CLIP Model for Images to Textual Prompts Based on Top-k Neighbors

Text-to-image synthesis, a subfield of multimodal generation, has gained significant attention in recent years. We propose a cost-effective approach for image-to-prompt generation that leverages generative models to generate textual prompts without the need for large amounts of annotated data. We divide our method into two stages: online stage and offline stage. We use a combination of the CLIP model and K-nearest neighbors (KNN) algorithm. The proposed system consists of two main parts: an offline task and an online task. Our method owns the highest metric 0.612 among these models, which is 0.013, 0.055, 0.011 higher than Clip, Clip + KNN(top 10) respectively.Comment: CLIP model, KNN, image-to-prompt

Optimization Method Based On Optimal Control

In this paper, we focus on a method based on optimal control to address the optimization problem. The objective is to find the optimal solution that minimizes the objective function. We transform the optimization problem into optimal control by designing an appropriate cost function. Using Pontryagin's Maximum Principle and the associated forward-backward difference equations (FBDEs), we derive the iterative update gain for the optimization. The steady system state can be considered as the solution to the optimization problem. Finally, we discuss the compelling characteristics of our method and further demonstrate its high precision, low oscillation, and applicability for finding different local minima of non-convex functions through several simulation examples

Prenatal detected retroperitoneal pulmonary sequestration with elevated serum levels of CA 19-9 – Case report and review of the literature

AbstractWe present a case of prenatal detected retroperitoneal pulmonary sequestration (RPS) with an interesting finding. Immunohistochemical staining of the specimen indicated that the elevated carbohydrate antigen (CA) 19-9 serum level was very likely caused by the sequestration. A review of the literature was made. RPS is an infrequent congenital malformation, which can be detected by routine obstetric sonographic screening during prenatal life. It can be misdiagnosed as neuroblastoma. The differential diagnosis can be tricky, which we hope our finding can help with. The management remains controversial

Multiscale Superpixel Structured Difference Graph Convolutional Network for VL Representation

Within the multimodal field, the key to integrating vision and language lies in establishing a good alignment strategy. Recently, benefiting from the success of self-supervised learning, significant progress has been made in multimodal semantic representation based on pre-trained models for vision and language. However, there is still room for improvement in visual semantic representation. The lack of spatial semantic coherence and vulnerability to noise makes it challenging for current pixel or patch-based methods to accurately extract complex scene boundaries. To this end, this paper develops superpixel as a comprehensive compact representation of learnable image data, which effectively reduces the number of visual primitives for subsequent processing by clustering perceptually similar pixels. To mine more precise topological relations, we propose a Multiscale Difference Graph Convolutional Network (MDGCN). It parses the entire image as a fine-to-coarse hierarchical structure of constituent visual patterns, and captures multiscale features by progressively merging adjacent superpixels as graph nodes. Moreover, we predict the differences between adjacent nodes through the graph structure, facilitating key information aggregation of graph nodes to reason actual semantic relations. Afterward, we design a multi-level fusion rule in a bottom-up manner to avoid understanding deviation by learning complementary spatial information at different regional scales. Our proposed method can be well applied to multiple downstream task learning. Extensive experiments demonstrate that our method is competitive with other state-of-the-art methods in visual reasoning. Our code will be released upon publication

Study on the Effect of Regional Water Pollution—Take Huaxi River in Chongqing as an Example

Water pollution management plays a crucial role in China’s ecological environment development. It has evolved from being solely the responsibility of the government to a collaborative effort involving multiple entities. This paper presents findings from a field survey conducted around the collaborative capacity and effectiveness of wastewater treatment in Huaxi River, Chongqing. The study collected 427 valid questionnaires and employed SPSS26.0 software and AMOS24.0 software, utilizing structural equation modelling and regression analysis to verify the relationship between the variables. The results highlight that synergy mechanism acts as a mediating variable between synergy capability and synergy governance effect, underscoring the role of mechanism in the relationship between capability and governance effect. The conclusion emphasizes the importance of enhancing synergistic capacity and synergistic mechanism to effectively promote synergistic governance effect in the water pollution management of Huaxi River in Chongqing. This can be achieved by improving the abilities of multiple stakeholders in managing water pollution, enhancing cooperation among parties, and encouraging participation of social organizations, the public, and enterprises in the management process to achieve sustainable development of ecological civilization

