How Many Cell Types Are in the Kidney and What Do They Do?

The kidney maintains electrolyte, water, and acid-base balance, eliminates foreign and waste compounds, regulates blood pressure, and secretes hormones. There are at least 16 different highly specialized epithelial cell types in the mammalian kidney. The number of specialized endothelial cells, immune cells, and interstitial cell types might even be larger. The concerted interplay between different cell types is critical for kidney function. Traditionally, cells were defined by their function or microscopical morphological appearance. With the advent of new single-cell modalities such as transcriptomics, epigenetics, metabolomics, and proteomics we are entering into a new era of cell type definition. This new technological revolution provides new opportunities to classify cells in the kidney and understand their functions. Expected final online publication date for the Annual Review of Physiology, Volume 84 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The Uniqueness of Heterogeneous Globigerina Limestone Reservoir and The Importance of Integrated Rock Type Definition for Field Development Plan: Case Study in Madura Strait, East Java

The Globigerina Limestone (GL) is the main reservoir of the seven gas fields that will be developed in the Madura Strait Block. The GL is a heterogeneous and unique clastic carbonate. However, the understanding of reservoir rock type of this reservoir are quite limited. Rock type definition in heterogeneous GL is very important aspect for reservoir modeling and will influences field development strategy. Rock type analysis in this study is using integration of core data, wireline logs and formation test data. Rock type determination applies porosity and permeability relationship approach from core data, which related to pore size distribution, lithofacies, and diagenesis. The analysis resulted eight rock types in the Globigerina Limestone reservoir. Result suggests that rock type definition is strongly influenced by lithofacies, which is dominated by packstone and wackestone - packstone. The diagenetic process in the deep burial environment causes decreasing of reservoir quality. Then the diagenesis process turns to be shallower in marine phreatic zone and causes dissolution which increasing the reservoir quality. Moreover, the analysis of rock type properties consist of clay volume, porosity, permeability, and water saturation. The good quality of a rock type will have the higher the porosity and permeability. The dominant rock type in this study area is RT4, which is identical to packstone lithofasies that has 0.40 v/v porosity and 5.2 mD as average permeability. The packstone litofacies could be found in RT 5, 6, 7, even 8 due to the increased of secondary porosity. It could also be found at a lower RT which is caused by intensive cementation.

APPLYING CONSUMER BEHAVIOR MODEL TO THE STUFF LABOR MOTIVATION

The article appeals to the problem of designing motivation model for the labor behavior of company stuff. Human behavior is one of the key areas of research in many fields of knowledge. The main forms of human behavior in economics are consumer and labor behavior. For each of them, extensive theoretical and practical material has been developed, a significant variety of behaviors has been proposed. Moreover, in the absence of general models of human behavior that would be applicable in any field of his activity, each science develops its own methodological apparatus and builds models based on its own approaches. Models of consumer behavior describe a clearly defined object (purchasing act), are specific and practically oriented. Patterns of labour behaviour are more general and relate to conduct in general, but not to a specific act of activity. The article attempts to apply the principles of building models of consumer behavior to modeling labor behavior. The model of type “Definition of target actions — Stimulus selection — Information and desire — Choice and location — Check and preference — Confirmation and relation” is proposed. The content of these stages for the task of changing labor behavior is shown. A methodological feature of the model is the isolation of rational and emotional aspects in some elements of labor behavior.

Critical Image Identification via Incident-Type Definition Using Smartphone Data during an Emergency: A Case Study of the 2020 Heavy Rainfall Event in Korea

In unpredictable disaster scenarios, it is important to recognize the situation promptly and take appropriate response actions. This study proposes a cloud computing-based data collection, processing, and analysis process that employs a crowd-sensing application. Clustering algorithms are used to define the major damage types, and hotspot analysis is applied to effectively filter critical data from crowdsourced data. To verify the utility of the proposed process, it is applied to Icheon-si and Anseong-si, both in Gyeonggi-do, which were affected by heavy rainfall in 2020. The results show that the types of incident at the damaged site were effectively detected, and images reflecting the damage situation could be classified using the application of the geospatial analysis technique. For 5 August 2020, which was close to the date of the event, the images were classified with a precision of 100% at a threshold of 0.4. For 24–25 August 2020, the image classification precision exceeded 95% at a threshold of 0.5, except for the mudslide mudflow in the Yul area. The location distribution of the classified images showed a distribution similar to that of damaged regions in unmanned aerial vehicle images.

