ONGOING FOLLOW-UP NEA OBSERVATIONS IN UKRAINE AND CHINA USING RDS CCD TECHNIQUE

The current state of near-Earth asteroids (NEAs) observations shows an annual increase in the number of newly discovered objects However, the frequency distribution of NEAs by size shows a sharp decrease in the number of objects with size less than 300 m, which contradicts the results of theoretical modeling of the NEA population. Considering definition of potentially hazardous asteroids (PHA), only objects with diameters more than 140 m could pose catastrophic consequences to the Earth and mankind in general. But in the same time, impacts of smaller size objects could lead to significant consequences on local level and their large predicted number increases this probability. Due to their small size which results in faint apparent magnitude, such NEAs are discovered in a short interval of their close approach (CA) to the Earth, when their apparent magnitude are tending to be as bright as possible for a given size. This is not only facilitates the detection of such new objects but also increases their observability by small ground-based telescopes. However, apparent rate of motion during this time might exceed 10 deg d −1 making the observations challenging. The used Rotating-drift-scan CCD (RDS CCD) technique allows to get images of fast-moving objects as a point, that in turn to determine the coordinates of their image centers with sufficient astrometric precision. Obtained in current research project positions show errors in the range ± (0.2″ − 0.3″) in both coordinates with comparison both to JPL's HORIZONS 1 system and NEODyS-2 2 service. The part of observations was obtained around time moment of minimal distance to the Earth during current CA for newly discovered NEAs. Such observations are important to extend observed orbital arc for reliable improvement of their orbit determinations and reducing orbital uncertainty, so it will be possible to recover them in next apparitions.

On graphs with minimal distance signless Laplacian energy

For a simple connected graph G of order n having distance signless Laplacian eigenvalues ρ 1 Q ≥ ρ 2 Q ≥ ⋯ ≥ ρ n Q \rho _1^Q \ge \rho _2^Q \ge \cdots \ge \rho _n^Q , the distance signless Laplacian energy DSLE(G) is defined as D S L E ( G ) = ∑ i = 1 n | ρ i Q - 2 W ( G ) n | DSLE\left( G \right) = \sum\nolimits_{i = 1}^n {\left| {\rho _i^Q - {{2W\left( G \right)} \over n}} \right|} where W(G) is the Weiner index of G. We show that the complete split graph has the minimum distance signless Laplacian energy among all connected graphs with given independence number. Further, we prove that the graph Kk ∨ ( Kt∪ Kn−k−t), 1 ≤ t ≤ ⌊ n - k 2 ⌋ 1 \le t \le \left\lfloor {{{n - k} \over 2}} \right\rfloor has the minimum distance signless Laplacian energy among all connected graphs with vertex connectivity k.

Autologous Gradient Formation Under Differential Interstitial Fluid Flow Environments

Fluid flow and chemokine gradients play a large part in not only regulating homeostatic processes in the brain, but also in pathologic conditions by directing cell migration. Tumor cells in particular are superior at invading into the brain resulting in tumor recurrence. One mechanism that governs cellular invasion is autologous chemotaxis, whereby pericellular chemokine gradients form due to interstitial fluid flow (IFF) leading cells to migrate up the gradient. Glioma cells have been shown to specifically use CXCL12 to increase their invasion under heightened interstitial flow. Computational modeling of this gradient offers better insight into the extent of its development around single cells, yet very few conditions have been modelled. In this paper, a computational model is developed to investigate how a CXCL12 gradient may form around a tumor cell and what conditions are necessary to affect its formation. Through finite element analysis using COMSOL and coupled convection-diffusion/mass transport equations, we show that velocity (IFF magnitude) has the largest parametric effect on gradient formation, multidirectional fluid flow causes gradient formation in the direction of the resultant which is governed by IFF magnitude, common treatments and flow patterns have a spatiotemporal effect on pericellular gradients, exogenous background concentrations can abrogate the autologous effect depending on how close the cell is to the source, that there is a minimal distance away from the tumor border required for a single cell to establish an autologous gradient, and finally that the development of a gradient formation is highly dependent on specific cell morphology.

