A method of weak lensing reconstruction through cosmic magnification with multi-band photometry information

Weak gravitational lensing induces flux dependent fluctuations in the observed galaxy number density distribution. This cosmic magnification (magnification bias) effect in principle enables lensing reconstruction alternative to cosmic shear and CMB lensing. However, the intrinsic galaxy clustering, which otherwise overwhelms the signal, has hindered its application. Through a scaling relation found by principal component analysis of the galaxy clustering in multi-band photometry space, we design a minimum variance linear estimator to suppress the intrinsic galaxy clustering and to reconstruct the lensing convergence map. In combination of the CosmoDC2 galaxy mock and the CosmicGrowth simulation, we test this proposal for a LSST-like galaxy survey with $ugrizY$ photometry bands. The scaling relation holds excellently at multipole $\ell<10^3$, and remains reasonably well to $\ell\sim 3000$. The linear estimator efficiently suppresses the galaxy intrinsic clustering, by a factor of $\sim 10^2$. For galaxies in the photo-z range $0.8<z_\kappa<1.2$, the reconstructed convergence map is cosmic variance limited per $\ell$ mode at $\ell= 200$. Its cross-correlation with cosmic shear of galaxies can achieve $S/N >= 200$. When the source redshift of cosmic shear galaxies $z_\gamma<z_\kappa$, the systematic error is negligible at all investigated scales ($\ell<3000$). When $z_\gamma\geq z_\kappa$, the systematic error caused by the residual intrinsic galaxy clustering becomes non-negligible. We discuss possible mitigation of the residual intrinsic galaxy clustering required for accurate measurement at $\ell>10^3$. This work further demonstrates the potential of lensing measurement through cosmic magnification to enhance the weak lensing cosmology

Immunoregulation of Glia after spinal cord injury: a bibliometric analysis

ObjectiveImmunoregulation is a complex and critical process in the pathological process of spinal cord injury (SCI), which is regulated by various factors and plays an important role in the functional repair of SCI. This study aimed to explore the research hotspots and trends of glial cell immunoregulation after SCI from a bibliometric perspective.MethodsData on publications related to glial cell immunoregulation after SCI, published from 2004 to 2023, were obtained from the Web of Science Core Collection. Countries, institutions, authors, journals, and keywords in the topic were quantitatively analyzed using the R package “bibliometrix”, VOSviewer, Citespace, and the Bibliometrics Online Analysis Platform.ResultsA total of 613 papers were included, with an average annual growth rate of 9.39%. The papers came from 36 countries, with the United States having the highest output, initiating collaborations with 27 countries. Nantong University was the most influential institution. We identified 3,177 authors, of whom Schwartz, m, of the Weizmann Institute of Science, was ranked first regarding both field-specific H-index (18) and average number of citations per document (151.44). Glia ranked first among journals with 2,574 total citations. The keywords “microglia,” “activation,” “macrophages,” “astrocytes,” and “neuroinflammation” represented recent hot topics and are expected to remain a focus of future research.ConclusionThese findings strongly suggest that the immunomodulatory effects of microglia, astrocytes, and glial cell interactions may be critical in promoting nerve regeneration and repair after SCI. Research on the immunoregulation of glial cells after SCI is emerging, and there should be greater cooperation and communication between countries and institutions to promote the development of this field and benefit more SCI patients

Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity

Reconstructing the viewed images from human brain activity bridges human and computer vision through the Brain-Computer Interface. The inherent variability in brain function between individuals leads existing literature to focus on acquiring separate models for each individual using their respective brain signal data, ignoring commonalities between these data. In this article, we devise Psychometry, an omnifit model for reconstructing images from functional Magnetic Resonance Imaging (fMRI) obtained from different subjects. Psychometry incorporates an omni mixture-of-experts (Omni MoE) module where all the experts work together to capture the inter-subject commonalities, while each expert associated with subject-specific parameters copes with the individual differences. Moreover, Psychometry is equipped with a retrieval-enhanced inference strategy, termed Ecphory, which aims to enhance the learned fMRI representation via retrieving from prestored subject-specific memories. These designs collectively render Psychometry omnifit and efficient, enabling it to capture both inter-subject commonality and individual specificity across subjects. As a result, the enhanced fMRI representations serve as conditional signals to guide a generation model to reconstruct high-quality and realistic images, establishing Psychometry as state-of-the-art in terms of both high-level and low-level metrics.Comment: Accepted to CVPR 202

Influence of Conformal Coatings on the Emc Performance of a Printed Circuit Board

Conformal coatings are often applied to printed circuit boards to protect the board and its components from environmental factors like moisture, chemicals, and vibration. The impact of a conformal coating on crosstalk and radiated emissions was studied in the following paper. Two coating materials were characterized in terms of their permittivity and permeability. The impact of the conformal coating was evaluated based on the crosstalk between microstrip traces, the radiated emissions from a switch-mode power supply (SMPS), and on coupling from an EMI filter to nearby components. The coatings increased crosstalk between microstrip traces by up to 5 ~ 6 dB, and increased radiated emissions from the SMPS by up to 8 dB. While the coating did not affect the performance of the EMI filter, a 5.5 dB increase in coupling was observed from the filter to nearby components. These effects should be considered if pre-compliance testing is performed before the coatings are applied

Additional effects of acupuncture on early comprehensive rehabilitation in patients with mild to moderate acute ischemic stroke: a multicenter randomized controlled trial

