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Introduction: Coronavirus disease 2019 (COVID-19) encephalitis is characterized by viral entry into the brain, resulting in inflammation and a cascade of neuronal damage. Clinical manifestations include headaches, seizures, and movement disorders. A mortality rate of 20% and infrequent presentation make COVID-19 encephalitis a diagnostic challenge. Case Presentation: We hereby present the case of a 55-year-old man with a history of diabetes mellitus (potential impact on COVID-19 severity discussed in the supplementary material) presenting with altered sensorium, swelling in the left eye, and involuntary jerky limb movements. Neurological examination revealed neck rigidity, myoclonic jerks, and an extensor plantar response. Brain magnetic resonance imaging (MRI) was performed, which revealed cortical enhancement in the bifrontal, temporal, and occipital lobes. Rapid progression of myoclonus, altered sensorium, and cortical enhancement on MRI suggested Creutzfeldt-Jacob disease. After a thorough workup, the diagnosis was COVID-19 encephalitis with rhino-orbital mucormycosis. The treatment regimen consisted of adequate glycemic control, remdesivir injection, intravenous and retroorbital liposomal amphotericin, and levetiracetam. The patient’s condition improved, and he was eventually discharged. Conclusion: This case illustrates the uncommon presentation of COVID-19 with neurological involvement and emphasizes the value of history-taking, neuroimaging, and cerebrospinal fluid analysis. A high index of suspicion is critical for a prompt diagnosis and initiating therapy.

In this paper, we have considered two graphs G1 and G2 to be any two vertex disjoint graphs with n1 and n2 vertices respectively. Let V (G1) ∪ U (G1) where, V (G1) = {v1, v2, v3, ..., vn1} and U(G1) = {x1, x2, x3, ..., xn1} be the vertex set of DG1, the duplication graph of G1. The vertex xi is a duplication of vi for each i = 1,2,..., n1. Duplication corresponding corona of G1 and G2, denoted by G1 ⋇ G2 is the graph obtained from DG1 and n1 copies of G2 by making xi and vi adjacent to every vertex in the i - th copy of G2. Our aim is to obtain the results on dominator and total dominator coloring of duplication corresponding corona of some graphs. [ABSTRACT FROM AUTHOR]

This work reports an efficient one-pot synthetic approach for the production of industrially essential silicon carbide (SiC) derived from the carbothermal reduction of an iminosilane resorcinol (ISR) composite. In this study, the utilization of activated carbon (AC) as the carbon source and well-known "resorcinol-formalin" chemistry to produce SiC are circumvented as the production of AC involves CO2 emissions and is energy intensive in the former process and due to the hazards associated with formaldehyde in the latter process. The ISR composite formation primarily occurred due to the presence of the imine functionality resulting from the reaction between aminosilane (3-aminopropyltriethoxysilane) and acetone, followed by the reaction with resorcinol. The formation of SiC was confirmed using X-ray diffraction (XRD), Raman spectroscopy, and X-ray photoelectron spectroscopy. The synthesized SiC exhibits high crystallinity with a crystallite size of 15.4 nm and a band gap of 2.36 eV. [ABSTRACT FROM AUTHOR]

Let be a simple connected graph consisting of n vertices and m edges. In a proper l -coloring, an r -dynamic coloring of a graph is one in which each vertex's neighbors are provided at least min { r , d (k) } different colors. The r -dynamic chromatic number of graph , given as χ r () , is the minimal l such that the graph has r -dynamic l coloring of . In this study, we combine a few common graphs to provide the r -dynamic coloring of the subdivision-edge neighborhood corona of path graph P s and star graph K 1 , s . These graphs include path graph P q , cycle graph C q , complete graph K q , star graph K 1 , q , and double star graph K 1 , q , q . [ABSTRACT FROM AUTHOR]

Let G be a simple, un-directed and connected graph. The graph G has a pair of sets (V (G) , E (G)) , where V (G) is nonempty vertex set and E (G) is an unordered pair of sets with two distinct vertices u , v in V (G). A total k -labeling is defined as a function f e from the edge set to a set { 1 , 2 , 3 , ... , k e } and a function f v from the vertex set to a set { 0 , 2 , 4 , ... , 2 k v } , where k = max { k e , 2 k v }. The total k -labeling is a vertex irregular reflexive k -labeling of the graph G , if for every two different vertices u and u ′ of G , wt (u) ≠ wt (u ′) , where wt (u) = f v (u) + ∑ u v ∈ E (G) f e (u v). The reflexive vertex strength of the graph G , denoted by rvs (G) is the minimum k for graph G which has a vertex irregular reflexive k -labeling. In this paper, we determined the exact value of the reflexive vertex strength of cycle and generalized friendship graph. [ABSTRACT FROM AUTHOR]

