Rebalanced Zero-shot Learning

Zero-shot learning (ZSL) aims to identify unseen classes with zero samples during training. Broadly speaking, present ZSL methods usually adopt class-level semantic labels and compare them with instance-level semantic predictions to infer unseen classes. However, we find that such existing models mostly produce imbalanced semantic predictions, i.e. these models could perform precisely for some semantics, but may not for others. To address the drawback, we aim to introduce an imbalanced learning framework into ZSL. However, we find that imbalanced ZSL has two unique challenges: (1) Its imbalanced predictions are highly correlated with the value of semantic labels rather than the number of samples as typically considered in the traditional imbalanced learning; (2) Different semantics follow quite different error distributions between classes. To mitigate these issues, we first formalize ZSL as an imbalanced regression problem which offers empirical evidences to interpret how semantic labels lead to imbalanced semantic predictions. We then propose a re-weighted loss termed Re-balanced Mean-Squared Error (ReMSE), which tracks the mean and variance of error distributions, thus ensuring rebalanced learning across classes. As a major contribution, we conduct a series of analyses showing that ReMSE is theoretically well established. Extensive experiments demonstrate that the proposed method effectively alleviates the imbalance in semantic prediction and outperforms many state-of-the-art ZSL methods. Our code is available at https://github.com/FouriYe/ReZSL-TIP23.Comment: Accepted to IEEE Transactions on Image Processing (TIP) 202

Climate System Ontology: A Formal Specification of the Complex Climate System

Modeling the climate system requires a formal representation of the characteristics of the system elements and the processes that change them. The Climate System Ontology (CSO) represents the semantics of the processes that continuously cause change at component and system levels. The CSO domain ontology logically represents various links that relate the nodes in this complex network. It models changes in the radiative balance caused by human activities and other forcings as solar energy flows through the system. CSO formally expresses various processes, including non-linear feedbacks and cycles, that change the compositional, structural, and behavioral characteristics of system components. By reusing the foundational logic of a set of top- and mid-level ontologies, we have modeled complex concepts such as hydrological cycle, forcing, greenhouse effect, feedback, and climate change in the ontology. This coherent, publicly available ontology can be queried to reveal the input and output of processes that directly impact the system elements and causal chains that bring change to the whole system. Our description of best practices in ontology development and explanation of the logics that underlie the extended upper-level ontologies help climate scientists to design interoperable domain and application ontologies, and share and reuse semantically rich climate data

Codimension-2 defects and higher symmetries in (3+1)D topological phases

(3+1)D topological phases of matter can host a broad class of non-trivial topological defects of codimension-1, 2, and 3, of which the well-known point charges and flux loops are special cases. The complete algebraic structure of these defects defines a higher category, and can be viewed as an emergent higher symmetry. This plays a crucial role both in the classification of phases of matter and the possible fault-tolerant logical operations in topological quantum error correcting codes. In this paper, we study several examples of such higher codimension defects from distinct perspectives. We mainly study a class of invertible codimension-2 topological defects, which we refer to as twist strings. We provide a number of general constructions for twist strings, in terms of gauging lower dimensional invertible phases, layer constructions, and condensation defects. We study some special examples in the context of $\mathbb{Z}_2$ gauge theory with fermionic charges, in $\mathbb{Z}_2 \times \mathbb{Z}_2$ gauge theory with bosonic charges, and also in non-Abelian discrete gauge theories based on dihedral ($D_n$) and alternating ($A_6$) groups. The intersection between twist strings and Abelian flux loops sources Abelian point charges, which defines an $H^4$ cohomology class that characterizes part of an underlying 3-group symmetry of the topological order. The equations involving background gauge fields for the 3-group symmetry have been explicitly written down for various cases. We also study examples of twist strings interacting with non-Abelian flux loops (defining part of a non-invertible higher symmetry), examples of non-invertible codimension-2 defects, and examples of interplay of codimension-2 defects with codimension-1 defects. We also find an example of geometric, not fully topological, twist strings in (3+1)D $A_6$ gauge theory.Comment: 70 pages, 42 figure

Effects of Nutritional Level of Concentrate‐Based Diets on Meat Quality and Expression Levels of Genes Related to Meat Quality in Hainan Black Goats

