Subset Sampling and Its Extensions

This paper studies the \emph{subset sampling} problem. The input is a set $\mathcal{S}$ of $n$ records together with a function $\textbf{p}$ that assigns each record $v\in\mathcal{S}$ a probability $\textbf{p}(v)$. A query returns a random subset $X$ of $\mathcal{S}$, where each record $v\in\mathcal{S}$ is sampled into $X$ independently with probability $\textbf{p}(v)$. The goal is to store $\mathcal{S}$ in a data structure to answer queries efficiently. If $\mathcal{S}$ fits in memory, the problem is interesting when $\mathcal{S}$ is dynamic. We develop a dynamic data structure with $\mathcal{O}(1+\mu_{\mathcal{S}})$ expected \emph{query} time, $\mathcal{O}(n)$ space and $\mathcal{O}(1)$ amortized expected \emph{update}, \emph{insert} and \emph{delete} time, where $\mu_{\mathcal{S}}=\sum_{v\in\mathcal{S}}\textbf{p}(v)$. The query time and space are optimal. If $\mathcal{S}$ does not fit in memory, the problem is difficult even if $\mathcal{S}$ is static. Under this scenario, we present an I/O-efficient algorithm that answers a \emph{query} in $\mathcal{O}\left((\log^*_B n)/B+(\mu_\mathcal{S}/B)\log_{M/B} (n/B)\right)$ amortized expected I/Os using $\mathcal{O}(n/B)$ space, where $M$ is the memory size, $B$ is the block size and $\log^*_B n$ is the number of iterative $\log_2(.)$ operations we need to perform on $n$ before going below $B$. In addition, when each record is associated with a real-valued key, we extend the \emph{subset sampling} problem to the \emph{range subset sampling} problem, in which we require that the keys of the sampled records fall within a specified input range $[a,b]$. For this extension, we provide a solution under the dynamic setting, with $\mathcal{O}(\log n+\mu_{\mathcal{S}\cap[a,b]})$ expected \emph{query} time, $\mathcal{O}(n)$ space and $\mathcal{O}(\log n)$ amortized expected \emph{update}, \emph{insert} and \emph{delete} time.Comment: 17 page

2-Selenouridine Triphosphate Synthesis and Se-RNA Transcription

2-Selenouridine (SeU) is one of the naturally occurring modifications of Se-tRNAs (SeU-RNA) at the wobble position of the anticodon loop. Its role in the RNA-RNA interaction, especially during the mRNA decoding, is elusive. To assist the research exploration, herein we report the enzymatic synthesis of the SeU-RNA via 2-selenouridine triphosphate (SeUTP) synthesis and RNA transcription. Moreover, we have demonstrated that the synthesized SeUTP is stable and recognizable by T7 RNA polymerase. Under the optimized conditions, the transcription yield of SeU-RNA can reach up to 85% of the corresponding native RNA. Furthermore, the transcribed SeU-hammerhead ribozyme has the similar activity as the corresponding native, which suggests usefulness of SeU-RNAs in function and structure studies of noncoding RNAs, including the Se-tRNAs

From Supercurrents to Soft Terms

In this paper,hidden sectors of Ferrara-Zumino multiplets with contributions to soft terms coming from quantum supergravity are investigated in framework of gravity mediation. The two-point correlator of Ferrara-Zumino multiplets can be parameterized, which implies the wave function renormalizations of components fields in gravity supermultiplet can be evaluated in relatively simple form. Soft terms are calculated via supercurrent approach. We find gaugino masses are independent of sfermion masses on general grounds. The unification of gaugino masses is not universal. In comparison with general gauge mediation, there are no sum rules for sfermion masses of each generation.Comment: v3, 9 p

Variant Supercurrents and Linearized Supergravity

In this paper the variant supercurrents based on consistency and completion in off-shell N=1 supergravity are studied. We formulate the embedding relations for supersymmetric current and energy tensor into supercurrent multiplet. Corresponding linearized supergravity is obtained with appropriate choice of Wess-Zumino gauge in each gravity supermultiplet.Comment: v1: 9 pp; v2: minor changes; v3: 10 pp, published versio

Size and Location Diagnosis of Rolling Bearing Faults: An Approach of Kernel Principal Component Analysis and Deep Belief Network

Diagnosing incipient faults of rotating machines is very important for reducing economic losses and avoiding accidents caused by faults. However, diagnoses of locations and sizes of incipient faults are very difficult in a noisy background. In this paper, we propose a fault diagnosis method that combines kernel principal component analysis (KPCA) and deep belief network (DBN) to detect sizes and locations of incipient faults on rolling bearings. Effective information of raw vibration signals processed by KPCA method is used as input signals of the DBN of which weights of the first RBM are initialized by contribution rates of principal components. A DBN with complex structures can be cut into a briefer network by KPCA-DBN model. That model reduces network structure and increases convergence rate. As a result, an average test accuracy by KPCA-DBN can reach 99.1% for identification of 12 labels including incipient faults and the training time is 28s which is half of that by DBN model. The average accuracy of rolling bearing location detection nearly gets to 100% and the average accuracy of fault size detection is above 99%. Compared with SVM, BP, CNN, Deep EMD-PCA (Empirical Mode Decomposition-Principal Component Analysis), CNN-SVM and DBN, it is found that training time can be shortened and detection accuracy can be improved by KPCA-DBN model. The proposed method is beneficial to realize sizes and locations detection of incipient faults online

Surface molecular pump enables ultrahigh catalyst activity.

