Kinetic parameter estimation for cooling crystallization process based on cell average technique and automatic differentiation

In this paper, a cell average technique(CAT) based parameter estimation method is proposed for cooling crystallization involved with particle growth, aggregation and breakage, by establishing a more efficient and accurate solution in terms of the automatic differentiation(AD) algorithm. To overcome the deficiency of CAT that demands high computation cost for implementation, a set of ordinary differential equations(ODEs) entailed from CAT based discretized population balance equation(PBE) are solved by using the AD based high-order Taylor expansion. Moreover, an AD based trust-region reflective(TRR) algorithm and another interior-point(IP) algorithm are established for estimating the kinetic parameters associated with particle growth, aggregation and breakage. As a result, the estimation accuracy can be further improved while the computation cost can be significantly reduced, compared to the existing algorithms. Benchmark examples from the literature are used to illustrate the accuracy and efficiency of the AD-based CAT, TRR and IP algorithms in comparison with the existing algorithms. Moreover, seeded batch cooling crystallization experiments of β form L-glutamic acid are performed to validate the proposed method.     

Primary Founder Mutations in the PRKDC Gene Increase Tumor Mutation Load in Colorectal Cancer

The clonal composition of a malignant tumor strongly depends on cellular dynamics influenced by the asynchronized loss of DNA repair mechanisms. Here, our aim was to identify founder mutations leading to subsequent boosts in mutation load. The overall mutation burden in 591 colorectal cancer tumors was analyzed, including the mutation status of DNA-repair genes. The number of mutations was first determined across all patients and the proportion of genes having mutation in each percentile was ranked. Early mutations in DNA repair genes preceding a mutational expansion were designated as founder mutations. Survival analysis for gene expression was performed using microarray data with available relapse-free survival. Of the 180 genes involved in DNA repair, the top five founder mutations were in PRKDC (n = 31), ATM (n = 26), POLE (n = 18), SRCAP (n = 18), and BRCA2 (n = 15). PRKDC expression was 6.4-fold higher in tumors compared to normal samples, and higher expression led to longer relapse-free survival in 1211 patients (HR = 0.72, p = 4.4 × 10⁻³). In an experimental setting, the mutational load resulting from UV radiation combined with inhibition of PRKDC was analyzed. Upon treatments, the mutational load exposed a significant two-fold increase. Our results suggest PRKDC as a new key gene driving tumor heterogeneity.     

Analysis of Polycyclic Aromatic Hydrocarbons in Egyptian Petroleum Condensate Oils

The polycyclic aromatic hydrocarbons (PAH) in Egyptian condensates are analyzed for the first. A solid phase extraction (SPE) followed by gas chromatography-mass selective detection was used for their analysis. The method was calibrated for optimal extraction conditions. Excellent recoveries were found (78–114%) for the PAHs that were identified using a variety of standards and GC-MS spectra. The solid-phase extracted PAH fraction was further separated by HPLC on a Ag(I) mercaptopropanosilica gel to reduce the complexity of the sample by separating the PAHs based on the number of aromatic rings. The analytes were quantified using GC with a flame ionization detector. For this kind of sample SPE is a more convenient separation technique than an open column. PAHs containing two to four rings in the concentration range 0.6–11 μg/L were measured. Some preliminary geochemical hypotheses based on the analyzed PAHs and the previously analyzed S-containing aromatic compounds were formed as to the depositional environment and source rock type.     

Bimetallic Zeolite Catalyst for CO2 Reforming of Methane

The catalytic activity of Ni–Rh on the synthesized BEA zeolite in carbon dioxide reforming of methane has been investigated. Catalysts were prepared using the incipient wetness impregnation method, with a total content of metals up to 5 wt%. Catalysts were characterized through XRD, TPR, N₂ adsorption, SEM, AAS, TG/DSC analyses. The prepared Ni–Rh zeolites were tested for their catalytic activity at 700 °C, at atmospheric pressure, and at CH₄/CO₂ ratio of 1. Catalytic results showed that bimetallic based zeolites exhibit high activity (CH₄ and CO₂ conversion equal to 73 and 78, respectively) but monometallic Rh catalysts were the only one stable against coke formation.     

