Computational chemistry aims to autonomously design specific molecules with target functionality. Generative frameworks provide useful tools to learn continuous representations of molecules in a latent space. While modelers could optimize chemical properties, many generated molecules are not synthesizable. To design synthetically accessible molecules that preserve main structural motifs of target molecules, we propose a reaction-embedded and structure-conditioned variational autoencoder. As the latent space jointly encodes molecular structures and their reaction routes, our new sampling method that measures the path-informed structural similarity allows us to effectively generate structurally analogous synthesizable molecules. When targeting out-of-domain as well as in-domain seed structures, our model generates structurally and property-wisely similar molecules equipped with well-defined reaction paths. By focusing on the important region in chemical space, we also demonstrate that our model can design new molecules with even higher activity than the seed molecules.

OBJECTIVE: With the scenario of limited labeled dataset, this paper introduces a deep learning-based approach that leverages Diabetic Retinopathy (DR) severity recognition performance using fundus images combined with wide-field swept-source optical coherence tomography angiography (SS-OCTA). METHODS: The proposed architecture comprises a backbone convolutional network associated with a Twofold Feature Augmentation mechanism, namely TFA-Net. The former includes multiple convolution blocks extracting representational features at various scales. The latter is constructed in a two-stage manner, i.e., the utilization of weight-sharing convolution kernels and the deployment of a Reverse Cross-Attention (RCA) stream. RESULTS: The proposed model achieves a Quadratic Weighted Kappa rate of 90.2% on the small-sized internal KHUMC dataset. The robustness of the RCA stream is also evaluated by the single-modal Messidor dataset, of which the obtained mean Accuracy (94.8%) and Area Under Receiver Operating Characteristic (99.4%) outperform those of the state-of-the-arts significantly. CONCLUSION: Utilizing a network strongly regularized at feature space to learn the amalgamation of different modalities is of proven effectiveness. Thanks to the widespread availability of multi-modal retinal imaging for each diabetes patient nowadays, such approach can reduce the heavy reliance on large quantity of labeled visual data. SIGNIFICANCE: Our TFA-Net is able to coordinate hybrid information of fundus photos and wide-field SS-OCTA for exhaustively exploiting DR-oriented biomarkers. Moreover, the embedded feature-wise augmentation scheme can enrich generalization ability efficiently despite learning from small-scale labeled data.

This paper describes development of a controllerfor bilateral robotic system for tele-echography with delayed communications. The system comprises two identical 6DOF robotic devices based on Stewart-Gough mechanisms, which were developed especially for the sake of the considered application. Controller design is facilitated by a symmetry of the teleoperation setup, in which the master and slave devices have identical geometry, actuation and measurement arrays. To further simplify the analysis, we treat coupling between degrees of freedom as exogenous disturbances and this allows us to split the control problem into six independent IDOF settings. The IDOF problems are addressed then using a novel approach to bilateral teleoperation control, based on a complete parameterization of feasible teleoperators. It allows to intuitively shape teleoperator performance while guaranteeing passivity and thus coupled stability of the system. The potential of the proposed control method is demonstrated with experimental results.

The use of snake-like robots for surgery is a popular choice for intra-luminal procedures. In practice, the requirements for strength, flexibility and accuracy are difficult to be satisfied simultaneously. This paper presents a computational approach for optimizing the design of a snake-like robot using serial rolling-joints and tendons as the base architecture. The method optimizes the design in terms of joint angle range and tendon placement to prevent the tendons and joints from colliding during bending motion. The resulting optimized joints were manufactured using 3D printing. The robot was characterized in terms of workspace, dexterity, precision and manipulation forces. The results show a repeatability as low as 0.9mm and manipulation forces of up to 5.6N.