Biomedical workflow applications' necessities have increased with the progress of the biotechnology industry and it involves large volumes of data which require large-scale computation. Due to the upcoming data deluge of biomedical data, processing and scheduling of the same in computing resources have presented many challenges. A biomedical workflow application requires heterogeneous resources for execution. Thus, it utilizes the advantage of cloud computing, as a cloud provides scalable high-performance computing resources. Scheduling of these workflows in the cloud is a crucial problem for which the proposed solution contributes greatly towards execution improvement. The proposed algorithm provides optimal and effective utilization of computational resources by novel scheduling of algorithms. Least Execution Time Cloud Workflow Scheduling (LETCWS) and Revised Heterogeneous Earliest Finish Time (RHEFT) algorithms are proposed and implemented in two distinct levels to schedule the biomedical workflow applications in such a way that it reduces the execution time while reducing the cost. The proposed algorithms are evaluated using the Workflowsim tool with real-world biomedical workflow applications. Experimental results illustrate the performance of scheduling workflow applications over the other existing approaches. The result shows that the proposed algorithm achieves better performance in terms of execution time and cost. [ABSTRACT FROM AUTHOR]

In 1998, Smarandache introduced the new theory - Neutrosophic sets. In order to achieve the best results in a current situation, policy makers must contend with uncertainty and unpredictability. The neutrosophic definition aids in the investigation of ambiguous or indeterminate values. Here, we have the amalgamated the theory of Single Valued Neutrosophic Vertex Coloring and r-dynamic coloring to introduce a new thought Single Valued Neutrosophic R-dynamic Vertex Coloring (SVNRVC) and have shown example. Further we have determined the Single Valued Neutrosophic R-dynamic chromatic number χR(G) for some graphs. [ABSTRACT FROM AUTHOR]

Let G be a simple, connected undirected graph with m vertices and n edges. Let vertex coloring c of a graph G be a mapping c : V (G) → S , where | S | = k and it is k -colorable. Vertex coloring is proper if none of the any two neighboring vertices receives the similar color. An r -dynamic coloring is a proper coloring such that | c (N b d (v)) | ≥ min { r , deg G (v) } , for each v ∈ V (G). The r -dynamic chromatic number of a graph G is the minutest coloring k of G which is r -dynamic k-colorable and denoted by χ r (G). By a simple view, we exhibit that χ r (G) ≤ χ r + 1 (G) , howbeit χ r + 1 (G) − χ r (G) cannot be arbitrarily small. Thus, finding the result of χ r (G) is useful. This study gave the result of r -dynamic chromatic number for the central graph, Line graph, Subdivision graph, Line of subdivision graph, Splitting graph and Mycielski graph of the Flower graph F n denoted by C (F n) , L (F n) , S (F n) , L (S (F n)) , S (F n) and μ (F n) , respectively. [ABSTRACT FROM AUTHOR]

Medical images are obtained straight from the medical acquisition devices so that, the image quality becomes poor and may contain noises. Low contrast and poor quality are the major issues in the production of medical images. Medical imaging enhancement technology gives way to solve these issues; it helps the doctors to see the interior portions of the body for early diagnosis, also it improves the features the visual aspects of an image for a right diagnosis. This paper proposes a new blend of Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO) called Hybrid Partial Swarm Optimization (HPSO) to enhance medical images and also gives optimal results. The work starts with (i) watershed segmentation followed by (ii) HPSO enhancement algorithm. The watershed segmentation is a morphological gradient-based transformation technique. The gradient map of an image has different gradient values corresponds to different heights. It extracts the continuous boundaries of each region to give solid results and intuitively provides better performance on noisy images. After segmentation, the HPSO algorithm is applied to improve the quality of Computed Tomography (CT) images by calculating the local and global information. The transformation function uses the calculated information to optimize the medical image. The algorithm is tested on a real time data set of CT images, which were collected from MIT-BIH dataset and the performance is analyzed and compared with existing Region Merging (RM), Fuzzy C Means (FCM), Histogram Thresholding, Discrete Wavelet Transformation (DWT), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Histogram Equalization (HE), Contrast Stretching and Adaptive Filtering based on PSNR, SSIM, CII, MSE, RMSE, BER and Execution time parameters. The experimental result shows that the proposed medical image enhancement algorithm achieves 96.7% accuracy and defeat the over segmentation problem of existing systems. [ABSTRACT FROM AUTHOR]