Boosting Few-Shot Semantic Segmentation Via Segment Anything Model

In semantic segmentation, accurate prediction masks are crucial for downstream tasks such as medical image analysis and image editing. Due to the lack of annotated data, few-shot semantic segmentation (FSS) performs poorly in predicting masks with precise contours. Recently, we have noticed that the large foundation model segment anything model (SAM) performs well in processing detailed features. Inspired by SAM, we propose FSS-SAM to boost FSS methods by addressing the issue of inaccurate contour. The FSS-SAM is training-free. It works as a post-processing tool for any FSS methods and can improve the accuracy of predicted masks. Specifically, we use predicted masks from FSS methods to generate prompts and then use SAM to predict new masks. To avoid predicting wrong masks with SAM, we propose a prediction result selection (PRS) algorithm. The algorithm can remarkably decrease wrong predictions. Experiment results on public datasets show that our method is superior to base FSS methods in both quantitative and qualitative aspects

Graph based Label Enhancement for Multi-instance Multi-label learning

Multi-instance multi-label (MIML) learning is widely applicated in numerous domains, such as the image classification where one image contains multiple instances correlated with multiple logic labels simultaneously. The related labels in existing MIML are all assumed as logical labels with equal significance. However, in practical applications in MIML, significance of each label for multiple instances per bag (such as an image) is significant different. Ignoring labeling significance will greatly lose the semantic information of the object, so that MIML is not applicable in complex scenes with a poor learning performance. To this end, this paper proposed a novel MIML framework based on graph label enhancement, namely GLEMIML, to improve the classification performance of MIML by leveraging label significance. GLEMIML first recognizes the correlations among instances by establishing the graph and then migrates the implicit information mined from the feature space to the label space via nonlinear mapping, thus recovering the label significance. Finally, GLEMIML is trained on the enhanced data through matching and interaction mechanisms. GLEMIML (AvgRank: 1.44) can effectively improve the performance of MIML by mining the label distribution mechanism and show better results than the SOTA method (AvgRank: 2.92) on multiple benchmark datasets.Comment: 7 pages,2 figure

A compendium of genetic regulatory effects across pig tissues

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.</p

Pre-Reinforcement Mechanism and Effect Analysis of Surface Infiltration Grouting in Shallow Buried Section of Long-Span Tunnel

In order to solve the problem that the hole-forming rate of boreholes is low and it is difficult to reach the designed length when supporting a long pipe shed in loose stratum in a shallow buried section of a long-span tunnel, it is necessary to pre-reinforce the loose stratum in order to improve the strength and integrity of the surrounding rock. Relying on the grouting project of the shallow buried section at the exit of Botanggou tunnel, it is assumed that the grouting material is Newtonian fluid and the steel floral tube shows cylindrical infiltration and diffusion. Through the analysis of the structural characteristics of the injected stratum, the conceptual model of infiltration grouting is established. Twelve groups of test slurry were prepared with ordinary Portland cement and ultra-fine cement, and through the analysis of the slurry parameters of each group, ordinary Portland cement slurry was selected with a water–cement ratio of 1:1 plus 3% water glass to strengthen the gravel layer, and ultra-fine cement slurry with a water–cement ratio of 1:1 plus 3% water glass and 0.3% polycarboxylate superplasticizer to strengthen the fully and strongly weathered porphyritic granite layer. Through the on-site single-hole grouting test and combining with the empirical formula, the maximum diffusion radius of single-hole infiltration grouting is calculated, and the sliding width of the sidewall is deduced using Terzaghi theory. To ensure the grouting effect, the 5 m expansion of the excavation profile is taken as the grouting range. Grouting construction adopts the overall order of periphery and then interior, and three-sequence opening and grouting are adopted in the same row of grouting holes, which can effectively prevent grouting running and grouting. For the strata treated by surface grouting, the construction of the long pipe shed is smooth and reaches the designed length, and there is no large deformation of the surrounding rock when excavated using the CD method. The treatment effect is analyzed by the P-Q-t control method, excavation observation method, and deformation monitoring method. The results show that the injected stratum is fully infiltrated and gelled, forms an obvious grouting stone body, the integrity and strength of surrounding rock are obviously improved, and the convergence values of the tunnel surface, vault subsidence, and clearance do not exceed the alarm value of 60 mm. The research results provide some awareness and understanding of the grouting pre-reinforcement of loose stratum in a shallow buried section of a long-span tunnel in the future

Growth, Nutritional Quality and Health-Promoting Compounds in Chinese Kale Grown under Different Ratios of Red:Blue LED Lights

Chinese kale (Brassica alboglabra Bailey) is one of the healthiest vegetables which is rich in health-promoting phytochemicals, including carotenoids, vitamin C, amino acid, glucosinolates, anthocyanin, flavonoids and phenolic compounds. The effects of different LEDs (white LED, 8R1B (red:blue = 8:1), 6R3B (red:blue = 6:3)) on nutritional quality in flower stalks and leaves of Chinese kale were investigated in this study. 8R1B and 6R3B were more effective than white LED light for improvement of growth and quality of Chinese kale. Flower stalk contained a higher content of nutritional compounds than leaves in Chinese kale. 8R1B significantly promoted plant growth, accumulation of biomass and soluble sugar content in flower stalks. In contrast, 6R3B significantly reduced plant dry matter, but it promoted nutritional compounds accumulation in flower stalks, such as soluble proteins, total glucosinolate, total anthocyanin, flavonoid, antioxidant activity. In addition, 6R3B enable to increase the amount of sourness and umami tasty amino acids, as well as precursor amino acids of glucosinolate. Accumulation balance of biomass and nutritional compounds is related to the ratio of red to blue light. Generally, 6R3B was more conducive to the enrichment of health-promoting compounds, as well as umami in Chinese kale

