Multi Task Consistency Guided Source-Free Test-Time Domain Adaptation Medical Image Segmentation

Source-free test-time adaptation for medical image segmentation aims to enhance the adaptability of segmentation models to diverse and previously unseen test sets of the target domain, which contributes to the generalizability and robustness of medical image segmentation models without access to the source domain. Ensuring consistency between target edges and paired inputs is crucial for test-time adaptation. To improve the performance of test-time domain adaptation, we propose a multi task consistency guided source-free test-time domain adaptation medical image segmentation method which ensures the consistency of the local boundary predictions and the global prototype representation. Specifically, we introduce a local boundary consistency constraint method that explores the relationship between tissue region segmentation and tissue boundary localization tasks. Additionally, we propose a global feature consistency constraint toto enhance the intra-class compactness. We conduct extensive experiments on the segmentation of benchmark fundus images. Compared to prediction directly by the source domain model, the segmentation Dice score is improved by 6.27\% and 0.96\% in RIM-ONE-r3 and Drishti GS datasets, respectively. Additionally, the results of experiments demonstrate that our proposed method outperforms existing competitive domain adaptation segmentation algorithms.Comment: 31 pages,7 figure

PL-CVIO: Point-Line Cooperative Visual-Inertial Odometry

Low-feature environments are one of the main Achilles' heels of geometric computer vision (CV) algorithms. In most human-built scenes often with low features, lines can be considered complements to points. In this paper, we present a multi-robot cooperative visual-inertial navigation system (VINS) using both point and line features. By utilizing the covariance intersection (CI) update within the multi-state constraint Kalman filter (MSCKF) framework, each robot exploits not only its own point and line measurements, but also constraints of common point and common line features observed by its neighbors. The line features are parameterized and updated by utilizing the Closest Point representation. The proposed algorithm is validated extensively in both Monte-Carlo simulations and a real-world dataset. The results show that the point-line cooperative visual-inertial odometry (PL-CVIO) outperforms the independent MSCKF and our previous work CVIO in both low-feature and rich-feature environments

High-Throughput Screening of Transition Metal Single-Atom Catalysts for Nitrogen Reduction Reaction

The discovery of metals as catalytic centers for nitrogen reduction reactions has stimulated great enthusiasm for single-atom catalysts. However, the poor activity and low selectivity of available SACs are far away from the industrial requirement. Through the high throughout first principles calculations, the doping engineering can effectively regulate the NRR performance of b-Sb monolayer. Especially, the origin of activated N2 is revealed from the perspective of the electronic structure of the active center. Among the 24 transition metal dopants, Re@Sb and Tc@Sb showed the best NRR catalytic performance with a low limiting potential. The Re@Sb and Tc@Sb also could significantly inhibit HER and achieve a high theoretical Faradaic efficiency of 100%. Our findings not only accelerate discovery of catalysts for ammonia synthesis but also contribute to further elucidate the structure-performance correlations

YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design

The rapid development and wide utilization of object detection techniques have aroused attention on both accuracy and speed of object detectors. However, the current state-of-the-art object detection works are either accuracy-oriented using a large model but leading to high latency or speed-oriented using a lightweight model but sacrificing accuracy. In this work, we propose YOLObile framework, a real-time object detection on mobile devices via compression-compilation co-design. A novel block-punched pruning scheme is proposed for any kernel size. To improve computational efficiency on mobile devices, a GPU-CPU collaborative scheme is adopted along with advanced compiler-assisted optimizations. Experimental results indicate that our pruning scheme achieves 14$\times$ compression rate of YOLOv4 with 49.0 mAP. Under our YOLObile framework, we achieve 17 FPS inference speed using GPU on Samsung Galaxy S20. By incorporating our proposed GPU-CPU collaborative scheme, the inference speed is increased to 19.1 FPS, and outperforms the original YOLOv4 by 5$\times$ speedup. Source code is at: \url{https://github.com/nightsnack/YOLObile}

Myeloid Hypoxia-Inducible Factor HIF1A Provides Cardio-Protection During Ischemia and Reperfusion

