A Novel Nanometric Fault Tolerant Reversible Subtractor Circuit

Abstract: Reversibility plays an important role when energy efficient computations are considered. Reversible logic circuits have received significant attention in quantum computing, low power CMOS design, optical information processing and nanotechnology in the recent years. This study proposes a new fault tolerant reversible half-subtractor and a new fault tolerant reversible full-subtractor circuit with nanometric scales. Also in this paper we demonstrate how the well-known and important, PERES gate and TR gate can be synthesized from parity preserving reversible gates. All the designs have nanometric scales

Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms.

Heart failure caused by iron deposits in the myocardium is the primary cause of mortality in beta-thalassemia major patients. Cardiac magnetic resonance imaging (CMRI) T2* is the primary screening technique used to detect myocardial iron overload, but inherently bears some limitations. In this study, we aimed to differentiate beta-thalassemia major patients with myocardial iron overload from those without myocardial iron overload (detected by T2*CMRI) based on radiomic features extracted from echocardiography images and machine learning (ML) in patients with normal left ventricular ejection fraction (LVEF > 55%) in echocardiography. Out of 91 cases, 44 patients with thalassemia major with normal LVEF (> 55%) and T2* ≤ 20 ms and 47 people with LVEF > 55% and T2* > 20 ms as the control group were included in the study. Radiomic features were extracted for each end-systolic (ES) and end-diastolic (ED) image. Then, three feature selection (FS) methods and six different classifiers were used. The models were evaluated using various metrics, including the area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). Maximum relevance-minimum redundancy-eXtreme gradient boosting (MRMR-XGB) (AUC = 0.73, ACC = 0.73, SPE = 0.73, SEN = 0.73), ANOVA-MLP (AUC = 0.69, ACC = 0.69, SPE = 0.56, SEN = 0.83), and recursive feature elimination-K-nearest neighbors (RFE-KNN) (AUC = 0.65, ACC = 0.65, SPE = 0.64, SEN = 0.65) were the best models in ED, ES, and ED&ES datasets. Using radiomic features extracted from echocardiographic images and ML, it is feasible to predict cardiac problems caused by iron overload

Structural response of the spiral-welded pipelines buried in different uniform soil types to the strike-slip fault

Buried steel pipelines, which are widely used in, often face the threat of Permanent Ground Deformations (PGD) caused by fault crossings. The structural response of the pipeline can be influenced by the pipe-trench-backfill interaction, resulting in various hoop strains, axial plastic strains, and consequently, formation of wrinkles at different locations in the fault zone. This paper investigates the structural response of spiral-welded pipelines at strike-slip fault crossings by incorporating the burial effects in a range of different soil materials. A dynamic explicit analysis is used to address the convergence issue commonly encountered in the analysis of post-buckling problems. The helix angles and the burial depth effects in different soil types and pipeline-ground interaction angles are examined. The study provides valuable insights into the influence of burial conditions and corresponding helix angle on the performance of spiral-welded pipelines in strike-slip faults

Assessment of the Response of Trenched–Backfilled Pipelines to Strike-Slip Faults: An Analytical Approach

Trenched pipelines may experience significant lateral displacement due to natural geohazards such as strike slip-fault movements, landslides, etc. Using pre-excavated soil to backfill trenches is a cost-effective option to protect pipelines against large deformations. These backfilling materials are heavily remolded and therefore softer than the native ground. Therefore, the shear strength difference between the backfill and native ground may affect the pipeline–backfill–trench interaction and the failure mechanism of the surrounding soil. By assuming a simplified uniform soil domain, the influence of softer pre-excavated backfilling material on the pipeline–backfill–trench interaction is neglected in the analytical methods that are usually used in the structural health monitoring of buried pipelines. In this study, the effects of trenching and backfilling were incorporated into an analytical solution for a fast assessment of the pipeline response at the early stages of engineering design projects and structural health monitoring. In comparison with other methods, this methodology provides a convenient and efficient method for computing pipeline strain and deflection curves in geohazardous regions

Assessment of the Response of Trenched–Backfilled Pipelines to Strike-Slip Faults: An Analytical Approach

Trenched pipelines may experience significant lateral displacement due to natural geohazards such as strike slip-fault movements, landslides, etc. Using pre-excavated soil to backfill trenches is a cost-effective option to protect pipelines against large deformations. These backfilling materials are heavily remolded and therefore softer than the native ground. Therefore, the shear strength difference between the backfill and native ground may affect the pipeline–backfill–trench interaction and the failure mechanism of the surrounding soil. By assuming a simplified uniform soil domain, the influence of softer pre-excavated backfilling material on the pipeline–backfill–trench interaction is neglected in the analytical methods that are usually used in the structural health monitoring of buried pipelines. In this study, the effects of trenching and backfilling were incorporated into an analytical solution for a fast assessment of the pipeline response at the early stages of engineering design projects and structural health monitoring. In comparison with other methods, this methodology provides a convenient and efficient method for computing pipeline strain and deflection curves in geohazardous regions

Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks

The purpose of this work was to assess the feasibility of acquisition time reduction in MPI-SPECT imaging using deep leering techniques through two main approaches, namely reduction of the acquisition time per projection and reduction of the number of angular projections