Design of Extended Hamming Code Technique Encryption for Audio Signals by Double Code Error Prediction

Noise can scramble a message that is sent. This is true for both voicemails and digital communications transmitted to and from computer systems. During transmission, mistakes tend to happen. Computer memory is the most commonplace to use Hamming code error correction. With extra parity/redundancy bits added to Hamming code, single-bit errors may be detected and corrected. Short-distance data transmissions often make use of Hamming coding. The redundancy bits are interspersed and evacuated subsequently when scaling it for longer data lengths. The new hamming code approach may be quickly and easily adapted to any situation. As a result, it's ideal for sending large data bitstreams since the overhead bits per data bit ratio is much lower. The investigation in this article is extended Hamming codes for product codes. The proposal particularly emphasises on how well it functions with low error rate, which is critical for multimedia wireless applications. It provides a foundation and a comprehensive set of methods for quantitatively evaluating this performance without the need of time-consuming simulations. It provides fresh theoretical findings on the well-known approximation, where the bit error rate roughly equal to the frame error rate times the minimal distance to the codeword length ratio. Moreover, the analytical method is applied to actual design considerations such as shorter and punctured codes along with the payload and redundancy bits calculation. Using the extended identity equation on the dual codes, decoding can be done at the first instance. The achievement of 43.48% redundancy bits is obtained during the testing process which is a huge proportion reduced in this research work.

In Silico Assessment of Safety and Efficacy of Screw Placement for Pediatric Image-Guided Otologic Surgery

Introduction: Current high-accuracy image-guided systems for otologic surgery use fiducial screws for patient-to-image registration. Thus far, these systems have only been used in adults, and the safety and efficacy of the fiducial screw placement has not yet been investigated in the pediatric population.Materials and Methods: In a retrospective study, CT image data of the temporal region from 11 subjects meeting inclusion criteria (8–48 months at the time of surgery) were selected, resulting in n = 20 sides. These datasets were investigated with respect to screw stability efficacy in terms of the cortical layer thickness, and safety in terms of the distance of potential fiducial screws to the dura mater or venous sinuses. All of these results are presented as distributions, thickness color maps, and with descriptive statistics. Seven regions within the temporal bone were analyzed individually. In addition, four fiducial screws per case with 4 mm thread-length were placed in an additively manufactured model according to the guidelines for robotic cochlear implantation surgery. For all these screws, the minimal distance to the dura mater or venous sinuses was measured, or if applicable how much they penetrated these structures.Results: The cortical layer has been found to be mostly between 0.7–3.3 mm thick (from the 5th to the 95th percentile), while even thinner areas exist. The distance from the surface of the temporal bone to the dura mater or the venous sinuses varied considerably between the subjects and ranged mostly from 1.1–9.3 mm (from the 5th to the 95th percentile). From all 80 placed fiducial screws of 4 mm thread length in the pediatric subject younger than two years old, 22 touched or penetrated either the dura or the sigmoid sinus. The best regions for fiducial placement would be the mastoid area and along the petrous pyramid in terms of safety. In terms of efficacy, the parietal followed by the petrous pyramid, and retrosigmoid regions are most suited.Conclusion: The current fiducial screws and the screw placement guidelines for adults are insufficiently safe or effective for pediatric patients.

CT-MRI Dual Information Registration for the Diagnosis of Liver Cancer: A Pilot Study Using Point-based Registration

Background: Early diagnosis of liver cancer may increase life expectancy. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) play a vital role in diagnosing liver cancer. Together, both modalities offer significant individual and specific diagnosis data to physicians; however, they lack the integration of both types of information. To address this concern, a registration process has to be utilized for the purpose, as multimodal details are crucial in providing the physician with complete information. Objective: The aim was to present a model of CT-MRI registration used to diagnose liver cancer, specifically for improving the quality of the liver images and provide all the required information for earlier detection of the tumors. This method should concurrently address the issues of imaging procedures for liver cancer to fasten the detection of the tumor from both modalities. Methods: In this work, a registration scheme for fusing the CT and MRI liver images is studied. A feature point-based method with normalized cross-correlation has been utilized to aid in the diagnosis of liver cancer and provide multimodal information to physicians. Data on ten patients from an online database were obtained. For each dataset, three planar views from both modalities were interpolated and registered using feature point-based methods. The registration of algorithms was carried out by MATLAB (vR2019b, Mathworks, Natick, USA) on an Intel (R) Core (TM) i5-5200U CPU @ 2.20 GHz computer. The accuracy of the registered image is being validated qualitatively and quantitatively. Results: The results show that an accurate registration is obtained with minimal distance errors by which CT and MRI were accurately registered based on the validation of the experts. The RMSE ranges from 0.02 to 1.01 for translation, which is equivalent in magnitude to approximately 0 to 5 pixels for CT and registered image resolution. Conclusion: The CT-MRI registration scheme can provide complementary information on liver cancer to physicians, thus improving the diagnosis and treatment planning process.

