Immobilization of acrylamide-modified oligonucleotides by co-polymerization

A flexible chemistry for solid phase attachment of oligonucleotides is described. Oligonucleotides bearing 5'-terminal acrylamide modifications efficiently co-polymerize with acrylamide monomers to form thermally stable DNA-containing polyacrylamide co-polymers. Co-polymerization attachment is specific for the terminal acrylamide group. Stable probe-containing layers are easily fabricated on supports bearing exposed acrylic groups, including plastic microtiter plates and silanized glass. Attachment can be accomplished using standard polyacrylamide gel recipes and polymerization techniques. Supports having a high surface density of hybridizable oligonucleotide (approximately 200 fmol/mm2) can be produced.     

High temperature bias-stress-induced instability in power trench-gated MOSFETs

We report on the high-temperature reverse-bias (HTRB) stress reliability of trench-gated n-channel metal-oxide-silicon field-effect transistors (n-UMOSFETs). The degradation induced by the HTRB is examined using changes in transistor parameters, optical microscopy, and scanning electron microscopy. The HTRB causes degradations in the threshold voltage and drain leakage of the n-UMOSFET and these degradations are particularly large when the stress is applied in a humid ambient. The observations were interpreted in terms of water molecule diffusion into the gate oxide through passivation cracks in the edge termination of the n-UMOSFET during HTRB in a humid ambient. The water molecules catalyze proton (H⁺) generation through electric-field assisted interactions and hole injection into the gate oxide at the bottom of the trench. Also, H⁺ is observed to be very stable in the gate oxide and to migrate between the gate-oxide and oxide–Si interfaces driven by an applied gate-voltage. It is proposed that the employed HTRB configuration and level give rise to negative-bias temperature instability (NBTI) in a parasitic p-channel MOSFET structure occurring in the trench base of the n-UMOSFET, and that NBTI is a serious reliability concern in power UMOSFETs subjected to stress in a moist ambient.     

Standardization of work-a statistical approach using spreadsheet

One of the techniques of work study is work measurement employed to ensure the best possible use of human in carrying out a specific activity. Using appropriate measurement procedures, a work standard can be set which will reflect the gross time required by a normal operator working under normal conditions and with normal pace to complete a unit of work satisfactorily. One of the approaches in setting the work standard is based on the statistical analysis of time data. This paper presents a method of establishing work standard by generating statistical control chart using Excell -- an integrated spreadsheet and graphics software for the Apple-Macintosh.     

Eliciting information about organizational culture via laddering

Abstract. Eliciting information about organizational culture is an important part of system analysis and design. However, eliciting knowledge of this sort is difficult. Laddering is an established technique that is particularly suitable for eliciting information about goals and for eliciting explanations, which are important issues when investigating organizational culture. This paper describes the method, its strengths and limitations, its use in several case studies and its relation to other elicitation techniques. Recommendations for further work are given.     

Use of radial basis functions for estimating monthly mean daily solar radiation

The present study utilizes the radial basis functions technique for the estimation of monthly mean daily values of solar radiation falling on horizontal surfaces and compares its performance with that of the multilayer perceptrons network and a classical regression model. In this work, we use solar radiation data from 41 stations that are spread over the Kingdom of Saudi Arabia. The solar radiation data from 31 locations are used for training the neural networks and the data from the remaining 10 locations are used for testing the estimated values. However, the testing data were not used in the modeling or training of the networks to give an indication of the performance of the system at unknown locations. Results indicate the viability of the radial basis for this kind of problem.     

Forced migration of soluble and suspended materials by freezing front in aqueous systems

Migration of soluble and suspended materials by directional freezing of aqueous systems has been studied qualitatively. Slow freezing was employed vertically as well as horizontally through solutions and suspensions. In all cases, the impurities (soluble salts as well as suspended materials) were appreciably forced out by dynamic freezing front. The phenomenon worked for concentrating/separating inorganic ions, soluble organic compounds and dyes in synthetic solutions as well as in natural streams. Various analytical techniques were employed to monitor the migrating species through the freezing media. It was found that separation efficiency depends on different factors like rate of cooling, pH and concentration. Model experiments were designed and exercised successfully to employ the technique for treatment of dye-polluted water.     

Increasing the toughness of nylon 12 by the incorporation of functionalized graphene

The effect of functionalized graphene (FG) on the mechanical properties, especially toughness, of nylon12 was investigated. The results revealed that the incorporation of a very small amount (about 0.6 wt%) of the FG caused a significant improvement in ultimate tensile strength, elongation, impact strength and toughness. With 0.6 wt% FG ultimate tensile strength and elongation at break of the nylon 12 are improved by ∼35% and ∼200%, respectively. The K_Ic of the nylon 12 is ∼1.28 MPa m^0.5 and the incorporation of 0.6 wt% FG causes a significant increase of 72% (∼2.2 MPa m^0.5). 0.6 wt% FG also causes a significant improvement of 175% in impact failure energy of the nylon 12. The incorporation of FG resulted in an increase in amount of γ-phase of nylon12 which could be the direct reason for the increase of toughness.     

Machine learning for post-traumatic stress disorder identification utilizing resting-state functional magnetic resonance imaging

Early detection of post-traumatic stress disorder (PTSD) is essential for proper treatment of the patients to recover from this disorder. The aligned purpose of this study was to investigate the performance deviations in regions of interest (ROI) of PTSD than the healthy brain regions, to assess interregional functional connectivity and applications of machine learning techniques to identify PTSD and healthy control using resting-state functional magnetic resonance imaging (rs-fMRI). The rs-fMRI data of 10 ROI was extracted from 14 approved PTSD subjects and 14 healthy controls. The rs-fMRI data of the selected ROI were used in ANOVA to measure performance level and Pearson's correlation to investigate the interregional functional connectivity in PTSD brains. In machine learning approaches, the logistic regression, K-nearest neighbor (KNN), support vector machine (SVM) with linear, radial basis function, and polynomial kernels were used to classify the PTSD and control subjects. The performance level in brain regions of PTSD deviated as compared to the regions in the healthy brain. In addition, significant positive or negative functional connectivity was observed among ROI in PTSD brains. The rs-fMRI data have been distributed in training, validation, and testing group for maturity, implementation of machine learning techniques. The KNN and SVM with radial basis function kernel were outperformed for classification among other methods with high accuracies (96.6%, 94.8%, 98.5%) and (93.7%, 95.2%, 99.2%) to train, validate, and test datasets, respectively. The study's findings may provide a guideline to observe performance and functional connectivity of the brain regions in PTSD and to discriminate PTSD subject using only the suggested algorithms.