DeepBL: a deep learning-based approach for in silico discovery of beta-lactamases

Beta-lactamases (BLs) are enzymes localized in the periplasmic space of bacterial pathogens, where they confer resistance to beta-lactam antibiotics. Experimental identification of BLs is costly yet crucial to understand beta-lactam resistance mechanisms. To address this issue, we present DeepBL, a deep learning-based approach by incorporating sequence-derived features to enable high-throughput prediction of BLs. Specifically, DeepBL is implemented based on the Small VGGNet architecture and the TensorFlow deep learning library. Furthermore, the performance of DeepBL models is investigated in relation to the sequence redundancy level and negative sample selection in the benchmark dataset. The models are trained on datasets of varying sequence redundancy thresholds, and the model performance is evaluated by extensive benchmarking tests. Using the optimized DeepBL model, we perform proteome-wide screening for all reviewed bacterium protein sequences available from the UniProt database. These results are freely accessible at the DeepBL webserver at http://deepbl.erc.monash.edu.au/.

Dynamic Reliability Management for FPGA-Based Systems

Radiation tolerance in FPGAs is an important field of research particularly for reliable computation in electronics used in aerospace and satellite missions. The motivation behind this research is the degradation of reliability in FPGA hardware due to single-event effects caused by radiation particles. Redundancy is a commonly used technique to enhance the fault-tolerance capability of radiation-sensitive applications. However, redundancy comes with an overhead in terms of excessive area consumption, latency, and power dissipation. Moreover, the redundant circuit implementations vary in structure and resource usage with the redundancy insertion algorithms as well as number of used redundant stages. The radiation environment varies during the operation time span of the mission depending on the orbit and space weather conditions. Therefore, the overheads due to redundancy should also be optimized at run-time with respect to the current radiation level. In this paper, we propose a technique called Dynamic Reliability Management (DRM) that utilizes the radiation data, interprets it, selects a suitable redundancy level, and performs the run-time reconfiguration, thus varying the reliability levels of the target computation modules. DRM is composed of two parts. The design-time tool flow of DRM generates a library of various redundant implementations of the circuit with different magnitudes of performance factors. The run-time tool flow, while utilizing the radiation/error-rate data, selects a required redundancy level and reconfigures the computation module with the corresponding redundant implementation. Both parts of DRM have been verified by experimentation on various benchmarks. The most significant finding we have from this experimentation is that the performance can be scaled multiple times by using partial reconfiguration feature of DRM, e.g., 7.7 and 3.7 times better performance results obtained for our data sorter and matrix multiplier case studies compared with static reliability management techniques. Therefore, DRM allows for maintaining a suitable trade-off between computation reliability and performance overhead during run-time of an application.

Reliability Approach to Optimal Thruster Configuration Design for Spacecraft Attitude Control Subsystem

An optimal thruster configuration for attitude control subsystem of a spacecraft is presented in this paper. The optimal configuration is designed according to minimum number of required thrusters for satisfying desired reliability with specific redundancy level. The genetic algorithm is employed for optimization process and feasibility of the results is evaluated using algebraic and geometry methods. The main feature of the proposed configuration among feasible configuration with minimum number of required thrusters, which has held to optimal configuration, is that this configuration has maximum reliability and minimum fuel consumption. In addition to feasibility, attitude control performance of some configurations is also examined through the simulation. The results of simulation confirm that the proposed configuration has desirable performance. It is noteworthy to mention that the configuration with maximum number of required thrusters, which is a conventional configuration such that each thruster belongs to only one control channel, has less fuel consumption than optimal configuration. However, the total mass of optimal configuration is less than that of conventional configuration due to a smaller number of thrusters.

Structural Redundancy Assessment of Adjacent Precast Concrete Box-Beam Bridges in Service

Present approaches for assessing bridge redundancy are mainly based on nonlinear finite element (FE) analysis. Unfortunately, the real behavior of bridges in the nonlinear range is difficult to evaluate and a sound basis for the nonlinear FE analysis is not available. In addition, a nonlinear FE analysis is not feasible for practitioners to use. To tackle this problem, a new simplified approach based on linear FE analysis and field load testing is introduced in this paper to address the particular structural feature and topology of adjacent precast concrete box-beam bridges for the assessment of structural redundancy. The approach was first experimentally analyzed on a model bridge and then validated by a case study. The approach agrees well with the existing recognized method while reducing the computation complexity and improving the reliability. The analysis reveals that the level of redundancy of the bridge in the case study does not meet the recommended standard, indicating that the system factor recommended by the current bridge evaluation code for this bridge is inappropriate if considering the field condition. Further research on the redundancy level of this type of bridges is consequently recommended.

