Revealing −1 Programmed Ribosomal Frameshifting Mechanisms by Single-Molecule Techniques and Computational Methods

Programmed ribosomal frameshifting (PRF) serves as an intrinsic translational regulation mechanism employed by some viruses to control the ratio between structural and enzymatic proteins. Most viral mRNAs which use PRF adapt an H-type pseudoknot to stimulate −1 PRF. The relationship between the thermodynamic stability and the frameshifting efficiency of pseudoknots has not been fully understood. Recently, single-molecule force spectroscopy has revealed that the frequency of −1 PRF correlates with the unwinding forces required for disrupting pseudoknots, and that some of the unwinding work dissipates irreversibly due to the torsional restraint of pseudoknots. Complementary to single-molecule techniques, computational modeling provides insights into global motions of the ribosome, whose structural transitions during frameshifting have not yet been elucidated in atomic detail. Taken together, recent advances in biophysical tools may help to develop antiviral therapies that target the ubiquitous −1 PRF mechanism among viruses

High-fidelity error injection and acceleration techniques

As technology scales down, the likelihood of hardware errors that silently corrupt the results of applications is increasing. Evaluating the resilience of applications against hardware errors is thus of significant concern. Current evaluation techniques via error injection are either low-fidelity or inefficient in terms of using computing resources. This dissertation demonstrates that sophisticated integration of injectors across abstraction layers and novel sampling algorithms can significantly improve both the fidelity and efficiency. Specifically, this dissertation describes an open-source instruction-level error injector that generates high-fidelity hardware errors due to particle strikes and voltage droops. Two acceleration techniques, nested Monte Carlo and Injection-Point Overprovisioning, are proposed to speed up error injection campaigns by 1−2 orders of magnitude. This dissertation also answers the question of when high-fidelity is needed to evaluate the impact of hardware errors on applications and the effectiveness of error detectors.Electrical and Computer Engineerin

Bridge damage detection using probability distribution of RMSE values of moving vehicle acceleration

The 20th working conference of the IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems (IFIP 2022) will be held at Kyoto University, Kyoto, Japan, September 19-20, 2022.In recent years, indirect bridge health monitoring methods using sensors mounted on measuring vehicles, known as drive-by methods, have received increasing attention. This study intends to investigate the feasibility of a drive-by bridge health monitoring method utilizing moving vehicle accelerations. The proposed method investigates whether there is any abnormality in the bridge by using the subtraction between the preliminary-measured vehicle acceleration when the bridge is healthy and the newly-measured vehicle acceleration when the bridge is tested. A band pass filter is applied to the vehicle accelerations before the subtraction in order to eliminate undesirable vibration components other than the frequency of the first bending mode of the bridge. The damage existence and level are investigated by calculating the RMS of the difference between the preliminary-measured and newly-measured accelerations of the vehicle. Considering the variation in the measurements, several measurements are conducted, and the RMS (Root Means Square) values and their probability distributions are examined. The laboratory experiment using a test vehicle equipped with accelerometers was conducted. Observations through this study demonstrated that the proposed method successfully determined the bridge damage existence and its level in a certain accuracy when the frequency of the first mode of the bridge varies with the damage of the bridge

Facebook and Google Usage in Taiwan’s College Students

This study proposes and tests a research model which was developed based on the uses-and-gratifications theory. The aim of this study was to investigate if selected factors have differential predicting power on the use of Facebook and Google service in Taiwan. This study employed seven constructs: purposive value, hedonic value, social identity, social support, interpersonal relationship, personality traits, and intimacy as the factors predicting Facebook and Google usage. An electronic survey technique was used to collect data from Internet. The results showed that hedonic value and social identity constructs can significantly predict Facebook usage and purposive value has significant predicting power on Google usage. The construct intimacy is the most significant factor for both Google and Facebook usages. Our findings make suggestions for social network sites (SNSs) providers that to differentiate their SNSs quality from others’, both functional aspects and emotional factors need to be taken into consideration

Linked optical and gene expression profiling of single cells at high-throughput.

Single-cell RNA sequencing has emerged as a powerful tool for characterizing cells, but not all phenotypes of interest can be observed through changes in gene expression. Linking sequencing with optical analysis has provided insight into the molecular basis of cellular function, but current approaches have limited throughput. Here, we present a high-throughput platform for linked optical and gene expression profiling of single cells. We demonstrate accurate fluorescence and gene expression measurements on thousands of cells in a single experiment. We use the platform to characterize DNA and RNA changes through the cell cycle and correlate antibody fluorescence with gene expression. The platform's ability to isolate rare cell subsets and perform multiple measurements, including fluorescence and sequencing-based analysis, holds potential for scalable multi-modal single-cell analysis

KINEMATICS ANALYSIS OF THE UPPER EXTREMITY DURING THE TWOHANDED BACKHAND DRIVE VOLLEY FOR FEMALE TENNIS PLAYERS

The purpose of this study was to discuss the motion characteristics of the arms in the two-handed backhand drive volley. Five elite female tennis players participated in this study, their two-handed backhand drive volley strokes were analysed, and all participants are right handed. Motion Analysis System with 10 Eagle Digital inferred high speed cameras at 200Hz were used for this study. The results show a similar elbow and wrist speed strategy in x-axis between two-handed ground stroke and drive volley, our study also found that the rear arm dominates the stroke and mainly provide the topspin that is required for the skill of the drive volley. In order to create better stroke efficiency, the right elbow reached peak velocity first, followed by the right wrist before racket impact with the ball

A Global Method for a Two-Dimensional Cutting Stock Problem in the Manufacturing Industry

A two-dimensional cutting stock problem (2DCSP) needs to cut a set of given rectangular items from standard-sized rectangular materials with the objective of minimizing the number of materials used. This problem frequently arises in different manufacturing industries such as glass, wood, paper, plastic, etc. However, the current literatures lack a deterministic method for solving the 2DCSP. However, this study proposes a global method to solve the 2DCSP. It aims to reduce the number of binary variables for the proposed model to speed up the solving time and obtain the optimal solution. Our experiments demonstrate that the proposed method is superior to current reference methods for solving the 2DCSP