The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ

This paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin

In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

Human interaction technology based on motion capture (MoCap) systems is a vital tool for human kinematics analysis, with applications in clinical settings, animations, and video games. We introduce a new method for analyzing and estimating dorsal spine movement using a MoCap system. The captured data by the MoCap system are processed and analyzed to estimate the motion kinematics of three primary regions; the shoulders, spine, and hips. This work contributes a non-invasive and anatomically guided framework that enables region-specific analysis of spinal motion which could be used as a clinical alternative to invasive measurement techniques. The hierarchy of our model consists of five main levels; motion capture system settings, marker data