A variable-precision square root implementation for field programmable gate arrays

Applications requiring variable-precision arithmetic often rely on software implementations because custom hardware is either unavailable or too costly to build. By using the flexibility of the Xilinx XC4010 field programmable gate arrays, we present a hardware implementation of square root that is easily tailored to any desired precision. Our design consists of three types of modules: a control logic module, a data path module to extend the precision in 4-bit increments, and an interface module to span multiple chips. Our data path design avoids the common problem of large fan-out delay in the critical path. Cycle time is independent of precision, and operation latency can be independent of interchip communication delays.Notation S_j square root digit of weight 2^–j - S _j {–1, 0, 1} - S[j] computed square root value as of stepj - S _j ^s sign bit in the representation ofS _j in sign and magnitude form - S _j ^m magnitude bit in the representation ofS _j in sign and magnitude form - w[j] residual at stepj in two's complement carry-save representation - a sum vector in the carry-save representation of 2w[j] - b carry vector in the carry-save representation of 2w[j] - a _i bit of weight 2^–i in the sum vector,a - b_i bit of weight 2^–i in the carry vector,b - T[j]=–S[j – 1]s_j – s _j ² 2^–(j+1) T _i bit of weight 2^–i inT     

State of the Art of Molecular Visualization in Immersive Virtual Environments

Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head-mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.     

Diagnostic performance of edited 2HG MR spectroscopy of central glioma in the clinical environment

Magnetic Resonance Materials in Physics, Biology and Medicine - Oncometabolite D-2-hydroxyglutarate (2HG) is pooled in isocitrate dehydrogenase (IDH)-mutant glioma cells. Detecting 2HG by MR...     

Evolutionary design of neural network architectures: a review of three decades of research

We present a comprehensive review of the evolutionary design of neural network architectures. This work is motivated by the fact that the success of an Artificial Neural Network (ANN) highly depends on its architecture and among many approaches Evolutionary Computation, which is a set of global-search methods inspired by biological evolution has been proved to be an efficient approach for optimizing neural network structures. Initial attempts for automating architecture design by applying evolutionary approaches start in the late 1980s and have attracted significant interest until today. In this context, we examined the historical progress and analyzed all relevant scientific papers with a special emphasis on how evolutionary computation techniques were adopted and various encoding strategies proposed. We summarized key aspects of methodology, discussed common challenges, and investigated the works in chronological order by dividing the entire timeframe into three periods. The first period covers early works focusing on the optimization of simple ANN architectures with a variety of solutions proposed on chromosome representation. In the second period, the rise of more powerful methods and hybrid approaches were surveyed. In parallel with the recent advances, the last period covers the Deep Learning Era, in which research direction is shifted towards configuring advanced models of deep neural networks. Finally, we propose open problems for future research in the field of neural architecture search and provide insights for fully automated machine learning. Our aim is to provide a complete reference of works in this subject and guide researchers towards promising directions.

     

Selective Al-Ti reactivity in laser-processed Al/Ti multilayers

Multilayers consisting of five (Al/Ti) bilayers were deposited on (100) silicon wafers. On top was deposited the Ti layer, aimed at preventing Al from diffusing to the surface upon laser treatment. The total thickness of the thin-film structure was 200?nm. Laser irradiations with Nd:YAG picoseconds laser pulses in the defocused regime were performed in air. Laser beam energy was 4?mJ and laser spot diameter on the sample surface was 3?mm (fluence 0.057?J?cm^?2). The samples were treated with different numbers of laser pulses. Structural characterizations were performed by different analytical methods and nano-hardness was also measured. Laser processing induced layer intermixing, formation of titanium aluminides, oxidation of the surface titanium layer and enhanced surface roughness. Aluminum appears at the sample surface only for the highest density of laser irradiation. Laser processing induces increment of nano-hardness by approximately 20% and decrease of residual Young’s modulus for a few percentages from the starting value of the untreated samples. These results can be interesting toward achieving structures with a selective extent of Al-Ti reactivity in this multilayered system, within the development of biocompatible materials.     

