Informative Data Mining for One-Shot Cross-Domain Semantic Segmentation

Contemporary domain adaptation offers a practical solution for achieving cross-domain transfer of semantic segmentation between labeled source data and unlabeled target data. These solutions have gained significant popularity; however, they require the model to be retrained when the test environment changes. This can result in unbearable costs in certain applications due to the time-consuming training process and concerns regarding data privacy. One-shot domain adaptation methods attempt to overcome these challenges by transferring the pre-trained source model to the target domain using only one target data. Despite this, the referring style transfer module still faces issues with computation cost and over-fitting problems. To address this problem, we propose a novel framework called Informative Data Mining (IDM) that enables efficient one-shot domain adaptation for semantic segmentation. Specifically, IDM provides an uncertainty-based selection criterion to identify the most informative samples, which facilitates quick adaptation and reduces redundant training. We then perform a model adaptation method using these selected samples, which includes patch-wise mixing and prototype-based information maximization to update the model. This approach effectively enhances adaptation and mitigates the overfitting problem. In general, we provide empirical evidence of the effectiveness and efficiency of IDM. Our approach outperforms existing methods and achieves a new state-of-the-art one-shot performance of 56.7\%/55.4\% on the GTA5/SYNTHIA to Cityscapes adaptation tasks, respectively. The code will be released at \url{https://github.com/yxiwang/IDM}.Comment: Accepted by ICCV 202

M^2-3DLaneNet: Multi-Modal 3D Lane Detection

Estimating accurate lane lines in 3D space remains challenging due to their sparse and slim nature. In this work, we propose the M^2-3DLaneNet, a Multi-Modal framework for effective 3D lane detection. Aiming at integrating complementary information from multi-sensors, M^2-3DLaneNet first extracts multi-modal features with modal-specific backbones, then fuses them in a unified Bird's-Eye View (BEV) space. Specifically, our method consists of two core components. 1) To achieve accurate 2D-3D mapping, we propose the top-down BEV generation. Within it, a Line-Restricted Deform-Attention (LRDA) module is utilized to effectively enhance image features in a top-down manner, fully capturing the slenderness features of lanes. After that, it casts the 2D pyramidal features into 3D space using depth-aware lifting and generates BEV features through pillarization. 2) We further propose the bottom-up BEV fusion, which aggregates multi-modal features through multi-scale cascaded attention, integrating complementary information from camera and LiDAR sensors. Sufficient experiments demonstrate the effectiveness of M^2-3DLaneNet, which outperforms previous state-of-the-art methods by a large margin, i.e., 12.1% F1-score improvement on OpenLane dataset

miR-24 is involved in vertebrate LC-PUFA biosynthesis as demonstrated in marine teleost Siganus canaliculatus

Recently, microRNAs (miRNAs) have emerged as crucial regulators of lipid metabolism. However, the miRNA-mediated regulatory mechanism on long-chain (≥C20) polyunsaturated fatty acids (LC-PUFA) biosynthesis in vertebrates remains largely unknown. Here, we address a potentially important role of miRNA-24 (miR-24) in the regulation of LC-PUFA biosynthesis in rabbitfish Siganus canaliculatus. miR-24 showed significantly higher abundance in liver of rabbitfish reared in brackish water than in seawater for fish fed vegetable oil diets and in S. canaliculatus hepatocyte line (SCHL) cells incubated with alpha-linolenic acid (ALA) than the control group. Similar expression patterns were also observed on the expression of sterol regulatory element-binding protein-1 (srebp1) and LC-PUFA biosynthesis related genes. While opposite results were observed on the expression of insulin-induced gene 1 (insig1), an endoplasmic reticulum membrane protein blocking Srebp1 proteolytic activation. Luciferase reporter assays revealed rabbitfish insig1 as a target of miR-24. Knockdown of miR-24 in SCHL cells resulted in increased Insig1 protein, and subsequently reduced mature Srebp1 protein and expression of genes required for LC-PUFA biosynthesis, and these effects could be attenuated after additional insig1 knockdown. Opposite results were observed with overexpression of miR-24. Moreover, increasing endogenous insig1 by knockdown of miR-24 inhibited Srebp1 processing and consequently suppressed LC-PUFA biosynthesis in rabbitfish hepatocytes. These results indicate a potentially critical role for miR-24 in regulating LC-PUFA biosynthesis through the Insig1/Srebp1 pathway by targeting insig1. This is the first report of miR-24 involved in LC-PUFA biosynthesis and thus may provide knowledge on the regulatory mechanisms of LC-PUFA biosynthesis in vertebrates

