Area, Delay, and Power Characteristics of Standard-Cell Implementations of the AES S-Box

Cryptographic substitution boxes (S-boxes) are an integral part of modern block ciphers like the Advanced Encryption Standard (AES). There exists a rich literature devoted to the efficient implementation of cryptographic S-boxes, wherein hardware designs for FPGAs and standard cells received particular attention. In this paper we present a comprehensive study of different standard-cell implementations of the AES S-box with respect to timing (i.e. critical path), silicon area, power consumption, and combinations of these cost metrics. We examine implementations which exploit the mathematical properties of the AES S-box, constructions based on hardware look-up tables, and dedicated low-power solutions. Our results show that the timing, area, and power properties of the different S-box realizations can vary by up to almost an order of magnitude. In terms of area and area-delay product, the best choice are implementations which calculate the S-box output. On the other hand, the hardware look-up solutions are characterized by the shortest critical path. The dedicated low-power implementations do not only reduce power consumption by a large degree, but they also show good timing properties and offer the best power-delay and power-area product, respectively.     

Experimental validation of the linear drive train for a total artificial heart system

In industrialized countries cardiovascular diseases are the major cause of death. Beside heart transplants, which are a limited option due to the limited number of available human donor hearts, Total Artificial Hearts (TAHs) are the only therapy available for some patients with terminal heart diseases. For various reasons a total implantable artificial heart is desirable, but also sets restrictions in terms of weight and dimensions due to the limited space in the human thorax. Therefore a precise requirement profile is needed for the drive design to provide sufficient force for the blood pump and to avoid oversizing of the drive and to prevent blood damage by overheating.     

给电压比较器添加滞后作用

正正反馈是围绕比较器来分配滞后作用的典型方法,前提是比较器的输出与非逆变输入之间具有电阻路径。正反馈形成两个具有(或呈现)固定值的阈值电压。另外,它们还取决于比较器输出级的饱     

Excellent Intrinsic Long-Term Thermal Stability of Co-Evaporated MAPbI3 Solar Cells at 85 °C

Thermal stability is a critical criterion for assessing the long-term stability of perovskite solar cells (PSCs). Here, it is shown that un-encapsulated co-evaporated MAPbI₃ (TE_MAPbI₃) PSCs demonstrate remarkable thermal stability even in an n-i-p structure that employs Spiro-OMeTAD as hole transport material (HTM). TE_MAPbI₃ PSCs maintain over ≈95% and ≈80% of their initial power conversion efficiency (PCE) after 1000 and 3600 h respectively under continuous thermal aging at 85 °C. TE_MAPbI₃ PSCs demonstrate remarkable structural robustness, absence of pinholes, or significant variation in grain sizes, and intact interfaces with the HTM, upon prolonged thermal aging. Here, the main factors driving TE_MAPbI₃ stability are assessed. It is demonstrated that the excellent TE_MAPbI₃ thermal stability is related to the perovskite growth process leading to a compact and almost strain-stress-free film. On the other hand, un-encapsulated PSCs with the same architecture, but incorporating solution-processed MAPbI₃ or Cs_0.05(MA_0.17FA_0.83)_0.95Pb(I_0.83Br_0.17)₃ as active layers, show a complete PCE degradation after 500 h under the same thermal aging condition. These results highlight that the control of the perovskite growth process can substantially enhance the PSCs thermal stability, besides the chemical composition. The TE_MAPbI₃ impressive long-term thermal stability features the potential for field-operating conditions.     

Pluggable SDN framework for managing heterogeneous SDN networks

Software‐defined networking (SDN) is a new network paradigm that is separating the data plane and the control plane of the network, making one or more centralized controllers to supervise the behaviour of the entire network. Different types of SDN controller software exist, and research dealing with the difficulties of consistently integrating these different controller types has mostly been declared future work. In this paper, the Domino framework is proposed, a pluggable SDN framework for managing heterogeneous SDN networks. In contrast to related work, the proposed framework allows research into SDN networks controlled by different types of SDN controllers attempting to standardize the northbound API of them. Domino implements a microservice plugin architecture where users can link different SDN networks to a processing algorithm. Such an algorithm allows for, eg, adapting the flows by building a pipeline using plugins that either invoke other SDN operations or generic data processing algorithms. The Domino framework is evaluated by implementing a proof‐of‐concept implementation, which is tested on the initial requirements. It achieves the modifiability and the interoperability with an average successful exchange ratio of 99.99%. The performance requirements are met for the frequently used commands with an average response time of 0.26 seconds, and the framework can handle at least 72 plugins simultaneously depending on the available amount of RAM. The proposed framework is evaluated by means of the implementation of a shortest path routing algorithm between heterogeneous SDN networks.     