The present study investigated the effects of the nutritional levels of diets on meat quality and related gene expression in Hainan black goat. Twenty-four goats were divided into six dietary treatments and were fed a concentrate-based diet with two levels of crude protein (CP) (15% or 17%) and three levels of digestive energy (DE) (11.72, 12.55 or 13.39 MJ/kg DM) for 90 days. Goats fed the concentrate-based diet with 17% CP had significantly (P \u3c 0.05) higher average daily gains (ADG) and better feed conversion rates (FCR). The pH 24h value tended to decrease (P \u3c 0.05) with increasing DE levels. The tenderness of Longissimus dorsi muscle (LD) and Semimembranosus muscle (SM) reduced with increasing CP levels (P \u3c 0.05). With increasing DE levels, tenderness was increased (P \u3c 0.05). The heart fatty acid-binding protein (H-FABP) mRNA expression levels in LD and SM increased with increasing DE levels (P \u3c 0.05), but decreased with increasing CP levels (P \u3c 0.05). The calpastatin (CAST) and μ-calpain mRNA expressions levels in LD and SM were affected significantly (P \u3c 0.05) by CP and DE levels in the diet. Therefore, the nutritional levels of diets affect meat quality and expression levels of genes associated with meat quality in Hainan black goats

Identification of cuproptosis-related subtypes, characterization of immune microenvironment infiltration, and development of a prognosis model for osteoarthritis

BackgroundOsteoarthritis (OA) is a prevalent chronic joint disease with an obscure underlying molecular signature. Cuproptosis plays a crucial role in various biological processes. However, the association between cuproptosis-mediated immune infifiltration and OA progression remains unexplored. Therefore, this study elucidates the pathological process and potential mechanisms underlying cuproptosis in OA by constructing a columnar line graph model and performing consensus clustering analysis.MethodsGene expression profifile datasets GSE12021, GSE32317, GSE55235, and GSE55457 of OA were obtained from the comprehensive gene expression database. Cuproptosis signature genes were screened by random forest (RF) and support vector machine (SVM). A nomogram was developed based on cuproptosis signature genes. A consensus clustering was used to distinguish OA patients into different cuproptosis patterns. To quantify the cuproptosis pattern, a principal component analysis was developed to generate the cuproptosis score for each sample. Single-sample gene set enrichment analysis (ssGSEA) was used to provide the abundance of immune cells in each sample and the relationship between these significant cuproptosis signature genes and immune cells.To quantify the cuproptosis pattern, a principal component analysis technique was developed to generate the cuproptosis score for each sample. Cuproptosis-related genes were extracted and subjected to differential expression analysis to construct a disease prediction model and confifirmed by RT-qPCR.ResultsSeven cuproptosis signature genes were screened (DBT, LIPT1, GLS, PDHB, FDX1, DLAT, and PDHA1) to predict the risk of OA disease. A column line graph model was developed based on these seven cuproptosis signature genes, which may assist patients based on decision curve analysis. A consensus clustering method was used to distinguish patients with disorder into two cuproptosis patterns (clusters A and B). To quantify the cuproptosis pattern, a principal component analysis technique was developed to generate the cuproptosis score for each sample. Furthermore, the OA characteristics of patients in cluster A were associated with the inflflammatory factors IL-1b, IL-17, IL-21, and IL-22, suggesting that the cuproptosis signature genes play a vital role in the development of OA.DiscussionIn this study, a risk prediction model based on cuproptosis signature genes was established for the fifirst time, and accurately predicted OA risk. In addition, patients with OA were classifified into two cuproptosis molecule subtypes (clusters A and B); cluster A was highly associated with Th17 immune responses, with higher IL-1b, IL-17, and IL-21 IL-22 expression levels, while cluster B had a higher correlation with cuproptosis. Our analysis will help facilitate future research related cuproptosis-associated OA immunotherapy. However, the specifific mechanisms remain to be elucidated

Stratosphere-to-Troposphere Transport Revealed by Ground-based Lidar and Ozonesonde at a Midlatitude Site

This paper presents ozone structures measured by a ground-based ozone lidar and ozonesonde at Huntsville, Alabama, on 27-29 April 2010 originating from a stratosphere-to-troposphere transport event associated with a cutoff cyclone and tropopause fold. In this case, the tropopause reached 6 km and the stratospheric intrusion resulted in a 2-km thick elevated ozone layer with values between 70 and 85 ppbv descending from the 306-K to 298-K isentropic surface at a rate of 5 km day1. The potential temperature was provided by a collocated microwave profiling radiometer. We examine the corresponding meteorological fields and potential vorticity (PV) structures derived from the analysis data from the North American Mesoscale model. The 2-PVU (PV unit) surface, defined as the dynamic tropopause, is able to capture the variations of the ozone tropopause estimated from the ozonesonde and lidar measurements. The estimated ozone/PV ratio, from the measured ozone and model derived PV, for the mixing layer between the troposphere and stratosphere is approximately 41 ppbv/PVU with an uncertainty of approximately 33%. Within two days, the estimated mass of ozone irreversibly transported from the stratospheric into the troposphere is between 0.07 Tg (0.9 10(exp33) molecules) and 0.11 Tg (1.3 10(exp33) molecules) with an estimated uncertainty of 59%. Tropospheric ozone exhibited enormous variability due to the complicated mixing processes. Low ozone and large variability were observed in the mid-troposphere after the stratospheric intrusion due to the westerly advection including the transition from a cyclonic system to an anticyclonic system. This study using high temporal and vertical-resolution measurements suggests that, in this case, stratospheric air quickly lost its stratospheric characteristics once it is irreversibly mixed down into the troposphere

