Polar codes have emerged as important error correction codes due to their capacity-achieving property. Successive cancellation (SC) algorithm is viewed as a good candidate for hardware design of ...polar decoders due to its low complexity. However, for (n, k) polar codes, the long latency of SC algorithm of (2n-2) is a bottleneck for designing high-throughput polar decoder. In this paper, we present a novel reformulation for the last stage of SC decoding. The proposed reformulation leads to two benefits. First, critical path and hardware complexity in the last stage of SC algorithm is significantly reduced. Second, 2 bits can be decoded simultaneously instead of 1 bit. As a result, this new decoder, referred to as 2b-SC decoder, reduces latency from (2n-2) to (1.5n-2) without performance loss. Additionally, overlapped-scheduling, precomputation and look-ahead techniques are used to design two additional decoders referred to as 2b-SC-Overlapped-scheduling decoder and 2b-SC-Precomputation decoder, respectively. All three architectures offer significant advantages with respect to throughput and hardware efficiency. Compared to known prior least-latency SC decoder, the 2b-SC-Precomputation decoder has 25% less latency. Synthesis results show that the proposed (1024, 512) 2b-SC-Precomputation decoder can achieve at least 4 times increase in throughput and 40% increase in hardware efficiency.
Many methods for quantifying chlorinated paraffins (CPs) yield only a total concentration of the mixture as a single value. With appropriate analytical instrumentation and quantification methods, ...more reliable and detailed analysis can be performed by quantifying total concentrations of short-, medium-, and long-chain CPs (SCCPs, MCCPs, and LCCPs), and in the current optimal situation by quantifying individual carbon-chlorine congener groups (CnClm). Sample extraction and clean-up methods for other persistent organochlorines that have been adapted for recovery of CPs must be applied prior to quantification with appropriate quality assurance and quality control to ensure applicability of the methods for SCCPs, MCCPs, and LCCPs. Part critical review, part tutorial, and part perspective, this paper provides practical guidance to analytical chemists who are interested in establishing a method for analysis of CPs in their lab facilities using commercial reference standards, or for expanding existing analysis of total CPs or SCCPs to analysis of SCCPs, MCCPs, and LCCPs, or to analysis of CnClm congener groups.
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•Guidance for establishing analytical methods for CPs with available lab facilities and commercial reference standards.•A review of pretreatment methods for environmental, biomonitoring, and consumer product analysis.•Analytical instrumentation is critical in distinguishing S/M/LCCPs.•Principles of quantifying CPs are summarized as ten equations.
Nonnegative matrix factorization (NMF) has become a popular dimension-reduction method and has been widely applied to image processing and pattern recognition problems. However, conventional NMF ...learning methods require the entire dataset to reside in the memory and thus cannot be applied to large-scale or streaming datasets. In this paper, we propose an efficient online RSA-NMF algorithm (OR-NMF) that learns NMF in an incremental fashion and thus solves this problem. In particular, OR-NMF receives one sample or a chunk of samples per step and updates the bases via robust stochastic approximation. Benefitting from the smartly chosen learning rate and averaging technique, OR-NMF converges at the rate of in each update of the bases. Furthermore, we prove that OR-NMF almost surely converges to a local optimal solution by using the quasi-martingale. By using a buffering strategy, we keep both the time and space complexities of one step of the OR-NMF constant and make OR-NMF suitable for large-scale or streaming datasets. Preliminary experimental results on real-world datasets show that OR-NMF outperforms the existing online NMF (ONMF) algorithms in terms of efficiency. Experimental results of face recognition and image annotation on public datasets confirm the effectiveness of OR-NMF compared with the existing ONMF algorithms.
A cage‐based metal–organic framework (Ni‐NKU‐101) with biphenyl‐3,3’,5,5’‐tetracarboxylic acid was synthesized via solvothermal method. Ni‐NKU‐101 contains two types of cages based on trinuclear and ...octa‐nuclear nickel‐clusters that are connected with each other by the 4‐connected ligands, to form a 3D framework with a new topology. A mixed‐metal strategy was used to synthesize isostructural bimetallic MOFs of MxNi1‐x‐NKU‐101 (M=Mn, Co, Cu, Zn). The electrocatalytic studies showed that the hydrogen evolution reaction (HER) activity of CuxNi1‐x‐NKU‐101 is much higher than that of other MxNi1‐x‐NKU‐101 catalysts in acidic aqueous solution, owing to the synergistic effect of the bimetallic centers. The optimized Cu0.19Ni0.81‐NKU‐101 has an overpotential of 324 mV at 10 mA cm−2 and a Tafel slope of 131 mV dec−1. The mechanism of HER activity over these bimetallic MOF‐based electrocatalysts are discussed in detail.
