EFNB1 Acts as a Novel Prognosis Marker in Glioblastoma through Bioinformatics Methods and Experimental Validation

Purpose. Ephrin B1 (EFNB1), the Eph-associated receptor tyrosine kinase ligand, is suggested to have an important function in neurodevelopment. However, its contribution to glioblastoma multiforme (GBM) remains uncertain. This study aimed to determine the prognostic power and immune implication of EFNB1 in GBM. Methods. We first identified differentially coexpressed genes within GBM relative to noncarcinoma samples from GEO and TCGA databases by WGCNA. The STRING online database and the maximum cluster centrality (MCC) algorithm in Cytoscape software were used to design for predicting protein-protein interactions (PPI) and calculating pivot nodes, respectively. The expression of hub genes in cancer and noncancer tissues was verified by an online tool gene expression profile interactive analysis (GEPIA). Thereafter, the TISIDB online tool with Cox correlation regression method was employed to screen for immunomodulators associated with EFNB1 and to model the risk associated with immunomodulators. Results. Altogether 201 differentially expressed genes (DEGs) were discovered. After that, 10 hub genes (CALB2, EFNB1, ENO2, EPHB4, NES, OBSCN, RAB9B, RPL23A, STMN2, and THY1) were incorporated to construct the PPI network. As revealed by survival analysis, EFNB1 upregulation predicted poor overall survival (OS) for GBM cases. Furthermore, we developed a prognostic risk signature according to the EFNB1-associated immunomodulators. Kaplan–Meier survival analysis and receiver operating characteristic method were adopted for analysis, which revealed that our signature showed favorable accuracy of prognosis prediction. Finally, EFNB1 inhibition was found to block cell proliferation and migration in GBM cells. Conclusion. The above results indicate that EFNB1 participates in cancer immunity and progression, which is the candidate biomarker for GBM.

ON OBSERVATION OF ULF ELECTROMAGNETIC SIGNALS FROM REMOTE EARTHQUAKES AND DISTRIBUTION OF THEIR SOURCES ON THE EARTH’S SURFACE

During long-term observations, the Borok and College Geophysical Observatories have registered ultralow-frequency (ULF) electromagnetic signals from remote earthquakes. We have analysed the characteristics of such signals that occur several minutes before a seismic event. Our analysis shows that the dynamic spectra of the signals from earthquakes that occurred in different regions are similar, although the earthquakes differ in magnitude and focal depth. We investigate and discuss daily and seasonal probabilities for the occurrence of ULF electromagnetic pulses. Attention is given to the uneven distribution of their sources (i.e. earthquakes) on the earth’s surface. Our study shows that the ULF electromagnetic signals are clustered in separate zones and cells. When mapped, these clusters mark seismic electromagnetically active regions. In the northern hemisphere, a maximum cluster is found at latitudes 30–45°. In the longitudinal direction, two maximum clusters are located in the western sector. They are considered as the major and additional peaks (latitudes 120–150° and 0–30°, respectively). Examples are given to illustrate earthquake precursors in various regions. Based on the analysis results, we conclude that the occurrence of ULF electromagnetic pulses before earthquakes is universal. These pulses need to be investigated in a more detail to clarify if an upcoming earthquake is detectable from such signals a few minutes before its occurrence, and whether it is possible, in principle, to use this information for safety alerts before seismic shaking arrives.

Genetic Diversity Analysis for Yield Associated and Quality Traits in Promising Rice Varieties of Tamil Nadu

An experiment was conducted with 55 rice varieties to assess the genetic diversity by using Mahalanobis D2 Statistical and characterization of genotypes using principal component analysis. All genotypes exhibited a wide and significant variation for 19 traits, by cluster analysis grouped into ten clusters. The maximum genotypes were included in Cluster 6 (16) followed by cluster 4 (10), cluster 3 (8), cluster 2 (7), cluster 5 (5), cluster 8 (4), cluster 1 (2), with 29.09, 18.18, 14.54, 12.72, 9.09, 7.27 and 3.63 proportion respectively, the rest of three clusters had one genotype each. Maximum cluster distance obtained between cluster×constituted by single entry (Pusa Basmati) showed highest inter cluster distance from cluster V (20727.37), VII (18414.79), I (17228.89) and cluster III (17010.24) are having very high inter cluster distance and also by cluster IX from cluster VIII (8852.36), VI (7559.67), I (7444.68) and cluster VII (6666.83) followed by cluster VI from cluster V (6225.95). The lowest inter cluster distance was observed between cluster II and cluster IV III and VI followed by between cluster I and cluster VIII, XI, II, VI and cluster IV. The intra cluster D2 values ranged from Zero (Cluster VII, IX, X) to 2233.91 (Cluster VIII). Contribution of amylose content was highest towards genetic divergence (23.43%) by taking 348 times ranked first followed by days to 50% flowering (23.37%) by 347 times, single plant yield (23.3%) by 346 times. The PCA analysis showed that first eight principal components accounted for about 85.4%.

