User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioning

Image captioning bridges the gap between vision and language by automatically generating natural language descriptions for images. Traditional image captioning methods often overlook the preferences and characteristics of users. Personalized image captioning solves this problem by incorporating user prior knowledge into the model, such as writing styles and preferred vocabularies. Most existing methods emphasize the user context fusion process by memory networks or transformers. However, these methods ignore the distinct domains of each dataset. Therefore, they need to update the entire caption model parameters when meeting new samples, which is time-consuming and calculation-intensive. To address this challenge, we propose a novel personalized image captioning framework that leverages user context to consider personality factors. Additionally, our framework utilizes the prefix-tuning paradigm to extract knowledge from a frozen large language model, reducing the gap between different language domains. Specifically, we employ CLIP to extract the visual features of an image and align the semantic space using a query-guided mapping network. By incorporating the transformer layer, we merge the visual features with the user's contextual prior knowledge to generate informative prefixes. Moreover, we employ GPT-2 as the frozen large language model. With a small number of parameters to be trained, our model performs efficiently and effectively. Our model outperforms existing baseline models on Instagram and YFCC100M datasets across five evaluation metrics, demonstrating its superiority, including twofold improvements in metrics such as BLEU-4 and CIDEr

Fructose-1,6-bisphosphatase deficiency: estimation of prevalence in the Chinese population and analysis of genotype-phenotype association

ObjectiveFructose-1,6-bisphosphatase deficiency (FBP1D) is a rare inborn error due to mutations in the FBP1 gene. The genetic spectrum of FBP1D in China is unknown, also nonspecific manifestations confuse disease diagnosis. We systematically estimated the FBP1D prevalence in Chinese and explored genotype-phenotype association.MethodsWe collected 101 FBP1 variants from our cohort and public resources, and manually curated pathogenicity of these variants. Ninety-seven pathogenic or likely pathogenic variants were used in our cohort to estimate Chinese FBP1D prevalence by three methods: 1) carrier frequency, 2) permutation and combination, 3) Bayesian framework. Allele frequencies (AFs) of these variants in our cohort, China Metabolic Analytics Project (ChinaMAP) and gnomAD were compared to reveal the different hotspots in Chinese and other populations. Clinical and genetic information of 122 FBP1D patients from our cohort and published literature were collected to analyze the genotype-phenotypes association. Phenotypes of 68 hereditary fructose intolerance (HFI) patients from our previous study were used to compare the phenotypic differences between these two fructose metabolism diseases.ResultsThe estimated Chinese FBP1D prevalence was 1/1,310,034. In the Chinese population, c.490G>A and c.355G>A had significantly higher AFs than in the non-Finland European population, and c.841G>A had significantly lower AF value than in the South Asian population (all p values < 0.05). The genotype-phenotype association analyses showed that patients carrying homozygous c.841G>A were more likely to present increased urinary glycerol, carrying two CNVs (especially homozygous exon1 deletion) were often with hepatic steatosis, carrying compound heterozygous variants were usually with lethargy, and carrying homozygous variants were usually with ketosis and hepatic steatosis (all p values < 0.05). By comparing to phenotypes of HFI patients, FBP1D patients were more likely to present hypoglycemia, metabolic acidosis, and seizures (all p-value < 0.05).ConclusionThe prevalence of FBP1D in the Chinese population is extremely low. Genetic sequencing could effectively help to diagnose FBP1D

Enhancing the acoustic-to-electrical conversion efficiency of nanofibrous membrane-based triboelectric nanogenerators by nanocomposite composition

Acoustic energy is difficult to capture and utilise in general. The current work proposes a novel nanofibrous membrane-based (NFM) triboelectric nanogenerator (TENG) that can harvest acoustic energy from the environment. The device is ultra-thin, lightweight, and compact. The electrospun NFM used in the TENG contains three nanocomponents: polyacrylonitrile (PAN), polyvinylidene fluoride (PVDF), and multi-walled carbon nanotubes (MWCNTs). The optimal concentration ratio of the three nanocomponents has been identified for the first time, resulting in higher electric output than a single-component NFM TENG. For an incident sound pressure level of 116 dB at 200 Hz, the optimised NFM TENG can output a maximum open-circuit voltage of over 120 V and a short-circuit current of 30μA, corresponding to a maximum areal power density of 2.25 W/m2. The specific power reached 259μW/g. The ability to power digital devices is illustrated by lighting up 62 light-emitting diodes in series and powering other devices. The findings may inspire the design of acoustic NFM TENGs comprising multiple nanocomponents, and show that the NFM TENG can promote the utilisation of acoustic energy for many applications, such as microelectronic devices and the Internet of Things

Metformin attenuates lipid accumulation in hepatocytes of blunt snout bream (Megalobrama amblycephala) via activation of AMP-activated protein kinase

Currently, there is a trend to use high-fat diets in intensive aquaculture that is accompanied with incidence of fatty liver when dietary lipid level surpasses an upper limit. So, it is necessary to develop appropriate strategies to reduce the risk of fatty liver in commercial fish farming. Studies in mammals have revealed a correlation between fatty liver and AMP-activated protein kinase (AMPK) activity, which has been recognized as a key modulator of lipid metabolism. Considering the frequent occurrence of fatty liver in blunt snout bream farming, an in-vitro study was designed to evaluate the efficiency of metformin, as a stimulator of AMPK, in activation of AMPK and its subsequent effects on lipid metabolism in primary hepatocytes. Fish hepatocytes were seeded at a density of 1 × 106 ml−1 in 6-well tissue culture plates and treated with three different media including: 1) Leibovitz's L-15 medium [L15] as control, 2) high-fat medium [L15 + 400 μM oleic acid], and 3) metformin medium [L15 + 400 μM oleic acid+200 μM metformin]. After 48 h of culture, the cells and supernatant were collected for analysis. The results showed significant (P