A cage‐based MOF (Ni‐NKU‐101) was synthesized with biphenyl‐3,3’,5,5’‐tetracarboxylic acid. Ni‐NKU‐101 contains two types of cages based on nickel‐clusters to form a 3D framework. A series of isostructural bimetallic MxNi1‐x‐NKU‐101 were synthesized and studied for the electrochemical HER. Among them, the bimetallic CuxNi1‐x‐NKU‐101 family exhibit improved electrocatalytic HER performance in 0.5 M sulfuric acid electrolyte, owing to the synergistic effect of the Cu/Ni bimetallic centers.
Microbiome sequencing data normalization is crucial for eliminating technical bias and ensuring accurate downstream analysis. However, this process can be challenging due to the high frequency of ...zero counts in microbiome data. We propose a novel reference-based normalization method called normalization via rank similarity (RSim) that corrects sample-specific biases, even in the presence of many zero counts. Unlike other normalization methods, RSim does not require additional assumptions or treatments for the high prevalence of zero counts. This makes it robust and minimizes potential bias resulting from procedures that address zero counts, such as pseudo-counts. Our numerical experiments demonstrate that RSim reduces false discoveries, improves detection power, and reveals true biological signals in downstream tasks such as PCoA plotting, association analysis, and differential abundance analysis.
Rapid growth of sensors and the Internet of Things is transforming society, the economy and the quality of life. Many devices at the extreme edge collect and transmit sensitive information wirelessly ...for remote computing. The device behavior can be monitored through side-channel emissions, including power consumption and electromagnetic (EM) emissions. This study presents a holistic self-testing approach incorporating nanoscale EM sensing devices and an energy-efficient learning module to detect security threats and malicious attacks directly at the front-end sensors. The built-in threat detection approach using the intelligent EM sensors distributed on the power lines is developed to detect abnormal data activities without degrading the performance while achieving good energy efficiency. The minimal usage of energy and space can allow the energy-constrained wireless devices to have an on-chip detection system to predict malicious attacks rapidly in the front line.
The main theme of this paper is to present a new digital-controlled technique for battery charger to achieve constant current and voltage control while not requiring current feedback. The basic idea ...is to achieve constant current charging control by limiting the duty cycle of charger. Therefore, the current feedback signal is not required and thereby reducing the cost of A/D converter, current sensor, and computation complexity required for current control. Moreover, when the battery voltage is increased to the preset voltage level using constant current charge, the charger changes the control mode to constant voltage charge. A digital-controlled charger is designed and implemented for uninterrupted power supply (UPS) applications. The charger control is based upon the proposed control method in software. As a result, the UPS control, including boost converter, charger, and inverter control can be realized using only one low cost MCU. Experimental results demonstrate that the effectiveness of the design and implementation.
Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases ...can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to form a whole. For practical classification tasks, however, NMF ignores both the local geometry of data and the discriminative information of different classes. In addition, existing research results show that the learned basis is unnecessarily parts-based because there is neither explicit nor implicit constraint to ensure the representation parts-based. In this paper, we introduce the manifold regularization and the margin maximization to NMF and obtain the manifold regularized discriminative NMF (MD-NMF) to overcome the aforementioned problems. The multiplicative update rule (MUR) can be applied to optimizing MD-NMF, but it converges slowly. In this paper, we propose a fast gradient descent (FGD) to optimize MD-NMF. FGD contains a Newton method that searches the optimal step length, and thus, FGD converges much faster than MUR. In addition, FGD includes MUR as a special case and can be applied to optimizing NMF and its variants. For a problem with 165 samples in R 1600 , FGD converges in 28 s, while MUR requires 282 s. We also apply FGD in a variant of MD-NMF and experimental results confirm its efficiency. Experimental results on several face image datasets suggest the effectiveness of MD-NMF.
Motivation: Identification of functional modules in protein interaction networks is a first step in understanding the organization and dynamics of cell functions. To ensure that the identified ...modules are biologically meaningful, network-partitioning algorithms should take into account not only topological features but also functional relationships, and identified modules should be rigorously validated. Results: In this study we first integrate proteomics and microarray datasets and represent the yeast protein–protein interaction network as a weighted graph. We then extend a betweenness-based partition algorithm, and use it to identify 266 functional modules in the yeast proteome network. For validation we show that the functional modules are indeed densely connected subgraphs. In addition, genes in the same functional module confer a similar phenotype. Furthermore, known protein complexes are largely contained in the functional modules in their entirety. We also analyze an example of a functional module and show that functional modules can be useful for gene annotation. Contact:yuan.33@osu.edu Supplementary Information: Supplementary data are available at Bioinformatics online
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