Gravitational-Wave Fringes at LIGO: Detecting Compact Dark Matter by Gravitational Lensing

Utilizing gravitational-wave (GW) lensing opens a new way to understand the small-scale structure of the universe. We show that, in spite of its coarse angular resolution and short duration of observation, LIGO can detect the GW lensing induced by compact structures, in particular by compact dark matter (DM) or primordial black holes of $10 - 10^5 \, M_\odot$, which remain interesting DM candidates. The lensing is detected through GW frequency chirping, creating the natural and rapid change of lensing patterns: \emph{frequency-dependent amplification and modulation} of GW waveforms. As a highest-frequency GW detector, LIGO is a unique GW lab to probe such light compact DM. With the design sensitivity of Advanced LIGO, one-year observation by three detectors can optimistically constrain the compact DM density fraction $f_{\rm DM}$ to the level of a few percent.Comment: 6 pages, 5 figures, v2: published version, Fig.5 updated with Poisson distribution, improved discussion on the optical dept

Depth-discriminative Metric Learning for Monocular 3D Object Detection

Monocular 3D object detection poses a significant challenge due to the lack of depth information in RGB images. Many existing methods strive to enhance the object depth estimation performance by allocating additional parameters for object depth estimation, utilizing extra modules or data. In contrast, we introduce a novel metric learning scheme that encourages the model to extract depth-discriminative features regardless of the visual attributes without increasing inference time and model size. Our method employs the distance-preserving function to organize the feature space manifold in relation to ground-truth object depth. The proposed (K, B, eps)-quasi-isometric loss leverages predetermined pairwise distance restriction as guidance for adjusting the distance among object descriptors without disrupting the non-linearity of the natural feature manifold. Moreover, we introduce an auxiliary head for object-wise depth estimation, which enhances depth quality while maintaining the inference time. The broad applicability of our method is demonstrated through experiments that show improvements in overall performance when integrated into various baselines. The results show that our method consistently improves the performance of various baselines by 23.51% and 5.78% on average across KITTI and Waymo, respectively.Comment: Accepted at NeurIPS 202

WEIGHT TRANSFER IN DIFFERENT GOLF SWING STYLES BASED ON SWING PLANE: A NONLINEAR DYNAMICS APPROACH

INTRODUCTION: Weight transfer has been considered as one of the most important aspects of golf swing in golf coaching theories. Previous studies present conflicting and restricted findings on weight transfer. The purpose of this study was to determine if swing style influences weight transfer pattern by analyzing select center-of-pressure parameters using the approximate entropy method

A 3-D DETERMINATION AND ANALYSIS OF THE SWING PLANE IN GOLF

INTRODUCTION: The direction and ball carry distance of a golf shot are determined by the trajectory of the clubhead near the impact and the impact conditions such as the clubhead speed, club face angle and orientation at impact. Swing plane, one of the most frequently used terms in golf coaching lately, is also one of the most controversial and misleading concepts: single-plane, multi-plane, one-plane, two-plane, on-plane, etc. The purpose of this study was twofold: (a) to develop a method to determine the true swing plane based on the clubhead motion (trajectory), and (b) to obtain a biomechanical profile of the swing planes of professional golfers through the swing plane analysis

Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator

Real-time processing is crucial in autonomous driving systems due to the imperative of instantaneous decision-making and rapid response. In real-world scenarios, autonomous vehicles are continuously tasked with interpreting their surroundings, analyzing intricate sensor data, and making decisions within split seconds to ensure safety through numerous computer vision tasks. In this paper, we present a new real-time multi-task network adept at three vital autonomous driving tasks: monocular 3D object detection, semantic segmentation, and dense depth estimation. To counter the challenge of negative transfer, which is the prevalent issue in multi-task learning, we introduce a task-adaptive attention generator. This generator is designed to automatically discern interrelations across the three tasks and arrange the task-sharing pattern, all while leveraging the efficiency of the hard-parameter sharing approach. To the best of our knowledge, the proposed model is pioneering in its capability to concurrently handle multiple tasks, notably 3D object detection, while maintaining real-time processing speeds. Our rigorously optimized network, when tested on the Cityscapes-3D datasets, consistently outperforms various baseline models. Moreover, an in-depth ablation study substantiates the efficacy of the methodologies integrated into our framework.Comment: Accepted at ICRA 202

