Correlation-Aware Mutual Learning for Semi-supervised Medical Image Segmentation

Semi-supervised learning has become increasingly popular in medical image segmentation due to its ability to leverage large amounts of unlabeled data to extract additional information. However, most existing semi-supervised segmentation methods only focus on extracting information from unlabeled data, disregarding the potential of labeled data to further improve the performance of the model. In this paper, we propose a novel Correlation Aware Mutual Learning (CAML) framework that leverages labeled data to guide the extraction of information from unlabeled data. Our approach is based on a mutual learning strategy that incorporates two modules: the Cross-sample Mutual Attention Module (CMA) and the Omni-Correlation Consistency Module (OCC). The CMA module establishes dense cross-sample correlations among a group of samples, enabling the transfer of label prior knowledge to unlabeled data. The OCC module constructs omni-correlations between the unlabeled and labeled datasets and regularizes dual models by constraining the omni-correlation matrix of each sub-model to be consistent. Experiments on the Atrial Segmentation Challenge dataset demonstrate that our proposed approach outperforms state-of-the-art methods, highlighting the effectiveness of our framework in medical image segmentation tasks. The codes, pre-trained weights, and data are publicly available.Comment: MICCAI2023 early accepted, camera ready versio

Resistin stimulates expression of chemokine genes in chondrocytes via combinatorial regulation of C/EBPβ and NF-κB

To further investigate the regulation role of two chemokine genes CCL3 and CCL4 in chondrocytes in response to resistin, human primary chondrocytes and T/C-28a2 cells were cultured. The function of resistin on the chemokine genes, and the expression of C/EBPβ, NF-κB isoforms were tested using qPCR. The methods used to investigate timed co-regulation of C/EBPβ and NF-κB were NF-κB inhibitor (IKK-NBD) and C/EBPβ inhibitor (SB303580) treatments, and subcellular localization, with or without resistin stimulation. Results showed that resistin could increase the up-regulation of chemokine genes independently. Resistin increased the expression of C/EBPβ and NF-κB isoforms. C/EBPβ regulated basal activity and steadily increased over time up to 24h with resistin. NF-κB was up-regulated upon induction with resistin, peaking at 4 h. C/EBPβ and NF-κB co-enhanced the chemokines expression; inhibition of their activity was additive. The timing of activation in chondrocytes was confirmed by subcellular localization of C/EBPβ and c-rel. Chondrocytes react to resistin in a non-restricted cell-specific manner, utilizing C/EBPβ and NF-κB in a combinatorial regulation of chemokine gene expression. The activity of C/EBPβ is augmented by a transient increase in activity of NF-κB, and both transcription factors act independently on the chemokine genes, CCL3 and CCL4. Thus, resistin stimulates CCL3 and CCL4 through combinatorial regulation of C/EBPβ and NF-κB in chondrocytes

Auto-Parallelizing Large Models with Rhino: A Systematic Approach on Production AI Platform

We present Rhino, a system for accelerating tensor programs with automatic parallelization on AI platform for real production environment. It transforms a tensor program written for a single device into an equivalent distributed program that is capable of scaling up to thousands of devices with no user configuration. Rhino firstly works on a semantically independent intermediate representation of tensor programs, which facilitates its generalization to unprecedented applications. Additionally, it implements a task-oriented controller and a distributed runtime for optimal performance. Rhino explores on a complete and systematic parallelization strategy space that comprises all the paradigms commonly employed in deep learning (DL), in addition to strided partitioning and pipeline parallelism on non-linear models. Aiming to efficiently search for a near-optimal parallel execution plan, our analysis of production clusters reveals general heuristics to speed up the strategy search. On top of it, two optimization levels are designed to offer users flexible trade-offs between the search time and strategy quality. Our experiments demonstrate that Rhino can not only re-discover the expert-crafted strategies of classic, research and production DL models, but also identify novel parallelization strategies which surpass existing systems for novel models

Emergent superconducting fluctuations in a compressed kagome superconductor

The recent discovery of superconductivity (SC) and charge density wave (CDW) in kagome metals AV3Sb5 (A = K, Rb, Cs) provides an ideal playground for the study of emergent electronic orders. Application of moderate pressure leads to a two-dome-shaped SC phase regime in CsV3Sb5 accompanied by the destabilizing of CDW phase; such unconventional evolution of SC may involve the pressure-induced formation of a new stripe-like CDW order resembling that in La-214 cuprate superconductors. Nonetheless, the nature of this pressure-tuned SC state and its interplay with the stripe order are yet to be explored. Here, we perform soft point-contact spectroscopy (SPCS) measurements in CsV3Sb5 to investigate the evolution of superconducting order parameter with pressure. Surprisingly, we find that the superconducting gap is significantly enhanced between the two SC domes, at which the zero-resistance temperature is suppressed and the transition is remarkably broadened. Moreover, the temperature dependence of the SC gap in this pressure range severely deviates from the conventional BCS behavior, evidencing for strong Cooper pair phase fluctuations. These findings reveal the complex intertwining of the stripe-like CDW with SC in the compressed CsV3Sb5, suggesting striking parallel to the cuprate superconductor La2-xBaxCuO4. Our results point to the essential role of charge degree of freedom in the development of intertwining electronic orders, thus provides new constraints for theories.Comment: 16 pages, 4 figure

Genome-wide analysis and identification of stress-responsive genes of the CCCH zinc finger family in Capsicum annuum L.

