Gd-Bi-M-Ce-O (M = Cu,Zr, Ni,Co, Mn) ceria-based solid solutions for low temperature CO oxidation

Ceria based solid solutions doped by Gd, Bi, and the third dopant were synthesized by the co-precipitation method with ultrasonic treatment, followed by calcination at the temperature of 500°С. Characterization of the synthesized nanosystems by XRD, TEM, TG, Raman spectroscopy, FTIR, XPS was carried out. It is shown that all obtained powders of solid solutions crystallized into a cubic structure of the fluorite type, with an average particle size of 5–15 nm. The samples had a mesoporous structure of the pore diameter of 2–5 nm. The catalytic activity of Gd-Bi-M-Ce-O (M = Cu, Zr, Ni, Co, Mn) solid solutions was carried out. The catalyst Gd_0.05Bi_0.15Mn_0.20Ce_0.60O₂ has the lowest oxidation temperature.     

Dependence of Fluid Catalytic Cracking Unit Performance on H-Oil Severity,Catalyst Activity,and Coke Selectivity

The effect of the quality of ebullated bed vacuum residue H-Oil hydrocracking gas oils cracked in a commercial fluid catalytic cracking unit (FCCU) on its performance was studied. Six different catalysts were employed in this study. Four catalysts were tested in a commercial FCCU, and two in a laboratory FCCU. An increase of the H-Oil hydrocracker reaction temperature was associated with a decrease in the K_W factor of the H-Oil gas oils. The diminished K_W factor of H-Oil gas oils resulted in lower FCCU conversion and higher regenerator temperatures. The FCC conversion at maximum gasoline yield is best predicted by the feed K_W factor. The higher-activity, higher-Δcoke catalyst is unfavorable for FCCU performance because the excessive regenerator temperature excursions require reduction of the throughput.     

Experimental Fuzzy/Split-Range Control: Novel Strategy for Biodiesel Batch Reactor Temperature Control

With respect to environmental concerns, biofuels have been used around the world, such as biodiesel, and any improvement in the biodiesel production process is desirable. This paper proposes three different control systems based on fuzzy logic and output control signal split-range. Regulating reaction temperature with low settling time and process variable oscillation are the process control aims, and smooth output control signal for actuators protection is also desired. An automated biodiesel production prototype was used and the experimental results demonstrate that a fuzzy/split-range structure with three input variables showed the best performance, resulting in process variable regulation in set-point value with small settling time and actuators premature wearing prevention.     

Determination of contact points between workpiece and fixture elements as a tool for augmented reality in fixture design

Wireless Networks - Fixtures play a significant role in ensuring the quality of products in manufacturing engineering. The paper considers fork-type parts that have a complex spatial configuration...     

Analysis of complexity indices for classification problems: Cancer gene expression data

Currently, cancer diagnosis at a molecular level has been made possible through the analysis of gene expression data. More specifically, one usually uses machine learning (ML) techniques to build, from cancer gene expression data, automatic diagnosis models (classifiers). Cancer gene expression data often present some characteristics that can have a negative impact in the generalization ability of the classifiers generated. Some of these properties are data sparsity and an unbalanced class distribution. We investigate the results of a set of indices able to extract the intrinsic complexity information from the data. Such measures can be used to analyze, among other things, which particular characteristics of cancer gene expression data mostly impact the prediction ability of support vector machine classifiers. In this context, we also show that, by applying a proper feature selection procedure to the data, one can reduce the influence of those characteristics in the error rates of the classifiers induced.     

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.     

BPC – A binary priority countdown protocol

In modern wireless ad hoc networks, with a high speed PHY, every collision means a significant loss of useful bandwidth. In the last few years different binary contention protocols have been introduced to address this problem. In this work we propose a novel binary contention protocol called binary priority countdown (BPC) protocol, whose goal is to reduce collisions as well as contention time. BPC uses a new priority countdown mechanism which exploits the efficiency of binary countdown, but the priority countdown process is not constrained to a single binary countdown round. This way, the priority space is not defined by the length of binary countdown round, like in other binary countdown protocols proposed in the literature, and arbitrary medium access priorities can be decremented through multiple binary countdown rounds if necessary. The ability of a new priority countdown mechanism to count down any priority number without changing the length of a binary countdown round, allows independent management of priority space. This “independence” of priority space introduces new optimization and adaptation possibilities. Collision memory effect is recognized and described. BPC protocol reveals connection between unary, binary and digit contention protocols. All three groups of protocols can now be seen as members of the same class of contention algorithms. Preliminary simulation results are shown.     

Shear dispersion in dense granular flows

We formulate and solve a model problem of dispersion of dense granular materials in rapid shear flow down an incline. The effective dispersivity of the depth-averaged concentration of the dispersing powder is shown to vary as the Péclet number squared, as in classical Taylor–Aris dispersion of molecular solutes. An extension to generic shear profiles is presented, and possible applications to industrial and geological granular flows are noted.