The performance of large-pitch AC-LGAD with different N+ dose

AC-Coupled LGAD (AC-LGAD) is a new 4D detector developed based on the Low Gain Avalanche Diode (LGAD) technology, which can accurately measure the time and spatial information of particles. Institute of High Energy Physics (IHEP) designed a large-size AC-LGAD with a pitch of 2000 {\mu}m and AC pad of 1000 {\mu}m, and explored the effect of N+ layer dose on the spatial resolution and time resolution. The spatial resolution varied from 32.7 {\mu}m to 15.1 {\mu}m depending on N+ dose. The time resolution does not change significantly at different N+ doses, which is about 15-17 ps. AC-LGAD with a low N+ dose has a large attenuation factor and better spatial resolution. Large signal attenuation factor and low noise level are beneficial to improve the spatial resolution of the AC-LGAD sensor

Characterization of the response of IHEP-IME LGAD with shallow carbon to Gamma Irradiation

Low Gain Avalanche Detectors (LGAD), as part of High-Granularity Timing Detector (HGTD), is crucial to reducing pileup in the upgrading to HL-LHC. Many studies have been done on the bulk damages of the LGAD. However, there's no study about the surface radiation hardness of the LGAD sensors with carbon implanted. The IHEP-IME LGAD version 3 with the shallow carbon and different interpad separations were irradiated up to 2 MGy by gamma irradiation. The performance of the IHEP-IME LGAD version 3 before and after irradiation had been tested, such as the leakage current, break-down voltage, capacitance, V$_{gl}$, and inter-pad resistance. The results showed that apart from minor fluctuations in some samples, no significant changes concerning inter-pad separation were observed before and after irradiation. Leakage current and break-down voltage increase after irradiation, which is considered due to surface passivation; the overall inter-pad resistance are larger than $10^9\ \Omega$before and after irradiation; capacitance is found to be less than 4.5 pF with a slight drop in V$_{gl}$ after irradiation. All parameters meet the requirements of HGTD, and the results indicated that IHEP-IME LGAD v3 has excellent anti-irradiation performance

Characterisation of Spatial and Timing Resolution of IHEP AC-LGAD Strip

AC-coupled LGAD(AC-LGAD) Strip is a new design of LGAD that allows high-precision detection of particle spatiotemporal information whereas reducing the density of readout electronics. For AC-LGAD Strips, there is limited research on the impact of different strip pitches on the spatiotemporal detection performance at the small amount of injected charge. The Institute of High Energy Physics has designed an AC-LGAD Strip prototype with pitches of 150 $\mu m$, 200 $\mu m$, and 250 $\mu m$. The spatial and timing resolutions of the prototype are studied through the laser Transient Current Technique (TCT) scan with different amounts of injected charge. The results show that both the spatial and timing resolution improves as the strip pitch decreases. Increases in both temporal and spatial resolutions as the amount of charge injected increases are observed. The spatial and timing resolution is better than 60 ps and 40 $\mu m$ at 1 Minimum Ionizing Particle (MIP), and better than 10 ps and 5 $\mu m$ at 40 MIPs. Increasing Signal-to-Noise Ratio (SNR) is the key to improving spatial and temporal resolution, whereas increasing the signal attenuation rate by reducing the gap between adjacent electrodes also helps to improve spatial resolution. The enhancements of spatial and timing resolutions by both SNR and signal attenuation rate decrease with increasing amount of MIP. This study can help design and optimize the AC-LGAD Strip detectors and readout electronics

miR-26a mediates LC-PUFA biosynthesis by targeting the Lxrα-Srebp1 pathway in the marine teleost Siganus canaliculatus

