SNSeg: An R Package for Time Series Segmentation via Self-Normalization

Time series segmentation aims to identify potential change-points in a sequence of temporally dependent data, so that the original sequence can be partitioned into several homogeneous subsequences. It is useful for modeling and predicting non-stationary time series and is widely applied in natural and social sciences. Existing segmentation methods primarily focus on only one type of parameter changes such as mean and variance, and they typically depend on laborious tuning or smoothing parameters, which can be challenging to choose in practice. The self-normalization based change-point estimation framework SNCP by Zhao et al. (2022), however, offers users more flexibility and convenience as it allows for change-point estimation of different types of parameters (e.g. mean, variance, quantile and autocovariance) in a unified fashion, and requires effortless tuning. In this paper, the R package SNSeg is introduced to implement SNCP for segmentation of univariate and multivariate time series. An extension of SNCP, named SNHD, is also designed and implemented for change-point estimation in the mean vector of high-dimensional time series. The estimated changepoints as well as segmented time series are available with graphical tools. Detailed examples of SNSeg are given in simulations of multivariate autoregressive processes with change-points

Information Retrieval and Classification of Real-Time Multi-Source Hurricane Evacuation Notices

For an approaching disaster, the tracking of time-sensitive critical information such as hurricane evacuation notices is challenging in the United States. These notices are issued and distributed rapidly by numerous local authorities that may spread across multiple states. They often undergo frequent updates and are distributed through diverse online portals lacking standard formats. In this study, we developed an approach to timely detect and track the locally issued hurricane evacuation notices. The text data were collected mainly with a spatially targeted web scraping method. They were manually labeled and then classified using natural language processing techniques with deep learning models. The classification of mandatory evacuation notices achieved a high accuracy (recall = 96%). We used Hurricane Ian (2022) to illustrate how real-time evacuation notices extracted from local government sources could be redistributed with a Web GIS system. Our method applied to future hurricanes provides live data for situation awareness to higher-level government agencies and news media. The archived data helps scholars to study government responses toward weather warnings and individual behaviors influenced by evacuation history. The framework may be applied to other types of disasters for rapid and targeted retrieval, classification, redistribution, and archiving of real-time government orders and notifications

BP-NUCA: Cache Pressure-Aware Migration for High-Performance Caching in CMPs

As the momentum behind Chip Multi-Processors (CMPs) continues to grow, Last Level Cache (LLC) management becomes a crucial issue to CMPs because off-chip accesses often involve a big latency. Private cache design is distinguished by smaller local access latency, good performance isolation and easy scalability, thus is becoming an attractive design alternative for LLC of CMPs. This paper proposes Balanced Private Non-Uniform Cache Architecture (BP-NUCA), a new LLC architecture that starts from private cache design for smaller local access latency and good performance isolation, then introduces a low cost mechanism to dynamically migrate private blocks among peer private caches of LLC to improve the overall space utilization. BP-NUCA achieves this by measuring the cache access pressure level that each cache set experiences at runtime and then using the information to guide block migration among different private caches of LLC. A heavily accessed set, namely a set with high access pressure level, is allowed to migrate its evicted blocks to peer private caches, replacing blocks of sets which are with the same index and have low access pressure level. By migrating blocks from heavily accessed cache sets to less accessed cache sets, BP-NUCA effectively balances space utilization of LLC among different cores. Experimental results using a full system CMP simulator show that BP-NUCA improves the overall throughput by as much as 20.3 %, 12.4 %, 14.5 % and 18.0 % (on average 7.7 %, 4.4 %, 4.0 % and 6.1 %) over private cache, shared cache, shared cache management scheme UCP and private cache organization CC respectively on a 4-core CMP for SPEC CPU2006 benchmarks

MBTFNet: Multi-Band Temporal-Frequency Neural Network For Singing Voice Enhancement

A typical neural speech enhancement (SE) approach mainly handles speech and noise mixtures, which is not optimal for singing voice enhancement scenarios. Music source separation (MSS) models treat vocals and various accompaniment components equally, which may reduce performance compared to the model that only considers vocal enhancement. In this paper, we propose a novel multi-band temporal-frequency neural network (MBTFNet) for singing voice enhancement, which particularly removes background music, noise and even backing vocals from singing recordings. MBTFNet combines inter and intra-band modeling for better processing of full-band signals. Dual-path modeling are introduced to expand the receptive field of the model. We propose an implicit personalized enhancement (IPE) stage based on signal-to-noise ratio (SNR) estimation, which further improves the performance of MBTFNet. Experiments show that our proposed model significantly outperforms several state-of-the-art SE and MSS models

RIP1 autophosphorylation is promoted by mitochondrial ROS and is essential for RIP3 recruitment into necrosome

