Effect of Supports and Promoters on the Performance of Ni-Based Catalysts in Ethanol Steam Reforming

Ethanol steam reforming (ESR) is one of the potential processes to convert ethanol into valuable products. Hydrogen produced from ESR is considered as green energy for the future and can be an excellent alternative to fossil fuels with the aim of mitigating the greenhouse gas effect. The ESR process has been well studied, using transition metals as catalysts coupled with both acidic and basic oxides as supports. Among various reported transition metals, Ni is an inexpensive material with activity comparable to that of noble metals, showing promising ethanol conversion and hydrogen yields. Additionally, different promoters and supports were utilized to enhance the hydrogen yield and the catalyst stability. This review summarizes and discusses the influences of the supports and promoters of Ni-based catalysts on the ESR process.     

On the SEP of Cooperative Diversity with Opportunistic Relaying

We analyze the exact symbol error probability (SEP) of cooperative diversity with opportunistic amplify-and-forward (AF) relaying. The benefit of this opportunism to the SEP is assessed by comparing with maximal ratio combining of orthogonal multiple AF relay transmissions.     

Experimental data and approximate estimation for dissociation time of hydrate plugs

New experimental data coupled with a numerical model and an approximate solution are proposed to predict dissociation time of hydrate plugs in oil sub-sea pipelines. The experimental hydrate plugs are dissociated by the method of symmetric depressurisation, both in a specially designed apparatus and a classical batch reactor. The agreement between the estimation of the model and the experimental data and the simplicity of the approximate equation presents an advantage in estimating the time of hydrate plug dissociation in pipelines.     

Personalized identification of abdominal wall hernia meshes on computed tomography

An abdominal wall hernia is a protrusion of the intestine through an opening or area of weakness in the abdominal wall. Correct pre-operative identification of abdominal wall hernia meshes could help surgeons adjust the surgical plan to meet the expected difficulty and morbidity of operating through or removing the previous mesh. First, we present herein for the first time the application of image analysis for automated identification of hernia meshes. Second, we discuss the novel development of a new entropy-based image texture feature using geostatistics and indicator kriging. Third, we seek to enhance the hernia mesh identification by combining the new texture feature with the gray-level co-occurrence matrix feature of the image. The two features can characterize complementary information of anatomic details of the abdominal hernia wall and its mesh on computed tomography. Experimental results have demonstrated the effectiveness of the proposed study. The new computational tool has potential for personalized mesh identification which can assist surgeons in the diagnosis and repair of complex abdominal wall hernias.     

Electrochemical behavior of Sn8Hg (gamma-2) and dental amalgam in a phosphate buffer solution

The gamma-2 phase (Sn₈Hg) and a dental amalgam in phosphate buffer have been studied by means of potentiostatic and galvanostatic techniques, along with a rotating ring-disc electrode (RRDE). The analysis of results has shown that phosphate ions play an important role in the corrosion of amalgam. The anodic reaction leads to the formation of soluble species and a passivating film, which is probably composed of tin hydroxide and tin phosphate.     

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.     

Development of a quadruped walking robot AiDIN-III using biologically inspired kinematic analysis

This paper presents a bio-inspired mechanism design for a quadruped walking robot. The approach is derived from the observation on the behaviors of quadruped locomotion, skeletal structure, and the study on the stability of walking based on morphological analysis. In the first, we define the design parameters such as the dimensions of the body and limbs, the center of mass position, and locomotion mechanisms based on surveys on the literatures from biologists. Then, by using the parameters, we propose an useful framework for determining the design parameters of a quadruped walking robot. For implementations, we manufacture a dog-type self-contained quadruped walking robot, named AiDIN-III (Artificial Digitigrade for Natural Environment version III) and the effectiveness of the proposed idea is validated via experimental works.     

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.