R-effect of decomposition of duplicate systems into equiprobable functional nodes

The work is devoted to the reliability of non-recoverable two-channel automation systems and computer equipment. As alternative options, a system with block duplication (SBD) and a system with a quasi-bridge structure (QBS) are considered. SBD in general is a two-channel system consisting of a series connection of duplicated nodes of different reliability. In case of failure of one of the functional subunits (FSU) of the duplicated node using the control and reconfiguration (SCR) scheme, it is masked, withdrawn from the computational process, and reconfigured the system structure in the “Non Stop” operating mode. A QBS system also represents a two-channel structure, but consisting of a serial connection of duplicated nodes of equal reliability, while the technical element intensity (redundancy level) and the functionality of this system are identical to SPD. The QBS system is also a fail-safe system that provides the “Non Stop” mode of operation. The probabilistic-physical calculation method (WF-method) is used as a tool for studying the reliability of systems, which is based on the diffusion distribution of mean-time-to-failure (DN-distribution), specially formalized for assessing the reliability of electronic, electrical and electromechanical elements and systems. While maintaining the redundancy level of the considered two-channel redundant systems, decomposing the channels into equally reliable duplicated nodes leads to the R-effect – an increase in the likelihood of system uptime with an increase in the number of nodes. The presence of the R-effect was established by other methods of calculation and by statistical modeling for both non-restored and restored systems.

Wind Power Performance Optimization Considering Redundancy and Opportunistic Maintenance

In This paper the redundancy and imperfect opportunistic maintenance optimization of a multi-state weighted k-out-of-n system is formulated. The objective is to determine the k-out-of-n system redundancy level and the maintenance strategy which will minimize the wind farm life cycle cost subject to an availability constraint. A new condition based opportunistic maintenance approach is developed. Different component health state thresholds are introduced for imperfect maintenance of failed subsystems and working subsystems and preventive dispatching of maintenance teams. In addition, a simulation method is developed to evaluate the performance measures of the system considering different types of subsystems, maintenance activation delays and durations, limited number of maintenance teams, and discrete inspection of the system. Also, a multi-seed tabu search heuristic algorithm is also proposed to solve the formulated problem. An application to the optimal design of a wind farm is provided to illustrate the proposed approach.

On Semantic Relation Extraction Over Enterprise Data

Relation extraction from the Web data has attracted a lot of attention recently. However, little work has been done when it comes to the enterprise data regardless of the urgent needs to such work in real applications (e.g., E-discovery). One distinct characteristic of the enterprise data (in comparison with the Web data) is its low redundancy. Previous work on relation extraction from the Web data largely relies on the data's high redundancy level and thus cannot be applied to the enterprise data effectively. This chapter reviews related work on relation extraction and introduces an unsupervised hybrid framework REACTOR for semantic relation extraction over enterprise data. REACTOR combines a statistical method, classification, and clustering to identify various types of relations among entities appearing in the enterprise data automatically. REACTOR was evaluated over a real-world enterprise data set from HP that contains over three million pages and the experimental results show its effectiveness.

Monte Carlo optimization of redundancy of nanotechnology computer memories in the conditions of background radiation

The aim of this paper is applying statistical laws and enlargement law to determine a redundancy level of nanotechnology computers with a pre-given statistical confidence. We have tested radiation hardness of MOS memory components (commercial EPROM memory) using both Monte Carlo simulation method and experimental procedure. Then, by using the statistical enlargement law, we have performed the analysis of redundancy optimization of MOS structure for nanotechnology computers, under the influence of background radiation, and obtained more than satisfying results.

Comparison of estimates calculated on the energy flow problem basis and using testing equations method

The article is devoted to the electrical energy measurements estimates calculation. Automatic Meter Reading systems are the source of measurements. Two methods are compared. The first one is based on the energy flow problem, which allows to receive the estimates of the electrical energy flows and losses on all elements of the electrical network. Calculations using the first method were made using the software product “Balance”. The second technique is simplified and uses a system of testing equations to calculate the measurements estimates. Comparison showed the use of a simplified procedure gives adequate accuracy on condition of sufficient redundancy level.