韩家淮教授课题组的这项研究揭示了活性氧簇（ROS）通过直接特异地氧化受体相互作用丝氨酸/苏氨酸激酶1（RIP1）上的三个关键的半胱氨酸，进而特异地增强RIP1在S161上的自磷酸化，从而促进坏死小体的形成和程序性细胞坏死的发生。证实了RIP1的激酶活性在程序性细胞坏死中的主要功能是自磷酸化S161，且S161就是人们长期寻找的RIP1上与坏死相关的功能性磷酸化位点。坏死小体的形成是程序性细胞坏死发生的必要复合物，而S161的磷酸化是RIP1有效募集RIP3形成有功能的坏死小体所必需的。由于ROS的产生依赖于坏死小体里的RIP3的功能，因此ROS介导了程序性坏死通路里的正反馈调控。研究阐明了ROS促进程序性细胞坏死的分子机制，回答了领域内长期存在的两个科学问题，对全面解析程序性坏死机制并协助疾病治疗具有重要意义。 张荧荧和苏晟为该论文的共同第一作者。该项研究得到了973计划和国家自然科学基金委员会重点和重大研究计划项目的经费支持。【Abstract】Necroptosis is a type of programmed cell death with great significance in many pathological processes. Tumour necrosis factor-a(TNF), a proinflammatory cytokine, is a prototypic trigger of necroptosis. It is known that mitochondrial reactive oxygen species (ROS) promote necroptosis, and that kinase activity of receptor interacting protein 1 (RIP1) is required for TNF-induced necroptosis. However, how ROS function and what RIP1 phosphorylates to promote necroptosis are largely unknown. Here we show that three crucial cysteines in RIP1 are required for sensing ROS, and ROS subsequently activates RIP1 autophosphorylation on serine residue 161 (S161). The major function of RIP1 kinase activity in TNF-induced necroptosis is to autophosphorylate S161. This specific phosphorylation then enables RIP1 to recruit RIP3 and form a functional necrosome, a central controller of necroptosis. Since ROS induction is known to require necrosomal RIP3, ROS therefore function in a positive feedback circuit that ensures effective induction of necroptosis.This work was supported by the National Natural Science Foundation of China (91029304, 31420103910, 31330047 and 81630042), the National Basic Research Program of China (973 Program; 2015CB553800, 2013CB944903, 2014CB541804), the 111 Project (B12001), the National Science Foundation of China for Fostering Talents in Basic Research (J1310027)

Effect of Ultrasonic Surface Rolling Process on Surface Properties and Microstructure of 6061 Aluminum Alloy

Nano-surface layers were prepared on the surface of 6061 aluminum alloy using the ultrasonic surface rolling process (USRP). The surface morphology, surface roughness, microstructure, hardness, and corrosion resistance of 6061 aluminum alloy were systematically characterized using X-ray diffraction (XRD), laser scanning confocal microscopy (LSCM), optical microscope(OM), scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), and other testing methods. The results showed that ultrasonic surface rolling strengthening did not change the surface phase composition of 6061 aluminum alloy. It changed the size of the surface phases and the distance between the phases while refining the surface grains. The static pressures has a great influence on the surface properties of 6061 aluminum alloy. The best surface properties were obtained under 500N static pressures. The surface hardness reached 129.5HV0.5, the surface morphology was flat and continuous, the surface roughness was reduced to Ra0.191μm, and the corrosion resistance was significantly improved

A MICROWAVE DIGITAL FREQUENCY SYNTHESIZER USED FOR S-BAND TELEMETRY RECEIVER

International Telemetering Conference Proceedings / October 27-30, 1997 / Riviera Hotel and Convention Center, Las Vegas, NevadaThis paper describes a kind of Microwave Digital Frequency Synthesizer used for S-band telemetry receivers. As well known many modern electronic systems employ a Frequency Synthesizer whose spectral purity is critical. The characteristics of a PLL (Phase-Locked Loop) Frequency Synthesizer, such as frequency resolution, phase noise, spurious suppression and switch time, should be compromised in our design. A heterodyne Frequency Synthesis is often considered as a good approach to solve the problem. But it is complicated in structure and circuit. A variable-reference-driven PLL Frequency Synthesizer was introduced which can give an improved trade-off among frequency resolution, phase noise, spurious suppression. In this paper the phase noise and spurious suppression characteristic of variable-reference-driven PLL Frequency Synthesizer is analyzed theoretically and compared with that of the heterodyne Frequency Synthesizer. For engineering application, a practical Microwave Digital Frequency Synthesizer used for telemetry receiver has been designed, which is characterized by simply structure, low phase noise and low spurious output. The output spectrum of experimental measurements is given.International Foundation for TelemeteringProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection

Differentially Private Autocorrelation Time-Series Data Publishing Based on Sliding Window

Privacy protection is one of the major obstacles for data sharing. Time-series data have the characteristics of autocorrelation, continuity, and large scale. Current research on time-series data publication mainly ignores the correlation of time-series data and the lack of privacy protection. In this paper, we study the problem of correlated time-series data publication and propose a sliding window-based autocorrelation time-series data publication algorithm, called SW-ATS. Instead of using global sensitivity in the traditional differential privacy mechanisms, we proposed periodic sensitivity to provide a stronger degree of privacy guarantee. SW-ATS introduces a sliding window mechanism, with the correlation between the noise-adding sequence and the original time-series data guaranteed by sequence indistinguishability, to protect the privacy of the latest data. We prove that SW-ATS satisfies ε-differential privacy. Compared with the state-of-the-art algorithm, SW-ATS is superior in reducing the error rate of MAE which is about 25%, improving the utility of data, and providing stronger privacy protection