The performance of electrocatalysts is critical for renewable energy technologies. While the electrocatalytic activity can be modulated through structural and compositional engineering following the Sabatier principle, the insufficiently explored catalyst-electrolyte interface is promising to promote microkinetic processes such as physisorption and desorption. By combining experimental designs and molecular dynamics simulations with explicit solvent in high accuracy, we demonstrated that dimethylformamide can work as an effective surface molecular pump to facilitate the entrapment of oxygen and outflux of water. Dimethylformamide disrupts the interfacial network of hydrogen bonds, leading to enhanced activity of the oxygen reduction reaction by a factor of 2 to 3. This strategy works generally for platinum-alloy catalysts, and we introduce an optimal model PtCuNi catalyst with an unprecedented specific activity of 21.8 ± 2.1 mA/cm2 at 0.9 V versus the reversible hydrogen electrode, nearly double the previous record, and an ultrahigh mass activity of 10.7 ± 1.1 A/mgPt

Sound trapping in an open resonator

The ability of sound energy confinement with high-quality factor resonance is of vital importance for acoustic devices requiring high intensity and hypersensitivity in biological ultrasonics, enhanced collimated sound emission (i.e. sound laser) and high-resolution sensing. However, structures reported so far have been experimentally demonstrated with a limited quality factor of acoustic resonances, up to several tens in an open resonator. The emergence of bound states in the continuum makes it possible to realize high quality factor acoustic modes. Here, we report the theoretical design and experimental demonstration of acoustic bound states in the continuum supported by a single open resonator. We predicted that such an open acoustic resonator could simultaneously support three types of bound states in the continuum, including symmetry protected bound states in the continuum, Friedrich-Wintgen bound states in the continuum induced by mode interference, as well as a new type-mirror symmetry induced bound states in the continuum. We also experimentally demonstrated their existence with quality factor up to one order of magnitude greater than the highest quality factor reported in an open resonator

OmniParser: A Unified Framework for Text Spotting, Key Information Extraction and Table Recognition

Recently, visually-situated text parsing (VsTP) has experienced notable advancements, driven by the increasing demand for automated document understanding and the emergence of Generative Large Language Models (LLMs) capable of processing document-based questions. Various methods have been proposed to address the challenging problem of VsTP. However, due to the diversified targets and heterogeneous schemas, previous works usually design task-specific architectures and objectives for individual tasks, which inadvertently leads to modal isolation and complex workflow. In this paper, we propose a unified paradigm for parsing visually-situated text across diverse scenarios. Specifically, we devise a universal model, called OmniParser, which can simultaneously handle three typical visually-situated text parsing tasks: text spotting, key information extraction, and table recognition. In OmniParser, all tasks share the unified encoder-decoder architecture, the unified objective: point-conditioned text generation, and the unified input & output representation: prompt & structured sequences. Extensive experiments demonstrate that the proposed OmniParser achieves state-of-the-art (SOTA) or highly competitive performances on 7 datasets for the three visually-situated text parsing tasks, despite its unified, concise design. The code is available at https://github.com/AlibabaResearch/AdvancedLiterateMachinery.Comment: CVPR 202

Topological Supercavity Resonances in the Finite System

Acoustic resonant cavities play a vital role in modern acoustical systems. The ultrahigh quality-factor resonances are highly desired for some applications such as high-resolution acoustic sensors and acoustic lasers. Here, a class of supercavity resonances is theoretically proposed and experimentally demonstrated in a coupled acoustic resonator system, arising from the merged bound states in the continuum (BICs) in geometry space. Their topological origin is demonstrated by explicitly calculating their topological charges before and after BIC merging, accompanied by charges annihilation. Compared with other types of BICs, they are robust to the perturbation brought by fabrication imperfection. Moreover, it is found that such supercavity modes can be linked with the Friedrich-Wintgen BICs supported by an entire rectangular (cuboid) resonator sandwiched between two rectangular (or circular) waveguides and thus more supercavity modes are constructed. Then, these coupled resonators are fabricated and such a unique phenomenon-moving, merging, and vanishing of BICs-is experimentally confirmed by measuring their reflection spectra, which show good agreement with the numerical simulation and theoretical prediction of mode evolution. The results may find exciting applications in acoustic and photonics, such as enhanced acoustic emission, filtering, and sensing