Multi Keyword Search on Encrypted Data with Ranking

To maintain the anonymity of users, cloud storage owners often outsource encrypted documents. As a consequence, it is important to establish efficient and precise cypher text search techniques. One issue would be that the connection between documents is typically obscured during the encryption process, resulting in a significant deterioration of search accuracy efficiency. Additionally, the volume of data stored in data centers has exploded. This will make it significantly more difficult to create cipher text search schemes capable of providing efficient and reliable online information retrieval on large quantities of encrypted data. The paper proposes a hierarchical clustering approach in order to accommodate additional search semantics and to satisfy the demand for fast cipher text search in a big data environment. The proposed hierarchical approach clusters documents according to their minimum importance levels and then sub-clusters them until the maximum cluster size is reached. This approach can achieve linear computational complexity throughout the search process, spite of the fact that its size of the record set grows exponentially. The minimum hash sub-tree structure is used in this paper to check the validity of search results. The results demonstrate that as the number of documents in the dataset increases, the proposed method's search time increases linearly, while the conventional method's search time increases exponentially. Additionally, the suggested method outperforms the standard method in terms of rank privacy and document relevance.

Finite system approximation in colloidal systems with aggregation and break-up

In this Thesis, reactive multiparticle collision dynamics (RMPC) is used to simulate red blood cell cluster concentration profiles in the presence of aggregation, as well as when aggregation and break-up are present together. RMPC dynamics involves local collisions, reactions and free-streaming of particles. Reactive mechanisms are used to model the aggregation and break-up of particles. This analogy is motivated by a system of ODES called the Smoluchowski differential equations that have been used to model aggregating systems in the well-mixed case. Exact solutions for the (infinite) systems of ODEs for the Smoluchowski equation are compared to a numerical ODE system solution where the maximum cluster size is N (finite) rather than infinite as assumed in the Smoluchowski equation. The numerical ODE solution is compared to the exact solution in the infinite system when the maximum cluster size is 20 or less. Stochastic RMPC simulations are performed when the maximum cluster size N = 3, and the simulation domain is a cubic volume subject to periodic boundary conditions. Constant and equal aggregation and break-up rates are considered, as well as much smaller aggregation rates compared to break-up rates and vice-versa. Two different initial conditions are considered: monomer-only, as well as non-zero initial concentrations for clusters of all sizes. The simulation for the RMPC (finite), numerical ODE (finite) and exact (infinite) can be shown to have good agreement in the equilibrium concentrations of the chemical species in the system in some cases, although agreement is poor in other cases. This work is an important stepping stone that can be expanded to incorporate flow conditions into the particle dynamics in future work, so as to more accurately investigate pathological conditions including atherosclerotic plaque formation.

Finite system approximation in colloidal systems with aggregation and break-up

In this Thesis, reactive multiparticle collision dynamics (RMPC) is used to simulate red blood cell cluster concentration profiles in the presence of aggregation, as well as when aggregation and break-up are present together. RMPC dynamics involves local collisions, reactions and free-streaming of particles. Reactive mechanisms are used to model the aggregation and break-up of particles. This analogy is motivated by a system of ODES called the Smoluchowski differential equations that have been used to model aggregating systems in the well-mixed case. Exact solutions for the (infinite) systems of ODEs for the Smoluchowski equation are compared to a numerical ODE system solution where the maximum cluster size is N (finite) rather than infinite as assumed in the Smoluchowski equation. The numerical ODE solution is compared to the exact solution in the infinite system when the maximum cluster size is 20 or less. Stochastic RMPC simulations are performed when the maximum cluster size N = 3, and the simulation domain is a cubic volume subject to periodic boundary conditions. Constant and equal aggregation and break-up rates are considered, as well as much smaller aggregation rates compared to break-up rates and vice-versa. Two different initial conditions are considered: monomer-only, as well as non-zero initial concentrations for clusters of all sizes. The simulation for the RMPC (finite), numerical ODE (finite) and exact (infinite) can be shown to have good agreement in the equilibrium concentrations of the chemical species in the system in some cases, although agreement is poor in other cases. This work is an important stepping stone that can be expanded to incorporate flow conditions into the particle dynamics in future work, so as to more accurately investigate pathological conditions including atherosclerotic plaque formation.

