A New Method for Piecewise Linear Representation of Time Series Data

AbstractIn various methods of modeling of time series, the piecewise linear representation has the advantage of being simple, straightforward and supporting dynamic incremental update of time series. This paper proposed a new method of Piecewise Linear Representation of Time Series based on Slope Change Threshold (SCT). Detailed experiments on real datasets from various fields show that STC representation, compared with several other Piecewise Linear Representations, can be easily calculated and has a high degree of fitting

A solution processed flexible nanocomposite electrode with efficient light extraction for organic light emitting diodes.

Highly efficient organic light emitting diodes (OLEDs) based on multiple layers of vapor evaporated small molecules, indium tin oxide transparent electrode, and glass substrate have been extensively investigated and are being commercialized. The light extraction from the exciton radiative decay is limited to less than 30% due to plasmonic quenching on the metallic cathode and the waveguide in the multi-layer sandwich structure. Here we report a flexible nanocomposite electrode comprising single-walled carbon nanotubes and silver nanowires stacked and embedded in the surface of a polymer substrate. Nanoparticles of barium strontium titanate are dispersed within the substrate to enhance light extraction efficiency. Green polymer OLED (PLEDs) fabricated on the nanocomposite electrode exhibit a maximum current efficiency of 118 cd/A at 10,000 cd/m(2) with the calculated external quantum efficiency being 38.9%. The efficiencies of white PLEDs are 46.7 cd/A and 30.5%, respectively. The devices can be bent to 3 mm radius repeatedly without significant loss of electroluminescent performance. The nanocomposite electrode could pave the way to high-efficiency flexible OLEDs with simplified device structure and low fabrication cost

Perimeter Control with Heterogeneous Cordon Signal Behaviors: A Semi-Model Dependent Reinforcement Learning Approach

Perimeter Control (PC) strategies have been proposed to address urban road network control in oversaturated situations by monitoring transfer flows of the Protected Network (PN). The uniform metering rate for cordon signals in existing studies ignores the variety of local traffic states at the intersection level, which may cause severe local traffic congestion and ruin the network stability. This paper introduces a semi-model dependent Multi-Agent Reinforcement Learning (MARL) framework to conduct PC with heterogeneous cordon signal behaviors. The proposed strategy integrates the MARL-based signal control method with centralized feedback PC policy and is applied to cordon signals of the PN. It operates as a two-stage system, with the feedback PC strategy detecting the overall traffic state within the PN and then distributing local instructions to cordon signals controlled by agents in the MARL framework. Each cordon signal acts independently and differently, creating a slack and distributed PC for the PN. The combination of the model-free and model-based methods is achieved by reconstructing the action-value function of the local agents with PC feedback reward without violating the integrity of the local signal control policy learned from the RL training process. Through numerical tests with different demand patterns in a microscopic traffic environment, the proposed PC strategy (a) is shown robustness, scalability, and transferability, (b) outperforms state-of-the-art model-based PC strategies in increasing network throughput, reducing cordon queue and carbon emission

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Ph.DDOCTOR OF PHILOSOPH

Analysis and Optimization of GNN-Based Recommender Systems on Persistent Memory

Graph neural networks (GNNs), which have emerged as an effective method for handling machine learning tasks on graphs, bring a new approach to building recommender systems, where the task of recommendation can be formulated as the link prediction problem on user-item bipartite graphs. Training GNN-based recommender systems (GNNRecSys) on large graphs incurs a large memory footprint, easily exceeding the DRAM capacity on a typical server. Existing solutions resort to distributed subgraph training, which is inefficient due to the high cost of dynamically constructing subgraphs and significant redundancy across subgraphs. The emerging persistent memory technologies provide a significantly larger memory capacity than DRAMs at an affordable cost, making single-machine GNNRecSys training feasible, which eliminates the inefficiencies in distributed training. One major concern of using persistent memory devices for GNNRecSys is their relatively low bandwidth compared with DRAMs. This limitation can be particularly detrimental to achieving high performance for GNNRecSys workloads since their dominant compute kernels are sparse and memory access intensive. To understand whether persistent memory is a good fit for GNNRecSys training, we perform an in-depth characterization of GNNRecSys workloads and a comprehensive analysis of their performance on a persistent memory device, namely, Intel Optane. Based on the analysis, we provide guidance on how to configure Optane for GNNRecSys workloads. Furthermore, we present techniques for large-batch training to fully realize the advantages of single-machine GNNRecSys training. Our experiment results show that with the tuned batch size and optimal system configuration, Optane-based single-machine GNNRecSys training outperforms distributed training by a large margin, especially when handling deep GNN models

Intrinsically stretchable and transparent thin-film transistors based on printable silver nanowires, carbon nanotubes and an elastomeric dielectric.

Thin-film field-effect transistor is a fundamental component behind various mordern electronics. The development of stretchable electronics poses fundamental challenges in developing new electronic materials for stretchable thin-film transistors that are mechanically compliant and solution processable. Here we report the fabrication of transparent thin-film transistors that behave like an elastomer film. The entire fabrication is carried out by solution-based techniques, and the resulting devices exhibit a mobility of ∼30 cm(2) V(-1) s(-1), on/off ratio of 10(3)-10(4), switching current >100 μA, transconductance >50 μS and relative low operating voltages. The devices can be stretched by up to 50% strain and subjected to 500 cycles of repeated stretching to 20% strain without significant loss in electrical property. The thin-film transistors are also used to drive organic light-emitting diodes. The approach and results represent an important progress toward the development of stretchable active-matrix displays

Genome-Wide Identification and Characterization of Auxin Response Factor (ARF) Gene Family Involved in Wood Formation and Response to Exogenous Hormone Treatment in Populus trichocarpa