The transcription factor hypoxia-inducible factor HIF1A induces cardioprotection from ischemia and reperfusion injury. Here, we investigate tissue-specific pathways that are critical for HIF1A-elicited tissue protection. Initial studies showed that mice with induced global Hif1a deletion (Hif1aloxP/loxP UbiquitinCre+) have exaggerated myocardial injury during in situ ischemia and reperfusion. Surprisingly, this phenotype was mirrored only in mice with myeloid-specific Hif1a deletion (Hif1aloxP/loxP LysM Cre+). In contrast, mice with myocardial specific (Hif1aloxP/loxP Myosin Cre+), or vascular Hif1a deletion (Hif1aloxP/loxP VEcadherin Cre+) experienced similar levels of injury as controls. Subsequent studies using adoptive transfer of Hif1a-deficient polymorphonuclear neutrophils (PMNs) prior to myocardial injury demonstrated increased reperfusion injury. On the contrary, the adoptive transfer of PMNs treated ex vivo with the hypoxia inducible factor (HIF) stabilizer dimethyloxalylglycine (DMOG) was associated with attenuated myocardial injury. Furthermore, DMOG-mediated cardioprotection was abolished in Hif1aloxP/loxP LysM Cre+ mice, but not in Hif2aloxP/loxP LysM Cre+ mice. Finally, studies of PMN-dependent HIF1A target genes implicated the neuronal guidance molecule netrin-1 in mediating the cardioprotective effects of myeloid HIF1A. Taken together, the present studies identified a functional role for myeloid-expressed HIF1A in providing cardioprotection during ischemia and reperfusion injury, which is mediated, at least in part, by the induction of the netrin-1 neuronal guidance molecule in neutrophils

Terahertz Radiation from Combined Metallic Slit Arrays

We report an approach to efficiently generate terahertz radiation from a combined periodic structure. The proposed configuration is composed of two metallic slit arrays deliberately designed with different periodic length, slit width and depth. We found that the combination of the two slit arrays could provide special electromagnetic modes, which exhibit nonradiative property above the surface of one slit array and radiative property inside the other one. An electron beam holding proper energy could resonate with those modes to generate strong and directional electromagnetic radiations in the terahertz regime, indicating that the approach has the potential in developing high-performance terahertz radiation sources

Transcriptional Responses of Different Brain Cell Types to Oxygen Decline

Brain hypoxia is associated with a wide range of physiological and clinical conditions. Although oxygen is an essential constituent of maintaining brain functions, our understanding of how specific brain cell types globally respond and adapt to decreasing oxygen conditions is incomplete. In this study, we exposed mouse primary neurons, astrocytes, and microglia to normoxia and two hypoxic conditions and obtained genome-wide transcriptional profiles of the treated cells. Analysis of differentially expressed genes under conditions of reduced oxygen revealed a canonical hypoxic response shared among different brain cell types. In addition, we observed a higher sensitivity of neurons to oxygen decline, and dissected cell type-specific biological processes affected by hypoxia. Importantly, this study establishes novel gene modules associated with brain cells responding to oxygen deprivation and reveals a state of profound stress incurred by hypoxia

Unveiling the origin of catalytic sites of Pt nanoparticles decorated on oxygen-deficient vanadium-doped cobalt hydroxide nanosheet for hybrid sodium-air batteries

Highly active bifunctional electrocatalysts are crucial for improving the performance of rechargeable metal-air batteries. However, most reported bifunctional electrocatalysts feature poor electrocatalytic activity and stability toward oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Here, we have reported the first-ever study of an effective one-step reduction-assisted exfoliation method to exfoliate bulk vanadium-doped cobalt hydroxide (V-doped Co(OH)2, denoted as V-Co(OH)2) into ultrathin nanosheets with abundant oxygen vacancies (V-Co(OH)2-Ov) and simultaneously anchor them with highly dispersed ultrafine Pt nanoparticles (NPs) with a nominal size of 0.8-2.4 nm (denoted as Pt/V-Co(OH)2-Ov). The Pt/V-Co(OH)2-Ov catalyst exhibits improved catalytic performance in ORR/OER. X-ray absorption spectroscopy analysis and theoretical calculations reveal the strong interfacial electronic interactions between Pt NPs and V-Co(OH)2-Ov, which synergistically improves oxygen intermediates' adsorption/desorption, enhancing the ORR and OER performance. Using Pt/V-Co(OH)2-Ov as a catalyst in the air cathode, a hybrid sodium-air battery displays a record value of an ultralow charging-discharging voltage gap of 0.07 V at a current density of 0.01 mA cm-2 with remarkable stability of up to 1000 cycles. This reduction-assisted exfoliation approach provides a new strategy to generate oxygen vacancies in metal hydroxides, which act as anchoring sites for deposition of sub-nanometal NPs via a strong interfacial effect