Experimental Simulation and Verification of Position Servo Control of Mechanical Rodless Cylinder

In order to improve the position control accuracy of rodless cylinder, the valve control cylinder system based on pneumatic proportional servo is studied deeply. According to the working principle of the mechanical rodless cylinder control system, under the condition of uniform speed, the driving voltage of the proportional valve is changed to measure multiple sets of friction force and corresponding velocity data. Analyzed the physical structure of each component in pneumatic system, established the mathematical model of pneumatic system, and introduced MATLAB system identification toolbox to identify the parameters of the transfer function. and the experiment verifies its correctness

The effects of litter input and increased precipitation on soil microbial communities in a temperate grassland

Global warming has contributed to shifts in precipitation patterns and increased plant productivity, resulting in a significant increase in litter input into the soils. The enhanced litter input, combined with higher levels of precipitation, may potentially affect soil microbial communities. This study aims to investigate the effects of litter input and increased precipitation on soil microbial biomass, community structure, and diversity in a temperate meadow steppe in northeastern China. Different levels of litter input (0%, +30%, +60%) and increased precipitation (0%, +15%, +30%) were applied over a three-year period (2015–2017). The results showed that litter input significantly increased the biomass of bacteria and fungi without altering their diversity, as well as the ratio of bacterial to fungal biomass. Increased precipitation did not have a notable effect on the biomass and diversity of bacteria and fungi, but it did increase the fungal-to-bacterial biomass ratio. However, when litter input and increased precipitation interacted, bacterial diversity significantly increased while the fungal-to-bacterial biomass ratio remained unchanged. These findings indicate that the projected increases in litter and precipitation would have a substantial impact on soil microbial communities. In energy-and water-limited temperate grasslands, the additional litter inputs and increased precipitation contribute to enhanced nutrient and water availability, which in turn promotes microbial growth and leads to shifts in community structure and diversity

Evaluation of the efficacy and safety of intravenous remdesivir in adult patients with severe COVID-19: study protocol for a phase 3 randomized, double-blind, placebo-controlled, multicentre trial.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by a novel corinavirus (later named SARS-CoV-2 virus), was fistly reported in Wuhan, Hubei Province, China towards the end of 2019. Large-scale spread within China and internationally led the World Health Organization to declare a Public Health Emergency of International Concern on 30th January 2020. The clinical manifestations of COVID-19 virus infection include asymptomatic infection, mild upper respiratory symptoms, severe viral pneumonia with respiratory failure, and even death. There are no antivirals of proven clinical efficacy in coronavirus infections. Remdesivir (GS-5734), a nucleoside analogue, has inhibitory effects on animal and human highly pathogenic coronaviruses, including MERS-CoV and SARS-CoV, in in vitro and in vivo experiments. It is also inhibitory against the COVID-19 virus in vitro. The aim of this study is to assess the efficacy and safety of remdesivir in adult patients with severe COVID-19. METHODS: The protocol is prepared in accordance with the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) guidelines. This is a phase 3, randomized, double-blind, placebo-controlled, multicentre trial. Adults (≥ 18 years) with laboratory-confirmed COVID-19 virus infection, severe pneumonia signs or symptoms, and radiologically confirmed severe pneumonia are randomly assigned in a 2:1 ratio to intravenously administered remdesivir or placebo for 10 days. The primary endpoint is time to clinical improvement (censored at day 28), defined as the time (in days) from randomization of study treatment (remdesivir or placebo) until a decline of two categories on a six-category ordinal scale of clinical status (1 = discharged; 6 = death) or live discharge from hospital. One interim analysis for efficacy and futility will be conducted once half of the total number of events required has been observed. DISCUSSION: This is the first randomized, placebo-controlled trial in COVID-19. Enrolment began in sites in Wuhan, Hubei Province, China on 6th February 2020. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04257656. Registered on 6 February 2020