Multifunctional Gadolinium‐Doped Mesoporous TiO2 Nanobeads: Photoluminescence,Enhanced Spin Relaxation,and Reactive Oxygen Species Photogeneration,Beneficial for Cancer Diagnosis and Treatment

Materials with controllable multifunctional abilities for optical imaging (OI) and magnetic resonant imaging (MRI) that also can be used in photodynamic therapy are very interesting for future applications. Mesoporous TiO₂ sub‐micrometer particles are doped with gadolinium to improve photoluminescence functionality and spin relaxation for MRI, with the added benefit of enhanced generation of reactive oxygen species (ROS). The Gd‐doped TiO₂ exhibits red emission at 637 nm that is beneficial for OI and significantly improves MRI relaxation times, with a beneficial decrease in spin–lattice and spin–spin relaxation times. Density functional theory calculations show that Gd³⁺ ions introduce impurity energy levels inside the bandgap of anatase TiO₂, and also create dipoles that are beneficial for charge separation and decreased electron–hole recombination in the doped lattice. The Gd‐doped TiO₂ nanobeads (NBs) show enhanced ability for ROS monitored via ^?OH radical photogeneration, in comparison with undoped TiO₂ nanobeads and TiO₂ P25, for Gd‐doping up to 10%. Cellular internalization and biocompatibility of TiO₂@x Gd NBs are tested in vitro on MG‐63 human osteosarcoma cells, showing full biocompatibility. After photoactivation of the particles, anticancer trace by means of ROS photogeneration is observed just after 3 min irradiation.     

New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management

Greening the supply chain is an increasingly important concern for many business enterprises and a challenge for logistics management. Critical functions within green supply chain management are internal improvements and selection of green suppliers. This study proposes a novel, hybrid model that addresses dependent relationships between various criteria and the vague information coming from decision-makers. The Decision-making Trial and Evaluation Laboratory (DEMATEL) technique structures the relationships among criteria, thereby constructing an influential network relationship map (INRM). Meanwhile the DEMATEL-based, analytical network process (ANP) method aids in obtaining influential weights of the criteria. Decision-makers may hold diverse opinions and preferences due to incomplete information, differences in knowledge or simply conflicts that are inherent between various departments. This can make it difficult to judge the performance of alternatives. One remedy is to apply a modified COmplex PRoportional ASsessment of alternatives with Grey relations. Next, this is applied to improve each criterion for integration of the performance values obtained in closing the aspiration level from different expert opinions based on INRM. An empirical example using data from a Taiwanese electronics company is provided to demonstrate our proposed method. The results can provide firms with a knowledge-based understanding of the source of some problems, thus reducing the performance gaps and closing the aspiration levels. Finally, there is a discussion on certain managerial implications.     

Determination of the Optimal Fourier Number on the Dynamic Thermal Transmission

This article represents the result of experimental research on transient heat transfer in a multilayered (heterogeneous) wall. Our non-steady thermal transmission simulation is based on a finite-difference calculation method. The value of a Fourier number shows the similarity of thermal variation in conditional layers of an enclosure. Most scientists recommend using no more than a value of 0.5 for the Fourier number when performing calculations on dynamic (transient) heat transfer. The value of the Fourier number is determined in order to acquire reliable calculation results with optimal accuracy. To compare the results of simulation with experimental research, a transient heat transfer calculation spreadsheet was created. Our research has shown that a Fourier number of around 0.5 or even 0.32 is not sufficient (\({\approx }17\,\%\) of oscillation amplitude) for calculations of transient heat transfer in a multilayered wall. The least distorted calculation results were obtained when the multilayered enclosure was divided into conditional layers with almost equal Fourier number values and when the value of the Fourier number was around 1/6, i.e., approximately 0.17. Statistical deviation analysis using the Statistical Analysis System was applied to assess the accuracy of the spreadsheet calculation and was developed on the basis of our established methodology. The mean and median absolute error as well as their confidence intervals has been estimated by the two methods with optimal accuracy (\({F}_{\mathrm{oMDF}}= 0.177\) and \(F_{\mathrm{oEPS}}= 0.1633\) values).