Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering for Noisy Data

Clustering is a crucial method for deciphering data structure and producing new information. Due to its significance in revealing fundamental connections between the human brain and events, it is essential to utilize clustering for cognitive research. Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties. Noisy data can lead to incorrect object recognition and inference. This research aims to innovate a novel clustering approach, named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering (PNTS3FCM), to solve the clustering problem with noisy data using neutral and refusal degrees in the definition of Picture Fuzzy Set (PFS) and Neutrosophic Set (NS). Our contribution is to propose a new optimization model with four essential components: clustering, outlier removal, safe semi-supervised fuzzy clustering and partitioning with labeled and unlabeled data. The effectiveness and flexibility of the proposed technique are estimated and compared with the state-of-art methods, standard Picture fuzzy clustering (FC-PFS) and Confidence-weighted safe semi-supervised clustering (CS3FCM) on benchmark UCI datasets. The experimental results show that our method is better at least 10/15 datasets than the compared methods in terms of clustering quality and computational time.     

Ketoconazole and other imidazole derivatives are potent inhibitors of peroxisomal phytanic acid alpha-oxidation

Twelve young adults were treated with either melatonin, 3 mg or 6 mg, or placebo, at two different times before an early evening nap (18.00-20.00 h) according to a balanced double-blind Latin square design. Polysomnographic monitoring revealed that both dosages of melatonin significantly shortened sleep latency and increased total sleep time in comparison to placebo, irrespective of the time of administration. Subjects also tended to assess their sleep as 'deeper' after melatonin treatment. Based on previous data and the present results, it was concluded that exogenous melatonin exerts hypnotic effects only when circulating levels of endogenous melatonin are low.     

Use ofLeucaena leucocephala (Lam. de Wit) leaves as a nitrogen source for crop production

Field and pot trials were conducted to determine optimum management practices for usingLeucaena leucocephala (Lam. de Wit) leaves as a N source for crop production. Field trials with maize showed no benefit from split application of leucaena leaves or from application of fresh as opposed to dried material. Field trials also failed to show any difference between incorporation as opposed to surface application of leucaena leaves. This may be attributed to the low nitrogen response observed. Pot trials however, showed that soil incorporation of leucaena leaves was more effective than surface application in increasing plant dry weight.Leucaena leaves were not as effective as inorganic N in increasing maize grain yield (field trials) or dry matter production (pot trial). Unlike inorganic N, leucaena leaves had a significant residual effect on the succeeding maize crop. In decomposition studies, buried leucaena leaves decomposed more quickly than surface-applied leaves, and fresh leaves decomposed more rapidly than dried leaves.     

Moment-based alignment for shape prior with variational B-spline level set

This paper presents a new shape prior-based implicit active contour model for image segmentation. The paper proposes an energy functional including a data term and a shape prior term. The data term, inspired from the region-based active contour approach, evolves the contour based on the region information of the image to segment. The shape prior term, defined as the distance between the evolving shape and a reference shape, constraints the evolution of the contour with respect to the reference shape. Especially, in this paper, we present shapes via geometric moments, and utilize the shape normalization procedure, which takes into account the affine transformation, to align the evolving shape with the reference one. By this way, we could directly calculate the shape transformation, instead of solving a set of coupled partial differential equations as in the gradient descent approach. In addition, we represent the level-set function in the proposed energy functional as a linear combination of continuous basic functions expressed on a B-spline basic. This allows a fast convergence to the segmentation solution. Experiment results on synthetic, real, and medical images show that the proposed model is able to extract object boundaries even in the presence of clutter and occlusion.     

A printed circuit board capacitive sensor for air bubble inside fluidic flow detection

This paper presents a three-electrode capacitive fluidic sensor for detecting an air bubble inside a fluidic channel such as blood vessels, oil or medical liquid channels. The capacitor is designed and fabricated based on a printed circuit board (PCB). The electrodes are fabricated by using copper via structure through top to bottom surface of the PCB. A plastic pipe is layout through the capacitive sensor and perpendicular to the PCB surface. Capacitance of sensor changes when an air bubble inside fluidic flow cross the sensor. The capacitance change can be monitored by using a differential capacitive amplifier, a lock-in amplifier, filter and an NI acquisition card. Signal is processed and calculated on a computer. Air bubble inside the liquid flow are detected by monitor the unbalance signal between the three electrode potential voltages. Output voltage depends on the volume of the air bubble due to dielectric change between capacitor’s electrodes. Output voltage is up to 53 mV when an 2.28 mm³ air bubble crosses the sensing channel. Air bubble velocity can be estimated based on the output pulse signal. This proposed fluidic sensor can be used for void fraction detection in medical devices and systems; fluidic characterization; and water–gas, oil–water and oil–water–gas multiphase flows in petroleum technology. That structure also can apply to the micro-size for detecting in microfluidic to monitor and control changes in microfluidic channels.     

Growth of Single‐Walled Carbon Nanotubes from Sharp Metal Tips

The nucleation and growth of single‐walled carbon nanotubes is observed in situ in a transmission electron microscope. Carbon atoms are implanted into catalytically active metal particles by electron‐beam sputtering. The metal particles are then shaped with a focused electron beam. Once the particles have a region of high surface curvature, spontaneous nucleation and growth of single‐walled carbon nanotubes occurs on the metal particles. It is shown that the local solubility of carbon in the metal determines the nucleation of nanotubes. This is confirmed by atomistic computer simulations treating the solubility of carbon in a metal particle as a function of the size of the system.     

Improved compressed sensing reconstruction for $$^{19}$$ F magnetic resonance imaging

Magnetic Resonance Materials in Physics, Biology and Medicine - In magnetic resonance imaging (MRI), compressed sensing (CS) enables the reconstruction of undersampled sparse data sets. Thus,...