LPN: Language-guided Prototypical Network for few-shot classification

Few-shot classification aims to adapt to new tasks with limited labeled examples. To fully use the accessible data, recent methods explore suitable measures for the similarity between the query and support images and better high-dimensional features with meta-training and pre-training strategies. However, the potential of multi-modality information has barely been explored, which may bring promising improvement for few-shot classification. In this paper, we propose a Language-guided Prototypical Network (LPN) for few-shot classification, which leverages the complementarity of vision and language modalities via two parallel branches. Concretely, to introduce language modality with limited samples in the visual task, we leverage a pre-trained text encoder to extract class-level text features directly from class names while processing images with a conventional image encoder. Then, a language-guided decoder is introduced to obtain text features corresponding to each image by aligning class-level features with visual features. In addition, to take advantage of class-level features and prototypes, we build a refined prototypical head that generates robust prototypes in the text branch for follow-up measurement. Finally, we aggregate the visual and text logits to calibrate the deviation of a single modality. Extensive experiments demonstrate the competitiveness of LPN against state-of-the-art methods on benchmark datasets

Toward an ecological understanding of transnational Chinese language teachers’ professional wellbeing in the United Kingdom

Given the lack of reports of Chinese language teachers’ wellbeing in the literature, this study aims to investigate the professional wellbeing of eight teachers of Chinese as a foreign language in the United Kingdom based on in-depth, semi-structured qualitative interviews. Interview data provided a rich picture of the rewarding aspects and challenges that they experienced in their professional lives. The main findings revealed the complex interplay of their professional wellbeing and different levels of ecology (i.e., cultural, institutional, classroom, and personal). The study also identified the specific strategies that the teachers deployed for (1) coping with work-related stress and for (2) maintaining wellbeing alongside professional productivity. The paper calls for further research to apply a close-up lens to the wellbeing of foreign language teachers across timescales. The implications for transnational language teachers’ mentoring interventions are discussed

HMG-CoA reductase, cholesterol 7α-hydroxylase, LCAT, ACAT, LDL receptor, and SRB-1 in hereditary analbuminemia

HMG-CoA reductase, cholesterol 7α-hydroxylase, LCAT, ACAT, LDL receptor, and SRB-1 in hereditary analbuminemia.BackgroundHereditary analbuminemia is associated with hypercholesterolemia, which has been shown to be primarily caused by increased extrahepatic production of cholesterol. Nagase rats with hereditary analbuminemia (NAR) have been used as a model to dissect the effect of primary hypoalbuminemia from that caused by proteinuria in nephrotic syndrome. The present study was undertaken to explore the effect of hereditary analbuminemia on protein expression of the key factors involved in cholesterol metabolism.MethodsHepatic tissue protein abundance of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, cholesterol 7α-hydroxylase (a rate-limiting enzyme in cholesterol catabolism), low density lipoprotein (LDL) receptor, high density lipoprotein (HDL) receptor (SRB-1), acyl-coA cholesterol acyltransferase-2 (ACAT-2), and plasma concentration of lecithin cholesterol acyltransferase (LCAT), as well as HMG-CoA reductase, ACAT, and LCAT activities were determined in fasting male NAR and Sprague-Dawley control rats.ResultsThe NAR group exhibited significant up-regulation of HMG-CoA reductase protein abundance but normal HMG-CoA reductase enzymatic activity. This was coupled with a significant up-regulation of cholesterol 7α-hydroxylase and a mild up-regulation of ACAT protein abundance and activity. However, hepatic LDL receptor and HDL receptor and plasma LCAT protein concentration and activity were normal in NAR.ConclusionHypercholesterolemia in NAR is associated with elevated hepatic HMG-CoA reductase protein abundance, but normal HMG-CoA reductase activity. These findings point to post-translational regulation of this enzyme and favor an extrahepatic origin of hypercholesterolemia in NAR. The observed up-regulation of cholesterol 7α-hydroxylase represents a compensatory response to the associated hypercholesterolemia. Unlike nephrotic syndrome, which causes severe LDL receptor, HDL receptor, and LCAT deficiencies, hereditary analbuminemia does not affect these proteins

1-(4-Bromo-2-fluoro­benz­yl)pyridinium bis­(2-thioxo-1,3-dithiole-4,5-dithiol­ato)nickelate(III)

The title compound, (C12H10BrFN)[Ni(C3S5)2], is an ion-pair complex consisting of N-(2-fluoro-4-bromo­benz­yl)pyridinium cations and [Ni(dmit)2]− anions (dmit = 2-thioxo-1,3-dithiole-4,5-dithiol­ate). In the anion, the NiIII ion exhibits a square-planar coordination involving four S atoms from two dmit ligands. In the crystal structure, weak S⋯S [3.474 (3), 3.478 (3) and 3.547 (3) Å] and S⋯π [S⋯centroid distances = 3.360 (3), 3.378 (2), 3.537 (2) and 3.681 (3) Å] inter­actions and C—H⋯F hydrogen bonds lead to a three-dimensional supra­molecular network

Household carbon inequality in the U.S

Household carbon emissions are mainly affected by income and other key demographic factors. Understanding the contribution of these factors can inform climate responsibilities and potential demand side climate mitigation strategies. By linking US consumer expenditure survey data with a nested national within a global multi-regional input-output model, this study estimates consumption-based GHG emissions for 9 income groups and assesses the carbon inequality in the US for 2015. Our results show that the per capita carbon footprint (CF) of the highest income group (200 thousand USD per year) with 32.3 tons is about 2.6 times the per capita CF of the lowest income group