Control of cortex development by ULK4, a rare risk gene for mental disorders including schizophrenia

This work was supported by the grants from British Council China (Sino-UK higher Education for PhD studies) to Y.D. and C.D.M., and also from the following funding resources: Tenovus Scotland (G12/05, B.L.), The Carnegie Trust (RG13060-10, B.L.) and National Natural Science Foundation of China (91232724, Y.D.; 31100788, L.Z.; 81200933, N.N.S.; 31528011, B.L. and Y.D.).Peer reviewedPublisher PD

Marine fungus Aspergillus c1. sp metabolite activates the HSF1/PGC-1α axis, inducing a thermogenic program for treating obesity

Background and aims: Obesity is one of the most prevalent diseases worldwide with less ideal approved agents in clinic. Activating the HSF1/PGC-1α axis in adipose tissues has been reported to induce thermogenesis in mice, which presents a promising therapeutic avenue for obesity treatment. The present study aimed to identified novel natural HSF1 activator and evaluated the therapeutic effects of the newly discovered compound on obesity-associated metabolic disorders and the molecular mechanisms of these effects.Methods: Our previous reported HSF1/PGC-1α activator screening system was used to identify novel natural HSF1 activator. The PGC-1α luciferase activity, immunoblot, protein nuclear-translocation, immunofluorescence, chromatin immunoprecipitation assays were used to evaluate the activity of compound HN-001 in activating HSF1. The experiments of mitochondrial number measurement, TG assay and imaging, cellular metabolic assay, gene assays, and CRISPR/Cas 9 were applied for investigating the metabolic effect of HN-001 in C3H10-T1/2 adipocytes. The in vivo anti-obesity efficacies and beneficial metabolic effects of HN-001 were evaluated by performing body and fat mass quantification, plasma chemical analysis, GTT, ITT, cold tolerance test, thermogenesis analysis.Results: HN-001 dose- and time-dependently activated HSF1 and induced HSF1 nuclear translocation, resulting in an enhancement in binding with the gene Pgc-1α. This improvement induced activation of adipose thermogenesis and enhancement of mitochondrial oxidation capacity, thus inhibiting adipocyte maturation. Deletion of HSF1 in adipocytes impaired mitochondrial oxidation and abolished the above beneficial metabolic effects of HN-001, including adipocyte browning induction, improvements in mitogenesis and oxidation capacity, and lipid-lowering ability. In mice, HN-001 treatment efficiently alleviated diet-induced obesity and metabolic disorders. These changes were associated with increased body temperature in mice and activation of the HSF1/PGC-1α axis in adipose tissues. UCP1 expression and mitochondrial biogenesis were increased in both white and brown adipose tissues of HN-001-treated mice.Conclusion: These data indicate that HN-001 may have therapeutic potential for obesity-related metabolic diseases by increasing the capacity of energy expenditure in adipose tissues through a mechanism involving the HSF1/PGC-1α axis, which shed new light on the development of novel anti-obesity agents derived from marine sources

Protein-retention expansion microscopy of cells and tissues labeled using standard fluorescent proteins and antibodies

Expansion microscopy (ExM) enables imaging of preserved specimens with nanoscale precision on diffraction-limited instead of specialized super-resolution microscopes. ExM works by physically separating fluorescent probes after anchoring them to a swellable gel. The first ExM method did not result in the retention of native proteins in the gel and relied on custom-made reagents that are not widely available. Here we describe protein retention ExM (proExM), a variant of ExM in which proteins are anchored to the swellable gel, allowing the use of conventional fluorescently labeled antibodies and streptavidin, and fluorescent proteins. We validated and demonstrated the utility of proExM for multicolor super-resolution (~70 nm) imaging of cells and mammalian tissues on conventional microscopes.United States. National Institutes of Health (1R01GM104948)United States. National Institutes of Health (1DP1NS087724)United States. National Institutes of Health ( NIH 1R01EY023173)United States. National Institutes of Health (1U01MH106011

Ozone Lidar Observations for Air Quality Studies

Tropospheric ozone lidars are well suited to measuring the high spatio-temporal variability of this important trace gas. Furthermore, lidar measurements in conjunction with balloon soundings, aircraft, and satellite observations provide substantial information about a variety of atmospheric chemical and physical processes. Examples of processes elucidated by ozone-lidar measurements are presented, and modeling studies using WRF-Chem, RAQMS, and DALES/LES models illustrate our current understanding and shortcomings of these processes