Auxin is a key regulator that virtually controls almost every aspect of plant growth and development throughout its life cycle. As the major components of auxin signaling, auxin response factors (ARFs) play crucial roles in various processes of plant growth and development. In this study, a total of 35 PtrARF genes were identified, and their phylogenetic relationships, chromosomal locations, synteny relationships, exon/intron structures, cis-elements, conserved motifs, and protein characteristics were systemically investigated. We also analyzed the expression patterns of these PtrARF genes and revealed that 16 of them, including PtrARF1, 3, 7, 11, 13–17, 21, 23, 26, 27, 29, 31, and 33, were preferentially expressed in primary stems, while 15 of them, including PtrARF2, 4, 6, 9, 10, 12, 18–20, 22, 24, 25, 28, 32, and 35, participated in different phases of wood formation. In addition, some PtrARF genes, with at least one cis-element related to indole-3-acetic acid (IAA) or abscisic acid (ABA) response, responded differently to exogenous IAA and ABA treatment, respectively. Three PtrARF proteins, namely PtrARF18, PtrARF23, and PtrARF29, selected from three classes, were characterized, and only PtrARF18 was a transcriptional self-activator localized in the nucleus. Moreover, Y2H and bimolecular fluorescence complementation (BiFC) assay demonstrated that PtrARF23 interacted with PtrIAA10 and PtrIAA28 in the nucleus, while PtrARF29 interacted with PtrIAA28 in the nucleus. Our results provided comprehensive information regarding the PtrARF gene family, which will lay some foundation for future research about PtrARF genes in tree development and growth, especially the wood formation, in response to cellular signaling and environmental cues

Motherwort Injection for Preventing Uterine Hemorrhage in Women With Induced Abortion: A Systematic Review and Meta-Analysis of Randomized Evidence

Objective: Motherwort injection (MI) is a modern patented injection extracted from motherwort (Leonurus japonicus Hoult). Empirical studies and systematic reviews have shown the benefits of motherwort injection for preventing postpartum hemorrhage after vaginal delivery and cesarean section. This study was conducted to explore the efficacy and safety of motherwort injection for women with the prevention of post-abortion uterine hemorrhage.Methods: A comprehensive literature search was conducted to identify RCTs regarding the effect of the use of motherwort injection in women after abortion. Data from trials were pooled by meta-analysis and a random-effects model was used to calculate the summarized relative risks (RRs) and their 95% confidence intervals (CIs). The grading of recommendations assessment, development, and evaluation (GRADE) methodology was used to access the quality of the evidence.Results: Nine trials with a total of 1,675 participants were identified. Overall, motherwort injection combined with oxytocin compared to oxytocin had a significantly lower blood loss within 2 hours (MD = −50.00, 95% CI −62.92 to −37.08, very low quality); lower blood loss within 24 h (MD = −50.00, 95% CI −62.92 to −37.08, very low quality); however, there was no significant difference between motherwort injection and oxytocin (24 h: MD: 0.72, 95% CI −7.76 to 9.20; 48 h: MD: −0.01, 95% CI −11.35 to 11.33; 72 h: MD: −1.12, 95% CI −14.39 to 12.15, very low quality). Compared with oxytocin or no intervention, both motherwort injection and motherwort injection combined with oxytocin had a significantly decreased duration of blood loss (MI vs. O: MD −2.59, 95% CI −4.59 to −0.60, very low quality; MI + O vs. O: MD −2.62, 95% CI -3.02 to −2.22, very low quality; MI + O vs. No intervention: MD: −1.80, 95% CI −2.28 to −1.33, low quality). Seven of nine included trials reported adverse event outcomes. Three cases were found in the motherwort injection group, and five induced abortion syndromes were found in the motherwort injection plus oxytocin group. 29 adverse events were reported in the oxytocin group instead. The recovery time of normal menstruation after abortion was significantly earlier in the group using motherwort injection compared with oxytocin (MDs −3.77, 95% CI −6.29 to −1.25, very low quality), and the endometrial thickness in the motherwort injection group was significantly different from that in the oxytocin group (MD: 2.24, 95% CI 1.58 to 2.90, very low quality).Conclusion: The results of this meta-analysis indicate prophylactic use of motherwort injection may reduce the risk of uterine hemorrhage in women after abortion, and more high-quality research is needed to confirm the efficacy and safety of motherwort injection in preventing uterine hemorrhage after abortion.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=274153, identifier CRD4202127415

Optical tuning of exciton and trion emissions in monolayer phosphorene

Monolayer phosphorene provides a unique two-dimensional (2D) platform to investigate the fundamental dynamics of excitons and trions (charged excitons) in reduced dimensions. However, owing to its high instability, unambiguous identification of monolayer phosphorene has been elusive. Consequently, many important fundamental properties, such as exciton dynamics, remain underexplored. We report a rapid, noninvasive, and highly accurate approach based on optical interferometry to determine the layer number of phosphorene, and confirm the results with reliable photoluminescence measurements. Furthermore, we successfully probed the dynamics of excitons and trions in monolayer phosphorene by controlling the photo-carrier injection in a relatively low excitation power range. Based on our measured optical gap and the previously measured electronic energy gap, we determined the exciton binding energy to be ~0.3 eV for the monolayer phosphorene on SiO2/Si substrate, which agrees well with theoretical predictions. A huge trion binding energy of ~100 meV was first observed in monolayer phosphorene, which is around five times higher than that in transition metal dichalcogenide (TMD) monolayer semiconductor, such as MoS2. The carrier lifetime of exciton emission in monolayer phosphorene was measured to be ~220 ps, which is comparable to those in other 2D TMD semiconductors. Our results open new avenues for exploring fundamental phenomena and novel optoelectronic applications using monolayer phosphorene