Structural entropy in detecting background patterns of AFM images

Structural entropy was developed for detecting the type of localization in charge distributions on a finite grid, especially in mesoscopic electronic systems. However, it is possible to detect and analyze superstructures, i.e., topologies consisting of more structures with different types of localization properties. In the definition of the structural entropy, the von Neumann entropy of the system is divided into two parts: first, the extension entropy, which is simply the logarithm of the occupation number; the second part is the structural entropy. On a structural entropy versus logarithm of the spatial filling factor map, the different types of localizations follow different, well-characterized curves. Spatial filling factor measures the percentage of the “filled” (i.e., high intensity) pixels of the image.An atomic force microscopy (AFM) image can be interpreted as some kind of charge distribution on a grid: after normalization, the darkness (or lightness) of the pixels fulfills all the necessary conditions. AFM image artifacts can be detected by plotting the structural entropy versus the logarithm of the spatial filling factor maps of the images. Not only the type of an added large-scale Gaussian, parabolic, exponential, or other function can be identified, but also by careful study of the curves belonging to the structures, the parameters can be detected, too.     

Sensitivity analysis of a directional potential drop sensor for creep monitoring

Recent research efforts indicated that directional potential drop (PD) measurements could be exploited for in-situ creep monitoring. The present work investigates the sensitivity of such measurements with a square-electrode configuration to geometrical and material variations caused by creep. This measurement technique is based on a modification of the conventional PD technique as it measures simultaneously two resistance values in orthogonal directions. Under uniaxial stress condition, the ratio of the lateral and axial resistances is roughly proportional to the applied strain. Experimental tests showed that small anisotropic changes in the resistance ratio caused by directional effects of creep can be distinguished from potentially far larger isotropic changes caused by non-directional reversible and irreversible thermal effects. The sensitivity of the square-electrode PD sensor to geometrical and material variations was analyzed separately and the analytical predictions were validated by experimental tests in both cases. The directional PD technique was found to exhibit high sensitivity that allows the detection of elastic and plastic strains as low as 0.05%. Additional experimental results from an accelerated 400-hour creep test are presented to demonstrate the feasibility of this technique to monitor creep degradation in 304 stainless steel at 600 °C.     

Within-school social comparison: How students perceive the standing of their class predicts academic self-concept.

Results from prior research indicate that a student’s academic self-concept is negatively influenced by the achievement of others in his or her school (a frame of reference effect) and that this negative frame of reference effect is not or only slightly reduced by the quality, standing, or prestige of the track or school attended (a “reflected glory” effect). Going beyond prior studies, the present research used both between-school and within-school approaches to investigate frame of reference and reflected glory effects in education, incorporating students’ own perceptions of the standing of their school and class. Multilevel analyses were performed with data from 3 large-scale assessments with 4,810, 1,502, and 4,247 students, respectively. Findings from all 3 studies showed that, given comparable individual achievement, placement in high-achieving learning groups was associated with comparatively low academic self-concepts. However, students’ academic self-concept was not merely a reflection of their relative position within the class but also substantively associated with their individual and shared perceptions of the class’s standing. Moreover, the negative effects of being placed in high-achieving learning groups were weaker for high-achieving students. Overall, the studies support both educational and social psychology theorizing on social comparison. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Honoring Dr. Bimal K. Bose [Tributes]

As a leading figure in the broad area of industrial electronics, Dr. Bimal K. Bose has made outstanding contributions in the fields of power electronics and motor drives. He is an innovator, educator, and mentor to many members of the industry all over the world. As part of this special issue, this column pays tribute to his lifetime achievements.