CONSORT checklist. (PDF 46 kb

Weak Lensing Reconstruction by Counting DECaLS Galaxies

Alternative to weak lensing measurements through cosmic shear, we present a weak lensing convergence $\hat{\kappa}$ map reconstructed through cosmic magnification effect in DECaLS galaxies of the DESI imaging surveys DR9. This is achieved by linearly weighing $12$ maps of galaxy number overdensity in different magnitude bins of $grz$ photometry bands. The weight is designed to eliminate the mean galaxy deterministic bias, minimize galaxy shot noise while maintaining the lensing convergence signal. We also perform corrections of imaging systematics in the galaxy number overdensity. The $\hat{\kappa}$ map has $8365$ deg$^2$ sky coverage. Given the low number density of DECaLS galaxies, the $\hat{\kappa}$ map is overwhelmed by shot noise and the map quality is difficult to evaluate using the lensing auto-correlation. Alternatively, we measure its cross-correlation with the cosmic shear catalogs of DECaLS galaxies of DESI imaging surveys DR8, which has $8365$ deg$^2$ overlap in sky coverage with the $\hat{\kappa}$ map. We detect a convergence-shear cross-correlation signal with $S/N\simeq 10$. The analysis also shows that the galaxy intrinsic clustering is suppressed by a factor $\mathcal{O}(10^2)$ and the residual galaxy clustering contamination in the $\hat{\kappa}$ map is consistent with zero. Various tests with different galaxy and shear samples, and the Akaike information criterion analysis all support the lensing detection. So is the imaging systematics corrections, which enhance the lensing signal detection by $\sim 30\%$. We discuss various issues for further improvement of the measurements

認識・イメージ 《人民日报》涉日报道研究（2003-2012年）

日中台共同研究「現代中国と東アジアの新環境」 ②21世紀の日中関係 : 青年研究者の思索と対

Predicting Radiated Emissions from a Complex Transportation System Wiring Harness

Low frequency radiated emissions problems are often caused by common mode currents flowing on wiring harnesses. The ability to predict radiated emissions problems early in the design process can save both time and money and result in a better product. Methods have previously been reported for rapidly characterizing common-mode sources driving a harness and then using these equivalent sources to predict radiated emissions. These methods are extended in the following paper to predict radiated emissions from a complex 32-wire harness bundle connected to an engine control unit. Rapid experimental characterization of the common mode sources is enabled using an equivalent cable bundle approximation of the original harness, where wires with roughly equivalent source and load impedances are lumped together and treated as a single equivalent wire. Sources driving the equivalent bundle were found using a specialized measurement fixture. Only a few measurements are required, even if there are many wires associated with the source and they originate at different ports on the component. Full-wave models of the equivalent harness were built and along with the equivalent source were used to predict radiated emissions. This model was able to predict radiated emissions from 20-300 MHz with reasonable accuracy, with peak emissions typically predicted within about 6 dB of measurements, when using multiple different harness lengths and routings

TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning

Despite recent progress in reinforcement learning (RL) from raw pixel data, sample inefficiency continues to present a substantial obstacle. Prior works have attempted to address this challenge by creating self-supervised auxiliary tasks, aiming to enrich the agent's learned representations with control-relevant information for future state prediction. However, these objectives are often insufficient to learn representations that can represent the optimal policy or value function, and they often consider tasks with small, abstract discrete action spaces and thus overlook the importance of action representation learning in continuous control. In this paper, we introduce TACO: Temporal Action-driven Contrastive Learning, a simple yet powerful temporal contrastive learning approach that facilitates the concurrent acquisition of latent state and action representations for agents. TACO simultaneously learns a state and an action representation by optimizing the mutual information between representations of current states paired with action sequences and representations of the corresponding future states. Theoretically, TACO can be shown to learn state and action representations that encompass sufficient information for control, thereby improving sample efficiency. For online RL, TACO achieves 40% performance boost after one million environment interaction steps on average across nine challenging visual continuous control tasks from Deepmind Control Suite. In addition, we show that TACO can also serve as a plug-and-play module adding to existing offline visual RL methods to establish the new state-of-the-art performance for offline visual RL across offline datasets with varying quality

A newly isolated roseophage represents a distinct member of Siphoviridae family.

BACKGROUND(#br)Members of the Roseobacter lineage are a major group of marine heterotrophic bacteria because of their wide distribution, versatile lifestyles and important biogeochemical roles. Bacteriophages, the most abundant biological entities in the ocean, play important roles in shaping their hosts’ population structures and mediating genetic exchange between hosts. However, our knowledge of roseophages (bacteriophages that infect Roseobacter) is far behind that of their host counterparts, partly reflecting the need to isolate and analyze the phages associated with this ecologically important bacterial clade.(#br)METHODS(#br)vB_DshS-R4C (R4C), a novel virulent roseophage that infects Dinoroseobacter shibae DFL12T, was isolated with the double-layer agar method. The phage morphology was visualized with transmission electron microscopy. We characterized R4C in-depth with a genomic analysis and investigated the distribution of the R4C genome in different environments with a metagenomic recruitment analysis.(#br)RESULTS(#br)The double-stranded DNA genome of R4C consists of 36,291 bp with a high GC content of 66.75%. It has 49 genes with low DNA and protein homologies to those of other known phages. Morphological and phylogenetic analyses suggested that R4C is a novel member of the family Siphoviridae and is most closely related to phages in the genus Cronusvirus. However, unlike the Cronusvirus phages, R4C encodes an integrase, implying its ability to establish a lysogenic life cycle. A terminal analysis shows that, like that of λ phage, the R4C genome utilize the ’cohesive ends’ DNA-packaging mechanism. Significantly, homologues of the R4C genes are more prevalent in coastal areas than in the open ocean.(#br)CONCLUSIONS(#br)Information about this newly discovered phage extends our understanding of bacteriophage diversity, evolution, and their roles in different environments