Fish Face Identification Based on Rotated Object Detection: Dataset and Exploration

At present, fish farming still uses manual identification methods. With the rapid development of deep learning, the application of computer vision in agriculture and farming to achieve agricultural intelligence has become a current research hotspot. We explored the use of facial recognition in fish. We collected and produced a fish identification dataset with 3412 images and a fish object detection dataset with 2320 images. A rotating box is proposed to detect fish, which avoids the problem where the traditional object detection produces a large number of redundant regions and affects the recognition accuracy. A self-SE module and a fish face recognition network (FFRNet) are proposed to implement the fish face identification task. The experiments proved that our model has an accuracy rate of over 90% and an FPS of 200

Efficiency Calculation and Configuration Design of a PEM Electrolyzer System for Hydrogen Production

A PEM electrolyzer system for hydrogen production is established and the corresponding efficiency is derived. Based on semi-empirical equations, thermodynamic-electrochemical modeling of water splitting reaction is systematically carried out. It is confirmed that the Joule heat resulting from the irreversibilities inside the PEM electrolyzer is larger than that needed in the water splitting process in the whole region of the electric current density. Some alternative configurations are designed to improve the overall performance of the system and the corresponding expressions of the efficiency are also derived. The curves of the efficiency varying with the electric current density are presented and the efficiencies of the different configurations are compared. The optimally operating region of the electric current density is determined. The effects of some of the important parameters on the performance of the PEM electrolyzer system are analyzed in detail. Some significant results for the optimum design strategies of a practical PEM electrolyzer system for hydrogen production are obtained.Fujian Natural Science Foundation; Fundamental Research Fund for the Central Universities, People's Republic of China [201112G006

Morphological and Physiological Responses of Cucumber Seedlings to Supplemental LED Light under Extremely Low Irradiance

In order to inhibit spindling growth and improve quality of cucumber seedlings under low irradiance, effects of supplemental light-emitting diodes (LED) light (SL) on morphological and physiological characteristics of cucumber seedlings at different growth stages under extremely low irradiance (ELI) were investigated. Supplementary monochromatic, dichromatic and trichromatic LED light on cucumber seedlings were conducted in experiment one, and supplements of combination ratios and intensity of blue and red LED light (RB) were conducted in experiment two. The morphological and physiological parameters of cucumber seedlings were promoted effectively by supplemental monochromatic red light or dichromatic containing red light (RB and RG) under ELI as early as one-leaf seedling stage, as demonstrated by suppressed length of hypocotyl and first internode, increased stem diameter and biomass, higher net photosynthetic rate (Pn) and soluble sugar content. Monochromatic or additional green light was not beneficial to cucumber seedlings under the ELI. The length of shoot and hypocotyl decreased, while stem diameter and leaf area increased as early as one-leaf seedling stage by RB SL. Root activities, root&ndash;shoot ratio, activities of catalase (CAT) and peroxidase (POD), as well as palisade&ndash;spongy ratio in the leaf of cucumber seedlings were promoted effectively by increasing blue light proportion (1R1B/1R2B). Increasing light intensity (50/75) enhanced soluble sugar accumulation in leaves. There were synergistic effects of RB ratio and light intensity on increasing stem diameter, leaf area, seedling index and decreasing hypocotyl cell area of the vertical section. In conclusion, 1R2B-75 may be the optimal SL to inhibit spindling growth of cucumber seedlings under ELI condition

Performance Analysis and Multi-Objective Optimization of a Molten Carbonate Fuel Cell-Braysson Heat Engine Hybrid System

A new hybrid system consisting of a molten carbonate fuel cell (MCFC) and a Braysson heat engine is established, in which multi-irreversibilities resulting from the overpotentials in the electrochemical reaction, heat leak from the MCFC to the environment, non-perfect regeneration in the regenerator, and finite-rate heat transfer in the Braysson heat engine are taken into account. Analytical expressions for the efficiency and power output of the hybrid system are derived through thermodynamic-electrochemical analyses, from which the general characteristics of the system are revealed and the optimum criteria of some of the main parameters such as the current density, efficiency and power output are given. The influence of the irreversible losses on the performance of the hybrid system is discussed. Moreover, a multi-objective function including both the power output and efficiency is introduced and used to further subdivide the parametric optimum regions according to different requirements which are often faced in the design and operation of practical fuel cell systems. The results obtained here are very general and may be directly used to derive the variously interesting conclusions of the hybrid system operated under different special cases.National Natural Science Foundation [51076134]; Fundamental Research Fund of Xiamen Universities, People's Republic of China [201112G006

Configuration Designs and Parametric Optimum Criteria of an Alkaline Water Electrolyzer System for Hydrogen Production

National Natural Science Foundation [51076134]; Fundamental Research Fund for the Central Universities, People's Republic of ChinaAn alkaline water electrolyzer system for hydrogen production and its semi-empirical equations are directly used to analyze and optimize the performance of the system. The results obtained through thermodynamic-electrochemical analysis show clearly that for such an alkaline water electrolyzer system, there exist some optimal values of the electrolyte concentration under different operating temperatures and the Joule heat resulting from the irreversibilities inside the alkaline water electrolyzer is larger than the additional heat needed in the water splitting process. Consequently, some new configurations for utilizing the surplus heat in the alkaline water electrolyzer are put forward to improve the performance of the system. The general performance of these new configurations is discussed, from which the lower bound of the operating current density is determined. In order to further optimize the characteristics of these configurations, a multi-objective function including both the efficiency and hydrogen production rate is originally put forward and used to determine the upper bound of the operating current density. The optimum criteria of main parameters and the optimally working region of the alkaline water electrolyzer system are given. In addition, the effects of some important parameters on the performance of the system are analyzed in detail