Varying VAWT Cluster Configuration and the Effect on Individual Rotor and Overall Cluster Performance

The effect of separation distance between turbines on overall cluster performance were simulated using computational fluid dynamics software and we found that at a distance equivalent to two rotors, there was an improvement of +8.06% in the average performance of the cluster compared to a single, isolated turbine. A very small improvement in performance was noted at the equivalent distance of 12 rotor diameters. The performances of three individual turbines in pyramid- and inverted pyramid-shaped vertical axis wind turbine clustered farm configurations with varying oblique angles at a fixed spacing of two equivalent rotor diameters were also investigated. The design experiment involves the simulation of test cases with oblique angles from 15° to 165° at an interval of 15° and the turbines were allowed to rotate through 18 full rotations. The results show that the left and right turbines increase in performance as the angle with respect to the streamline axis increases, with the exception of the 165° angle. The center turbine, meanwhile, attained its maximum performance at a 45° oblique angle. The maximum cluster performance was found to be in the configuration where the turbines were oriented in a line (i.e., side by side) and perpendicular to the free-stream wind velocity, exhibiting an overall performance improvement of 9.78% compared to the isolated turbine. Other array configurations show improvements ranging from 6.58% to 9.57% compared to the isolated turbine, except in the extreme cases of 15° and 165°, where a decrease in the cluster performance was noted due to blockage induced by the left and right turbines, and the center turbines, respectively.

Inter-cluster velocity structures of star cluster complexes

Star clusters are often born as star-cluster systems, which include several stellar clumps. Such star-cluster complexes could have formed from turbulent molecular clouds. Since Gaia Data Release 2 provided us high quality velocity data of individual stars in known star-cluster complexes, we now can compare the velocity structures of the observed star-cluster complexes with simulated ones. We performed a series of N-body simulations for the formation of star-cluster complexes starting from turbulent molecular clouds. We measured the inter-cluster velocity dispersions of our simulated star-cluster complexes and compared them with the Carina region and NGC 2264. We found that the Carina region and NGC 2264 formed from molecular clouds with a mass of ∼4 × 105M⊙ and ∼4 × 104M⊙, respectively. In our simulations, we also found that the maximum cluster mass (Mc,max) in the complex follows ${M_{{\rm{c}},{\rm{max}}}} = 0.{\rm{2}}0M_g^{0.76}$, where Mg is the initial gas mass.

ALGORITHMS OF CLUSTERING AT DECODING PHOTOES OF UNMANNED AERIAL VEHICLES (DRONES)

The procedures and algorithms automating a process of a multilevel subject decoding are of particular interest. In the paper there is described a development of algorithms for automatic object identification on the basis of clustering. In the investigation the algorithm for a cluster analysis of AKM (improved of k- means) which allows identifying first an object in the picture and then highlighting it graphically is used. This algorithm is formed on the basis of the k-means al-gorithm allowing the fulfillment of a rapid cluster analysis. The improvement of AKM algorithm consists in a possibility of the computation of an optimum cluster number at a specified maximum cluster number. The accuracy of the results of subject decoding is as-sessed. One of the methods for the assessment of relia-bility is a statistic assessment of picture decoding re-liability. For this it is necessary to create a matrix of errors at cluster definition and to calculate accuracy. It is possible to use a method of cross-tabulation for the presentation of pixels defined correctly in an obtained subject map of forest roads and a map formed on the basis of UAV pictures and data of ground investiga-tions. A general accuracy of object decoding as a re-sult of the work of AKM algorithm and a procedure of UAV picture processing of forest roads characterizes a degree of reliability as a high one. The options for the further improvement of a procedure and algorithms are offered.