough performance in the last few years for knowledge extraction and management. KM and knowledge pyramid helps the project with its relationship with big data and IoT. The layers were selected randomly by which the performance of all the cases was found different. Data layers of the knowledge pyramid are formed by the sensors and input devices, whereas knowledge layers are the result of knowledge extraction applied on data layers. The knowledge pyramid and KM helps in making the use of IoT and big data easily. In this manuscript, the knowledge management principles capture the handwritten gestures numerically and get it recognized correctly by the software. The application of AI and DNN has increased the acceptability significantly. The accuracy is better than other available software on the market.

Environmental Impact Assessment (EIA) Using Geographical Information System (GIS): An Integrated Land Suitability Analysis of Filling Stations

A stable methodology for conserving the natural environment has been a concern for developing countries. The fast-paced growth of urbanization generated significant demand for automobiles, leading to greater utilization of fuel. The consumption of fuel is fulfilled by the Filling Station (FS). An FS is undoubtedly an important facility, but it is reported that it has high potential for degradation of natural resources, pollution problems, environmental degradation, and hydrological, geological, and socio-economic hazards, and therefore the site selection of such facilities is an essential problem. The traditional approach utilizes EIA assessments and GIS separately and existing models lacks integration. Thus, this study provides an integrated GIS-based land suitability modeling using EIA assessments, and the Analytic Hierarchy Process (AHP) has been used as key land use feature prioritization for the appropriate selection of FS locations. A case study is also carried out to assess the precision of the suggested model. The findings indicate that more than 73% of the present FS are in the acceptable region, while 27% of the FS are not in the adequate region using the local code. Furthermore, 58% of the present FS are in the acceptable region, while 42% of current FS are not in the adequate region using the international code. The findings of the comparative code analysis show a difference in the codes. The international code looks safer compared to the local code because it has higher buffer distances. This model will assist decision-makers in making better decisions for such land suitability problems for filling stations, and this model can also be extended to other facilities by some modifications in the filters and data layers of the model.

Examining patterns and drivers of variability in playa water status on the High Plains of western Kansas, 2016–2019

Playa wetlands are widely distributed across the High Plains of the central United States, providing a range of ecosystem services, such as groundwater recharge, surface water storage, and wetland habitat. Although playas are essential resources, few studies have examined the variability and controls on playa water storage. The purpose of this project is to determine how playa and watershed morphology, watershed land cover, and precipitation patterns affect timing and duration of water storage in playas. This project focuses on 92 playas distributed throughout a 10-county region in western Kansas. Playa and watershed morphology were calculated in a GIS environment and classified into quartiles based on playa and watershed surface area. Watershed tilled index (i.e., percent cropland versus grassland) was determined using 2016, 2017, 2018, and 2019 Cropland Data Layers available from the National Agricultural Statistics Service and classified as either cropland (more than 75% cropland), grassland (more than 75% grassland), or mixed. Monthly precipitation data for 2016–2019 were compiled from the Oakley 22S High Plains Regional Climate Center weather station. Playa water status for 2016–2019 was classified monthly as either standing water or dry (i.e., no visible standing water) by visually examining four-band satellite imagery with 3.7 m resolution available from Planet Explorer (www.planet.com). Playa water status is influenced by a combination of factors, including playa and watershed morphology, watershed land cover, and precipitation patterns. Larger playas have larger watersheds and standing water more frequently and for longer periods than smaller playas. Playas in cropland watersheds store water more frequently and for longer periods than playas in grassland watersheds, though differences are not statistically significant. Standing water within playas is positively correlated with monthly precipitation and reflects a short-term response to precipitation patterns, regardless of playa size or watershed land cover. The strongest controls on playa water status are playa area, monthly precipitation, and watershed area. Playas are critical resources for the High Plains, providing a range of ecosystem services that are dependent upon the playa’s ability to store water. Playa functions are under continued threat from cropland expansion, climate change, and playa and watershed modifications. To sustain playa functions in Kansas, efforts should focus on conserving larger grassland playas and reducing sediment inputs to playas in cropland watersheds.

Designing a database model of district-level land use planning with community consultation in Vung Tau city, Ba Ria - Vung Tau province

Nowadays, building a land database and land use planning database is an indispensable requirement, especially for a seaport city as Vung Tau city (Ba Ria - Vung Tau province) where there are complex land fluctuations. Accordingly, a complete land use planning database with the participation of community will contribute to connecting planners, managers and people, and increase the publicity, transparency and feasibility of land use planning options. The study designed a database model of land use planning with the community consultation for Vung Tau city in accordance with the land data standards of Circular No. 75/2015/TT-BTNMT. Based on the designed model, a set of land use planning database with high accuracy was created and it was in line with the data standards of the Ministry of Natural Resources and Environment and the designed database model. This database structure contained 22 spatial data tables on ArcGIS and 8 attribute data tables (with the community consultation) on Microsoft SQL Server. Finally, we successfully used the VBDLIS software to build the land use planning database (period 2010 - 2020) for Vung Tau city with 6 data layers, including land use planning data layer (15.060 records), project layer (163 records), adjustment layer for land use planning (12.002 records), adjustment layer for project (570 records), and 2 attribute data layers of community consultation. The results of this study indicated that the correct model and complete database structure were the basis for successfully building and effectively exploiting the database of land use planning. The designed model could contribute to the planning of land management and improve the efficiency of land use.

Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale

The unexpected Ebola virus outbreak in West Africa in 2014 involving the Zaire ebolavirus made clear that other regions outside Central Africa, its previously documented niche, were at risk of future epidemics. The complex transmission cycle and a lack of epidemiological data make mapping areas at risk of the disease challenging. We used a Geographic Information System-based multicriteria evaluation (GIS-MCE), a knowledge-based approach, to identify areas suitable for Ebola virus spillover to humans in regions of Guinea, Congo and Gabon where Ebola viruses already emerged. We identified environmental, climatic and anthropogenic risk factors and potential hosts from a literature review. Geographical data layers, representing risk factors, were combined to produce suitability maps of Ebola virus spillover at the landscape scale. Our maps show high spatial and temporal variability in the suitability for Ebola virus spillover at a fine regional scale. Reported spillover events fell in areas of intermediate to high suitability in our maps, and a sensitivity analysis showed that the maps produced were robust. There are still important gaps in our knowledge about what factors are associated with the risk of Ebola virus spillover. As more information becomes available, maps produced using the GIS-MCE approach can be easily updated to improve surveillance and the prevention of future outbreaks.

Determination of emergency roads to emergency accommodation using loss analysis results

Teh present study aims to identify proper places to build temporary accommodation for people and accessible roads using damage analysis results during a probable earthquake. Teh HAZUS damage estimation method, which is one of teh most common ones currently used in teh world, was used in dis study. Teh influential factors in locating teh temporary accommodation in Shiraz were studied by using damage results, AHP model, and Expert Choice software. Then, map for temporary accommodation was prepared. By integrating layers, teh ultimate map of optimal locating for temporary accommodation was presented. Subsequently, all teh parameters influencing teh safety of emergency evacuation and relief network were identified and teh impact rate of each one was determined based on experts’ opinions through AHP. Based on teh importance of each index, roads were weighed and coded. Then, teh optimal safe road for relief and emergency evacuation was proposed. Teh results suggested dat relief roads are different based on different indices and teh optimal road was obtained through overlapping teh data layers according to teh importance of each parameter. dis optimal road could provide maximum services in teh minimum time duration and subsequently create capacity building in urban crisis management.

JOINT LAND COVER AND CROP TYPE MAPPING USING MULTI-TEMPORAL SENTINEL-2 DATA FROM VARIOUS ENVIRONMENTAL ZONES IN GREECE

In this work, we elaborate on the gained insights from various classification experiments towards detailed land cover mapping over four representative regions of different environmental characteristics in Greece. In particular, the proposed methodology exploits Sentinel-2 data at an annual basis, for the joint classification of 35 land cover and crop type classes. A number of pre-processing steps were employed on the satellite data, in order to address atmospheric and geometric effects, as well as clouds and pertinent shadows. Several classification set-ups were designed and performed using either time series of spectral features or temporal features. The latter consisted of statistical metrics, derived from the spectral time series, and therefore were significantly reduced in dimension. Experiments using the Random Forest algorithm were performed by building several per-tile models, as well as cross- regional models based on training data from all considered regions/tiles. Overall classification accuracy rates exceeded 90% for most experiments. Further analysis on the experimental results highlighted that crop types were classified more accurately when using the spectral time series features, compared to the temporal ones. Classification accuracy for non-crop classes proved much less affected by the type of employed features. The inclusion of auxiliary data layers was beneficial in all cases, both for overall and for per-class accuracy metrics. Qualitative evaluation on the predicted maps further affirmed the efficiency of the developed methodology.

Potential Distribution of Colonizing Nine-Banded Armadillos at Their Northern Range Edge

The nine-banded armadillo (Dasypus novemcinctus) has become a recent addition to the local fauna of Illinois as a response to habitat alteration and climate change. This range expansion has resulted in the presence of armadillos in areas not predicted by earlier models. Although these models have been revised, armadillos continue to move north and have reached areas of heavy agricultural use. We identified conditions that favor the presence of armadillos and potential corridors for dispersal. Identifying the distribution of the armadillo in Illinois is a vital step in anticipating their arrival in areas containing potentially sensitive wildlife populations and habitats. Armadillo locations (n = 37) collected during 2016–2020 were used to develop a map of the potential distribution of armadillos in southern Illinois. Environmental data layers included in the model were land cover type, distance to water, distance to forest edge, human modification, and climactic variables. Land cover type was the most important contributing variable to the model. Our results are consistent with the tenet that armadillo activity and dispersal corridors are centered around riparian areas, and that forested cover may provide corridors an agricultural mosaic.

Multi-Omics Approaches in Immunological Research

The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.