Copy Number Analysis of 24 Oncogenes: MDM4 Identified as a Putative Marker for Low Recurrence Risk in Non Muscle Invasive Bladder Cancer

Patients with non-muscle invasive bladder cancer (NMIBC) generally have a high risk of relapsing locally after primary tumor resection. The search for new predictive markers of local recurrence thus represents an important goal for the management of this disease. We studied the copy number variations (CNVs) of 24 oncogenes (MDM4, MYCN, ALK, PDGFRA, KIT, KDR, DHFR, EGFR, MET, SMO, FGFR1, MYC, ABL1, RET, CCND1, CCND2, CDK4, MDM2, AURKB, ERBB2, TOP2A, AURKA, AR and BRAF) using multiplex ligation probe amplification technique to verify their role as predictive markers of recurrence. Formalin-fixed paraffin-embedded tissue samples from 43 patients who underwent transurethral resection of the bladder (TURB) were used; 23 patients had relapsed and 20 were disease-free after 5 years. Amplification frequencies were analyzed for all genes and MDM4 was the only gene that showed significantly higher amplification in non recurrent patients than in recurrent ones (0.65 vs. 0.3; Fisher’s test p = 0.023). Recurrence-free survival analysis confirmed the predictive role of MDM4 (log-rank test p = 0.041). Our preliminary results indicate a putative role for the MDM4 gene in predicting local recurrence of bladder cancer. Confirmation of this hypothesis is needed in a larger cohort of NMIBC patients.     

A novel concept on discrete samples for efficient microwave processing of materials

A novel concept on discrete samples has been introduced to analyze the efficient heating processes due to microwave radiations. A preliminary investigation on average power absorption within samples vs sample thickness has been carried out for continuous samples and various regimes have been identified such that these regimes may correspond to minima or maxima of average power. Two discrete sample pieces replace a continuous sample for each of these regimes such that the total thickness of the discrete samples is identical with the thickness of the continuous sample. Electric fields and temperature have been solved for each discrete sample layer and the intermediate air layer. The thickness of air layer plays a significant role to dramatically alter the interference of waves and power absorption within each sample layer. It is observed that the discrete sample layers exhibit larger heating rate than that within continuous sample especially for smaller sample thicknesses. Suitable ratios of discrete sample thickness and the thickness of air layer also show large heating rate for larger sample thicknesses. The discrete samples also play important role to optimize thermal runaway. Based on two factors: ‘large heating rate’ and ‘optimal thermal runaway’, the efficient heating strategy has been recommended for highly lossy food substances, and case studies are also demonstrated for low lossy substances.     

Studies on the structural properties of SiO:H films prepared from (SiH4+CO2+He) plasma in RF-PECVD

A comprehensive report on the structural studies on SiO:H films prepared at high growth rate from He-diluted (SiH₄+CO₂) plasma has been presented and extraction of some intriguing ideas that deserve high relevance for the potential development of nano-crystalline hydrogenated silicon oxide (nc-SiO:H) films has been tried. Poly-hydrogenation has been found as inherent to increasing alloying of the network; however, the bonded H-content reduces linearly with the degree of oxygen incorporation, i.e., the solubility of H in the SiO:H network decreases as the O-content increases in the presence of He. This result happens to be opposite to the conventional H₂-diluted plasma condition and appears to be attractive as well. In addition, He-dilution contributes to a high growth rate of the material. Dynamic interaction of He* in the formation of activated oxygen atoms in the plasma and their efficient mobilization on the surface reaction process at the growing network induces abstraction of H from the SiH_n groups and the terminal H atoms are replaced by bridging O atoms to form the SiO:H network. Abstraction of H from the network being an essential criteria for developing nanocrystallinity and it being inherent to oxygenation in Si network when prepared from He-diluted (SiH₄+CO₂) plasma in PECVD, the process could provide an appropriate pathway for preparing nc-SiO:H structures for solar cells, from such plasma in suitable parametric conditions.     

Toughening of epoxy resin with amine functional aniline acetaldehyde condensate

The diglycidyl ether of bisphenol-A (DGEBA) resin was modified with amine functional aniline acetaldehyde condensate (AFAAC) and cured with an ambient temperature curing agent triethylene tetramine. The resulting networks displayed significantly improved fracture toughness. The AFAAC was synthesized by the condensation reaction of aniline and acetaldehyde in the acid medium (pH 4) and characterized by FTIR and NMR spectroscopy, elemental analysis, viscosity measurements, and mole of primary and secondary amine analysis. The DGEBA and AFAAC were molecularly miscible but developed a two-phase microstructure upon network formation. Epoxy/AFAAC compositions were systematically varied to study the effect of AFAAC concentration on the impact, adhesive, tensile, and flexural properties of modified networks. The dynamic mechanical analysis and scanning electron microscopy studies showed two phase morphology in the cured networks, where AFAAC particles were dispersed. The AFAAC modified epoxy network was thermally stable up to around 280°C. POLYM. ENG. SCI., 47:1695–1702, 2007. © 2007 Society of Plastics Engineers     