The CCCH zinc finger gene family encodes a class of proteins that can bind to both DNA and RNA, and an increasing number of studies have demonstrated that the CCCH gene family plays a key role in growth and development and responses to environmental stress. Here, we identified 57 CCCH genes in the pepper (Capsicum annuum L.) genome and explored the evolution and function of the CCCH gene family in C. annuum. Substantial variation was observed in the structure of these CCCH genes, and the number of exons ranged from one to fourteen. Analysis of gene duplication events revealed that segmental duplication was the main driver of gene expansion in the CCCH gene family in pepper. We found that the expression of CCCH genes was significantly up-regulated during the response to biotic and abiotic stress, especially cold and heat stress, indicating that CCCH genes play key roles in stress responses. Our results provide new information on CCCH genes in pepper and will aid future studies of the evolution, inheritance, and function of CCCH zinc finger genes in pepper

Spin-orbit-coupled triangular-lattice spin liquid in rare-earth chalcogenides

Spin-orbit coupling is an important ingredient in many spin liquid candidate materials, especially among the rare-earth magnets and Kitaev materials. We explore the rare-earth chalcogenides NaYbS$_2$ where the Yb$^{3+}$ ions form a perfect triangular lattice. Unlike its isostructural counterpart YbMgGaO$_4$ and the kagom\'{e} lattice herbertsmithite, this material does not have any site disorders both in magnetic and non-magnetic sites. We carried out the thermodynamic and inelastic neutron scattering measurements. The magnetic dynamics could be observed with a broad gapless excitation band up to 1.0 meV at 50 mK and 0 T, no static long-range magnetic ordering is detected down to 50 mK. We discuss the possibility of Dirac spin liquid for NaYbS$_2$. We identify the experimental signatures of field-induced transitions from the disordered spin liquid to an ordered antiferromagnet with an excitation gap at finite magnetic fields and discuss this result with our Monte Carlo calculation of the proposed spin model. Our findings could inspire further interests in the spin-orbit-coupled spin liquids and the magnetic ordering transition from them

Turbulent orifice flow in hydropower applications, a numerical and experimental study

This thesis reports the methods to simulate flows withcomplex boundary such as orifice flow. The method is forgeneral purposes so that it has been tested on different flowsincluding orifice flow. Also it contains a chapter about theexperiment of orifice flow. Higher-order precision interpolation schemes are used inumerical simulation to improve prediction at acceptable gridrefinement. Because higher-order schemes cause instability inconvection-diffusion problems or involve a large computationalkernel, they are implemented with deferred correction method. Alower-order scheme such as upwind numerical scheme is used tomake preliminary guess. A deferred (defect) correction term isadded to maintain precision. This avoids the conflict betweenprecision order and implementation difficulty. The authorproposes a shifting between upwind scheme and centraldifference scheme for the preliminary guess. This has beenproven to improve convergence while higher order schemes havewider range of stability. Non-orthogonal grid is a necessity for complex flow. Usuallyone can map coordinate of such a grid to a transformed domainwhere the grid is regular. The cost is that differentialequations get much more complex form. If calculated directly innon-orthogonal grid, the equations keep simple forms. However,it is difficult to make interpolation in a non-orthogonal grid.Three methods can be used: local correction, shape function andcurvilinear interpolation. The local correction method cannotinsure second-order precision. The shape function method uses alarge computational molecule. The curvilinear interpolationthis author proposes imports the advantage of coordinatetransformation method: easy to do interpolation. A coordinatesystem staggered half control volume used in the coordinatetransformation method is used as accessory to deriveinterpolation schemes. The calculation in physical domain withnon-orthogonal grid becomes as easy as that in a Cartesianorthogonal grid. The author applies this method to calculate turbulentorifice flow. The usual under-prediction of eddy length isimproved with the ULTRA-QUICK scheme to reflect the highgradients in orifice flow. In the last chapter, the author quantifies hydraulicabruptness to describe orifice geometry. The abruptness canhelp engineers to interpolate existing data to a new orifice,which saves detailed experimentsNR 2014080