Towards Using Scientific Publications to Automatically Extract Information on Rare Diseases

A small percentage of the population is afflicted by what is called an orphan or a rare disease. All over the world, there are about several thousand of these diseases. When adding up together all the individuals who are affected, it amounts for up to 10% of the US population. Scientific works on these diseases are often poorly financed due to the lack of potential markets for a treatment, which means for patients and clinicians a very limited and scattered access to vital information. To contribute addressing this issue, we present in this paper a new software tool for automating the extraction of information related to rare diseases from scientific publications. More precisely, our contribution consists in a new method of extracting automatically symptoms of these diseases from research papers exploiting a Named Entity Recognition (NER) algorithm based on the numerical statistic Term Frequency - Inverse Document Frequency (TF-IDF). The proposed tool has been tested using PubMed Central (PMC) database.

     

Capacitance DNA bio-chips improved by new probe immobilization strategies

Label-free DNA detection plays a crucial role in developing point-of-care biochips. Capacitance detection is a promising technology for label-free detection. However, data published in literature often show evident time drift, large standard deviation, scattered data points, and poor reproducibility. To address these problems, mercapto-hexanol or similar alkanethiols are usually considered as blocking agents. The aim of the present paper is to investigate new blocking agents to further improve DNA probe surfaces. Data from AFM, SPR, florescence microscopy, and capacitance measurements are used to investigate new lipoate and ethylene-glycol molecules. The new surfaces offer further improvements in terms of diminished detection errors. Film structures are investigated at the nano-scale to justify the detection improvements in terms of probe surface quality. This study demonstrates the superiority of lipoate and ethylene-glycol molecules as blocking candidates when immobilizing molecular probes onto spot surfaces in label-free DNA biochip.     

Semi‐Markovian modelling and performance analysis of variable rate traffic in ATM networks

Semi‐Markovian processes (SMP) serve as a versatile means to model various traffic types generated by sources or superposed from links in ATM networks. An efficient discrete time analysis method is proposed for SMP/G/1 queueing systems to evaluate ATM switches with non‐renewal input. Some basic results are derived for the autocorrelation function of semi‐Markovian processes and for the effect of state space reduction on autocorrelation, which show how to represent correlated traffic with given characteristic by an adequate SMP model of limited size. This revised version was published online in June 2006 with corrections to the Cover Date.     

Computational reflection and its application to platform verification

The complexity of modern hardware design has created the need for higher levels of abstraction, where system modeling is used to integrate modules into complex System-on-Chip (SoCs) platforms. SystemC, and its TLM (Transaction Level Modeling) extensions, have been used for this purpose mainly because of their fast prototyping and simulation features, which allow for early design space exploration. This paper proposes an approach to explore and interact with SystemC models by means of an introspection technique known as Computational Reflection. We use reflection to implement a white-box introspection mechanism called ReflexBox. We show that ReflexBox is a fast, non-intrusive technique that can be used to dynamically gather and inject stimuli into any SystemC module, without the need to use a proprietary SystemC implementation, change the SystemC library, instrument or even inspect the module source code. Our approach can be used to support many different verification tasks like platform debugging, performance evaluation and communication analysis. To show ReflexBox effectiveness we used it in three platforms case studies to address tasks like register inspection, performance analysis and signal replaying for testbench reuse. In all cases we assumed no source code availability and measured the impact on the overall platform performance.     

Extraction and analysis of T waves in electrocardiograms during atrial flutter

Analysis of T waves in the ECG is an essential clinical tool for diagnosis, monitoring, and follow-up of patients with heart dysfunction. During atrial flutter, this analysis has been so far limited by the perturbation of flutter waves superimposed over the T wave. This paper presents a method based on missing data interpolation for eliminating flutter waves from the ECG during atrial flutter. To cope with the correlation between atrial and ventricular electrical activations, the CLEAN deconvolution algorithm was applied to reconstruct the spectrum of the atrial component of the ECG from signal segments corresponding to TQ intervals. The locations of these TQ intervals, where the atrial contribution is presumably dominant, were identified iteratively. The algorithm yields the extracted atrial and ventricular contributions to the ECG. Standard T-wave morphology parameters (T-wave amplitude, T peak-T end duration, QT interval) were measured. This technique was validated using synthetic signals, compared to average beat subtraction in a patient with a pacemaker, and tested on pseudo-orthogonal ECGs from patients in atrial flutter. Results demonstrated improvements in accuracy and robustness of T-wave analysis as compared to current clinical practice.