The most timing critical part of logic design usually contains one or more arithmetic operations, in which addition is commonly involved. The carry-skip adder, which is designed to reduce the time needed to propagate the carry by skipping over groups of consecutive adder stages, is known to be comparable in speed to the carry look-ahead technique while it uses less logic area and less power. Nevertheless, only recently has it become popular, mainly because of its high synthesis complexity and complicated timing analysis, especially false path analysis. In this paper, we address the problem of automatic and systematic synthesis of (true) timing minimal carry-skip adder in the context of the whole design containing the adder. Precisely, unlike the previous works which invariably assume a uniform or a fixed pattern of input arrival times, thus limiting their application to the optimization of an isolated single addition or additions in specific design structures, e.g., final addition in a parallel multiplier, our synthesis algorithm allows to accept any arbitrary, but known in advance, bit-level arrival times of the addends and generates a structure of carry-skip adder that leads to minimize the timing of the whole design. We formulate the carry group (or block) partitioning problem for minimal timing into a dynamic programming problem and solved it effectively. The experimental results with various arithmetic designs show that our synthesis algorithm is able to reduce the circuit timing by up to 16% and 10%, compared with the results produced by the conventional optimal algorithm in [1], which does not support the variation of input times and the algorithm in [2], which nearly optimally supports only a specific pattern of input time variation. In addition, the proposed algorithm is very fast, taking only 2 seconds in synthesizing 256-bit two-level carry-skip adder.

We propose a real-time solution for modeling and tracking multiple 3D objects in unknown environments. Our contribution is two-fold: First, we show how to scale with the number of objects. This is done by combining recent techniques for image retrieval and online Structure from Motion, which can be run in parallel. As a result, tracking 40 objects in 3D can be done within 6 to 25 milliseconds per frame, even under difficult conditions for tracking. Second, we propose a method to let the user add new objects very quickly. The user simply has to select in an image a 2D region lying on the object. A 3D primitive is then fitted to the features within this region, and adjusted to create the object 3D model. In practice, this procedure takes less than a minute.

MapReduce is Google's programming model for easy development of scalable parallel applications which process huge quantity of data on many clusters. Due to its conveniency and efficiency, MapReduce is used in various applications (e.g., Web search services and online analytical processing). However, there are only few good benchmarks to evaluate MapReduce implementations by realistic testsets. In this paper, we present MRBench that is a benchmark for evaluating MapReduce systems. MRBench focuses on processing business oriented queries and concurrent data modifications. To this end, we build MRBench to deal with large volumes of relational data and execute highly complex queries. By MRBench, users can evaluate the performance of MapReduce systems while varying environmental parameters such as data size and the number of (map/reduce) tasks. Our extensive experimental results show that MRBench is a useful tool to benchmark the capability of answering critical business questions.

Many areas of science currently use computing resources as a important part of their research, and many research groups adopt cluster architecture to use them efficiently and manage them easily. Therefore, faulttolerance becomes a very important property for the computing resources. However, fault-tolerant systems have not yet been widely adopted because they are either hard to deploy, hard to use, hard to manage, hard to maintain, or hard to justify. This paper proposes a practical fault-tolerant system for eScience infrastructures. Our system uses checkpoint/ restart mechanism for fault-tolerance, and provides a easy mechanism to integrate with Grid services widely used in eScience. Additionally, we run rigorous tests using scientific applications to verify that our system can be used in clusters. We also describe improvements made to our system to solve various problems that arose when deploying it on a cluster. The experimental results show that not only does our system conform to various types of running environment well, but that it can also be practically deployed in clusters.

The one of the biggest barrier that hinders Internet development is security problem caused by malicious user. In this paper, we deal with distributed denial of service (DDoS) attacks that monopolize network resource, thus result in network or system congestion. Under DDoS attack, its very difficult to provide legitimate users with their fair share of available network resource. This paper proposes MF (minority first) as a traffic metering and control scheme that can provide quick weakness of DDoS attack, while protecting legitimate user's traffic. The key idea of MF scheme is to provide good quality of service (QoS) to sources that use the network resource properly and poor QoS to sources that use network resource so excessively as to result in network congestion. MF scheme is composed of both source-traffic-trunk based metering and queue mapping mechanism for controlling malicious DDoS traffic and legitimate traffic. To show our scheme's excellence, its performance is measured and compared with that of the existing queuing services and static rate-limit through simulation.