Coordinated Recovery Strategy for Multi-infeed HVDC Systems Based on MIESCR

A coordinated recovery strategy, based on MIESCR, is proposed for the converters Excessive dynamic reactive power demand and the low speed of power transmission recovery in multi-infeed HVDC system in this paper. Firstly, the article deduces the consistency of two type definition of MIESCR, and uses the respective advantages of the definition to improve the physical meaning of MIESCR; and then it elaborates the role of MIESCR played in in MIDC system voltage and power-angle stability Third, this pages put forward MIESCR as the fundamental to distinguish the strength of AC system, and use the size of MIESCR to arrange the recovery order of DC systems. Furthermore, the parameter of PI controller is used to realize the control of each DC system current. There is a great method to ensure coordinate control of PI controller. The last, a double infeed HVDC system simulation model, based on two actual DC system of China Southern Power Grid, is built on Electromagnetic transient simulation software of PSCAD/EMTDC to confirm the validity of this method proposed in this paper.

Geometric and semantic quality assessments of building features in OpenStreetMap for some areas of Istanbul

Nowadays volunteered geographic information (VGI) and collaborative mapping projects such as OpenStreetMap (OSM) have gained popularity as they not only offer free data but also allow crowdsourced contributions. Spatial data entry in this manner creates quality concerns for further use of the VGI data. In this regard, this article focuses on the assessments of geometric and semantic quality of the OSM building features (BFs) against a large-scale topographic (TOPO) data belonging to some areas of Istanbul. The comparison is carried out based on the one-to-one matched BFs according to a geometric matching ratio. In geometric terms, various parameters of position (i.e. X, Y), size (i.e. area, perimeter and granularity), shape (i.e. convexity, circularity, elongation, equivalent rectangular index, rectangularity and roughness index), and orientation (i.e. orientation angle) elements are computed and compared. In semantic terms, BF type coherences are evaluated. According to the findings of geometric quality, the average positional difference was less than three meters. In addition, the perimeter values tended to decrease while area and granularity values tended to increase in OSM data against TOPO data. Those showed that the level of the detail of the OSM BFs was lower than TOPO BFs in general. This was also confirmed by the decreasing tendency of shape complexity according to the parameters of shape element. Orientation angle differences was often low except for some special cases. It was found that the scale of the OSM dataset, even though not homogenous, approximately corresponded to the lower limit of medium scale maps (i.e. 1:10,000) or a slightly smaller scale. According to the findings of semantic quality, in case of the presence of specific type definition, the coherence was rather high between OSM and TOPO BFs while the most OSM BFs did not have a specific type attribute. This study showed that the matching process needed some improvements while the followed approach was largely successful in the evaluation of the matched buildings from geometric and semantic aspects.

Using DenseFly algorithm for cell searching on massive scRNA-seq datasets

Background High throughput single-cell transcriptomic technology produces massive high-dimensional data, enabling high-resolution cell type definition and identification. To uncover the expressional patterns beneath the big data, a transcriptional landscape searching algorithm at a single-cell level is desirable. Results We explored the feasibility of using DenseFly algorithm for cell searching on scRNA-seq data. DenseFly is a locality sensitive hashing algorithm inspired by the fruit fly olfactory system. The experiments indicate that DenseFly outperforms the baseline methods FlyHash and SimHash in classification tasks, and the performance is robust to dropout events and batch effects. Conclusion We developed a method for mapping cells across scRNA-seq datasets based on the DenseFly algorithm. It can be an efficient tool for cell atlas searching.

CLASSIFICATION OF BRAIN MRI IMAGES BY USING THE AUTOMATIC SEGMENTATION AND TEXTURE ANALYSIS

Brain tumor is a relatively severe human disease type. Its timely diagnosis and tumor type definition are an actual task in modern medicine. Lately, the segmentation methods on 3D brain images (like computer and magnetic resonance tomography) are used for definition of a certain tumor type. Nevertheless, the segmentation is usually conducted manually, which requires a lot of time and depends on the experience of a doctor. This paper looks at the possibility of creating a method for the automatic segmentation of images. As a training sample, the medical database of MRI brain tomography with three tumor types (meningioma, glioma, and pituitary tumor) was taken. Taking into account the different slices, the base had: 708 examples of meningioma, 1426 examples of glioma, and 930 examples of pituitary tumor. The database authors marked the regions of interest on each image, which were used as a tutor (supervised learning) for automatic segmentation model. Before model creation, currently existing popular automatic segmentation models were analyzed. U-Net deep convolution neural network architecture was used as the most suitable one. As the result of its use, the model was obtained, which can segment the image correctly in seventy four percent of six hundred images (testing sample). After obtaining the automatic segmentation model, the Random Forest models for three “One versus All” tasks and one multiclass task were created for brain tumor classification. The total sample was divided into training (70 %), testing (20 %), and examining (10 %) ones before creating the models. The accuracy of the models in the examining sample varies from 84 to 94 percent. For model classification creation, the texture features were used, obtained by texture analysis method, and created by the co-authors of the Department of Biomedical Cybernetics in the task of liver ultrasound image classification. They were compared with well-known Haralick texture features. The comparison showed that the best way to achieve an accurate classification model is to combine all the features into one stack