The importance of critically short telomere in myelodysplastic syndrome

A few critically short telomeres trigger genomic instability regardless of average telomere length (TL). Recently, the telomere shortest length assay (TeSLA) was developed to detect critically short telomeres and measure absolute telomeres. Using TeSLA with the internally labeled biotin probe, we measured the TL of bone marrow (BM) aspirates from 52 patients with myelodysplastic syndrome (MDS). A percentage of shortest telomeres (< 1.0 kb (ShTL1.0)) were calculated. ShTL1.0 was correlated to IPSS-R risk (spearman’s rho = 0.35 and p = 0.0196), and ShTL1.0 and BM blast (2.61% in < 5% blast, 4.15% in 5–10% blast, and 6.80% in 10–20% blast, respectively, p = 0.0332). Interestingly, MDS patients with a shortest TL ≥ 0.787 kb at the time of diagnosis showed better overall survival (OS) and progression-free survival (PFS) than patients with a shortest TL < 0.787 kb in the multivariate analyses (HR = 0.13 and 0.30, p = 0.011 and 0.048 for OS and PFS, respectively). Our results clearly show the presence and abundance of critically short telomeres in MDS patients. These pathologic telomeres are associated with IPSS-R which is a validated prognostic scoring system in MDS. Furthermore, they are independent prognostic factors for OS in MDS patients. Future prospective studies are needed to validate our results.Highlights Telomere length (TL) has been reported to be important in myelodysplastic syndrome (MDS).A novel TeSLA method demonstrated the presence and abundance of extremely short telomeres (<1.0kb) in MDS.Critically short TL rather than an average TL is associated with the IPSS-R and BM blast in MDS.The shortest TL is an independent prognostic factor for PFS and OS.Short TL should be incorporated into the risk scoring system in MDS in the future.This work was supported by the Ministry of Science and ICT(MSIT) of the Republic of Korea and the National Research Foundation of Korea (NRF-2020R1A3B3079653)

Cancer-Associated Splicing Variant of Tumor Suppressor AIMP2/p38: Pathological Implication in Tumorigenesis

Although ARS-interacting multifunctional protein 2 (AIMP2, also named as MSC p38) was first found as a component for a macromolecular tRNA synthetase complex, it was recently discovered to dissociate from the complex and work as a potent tumor suppressor. Upon DNA damage, AIMP2 promotes apoptosis through the protective interaction with p53. However, it was not demonstrated whether AIMP2 was indeed pathologically linked to human cancer. In this work, we found that a splicing variant of AIMP2 lacking exon 2 (AIMP2-DX2) is highly expressed by alternative splicing in human lung cancer cells and patient's tissues. AIMP2-DX2 compromised pro-apoptotic activity of normal AIMP2 through the competitive binding to p53. The cells with higher level of AIMP2-DX2 showed higher propensity to form anchorage-independent colonies and increased resistance to cell death. Mice constitutively expressing this variant showed increased susceptibility to carcinogen-induced lung tumorigenesis. The expression ratio of AIMP2-DX2 to normal AIMP2 was increased according to lung cancer stage and showed a positive correlation with the survival of patients. Thus, this work identified an oncogenic splicing variant of a tumor suppressor, AIMP2/p38, and suggests its potential for anti-cancer target

Variation block-based genomics method for crop plants

BACKGROUND: In contrast with wild species, cultivated crop genomes consist of reshuffled recombination blocks, which occurred by crossing and selection processes. Accordingly, recombination block-based genomics analysis can be an effective approach for the screening of target loci for agricultural traits. RESULTS: We propose the variation block method, which is a three-step process for recombination block detection and comparison. The first step is to detect variations by comparing the short-read DNA sequences of the cultivar to the reference genome of the target crop. Next, sequence blocks with variation patterns are examined and defined. The boundaries between the variation-containing sequence blocks are regarded as recombination sites. All the assumed recombination sites in the cultivar set are used to split the genomes, and the resulting sequence regions are termed variation blocks. Finally, the genomes are compared using the variation blocks. The variation block method identified recurring recombination blocks accurately and successfully represented block-level diversities in the publicly available genomes of 31 soybean and 23 rice accessions. The practicality of this approach was demonstrated by the identification of a putative locus determining soybean hilum color. CONCLUSIONS: We suggest that the variation block method is an efficient genomics method for the recombination block-level comparison of crop genomes. We expect that this method will facilitate the development of crop genomics by bringing genomics technologies to the field of crop breeding