MicroRNAs (miRNAs) have been recently shown to be important regulators of lipid metabolism. However, the mechanisms of miRNA-mediated regulation of long-chain polyunsaturated fatty acids (LC-PUFA) biosynthesis in vertebrates remain largely unknown. Herein, we for the first time addressed the role of miR-26a in LC-PUFA biosynthesis in the marine rabbitfish Siganus canaliculatus. The results showed that miR-26a was significantly down-regulated in liver of rabbitfish reared in seawater and in S. canaliculatus hepatocyte line (SCHL) incubated with the LC-PUFA precursor α-linolenic acid (ALA), suggesting that miR-26a may be involved in LC-PUFA biosynthesis due to its abundance being regulated by factors affecting LC-PUFA biosynthesis. Opposite patterns were observed in the expression of liver X receptor α (lxrα) and sterol regulatory element-binding protein-1 (srebp1), as well as the LC-PUFA biosynthesis related genes (Δ4 fads2, Δ6Δ5 fads2 and elovl5) in SCHL cells incubated with ALA. Luciferase reporter assays revealed rabbitfish lxrα as a target of miR-26a, and overexpression of miR-26a in SCHL cells markedly reduced protein levels of Lxrα, Srebp1 and Δ6Δ5 Fads2 induced by the agonist T0901317. Moreover, increasing endogenous Lxrα by knockdown of miR-26a facilitated Srebp1 activation and concomitant increased expression of genes involved in LC-PUFA biosynthesis, and consequently promoted LC-PUFA biosynthesis both in vitro and in vivo. These results indicate a critical role of miR-26a in regulating LC-PUFA biosynthesis through targeting the Lxrα-Srebp1 pathway and provide new insights into the regulatory network controlling LC-PUFA biosynthesis and accumulation in vertebrates

Leakage current simulations of Low Gain Avalanche Diode with improved Radiation Damage Modeling

We report precise TCAD simulations of IHEP-IME-v1 Low Gain Avalanche Diode (LGAD) calibrated by secondary ion mass spectroscopy (SIMS). Our setup allows us to evaluate the leakage current, capacitance, and breakdown voltage of LGAD, which agree with measurements' results before irradiation. And we propose an improved LGAD Radiation Damage Model (LRDM) which combines local acceptor removal with global deep energy levels. The LRDM is applied to the IHEP-IME-v1 LGAD and able to predict the leakage current well at -30 $^{\circ}$C after an irradiation fluence of $\Phi_{eq}=2.5 \times 10^{15} ~n_{eq}/cm^{2}$. The charge collection efficiency (CCE) is under development

MEI Kodierung der frühesten Notation in linienlosen Neumen

Das Optical Neume Recognition Project (ONRP) hat die digitale Kodierung von musikalischen Notationszeichen aus dem Jahr um 1000 zum Ziel – ein ambitioniertes Vorhaben, das die Projektmitglieder veranlasste, verschiedenste methodische Ansätze zu evaluieren. Die Optical Music Recognition-Software soll eine linienlose Notation aus einem der ältesten erhaltenen Quellen mit Notationszeichen, dem Antiphonar Hartker aus der Benediktinerabtei St. Gallen (Schweiz), welches heute in zwei Bänden in der Stiftsbibliothek in St. Gallen aufbewahrt wird, erfassen. Aufgrund der handgeschriebenen, linienlosen Notation stellt dieser Gregorianische Gesang den Forscher vor viele Herausforderungen. Das Werk umfasst über 300 verschiedene Neumenzeichen und ihre Notation, die mit Hilfe der Music Encoding Initiative (MEI) erfasst und beschrieben werden sollen. Der folgende Artikel beschreibt den Prozess der Adaptierung, um die MEI auf die Notation von Neumen ohne Notenlinien anzuwenden. Beschrieben werden Eigenschaften der Neumennotation, um zu verdeutlichen, wo die Herausforderungen dieser Arbeit liegen sowie die Funktionsweise des Classifiers, einer Art digitalen Neumenwörterbuchs