Bunch graph based dimensionality reduction using auto-encoder for character recognition

Sometimes a group of similar types of dimensions is also treated as nodes. However, these groups can be considered as bunch nodes which may contain several nodes. This paper also justifies the study on bunch graphs which introduced a concept of graphs, where bunch nodes are also allowed. The auto-encoder, a specific type of feedforward neural network generally applied for encoding data in an unsupervised learning methodology to achieve good performance and better-classified data. This kind of network is composed of an encoder and decoder. The encoder compresses the data to an extent or layer, and then from that central layer decoder starts reconstructing the original data. This paper also investigates the dimensionality reduction ability of auto-encoders for character recognition and manipulates the results to accomplish better handling side of auto-encoders. This paper also focuses on the abilities of auto-encoders to reduce noise in data along with dimensionality reduction, trying to interpret the difference between results generated using bunch graph cut techniques. The dataset associated with computing for implementation purposes has been taken from MNIST dataset. Mainly, the two-dimensional plots are used in this paper for comparing results generated associated with different parameters that help in recognizing the character as partial and non-partial separabilities.

     

Manufacturing-error-based maintenance for high-precision machine tools

Nowadays, the condition-based maintenance (CBM), in which repairs are triggered by the heuristic symptoms of the component faults, is finding increasing applications in the industrial fields. However, for the high-precision machine tools, the conventional CBM might not be the optimal option, which is uneconomic and incapable of ensuring their machining accuracy. In order to overcome these shortcomings, this paper propose the manufacturing-error-based maintenance (MEBM), where the repairs are initiated based on the manufacturing errors instead of the heuristic symptoms. In MEBM, repairs are taken properly at the occurrence of the excessive machining errors, and therefore, the premature and redundant maintenance can be avoided and the maintenance cost can be minimized; what is more, the machining errors are controlled in the closed loops, and therefore, the machining accuracy can be guaranteed. Based on the principles of the MEBM, a prototype maintenance system—the transient backlash error (TBE)-based maintenance system—is established. To achieve this aim, first, the width of the backlash in the mechanical chain is measured by utilizing the built-in encoders and the analytical mapping relationship between the backlash width and the TBE is derived. Relying on these foundations, the TBE can be indirectly estimated. Then, the warning threshold of the TBE is customized according to the permissible roundness error of the workpiece. Thus, the maintenance actions can be precisely implemented: when the monitored TBE exceeds its warning threshold, maintenance workers will be notified to lessen the backlash width, and meanwhile, the permissible maximal size for the backlash will also be informed.     

Tunable antireflection from conformal Al-doped ZnO films on nanofaceted Si templates

Photon harvesting by reducing reflection loss is the basis of photovoltaic devices. Here, we show the efficacy of Al-doped ZnO (AZO) overlayer on ion beam-synthesized nanofaceted silicon for suppressing reflection loss. In particular, we demonstrate thickness-dependent tunable antireflection (AR) from conformally grown AZO layer, showing a systematic shift in the reflection minima from ultraviolet to visible to near-infrared ranges with increasing thickness. Tunable AR property is understood in light of depth-dependent refractive index of nanofaceted silicon and AZO overlayer. This improved AR property significantly increases the fill factor of such textured heterostructures, which reaches its maximum for 60-nm AZO compared to the ones based on planar silicon. This thickness matches with the one that shows the maximum reduction in surface reflectance.

PACS

81.07.-b; 42.79.Wc; 81.16.Rf; 81.15.Cd     

Performance improvement of flash memory using AlN as charge-trapping Layer

Potential of high-k dielectric films for future scaled charge storage non-volatile memory (NVM) device applications is discussed. To overcome the problems of charge loss encountered in conventional flash memories with silicon-nitride (Si₃N₄) films and polysilicon-oxide-nitride-oxide-silicon (SONOS) and nonuniformity issues in nanocrystal memories (NC), such as Si, Ge and metal, it is shown that the use of high-k dielectrics allows more aggressive scaling of the tunnel dielectric, smaller operating voltage, better endurance, and faster program/erase speeds. Charge-trapping characteristics of high-k AlN films with SiO₂ as a blocking oxide in p-Si/SiO₂/AlN/SiO₂/poly-silicon (SOHOS) memory structures have been investigated in detail. The experimental results of program/erase characteristics obtained as the functions of gate bias voltage and pulse width are presented.