Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunc...
Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunctioning of macromolecular interactions is also linked to a number of diseases. Structural knowledge of the macromolecular interaction allows one to understand the interaction's mechanism, determine its functional implications and characterize the effects of genetic variations, such as single nucleotide polymorphisms, on the interaction. Unfortunately, until now the interactions mediated by different types of macromolecules, e.g. protein-protein interactions or protein-DNA interactions, are collected into individual and unrelated structural databases. This presents a significant obstacle in the analysis of macromolecular interactions. For instance, the homogeneous structural interaction databases prevent scientists from studying structural interactions of different types but occurring in the same macromolecular complex. Here, we introduce DOMMINO 2.0, a structural Database Of Macro-Molecular INteractiOns. Compared to DOMMINO 1.0, a comprehensive database on protein-protein interactions, DOMMINO 2.0 includes the interactions between all three basic types of macromolecules extracted from PDB files. DOMMINO 2.0 is automatically updated on a weekly basis. It currently includes ∼1 040 000 interactions between two polypeptide subunits (e.g. domains, peptides, termini and interdomain linkers), ∼43 000 RNA-mediated interactions, and ∼12 000 DNA-mediated interactions. All protein structures in the database are annotated using SCOP and SUPERFAMILY family annotation. As a result, protein-mediated interactions involving protein domains, interdomain linkers, C- and N-termini, and peptides are identified. Our database provides an intuitive web interface, allowing one to investigate interactions at three different resolution levels: whole subunit network, binary intera
This paper describes a real-time implementation of precise synchronization between a master and slave node. The nodes were both implemented on separate Texas Instruments DSP boards with real-time software implemented ...
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Simulatability condition is a fundamental concept in studying key generation over a non-authenticated public channel, in which Eve is active and can intercept, modify and falsify messages exchanged over the non-authen...
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Simulatability condition is a fundamental concept in studying key generation over a non-authenticated public channel, in which Eve is active and can intercept, modify and falsify messages exchanged over the non-authenticated public channel. Using this condition, Maurer and Wolf showed a remarkable “all or nothing” result: if the simulatability condition does not hold, the key capacity over the non-authenticated public channel will be the same as that of the case with a passive Eve, while the key capacity over the non-authenticated channel will be zero if the simulatability condition holds. However, two questions remain open so far: 1) For a given joint probability mass function (PMF), are there efficient algorithms (polynomial complexity algorithms) for checking whether the simulatability condition holds or not?; and 2) If the simulatability condition holds, are there efficient algorithms for finding the corresponding attack strategy? In this paper, we answer these two open questions affirmatively. In particular, for a given joint PMF, we construct a linear programming (LP) problem and show that the simulatability condition holds if and only if the optimal value obtained from the constructed LP is zero. Furthermore, we construct another LP and show that the minimizer of the newly constructed LP is a valid attack strategy. Both LPs can be solved with a polynomial complexity.
This paper presents a design technique using a digitally-controlled delay line (DCDL) for the generation of sub-picosecond-jitter ADC sampling clock phases from a low-cost low-frequency clock source. In a test chip fa...
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This paper presents a design technique using a digitally-controlled delay line (DCDL) for the generation of sub-picosecond-jitter ADC sampling clock phases from a low-cost low-frequency clock source. In a test chip fabricated in a 0.18-μm CMOS technology, measured rms jitter is 0.28ps for each delay stage and 0.9ps through a 10 stage delay line.
This paper considers the problem of key generation with a helper, which might be subjected to Byzantine attacks. If the helper is not under attack, it will follow the key generation protocol. However, if the helper is...
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ISBN:
(纸本)9781467363068
This paper considers the problem of key generation with a helper, which might be subjected to Byzantine attacks. If the helper is not under attack, it will follow the key generation protocol. However, if the helper is under attack, it will modify the messages to mislead the key generation parties. We propose a scheme that can benefit from the helper, if the helper is not under attack, and can detect the presence of the attack, if the helper is under Byzantine attacks. We show that our key generation scheme can achieve the secret key capacity when the helper is not under attack. At the same time, if the helper is under Byzantine attacks, our scheme can achieve the key rate as if the attacker is a passive eavesdropper.
In recent years, deep learning has attracted lots of research interests for pattern recognition and artificial intelligence. PCA Network (PCANet) is a simple deep learning network with highly competitive performance f...
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In recent years, deep learning has attracted lots of research interests for pattern recognition and artificial intelligence. PCA Network (PCANet) is a simple deep learning network with highly competitive performance for texture classification and object recognition. When compared to other deep neural networks such as convolutional neural network (CNN), PCANet has much simpler structure, which makes it attractive for hardware design on an FPGA. In this paper, an efficient, high-throughput, pipeline architecture is proposed for the PCANet classifier. The implementation on an FPGA is more than 1,000 times faster than software execution on a general purpose processor. When evaluated using the MNIST handwritten digits dataset, the PCANet design results an accuracy of about 99.46%.
In this short paper, we present an analysis for co- channel interference between femtocell (FC) downlink transmissions in a purely homogeneous femtocell type network. We assume no direct coordination between FCs since...
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ISBN:
(纸本)9781479980925
In this short paper, we present an analysis for co- channel interference between femtocell (FC) downlink transmissions in a purely homogeneous femtocell type network. We assume no direct coordination between FCs since, as of Release 12, no low-latency links are provided for intra-cell communication. Our simulations utilize VoIP traffic models to understand the interference impact of QoS oriented traffic as network densities increase. The preliminary results demonstrate the reduced performance of FCs under this co-channel model when resource allocations depend on existing sensing and traditional usage of sensing information.
Motivated by distributed inference over big datasets problems, we study multi-terminal distributed hypothesis testing problems in which each terminal has data related to only one random variable. We consider a case of...
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ISBN:
(纸本)9781467377058
Motivated by distributed inference over big datasets problems, we study multi-terminal distributed hypothesis testing problems in which each terminal has data related to only one random variable. We consider a case of practical interest in which each terminal is allowed to send zero-rate messages to a decision maker. Subject to a constraint that the error exponent of the type 1 error probability is larger than a certain level, we characterize the best error exponent of the type 2 error probability using basic properties of the r-divergent sequences.
In this paper, we analyze the performance of high-velocity connected vehicles network. We assess the V2V (vehicle-to-vehicle) architecture in two different scenarios. The first scenario involves direct communication b...
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ISBN:
(纸本)9781479980895
In this paper, we analyze the performance of high-velocity connected vehicles network. We assess the V2V (vehicle-to-vehicle) architecture in two different scenarios. The first scenario involves direct communication between source and the destination via a non-line-of-sight (NLOS) link. The second scenario uses line-of-sight (LOS) multi-hop relay links to connect source and destination. For both scenarios, we use two performance metrics: the probability of error and latency. The results of our analysis show the performance limits of this type of networks in practical situations. For example, the LOS network outperforms the NLOS one at an SNR of 7dB if the connected vehicles are moving at consistent velocities, and the number of hops is limited to 8.
Motivated by distributed inference over big datasets problems, we study multi-terminal distributed hypothesis testing problems in which each terminal has data related to only one random variable. Due to the restrictio...
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Motivated by distributed inference over big datasets problems, we study multi-terminal distributed hypothesis testing problems in which each terminal has data related to only one random variable. Due to the restriction of one-shot communication, we consider the distributed testing against independence problem when interaction among the encoders are allowed. Subject to type 1 error probability and communication rates constraints, we first provide a scheme for the general case and then show that this scheme is optimal for some special cases.
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