Energy Efficient Data Distribution on Cloud with Optimal Routing Path Based Congestion Control in WSN Environment

Presently, Wireless Sensor Network (WSN) is the extremely standard services utilized in commercial in addition to industrial applications, owing to its technical development in the embedded computing devices’ processor, communication, along with less-power usage. Moreover, in the WSN’s advantages, the sensor data’s energy-efficient distribution onto the cloud data centre is amid the core challenges caused by higher data loads and also congestion. Aimed at overcoming these problems, this work proffers an energy-efficient Data Packet (DP) distribution protocol comprising an optimal routing path centred congestion control technique in the WSN environment. This system not just ponders the energy-efficient DP distribution nevertheless increments the sensor’s lifetime by choosing the Cluster Head (CH) centred on the sensor’s residual energy, packet loss factor, data forwarding rate, and minimal distance. Next, the numerous routing paths prevalent in inter-cluster and intra-clusters are detected utilizing the QLA2ODV method; the congested nodes are detected as of these paths utilizing LM-NN classifier; if congestion happens, the QLA2ODV distributes the DP onto the Base Station (BS) via the optimum congestion-free routing path. The optimal routing paths were elected as of the congestion-free paths utilizing the WFCSO method. Past obtaining the sensor data, the BS transmits the DPs onto the Fog Nodes (FNs). At last, the sensor data are effectively distributed onto the cloud data centres grounded on the data’s features and cloud features utilizing the BD-SBO technique. The experiential outcomes determine the proposed system’s effectiveness.

A Polylobar Nucleus Identifying and Extracting Method for Leukocyte Counting

Accurate counting of leukocytes is an important method for diagnosing human blood diseases. Because most nuclei of neutrophils and eosinophils are polylobar, it is easily confused with the unilobar nuclei in nucleus segmentation. Therefore, it is very essential to accurately identify and determine the polylobar leukocytes. In this paper, a polylobar nucleus identification and extracting method is proposed. Firstly, by using the Otsu threshold and area threshold method, the nuclei of leukocytes are accurately segmented. According to the morphological characteristics of polylobar leukocytes, the edges of the mitotic polylobar leukocytes are detected, and the numbers of polylobar leukocytes are determined according to the minimal distance rule. Therefore, the accurate counting of leukocytes can be realized. From the experimental results, we can see that using the Otsu method and the area threshold to segment the polylobar nuclear leukocytes, the segmentation ratio of the leukocyte nucleus reached 98.3%. After using the morphological features, the polylobar nuclear leukocytes can be accurately counted. The experimental results have verified the feasibility and practicability of the proposed method.

Epileptogenic zone detection in MRI negative epilepsy using adaptive thresholding of arterial spin labeling data

Drug-resistant epilepsy is a diagnostic and therapeutic challenge, mainly in patients with negative MRI findings. State-of-the-art imaging methods complement standard epilepsy protocols with new information and help epileptologists to increase the reliability of their decisions. In this study, we investigate whether arterial spin labeling (ASL) perfusion MRI can help localize the epileptogenic zone (EZ). To that end, we developed an image processing method to detect the EZ as an area with hypoperfusion relative to the contralateral unaffected side, using subject-specific thresholding of the asymmetry index in ASL images. We demonstrated three thresholding criteria (termed minimal product criterion, minimal distance criterion, and elbow criterion) on 29 patients with MRI-negative epilepsy (age 32.98 ± 10.4 years). The minimal product criterion showed optimal results in terms of positive predictive value (mean 0.12 in postoperative group and 0.22 in preoperative group) and true positive rate (mean 0.71 in postoperative group and 1.82 in preoperative group). Additionally, we found high accuracy in determining the EZ side (mean 0.86 in postoperative group and 0.73 in preoperative group out of 1.00). ASL can be easily incorporated into the standard presurgical MR protocol, and it provides an additional benefit in EZ localization.

Potts Clustering with Complete Shrinkage: a novel clustering methodology with its Software Package pottscompleteshrinkage in Python

We have modified the Potts Model Swendsen-Wang algorithm to insert some clusters constraints by applying a modified agglomerative clustering approach (Kurita, 1991). We have called the induced Potts Model, the Potts Clustering with Complete Shrinkage (PCCS), under the Python package pottscompleteshrinkage deployed on PyPi Index under its current release. In this approach, we deal with the increasing number of small clusters generated in a given partition by merging all small clusters of size ≤ h with their closest cluster in terms of minimal distance respectively, where h is an integer greater or equal to 2. The algorithm uses a technique in which distances of all pairs of observations are stored. Then the nearest cluster (with size ≥ h) is given by the cluster with the closest node in terms of minimal distance to the cluster to be merged using complete linkage. This approach is truly effective as it helps to control the clusters size, and we have found empirical evidence of Chi-Square and Gamma density curves for the constrained cluster size distribution of PCCS, when applied to some datasets taken from the multiple-output benchmark datasets available in the Mulan project website (Tsoumakas et al., 2020). We add a last framework based on Frequency of frequency distribution (FoF) to find the conditional bonds distribution given the clusters size constraints which results in an intractable distribution for large datasets, but its computation framework is a land of rich mathematical developments.